Welcome to the Empirical Cycling Podcast. I'm your host, Kolie Moore. Thank you all for listening as always. And of course, please subscribe to the podcast if you haven't yet already and give us a nice five-star iTunes rating and perhaps even a nice review. Would not go amiss. Thank you so much for all of those. Remember, we're also an ad-free podcast. If you'd like to donate and support the show, you can do so at empiricalcycling.com slash donate. We've also got our show notes up on the website. We're going to reference all the studies. I've even included a couple of the figures from the studies. Although I think a lot of them are actually open access. So not a problem there. And I'm not encouraging people to pirate science, but Sci-Hub is always an option if you are so inclined. And of course, for all coaching and consultation inquiries, please shoot me an email, empiricalcycling at gmail.com. We have always... 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So I'm going to apologize ahead of time, by the way, I've had the flu now for this is going on, getting into my third week. It's been two weeks now. Not fun. No fun. Yeah, so my voice is a little rough. I apologize for that. But yeah, it's going around pretty bad this year. So I got it. What fun. I've been to the gym once and it hurt. So yeah, it's not fun. So I apologize. My voice is probably going to get pretty gravelly and Tom Waits-y by the end of this one. So sorry about that ahead of time. I'm going to ask Kyle to do some lifting for me while we're, you know, getting into here. So the podcast has to go on. And so here we are. And I had gotten over the last month or so, probably 10 to 15 people sent me this study, the Flockhart Overtraining Study in Mitochondrial Dysfunction. and Oscar Eukendrup also had a blog article about this and that's where I actually found the official response from John Hawley and David Bishop that we're going to get into later in this episode too. And so it was a pretty fascinating study and I actually had a lot of high hopes for it at first when I saw the title and I saw the main graphics and I went, oh wow. Maybe this is a clue into mechanisms for overtraining. And I was super excited. So then we went to the study. And we're going to take you through what I went through reading this study and also another study from Nature Communications that is very, very relevant to this. And then we're going to go into, like I said, the Bishop and Holly response to this. They also raise some very, very interesting points. And so, Kyle, why don't you describe... The main kind of graphic that we're looking at here on, you know, does overtraining result in mitochondrial dysfunction? So week one training, week two, week three, and we see different things happening. So kind of describe what we're looking at here that summarizes the study. Yeah, so there are four vertical columns and you have week one, two, three, and four is each vertical column. And each line, there are three. Plots of a particular metric. So these metrics are performance, mitochondrial function, and glucose tolerance. And week one and two, when you're ramping up the load that you can take and you are still below the maximum amount of... Training you can recover from, your performance is going up from week one to week two, your mitochondrial function goes up from week one to week two, and your glucose tolerance goes up from week one to week two. And then week three in that column, when you exceed or you overtrain, you exceed the amount of volume or intensity you can recover from, all three of those things dip down. And so your performance decreases, your mitochondrial function decreases, and your glucose tolerance Decreases. However, week four, when you do less as a recovery week or you are taking it easy, all of those things go back up and actually go back up to a higher point than they were at the start of week three or the end of week two before you got into the overtraining or the sort of red zone, if you will, on this chart. And that kind of suggests that So after you, even if you do overtrain, if you aren't throwing away all of the training that you did, as long as you recover from it, you know, I think there's some fear that, oh, if I overtrain and I take a week or two easy, am I just going to lose all of those gains or something? And you're like, well, no, at least not, not according to this, this chart or not how this chart would not, this chart would not suggest that. Another reason to get into the study is that there are actually a lot of practical takeaways from the training design that they have here and also kind of the things that we see happening to folks. So let's get right into this study because my voice is not going to last that long. So we're going to start with six female and five male athletes in this study. So good representation of women, finally. It doesn't happen a lot in studies, but I love it when I see it. Now here's the interesting thing. They're all recreationally active. They do regular endurance and strength training, but they excluded any potential subjects who were doing more than five hours of systematic training per week or regular HIT training, right? So this makes sense because, well, why would we want this to be the case for our participants? Wouldn't we want well-trained people? Well, well-trained people might get nothing out of the protocol here. We might not see any kind of adaptations. We might see some people responding and some people not. And so we want all of our participants to respond to the training stimulus. And we want to make sure that things like mitochondria are growing and responding to the stimulus. So getting moderately trained people actually makes the most sense for this purpose. So the training intervention, Kyle, you're going to get kicked out of this. HIT session as 5x4 or 5x8 minutes intervals at about 95% VO2 max with 3-minute passive rests. And so week one, light training. Two sessions of 5x4. Pretty dual, right? Week two, moderate training. Three sessions, 5x8 twice and a 5x4. Week three, excessive training. Three 5x8s and two 5x4s. Ugh. Yeah. Week 4 recovery, 3x8, 3x4, 3x8, and then a performance test of 5x4. And it's not explicit, but presumably this entire study was not 4 weeks, it was 5 because the last day is day 38. And the figure says... Oh, okay, yeah. Yeah, so I think that week 4 actually went from week 4 also into week 5. But, you know, the study's not explicit about this, so I kind of had to do a little reading between the lines. The other thing is that in their main figure about this, about their protocol, because a lot of most studies now actually have a graphic, something to represent visually the training protocol. And so it said in their last week, they did 53 minutes of total HIT time. even though doing the math and even though I'm not great at math I can plug things into a calculator minus the test session they had 60 minutes so and also like if you've got 53 minutes of HIT and all of your interval lengths are even that that doesn't add up like to begin with. So a little math error. I don't begrudge them that. I've definitely made some very public math errors, not an issue. But they gave us the protocol. Yeah, the three 5x8s and two 5x4s. That's like when we joke about, oh, just do VO2 max every day of the week. Yeah, no. And the thing is, even with somebody like Corey, where we're just crushing that poor man's soul with VO2 max training, Um, there's a lot of rest days. Like, he only does, like, two to three actual days per week, usually three, of real VO to max training, and the other four are pretty chill. Even if you're, you know, he's riding long, it's pretty chill otherwise. So, um, you know, doing these back-to-back-to-back-to-back, et cetera, et cetera, like, oh my god. Okay, excessive training, yes, probably excessive. Um, nailed it. Got it. So. They did a biopsy before the training started, and after the last exercise session of each block, they did the biopsy 14 hours after the finish of the last session. So that is presumably overnight. So you finish your last session, you have dinner, you go to bed, you get up, you go back to the lab, and now you get stuck with a needle. So while not having had breakfast yet, I would be very grumpy. It's a pretty good training intervention, right? So you're progressively overloading the training and you're allowing recovery and then you're doing a final test. So let's look at the headline now because now we can get right into the results. Mitochondrial dysfunction. So the values we're going to look at here are from state three mitochondria. And so we need to know what that is and why it's important. So in mitochondrial physiology, If you want to see what mitochondria's absolute maximal rate is, you isolate them, and then you throw in a bunch of ADP with everything else being sufficient too, so saturating conditions, and then you measure the rate of O2 consumed, and that gives you a measurement usually in picomoles of O2 per second, and so if you want to normalize it to mitochondrial mass or perhaps muscle mass, if you don't isolate the mitochondria out of the muscle, you're going to get Picomoles of O2 per second per microgram of wet weight. And the authors call this intrinsic mitochondrial respiration or IMR. And we're just going to call it maximal mitochondrial respiration rate or something like that. Because IMR is a bit confusing for reasons that we're going to look at. So in context, the authors state in the intro that, quote, Mitochondrial Capacity is tightly correlated to whole body maximal oxygen uptake, which itself is a strong proxy for metabolic function and health, unquote. All right, so what do we see indeed? Yes, mitochondrial maximal respiration during week three, we're just going to call it hell week, is reduced from 15 to 7 picomoles per second per microgram. And this carries through to many other isolated mitochondrial respiration metrics because they did quite a few of these because once you've got the mitochondria isolated, you could do a lot of interesting stuff. So like leak state and others you can look into. It's all in the paper. You can check it out. And they're all relative to the mitochondrial mass. So the same way you would do a VO2 max relative to weight. is the same thing with these mitochondria. So now we have a pretty good parallel between isolated mitochondria, relative respiration, and whole body maximal oxygen uptake, right? So it makes pretty good sense. And so what happens basically in the study is it looks like the maximal mitochondrial respiration rate goes up a bit from baseline when you go from baseline to light training. and then again to moderate training and then it goes down for excessive training and then only rebounds to sub-baseline levels. So during rest weeks, so that would be like around 10 picomoles per second per microgram versus baselines 12. So sounds pretty bad, right? Yeah. You would... That is not exactly illustrated in that plot they showed at the outset, but yeah. Yeah, so not reaching baseline is not ideal after. Yeah, and actually, you know what's interesting about that is that was the Oscar Yukindrup version of that graphic. In the actual graphic at the top of this paper, which a lot of a lot of journals are now including. So they've got like an in brief section and highlights and yada yada. They actually do look at mitochondrial respiration going up, like over baseline, then going down below baseline, then returning to below baseline. So in the actual paper, that's, you know, that's, you know, well represented. And so I thought it was interesting to start with having you describe that because now we can compare these two things about how some things can get lost even for people who are extremely well-educated like Oscar Yukindrup who can try to draw a cartoon of this kind of thing and replicate the graphic and not quite get it right. So no fault of Oscar Yukindrup's for sure. So, okay, next thing here is oral glucose tolerance test. And we're going to return to all these points, by the way, and kind of break it all down. So this was done with biopsy at all points except for the moderate training. I don't know why they didn't include it there. They must have had some sample corruption or something like that. So this was at rest while overnight fasted. And they looked at the area under the glucose curve for minutes 0 to 120. And so you're just lying there and you ingest 75 milligrams of glucose and 300 milliliters of water every 15 minutes for two hours. And they're looking at blood glucose and watching what happens. And so the area under the curve, which is typically how these things are looked at, is indeed higher. But when you look at the area under the curve, generally speaking, it's not, none of, no areas, like no points are significantly different than any other points from baseline, normal training, or excessive training, or recovery week. Like, they're not quite different. When we look at the area under the curve, yeah, then we get a difference. And so looking at the specific traces, minutes 60 to 90 are actually the only trouble spots that we can obviously see in the actual glucose curves, blood glucose curves over the two hours. Everything else looks actually about normal. And so my thought for this was that actually it's explained by insulin. and how the beta cells can actually fatigue sometimes. So after a week of really, really hard training, I could see them being a little sluggish, kind of getting insulin out. But once you get to the two-hour point, everything is normal. So that's where my brain goes with that. And so the last interesting figure to me, if you're going to read along with this, is 3C. the maximal mitochondrial respiration rate versus the glucose area under the curve. And so plotting these two things together implies at least a correlation if not causality, right? And so because the three normal baseline and rest weeks are all clustered together and the hell week is very, very far away. So graphically, it looks really, really bad. But, you know, we could look at it other ways where it's not so bad. Anyway, last one I think is really interesting is performance, because these are our three big headline pieces, right? So, Kyle, why don't you take a look at C for this chart? So I've got the... figure out in our show notes. So Kyle, look at C. This is the power output during HIT in watts per kilogram. So because they actually recorded power output for two of the regular training sessions and then one for excessive training and then recovery week. So we got baseline, you know, normal, yada, yada. So Kyle, why don't you tell me what you see here? So the first week is, or the first, Bar, is baseline, and it is, it's a number, it's just under 3.2 with an error bar that reaches just over 3.2, maybe 3.3, and then the low training is slightly higher, and then the moderate training one and moderate training two, both of those power outputs are slightly higher than The moderate training two is very much higher than the moderate training one. The moderate training one is only a little bit taller than the low training. But then when you get to the excessive training regime, the amount of power goes down slightly compared to the moderate training or stays the same. Honestly, it's like it goes down like a pixel. Yeah. It's barely noticeable. But then after the rest or recovery, The power output goes way up another, you know, probably 10% on this plot. So the total change from baseline to after the recovery week is something like 30% probably. So I'm like just under 3.2 to 3.5 almost. Is that right? Is that my math right? It's like 10%. Sorry. It's like 10%. So that's actually a pretty significant change. But there is a very big jump between the overtrained regime and then the recovered regime. Yes. And in the second chart that we have here, it actually looks at the delta from one training regimen to the next. For the excessive training, it's actually at zero with an error bar up. So it basically stays the same. But our headline was that performance went down. But we've got actual data here that says it was flat. So I don't necessarily think that that part of the headline actually holds any water. I would say... You know, if you're looking at this kind of training, because, you know, in practical terms, if you're doing like a VO2max block, you know, super, super good responders, although, to be clear, five days in a row is not how you do a VO2max block. But, you know, a lot of people will have, like, kind of flat-ish performances and will look at other stuff to make sure that the training is working. But in terms of power output staying steady, that's pretty normal. Like, so you want to overload a little bit and then recover and then you bounce back better than before and that's what we see happening. Look at... Look at E for this. So the mean VO2 during HIT in milliliters per kilogram per minute. So do you see any flatness when we get to the excessive training? No, it's actually sort of monotonically increasing from baseline to low training to moderate, moderate one, moderate two, excessive and then recovered. You are using more oxygen the whole time. Yeah. And if we look at... Parts F and G for this, we're looking at max heart frequency during HIT and also max heart frequency at 100 watts. So they had people warm up at 100 watts and they hooked them up to a metabolic heart or they tracked, you know, carbs and fat usage and we'll get into that in a minute. But it goes down. Yeah. It goes down once we get to excessive training. So our heart frequency, you know, is probably at, for, you know, low training is Averaging probably 178 BPM. Once we get to excessive training, we're doing like 174 average for everybody. That is a common symptom people always mention about overtraining is the inability to get your heart rate up. I would say this is different from the inability to get the heart rate up because it looks to me like the heart rate is getting up but not as high. which to me for VO2max training is something that we commonly see as VO2max goes up is the stroke volume gets higher. So for the same power output, we're going to see slower heart beating because it's beating with larger volume each time. So we can actually achieve the same cardiac output over the course of 20 seconds or a minute or whatever. But the heart has to work less hard to actually achieve that output. So that's what I see here. And then it recovers a bit for the recovery week. But also, you know, there's also other stuff here, which is like, you know, your nervous system, your heart tissues, like your whatever might be getting a little desensitized to adrenaline also. And so that could be another reason for heart rate depression as well. So there's a couple things here. And, you know, we would have to look at another study to really tease those apart. So that's where we stand with the performance stuff is the performance doesn't necessarily drop like the headline says. It kind of stays flat. Although if you are looking for performance to, like you said, monotonically go up every single training block, then we would see something suboptimal if that's what our expectation is. So I would say that the performance doesn't decrease, it stagnates, whether that's good or bad. The glucose tolerance thing, you know, I would say the quote-unquote intolerance was temporary. And, you know, they actually, in this paper, they actually look at another, we're not going to get into it, but they look at professional athletes, like well-trained athletes, blood glucose throughout the day. I think they measure it every 15 or 20 minutes or something like that. And actually see times where blood glucose is like way higher and way lower than like a control. and so but it's temporary but we don't also have workout times we don't have feeding times like it's it's hard to tell so we're gonna we're gonna let Holly and Bishop discuss that in a little bit so so okay so here's where I want to go with this is I could rewrite the headline as from X is not impaired by excessive training Or sorry, I could rewrite the headline from X is impaired by excessive training to X is not impaired by excessive training or X increases with excessive training. We could take the same data and rewrite the headline many ways. So we could say excessive training reduces blood lactate with the maintenance of performance. We could say it increases fat oxidation during exercise despite increased hexokinous activity. Crazy, right? Increases whole muscle. GLUT4 expression, so that's the main glucose importer, does not show significant impairment of function relative to citrate synthase activity or expression. So if we look at our normal, you know, way to, you know, most studies would normalize things to mitochondrial mass would be citrate synthase activity. So if we, so we don't find any significant differences in mitochondrial respiration if we normalize to that. We also would say it does not impair performance, might stagnate performance. We would also say excessive training does not affect resting metabolic rate, because that's something else they looked at. We could also say excessive training does not show differences between male and female subjects, which across the board is what they found. So I think that's actually a really, really important thing here. It's a big headline. Yeah, that's a nice takeaway. Yeah. We could also say excessive training reduces maximum heart rate during HIT. Increases VO2 Max Despite Performance Stagnation. So, you know, what do we have here as takeaways before we kind of start breaking this down even further? Yeah, I think that this is it. They try. I mean, I think that to maybe give them some credit on the headline of You know, performance decreases. You might expect that constantly training, you should be constantly getting better. And so if you do have a region where you don't get better, if the expectation is you always get better and you do not, that might be a decrease in performance. Like it is a deviation from this monotonically increasing line of measuring performance. I can see why that would be one interpretation or they just, they like splashy headlines, you know. I mean, who doesn't? Yeah, exactly. And who doesn't? And especially when you're trying to get published, a lot of times a splashier headline can help. But I think that this is, I wouldn't, I wouldn't say, it does not seem to me like they were trying to be disingenuous with that title. No, I don't think so. Yeah, so. No. So I've got one more headline for you. Excessive training significantly increases expression of electron transport chain subunits. Because they look at this too. So complex one through four and five increase their expression. And this is something that I think doesn't square with the data at the moment because respiration rate of mitochondria was impaired per total unit of mitochondrial mass during hell week. But if the electron transport chains all got a significant bump, what's going on? Because if we're looking at maximal respiration rate, we're going to maximally tax the electron transport chain that's in our sample. So what happened? 

Well, it looks to me like the creation of new mitochondria does not happen while maintaining the same ratio of mitochondrial proteins. So we probably got a larger bump in volume while getting electron transport chain lagging. So that's the only way I can square this. So remember, VO2 max kept going up even during hell week. And the performance stagnated didn't drop. And so it seems like the pattern of muscle glycogen actually reported in dry weight, by the way, matched actually the performance stagnation because muscle glycogen also the amount stagnated as well. So it didn't increase from moderate week to hell week despite VO2 max increasing. Maximal mitochondrial respiration rate, the IMR, the intrinsic mitochondrial respiration, the quote-unquote impairments are not actually part of the performance drop or stagnation. Like if we see real mitochondrial dysfunction, something we're going to talk about as we get towards the end, by the way, if we see real mitochondrial dysfunction, we will probably see it in the performance. and we see VO2 Max going up and what happens if you screw up your mitochondria? They've got to use that oxygen, don't they? Wouldn't VO2 Max drop? Who knows? Yeah, that's interesting. It seems like it was interesting when I'm reading that plot that VO2 Max just kept going up. And I guess it's not, maybe it's not VO2 Max, but it's peak anyway. Yeah, VO2 peak, VO2 Max, something like that, yeah. But yeah, it's interesting that it keeps going up because your body is doing something with the oxygen, right? It's not going to inhale it and then just have it sit there and then exhale it. Well, if you don't use it, that's what happens, yeah. Right, yeah, yeah, yeah. So it's using it, you know, they're not just measuring the amount of air you're inhaling, they're actually analyzing the gas and so they know that you're actually using it and you're outputting CO2 as a result. So it is strange to like... What, what, your body's doing something with the oxygen. It's not, it's not just giving it away. It's not just, so, that does seem interesting. This is maybe also a glimpse into why the science or studying overtraining and what actually happens during overtraining is so hard because there are all these little different things you can measure and they measured a half a dozen of them and it's a mixed bag of, oh, is it actually How would you actually be able to tell what's happening during overtraining if a bunch of the metrics, maybe they don't conflict, but they don't necessarily present a consistent picture of, oh, this is bad, this is what you should look out for, right? You have to kind of weigh them all together. Yeah, yeah, exactly. And something that we've actually mentioned on the podcast before is that mitochondria in the muscles, they're not maximally taxed in terms of rate. If you get there, chances are you are not a healthy person by a long shot. And I'm not even sure that it is possible even in unhealthy people. So I think it's really interesting that this is something that we're relating to each other because it shows that there would be a disconnect between isolated mitochondrial maximal respiration rate and what we do in the body because if that impairment in respiration rate were really a big problem, we're going to see it in the VO2 max. If we actually hit that max, we would see it drop. But remember what we discussed in Wattstock 40 is that – and actually many, many other Wattstock episodes on like fat oxidation and stuff is – mitochondrial mass, like the surface area to import things like fats and lactate. This is hugely important for our actual rate of ATP production to maintain homeostasis in the cell. It's like one of the biggest adaptations that happens. And so it would kind of make sense based on that, that the body Evolution, would prioritize mitochondrial mass versus making sure that the electron transport chain subunits are actually keeping up with the mitochondrial mass. And they've got to have some, obviously. You can't have none. But the stoichiometric ratio is not quite maintained is what all this data points to for me. And so I think also that this article shows that there's a need to actually define mitochondrial dysfunction. You know, since some people would say mitochondrial dysfunction is not enough whole body fat oxidations, these authors, Flockhart was the lead author on the study. So Flockhart and the other authors say that it's a decrease in isolated mitochondrial maximal respiration rate. Which is it? Do we have other ways of mitochondrial dysfunction? We sure do. We'll talk about that in a little bit. And so, you know, we would really want to have a good way to define mitochondrial dysfunction, but we also need better normalization metrics to make sure that what we're measuring is in fact normal. You know, a consistent stoichiometry between electron transport chain density of subunits and mitochondrial mass, then we're going to get things like seemingly impaired mitochondrial respiration rate at max for isolated mitochondria. So, you know, all this is actually supported in figure five, by the way, for Flockhart because their mitochondrial fission and fusion protein expressions Track with Expected Mitochondrial Biogenesis Responsive Training. So they did include quite a lot of data. I really like the study. But my brain goes right to, I think we need more evidence. What do you think, Kyle? Do we need more evidence? Or is there enough for this paper that we can make any definitive judgments? I think this paper is a good It's a good effort. I am generally hesitant to make any definitive judgments off of just one paper on anything. It's a little risky and that's why probably things like science and nature, the big headlines, have a pretty high rate of retraction because if you have one, just in general in a vacuum, one big headline from one paper is hopefully going to be repeated by someone else or repeatable and not just a one-off result. And so generally it would be maybe a little premature, let's say, or a little too optimistic to go off of just one paper. Yeah, we've got 11 subjects here. You know, like, there's not a lot of statistical power that we can actually confidently have at this point. That is also an excellent point. Yeah. So, I then remembered a study that might tell us a little more about this. So, speaking of... Nature Retractions. No, this paper has not been retracted by Nature. I think it's actually quite robust. Yet. No. I mean, when you say retraction rate, you mean like 1% up to like 4% or something like that. Yeah, it's high. It's not like it's 50% of the papers are garbage. It's just relative to other journals with a lower impact factor that get fewer eyeballs, science and nature tend to have higher retraction rates. I also wonder if that's a fact or an artifact of science and nature getting more eyeballs. So you've got more people being critical of papers and calling for retractions and stuff like that. Could be. Yeah, that would be interesting. You'd have to like normalize it, I guess. Yeah, well, that's for people smarter than me to do. But anyway, so people smarter than me also wrote this next paper. So this paper is really cool because this is the first paper because I remember, you know, back when I was in school, bioinformatics was really starting to be a thing. Like, because really large throughput. Sequencing of proteins, DNA, RNA, stuff like that was really just starting to be a thing. And so it's been a little while since I've really looked into it because first of all, the methods and the math are intimidating to me. But I sat there for many hours learning about bioinformatics and learning how this data was put together. And so it's actually pretty simple. It's like basic bioinformatics at this point. But, and Kyle, I asked for your help at a couple points with this stuff too. So this paper, anyway, Spy Informatics, and they did it on isolated mitochondrial RNA. So when you are adapting to a thing and you are going to increase the amount of protein that you have or something like that, you are going to increase the amount of RNA, which is the thing that goes to ribosomes to make protein. So it's like an intermediate. It's sort of like putting in your order and then that's your order slip at the restaurant. Like give me a burger and fries and a soda. And then you sit there and wait and your burger and fries and soda shows up at the counter after it goes through the, I don't know, five guys ribosome chain. Two patties. So they did this with RNA, they did it with proteins, and they did it with lipid content. So we're not going to look at RNA or lipid content really, we're just going to look at proteins because this is the most interesting and this is what we're after. So they didn't also just look at five or ten things. They looked at hundreds of genes and proteins, like over a thousand actually at one point. And we're going to keep an eye on the closer... Oh, fuck, sorry. So we're going to keep an eye on the classic ones, the same as Flockhart did, like citrate synthase, electron transport chain complexes. And this paper also does this too. And also this paper is open access, by the way. So you can just go to empiricalcycling.com slash podcast episodes and just go to the show notes and click the link and you're going to see everything that we see. if you want to follow along at home. If you're on the bike, I apologize. We'll do our best. You'll need an iPad, like an iPad stand or the paper reader. Oh, yeah, yeah, like right on your stem. So it's like the world's biggest Garmin. So, but peripherally for us, but centrally for this paper, they were actually looking at whether super complexes form to a greater degree than normal with training. So they actually find out that this is not the case. according to their data. But they are also attempting, and here's what I like, a new method to normalize protein expression. So most studies, like with Flockhart, will use isolated mitochondria, and you do this by you take a little bit of muscle, you grind it up in a blender, literally a blender, and you centrifuge it, and then you isolate different fractions of what you've centrifuged because it all separates by weight. and then you can have isolated mitochondria or whatever. So yeah, yeah, two patties, sorry. Yeah, liquid muscle. So let's see, where am I? Yeah, so most studies will use Isolated Mitochondria from Centrifused Muscle Homogenates. And when you see homogenate, that literally means blended up. Or they're looking at citrate synthase activity, which is pretty typical, like Wattstock 37, by the way, the oxidative fast-switch fiber paper that we looked at. They didn't have a training intervention, though. That was just like a one snapshot of people who were well-trained. Past tense. or are still trained well. So when you look at these things in the middle of a training intervention, they might have unexpected behavior. So that's what I like about this paper. So this paper, this is the Granada paper we're going to call it because that's the lead author. It begins its results and discussion section stating that the traditional view is indeed that the stoichiometry between the number of mitochondria and respiratory proteins is constant, right? And this is actually a pretty large tacit assumption by a lot of exercise physiology. And pretty much up until a couple of weeks ago when I was looking at this stuff, I held it too. I mean, I was questioning it a little bit, like I think most people do. Like I even, I remember once I emailed Andy Coggin about this. It's like, Andy, does this happen? He's like, well, yes, but no, but also close enough. Yeah. It depends. Yeah, it depends. It depends like everything. And Andy probably didn't want to. spent all the time explaining it to me, so I understand that. So the other thing is that Granada starts the results section by looking at these pretty typical normalization methods to mitochondrial mass, citrate synthase. They mostly focus on citrate synthase activity for this paper as the normalization method they have for mitochondrial behavior, let's say. and they actually thought that these normal metrics were so kind of blasé that they put them down in these supplemental figures. Nice. Like it wasn't even part of the main paper. It's like you've got to like go to the website, click on the supplementals and then you get them. Like they don't even publish it in the physical nature unless you get like I think there's like maybe a supplemental issue with all the figures maybe. I forget. It's been a long time since I held a physical copy of nature. It's probably a page count cost thing where they don't want to pay the extra fees just to get all of the figures. Yes, a lot of journals make you pay per figure. So I don't exactly know for nature communications what the rules are. Yeah. Anyway, actually, you know what's interesting about the Flockhart paper as well is they also put some of these metrics down in the supplementals. like citrate synthase normalized activity and basically like non-results or like typical results that you would see from typical papers. So, you know, you know, they're very similar papers in a lot of regards and we'll see more of that in a second. So the title is, by the way, ignore this if you don't want any spoilers because this is classic academic writing. So the title is High-intensity training induces non-stoichiometric changes in the mitochondrial proteome of human skeletal muscle without reorganization of respiratory chain content, as in super complexes. There you go. Well, there you go. Yeah. So if that's enough for you, okay. Thanks for listening. We'll see you later. For everybody else, the setup of the Granada paper is similar to Flockhart. And they had also used this same training intervention in a previous study because they knew that it would give them the changes in mitochondria that were needed. So they had 10 male subjects, moderately trained, same as Flockhart, less than four hours of activity per week, not engaged in regular cycling training. So the training intervention, buckle your seatbelts. They did baselines with biopsy, biopsies done after each training period, et cetera, et cetera. So they had a normal training period, which was two weeks, with six HIT sessions. So they did five to seven by four minutes, two to one work to rest. And they maintained the intensity between lactate threshold and VO2 max power W peak. So over FTP for all. So not maximal efforts, but you could imagine some people were having a really hard time at many points. Especially once you got to seven rounds. Yes. Now, this is not hell week. This is hell weeks, plural. So they did three weeks. I can't believe I'm going to say this. These poor people. 40 HIT sessions for 20 consecutive days. Ugh. Let that sink in. Oh man. So I think we also need to redefine what constitutes excessive training as well. So I think five sessions in a week, it's pretty mild compared to this. Yeah, no question here. They're like, we don't want anyone to question our methods. Yeah. Excessive training, we'll give you excessive training. Don't doubt us. Oh God. I think these are Aussies too. So yeah, high standards for excessive training for Australians. So they did. The sessions for the overload week were weeks, sorry, 7 to 10 by 4 minutes or 15 to 20 by 2 minutes, also 2 to 1 work to rest ratios. Oh gosh. Ouch. 20 by 2 minutes. Even at like 90% sounds pretty awful. No. 20, like 20 reps, you just like, just don't even tell me how many left, right? You want a lap counter there, just counting them down so you can look at them occasionally, but you don't have to stare at it. I wouldn't even want that. I would want no feedback. Just like, this is me now, just always and forever. God, these poor people. So the reduced training period was one week. with six HIT sessions in six days with decreasing intervals. So they did 10, 9, 8, 7, 6, and then four by four minutes on the last day. So compared to 20 and 40, I mean, that's a new way to do 2040s too. This is pretty mild. So performance tests. So they did the regular VO2Max step test. They did a 20K TT. and they also made sure that there was 48 hours of no vigorous exercise before these tests but also different than the Flockhart. Remember Flockhart had 14 hours. You finish your last session, you go to sleep after you have some food, you wake up and then you get stabbed and then you drink some glucose serum and then they check your blood glucose and stuff like that. This was No vigorous exercise for 72 hours before these biopsies. So a much, much larger thing here. So I think it's interesting because the flock heart subjects are probably not fully recovered, but were similarly not recovered each time. Similarly, sorry. And the Granada paper made sure that they were better recovered. So 72 hours. Not bad. So Kyle, do you think with 58 hours of extra recovery, we're going to see something similar to the Flockhart paper, where we see potential lagging of respiratory proteins, or do you think it normalizes in 72 hours? I'm going to guess, 72 hours is a while, so I'm going to guess that it comes back to normal, just because you've got a lot of sleeps in there, hopefully, and a lot of food. Yeah. But. Yeah. Well, I thought so too and we're both wrong. Oh no. I know. All right. Let's get into this. So we're going to get right into their proteomics. So a quick note on the proteomics they did here. The caveman way of measuring protein is not to put it on a scale unless you've literally got a whole muscle. So when you've isolated proteins, you can no longer slap it on a scale because Like Kyle, what's the smallest weight that you think a scale can measure? Like against gravity? So you can get, I know for a fact that you can get really nice analytical balances and these costs sort of in the many thousands of dollars. You can get them that will measure Like, I think, micrograms. Yeah, like, fractions of a milligram, definitely. But they're, once you're into that range, like, fractions of a milligram, you know, sort of like... If you want 10 microgram precision, you have to put it in a box to prevent the air from pushing things around. It's got a cup and you tear it and then you put the stuff into the cup or into whatever the weighing dish is or the surface and then you have to close a plastic box around it because just the air currents to go away. Exactly, yeah. Yeah, so they're a pain in the ass. So in an actual wet lab, one of the things that you do is you actually dilute it in distilled water and you measure it against like spectrophotometrically. You just pass light through it and you measure different wavelengths for certain amino acids and you measure it against. known quantities of protein. So you make like a standard dilution series for like bovine serum albumin or something like that. And then you make a standard curve and you're looking for really good precision, like R squared of 0.9999 or something like that is basically the standard. And then you can measure your sample and see how much is in there. But you're looking at a test tube of clear liquid. So that's how little... Protein, you can measure. And if you try to measure that on a scale, it'd be very, very hard. So that is the old school way of doing it. And it's already fairly precise. So it also has a drawback. Like if you have a mitochondrial protein fraction and It has bits of Myosin Heavy Chain or Lactate Dehydrogenase in it. You would never know unless you assay for it. Like you put in chemicals that these things are going to react with and then you look at what happens on the other side. That's how you would look for it. So you don't have the greatest idea of how clean your sample is. There's always going to be some kind of other stuff in it. So we can also do things like you can Western blot, which is basically a highly specific Way to probe for proteins and then you basically run a gel and then you put your stuff in it and then you the Flockhart paper actually has a bunch of gels that they ran. They did a lot of Western blots for this in order to assay how much of a thing you have and they also and when you look at this they have a standard curve and they know how much is in each fraction and they They don't have, like, this is how many micrograms or milligrams of this we have. They have arbitrary units because they're literally measuring how much black splotch they have versus this other black splotch. So not a very precise method. It's precise enough to track large changes over time, but it's not amazing. So one of the things that the Granada paper does that's awesome, they use... Label-Free Quantification. They use mass spec, which uses tiny, tiny samples, but you can get much more precise about what you're looking at and how much, especially the relative amounts. So Kyle, give us the three-sentence definition or explanation of how mass spec works. So a mass spectrometer measures the charge Like electric charge to mass ratio of the molecules or atoms or whatever you dump in. And it does so by applying a known electric and magnetic fields and then measuring how much the path of the molecules or atoms bend in that electromagnetic field. That tells you the ratio of the charge to mass. Yeah, and so there's basically some tube that's curved and there's a detector on the outer wall of the curved tube. Imagine if you walk into a room and the wall on your left is the detector. That's what it looks like. Yeah, and basically just depending on where along that wall the molecules or atoms hit, that tells you something about the charge-to-mass ratio. Yeah, exactly. So they looked at isolated mitochondrial samples and they found... 1,411 proteins differentially expressed across the training phases. So that's how many things changed in their samples across these phases. And so in order to start narrowing this down to just genes for mitochondria and proteins for mitochondria, they compared it against two databases for known or predicted mitochondrial genes. And by the way, mitochondria don't have a ton of genes. They have their own DNA. It's a circular DNA. It's not like the chromosomes that we have. But they don't have a ton of genes on it, but they have some. Most mitochondrial genes have, by this point, migrated to the host cell's DNA. And I say host cell because mitochondria used to be independent bacteria. And so you've got to look for both mitochondrial DNA and nuclear DNA for mitochondria. There are other ways to, you know, suss that out. We won't get into it. But they pulled out proteins that did not match because there were unavoidable sample contamination, like we talked about. And they ended up with 584, which is only 32% of the isolated proteins by mass. Out of the 1,411 proteins that were differentially expressed. So, a lot of contamination, a lot of extra stuff. Like, most of it was from the, you know, sarcomeres and, you know, blah, blah, blah. It's muscle. Like, of course, that's what you would expect. Yeah, you blend it up. You can't, it would be extremely difficult to... somehow take this biopsy and then pre-extract. I guess you could maybe centrifuge it. I don't know how you would go about trying to decrease the amount of extra stuff you get in that biopsy. Yeah, exactly. So it's really difficult to do that. And so I think one of the things that they noted was that they call this in the paper mitochondrial protein enrichment, MPE. and don't worry about that we're not going to spend really any time on it but it might be interesting to note that as people trained the amount of mitochondrial protein in their samples actually went up and it peaked it started at 32% and it got up to 39% after the hell triple so we're going in the direction that we want for this stuff we are now taking a sample of mitochondria and we're really going to be able to look precisely quite precisely at how much protein we have versus how much mitochondrial total protein that we have, mitochondrial mass, et cetera, et cetera. So they went one step further than this. So I said they've got 584 proteins. And they also removed proteins identified in less than 70% of the samples. Okay, yeah. I mean, that seems like a reasonable strategy to try to improve your odds that these are actually... things coming from the mitochondria, not, you know, when you do a biopsy, I'm sure you get some skin in there and, you know, all this stuff. Yeah, exactly, yeah. Yeah, when you do a muscle biopsy, I mean, I've seen them do it. They, like, they sit there and remove fat and connective tissue from it. Like, there's, you know, you gotta, you know, you gotta clean it up. And so, they also removed proteins that were not high-confidence mitochondrial proteins. They're not like, okay, wow, this matches both of our databases, yada, yada. If they weren't entirely sure, they were like, great, get it out of here. So now they go from 584 to 498 proteins total. And so instead of normalizing against citrate synthase activity, which they also did, like I said, as one data point normalized against, they now normalize against all 500 proteins or 498. So does this seem like a better normalization strategy or what? Yeah, this certainly seems like they're trying to give a very conservative way of trying to normalize, right? They want to take only high-confidence things or at least things that appear twice and make sure that they appear in both databases, they appear every time in their samples or almost every time, 70%. So yeah, they're really trying to be as conservative as possible, you'd imagine. Yeah. And they still end up with a ton of proteins to look at. A ton! We're going to hire 500 grad students and each of them is going to get one protein. Yeah. Okay. So if you're reading along with this paper, they have one more thing for us to cover. And this is how they report the fold change from their normalization values. So a log two fold change is a standard omics, like, you know, proteomics, genomics, et cetera, et cetera, way of looking at fold change. So one fold, you know, if it increases like one fold, it goes up 100%. If it increases two fold, it doubles, et cetera, et cetera. So they do, remember a log is an exponent, right? So a log base two is two to the what is my value, right? If a two-fold change is reported as Kyle is what? Four, it'd be one, like a factor of one, you know, or factor of one is not correct. It'd be an increase of one, a unity increase. Yeah, yeah, it's a log two-fold change of one. So a four-fold change reported as two, eight as three, et cetera, et cetera. So it's a nice way to linearly scale, you know, this kind of stuff. And so a lot of it, when you look at log twofold change in a lot of these informatics papers, they will color code it. And so you can look at a very large swath of proteins, like the group, like 30 proteins together, or 30 RNAs together. And they'll look at... They'll color code the log twofold change so you can actually visually see real quick what goes up and down over the course of some intervention. You add some chemical to this thing, it goes up or goes down. It's pretty, pretty simple to see and interpret that way. And you can also get technical with it. They also have all of their supplemental data is available if you want to download it and run your own analysis on it. It's pretty cool stuff. That is kind of cool. Like, that's nice that they give away their data like that. Like, a lot of people feel this weird sort of extreme, I don't know, possessiveness over their data, and once the data have been collected, and even though they publish their paper, they are, some people are just weird about giving it away or letting other people see it for whatever reason. And I understand for a lot of people, They want to be the first to publish on the data they collect, which is fair. But once you've published on it and you got to be like, first, hey, look at this new data, it kind of feels, especially if you're supported by, you know, public funds like government research, it kind of feels like you should make it publicly available after that. Yeah, that's our data. I paid taxes on that. Yeah. You get the first crack, sure, because you did it, but you did the work. primarily. Although I've heard of also another thing, this is a little sidetrack, in academia where if you are aware of a major property of something, you can leak papers out and make predictions about stuff too. So you can increase your output and you can also increase the predictive value that you have of certain things if you know how something works and nobody else does. And so this can actually be something to really improve your, I guess, brand as a scientist? Yeah, I guess if that's what you're into science for. Yeah, I don't know why anybody would be, but I hear about it. Anyway, so I think the other thing about the log twofold change is that once you look at this paper, the normalization method that is used, does not mean that your first value is zero. So your fold change might start as plus two or minus two and go up or down from there. So if something starts from plus two to minus two, that's quite a large fold change to see. It's not like, oh, wow, it's just like minus four. It's like that is a huge amount of reduction in expression. Yeah, absolutely. Yeah. It's kind of – that is one reason why sometimes log is nice and also log can be deceiving. Yes. So what is our result? So as spoiled in the headline, yes, indeed, proteins in the electron transport chain are deprioritized during times of mitochondrial biogenesis. So we're talking about log FC values from – Plus 2 to Minus 1 or Minus 2 between baseline versus normal training values and also from normal versus the intense training period. And so, Kyle, do you have this paper up? Yeah. Let's look at normalized versus – or non-normalized versus their best normalized. So best is their way of – their name for their own normalization scheme of like isolating proteins and looking at only mitochondrial proteins, et cetera, et cetera. Oh, so clever. Ha, ha, ha. Yeah. So, I mean, look at complex one for electron transport chain, like not normalized versus they're normalized. So like, what's the difference in the two? It's huge. Yeah. Yeah, yeah. You see, so what they do in these plots, they show the grayed out area of their, of all of the proteins, and then they highlight the ones that they think are the ones they want to track for their best normalized. And so it gives you an idea of the fraction of total amount of proteins as well as the ones that they were actually looking at, how much they change. And again, it is a little weird just because it is a little bit of a log plot, but... Okay, anyway, so yeah, so normalized versus non-normalized is, yeah, it's fascinating because in the normalized, complex ones through five, they all start at like a, you know, like a plus two or something like that, and they all drop to like minus one. Yeah, and immediately too, right? It's just with, it's not even, it doesn't even take getting to the intense, clearly overreaching regime. Yeah, it's baseline to like the first, the normal week of training. So, and then they start to creep up again. Like even through hell weeks, plural, and then, you know, the reduced volume week. Like they just, they have a linearly increasing amount. But one of the things that I think is fascinating is the mitochondrial ribosomes. Baseline, they start low. And they increase in a linear fashion until you get to hell week. So this is post three hell weeks. We have increased linearly mitochondrial ribosomes and then it starts to drop. So why does this make sense? That we would want to increase mitochondrial ribosomes at the same time that we are probably having a large increase in mitochondrial mass. Well, ribosomes are there to replicate DNA, right? Not DNA. They make proteins out of RNA. Yeah, sorry. They read the RNA and they make the proteins. So if you are actually making proteins and you need to make more proteins, you can't make ribosomes work faster. So you have to parallelize it. Yes. Yeah. So it's really cool. Like during these expansion periods, or what we would expect to be expansion periods and judging by the increase in mitochondrial protein fractions which you can actually see in figure 2a. So the mitochondrial proteins they have as purple over like a salmon kind of thing and the mitochondrial protein amount is increasing linearly along with ribosomes and then it starts to decline once we get from the hell weeks to recovery week. But once we normalize it, straight across the board. So anyway, so this is, I think, fascinating. So I spent probably too much time staring at figure two. I also spent too much time staring at figure three. Beyond that, it's a little beyond our scope, but it's fascinating nonetheless. So yeah, so no, we do not have a steady stoichiometry. We do not have a steady ratio. Between mitochondria, the volume, and mitochondrial respiratory proteins. So, you know, kind of like I speculated, you know, probably 20 minutes ago, this is actually what happens, that we get mitochondrial expansion because it's more important to be able to consume substrate for the other kind of transport chain in a large, you know, more surface area, more import area. This is more important than having mitochondrial electronic transport chains because our electronic transport chains are not maximally taxed. So that's what is happening. And what I think is also interesting is that even with the extra 50-whatever hours of recovery from Flockhart's 14 to the Granada's 72, we still don't see this normalization, which is why we're both wrong. Yeah, that's fascinating. I mean, so you're really digging a hole there with that extreme overtreating. Yeah, yeah. And this is exactly how Flockhart and probably many others would see decreased mass-specific respiration rates, or mitochondrial mass-specific, since we're maxing out what's there in the electron transport chain when they're isolated. But, you know, having more in the sample would increase the maximum, you know, we've been over this. One more thing that really interests me here before we wrap this paper up. So in addition to everything else they did, and this is figure three, they looked at six clusters of mitochondrial proteins designed to do certain tasks. And the clusters don't break out exactly the way I expected them to. So some of them are Krebs cycle and fat oxidation, some of them are for translation, some of them are for electron transport chain, but it's like 70% of the Krebs cycle proteins. This one has, this cluster over here has 30%. They might. be close on certain areas of DNA and usually be co-expressed together. It might be something like that. I'm not entirely sure. But they looked at the two consecutive periods. So they compared baseline versus normal, normal versus excessive, and excessive versus reduced training using their normalization methods. So two things that stand out to me is that during recovery after the three hell weeks, the cluster that had the biggest increase That was, you know, it was deprioritized during the training and then increased while recovering, cristae formation and protein import. Like, I don't know why, this is so fascinating to me. It's because you're a nerd, that's why. Yeah, because, I mean, what's so important about cristae? So, cristae are the very, very inside folds of mitochondria. So this is what textbooks would call invaginations inside the mitochondrial membrane. And so this is where we get electronic transport chain stuff happening. Like this is where it all happens. That makes sense. It's a way to internally have a lot more surface area. You think about charcoal or things like that as opposed to being just a smooth ball. It's a very wrinkly surface on the inside, and that adds a ton of surface area. Yeah, and so it goes from, you know, like a minus one, minus two expression to like a plus one, plus two. You know, some genes are kind of neutral-ish, but this is the biggest change that I see from training to non-training for all of these. And other things are really interesting, like proteins for translation have the, you know, they actually... Drop Off After Excessive Training. Mitochondriol Fatty Acid Beta Oxidation, 30% of Krebs Cycle Proteins, 25% of amino acids and derivatives proteins. These have the highest expression from baseline to normal. And then they drop and then they start to come back up. So you could stare at this figure as long as I did and just keep... going, oh, wow, that's interesting. But nothing that we can really talk about too much at this point. Yeah, when you sent me this figure, I was like, this is an intense figure. I've seen some figures in my day, but there's so much going on. You're just like, uh. I know, bioinformatics, right? It's just so much information at once. Because the figure caption is on a different page, you're like scrolling up and down and being like, wait, what's part A, part F, like, ah, what am I? Yeah. It's a lot. I know. That's one of the reasons this took me so long to kind of get my head around it. But yeah, I expect most people who are reading this are like, oh, it took you that long? I'm sorry. I'm not that smart of people. I'm just doing the best I can. So anyway, so Wattstock number 40 kind of goes into more details again about why more mitochondrial service area. might be more important than electron transport chain stuff, et cetera, et cetera. So the other thing is that... Would you say that Wattstock number 40 is a non-friction episode? I would say WD-40 is intended to create less friction in some ways. Just don't leave your chain with WD-40. So the other thing that's interesting to me is... Figure 3. So they have Krebs cycle, TCA cycle, they have each protein expression, and also subunits of each protein. So isocitrate has four subunits. They look at each of the subunits, or no, not isocitrate, alpha-ketoglutarate, you know, suction, et cetera, et cetera. So I am fascinated by this stuff. because a lot of the Krebs cycle stuff actually has its highest expression from going to baseline to normal training and then starts to fall off a little bit as we get into recovery week. But it still looks like it's like lagging until we get to recovery. But we have the same thing happening with fatty acid oxidation. We have the same thing happening with protein folding. We have the same thing happening for reactive oxygen species formation, mitochondrial translation, so that's ribosomes and stuff like that. All this stuff has the highest expression going from baseline to normal training. And if we scroll down to the second half of this, so this is our electron transport chain. Oxidated Phosphorylations. We have subunits for Complex I, Assembly Factors, et cetera, et cetera. All has the lowest expression going from baseline to normal training. And then has some more expression going from normal to excessive and then, you know, et cetera, et cetera. And so looking at the two, this actually supports our hypothesis that being able to consume more fats and lactates are much more important. than maintaining the electron transport chain stoichiometry and normal mitochondrial physiology because during excessive training, you've got to really, really be able to support the ATP demands and this is one of the best ways to sustainably without, you know, with the least amount of homeostasis disturbance. This is another reason why during excessive training for Flockhart, we saw the highest amount of fat oxidation because we had the most mitochondria. We have the most surface area, even if our electron transport chain density isn't quite as up to snuff as we might expect it to be. Yeah. Yeah, and kind of like you keep saying that the electron transport chain is not the limiting factor. Like, just raw processing volume, like throughput of all this stuff as you're working so hard is what all, you know, making more mitochondria is addressing. Yeah. Okay, cool. So do we have any more thoughts on this article before we push on to our last topic, which is the Hawley and Bishop response to Flockhart? I found a five-gram maximum weight analytical balance that will measure one microgram increments, and it's only a cool $11,000. And it probably takes like one or two grand. and maintenance fees every year too. Yeah, calibrating this thing must be an enormous pain. Yeah, but oh my God, can you imagine having a kitchen scale like that? I mean, this thing maxes out at five grams though, so. So no. Maybe to measure out like five grams of creatine, that's it. You're very precisely loading like espresso shots with it or something, you know, I don't know. Oh, there we go. If anybody does that. Let me know. I'm curious about your setup. Okay, so let's get into the Hawley and Bishop response. So I didn't actually know that this existed until I read the Oscar Yukindroop article about it, about this paper. And then I was like, oh, I got to go back to my show notes and actually add this in. So I'll have a link to this in the show notes as well. So they go through a lot of background information. They go through a lot of pretty standard stuff. But they have a couple really good points, a very good different take than I've got on the Flockhart paper. So their first point is to question whether isolated mitochondria can be representative of all mitochondria, like in the same muscle even. And so, you know, this is... You know, this is me talking, but I think this will probably remain an open question until somebody wants to get biopsied a whole lot more during a whole week protocol. Oh no. Like imagine getting 20 or 30 biopsies from like your quad muscle on the outside, your vastus lateralis. Yeah, in three weeks, like a biopsy a day. God. Well, you would want to get them all at the same time. So not a good time. Although if somebody wants to do that, I bet somebody out there is starting to set up that study as we speak. They're going to get so many participants. Yeah. So many. I mean, because so many people probably read this Holly Bishop thing. They're like, oh, that's a good experiment. We should do that. So if you're probably in Australia, which is where this is probably going to happen, go sign up for it. So Holly and Bishop also follow this up. with the fact that in muscle fibers, both skinned and permeabilized, they show normal respiration function versus isolated mitochondria. So what are we talking about here? So when you take a muscle sample and you get all the bits off of the outside of the muscle, you can actually take off the muscle sarcolemma, the muscle membrane, and have isolated muscle fibers, basically. And now you have a good way to get your solution into them very quickly because the membrane is the barrier between the inside of the cell and the outside. So when you remove that, you can actually have muscle fibers operate somewhat like normal, but also kind of not. It's an interesting prep where we don't quite have all the data to relate to whole body, yada, yada. So yeah, anyway, it's a really interesting prep. And so it's actually a very common prep because Granada did this prep as well. Flockhart did not do this prep. They were looking for isolated mitochondria. But they did have mitochondrial max rate normalized to citrate synthase activity. And Bishop and Hawley point out that these were not significantly different when normalized to citrate synthase activity, which is, as Bishop and Hawley point out, the normal method. to normalize respiration in all mitochondrial-related things. So they're basically saying, you know what? This might be a nothing burger. Don't worry about it. It's isolated versus normalized. If we normalize to our normal usual thing to show mitochondrial mass, not a big difference. It doesn't take a hit. Yeah, and this is one of those things when you... read the nature paper when they're looking at all this normalization like it that it was definitely when I was reading the in the skimming the paper like oh there's a huge sort of question mark in there about this normalization scheme and they they try their best and certainly that's probably where lots of people will can take the same data and give you significantly different results, you know? Yeah. Yeah, I mean, I mean, how many times have I done that in the past where, like, I'll open up, you know, determinants of endurance, you know, that coil paper, and they've provided so much data, I'll go, oh, I wonder what the correlation is between these two things, and I'll just be able to do my own analysis on it. I've done that, I don't know, five, ten times over the last couple years. So, yeah, it's... Anyway, so guess who did do the permeabilized muscle fiber prep? Granada. So, right? Now, do we have any guesses on if the respiration rate was impaired for the stripped muscle fiber as opposed to isolated mitochondria? Did we see a reduction in maximal respiration rate per unit muscle mass? Hmm. All right. Time's up. Yes or no? I'm going to say no. I thought yes. I was wrong. You're right. It's no. See, now I'm going with what I think is not, like, since we were wrong. Yeah. So, yeah, so relative to muscle wet weight, because you can't dry it out and have functional muscle, it was not impaired for how weak. And in fact, it actually kept going up. Not significantly different from the normal training, but it was trending up a little bit. But, you know, basically, statistically, the same. Even more interesting, Granada normalized the muscle mass-specific respiration to their mitochondrial protein normalization. Like, their particular normalization method. Straight across the board. Yeah, so like, so muscle mass, like per unit, like doesn't matter what the mitochondria seem to be doing. It seems that they're just fine. Like they're able to process the same amount of oxygen, given saturating conditions, like maximally, in muscle, the same, pretty much no matter what, like given these normalization schemes. Yeah, that's interesting. Oh, man. Well, and also, I think as much as I like the Ganada normalization scheme for looking at all these proteins and picking your 498 of your best friends to track, and this is the kind of specialization that a lot of labs don't have the ability to do. You've got to get your mass spec and you've got to get people who know how to work that stuff and you've got to do all the stats and you've got to do all the number crunching. It's difficult. It's a whole project in and of itself, yeah. Yeah, and so this is like the start of finding a good way to normalize things. But for now, if we're looking at citrate synthase activity, normalizing to that, that also shows no significant differences across the board for both Granada and Flockhart. through these training sessions. So that might just be a fine method to use with the asterisk knowing that it may not always have a good stoichiometric consistent ratio during periods of training adaptation. And as long as you know that going in, then you can take that into account. Yeah. So the other question raised by Hickson and Bishop, is they actually focus in on the 14 hours for Flockhart after the last training session before biopsy. And so this is me reading between the lines. They seem to be implying that they caught the mitochondria mid-adaptation with mitochondrial pants down, if it were. Very tiny pants. If mitochondria wore pants, would they wear them like this or like this? I will make that a meme. Actually, I don't know if I have the Photoshop skills for that. So lastly, they ask whether the maximum mitochondrial aspiration rate for isolated mitochondria can actually cause a role in whole body glucose control. Because they note that it's difficult to reconcile reductions in glucose tolerance when whole muscle GLUT4 Expression on Whole Muscle was the most abundant. And also whole body fat oxidation peaked. Because if we look at our, you know, some of our other ways to talk about mitochondrial function or dysfunction, if fat oxidation is peaking, this is a sign of mitochondrial function, according to some, and not dysfunction. So we have, again, they're pointing out that the data doesn't quite square for what the headline is. But this is also pretty typical of headlines. Yeah. I think it's also interesting because you're getting into this regime of, yeah, you want to know why, like, okay, so in a vacuum, you say like, oh, you're training too hard and you're not recovering. Why aren't you recovering? And you're like, oh, well, it turns out, just like everything else, we're even recovering and adaptation to training has all these different knobs to turn. And so you can spend decades, right, of people chasing, trying to chase down all this stuff. And it takes some pretty advanced science and methods to track some of these things down, which is one reason why this is so difficult. And it's not just, oh, we can just track this one metric and we know how close you are to overtraining. Yeah. Yeah. Yeah. And, you know, I swear, like, I was so hopeful for this paper and I'm still hopeful for... you know, for, uh, for science to uncover something, but, um, you know, it looks like for now, at least the Flockhart paper does not give us what I hoped it would. Um, cause I honestly, like I, I was like, as soon as I saw the headline, I, I was hopeful too. Uh, I, I immediately opened up a new show notes and I was like, what's up number 41 over training question mark? Like, are we going to have a potential mechanism? And the answer is, uh, no, unfortunately we don't. Although maybe we do. Who knows? I don't know. Is this part of a mechanism for overtraining? Is this something that we see happening in people who are chronically overtrained and chronically just hating exercising and feeling sluggish and lethargic? Is this something that happens? I don't know. Should we check them out? Probably. So I think it really provides an interesting potential window into a gap in our understanding of not only over training, but also just exercise in general. Like we still don't know a lot of some things that might be considered fundamentals about mitochondrial biogenesis. Do certain proteins maintain stoichiometric ratios during mitochondrial biogenesis, like, you know, in response to training? Seems like no. Some yes, some no, and I'm sure that there are even a lot more details to be sussed out. You know, what if we do threshold training? What if we do endurance training? These are all high-intensity training. So there's a lot more questions that this opens up, like good science does, which is why both the Flockhart and the Granada papers are excellent for this kind of thing. So anyway, Holly and Bishop make one last point in their response, which is that, you know, they're talking about our gaps in our understanding, too. They're talking about the need to integrate cellular, tissue, and whole body level responses in context of each other. Because this is actually one of the, I've said this in the podcast before many times, where being able to go from cellular mechanism to whole body performance is a really, really difficult bridge to build. Yeah, that sounds hard. Like, and you think about this, all these metrics were very, you know, essentially cellular level. Measurements, right? You're doing muscle biopsies. So, you know, you're very down in the weeds, quote unquote, relative to whole body things. Yeah. And I agree with Bishop and Hawley fully. But I think we should take this a step further because this is Wattstock and if it's worth doing, it's worth overdoing. And, you know, in regular old Mythbusters fashion, not that we're Mythbusters, although. I wanted that job for the longest time to be on that show. It did seem like a cool job. Oh my God, yeah. So, I think we need a better definition of mitochondrial dysfunction. So, clearly in Flockhart and Granada, mitochondria are probably functioning just fine. I think it's interesting to see if the overtraining goes longer. Will we get to a point where we see some actual dysfunction? Like, is, the question is, like, is this, like, the first step for overtraining? It's sort of like, if you're overtraining, you know, your power output stagnates. First step in overtraining. Once it starts to go down, you know, that's possibly non-functional. Like, if your threshold is 300 watts one day, and now you're really, really training hard, and you feel like it's only 270, that's a problem. So cellularly, in terms of mitochondrial physiology, is this uncovering a first step? We don't know. I don't know. Well, mostly I don't know. Maybe somebody else out there does. I hope to talk to them someday. So for Flockhart-Granada, mitochondria seem to be functioning just fine because periods of hard training happen to people and they come out the other side all right with enough recovery, of course. So are mitochondria dysfunctioning when you're training hard? Probably not. Others, though, will define mitochondrial dysfunction as not using fats. Just sort of weird. Yeah, like whole body fat oxidation is reduced. Why? Is this mitochondrial dysfunction? But typically when I see this, I don't see any attempt to control for known factors that improve fat oxidation like mitochondrial mass. So they have even less type of normalization than Flockhart or Granada do. Like no citrus synthase activity, no total mitochondrial protein content, like none of that kind of stuff in terms of normalization. But do you know what real mitochondrial dysfunction looks like? Elhan, Lieber Hereditary Optic Neuropathy. Kyle, you used to be pre-med, you know this one, right? I've heard of it, but I don't remember anymore. Yeah, it's rough. It's a bad one. This is one of the ones that I remember from school, which is there's a mutation somewhere in mitochondrial DNA that causes an actual dysfunction of complex one in the electron transport chain. So using NADH to shuttle electrons and protons into the electron transport chain is greatly reduced or like not done entirely. So this results in a loss of color vision. Eventual Blindness, because the function of complex one is impaired or lost. And the eyes are hungry for energy. So mitochondrial dysfunction means pathology. And so clearly there's a pathology in overtrained people, but we still don't know why it happens. And we can see normal mitochondrial dysfunction, if we can say mitochondrial dysfunction is normal to any degree, we can see it as neuropathies. Diabetes, Seizures, Heart Problems. And as far as I know, they're all genetically produced. Mm-hmm. Yeah. And so I would hope the authors of the Granada and Flockhart papers would have definitely noted if their participants started losing their vision or having seizures or heart problems. It sounds like one of those drug commercials where they're like, side effects include. 40 high-intensity workouts might include punching investigators in the face. And so also remember, how many things were going well during the excessive exercise training in Flockhart, from improving fat oxidation to improving VO2 max, despite this performance stagnating? Yeah, it's interesting. And I think too, like, It is, yeah, the word dysfunction is like a, you know, there's no formal definition, right? Like, especially, I'm sure in these contexts, people are using dysfunction in a much more colloquial term and not necessarily meaning a specific pathology or pathologies like this. And so, I think this is one of those realms where the crossover between science and then, like, popular science gets a little messy. Yeah. Yeah, it does. Although I, you know, I attempt to do the same thing sometimes. I certainly want to, you know, bridge these things. And it's hard. It's genuinely hard. Because, you know, we can't yet directly compare function of isolated mitochondria versus in permeabilized muscle fiber preps versus whole body athletic performance. They haven't been investigated in relationship to each other enough that we can draw any conclusions. It's like how many times in science, like if you look at like one isolated thing, then you put it in the context of a whole, its behavior entirely changes. Right. Right. Yeah. Or its behavior doesn't matter because it's never at a rate limit or whatever. So that's part of what we're dealing with here. So this is literally the edge of science. We've gotten here on the podcast before, and I wish I had better conclusions for people. I apologize for that. But I think we can definitely say five HIT sessions in a week and 40 in two weeks is probably too much. I think we can conclusively say that. We found two training protocols that are too much for most people or for many people. Yeah, although actually I think it's interesting because You know, this is another thing that Bishop and Holly mentioned is this was a one-dimensional training program. It's only high-intensity training. And most training programs don't look like this. You know, even when I've got people doing VO2 max training, the rest of the training is very, very easy. Very, very easy. And so... I mean, I... I wonder too if it's a time thing where if you wanted to do an overtraining study with aerobic base volume like 30 hours a week, 40 hours a week. Yeah, I think you'd have to. Yeah, for sure. And that's another thing where you have to get people to do that. It's going to be difficult to get somebody to ride a bike 40 hours a week and how do you control the intensity, et cetera, et cetera. But, you know, they, Holly and Bishop and, you know, everybody listening obviously recognizes the fact that if you want to overtrain somebody, you're going to have to fucking crush them with intervals. And that's going to be the easiest, most effective, time-effective way to do it. And they did. So I think that's probably, you know, a pretty obvious reason for this. You know, the next big step in, you know, getting a overtraining protocol would be to figure out some kind of thing that's all intensities. Like, you remember the Hickson study, you know, heavy squats and deadlifts, like four or five days a week or something like that. Yeah. Oh. For eight weeks, nine weeks. Oh, man. Yeah. I want to see, see someone having to do like. 8x20 sweet spot or something for their overtraining sweet spot, you know, or something ridiculous. Like, oh, every day, 6x20 for four weeks. I mean, that does sound like that Niels Vanderpool training. He's like, 4x30 at threshold, five days a week. Okay, Niels, have fun with that. Actually, I think there's one more thing that these papers prove that we need beyond a doubt. Recovery. So, snacks and naps, everybody. Snacks and naps. We need a t-shirt that says snacks and naps. Oh, that's a good one. Yeah. I will say, though, I guess in hindsight, it kind of makes sense that the extra 72 hours maybe wasn't enough if these people are just so royally beat up. from 40 sessions in two weeks. Well, actually, I think it's pretty telling. I actually had a thought to write that down for our notes, but I didn't. But I figured you would think that up, which is we don't have a recovery day and after, or even like two or three days, and after that, we're like back to 110%. Like that's not how long the super compensation takes. It can take, you know, many days. It can take a week. It can take more than a week. Like, so it clearly takes a little while for things to normalize and, you know, having mitochondrial proteins and cristae, you know, come back up to normal and, you know, the mitochondria not having to support so many freaking ribosomes, you know, that can, you know, be a big energy sink is just like making and maintaining ribosomal content. And so it can definitely seemingly take some time. And if you've got more mitochondria and they're going, hey, we need extra stuff, yeah, you're going to have to take some time to adapt it seems. That's another thing that these papers are definitely showing is that you are not fully recovered. Everything doesn't return to baseline like after a couple days or weeks. And the question I would have also is how long does it take for things to recover to baseline? Or are these stoichiometric ratios changed once we are well-trained and forever training from being sedentary? Another open question. So that's, like I said, another reason that these papers are great is they ask more questions than they answer. Well done science always gives you new avenues to chase down. Yeah. That's interesting too because I don't know the answer but I would be interested to know what, so your body has to constantly overturn cells and renew and regenerate just, you know, your skin, all the the tissues in your body like just get turned over periodically, right? So what fraction of that, like how much energy does your body spend doing that versus the amount of energy your body spends recovering from exercise? So you figure basal metabolic rates, right, for people are, can be thousands of calories and you figure doing a lot of exercise you may burn, you know, another thousand 1500, 2000 calories, however many kilojoules you burn on your long ride. But that's not energy that you're – not all that is energy that your body is then subsequently using to recover. Like what fraction more, you know, of your basal metabolic rate goes up because you're recovering? Or like, you know, you hear people like they crash and they break a bone. You're like, oh, you should probably eat a little bit more when your body's like, oh, we got to like heal a hole in your bone or something like that because that's a very – like intensive process. That is actually a very interesting thought because they measured basal metabolic rate in the Flockhart study. And give me a second to pull it up. And if I'm not mistaken, it was pretty much the same. However, there is definitely a thing called the EPOC, E-P-O-C, Elevated Post-Exercise Oxygen Consumption. Right. Where, and this is why after like a super, super, super hard training ride, you're going to have elevated heart rate the next morning, stuff like that, because your body's still repairing itself and it takes oxygen and energy to do that. And so as you are, excuse me, and as you are recovering, it takes more energy. Oh, here we go. Resting metabolic rate in kilojoules per minute. So they did this before the biopsies. And it looks like there was, yeah, nothing. Really nothing. Although visually I see there is a little bump for recovery. But yeah, nothing really. And here's the thing is that, you know, all this kind of thing is more complicated because you might be more lethargic afterwards. So you might have the same, you know. Energy Expenditure Needs, but you also might not get up and move as much because you're tired. And so that energy would be spent on repairs. And also, like, it just also can show that sometimes, you know, you're not going to be breathing hard when you get up in the morning after a hard workout, right? Because that would be a sign of, oh, wow, oxygen consumption is really elevated. Yeah. Although... I think everyone, a lot of people are probably familiar with that feeling of you get done with a hard workout and you're still hot, right? You're warm and you're sweaty even though you're done and you're like, yeah, my heart rate's definitely up. I am warm for not doing anything. And then also that like fatigue where you hit a certain training volume and intensity and you're just like, I am a shell of a person at work. Like I just can't, I can't think I'm just, you're like, oh, I gotta look at the calendar when that rest week is coming because you're just like, oh. Absolutely. Yeah, so I think, yeah, recovery, snacks and naps. Anyway, you want to get to a couple Instagram questions? Yeah, let's go. Before we go. All right, so I love our listeners, by the way, because they ask great questions. I took a sneak peek at one or two before we started recording, and there are only a couple at that point. But, yeah, great questions. So the first one, Is it this dysfunction that in fact elicits the signaling to create the adaptation we want? And I would say that it is probably, so the quote unquote dysfunction would be electron transport chain proteins lagging behind mitochondrial volume. And I would say that there is probably some kind of sensing mechanism. Obviously nobody really knows exactly how this works and it's probably decades before we even get a clue, but that there's probably some kind of mechanism where, yes, when these things lag, there is some kind of sensor that says, okay, we need to bump up these things that are lagging. So that would be possibly, yes. That answer. I know, it's the most hand-wavy, it depends, I'm so sorry. I mean, everybody now, you all know as much as I do about the study, so, you know, you can make up your own mind about this. My answers are just mine. I have not thought any of these through. I like that question a lot, by the way. So, not a question, but make a drinking game anytime you say mitochondria is the powerhouse of the cell. I just said it, so drink. That's the first time though. I don't think we said that. We'd never said that the whole rest of the previous episode. No. So thank you, kind listener. How much overtraining is too much overtraining to get adaptations versus crash and burn? This is actually a really interesting question and I don't exactly know. With VO2s when I'm coaching somebody, we'll get to a point where somebody's legs kind of fall off and then we recover as much as needed. that's pretty normal. Uh, and well, for the way I operate anyway, uh, for threshold stuff, um, you know, sometimes it's like that's, well, I think this is one of the other reasons I like TTE training. It's like adding time and zone. Cause when you stop adding time and zone and you're like, man, I'm only at two weeks into a three week block. What am I doing? You are, you might be riding too hard besides that. Besides the intervals, you might not be recovering very well. Like it exposes a weakness. And so, you know, yeah, I don't know. Because, you know, you can't just retread old pathways. You can't do the same thing because your body doesn't get that stimulus to adapt. We've said this on the podcast probably hundreds of times. And so you do have to overreach at some point. Where is the limit? You know. I don't know, but I recognize it when I see it. That's a terrible answer. I don't know what pornography is, but I know it when I see it. Yes. Kyle, you can tell Kyle's a Supreme Court fan. Yeah, there you go. Yeah. Does overdoing volume cause the same results? We do not know. I mean, obviously, yes, it can. You've got to build up to the volume. So if you go from couch to, like we were saying, like 30, 40 hours of riding easy a week, sure, especially if you're not eating enough or sleeping enough, yeah, yeah, why not? But there's another question where you don't know what the conversion rate is, right? Like, oh, how much overtraining, you know, an hour of too much zone two you would think is going to be less overtraining stimulus than an hour of HIT intervals. But Yeah Yeah, so like we said before, you know, these studies open up a lot of questions, and that's one of them. But I would also say, typically, if you're overtraining while doing volume, you're probably riding too hard or not eating enough. Possibly both. What if we come up with a new metric that gives you more TSS if you eat less? I think that's stupid. Why would anybody do that? No, I did see that, and I think it's a good way to encourage people to not eat on their rides, which is a horrible idea. A terrible idea, yeah. Like, even when I was doing experimentation with, like, low glycogen rides, you still have to eat on the ride. That's, like, you don't just go fasted, like, you eat on the ride. And just because the ride gets harder... while you are riding doesn't mean that you are actually increasing adaptation because that's the implicit thing about training stress scores that you're increasing training stress and tacitly on the other side, there should be adaptation. So I don't see that happening if you're not eating enough on your rides. Typically, if people are not eating enough on their rides, their adaptations actually don't happen. And so I could see if that score, I didn't read into it, but I just saw the basics. But if that score were like, we're going to increase what we expect your fatigue level is, but dock you for adaptation, okay, yeah, sure, I could see that. So I don't know a lot about it, but at first glance, I was not a fan, but I probably am misunderstanding a lot of it. So I apologize if I don't want to malign something I don't fully understand. So I retract calling it stupid. I reserve the right to pass judgment at a later time. So how big was the overtraining and what does an easy week look like? Okay, so 40 workouts over threshold in 20 days is pretty big overtraining. And I would say that their easy week where they go from 10, 9, 8, 7, 6, yada, yada, down to 4 intervals. was probably a little rough. It's definitely a reduction in the training, but it's not like a proper recovery week. Calling that easy. Yeah. It's not easy. Yeah. Easier. Yeah. And to be fair to them, they all, both Flockhart and Granada called it reduced weeks instead of recovery. I kept calling it recovery because I keep thinking about recovering and going, ah, I don't have to do 40 more workouts in the next three weeks. So yeah, so a proper easy week I would say is like one or two days off the bike, probably one or two days recovery rides and maybe like a two, three hour kind of easy moderate pace group ride and then kind of make the call about how you're doing for the next weekend or next training block. So what are the signs of mitochondrial dysfunction? So for whole body, yeah, you're looking at like real problems, like real pathologies. Diabetes is another sign of mitochondrial dysfunction. Named diseases, not just, oh, I feel tired because I've been riding my bike too much. Yeah. Oh, actually, you know what I thought was really interesting while I was researching mitochondrial diseases is when you get mitochondrial disease, diabetes, rates of losing feet and stuff like that are apparently reduced. So it's a slightly different kind of manifestation, I guess, which I thought was really interesting. Yeah. So, do we have to find this overtraining or just stop at the limit? For the purposes of the study, you kind of have to find the overtraining, but, you know, I think there's, yeah, so did they train more than they needed to? Yes, that is overtraining. Is it overtraining, like chronic overtraining, like a lot of us probably think of when we first hear that word? No, it's not. because you recover on the other side of it. Like chronic overtraining, it takes you months and you possibly never recover. So that's, you know. It's a very different realm. Yeah. Yeah. Not a question about the study. I'd like to hear your story about overtraining and burnout and learnings. I was one of those more is more people before I knew shit about shit. And I fucked myself up good. I really did. I was doing stuff like 8x1 minute all out followed by threshold training and I was doing many, many, many days in a row and by the time I got to my first race of the season which was bat and kill I was out the back in about 10 miles and then I took that summer off the bike and pretty much what I learned is don't do that. The hard way, yeah. I don't have any like really acute memories of extreme overtraining aside from my 10 years as a competitive swimmer doing like 20 hours plus a week. I'd say that qualifies as chronic overtraining. But it was not acute, right? It was just the like, you're like, oh, we are, you're in a slog. Yeah, you're always tired. You're always tired. And I think it was fairly evident to me that I was definitely always tired maybe a little bit more than other people because sometimes we would have bigger meets, bigger competitions and we'd rest two, three, four days before them. So not very much, but a lot compared to just training through everything, which is what most in-season competitions were. And I would still swim like shit and a bunch of my teammates would go faster and it's like, oh, the three days easy or whatever, not enough. You know, and I remember coming back from a lot of training trips. We'd go to training trip into Florida in January and spend 10 days, 10 to 14 days training two times a day. They'd give us every, what was it? They would give us every eighth or every seventh session off. So if you're doing, you know, double days every day, every once in a while, you gotta, there were two days where you only did one workout. Jesus. So anyway, so that – Fucking swimming. I'm sorry, but oh my god. Katie's got the same stories about swimming whenever we talk about it. Yeah. She's rightfully much more upset about it in hindsight than you are. I think you should probably – where's your moral outrage, Kyle? I have Stockholm Syndrome. No, but a lot of times we would have a meet like the weekend after getting back and I remember just like – Swimming all of the races that I was racing and just being like, I'm not even going to look at the time that I went because I know it was so bad that it's not even recording as a memory, like it's not even worth recording as a memory as a time, you know, you're just like, oh, you know, and it made sense because we got back then and then our big championship meet was in February so you like destroy yourself in January and then you have a three or four week taper into championships and it worked but like, ugh. I think that actually highlights something really interesting which is people have a different tolerance for that kind of overtraining and also it might actually reveal that some people have different strategies during the training of like being able to kind of dog the workouts a little bit so that way you're not slogging through it like you and I have talked about maybe on the podcast I forget about Way back in the day with Russian and Bulgarian weightlifters, how their coach would sit to one side and to reduce the load, they would load the bar differentially, like 10 kilos less on the far side and they got used to cleaning and jerking less weight like that just to get a little bit of recovery in on that left side. Oh, God. My strategy was just blowing up. You'd be cruising along in a workout, right? And it'd be like the equivalent of a VO2 max workout or a threshold. Sweet Spot Session. And eventually I would just like blow up and not be able to hold the pace anymore and just like get lapped basically was my strategy. Like, because yeah, you'd be like, I'm going to hold on until, until that feeling of like when you're doing VO2s or when you're doing, you know, hard anaerobic work where you're just like, I literally cannot keep going. You know, like your body's just like shutting it down because this is, this is clearly. too much. Obviously, you get more fatigued and you're overreaching more. For me, you're probably just going more anaerobic every time. Yeah, you just blow up and die. That was my strategy. Oh, God. That sounds terrible. All right. So, next question. For those of us who can't measure mitochondrial respiration slash OGT or glucose tolerance, are there any clearly defined... Quote-unquote friendlier. So are there any better ways? Yes, I actually have an easy way to watch for fatigue and overtraining, which is your RPE at threshold. It's that simple. Like, does threshold feel like threshold? It feels harder? Maybe you need some rest. If it feels easy, great, you're getting more fit. It's very, very, very simple. that's it there's and having a good RPE when you're feeling good and like kind of keeping that in your memory or in your periphery somehow is it's absolutely necessary so you've got to start with a good baseline because if you start with what threshold feels like when you're on death's door that's not going to be a great reference point for you yeah peak power also a good one that correlates really well with being recovered. So if your sprints, watts are looking pretty decent, all right, you're probably good to go. If they're kind of shit, maybe you need a better warmup or maybe you're really fatigued. So that's something where you need to really consider what your situation is and why things might not be right. Same with threshold. Like if your threshold feels terrible and you haven't eaten enough that day, Maybe you should go eat more and maybe things will feel better. So there's, um, it's, but it's just a good way to start cluing in on something's off. Uh, if, if you don't get on the bike right away and feel something's off, some people can, uh, I'm kind of hit or miss with that kind of thing. Um, I always need a couple efforts usually to figure it out. So, um, yeah, that's, those are my two easy, uh, kind of not quite foolproof, but, um. Reliable ways to gauge fatigue or being off. You mean heart rate variability connected to a 12-lead EKG isn't your go-to? I have a 1-lead EKG that barely works. For all of you with a home 12-lead, maybe 6-lead is probably fine. I think 6-lead is reasonable, definitely. Let's just hook that up to the metabolic cart too. Yeah, just get all the data all at once. Next question, what's the mechanism here? Excessive reactive oxygen species? What's going on long-term on a chronic level? So long-term on a chronic level, we don't know. I wish we did. It's not adrenal fatigue, that's for sure. That used to be the mechanism of overtraining, is your adrenal glands have a hard time producing epinephrine and norepinephrine and yada yada. But it turns out that that's not the case. Yeah. It's been very definitively disproven. Yeah. It sounds like a nice explanation. It's just not. Oh, way back in the day, I gave it to people too before I knew any better. I was like, oh, it's adrenal fatigue. And the thing is, if having an explanation of some sort for people is enough to go, okay, yeah, I need to chill out. And I think some people are like, oh, it's not adrenal fatigue. My adrenal glands are fine. Some people will keep going. Carry on. Not everybody. But some people will be like, ah, that's pupkiss, whatever, just keep hammering. It's fine. Actually, I think it's interesting to note, this is why I love our listeners so much. So excessive reactive oxygen species. There is on, I've actually looked at this quite a bit because for a little while I was thinking maybe it is reactive oxygen species. The answer is actually no. There is not excessive reactive oxygen species produced during times of overtraining. And I've seen quite a few papers now that look at this. And actually, the amount of things like superoxide dismutase and catalase and all sorts of stuff that are made specifically to counteract reactive oxygen species, they actually increase in expression. Superoxide and other reactions of oxygen species, things like that are actually reduced typically during times of training because that's one of the basic mechanisms of adaptation is you have to mop these things up or they're going to really damage your cells. And so that is like something that does not seem to happen. because for a long time I was like I had on the back of my mind is that's a potential mechanism for overtraining and I downloaded a lot of papers that I half read and I was like I'll just really get into these later and then I started seeing stuff that was like oh maybe that's not the case and it seems not to be so if the Flockhart study down to figure six The headline for figure six, oxidative stress is maintained during excessive training owing to reduced mitochondrial H2O2 emission with a simultaneous loss of NRF2. There you go. Last question. Would functionally understanding mitochondrial function and its fatigue lead to better training modalities? I think it might. If, you know, not only, not... quite understanding mitochondrial dysfunction because we have to define that first. But yeah, understanding mitochondrial physiology better and muscular physiology and mitochondria's role in the cell and what normal training adaptations look like versus abnormal training adaptations, excessive training adaptations, what they look like. Yeah, I think that that would possibly help quite a bit. I think we're a long way from that though. Yeah, more science, please. People do more science. We like science. All right, Kyle, so where are we at? Let's put a bow on this. Yeah, we still don't know a ton about exactly why overtraining happens, nor have we, unfortunately, identified a go-to fail-proof metric for telling you when you're getting too close to the sun. It'd be cool if we did, but we don't. That being said, as you kind of said, there's a holistic way you can kind of view. There are a couple sort of self-checks, sanity checks that you can use in addition to if you just take a step back and just listen to your body generally. You feel like shit. That's a pretty good sign for overtraining. Ideally, yeah. In the future, there would be some sort of metric where even if it was kind of inconvenient to get and it was like a blood test, at least that could be a useful definitive tool in high-performance sports, national teams, Olympic teams, things like that, where you could arrange for team doctors to do this or something like that. That would be super interesting. But unfortunately... You know, if muscle biopsies aren't a very clear, yeah, practical solution, like odds that something as simple as like a blood test would be able to tell you this, you know, secret metric that we're all searching for, also kind of low. So, you know, it's just, it's interesting and it feels like one of those things where you're it's not you're not even like tantalizingly close you're just like oh if I just you know this seems like the right route to go down but you still feel like you're really far away from being able to say a lot of definitive statements on this is why overtraining happens aside from just you're doing too much and your body can't keep up like that that is in a holistic way just saying you know your body can't keep up with the demands you're placing on it that's true right that's a Yeah. No, I wonder about that in the long term too because – so yeah, when it comes to all the stuff like – nothing that we've seen today says that you should deviate from your normal amount of training routine except for maybe more recovery if you're not getting enough. That's really about it and having a good sense – Kyle, like you said about some people tapering for like two or three days not being enough for you and – Being Enough for Others, getting a good sense of where you personally are in that spectrum versus your normal training routine and training load is actually a great idea because some people do way better with more recovery and some people need recovery and then to kind of get their legs back under them with a little bit of riding and training first. And knowing where you are there is a big, big thing to watch for. And also everybody's got personally different signs of overtraining. Like I get really, really grumpy when I'm training too much. Even if I'm eating enough, like I just have the worst brain fog because, you know, what we do is all like, it's all neural, like it's all maximal contractions, like a lot of the time. And so I get that kind of fatigue from it. And I, when I was doing endurance training, it was very much the same. So if that was me personally, it may be you, it may not be you. So individualizing that kind of stuff is something that's quite necessary. So yeah, is that about wrap us up? Yeah, sounds good to me. All right. So if you like this podcast, we don't usually get into papers like this where there's not much on the other side of it. for actionable conclusions. Like usually I like to have something that people can go, oh cool, I know this about this or this will inform me about this. This will inform you about, you know, different normalization schemes for mitochondria and all that kind of stuff, but there's not a lot of practical takeaways here really. So if you want to hear us do more of this, let me know. DM me on Instagram or respond to one of the AMA questions on the weekends or email me. Let me know because we can do more of these because there's a lot of papers out there that I think are really interesting where I'm like, eh, there's nothing on the other side of this. I don't know if we can turn this into a good Wattstock episode. Yeah. Although I would say the takeaway here is if someone tells you that they have a clear-cut reason on why overtraining happens or the impetus behind overtraining symptoms, they're wrong. Yeah. Oh, no, for sure. I mean, I think, actually, I think we talked about, this was on a podcast, I forget exactly which one, so many now, where I think I was saying that, you know, having the, you know, the background that I do, it doesn't give me that much better idea for new training methods, but I feel like it allows, at least me personally, it allows me to sniff out things not to do. Because you can go, oh, this won't work because this, this, that, and the other things. And everything I've learned, for the most part, really reinforces the basics. And it's not sexy, it's not fun, it's not a good headline grabber of, you know, ride your bike and have a snack. That's not a good headline. Actually, it's a pretty good headline, but... But yeah. Yeah, sometimes this stuff is more about recognizing the BS and recognizing the hype people versus actually having a good practical takeaway. And so I think in a way it can be helpful because I think if we can help people... you know arm themselves with some kind of knowledge like this then they can actually make better decisions for themselves rather than potentially jumping on every single training bandwagon which not everybody does obviously but you know I'm not beyond it myself for sure so hopefully we can save some other people some time that kind of stuff all right so Thank you everybody for listening. Subscribe to the podcast as always. iTunes ratings. Thank you all for all of those. Reviews wherever you listen to your podcasts. Hopefully they're nice. Appreciate them. We're ad-free, so if you'd like to donate to the show, empiricalcycling.com slash donate, and of course we've got our show notes up on the website, empiricalcycling.com, head over to the podcast episodes, or yeah, you can get a link to all the studies, especially the nature one is open text, I remember, Flockhart maybe, I forget. But go check out the studies. They're really, really fascinating. And honestly, even if you only look at the figures, that is the way I start reading every paper is I look at the figures. If they've got a main point, it's going to be in the figures. Like, go understand those. Read the captions. It's good stuff and let me know if you have any questions on that. I'm always happy to help. So if you have any coaching or consultation inquiries, email me, empiricalcycling at gmail.com and of course we are always taking on athletes and we are always looking to do consultations to answer your questions. Our time is your time. We will look at your training files. We can consult with coaches. We can consult with teams. We can do the whole shebang. Up on Instagram, Empirical Cycling. We get an AMA stuff in the stories and if you would like to stalk these stories and ask some questions for future episodes, I will. gave you a prompt and you can ask some questions on what we're going to be talking about. So thank you everybody. Thank you for sticking through my raspy voice. I apologize for that. Hopefully I'll be better for the next episode. So we'll see you then. Bye. Thanks everyone.