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[00:00:10.960 --> 00:00:13.760] Hey everyone, welcome to the Drive podcast.
[00:00:13.760 --> 00:00:15.600] I'm your host, Peter Attia.
[00:00:15.600 --> 00:00:24.160] This podcast, my website, and my weekly newsletter all focus on the goal of translating the science of longevity into something accessible for everyone.
[00:00:24.160 --> 00:00:30.960] Our goal is to provide the best content in health and wellness, and we've established a great team of analysts to make this happen.
[00:00:30.960 --> 00:00:36.000] It is extremely important to me to provide all of this content without relying on paid ads.
[00:00:36.000 --> 00:00:46.480] To do this, our work is made entirely possible by our members, and in return, we offer exclusive member-only content and benefits above and beyond what is available for free.
[00:00:46.480 --> 00:00:54.480] If you want to take your knowledge of this space to the next level, it's our goal to ensure members get back much more than the price of the subscription.
[00:00:54.480 --> 00:01:03.200] If you want to learn more about the benefits of our premium membership, head over to peteratiamd.com forward slash subscribe.
[00:01:04.480 --> 00:01:07.040] Welcome to a special episode of The Drive.
[00:01:07.040 --> 00:01:21.360] For this week's episode, we want to rebroadcast one of our most popular episodes, which is the second conversation I had with Inigo San Milan in March of 2022, which was a deep dive into all things pertaining to Zone 2 exercise.
[00:01:21.360 --> 00:01:28.240] Inigo is an internationally renowned applied physiologist and assistant professor at the University of Colorado School of Medicine.
[00:01:28.240 --> 00:01:34.320] His research focuses on exercise-related metabolism, metabolic health, diabetes, and cancer.
[00:01:34.320 --> 00:01:50.720] In this conversation, we talk about Inigo's work with two-time Tour de France champion Tadi Pogacher, looking at the type of training that he does and what we can learn about training and cardiovascular physiology from the world's most elite performers.
[00:01:50.720 --> 00:01:58.480] We talk about lactate and fat oxidation as it relates to cardiorespiratory training and how carbohydrates in our food can affect lactate.
[00:01:58.480 --> 00:02:04.440] And we talk about what different lactate levels mean in the context of healthy versus unhealthy people.
[00:02:04.440 --> 00:02:19.400] We get into very specific detail around zone two exercise, how to measure it, how to know you're in zone two, what to do if you don't want to use a lactate meter, how you can structure your training around it, how to think about duration, timing, and frequency.
[00:02:19.400 --> 00:02:31.800] Talk about the importance and the compounding rate of improvement that can happen with zone two training, VO2 max training, high-intensity training, and how different exercises of this nature can improve your lifespan and health span.
[00:02:31.800 --> 00:02:47.480] This is a rather tour de force episode when it comes to zone two training, and obviously it's a term that many of you are very familiar with, but it's really great to go back to the source where we started talking about this with Indigo several years ago and then followed up again in 2022.
[00:02:47.480 --> 00:02:53.080] So without further delay, please enjoy or potentially re-enjoy my conversation with Inugo Sunala.
[00:02:57.880 --> 00:03:01.000] Indigo, it is so great to be sitting down with you again.
[00:03:01.000 --> 00:03:07.960] Last time, of course, we did this in person, but these days I've become too lazy to travel around and do podcasts in person, so do it by video.
[00:03:07.960 --> 00:03:13.720] But that said, I really hope you can get out here to Austin so we can train together and do some cool ex-fiz.
[00:03:13.720 --> 00:03:18.120] And also, I need to get out there to sort of do some of the ex-fiz stuff we've talked about.
[00:03:18.120 --> 00:03:24.680] But I almost don't know where to begin because there's so much stuff we talked about last time that we want to double-click on this time.
[00:03:24.680 --> 00:03:31.880] There's so much that has changed in the interval from when we spoke, gosh, probably two years ago, a little over two years ago.
[00:03:31.880 --> 00:03:39.000] I thought one place we could pick it up, something we didn't really talk about last time, was your work with Taddy Pogacho.
[00:03:39.000 --> 00:03:42.760] Because of course, I don't think anybody knew who he was two and a half years ago.
[00:03:42.760 --> 00:04:06.640] And of course, now he is, I don't know, I mean, I think it's safe to say he has the potential to potentially go down as the greatest Tour de France cyclist of all time, given how young he is, not to put that expectation out there, but to win the tour at such a young age, to not just win the yellow jersey, but the white jersey, polka dot jersey, repeatedly, he looks like something of a different species almost.
[00:04:06.640 --> 00:04:12.400] And I say that not in the way that people typically say those things of cyclists in a way that's suspicious of anything.
[00:04:12.400 --> 00:04:27.040] So for the listeners who are not familiar with the Tour de France, not familiar with your work with the UAE team and your work with Taddy Pogachar, maybe give folks a little bit of an update as to what you've been doing in professional cycling over the past couple of years.
[00:04:27.040 --> 00:04:29.120] First of all, thank you very much for having me here.
[00:04:29.120 --> 00:04:29.920] It's an honor.
[00:04:30.080 --> 00:04:33.440] Really excited for this, and I appreciate the opportunity.
[00:04:33.440 --> 00:04:37.280] I had a lot of fun last time, hopefully I have fun again.
[00:04:37.280 --> 00:04:44.320] My work with Tadé started in late 2018 when he signed up for the team.
[00:04:44.320 --> 00:04:50.720] Yeah, I was introduced to him by our CEO, Giannetti, and our general manager, Machine.
[00:04:50.880 --> 00:04:53.120] Told me, hey, start working with this guy.
[00:04:53.120 --> 00:04:55.360] And he was, what, at the time, 19, maybe?
[00:04:55.680 --> 00:04:56.640] Yeah, 19.
[00:04:56.640 --> 00:04:58.160] He was 19 at the time.
[00:04:58.240 --> 00:04:59.520] Just turned 19.
[00:04:59.520 --> 00:05:02.480] In fact, I started to work with him right away.
[00:05:02.480 --> 00:05:04.400] I realized he had potential.
[00:05:04.640 --> 00:05:10.320] And I think like a couple months earlier, no, or later, I forgot when we had that podcast.
[00:05:10.320 --> 00:05:12.320] I already told you about him.
[00:05:12.400 --> 00:05:15.600] Told you, like, we have a guy that has good potential.
[00:05:15.600 --> 00:05:16.640] That was Tade.
[00:05:16.800 --> 00:05:20.880] To put it in perspective, I mean, has good potential is one thing.
[00:05:20.880 --> 00:05:29.920] To then go and do what he did would make that statement the understatement of the century for folks who maybe don't follow cycling as closely, right?
[00:05:30.440 --> 00:05:32.760] Yeah, yeah, I mean, I try to be cautious.
[00:05:32.760 --> 00:05:37.800] I don't usually say that out loud of people who have good potential.
[00:05:37.800 --> 00:05:39.800] We talked about it over dinner that night.
[00:05:39.800 --> 00:05:40.520] Yeah, yeah.
[00:05:40.520 --> 00:05:45.800] When I say someone who has good potential, I don't usually say that lightly of anybody.
[00:05:45.800 --> 00:06:01.240] What did you see in him in 2018, 2019, that led you to believe that even amongst that class, because professional cyclists from a physiologic standpoint are all very special individuals.
[00:06:01.240 --> 00:06:06.520] What did you see in him that made you think he has potential in your understated way?
[00:06:06.680 --> 00:06:10.440] The physiological testing, we started doing right off the bat.
[00:06:10.440 --> 00:06:19.240] I saw like amazing capabilities, ability to clear lactate and to put out great amount of power for long periods of time.
[00:06:19.240 --> 00:06:28.360] So when you say that, was it specifically his FTP that impressed you, or was it his, as you said, lactate clearance?
[00:06:28.360 --> 00:06:36.520] Was it shorter bursts of power that were higher than FTP, but the speed with which he could do or the successive repeats that he could do?
[00:06:36.520 --> 00:06:41.320] I mean, tell me some of the testing you were putting cyclists through and how he stood out.
[00:06:41.320 --> 00:06:44.040] It's kind of like a similar test that I did to you.
[00:06:44.040 --> 00:06:51.480] And this is where I saw that at a given power output, his lactate levels, blood lactate levels, were extremely low.
[00:06:51.480 --> 00:07:05.000] And since I've been doing this specific protocol for 20 years with professional athletes, professional cyclists in this specific case, that's where I have my cheat sheet where I know I can categorize where people are.
[00:07:05.000 --> 00:07:12.840] He was like, whoa, way on the other side, way above almost everybody that I had tested or around the same category.
[00:07:12.840 --> 00:07:20.960] And for that age, that's what I saw, like, whoa, first of all, he is at a different category and he's first year pro, pretty much a junior.
[00:07:21.280 --> 00:07:28.960] And then that's where like I could see he could sustain a high amount of power with very low lactate compared to the rest.
[00:07:28.960 --> 00:07:34.000] And then throughout the trainings, we used training pics, the software, looking at training picks.
[00:07:34.000 --> 00:07:47.600] That's where I would see his different abilities to sustain a given power output for the whole day or for a specific effort, a glycolytic effort, and a client would see the power output that he would be putting out.
[00:07:47.600 --> 00:07:59.280] And so all together, then I saw his trainability, how easy he would get the concepts, how easy he would be comfortable with the training, how easy he would recover.
[00:07:59.280 --> 00:08:00.240] I like the feedback.
[00:08:00.240 --> 00:08:05.360] I talked to him once, twice a day over WhatsApp to the feedback.
[00:08:05.360 --> 00:08:10.400] I know very well when a hard week is or what a hard week is.
[00:08:10.400 --> 00:08:13.520] And when you see this kid telling you, I'm pretty good.
[00:08:13.520 --> 00:08:15.040] I'm recovering very well.
[00:08:15.040 --> 00:08:19.920] When other ones are telling you, woof, I had to take it a little bit easier today because I couldn't do this effort.
[00:08:19.920 --> 00:08:22.080] And we're talking about high-level pros.
[00:08:22.080 --> 00:08:24.960] And you see this kid telling you, like, yeah, no problem.
[00:08:24.960 --> 00:08:26.960] That's where you start putting together things.
[00:08:26.960 --> 00:08:40.480] And also, around the same time with my two colleagues at the university, Angelo Dalessandra and Travis Nenkov, we started to develop a platform for metabolomics where we can look at hundreds, if not thousands, of metabolites in the human body.
[00:08:40.480 --> 00:08:45.440] And we did it the tour of California in 2019, which was like around April.
[00:08:45.440 --> 00:08:47.280] That's where he won it.
[00:08:47.280 --> 00:08:49.600] And that's where when we analyze all his metabolites.
[00:08:49.600 --> 00:08:53.760] And we did already at the training camp in January 2018.
[00:08:53.760 --> 00:09:02.600] And we already saw, wow, this guy has different metabolites at the glycolytic level, exceeded level, recovery level.
[00:08:59.920 --> 00:09:05.000] And we confirmed that at the tour of California.
[00:09:05.320 --> 00:09:09.400] And this is where, putting all together, yeah, this guy is different.
[00:09:09.720 --> 00:09:24.280] So, going back to what you said about lactate, I assume that one of the data points that is most telling of a cyclist is if you plot on the x-axis watts per kilo and on the y-axis lactate production.
[00:09:24.280 --> 00:09:31.160] I mean, that might be one of the most telling graphs you could generate to predict success in the tour, correct?
[00:09:31.160 --> 00:09:31.880] Absolutely.
[00:09:31.880 --> 00:09:38.680] You see a normal tempo climbing in the tour de France, tempo A, that is the whole Peloton going up.
[00:09:38.680 --> 00:09:39.960] It's got to be four.
[00:09:39.960 --> 00:09:40.280] Yeah, okay.
[00:09:40.520 --> 00:09:42.600] As if I was about to say, wow, yeah, I was going to say four and a half.
[00:09:42.600 --> 00:09:46.840] Okay, so wow, the whole Peloton is going up at five watts per kilo.
[00:09:46.840 --> 00:09:48.200] Yeah, something like that.
[00:09:48.200 --> 00:09:53.560] And that's what you see, like someone at that intensity might have already six millimoles.
[00:09:53.560 --> 00:09:59.080] So you can tell it's going to be very tasking, and others might have one resting levels.
[00:09:59.080 --> 00:10:01.960] It really, really predicts performance.
[00:10:01.960 --> 00:10:08.600] In fact, when we go to these training camps, I'm going to go next week for the first training camp of the year with the team.
[00:10:08.600 --> 00:10:13.960] We do this physiological testing and I do this protocol and I get this data.
[00:10:13.960 --> 00:10:18.840] So right away I tell the team managers, this guy is way above the rest.
[00:10:18.840 --> 00:10:22.440] These three guys are really, really good immediately behind it.
[00:10:22.440 --> 00:10:24.920] These two guys are at the third level.
[00:10:24.920 --> 00:10:29.240] And then we have all these guys that they're like really, really bad form.
[00:10:29.240 --> 00:10:30.680] And it pretty much works.
[00:10:30.680 --> 00:10:35.960] Then we do different racing simulation and they tell you, boom, right away, this is how it is.
[00:10:35.960 --> 00:10:37.480] So, this is why it's very predictive.
[00:10:37.480 --> 00:10:45.040] And the same thing, too, moving into the season, you see, okay, all these three guys are going to be at a very good level when we start the season.
[00:10:44.120 --> 00:10:50.960] This guy, who we thought that he was going to be a very good level, he's not there at all when the season starts.
[00:10:51.280 --> 00:10:55.040] You see that it reflects very well what's going to happen.
[00:10:55.040 --> 00:10:57.120] Yeah, that's one of the things about cycling that I really love.
[00:10:57.120 --> 00:11:03.040] I mean, I don't know if you saw, but I interviewed Lance Armstrong back in, oh gosh, probably back in June, or maybe it came out in September.
[00:11:03.040 --> 00:11:16.160] But one of the things that we talked about was both on and off EPO or blood transfusions, you sort of knew where you stood before the race based on your FTP in watts per kilo.
[00:11:16.160 --> 00:11:22.480] He talked about when he was off EPO, he could hold 450 watts for 30 minutes.
[00:11:22.480 --> 00:11:28.000] So that would be slightly above FTP at 70, I think he was 70 to 75 kilos.
[00:11:28.000 --> 00:11:30.480] But it was in the ballpark of six watts per kilo.
[00:11:30.480 --> 00:11:35.280] And then, of course, on EPO, it was 7.1 watts per kilo, a huge difference.
[00:11:35.280 --> 00:11:41.280] But you knew that number going in, and you sort of knew only the GC contenders could do that.
[00:11:41.280 --> 00:11:54.080] I think that's the thing that a lot of people don't understand about cycling, which is there's relatively few moments in the tour when you need to sustain that level, but they always occur at the most important strategic times.
[00:11:54.080 --> 00:11:58.400] And that's sort of where the race is won and lost, because the race is won and lost by minutes.
[00:11:58.400 --> 00:12:00.400] How many hours does it take to complete the tour?
[00:12:00.400 --> 00:12:01.760] 100 hours or something?
[00:12:01.760 --> 00:12:04.560] On average, about four and a half, five hours a day.
[00:12:04.560 --> 00:12:05.760] Yeah, so something like that.
[00:12:05.760 --> 00:12:06.240] Yeah.
[00:12:06.240 --> 00:12:15.520] It's about a hundred-hour race, and yet the difference between the first, second, third guy will be, in some cases, seconds, in some cases, a few minutes.
[00:12:15.520 --> 00:12:19.600] For someone to win by five minutes is considered a blowout.
[00:12:19.600 --> 00:12:23.680] And so, what it really tells you is that there are a handful of minutes in that race.
[00:12:23.680 --> 00:12:29.320] There are a handful of climbs and time trials that set apart the winners from everybody else.
[00:12:28.960 --> 00:12:33.320] And to me, that's one of the beautiful things about cycling physiology: you have these metrics.
[00:12:33.480 --> 00:12:39.640] And now, I think it's not just FTP, it's watts per kilo with lactate production.
[00:12:39.640 --> 00:12:44.680] So, it gets even more into the critical physiology of recovery.
[00:12:44.680 --> 00:12:49.640] And in fact, we use these metrics a lot for the competition, and we did it this year at the Tour de France.
[00:12:49.640 --> 00:12:59.240] So, knowing the power output that he could sustain for, as you very well said, for specific times and climbs, we knew his capabilities.
[00:12:59.240 --> 00:13:05.080] And one of the things that we knew was that in the Alps, he was at a very, very high level.
[00:13:05.080 --> 00:13:10.600] That famous stage where he broke away and called the Rome 35 kilometers to the finish line.
[00:13:10.600 --> 00:13:20.280] We were seeing not only his data, but we see by knowing our writers' data, you can also guess the other writers' data too.
[00:13:20.280 --> 00:13:21.960] It's not rocket science.
[00:13:21.960 --> 00:13:27.400] So, we knew that he was at a very high level and discussing the ticks, you know, because it's part of the thing that we do.
[00:13:27.400 --> 00:13:34.520] We observe the data that we have, the data that we think the other ones have, and we structure a strategy for the next day.
[00:13:34.520 --> 00:13:37.080] And hey, does he have the legs to attack?
[00:13:37.080 --> 00:13:39.640] Should be holding back, or what should we do?
[00:13:39.640 --> 00:13:49.400] And clearly, it was like, well, tomorrow, if he attacks 35 kilometers to the finish line, he's going to get there with three minutes because the other guys, they're not at that level.
[00:13:49.400 --> 00:13:52.680] Why wait to the end of the tour when we can try to solve the situation?
[00:13:52.680 --> 00:13:55.000] So, we knew his capabilities very well.
[00:13:55.000 --> 00:13:59.560] And discussing this with him and the manager, yeah, that was the strategy.
[00:13:59.560 --> 00:14:05.800] First, test the legs, and like if he had, in fact, good legs, boom, go for it, and that's exactly what he did.
[00:14:06.040 --> 00:14:18.320] How much of that are you going to determine after a night of sleep, where you say, we're going to look at his resting lactate first thing in the morning, we're going to look at his heart rate overnight, we're going to look at his heart rate variability overnight.
[00:14:18.640 --> 00:14:29.200] So, in addition to the subjective, for example, how he felt during the previous day's attacks, coupled with some of that objective data, does that partially formulate the strategy also?
[00:14:29.200 --> 00:14:40.880] Or is it mostly based on historical data from training where you say, I know that when he's at this many watts per kilo for this many minutes, he has the capacity to recover?
[00:14:41.200 --> 00:14:45.680] The latter, where we have all that physiological data and the trends.
[00:14:45.680 --> 00:14:51.280] What we see at this level, these guys, they're so good at knowing their feelings.
[00:14:51.280 --> 00:14:54.160] Sometimes it's just kind of how they wake up.
[00:14:54.160 --> 00:14:55.760] You know his capabilities.
[00:14:55.760 --> 00:15:01.280] So if he wakes up fresh, he's like a baby, boom, then you're ready.
[00:15:01.280 --> 00:15:08.000] And sometimes, yeah, it's just we try not to focus on many other metrics that they, because we have already things.
[00:15:08.000 --> 00:15:13.360] And sometimes heart revility might not be very precise.
[00:15:13.360 --> 00:15:30.480] And we don't want to put some ideas in the head that, and in fact, speaking with him, you know, and I'm not going to mention any brand or anything, but looking at heart rate variability some days, you say, like, look, today you told me that I was fatigued, that algorithm, and I went out there and beat my record and the clients.
[00:15:30.640 --> 00:15:31.920] Obviously, I'm not fatigued.
[00:15:32.080 --> 00:15:36.240] Third days, it tells you you're in top form, and I feel a little more fatigued.
[00:15:36.240 --> 00:15:40.080] So, this is what these algorithms we need to be careful sometimes.
[00:15:40.080 --> 00:15:47.120] And might work with maybe general population, but with this type of athletes, at this level, I really feel that it's better.
[00:15:47.120 --> 00:15:50.320] Once you have all the work done, you know their capabilities.
[00:15:50.320 --> 00:15:51.920] Like, are you ready to go?
[00:15:51.920 --> 00:15:54.960] It's like a top performer at a theater.
[00:15:54.960 --> 00:15:56.720] You have worked very hard.
[00:15:56.720 --> 00:15:58.880] Now it's up to, like, are you ready to go?
[00:15:58.880 --> 00:16:00.520] Do you have a good night's lead?
[00:15:59.920 --> 00:16:01.560] Are you ready to perform?
[00:16:01.880 --> 00:16:05.000] And a good performer will say, yes, I'm ready to go.
[00:16:05.000 --> 00:16:06.440] I agree with you completely.
[00:16:06.440 --> 00:16:14.760] Even for me, and I'm not a top-level anything, I have not found the predictors of readiness.
[00:16:14.760 --> 00:16:18.600] to be very accurate or to necessarily reflect how well I'm going to perform.
[00:16:18.600 --> 00:16:21.240] I've had amazing performances.
[00:16:21.240 --> 00:16:22.840] By performances, I mean workouts.
[00:16:22.840 --> 00:16:24.680] That's the only metric I'm performing in.
[00:16:24.680 --> 00:16:30.520] I've had amazing workouts when my prediction was that it would not be good.
[00:16:30.520 --> 00:16:35.720] And I've also had the predictions saying you're on top of the world and I've not performed well.
[00:16:35.720 --> 00:16:42.440] So I wish I could say with more clarity what the frequency of those deviations or discordances are.
[00:16:42.440 --> 00:16:47.800] But I can agree that putting the wrong idea in somebody's head when there's nothing you can do about it.
[00:16:47.800 --> 00:16:48.840] I mean, that's the other thing, too.
[00:16:48.840 --> 00:16:55.640] It's sort of like, at best, if it was perfectly accurate, it would be great because you could say, look, today maybe we shouldn't attack.
[00:16:55.640 --> 00:16:57.640] Today it's damage control day.
[00:16:57.640 --> 00:17:21.960] One of the things I want to ask you about here, and you've spoken about this publicly, so it might be that you're just going to restate the views that you've shared publicly, but I've always felt that now that we have such great transparency from that high octane era of the maximum probably cheating in cycling, which in my view is kind of that two decades of the 90s and 2000s.
[00:17:21.960 --> 00:17:30.120] We pretty much know now what kind of numbers cyclists were putting out when they were being assisted by EPO and blood transfusions.
[00:17:30.120 --> 00:17:38.040] And we sort of know that the best of the best were able to put out somewhere between about 6.8 and 7.1 watts per kilo at FTP.
[00:17:38.040 --> 00:17:41.480] We also know today that cyclists are not doing that.
[00:17:41.480 --> 00:17:44.600] Those numbers are nowhere to be found in the Peloton.
[00:17:44.600 --> 00:17:48.400] Now, that's information you and I share confidentially.
[00:17:48.400 --> 00:17:50.880] That's not public knowledge.
[00:17:50.880 --> 00:17:59.760] But I know it, you know it, and anyone coaching people at that level know that nobody's putting out 7.1 watts per kilo.
[00:17:59.760 --> 00:18:02.960] You don't need to be at 7.1 watts per kilo to win the tour today.
[00:18:02.960 --> 00:18:06.720] You could probably win the tour today at 6.1 watts per kilo.
[00:18:06.720 --> 00:18:19.680] Do you think that making that data public would put to rest a lot of the criticisms that say they've just found new ways to cheat, but it's still basically a dirty sport?
[00:18:19.680 --> 00:18:28.800] Because when you look at the data objectively, it would be very hard to say that today based on what we know from the era when drug use was rampant.
[00:18:28.800 --> 00:18:30.800] No, I think you make a very good point.
[00:18:30.800 --> 00:18:38.880] It frustrates me when people think that they're doing 7 watts per kilogram, 7.2, and then you have the real data from the day.
[00:18:38.880 --> 00:18:40.800] And this is way lower.
[00:18:40.800 --> 00:18:44.800] The short climbs where they would do maybe 7.2.
[00:18:44.800 --> 00:18:46.880] Now they're doing 6.3 maybe.
[00:18:46.880 --> 00:18:50.880] And the longer climbs, they're doing 5.5, 5.8.
[00:18:50.880 --> 00:18:53.280] It frustrates me because I see this data.
[00:18:53.280 --> 00:18:56.560] Gosh, I wish I could just boom release it.
[00:18:56.560 --> 00:18:59.040] I have absolutely no problem with that.
[00:18:59.040 --> 00:19:00.480] We debated it with the team.
[00:19:00.560 --> 00:19:01.680] We're keeping all this.
[00:19:01.680 --> 00:19:04.560] At the end of the day, people can figure that out.
[00:19:04.560 --> 00:19:15.520] And some people, what I see on internet, because you can see the weight of the cyclist, the grade of the grade, when it starts, the time, and the wind, you can be very accurate at knowing that.
[00:19:15.520 --> 00:19:20.080] And I see some people, they're quite accurate on the internet, but I see other ones are all over the map.
[00:19:20.080 --> 00:19:22.080] Did the formula in 7.2?
[00:19:22.400 --> 00:19:24.160] My gosh, I wish I could show him.
[00:19:24.160 --> 00:19:26.640] Maybe this is the real data that we're seeing.
[00:19:26.640 --> 00:19:27.600] Two points there.
[00:19:27.600 --> 00:19:33.320] It's like one, it's private data that the team considers, like not release it.
[00:19:29.840 --> 00:19:34.360] That's team policy.
[00:19:34.680 --> 00:19:51.160] But the other one, too, is like, even if you release that data, there are always going to be people that are not going to believe you, or they might say, oh, they probably altering the data or they're tricking it somehow or putting more weight to the data so it looks like there's less power output.
[00:19:51.160 --> 00:19:54.120] I don't know if it's, it'll be an endless fight.
[00:19:54.120 --> 00:19:55.400] I don't have the answer.
[00:19:55.400 --> 00:20:01.640] I just have that frustration that I wish that I could really show the data and people can see it.
[00:20:01.640 --> 00:20:06.440] There's always going to be someone who is not going to believe it and going to make a lot of noise out of that.
[00:20:07.400 --> 00:20:12.280] That's the other thing too, is like other teams and other writers are releasing their data.
[00:20:12.280 --> 00:20:16.920] So by releasing their data, you can see pretty much where Pogatar is.
[00:20:16.920 --> 00:20:34.760] Okay, if it's a minute ahead or 30 minutes, or sometimes with the same time, you can see, you know, like, whoa, whatever the writer has done and has entering Pogato's group or 30 seconds later and has done 5.9, Bagshar is going to be in that neighborhood, not going to be seven, you know, with 30 seconds ahead.
[00:20:34.760 --> 00:20:51.560] In the spirit of releasing data, the other thing it would potentially do, especially if you could see it in real time, I don't know if you watch Formula One, but one of the things about Formula One that I think the sport has been able to do because of the advances in technology is make more of the data available to the viewer.
[00:20:51.560 --> 00:20:57.240] If you're watching Lewis Hamilton driving a lap, you see what he sees now.
[00:20:57.240 --> 00:21:00.680] You can see, and it's not the end-of-the-world data, but you see his speed.
[00:21:00.680 --> 00:21:02.200] You see what gear he's in.
[00:21:02.200 --> 00:21:05.240] You see the difference between throttle and brake pressure.
[00:21:05.240 --> 00:21:14.120] They could show even more data, certainly, and someone who drives would appreciate it if you really saw brake bias and if you saw brake pressure and lockup and things like that.
[00:21:14.120 --> 00:21:18.000] And you can hear the drivers speaking with their race engineers.
[00:21:14.840 --> 00:21:21.440] So it basically allows you to come more and more into what they're doing.
[00:21:21.680 --> 00:21:26.080] This year they introduced a new camera angle, which is what the driver sees.
[00:21:26.080 --> 00:21:33.920] And I think it's fantastic because historically you see above them and it looks so smooth, but that's not at all what it feels like to be in a race car.
[00:21:33.920 --> 00:21:40.000] So now they just literally put like a camera at their shoulder and now you see how restrictive the halo is.
[00:21:40.000 --> 00:21:43.440] You see the bumps and it looks a lot faster.
[00:21:43.440 --> 00:22:01.840] You know, I've had this discussion with a number of people, which is if you could show the same sort of information in cycling, if every time the camera went over to a cyclist, you saw their heart rate, their watts per kilo, their speed, all of these other things, and you could hear some of the communications back and forth with their teams.
[00:22:01.840 --> 00:22:03.680] Yes, that changes the sport.
[00:22:03.680 --> 00:22:06.720] Strategically now, you have to be careful what you say on the radio.
[00:22:06.720 --> 00:22:11.440] But it also allows you to see the human element of this sport a little bit more.
[00:22:11.440 --> 00:22:13.120] Do you think that will ever happen?
[00:22:13.120 --> 00:22:19.280] Where you'll be able to flip on the Tour de France and you'll be able to actually see real-time physiology?
[00:22:19.280 --> 00:22:20.000] I would love it.
[00:22:20.000 --> 00:22:22.560] It would be so much fun for the viewer.
[00:22:22.560 --> 00:22:31.200] And cycling has so many possibilities to engage people more and be fascinated by the physiology and looking at these numbers.
[00:22:31.200 --> 00:22:36.240] It's already in a way, you see some cameras already installed in the front and the back.
[00:22:36.240 --> 00:22:37.600] It's called Velon.
[00:22:37.840 --> 00:22:43.520] You can see really cool images when they're preparing a sprint that is like what feels inside.
[00:22:43.520 --> 00:22:45.360] And you can see it's really scary.
[00:22:45.360 --> 00:22:56.000] Sometimes you can appreciate how difficult it is to be at 40 miles an hour sprinting or 35 miles an hour leading to a sprint or in a descent at 60 miles an hour or 70 miles an hour.
[00:22:56.000 --> 00:22:57.440] 70 miles an hour descent.
[00:22:57.440 --> 00:22:58.160] Exactly.
[00:22:58.480 --> 00:23:02.280] And then you can see the power output in real time.
[00:22:59.840 --> 00:23:03.800] I think it's a great step.
[00:23:04.120 --> 00:23:10.520] You don't see all the writers, but it's estimation, only the writers who wear that villain or the villain decides to do that.
[00:23:10.520 --> 00:23:14.920] And I think that they're still not doing that with all the top contenders.
[00:23:14.920 --> 00:23:16.360] But I think it's a first step.
[00:23:16.360 --> 00:23:20.920] And obviously, I haven't spoken with them, but maybe it's like, hey, let's see what's the feedback.
[00:23:20.920 --> 00:23:22.840] And I think that people are loving it.
[00:23:22.840 --> 00:23:25.160] I would expect that this will increase.
[00:23:25.160 --> 00:23:37.560] I would love at some point, you know, and as you know very well, in the world of biosensors, it's going to revolutionize sports where we're going to be able to see so many different parameters of athletes in real time.
[00:23:37.560 --> 00:23:41.080] Yeah, imagine you could see lactate and glucose in real time.
[00:23:41.080 --> 00:23:41.400] Absolutely.
[00:23:41.560 --> 00:23:44.280] Which, of course, is technologically feasible already.
[00:23:44.280 --> 00:23:45.160] Exactly.
[00:23:45.160 --> 00:23:45.720] Yeah.
[00:23:46.040 --> 00:23:48.280] I think I would love for all sports too.
[00:23:48.280 --> 00:23:55.560] Imagine you can see an NBA basketball game and see that the lactate of LeBron James compared to the other ones.
[00:23:55.560 --> 00:23:58.120] I mean, I would love to see that as a spectator.
[00:23:58.120 --> 00:24:01.640] And I hope that someday we were able to see these parameters.
[00:24:01.640 --> 00:24:05.640] So last thing on the tour, talk to me about Vantu this year.
[00:24:05.640 --> 00:24:07.080] That was a tough stage.
[00:24:07.080 --> 00:24:08.760] It looked like his toughest stage.
[00:24:08.760 --> 00:24:10.120] Is that a fair assessment?
[00:24:10.120 --> 00:24:11.320] Yes, probably.
[00:24:11.320 --> 00:24:14.360] And what's amazing, I think, is the poise on that stage.
[00:24:14.360 --> 00:24:22.200] It's hard to tell if he was really struggling on the ascent of Vantu or he was just deciding strategically, I'm going to conserve a little bit of energy here.
[00:24:22.200 --> 00:24:23.560] What was your take on that?
[00:24:23.560 --> 00:24:25.080] Or what can you say about that?
[00:24:25.080 --> 00:24:28.360] It was a very difficult climb and a very long climb.
[00:24:28.360 --> 00:24:32.280] Tadeh, his mentality is wired like a champion.
[00:24:32.280 --> 00:24:41.800] When someone goes and they were full gas in the last part, Vineagar attacked, Tadeh knew that this is not going to be the top of Bon Van 2 is not going to be the end of the stage.
[00:24:41.800 --> 00:24:48.240] That's a very, very long descent and I have some partners with me that they can help me out.
[00:24:48.560 --> 00:24:53.360] I'm not going to panic at all, but I'm not going to also waste a lot of energy.
[00:24:53.360 --> 00:24:55.440] He also had a big gap.
[00:24:55.600 --> 00:24:58.560] A whole different thing would have been if he had 20 seconds.
[00:24:58.560 --> 00:25:06.720] But having a big gap and knowing that you have a big descent and how calmed it is, that's one thing that is a very important strategy.
[00:25:06.720 --> 00:25:07.840] This is what happened.
[00:25:07.840 --> 00:25:14.400] This reminds me in a way what happened the first year that he was pro when he was 19 at the tour of California.
[00:25:14.400 --> 00:25:21.520] It was the previous stage before Bear Lake, Top Mountain in the Tour of California, where it's going to be decided.
[00:25:21.520 --> 00:25:28.400] So the day before, two cyclists, George Bennett and Yugita, attacked in a short but very steep climb.
[00:25:28.400 --> 00:25:31.040] And there were only like 12 riders left.
[00:25:31.040 --> 00:25:32.800] And Yuita and Bennett attacked.
[00:25:32.800 --> 00:25:37.920] Then there was like a descent and a long highway all the way to the finish line.
[00:25:37.920 --> 00:25:40.080] So there was plenty of time to catch him up.
[00:25:40.080 --> 00:25:41.920] But Tale didn't follow them up.
[00:25:41.920 --> 00:25:44.720] Another rider would have just followed their wheel.
[00:25:44.720 --> 00:25:47.360] And Tale decided, no, I'm not going to follow them.
[00:25:47.360 --> 00:25:51.280] We have time and I'm going to take the chance because I'm confident for tomorrow.
[00:25:51.280 --> 00:25:57.600] And when I asked him as soon as he crossed the finish line, I asked him, are you okay why you didn't follow their attack?
[00:25:57.600 --> 00:26:02.640] He said, well, I just, I wanted to know who is going to be good tomorrow.
[00:26:02.640 --> 00:26:14.400] So I know those two guys are going to be good tomorrow, but I wanted to take my time and see the other 10 guys, how they're breathing, what's their body language, take my time to observe to start preparing my strategy for tomorrow.
[00:26:14.400 --> 00:26:15.920] And in fact, that's what he did.
[00:26:15.920 --> 00:26:19.200] They were then caught up two, three kilometers to the finish line.
[00:26:19.200 --> 00:26:22.480] So all those 12, 13 guys, whatever they were, they got together.
[00:26:22.480 --> 00:26:26.800] And the next day, in fact, he noticed those two guys attacked.
[00:26:26.800 --> 00:26:29.880] He just followed them and he just eliminated one by one.
[00:26:29.880 --> 00:26:31.560] That's how this guy thinks.
[00:26:31.560 --> 00:26:33.640] No panic, plenty of time today.
[00:26:29.440 --> 00:26:35.880] I had a good gap in the GC.
[00:26:36.200 --> 00:26:46.440] Why am I going to go full gas when I know that he's going to go full gas and he might lose energy for tomorrow because he might pay for this at this time of the tour de France?
[00:26:46.440 --> 00:26:48.520] And we have plenty of time to catch him up.
[00:26:48.520 --> 00:26:51.080] So that's kind of the strategy that he had.
[00:26:51.080 --> 00:26:58.600] How much time does someone like Tadi spend in zone two, which we're going to talk a lot about?
[00:26:58.600 --> 00:27:07.080] And let's do it more as percentage of training time because I think absolute numbers will be very large given that that's his job.
[00:27:07.080 --> 00:27:14.680] But when you think about the percentage of time he spends in that energy zone, how does it change over the course of the year?
[00:27:14.680 --> 00:27:24.360] So presumably during the winter months, a greater amount of his time would be spent there as he's base building right before a race when he's kind of sharpening, maybe less.
[00:27:24.360 --> 00:27:26.120] What would be the range of time?
[00:27:26.120 --> 00:27:27.080] Or percent, rather?
[00:27:27.080 --> 00:27:27.880] Yeah, yeah.
[00:27:27.880 --> 00:27:28.440] You're right.
[00:27:28.440 --> 00:27:36.520] When we talk about percentage, I like to put it this way: more like a percentage of days dedicated to cultivate that energy system.
[00:27:36.520 --> 00:27:42.200] Obviously, if you put in just every single minute together, the majority is going to be that.
[00:27:42.200 --> 00:27:43.800] But I would say more in days.
[00:27:43.800 --> 00:27:49.800] In the winter months, might be about 80%, 70 to 80% of the days.
[00:27:49.800 --> 00:27:57.720] As the season gets closer, he starts increasing more the intensity days and sessions when the start of the season racing.
[00:27:57.720 --> 00:27:59.480] And you have, it depends.
[00:27:59.480 --> 00:28:07.240] You might have one stage race of five, seven days, and then you have a five-day block or one week to recover, and then you have the next stage rate.
[00:28:07.240 --> 00:28:09.480] So in that week, we do a lot of recovery.
[00:28:09.480 --> 00:28:11.720] We might do some sessions here and there.
[00:28:11.720 --> 00:28:23.280] And then after a few blocks of races, that's where you have another long time to train, period, to train, go to altitude towards the True de France or toward the next goal.
[00:28:23.280 --> 00:28:28.960] And that's where you may revisit these different energy systems and train specifically.
[00:28:28.960 --> 00:28:38.800] We alternate, and each energy system has a time in the year, in the calendar, what it's built in order to try to achieve what we want.
[00:28:39.120 --> 00:28:41.120] So let's remind people now.
[00:28:41.120 --> 00:28:46.880] I've put out a few posts on social over, gosh, the past year and even in the past little while.
[00:28:46.880 --> 00:28:53.680] And anytime I'm talking about zone two, it's really one of the topics that generates the most curiosity, the most inquiry from people.
[00:28:53.680 --> 00:28:57.680] I think people really intuitively kind of resonate with this.
[00:28:57.680 --> 00:29:02.880] And then, of course, a million questions follow because there's so much minutia and detail around it.
[00:29:02.880 --> 00:29:04.800] And a lot of that we're going to cover today.
[00:29:04.800 --> 00:29:12.000] But let's start from a place of maybe someone hasn't heard the first podcast where we go through some of the semantics of this.
[00:29:12.000 --> 00:29:14.000] Define zone two.
[00:29:14.320 --> 00:29:23.280] From my point of view, it is the exercise intensity at the one you are stressing the mitochondria and oxidative capacity to the most.
[00:29:23.280 --> 00:29:27.120] This is where you're recruiting mainly type 1 muscle fibers.
[00:29:27.120 --> 00:29:36.800] This is where you are mobilizing the highest amount of fat, both from lipolysis, from matipose tissue, as well as from fat oxidation inside the mitochondria.
[00:29:36.800 --> 00:29:44.400] And this is also where you stimulate all those bioenergetics, which is oxidative phosphorylation.
[00:29:44.400 --> 00:29:51.120] This is where you burn both the fat inside a mitochondria as well as the glucose inside the mitochondria.
[00:29:51.120 --> 00:30:02.200] There's not a very high glycolytic flux that it's going to be transforming to pyruvate and reduced to lactate, but that flux still is oxidized inside mitochondria.
[00:30:02.520 --> 00:30:08.440] This is looking at from a bioenergetics standpoint, this is what I would consider the zone two.
[00:30:08.440 --> 00:30:22.840] And what I have seen is that throughout the years is that this is the exercise intensity that achieves or stimulates that mitochondrial function and fat oxidation and lactate cleanse capacity the most.
[00:30:22.840 --> 00:30:24.520] That's the other thing too.
[00:30:24.520 --> 00:30:31.160] This is where other things involving lactate, so lactate is a great fuel to cells.
[00:30:31.160 --> 00:30:36.840] It's in fact probably the preferred fuel for the cells, for most cells in the body.
[00:30:36.840 --> 00:30:42.040] This is a work that my colleague and mentor and friend George Brooks discovered.
[00:30:42.040 --> 00:30:45.080] You should have him someday in the podcast because he's fascinating.
[00:30:45.080 --> 00:30:50.200] I mean, I would not be surprised if someday soon we hear that he wins a Nobel Prize.
[00:30:50.200 --> 00:30:51.240] He's amazing.
[00:30:51.240 --> 00:30:54.760] And every time I talk to him, I'm still learning a lot of things.
[00:30:54.760 --> 00:30:57.640] And I've been translating a lot of his research.
[00:30:57.640 --> 00:31:05.640] That's how I see that you have within the mitochondrial function, you see how lactate is oxidized in the mitochondria back to energy.
[00:31:05.640 --> 00:31:08.680] And that happens in those muscle fiber types.
[00:31:08.680 --> 00:31:21.560] Those muscle fiber types in the mitochondria, those fiber types also develop these transporters, which are MCT1s, which are the ones that transport lactate inside the cell and inside the mitochondria.
[00:31:21.560 --> 00:31:28.200] So when you stimulate that training zone, you stimulate all these energy systems and the components that come with them.
[00:31:28.200 --> 00:31:32.920] So let's talk about the different ways that one can go about estimating this.
[00:31:32.920 --> 00:31:45.280] Based on the definition you've just given, it seems to me that the purest way to estimate this would be via indirect calorimetry, because that will actually tell us the fat oxidation.
[00:31:45.280 --> 00:31:46.800] Is that a fair assessment?
[00:31:46.800 --> 00:31:48.560] Yes, it's a very good assessment.
[00:31:44.840 --> 00:31:51.360] That usually correlates with the fat max.
[00:31:51.440 --> 00:31:52.880] That's how we call it too, right?
[00:31:52.880 --> 00:31:54.320] That's fat oxidation.
[00:31:54.320 --> 00:32:08.720] And when you see that you start oxidizing fat and might increase in cases and gets to a point that it maxed out, which is the fat max, and then it starts going down sharply as exercise intensity increases.
[00:32:08.720 --> 00:32:10.720] So let's tell people how that's measured.
[00:32:10.720 --> 00:32:21.440] We do this with all of our patients, and I find it to be not that easy to explain because there's some physiology involved and there's some math involved.
[00:32:21.440 --> 00:32:24.000] But let me try to see if I can explain this to folks.
[00:32:24.000 --> 00:32:27.200] So you hook me up to an indirect calorimeter.
[00:32:27.200 --> 00:32:30.320] So you're going to put a little plug on my nose.
[00:32:30.320 --> 00:32:33.680] You're going to put a mask over my nose and mouth.
[00:32:33.680 --> 00:32:41.040] That mask has the ability to measure the amount of oxygen that I consume because it has a sensor for O2.
[00:32:41.040 --> 00:32:45.920] So it knows that the O2 that's coming in is at 21%.
[00:32:45.920 --> 00:32:48.240] The air is coming in at 21% O2.
[00:32:48.240 --> 00:32:51.520] And whatever I exhale is the difference between that.
[00:32:51.520 --> 00:32:54.240] So you can now tell how much O2 is consumed.
[00:32:54.240 --> 00:32:56.640] And you can have a similar sensor for carbon dioxide.
[00:32:56.640 --> 00:32:58.480] So you know how much carbon dioxide is produced.
[00:32:58.480 --> 00:33:07.040] So it's very easy to measure consumed oxygen and produced carbon dioxide provided you can completely isolate around the nose and the mouth.
[00:33:07.040 --> 00:33:17.600] As you hook a person up to some form of ergometer, usually a bike, could be a treadmill, a rowing machine, or something like that, you can increase the demand on the muscle.
[00:33:17.600 --> 00:33:20.880] So you increase the wattage or the speed or the something.
[00:33:20.880 --> 00:33:26.320] You then get out these numbers, VO2 and VCO2, which are what we just talked about.
[00:33:26.320 --> 00:33:29.960] So consumption of oxygen, production of carbon dioxide.
[00:33:29.440 --> 00:33:35.160] These numbers fit into a relatively straightforward linear equation called the Weir equation.
[00:33:35.480 --> 00:33:38.200] And it tells you three things.
[00:33:38.200 --> 00:33:43.720] It tells you total energy consumption in kilocalories per minute.
[00:33:43.720 --> 00:33:54.440] And then the ratio of VO2 and VCO2 tell you how much of that energy is coming from fat oxidation and how much of it is glycolytic.
[00:33:54.440 --> 00:34:13.240] So at any moment in time, you can look at a VCO2 and a VO2, which are usually measured in liters per minute, and you can convert that into a total grams of fat oxidation and a total grams of glucose oxidation per minute.
[00:34:13.240 --> 00:34:22.680] And so you could then plot on the x-axis work or power, and on the y-axis, you could plot fat oxidation.
[00:34:22.680 --> 00:34:32.440] Again, describe for people what the shape of that curve looks like and what differentiates Pogacha from the average human being.
[00:34:32.440 --> 00:34:33.720] You explain it very well.
[00:34:33.720 --> 00:34:36.600] Yeah, those are based on stoichiometric equations.
[00:34:36.600 --> 00:34:40.680] The combustion of carbohydrates and fatty acids by done in the body.
[00:34:40.680 --> 00:34:47.880] Already in the 1920s, Francis Benedict, one of the first ones, probably the first one who started to look into this at this level.
[00:34:47.880 --> 00:34:56.040] Obviously, we have evolved, do it in a more automatic way with these indirect calorimetries, machines or calls or metabolic cards.
[00:34:56.040 --> 00:35:06.520] As exercise intensity increases, I mean, you need more oxygen, so your VO2 increases, and then you produce or give up more CO2.
[00:35:06.840 --> 00:35:08.920] So this is kind of what it shows.
[00:35:08.920 --> 00:35:18.000] When you're in a more licolytic state, more fatty oxidation state, you still consume oxygen but you do not produce as much CO2.
[00:35:18.320 --> 00:35:34.880] When you are more into a more glycolytic state, which is higher exercise intensities, when you're recruiting the type 2 muscle fibers, and therefore using more glucose for energy purposes, you're going to consume more oxygen and you're going to produce more CO2.
[00:35:34.880 --> 00:35:51.200] Plugging in all these numbers into these stoichiometric equations, it's going to give you that profile, the X and the Y axis, and it's going to see what is the fat oxidation throughout RAMP state, a RAMP test.
[00:35:51.200 --> 00:36:09.040] And this is where you're going to see elite athletes like Bogachar, they have an amazing fat oxidation capacity compared to other competitive athletes or recreationals or people with even type 2 diabetes or metabolic syndrome or in a recent study that we have published with COVID patients.
[00:36:09.040 --> 00:36:19.600] So it reflects in a way, ultimately, what happens in your mitochondria and how the mitochondria oxidizes those fuels at different exercise intensities.
[00:36:19.600 --> 00:36:33.280] So for example, let's say at the intensity of 200 watts, a lead athlete doesn't need to incur in that glycolytic capacity as much as someone who is not very well trained.
[00:36:33.280 --> 00:36:47.200] So the elite athlete, they can still recruit slow twitch muscle fibers and rely a lot on fat to produce ATP because they have an amazing mitochondrial function and they're very efficient, metabolically speaking.
[00:36:47.200 --> 00:36:50.000] Therefore, they're going to be oxidizing a lot of fat.
[00:36:50.000 --> 00:37:15.880] However, someone whose mitochondria are not working as well, whether you are like a recreational athlete or sedentary individual or someone with type 2 diabetes, which is one of the hallmarks of the disease, that mitochondrial impairment or dysfunction at 200 watts, you fully rely on glucose pretty much because you cannot sustain that effort with fat alone.
[00:37:15.880 --> 00:37:21.080] And this is what you're going to be seeing, this gas exchange, the CO2 and the VO2.
[00:37:21.240 --> 00:37:33.640] You can just plot it into the equation, and it's going to give you all that what I call metabolic map, where you see the fat oxidation, the carbohydrate oxidation, and then I plug in also the lactate.
[00:37:33.640 --> 00:37:36.840] And that's where everything comes together quite well.
[00:37:36.840 --> 00:37:48.360] And you can then first, in an indirect way, calculate the mitochondrial function and metabolic flexibility, how flexible they are at using fats or carbohydrates.
[00:37:48.360 --> 00:37:51.480] And also, you can determine training zones.
[00:37:51.480 --> 00:37:56.520] I've been using this methodology for 16 years, 17, something like that.
[00:37:56.520 --> 00:38:19.640] I didn't think to ask you this earlier, but if you have it handy, do you want to pull up a graph of what fat oxidation looks like versus power so that people can see the difference between a highly trained individual, a reasonably trained individual, an untrained individual, and at the other end of that spectrum somebody with type 2 diabetes?
[00:38:19.960 --> 00:38:27.160] So this is from a publication that my colleague George Brooks and I published in 2017.
[00:38:27.480 --> 00:38:30.920] This is the formula, and we have realized that this is flipped.
[00:38:30.920 --> 00:38:37.160] So we need to work now with the editor to change it because the formula is flipped here in the methods section.
[00:38:37.160 --> 00:38:38.360] Which is so funny, by the way.
[00:38:38.360 --> 00:38:39.240] I like seeing that.
[00:38:39.240 --> 00:38:54.720] I'm embarrassed to say when we do this for our patients, we do it in two steps, which yields the same result, but we first calculate energy expenditure using the weir coefficients of 3.94 times VO2 minus plus 1.
[00:38:55.040 --> 00:38:57.920] I think it's 1,2 times VCO2.
[00:38:57.920 --> 00:39:08.320] And then we convert that to fat ox and carbohydrate oxidation using the ratio of VCO2 to VO2.
[00:39:08.320 --> 00:39:15.680] And I never even thought to do what you've done here, which is so much more logical, which is combine them into a single equation for each.
[00:39:15.680 --> 00:39:21.920] Well, we use what Fryan observed already in 1983, and this is Fryan's equation.
[00:39:21.920 --> 00:39:25.760] And it's been validated with tracers, stable isotope tracers.
[00:39:25.760 --> 00:39:26.800] Doubly labeled water.
[00:39:26.800 --> 00:39:28.400] Yeah, and that's what it shows.
[00:39:28.400 --> 00:39:29.840] There's a very high correlation.
[00:39:29.840 --> 00:39:40.800] Now, furthermore, in a study that we were going to be publishing soon, we have validated this fat oxidation and carbohydrate directly with mitochondrial respiration.
[00:39:40.800 --> 00:40:04.720] So in muscle biopsies, we inject directly fatty acids, pyruvate representative of carbohydrates, glutamine representative of amino acids, and then we can see that there's a very high correlation between this indirect methodology to look at mitochondrial function and the direct methodology, which is through muscle biopsy and injecting the substrate and see how it's oxidized.
[00:40:04.720 --> 00:40:06.960] So these two graphs are really powerful.
[00:40:06.960 --> 00:40:10.080] Let's talk about what the first graph is showing us.
[00:40:10.080 --> 00:40:14.560] So both of these graphs, it's important to note, have the same x-axis.
[00:40:14.560 --> 00:40:20.400] In other words, the independent variable here is the workload in watts.
[00:40:20.400 --> 00:40:25.280] That's the metric that matters in cycling, which is, I think, the easiest way to do this test.
[00:40:25.280 --> 00:40:26.960] And so you're increasing wattage.
[00:40:26.960 --> 00:40:30.000] This is a progressive increase in workload.
[00:40:30.520 --> 00:40:37.960] And what you're plotting on the y-axis, your dependent variable here in the first graph, figure one, is blood lactate.
[00:40:37.960 --> 00:40:40.680] What stands out to me is a couple of things.
[00:40:40.680 --> 00:40:44.760] So you have the triangles represent metabolic syndrome.
[00:40:44.760 --> 00:40:49.080] The squares represent a modestly trained athlete.
[00:40:49.080 --> 00:40:52.200] And then the little diamonds represent a professional athlete.
[00:40:52.200 --> 00:41:02.600] The first thing that stands out to me, and we're going to talk about this later, so I'll put a little pin in this, is that the people with metabolic syndrome have a resting lactate that's almost two millimole.
[00:41:02.600 --> 00:41:04.200] Yes, we see already this.
[00:41:04.200 --> 00:41:09.960] I think that it's going to become more and more as a biomarker, like resting blood glucose levels.
[00:41:09.960 --> 00:41:11.800] What is your resting lactate?
[00:41:11.800 --> 00:41:25.160] You can see already in patients with type 2 diabetes or profound metabolic syndrome that, yeah, as you say perfectly, yeah, resting levels are in the neighborhood of like a 1.8, 1.5 to even 3.
[00:41:25.480 --> 00:41:34.520] So one of the metrics that we've discussed at length, and we'll revisit it, of course, is using this lactate level of about 2 millimole as being that threshold.
[00:41:34.520 --> 00:41:43.160] So once lactate exceeds 2 millimole, the individual is now escaping out of zone 2 and they're actually now into zone 3.
[00:41:43.160 --> 00:41:51.880] So when you look at these data here, you can see that the individual with metabolic syndrome is basically tapping out zone 2 initially.
[00:41:51.880 --> 00:41:57.880] So any incremental workload that is placed on them takes them right out of zone 2.
[00:41:57.880 --> 00:42:04.280] For all intents and purposes, by the time they're at 100 watts, they're already at the threshold of their zone 2.
[00:42:04.280 --> 00:42:21.840] Now, conversely, when you look at that medium-trained or reasonably well-trained individual, I think it's referred to as moderately active, healthy individuals, they start out with a lactate of about one, and it's not really until they hit about 175 watts that they pass that inflection point.
[00:42:22.160 --> 00:42:42.800] And then, when you look at the professional athletes, the professional endurance athletes specifically, they're starting out at a lactate level of 0.5 millimol, and they stay relatively flat until they hit about 300 watts, is when they finally cross over that threshold.
[00:42:42.800 --> 00:42:51.200] Now, what's not captured here is that as you move from left to right, the athletes are getting lighter.
[00:42:51.520 --> 00:42:58.400] So, this graph, if I'm going to be critical of it in Yugo, I would say it should be done in watts per kilo.
[00:42:58.400 --> 00:43:03.040] And that would show a much starker difference between these.
[00:43:03.040 --> 00:43:10.080] And in our patients, when we benchmark them, we benchmark them in watts per kilo for this reason, so that you normalize by weight.
[00:43:10.080 --> 00:43:12.400] And I'm certain, Travis, you're absolutely right.
[00:43:12.400 --> 00:43:14.080] And that's how we do it also.
[00:43:14.080 --> 00:43:18.240] One of the reviewers didn't allow us to use watts per kilogram.
[00:43:18.240 --> 00:43:23.360] Clearly, that reviewer was an idiot, so that's I won't hold it against you because the idiot reviewer.
[00:43:23.520 --> 00:43:24.800] You know how it is in review papers.
[00:43:24.800 --> 00:43:32.720] You want to show something, and eventually it's changed, and it's not exactly sometimes what you want to show because otherwise they don't allow you to publish it.
[00:43:32.720 --> 00:43:33.520] But, anyways.
[00:43:33.520 --> 00:43:41.840] But what's amazing here is that person with metabolic syndrome is probably about one watt per kilo, easily.
[00:43:41.840 --> 00:43:45.520] One to 1.3 watts per kilo is their zone two.
[00:43:45.520 --> 00:43:51.040] When you look at the modestly trained individual, they're about 2 watts per kilo.
[00:43:51.040 --> 00:43:55.920] They probably weigh maybe 2 to 2.1, 2.2 watts per kilo.
[00:43:55.920 --> 00:44:02.040] That professional endurance athlete probably weighs in the neighborhood of 70 kilos.
[00:43:59.600 --> 00:44:06.120] So they're in the ballpark of 4 watts per kilo.
[00:44:06.360 --> 00:44:11.240] For our patients, Inigo, we set the aspiration at 3 watts per kilo.
[00:44:11.240 --> 00:44:19.880] So again, our patients aren't professional athletes, but we think that 3 watts per kilo would be kind of the elite level that we would want to see people.
[00:44:19.880 --> 00:44:21.880] And then, of course, we stratify from there.
[00:44:21.880 --> 00:44:25.000] Let's look at the lower figure, figure two, just beneath this.
[00:44:25.000 --> 00:44:28.120] So here, we're looking at the same group of individuals.
[00:44:28.120 --> 00:44:36.600] We have the same independent variable, which is work, but now we're calculating fat oxidation as a function of that work.
[00:44:36.600 --> 00:44:42.520] So now your dependent variable is fat oxidation, which again, very easy to calculate via indirect calorimetry.
[00:44:42.520 --> 00:44:44.440] Two things stand out again.
[00:44:44.440 --> 00:44:51.960] The first is the obvious, which is the fitter the individual, the higher their absolute capacity for fat oxidation.
[00:44:51.960 --> 00:45:08.600] But something else stands out to me in you go, and I have now seen this repeatedly across multiple data sets, which is a fit individual actually increases fat oxidation to a local maxima before beginning that decline.
[00:45:08.600 --> 00:45:13.880] Whereas most mortals begin at a maximum and decline from there.
[00:45:13.880 --> 00:45:15.800] Can you explain why that's happening?
[00:45:15.800 --> 00:45:16.280] I agree.
[00:45:16.280 --> 00:45:17.960] I see this all the time.
[00:45:17.960 --> 00:45:21.480] I think that on one hand is how you start a protocol.
[00:45:21.480 --> 00:45:23.800] In this case, we started like at one.
[00:45:23.800 --> 00:45:27.400] We start about 1 to 1.5 watts per kilogram.
[00:45:27.400 --> 00:45:33.480] And that obviously for an elite athlete is the low resting levels, so this is what they're very low.
[00:45:33.480 --> 00:45:38.360] And they don't need to use much fat for energy purposes until you push them more.
[00:45:38.360 --> 00:45:43.640] And that's when you get to like 2, 2.5, 3, 3.5 watts per kilogram, right?
[00:45:43.640 --> 00:45:50.640] And again, this protocol comes originally from the work that I've been doing for 20 years, the same protocol with elite affiliates.
[00:45:51.040 --> 00:46:01.600] When you do the same protocol with other populations, especially people with metabolic syndrome or not very fit, and you start at 1.5 watts per kilogram, that might be too much.
[00:46:01.600 --> 00:46:11.440] And I'm sure you have observed that if you start at 0.5 watts per kilogram, you might see a higher fat oxidation, and then you might see the same phenomenon.
[00:46:11.440 --> 00:46:19.760] So, on one hand, is that protocol, but on the other hand, yeah, sure, like 0.5 watts per kilogram, it's like nothing.
[00:46:19.760 --> 00:46:23.760] It's close to resting levels, so it will take you for a long time.
[00:46:23.760 --> 00:46:34.800] But that being said, I think that one thing that we're doing with populations, more clinical populations, is really starting at a very low level, even up to 50 watts or 25 watts sometimes.
[00:46:34.800 --> 00:46:46.240] So we can establish these points because if you start at 2 watts per kilogram or 1.5 watts per kilogram with someone with a significant metabolic dysregulation, you're going to miss the fat max.
[00:46:46.240 --> 00:46:47.360] Yeah, I agree with you.
[00:46:47.360 --> 00:46:53.440] We have been struggling to tune our algorithm to exactly that.
[00:46:53.440 --> 00:47:05.440] I actually think, and I had this discussion with our team a week ago, which was the physiologists who are doing this with our patients are probably overcooking the people who are not fit during the warm-up.
[00:47:05.440 --> 00:47:13.600] So they do a warm-up, and the warm-up is actually too stressful, and it overcooks them, and then we're missing the true max fat.
[00:47:13.600 --> 00:47:20.880] The next thing I want to point out here, and let's just look at the fittest person, but it's true for all of them, but it's easiest to see here.
[00:47:20.880 --> 00:47:24.400] Fat max, so fat max ox, right?
[00:47:24.400 --> 00:47:30.280] So maximum fat oxidation is occurring earlier than lactate is two.
[00:47:29.840 --> 00:47:34.920] And that's true for all of them, except for the MET-SIN person, because that's so low.
[00:47:35.240 --> 00:47:46.760] If you look at the moderately fit person, they're hitting maximum fat oxidation at about 130 watts, but they're hitting lactate of two at 175 watts in the upper figure.
[00:47:46.760 --> 00:48:00.920] And the professional athlete is hitting an absolute fat oxidation maxima at a little shy of 250 watts, but they're hitting lactate of two closer to 300 watts.
[00:48:00.920 --> 00:48:11.640] So I guess the question then becomes: you've already answered part of the question, which is we're really defining zone two as the place where maximum fat oxidation occurs.
[00:48:11.640 --> 00:48:19.320] But I guess this would suggest that using a lactate level of two is maybe overestimating where that is.
[00:48:19.320 --> 00:48:25.000] And should we be using a lower level of lactate, such as 1.5 or something like that?
[00:48:25.320 --> 00:48:32.840] This is what I've been learning all these years is that the blood lactate levels might change between different groups.
[00:48:32.840 --> 00:48:38.680] And it's everything related to the lactate kinetics and lactate oxidation in the mitochondria.
[00:48:38.680 --> 00:49:02.680] So for example, elite athletes, this was part of my doctorate thesis and some of this that never published it 20 something years ago, but the same blood lactate concentration does not correspond in an elite athlete, does not correspond necessarily to the same lactate concentration in a recreational athlete, the metabolic stress.
[00:49:02.680 --> 00:49:13.400] So for example, two millimoles, two millimolar of lactate in these elite athletes might be a higher metabolic stress than two millimoles in a metabolic patient.
[00:49:13.400 --> 00:49:16.160] So this is why it would be very difficult.
[00:49:16.160 --> 00:49:26.560] For example, you can have a, let's say, two and a half millimoles, you can have a metabolic syndrome patient exercising for a couple hours without a big deal.
[00:49:26.560 --> 00:49:30.560] You try to do that with a professional athlete, and they're going to be hurting.
[00:49:30.560 --> 00:49:39.600] And in fact, one of the things that I observe is like I use the four millimoles or millimolar, which is kind of that gold standard, it's been forever like the lactate threshold, etc.
[00:49:39.920 --> 00:49:57.280] If you put a world-class athlete at four millimoles at the intensity and power output that elicits four millimoles, and you put a recreational athlete at the power output that elicits also four millimoles, and you say now go, see who likes the most.
[00:49:57.280 --> 00:50:00.720] Intuitively, we're going to say, obviously, it's going to be the professional athlete.
[00:50:00.720 --> 00:50:01.840] It's the opposite.
[00:50:01.840 --> 00:50:04.400] And this is the data that I saw 20-something years ago.
[00:50:04.400 --> 00:50:12.720] The recreational athletes at the same blood lactate concentration would go about 30% longer period of time.
[00:50:12.720 --> 00:50:16.000] And that's because metabolically is not as tusking.
[00:50:16.000 --> 00:50:23.680] And the main reason is that the lactate that we see in the blood, it reflects the mitochondrial oxidation.
[00:50:23.680 --> 00:50:33.520] So someone who has, obviously, when we're talking about high power output, when you need a lot of glycolysis to produce energy, you're going to produce lactate.
[00:50:33.520 --> 00:50:40.480] Lactate is the mandatory, obligatory byproduct, not waste product, but byproduct of glycolysis.
[00:50:40.480 --> 00:50:43.520] So the higher the glycolysis, the higher the lactate.
[00:50:43.520 --> 00:50:46.880] Now that lactate has two routes mainly.
[00:50:46.880 --> 00:50:52.320] One is going from the fast twitch muscle fibers to the slow twitch muscle fibers.
[00:50:52.320 --> 00:51:00.280] It's the lactate chattel that George Brooke discovered and is oxidizing the mitochondria of those slow twitch muscle fibers.
[00:50:59.840 --> 00:51:06.360] If you have a very good lactate clearance capacity, you're going to be oxidizing it very, very well for fuel.
[00:51:06.680 --> 00:51:12.280] Therefore, you're not going to incur in the second step, which is exporting it to the blood.
[00:51:12.280 --> 00:51:25.400] When you have a poorer mitochondrial function, it's going to get to a point that that capacity is going to get saturated at a lower power output, and therefore, you're going to be forced to export that to the blood.
[00:51:25.400 --> 00:51:29.480] So that's why looking at blood lactates might not mean the same.
[00:51:29.480 --> 00:51:32.120] I'm not saying that the disparities are huge by no means.
[00:51:32.120 --> 00:51:40.440] But as you very well said, those two millimoles might not correspond in an elite athlete with a fat max, but might be more maybe towards 1.5.
[00:51:40.440 --> 00:51:46.680] Whereas maybe in someone with a more recreational or metabolic syndrome, it might correspond there.
[00:51:46.680 --> 00:51:48.360] I don't know if it makes sense.
[00:51:48.360 --> 00:51:49.560] It completely makes sense.
[00:51:49.560 --> 00:51:54.760] And this is definitely the level of nuance I don't think we captured in the first podcast.
[00:51:54.760 --> 00:52:00.840] And I want to now ask a more telling question specifically for the middle person here.
[00:52:00.840 --> 00:52:05.560] So the one that's called the moderately active individual, where again, we have a disparity.
[00:52:05.560 --> 00:52:19.560] So based on these data, the moderately fit individual hits a lactate of two millimole at 175 watts, but hits a max fat oxidation at, gosh, 125 watts.
[00:52:19.560 --> 00:52:21.400] So it's a 50 watt difference.
[00:52:21.400 --> 00:52:29.880] So now the question for you is, when that person comes to you and says, Inugo, I want to improve my metabolic function.
[00:52:29.880 --> 00:52:33.560] I want to improve my mitochondrial performance.
[00:52:33.560 --> 00:52:38.600] I want to improve my fuel partitioning, my flexibility, all the things we talk about.
[00:52:38.600 --> 00:52:47.840] Are you going to train them as a zone 2 of 125 watts or as a zone 2 of 175 watts as represented by these deltas?
[00:52:48.160 --> 00:52:50.960] Normally, I would try to do something in the middle.
[00:52:50.960 --> 00:52:56.400] Normally, it might not coincide perfectly, but normally they do quite well.
[00:52:56.400 --> 00:53:00.320] And another parameter, if you allow me, I can show you in this paper.
[00:53:00.320 --> 00:53:06.960] When decided, we see individually the lactates, and then we see the fat oxidation.
[00:53:06.960 --> 00:53:09.760] But then I decided to cross them over.
[00:53:09.760 --> 00:53:12.480] This is what we saw in this graph over here.
[00:53:12.480 --> 00:53:21.440] So, this is where you see the lactate versus the fat oxidation in the elite athlete, and the R is 0.97.
[00:53:21.440 --> 00:53:23.120] This is true Bonferroni equations.
[00:53:23.120 --> 00:53:25.680] So, this is an average of all of them.
[00:53:25.680 --> 00:53:31.760] And this is where you see the same pattern, the same graph, for the motorally active.
[00:53:31.760 --> 00:53:35.040] And this is also what you see in the person with metabolic syndrome.
[00:53:35.040 --> 00:53:37.120] The correlations are very, very strong.
[00:53:37.120 --> 00:53:38.560] They're almost perfect.
[00:53:38.560 --> 00:53:44.000] So, this is what normally fat oxidation and lactate, they go together.
[00:53:44.000 --> 00:53:53.520] So, for people who are going to be listening to this, Inugo, and not able to see what we're seeing, can you describe the differences between these graphs?
[00:53:53.520 --> 00:54:00.480] These are obviously showing the same data that we discussed earlier, but now we're using two y-axes.
[00:54:00.480 --> 00:54:03.680] So, let's even just talk about it as looking at the elite athletes.
[00:54:03.680 --> 00:54:14.560] So, you're basically plotting the decline in fat oxidation, or in their case, the initial increase in fat oxidation followed by a decline in fat oxidation.
[00:54:14.560 --> 00:54:18.800] And on the same graph, you're showing the increase in lactate production.
[00:54:18.800 --> 00:54:22.640] Again, both plotted to the same x-axis of power.
[00:54:22.640 --> 00:54:26.160] Does the cross point here indicate any significance?
[00:54:26.160 --> 00:54:29.280] So, they're crossing at about 325 watts.
[00:54:29.280 --> 00:54:31.320] Is there anything about that that means anything?
[00:54:29.920 --> 00:54:36.760] I mean, to me, I think it's an artifact of the graph because it's really just a function of how you scale it, correct?
[00:54:37.320 --> 00:54:38.360] Yes, exactly.
[00:54:38.360 --> 00:54:49.240] I mean, it shows to me that, yeah, the crossover point for blood lactate and fat oxidation very high, obviously, in the elite athletes, very far to the right.
[00:54:49.240 --> 00:55:00.600] And then, of course, in the moderately fit people, it looks like it's closer to 1 maybe 80 watts, and in the unfit individual, it's about 125 watts, a person with metabolic syndrome.
[00:55:00.600 --> 00:55:16.440] If you started, and I'm sure you have seen this, but if you started with the metabolic syndrome, for example, at 25 watts, even in the recreational athlete, even earlier, you might see a similar pattern as you would see in the elite athlete, but at much lower watts, obviously.
[00:55:16.440 --> 00:55:20.760] We just did the same protocol for everybody, just to show the concept.
[00:55:20.760 --> 00:55:24.680] Both fat oxidation and lactate go together.
[00:55:24.680 --> 00:55:29.000] And also, when we look into, and I'm sorry, I should have gone to this directly.
[00:55:29.000 --> 00:55:34.600] When we look into fat oxidation and carbohydrate oxides, we see the same concept.
[00:55:34.600 --> 00:55:40.280] So we see as exercise intensity increases, you need to oxidize more carbohydrates.
[00:55:40.280 --> 00:55:44.040] And then, as exercise intensity increases, you might get to the fat max.
[00:55:44.040 --> 00:55:47.880] And then, in the moment, you switch to the glycolytic fibers.
[00:55:47.880 --> 00:55:51.160] You cannot use much fat for energy purposes.
[00:55:51.160 --> 00:55:58.120] So, you see a sharp decline, and eventually, fat oxidation disappears, and it's all full glycolytic.
[00:55:58.120 --> 00:56:05.240] And the same pattern we see in the rest of populations with also very high statistical significances and correlations.
[00:56:05.240 --> 00:56:10.840] All these elements, fat oxidation, carbohydrates, and lactate, they're very well connected.
[00:56:10.840 --> 00:56:15.000] If we look in the other graph, this is the correlation between lactate and carbohydrates.
[00:56:16.240 --> 00:56:24.480] We see that overall the correlations are quite good because lactate is the byproduct of glucose utilization.
[00:56:24.480 --> 00:56:28.720] You may see that in the elite athletes, though, the gap is wider here.
[00:56:28.720 --> 00:56:30.800] And this is for the same reason I was seeing earlier.
[00:56:30.800 --> 00:56:32.480] They use a lot of glucose.
[00:56:32.480 --> 00:56:35.840] They're using so much fat there as well, is really the point.
[00:56:35.840 --> 00:56:43.440] So the bigger the gap between the blood lactate curve and the carbohydrate oxidation curve, the more efficient the individual is.
[00:56:43.440 --> 00:56:49.280] The more they're able to oxidize fatty acid, then they have to require glucose.
[00:56:49.280 --> 00:56:50.560] And clear lactate.
[00:56:50.560 --> 00:56:51.200] Yes.
[00:56:51.200 --> 00:56:57.360] The mandatory byproduct of glucose oxidation is lactate.
[00:56:57.360 --> 00:57:00.320] So here, the lactate doesn't show up in the blood.
[00:57:00.320 --> 00:57:02.080] It stays in the muscle.
[00:57:02.080 --> 00:57:06.800] It's hard to disentangle those two because you mentioned a good point that I omitted.
[00:57:06.800 --> 00:57:10.320] This in part reflects the lactate shuttle.
[00:57:10.320 --> 00:57:22.640] This in part reflects the ability for them to reuse lactate as a fuel as opposed to just letting it get out there with hydrogen and start to poison sarcomeres.
[00:57:22.960 --> 00:57:29.360] Let me see the other slide that you wanted to show that explains, I think, how the MCT transporters work.
[00:57:29.360 --> 00:57:37.920] This is a little bit more of the bioenergetics of the cells, of the main two substrates, which are fatty acids and pyruvate, and also lactate, right?
[00:57:37.920 --> 00:57:45.440] So normally glucose goes through glycolysis and it ends up, this is the cytosol, this is the outside of the mitochondria, the inside of the cell.
[00:57:45.440 --> 00:57:49.760] And glucose, when it enters the cell, it's oxidized to pyruvate.
[00:57:49.760 --> 00:58:01.240] That pyruvate needs to enter the mitochondria through what's called the mitochondrial pyruvate carrier, and it's oxidized to acetyl-CoA, which enters the Krebs cycle.
[00:58:01.240 --> 00:58:08.520] This is a complete oxidation of glucose through oxidative phosphorylation in the Krebs cycle and electron transport chain.
[00:58:08.520 --> 00:58:12.440] Then fatty acids have the same mechanisms too.
[00:58:12.440 --> 00:58:16.200] They also get converted to acetyl-CoA through different mechanisms.
[00:58:16.200 --> 00:58:23.960] Fatty acids are transporter through CPT1 and then CPT2 go through beta oxidation, acetyl-CoA, and enter the cell.
[00:58:23.960 --> 00:58:32.840] But every time that you use glucose to produce pyruvate, and every single time that pyruvate is going to be reduced to lactate, always.
[00:58:32.840 --> 00:58:34.280] And this is the key concept.
[00:58:34.280 --> 00:58:47.480] So when you have a constant glycolytic flux, in one of the steps of glycolysis, you're going to utilize NAD and it's going to be transformed to NADH plus hydrogen.
[00:58:47.480 --> 00:58:53.480] So if you use this mechanism a lot, you're going to deplete NAD.
[00:58:53.480 --> 00:59:02.200] The only way that rescues NAD is the reduction of pyruvate to lactate, which replenishes NAD going back for glycolysis.
[00:59:02.200 --> 00:59:05.960] And this is absolutely necessary for the continuation of glycolysis.
[00:59:05.960 --> 00:59:20.600] But this lactate enters the mitochondria through a specific transporter, MCT1, and has a specific enzyme, LDH, that oxidizes lactate back to pyruvate and going back to the Krebs cycle.
[00:59:20.600 --> 00:59:22.760] So again, this is an extra fuel.
[00:59:22.760 --> 00:59:27.720] But for that, you need to have these transporters very well developed.
[00:59:27.720 --> 00:59:33.880] Let me try to explain this to people who aren't able to see the graph because this is such an important point.
[00:59:33.880 --> 00:59:36.920] So, you're showing a picture of the mitochondria.
[00:59:36.920 --> 00:59:38.920] We're looking at the outer mitochondrial membrane.
[00:59:39.000 --> 00:59:51.360] We're talking about three transporters, three things that let substrates from the outside to the inside, where they will undergo the most efficient form of ATP production.
[00:59:51.680 --> 01:00:01.680] So, the first is we have the fatty acids, they enter directly, then they undergo an oxidation where they get truncated into little two-carbon chains and they enter the Krebs cycle.
[01:00:01.680 --> 01:00:03.920] We get that one, and we know why that one's very good.
[01:00:03.920 --> 01:00:11.920] What I think is very interesting here is when you contrast the two different fates of glucose byproducts.
[01:00:11.920 --> 01:00:27.200] So, the traditional way that we think about this: glucose being reduced to pyruvate, pyruvate directly entering the cell through its own carrier, and then being converted to acetyl-CoA, which follows the same fate as the fatty acid.
[01:00:27.200 --> 01:00:39.360] Now, when energy demand increases, and we just looked at graph after graph that demonstrate that no matter how fit you are, at some point you have to produce more lactate.
[01:00:39.360 --> 01:00:46.960] So, you now don't have sufficient cellular oxygen to go down that first route, so you start making lactate.
[01:00:46.960 --> 01:00:58.800] But if you have enough MCT1 transporters on the outer mitochondrial, you can now bring that lactate in the cell and actually do the reverse of what just happened.
[01:00:58.800 --> 01:01:04.640] Turn that lactate back into pyruvate, pyruvate becomes acetyl-CoA, and everybody wins the game again.
[01:01:04.640 --> 01:01:14.000] The game being one, of course, because now you're making 32 units of ATP instead of just the two units you would make converting pyruvate to lactate.
[01:01:14.000 --> 01:03:15.280] So, it begs a very important question: which is: earlier when you spoke about what makes Pogachar so remarkable physiologically, one of those things is he must have a boatload of MCT1 transporters on his outer mitochondrial membrane and that must explain in part why his lactate levels are so much lower than everybody else's at a comparable work level how much of that is genetic and how much of that is a result of his training exactly so you're right he has a much higher level to oxidized lactate so there's a genetic component no doubt about it there's also an epigenetic component and as we know nowadays the genes are not your fate necessarily from the genes to be able to be transcribed and form a protein with biological action the probability is less than 20 percent kind of what the scienc

Prompt 2: Key Takeaways

Now please extract the key takeaways from the transcript content I provided.

Extract the most important key takeaways from this part of the conversation. Use a single sentence statement (the key takeaway) rather than milquetoast descriptions like "the hosts discuss...". 

Limit the key takeaways to a maximum of 3. The key takeaways should be insightful and knowledge-additive. 

IMPORTANT: Return ONLY valid JSON, no explanations or markdown. Ensure:
- All strings are properly quoted and escaped
- No trailing commas
- All braces and brackets are balanced
Format: {"key_takeaways": ["takeaway 1", "takeaway 2"]}

Prompt 3: Segments

Now identify 2-4 distinct topical segments from this part of the conversation.

For each segment, identify:
- Descriptive title (3-6 words)  
- START timestamp when this topic begins (HH:MM:SS format)
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Most important Key takeaway from that segment. Key takeaway must be specific and knowledge-additive.
- Brief summary of the discussion

IMPORTANT: The timestamp should mark when the topic/segment STARTS, not a range. Look for topic transitions and conversation shifts.

Return ONLY valid JSON. Ensure all strings are properly quoted, no trailing commas:
{
  "segments": [
    {
      "segment_title": "Topic Discussion", 
      "timestamp": "01:15:30",
      "key_takeaway": "main point from this segment",
      "segment_summary": "brief description of what was discussed"
    }
  ]
}

Timestamp format: HH:MM:SS (e.g., 00:05:30, 01:22:45) marking the START of each segment.

Prompt 4: Media Mentions

Now scan the transcript content I provided for ACTUAL mentions of specific media titles:

Find explicit mentions of:
- Books (with specific titles)
- Movies (with specific titles)  
- TV Shows (with specific titles)
- Music/Songs (with specific titles)

DO NOT include:
- Websites, URLs, or web services
- Other podcasts or podcast names

IMPORTANT: 
- Only include items explicitly mentioned by name. Do not invent titles.
- Valid categories are: "Book", "Movie", "TV Show", "Music"
- Include the exact phrase where each item was mentioned
- Find the nearest proximate timestamp where it appears in the conversation
- THE TIMESTAMP OF THE MEDIA MENTION IS IMPORTANT - DO NOT INVENT TIMESTAMPS AND DO NOT MISATTRIBUTE TIMESTAMPS
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Timestamps are given as ranges, e.g. 01:13:42.520 --> 01:13:46.720. Use the EARLIER of the 2 timestamps in the range.

Return ONLY valid JSON. Ensure all strings are properly quoted and escaped, no trailing commas:
{
  "media_mentions": [
    {
      "title": "Exact Title as Mentioned",
      "category": "Book",
      "author_artist": "N/A",
      "context": "Brief context of why it was mentioned",
      "context_phrase": "The exact sentence or phrase where it was mentioned",
      "timestamp": "estimated time like 01:15:30"
    }
  ]
}

If no media is mentioned, return: {"media_mentions": []}

Prompt 5: Context Setup

You are an expert data extractor tasked with analyzing a podcast transcript. 
I will provide you with part 2 of 3 from a podcast transcript. 
I will then ask you to extract different types of information from this content in subsequent messages. Please confirm you have received and understood the transcript content.

Transcript section:
 the two different fates of glucose byproducts.
[01:00:11.920 --> 01:00:27.200] So, the traditional way that we think about this: glucose being reduced to pyruvate, pyruvate directly entering the cell through its own carrier, and then being converted to acetyl-CoA, which follows the same fate as the fatty acid.
[01:00:27.200 --> 01:00:39.360] Now, when energy demand increases, and we just looked at graph after graph that demonstrate that no matter how fit you are, at some point you have to produce more lactate.
[01:00:39.360 --> 01:00:46.960] So, you now don't have sufficient cellular oxygen to go down that first route, so you start making lactate.
[01:00:46.960 --> 01:00:58.800] But if you have enough MCT1 transporters on the outer mitochondrial, you can now bring that lactate in the cell and actually do the reverse of what just happened.
[01:00:58.800 --> 01:01:04.640] Turn that lactate back into pyruvate, pyruvate becomes acetyl-CoA, and everybody wins the game again.
[01:01:04.640 --> 01:01:14.000] The game being one, of course, because now you're making 32 units of ATP instead of just the two units you would make converting pyruvate to lactate.
[01:01:14.000 --> 01:03:15.280] So, it begs a very important question: which is: earlier when you spoke about what makes Pogachar so remarkable physiologically, one of those things is he must have a boatload of MCT1 transporters on his outer mitochondrial membrane and that must explain in part why his lactate levels are so much lower than everybody else's at a comparable work level how much of that is genetic and how much of that is a result of his training exactly so you're right he has a much higher level to oxidized lactate so there's a genetic component no doubt about it there's also an epigenetic component and as we know nowadays the genes are not your fate necessarily from the genes to be able to be transcribed and form a protein with biological action the probability is less than 20 percent kind of what the science is showing roughly this is the whole from genetics to transcriptnomics proteomics and metabolomics it's about 20 percent chances that one gene is going to be ultimately expressed obviously we're still trying to understand all this so these elite athletes probably they have a much higher possibilities but there's a long journey and this is where epigenetics occur is like what you eat how you rest how you train and i think that the training is also an important component of this this is for example why we train very very specifically this energy system and we try to dial in as much as we can specifically to try to stimulate this bioenergetics system and increase the mct1s the transporters for lactate as well as all the components in the krebs cycle, which is the mitochondrial respiration, and also to increase also the mitochondrial pyruvic carrier, because we might discuss later, this is already dysregulated in people or down-regulated in people who are sedentary.
[01:03:15.280 --> 01:03:18.560] But the thing is, like if you see this next slide, can you see it?
[01:03:18.560 --> 01:03:21.520] Okay, this is what makes the difference in these athletes.
[01:03:21.520 --> 01:03:25.520] So this is a fast twitch muscle fiber and they use glucose.
[01:03:25.520 --> 01:03:44.560] So this is when you're like a high exercise intensities, climbing or running at a high intensity or swimming or whatever the activity you do, you need glucose because glucose is, as you said very well, it yields less ATP, but it does it much faster than the diesel gasoline, which is the fat.
[01:03:44.560 --> 01:03:48.720] But when you use glucose, you're always going to produce pyruvate.
[01:03:48.720 --> 01:03:55.280] The higher the intensity, the more glucose you need, more pyruvate you will need, and the more lactate that you will produce.
[01:03:55.280 --> 01:03:59.440] So that lactate has, as I said earlier, two routes.
[01:03:59.440 --> 01:04:07.760] One route is like it's exported through the MCT force, which is the transporter of lactate outside the fast-twitch muscle fibers.
[01:04:07.760 --> 01:04:13.680] Something that also is trainable, the capacity to export lactate through high-intensity exercise.
[01:04:13.680 --> 01:04:17.920] And then it travels to the adjacent slow-twitch muscle fibers.
[01:04:17.920 --> 01:04:22.480] We blow up this mitochondria in the slow twitch muscle fibers.
[01:04:22.480 --> 01:04:23.520] This is what will happen.
[01:04:23.520 --> 01:04:31.520] The entrance of that lactate, it goes through another transporter, MCT1, it's the same family, but instead of four, it's called MCT1.
[01:04:31.680 --> 01:04:38.160] I mentioned earlier, that lactate is converted to pyruvate and acetyl-CoA and goes into the Krebs cycle.
[01:04:38.160 --> 01:04:46.880] So in these well-trained athletes like Bohachar, for example, they have an amazing ability to oxidize the lactate inside mitochondria.
[01:04:46.880 --> 01:04:53.520] At some point, every single human gets to a point that they cannot sustain the effort anymore.
[01:04:53.520 --> 01:05:03.000] But what makes the difference is obviously like these guys can do 400 watts for a long time versus a mermaid who cannot even do two strokes at 400 watts.
[01:05:03.320 --> 01:05:12.120] So what happens is like when you have a lot of the right MCT1 and mitochondrial function, this lactate is going to increase and accumulate.
[01:05:12.120 --> 01:05:14.200] And it's not lactate per se.
[01:05:14.200 --> 01:05:27.240] but the hydrogen ions associated to lactate elicit an acidosis of the microenvironment of the muscle, which is something that we know and we have learned also from cancer, the famous cancer microenvironment, which is very acidic.
[01:05:27.240 --> 01:05:34.440] And that's going to interfere with different functions in the muscle with both the contractive force and the velocity of the muscle fibers.
[01:05:34.440 --> 01:05:44.360] I'm not saying that this is the cause of fatigue by no means because there are multiple theories and we're still trying to understand it's a central fatigue as well and everything probably is interrelated or it must be interrelated.
[01:05:44.360 --> 01:05:49.880] But the bottom line is like when this lactate cannot be oxidized, it is exported to the blood.
[01:05:49.880 --> 01:06:02.680] And this is why you see that people with metabolic syndrome, for example, or type 2 diabetes who are characterized by having a very poor mitochondrial function, they cannot during exercise oxidize this lactate.
[01:06:02.680 --> 01:06:10.920] In the moment they start using glucose, which is very fast also because they don't have the slow twitch muscle fibers, mitochondria to use fat, they need to rely on glucose.
[01:06:10.920 --> 01:06:14.600] That's that metabolic reprogramming or partitioning they have.
[01:06:14.600 --> 01:06:17.560] They produce lactate, but they cannot oxidize the lactate.
[01:06:17.560 --> 01:06:22.920] That's why this lactate chooses mandatorily the route of being exported to the blood.
[01:06:22.920 --> 01:06:25.800] And in the blood, then it goes to any tissue in the body.
[01:06:25.800 --> 01:06:31.000] So this is what I meant earlier about what is two millimoles versus one millimole.
[01:06:31.000 --> 01:06:36.120] Whereas Pogacha, for example, he oxidizes a lot of this lactate.
[01:06:36.120 --> 01:08:22.200] So by the time that Porgachar saturates this transporter and this mitochondrial capacity to oxidize lactate, it's a tremendous amount of power output and a tremendous amount of glucose that he puts out so this is why that one millimo 1.5 millimole and a world-class athlete necessarily represent the same metabolic status over 1.5 or 2 millimoles in the blood of a normal person this is a fantastic tutorial in muscle physiology and again this very important distinction between lactate production at the local level and lactate that we measure at the global level that's the challenge we have when we are measuring lactate we cannot impute lactate clearance and lactate production we can only impute the sum of those it's originally thought right that these athletes they don't use as much glucose well in fact the reach shows and brooks and his team showed it and others too that the well-trained athletes in fact they use more glucose because they have to you cannot do 400 watts without massive amount of carbohydrate and this is what we also see in the indirect calorimetry that you see people recreational for people with metabolic syndrome they have like four grams per minute at max carbohydration whereas elite athletes they can get to six and a half grams per minute it's massive amount of glucose and they produce a lot more lactate but the key it doesn't show up in the blood is the rate of appearance in the blood because it's oxidized in the muscle so it doesn't show up in the blood is the balance of lactate production and lactate oxidation without getting to the blood.
[01:08:22.200 --> 01:08:29.960] And this is what it correlates a lot also with fat oxidation as well and the graphs that I was showing earlier.
[01:08:29.280 --> 01:08:38.920] So one of the things I want to ask you about here that is a bit of a confounder when we do this type of analysis is the carbohydrate content within the diet.
[01:08:38.920 --> 01:08:42.120] So I'll share with you my data.
[01:08:42.120 --> 01:08:47.960] But I've now seen this with multiple people, including one individual who's remarkably fit.
[01:08:47.960 --> 01:08:49.240] God, it's how many years now?
[01:08:49.240 --> 01:08:52.600] 10 years ago, I was on a ketogenic diet for three years.
[01:08:52.600 --> 01:08:57.320] And the very end of that three-year period was when I kind of got back into cycling.
[01:08:57.320 --> 01:09:02.440] At my fittest as an adult cyclist, I was back eating a lot of carbohydrates.
[01:09:02.440 --> 01:09:08.840] But there was about a six to twelve month period when I was still in ketosis.
[01:09:08.840 --> 01:09:11.080] I was kind of getting back into cycling shape.
[01:09:11.080 --> 01:09:20.760] And I do have one VO2 max test from that window of time, probably six months after getting back to cycling and still on ketosis.
[01:09:20.760 --> 01:09:23.880] I've gone back and looked at the data, and they're very interesting.
[01:09:23.880 --> 01:09:30.920] What I would observe is maximum fat oxidation was 1.3 grams per minute.
[01:09:30.920 --> 01:09:33.960] And that occurred almost immediately.
[01:09:33.960 --> 01:09:37.240] And it sustained until...
[01:09:37.240 --> 01:09:42.040] So at the time my FTP was about 4.1 watts per kilo.
[01:09:42.040 --> 01:09:47.320] This would have been sustained until about 3.5 watts per kilo.
[01:09:47.320 --> 01:09:53.640] So at 3.5 watts per kilo, I was still oxidizing about 1.2 grams per minute.
[01:09:53.640 --> 01:09:55.960] And then that sort of fell off.
[01:09:55.960 --> 01:09:59.720] And glucose became then the dominant fuel source.
[01:09:59.720 --> 01:10:15.000] At the completion of the test, when I was done, you know, when I failed, I was obviously not oxidizing any fat, and glucose oxidation was just under six grams per minute, about six grams per minute, about 24 kcal per minute.
[01:10:15.280 --> 01:10:23.920] So, I've also seen this with another athlete who's been in ketosis for seven years, is a very fit cyclist.
[01:10:23.920 --> 01:10:27.680] Actually, he just sent me his data, and it's comparable.
[01:10:27.680 --> 01:10:29.280] In fact, he's much fitter than I was.
[01:10:29.280 --> 01:10:34.720] So, his 20-minute FTP test is about 412 watts for 20 minutes.
[01:10:34.720 --> 01:10:37.920] And surprisingly, he has decent glycolytic power.
[01:10:37.920 --> 01:10:45.520] So, that's the other thing: I never really had good power at the low end because I only cared about time trialing, so it didn't matter how many watts I could hold for two minutes or three minutes.
[01:10:45.520 --> 01:10:47.200] I only cared about one hour.
[01:10:47.200 --> 01:10:54.160] But this guy could still hold 1,200 watts for 15 seconds, even for three minutes.
[01:10:54.160 --> 01:10:57.520] He's north of 500 watts, 600 watts.
[01:10:57.520 --> 01:11:02.080] And again, fat oxidation is, you know, 1.5 grams per minute.
[01:11:02.080 --> 01:11:10.720] So, it becomes a bit confusing because it would be very difficult to define zone two by maximum fat oxidation.
[01:11:10.720 --> 01:11:13.360] So, ketosis is an extreme example.
[01:11:13.360 --> 01:11:26.640] But given how much RQ, respiratory quotient, the ratio of VCO2 to VO2, depends on baseline carbohydrate intake, how do we make the adjustment so that we understand and we're not being misled?
[01:11:26.640 --> 01:11:34.320] Because if you just looked at my data, you would dramatically overestimate my mitochondrial efficiency.
[01:11:34.320 --> 01:11:43.840] Is that a situation where you say, well, actually, the lactate, and unfortunately, I don't have lactate data from that test, so I can't tell you what my lactate levels were doing.
[01:11:43.840 --> 01:11:50.080] But it might not be a problem in the Peloton, because you're not going to be in ketosis if you're trying to win the Tour de France.
[01:11:50.080 --> 01:11:58.000] But we do see a great degree of carbohydrate and fat variation in the diet amongst people that we're trying to test.
[01:11:58.000 --> 01:11:59.440] How do you make that correction?
[01:11:59.640 --> 01:12:08.600] My humble opinion, what we see in these cases, because I see them all the time too, is that there's an artifact in the metabolic heart.
[01:12:08.600 --> 01:12:11.880] The metabolic heart measures gas exchange.
[01:12:11.880 --> 01:12:18.520] And then through the equations, it says, okay, this person must be burning fat or burning carbohydrates.
[01:12:18.520 --> 01:12:22.280] The equations are calibrated on high-carb diets, presumably.
[01:12:22.280 --> 01:12:30.200] Yeah, so the thing is, like, as you exercise, no matter what fuel you're using, you keep increasing oxygen consumption.
[01:12:30.200 --> 01:12:34.920] But if you don't have much carbohydrates, you're not going to produce much CO2.
[01:12:34.920 --> 01:12:47.400] So that's going to tweak or mislead my stoichiometric equation because the algorithm is going to think that, oh, whoa, he's using a lot of oxygen and not producing enough CO2.
[01:12:47.400 --> 01:12:49.720] So he's got to be burning a lot of fat.
[01:12:49.720 --> 01:12:53.240] That's when you see fats in north of one gram per minute.
[01:12:53.240 --> 01:12:54.920] Those are fat oxidations.
[01:12:54.920 --> 01:12:56.920] I think they're an artifact.
[01:12:56.920 --> 01:13:07.320] And I see this because three days later, when you change the diet of that person, three days later, that person's fat oxidation might be 0.35.
[01:13:07.640 --> 01:13:28.040] So there's no way that the mitochondria adjusts first, like it reflects a very high fat oxidation capacity in someone who we know very well, who is not an elite athlete, whose mitochondrial function is not incredibly high, to be able to oxidize so much fat and in three days reduces like by three or four times.
[01:13:28.040 --> 01:13:31.720] I attribute this to an artifact of the gas exchange.
[01:13:31.720 --> 01:13:36.600] And this is where looking at lactate, you should give you those parameters.
[01:13:36.600 --> 01:13:46.800] Normally, what I see in these individuals is that you see maximum lactates of two, three millimoles because simply they don't have carbohydrates.
[01:13:47.120 --> 01:13:54.800] Also, the thing when you see that, yeah, my maximum grams per minute of carbohydrates was in the six, but you're in ketosis.
[01:13:54.800 --> 01:14:02.160] So, how can you have enough glycogen or glycolytic capacity to elicit such a high carbohydrate production?
[01:14:02.160 --> 01:14:08.080] Even when you're in ketosis, remember my blood glucose is still four to five millimole.
[01:14:08.080 --> 01:14:21.520] I would really like to see this studied because, again, even if you're only eating 50 grams of glucose a day, think of how much glycogen you're making from all the glycerol, from all the fat that's being converted to ketone.
[01:14:21.520 --> 01:14:38.080] So, I mean, I think Jeff Volick and Steve Finney have looked at this, and when they put people into very, very strict ketosis but do muscle biopsies, they're still seeing 60% of the glycogen content in the muscle that was there under high carb conditions.
[01:14:38.080 --> 01:14:44.240] I mean, I think my capacity to oxidize five and a half to six grams of glucose per minute was still there.
[01:14:44.400 --> 01:14:47.520] Just took a long time to get there, I think, is the difference.
[01:14:47.520 --> 01:14:58.880] So, I guess the question is: if the VCO2 estimation is off because of the stoichiometric coefficients, do you think the VO2 estimation is off also?
[01:14:59.200 --> 01:15:05.200] No, I don't think so because, as you said very well, ketones are used for energy purposes.
[01:15:05.200 --> 01:15:10.480] And then we have a third element which is absolutely key in bioenergetics, which is glutamine.
[01:15:10.480 --> 01:15:13.760] Glutamine olycids are highly expressed and utilized.
[01:15:13.760 --> 01:15:16.960] We have learned that from ICU patients.
[01:15:16.960 --> 01:15:22.080] ISU patients is a great model to study metabolism or stress metabolism.
[01:15:22.080 --> 01:15:30.840] ICU patients, they utilize for wound healing about three times more glucose at rest than what we have.
[01:15:29.520 --> 01:15:32.200] And it's part of the healing process.
[01:15:32.360 --> 01:15:40.440] Glucose is instrumental for cell proliferation, wound healing, and part of it is lactate too as a byproduct in a signal molecule.
[01:15:40.440 --> 01:15:46.120] But we see that, and this is a study that we published, looking indirectly a methodology to look at glycogen.
[01:15:46.120 --> 01:15:49.240] It's a pilot study we did with ICU patients.
[01:15:49.240 --> 01:15:50.600] They don't have glycogen.
[01:15:50.600 --> 01:15:57.400] When you say they don't have glycogen, you mean liver glycogen, muscle glycogen, or depleted by how much?
[01:15:57.400 --> 01:15:58.760] Depleted to what level?
[01:15:58.760 --> 01:16:05.080] Let's say that you have 500 grams of glycogen if you have a full high carbohydrate diet.
[01:16:05.080 --> 01:16:08.760] So that might not be the case of someone entering the ICU.
[01:16:08.760 --> 01:16:16.120] First, because they might not be elite athletes or they might have maybe 300 grams or they might not have that adaptation to hold more glycogen.
[01:16:16.120 --> 01:16:18.840] So let's say they have 300 grams or so.
[01:16:18.840 --> 01:16:25.080] By the time they get into that condition, the body uses about three times the glucose at rest.
[01:16:25.080 --> 01:16:34.920] Now, an athlete used that same glucose, but at higher intensities, but only for a reduced amount of time, two hours, three hours, four hours.
[01:16:34.920 --> 01:16:37.960] Whereas the ICU patient is 24-7.
[01:16:37.960 --> 01:16:44.680] So eventually the body is going to run out of glycogen in the muscle or is going to be under huge stress.
[01:16:44.680 --> 01:16:50.520] The body has evolutionary mechanisms because it's a wonderful machine and it needs to continue.
[01:16:50.520 --> 01:16:54.920] So it increases another route, which is glutaminolysis.
[01:16:54.920 --> 01:16:58.120] So glutamine is an excellent source of fuel.
[01:16:58.120 --> 01:17:00.600] It enters directly the mitochondria.
[01:17:00.760 --> 01:17:11.640] We have seen in a publication that we're going to show when we publish it, is that when we inject mitochondria with glutamate, it's incredibly well oxidized.
[01:17:11.640 --> 01:17:15.120] And what's the source of glutamate in these ICU patients?
[01:17:14.840 --> 01:17:16.880] Are they breaking down muscle?
[01:17:17.200 --> 01:17:19.680] This is where cachexia comes into place.
[01:17:19.680 --> 01:17:29.760] We know that pretty much every single ICU patient becomes cachectic or suffers from muscle waste, and this is the syndrome, post-ICU muscle waste syndrome.
[01:17:29.760 --> 01:17:36.960] Why do they get cachectic or catabolic and why they overexpress tremendously levels of glutamine?
[01:17:36.960 --> 01:17:42.800] Because they need it for either enter the Krebs cycle for energy or for gluconeogenesis.
[01:17:42.800 --> 01:17:46.080] So this is one of the things that we learned a lot from ICU.
[01:17:46.080 --> 01:17:53.200] These ICU patients, they have hyperglycemia, yet they're not giving them usually because they have hyperglycemia.
[01:17:53.200 --> 01:17:59.680] It's true too that in the acute ICU phase, they also have insulin resistance.
[01:17:59.680 --> 01:18:08.320] But obviously this hyperglycemia and ICU doctors historically have seen this, like, whoa, this patient has hyperglycemia of the chart.
[01:18:08.320 --> 01:18:11.520] So obviously we're not going to give them IVs of glucose.
[01:18:11.520 --> 01:18:14.240] We're going to give more protein and glucose, I mean, and phytos.
[01:18:14.240 --> 01:18:18.640] And in fact, glutamine has shown that increased survival rate in these patients.
[01:18:18.640 --> 01:18:23.520] Where is this hyperglycemia coming from when you do not have glycogen?
[01:18:23.520 --> 01:18:32.160] It comes probably from proteolysis, where you break down protein from your muscles to release glutamine.
[01:18:32.160 --> 01:18:43.280] We would only know that if we understood hepatic glucose stores, because regardless of how much glycogen is in the muscle, it's never going to make its way into circulation because the muscle can't fully dephosphorylate it.
[01:18:43.280 --> 01:18:47.680] So do we have a sense of what the hepatic glycogen content is?
[01:18:47.680 --> 01:18:59.760] Because I can't imagine the body would ever let anything compromise that, given that if the liver can't produce glucose continuously, the brain dies.
[01:19:00.120 --> 01:19:03.320] So it might be that this is true, true, and unrelated, right?
[01:19:03.320 --> 01:19:14.600] It could be that the muscles are depleting glycogen because of high utilization, but the liver, through gluconeogenesis, has plenty of glucose.
[01:19:14.600 --> 01:19:21.800] That's what's making it into the circulation because of hypercortisalemia, because of other acute phase reactants.
[01:19:21.800 --> 01:19:28.440] And so we have hyperglycemia, but it's all being mediated by the liver, which has no trouble maintaining glycogen levels.
[01:19:28.440 --> 01:19:37.320] And again, from an evolutionary perspective, you much rather err on the side of hyperglycemia than hypoglycemia under a period of stress.
[01:19:37.320 --> 01:19:38.520] Absolutely, necessarily.
[01:19:38.520 --> 01:19:42.040] And that's, I think, what's the source of that gluconeogenesis?
[01:19:42.040 --> 01:19:45.480] It's probably glutaminolysis coming from the muscles.
[01:19:45.480 --> 01:19:52.520] So this is what my hypothesis, right, that those muscles, they eat themselves to feed themselves or to feed the rest of the body.
[01:19:52.520 --> 01:19:57.400] So that would suggest that exercising ICU patients would be important.
[01:19:57.400 --> 01:20:07.800] Getting some load-bearing resistance, even, of course, they're in a bed, but moving their extremities against a load, supplementing with amino acids, could actually improve outcomes.
[01:20:07.960 --> 01:20:08.600] Absolutely.
[01:20:08.600 --> 01:20:10.520] There's a lot of research in this area.
[01:20:10.520 --> 01:20:15.800] My colleague Paul Wishmeyer, who used to work here with me at the university, now he's in Duke.
[01:20:15.800 --> 01:20:18.760] He's doing a lot of research and practical work with that.
[01:20:18.760 --> 01:20:23.320] With this, it's like, yeah, this hyperglycemia probably comes from gluconeogenesis.
[01:20:23.320 --> 01:20:34.840] Going back to where we started, yeah, could be that there's a lot of glutamine released, you know, when you're also ketoacidosis state as well, especially in the first phases of that.
[01:20:34.840 --> 01:20:37.240] We know cortisol is very high at first.
[01:20:37.240 --> 01:20:49.040] The same thing that we see in ICU patients, that two main parameters that are predictors of mortality at the ICU is a hypercortisulinemia, high cortisol levels, and high lactate levels.
[01:20:45.000 --> 01:20:50.720] They both are completely related.
[01:20:50.960 --> 01:20:52.880] But, anyways, yeah, I think this is fascinating.
[01:20:52.880 --> 01:20:59.840] There's a great model to understand metabolism, stress metabolism of these patients and the ICU patients.
[01:20:59.840 --> 01:21:01.360] And that's the other thing, too.
[01:21:01.360 --> 01:21:20.800] Once you exercise, and this is a very important concept for people with type 2 diabetes, with type 1 diabetes, and hyperinsulinemia is that you have insulin resistance and you have difficulty to translocate, therefore, to translocate the glute 4 transporters to the surface of the muscle, the sarcolemma.
[01:21:20.800 --> 01:21:40.960] And we know that probably the first tissue or organ where diabetes debuts starts is the skeletal muscle, because about 80% of the carbohydrates that we have, they're oxidized in skeletal muscle, and because we're at rest, should be oxidized within the mitochondria of the skeletal muscle, that pyruvate.
[01:21:40.960 --> 01:21:43.360] This is what doing research and seeing it clearly.
[01:21:43.360 --> 01:21:49.040] But when you have insulin resistance, you cannot translocate those transporters.
[01:21:49.040 --> 01:21:56.480] Now, we have a second way to translocate those transporters that not many people know about, and that's muscle contraction.
[01:21:56.480 --> 01:22:03.280] This is the insulin-independent glucose uptake, which also seems to be heavily dependent on fitness.
[01:22:03.280 --> 01:22:13.120] The fittest athletes here require virtually no insulin to translocate glucose into the muscle through the insulin-independent pathway.
[01:22:13.120 --> 01:22:23.200] I think we may have even discussed this, I don't know, over dinner one night, but you look at the type 1 diabetics who are highly, highly active, require very little insulin.
[01:22:23.200 --> 01:22:23.920] Exactly.
[01:22:23.920 --> 01:22:29.800] This explains hypoglycemia in these patients shortly after they start exercising.
[01:22:29.360 --> 01:22:35.880] They might have something to eat and they inject themselves with insulin, and there's nothing you can do once you have insulin on board.
[01:22:36.200 --> 01:22:41.800] So that insulin is going to translocate those transporters and it's going to start bringing insulin inside.
[01:22:41.800 --> 01:22:42.840] I mean, sorry, glucose.
[01:22:42.840 --> 01:22:43.160] Thanks.
[01:22:43.160 --> 01:22:48.920] In the moment you start exercising, you do the same function through contraction of exercise, of the muscles.
[01:22:48.920 --> 01:22:57.080] So you have two mechanisms acting at the same time, pulling more glucose inside the cells, leading to hypoglycemia.
[01:22:57.080 --> 01:23:02.840] So this is what we learned a lot with persons with people with type 1 diabetes in exercise, and then we can prevent them.
[01:23:02.840 --> 01:23:11.160] So, for example, do not inject yourself before exercising, because exercise alone is going to take care of that glucose.
[01:23:11.160 --> 01:23:18.200] But we can take these concepts also with people with type 2 diabetes, that they have insulin resistance or pre-type 2 diabetes.
[01:23:18.200 --> 01:23:23.880] But like, why not exercise right after you eat that carbohydrate you have?
[01:23:23.880 --> 01:23:25.880] You have insulin resistance already.
[01:23:25.880 --> 01:23:29.320] But when you exercise, you're not going to need that insulin.
[01:23:29.320 --> 01:23:33.640] And yet, you can translocate those transporters and you bring glucose levels down.
[01:23:33.640 --> 01:23:38.280] And I'm sure that you see this all the time with your glucose sensor.
[01:23:38.280 --> 01:23:43.320] Yes, I've gone periods of time when I've done incredibly frequent lactate testing.
[01:23:43.320 --> 01:23:50.520] So lactate testing every 30 minutes for a day or something insane like that, which is incredibly expensive and incredibly painful in your fingers.
[01:23:50.520 --> 01:23:56.120] But you learn how much, for example, a meal impacts lactate.
[01:23:56.120 --> 01:24:02.440] So when I wake up in the morning, my resting lactate level varies.
[01:24:02.440 --> 01:24:06.280] I've been tracking this over a period of probably 40 days.
[01:24:06.280 --> 01:24:08.440] So 40 days of tracking.
[01:24:08.440 --> 01:24:14.320] What range do you think my morning resting lactate level has been over a 40-day period?
[01:24:14.200 --> 01:24:15.200] In the morning, first thing in the morning?
[01:24:15.920 --> 01:24:20.320] I would say neighborhood of 0.8 to 1.2, 1.3.
[01:24:20.320 --> 01:24:20.960] Pretty good guess.
[01:24:20.960 --> 01:24:24.480] So 0.3 to about 1.1.
[01:24:24.480 --> 01:24:27.120] But that's a pretty big variation.
[01:24:27.120 --> 01:24:31.520] And probably median level of about 0.8.
[01:24:31.520 --> 01:24:34.960] Yeah, in the neighborhood of wine, which is normally in a feed individual.
[01:24:34.960 --> 01:24:35.600] Yes.
[01:24:35.600 --> 01:24:46.880] So then what I can do is I can eat a very high carb breakfast and go and do a zone two ride, or don't eat anything at all and go and do a zone two ride.
[01:24:46.880 --> 01:24:49.040] Very different lactate performance curve.
[01:24:49.040 --> 01:24:52.560] So the high carb meal raises lactate.
[01:24:52.560 --> 01:25:11.840] So it becomes a bit of an artifact in a way, which now gets me to, we've talked about this at the level of the most precision possible, the way in which I would measure it in a patient, you would measure it in a world-class athlete where we have the ability to do indirect calorimetry and lactate testing.
[01:25:11.840 --> 01:25:16.960] But now I want to talk about it in the way that we train people, normal people.
[01:25:16.960 --> 01:25:28.400] So we've talked about this, call it difference between the lactate level that you measure in the blood, which is now heavily influenced by production and clearance.
[01:25:28.400 --> 01:25:34.320] And then we've talked about the gold standard, which would probably be fat oxidation, but even that can be confounded.
[01:25:34.320 --> 01:25:41.120] But let's take off the table the people who are consuming a high-fat, low-carbohydrate diet, because that confuses things a bit.
[01:25:41.120 --> 01:26:05.800] If I have a patient and I'm looking at their biometrics and we do a zone 2 test based on looking at their fat oxidation during an escalated test of part of a VO2 max test, and it comes back that their maximum fat oxidation, which is 0.3 grams per minute, occurs at a wattage of 1.5 watts per kilo.
[01:26:05.800 --> 01:26:07.400] That's a pretty average person.
[01:26:07.400 --> 01:26:14.520] And I say, I want that number higher, both the absolute number of fat oxidation, but where it occurs on the graph.
[01:26:14.520 --> 01:26:19.880] Now I want you in a year to be 2.5 watts per kilo.
[01:26:19.880 --> 01:26:22.200] Let's talk about two things.
[01:26:22.200 --> 01:26:27.560] One, how they should train, and that means duration, intensity, frequency, et cetera.
[01:26:27.560 --> 01:26:40.680] And secondly, what we should use as the readout to know we're in the right training zone, given that they won't be able to train daily or weekly or whatever frequency with indirect calorimetry.
[01:26:40.680 --> 01:26:47.960] And by the way, let's assume that some people will want to use the point of care lactate meters and some people will not.
[01:26:47.960 --> 01:26:53.160] Let's start with what's our surrogate for training zone, starting with what we knew.
[01:26:53.160 --> 01:27:00.920] So we learned that 1.5 watts per kilo was maximum fat oxidation, but we want to increase that to 2.5.
[01:27:00.920 --> 01:27:04.040] So what metric do you use to train them?
[01:27:04.040 --> 01:27:13.960] Normally what I do is like starting with the metabolic test, I translate that information into whether it's watts or speed or heart rate.
[01:27:13.960 --> 01:27:16.680] All of them normally they correlate quite well.
[01:27:16.680 --> 01:27:18.120] And you can individualize it.
[01:27:18.120 --> 01:27:19.720] There are people that don't have a power meter.
[01:27:19.720 --> 01:27:24.840] Okay, you can do heart rate, for example, or people that just obviously run or they walk.
[01:27:24.840 --> 01:27:27.000] You can do speed or heart rate as well.
[01:27:27.000 --> 01:27:27.960] Very good surrogate.
[01:27:27.960 --> 01:27:30.520] So that's the first metric, the surrogate.
[01:27:30.520 --> 01:27:39.880] Then it's about, at least from my experience, the three main principles that I've learned over the years and how to apply this.
[01:27:39.880 --> 01:27:42.600] So first is frequency.
[01:27:42.600 --> 01:27:46.480] Before we go to the frequency and the duration, I do want to go back and ask you another question.
[01:27:46.800 --> 01:27:53.840] We have some patients who don't want to use a lactate meter, either because it's cumbersome or somewhat intimidating.
[01:27:53.840 --> 01:27:59.680] We also add another metric, which is relative perceived exertion, RPE.
[01:27:59.680 --> 01:28:06.880] I'll tell you what my rule of thumb is, but I'd like you to sharpen it, refine it, throw it out, make it better, whatever.
[01:28:06.880 --> 01:28:25.760] I tell patients based on my experience, so I don't know how extrapolatable that is, when I'm in zone two, as confirmed by lactate levels, so call it 1.7 to 1.9 millimole, which is what I target, I can carry out a conversation, because I do most of mine on a Wahoo kicker.
[01:28:25.760 --> 01:28:27.680] I put my bike on a Wahoo kicker.
[01:28:27.680 --> 01:28:34.560] I can spend the entire 45 minutes on a phone call, but it's not as comfortable as this discussion here.
[01:28:34.560 --> 01:28:36.480] I'm a little more strained.
[01:28:36.480 --> 01:28:42.640] But if I can't talk, if I feel like I can't talk, I'm too high in the intensity.
[01:28:42.640 --> 01:28:52.320] Do you think that that's a reasonable surrogate for people to use across the spectrum of not particularly fit all the way up to pogacha?
[01:28:52.320 --> 01:28:53.680] 1,000%.
[01:28:53.680 --> 01:29:01.280] And I use the same metrics also with people who you mentioned they don't want to do a lactate meter or they don't have access.
[01:29:01.280 --> 01:29:07.440] I get hundreds of emails about where can I do this test or is there anything that I can do?
[01:29:07.440 --> 01:29:08.880] And I agree 100%.
[01:29:08.880 --> 01:29:19.600] With everything that we know at the granular cellular level, by injecting fuels and sustrays directly into the matter conditions, we cannot get more cellular level and scientific than that.
[01:29:19.600 --> 01:29:23.360] The surrogate or the perceived exertion, it works beautifully.
[01:29:23.360 --> 01:29:30.760] I know that people are coming up with different algorithms based on Harris variability or DFA, one alpha, et cetera.
[01:29:29.840 --> 01:29:32.920] But honestly, I agree 100% with you.
[01:29:33.160 --> 01:29:40.360] I always tell people: if you can exercise, whatever the exercise you do, and maintain a conversation like you and I are doing, you're way too easy.
[01:29:40.360 --> 01:29:42.040] You're probably zone one.
[01:29:42.040 --> 01:29:45.240] If you can talk, but it's some form of strain.
[01:29:45.240 --> 01:29:50.200] You can talk for two hours, but we're talking a little bit like that.
[01:29:50.200 --> 01:29:51.800] You're just at that threshold.
[01:29:51.800 --> 01:29:57.720] Put it this way: the other litmus test I tell people is the person on the other end will know you are exercising.
[01:29:57.720 --> 01:29:58.360] Exactly.
[01:29:58.360 --> 01:30:01.640] You will not be able to mask from them that you are exercising.
[01:30:01.640 --> 01:30:02.360] Exactly.
[01:30:02.360 --> 01:30:07.880] And in fact, I have many conference calls with people that I know to be respectful, but I do it on the bike.
[01:30:07.880 --> 01:30:13.320] They call me and I'm on the bike, either outside or in the trainer, and they tell me, you're exercising, right?
[01:30:13.320 --> 01:30:14.600] Because you can feel it.
[01:30:14.600 --> 01:30:20.280] But yet, I can maintain a full hour meeting on the bike without bothering the other person because they can understand me.
[01:30:20.280 --> 01:30:29.400] But instead, if you cross to the point where you cannot maintain that conversation, you need to breathe much faster because you're producing more CO2.
[01:30:29.400 --> 01:30:39.240] And that's probably because you're already transitioning from the slow twitch muscle fibers to the fast twitch muscle fibers, more glycolytic, more lactate, more CO2, more buffering capacity.
[01:30:39.240 --> 01:30:42.840] So it seems old school, but it works beautifully.
[01:30:42.840 --> 01:30:43.400] Agreed.
[01:30:43.400 --> 01:30:48.120] And the other thing I do, because I really like people to triangulate and give them a starting point.
[01:30:48.120 --> 01:30:55.880] So if someone has not done a metabolic test yet, and that's usually the case, by the way, is that we're starting with just a zone two training protocol.
[01:30:55.880 --> 01:30:58.280] I also give them some ranges on heart rate.
[01:30:58.280 --> 01:31:00.520] Now, here I have found much more variability.
[01:31:00.520 --> 01:31:09.320] So the first thing I say is to do this, you do need to know your maximum heart rate, not your predicted maximum heart rate, but your actual achieved maximum heart rate.
[01:31:09.320 --> 01:31:19.440] In my experience, personally, my zone two is actually at about 78 to 81% of my maximum heart rate.
[01:31:19.440 --> 01:31:23.440] But I know that for less trained people, it's lower.
[01:31:23.440 --> 01:31:37.120] So I tell people a broad range of 70 to 80% of your realized maximum heart rate is a good place to start and then make adjustments based on relative perceived exertion.
[01:31:37.120 --> 01:31:38.000] I agree.
[01:31:38.000 --> 01:31:39.760] What do you know about heart rate?
[01:31:39.760 --> 01:31:45.120] I would agree that I usually also say the same thing somewhere between 70 to 80.
[01:31:45.120 --> 01:31:49.120] That being said, right, if you want to be very, it's a big range, exactly.
[01:31:49.120 --> 01:31:57.520] So you can be at 70, let's say at 1.7 millimoles, and then at 80, you can be at 5 millimoles.
[01:31:57.520 --> 01:31:59.040] You're completely away from one zone.
[01:31:59.040 --> 01:32:00.480] But as you said, it's a good starting point.
[01:32:00.480 --> 01:32:07.600] And as you very well said, and I agree 100% with you is like, yeah, then you tweak it with your perceived exertion.
[01:32:07.600 --> 01:32:14.400] The other thing, too, with the heart rate, and this is where the heart rate variability, there are different interpretations.
[01:32:14.400 --> 01:32:20.240] So the modern interpretation of the heart rate variability is the differences between bit to bit.
[01:32:20.240 --> 01:32:22.560] And that's where there are different algorithms.
[01:32:22.560 --> 01:32:31.040] For me, the heart rate variability, it's more at a broader spectrum and it's more on adrenergic activation that you have.
[01:32:31.040 --> 01:32:33.680] So for example, you're fatigued today.
[01:32:33.680 --> 01:32:39.680] First of all, normally you're going to wake up with your resting heart rate a little bit higher than normally.
[01:32:39.680 --> 01:32:46.080] If your normal heart rate, let's say it's 50, and you're being fatigued, you might wake up with 65.
[01:32:46.080 --> 01:32:49.120] So that alone is a heart rate variability concept.
[01:32:49.120 --> 01:32:52.000] It varies from the norm to one day.
[01:32:52.000 --> 01:32:54.640] So that's our red flag that you might be tired that day.
[01:32:54.720 --> 01:32:59.480] Might not be super sensitive, but it is very sensitive for elite athletes, without a doubt.
[01:32:59.120 --> 01:33:02.600] The second aspect is like when you go out there and exercise.
[01:33:02.920 --> 01:33:11.960] As you might see, there are days that you're like 130 bits per minute, whatever you think your zone 2 is 130, 138, for example.
[01:33:11.960 --> 01:33:15.800] But some days it's really hard to get that heart rate.
[01:33:15.800 --> 01:33:20.440] You're already struggling at 110 bits per minute or 115 bits per minute.
[01:33:20.440 --> 01:33:21.960] Where that's not the norm.
[01:33:21.960 --> 01:33:23.320] That's another deviation.
[01:33:23.320 --> 01:33:25.240] That's a variability of the heart.
[01:33:25.320 --> 01:33:32.040] So this is what I've been historically used for heart rate variability, which tells me a lot more information.
[01:33:32.040 --> 01:33:34.200] This is what all the athletes also tell you.
[01:33:34.200 --> 01:33:37.000] Like, man, my heart rate doesn't get up today.
[01:33:37.320 --> 01:33:38.520] You see on training peaks.
[01:33:38.520 --> 01:33:45.480] You know, you see when someone is fatigued, they do an interval and they know they're always 180, 185, let's say, the lack of threshold.
[01:33:45.480 --> 01:33:48.840] And today they cannot get up until more than 170.
[01:33:48.840 --> 01:33:55.240] You see in the competition, the first week of the Tour de France, the maximal heart rate, let's say it's 195.
[01:33:55.240 --> 01:33:58.440] Last week, the maximal heart rate is 170.
[01:33:58.760 --> 01:34:01.080] That's what I interpret by heart rate variability.
[01:34:01.080 --> 01:34:05.160] And I know that a lot of people might criticize me because, oh, that has nothing to do with...
[01:34:05.160 --> 01:34:07.240] No, I think it's macro versus micro.
[01:34:07.240 --> 01:34:07.960] I agree.
[01:34:07.960 --> 01:34:09.800] I read it as macro versus micro.
[01:34:09.800 --> 01:34:13.080] I'll share with you an interesting self-experiment I've done a couple of times.
[01:34:13.080 --> 01:34:15.560] It's not pleasant, but it's interesting.
[01:34:15.560 --> 01:34:23.480] If I take a huge dose of a beta blocker, and the only beta blocker you can do this with, if you have low blood pressure, as I do, you have to be careful.
[01:34:23.480 --> 01:34:30.360] But propranolol is fine because it really disproportionately lowers heart rate, but not blood pressure.
[01:34:30.360 --> 01:34:44.040] But I've done this experiment a few times to test an idea, which is: would taking all of the gas out of my heart rate allow me to push harder and generate a higher zone 2?
[01:34:44.040 --> 01:34:45.840] And it turns out it does.
[01:34:45.840 --> 01:34:49.200] So my zone two is just under three watts per kilo.
[01:34:44.840 --> 01:34:51.680] I really want to talk with you about getting over three watts per kilo.
[01:34:51.760 --> 01:34:56.880] I'm still furious because in July, remember, I was at 2.95.
[01:34:56.880 --> 01:34:59.360] I was just kissing on the door of three.
[01:34:59.360 --> 01:35:04.720] I've come back, you know, I'm now at about 2.75 to 2.85, so I've lost a bit.
[01:35:05.040 --> 01:35:06.320] Aging, too.
[01:35:06.960 --> 01:35:08.880] We're going to talk about training in a moment.
[01:35:08.880 --> 01:35:12.080] So, and for me, I'm at that upper end of maximum heart rate.
[01:35:12.080 --> 01:35:16.240] So, I'm going to be doing that at about 80, 81% of maximum heart rate.
[01:35:16.240 --> 01:35:30.000] But if I took propranolol, 60 milligrams of a time-release propranolol, I will be able to get over 3 watts per kilo, and I'll do it at a heart rate of 68% of maximum.
[01:35:30.000 --> 01:35:31.680] But it feels horrible.
[01:35:31.680 --> 01:35:33.760] I feel like I'm going to die.
[01:35:33.760 --> 01:35:37.680] It is the worst feeling in the world.
[01:35:37.680 --> 01:35:39.040] And it's not pain.
[01:35:39.040 --> 01:35:43.680] I don't know how to explain it other than it feels like what it feels like when you're overtrained.
[01:35:43.680 --> 01:35:45.840] It feels like you just can't get moving.
[01:35:45.840 --> 01:35:54.880] It's like an engine that's being taken from 9,000 RPM to 6,000 RPM, but yet somehow is able to generate the horsepower.
[01:35:54.880 --> 01:35:56.320] But it just doesn't feel right.
[01:35:56.320 --> 01:36:00.640] So that's my drug-cheating way to get over 3 watts per kilo.
[01:36:00.640 --> 01:36:02.000] But more to illustrate the point, right?
[01:36:02.000 --> 01:36:06.960] Which is when you put the governor on heart rate, you can get there at a lower heart rate.
[01:36:06.960 --> 01:36:08.880] Subjectively, it's a miserable feeling.
[01:36:08.880 --> 01:36:14.800] Yeah, and this is kind of in a way what happens when you're fatigued, when you don't have enough fuel.
[01:36:14.800 --> 01:36:20.960] Again, going back to like my heart doesn't get up today, and I'm struggling if you were taking some better blocker.
[01:36:20.960 --> 01:36:23.920] But the thing is that it has to do a lot with fuel.
[01:36:23.920 --> 01:36:27.280] For example, and I experiment this a lot too.
[01:36:27.280 --> 01:36:48.200] I try to understand how this works, so I do maybe intermittent fasting for a few days and I go out there and good at adjusting at that and I cannot do that I know others can do it and I admire that but I can see my heart rate right away when you don't have enough glycogen storages it's very possible that adrenaline activity is decreased.
[01:36:48.200 --> 01:36:58.280] You need to break down glycogen and we know that what it takes to break down glycogen is forcephorylase in the muscle and that's directly regulated by catecholamines.
[01:36:58.280 --> 01:37:02.440] So when there's a decrease in glycogen, this is my hypothesis, right?
[01:37:02.440 --> 01:37:09.560] When there's a decrease in glycogen storages, because of the evolutionary mechanisms that humans have, the brain is the boss.
[01:37:09.560 --> 01:37:17.560] The brain says, like, I don't care about your legs, but don't use up all the glycogen because you have to give me, and the liver has to give me glycogen as well.
[01:37:17.560 --> 01:37:23.880] So I'm not going to shut you down completely of breaking down glycogen, but I'm going to slow you down.
[01:37:23.880 --> 01:37:29.080] So I'm going to release less catecholamine so that you break down less glycogen.
[01:37:29.080 --> 01:37:36.200] The collateral effect of that is the heart because the heart contractility is regulated by catecholamines as well.
[01:37:36.200 --> 01:37:41.160] So this is why using that, my version of heart rate variability, it's quite useful.
[01:37:41.160 --> 01:37:48.680] I've been using it incredibly successfully for 25 years with my athletes where I see that, hey, your heart rate is not going up today.
[01:37:48.680 --> 01:37:55.000] And usually it's 185, 190, for example, when you do a lactic threshold, for example, and today it was 170.
[01:37:55.000 --> 01:38:04.760] So tomorrow, take it easy or pile up on glycogen, I mean on carbohydrates, or take it easy day, and you see how you're going to be very responsive the next day, the following day.
[01:38:04.760 --> 01:38:06.360] And in fact, that's what happens.
[01:38:06.360 --> 01:38:10.040] I would say 10 out of 10 times, but let's say 9 out of 10 times, right?
[01:38:10.040 --> 01:38:12.040] But I do that with myself as well.
[01:38:12.040 --> 01:38:20.800] And I see also I work a lot with the head, you think a lot, and the brain uses about 100 to 125 grams of glucose daily.
[01:38:21.120 --> 01:38:30.960] When you go, and I don't know that fact, when you work a lot of hours and thinking and thinking and thinking and stressed, the brain might need a lot more glucose.
[01:38:30.960 --> 01:38:39.280] So that's training your glycogen storages from the brain, probably, and even from the muscles, because the muscle can release glucose to be utilized as well.
[01:38:39.280 --> 01:38:39.840] Yes.
[01:38:39.840 --> 01:38:48.000] The muscle has phosphorylase and can be degraded to glycogen, and that glucose can go to the circulation as well to feed other organs.
[01:38:48.000 --> 01:38:51.680] I didn't realize that we had glucose 1-phosphatase in the muscle.
[01:38:51.680 --> 01:38:55.280] I thought the muscle glycogen fate was sealed in the muscle.
[01:38:55.280 --> 01:38:55.920] It's possible.
[01:38:55.920 --> 01:38:56.880] There are a few studies.
[01:38:56.880 --> 01:38:58.400] I'm happy to send them to you.
[01:38:58.400 --> 01:39:06.240] I cannot refer them out of memory, but the muscles can also release glucose to and export glucose.
[01:39:06.480 --> 01:39:10.640] I assume this is a relatively small amount compared to what the liver is doing.
[01:39:10.640 --> 01:39:12.320] Yeah, absolutely, exactly.
[01:39:12.320 --> 01:39:13.920] But it's possible too.
[01:39:13.920 --> 01:39:21.840] So those days where I'm thinking a lot and I'm very stressed and I'm not dieting or anything, I just go out there and I'm dead.
[01:39:21.840 --> 01:39:24.800] And I'm sure that many people listening to this feel the same way.
[01:39:24.800 --> 01:39:26.880] Like, what the hell is going on today?
[01:39:26.880 --> 01:39:28.800] I don't have energy at all today.
[01:39:29.120 --> 01:39:32.160] And you will see that your heart rate doesn't get up those days.
[01:39:32.160 --> 01:39:36.480] And you can get to that by just training five hours a week or seven hours a week.
[01:39:36.480 --> 01:39:41.120] And sometimes people say, Look, I cannot be overtrained because I only train five hours a week.
[01:39:41.120 --> 01:39:43.120] Yeah, but you're overworked.
[01:39:43.120 --> 01:39:45.440] That's a big artifact with your training.
[01:39:45.440 --> 01:39:53.760] That's what most of us are aspire to pre-retire before 60, you know, so we can have more time to exercise and less time to work.
[01:39:53.760 --> 01:39:55.160] But yeah, that's what I do this.
[01:39:54.960 --> 01:39:57.200] This I take a day off completely.
[01:39:57.200 --> 01:39:58.320] I sleep more.
[01:39:58.320 --> 01:40:00.760] I increase my carbohydrate intake.
[01:40:00.760 --> 01:40:05.160] And the following day, I can even break my PR and a climb or something.
[01:39:59.920 --> 01:40:06.680] I feel like a million dollars.
[01:40:07.000 --> 01:40:10.040] So resting recovery is key for that.
[01:40:10.040 --> 01:40:22.760] I think that's a very important point, and it's actually something I've only been able to pay attention to in the last year, which is I used to judge my performance by training load.
[01:40:22.760 --> 01:40:24.520] I used to use training peaks when I was training.
[01:40:24.520 --> 01:40:25.240] I don't anymore.
[01:40:25.240 --> 01:40:33.880] But the concepts of acute and chronic training balance, any day that was suboptimal could be explained by training volume in some capacity.
[01:40:33.880 --> 01:40:36.360] But now, my training volume is relatively low.
[01:40:36.360 --> 01:40:38.200] It's 10 hours a week of total training.
[01:40:38.200 --> 01:40:40.200] That's both cardio and strength.
[01:40:40.200 --> 01:40:41.880] This is not a lot of training.
[01:40:41.880 --> 01:40:46.520] And yet, when I'm under stress, work-wise, I'm just doing too much.
[01:40:46.600 --> 01:40:47.960] I don't even use the word stress.
[01:40:47.960 --> 01:40:50.280] It has a real negative connotation to it.
[01:40:50.280 --> 01:41:09.400] I just mean when I'm overworked, when I'm doing too much, my performance, I have to either adjust my parameters for what I deem successful, or I just have to cut back on the actual training a little bit to make time for more sleep or more relaxation.
[01:41:09.400 --> 01:41:12.840] So I think that's a very important point that is easily lost.
[01:41:12.840 --> 01:41:16.920] So we've got a very good handle on the metrics we're going to be using.
[01:41:16.920 --> 01:41:19.960] So now let's talk about two scenarios.
[01:41:19.960 --> 01:41:23.480] The first is the person who is new to this type of training.
[01:41:23.480 --> 01:41:33.160] So they've listened to this podcast, or they're one of my patients, and I've made the case convincingly to them that you really need to do this type of training.
[01:41:33.160 --> 01:41:37.240] I want to come back, by the way, to a justification for that.
[01:41:37.240 --> 01:41:42.280] So let's explain why high-intensity training is not sufficient, but we'll park that for a moment.
[01:41:42.280 --> 01:41:45.000] But they really don't have much of a background in this type of training.
[01:41:45.280 --> 01:41:55.040] Maybe they do some high-intensity training, they do some weights, they play some tennis, but they really don't do the sort of steady-state, sustained cardio that we're talking about.
[01:41:55.040 --> 01:41:59.600] How would you structure a training program in dose, duration, frequency?
[01:41:59.600 --> 01:43:43.800] for that individual and tell me a little bit about the choices that you would make if they're agnostic to running walking cycling rowing swimming i have my biases there but i want to kind of hear what you have to say about it i want to apologize to many of your audience because i get a lot of emails asking me about these questions and it's hard to keep up well that's why we're doing the podcast so you don't have to apologize it's easier to do it this way i appreciate it this way but see i get emails and before i used to see people here at the university but now the university don't have these services trying to convince them that these services are important to offer to population but anyways i want to apologize because i cannot answer to everybody i have the three main rules or parameters that i have learned over the years so one is the duration we have in mind sometimes that this is like endurance training long days like i only have it six hours a week or seven hours a week at most to do this type of training or less there's no way i can do that it's usually less because they might have six hours a week for total exercise and we're going to take half of that for strength training exactly which is very important as you know it's where i fail because i i should do more of that and i try to get a little bit more of time to do that it's not easy but i aspire really to dial that in but yeah you're right they might have less than six hours and they might think like well i'm not an endurance athlete so you need to do four hours to accomplish this so therefore i'm just going to move to do just high intensity and just get out of the way that's not completely true you can accomplish very important mitochondrial adaptations and very important metabolic adaptations by exercising one hour Let's start by the duration.
[01:43:43.800 --> 01:43:48.600] If you try to do that one hour to one hour and a half range, you're on target.
[01:43:48.600 --> 01:43:50.680] Is that total or one setting?
[01:43:50.680 --> 01:43:58.280] Meaning, is it one to one and a half hours per week or does that need to be in one continuous exercise bout?
[01:43:58.280 --> 01:44:06.840] So the frequency that I see is that this type of training ideally needs to be done between three to four days a week, ideally.
[01:44:06.840 --> 01:44:08.440] And how can I know this?
[01:44:08.440 --> 01:44:12.280] I know this because I've seen in the laboratory everything.
[01:44:12.280 --> 01:44:19.480] The person who trains one day at these zones or two days or three days or four days or high intensity, low intensity, and I see the adaptations.
[01:44:19.480 --> 01:44:20.840] How do I see the adaptations?
[01:44:20.840 --> 01:44:26.440] Again, looking at fat oxidation, lactate cleanse capacity, all surrogates of mitochondrial function.
[01:44:26.440 --> 01:44:29.400] I've been identifying the dose of that training.
[01:44:29.400 --> 01:44:36.360] So if you train once a week, there, chances are that you're going to deteriorate over time, and especially as we age.
[01:44:36.360 --> 01:44:48.600] Something that I see, for example, in high-intensity exercisers and bodybuilders, they have a very poor mitochondrial function compared to people who do more a little bit of everything.
[01:44:48.600 --> 01:44:50.760] So one day a week is not going to work.
[01:44:50.760 --> 01:44:54.200] Two days a week, it might maintain what you have.
[01:44:54.200 --> 01:44:58.440] But if you're new to an exercise program, it might not be enough.
[01:44:58.440 --> 01:45:02.120] Three days a week, now we're starting to see for sure.
[01:45:02.120 --> 01:45:08.360] Four days a week, now we're talking ideally five days a week or six, but not everybody has obviously six days a week to train.
[01:45:08.360 --> 01:45:11.000] But I think that you are a very busy guy.
[01:45:11.000 --> 01:45:12.280] I'm a very busy guy.
[01:45:12.280 --> 01:45:22.240] Try to squeeze four or five days a week, maybe six in the summer, but four or five days is achievable for most individuals and put aside an hour to an hour and a half.
[01:45:22.560 --> 01:45:25.280] So I would say that four days a week is ideal.
[01:45:25.280 --> 01:45:26.800] That's the first principle.
[01:45:26.800 --> 01:45:28.880] The second principle is the duration.
[01:45:28.880 --> 01:45:39.120] Going back to what I was saying, with one hour, maybe Pogatsra needs four hours, five hours, to keep increasing those huge mitochondria for a long time.
[01:45:39.120 --> 01:45:57.840] But a meromortal, especially someone who might be pre-diabetic or might be out of fitness or hasn't exercised in a long time, or someone who coming from a disease or a mother who just had a baby and has been out of say for a while, one hour, if you walk or if you run, might be very, very good for you.
[01:45:57.840 --> 01:46:00.800] One hour walk or run, you might have to bring it up.
[01:46:00.800 --> 01:46:02.400] That's part of the plan too.
[01:46:02.400 --> 01:46:04.800] You cannot start off the bat with one hour.
[01:46:04.800 --> 01:46:09.120] You might start by 20 minutes, 30 minutes, 40 minutes, increasing it, but maybe about an hour.
[01:46:09.120 --> 01:46:14.480] And if you bike, for example, about an hour, 20 minutes, hour and a half.
[01:46:14.480 --> 01:46:19.520] That's what I see that if you do that for four days a week, things are starting to move.
[01:46:19.520 --> 01:46:26.720] Even if you bike on a trainer where you can be much more efficient and you can really get straight to the wattage and stay there.
[01:46:26.720 --> 01:46:37.520] We tell patients, again, it depends where they are in their cycle, but if they're starting out, I mean, we'll be happy if they give us 30 minutes, three to four times a week of dedicated exercise.
[01:46:37.520 --> 01:46:39.600] I can't do zone two on the road.
[01:46:39.600 --> 01:46:41.520] I can really only do it on the trainer.
[01:46:41.520 --> 01:46:48.480] I just can't stay at a constant level on the road with starting and stopping and wind and hills and stuff like that.
[01:46:48.480 --> 01:46:49.360] That's a very good point.
[01:46:49.360 --> 01:46:55.840] That's why an hour and a half on the bike, it might actually be one hour or so because you have all these artifacts.
[01:46:55.840 --> 01:46:59.200] But you're right, when you're on the trainer, you isolate everything completely.
[01:46:59.200 --> 01:47:02.840] And what I also recommend is about an hour if you can get there.
[01:47:02.840 --> 01:47:09.560] But again, you know, like, yeah, sure, you might, to me, it's it feels like a torture sometimes to be an hour on the trainer.
[01:47:09.560 --> 01:47:10.280] I hate it.
[01:47:10.280 --> 01:47:13.160] I like to be outside, but we have had to do it.
[01:47:13.160 --> 01:47:13.640] I do it.
[01:47:13.640 --> 01:47:16.280] I watch a movie or just catch up on work.
[01:47:16.280 --> 01:47:22.280] I have one with special desks where I can type or read articles or answers and emails.
[01:47:22.280 --> 01:47:27.000] Low-key activity because, again, you know, you're not very sharp to think very intellectually.
[01:47:27.000 --> 01:47:28.760] But yeah, one hour might do the trick.
[01:47:28.760 --> 01:47:37.720] What I've seen is like, yeah, in those people who haven't done much at all, even 30 minutes, 20 minutes might start moving the needle, but eventually it's not enough.
[01:47:37.720 --> 01:47:40.040] Those the body needs more.
[01:47:40.040 --> 01:47:47.640] If you can get to a goal about an hour to an hour and a half, that should really work, in my modest opinion, in my experience.
[01:47:47.640 --> 01:47:49.320] So that's the duration.
[01:47:49.320 --> 01:47:54.040] And the third is always the frequency, which we have talked about, which is usually the zone two.
[01:47:54.040 --> 01:48:02.280] That being said, I think that it's also important to stimulate other energy systems like the glycolytic system.
[01:48:02.280 --> 01:48:05.320] And again, continue with the model that we do with elite athletes.
[01:48:05.320 --> 01:48:14.040] People think that elite athletes, whatever the sport are, all they do is high intensity all the time and intervals, intervals.
[01:48:14.040 --> 01:48:15.720] And it's the exact opposite.
[01:48:15.720 --> 01:48:27.240] If you look at the workload of an elite athlete, whether that elite athlete is, especially in individual sports, it's easier to see this, whether it's a triathlete or a cyclist or a marathon runner or a swimmer.
[01:48:27.240 --> 01:48:29.720] A hundred meter swimmer is under a minute.
[01:48:29.720 --> 01:48:31.560] Maximal exercise.
[01:48:31.560 --> 01:48:33.880] If you look at the workload, it's very similar.
[01:48:33.880 --> 01:48:37.240] The majority of the sessions are in the lower intensity.
[01:48:37.240 --> 01:48:39.320] They're not intervals, intervals, intervals.
[01:48:39.320 --> 01:48:48.640] And I always say, we cannot be so naive to think that the best coaches and athletes in the world haven't figured this out when they're always trying new things and they want to try the cut and edge things.
[01:48:48.960 --> 01:48:53.760] Obviously, they have said, oh, our sport is swimming under a minute.
[01:48:53.760 --> 01:48:57.280] All we need to do is like intervals, intervals, intervals, intervals.
[01:48:57.280 --> 01:49:05.040] Well, if you look at what swimmers do, they train, and if you ask Michael Phelps, hours and hours and hours and hours and hours.
[01:49:05.040 --> 01:49:19.280] Because if you can travel through the competition in that under a minute with a slightly better function to clear lactate, even if it's one millimole or less, the muscle contractual force might be improved.
[01:49:19.280 --> 01:49:24.800] So all the hours and hours and hours might be that just to improve a fraction of a second.
[01:49:24.800 --> 01:49:35.280] But anyway, so this is what I'm saying: that these concepts of glycolytic capacity and high-intensity training, they're necessary, but they're not what the elite athletes do.
[01:49:35.280 --> 01:49:39.760] The elite athletes have the best metabolic function of any humans.
[01:49:39.760 --> 01:49:43.920] Why not try to imitate their philosophy of exercise?
[01:49:44.240 --> 01:49:52.640] And so, just to come back to the frequency duration question, I think the answer to the following question is going to be the more frequent training sessions.
[01:49:52.640 --> 01:50:10.480] But if you compared four training regimens that were four hours a week each, one of them would be four 60-minute sessions, one of them would be three 80-minute sessions, one of them would be two two-hour sessions, and then one of them would be one four-hour session.
[01:50:10.480 --> 01:50:23.200] So it's the same total volume, and notwithstanding the brain damage of one four-hour session, is it safe to say that the four 60-minute sessions, because it's a higher frequency, would be the optimal one there?
[01:50:23.520 --> 01:50:24.320] I would say so.
[01:50:24.640 --> 01:50:27.200] I think from my experience that it might be better.
[01:50:27.200 --> 01:50:28.160] It's the frequency.
[01:50:28.160 --> 01:50:37.720] It's like if you take a medication, if you take a medication twice the dose and only three days a week, might not work as well as if you take the right dose every day.
[01:50:37.720 --> 01:50:42.200] Because at the end of the day, we're talking about the whole exercise as medicine, right?
[01:50:42.200 --> 01:50:43.480] How do we prescribe that?
[01:50:43.480 --> 01:50:44.360] What's the dose?
[01:50:44.360 --> 01:50:45.240] What's the frequency?
[01:50:45.400 --> 01:50:49.160] I'm assuming that you will have to take it as many days as possible.
[01:50:49.320 --> 01:50:51.640] I would say that it's better to do that.
[01:50:51.640 --> 01:51:00.120] That being said, obviously, if you have the weekend and you have the possibility, which I don't have, to do three hours, go ahead.
[01:51:00.120 --> 01:51:05.320] And another thing I wanted to point out is that for many people, they need that adrenaline for training.
[01:51:05.320 --> 01:51:07.160] So other people don't care.
[01:51:07.160 --> 01:51:09.160] Other people say, whoa, I love this.
[01:51:09.160 --> 01:51:11.640] I don't like to kill myself into high-intensity.
[01:51:11.640 --> 01:51:14.920] But I think you need to do some high-intensity, right, at some point.
[01:51:14.920 --> 01:51:15.800] I want to talk about that.
[01:51:15.800 --> 01:51:18.360] So how do we bring in the other energy systems?
[01:51:18.360 --> 01:51:35.560] Of the four pillars of exercise in my world, stability, strength, low-end aerobic, which I describe really as talk about it as kind of mitochondrial efficiency, and then high-end aerobic, which is peak aerobic capacity slash anaerobic performance.
[01:51:35.560 --> 01:51:42.120] So anaerobic power, peak aerobic, low-end aerobic, mitochondrial efficiency, strength stability.
[01:51:42.120 --> 01:51:54.200] Of those four, I, for some reason, struggle to make the time for the peak aerobic, in part because, one, it's the least enjoyable, if we're going to be brutally honest.
[01:51:54.200 --> 01:51:56.680] If you're doing it right, it hurts the most.
[01:51:56.680 --> 01:52:00.760] It's also no longer as relevant because I don't compete at anything.
[01:52:00.760 --> 01:52:12.760] I actually really enjoyed that type of training when I competed because you have to spend time in that energy system and you see the rewards of 60 minutes of repeating two-minute intervals or something like that.
[01:52:12.760 --> 01:52:24.480] So if we're really talking about this from the lens of health, maximizing health, the data are unambiguous that VO2 max is highly correlated with longevity.
[01:52:24.480 --> 01:52:27.680] There are not many variables that are more strongly correlated.
[01:52:27.680 --> 01:52:29.520] But the levels don't have to be that high.
[01:52:29.520 --> 01:52:32.640] Pogots are VO2 max is probably 85.
[01:52:32.640 --> 01:52:38.720] It's probably in the 80s at least in terms of milliliters per minute per kilogram.
[01:52:38.720 --> 01:53:00.560] But someone my age to be considered absolutely elite, which means the top 2.5 to 2.7% of the population, which carries with it a five-fold reduction in risk to the bottom 25% of the population, my VO2 max requirement is about 52, 53 milliliters per minute per kilogram.
[01:53:00.560 --> 01:53:06.960] So the question is, can I use that as the gauge for how much high-intensity training I need to do?
[01:53:06.960 --> 01:53:11.280] Basically just enough to make sure I maintain that VO2 max?
[01:53:11.280 --> 01:53:13.360] Or do you think about it in a different way?
[01:53:13.360 --> 01:53:17.040] Well, I think about it more by energetics, energy systems.
[01:53:17.040 --> 01:53:24.480] Ultimately, and we know that longevity is also high related with mitochondrial function and metabolic health.
[01:53:24.480 --> 01:53:33.040] I think that more and more, and this is what you see in so many fields in medicine nowadays, everybody is stumbling upon mitochondria.
[01:53:33.040 --> 01:53:41.600] So there's an aging process where we lose mitochondrial function, and there's like a sedentary component where we lose mitochondrial function.
[01:53:41.600 --> 01:53:49.760] I wish that we could have a medication or PL you could take it and increase the mitochondrial function because it would increase metabolic health and longevity.
[01:53:49.760 --> 01:53:52.560] But the only medication that we know is exercise.
[01:53:52.560 --> 01:54:01.080] Within exercise, the dose that we see that improves the most and also is sustainable in the long term, which is another important concept.
[01:54:01.080 --> 01:54:04.520] Very high-intensity training is not sustainable.
[01:54:04.520 --> 01:54:06.920] Very extreme diets are not sustainable.
[01:54:06.920 --> 01:54:09.080] If you combine both, it's even worse.
[01:54:09.080 --> 01:54:11.080] And this is what a lot of people are doing together.
[01:54:11.080 --> 01:54:16.840] But you need to have some sustainability, but this is important to improve that mitochondrial function.
[01:54:16.840 --> 01:54:24.920] But going back to the high-intensity, I think, is necessary because we also lose glycolytic capacity as we age, and it's important to stimulate it.
[01:54:24.920 --> 01:54:31.960] As you very well said, for all of us who are not competing, I couldn't care less about being super high-intensity.
[01:54:32.120 --> 01:54:33.080] I'm not competing.
[01:54:33.080 --> 01:54:35.880] But that said, I want to have also my adrenaline rush.
[01:54:35.880 --> 01:54:37.480] But how much does it feed into it?
[01:54:37.480 --> 01:54:47.720] So, for example, if, and I've often thought about this now as I just want to make sure my zone two is above three watts per kilo, would I be better off taking that extra training?
[01:54:47.720 --> 01:54:53.240] If I have one additional training session per week, should I make it an additional zone two workout?
[01:54:53.240 --> 01:54:54.440] I do four now.
[01:54:54.440 --> 01:55:02.120] Should I be doing a fifth one, or should I be taking that fifth one and doing a VO2 max protocol?
[01:55:02.120 --> 01:55:14.280] And that's what we'll typically prescribe to our patients: a four by four protocol of highest intensity sustained for four minutes, followed by four minutes of recovery, and then repeat that four, five, six times.
[01:55:14.280 --> 01:55:18.680] When you put a warm-up and cool down on either end of that, that's a little over an hour.
[01:55:18.680 --> 01:55:24.280] Would you spend that hour doing that in an effort to make your zone two even better?
[01:55:24.280 --> 01:55:27.320] Or would you just do an extra hour of zone two?
[01:55:27.320 --> 01:55:34.520] I agree that if you have a fifth day, you can convert it into any type of high-intensity session, structured.
[01:55:34.520 --> 01:55:39.480] What I can tell people also: hey, you're a cyclist or a runner, you want to go with your friends on the fifth.
[01:55:39.640 --> 01:55:40.600] That's your group ride.
[01:55:40.600 --> 01:55:43.160] The group ride, go ahead and boom, go at it.
[01:55:43.160 --> 01:57:17.240] Or if you don't have that possibility this is my situation for example where i i don't have the time to train more than an hour and a half usually two hours max so what i do almost on every session i do my zone two so it's clean and at the end that's what i do a very high intensity interval tell me the duration so if you did an hour of zone two yeah so i do usually let's say an hour and a half so you'll do an hour and a half of zone two three or four times a week i shoot for four or five not all the time it's easy but yeah i shoot four or five and i try to be strict on that but and unfortunate that where i live i live more in a thailand area so you have to go up so the last part i just go at it sometimes you find another cyclist and you just compete you know to see who's the fastest in that short climb but i try to do like a good five minute interval roughly i arrive home like man i kicked my ass today this kicked my ass today or sometimes you try it and you don't have the energy as i mentioned earlier oh my gosh i can barely move the pedals today i just quit and go home but when i feel fresh i stimulate that glycolytic system what we know well too is that that increases the mitochondrial function it takes months or years increasing the glycolytic system it takes much much less amount of time you can do that in weeks or months if you stimulate on a regular base two days a week or three days a week at the end of that zone two that's where you can target both high energy systems the oxidative mitochondrial system and the glycolytic energy system.
[01:57:17.560 --> 01:57:22.920] We don't blunt the benefit we had from the zone two if we immediately follow it with the zone five.
[01:57:22.920 --> 01:57:24.760] No, because that's done, right?
[01:57:24.760 --> 01:57:26.840] What I see is like if you do the same things in the middle.
[01:57:27.080 --> 01:57:28.840] But you don't want to do the reverse order.
[01:57:28.840 --> 01:57:30.200] You don't want to start with the high intensity.
[01:57:30.360 --> 01:57:30.600] Exactly.
[01:57:30.600 --> 01:57:40.280] One of the things like because you start having all these hormonal responses and also you see you have high lactate levels in the blood and what we know very well is like lactate inhibits lipolysis.
[01:57:40.600 --> 01:57:52.360] So if you have a high interval in the middle or the beginning and you don't clear lactate very well, you might have high lactate levels for a while and it's going to inhibit lipolysis.
[01:57:52.360 --> 01:58:01.000] Also another study we have under review, lactate at the autocrete level decreases the activity of CPT1 and CPT2.
[01:58:01.000 --> 01:58:04.840] So it interferes with the transport of fatty acids as well.
[01:58:04.840 --> 01:58:07.880] So that's where like if you do all these, you might change things.
[01:58:07.880 --> 01:58:10.520] You have high cortisoidinemia as well.
[01:58:10.520 --> 01:58:23.480] I'm glad you raised that because I explained this to patients when they say, I went out and did a two-hour ride today and it showed me that I spent 45 of those minutes, 45 of those 120 minutes were in zone two.
[01:58:23.480 --> 01:58:29.240] So I did 45 minutes of zone two and I say, no, you didn't really do it because you were going up and down and up and down and up and down.
[01:58:29.240 --> 01:58:34.440] And so that's not the same as spending 45 minutes in the dedicated energy system.
[01:58:34.440 --> 01:58:34.840] Right.
[01:58:34.840 --> 01:58:44.120] I mean, when I look at the training peaks, you see the elite athletes, they're like, what power output and heart rate, this is like goes together incredible.
[01:58:44.360 --> 01:58:46.120] Whereas, yeah, you're right, up and down, down.
[01:58:46.120 --> 01:58:52.040] The average might be zone two, but actually you're between oscillating zone one, zone three, zone four all the time.
[01:58:52.040 --> 01:58:58.440] So if you don't mind sharing, in watts per kilo, what is your zone two in Colorado where you're at altitude?
[01:58:58.440 --> 01:59:00.760] I don't look so much into this.
[01:59:00.760 --> 01:59:04.200] I have done so many tests in my life.
[01:59:04.200 --> 01:59:07.840] Since I was 15 years old, I was using a heart rate monitor.
[01:59:07.840 --> 01:59:12.520] I'm talking about 1986 when the first heart rate monitors came out.
[01:59:12.520 --> 01:59:15.360] What you're getting at is you don't like to have a lot of data when you're doing it.
[01:59:15.000 --> 01:59:22.080] You're going off RPE and you're not looking at your power meter or a heart rate monitor and you're not poking your finger when you're done.
[01:59:22.400 --> 01:59:27.120] I do it here and there because I still want to look at this and I do metabolic testing here and there.
[01:59:27.120 --> 01:59:28.480] But I've done so much.
[01:59:28.480 --> 01:59:35.600] And me, since I was 15 years old and I was obsessed by this, I got to a point that I know my body quite well.
[01:59:35.680 --> 01:59:39.680] I can just go by the sensations and but here and there I double check.
[01:59:39.680 --> 01:59:48.080] But it's hard for you to then get at what I've observed the few times I've tried to do my zone to at altitude, like in Colorado.
[01:59:48.080 --> 01:59:49.840] It's an enormous discount.
[01:59:49.840 --> 01:59:53.200] I feel like it's a 20% discount at altitude.
[01:59:53.200 --> 01:59:58.880] Yeah, mine's around 2.5, 2.8, something like that watts per kilogram when I do it.
[01:59:58.880 --> 02:00:01.920] At sea level, you'd be over three probably.
[02:00:01.920 --> 02:00:04.720] Based on what I experienced it going in the reverse direction.
[02:00:05.120 --> 02:00:06.240] I would say roughly.
[02:00:06.240 --> 02:00:11.840] And one thing that I'm very proud of is that I have been doing, because I do sporadically this testing.
[02:00:12.000 --> 02:00:19.040] I don't know my PRs because I think we have climbs here and one day I go for this climb and I go full out on that climb, right?
[02:00:19.040 --> 02:00:20.480] I'm 50 now.
[02:00:20.480 --> 02:00:24.720] I have the same metabolic parameters that when I was 40.
[02:00:24.720 --> 02:00:26.320] To me, I'm very proud of this because.
[02:00:26.480 --> 02:00:30.160] And when you say parameters, you don't mean times up the climbs.
[02:00:30.160 --> 02:00:32.000] Which parameters are the same?
[02:00:32.000 --> 02:00:34.800] Lactating power output, VO2.
[02:00:34.800 --> 02:00:36.640] I look at time as well.
[02:00:36.640 --> 02:00:38.880] The PR that I had, it was similar.
[02:00:38.880 --> 02:00:40.800] What's your VO2 max now?
[02:00:40.800 --> 02:00:44.800] So my VO2 max now is four liters per minute.
[02:00:44.800 --> 02:00:46.720] So that's about 51, 52.
[02:00:47.040 --> 02:00:51.200] You could easily raise that if you lost three kilos, which you could probably do.
[02:00:51.200 --> 02:00:51.680] Yeah, yeah, yeah.
[02:00:51.840 --> 02:00:52.080] Yeah.
[02:00:52.080 --> 02:00:58.960] And the thing is, because I've obviously, when I was a cyclist, I was 141, 143 pounds.
[02:00:58.960 --> 02:00:59.960] So my VO2 was...
[02:00:59.280 --> 02:01:03.320] And you were probably, your VO2 was five and a half liters or something.
[02:01:03.320 --> 02:01:05.640] It was 76.7.
[02:01:05.640 --> 02:01:06.200] Let me see.
[02:00:59.760 --> 02:01:08.040] It was 4.5, I believe.
[02:01:08.040 --> 02:01:10.760] It was about 4.8, something like that.
[02:01:10.760 --> 02:01:20.440] 30 years later, I have decreased only about 0.5, 0.7, which, whoa, I'm really happy about that because I'm not training like I did.
[02:01:20.440 --> 02:01:21.800] But this is one of the parameters.
[02:01:21.800 --> 02:01:25.560] But in a decade, I haven't decreased my parameters.
[02:01:25.560 --> 02:01:37.080] So this is, to me, it's a proving point to myself at least that doing this routine, it helps to maintain that metabolic health that you had a decade ago.
[02:01:37.080 --> 02:01:41.400] Now, can you do this 10 more years and when I turn 60?
[02:01:41.400 --> 02:01:42.680] I don't know.
[02:01:42.680 --> 02:01:46.200] But what I know is that from others, I'm seeing it.
[02:01:46.200 --> 02:01:54.920] So I see typical person who just retired, as I discussed earlier, aspire to pre-retire at the age of 60 or a little bit before.
[02:01:54.920 --> 02:02:02.520] And these are like people like us who are struggling to squeeze in time, do five hours here, 

Prompt 6: Key Takeaways

Now please extract the key takeaways from the transcript content I provided.

Extract the most important key takeaways from this part of the conversation. Use a single sentence statement (the key takeaway) rather than milquetoast descriptions like "the hosts discuss...". 

Limit the key takeaways to a maximum of 3. The key takeaways should be insightful and knowledge-additive. 

IMPORTANT: Return ONLY valid JSON, no explanations or markdown. Ensure:
- All strings are properly quoted and escaped
- No trailing commas
- All braces and brackets are balanced
Format: {"key_takeaways": ["takeaway 1", "takeaway 2"]}

Prompt 7: Segments

Now identify 2-4 distinct topical segments from this part of the conversation.

For each segment, identify:
- Descriptive title (3-6 words)  
- START timestamp when this topic begins (HH:MM:SS format)
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Most important Key takeaway from that segment. Key takeaway must be specific and knowledge-additive.
- Brief summary of the discussion

IMPORTANT: The timestamp should mark when the topic/segment STARTS, not a range. Look for topic transitions and conversation shifts.

Return ONLY valid JSON. Ensure all strings are properly quoted, no trailing commas:
{
  "segments": [
    {
      "segment_title": "Topic Discussion", 
      "timestamp": "01:15:30",
      "key_takeaway": "main point from this segment",
      "segment_summary": "brief description of what was discussed"
    }
  ]
}

Timestamp format: HH:MM:SS (e.g., 00:05:30, 01:22:45) marking the START of each segment.

Prompt 8: Media Mentions

Now scan the transcript content I provided for ACTUAL mentions of specific media titles:

Find explicit mentions of:
- Books (with specific titles)
- Movies (with specific titles)  
- TV Shows (with specific titles)
- Music/Songs (with specific titles)

DO NOT include:
- Websites, URLs, or web services
- Other podcasts or podcast names

IMPORTANT: 
- Only include items explicitly mentioned by name. Do not invent titles.
- Valid categories are: "Book", "Movie", "TV Show", "Music"
- Include the exact phrase where each item was mentioned
- Find the nearest proximate timestamp where it appears in the conversation
- THE TIMESTAMP OF THE MEDIA MENTION IS IMPORTANT - DO NOT INVENT TIMESTAMPS AND DO NOT MISATTRIBUTE TIMESTAMPS
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Timestamps are given as ranges, e.g. 01:13:42.520 --> 01:13:46.720. Use the EARLIER of the 2 timestamps in the range.

Return ONLY valid JSON. Ensure all strings are properly quoted and escaped, no trailing commas:
{
  "media_mentions": [
    {
      "title": "Exact Title as Mentioned",
      "category": "Book",
      "author_artist": "N/A",
      "context": "Brief context of why it was mentioned",
      "context_phrase": "The exact sentence or phrase where it was mentioned",
      "timestamp": "estimated time like 01:15:30"
    }
  ]
}

If no media is mentioned, return: {"media_mentions": []}

Prompt 9: Context Setup

You are an expert data extractor tasked with analyzing a podcast transcript. 
I will provide you with part 3 of 3 from a podcast transcript. 
I will then ask you to extract different types of information from this content in subsequent messages. Please confirm you have received and understood the transcript content.

Transcript section:
:34.800 --> 02:00:36.640] I look at time as well.
[02:00:36.640 --> 02:00:38.880] The PR that I had, it was similar.
[02:00:38.880 --> 02:00:40.800] What's your VO2 max now?
[02:00:40.800 --> 02:00:44.800] So my VO2 max now is four liters per minute.
[02:00:44.800 --> 02:00:46.720] So that's about 51, 52.
[02:00:47.040 --> 02:00:51.200] You could easily raise that if you lost three kilos, which you could probably do.
[02:00:51.200 --> 02:00:51.680] Yeah, yeah, yeah.
[02:00:51.840 --> 02:00:52.080] Yeah.
[02:00:52.080 --> 02:00:58.960] And the thing is, because I've obviously, when I was a cyclist, I was 141, 143 pounds.
[02:00:58.960 --> 02:00:59.960] So my VO2 was...
[02:00:59.280 --> 02:01:03.320] And you were probably, your VO2 was five and a half liters or something.
[02:01:03.320 --> 02:01:05.640] It was 76.7.
[02:01:05.640 --> 02:01:06.200] Let me see.
[02:00:59.760 --> 02:01:08.040] It was 4.5, I believe.
[02:01:08.040 --> 02:01:10.760] It was about 4.8, something like that.
[02:01:10.760 --> 02:01:20.440] 30 years later, I have decreased only about 0.5, 0.7, which, whoa, I'm really happy about that because I'm not training like I did.
[02:01:20.440 --> 02:01:21.800] But this is one of the parameters.
[02:01:21.800 --> 02:01:25.560] But in a decade, I haven't decreased my parameters.
[02:01:25.560 --> 02:01:37.080] So this is, to me, it's a proving point to myself at least that doing this routine, it helps to maintain that metabolic health that you had a decade ago.
[02:01:37.080 --> 02:01:41.400] Now, can you do this 10 more years and when I turn 60?
[02:01:41.400 --> 02:01:42.680] I don't know.
[02:01:42.680 --> 02:01:46.200] But what I know is that from others, I'm seeing it.
[02:01:46.200 --> 02:01:54.920] So I see typical person who just retired, as I discussed earlier, aspire to pre-retire at the age of 60 or a little bit before.
[02:01:54.920 --> 02:02:02.520] And these are like people like us who are struggling to squeeze in time, do five hours here, six hours a week here, or 10.
[02:02:02.520 --> 02:02:09.880] But then they have the whole time in the world, sleeping, they're not overworked, they can exercise.
[02:02:09.880 --> 02:02:15.480] It's unbelievable and super inspiring how much they improve in their 60s.
[02:02:15.480 --> 02:02:25.080] I've seen people in their 70s with the metabolic parameters of people active, motorally active in their 30s.
[02:02:25.080 --> 02:02:30.600] World champion in the cycling was 81, in the category of 80 to 85.
[02:02:30.600 --> 02:02:32.440] Believe me, there's a category of that.
[02:02:32.440 --> 02:02:37.240] Metabolic parameters were those of someone in their 30s, healthy, active.
[02:02:37.240 --> 02:02:39.400] So this is incredibly inspiring.
[02:02:39.400 --> 02:02:44.520] And I think that we're rewriting what's been taught to us in the books.
[02:02:44.520 --> 02:02:46.800] Was that person an elite athlete?
[02:02:44.840 --> 02:02:49.680] Were they a professional athlete in their 20s and 30s?
[02:02:50.000 --> 02:02:50.640] Never.
[02:02:50.640 --> 02:02:52.400] And this is what struck me.
[02:02:52.400 --> 02:02:59.680] He was a smoker, hypertensive, and he started cycling because he needed to change his lifestyle in his 40s.
[02:02:59.680 --> 02:03:00.880] Because that's the same question.
[02:03:00.880 --> 02:03:02.720] Like, whoa, you must have been doing this all your life.
[02:03:02.800 --> 02:03:05.680] Like, no, I started riding my bike when I was in my 40s.
[02:03:05.680 --> 02:03:06.640] I was a smoker.
[02:03:06.640 --> 02:03:07.360] I was heavy.
[02:03:07.360 --> 02:03:08.480] I was hypertensive.
[02:03:08.480 --> 02:03:09.440] Like, what?
[02:03:09.440 --> 02:03:13.200] So it's incredible 40 years later.
[02:03:13.200 --> 02:03:18.560] What I take away from that as well is the benefits and the importance of compounding.
[02:03:18.560 --> 02:03:24.320] You see, you alluded to it earlier, and I think the listener could be forgiven if they missed this point.
[02:03:24.320 --> 02:03:28.800] You can make relatively quick changes in your glycolytic efficiency.
[02:03:28.800 --> 02:03:41.120] You can take an untrained person with a VO2 max of 20 mil per gig per minute, and you could take them from 20 to 30 in a period of months with the right amount of training.
[02:03:41.120 --> 02:03:44.880] A 50% improvement in a few months.
[02:03:44.880 --> 02:03:51.520] It's very difficult to see a 50% improvement in mitochondrial function in a few months.
[02:03:51.520 --> 02:04:03.520] You've already made this point, but I just want to restate it because it's important to set expectations, and it speaks to why this level of training should be thought of in the same way that you think of accumulating wealth.
[02:04:03.520 --> 02:04:23.520] It's day in and day out, day in and day out, small compounded gains over years and years and years is why a 40-year-old overweight smoker can become a world champion at 80 because he probably never once again got out of shape in that 40 years.
[02:04:23.520 --> 02:04:24.160] Absolutely.
[02:04:24.160 --> 02:04:25.920] And this is incredibly inspiring.
[02:04:25.920 --> 02:04:42.600] When I see these people in their 60s just retired and they come to do their first test, and one year later they come back, it gives me the goosebumps because it is like, oh my gosh, I'm 64, I feel strong as when I was in my 30s.
[02:04:42.600 --> 02:04:43.720] And like, oh.
[02:04:43.960 --> 02:04:50.120] And of course, no medications, really good state of mind, which is absolutely key for longevity.
[02:04:50.120 --> 02:05:01.160] They eat in moderation, that they can have a little bit of everything, which is also, in my modest opinion, is part of the enjoyment of life, eating what you like in moderation as well.
[02:05:01.160 --> 02:05:03.160] So it's incredibly inspiring.
[02:05:03.160 --> 02:05:10.040] In a way, we're rewriting what we've been thought for years: that once you turn 40, everything is going down.
[02:05:10.040 --> 02:05:11.560] You can really, really change.
[02:05:11.560 --> 02:05:18.840] And again, you know, you own your own body and you can really take ownership of that and improve it at any age.
[02:05:18.840 --> 02:05:19.720] You mentioned drugs.
[02:05:19.720 --> 02:05:23.080] I want to talk about one drug in particular and maybe some supplements.
[02:05:23.080 --> 02:05:35.000] You and I have spoken so much about this, and myself and another person are committed to funding a study that we're going to be doing once we get through kind of the backlog of COVID issues at the university.
[02:05:35.000 --> 02:05:53.720] The question really arises around the use of metformin and whether or not there's a true impairment of mitochondrial function or whether the elevated lactate levels we see in patients taking metformin is an artifact of the drug itself, but says nothing of the mitochondrial function.
[02:05:53.720 --> 02:06:09.080] Do you have any more insight into this question that we struggle with greatly because we have some patients who take metformin who receive much benefit from taking metformin, but it makes it confusing to interpret their zone 2 data?
[02:06:09.080 --> 02:06:19.680] And it makes me ask the question: in those patients, it's maybe less relevant, but now it becomes relevant when we think about using metformin as a giro-protective agent, an agent to enhance longevity.
[02:06:20.000 --> 02:06:23.920] We need a lot of research on that, I think, to understand this better.
[02:06:23.920 --> 02:06:26.240] Definitely it seems to work in many patients.
[02:06:26.240 --> 02:06:31.840] Obviously for those ones in the pre-diabetic first stage diabetes, it's a very good medication.
[02:06:31.840 --> 02:06:34.640] It's been used for a long time with good results.
[02:06:34.640 --> 02:06:36.640] But how about the long-term results?
[02:06:36.640 --> 02:06:44.320] We know that metformin inhibits complex 1, which is key for mitochondrial function in the electron transport chain.
[02:06:44.320 --> 02:06:48.240] We don't know the long-term effects of metformin in longevity.
[02:06:48.240 --> 02:06:51.360] This is where I think that we need more information as well.
[02:06:51.360 --> 02:06:56.080] We see someone showing up with lactate of 3.5 millimoles at rest.
[02:06:56.080 --> 02:06:59.120] And the first thing I ask is, like, are you at metformin?
[02:06:59.120 --> 02:07:00.320] And Metan say yes.
[02:07:00.320 --> 02:07:01.920] And I'm sure you see the same thing, right?
[02:07:02.240 --> 02:07:04.560] Wow, it's definitely an artifact.
[02:07:04.560 --> 02:07:09.120] And why do you see at rest 3.5 millimoles or 3 millimoles of lactate?
[02:07:09.200 --> 02:07:12.720] Their fat oxidation commensurately suppressed?
[02:07:12.720 --> 02:07:21.200] Because when you metabolically test them on the cart, do you see in that individual a very, very low fat oxidation?
[02:07:21.200 --> 02:07:29.600] If not, it might suggest that that lactate level of 2 or 3 millimole is an artifact, but doesn't really speak to what's happening in the mitochondria, right?
[02:07:29.600 --> 02:07:35.520] I haven't seen people taking metformin as medication, you know, for longevity, for example, or for health.
[02:07:35.520 --> 02:07:38.720] What I see people on metformin are already clinical patients.
[02:07:38.720 --> 02:07:40.160] So of course they're low.
[02:07:40.160 --> 02:07:48.240] Yeah, so they're taking metformin in the first place because of their clinical condition, which is driven by a mitochondrial impairment or dysfunction.
[02:07:48.240 --> 02:07:53.280] It's difficult to discern, but I mean, I'm sure you have more experience of people taking metformin.
[02:07:53.600 --> 02:08:00.680] We do, but that's why this study that we're eventually going to get around to doing is going to be so important, because it will answer this question directly.
[02:08:01.160 --> 02:08:15.320] We can do it the muscle biopsies, and as you say, does it really mess up with the whole mitochondrial function, or even like the mitochondrial function overall override that inhibition of complex one and override other pathways?
[02:08:15.320 --> 02:08:17.240] I don't think we know the answer to that.
[02:08:17.240 --> 02:08:20.360] Do you have an insight into any other supplements?
[02:08:20.360 --> 02:08:28.920] No shortage of supplements that are out there that are touted as longevity boosting agents and mitochondrial health agents.
[02:08:28.920 --> 02:08:34.200] So the most talked about of all of these, I think, is the precursors to NAD.
[02:08:34.200 --> 02:08:41.800] The most common of these would be NR or NMN, both of which are pretty clear that they are precursors to NAD.
[02:08:41.800 --> 02:08:45.800] There's certainly some debate about how clinically relevant it is.
[02:08:45.800 --> 02:08:53.960] Do you have a point of view on whether or not taking a supplement that boosts NAD, at least in the plasma?
[02:08:53.960 --> 02:09:04.200] I still don't know how well it's boosting NAD in the cell, but do you have a sense of if that is beneficial to the mitochondria, both theoretically, but more importantly, experimentally?
[02:09:04.200 --> 02:09:09.960] I don't think we have the answer, but I think we need to be cautious about how we interpret this data.
[02:09:09.960 --> 02:09:17.800] It's definitely been shown multiple times that NAD levels at the cellular level or even mitochondrial level are decreased with aging.
[02:09:17.800 --> 02:09:20.440] Therefore, the whole thing, well, if it's low, let's take it.
[02:09:20.440 --> 02:09:22.600] But it's not only NAD.
[02:09:22.600 --> 02:09:29.080] If you look at so many metabolites at the cellular level and mitochondrial level, they're down-regulated with aging.
[02:09:29.080 --> 02:09:31.720] The question is: why are they down-regulated?
[02:09:31.720 --> 02:09:42.360] It's because mitochondria, per se, to start with, is down-regulated, so it doesn't need so much NAD because it cannot take it, or other supplements or other metabolites.
[02:09:42.360 --> 02:10:04.080] This is at least how I think of NAD, as we mentioned earlier, it's very important in glycolysis and redox status to maintain redox and it's very important in the visceral 3-phosphate to 2,3-biphosphoglycerate phosphate where NAD is utilized to convert glycerin 3-phosphate to 2,3-phosphoglycerate, but it's depleted.
[02:10:04.080 --> 02:10:07.760] And this is what the only thing that rescues that is lactate, right, as we mentioned.
[02:10:07.760 --> 02:10:11.520] Now, taking NAD, is that going to increase longevity?
[02:10:11.520 --> 02:10:12.560] I don't think so.
[02:10:12.560 --> 02:10:18.000] That's my opinion, because longevity is not just one supplement or two or three or four or five.
[02:10:18.000 --> 02:10:22.320] It's a compendium on an incredible amount of things that happen at the cellular level.
[02:10:22.320 --> 02:10:24.320] And I don't think that one supplement.
[02:10:24.320 --> 02:10:29.520] I remember those days where resveratrol was the thing for longevity.
[02:10:29.520 --> 02:10:31.120] And everybody was, not everybody.
[02:10:31.200 --> 02:10:33.040] A lot of people were buying resveratrol.
[02:10:33.040 --> 02:10:39.360] And there are studies with mice showing that increased 50% longevity in mice or therefore this do it in humans.
[02:10:39.360 --> 02:10:45.280] Well, as you probably know, a lot of people started taking resveratrol when they were 50 and they're dead now.
[02:10:45.280 --> 02:10:47.680] It doesn't increase longevity in humans.
[02:10:47.760 --> 02:10:51.120] The data in the mice, we can debate the merits of that.
[02:10:51.120 --> 02:10:53.040] I want to ask you about a theoretical risk, though.
[02:10:53.040 --> 02:10:54.240] You kind of alluded to it.
[02:10:54.240 --> 02:10:59.120] Isn't there a scenario under which too much NAD could be harmful?
[02:10:59.120 --> 02:11:15.360] I don't know if this study has been done, but if you took cancer patients or patients who had tumors that were undiagnosed and gave them, if you doubled their NAD levels, wouldn't you actually favor the tumor's metabolism?
[02:11:15.680 --> 02:11:19.280] Well, in fact, we have done that pilot study with mice.
[02:11:19.280 --> 02:11:24.320] The whole thing is like looking at, in my area of research in cancer, is cancer metabolism.
[02:11:24.320 --> 02:11:32.280] And we know that glycolysis is key for cancer, and NAD is absolutely indispensable to feed that glycolysis.
[02:11:32.600 --> 02:11:41.240] The question is, like, as you said, would NAD increase that glycolytic rate or glycolytic flux?
[02:11:41.240 --> 02:11:45.640] Therefore, would be favoring more cancer phenotype.
[02:11:45.640 --> 02:11:52.200] So what we did, we haven't published that, it's a pilot study, which is, we're curious about it, and we had two mice.
[02:11:52.200 --> 02:11:56.120] We have NN of eight mice, four and four.
[02:11:56.120 --> 02:12:00.040] So what we did is we transfected tumors, triple negative breast cancer.
[02:12:00.040 --> 02:12:03.080] It's very aggressive, and it grows very, very fast.
[02:12:03.080 --> 02:12:14.840] One group, we give implants water, and the other group, nicotinamida ribocyte, which is the NAD precursor, because NAD, obviously, as you know, you cannot take it, you need to take the precursor.
[02:12:14.840 --> 02:12:18.120] And we observed the tumor growth over 23 days.
[02:12:18.120 --> 02:12:24.760] After that, the IRB at the university, because you cannot have animals with high tumors.
[02:12:24.760 --> 02:12:28.360] So it was a flank tumor, and you need to harvest them.
[02:12:28.360 --> 02:12:31.880] We were measuring every five days the tumor growth.
[02:12:31.880 --> 02:12:38.120] And we saw in these animals that there was about 15% increase in tumor growth in the NAD group.
[02:12:38.120 --> 02:12:42.040] You saw that difference with only four mice in each group?
[02:12:42.040 --> 02:12:44.840] It's four and four, but all consistent.
[02:12:44.840 --> 02:12:48.120] We have statistical significancy, even with a small four.
[02:12:48.120 --> 02:12:50.360] I mean, there was no cross-results.
[02:12:50.360 --> 02:12:56.920] All the four mice, they grew cancer at a higher rate in the NAD than the control group.
[02:12:56.920 --> 02:13:00.760] Again, that's where, like, obviously, this is not like a publishable.
[02:13:01.240 --> 02:13:05.640] Is that a study you'll repeat at a sufficiently powered size?
[02:13:05.640 --> 02:13:06.600] I would love to.
[02:13:06.600 --> 02:13:08.600] This is why we just did this pilot study.
[02:13:08.600 --> 02:13:15.280] We had, because we have many mice and say, hey, let's leave it a shot and see, because there's a lot of hype of NAD, and we saw this.
[02:13:15.600 --> 02:13:29.920] Love to do it at a much higher level because my question, which might be a disruptive question, is like, what if you have a small tumor that you're unaware of, like in the pancreas or in the colon or in the lung?
[02:13:29.920 --> 02:13:38.720] Could NAD over time, day after day after day, could favor that glycolytic flux to that tumor and increase the growth?
[02:13:38.720 --> 02:13:44.880] I've never looked because it just kind of occurred to me when you had that slide up earlier, earlier and you showed the mitochondrial slide.
[02:13:44.880 --> 02:13:48.000] It occurred to me that you have that lactate escape from the tumor.
[02:13:48.000 --> 02:13:49.200] Hey, this would feed it.
[02:13:49.200 --> 02:13:52.080] But has anybody in the literature examined this question?
[02:13:52.080 --> 02:13:54.640] It seems like a very reasonable question to ask.
[02:13:54.640 --> 02:13:55.920] There are a couple of studies.
[02:13:55.920 --> 02:13:57.440] I think one's a review.
[02:13:57.440 --> 02:13:59.600] It's more at the conceptual level.
[02:13:59.600 --> 02:14:07.120] And this is what got me thinking: like, yeah, this is something that for us working in cancer metabolism, we look into this.
[02:14:07.120 --> 02:14:11.280] Obviously, one of the things that we have shown is that lactate is an oncometabolite.
[02:14:11.280 --> 02:14:20.240] Lactate, we have shown, we have a first paper, and we have like a good six, seven papers more to come, working hard for three years looking into this.
[02:14:20.240 --> 02:14:26.960] But we saw that lactate regulates genetic expression of the most important genes in breast cancer.
[02:14:26.960 --> 02:14:29.680] We're seeing the same thing now with lung cancer.
[02:14:29.680 --> 02:14:35.040] And lactate, as we keep talking about this, is that mandatory byproduct of glycolysis.
[02:14:35.040 --> 02:14:42.320] And as Warburg saw in 1923, the characteristic of cancer cells, or most cancer cells, is the high glycolytic flux.
[02:14:42.320 --> 02:14:45.800] But what struck Warburg was not the glucose itself.
[02:14:45.800 --> 02:14:47.920] What's the lactate production.
[02:14:47.920 --> 02:14:51.680] So many ways, we are showing that it's an oncometabolite.
[02:14:51.680 --> 02:14:56.480] So if you have a high glycolytic rate in a cell, you're going to produce a lot of lactate.
[02:14:56.480 --> 02:15:01.880] If you cannot clear that lactate, it's going to drive cell growth and proliferation as we're seeing.
[02:15:02.200 --> 02:15:11.000] And in fact, we're now blocking lactate production, both through genetic engineering as well as DCA, for example.
[02:15:11.000 --> 02:15:16.360] And we're seeing that cancer growth and proliferation completely stops within hours.
[02:15:16.360 --> 02:15:28.840] Now that poses an interesting dilemma, which is exercise would increase your capacity for clearing lactate in the long term, but in the short term raises lactate.
[02:15:28.840 --> 02:15:35.800] So it begs the question, in a cancer patient specifically, what's the net impact of exercise?
[02:15:35.800 --> 02:15:40.120] This is what we're working on, the hypothesis, you know, with my colleague George Brooks.
[02:15:40.120 --> 02:15:48.440] He's shown that acute response to lactate, it increases overexpressions of 600 and something genes.
[02:15:48.440 --> 02:15:49.400] I forgot right now.
[02:15:49.400 --> 02:15:54.280] All these genes are involved in cellular homeostasis and in the benefits of exercise.
[02:15:54.280 --> 02:15:59.080] We know very, very well through his work that lactate is a signaling molecule.
[02:15:59.080 --> 02:16:04.200] Now, the question is like, we know this at an acute exposure, which is exercise.
[02:16:04.200 --> 02:16:07.080] You do exercise, boo-poo-poon, you're out.
[02:16:07.080 --> 02:16:09.400] But cancer doesn't do that.
[02:16:09.400 --> 02:16:12.440] Cancer accumulates lactate and it keeps accumulating.
[02:16:12.440 --> 02:16:16.760] This is the main responsible for the tumor microenvironment, which is acidic.
[02:16:16.760 --> 02:16:25.320] And the more acidic the tumor microenvironment, the more metastatic the cancer is and the more aggressive, like the more glycolytic the tumor is.
[02:16:25.320 --> 02:16:27.240] And this is very well documented.
[02:16:27.240 --> 02:16:30.200] The more glycolytic the tumor is, the more aggressive is.
[02:16:30.200 --> 02:16:36.120] And the more lactogenic, that is more lactate, the tumor produces, the more aggressive is.
[02:16:36.120 --> 02:16:39.240] Now, why is that lactate accumulating?
[02:16:39.240 --> 02:16:40.840] That's what we need to try to find out.
[02:16:40.840 --> 02:16:43.080] But we know that that is not acute anymore.
[02:16:43.080 --> 02:16:45.000] It's chronic exposure to lactate.
[02:16:45.600 --> 02:16:47.760] Can exercise counteract that?
[02:16:47.760 --> 02:17:02.480] When we see that exercise might be beneficial for many patients, but again, going back to the right intensity, we know particles which are exosomes, they're microvesicles in the body, they're mainly responsible for metastasis.
[02:17:02.480 --> 02:17:08.080] We have seen that, and this is another publication we want to have in breast cancer cells and lung cancer cells.
[02:17:08.080 --> 02:17:14.160] We are looking at the protein content and the microRNAs of those exosomes released by these cancer cells.
[02:17:14.320 --> 02:17:16.960] It's incredible the information that they have.
[02:17:16.960 --> 02:17:27.600] If you were to genetically engineer a molecule that can inject it into a tissue and transform into cancer, you would replicate an exosome.
[02:17:27.600 --> 02:17:29.760] It has all the components needed.
[02:17:29.760 --> 02:17:34.080] On the other side, muscles also release exosomes.
[02:17:34.080 --> 02:17:43.680] And this could be one of the benefits of exercise as an organ and the crosstalk between skeletal muscle and many organs.
[02:17:43.680 --> 02:17:50.240] We know that if you have very good muscle health, your health overall, your metabolic health is going to be good.
[02:17:50.240 --> 02:17:52.640] Could you be releasing great exosomes?
[02:17:52.640 --> 02:17:57.600] They're very pro-oxidative, which counteract the glycolated phenotype of cancer.
[02:17:57.600 --> 02:18:13.440] And could those exosomes travel directly to the cancer cells and counteract that and penetrate inside the cancer cells and transform the glycolytic phenotype of the cancer cells into more oxidative phenotype and keep cancer at bay?
[02:18:13.440 --> 02:18:14.480] We don't know yet.
[02:18:14.480 --> 02:18:25.200] We're suspecting that we're scratching the surface of something that potentially could be a very interesting thing to understand better the effects of exercise as well as neurotherapeutics.
[02:18:25.200 --> 02:18:44.360] The deeper I go in the rabbit hole into all things that relate to longevity, the more convinced I am that if you're going to rank order things, if you were forced to rank order things, there's nothing that ranks above exercise as the single most potent tool or agent we have to impact longevity.
[02:18:44.360 --> 02:18:51.000] And yet, paradoxically, in the acute setting, exercise seems to do everything incorrectly.
[02:18:51.000 --> 02:18:59.320] In the very short, acute setting, if you look at it in that narrow context, exercise does not appear to be giro-protective.
[02:18:59.320 --> 02:19:08.360] But of course, when you look at the chronic impacts of exercise and what's taking place after the bouts of exercise, the data seem undeniable.
[02:19:08.360 --> 02:19:17.160] I want to kind of pivot from exercise a bit into a subset of that, which is something you published this year in long COVID patients.
[02:19:17.160 --> 02:19:37.000] So we'll link to the study so people can see it, but you demonstrated that in people with long COVID, even previously healthy people, they basically, from a mitochondrial standpoint, end up looking like people with type 2 diabetes when they're done, in terms of fat oxidation and lactate production.
[02:19:37.000 --> 02:19:45.880] So, first question for you is: what fraction of patients recovering from COVID do you believe are susceptible to that phenotype?
[02:19:45.880 --> 02:19:55.560] Everything is started by National Jewish Hospital is probably, if you know, is with Mayo Clinic competing for the top one pulmonology hospital in the country.
[02:19:55.560 --> 02:19:59.960] You have these people with long COVID who are struggling.
[02:19:59.960 --> 02:20:02.120] They go up the stairs and they can't breathe.
[02:20:02.120 --> 02:20:07.720] So, the first thing they do is they go to different doctors and they end up going to this top hospital.
[02:20:07.720 --> 02:20:11.880] So, they do a pulmonary function test and it's completely normal.
[02:20:11.880 --> 02:20:17.520] Then they, okay, the next suspicious is because COVID also affects the cardiac muscles.
[02:20:17.520 --> 02:20:18.720] Let's look at the cardiofunction.
[02:20:14.840 --> 02:20:19.760] It's completely normal.
[02:20:20.080 --> 02:20:24.320] They're very good at this hospital where they do metabolic testing.
[02:20:24.320 --> 02:20:27.440] They do a CPET testing, that's how you call it medically, right?
[02:20:27.440 --> 02:20:30.000] Physiological testing, and they even do lactate.
[02:20:30.320 --> 02:20:34.400] I've been interacting with them a few times, so they do lactate as well.
[02:20:34.400 --> 02:20:38.240] So they contacted me and said, Inigo, look, we're seeing these patients.
[02:20:38.240 --> 02:20:39.280] We have 50.
[02:20:39.280 --> 02:20:43.280] 25 of them, they had previously underlying conditions.
[02:20:43.280 --> 02:20:46.800] The other 25, they were normal people.
[02:20:46.800 --> 02:20:49.760] And in fact, most of them, they were motorly active.
[02:20:49.760 --> 02:20:52.720] Some of them, they were doing marathons, triathlons.
[02:20:52.720 --> 02:20:54.160] The average is 50.
[02:20:54.160 --> 02:20:56.640] So they're not very old either.
[02:20:56.640 --> 02:21:00.720] But their pulmonary function is completely normal and cardiac function is completely normal.
[02:21:00.720 --> 02:21:03.920] So we suspected there's some metabolic issue here.
[02:21:03.920 --> 02:21:18.880] So they sent me all the information, the raw information, and I applied the methodology that we've been discussing, looking at fat oxidation and lactate production as a surrogate for metabolic function and metabolic flexibility and mitochondrial function.
[02:21:18.880 --> 02:21:32.960] And I was shocked because they were significantly worse than people with type 2 diabetes and metabolic syndrome, which could explain why these people cannot go up the stairs and where before they were doing marathons.
[02:21:32.960 --> 02:21:35.200] Now, what are the mechanisms?
[02:21:35.200 --> 02:21:43.200] We know that viruses, multiple viruses, are known to hijack mitochondria for their own benefit, for reproduction.
[02:21:43.200 --> 02:21:45.040] Could COVID do the same thing?
[02:21:45.040 --> 02:21:50.160] We are suspecting it, and we're trying to understand that at a more at a cellular level.
[02:21:50.160 --> 02:22:01.800] Now, unfortunately, the majority of these long COVID, because as you know, there are people with long COVID syndromes that within weeks, months, they improve, they go back to normal.
[02:22:01.800 --> 02:22:08.920] But there are a handful of people that I'm assuming they're going to be growing, that after one year, they haven't improved a bit.
[02:22:08.920 --> 02:22:09.800] This is the concern.
[02:22:09.800 --> 02:22:13.480] Like, can we use exercise as a therapeutic way?
[02:22:13.480 --> 02:22:58.280] to stimulate mitochondrial function if in fact there's a mitochondrial dysfunction which is severe because if that's the situation it's going to expose these patients to multiple diseases so this is an area of concern and this isn't talked about as much as what i think people initially spoke about here which is basically myocarditis now of course we know that the risk of myocarditis is actually much higher in young males through the moderna vaccine than it's ever going to be with covid but the rate with covet is not zero it's i believe it's 2.3 cases per it's going to be a big difference i think it's 2.3 cases per 100,000 of people with COVID are getting myocarditis.
[02:22:58.280 --> 02:22:59.880] Most of those are transient.
[02:22:59.880 --> 02:23:00.840] They recover.
[02:23:00.840 --> 02:23:01.880] Not all of them are.
[02:23:01.880 --> 02:23:03.640] So a subset are not.
[02:23:03.640 --> 02:23:06.440] But this mechanism would be distinct from just myocarditis.
[02:23:06.440 --> 02:23:12.280] Myocarditis, of course, speaks to the inflammation of the cardiac muscle that would explain depressed ejection fraction.
[02:23:12.280 --> 02:23:20.200] But what you're describing is a far more diffuse problem, is a global insult on the mitochondria in the skeletal muscle, correct?
[02:23:20.520 --> 02:23:29.560] That's what we suspect from this data, which again is indirect from the indirect colorimetry in the lactate, that it points out towards mitochondrial dysfunction.
[02:23:29.560 --> 02:23:35.080] So that's what we need to do now, biopsies, to understand this setup better detail.
[02:23:35.080 --> 02:23:36.440] What the heck is going on?
[02:23:36.520 --> 02:23:39.160] Could be at the micro-perfusion level, too.
[02:23:39.160 --> 02:23:45.000] It might not be at the muscle per se, it might be at the microfusion in the blood, in the capillaries.
[02:23:45.280 --> 02:23:52.400] Meaning something like microthromboses that are preventing perfusion and raising lactate that way?
[02:23:52.400 --> 02:23:53.920] Could be, could be.
[02:23:53.920 --> 02:23:55.200] That's what we need to find out.
[02:23:55.200 --> 02:23:58.720] But we know from other viruses that they hijack mitochondria.
[02:23:58.720 --> 02:24:03.760] They interfere especially with the fission and fusion processes.
[02:24:03.760 --> 02:24:10.240] Some causes increase fission, some other causes increase fusion, some other causes increase elongation.
[02:24:10.240 --> 02:24:19.760] So we know there's a wealth of studies out there from virology showing that, yeah, many viruses and bacteria, they hijack mitochondria.
[02:24:19.760 --> 02:24:22.000] They disrupt it significantly.
[02:24:22.000 --> 02:24:26.400] But most of the times, like myocarditis, it subsides.
[02:24:26.400 --> 02:24:30.400] It's restored shortly after the symptoms are gone.
[02:24:30.400 --> 02:24:32.480] Why this virus is different?
[02:24:32.480 --> 02:24:34.480] That's what we are trying to understand.
[02:24:34.480 --> 02:24:41.200] Why people after one year, by the way, you know, most of these people, they had just a normal, mild course of COVID.
[02:24:41.200 --> 02:24:43.760] They were not hospitalized, they were not in the ICU.
[02:24:44.080 --> 02:24:53.840] Any evidence or inkling that if people go back to exercising too intensely following recovery, it could exacerbate this problem?
[02:24:53.840 --> 02:24:56.480] And do you have a sense of which strains this was?
[02:24:56.480 --> 02:25:02.240] Your work would have been predominantly alpha and not delta and obviously not Omicron, correct?
[02:25:02.240 --> 02:25:08.080] Yeah, even a mixture between the original variant and delta, so not Omicron.
[02:25:08.080 --> 02:25:15.760] So in this population, which again is presumably mostly alpha, maybe some delta, what was the distribution of male and female?
[02:25:15.760 --> 02:25:21.040] We have 35 females and 15 males, more female predominant.
[02:25:21.040 --> 02:25:23.360] Which again, maybe is too small a sample to know.
[02:25:23.360 --> 02:25:25.680] That could be more an indication of who's seeking out.
[02:25:26.080 --> 02:25:28.080] And again, we don't really know the denominator.
[02:25:28.080 --> 02:25:29.440] We don't know what this represents.
[02:25:29.480 --> 02:25:31.560] Is this one in 100,000?
[02:25:31.560 --> 02:25:35.080] It could be one in a million if this was everybody that's reporting it at the time.
[02:25:35.080 --> 02:25:38.760] Our guess is it's a rare event can last that long.
[02:25:38.760 --> 02:25:42.280] But we're talking about millions of people infected, right?
[02:25:42.360 --> 02:25:46.920] If it's one in a million, we're talking about a population that is going to need help.
[02:25:46.920 --> 02:25:50.680] I want to kind of go back to just a few other questions that we didn't get to.
[02:25:50.680 --> 02:25:53.560] So not necessarily in any thematic order.
[02:25:53.560 --> 02:26:04.280] What's the relationship between, or how predictable I should say, is the relationship between zone 2 as defined by maximum fat oxidation and VO2 max?
[02:26:04.280 --> 02:26:18.280] So if you run somebody through a CPET and you figure out that their VO2 max is at 4 liters, how predictably can you say at X percent of that, you will be at maximum fat oxidation?
[02:26:18.280 --> 02:26:27.640] There's another study that we're preparing the manuscript with 225 subjects where we look at fat oxidation, VO2, and the relationships.
[02:26:27.640 --> 02:26:35.400] Going back to the same thing, we tend, and historically, the research studies with exercise have been done based on VO2 max.
[02:26:35.400 --> 02:26:38.920] That's been the parameter to prescribe exercise.
[02:26:38.920 --> 02:26:45.560] How many times we read X amount of subjects, they were exercising for six months at 60% of VO2 max or whatever.
[02:26:45.560 --> 02:26:48.760] Now, that's another thing that I've been thinking of years.
[02:26:48.760 --> 02:27:02.120] And by the way, when they say that, do they mean 60% of the heart rate that produced VO2 max or 60% of the power that is their max power at VO2 max?
[02:27:02.120 --> 02:27:07.720] Yeah, I mean, there's so many different ways you can do this that I've always found it you have to get into the methodology very closely.
[02:27:07.720 --> 02:27:08.200] I agree.
[02:27:08.200 --> 02:27:09.320] I agree 100%.
[02:27:09.320 --> 02:27:23.600] And this is where I think we need to dial in things in better because, yeah, 60% of the power output, the intensity might be translated into power output, 60% of VO2 max, and then you translate into power output, or you translate into heart rate.
[02:27:23.600 --> 02:27:26.000] Or is it 60% of the VO2?
[02:27:26.000 --> 02:27:41.840] So for example, if somebody's four liters VO2 and then they hit that at 300 watts, would 60% be 2.4 liters, which of course is not a very helpful way outside of a laboratory to prescribe exercise to somebody?
[02:27:41.840 --> 02:27:47.760] Or would it be 180 watts, which is 60% of the 300 watts?
[02:27:47.760 --> 02:27:48.560] Yeah, exactly.
[02:27:48.560 --> 02:27:54.000] I think that normally the studies they look at where do you hit 60% of VO2 max?
[02:27:54.000 --> 02:27:55.680] How many watts is this?
[02:27:55.680 --> 02:27:57.200] Or what's your heart rate?
[02:27:57.200 --> 02:28:02.960] What's the wattage that corresponds to 60% of your max VO2?
[02:28:02.960 --> 02:28:14.720] And in our study, what we are seeing, and this is what, because I've been curious about this, because we look at the cardiorespiratory adaptations to exercise and we look at the cellular adaptations to exercise, do they really correspond?
[02:28:14.720 --> 02:28:30.480] We know very well with athletes, you can improve tremendously at the cellular level, but not at all at the cardiorespiratory level, at least based on the VO2 max, which is the representative of the cardiorespiratory adaptations to exercise.
[02:28:30.640 --> 02:28:40.960] An example that I always give when I give talks, an athlete who used to be an average professional, the VO2 max was 72.3 or something like that.
[02:28:40.960 --> 02:28:44.640] And then two years later, he is a very good professional.
[02:28:44.640 --> 02:28:49.360] The VO2 max is the same, but the lactate levels were incredibly better.
[02:28:49.480 --> 02:28:51.760] For a guy, at five watts per kilogram.
[02:28:51.760 --> 02:28:55.120] He was at five millimoles, and now it's at 1.7.
[02:28:55.120 --> 02:28:58.080] This is where the magic happened to this specific athlete.
[02:28:58.080 --> 02:28:59.640] It was at the cellular level.
[02:28:59.640 --> 02:29:01.080] We see this across the board, right?
[02:28:58.960 --> 02:29:06.040] VO2 max at the elite level does not come close to predicting performance.
[02:29:06.360 --> 02:29:07.320] Not at all.
[02:29:07.320 --> 02:29:15.400] This is why we're putting together this study with all this population of different from people with metabolic syndrome all the way from to the France athlete.
[02:29:15.400 --> 02:29:25.720] So longitudinally, we see that, yeah, sure, VO2 max corresponds with fitness in the same manner that watts corresponds with fitness.
[02:29:25.720 --> 02:29:37.880] So we can also imply that instead of doing a VO2 max to look at longevity and fitness, we can also do a power test or speed test and a treadmill because we're going to see the same thing.
[02:29:37.880 --> 02:29:41.960] Those ones who are very poorly active, they have a very poor fitness.
[02:29:41.960 --> 02:29:49.320] They're going to have a lower VO2 max, they're going to have a lower power output, they have a lower speed, lower lactic lens capacity.
[02:29:49.320 --> 02:29:55.560] VO2 max has been forever a great surrogate for fitness, cardiorespiratory fitness and longevity.
[02:29:55.560 --> 02:29:59.480] But we wanted to see if in fact it's really that specific.
[02:29:59.480 --> 02:30:08.440] So in our study, we see that people in different categories at the same VO2 max, they might be in different metabolic states.
[02:30:08.440 --> 02:30:15.640] So some people at the same VO2 max might be oxidizing a lot more fat or a lot more carbohydrates.
[02:30:15.640 --> 02:30:20.920] So that means that does not correspond to the same metabolic status.
[02:30:20.920 --> 02:30:27.560] I would have thought that most people by the time they're at VO2 max they would be disproportionately carbohydrate.
[02:30:27.560 --> 02:30:32.680] So really you're just saying how much fat oxidation still remains there is really what you're saying.
[02:30:32.680 --> 02:30:43.720] And I'm assuming a very untrained person has zero fat oxidation by the time they reach VO2 max, whereas a more highly trained person would still have some amount.
[02:30:43.720 --> 02:30:46.560] They might still be at 0.2 or 2.3 grams per minute.
[02:30:46.880 --> 02:31:01.680] Yeah, for example, we see that like a sedentary individual at 75% of the VO2 max might be around 3 millimoles, whereas a world-class athlete at the same percentage of VO2 max is about one and a half.
[02:31:01.680 --> 02:31:06.240] So metabolically, they're different, yet the VO2 max is the same.
[02:31:06.240 --> 02:31:12.240] So if we prescribe exercise based on VO2 max, we might not do things correctly.
[02:31:12.240 --> 02:31:25.520] And the same thing with carbohydrate, that at a 75% of a VO2 max, like a sedentary individual oxidizes about two grams per minute, where an elite athlete oxidizes about three grams per minute.
[02:31:25.520 --> 02:31:27.840] So that's a significant difference.
[02:31:27.840 --> 02:31:30.800] And we also see it at 50% already.
[02:31:30.800 --> 02:31:34.000] So this is why longitudinally they correspond quite well.
[02:31:34.000 --> 02:31:35.600] And same thing as fat oxidation.
[02:31:35.600 --> 02:31:47.440] Fat oxidation at a 50% of VO2 max is about 75% of CO2 max, 0.23 in a sedentary, it's 0.6 in an elite athlete.
[02:31:47.440 --> 02:31:57.280] We look at the different intensities, for example, at an athlete that can have one millimole of lactate within the same group, not just comparing group.
[02:31:57.280 --> 02:32:06.480] But we can see that someone within the very same group, whatever the category they are, the lactate and the VO2 max don't correlate.
[02:32:06.480 --> 02:32:12.080] The correlations are sometimes either 0.2 or 0.1 or 0.3.
[02:32:12.080 --> 02:32:13.680] That's the R squared you're saying.
[02:32:13.680 --> 02:32:14.480] Yes.
[02:32:14.480 --> 02:32:15.520] No correlation.
[02:32:15.520 --> 02:32:16.720] Very poor correlation.
[02:32:16.720 --> 02:32:25.360] When we talk about individual groups, when we look at specific one parameter, which is lactate, with the VO2 max, it doesn't really correspond.
[02:32:25.360 --> 02:32:40.760] So, anyways, this is what I think that we have learned a lot over these last decades, where we can really pinpoint more at the cellular level to improve metabolism more than at the cardiorespiratory function, which is very important, absolutely.
[02:32:40.760 --> 02:32:42.520] They both are going to improve.
[02:32:42.520 --> 02:32:56.200] But I think that if we want to prescribe exercise, it's going to be more specific if we look at cellular surrogates like lactate, like fat oxidation, for example, than looking at VO2 max or METs.
[02:32:56.200 --> 02:32:58.600] I mean, don't get me into there.
[02:32:58.600 --> 02:33:02.680] That's very prehistoric, in my mom's opinion.
[02:33:02.680 --> 02:33:03.960] I don't want to offend anybody, right?
[02:33:03.960 --> 02:33:11.560] But the whole MET concept used for exercise prescription, it's hard to swallow in today's times.
[02:33:11.560 --> 02:33:15.240] Yeah, I was just about to say, I mean, it served its purpose in the 1950s.
[02:33:15.240 --> 02:33:27.800] When we think about some of the muscle biopsy data, again, this term of mitochondrial function, it's such an important part of longevity because it is one of the hallmarks of aging, is declining mitochondrial function.
[02:33:27.800 --> 02:33:38.120] I usually explain to patients that the type of physiologic exercise that we're prescribing, this zone 2 exercise, is the way to measure mitochondrial function.
[02:33:38.120 --> 02:33:40.760] It's both the treatment and the test.
[02:33:40.760 --> 02:33:44.760] But I'm guessing on the cellular level, there's even more that we can talk about.
[02:33:44.760 --> 02:33:49.720] The last thing I really want to talk about today, because I know we've been going for a while, you've been generous with your time.
[02:33:49.720 --> 02:34:08.200] When you get into the omics, when you start to biopsy the muscles, when you start to look at the mitochondria in a way that we can't do it in a regular clinical setting, what else are you seeing that's differentiating the healthy from the unhealthy mitochondria or the high-functioning from the low-functioning mitochondria?
[02:34:08.200 --> 02:34:09.560] Again, I keep talking about papers.
[02:34:09.560 --> 02:34:15.200] I wouldn't publish it, but we've been working for three years quite hard, and now we cannot continue doing this.
[02:34:15.200 --> 02:34:17.600] We need to start writing the papers, right?
[02:34:14.840 --> 02:34:18.720] You need more postdocs.
[02:34:19.200 --> 02:34:22.720] You need more graduate students and postdocs to help with the writing.
[02:34:23.040 --> 02:34:29.760] But we have completed a pretty cool study, and they're writing the manuscript now looking between sedentary and active.
[02:34:29.760 --> 02:34:41.440] We know already there are a bunch of research showing at the cellular level the difference between people with type 2 diabetes or metabolic syndrome and active individuals or even sedentary.
[02:34:41.440 --> 02:34:48.640] We want to see also, or want to show that people who are sedentary, they already have problems.
[02:34:48.640 --> 02:34:54.720] And we wanted to compare them with motor active people, which should be kind of how we should be as humans.
[02:34:54.720 --> 02:34:57.360] So we looked into the mitochondria, into mitochondria.
[02:34:57.360 --> 02:35:06.640] So we looked at there's significant dysregulation at the mitochondrial level everywhere you look in the mitochondria in sedentary individuals.
[02:35:06.640 --> 02:35:15.440] You see a decreased capacity to oxidize, to burn glucose in terms of pyruvate, fatty acids, amino acids.
[02:35:15.440 --> 02:35:21.120] You see a significantly decrease in electron transport chain as well, all the complexes.
[02:35:21.120 --> 02:35:27.200] And you see also a significantly decreased capacity in the transporters of different substrates.
[02:35:27.200 --> 02:35:54.880] One thing that really caught our attention, and we think that this is something that we really want to emphasize and hopefully others in the future, is that we have identified that there is a mitochondrial pyruvid carrier, which is, as I discussed earlier, that's the transporter of pyruvate into the mitochondria, which is dysregulated already, significantly downregulated in sedentary individuals compared to active individuals.
[02:35:54.880 --> 02:35:58.800] Then we are matching it with the pyruvid flux, the oxidation itself.
[02:35:58.800 --> 02:36:04.280] So both the transporter and the flux are significantly dysregulated.
[02:36:04.280 --> 02:36:06.040] What does this mean?
[02:36:06.040 --> 02:36:11.160] That's going to shuttle pyruvate to the other way it's going to get in the cell, which is through lactate.
[02:36:11.160 --> 02:36:12.680] Exactly, exactly.
[02:36:12.680 --> 02:36:14.200] What are the implications of this?
[02:36:14.200 --> 02:36:18.680] So again, these people don't have diabetes or prediabetes.
[02:36:18.680 --> 02:36:21.400] This could be a healthy person who's not active.
[02:36:21.400 --> 02:36:31.960] And this is what, unfortunately, this has been the model in most research papers out there, comparing the unhealthy with a sedentary health individual.
[02:36:31.960 --> 02:36:40.040] I've been pushing for years that the model should not be the healthy sedentary individual because that is the intervention.
[02:36:40.040 --> 02:36:43.880] As humans, we are meant to walk or to exercise.
[02:36:43.880 --> 02:36:47.880] So we need to look at perfection to understand imperfection.
[02:36:47.880 --> 02:36:52.760] The intervention of human evolution has been becoming sedentary.
[02:36:52.760 --> 02:36:56.840] And in fact, I had a hard time to get IRB, you know, to try this study.
[02:36:56.840 --> 02:37:06.280] I have a hard time with the committee to convince them that using active people as the gold standard to understand imperfection, that's the way to go.
[02:37:06.280 --> 02:37:13.560] But anyways, what we see is that these people already, they don't have clinic, but yet they have a significant down-regulation.
[02:37:13.560 --> 02:37:14.680] They don't have clinical signs.
[02:37:14.920 --> 02:37:16.040] Clinical symptoms, sorry.
[02:37:16.040 --> 02:37:17.240] They don't have clinical symptoms.
[02:37:17.240 --> 02:37:19.400] They're the healthy sedentary individuals.
[02:37:19.400 --> 02:37:25.160] They don't have insulin resistance and they don't have down-regulation of gluthor transporters.
[02:37:25.160 --> 02:37:26.920] Even hyperinsulinemia?
[02:37:26.920 --> 02:37:31.400] Are they hyperinsulinemic when challenged with the glucose tolerance test?
[02:37:31.720 --> 02:37:34.200] These people, they have no symptoms.
[02:37:34.200 --> 02:37:38.600] They haven't reported any glucose trollearance tests, normal people.
[02:37:38.600 --> 02:37:50.880] And then they have a significant disruption in this mitochondrial pyruvic carrier, which might mean that the first door that might be jammed is that entrance of pyruvate inside mitochondria.
[02:37:51.120 --> 02:38:03.040] Most of the research in diabetes has done more at the peripheral level, if you will, glucose levels, more at the surface levels of the cell, the glute for the insulin resistance, the pancreas release of insulin, better cells, etc.
[02:38:03.360 --> 02:38:08.000] But what's the fate of glucose once it enters the cell?
[02:38:08.000 --> 02:38:09.440] And this is what we're looking to this.
[02:38:09.440 --> 02:38:12.800] So, and the fate is pyruvate, but what's the fate of pyruvate?
[02:38:12.800 --> 02:38:18.160] As you said very well, does it enter the mitochondria or is shuttled to or reduced to lactate?
[02:38:18.160 --> 02:38:24.240] So, I think that this is important to see because it could be a marker down the road.
[02:38:24.240 --> 02:38:31.040] Because, again, these people don't have clinical symptoms yet, they have a significant dysregulation in their glucose metabolism.
[02:38:31.040 --> 02:38:37.440] So, could this be 10-15 years ahead of clinical symptoms and insulin resistance?
[02:38:37.440 --> 02:38:43.680] This is more reasonable to consider sedentary individuals to see, hey, they have a metabolic dysregulation already.
[02:38:43.680 --> 02:38:46.480] Same thing we're doing at the fat oxidation level.
[02:38:46.480 --> 02:38:52.400] The CPT1 and CPT2, the transporters of fat, they're significantly downregulated as well.
[02:38:52.400 --> 02:38:59.120] So, that means they're not going to be able to transport fat very well, which also matches to the fat oxidation itself.
[02:38:59.120 --> 02:39:03.120] When we inject fatty acids into the mitochondria, they don't oxidize it well.
[02:39:03.120 --> 02:39:04.960] So, they all match as well.
[02:39:04.960 --> 02:39:13.920] So, they have a dysregulation already that is significant compared to motor active individuals at the glucose metabolism and fat metabolism.
[02:39:13.920 --> 02:39:26.400] Then, we see that many of these people, I mean, who have diabetes or metabolic syndrome, they have what's called intramuscular triglycerides, the fat droplet, and it's adjusted right by the mitochondria.
[02:39:26.400 --> 02:39:45.240] In elite athletes, it's also there, that fat droplet, but it's very active because about 25 to 30 percent of the fat oxidation comes from that fat droplet adjusting to mitochondria, which it could probably is an evolutionary mechanism to not rely on the adipush tissue, which might take time and have something right away there.
[02:39:45.240 --> 02:39:54.760] So, when you say it's metabolically active, the difference between the intramuscular fat of the athlete and the intramuscular fat of the person with type 2 diabetes, is it the flux then?
[02:39:54.760 --> 02:39:58.200] In the person with type 2 diabetes, it's a static source of fat.
[02:39:58.200 --> 02:40:02.760] In the athlete, it's constantly turning over and being oxidized and replenished.
[02:40:02.920 --> 02:40:06.920] Exactly, whereas in this population, it continues to grow.
[02:40:06.920 --> 02:40:13.480] My colleague Brian Bergman from the university is working a lot into the content of what's inside these fat droplets.
[02:40:13.480 --> 02:40:19.000] But one thing that we know is like they're very high in ceramides and diglycerides.
[02:40:19.000 --> 02:40:22.920] And especially ceramides are key in the atherosclerotic process.
[02:40:22.920 --> 02:40:26.520] Atherosclerosis, it's a hallmark of cardiovascular disease.
[02:40:26.520 --> 02:40:28.840] Ceramides are key for this process.
[02:40:28.840 --> 02:40:33.400] Historically, it's been thought and it's been shown that ceramides come from the liver, they're released.
[02:40:33.400 --> 02:40:37.560] But we're seeing that these intramuscular triglycerides are high in ceramides.
[02:40:37.560 --> 02:40:43.400] So, could this be a connection between also cardiovascular disease and type 2 diabetes?
[02:40:43.400 --> 02:40:47.160] In the high-turnover, high-flux one, you're not accumulating them as much?
[02:40:47.480 --> 02:40:48.040] Yes.
[02:40:48.040 --> 02:40:53.080] People who end up having type 2 diabetes, they accumulate fat droplets.
[02:40:53.080 --> 02:40:55.240] Athletes as well, that's the athlete's paradox.
[02:40:55.240 --> 02:40:58.680] But athletes, as you said, they keep turning around and it's very active.
[02:40:58.680 --> 02:41:02.760] Whereas people with type 2 diabetes or obesity, it keeps growing.
[02:41:02.760 --> 02:41:09.400] It releases pre-inflammatory mediators, and it also is high in ceramides, which are key in atherosclerosis.
[02:41:09.400 --> 02:41:16.640] So, this is what we're trying to establish the connections between Tech 2 diabetes and cardiovascular disease at the mitochondrial level as a nexus.
[02:41:16.960 --> 02:41:25.360] Because we know that about 80% of people with type 2 diabetes, they also have cardiovascular disease and vice versa, which is what we call cardiometabolic disease.
[02:41:25.360 --> 02:41:29.280] So, could the nexus of all that a mitochondrial impairment?
[02:41:29.280 --> 02:41:30.720] That's what we believe.
[02:41:30.720 --> 02:41:40.080] Well, what I take away from this is we're probably going to have to do a third podcast in a couple of years because there's going to be a lot of data that's going to be published then that isn't published now.
[02:41:40.080 --> 02:41:43.120] There's going to be a lot more questions that we're going to have answered.
[02:41:43.120 --> 02:41:52.400] Again, I'm still really yearning to understand the effect of metformin in terms of pure mitochondrial function and performance in a trained individual.
[02:41:52.400 --> 02:41:56.000] So, as always, I can't thank you enough for your generosity of insight.
[02:41:56.000 --> 02:42:01.120] And look forward to talking tomorrow when we have a call about some other nerdy stuff we're going to get into.
[02:42:01.120 --> 02:42:09.280] But thank you so much, Inigo, and also congratulations on the remarkable success of your team and Pogacher, who's an amazing cyclist to watch.
[02:42:09.280 --> 02:42:12.560] He's got everybody very excited about the Tour de France again.
[02:42:12.560 --> 02:42:14.880] Well, thank you very much, Peter, all the listeners.
[02:42:14.880 --> 02:42:16.720] I really appreciate what you do.
[02:42:16.720 --> 02:42:21.200] The first time I met you, Kaz, we were two and a half hours talking about mitochondria.
[02:42:21.200 --> 02:42:23.360] And at first I thought, like, this guy's crazy.
[02:42:23.360 --> 02:42:29.280] There's nobody out there who's going to be interested in listening to two and a half hours about mitochondria and metabolic health.
[02:42:29.280 --> 02:42:32.000] You showed me, yeah, the concepts are out there.
[02:42:32.000 --> 02:42:37.360] And I was in a moment where I was, not many people seemed interested in this.
[02:42:37.360 --> 02:42:41.040] And you were already an inspiration for me to continue doing this.
[02:42:41.040 --> 02:42:46.480] And the remarkable work that you're doing to educate people and inspire people.
[02:42:46.480 --> 02:42:47.840] It's transformational.
[02:42:47.840 --> 02:42:49.640] So I really appreciate the invitation.
[02:42:49.640 --> 02:42:50.640] It's such an honor.
[02:42:50.640 --> 02:42:52.160] Thanks for being with us today.
[02:42:52.160 --> 02:42:53.680] Thank you very much.
[02:42:53.680 --> 02:42:56.560] Thank you for listening to this week's episode of The Drive.
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Prompt 10: Key Takeaways

Now please extract the key takeaways from the transcript content I provided.

Extract the most important key takeaways from this part of the conversation. Use a single sentence statement (the key takeaway) rather than milquetoast descriptions like "the hosts discuss...". 

Limit the key takeaways to a maximum of 3. The key takeaways should be insightful and knowledge-additive. 

IMPORTANT: Return ONLY valid JSON, no explanations or markdown. Ensure:
- All strings are properly quoted and escaped
- No trailing commas
- All braces and brackets are balanced
Format: {"key_takeaways": ["takeaway 1", "takeaway 2"]}

Prompt 11: Segments

Now identify 2-4 distinct topical segments from this part of the conversation.

For each segment, identify:
- Descriptive title (3-6 words)  
- START timestamp when this topic begins (HH:MM:SS format)
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Most important Key takeaway from that segment. Key takeaway must be specific and knowledge-additive.
- Brief summary of the discussion

IMPORTANT: The timestamp should mark when the topic/segment STARTS, not a range. Look for topic transitions and conversation shifts.

Return ONLY valid JSON. Ensure all strings are properly quoted, no trailing commas:
{
  "segments": [
    {
      "segment_title": "Topic Discussion", 
      "timestamp": "01:15:30",
      "key_takeaway": "main point from this segment",
      "segment_summary": "brief description of what was discussed"
    }
  ]
}

Timestamp format: HH:MM:SS (e.g., 00:05:30, 01:22:45) marking the START of each segment.

Prompt 12: Media Mentions

Now scan the transcript content I provided for ACTUAL mentions of specific media titles:

Find explicit mentions of:
- Books (with specific titles)
- Movies (with specific titles)  
- TV Shows (with specific titles)
- Music/Songs (with specific titles)

DO NOT include:
- Websites, URLs, or web services
- Other podcasts or podcast names

IMPORTANT: 
- Only include items explicitly mentioned by name. Do not invent titles.
- Valid categories are: "Book", "Movie", "TV Show", "Music"
- Include the exact phrase where each item was mentioned
- Find the nearest proximate timestamp where it appears in the conversation
- THE TIMESTAMP OF THE MEDIA MENTION IS IMPORTANT - DO NOT INVENT TIMESTAMPS AND DO NOT MISATTRIBUTE TIMESTAMPS
- Double check that the timestamp is accurate - a timestamp will NEVER be greater than the total length of the audio
- Timestamps are given as ranges, e.g. 01:13:42.520 --> 01:13:46.720. Use the EARLIER of the 2 timestamps in the range.

Return ONLY valid JSON. Ensure all strings are properly quoted and escaped, no trailing commas:
{
  "media_mentions": [
    {
      "title": "Exact Title as Mentioned",
      "category": "Book",
      "author_artist": "N/A",
      "context": "Brief context of why it was mentioned",
      "context_phrase": "The exact sentence or phrase where it was mentioned",
      "timestamp": "estimated time like 01:15:30"
    }
  ]
}

If no media is mentioned, return: {"media_mentions": []}

Full Transcript

[00:00:10.960 --> 00:00:13.760] Hey everyone, welcome to the Drive podcast.
[00:00:13.760 --> 00:00:15.600] I'm your host, Peter Attia.
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[00:01:04.480 --> 00:01:07.040] Welcome to a special episode of The Drive.
[00:01:07.040 --> 00:01:21.360] For this week's episode, we want to rebroadcast one of our most popular episodes, which is the second conversation I had with Inigo San Milan in March of 2022, which was a deep dive into all things pertaining to Zone 2 exercise.
[00:01:21.360 --> 00:01:28.240] Inigo is an internationally renowned applied physiologist and assistant professor at the University of Colorado School of Medicine.
[00:01:28.240 --> 00:01:34.320] His research focuses on exercise-related metabolism, metabolic health, diabetes, and cancer.
[00:01:34.320 --> 00:01:50.720] In this conversation, we talk about Inigo's work with two-time Tour de France champion Tadi Pogacher, looking at the type of training that he does and what we can learn about training and cardiovascular physiology from the world's most elite performers.
[00:01:50.720 --> 00:01:58.480] We talk about lactate and fat oxidation as it relates to cardiorespiratory training and how carbohydrates in our food can affect lactate.
[00:01:58.480 --> 00:02:04.440] And we talk about what different lactate levels mean in the context of healthy versus unhealthy people.
[00:02:04.440 --> 00:02:19.400] We get into very specific detail around zone two exercise, how to measure it, how to know you're in zone two, what to do if you don't want to use a lactate meter, how you can structure your training around it, how to think about duration, timing, and frequency.
[00:02:19.400 --> 00:02:31.800] Talk about the importance and the compounding rate of improvement that can happen with zone two training, VO2 max training, high-intensity training, and how different exercises of this nature can improve your lifespan and health span.
[00:02:31.800 --> 00:02:47.480] This is a rather tour de force episode when it comes to zone two training, and obviously it's a term that many of you are very familiar with, but it's really great to go back to the source where we started talking about this with Indigo several years ago and then followed up again in 2022.
[00:02:47.480 --> 00:02:53.080] So without further delay, please enjoy or potentially re-enjoy my conversation with Inugo Sunala.
[00:02:57.880 --> 00:03:01.000] Indigo, it is so great to be sitting down with you again.
[00:03:01.000 --> 00:03:07.960] Last time, of course, we did this in person, but these days I've become too lazy to travel around and do podcasts in person, so do it by video.
[00:03:07.960 --> 00:03:13.720] But that said, I really hope you can get out here to Austin so we can train together and do some cool ex-fiz.
[00:03:13.720 --> 00:03:18.120] And also, I need to get out there to sort of do some of the ex-fiz stuff we've talked about.
[00:03:18.120 --> 00:03:24.680] But I almost don't know where to begin because there's so much stuff we talked about last time that we want to double-click on this time.
[00:03:24.680 --> 00:03:31.880] There's so much that has changed in the interval from when we spoke, gosh, probably two years ago, a little over two years ago.
[00:03:31.880 --> 00:03:39.000] I thought one place we could pick it up, something we didn't really talk about last time, was your work with Taddy Pogacho.
[00:03:39.000 --> 00:03:42.760] Because of course, I don't think anybody knew who he was two and a half years ago.
[00:03:42.760 --> 00:04:06.640] And of course, now he is, I don't know, I mean, I think it's safe to say he has the potential to potentially go down as the greatest Tour de France cyclist of all time, given how young he is, not to put that expectation out there, but to win the tour at such a young age, to not just win the yellow jersey, but the white jersey, polka dot jersey, repeatedly, he looks like something of a different species almost.
[00:04:06.640 --> 00:04:12.400] And I say that not in the way that people typically say those things of cyclists in a way that's suspicious of anything.
[00:04:12.400 --> 00:04:27.040] So for the listeners who are not familiar with the Tour de France, not familiar with your work with the UAE team and your work with Taddy Pogachar, maybe give folks a little bit of an update as to what you've been doing in professional cycling over the past couple of years.
[00:04:27.040 --> 00:04:29.120] First of all, thank you very much for having me here.
[00:04:29.120 --> 00:04:29.920] It's an honor.
[00:04:30.080 --> 00:04:33.440] Really excited for this, and I appreciate the opportunity.
[00:04:33.440 --> 00:04:37.280] I had a lot of fun last time, hopefully I have fun again.
[00:04:37.280 --> 00:04:44.320] My work with Tadé started in late 2018 when he signed up for the team.
[00:04:44.320 --> 00:04:50.720] Yeah, I was introduced to him by our CEO, Giannetti, and our general manager, Machine.
[00:04:50.880 --> 00:04:53.120] Told me, hey, start working with this guy.
[00:04:53.120 --> 00:04:55.360] And he was, what, at the time, 19, maybe?
[00:04:55.680 --> 00:04:56.640] Yeah, 19.
[00:04:56.640 --> 00:04:58.160] He was 19 at the time.
[00:04:58.240 --> 00:04:59.520] Just turned 19.
[00:04:59.520 --> 00:05:02.480] In fact, I started to work with him right away.
[00:05:02.480 --> 00:05:04.400] I realized he had potential.
[00:05:04.640 --> 00:05:10.320] And I think like a couple months earlier, no, or later, I forgot when we had that podcast.
[00:05:10.320 --> 00:05:12.320] I already told you about him.
[00:05:12.400 --> 00:05:15.600] Told you, like, we have a guy that has good potential.
[00:05:15.600 --> 00:05:16.640] That was Tade.
[00:05:16.800 --> 00:05:20.880] To put it in perspective, I mean, has good potential is one thing.
[00:05:20.880 --> 00:05:29.920] To then go and do what he did would make that statement the understatement of the century for folks who maybe don't follow cycling as closely, right?
[00:05:30.440 --> 00:05:32.760] Yeah, yeah, I mean, I try to be cautious.
[00:05:32.760 --> 00:05:37.800] I don't usually say that out loud of people who have good potential.
[00:05:37.800 --> 00:05:39.800] We talked about it over dinner that night.
[00:05:39.800 --> 00:05:40.520] Yeah, yeah.
[00:05:40.520 --> 00:05:45.800] When I say someone who has good potential, I don't usually say that lightly of anybody.
[00:05:45.800 --> 00:06:01.240] What did you see in him in 2018, 2019, that led you to believe that even amongst that class, because professional cyclists from a physiologic standpoint are all very special individuals.
[00:06:01.240 --> 00:06:06.520] What did you see in him that made you think he has potential in your understated way?
[00:06:06.680 --> 00:06:10.440] The physiological testing, we started doing right off the bat.
[00:06:10.440 --> 00:06:19.240] I saw like amazing capabilities, ability to clear lactate and to put out great amount of power for long periods of time.
[00:06:19.240 --> 00:06:28.360] So when you say that, was it specifically his FTP that impressed you, or was it his, as you said, lactate clearance?
[00:06:28.360 --> 00:06:36.520] Was it shorter bursts of power that were higher than FTP, but the speed with which he could do or the successive repeats that he could do?
[00:06:36.520 --> 00:06:41.320] I mean, tell me some of the testing you were putting cyclists through and how he stood out.
[00:06:41.320 --> 00:06:44.040] It's kind of like a similar test that I did to you.
[00:06:44.040 --> 00:06:51.480] And this is where I saw that at a given power output, his lactate levels, blood lactate levels, were extremely low.
[00:06:51.480 --> 00:07:05.000] And since I've been doing this specific protocol for 20 years with professional athletes, professional cyclists in this specific case, that's where I have my cheat sheet where I know I can categorize where people are.
[00:07:05.000 --> 00:07:12.840] He was like, whoa, way on the other side, way above almost everybody that I had tested or around the same category.
[00:07:12.840 --> 00:07:20.960] And for that age, that's what I saw, like, whoa, first of all, he is at a different category and he's first year pro, pretty much a junior.
[00:07:21.280 --> 00:07:28.960] And then that's where like I could see he could sustain a high amount of power with very low lactate compared to the rest.
[00:07:28.960 --> 00:07:34.000] And then throughout the trainings, we used training pics, the software, looking at training picks.
[00:07:34.000 --> 00:07:47.600] That's where I would see his different abilities to sustain a given power output for the whole day or for a specific effort, a glycolytic effort, and a client would see the power output that he would be putting out.
[00:07:47.600 --> 00:07:59.280] And so all together, then I saw his trainability, how easy he would get the concepts, how easy he would be comfortable with the training, how easy he would recover.
[00:07:59.280 --> 00:08:00.240] I like the feedback.
[00:08:00.240 --> 00:08:05.360] I talked to him once, twice a day over WhatsApp to the feedback.
[00:08:05.360 --> 00:08:10.400] I know very well when a hard week is or what a hard week is.
[00:08:10.400 --> 00:08:13.520] And when you see this kid telling you, I'm pretty good.
[00:08:13.520 --> 00:08:15.040] I'm recovering very well.
[00:08:15.040 --> 00:08:19.920] When other ones are telling you, woof, I had to take it a little bit easier today because I couldn't do this effort.
[00:08:19.920 --> 00:08:22.080] And we're talking about high-level pros.
[00:08:22.080 --> 00:08:24.960] And you see this kid telling you, like, yeah, no problem.
[00:08:24.960 --> 00:08:26.960] That's where you start putting together things.
[00:08:26.960 --> 00:08:40.480] And also, around the same time with my two colleagues at the university, Angelo Dalessandra and Travis Nenkov, we started to develop a platform for metabolomics where we can look at hundreds, if not thousands, of metabolites in the human body.
[00:08:40.480 --> 00:08:45.440] And we did it the tour of California in 2019, which was like around April.
[00:08:45.440 --> 00:08:47.280] That's where he won it.
[00:08:47.280 --> 00:08:49.600] And that's where when we analyze all his metabolites.
[00:08:49.600 --> 00:08:53.760] And we did already at the training camp in January 2018.
[00:08:53.760 --> 00:09:02.600] And we already saw, wow, this guy has different metabolites at the glycolytic level, exceeded level, recovery level.
[00:08:59.920 --> 00:09:05.000] And we confirmed that at the tour of California.
[00:09:05.320 --> 00:09:09.400] And this is where, putting all together, yeah, this guy is different.
[00:09:09.720 --> 00:09:24.280] So, going back to what you said about lactate, I assume that one of the data points that is most telling of a cyclist is if you plot on the x-axis watts per kilo and on the y-axis lactate production.
[00:09:24.280 --> 00:09:31.160] I mean, that might be one of the most telling graphs you could generate to predict success in the tour, correct?
[00:09:31.160 --> 00:09:31.880] Absolutely.
[00:09:31.880 --> 00:09:38.680] You see a normal tempo climbing in the tour de France, tempo A, that is the whole Peloton going up.
[00:09:38.680 --> 00:09:39.960] It's got to be four.
[00:09:39.960 --> 00:09:40.280] Yeah, okay.
[00:09:40.520 --> 00:09:42.600] As if I was about to say, wow, yeah, I was going to say four and a half.
[00:09:42.600 --> 00:09:46.840] Okay, so wow, the whole Peloton is going up at five watts per kilo.
[00:09:46.840 --> 00:09:48.200] Yeah, something like that.
[00:09:48.200 --> 00:09:53.560] And that's what you see, like someone at that intensity might have already six millimoles.
[00:09:53.560 --> 00:09:59.080] So you can tell it's going to be very tasking, and others might have one resting levels.
[00:09:59.080 --> 00:10:01.960] It really, really predicts performance.
[00:10:01.960 --> 00:10:08.600] In fact, when we go to these training camps, I'm going to go next week for the first training camp of the year with the team.
[00:10:08.600 --> 00:10:13.960] We do this physiological testing and I do this protocol and I get this data.
[00:10:13.960 --> 00:10:18.840] So right away I tell the team managers, this guy is way above the rest.
[00:10:18.840 --> 00:10:22.440] These three guys are really, really good immediately behind it.
[00:10:22.440 --> 00:10:24.920] These two guys are at the third level.
[00:10:24.920 --> 00:10:29.240] And then we have all these guys that they're like really, really bad form.
[00:10:29.240 --> 00:10:30.680] And it pretty much works.
[00:10:30.680 --> 00:10:35.960] Then we do different racing simulation and they tell you, boom, right away, this is how it is.
[00:10:35.960 --> 00:10:37.480] So, this is why it's very predictive.
[00:10:37.480 --> 00:10:45.040] And the same thing, too, moving into the season, you see, okay, all these three guys are going to be at a very good level when we start the season.
[00:10:44.120 --> 00:10:50.960] This guy, who we thought that he was going to be a very good level, he's not there at all when the season starts.
[00:10:51.280 --> 00:10:55.040] You see that it reflects very well what's going to happen.
[00:10:55.040 --> 00:10:57.120] Yeah, that's one of the things about cycling that I really love.
[00:10:57.120 --> 00:11:03.040] I mean, I don't know if you saw, but I interviewed Lance Armstrong back in, oh gosh, probably back in June, or maybe it came out in September.
[00:11:03.040 --> 00:11:16.160] But one of the things that we talked about was both on and off EPO or blood transfusions, you sort of knew where you stood before the race based on your FTP in watts per kilo.
[00:11:16.160 --> 00:11:22.480] He talked about when he was off EPO, he could hold 450 watts for 30 minutes.
[00:11:22.480 --> 00:11:28.000] So that would be slightly above FTP at 70, I think he was 70 to 75 kilos.
[00:11:28.000 --> 00:11:30.480] But it was in the ballpark of six watts per kilo.
[00:11:30.480 --> 00:11:35.280] And then, of course, on EPO, it was 7.1 watts per kilo, a huge difference.
[00:11:35.280 --> 00:11:41.280] But you knew that number going in, and you sort of knew only the GC contenders could do that.
[00:11:41.280 --> 00:11:54.080] I think that's the thing that a lot of people don't understand about cycling, which is there's relatively few moments in the tour when you need to sustain that level, but they always occur at the most important strategic times.
[00:11:54.080 --> 00:11:58.400] And that's sort of where the race is won and lost, because the race is won and lost by minutes.
[00:11:58.400 --> 00:12:00.400] How many hours does it take to complete the tour?
[00:12:00.400 --> 00:12:01.760] 100 hours or something?
[00:12:01.760 --> 00:12:04.560] On average, about four and a half, five hours a day.
[00:12:04.560 --> 00:12:05.760] Yeah, so something like that.
[00:12:05.760 --> 00:12:06.240] Yeah.
[00:12:06.240 --> 00:12:15.520] It's about a hundred-hour race, and yet the difference between the first, second, third guy will be, in some cases, seconds, in some cases, a few minutes.
[00:12:15.520 --> 00:12:19.600] For someone to win by five minutes is considered a blowout.
[00:12:19.600 --> 00:12:23.680] And so, what it really tells you is that there are a handful of minutes in that race.
[00:12:23.680 --> 00:12:29.320] There are a handful of climbs and time trials that set apart the winners from everybody else.
[00:12:28.960 --> 00:12:33.320] And to me, that's one of the beautiful things about cycling physiology: you have these metrics.
[00:12:33.480 --> 00:12:39.640] And now, I think it's not just FTP, it's watts per kilo with lactate production.
[00:12:39.640 --> 00:12:44.680] So, it gets even more into the critical physiology of recovery.
[00:12:44.680 --> 00:12:49.640] And in fact, we use these metrics a lot for the competition, and we did it this year at the Tour de France.
[00:12:49.640 --> 00:12:59.240] So, knowing the power output that he could sustain for, as you very well said, for specific times and climbs, we knew his capabilities.
[00:12:59.240 --> 00:13:05.080] And one of the things that we knew was that in the Alps, he was at a very, very high level.
[00:13:05.080 --> 00:13:10.600] That famous stage where he broke away and called the Rome 35 kilometers to the finish line.
[00:13:10.600 --> 00:13:20.280] We were seeing not only his data, but we see by knowing our writers' data, you can also guess the other writers' data too.
[00:13:20.280 --> 00:13:21.960] It's not rocket science.
[00:13:21.960 --> 00:13:27.400] So, we knew that he was at a very high level and discussing the ticks, you know, because it's part of the thing that we do.
[00:13:27.400 --> 00:13:34.520] We observe the data that we have, the data that we think the other ones have, and we structure a strategy for the next day.
[00:13:34.520 --> 00:13:37.080] And hey, does he have the legs to attack?
[00:13:37.080 --> 00:13:39.640] Should be holding back, or what should we do?
[00:13:39.640 --> 00:13:49.400] And clearly, it was like, well, tomorrow, if he attacks 35 kilometers to the finish line, he's going to get there with three minutes because the other guys, they're not at that level.
[00:13:49.400 --> 00:13:52.680] Why wait to the end of the tour when we can try to solve the situation?
[00:13:52.680 --> 00:13:55.000] So, we knew his capabilities very well.
[00:13:55.000 --> 00:13:59.560] And discussing this with him and the manager, yeah, that was the strategy.
[00:13:59.560 --> 00:14:05.800] First, test the legs, and like if he had, in fact, good legs, boom, go for it, and that's exactly what he did.
[00:14:06.040 --> 00:14:18.320] How much of that are you going to determine after a night of sleep, where you say, we're going to look at his resting lactate first thing in the morning, we're going to look at his heart rate overnight, we're going to look at his heart rate variability overnight.
[00:14:18.640 --> 00:14:29.200] So, in addition to the subjective, for example, how he felt during the previous day's attacks, coupled with some of that objective data, does that partially formulate the strategy also?
[00:14:29.200 --> 00:14:40.880] Or is it mostly based on historical data from training where you say, I know that when he's at this many watts per kilo for this many minutes, he has the capacity to recover?
[00:14:41.200 --> 00:14:45.680] The latter, where we have all that physiological data and the trends.
[00:14:45.680 --> 00:14:51.280] What we see at this level, these guys, they're so good at knowing their feelings.
[00:14:51.280 --> 00:14:54.160] Sometimes it's just kind of how they wake up.
[00:14:54.160 --> 00:14:55.760] You know his capabilities.
[00:14:55.760 --> 00:15:01.280] So if he wakes up fresh, he's like a baby, boom, then you're ready.
[00:15:01.280 --> 00:15:08.000] And sometimes, yeah, it's just we try not to focus on many other metrics that they, because we have already things.
[00:15:08.000 --> 00:15:13.360] And sometimes heart revility might not be very precise.
[00:15:13.360 --> 00:15:30.480] And we don't want to put some ideas in the head that, and in fact, speaking with him, you know, and I'm not going to mention any brand or anything, but looking at heart rate variability some days, you say, like, look, today you told me that I was fatigued, that algorithm, and I went out there and beat my record and the clients.
[00:15:30.640 --> 00:15:31.920] Obviously, I'm not fatigued.
[00:15:32.080 --> 00:15:36.240] Third days, it tells you you're in top form, and I feel a little more fatigued.
[00:15:36.240 --> 00:15:40.080] So, this is what these algorithms we need to be careful sometimes.
[00:15:40.080 --> 00:15:47.120] And might work with maybe general population, but with this type of athletes, at this level, I really feel that it's better.
[00:15:47.120 --> 00:15:50.320] Once you have all the work done, you know their capabilities.
[00:15:50.320 --> 00:15:51.920] Like, are you ready to go?
[00:15:51.920 --> 00:15:54.960] It's like a top performer at a theater.
[00:15:54.960 --> 00:15:56.720] You have worked very hard.
[00:15:56.720 --> 00:15:58.880] Now it's up to, like, are you ready to go?
[00:15:58.880 --> 00:16:00.520] Do you have a good night's lead?
[00:15:59.920 --> 00:16:01.560] Are you ready to perform?
[00:16:01.880 --> 00:16:05.000] And a good performer will say, yes, I'm ready to go.
[00:16:05.000 --> 00:16:06.440] I agree with you completely.
[00:16:06.440 --> 00:16:14.760] Even for me, and I'm not a top-level anything, I have not found the predictors of readiness.
[00:16:14.760 --> 00:16:18.600] to be very accurate or to necessarily reflect how well I'm going to perform.
[00:16:18.600 --> 00:16:21.240] I've had amazing performances.
[00:16:21.240 --> 00:16:22.840] By performances, I mean workouts.
[00:16:22.840 --> 00:16:24.680] That's the only metric I'm performing in.
[00:16:24.680 --> 00:16:30.520] I've had amazing workouts when my prediction was that it would not be good.
[00:16:30.520 --> 00:16:35.720] And I've also had the predictions saying you're on top of the world and I've not performed well.
[00:16:35.720 --> 00:16:42.440] So I wish I could say with more clarity what the frequency of those deviations or discordances are.
[00:16:42.440 --> 00:16:47.800] But I can agree that putting the wrong idea in somebody's head when there's nothing you can do about it.
[00:16:47.800 --> 00:16:48.840] I mean, that's the other thing, too.
[00:16:48.840 --> 00:16:55.640] It's sort of like, at best, if it was perfectly accurate, it would be great because you could say, look, today maybe we shouldn't attack.
[00:16:55.640 --> 00:16:57.640] Today it's damage control day.
[00:16:57.640 --> 00:17:21.960] One of the things I want to ask you about here, and you've spoken about this publicly, so it might be that you're just going to restate the views that you've shared publicly, but I've always felt that now that we have such great transparency from that high octane era of the maximum probably cheating in cycling, which in my view is kind of that two decades of the 90s and 2000s.
[00:17:21.960 --> 00:17:30.120] We pretty much know now what kind of numbers cyclists were putting out when they were being assisted by EPO and blood transfusions.
[00:17:30.120 --> 00:17:38.040] And we sort of know that the best of the best were able to put out somewhere between about 6.8 and 7.1 watts per kilo at FTP.
[00:17:38.040 --> 00:17:41.480] We also know today that cyclists are not doing that.
[00:17:41.480 --> 00:17:44.600] Those numbers are nowhere to be found in the Peloton.
[00:17:44.600 --> 00:17:48.400] Now, that's information you and I share confidentially.
[00:17:48.400 --> 00:17:50.880] That's not public knowledge.
[00:17:50.880 --> 00:17:59.760] But I know it, you know it, and anyone coaching people at that level know that nobody's putting out 7.1 watts per kilo.
[00:17:59.760 --> 00:18:02.960] You don't need to be at 7.1 watts per kilo to win the tour today.
[00:18:02.960 --> 00:18:06.720] You could probably win the tour today at 6.1 watts per kilo.
[00:18:06.720 --> 00:18:19.680] Do you think that making that data public would put to rest a lot of the criticisms that say they've just found new ways to cheat, but it's still basically a dirty sport?
[00:18:19.680 --> 00:18:28.800] Because when you look at the data objectively, it would be very hard to say that today based on what we know from the era when drug use was rampant.
[00:18:28.800 --> 00:18:30.800] No, I think you make a very good point.
[00:18:30.800 --> 00:18:38.880] It frustrates me when people think that they're doing 7 watts per kilogram, 7.2, and then you have the real data from the day.
[00:18:38.880 --> 00:18:40.800] And this is way lower.
[00:18:40.800 --> 00:18:44.800] The short climbs where they would do maybe 7.2.
[00:18:44.800 --> 00:18:46.880] Now they're doing 6.3 maybe.
[00:18:46.880 --> 00:18:50.880] And the longer climbs, they're doing 5.5, 5.8.
[00:18:50.880 --> 00:18:53.280] It frustrates me because I see this data.
[00:18:53.280 --> 00:18:56.560] Gosh, I wish I could just boom release it.
[00:18:56.560 --> 00:18:59.040] I have absolutely no problem with that.
[00:18:59.040 --> 00:19:00.480] We debated it with the team.
[00:19:00.560 --> 00:19:01.680] We're keeping all this.
[00:19:01.680 --> 00:19:04.560] At the end of the day, people can figure that out.
[00:19:04.560 --> 00:19:15.520] And some people, what I see on internet, because you can see the weight of the cyclist, the grade of the grade, when it starts, the time, and the wind, you can be very accurate at knowing that.
[00:19:15.520 --> 00:19:20.080] And I see some people, they're quite accurate on the internet, but I see other ones are all over the map.
[00:19:20.080 --> 00:19:22.080] Did the formula in 7.2?
[00:19:22.400 --> 00:19:24.160] My gosh, I wish I could show him.
[00:19:24.160 --> 00:19:26.640] Maybe this is the real data that we're seeing.
[00:19:26.640 --> 00:19:27.600] Two points there.
[00:19:27.600 --> 00:19:33.320] It's like one, it's private data that the team considers, like not release it.
[00:19:29.840 --> 00:19:34.360] That's team policy.
[00:19:34.680 --> 00:19:51.160] But the other one, too, is like, even if you release that data, there are always going to be people that are not going to believe you, or they might say, oh, they probably altering the data or they're tricking it somehow or putting more weight to the data so it looks like there's less power output.
[00:19:51.160 --> 00:19:54.120] I don't know if it's, it'll be an endless fight.
[00:19:54.120 --> 00:19:55.400] I don't have the answer.
[00:19:55.400 --> 00:20:01.640] I just have that frustration that I wish that I could really show the data and people can see it.
[00:20:01.640 --> 00:20:06.440] There's always going to be someone who is not going to believe it and going to make a lot of noise out of that.
[00:20:07.400 --> 00:20:12.280] That's the other thing too, is like other teams and other writers are releasing their data.
[00:20:12.280 --> 00:20:16.920] So by releasing their data, you can see pretty much where Pogatar is.
[00:20:16.920 --> 00:20:34.760] Okay, if it's a minute ahead or 30 minutes, or sometimes with the same time, you can see, you know, like, whoa, whatever the writer has done and has entering Pogato's group or 30 seconds later and has done 5.9, Bagshar is going to be in that neighborhood, not going to be seven, you know, with 30 seconds ahead.
[00:20:34.760 --> 00:20:51.560] In the spirit of releasing data, the other thing it would potentially do, especially if you could see it in real time, I don't know if you watch Formula One, but one of the things about Formula One that I think the sport has been able to do because of the advances in technology is make more of the data available to the viewer.
[00:20:51.560 --> 00:20:57.240] If you're watching Lewis Hamilton driving a lap, you see what he sees now.
[00:20:57.240 --> 00:21:00.680] You can see, and it's not the end-of-the-world data, but you see his speed.
[00:21:00.680 --> 00:21:02.200] You see what gear he's in.
[00:21:02.200 --> 00:21:05.240] You see the difference between throttle and brake pressure.
[00:21:05.240 --> 00:21:14.120] They could show even more data, certainly, and someone who drives would appreciate it if you really saw brake bias and if you saw brake pressure and lockup and things like that.
[00:21:14.120 --> 00:21:18.000] And you can hear the drivers speaking with their race engineers.
[00:21:14.840 --> 00:21:21.440] So it basically allows you to come more and more into what they're doing.
[00:21:21.680 --> 00:21:26.080] This year they introduced a new camera angle, which is what the driver sees.
[00:21:26.080 --> 00:21:33.920] And I think it's fantastic because historically you see above them and it looks so smooth, but that's not at all what it feels like to be in a race car.
[00:21:33.920 --> 00:21:40.000] So now they just literally put like a camera at their shoulder and now you see how restrictive the halo is.
[00:21:40.000 --> 00:21:43.440] You see the bumps and it looks a lot faster.
[00:21:43.440 --> 00:22:01.840] You know, I've had this discussion with a number of people, which is if you could show the same sort of information in cycling, if every time the camera went over to a cyclist, you saw their heart rate, their watts per kilo, their speed, all of these other things, and you could hear some of the communications back and forth with their teams.
[00:22:01.840 --> 00:22:03.680] Yes, that changes the sport.
[00:22:03.680 --> 00:22:06.720] Strategically now, you have to be careful what you say on the radio.
[00:22:06.720 --> 00:22:11.440] But it also allows you to see the human element of this sport a little bit more.
[00:22:11.440 --> 00:22:13.120] Do you think that will ever happen?
[00:22:13.120 --> 00:22:19.280] Where you'll be able to flip on the Tour de France and you'll be able to actually see real-time physiology?
[00:22:19.280 --> 00:22:20.000] I would love it.
[00:22:20.000 --> 00:22:22.560] It would be so much fun for the viewer.
[00:22:22.560 --> 00:22:31.200] And cycling has so many possibilities to engage people more and be fascinated by the physiology and looking at these numbers.
[00:22:31.200 --> 00:22:36.240] It's already in a way, you see some cameras already installed in the front and the back.
[00:22:36.240 --> 00:22:37.600] It's called Velon.
[00:22:37.840 --> 00:22:43.520] You can see really cool images when they're preparing a sprint that is like what feels inside.
[00:22:43.520 --> 00:22:45.360] And you can see it's really scary.
[00:22:45.360 --> 00:22:56.000] Sometimes you can appreciate how difficult it is to be at 40 miles an hour sprinting or 35 miles an hour leading to a sprint or in a descent at 60 miles an hour or 70 miles an hour.
[00:22:56.000 --> 00:22:57.440] 70 miles an hour descent.
[00:22:57.440 --> 00:22:58.160] Exactly.
[00:22:58.480 --> 00:23:02.280] And then you can see the power output in real time.
[00:22:59.840 --> 00:23:03.800] I think it's a great step.
[00:23:04.120 --> 00:23:10.520] You don't see all the writers, but it's estimation, only the writers who wear that villain or the villain decides to do that.
[00:23:10.520 --> 00:23:14.920] And I think that they're still not doing that with all the top contenders.
[00:23:14.920 --> 00:23:16.360] But I think it's a first step.
[00:23:16.360 --> 00:23:20.920] And obviously, I haven't spoken with them, but maybe it's like, hey, let's see what's the feedback.
[00:23:20.920 --> 00:23:22.840] And I think that people are loving it.
[00:23:22.840 --> 00:23:25.160] I would expect that this will increase.
[00:23:25.160 --> 00:23:37.560] I would love at some point, you know, and as you know very well, in the world of biosensors, it's going to revolutionize sports where we're going to be able to see so many different parameters of athletes in real time.
[00:23:37.560 --> 00:23:41.080] Yeah, imagine you could see lactate and glucose in real time.
[00:23:41.080 --> 00:23:41.400] Absolutely.
[00:23:41.560 --> 00:23:44.280] Which, of course, is technologically feasible already.
[00:23:44.280 --> 00:23:45.160] Exactly.
[00:23:45.160 --> 00:23:45.720] Yeah.
[00:23:46.040 --> 00:23:48.280] I think I would love for all sports too.
[00:23:48.280 --> 00:23:55.560] Imagine you can see an NBA basketball game and see that the lactate of LeBron James compared to the other ones.
[00:23:55.560 --> 00:23:58.120] I mean, I would love to see that as a spectator.
[00:23:58.120 --> 00:24:01.640] And I hope that someday we were able to see these parameters.
[00:24:01.640 --> 00:24:05.640] So last thing on the tour, talk to me about Vantu this year.
[00:24:05.640 --> 00:24:07.080] That was a tough stage.
[00:24:07.080 --> 00:24:08.760] It looked like his toughest stage.
[00:24:08.760 --> 00:24:10.120] Is that a fair assessment?
[00:24:10.120 --> 00:24:11.320] Yes, probably.
[00:24:11.320 --> 00:24:14.360] And what's amazing, I think, is the poise on that stage.
[00:24:14.360 --> 00:24:22.200] It's hard to tell if he was really struggling on the ascent of Vantu or he was just deciding strategically, I'm going to conserve a little bit of energy here.
[00:24:22.200 --> 00:24:23.560] What was your take on that?
[00:24:23.560 --> 00:24:25.080] Or what can you say about that?
[00:24:25.080 --> 00:24:28.360] It was a very difficult climb and a very long climb.
[00:24:28.360 --> 00:24:32.280] Tadeh, his mentality is wired like a champion.
[00:24:32.280 --> 00:24:41.800] When someone goes and they were full gas in the last part, Vineagar attacked, Tadeh knew that this is not going to be the top of Bon Van 2 is not going to be the end of the stage.
[00:24:41.800 --> 00:24:48.240] That's a very, very long descent and I have some partners with me that they can help me out.
[00:24:48.560 --> 00:24:53.360] I'm not going to panic at all, but I'm not going to also waste a lot of energy.
[00:24:53.360 --> 00:24:55.440] He also had a big gap.
[00:24:55.600 --> 00:24:58.560] A whole different thing would have been if he had 20 seconds.
[00:24:58.560 --> 00:25:06.720] But having a big gap and knowing that you have a big descent and how calmed it is, that's one thing that is a very important strategy.
[00:25:06.720 --> 00:25:07.840] This is what happened.
[00:25:07.840 --> 00:25:14.400] This reminds me in a way what happened the first year that he was pro when he was 19 at the tour of California.
[00:25:14.400 --> 00:25:21.520] It was the previous stage before Bear Lake, Top Mountain in the Tour of California, where it's going to be decided.
[00:25:21.520 --> 00:25:28.400] So the day before, two cyclists, George Bennett and Yugita, attacked in a short but very steep climb.
[00:25:28.400 --> 00:25:31.040] And there were only like 12 riders left.
[00:25:31.040 --> 00:25:32.800] And Yuita and Bennett attacked.
[00:25:32.800 --> 00:25:37.920] Then there was like a descent and a long highway all the way to the finish line.
[00:25:37.920 --> 00:25:40.080] So there was plenty of time to catch him up.
[00:25:40.080 --> 00:25:41.920] But Tale didn't follow them up.
[00:25:41.920 --> 00:25:44.720] Another rider would have just followed their wheel.
[00:25:44.720 --> 00:25:47.360] And Tale decided, no, I'm not going to follow them.
[00:25:47.360 --> 00:25:51.280] We have time and I'm going to take the chance because I'm confident for tomorrow.
[00:25:51.280 --> 00:25:57.600] And when I asked him as soon as he crossed the finish line, I asked him, are you okay why you didn't follow their attack?
[00:25:57.600 --> 00:26:02.640] He said, well, I just, I wanted to know who is going to be good tomorrow.
[00:26:02.640 --> 00:26:14.400] So I know those two guys are going to be good tomorrow, but I wanted to take my time and see the other 10 guys, how they're breathing, what's their body language, take my time to observe to start preparing my strategy for tomorrow.
[00:26:14.400 --> 00:26:15.920] And in fact, that's what he did.
[00:26:15.920 --> 00:26:19.200] They were then caught up two, three kilometers to the finish line.
[00:26:19.200 --> 00:26:22.480] So all those 12, 13 guys, whatever they were, they got together.
[00:26:22.480 --> 00:26:26.800] And the next day, in fact, he noticed those two guys attacked.
[00:26:26.800 --> 00:26:29.880] He just followed them and he just eliminated one by one.
[00:26:29.880 --> 00:26:31.560] That's how this guy thinks.
[00:26:31.560 --> 00:26:33.640] No panic, plenty of time today.
[00:26:29.440 --> 00:26:35.880] I had a good gap in the GC.
[00:26:36.200 --> 00:26:46.440] Why am I going to go full gas when I know that he's going to go full gas and he might lose energy for tomorrow because he might pay for this at this time of the tour de France?
[00:26:46.440 --> 00:26:48.520] And we have plenty of time to catch him up.
[00:26:48.520 --> 00:26:51.080] So that's kind of the strategy that he had.
[00:26:51.080 --> 00:26:58.600] How much time does someone like Tadi spend in zone two, which we're going to talk a lot about?
[00:26:58.600 --> 00:27:07.080] And let's do it more as percentage of training time because I think absolute numbers will be very large given that that's his job.
[00:27:07.080 --> 00:27:14.680] But when you think about the percentage of time he spends in that energy zone, how does it change over the course of the year?
[00:27:14.680 --> 00:27:24.360] So presumably during the winter months, a greater amount of his time would be spent there as he's base building right before a race when he's kind of sharpening, maybe less.
[00:27:24.360 --> 00:27:26.120] What would be the range of time?
[00:27:26.120 --> 00:27:27.080] Or percent, rather?
[00:27:27.080 --> 00:27:27.880] Yeah, yeah.
[00:27:27.880 --> 00:27:28.440] You're right.
[00:27:28.440 --> 00:27:36.520] When we talk about percentage, I like to put it this way: more like a percentage of days dedicated to cultivate that energy system.
[00:27:36.520 --> 00:27:42.200] Obviously, if you put in just every single minute together, the majority is going to be that.
[00:27:42.200 --> 00:27:43.800] But I would say more in days.
[00:27:43.800 --> 00:27:49.800] In the winter months, might be about 80%, 70 to 80% of the days.
[00:27:49.800 --> 00:27:57.720] As the season gets closer, he starts increasing more the intensity days and sessions when the start of the season racing.
[00:27:57.720 --> 00:27:59.480] And you have, it depends.
[00:27:59.480 --> 00:28:07.240] You might have one stage race of five, seven days, and then you have a five-day block or one week to recover, and then you have the next stage rate.
[00:28:07.240 --> 00:28:09.480] So in that week, we do a lot of recovery.
[00:28:09.480 --> 00:28:11.720] We might do some sessions here and there.
[00:28:11.720 --> 00:28:23.280] And then after a few blocks of races, that's where you have another long time to train, period, to train, go to altitude towards the True de France or toward the next goal.
[00:28:23.280 --> 00:28:28.960] And that's where you may revisit these different energy systems and train specifically.
[00:28:28.960 --> 00:28:38.800] We alternate, and each energy system has a time in the year, in the calendar, what it's built in order to try to achieve what we want.
[00:28:39.120 --> 00:28:41.120] So let's remind people now.
[00:28:41.120 --> 00:28:46.880] I've put out a few posts on social over, gosh, the past year and even in the past little while.
[00:28:46.880 --> 00:28:53.680] And anytime I'm talking about zone two, it's really one of the topics that generates the most curiosity, the most inquiry from people.
[00:28:53.680 --> 00:28:57.680] I think people really intuitively kind of resonate with this.
[00:28:57.680 --> 00:29:02.880] And then, of course, a million questions follow because there's so much minutia and detail around it.
[00:29:02.880 --> 00:29:04.800] And a lot of that we're going to cover today.
[00:29:04.800 --> 00:29:12.000] But let's start from a place of maybe someone hasn't heard the first podcast where we go through some of the semantics of this.
[00:29:12.000 --> 00:29:14.000] Define zone two.
[00:29:14.320 --> 00:29:23.280] From my point of view, it is the exercise intensity at the one you are stressing the mitochondria and oxidative capacity to the most.
[00:29:23.280 --> 00:29:27.120] This is where you're recruiting mainly type 1 muscle fibers.
[00:29:27.120 --> 00:29:36.800] This is where you are mobilizing the highest amount of fat, both from lipolysis, from matipose tissue, as well as from fat oxidation inside the mitochondria.
[00:29:36.800 --> 00:29:44.400] And this is also where you stimulate all those bioenergetics, which is oxidative phosphorylation.
[00:29:44.400 --> 00:29:51.120] This is where you burn both the fat inside a mitochondria as well as the glucose inside the mitochondria.
[00:29:51.120 --> 00:30:02.200] There's not a very high glycolytic flux that it's going to be transforming to pyruvate and reduced to lactate, but that flux still is oxidized inside mitochondria.
[00:30:02.520 --> 00:30:08.440] This is looking at from a bioenergetics standpoint, this is what I would consider the zone two.
[00:30:08.440 --> 00:30:22.840] And what I have seen is that throughout the years is that this is the exercise intensity that achieves or stimulates that mitochondrial function and fat oxidation and lactate cleanse capacity the most.
[00:30:22.840 --> 00:30:24.520] That's the other thing too.
[00:30:24.520 --> 00:30:31.160] This is where other things involving lactate, so lactate is a great fuel to cells.
[00:30:31.160 --> 00:30:36.840] It's in fact probably the preferred fuel for the cells, for most cells in the body.
[00:30:36.840 --> 00:30:42.040] This is a work that my colleague and mentor and friend George Brooks discovered.
[00:30:42.040 --> 00:30:45.080] You should have him someday in the podcast because he's fascinating.
[00:30:45.080 --> 00:30:50.200] I mean, I would not be surprised if someday soon we hear that he wins a Nobel Prize.
[00:30:50.200 --> 00:30:51.240] He's amazing.
[00:30:51.240 --> 00:30:54.760] And every time I talk to him, I'm still learning a lot of things.
[00:30:54.760 --> 00:30:57.640] And I've been translating a lot of his research.
[00:30:57.640 --> 00:31:05.640] That's how I see that you have within the mitochondrial function, you see how lactate is oxidized in the mitochondria back to energy.
[00:31:05.640 --> 00:31:08.680] And that happens in those muscle fiber types.
[00:31:08.680 --> 00:31:21.560] Those muscle fiber types in the mitochondria, those fiber types also develop these transporters, which are MCT1s, which are the ones that transport lactate inside the cell and inside the mitochondria.
[00:31:21.560 --> 00:31:28.200] So when you stimulate that training zone, you stimulate all these energy systems and the components that come with them.
[00:31:28.200 --> 00:31:32.920] So let's talk about the different ways that one can go about estimating this.
[00:31:32.920 --> 00:31:45.280] Based on the definition you've just given, it seems to me that the purest way to estimate this would be via indirect calorimetry, because that will actually tell us the fat oxidation.
[00:31:45.280 --> 00:31:46.800] Is that a fair assessment?
[00:31:46.800 --> 00:31:48.560] Yes, it's a very good assessment.
[00:31:44.840 --> 00:31:51.360] That usually correlates with the fat max.
[00:31:51.440 --> 00:31:52.880] That's how we call it too, right?
[00:31:52.880 --> 00:31:54.320] That's fat oxidation.
[00:31:54.320 --> 00:32:08.720] And when you see that you start oxidizing fat and might increase in cases and gets to a point that it maxed out, which is the fat max, and then it starts going down sharply as exercise intensity increases.
[00:32:08.720 --> 00:32:10.720] So let's tell people how that's measured.
[00:32:10.720 --> 00:32:21.440] We do this with all of our patients, and I find it to be not that easy to explain because there's some physiology involved and there's some math involved.
[00:32:21.440 --> 00:32:24.000] But let me try to see if I can explain this to folks.
[00:32:24.000 --> 00:32:27.200] So you hook me up to an indirect calorimeter.
[00:32:27.200 --> 00:32:30.320] So you're going to put a little plug on my nose.
[00:32:30.320 --> 00:32:33.680] You're going to put a mask over my nose and mouth.
[00:32:33.680 --> 00:32:41.040] That mask has the ability to measure the amount of oxygen that I consume because it has a sensor for O2.
[00:32:41.040 --> 00:32:45.920] So it knows that the O2 that's coming in is at 21%.
[00:32:45.920 --> 00:32:48.240] The air is coming in at 21% O2.
[00:32:48.240 --> 00:32:51.520] And whatever I exhale is the difference between that.
[00:32:51.520 --> 00:32:54.240] So you can now tell how much O2 is consumed.
[00:32:54.240 --> 00:32:56.640] And you can have a similar sensor for carbon dioxide.
[00:32:56.640 --> 00:32:58.480] So you know how much carbon dioxide is produced.
[00:32:58.480 --> 00:33:07.040] So it's very easy to measure consumed oxygen and produced carbon dioxide provided you can completely isolate around the nose and the mouth.
[00:33:07.040 --> 00:33:17.600] As you hook a person up to some form of ergometer, usually a bike, could be a treadmill, a rowing machine, or something like that, you can increase the demand on the muscle.
[00:33:17.600 --> 00:33:20.880] So you increase the wattage or the speed or the something.
[00:33:20.880 --> 00:33:26.320] You then get out these numbers, VO2 and VCO2, which are what we just talked about.
[00:33:26.320 --> 00:33:29.960] So consumption of oxygen, production of carbon dioxide.
[00:33:29.440 --> 00:33:35.160] These numbers fit into a relatively straightforward linear equation called the Weir equation.
[00:33:35.480 --> 00:33:38.200] And it tells you three things.
[00:33:38.200 --> 00:33:43.720] It tells you total energy consumption in kilocalories per minute.
[00:33:43.720 --> 00:33:54.440] And then the ratio of VO2 and VCO2 tell you how much of that energy is coming from fat oxidation and how much of it is glycolytic.
[00:33:54.440 --> 00:34:13.240] So at any moment in time, you can look at a VCO2 and a VO2, which are usually measured in liters per minute, and you can convert that into a total grams of fat oxidation and a total grams of glucose oxidation per minute.
[00:34:13.240 --> 00:34:22.680] And so you could then plot on the x-axis work or power, and on the y-axis, you could plot fat oxidation.
[00:34:22.680 --> 00:34:32.440] Again, describe for people what the shape of that curve looks like and what differentiates Pogacha from the average human being.
[00:34:32.440 --> 00:34:33.720] You explain it very well.
[00:34:33.720 --> 00:34:36.600] Yeah, those are based on stoichiometric equations.
[00:34:36.600 --> 00:34:40.680] The combustion of carbohydrates and fatty acids by done in the body.
[00:34:40.680 --> 00:34:47.880] Already in the 1920s, Francis Benedict, one of the first ones, probably the first one who started to look into this at this level.
[00:34:47.880 --> 00:34:56.040] Obviously, we have evolved, do it in a more automatic way with these indirect calorimetries, machines or calls or metabolic cards.
[00:34:56.040 --> 00:35:06.520] As exercise intensity increases, I mean, you need more oxygen, so your VO2 increases, and then you produce or give up more CO2.
[00:35:06.840 --> 00:35:08.920] So this is kind of what it shows.
[00:35:08.920 --> 00:35:18.000] When you're in a more licolytic state, more fatty oxidation state, you still consume oxygen but you do not produce as much CO2.
[00:35:18.320 --> 00:35:34.880] When you are more into a more glycolytic state, which is higher exercise intensities, when you're recruiting the type 2 muscle fibers, and therefore using more glucose for energy purposes, you're going to consume more oxygen and you're going to produce more CO2.
[00:35:34.880 --> 00:35:51.200] Plugging in all these numbers into these stoichiometric equations, it's going to give you that profile, the X and the Y axis, and it's going to see what is the fat oxidation throughout RAMP state, a RAMP test.
[00:35:51.200 --> 00:36:09.040] And this is where you're going to see elite athletes like Bogachar, they have an amazing fat oxidation capacity compared to other competitive athletes or recreationals or people with even type 2 diabetes or metabolic syndrome or in a recent study that we have published with COVID patients.
[00:36:09.040 --> 00:36:19.600] So it reflects in a way, ultimately, what happens in your mitochondria and how the mitochondria oxidizes those fuels at different exercise intensities.
[00:36:19.600 --> 00:36:33.280] So for example, let's say at the intensity of 200 watts, a lead athlete doesn't need to incur in that glycolytic capacity as much as someone who is not very well trained.
[00:36:33.280 --> 00:36:47.200] So the elite athlete, they can still recruit slow twitch muscle fibers and rely a lot on fat to produce ATP because they have an amazing mitochondrial function and they're very efficient, metabolically speaking.
[00:36:47.200 --> 00:36:50.000] Therefore, they're going to be oxidizing a lot of fat.
[00:36:50.000 --> 00:37:15.880] However, someone whose mitochondria are not working as well, whether you are like a recreational athlete or sedentary individual or someone with type 2 diabetes, which is one of the hallmarks of the disease, that mitochondrial impairment or dysfunction at 200 watts, you fully rely on glucose pretty much because you cannot sustain that effort with fat alone.
[00:37:15.880 --> 00:37:21.080] And this is what you're going to be seeing, this gas exchange, the CO2 and the VO2.
[00:37:21.240 --> 00:37:33.640] You can just plot it into the equation, and it's going to give you all that what I call metabolic map, where you see the fat oxidation, the carbohydrate oxidation, and then I plug in also the lactate.
[00:37:33.640 --> 00:37:36.840] And that's where everything comes together quite well.
[00:37:36.840 --> 00:37:48.360] And you can then first, in an indirect way, calculate the mitochondrial function and metabolic flexibility, how flexible they are at using fats or carbohydrates.
[00:37:48.360 --> 00:37:51.480] And also, you can determine training zones.
[00:37:51.480 --> 00:37:56.520] I've been using this methodology for 16 years, 17, something like that.
[00:37:56.520 --> 00:38:19.640] I didn't think to ask you this earlier, but if you have it handy, do you want to pull up a graph of what fat oxidation looks like versus power so that people can see the difference between a highly trained individual, a reasonably trained individual, an untrained individual, and at the other end of that spectrum somebody with type 2 diabetes?
[00:38:19.960 --> 00:38:27.160] So this is from a publication that my colleague George Brooks and I published in 2017.
[00:38:27.480 --> 00:38:30.920] This is the formula, and we have realized that this is flipped.
[00:38:30.920 --> 00:38:37.160] So we need to work now with the editor to change it because the formula is flipped here in the methods section.
[00:38:37.160 --> 00:38:38.360] Which is so funny, by the way.
[00:38:38.360 --> 00:38:39.240] I like seeing that.
[00:38:39.240 --> 00:38:54.720] I'm embarrassed to say when we do this for our patients, we do it in two steps, which yields the same result, but we first calculate energy expenditure using the weir coefficients of 3.94 times VO2 minus plus 1.
[00:38:55.040 --> 00:38:57.920] I think it's 1,2 times VCO2.
[00:38:57.920 --> 00:39:08.320] And then we convert that to fat ox and carbohydrate oxidation using the ratio of VCO2 to VO2.
[00:39:08.320 --> 00:39:15.680] And I never even thought to do what you've done here, which is so much more logical, which is combine them into a single equation for each.
[00:39:15.680 --> 00:39:21.920] Well, we use what Fryan observed already in 1983, and this is Fryan's equation.
[00:39:21.920 --> 00:39:25.760] And it's been validated with tracers, stable isotope tracers.
[00:39:25.760 --> 00:39:26.800] Doubly labeled water.
[00:39:26.800 --> 00:39:28.400] Yeah, and that's what it shows.
[00:39:28.400 --> 00:39:29.840] There's a very high correlation.
[00:39:29.840 --> 00:39:40.800] Now, furthermore, in a study that we were going to be publishing soon, we have validated this fat oxidation and carbohydrate directly with mitochondrial respiration.
[00:39:40.800 --> 00:40:04.720] So in muscle biopsies, we inject directly fatty acids, pyruvate representative of carbohydrates, glutamine representative of amino acids, and then we can see that there's a very high correlation between this indirect methodology to look at mitochondrial function and the direct methodology, which is through muscle biopsy and injecting the substrate and see how it's oxidized.
[00:40:04.720 --> 00:40:06.960] So these two graphs are really powerful.
[00:40:06.960 --> 00:40:10.080] Let's talk about what the first graph is showing us.
[00:40:10.080 --> 00:40:14.560] So both of these graphs, it's important to note, have the same x-axis.
[00:40:14.560 --> 00:40:20.400] In other words, the independent variable here is the workload in watts.
[00:40:20.400 --> 00:40:25.280] That's the metric that matters in cycling, which is, I think, the easiest way to do this test.
[00:40:25.280 --> 00:40:26.960] And so you're increasing wattage.
[00:40:26.960 --> 00:40:30.000] This is a progressive increase in workload.
[00:40:30.520 --> 00:40:37.960] And what you're plotting on the y-axis, your dependent variable here in the first graph, figure one, is blood lactate.
[00:40:37.960 --> 00:40:40.680] What stands out to me is a couple of things.
[00:40:40.680 --> 00:40:44.760] So you have the triangles represent metabolic syndrome.
[00:40:44.760 --> 00:40:49.080] The squares represent a modestly trained athlete.
[00:40:49.080 --> 00:40:52.200] And then the little diamonds represent a professional athlete.
[00:40:52.200 --> 00:41:02.600] The first thing that stands out to me, and we're going to talk about this later, so I'll put a little pin in this, is that the people with metabolic syndrome have a resting lactate that's almost two millimole.
[00:41:02.600 --> 00:41:04.200] Yes, we see already this.
[00:41:04.200 --> 00:41:09.960] I think that it's going to become more and more as a biomarker, like resting blood glucose levels.
[00:41:09.960 --> 00:41:11.800] What is your resting lactate?
[00:41:11.800 --> 00:41:25.160] You can see already in patients with type 2 diabetes or profound metabolic syndrome that, yeah, as you say perfectly, yeah, resting levels are in the neighborhood of like a 1.8, 1.5 to even 3.
[00:41:25.480 --> 00:41:34.520] So one of the metrics that we've discussed at length, and we'll revisit it, of course, is using this lactate level of about 2 millimole as being that threshold.
[00:41:34.520 --> 00:41:43.160] So once lactate exceeds 2 millimole, the individual is now escaping out of zone 2 and they're actually now into zone 3.
[00:41:43.160 --> 00:41:51.880] So when you look at these data here, you can see that the individual with metabolic syndrome is basically tapping out zone 2 initially.
[00:41:51.880 --> 00:41:57.880] So any incremental workload that is placed on them takes them right out of zone 2.
[00:41:57.880 --> 00:42:04.280] For all intents and purposes, by the time they're at 100 watts, they're already at the threshold of their zone 2.
[00:42:04.280 --> 00:42:21.840] Now, conversely, when you look at that medium-trained or reasonably well-trained individual, I think it's referred to as moderately active, healthy individuals, they start out with a lactate of about one, and it's not really until they hit about 175 watts that they pass that inflection point.
[00:42:22.160 --> 00:42:42.800] And then, when you look at the professional athletes, the professional endurance athletes specifically, they're starting out at a lactate level of 0.5 millimol, and they stay relatively flat until they hit about 300 watts, is when they finally cross over that threshold.
[00:42:42.800 --> 00:42:51.200] Now, what's not captured here is that as you move from left to right, the athletes are getting lighter.
[00:42:51.520 --> 00:42:58.400] So, this graph, if I'm going to be critical of it in Yugo, I would say it should be done in watts per kilo.
[00:42:58.400 --> 00:43:03.040] And that would show a much starker difference between these.
[00:43:03.040 --> 00:43:10.080] And in our patients, when we benchmark them, we benchmark them in watts per kilo for this reason, so that you normalize by weight.
[00:43:10.080 --> 00:43:12.400] And I'm certain, Travis, you're absolutely right.
[00:43:12.400 --> 00:43:14.080] And that's how we do it also.
[00:43:14.080 --> 00:43:18.240] One of the reviewers didn't allow us to use watts per kilogram.
[00:43:18.240 --> 00:43:23.360] Clearly, that reviewer was an idiot, so that's I won't hold it against you because the idiot reviewer.
[00:43:23.520 --> 00:43:24.800] You know how it is in review papers.
[00:43:24.800 --> 00:43:32.720] You want to show something, and eventually it's changed, and it's not exactly sometimes what you want to show because otherwise they don't allow you to publish it.
[00:43:32.720 --> 00:43:33.520] But, anyways.
[00:43:33.520 --> 00:43:41.840] But what's amazing here is that person with metabolic syndrome is probably about one watt per kilo, easily.
[00:43:41.840 --> 00:43:45.520] One to 1.3 watts per kilo is their zone two.
[00:43:45.520 --> 00:43:51.040] When you look at the modestly trained individual, they're about 2 watts per kilo.
[00:43:51.040 --> 00:43:55.920] They probably weigh maybe 2 to 2.1, 2.2 watts per kilo.
[00:43:55.920 --> 00:44:02.040] That professional endurance athlete probably weighs in the neighborhood of 70 kilos.
[00:43:59.600 --> 00:44:06.120] So they're in the ballpark of 4 watts per kilo.
[00:44:06.360 --> 00:44:11.240] For our patients, Inigo, we set the aspiration at 3 watts per kilo.
[00:44:11.240 --> 00:44:19.880] So again, our patients aren't professional athletes, but we think that 3 watts per kilo would be kind of the elite level that we would want to see people.
[00:44:19.880 --> 00:44:21.880] And then, of course, we stratify from there.
[00:44:21.880 --> 00:44:25.000] Let's look at the lower figure, figure two, just beneath this.
[00:44:25.000 --> 00:44:28.120] So here, we're looking at the same group of individuals.
[00:44:28.120 --> 00:44:36.600] We have the same independent variable, which is work, but now we're calculating fat oxidation as a function of that work.
[00:44:36.600 --> 00:44:42.520] So now your dependent variable is fat oxidation, which again, very easy to calculate via indirect calorimetry.
[00:44:42.520 --> 00:44:44.440] Two things stand out again.
[00:44:44.440 --> 00:44:51.960] The first is the obvious, which is the fitter the individual, the higher their absolute capacity for fat oxidation.
[00:44:51.960 --> 00:45:08.600] But something else stands out to me in you go, and I have now seen this repeatedly across multiple data sets, which is a fit individual actually increases fat oxidation to a local maxima before beginning that decline.
[00:45:08.600 --> 00:45:13.880] Whereas most mortals begin at a maximum and decline from there.
[00:45:13.880 --> 00:45:15.800] Can you explain why that's happening?
[00:45:15.800 --> 00:45:16.280] I agree.
[00:45:16.280 --> 00:45:17.960] I see this all the time.
[00:45:17.960 --> 00:45:21.480] I think that on one hand is how you start a protocol.
[00:45:21.480 --> 00:45:23.800] In this case, we started like at one.
[00:45:23.800 --> 00:45:27.400] We start about 1 to 1.5 watts per kilogram.
[00:45:27.400 --> 00:45:33.480] And that obviously for an elite athlete is the low resting levels, so this is what they're very low.
[00:45:33.480 --> 00:45:38.360] And they don't need to use much fat for energy purposes until you push them more.
[00:45:38.360 --> 00:45:43.640] And that's when you get to like 2, 2.5, 3, 3.5 watts per kilogram, right?
[00:45:43.640 --> 00:45:50.640] And again, this protocol comes originally from the work that I've been doing for 20 years, the same protocol with elite affiliates.
[00:45:51.040 --> 00:46:01.600] When you do the same protocol with other populations, especially people with metabolic syndrome or not very fit, and you start at 1.5 watts per kilogram, that might be too much.
[00:46:01.600 --> 00:46:11.440] And I'm sure you have observed that if you start at 0.5 watts per kilogram, you might see a higher fat oxidation, and then you might see the same phenomenon.
[00:46:11.440 --> 00:46:19.760] So, on one hand, is that protocol, but on the other hand, yeah, sure, like 0.5 watts per kilogram, it's like nothing.
[00:46:19.760 --> 00:46:23.760] It's close to resting levels, so it will take you for a long time.
[00:46:23.760 --> 00:46:34.800] But that being said, I think that one thing that we're doing with populations, more clinical populations, is really starting at a very low level, even up to 50 watts or 25 watts sometimes.
[00:46:34.800 --> 00:46:46.240] So we can establish these points because if you start at 2 watts per kilogram or 1.5 watts per kilogram with someone with a significant metabolic dysregulation, you're going to miss the fat max.
[00:46:46.240 --> 00:46:47.360] Yeah, I agree with you.
[00:46:47.360 --> 00:46:53.440] We have been struggling to tune our algorithm to exactly that.
[00:46:53.440 --> 00:47:05.440] I actually think, and I had this discussion with our team a week ago, which was the physiologists who are doing this with our patients are probably overcooking the people who are not fit during the warm-up.
[00:47:05.440 --> 00:47:13.600] So they do a warm-up, and the warm-up is actually too stressful, and it overcooks them, and then we're missing the true max fat.
[00:47:13.600 --> 00:47:20.880] The next thing I want to point out here, and let's just look at the fittest person, but it's true for all of them, but it's easiest to see here.
[00:47:20.880 --> 00:47:24.400] Fat max, so fat max ox, right?
[00:47:24.400 --> 00:47:30.280] So maximum fat oxidation is occurring earlier than lactate is two.
[00:47:29.840 --> 00:47:34.920] And that's true for all of them, except for the MET-SIN person, because that's so low.
[00:47:35.240 --> 00:47:46.760] If you look at the moderately fit person, they're hitting maximum fat oxidation at about 130 watts, but they're hitting lactate of two at 175 watts in the upper figure.
[00:47:46.760 --> 00:48:00.920] And the professional athlete is hitting an absolute fat oxidation maxima at a little shy of 250 watts, but they're hitting lactate of two closer to 300 watts.
[00:48:00.920 --> 00:48:11.640] So I guess the question then becomes: you've already answered part of the question, which is we're really defining zone two as the place where maximum fat oxidation occurs.
[00:48:11.640 --> 00:48:19.320] But I guess this would suggest that using a lactate level of two is maybe overestimating where that is.
[00:48:19.320 --> 00:48:25.000] And should we be using a lower level of lactate, such as 1.5 or something like that?
[00:48:25.320 --> 00:48:32.840] This is what I've been learning all these years is that the blood lactate levels might change between different groups.
[00:48:32.840 --> 00:48:38.680] And it's everything related to the lactate kinetics and lactate oxidation in the mitochondria.
[00:48:38.680 --> 00:49:02.680] So for example, elite athletes, this was part of my doctorate thesis and some of this that never published it 20 something years ago, but the same blood lactate concentration does not correspond in an elite athlete, does not correspond necessarily to the same lactate concentration in a recreational athlete, the metabolic stress.
[00:49:02.680 --> 00:49:13.400] So for example, two millimoles, two millimolar of lactate in these elite athletes might be a higher metabolic stress than two millimoles in a metabolic patient.
[00:49:13.400 --> 00:49:16.160] So this is why it would be very difficult.
[00:49:16.160 --> 00:49:26.560] For example, you can have a, let's say, two and a half millimoles, you can have a metabolic syndrome patient exercising for a couple hours without a big deal.
[00:49:26.560 --> 00:49:30.560] You try to do that with a professional athlete, and they're going to be hurting.
[00:49:30.560 --> 00:49:39.600] And in fact, one of the things that I observe is like I use the four millimoles or millimolar, which is kind of that gold standard, it's been forever like the lactate threshold, etc.
[00:49:39.920 --> 00:49:57.280] If you put a world-class athlete at four millimoles at the intensity and power output that elicits four millimoles, and you put a recreational athlete at the power output that elicits also four millimoles, and you say now go, see who likes the most.
[00:49:57.280 --> 00:50:00.720] Intuitively, we're going to say, obviously, it's going to be the professional athlete.
[00:50:00.720 --> 00:50:01.840] It's the opposite.
[00:50:01.840 --> 00:50:04.400] And this is the data that I saw 20-something years ago.
[00:50:04.400 --> 00:50:12.720] The recreational athletes at the same blood lactate concentration would go about 30% longer period of time.
[00:50:12.720 --> 00:50:16.000] And that's because metabolically is not as tusking.
[00:50:16.000 --> 00:50:23.680] And the main reason is that the lactate that we see in the blood, it reflects the mitochondrial oxidation.
[00:50:23.680 --> 00:50:33.520] So someone who has, obviously, when we're talking about high power output, when you need a lot of glycolysis to produce energy, you're going to produce lactate.
[00:50:33.520 --> 00:50:40.480] Lactate is the mandatory, obligatory byproduct, not waste product, but byproduct of glycolysis.
[00:50:40.480 --> 00:50:43.520] So the higher the glycolysis, the higher the lactate.
[00:50:43.520 --> 00:50:46.880] Now that lactate has two routes mainly.
[00:50:46.880 --> 00:50:52.320] One is going from the fast twitch muscle fibers to the slow twitch muscle fibers.
[00:50:52.320 --> 00:51:00.280] It's the lactate chattel that George Brooke discovered and is oxidizing the mitochondria of those slow twitch muscle fibers.
[00:50:59.840 --> 00:51:06.360] If you have a very good lactate clearance capacity, you're going to be oxidizing it very, very well for fuel.
[00:51:06.680 --> 00:51:12.280] Therefore, you're not going to incur in the second step, which is exporting it to the blood.
[00:51:12.280 --> 00:51:25.400] When you have a poorer mitochondrial function, it's going to get to a point that that capacity is going to get saturated at a lower power output, and therefore, you're going to be forced to export that to the blood.
[00:51:25.400 --> 00:51:29.480] So that's why looking at blood lactates might not mean the same.
[00:51:29.480 --> 00:51:32.120] I'm not saying that the disparities are huge by no means.
[00:51:32.120 --> 00:51:40.440] But as you very well said, those two millimoles might not correspond in an elite athlete with a fat max, but might be more maybe towards 1.5.
[00:51:40.440 --> 00:51:46.680] Whereas maybe in someone with a more recreational or metabolic syndrome, it might correspond there.
[00:51:46.680 --> 00:51:48.360] I don't know if it makes sense.
[00:51:48.360 --> 00:51:49.560] It completely makes sense.
[00:51:49.560 --> 00:51:54.760] And this is definitely the level of nuance I don't think we captured in the first podcast.
[00:51:54.760 --> 00:52:00.840] And I want to now ask a more telling question specifically for the middle person here.
[00:52:00.840 --> 00:52:05.560] So the one that's called the moderately active individual, where again, we have a disparity.
[00:52:05.560 --> 00:52:19.560] So based on these data, the moderately fit individual hits a lactate of two millimole at 175 watts, but hits a max fat oxidation at, gosh, 125 watts.
[00:52:19.560 --> 00:52:21.400] So it's a 50 watt difference.
[00:52:21.400 --> 00:52:29.880] So now the question for you is, when that person comes to you and says, Inugo, I want to improve my metabolic function.
[00:52:29.880 --> 00:52:33.560] I want to improve my mitochondrial performance.
[00:52:33.560 --> 00:52:38.600] I want to improve my fuel partitioning, my flexibility, all the things we talk about.
[00:52:38.600 --> 00:52:47.840] Are you going to train them as a zone 2 of 125 watts or as a zone 2 of 175 watts as represented by these deltas?
[00:52:48.160 --> 00:52:50.960] Normally, I would try to do something in the middle.
[00:52:50.960 --> 00:52:56.400] Normally, it might not coincide perfectly, but normally they do quite well.
[00:52:56.400 --> 00:53:00.320] And another parameter, if you allow me, I can show you in this paper.
[00:53:00.320 --> 00:53:06.960] When decided, we see individually the lactates, and then we see the fat oxidation.
[00:53:06.960 --> 00:53:09.760] But then I decided to cross them over.
[00:53:09.760 --> 00:53:12.480] This is what we saw in this graph over here.
[00:53:12.480 --> 00:53:21.440] So, this is where you see the lactate versus the fat oxidation in the elite athlete, and the R is 0.97.
[00:53:21.440 --> 00:53:23.120] This is true Bonferroni equations.
[00:53:23.120 --> 00:53:25.680] So, this is an average of all of them.
[00:53:25.680 --> 00:53:31.760] And this is where you see the same pattern, the same graph, for the motorally active.
[00:53:31.760 --> 00:53:35.040] And this is also what you see in the person with metabolic syndrome.
[00:53:35.040 --> 00:53:37.120] The correlations are very, very strong.
[00:53:37.120 --> 00:53:38.560] They're almost perfect.
[00:53:38.560 --> 00:53:44.000] So, this is what normally fat oxidation and lactate, they go together.
[00:53:44.000 --> 00:53:53.520] So, for people who are going to be listening to this, Inugo, and not able to see what we're seeing, can you describe the differences between these graphs?
[00:53:53.520 --> 00:54:00.480] These are obviously showing the same data that we discussed earlier, but now we're using two y-axes.
[00:54:00.480 --> 00:54:03.680] So, let's even just talk about it as looking at the elite athletes.
[00:54:03.680 --> 00:54:14.560] So, you're basically plotting the decline in fat oxidation, or in their case, the initial increase in fat oxidation followed by a decline in fat oxidation.
[00:54:14.560 --> 00:54:18.800] And on the same graph, you're showing the increase in lactate production.
[00:54:18.800 --> 00:54:22.640] Again, both plotted to the same x-axis of power.
[00:54:22.640 --> 00:54:26.160] Does the cross point here indicate any significance?
[00:54:26.160 --> 00:54:29.280] So, they're crossing at about 325 watts.
[00:54:29.280 --> 00:54:31.320] Is there anything about that that means anything?
[00:54:29.920 --> 00:54:36.760] I mean, to me, I think it's an artifact of the graph because it's really just a function of how you scale it, correct?
[00:54:37.320 --> 00:54:38.360] Yes, exactly.
[00:54:38.360 --> 00:54:49.240] I mean, it shows to me that, yeah, the crossover point for blood lactate and fat oxidation very high, obviously, in the elite athletes, very far to the right.
[00:54:49.240 --> 00:55:00.600] And then, of course, in the moderately fit people, it looks like it's closer to 1 maybe 80 watts, and in the unfit individual, it's about 125 watts, a person with metabolic syndrome.
[00:55:00.600 --> 00:55:16.440] If you started, and I'm sure you have seen this, but if you started with the metabolic syndrome, for example, at 25 watts, even in the recreational athlete, even earlier, you might see a similar pattern as you would see in the elite athlete, but at much lower watts, obviously.
[00:55:16.440 --> 00:55:20.760] We just did the same protocol for everybody, just to show the concept.
[00:55:20.760 --> 00:55:24.680] Both fat oxidation and lactate go together.
[00:55:24.680 --> 00:55:29.000] And also, when we look into, and I'm sorry, I should have gone to this directly.
[00:55:29.000 --> 00:55:34.600] When we look into fat oxidation and carbohydrate oxides, we see the same concept.
[00:55:34.600 --> 00:55:40.280] So we see as exercise intensity increases, you need to oxidize more carbohydrates.
[00:55:40.280 --> 00:55:44.040] And then, as exercise intensity increases, you might get to the fat max.
[00:55:44.040 --> 00:55:47.880] And then, in the moment, you switch to the glycolytic fibers.
[00:55:47.880 --> 00:55:51.160] You cannot use much fat for energy purposes.
[00:55:51.160 --> 00:55:58.120] So, you see a sharp decline, and eventually, fat oxidation disappears, and it's all full glycolytic.
[00:55:58.120 --> 00:56:05.240] And the same pattern we see in the rest of populations with also very high statistical significances and correlations.
[00:56:05.240 --> 00:56:10.840] All these elements, fat oxidation, carbohydrates, and lactate, they're very well connected.
[00:56:10.840 --> 00:56:15.000] If we look in the other graph, this is the correlation between lactate and carbohydrates.
[00:56:16.240 --> 00:56:24.480] We see that overall the correlations are quite good because lactate is the byproduct of glucose utilization.
[00:56:24.480 --> 00:56:28.720] You may see that in the elite athletes, though, the gap is wider here.
[00:56:28.720 --> 00:56:30.800] And this is for the same reason I was seeing earlier.
[00:56:30.800 --> 00:56:32.480] They use a lot of glucose.
[00:56:32.480 --> 00:56:35.840] They're using so much fat there as well, is really the point.
[00:56:35.840 --> 00:56:43.440] So the bigger the gap between the blood lactate curve and the carbohydrate oxidation curve, the more efficient the individual is.
[00:56:43.440 --> 00:56:49.280] The more they're able to oxidize fatty acid, then they have to require glucose.
[00:56:49.280 --> 00:56:50.560] And clear lactate.
[00:56:50.560 --> 00:56:51.200] Yes.
[00:56:51.200 --> 00:56:57.360] The mandatory byproduct of glucose oxidation is lactate.
[00:56:57.360 --> 00:57:00.320] So here, the lactate doesn't show up in the blood.
[00:57:00.320 --> 00:57:02.080] It stays in the muscle.
[00:57:02.080 --> 00:57:06.800] It's hard to disentangle those two because you mentioned a good point that I omitted.
[00:57:06.800 --> 00:57:10.320] This in part reflects the lactate shuttle.
[00:57:10.320 --> 00:57:22.640] This in part reflects the ability for them to reuse lactate as a fuel as opposed to just letting it get out there with hydrogen and start to poison sarcomeres.
[00:57:22.960 --> 00:57:29.360] Let me see the other slide that you wanted to show that explains, I think, how the MCT transporters work.
[00:57:29.360 --> 00:57:37.920] This is a little bit more of the bioenergetics of the cells, of the main two substrates, which are fatty acids and pyruvate, and also lactate, right?
[00:57:37.920 --> 00:57:45.440] So normally glucose goes through glycolysis and it ends up, this is the cytosol, this is the outside of the mitochondria, the inside of the cell.
[00:57:45.440 --> 00:57:49.760] And glucose, when it enters the cell, it's oxidized to pyruvate.
[00:57:49.760 --> 00:58:01.240] That pyruvate needs to enter the mitochondria through what's called the mitochondrial pyruvate carrier, and it's oxidized to acetyl-CoA, which enters the Krebs cycle.
[00:58:01.240 --> 00:58:08.520] This is a complete oxidation of glucose through oxidative phosphorylation in the Krebs cycle and electron transport chain.
[00:58:08.520 --> 00:58:12.440] Then fatty acids have the same mechanisms too.
[00:58:12.440 --> 00:58:16.200] They also get converted to acetyl-CoA through different mechanisms.
[00:58:16.200 --> 00:58:23.960] Fatty acids are transporter through CPT1 and then CPT2 go through beta oxidation, acetyl-CoA, and enter the cell.
[00:58:23.960 --> 00:58:32.840] But every time that you use glucose to produce pyruvate, and every single time that pyruvate is going to be reduced to lactate, always.
[00:58:32.840 --> 00:58:34.280] And this is the key concept.
[00:58:34.280 --> 00:58:47.480] So when you have a constant glycolytic flux, in one of the steps of glycolysis, you're going to utilize NAD and it's going to be transformed to NADH plus hydrogen.
[00:58:47.480 --> 00:58:53.480] So if you use this mechanism a lot, you're going to deplete NAD.
[00:58:53.480 --> 00:59:02.200] The only way that rescues NAD is the reduction of pyruvate to lactate, which replenishes NAD going back for glycolysis.
[00:59:02.200 --> 00:59:05.960] And this is absolutely necessary for the continuation of glycolysis.
[00:59:05.960 --> 00:59:20.600] But this lactate enters the mitochondria through a specific transporter, MCT1, and has a specific enzyme, LDH, that oxidizes lactate back to pyruvate and going back to the Krebs cycle.
[00:59:20.600 --> 00:59:22.760] So again, this is an extra fuel.
[00:59:22.760 --> 00:59:27.720] But for that, you need to have these transporters very well developed.
[00:59:27.720 --> 00:59:33.880] Let me try to explain this to people who aren't able to see the graph because this is such an important point.
[00:59:33.880 --> 00:59:36.920] So, you're showing a picture of the mitochondria.
[00:59:36.920 --> 00:59:38.920] We're looking at the outer mitochondrial membrane.
[00:59:39.000 --> 00:59:51.360] We're talking about three transporters, three things that let substrates from the outside to the inside, where they will undergo the most efficient form of ATP production.
[00:59:51.680 --> 01:00:01.680] So, the first is we have the fatty acids, they enter directly, then they undergo an oxidation where they get truncated into little two-carbon chains and they enter the Krebs cycle.
[01:00:01.680 --> 01:00:03.920] We get that one, and we know why that one's very good.
[01:00:03.920 --> 01:00:11.920] What I think is very interesting here is when you contrast the two different fates of glucose byproducts.
[01:00:11.920 --> 01:00:27.200] So, the traditional way that we think about this: glucose being reduced to pyruvate, pyruvate directly entering the cell through its own carrier, and then being converted to acetyl-CoA, which follows the same fate as the fatty acid.
[01:00:27.200 --> 01:00:39.360] Now, when energy demand increases, and we just looked at graph after graph that demonstrate that no matter how fit you are, at some point you have to produce more lactate.
[01:00:39.360 --> 01:00:46.960] So, you now don't have sufficient cellular oxygen to go down that first route, so you start making lactate.
[01:00:46.960 --> 01:00:58.800] But if you have enough MCT1 transporters on the outer mitochondrial, you can now bring that lactate in the cell and actually do the reverse of what just happened.
[01:00:58.800 --> 01:01:04.640] Turn that lactate back into pyruvate, pyruvate becomes acetyl-CoA, and everybody wins the game again.
[01:01:04.640 --> 01:01:14.000] The game being one, of course, because now you're making 32 units of ATP instead of just the two units you would make converting pyruvate to lactate.
[01:01:14.000 --> 01:03:15.280] So, it begs a very important question: which is: earlier when you spoke about what makes Pogachar so remarkable physiologically, one of those things is he must have a boatload of MCT1 transporters on his outer mitochondrial membrane and that must explain in part why his lactate levels are so much lower than everybody else's at a comparable work level how much of that is genetic and how much of that is a result of his training exactly so you're right he has a much higher level to oxidized lactate so there's a genetic component no doubt about it there's also an epigenetic component and as we know nowadays the genes are not your fate necessarily from the genes to be able to be transcribed and form a protein with biological action the probability is less than 20 percent kind of what the science is showing roughly this is the whole from genetics to transcriptnomics proteomics and metabolomics it's about 20 percent chances that one gene is going to be ultimately expressed obviously we're still trying to understand all this so these elite athletes probably they have a much higher possibilities but there's a long journey and this is where epigenetics occur is like what you eat how you rest how you train and i think that the training is also an important component of this this is for example why we train very very specifically this energy system and we try to dial in as much as we can specifically to try to stimulate this bioenergetics system and increase the mct1s the transporters for lactate as well as all the components in the krebs cycle, which is the mitochondrial respiration, and also to increase also the mitochondrial pyruvic carrier, because we might discuss later, this is already dysregulated in people or down-regulated in people who are sedentary.
[01:03:15.280 --> 01:03:18.560] But the thing is, like if you see this next slide, can you see it?
[01:03:18.560 --> 01:03:21.520] Okay, this is what makes the difference in these athletes.
[01:03:21.520 --> 01:03:25.520] So this is a fast twitch muscle fiber and they use glucose.
[01:03:25.520 --> 01:03:44.560] So this is when you're like a high exercise intensities, climbing or running at a high intensity or swimming or whatever the activity you do, you need glucose because glucose is, as you said very well, it yields less ATP, but it does it much faster than the diesel gasoline, which is the fat.
[01:03:44.560 --> 01:03:48.720] But when you use glucose, you're always going to produce pyruvate.
[01:03:48.720 --> 01:03:55.280] The higher the intensity, the more glucose you need, more pyruvate you will need, and the more lactate that you will produce.
[01:03:55.280 --> 01:03:59.440] So that lactate has, as I said earlier, two routes.
[01:03:59.440 --> 01:04:07.760] One route is like it's exported through the MCT force, which is the transporter of lactate outside the fast-twitch muscle fibers.
[01:04:07.760 --> 01:04:13.680] Something that also is trainable, the capacity to export lactate through high-intensity exercise.
[01:04:13.680 --> 01:04:17.920] And then it travels to the adjacent slow-twitch muscle fibers.
[01:04:17.920 --> 01:04:22.480] We blow up this mitochondria in the slow twitch muscle fibers.
[01:04:22.480 --> 01:04:23.520] This is what will happen.
[01:04:23.520 --> 01:04:31.520] The entrance of that lactate, it goes through another transporter, MCT1, it's the same family, but instead of four, it's called MCT1.
[01:04:31.680 --> 01:04:38.160] I mentioned earlier, that lactate is converted to pyruvate and acetyl-CoA and goes into the Krebs cycle.
[01:04:38.160 --> 01:04:46.880] So in these well-trained athletes like Bohachar, for example, they have an amazing ability to oxidize the lactate inside mitochondria.
[01:04:46.880 --> 01:04:53.520] At some point, every single human gets to a point that they cannot sustain the effort anymore.
[01:04:53.520 --> 01:05:03.000] But what makes the difference is obviously like these guys can do 400 watts for a long time versus a mermaid who cannot even do two strokes at 400 watts.
[01:05:03.320 --> 01:05:12.120] So what happens is like when you have a lot of the right MCT1 and mitochondrial function, this lactate is going to increase and accumulate.
[01:05:12.120 --> 01:05:14.200] And it's not lactate per se.
[01:05:14.200 --> 01:05:27.240] but the hydrogen ions associated to lactate elicit an acidosis of the microenvironment of the muscle, which is something that we know and we have learned also from cancer, the famous cancer microenvironment, which is very acidic.
[01:05:27.240 --> 01:05:34.440] And that's going to interfere with different functions in the muscle with both the contractive force and the velocity of the muscle fibers.
[01:05:34.440 --> 01:05:44.360] I'm not saying that this is the cause of fatigue by no means because there are multiple theories and we're still trying to understand it's a central fatigue as well and everything probably is interrelated or it must be interrelated.
[01:05:44.360 --> 01:05:49.880] But the bottom line is like when this lactate cannot be oxidized, it is exported to the blood.
[01:05:49.880 --> 01:06:02.680] And this is why you see that people with metabolic syndrome, for example, or type 2 diabetes who are characterized by having a very poor mitochondrial function, they cannot during exercise oxidize this lactate.
[01:06:02.680 --> 01:06:10.920] In the moment they start using glucose, which is very fast also because they don't have the slow twitch muscle fibers, mitochondria to use fat, they need to rely on glucose.
[01:06:10.920 --> 01:06:14.600] That's that metabolic reprogramming or partitioning they have.
[01:06:14.600 --> 01:06:17.560] They produce lactate, but they cannot oxidize the lactate.
[01:06:17.560 --> 01:06:22.920] That's why this lactate chooses mandatorily the route of being exported to the blood.
[01:06:22.920 --> 01:06:25.800] And in the blood, then it goes to any tissue in the body.
[01:06:25.800 --> 01:06:31.000] So this is what I meant earlier about what is two millimoles versus one millimole.
[01:06:31.000 --> 01:06:36.120] Whereas Pogacha, for example, he oxidizes a lot of this lactate.
[01:06:36.120 --> 01:08:22.200] So by the time that Porgachar saturates this transporter and this mitochondrial capacity to oxidize lactate, it's a tremendous amount of power output and a tremendous amount of glucose that he puts out so this is why that one millimo 1.5 millimole and a world-class athlete necessarily represent the same metabolic status over 1.5 or 2 millimoles in the blood of a normal person this is a fantastic tutorial in muscle physiology and again this very important distinction between lactate production at the local level and lactate that we measure at the global level that's the challenge we have when we are measuring lactate we cannot impute lactate clearance and lactate production we can only impute the sum of those it's originally thought right that these athletes they don't use as much glucose well in fact the reach shows and brooks and his team showed it and others too that the well-trained athletes in fact they use more glucose because they have to you cannot do 400 watts without massive amount of carbohydrate and this is what we also see in the indirect calorimetry that you see people recreational for people with metabolic syndrome they have like four grams per minute at max carbohydration whereas elite athletes they can get to six and a half grams per minute it's massive amount of glucose and they produce a lot more lactate but the key it doesn't show up in the blood is the rate of appearance in the blood because it's oxidized in the muscle so it doesn't show up in the blood is the balance of lactate production and lactate oxidation without getting to the blood.
[01:08:22.200 --> 01:08:29.960] And this is what it correlates a lot also with fat oxidation as well and the graphs that I was showing earlier.
[01:08:29.280 --> 01:08:38.920] So one of the things I want to ask you about here that is a bit of a confounder when we do this type of analysis is the carbohydrate content within the diet.
[01:08:38.920 --> 01:08:42.120] So I'll share with you my data.
[01:08:42.120 --> 01:08:47.960] But I've now seen this with multiple people, including one individual who's remarkably fit.
[01:08:47.960 --> 01:08:49.240] God, it's how many years now?
[01:08:49.240 --> 01:08:52.600] 10 years ago, I was on a ketogenic diet for three years.
[01:08:52.600 --> 01:08:57.320] And the very end of that three-year period was when I kind of got back into cycling.
[01:08:57.320 --> 01:09:02.440] At my fittest as an adult cyclist, I was back eating a lot of carbohydrates.
[01:09:02.440 --> 01:09:08.840] But there was about a six to twelve month period when I was still in ketosis.
[01:09:08.840 --> 01:09:11.080] I was kind of getting back into cycling shape.
[01:09:11.080 --> 01:09:20.760] And I do have one VO2 max test from that window of time, probably six months after getting back to cycling and still on ketosis.
[01:09:20.760 --> 01:09:23.880] I've gone back and looked at the data, and they're very interesting.
[01:09:23.880 --> 01:09:30.920] What I would observe is maximum fat oxidation was 1.3 grams per minute.
[01:09:30.920 --> 01:09:33.960] And that occurred almost immediately.
[01:09:33.960 --> 01:09:37.240] And it sustained until...
[01:09:37.240 --> 01:09:42.040] So at the time my FTP was about 4.1 watts per kilo.
[01:09:42.040 --> 01:09:47.320] This would have been sustained until about 3.5 watts per kilo.
[01:09:47.320 --> 01:09:53.640] So at 3.5 watts per kilo, I was still oxidizing about 1.2 grams per minute.
[01:09:53.640 --> 01:09:55.960] And then that sort of fell off.
[01:09:55.960 --> 01:09:59.720] And glucose became then the dominant fuel source.
[01:09:59.720 --> 01:10:15.000] At the completion of the test, when I was done, you know, when I failed, I was obviously not oxidizing any fat, and glucose oxidation was just under six grams per minute, about six grams per minute, about 24 kcal per minute.
[01:10:15.280 --> 01:10:23.920] So, I've also seen this with another athlete who's been in ketosis for seven years, is a very fit cyclist.
[01:10:23.920 --> 01:10:27.680] Actually, he just sent me his data, and it's comparable.
[01:10:27.680 --> 01:10:29.280] In fact, he's much fitter than I was.
[01:10:29.280 --> 01:10:34.720] So, his 20-minute FTP test is about 412 watts for 20 minutes.
[01:10:34.720 --> 01:10:37.920] And surprisingly, he has decent glycolytic power.
[01:10:37.920 --> 01:10:45.520] So, that's the other thing: I never really had good power at the low end because I only cared about time trialing, so it didn't matter how many watts I could hold for two minutes or three minutes.
[01:10:45.520 --> 01:10:47.200] I only cared about one hour.
[01:10:47.200 --> 01:10:54.160] But this guy could still hold 1,200 watts for 15 seconds, even for three minutes.
[01:10:54.160 --> 01:10:57.520] He's north of 500 watts, 600 watts.
[01:10:57.520 --> 01:11:02.080] And again, fat oxidation is, you know, 1.5 grams per minute.
[01:11:02.080 --> 01:11:10.720] So, it becomes a bit confusing because it would be very difficult to define zone two by maximum fat oxidation.
[01:11:10.720 --> 01:11:13.360] So, ketosis is an extreme example.
[01:11:13.360 --> 01:11:26.640] But given how much RQ, respiratory quotient, the ratio of VCO2 to VO2, depends on baseline carbohydrate intake, how do we make the adjustment so that we understand and we're not being misled?
[01:11:26.640 --> 01:11:34.320] Because if you just looked at my data, you would dramatically overestimate my mitochondrial efficiency.
[01:11:34.320 --> 01:11:43.840] Is that a situation where you say, well, actually, the lactate, and unfortunately, I don't have lactate data from that test, so I can't tell you what my lactate levels were doing.
[01:11:43.840 --> 01:11:50.080] But it might not be a problem in the Peloton, because you're not going to be in ketosis if you're trying to win the Tour de France.
[01:11:50.080 --> 01:11:58.000] But we do see a great degree of carbohydrate and fat variation in the diet amongst people that we're trying to test.
[01:11:58.000 --> 01:11:59.440] How do you make that correction?
[01:11:59.640 --> 01:12:08.600] My humble opinion, what we see in these cases, because I see them all the time too, is that there's an artifact in the metabolic heart.
[01:12:08.600 --> 01:12:11.880] The metabolic heart measures gas exchange.
[01:12:11.880 --> 01:12:18.520] And then through the equations, it says, okay, this person must be burning fat or burning carbohydrates.
[01:12:18.520 --> 01:12:22.280] The equations are calibrated on high-carb diets, presumably.
[01:12:22.280 --> 01:12:30.200] Yeah, so the thing is, like, as you exercise, no matter what fuel you're using, you keep increasing oxygen consumption.
[01:12:30.200 --> 01:12:34.920] But if you don't have much carbohydrates, you're not going to produce much CO2.
[01:12:34.920 --> 01:12:47.400] So that's going to tweak or mislead my stoichiometric equation because the algorithm is going to think that, oh, whoa, he's using a lot of oxygen and not producing enough CO2.
[01:12:47.400 --> 01:12:49.720] So he's got to be burning a lot of fat.
[01:12:49.720 --> 01:12:53.240] That's when you see fats in north of one gram per minute.
[01:12:53.240 --> 01:12:54.920] Those are fat oxidations.
[01:12:54.920 --> 01:12:56.920] I think they're an artifact.
[01:12:56.920 --> 01:13:07.320] And I see this because three days later, when you change the diet of that person, three days later, that person's fat oxidation might be 0.35.
[01:13:07.640 --> 01:13:28.040] So there's no way that the mitochondria adjusts first, like it reflects a very high fat oxidation capacity in someone who we know very well, who is not an elite athlete, whose mitochondrial function is not incredibly high, to be able to oxidize so much fat and in three days reduces like by three or four times.
[01:13:28.040 --> 01:13:31.720] I attribute this to an artifact of the gas exchange.
[01:13:31.720 --> 01:13:36.600] And this is where looking at lactate, you should give you those parameters.
[01:13:36.600 --> 01:13:46.800] Normally, what I see in these individuals is that you see maximum lactates of two, three millimoles because simply they don't have carbohydrates.
[01:13:47.120 --> 01:13:54.800] Also, the thing when you see that, yeah, my maximum grams per minute of carbohydrates was in the six, but you're in ketosis.
[01:13:54.800 --> 01:14:02.160] So, how can you have enough glycogen or glycolytic capacity to elicit such a high carbohydrate production?
[01:14:02.160 --> 01:14:08.080] Even when you're in ketosis, remember my blood glucose is still four to five millimole.
[01:14:08.080 --> 01:14:21.520] I would really like to see this studied because, again, even if you're only eating 50 grams of glucose a day, think of how much glycogen you're making from all the glycerol, from all the fat that's being converted to ketone.
[01:14:21.520 --> 01:14:38.080] So, I mean, I think Jeff Volick and Steve Finney have looked at this, and when they put people into very, very strict ketosis but do muscle biopsies, they're still seeing 60% of the glycogen content in the muscle that was there under high carb conditions.
[01:14:38.080 --> 01:14:44.240] I mean, I think my capacity to oxidize five and a half to six grams of glucose per minute was still there.
[01:14:44.400 --> 01:14:47.520] Just took a long time to get there, I think, is the difference.
[01:14:47.520 --> 01:14:58.880] So, I guess the question is: if the VCO2 estimation is off because of the stoichiometric coefficients, do you think the VO2 estimation is off also?
[01:14:59.200 --> 01:15:05.200] No, I don't think so because, as you said very well, ketones are used for energy purposes.
[01:15:05.200 --> 01:15:10.480] And then we have a third element which is absolutely key in bioenergetics, which is glutamine.
[01:15:10.480 --> 01:15:13.760] Glutamine olycids are highly expressed and utilized.
[01:15:13.760 --> 01:15:16.960] We have learned that from ICU patients.
[01:15:16.960 --> 01:15:22.080] ISU patients is a great model to study metabolism or stress metabolism.
[01:15:22.080 --> 01:15:30.840] ICU patients, they utilize for wound healing about three times more glucose at rest than what we have.
[01:15:29.520 --> 01:15:32.200] And it's part of the healing process.
[01:15:32.360 --> 01:15:40.440] Glucose is instrumental for cell proliferation, wound healing, and part of it is lactate too as a byproduct in a signal molecule.
[01:15:40.440 --> 01:15:46.120] But we see that, and this is a study that we published, looking indirectly a methodology to look at glycogen.
[01:15:46.120 --> 01:15:49.240] It's a pilot study we did with ICU patients.
[01:15:49.240 --> 01:15:50.600] They don't have glycogen.
[01:15:50.600 --> 01:15:57.400] When you say they don't have glycogen, you mean liver glycogen, muscle glycogen, or depleted by how much?
[01:15:57.400 --> 01:15:58.760] Depleted to what level?
[01:15:58.760 --> 01:16:05.080] Let's say that you have 500 grams of glycogen if you have a full high carbohydrate diet.
[01:16:05.080 --> 01:16:08.760] So that might not be the case of someone entering the ICU.
[01:16:08.760 --> 01:16:16.120] First, because they might not be elite athletes or they might have maybe 300 grams or they might not have that adaptation to hold more glycogen.
[01:16:16.120 --> 01:16:18.840] So let's say they have 300 grams or so.
[01:16:18.840 --> 01:16:25.080] By the time they get into that condition, the body uses about three times the glucose at rest.
[01:16:25.080 --> 01:16:34.920] Now, an athlete used that same glucose, but at higher intensities, but only for a reduced amount of time, two hours, three hours, four hours.
[01:16:34.920 --> 01:16:37.960] Whereas the ICU patient is 24-7.
[01:16:37.960 --> 01:16:44.680] So eventually the body is going to run out of glycogen in the muscle or is going to be under huge stress.
[01:16:44.680 --> 01:16:50.520] The body has evolutionary mechanisms because it's a wonderful machine and it needs to continue.
[01:16:50.520 --> 01:16:54.920] So it increases another route, which is glutaminolysis.
[01:16:54.920 --> 01:16:58.120] So glutamine is an excellent source of fuel.
[01:16:58.120 --> 01:17:00.600] It enters directly the mitochondria.
[01:17:00.760 --> 01:17:11.640] We have seen in a publication that we're going to show when we publish it, is that when we inject mitochondria with glutamate, it's incredibly well oxidized.
[01:17:11.640 --> 01:17:15.120] And what's the source of glutamate in these ICU patients?
[01:17:14.840 --> 01:17:16.880] Are they breaking down muscle?
[01:17:17.200 --> 01:17:19.680] This is where cachexia comes into place.
[01:17:19.680 --> 01:17:29.760] We know that pretty much every single ICU patient becomes cachectic or suffers from muscle waste, and this is the syndrome, post-ICU muscle waste syndrome.
[01:17:29.760 --> 01:17:36.960] Why do they get cachectic or catabolic and why they overexpress tremendously levels of glutamine?
[01:17:36.960 --> 01:17:42.800] Because they need it for either enter the Krebs cycle for energy or for gluconeogenesis.
[01:17:42.800 --> 01:17:46.080] So this is one of the things that we learned a lot from ICU.
[01:17:46.080 --> 01:17:53.200] These ICU patients, they have hyperglycemia, yet they're not giving them usually because they have hyperglycemia.
[01:17:53.200 --> 01:17:59.680] It's true too that in the acute ICU phase, they also have insulin resistance.
[01:17:59.680 --> 01:18:08.320] But obviously this hyperglycemia and ICU doctors historically have seen this, like, whoa, this patient has hyperglycemia of the chart.
[01:18:08.320 --> 01:18:11.520] So obviously we're not going to give them IVs of glucose.
[01:18:11.520 --> 01:18:14.240] We're going to give more protein and glucose, I mean, and phytos.
[01:18:14.240 --> 01:18:18.640] And in fact, glutamine has shown that increased survival rate in these patients.
[01:18:18.640 --> 01:18:23.520] Where is this hyperglycemia coming from when you do not have glycogen?
[01:18:23.520 --> 01:18:32.160] It comes probably from proteolysis, where you break down protein from your muscles to release glutamine.
[01:18:32.160 --> 01:18:43.280] We would only know that if we understood hepatic glucose stores, because regardless of how much glycogen is in the muscle, it's never going to make its way into circulation because the muscle can't fully dephosphorylate it.
[01:18:43.280 --> 01:18:47.680] So do we have a sense of what the hepatic glycogen content is?
[01:18:47.680 --> 01:18:59.760] Because I can't imagine the body would ever let anything compromise that, given that if the liver can't produce glucose continuously, the brain dies.
[01:19:00.120 --> 01:19:03.320] So it might be that this is true, true, and unrelated, right?
[01:19:03.320 --> 01:19:14.600] It could be that the muscles are depleting glycogen because of high utilization, but the liver, through gluconeogenesis, has plenty of glucose.
[01:19:14.600 --> 01:19:21.800] That's what's making it into the circulation because of hypercortisalemia, because of other acute phase reactants.
[01:19:21.800 --> 01:19:28.440] And so we have hyperglycemia, but it's all being mediated by the liver, which has no trouble maintaining glycogen levels.
[01:19:28.440 --> 01:19:37.320] And again, from an evolutionary perspective, you much rather err on the side of hyperglycemia than hypoglycemia under a period of stress.
[01:19:37.320 --> 01:19:38.520] Absolutely, necessarily.
[01:19:38.520 --> 01:19:42.040] And that's, I think, what's the source of that gluconeogenesis?
[01:19:42.040 --> 01:19:45.480] It's probably glutaminolysis coming from the muscles.
[01:19:45.480 --> 01:19:52.520] So this is what my hypothesis, right, that those muscles, they eat themselves to feed themselves or to feed the rest of the body.
[01:19:52.520 --> 01:19:57.400] So that would suggest that exercising ICU patients would be important.
[01:19:57.400 --> 01:20:07.800] Getting some load-bearing resistance, even, of course, they're in a bed, but moving their extremities against a load, supplementing with amino acids, could actually improve outcomes.
[01:20:07.960 --> 01:20:08.600] Absolutely.
[01:20:08.600 --> 01:20:10.520] There's a lot of research in this area.
[01:20:10.520 --> 01:20:15.800] My colleague Paul Wishmeyer, who used to work here with me at the university, now he's in Duke.
[01:20:15.800 --> 01:20:18.760] He's doing a lot of research and practical work with that.
[01:20:18.760 --> 01:20:23.320] With this, it's like, yeah, this hyperglycemia probably comes from gluconeogenesis.
[01:20:23.320 --> 01:20:34.840] Going back to where we started, yeah, could be that there's a lot of glutamine released, you know, when you're also ketoacidosis state as well, especially in the first phases of that.
[01:20:34.840 --> 01:20:37.240] We know cortisol is very high at first.
[01:20:37.240 --> 01:20:49.040] The same thing that we see in ICU patients, that two main parameters that are predictors of mortality at the ICU is a hypercortisulinemia, high cortisol levels, and high lactate levels.
[01:20:45.000 --> 01:20:50.720] They both are completely related.
[01:20:50.960 --> 01:20:52.880] But, anyways, yeah, I think this is fascinating.
[01:20:52.880 --> 01:20:59.840] There's a great model to understand metabolism, stress metabolism of these patients and the ICU patients.
[01:20:59.840 --> 01:21:01.360] And that's the other thing, too.
[01:21:01.360 --> 01:21:20.800] Once you exercise, and this is a very important concept for people with type 2 diabetes, with type 1 diabetes, and hyperinsulinemia is that you have insulin resistance and you have difficulty to translocate, therefore, to translocate the glute 4 transporters to the surface of the muscle, the sarcolemma.
[01:21:20.800 --> 01:21:40.960] And we know that probably the first tissue or organ where diabetes debuts starts is the skeletal muscle, because about 80% of the carbohydrates that we have, they're oxidized in skeletal muscle, and because we're at rest, should be oxidized within the mitochondria of the skeletal muscle, that pyruvate.
[01:21:40.960 --> 01:21:43.360] This is what doing research and seeing it clearly.
[01:21:43.360 --> 01:21:49.040] But when you have insulin resistance, you cannot translocate those transporters.
[01:21:49.040 --> 01:21:56.480] Now, we have a second way to translocate those transporters that not many people know about, and that's muscle contraction.
[01:21:56.480 --> 01:22:03.280] This is the insulin-independent glucose uptake, which also seems to be heavily dependent on fitness.
[01:22:03.280 --> 01:22:13.120] The fittest athletes here require virtually no insulin to translocate glucose into the muscle through the insulin-independent pathway.
[01:22:13.120 --> 01:22:23.200] I think we may have even discussed this, I don't know, over dinner one night, but you look at the type 1 diabetics who are highly, highly active, require very little insulin.
[01:22:23.200 --> 01:22:23.920] Exactly.
[01:22:23.920 --> 01:22:29.800] This explains hypoglycemia in these patients shortly after they start exercising.
[01:22:29.360 --> 01:22:35.880] They might have something to eat and they inject themselves with insulin, and there's nothing you can do once you have insulin on board.
[01:22:36.200 --> 01:22:41.800] So that insulin is going to translocate those transporters and it's going to start bringing insulin inside.
[01:22:41.800 --> 01:22:42.840] I mean, sorry, glucose.
[01:22:42.840 --> 01:22:43.160] Thanks.
[01:22:43.160 --> 01:22:48.920] In the moment you start exercising, you do the same function through contraction of exercise, of the muscles.
[01:22:48.920 --> 01:22:57.080] So you have two mechanisms acting at the same time, pulling more glucose inside the cells, leading to hypoglycemia.
[01:22:57.080 --> 01:23:02.840] So this is what we learned a lot with persons with people with type 1 diabetes in exercise, and then we can prevent them.
[01:23:02.840 --> 01:23:11.160] So, for example, do not inject yourself before exercising, because exercise alone is going to take care of that glucose.
[01:23:11.160 --> 01:23:18.200] But we can take these concepts also with people with type 2 diabetes, that they have insulin resistance or pre-type 2 diabetes.
[01:23:18.200 --> 01:23:23.880] But like, why not exercise right after you eat that carbohydrate you have?
[01:23:23.880 --> 01:23:25.880] You have insulin resistance already.
[01:23:25.880 --> 01:23:29.320] But when you exercise, you're not going to need that insulin.
[01:23:29.320 --> 01:23:33.640] And yet, you can translocate those transporters and you bring glucose levels down.
[01:23:33.640 --> 01:23:38.280] And I'm sure that you see this all the time with your glucose sensor.
[01:23:38.280 --> 01:23:43.320] Yes, I've gone periods of time when I've done incredibly frequent lactate testing.
[01:23:43.320 --> 01:23:50.520] So lactate testing every 30 minutes for a day or something insane like that, which is incredibly expensive and incredibly painful in your fingers.
[01:23:50.520 --> 01:23:56.120] But you learn how much, for example, a meal impacts lactate.
[01:23:56.120 --> 01:24:02.440] So when I wake up in the morning, my resting lactate level varies.
[01:24:02.440 --> 01:24:06.280] I've been tracking this over a period of probably 40 days.
[01:24:06.280 --> 01:24:08.440] So 40 days of tracking.
[01:24:08.440 --> 01:24:14.320] What range do you think my morning resting lactate level has been over a 40-day period?
[01:24:14.200 --> 01:24:15.200] In the morning, first thing in the morning?
[01:24:15.920 --> 01:24:20.320] I would say neighborhood of 0.8 to 1.2, 1.3.
[01:24:20.320 --> 01:24:20.960] Pretty good guess.
[01:24:20.960 --> 01:24:24.480] So 0.3 to about 1.1.
[01:24:24.480 --> 01:24:27.120] But that's a pretty big variation.
[01:24:27.120 --> 01:24:31.520] And probably median level of about 0.8.
[01:24:31.520 --> 01:24:34.960] Yeah, in the neighborhood of wine, which is normally in a feed individual.
[01:24:34.960 --> 01:24:35.600] Yes.
[01:24:35.600 --> 01:24:46.880] So then what I can do is I can eat a very high carb breakfast and go and do a zone two ride, or don't eat anything at all and go and do a zone two ride.
[01:24:46.880 --> 01:24:49.040] Very different lactate performance curve.
[01:24:49.040 --> 01:24:52.560] So the high carb meal raises lactate.
[01:24:52.560 --> 01:25:11.840] So it becomes a bit of an artifact in a way, which now gets me to, we've talked about this at the level of the most precision possible, the way in which I would measure it in a patient, you would measure it in a world-class athlete where we have the ability to do indirect calorimetry and lactate testing.
[01:25:11.840 --> 01:25:16.960] But now I want to talk about it in the way that we train people, normal people.
[01:25:16.960 --> 01:25:28.400] So we've talked about this, call it difference between the lactate level that you measure in the blood, which is now heavily influenced by production and clearance.
[01:25:28.400 --> 01:25:34.320] And then we've talked about the gold standard, which would probably be fat oxidation, but even that can be confounded.
[01:25:34.320 --> 01:25:41.120] But let's take off the table the people who are consuming a high-fat, low-carbohydrate diet, because that confuses things a bit.
[01:25:41.120 --> 01:26:05.800] If I have a patient and I'm looking at their biometrics and we do a zone 2 test based on looking at their fat oxidation during an escalated test of part of a VO2 max test, and it comes back that their maximum fat oxidation, which is 0.3 grams per minute, occurs at a wattage of 1.5 watts per kilo.
[01:26:05.800 --> 01:26:07.400] That's a pretty average person.
[01:26:07.400 --> 01:26:14.520] And I say, I want that number higher, both the absolute number of fat oxidation, but where it occurs on the graph.
[01:26:14.520 --> 01:26:19.880] Now I want you in a year to be 2.5 watts per kilo.
[01:26:19.880 --> 01:26:22.200] Let's talk about two things.
[01:26:22.200 --> 01:26:27.560] One, how they should train, and that means duration, intensity, frequency, et cetera.
[01:26:27.560 --> 01:26:40.680] And secondly, what we should use as the readout to know we're in the right training zone, given that they won't be able to train daily or weekly or whatever frequency with indirect calorimetry.
[01:26:40.680 --> 01:26:47.960] And by the way, let's assume that some people will want to use the point of care lactate meters and some people will not.
[01:26:47.960 --> 01:26:53.160] Let's start with what's our surrogate for training zone, starting with what we knew.
[01:26:53.160 --> 01:27:00.920] So we learned that 1.5 watts per kilo was maximum fat oxidation, but we want to increase that to 2.5.
[01:27:00.920 --> 01:27:04.040] So what metric do you use to train them?
[01:27:04.040 --> 01:27:13.960] Normally what I do is like starting with the metabolic test, I translate that information into whether it's watts or speed or heart rate.
[01:27:13.960 --> 01:27:16.680] All of them normally they correlate quite well.
[01:27:16.680 --> 01:27:18.120] And you can individualize it.
[01:27:18.120 --> 01:27:19.720] There are people that don't have a power meter.
[01:27:19.720 --> 01:27:24.840] Okay, you can do heart rate, for example, or people that just obviously run or they walk.
[01:27:24.840 --> 01:27:27.000] You can do speed or heart rate as well.
[01:27:27.000 --> 01:27:27.960] Very good surrogate.
[01:27:27.960 --> 01:27:30.520] So that's the first metric, the surrogate.
[01:27:30.520 --> 01:27:39.880] Then it's about, at least from my experience, the three main principles that I've learned over the years and how to apply this.
[01:27:39.880 --> 01:27:42.600] So first is frequency.
[01:27:42.600 --> 01:27:46.480] Before we go to the frequency and the duration, I do want to go back and ask you another question.
[01:27:46.800 --> 01:27:53.840] We have some patients who don't want to use a lactate meter, either because it's cumbersome or somewhat intimidating.
[01:27:53.840 --> 01:27:59.680] We also add another metric, which is relative perceived exertion, RPE.
[01:27:59.680 --> 01:28:06.880] I'll tell you what my rule of thumb is, but I'd like you to sharpen it, refine it, throw it out, make it better, whatever.
[01:28:06.880 --> 01:28:25.760] I tell patients based on my experience, so I don't know how extrapolatable that is, when I'm in zone two, as confirmed by lactate levels, so call it 1.7 to 1.9 millimole, which is what I target, I can carry out a conversation, because I do most of mine on a Wahoo kicker.
[01:28:25.760 --> 01:28:27.680] I put my bike on a Wahoo kicker.
[01:28:27.680 --> 01:28:34.560] I can spend the entire 45 minutes on a phone call, but it's not as comfortable as this discussion here.
[01:28:34.560 --> 01:28:36.480] I'm a little more strained.
[01:28:36.480 --> 01:28:42.640] But if I can't talk, if I feel like I can't talk, I'm too high in the intensity.
[01:28:42.640 --> 01:28:52.320] Do you think that that's a reasonable surrogate for people to use across the spectrum of not particularly fit all the way up to pogacha?
[01:28:52.320 --> 01:28:53.680] 1,000%.
[01:28:53.680 --> 01:29:01.280] And I use the same metrics also with people who you mentioned they don't want to do a lactate meter or they don't have access.
[01:29:01.280 --> 01:29:07.440] I get hundreds of emails about where can I do this test or is there anything that I can do?
[01:29:07.440 --> 01:29:08.880] And I agree 100%.
[01:29:08.880 --> 01:29:19.600] With everything that we know at the granular cellular level, by injecting fuels and sustrays directly into the matter conditions, we cannot get more cellular level and scientific than that.
[01:29:19.600 --> 01:29:23.360] The surrogate or the perceived exertion, it works beautifully.
[01:29:23.360 --> 01:29:30.760] I know that people are coming up with different algorithms based on Harris variability or DFA, one alpha, et cetera.
[01:29:29.840 --> 01:29:32.920] But honestly, I agree 100% with you.
[01:29:33.160 --> 01:29:40.360] I always tell people: if you can exercise, whatever the exercise you do, and maintain a conversation like you and I are doing, you're way too easy.
[01:29:40.360 --> 01:29:42.040] You're probably zone one.
[01:29:42.040 --> 01:29:45.240] If you can talk, but it's some form of strain.
[01:29:45.240 --> 01:29:50.200] You can talk for two hours, but we're talking a little bit like that.
[01:29:50.200 --> 01:29:51.800] You're just at that threshold.
[01:29:51.800 --> 01:29:57.720] Put it this way: the other litmus test I tell people is the person on the other end will know you are exercising.
[01:29:57.720 --> 01:29:58.360] Exactly.
[01:29:58.360 --> 01:30:01.640] You will not be able to mask from them that you are exercising.
[01:30:01.640 --> 01:30:02.360] Exactly.
[01:30:02.360 --> 01:30:07.880] And in fact, I have many conference calls with people that I know to be respectful, but I do it on the bike.
[01:30:07.880 --> 01:30:13.320] They call me and I'm on the bike, either outside or in the trainer, and they tell me, you're exercising, right?
[01:30:13.320 --> 01:30:14.600] Because you can feel it.
[01:30:14.600 --> 01:30:20.280] But yet, I can maintain a full hour meeting on the bike without bothering the other person because they can understand me.
[01:30:20.280 --> 01:30:29.400] But instead, if you cross to the point where you cannot maintain that conversation, you need to breathe much faster because you're producing more CO2.
[01:30:29.400 --> 01:30:39.240] And that's probably because you're already transitioning from the slow twitch muscle fibers to the fast twitch muscle fibers, more glycolytic, more lactate, more CO2, more buffering capacity.
[01:30:39.240 --> 01:30:42.840] So it seems old school, but it works beautifully.
[01:30:42.840 --> 01:30:43.400] Agreed.
[01:30:43.400 --> 01:30:48.120] And the other thing I do, because I really like people to triangulate and give them a starting point.
[01:30:48.120 --> 01:30:55.880] So if someone has not done a metabolic test yet, and that's usually the case, by the way, is that we're starting with just a zone two training protocol.
[01:30:55.880 --> 01:30:58.280] I also give them some ranges on heart rate.
[01:30:58.280 --> 01:31:00.520] Now, here I have found much more variability.
[01:31:00.520 --> 01:31:09.320] So the first thing I say is to do this, you do need to know your maximum heart rate, not your predicted maximum heart rate, but your actual achieved maximum heart rate.
[01:31:09.320 --> 01:31:19.440] In my experience, personally, my zone two is actually at about 78 to 81% of my maximum heart rate.
[01:31:19.440 --> 01:31:23.440] But I know that for less trained people, it's lower.
[01:31:23.440 --> 01:31:37.120] So I tell people a broad range of 70 to 80% of your realized maximum heart rate is a good place to start and then make adjustments based on relative perceived exertion.
[01:31:37.120 --> 01:31:38.000] I agree.
[01:31:38.000 --> 01:31:39.760] What do you know about heart rate?
[01:31:39.760 --> 01:31:45.120] I would agree that I usually also say the same thing somewhere between 70 to 80.
[01:31:45.120 --> 01:31:49.120] That being said, right, if you want to be very, it's a big range, exactly.
[01:31:49.120 --> 01:31:57.520] So you can be at 70, let's say at 1.7 millimoles, and then at 80, you can be at 5 millimoles.
[01:31:57.520 --> 01:31:59.040] You're completely away from one zone.
[01:31:59.040 --> 01:32:00.480] But as you said, it's a good starting point.
[01:32:00.480 --> 01:32:07.600] And as you very well said, and I agree 100% with you is like, yeah, then you tweak it with your perceived exertion.
[01:32:07.600 --> 01:32:14.400] The other thing, too, with the heart rate, and this is where the heart rate variability, there are different interpretations.
[01:32:14.400 --> 01:32:20.240] So the modern interpretation of the heart rate variability is the differences between bit to bit.
[01:32:20.240 --> 01:32:22.560] And that's where there are different algorithms.
[01:32:22.560 --> 01:32:31.040] For me, the heart rate variability, it's more at a broader spectrum and it's more on adrenergic activation that you have.
[01:32:31.040 --> 01:32:33.680] So for example, you're fatigued today.
[01:32:33.680 --> 01:32:39.680] First of all, normally you're going to wake up with your resting heart rate a little bit higher than normally.
[01:32:39.680 --> 01:32:46.080] If your normal heart rate, let's say it's 50, and you're being fatigued, you might wake up with 65.
[01:32:46.080 --> 01:32:49.120] So that alone is a heart rate variability concept.
[01:32:49.120 --> 01:32:52.000] It varies from the norm to one day.
[01:32:52.000 --> 01:32:54.640] So that's our red flag that you might be tired that day.
[01:32:54.720 --> 01:32:59.480] Might not be super sensitive, but it is very sensitive for elite athletes, without a doubt.
[01:32:59.120 --> 01:33:02.600] The second aspect is like when you go out there and exercise.
[01:33:02.920 --> 01:33:11.960] As you might see, there are days that you're like 130 bits per minute, whatever you think your zone 2 is 130, 138, for example.
[01:33:11.960 --> 01:33:15.800] But some days it's really hard to get that heart rate.
[01:33:15.800 --> 01:33:20.440] You're already struggling at 110 bits per minute or 115 bits per minute.
[01:33:20.440 --> 01:33:21.960] Where that's not the norm.
[01:33:21.960 --> 01:33:23.320] That's another deviation.
[01:33:23.320 --> 01:33:25.240] That's a variability of the heart.
[01:33:25.320 --> 01:33:32.040] So this is what I've been historically used for heart rate variability, which tells me a lot more information.
[01:33:32.040 --> 01:33:34.200] This is what all the athletes also tell you.
[01:33:34.200 --> 01:33:37.000] Like, man, my heart rate doesn't get up today.
[01:33:37.320 --> 01:33:38.520] You see on training peaks.
[01:33:38.520 --> 01:33:45.480] You know, you see when someone is fatigued, they do an interval and they know they're always 180, 185, let's say, the lack of threshold.
[01:33:45.480 --> 01:33:48.840] And today they cannot get up until more than 170.
[01:33:48.840 --> 01:33:55.240] You see in the competition, the first week of the Tour de France, the maximal heart rate, let's say it's 195.
[01:33:55.240 --> 01:33:58.440] Last week, the maximal heart rate is 170.
[01:33:58.760 --> 01:34:01.080] That's what I interpret by heart rate variability.
[01:34:01.080 --> 01:34:05.160] And I know that a lot of people might criticize me because, oh, that has nothing to do with...
[01:34:05.160 --> 01:34:07.240] No, I think it's macro versus micro.
[01:34:07.240 --> 01:34:07.960] I agree.
[01:34:07.960 --> 01:34:09.800] I read it as macro versus micro.
[01:34:09.800 --> 01:34:13.080] I'll share with you an interesting self-experiment I've done a couple of times.
[01:34:13.080 --> 01:34:15.560] It's not pleasant, but it's interesting.
[01:34:15.560 --> 01:34:23.480] If I take a huge dose of a beta blocker, and the only beta blocker you can do this with, if you have low blood pressure, as I do, you have to be careful.
[01:34:23.480 --> 01:34:30.360] But propranolol is fine because it really disproportionately lowers heart rate, but not blood pressure.
[01:34:30.360 --> 01:34:44.040] But I've done this experiment a few times to test an idea, which is: would taking all of the gas out of my heart rate allow me to push harder and generate a higher zone 2?
[01:34:44.040 --> 01:34:45.840] And it turns out it does.
[01:34:45.840 --> 01:34:49.200] So my zone two is just under three watts per kilo.
[01:34:44.840 --> 01:34:51.680] I really want to talk with you about getting over three watts per kilo.
[01:34:51.760 --> 01:34:56.880] I'm still furious because in July, remember, I was at 2.95.
[01:34:56.880 --> 01:34:59.360] I was just kissing on the door of three.
[01:34:59.360 --> 01:35:04.720] I've come back, you know, I'm now at about 2.75 to 2.85, so I've lost a bit.
[01:35:05.040 --> 01:35:06.320] Aging, too.
[01:35:06.960 --> 01:35:08.880] We're going to talk about training in a moment.
[01:35:08.880 --> 01:35:12.080] So, and for me, I'm at that upper end of maximum heart rate.
[01:35:12.080 --> 01:35:16.240] So, I'm going to be doing that at about 80, 81% of maximum heart rate.
[01:35:16.240 --> 01:35:30.000] But if I took propranolol, 60 milligrams of a time-release propranolol, I will be able to get over 3 watts per kilo, and I'll do it at a heart rate of 68% of maximum.
[01:35:30.000 --> 01:35:31.680] But it feels horrible.
[01:35:31.680 --> 01:35:33.760] I feel like I'm going to die.
[01:35:33.760 --> 01:35:37.680] It is the worst feeling in the world.
[01:35:37.680 --> 01:35:39.040] And it's not pain.
[01:35:39.040 --> 01:35:43.680] I don't know how to explain it other than it feels like what it feels like when you're overtrained.
[01:35:43.680 --> 01:35:45.840] It feels like you just can't get moving.
[01:35:45.840 --> 01:35:54.880] It's like an engine that's being taken from 9,000 RPM to 6,000 RPM, but yet somehow is able to generate the horsepower.
[01:35:54.880 --> 01:35:56.320] But it just doesn't feel right.
[01:35:56.320 --> 01:36:00.640] So that's my drug-cheating way to get over 3 watts per kilo.
[01:36:00.640 --> 01:36:02.000] But more to illustrate the point, right?
[01:36:02.000 --> 01:36:06.960] Which is when you put the governor on heart rate, you can get there at a lower heart rate.
[01:36:06.960 --> 01:36:08.880] Subjectively, it's a miserable feeling.
[01:36:08.880 --> 01:36:14.800] Yeah, and this is kind of in a way what happens when you're fatigued, when you don't have enough fuel.
[01:36:14.800 --> 01:36:20.960] Again, going back to like my heart doesn't get up today, and I'm struggling if you were taking some better blocker.
[01:36:20.960 --> 01:36:23.920] But the thing is that it has to do a lot with fuel.
[01:36:23.920 --> 01:36:27.280] For example, and I experiment this a lot too.
[01:36:27.280 --> 01:36:48.200] I try to understand how this works, so I do maybe intermittent fasting for a few days and I go out there and good at adjusting at that and I cannot do that I know others can do it and I admire that but I can see my heart rate right away when you don't have enough glycogen storages it's very possible that adrenaline activity is decreased.
[01:36:48.200 --> 01:36:58.280] You need to break down glycogen and we know that what it takes to break down glycogen is forcephorylase in the muscle and that's directly regulated by catecholamines.
[01:36:58.280 --> 01:37:02.440] So when there's a decrease in glycogen, this is my hypothesis, right?
[01:37:02.440 --> 01:37:09.560] When there's a decrease in glycogen storages, because of the evolutionary mechanisms that humans have, the brain is the boss.
[01:37:09.560 --> 01:37:17.560] The brain says, like, I don't care about your legs, but don't use up all the glycogen because you have to give me, and the liver has to give me glycogen as well.
[01:37:17.560 --> 01:37:23.880] So I'm not going to shut you down completely of breaking down glycogen, but I'm going to slow you down.
[01:37:23.880 --> 01:37:29.080] So I'm going to release less catecholamine so that you break down less glycogen.
[01:37:29.080 --> 01:37:36.200] The collateral effect of that is the heart because the heart contractility is regulated by catecholamines as well.
[01:37:36.200 --> 01:37:41.160] So this is why using that, my version of heart rate variability, it's quite useful.
[01:37:41.160 --> 01:37:48.680] I've been using it incredibly successfully for 25 years with my athletes where I see that, hey, your heart rate is not going up today.
[01:37:48.680 --> 01:37:55.000] And usually it's 185, 190, for example, when you do a lactic threshold, for example, and today it was 170.
[01:37:55.000 --> 01:38:04.760] So tomorrow, take it easy or pile up on glycogen, I mean on carbohydrates, or take it easy day, and you see how you're going to be very responsive the next day, the following day.
[01:38:04.760 --> 01:38:06.360] And in fact, that's what happens.
[01:38:06.360 --> 01:38:10.040] I would say 10 out of 10 times, but let's say 9 out of 10 times, right?
[01:38:10.040 --> 01:38:12.040] But I do that with myself as well.
[01:38:12.040 --> 01:38:20.800] And I see also I work a lot with the head, you think a lot, and the brain uses about 100 to 125 grams of glucose daily.
[01:38:21.120 --> 01:38:30.960] When you go, and I don't know that fact, when you work a lot of hours and thinking and thinking and thinking and stressed, the brain might need a lot more glucose.
[01:38:30.960 --> 01:38:39.280] So that's training your glycogen storages from the brain, probably, and even from the muscles, because the muscle can release glucose to be utilized as well.
[01:38:39.280 --> 01:38:39.840] Yes.
[01:38:39.840 --> 01:38:48.000] The muscle has phosphorylase and can be degraded to glycogen, and that glucose can go to the circulation as well to feed other organs.
[01:38:48.000 --> 01:38:51.680] I didn't realize that we had glucose 1-phosphatase in the muscle.
[01:38:51.680 --> 01:38:55.280] I thought the muscle glycogen fate was sealed in the muscle.
[01:38:55.280 --> 01:38:55.920] It's possible.
[01:38:55.920 --> 01:38:56.880] There are a few studies.
[01:38:56.880 --> 01:38:58.400] I'm happy to send them to you.
[01:38:58.400 --> 01:39:06.240] I cannot refer them out of memory, but the muscles can also release glucose to and export glucose.
[01:39:06.480 --> 01:39:10.640] I assume this is a relatively small amount compared to what the liver is doing.
[01:39:10.640 --> 01:39:12.320] Yeah, absolutely, exactly.
[01:39:12.320 --> 01:39:13.920] But it's possible too.
[01:39:13.920 --> 01:39:21.840] So those days where I'm thinking a lot and I'm very stressed and I'm not dieting or anything, I just go out there and I'm dead.
[01:39:21.840 --> 01:39:24.800] And I'm sure that many people listening to this feel the same way.
[01:39:24.800 --> 01:39:26.880] Like, what the hell is going on today?
[01:39:26.880 --> 01:39:28.800] I don't have energy at all today.
[01:39:29.120 --> 01:39:32.160] And you will see that your heart rate doesn't get up those days.
[01:39:32.160 --> 01:39:36.480] And you can get to that by just training five hours a week or seven hours a week.
[01:39:36.480 --> 01:39:41.120] And sometimes people say, Look, I cannot be overtrained because I only train five hours a week.
[01:39:41.120 --> 01:39:43.120] Yeah, but you're overworked.
[01:39:43.120 --> 01:39:45.440] That's a big artifact with your training.
[01:39:45.440 --> 01:39:53.760] That's what most of us are aspire to pre-retire before 60, you know, so we can have more time to exercise and less time to work.
[01:39:53.760 --> 01:39:55.160] But yeah, that's what I do this.
[01:39:54.960 --> 01:39:57.200] This I take a day off completely.
[01:39:57.200 --> 01:39:58.320] I sleep more.
[01:39:58.320 --> 01:40:00.760] I increase my carbohydrate intake.
[01:40:00.760 --> 01:40:05.160] And the following day, I can even break my PR and a climb or something.
[01:39:59.920 --> 01:40:06.680] I feel like a million dollars.
[01:40:07.000 --> 01:40:10.040] So resting recovery is key for that.
[01:40:10.040 --> 01:40:22.760] I think that's a very important point, and it's actually something I've only been able to pay attention to in the last year, which is I used to judge my performance by training load.
[01:40:22.760 --> 01:40:24.520] I used to use training peaks when I was training.
[01:40:24.520 --> 01:40:25.240] I don't anymore.
[01:40:25.240 --> 01:40:33.880] But the concepts of acute and chronic training balance, any day that was suboptimal could be explained by training volume in some capacity.
[01:40:33.880 --> 01:40:36.360] But now, my training volume is relatively low.
[01:40:36.360 --> 01:40:38.200] It's 10 hours a week of total training.
[01:40:38.200 --> 01:40:40.200] That's both cardio and strength.
[01:40:40.200 --> 01:40:41.880] This is not a lot of training.
[01:40:41.880 --> 01:40:46.520] And yet, when I'm under stress, work-wise, I'm just doing too much.
[01:40:46.600 --> 01:40:47.960] I don't even use the word stress.
[01:40:47.960 --> 01:40:50.280] It has a real negative connotation to it.
[01:40:50.280 --> 01:41:09.400] I just mean when I'm overworked, when I'm doing too much, my performance, I have to either adjust my parameters for what I deem successful, or I just have to cut back on the actual training a little bit to make time for more sleep or more relaxation.
[01:41:09.400 --> 01:41:12.840] So I think that's a very important point that is easily lost.
[01:41:12.840 --> 01:41:16.920] So we've got a very good handle on the metrics we're going to be using.
[01:41:16.920 --> 01:41:19.960] So now let's talk about two scenarios.
[01:41:19.960 --> 01:41:23.480] The first is the person who is new to this type of training.
[01:41:23.480 --> 01:41:33.160] So they've listened to this podcast, or they're one of my patients, and I've made the case convincingly to them that you really need to do this type of training.
[01:41:33.160 --> 01:41:37.240] I want to come back, by the way, to a justification for that.
[01:41:37.240 --> 01:41:42.280] So let's explain why high-intensity training is not sufficient, but we'll park that for a moment.
[01:41:42.280 --> 01:41:45.000] But they really don't have much of a background in this type of training.
[01:41:45.280 --> 01:41:55.040] Maybe they do some high-intensity training, they do some weights, they play some tennis, but they really don't do the sort of steady-state, sustained cardio that we're talking about.
[01:41:55.040 --> 01:41:59.600] How would you structure a training program in dose, duration, frequency?
[01:41:59.600 --> 01:43:43.800] for that individual and tell me a little bit about the choices that you would make if they're agnostic to running walking cycling rowing swimming i have my biases there but i want to kind of hear what you have to say about it i want to apologize to many of your audience because i get a lot of emails asking me about these questions and it's hard to keep up well that's why we're doing the podcast so you don't have to apologize it's easier to do it this way i appreciate it this way but see i get emails and before i used to see people here at the university but now the university don't have these services trying to convince them that these services are important to offer to population but anyways i want to apologize because i cannot answer to everybody i have the three main rules or parameters that i have learned over the years so one is the duration we have in mind sometimes that this is like endurance training long days like i only have it six hours a week or seven hours a week at most to do this type of training or less there's no way i can do that it's usually less because they might have six hours a week for total exercise and we're going to take half of that for strength training exactly which is very important as you know it's where i fail because i i should do more of that and i try to get a little bit more of time to do that it's not easy but i aspire really to dial that in but yeah you're right they might have less than six hours and they might think like well i'm not an endurance athlete so you need to do four hours to accomplish this so therefore i'm just going to move to do just high intensity and just get out of the way that's not completely true you can accomplish very important mitochondrial adaptations and very important metabolic adaptations by exercising one hour Let's start by the duration.
[01:43:43.800 --> 01:43:48.600] If you try to do that one hour to one hour and a half range, you're on target.
[01:43:48.600 --> 01:43:50.680] Is that total or one setting?
[01:43:50.680 --> 01:43:58.280] Meaning, is it one to one and a half hours per week or does that need to be in one continuous exercise bout?
[01:43:58.280 --> 01:44:06.840] So the frequency that I see is that this type of training ideally needs to be done between three to four days a week, ideally.
[01:44:06.840 --> 01:44:08.440] And how can I know this?
[01:44:08.440 --> 01:44:12.280] I know this because I've seen in the laboratory everything.
[01:44:12.280 --> 01:44:19.480] The person who trains one day at these zones or two days or three days or four days or high intensity, low intensity, and I see the adaptations.
[01:44:19.480 --> 01:44:20.840] How do I see the adaptations?
[01:44:20.840 --> 01:44:26.440] Again, looking at fat oxidation, lactate cleanse capacity, all surrogates of mitochondrial function.
[01:44:26.440 --> 01:44:29.400] I've been identifying the dose of that training.
[01:44:29.400 --> 01:44:36.360] So if you train once a week, there, chances are that you're going to deteriorate over time, and especially as we age.
[01:44:36.360 --> 01:44:48.600] Something that I see, for example, in high-intensity exercisers and bodybuilders, they have a very poor mitochondrial function compared to people who do more a little bit of everything.
[01:44:48.600 --> 01:44:50.760] So one day a week is not going to work.
[01:44:50.760 --> 01:44:54.200] Two days a week, it might maintain what you have.
[01:44:54.200 --> 01:44:58.440] But if you're new to an exercise program, it might not be enough.
[01:44:58.440 --> 01:45:02.120] Three days a week, now we're starting to see for sure.
[01:45:02.120 --> 01:45:08.360] Four days a week, now we're talking ideally five days a week or six, but not everybody has obviously six days a week to train.
[01:45:08.360 --> 01:45:11.000] But I think that you are a very busy guy.
[01:45:11.000 --> 01:45:12.280] I'm a very busy guy.
[01:45:12.280 --> 01:45:22.240] Try to squeeze four or five days a week, maybe six in the summer, but four or five days is achievable for most individuals and put aside an hour to an hour and a half.
[01:45:22.560 --> 01:45:25.280] So I would say that four days a week is ideal.
[01:45:25.280 --> 01:45:26.800] That's the first principle.
[01:45:26.800 --> 01:45:28.880] The second principle is the duration.
[01:45:28.880 --> 01:45:39.120] Going back to what I was saying, with one hour, maybe Pogatsra needs four hours, five hours, to keep increasing those huge mitochondria for a long time.
[01:45:39.120 --> 01:45:57.840] But a meromortal, especially someone who might be pre-diabetic or might be out of fitness or hasn't exercised in a long time, or someone who coming from a disease or a mother who just had a baby and has been out of say for a while, one hour, if you walk or if you run, might be very, very good for you.
[01:45:57.840 --> 01:46:00.800] One hour walk or run, you might have to bring it up.
[01:46:00.800 --> 01:46:02.400] That's part of the plan too.
[01:46:02.400 --> 01:46:04.800] You cannot start off the bat with one hour.
[01:46:04.800 --> 01:46:09.120] You might start by 20 minutes, 30 minutes, 40 minutes, increasing it, but maybe about an hour.
[01:46:09.120 --> 01:46:14.480] And if you bike, for example, about an hour, 20 minutes, hour and a half.
[01:46:14.480 --> 01:46:19.520] That's what I see that if you do that for four days a week, things are starting to move.
[01:46:19.520 --> 01:46:26.720] Even if you bike on a trainer where you can be much more efficient and you can really get straight to the wattage and stay there.
[01:46:26.720 --> 01:46:37.520] We tell patients, again, it depends where they are in their cycle, but if they're starting out, I mean, we'll be happy if they give us 30 minutes, three to four times a week of dedicated exercise.
[01:46:37.520 --> 01:46:39.600] I can't do zone two on the road.
[01:46:39.600 --> 01:46:41.520] I can really only do it on the trainer.
[01:46:41.520 --> 01:46:48.480] I just can't stay at a constant level on the road with starting and stopping and wind and hills and stuff like that.
[01:46:48.480 --> 01:46:49.360] That's a very good point.
[01:46:49.360 --> 01:46:55.840] That's why an hour and a half on the bike, it might actually be one hour or so because you have all these artifacts.
[01:46:55.840 --> 01:46:59.200] But you're right, when you're on the trainer, you isolate everything completely.
[01:46:59.200 --> 01:47:02.840] And what I also recommend is about an hour if you can get there.
[01:47:02.840 --> 01:47:09.560] But again, you know, like, yeah, sure, you might, to me, it's it feels like a torture sometimes to be an hour on the trainer.
[01:47:09.560 --> 01:47:10.280] I hate it.
[01:47:10.280 --> 01:47:13.160] I like to be outside, but we have had to do it.
[01:47:13.160 --> 01:47:13.640] I do it.
[01:47:13.640 --> 01:47:16.280] I watch a movie or just catch up on work.
[01:47:16.280 --> 01:47:22.280] I have one with special desks where I can type or read articles or answers and emails.
[01:47:22.280 --> 01:47:27.000] Low-key activity because, again, you know, you're not very sharp to think very intellectually.
[01:47:27.000 --> 01:47:28.760] But yeah, one hour might do the trick.
[01:47:28.760 --> 01:47:37.720] What I've seen is like, yeah, in those people who haven't done much at all, even 30 minutes, 20 minutes might start moving the needle, but eventually it's not enough.
[01:47:37.720 --> 01:47:40.040] Those the body needs more.
[01:47:40.040 --> 01:47:47.640] If you can get to a goal about an hour to an hour and a half, that should really work, in my modest opinion, in my experience.
[01:47:47.640 --> 01:47:49.320] So that's the duration.
[01:47:49.320 --> 01:47:54.040] And the third is always the frequency, which we have talked about, which is usually the zone two.
[01:47:54.040 --> 01:48:02.280] That being said, I think that it's also important to stimulate other energy systems like the glycolytic system.
[01:48:02.280 --> 01:48:05.320] And again, continue with the model that we do with elite athletes.
[01:48:05.320 --> 01:48:14.040] People think that elite athletes, whatever the sport are, all they do is high intensity all the time and intervals, intervals.
[01:48:14.040 --> 01:48:15.720] And it's the exact opposite.
[01:48:15.720 --> 01:48:27.240] If you look at the workload of an elite athlete, whether that elite athlete is, especially in individual sports, it's easier to see this, whether it's a triathlete or a cyclist or a marathon runner or a swimmer.
[01:48:27.240 --> 01:48:29.720] A hundred meter swimmer is under a minute.
[01:48:29.720 --> 01:48:31.560] Maximal exercise.
[01:48:31.560 --> 01:48:33.880] If you look at the workload, it's very similar.
[01:48:33.880 --> 01:48:37.240] The majority of the sessions are in the lower intensity.
[01:48:37.240 --> 01:48:39.320] They're not intervals, intervals, intervals.
[01:48:39.320 --> 01:48:48.640] And I always say, we cannot be so naive to think that the best coaches and athletes in the world haven't figured this out when they're always trying new things and they want to try the cut and edge things.
[01:48:48.960 --> 01:48:53.760] Obviously, they have said, oh, our sport is swimming under a minute.
[01:48:53.760 --> 01:48:57.280] All we need to do is like intervals, intervals, intervals, intervals.
[01:48:57.280 --> 01:49:05.040] Well, if you look at what swimmers do, they train, and if you ask Michael Phelps, hours and hours and hours and hours and hours.
[01:49:05.040 --> 01:49:19.280] Because if you can travel through the competition in that under a minute with a slightly better function to clear lactate, even if it's one millimole or less, the muscle contractual force might be improved.
[01:49:19.280 --> 01:49:24.800] So all the hours and hours and hours might be that just to improve a fraction of a second.
[01:49:24.800 --> 01:49:35.280] But anyway, so this is what I'm saying: that these concepts of glycolytic capacity and high-intensity training, they're necessary, but they're not what the elite athletes do.
[01:49:35.280 --> 01:49:39.760] The elite athletes have the best metabolic function of any humans.
[01:49:39.760 --> 01:49:43.920] Why not try to imitate their philosophy of exercise?
[01:49:44.240 --> 01:49:52.640] And so, just to come back to the frequency duration question, I think the answer to the following question is going to be the more frequent training sessions.
[01:49:52.640 --> 01:50:10.480] But if you compared four training regimens that were four hours a week each, one of them would be four 60-minute sessions, one of them would be three 80-minute sessions, one of them would be two two-hour sessions, and then one of them would be one four-hour session.
[01:50:10.480 --> 01:50:23.200] So it's the same total volume, and notwithstanding the brain damage of one four-hour session, is it safe to say that the four 60-minute sessions, because it's a higher frequency, would be the optimal one there?
[01:50:23.520 --> 01:50:24.320] I would say so.
[01:50:24.640 --> 01:50:27.200] I think from my experience that it might be better.
[01:50:27.200 --> 01:50:28.160] It's the frequency.
[01:50:28.160 --> 01:50:37.720] It's like if you take a medication, if you take a medication twice the dose and only three days a week, might not work as well as if you take the right dose every day.
[01:50:37.720 --> 01:50:42.200] Because at the end of the day, we're talking about the whole exercise as medicine, right?
[01:50:42.200 --> 01:50:43.480] How do we prescribe that?
[01:50:43.480 --> 01:50:44.360] What's the dose?
[01:50:44.360 --> 01:50:45.240] What's the frequency?
[01:50:45.400 --> 01:50:49.160] I'm assuming that you will have to take it as many days as possible.
[01:50:49.320 --> 01:50:51.640] I would say that it's better to do that.
[01:50:51.640 --> 01:51:00.120] That being said, obviously, if you have the weekend and you have the possibility, which I don't have, to do three hours, go ahead.
[01:51:00.120 --> 01:51:05.320] And another thing I wanted to point out is that for many people, they need that adrenaline for training.
[01:51:05.320 --> 01:51:07.160] So other people don't care.
[01:51:07.160 --> 01:51:09.160] Other people say, whoa, I love this.
[01:51:09.160 --> 01:51:11.640] I don't like to kill myself into high-intensity.
[01:51:11.640 --> 01:51:14.920] But I think you need to do some high-intensity, right, at some point.
[01:51:14.920 --> 01:51:15.800] I want to talk about that.
[01:51:15.800 --> 01:51:18.360] So how do we bring in the other energy systems?
[01:51:18.360 --> 01:51:35.560] Of the four pillars of exercise in my world, stability, strength, low-end aerobic, which I describe really as talk about it as kind of mitochondrial efficiency, and then high-end aerobic, which is peak aerobic capacity slash anaerobic performance.
[01:51:35.560 --> 01:51:42.120] So anaerobic power, peak aerobic, low-end aerobic, mitochondrial efficiency, strength stability.
[01:51:42.120 --> 01:51:54.200] Of those four, I, for some reason, struggle to make the time for the peak aerobic, in part because, one, it's the least enjoyable, if we're going to be brutally honest.
[01:51:54.200 --> 01:51:56.680] If you're doing it right, it hurts the most.
[01:51:56.680 --> 01:52:00.760] It's also no longer as relevant because I don't compete at anything.
[01:52:00.760 --> 01:52:12.760] I actually really enjoyed that type of training when I competed because you have to spend time in that energy system and you see the rewards of 60 minutes of repeating two-minute intervals or something like that.
[01:52:12.760 --> 01:52:24.480] So if we're really talking about this from the lens of health, maximizing health, the data are unambiguous that VO2 max is highly correlated with longevity.
[01:52:24.480 --> 01:52:27.680] There are not many variables that are more strongly correlated.
[01:52:27.680 --> 01:52:29.520] But the levels don't have to be that high.
[01:52:29.520 --> 01:52:32.640] Pogots are VO2 max is probably 85.
[01:52:32.640 --> 01:52:38.720] It's probably in the 80s at least in terms of milliliters per minute per kilogram.
[01:52:38.720 --> 01:53:00.560] But someone my age to be considered absolutely elite, which means the top 2.5 to 2.7% of the population, which carries with it a five-fold reduction in risk to the bottom 25% of the population, my VO2 max requirement is about 52, 53 milliliters per minute per kilogram.
[01:53:00.560 --> 01:53:06.960] So the question is, can I use that as the gauge for how much high-intensity training I need to do?
[01:53:06.960 --> 01:53:11.280] Basically just enough to make sure I maintain that VO2 max?
[01:53:11.280 --> 01:53:13.360] Or do you think about it in a different way?
[01:53:13.360 --> 01:53:17.040] Well, I think about it more by energetics, energy systems.
[01:53:17.040 --> 01:53:24.480] Ultimately, and we know that longevity is also high related with mitochondrial function and metabolic health.
[01:53:24.480 --> 01:53:33.040] I think that more and more, and this is what you see in so many fields in medicine nowadays, everybody is stumbling upon mitochondria.
[01:53:33.040 --> 01:53:41.600] So there's an aging process where we lose mitochondrial function, and there's like a sedentary component where we lose mitochondrial function.
[01:53:41.600 --> 01:53:49.760] I wish that we could have a medication or PL you could take it and increase the mitochondrial function because it would increase metabolic health and longevity.
[01:53:49.760 --> 01:53:52.560] But the only medication that we know is exercise.
[01:53:52.560 --> 01:54:01.080] Within exercise, the dose that we see that improves the most and also is sustainable in the long term, which is another important concept.
[01:54:01.080 --> 01:54:04.520] Very high-intensity training is not sustainable.
[01:54:04.520 --> 01:54:06.920] Very extreme diets are not sustainable.
[01:54:06.920 --> 01:54:09.080] If you combine both, it's even worse.
[01:54:09.080 --> 01:54:11.080] And this is what a lot of people are doing together.
[01:54:11.080 --> 01:54:16.840] But you need to have some sustainability, but this is important to improve that mitochondrial function.
[01:54:16.840 --> 01:54:24.920] But going back to the high-intensity, I think, is necessary because we also lose glycolytic capacity as we age, and it's important to stimulate it.
[01:54:24.920 --> 01:54:31.960] As you very well said, for all of us who are not competing, I couldn't care less about being super high-intensity.
[01:54:32.120 --> 01:54:33.080] I'm not competing.
[01:54:33.080 --> 01:54:35.880] But that said, I want to have also my adrenaline rush.
[01:54:35.880 --> 01:54:37.480] But how much does it feed into it?
[01:54:37.480 --> 01:54:47.720] So, for example, if, and I've often thought about this now as I just want to make sure my zone two is above three watts per kilo, would I be better off taking that extra training?
[01:54:47.720 --> 01:54:53.240] If I have one additional training session per week, should I make it an additional zone two workout?
[01:54:53.240 --> 01:54:54.440] I do four now.
[01:54:54.440 --> 01:55:02.120] Should I be doing a fifth one, or should I be taking that fifth one and doing a VO2 max protocol?
[01:55:02.120 --> 01:55:14.280] And that's what we'll typically prescribe to our patients: a four by four protocol of highest intensity sustained for four minutes, followed by four minutes of recovery, and then repeat that four, five, six times.
[01:55:14.280 --> 01:55:18.680] When you put a warm-up and cool down on either end of that, that's a little over an hour.
[01:55:18.680 --> 01:55:24.280] Would you spend that hour doing that in an effort to make your zone two even better?
[01:55:24.280 --> 01:55:27.320] Or would you just do an extra hour of zone two?
[01:55:27.320 --> 01:55:34.520] I agree that if you have a fifth day, you can convert it into any type of high-intensity session, structured.
[01:55:34.520 --> 01:55:39.480] What I can tell people also: hey, you're a cyclist or a runner, you want to go with your friends on the fifth.
[01:55:39.640 --> 01:55:40.600] That's your group ride.
[01:55:40.600 --> 01:55:43.160] The group ride, go ahead and boom, go at it.
[01:55:43.160 --> 01:57:17.240] Or if you don't have that possibility this is my situation for example where i i don't have the time to train more than an hour and a half usually two hours max so what i do almost on every session i do my zone two so it's clean and at the end that's what i do a very high intensity interval tell me the duration so if you did an hour of zone two yeah so i do usually let's say an hour and a half so you'll do an hour and a half of zone two three or four times a week i shoot for four or five not all the time it's easy but yeah i shoot four or five and i try to be strict on that but and unfortunate that where i live i live more in a thailand area so you have to go up so the last part i just go at it sometimes you find another cyclist and you just compete you know to see who's the fastest in that short climb but i try to do like a good five minute interval roughly i arrive home like man i kicked my ass today this kicked my ass today or sometimes you try it and you don't have the energy as i mentioned earlier oh my gosh i can barely move the pedals today i just quit and go home but when i feel fresh i stimulate that glycolytic system what we know well too is that that increases the mitochondrial function it takes months or years increasing the glycolytic system it takes much much less amount of time you can do that in weeks or months if you stimulate on a regular base two days a week or three days a week at the end of that zone two that's where you can target both high energy systems the oxidative mitochondrial system and the glycolytic energy system.
[01:57:17.560 --> 01:57:22.920] We don't blunt the benefit we had from the zone two if we immediately follow it with the zone five.
[01:57:22.920 --> 01:57:24.760] No, because that's done, right?
[01:57:24.760 --> 01:57:26.840] What I see is like if you do the same things in the middle.
[01:57:27.080 --> 01:57:28.840] But you don't want to do the reverse order.
[01:57:28.840 --> 01:57:30.200] You don't want to start with the high intensity.
[01:57:30.360 --> 01:57:30.600] Exactly.
[01:57:30.600 --> 01:57:40.280] One of the things like because you start having all these hormonal responses and also you see you have high lactate levels in the blood and what we know very well is like lactate inhibits lipolysis.
[01:57:40.600 --> 01:57:52.360] So if you have a high interval in the middle or the beginning and you don't clear lactate very well, you might have high lactate levels for a while and it's going to inhibit lipolysis.
[01:57:52.360 --> 01:58:01.000] Also another study we have under review, lactate at the autocrete level decreases the activity of CPT1 and CPT2.
[01:58:01.000 --> 01:58:04.840] So it interferes with the transport of fatty acids as well.
[01:58:04.840 --> 01:58:07.880] So that's where like if you do all these, you might change things.
[01:58:07.880 --> 01:58:10.520] You have high cortisoidinemia as well.
[01:58:10.520 --> 01:58:23.480] I'm glad you raised that because I explained this to patients when they say, I went out and did a two-hour ride today and it showed me that I spent 45 of those minutes, 45 of those 120 minutes were in zone two.
[01:58:23.480 --> 01:58:29.240] So I did 45 minutes of zone two and I say, no, you didn't really do it because you were going up and down and up and down and up and down.
[01:58:29.240 --> 01:58:34.440] And so that's not the same as spending 45 minutes in the dedicated energy system.
[01:58:34.440 --> 01:58:34.840] Right.
[01:58:34.840 --> 01:58:44.120] I mean, when I look at the training peaks, you see the elite athletes, they're like, what power output and heart rate, this is like goes together incredible.
[01:58:44.360 --> 01:58:46.120] Whereas, yeah, you're right, up and down, down.
[01:58:46.120 --> 01:58:52.040] The average might be zone two, but actually you're between oscillating zone one, zone three, zone four all the time.
[01:58:52.040 --> 01:58:58.440] So if you don't mind sharing, in watts per kilo, what is your zone two in Colorado where you're at altitude?
[01:58:58.440 --> 01:59:00.760] I don't look so much into this.
[01:59:00.760 --> 01:59:04.200] I have done so many tests in my life.
[01:59:04.200 --> 01:59:07.840] Since I was 15 years old, I was using a heart rate monitor.
[01:59:07.840 --> 01:59:12.520] I'm talking about 1986 when the first heart rate monitors came out.
[01:59:12.520 --> 01:59:15.360] What you're getting at is you don't like to have a lot of data when you're doing it.
[01:59:15.000 --> 01:59:22.080] You're going off RPE and you're not looking at your power meter or a heart rate monitor and you're not poking your finger when you're done.
[01:59:22.400 --> 01:59:27.120] I do it here and there because I still want to look at this and I do metabolic testing here and there.
[01:59:27.120 --> 01:59:28.480] But I've done so much.
[01:59:28.480 --> 01:59:35.600] And me, since I was 15 years old and I was obsessed by this, I got to a point that I know my body quite well.
[01:59:35.680 --> 01:59:39.680] I can just go by the sensations and but here and there I double check.
[01:59:39.680 --> 01:59:48.080] But it's hard for you to then get at what I've observed the few times I've tried to do my zone to at altitude, like in Colorado.
[01:59:48.080 --> 01:59:49.840] It's an enormous discount.
[01:59:49.840 --> 01:59:53.200] I feel like it's a 20% discount at altitude.
[01:59:53.200 --> 01:59:58.880] Yeah, mine's around 2.5, 2.8, something like that watts per kilogram when I do it.
[01:59:58.880 --> 02:00:01.920] At sea level, you'd be over three probably.
[02:00:01.920 --> 02:00:04.720] Based on what I experienced it going in the reverse direction.
[02:00:05.120 --> 02:00:06.240] I would say roughly.
[02:00:06.240 --> 02:00:11.840] And one thing that I'm very proud of is that I have been doing, because I do sporadically this testing.
[02:00:12.000 --> 02:00:19.040] I don't know my PRs because I think we have climbs here and one day I go for this climb and I go full out on that climb, right?
[02:00:19.040 --> 02:00:20.480] I'm 50 now.
[02:00:20.480 --> 02:00:24.720] I have the same metabolic parameters that when I was 40.
[02:00:24.720 --> 02:00:26.320] To me, I'm very proud of this because.
[02:00:26.480 --> 02:00:30.160] And when you say parameters, you don't mean times up the climbs.
[02:00:30.160 --> 02:00:32.000] Which parameters are the same?
[02:00:32.000 --> 02:00:34.800] Lactating power output, VO2.
[02:00:34.800 --> 02:00:36.640] I look at time as well.
[02:00:36.640 --> 02:00:38.880] The PR that I had, it was similar.
[02:00:38.880 --> 02:00:40.800] What's your VO2 max now?
[02:00:40.800 --> 02:00:44.800] So my VO2 max now is four liters per minute.
[02:00:44.800 --> 02:00:46.720] So that's about 51, 52.
[02:00:47.040 --> 02:00:51.200] You could easily raise that if you lost three kilos, which you could probably do.
[02:00:51.200 --> 02:00:51.680] Yeah, yeah, yeah.
[02:00:51.840 --> 02:00:52.080] Yeah.
[02:00:52.080 --> 02:00:58.960] And the thing is, because I've obviously, when I was a cyclist, I was 141, 143 pounds.
[02:00:58.960 --> 02:00:59.960] So my VO2 was...
[02:00:59.280 --> 02:01:03.320] And you were probably, your VO2 was five and a half liters or something.
[02:01:03.320 --> 02:01:05.640] It was 76.7.
[02:01:05.640 --> 02:01:06.200] Let me see.
[02:00:59.760 --> 02:01:08.040] It was 4.5, I believe.
[02:01:08.040 --> 02:01:10.760] It was about 4.8, something like that.
[02:01:10.760 --> 02:01:20.440] 30 years later, I have decreased only about 0.5, 0.7, which, whoa, I'm really happy about that because I'm not training like I did.
[02:01:20.440 --> 02:01:21.800] But this is one of the parameters.
[02:01:21.800 --> 02:01:25.560] But in a decade, I haven't decreased my parameters.
[02:01:25.560 --> 02:01:37.080] So this is, to me, it's a proving point to myself at least that doing this routine, it helps to maintain that metabolic health that you had a decade ago.
[02:01:37.080 --> 02:01:41.400] Now, can you do this 10 more years and when I turn 60?
[02:01:41.400 --> 02:01:42.680] I don't know.
[02:01:42.680 --> 02:01:46.200] But what I know is that from others, I'm seeing it.
[02:01:46.200 --> 02:01:54.920] So I see typical person who just retired, as I discussed earlier, aspire to pre-retire at the age of 60 or a little bit before.
[02:01:54.920 --> 02:02:02.520] And these are like people like us who are struggling to squeeze in time, do five hours here, six hours a week here, or 10.
[02:02:02.520 --> 02:02:09.880] But then they have the whole time in the world, sleeping, they're not overworked, they can exercise.
[02:02:09.880 --> 02:02:15.480] It's unbelievable and super inspiring how much they improve in their 60s.
[02:02:15.480 --> 02:02:25.080] I've seen people in their 70s with the metabolic parameters of people active, motorally active in their 30s.
[02:02:25.080 --> 02:02:30.600] World champion in the cycling was 81, in the category of 80 to 85.
[02:02:30.600 --> 02:02:32.440] Believe me, there's a category of that.
[02:02:32.440 --> 02:02:37.240] Metabolic parameters were those of someone in their 30s, healthy, active.
[02:02:37.240 --> 02:02:39.400] So this is incredibly inspiring.
[02:02:39.400 --> 02:02:44.520] And I think that we're rewriting what's been taught to us in the books.
[02:02:44.520 --> 02:02:46.800] Was that person an elite athlete?
[02:02:44.840 --> 02:02:49.680] Were they a professional athlete in their 20s and 30s?
[02:02:50.000 --> 02:02:50.640] Never.
[02:02:50.640 --> 02:02:52.400] And this is what struck me.
[02:02:52.400 --> 02:02:59.680] He was a smoker, hypertensive, and he started cycling because he needed to change his lifestyle in his 40s.
[02:02:59.680 --> 02:03:00.880] Because that's the same question.
[02:03:00.880 --> 02:03:02.720] Like, whoa, you must have been doing this all your life.
[02:03:02.800 --> 02:03:05.680] Like, no, I started riding my bike when I was in my 40s.
[02:03:05.680 --> 02:03:06.640] I was a smoker.
[02:03:06.640 --> 02:03:07.360] I was heavy.
[02:03:07.360 --> 02:03:08.480] I was hypertensive.
[02:03:08.480 --> 02:03:09.440] Like, what?
[02:03:09.440 --> 02:03:13.200] So it's incredible 40 years later.
[02:03:13.200 --> 02:03:18.560] What I take away from that as well is the benefits and the importance of compounding.
[02:03:18.560 --> 02:03:24.320] You see, you alluded to it earlier, and I think the listener could be forgiven if they missed this point.
[02:03:24.320 --> 02:03:28.800] You can make relatively quick changes in your glycolytic efficiency.
[02:03:28.800 --> 02:03:41.120] You can take an untrained person with a VO2 max of 20 mil per gig per minute, and you could take them from 20 to 30 in a period of months with the right amount of training.
[02:03:41.120 --> 02:03:44.880] A 50% improvement in a few months.
[02:03:44.880 --> 02:03:51.520] It's very difficult to see a 50% improvement in mitochondrial function in a few months.
[02:03:51.520 --> 02:04:03.520] You've already made this point, but I just want to restate it because it's important to set expectations, and it speaks to why this level of training should be thought of in the same way that you think of accumulating wealth.
[02:04:03.520 --> 02:04:23.520] It's day in and day out, day in and day out, small compounded gains over years and years and years is why a 40-year-old overweight smoker can become a world champion at 80 because he probably never once again got out of shape in that 40 years.
[02:04:23.520 --> 02:04:24.160] Absolutely.
[02:04:24.160 --> 02:04:25.920] And this is incredibly inspiring.
[02:04:25.920 --> 02:04:42.600] When I see these people in their 60s just retired and they come to do their first test, and one year later they come back, it gives me the goosebumps because it is like, oh my gosh, I'm 64, I feel strong as when I was in my 30s.
[02:04:42.600 --> 02:04:43.720] And like, oh.
[02:04:43.960 --> 02:04:50.120] And of course, no medications, really good state of mind, which is absolutely key for longevity.
[02:04:50.120 --> 02:05:01.160] They eat in moderation, that they can have a little bit of everything, which is also, in my modest opinion, is part of the enjoyment of life, eating what you like in moderation as well.
[02:05:01.160 --> 02:05:03.160] So it's incredibly inspiring.
[02:05:03.160 --> 02:05:10.040] In a way, we're rewriting what we've been thought for years: that once you turn 40, everything is going down.
[02:05:10.040 --> 02:05:11.560] You can really, really change.
[02:05:11.560 --> 02:05:18.840] And again, you know, you own your own body and you can really take ownership of that and improve it at any age.
[02:05:18.840 --> 02:05:19.720] You mentioned drugs.
[02:05:19.720 --> 02:05:23.080] I want to talk about one drug in particular and maybe some supplements.
[02:05:23.080 --> 02:05:35.000] You and I have spoken so much about this, and myself and another person are committed to funding a study that we're going to be doing once we get through kind of the backlog of COVID issues at the university.
[02:05:35.000 --> 02:05:53.720] The question really arises around the use of metformin and whether or not there's a true impairment of mitochondrial function or whether the elevated lactate levels we see in patients taking metformin is an artifact of the drug itself, but says nothing of the mitochondrial function.
[02:05:53.720 --> 02:06:09.080] Do you have any more insight into this question that we struggle with greatly because we have some patients who take metformin who receive much benefit from taking metformin, but it makes it confusing to interpret their zone 2 data?
[02:06:09.080 --> 02:06:19.680] And it makes me ask the question: in those patients, it's maybe less relevant, but now it becomes relevant when we think about using metformin as a giro-protective agent, an agent to enhance longevity.
[02:06:20.000 --> 02:06:23.920] We need a lot of research on that, I think, to understand this better.
[02:06:23.920 --> 02:06:26.240] Definitely it seems to work in many patients.
[02:06:26.240 --> 02:06:31.840] Obviously for those ones in the pre-diabetic first stage diabetes, it's a very good medication.
[02:06:31.840 --> 02:06:34.640] It's been used for a long time with good results.
[02:06:34.640 --> 02:06:36.640] But how about the long-term results?
[02:06:36.640 --> 02:06:44.320] We know that metformin inhibits complex 1, which is key for mitochondrial function in the electron transport chain.
[02:06:44.320 --> 02:06:48.240] We don't know the long-term effects of metformin in longevity.
[02:06:48.240 --> 02:06:51.360] This is where I think that we need more information as well.
[02:06:51.360 --> 02:06:56.080] We see someone showing up with lactate of 3.5 millimoles at rest.
[02:06:56.080 --> 02:06:59.120] And the first thing I ask is, like, are you at metformin?
[02:06:59.120 --> 02:07:00.320] And Metan say yes.
[02:07:00.320 --> 02:07:01.920] And I'm sure you see the same thing, right?
[02:07:02.240 --> 02:07:04.560] Wow, it's definitely an artifact.
[02:07:04.560 --> 02:07:09.120] And why do you see at rest 3.5 millimoles or 3 millimoles of lactate?
[02:07:09.200 --> 02:07:12.720] Their fat oxidation commensurately suppressed?
[02:07:12.720 --> 02:07:21.200] Because when you metabolically test them on the cart, do you see in that individual a very, very low fat oxidation?
[02:07:21.200 --> 02:07:29.600] If not, it might suggest that that lactate level of 2 or 3 millimole is an artifact, but doesn't really speak to what's happening in the mitochondria, right?
[02:07:29.600 --> 02:07:35.520] I haven't seen people taking metformin as medication, you know, for longevity, for example, or for health.
[02:07:35.520 --> 02:07:38.720] What I see people on metformin are already clinical patients.
[02:07:38.720 --> 02:07:40.160] So of course they're low.
[02:07:40.160 --> 02:07:48.240] Yeah, so they're taking metformin in the first place because of their clinical condition, which is driven by a mitochondrial impairment or dysfunction.
[02:07:48.240 --> 02:07:53.280] It's difficult to discern, but I mean, I'm sure you have more experience of people taking metformin.
[02:07:53.600 --> 02:08:00.680] We do, but that's why this study that we're eventually going to get around to doing is going to be so important, because it will answer this question directly.
[02:08:01.160 --> 02:08:15.320] We can do it the muscle biopsies, and as you say, does it really mess up with the whole mitochondrial function, or even like the mitochondrial function overall override that inhibition of complex one and override other pathways?
[02:08:15.320 --> 02:08:17.240] I don't think we know the answer to that.
[02:08:17.240 --> 02:08:20.360] Do you have an insight into any other supplements?
[02:08:20.360 --> 02:08:28.920] No shortage of supplements that are out there that are touted as longevity boosting agents and mitochondrial health agents.
[02:08:28.920 --> 02:08:34.200] So the most talked about of all of these, I think, is the precursors to NAD.
[02:08:34.200 --> 02:08:41.800] The most common of these would be NR or NMN, both of which are pretty clear that they are precursors to NAD.
[02:08:41.800 --> 02:08:45.800] There's certainly some debate about how clinically relevant it is.
[02:08:45.800 --> 02:08:53.960] Do you have a point of view on whether or not taking a supplement that boosts NAD, at least in the plasma?
[02:08:53.960 --> 02:09:04.200] I still don't know how well it's boosting NAD in the cell, but do you have a sense of if that is beneficial to the mitochondria, both theoretically, but more importantly, experimentally?
[02:09:04.200 --> 02:09:09.960] I don't think we have the answer, but I think we need to be cautious about how we interpret this data.
[02:09:09.960 --> 02:09:17.800] It's definitely been shown multiple times that NAD levels at the cellular level or even mitochondrial level are decreased with aging.
[02:09:17.800 --> 02:09:20.440] Therefore, the whole thing, well, if it's low, let's take it.
[02:09:20.440 --> 02:09:22.600] But it's not only NAD.
[02:09:22.600 --> 02:09:29.080] If you look at so many metabolites at the cellular level and mitochondrial level, they're down-regulated with aging.
[02:09:29.080 --> 02:09:31.720] The question is: why are they down-regulated?
[02:09:31.720 --> 02:09:42.360] It's because mitochondria, per se, to start with, is down-regulated, so it doesn't need so much NAD because it cannot take it, or other supplements or other metabolites.
[02:09:42.360 --> 02:10:04.080] This is at least how I think of NAD, as we mentioned earlier, it's very important in glycolysis and redox status to maintain redox and it's very important in the visceral 3-phosphate to 2,3-biphosphoglycerate phosphate where NAD is utilized to convert glycerin 3-phosphate to 2,3-phosphoglycerate, but it's depleted.
[02:10:04.080 --> 02:10:07.760] And this is what the only thing that rescues that is lactate, right, as we mentioned.
[02:10:07.760 --> 02:10:11.520] Now, taking NAD, is that going to increase longevity?
[02:10:11.520 --> 02:10:12.560] I don't think so.
[02:10:12.560 --> 02:10:18.000] That's my opinion, because longevity is not just one supplement or two or three or four or five.
[02:10:18.000 --> 02:10:22.320] It's a compendium on an incredible amount of things that happen at the cellular level.
[02:10:22.320 --> 02:10:24.320] And I don't think that one supplement.
[02:10:24.320 --> 02:10:29.520] I remember those days where resveratrol was the thing for longevity.
[02:10:29.520 --> 02:10:31.120] And everybody was, not everybody.
[02:10:31.200 --> 02:10:33.040] A lot of people were buying resveratrol.
[02:10:33.040 --> 02:10:39.360] And there are studies with mice showing that increased 50% longevity in mice or therefore this do it in humans.
[02:10:39.360 --> 02:10:45.280] Well, as you probably know, a lot of people started taking resveratrol when they were 50 and they're dead now.
[02:10:45.280 --> 02:10:47.680] It doesn't increase longevity in humans.
[02:10:47.760 --> 02:10:51.120] The data in the mice, we can debate the merits of that.
[02:10:51.120 --> 02:10:53.040] I want to ask you about a theoretical risk, though.
[02:10:53.040 --> 02:10:54.240] You kind of alluded to it.
[02:10:54.240 --> 02:10:59.120] Isn't there a scenario under which too much NAD could be harmful?
[02:10:59.120 --> 02:11:15.360] I don't know if this study has been done, but if you took cancer patients or patients who had tumors that were undiagnosed and gave them, if you doubled their NAD levels, wouldn't you actually favor the tumor's metabolism?
[02:11:15.680 --> 02:11:19.280] Well, in fact, we have done that pilot study with mice.
[02:11:19.280 --> 02:11:24.320] The whole thing is like looking at, in my area of research in cancer, is cancer metabolism.
[02:11:24.320 --> 02:11:32.280] And we know that glycolysis is key for cancer, and NAD is absolutely indispensable to feed that glycolysis.
[02:11:32.600 --> 02:11:41.240] The question is, like, as you said, would NAD increase that glycolytic rate or glycolytic flux?
[02:11:41.240 --> 02:11:45.640] Therefore, would be favoring more cancer phenotype.
[02:11:45.640 --> 02:11:52.200] So what we did, we haven't published that, it's a pilot study, which is, we're curious about it, and we had two mice.
[02:11:52.200 --> 02:11:56.120] We have NN of eight mice, four and four.
[02:11:56.120 --> 02:12:00.040] So what we did is we transfected tumors, triple negative breast cancer.
[02:12:00.040 --> 02:12:03.080] It's very aggressive, and it grows very, very fast.
[02:12:03.080 --> 02:12:14.840] One group, we give implants water, and the other group, nicotinamida ribocyte, which is the NAD precursor, because NAD, obviously, as you know, you cannot take it, you need to take the precursor.
[02:12:14.840 --> 02:12:18.120] And we observed the tumor growth over 23 days.
[02:12:18.120 --> 02:12:24.760] After that, the IRB at the university, because you cannot have animals with high tumors.
[02:12:24.760 --> 02:12:28.360] So it was a flank tumor, and you need to harvest them.
[02:12:28.360 --> 02:12:31.880] We were measuring every five days the tumor growth.
[02:12:31.880 --> 02:12:38.120] And we saw in these animals that there was about 15% increase in tumor growth in the NAD group.
[02:12:38.120 --> 02:12:42.040] You saw that difference with only four mice in each group?
[02:12:42.040 --> 02:12:44.840] It's four and four, but all consistent.
[02:12:44.840 --> 02:12:48.120] We have statistical significancy, even with a small four.
[02:12:48.120 --> 02:12:50.360] I mean, there was no cross-results.
[02:12:50.360 --> 02:12:56.920] All the four mice, they grew cancer at a higher rate in the NAD than the control group.
[02:12:56.920 --> 02:13:00.760] Again, that's where, like, obviously, this is not like a publishable.
[02:13:01.240 --> 02:13:05.640] Is that a study you'll repeat at a sufficiently powered size?
[02:13:05.640 --> 02:13:06.600] I would love to.
[02:13:06.600 --> 02:13:08.600] This is why we just did this pilot study.
[02:13:08.600 --> 02:13:15.280] We had, because we have many mice and say, hey, let's leave it a shot and see, because there's a lot of hype of NAD, and we saw this.
[02:13:15.600 --> 02:13:29.920] Love to do it at a much higher level because my question, which might be a disruptive question, is like, what if you have a small tumor that you're unaware of, like in the pancreas or in the colon or in the lung?
[02:13:29.920 --> 02:13:38.720] Could NAD over time, day after day after day, could favor that glycolytic flux to that tumor and increase the growth?
[02:13:38.720 --> 02:13:44.880] I've never looked because it just kind of occurred to me when you had that slide up earlier, earlier and you showed the mitochondrial slide.
[02:13:44.880 --> 02:13:48.000] It occurred to me that you have that lactate escape from the tumor.
[02:13:48.000 --> 02:13:49.200] Hey, this would feed it.
[02:13:49.200 --> 02:13:52.080] But has anybody in the literature examined this question?
[02:13:52.080 --> 02:13:54.640] It seems like a very reasonable question to ask.
[02:13:54.640 --> 02:13:55.920] There are a couple of studies.
[02:13:55.920 --> 02:13:57.440] I think one's a review.
[02:13:57.440 --> 02:13:59.600] It's more at the conceptual level.
[02:13:59.600 --> 02:14:07.120] And this is what got me thinking: like, yeah, this is something that for us working in cancer metabolism, we look into this.
[02:14:07.120 --> 02:14:11.280] Obviously, one of the things that we have shown is that lactate is an oncometabolite.
[02:14:11.280 --> 02:14:20.240] Lactate, we have shown, we have a first paper, and we have like a good six, seven papers more to come, working hard for three years looking into this.
[02:14:20.240 --> 02:14:26.960] But we saw that lactate regulates genetic expression of the most important genes in breast cancer.
[02:14:26.960 --> 02:14:29.680] We're seeing the same thing now with lung cancer.
[02:14:29.680 --> 02:14:35.040] And lactate, as we keep talking about this, is that mandatory byproduct of glycolysis.
[02:14:35.040 --> 02:14:42.320] And as Warburg saw in 1923, the characteristic of cancer cells, or most cancer cells, is the high glycolytic flux.
[02:14:42.320 --> 02:14:45.800] But what struck Warburg was not the glucose itself.
[02:14:45.800 --> 02:14:47.920] What's the lactate production.
[02:14:47.920 --> 02:14:51.680] So many ways, we are showing that it's an oncometabolite.
[02:14:51.680 --> 02:14:56.480] So if you have a high glycolytic rate in a cell, you're going to produce a lot of lactate.
[02:14:56.480 --> 02:15:01.880] If you cannot clear that lactate, it's going to drive cell growth and proliferation as we're seeing.
[02:15:02.200 --> 02:15:11.000] And in fact, we're now blocking lactate production, both through genetic engineering as well as DCA, for example.
[02:15:11.000 --> 02:15:16.360] And we're seeing that cancer growth and proliferation completely stops within hours.
[02:15:16.360 --> 02:15:28.840] Now that poses an interesting dilemma, which is exercise would increase your capacity for clearing lactate in the long term, but in the short term raises lactate.
[02:15:28.840 --> 02:15:35.800] So it begs the question, in a cancer patient specifically, what's the net impact of exercise?
[02:15:35.800 --> 02:15:40.120] This is what we're working on, the hypothesis, you know, with my colleague George Brooks.
[02:15:40.120 --> 02:15:48.440] He's shown that acute response to lactate, it increases overexpressions of 600 and something genes.
[02:15:48.440 --> 02:15:49.400] I forgot right now.
[02:15:49.400 --> 02:15:54.280] All these genes are involved in cellular homeostasis and in the benefits of exercise.
[02:15:54.280 --> 02:15:59.080] We know very, very well through his work that lactate is a signaling molecule.
[02:15:59.080 --> 02:16:04.200] Now, the question is like, we know this at an acute exposure, which is exercise.
[02:16:04.200 --> 02:16:07.080] You do exercise, boo-poo-poon, you're out.
[02:16:07.080 --> 02:16:09.400] But cancer doesn't do that.
[02:16:09.400 --> 02:16:12.440] Cancer accumulates lactate and it keeps accumulating.
[02:16:12.440 --> 02:16:16.760] This is the main responsible for the tumor microenvironment, which is acidic.
[02:16:16.760 --> 02:16:25.320] And the more acidic the tumor microenvironment, the more metastatic the cancer is and the more aggressive, like the more glycolytic the tumor is.
[02:16:25.320 --> 02:16:27.240] And this is very well documented.
[02:16:27.240 --> 02:16:30.200] The more glycolytic the tumor is, the more aggressive is.
[02:16:30.200 --> 02:16:36.120] And the more lactogenic, that is more lactate, the tumor produces, the more aggressive is.
[02:16:36.120 --> 02:16:39.240] Now, why is that lactate accumulating?
[02:16:39.240 --> 02:16:40.840] That's what we need to try to find out.
[02:16:40.840 --> 02:16:43.080] But we know that that is not acute anymore.
[02:16:43.080 --> 02:16:45.000] It's chronic exposure to lactate.
[02:16:45.600 --> 02:16:47.760] Can exercise counteract that?
[02:16:47.760 --> 02:17:02.480] When we see that exercise might be beneficial for many patients, but again, going back to the right intensity, we know particles which are exosomes, they're microvesicles in the body, they're mainly responsible for metastasis.
[02:17:02.480 --> 02:17:08.080] We have seen that, and this is another publication we want to have in breast cancer cells and lung cancer cells.
[02:17:08.080 --> 02:17:14.160] We are looking at the protein content and the microRNAs of those exosomes released by these cancer cells.
[02:17:14.320 --> 02:17:16.960] It's incredible the information that they have.
[02:17:16.960 --> 02:17:27.600] If you were to genetically engineer a molecule that can inject it into a tissue and transform into cancer, you would replicate an exosome.
[02:17:27.600 --> 02:17:29.760] It has all the components needed.
[02:17:29.760 --> 02:17:34.080] On the other side, muscles also release exosomes.
[02:17:34.080 --> 02:17:43.680] And this could be one of the benefits of exercise as an organ and the crosstalk between skeletal muscle and many organs.
[02:17:43.680 --> 02:17:50.240] We know that if you have very good muscle health, your health overall, your metabolic health is going to be good.
[02:17:50.240 --> 02:17:52.640] Could you be releasing great exosomes?
[02:17:52.640 --> 02:17:57.600] They're very pro-oxidative, which counteract the glycolated phenotype of cancer.
[02:17:57.600 --> 02:18:13.440] And could those exosomes travel directly to the cancer cells and counteract that and penetrate inside the cancer cells and transform the glycolytic phenotype of the cancer cells into more oxidative phenotype and keep cancer at bay?
[02:18:13.440 --> 02:18:14.480] We don't know yet.
[02:18:14.480 --> 02:18:25.200] We're suspecting that we're scratching the surface of something that potentially could be a very interesting thing to understand better the effects of exercise as well as neurotherapeutics.
[02:18:25.200 --> 02:18:44.360] The deeper I go in the rabbit hole into all things that relate to longevity, the more convinced I am that if you're going to rank order things, if you were forced to rank order things, there's nothing that ranks above exercise as the single most potent tool or agent we have to impact longevity.
[02:18:44.360 --> 02:18:51.000] And yet, paradoxically, in the acute setting, exercise seems to do everything incorrectly.
[02:18:51.000 --> 02:18:59.320] In the very short, acute setting, if you look at it in that narrow context, exercise does not appear to be giro-protective.
[02:18:59.320 --> 02:19:08.360] But of course, when you look at the chronic impacts of exercise and what's taking place after the bouts of exercise, the data seem undeniable.
[02:19:08.360 --> 02:19:17.160] I want to kind of pivot from exercise a bit into a subset of that, which is something you published this year in long COVID patients.
[02:19:17.160 --> 02:19:37.000] So we'll link to the study so people can see it, but you demonstrated that in people with long COVID, even previously healthy people, they basically, from a mitochondrial standpoint, end up looking like people with type 2 diabetes when they're done, in terms of fat oxidation and lactate production.
[02:19:37.000 --> 02:19:45.880] So, first question for you is: what fraction of patients recovering from COVID do you believe are susceptible to that phenotype?
[02:19:45.880 --> 02:19:55.560] Everything is started by National Jewish Hospital is probably, if you know, is with Mayo Clinic competing for the top one pulmonology hospital in the country.
[02:19:55.560 --> 02:19:59.960] You have these people with long COVID who are struggling.
[02:19:59.960 --> 02:20:02.120] They go up the stairs and they can't breathe.
[02:20:02.120 --> 02:20:07.720] So, the first thing they do is they go to different doctors and they end up going to this top hospital.
[02:20:07.720 --> 02:20:11.880] So, they do a pulmonary function test and it's completely normal.
[02:20:11.880 --> 02:20:17.520] Then they, okay, the next suspicious is because COVID also affects the cardiac muscles.
[02:20:17.520 --> 02:20:18.720] Let's look at the cardiofunction.
[02:20:14.840 --> 02:20:19.760] It's completely normal.
[02:20:20.080 --> 02:20:24.320] They're very good at this hospital where they do metabolic testing.
[02:20:24.320 --> 02:20:27.440] They do a CPET testing, that's how you call it medically, right?
[02:20:27.440 --> 02:20:30.000] Physiological testing, and they even do lactate.
[02:20:30.320 --> 02:20:34.400] I've been interacting with them a few times, so they do lactate as well.
[02:20:34.400 --> 02:20:38.240] So they contacted me and said, Inigo, look, we're seeing these patients.
[02:20:38.240 --> 02:20:39.280] We have 50.
[02:20:39.280 --> 02:20:43.280] 25 of them, they had previously underlying conditions.
[02:20:43.280 --> 02:20:46.800] The other 25, they were normal people.
[02:20:46.800 --> 02:20:49.760] And in fact, most of them, they were motorly active.
[02:20:49.760 --> 02:20:52.720] Some of them, they were doing marathons, triathlons.
[02:20:52.720 --> 02:20:54.160] The average is 50.
[02:20:54.160 --> 02:20:56.640] So they're not very old either.
[02:20:56.640 --> 02:21:00.720] But their pulmonary function is completely normal and cardiac function is completely normal.
[02:21:00.720 --> 02:21:03.920] So we suspected there's some metabolic issue here.
[02:21:03.920 --> 02:21:18.880] So they sent me all the information, the raw information, and I applied the methodology that we've been discussing, looking at fat oxidation and lactate production as a surrogate for metabolic function and metabolic flexibility and mitochondrial function.
[02:21:18.880 --> 02:21:32.960] And I was shocked because they were significantly worse than people with type 2 diabetes and metabolic syndrome, which could explain why these people cannot go up the stairs and where before they were doing marathons.
[02:21:32.960 --> 02:21:35.200] Now, what are the mechanisms?
[02:21:35.200 --> 02:21:43.200] We know that viruses, multiple viruses, are known to hijack mitochondria for their own benefit, for reproduction.
[02:21:43.200 --> 02:21:45.040] Could COVID do the same thing?
[02:21:45.040 --> 02:21:50.160] We are suspecting it, and we're trying to understand that at a more at a cellular level.
[02:21:50.160 --> 02:22:01.800] Now, unfortunately, the majority of these long COVID, because as you know, there are people with long COVID syndromes that within weeks, months, they improve, they go back to normal.
[02:22:01.800 --> 02:22:08.920] But there are a handful of people that I'm assuming they're going to be growing, that after one year, they haven't improved a bit.
[02:22:08.920 --> 02:22:09.800] This is the concern.
[02:22:09.800 --> 02:22:13.480] Like, can we use exercise as a therapeutic way?
[02:22:13.480 --> 02:22:58.280] to stimulate mitochondrial function if in fact there's a mitochondrial dysfunction which is severe because if that's the situation it's going to expose these patients to multiple diseases so this is an area of concern and this isn't talked about as much as what i think people initially spoke about here which is basically myocarditis now of course we know that the risk of myocarditis is actually much higher in young males through the moderna vaccine than it's ever going to be with covid but the rate with covet is not zero it's i believe it's 2.3 cases per it's going to be a big difference i think it's 2.3 cases per 100,000 of people with COVID are getting myocarditis.
[02:22:58.280 --> 02:22:59.880] Most of those are transient.
[02:22:59.880 --> 02:23:00.840] They recover.
[02:23:00.840 --> 02:23:01.880] Not all of them are.
[02:23:01.880 --> 02:23:03.640] So a subset are not.
[02:23:03.640 --> 02:23:06.440] But this mechanism would be distinct from just myocarditis.
[02:23:06.440 --> 02:23:12.280] Myocarditis, of course, speaks to the inflammation of the cardiac muscle that would explain depressed ejection fraction.
[02:23:12.280 --> 02:23:20.200] But what you're describing is a far more diffuse problem, is a global insult on the mitochondria in the skeletal muscle, correct?
[02:23:20.520 --> 02:23:29.560] That's what we suspect from this data, which again is indirect from the indirect colorimetry in the lactate, that it points out towards mitochondrial dysfunction.
[02:23:29.560 --> 02:23:35.080] So that's what we need to do now, biopsies, to understand this setup better detail.
[02:23:35.080 --> 02:23:36.440] What the heck is going on?
[02:23:36.520 --> 02:23:39.160] Could be at the micro-perfusion level, too.
[02:23:39.160 --> 02:23:45.000] It might not be at the muscle per se, it might be at the microfusion in the blood, in the capillaries.
[02:23:45.280 --> 02:23:52.400] Meaning something like microthromboses that are preventing perfusion and raising lactate that way?
[02:23:52.400 --> 02:23:53.920] Could be, could be.
[02:23:53.920 --> 02:23:55.200] That's what we need to find out.
[02:23:55.200 --> 02:23:58.720] But we know from other viruses that they hijack mitochondria.
[02:23:58.720 --> 02:24:03.760] They interfere especially with the fission and fusion processes.
[02:24:03.760 --> 02:24:10.240] Some causes increase fission, some other causes increase fusion, some other causes increase elongation.
[02:24:10.240 --> 02:24:19.760] So we know there's a wealth of studies out there from virology showing that, yeah, many viruses and bacteria, they hijack mitochondria.
[02:24:19.760 --> 02:24:22.000] They disrupt it significantly.
[02:24:22.000 --> 02:24:26.400] But most of the times, like myocarditis, it subsides.
[02:24:26.400 --> 02:24:30.400] It's restored shortly after the symptoms are gone.
[02:24:30.400 --> 02:24:32.480] Why this virus is different?
[02:24:32.480 --> 02:24:34.480] That's what we are trying to understand.
[02:24:34.480 --> 02:24:41.200] Why people after one year, by the way, you know, most of these people, they had just a normal, mild course of COVID.
[02:24:41.200 --> 02:24:43.760] They were not hospitalized, they were not in the ICU.
[02:24:44.080 --> 02:24:53.840] Any evidence or inkling that if people go back to exercising too intensely following recovery, it could exacerbate this problem?
[02:24:53.840 --> 02:24:56.480] And do you have a sense of which strains this was?
[02:24:56.480 --> 02:25:02.240] Your work would have been predominantly alpha and not delta and obviously not Omicron, correct?
[02:25:02.240 --> 02:25:08.080] Yeah, even a mixture between the original variant and delta, so not Omicron.
[02:25:08.080 --> 02:25:15.760] So in this population, which again is presumably mostly alpha, maybe some delta, what was the distribution of male and female?
[02:25:15.760 --> 02:25:21.040] We have 35 females and 15 males, more female predominant.
[02:25:21.040 --> 02:25:23.360] Which again, maybe is too small a sample to know.
[02:25:23.360 --> 02:25:25.680] That could be more an indication of who's seeking out.
[02:25:26.080 --> 02:25:28.080] And again, we don't really know the denominator.
[02:25:28.080 --> 02:25:29.440] We don't know what this represents.
[02:25:29.480 --> 02:25:31.560] Is this one in 100,000?
[02:25:31.560 --> 02:25:35.080] It could be one in a million if this was everybody that's reporting it at the time.
[02:25:35.080 --> 02:25:38.760] Our guess is it's a rare event can last that long.
[02:25:38.760 --> 02:25:42.280] But we're talking about millions of people infected, right?
[02:25:42.360 --> 02:25:46.920] If it's one in a million, we're talking about a population that is going to need help.
[02:25:46.920 --> 02:25:50.680] I want to kind of go back to just a few other questions that we didn't get to.
[02:25:50.680 --> 02:25:53.560] So not necessarily in any thematic order.
[02:25:53.560 --> 02:26:04.280] What's the relationship between, or how predictable I should say, is the relationship between zone 2 as defined by maximum fat oxidation and VO2 max?
[02:26:04.280 --> 02:26:18.280] So if you run somebody through a CPET and you figure out that their VO2 max is at 4 liters, how predictably can you say at X percent of that, you will be at maximum fat oxidation?
[02:26:18.280 --> 02:26:27.640] There's another study that we're preparing the manuscript with 225 subjects where we look at fat oxidation, VO2, and the relationships.
[02:26:27.640 --> 02:26:35.400] Going back to the same thing, we tend, and historically, the research studies with exercise have been done based on VO2 max.
[02:26:35.400 --> 02:26:38.920] That's been the parameter to prescribe exercise.
[02:26:38.920 --> 02:26:45.560] How many times we read X amount of subjects, they were exercising for six months at 60% of VO2 max or whatever.
[02:26:45.560 --> 02:26:48.760] Now, that's another thing that I've been thinking of years.
[02:26:48.760 --> 02:27:02.120] And by the way, when they say that, do they mean 60% of the heart rate that produced VO2 max or 60% of the power that is their max power at VO2 max?
[02:27:02.120 --> 02:27:07.720] Yeah, I mean, there's so many different ways you can do this that I've always found it you have to get into the methodology very closely.
[02:27:07.720 --> 02:27:08.200] I agree.
[02:27:08.200 --> 02:27:09.320] I agree 100%.
[02:27:09.320 --> 02:27:23.600] And this is where I think we need to dial in things in better because, yeah, 60% of the power output, the intensity might be translated into power output, 60% of VO2 max, and then you translate into power output, or you translate into heart rate.
[02:27:23.600 --> 02:27:26.000] Or is it 60% of the VO2?
[02:27:26.000 --> 02:27:41.840] So for example, if somebody's four liters VO2 and then they hit that at 300 watts, would 60% be 2.4 liters, which of course is not a very helpful way outside of a laboratory to prescribe exercise to somebody?
[02:27:41.840 --> 02:27:47.760] Or would it be 180 watts, which is 60% of the 300 watts?
[02:27:47.760 --> 02:27:48.560] Yeah, exactly.
[02:27:48.560 --> 02:27:54.000] I think that normally the studies they look at where do you hit 60% of VO2 max?
[02:27:54.000 --> 02:27:55.680] How many watts is this?
[02:27:55.680 --> 02:27:57.200] Or what's your heart rate?
[02:27:57.200 --> 02:28:02.960] What's the wattage that corresponds to 60% of your max VO2?
[02:28:02.960 --> 02:28:14.720] And in our study, what we are seeing, and this is what, because I've been curious about this, because we look at the cardiorespiratory adaptations to exercise and we look at the cellular adaptations to exercise, do they really correspond?
[02:28:14.720 --> 02:28:30.480] We know very well with athletes, you can improve tremendously at the cellular level, but not at all at the cardiorespiratory level, at least based on the VO2 max, which is the representative of the cardiorespiratory adaptations to exercise.
[02:28:30.640 --> 02:28:40.960] An example that I always give when I give talks, an athlete who used to be an average professional, the VO2 max was 72.3 or something like that.
[02:28:40.960 --> 02:28:44.640] And then two years later, he is a very good professional.
[02:28:44.640 --> 02:28:49.360] The VO2 max is the same, but the lactate levels were incredibly better.
[02:28:49.480 --> 02:28:51.760] For a guy, at five watts per kilogram.
[02:28:51.760 --> 02:28:55.120] He was at five millimoles, and now it's at 1.7.
[02:28:55.120 --> 02:28:58.080] This is where the magic happened to this specific athlete.
[02:28:58.080 --> 02:28:59.640] It was at the cellular level.
[02:28:59.640 --> 02:29:01.080] We see this across the board, right?
[02:28:58.960 --> 02:29:06.040] VO2 max at the elite level does not come close to predicting performance.
[02:29:06.360 --> 02:29:07.320] Not at all.
[02:29:07.320 --> 02:29:15.400] This is why we're putting together this study with all this population of different from people with metabolic syndrome all the way from to the France athlete.
[02:29:15.400 --> 02:29:25.720] So longitudinally, we see that, yeah, sure, VO2 max corresponds with fitness in the same manner that watts corresponds with fitness.
[02:29:25.720 --> 02:29:37.880] So we can also imply that instead of doing a VO2 max to look at longevity and fitness, we can also do a power test or speed test and a treadmill because we're going to see the same thing.
[02:29:37.880 --> 02:29:41.960] Those ones who are very poorly active, they have a very poor fitness.
[02:29:41.960 --> 02:29:49.320] They're going to have a lower VO2 max, they're going to have a lower power output, they have a lower speed, lower lactic lens capacity.
[02:29:49.320 --> 02:29:55.560] VO2 max has been forever a great surrogate for fitness, cardiorespiratory fitness and longevity.
[02:29:55.560 --> 02:29:59.480] But we wanted to see if in fact it's really that specific.
[02:29:59.480 --> 02:30:08.440] So in our study, we see that people in different categories at the same VO2 max, they might be in different metabolic states.
[02:30:08.440 --> 02:30:15.640] So some people at the same VO2 max might be oxidizing a lot more fat or a lot more carbohydrates.
[02:30:15.640 --> 02:30:20.920] So that means that does not correspond to the same metabolic status.
[02:30:20.920 --> 02:30:27.560] I would have thought that most people by the time they're at VO2 max they would be disproportionately carbohydrate.
[02:30:27.560 --> 02:30:32.680] So really you're just saying how much fat oxidation still remains there is really what you're saying.
[02:30:32.680 --> 02:30:43.720] And I'm assuming a very untrained person has zero fat oxidation by the time they reach VO2 max, whereas a more highly trained person would still have some amount.
[02:30:43.720 --> 02:30:46.560] They might still be at 0.2 or 2.3 grams per minute.
[02:30:46.880 --> 02:31:01.680] Yeah, for example, we see that like a sedentary individual at 75% of the VO2 max might be around 3 millimoles, whereas a world-class athlete at the same percentage of VO2 max is about one and a half.
[02:31:01.680 --> 02:31:06.240] So metabolically, they're different, yet the VO2 max is the same.
[02:31:06.240 --> 02:31:12.240] So if we prescribe exercise based on VO2 max, we might not do things correctly.
[02:31:12.240 --> 02:31:25.520] And the same thing with carbohydrate, that at a 75% of a VO2 max, like a sedentary individual oxidizes about two grams per minute, where an elite athlete oxidizes about three grams per minute.
[02:31:25.520 --> 02:31:27.840] So that's a significant difference.
[02:31:27.840 --> 02:31:30.800] And we also see it at 50% already.
[02:31:30.800 --> 02:31:34.000] So this is why longitudinally they correspond quite well.
[02:31:34.000 --> 02:31:35.600] And same thing as fat oxidation.
[02:31:35.600 --> 02:31:47.440] Fat oxidation at a 50% of VO2 max is about 75% of CO2 max, 0.23 in a sedentary, it's 0.6 in an elite athlete.
[02:31:47.440 --> 02:31:57.280] We look at the different intensities, for example, at an athlete that can have one millimole of lactate within the same group, not just comparing group.
[02:31:57.280 --> 02:32:06.480] But we can see that someone within the very same group, whatever the category they are, the lactate and the VO2 max don't correlate.
[02:32:06.480 --> 02:32:12.080] The correlations are sometimes either 0.2 or 0.1 or 0.3.
[02:32:12.080 --> 02:32:13.680] That's the R squared you're saying.
[02:32:13.680 --> 02:32:14.480] Yes.
[02:32:14.480 --> 02:32:15.520] No correlation.
[02:32:15.520 --> 02:32:16.720] Very poor correlation.
[02:32:16.720 --> 02:32:25.360] When we talk about individual groups, when we look at specific one parameter, which is lactate, with the VO2 max, it doesn't really correspond.
[02:32:25.360 --> 02:32:40.760] So, anyways, this is what I think that we have learned a lot over these last decades, where we can really pinpoint more at the cellular level to improve metabolism more than at the cardiorespiratory function, which is very important, absolutely.
[02:32:40.760 --> 02:32:42.520] They both are going to improve.
[02:32:42.520 --> 02:32:56.200] But I think that if we want to prescribe exercise, it's going to be more specific if we look at cellular surrogates like lactate, like fat oxidation, for example, than looking at VO2 max or METs.
[02:32:56.200 --> 02:32:58.600] I mean, don't get me into there.
[02:32:58.600 --> 02:33:02.680] That's very prehistoric, in my mom's opinion.
[02:33:02.680 --> 02:33:03.960] I don't want to offend anybody, right?
[02:33:03.960 --> 02:33:11.560] But the whole MET concept used for exercise prescription, it's hard to swallow in today's times.
[02:33:11.560 --> 02:33:15.240] Yeah, I was just about to say, I mean, it served its purpose in the 1950s.
[02:33:15.240 --> 02:33:27.800] When we think about some of the muscle biopsy data, again, this term of mitochondrial function, it's such an important part of longevity because it is one of the hallmarks of aging, is declining mitochondrial function.
[02:33:27.800 --> 02:33:38.120] I usually explain to patients that the type of physiologic exercise that we're prescribing, this zone 2 exercise, is the way to measure mitochondrial function.
[02:33:38.120 --> 02:33:40.760] It's both the treatment and the test.
[02:33:40.760 --> 02:33:44.760] But I'm guessing on the cellular level, there's even more that we can talk about.
[02:33:44.760 --> 02:33:49.720] The last thing I really want to talk about today, because I know we've been going for a while, you've been generous with your time.
[02:33:49.720 --> 02:34:08.200] When you get into the omics, when you start to biopsy the muscles, when you start to look at the mitochondria in a way that we can't do it in a regular clinical setting, what else are you seeing that's differentiating the healthy from the unhealthy mitochondria or the high-functioning from the low-functioning mitochondria?
[02:34:08.200 --> 02:34:09.560] Again, I keep talking about papers.
[02:34:09.560 --> 02:34:15.200] I wouldn't publish it, but we've been working for three years quite hard, and now we cannot continue doing this.
[02:34:15.200 --> 02:34:17.600] We need to start writing the papers, right?
[02:34:14.840 --> 02:34:18.720] You need more postdocs.
[02:34:19.200 --> 02:34:22.720] You need more graduate students and postdocs to help with the writing.
[02:34:23.040 --> 02:34:29.760] But we have completed a pretty cool study, and they're writing the manuscript now looking between sedentary and active.
[02:34:29.760 --> 02:34:41.440] We know already there are a bunch of research showing at the cellular level the difference between people with type 2 diabetes or metabolic syndrome and active individuals or even sedentary.
[02:34:41.440 --> 02:34:48.640] We want to see also, or want to show that people who are sedentary, they already have problems.
[02:34:48.640 --> 02:34:54.720] And we wanted to compare them with motor active people, which should be kind of how we should be as humans.
[02:34:54.720 --> 02:34:57.360] So we looked into the mitochondria, into mitochondria.
[02:34:57.360 --> 02:35:06.640] So we looked at there's significant dysregulation at the mitochondrial level everywhere you look in the mitochondria in sedentary individuals.
[02:35:06.640 --> 02:35:15.440] You see a decreased capacity to oxidize, to burn glucose in terms of pyruvate, fatty acids, amino acids.
[02:35:15.440 --> 02:35:21.120] You see a significantly decrease in electron transport chain as well, all the complexes.
[02:35:21.120 --> 02:35:27.200] And you see also a significantly decreased capacity in the transporters of different substrates.
[02:35:27.200 --> 02:35:54.880] One thing that really caught our attention, and we think that this is something that we really want to emphasize and hopefully others in the future, is that we have identified that there is a mitochondrial pyruvid carrier, which is, as I discussed earlier, that's the transporter of pyruvate into the mitochondria, which is dysregulated already, significantly downregulated in sedentary individuals compared to active individuals.
[02:35:54.880 --> 02:35:58.800] Then we are matching it with the pyruvid flux, the oxidation itself.
[02:35:58.800 --> 02:36:04.280] So both the transporter and the flux are significantly dysregulated.
[02:36:04.280 --> 02:36:06.040] What does this mean?
[02:36:06.040 --> 02:36:11.160] That's going to shuttle pyruvate to the other way it's going to get in the cell, which is through lactate.
[02:36:11.160 --> 02:36:12.680] Exactly, exactly.
[02:36:12.680 --> 02:36:14.200] What are the implications of this?
[02:36:14.200 --> 02:36:18.680] So again, these people don't have diabetes or prediabetes.
[02:36:18.680 --> 02:36:21.400] This could be a healthy person who's not active.
[02:36:21.400 --> 02:36:31.960] And this is what, unfortunately, this has been the model in most research papers out there, comparing the unhealthy with a sedentary health individual.
[02:36:31.960 --> 02:36:40.040] I've been pushing for years that the model should not be the healthy sedentary individual because that is the intervention.
[02:36:40.040 --> 02:36:43.880] As humans, we are meant to walk or to exercise.
[02:36:43.880 --> 02:36:47.880] So we need to look at perfection to understand imperfection.
[02:36:47.880 --> 02:36:52.760] The intervention of human evolution has been becoming sedentary.
[02:36:52.760 --> 02:36:56.840] And in fact, I had a hard time to get IRB, you know, to try this study.
[02:36:56.840 --> 02:37:06.280] I have a hard time with the committee to convince them that using active people as the gold standard to understand imperfection, that's the way to go.
[02:37:06.280 --> 02:37:13.560] But anyways, what we see is that these people already, they don't have clinic, but yet they have a significant down-regulation.
[02:37:13.560 --> 02:37:14.680] They don't have clinical signs.
[02:37:14.920 --> 02:37:16.040] Clinical symptoms, sorry.
[02:37:16.040 --> 02:37:17.240] They don't have clinical symptoms.
[02:37:17.240 --> 02:37:19.400] They're the healthy sedentary individuals.
[02:37:19.400 --> 02:37:25.160] They don't have insulin resistance and they don't have down-regulation of gluthor transporters.
[02:37:25.160 --> 02:37:26.920] Even hyperinsulinemia?
[02:37:26.920 --> 02:37:31.400] Are they hyperinsulinemic when challenged with the glucose tolerance test?
[02:37:31.720 --> 02:37:34.200] These people, they have no symptoms.
[02:37:34.200 --> 02:37:38.600] They haven't reported any glucose trollearance tests, normal people.
[02:37:38.600 --> 02:37:50.880] And then they have a significant disruption in this mitochondrial pyruvic carrier, which might mean that the first door that might be jammed is that entrance of pyruvate inside mitochondria.
[02:37:51.120 --> 02:38:03.040] Most of the research in diabetes has done more at the peripheral level, if you will, glucose levels, more at the surface levels of the cell, the glute for the insulin resistance, the pancreas release of insulin, better cells, etc.
[02:38:03.360 --> 02:38:08.000] But what's the fate of glucose once it enters the cell?
[02:38:08.000 --> 02:38:09.440] And this is what we're looking to this.
[02:38:09.440 --> 02:38:12.800] So, and the fate is pyruvate, but what's the fate of pyruvate?
[02:38:12.800 --> 02:38:18.160] As you said very well, does it enter the mitochondria or is shuttled to or reduced to lactate?
[02:38:18.160 --> 02:38:24.240] So, I think that this is important to see because it could be a marker down the road.
[02:38:24.240 --> 02:38:31.040] Because, again, these people don't have clinical symptoms yet, they have a significant dysregulation in their glucose metabolism.
[02:38:31.040 --> 02:38:37.440] So, could this be 10-15 years ahead of clinical symptoms and insulin resistance?
[02:38:37.440 --> 02:38:43.680] This is more reasonable to consider sedentary individuals to see, hey, they have a metabolic dysregulation already.
[02:38:43.680 --> 02:38:46.480] Same thing we're doing at the fat oxidation level.
[02:38:46.480 --> 02:38:52.400] The CPT1 and CPT2, the transporters of fat, they're significantly downregulated as well.
[02:38:52.400 --> 02:38:59.120] So, that means they're not going to be able to transport fat very well, which also matches to the fat oxidation itself.
[02:38:59.120 --> 02:39:03.120] When we inject fatty acids into the mitochondria, they don't oxidize it well.
[02:39:03.120 --> 02:39:04.960] So, they all match as well.
[02:39:04.960 --> 02:39:13.920] So, they have a dysregulation already that is significant compared to motor active individuals at the glucose metabolism and fat metabolism.
[02:39:13.920 --> 02:39:26.400] Then, we see that many of these people, I mean, who have diabetes or metabolic syndrome, they have what's called intramuscular triglycerides, the fat droplet, and it's adjusted right by the mitochondria.
[02:39:26.400 --> 02:39:45.240] In elite athletes, it's also there, that fat droplet, but it's very active because about 25 to 30 percent of the fat oxidation comes from that fat droplet adjusting to mitochondria, which it could probably is an evolutionary mechanism to not rely on the adipush tissue, which might take time and have something right away there.
[02:39:45.240 --> 02:39:54.760] So, when you say it's metabolically active, the difference between the intramuscular fat of the athlete and the intramuscular fat of the person with type 2 diabetes, is it the flux then?
[02:39:54.760 --> 02:39:58.200] In the person with type 2 diabetes, it's a static source of fat.
[02:39:58.200 --> 02:40:02.760] In the athlete, it's constantly turning over and being oxidized and replenished.
[02:40:02.920 --> 02:40:06.920] Exactly, whereas in this population, it continues to grow.
[02:40:06.920 --> 02:40:13.480] My colleague Brian Bergman from the university is working a lot into the content of what's inside these fat droplets.
[02:40:13.480 --> 02:40:19.000] But one thing that we know is like they're very high in ceramides and diglycerides.
[02:40:19.000 --> 02:40:22.920] And especially ceramides are key in the atherosclerotic process.
[02:40:22.920 --> 02:40:26.520] Atherosclerosis, it's a hallmark of cardiovascular disease.
[02:40:26.520 --> 02:40:28.840] Ceramides are key for this process.
[02:40:28.840 --> 02:40:33.400] Historically, it's been thought and it's been shown that ceramides come from the liver, they're released.
[02:40:33.400 --> 02:40:37.560] But we're seeing that these intramuscular triglycerides are high in ceramides.
[02:40:37.560 --> 02:40:43.400] So, could this be a connection between also cardiovascular disease and type 2 diabetes?
[02:40:43.400 --> 02:40:47.160] In the high-turnover, high-flux one, you're not accumulating them as much?
[02:40:47.480 --> 02:40:48.040] Yes.
[02:40:48.040 --> 02:40:53.080] People who end up having type 2 diabetes, they accumulate fat droplets.
[02:40:53.080 --> 02:40:55.240] Athletes as well, that's the athlete's paradox.
[02:40:55.240 --> 02:40:58.680] But athletes, as you said, they keep turning around and it's very active.
[02:40:58.680 --> 02:41:02.760] Whereas people with type 2 diabetes or obesity, it keeps growing.
[02:41:02.760 --> 02:41:09.400] It releases pre-inflammatory mediators, and it also is high in ceramides, which are key in atherosclerosis.
[02:41:09.400 --> 02:41:16.640] So, this is what we're trying to establish the connections between Tech 2 diabetes and cardiovascular disease at the mitochondrial level as a nexus.
[02:41:16.960 --> 02:41:25.360] Because we know that about 80% of people with type 2 diabetes, they also have cardiovascular disease and vice versa, which is what we call cardiometabolic disease.
[02:41:25.360 --> 02:41:29.280] So, could the nexus of all that a mitochondrial impairment?
[02:41:29.280 --> 02:41:30.720] That's what we believe.
[02:41:30.720 --> 02:41:40.080] Well, what I take away from this is we're probably going to have to do a third podcast in a couple of years because there's going to be a lot of data that's going to be published then that isn't published now.
[02:41:40.080 --> 02:41:43.120] There's going to be a lot more questions that we're going to have answered.
[02:41:43.120 --> 02:41:52.400] Again, I'm still really yearning to understand the effect of metformin in terms of pure mitochondrial function and performance in a trained individual.
[02:41:52.400 --> 02:41:56.000] So, as always, I can't thank you enough for your generosity of insight.
[02:41:56.000 --> 02:42:01.120] And look forward to talking tomorrow when we have a call about some other nerdy stuff we're going to get into.
[02:42:01.120 --> 02:42:09.280] But thank you so much, Inigo, and also congratulations on the remarkable success of your team and Pogacher, who's an amazing cyclist to watch.
[02:42:09.280 --> 02:42:12.560] He's got everybody very excited about the Tour de France again.
[02:42:12.560 --> 02:42:14.880] Well, thank you very much, Peter, all the listeners.
[02:42:14.880 --> 02:42:16.720] I really appreciate what you do.
[02:42:16.720 --> 02:42:21.200] The first time I met you, Kaz, we were two and a half hours talking about mitochondria.
[02:42:21.200 --> 02:42:23.360] And at first I thought, like, this guy's crazy.
[02:42:23.360 --> 02:42:29.280] There's nobody out there who's going to be interested in listening to two and a half hours about mitochondria and metabolic health.
[02:42:29.280 --> 02:42:32.000] You showed me, yeah, the concepts are out there.
[02:42:32.000 --> 02:42:37.360] And I was in a moment where I was, not many people seemed interested in this.
[02:42:37.360 --> 02:42:41.040] And you were already an inspiration for me to continue doing this.
[02:42:41.040 --> 02:42:46.480] And the remarkable work that you're doing to educate people and inspire people.
[02:42:46.480 --> 02:42:47.840] It's transformational.
[02:42:47.840 --> 02:42:49.640] So I really appreciate the invitation.
[02:42:49.640 --> 02:42:50.640] It's such an honor.
[02:42:50.640 --> 02:42:52.160] Thanks for being with us today.
[02:42:52.160 --> 02:42:53.680] Thank you very much.
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