WEBVTT 00:00:00.000 --> 00:00:01.960 We talked about the differences physiologically 00:00:01.960 --> 00:00:03.899 between males and females, and we talked about 00:00:03.899 --> 00:00:06.160 how the fiber type, you know, fiber sizes are 00:00:06.160 --> 00:00:08.380 different, but also the proportions, right? And 00:00:08.380 --> 00:00:10.839 how those proportions then influence metabolism 00:00:10.839 --> 00:00:13.820 is huge. So if you have more type two fibers, 00:00:13.960 --> 00:00:16.100 which is what we see generally again in males, 00:00:16.160 --> 00:00:18.019 generally depending on training status, then 00:00:18.019 --> 00:00:19.699 you're going to have more glycolytic pathways, 00:00:19.859 --> 00:00:22.719 which is reliance more on carbohydrates. When 00:00:22.719 --> 00:00:25.160 you have more oxidative fibers or type one fibers 00:00:25.160 --> 00:00:28.260 in females, you're going to have more capacity. 00:00:28.920 --> 00:00:34.640 to utilize fats as a fuel. Hi, Shani. It's my 00:00:34.640 --> 00:00:36.840 pleasure to have you on Evidence Strong Show. 00:00:37.000 --> 00:00:38.740 If you could briefly introduce yourself. Hi, 00:00:38.759 --> 00:00:40.960 Alex. Thanks so much for having me. So my name 00:00:40.960 --> 00:00:43.920 is Shani Landon. I'm a postdoctoral researcher 00:00:43.920 --> 00:00:46.920 at the Hudson Institute studying genetics and 00:00:46.920 --> 00:00:49.399 physiology. Other than research, I also compete 00:00:49.399 --> 00:00:52.979 over 800 meters. So it kind of gives me an extra 00:00:52.979 --> 00:00:56.500 interest in understanding how our bodies work 00:00:56.500 --> 00:00:59.500 when we adapt and when we exercise and having 00:00:59.500 --> 00:01:01.799 a kind of molecular explanation for that. That's 00:01:01.799 --> 00:01:04.920 perfect. The paper you just published is titled 00:01:04.920 --> 00:01:08.540 Physiological and Molecular Sex Differences in 00:01:08.540 --> 00:01:11.900 Human Skeletal Muscle in Response to Exercise 00:01:11.900 --> 00:01:16.180 Training. Let's start with the most obvious and 00:01:16.180 --> 00:01:19.560 burning question, which is what are the differences 00:01:19.560 --> 00:01:22.980 in physiology between females and males? If you 00:01:22.980 --> 00:01:25.140 kind of break it down into the different organs 00:01:25.140 --> 00:01:27.719 or the different tissues that we have. So males 00:01:27.719 --> 00:01:30.640 tend to have larger hearts, which means then 00:01:30.640 --> 00:01:33.209 larger stroke volume. higher cardiac output, 00:01:33.450 --> 00:01:37.010 that males have larger lungs and cross -sectional 00:01:37.010 --> 00:01:40.010 areas of their conducting airways. Males have 00:01:40.010 --> 00:01:43.000 more... hematocrit and hemoglobin in their blood 00:01:43.000 --> 00:01:45.879 cells and more hemoglobin mass, stronger bones, 00:01:46.120 --> 00:01:49.280 more dense, and with what it means for muscles 00:01:49.280 --> 00:01:51.819 then and for adipose tissue. So males have a 00:01:51.819 --> 00:01:54.299 higher proportion, and I'll talk a bit more about 00:01:54.299 --> 00:01:56.920 this and kind of how this links in to the sex 00:01:56.920 --> 00:01:59.120 differences that we discussed in the paper, but 00:01:59.120 --> 00:02:01.379 males have a higher proportion or tend to on 00:02:01.379 --> 00:02:04.340 average of type 2, so the fast twitch glycolytic 00:02:04.340 --> 00:02:07.140 muscle fibers, while females, again, on average, 00:02:07.200 --> 00:02:09.000 and it depends on training status, will have 00:02:09.000 --> 00:02:11.870 a higher proportion of the type 1 or the slow 00:02:11.870 --> 00:02:13.909 twitch muscle fibers, the oxidative ones. With 00:02:13.909 --> 00:02:15.830 adipose tissues, there's a different distribution 00:02:15.830 --> 00:02:19.770 of fat between males and females with also males 00:02:19.770 --> 00:02:23.050 having relatively less fat percentage. So a healthy 00:02:23.050 --> 00:02:26.180 male on average versus a healthy female. on average, 00:02:26.319 --> 00:02:29.159 males will have less fat. And that kind of sums 00:02:29.159 --> 00:02:32.580 up the components of the organs that we would 00:02:32.580 --> 00:02:34.020 think about when we're thinking about physiological 00:02:34.020 --> 00:02:36.139 performance. And what that then contributes to 00:02:36.139 --> 00:02:39.400 is males, quote unquote, outperforming females 00:02:39.400 --> 00:02:43.139 or having higher personal bests by 10 to 30 percent, 00:02:43.199 --> 00:02:46.259 depending on the event. And that will then contribute 00:02:46.259 --> 00:02:48.500 also to strengthen many different aspects. So 00:02:48.500 --> 00:02:51.550 in females. relative strength between the upper 00:02:51.550 --> 00:02:53.590 body and the lower body is that females have 00:02:53.590 --> 00:02:55.669 more relative strength in their lower bodies 00:02:55.669 --> 00:02:57.530 compared to their upper bodies while that phenomenon 00:02:57.530 --> 00:02:59.689 does not exist in males so that just means you 00:02:59.689 --> 00:03:02.050 know if you're if you're squatting more as a 00:03:02.050 --> 00:03:04.310 as a female and not able to do as much bench 00:03:04.310 --> 00:03:06.810 press like there's potentially a bit of a physiological 00:03:06.810 --> 00:03:10.530 explanation for that and then that the relative 00:03:10.530 --> 00:03:13.349 between males and females is that again on average 00:03:13.349 --> 00:03:17.659 the males upper body strength is 157 percent 00:03:17.659 --> 00:03:20.479 of the females upper body strength and for the 00:03:20.479 --> 00:03:23.580 lower body strength it's about 60 percent more 00:03:23.580 --> 00:03:25.960 so that just shows you that the discrepancy is 00:03:25.960 --> 00:03:28.080 much greater in the upper body between males 00:03:28.080 --> 00:03:30.939 and females than it is in the lower body so yeah 00:03:30.939 --> 00:03:33.900 despite those differences in in strength and 00:03:33.900 --> 00:03:36.580 the capacity males and females still from what 00:03:36.580 --> 00:03:39.099 studies have shown are able to increase their 00:03:39.099 --> 00:03:41.960 strength to the same degree and so respond and 00:03:41.960 --> 00:03:44.379 adapt to the same degree and that the differences 00:03:44.379 --> 00:03:46.560 in strength between males and females tend to 00:03:46.560 --> 00:03:50.259 appear more due to the muscle mass rather than 00:03:50.259 --> 00:03:53.120 the force generating capacity of each unit. So 00:03:53.120 --> 00:03:55.580 it's just the fact that there's more muscle fibers 00:03:55.580 --> 00:03:57.919 and they're bigger that can produce more force. 00:03:58.139 --> 00:04:01.360 What are the molecular differences we know about? 00:04:01.599 --> 00:04:04.000 So I kind of think about this is that there is 00:04:04.000 --> 00:04:07.639 multiple levels of kind of the molecular profile. 00:04:07.860 --> 00:04:09.800 So you have, we'll go through the central dogma 00:04:09.800 --> 00:04:12.500 just to... The central dogma for genetics is 00:04:12.500 --> 00:04:15.009 that you have... DNA, which is the same in every 00:04:15.009 --> 00:04:17.550 single cell of your body, essentially. And that 00:04:17.550 --> 00:04:23.060 DNA then so gets transcribed into mRNA. the messenger 00:04:23.060 --> 00:04:25.000 RNA, and that will be different between different 00:04:25.000 --> 00:04:27.800 cells, between different tissues. And that mRNA 00:04:27.800 --> 00:04:30.600 then gets translated into proteins and proteins 00:04:30.600 --> 00:04:33.120 go on to have their function within the cell 00:04:33.120 --> 00:04:35.439 and to communicate between other cells. There's 00:04:35.439 --> 00:04:38.600 then several layers of what we call gene regulation. 00:04:38.740 --> 00:04:43.000 So basically impacting which genes, so the DNA 00:04:43.000 --> 00:04:45.660 component, in the end get translated into proteins. 00:04:45.759 --> 00:04:47.519 And there's kind of many steps in which you can 00:04:47.519 --> 00:04:50.139 affect that process. So one of the ones that 00:04:50.139 --> 00:04:52.399 we looked at, which is type of... epigenetic 00:04:52.399 --> 00:04:55.339 modification. So epigenetic is kind of how our 00:04:55.339 --> 00:04:57.660 genes are interacting with their environment, 00:04:57.779 --> 00:04:59.819 with the environment in the cell. And that can 00:04:59.819 --> 00:05:01.899 come from a lot of different factors. It can 00:05:01.899 --> 00:05:04.379 be our diet, it can be our exercise, our sleep, 00:05:04.420 --> 00:05:06.819 the different toxins that we have that can interact 00:05:06.819 --> 00:05:09.139 with our DNA. And they don't change the sequence, 00:05:09.180 --> 00:05:11.879 but they tag on different things onto the DNA. 00:05:12.079 --> 00:05:14.779 So one thing that can get tagged on is what's 00:05:14.779 --> 00:05:17.420 called a methyl group. So then it's called DNA 00:05:17.420 --> 00:05:19.879 methylation because a methyl group gets tagged 00:05:19.879 --> 00:05:23.180 onto the DNA that then determines how tight or 00:05:23.180 --> 00:05:25.579 how open the DNA is. And that can then decide 00:05:25.579 --> 00:05:29.300 which genes get then transcribed into the mRNA. 00:05:29.540 --> 00:05:33.839 Then we have another process that is the microRNAs. 00:05:33.839 --> 00:05:36.160 And that's different than the mRNAs in that the 00:05:36.160 --> 00:05:38.879 microRNAs will find an mRNA and they'll say, 00:05:38.980 --> 00:05:41.620 oh, we're going to go attach to that one and 00:05:41.620 --> 00:05:44.160 degrade it. So that then influences how much 00:05:44.160 --> 00:05:46.819 mRNA is present in the cell. So that's another 00:05:46.819 --> 00:05:49.060 level. And then there's other levels of gene 00:05:49.060 --> 00:05:50.790 regulation that I won't go into. into because 00:05:50.790 --> 00:05:52.709 I won't talk about them today, but there's other 00:05:52.709 --> 00:05:54.930 components as well. So it's not so, you know, 00:05:54.930 --> 00:05:56.910 it's just those two. There are different levels 00:05:56.910 --> 00:06:00.410 in which the DNA then gets decided how much protein 00:06:00.410 --> 00:06:03.149 of that gene is left in the cell at the end, 00:06:03.170 --> 00:06:05.129 if that makes sense. Okay. So in your study, 00:06:05.189 --> 00:06:09.230 you took biopsies of females and males and you 00:06:09.230 --> 00:06:13.850 check what is the state of molecular translation. 00:06:14.699 --> 00:06:17.199 in these cells, including the effect. So including 00:06:17.199 --> 00:06:20.379 the final product, the proteins that were produced. 00:06:20.680 --> 00:06:22.980 Yeah. So the first thing we wanted to do was 00:06:22.980 --> 00:06:25.319 to just see at baseline, what are the differences 00:06:25.319 --> 00:06:27.220 between males and females in the muscle? Because 00:06:27.220 --> 00:06:29.779 at the time it was not even ever looked at or 00:06:29.779 --> 00:06:32.339 known if DNA methylation even differs between 00:06:32.339 --> 00:06:34.180 males and females in muscle. It had been shown 00:06:34.180 --> 00:06:36.439 in blood, it had been shown in some other type 00:06:36.439 --> 00:06:39.360 of cells, but not in muscle. And then same thing 00:06:39.360 --> 00:06:41.939 with proteins. We didn't know on a kind of global 00:06:41.939 --> 00:06:44.160 level. So when I say global, it means that With 00:06:44.160 --> 00:06:46.800 our methodology, we used high -throughput methods 00:06:46.800 --> 00:06:49.839 that are now very common practice, but it's technology 00:06:49.839 --> 00:06:53.480 that's come out in the last couple decades or 00:06:53.480 --> 00:06:56.779 decade or two, and they basically allow you to 00:06:56.779 --> 00:06:59.420 look at... all of the proteins or, you know, 00:06:59.420 --> 00:07:02.639 thousands and thousands of genes at one time 00:07:02.639 --> 00:07:04.680 when it comes to DNA methylation as well. So 00:07:04.680 --> 00:07:06.860 it gives you kind of a genome wide is what we 00:07:06.860 --> 00:07:08.740 call it, or a picture of kind of everything that's 00:07:08.740 --> 00:07:11.480 going on in the muscle. And because those methodologies 00:07:11.480 --> 00:07:13.920 have, you know, developed over time, I say they've 00:07:13.920 --> 00:07:15.500 been around for a decade or two, but that's kind 00:07:15.500 --> 00:07:17.480 of like, it depends on which component we're 00:07:17.480 --> 00:07:19.620 looking at. And also the development with it 00:07:19.620 --> 00:07:21.660 has meant that it's become a lot more sensitive, 00:07:21.800 --> 00:07:25.040 a lot more accurate in the quantification. So 00:07:25.040 --> 00:07:27.290 what we were able to see is that that just at 00:07:27.290 --> 00:07:30.410 baseline, before anyone does any exercise, there 00:07:30.410 --> 00:07:33.189 are thousands of genes that show different methylation 00:07:33.189 --> 00:07:35.850 in the muscle between males and females. And 00:07:35.850 --> 00:07:38.230 that then means that we expect them to have differences 00:07:38.230 --> 00:07:40.569 downstream, right? Differences in the mRNA, that 00:07:40.569 --> 00:07:42.790 was already known at the time. mRNA is kind of 00:07:42.790 --> 00:07:46.389 the most advanced in what technology has been 00:07:46.389 --> 00:07:48.949 around and for how long. And so it was already 00:07:48.949 --> 00:07:51.709 known that there are differences at baseline 00:07:51.709 --> 00:07:53.970 between males and females in skeletal muscle 00:07:53.970 --> 00:07:56.680 and their gene expression or their mRNA. And 00:07:56.680 --> 00:07:59.180 then with the proteins, we also found that just 00:07:59.180 --> 00:08:01.420 at baseline before exercise, there were several 00:08:01.420 --> 00:08:04.019 hundreds of proteins that were. differentially 00:08:04.019 --> 00:08:06.879 expressed between males and females. So the functional 00:08:06.879 --> 00:08:09.600 unit protein at the end, if you just look at 00:08:09.600 --> 00:08:11.420 a male muscle and just look at a female muscle, 00:08:11.579 --> 00:08:14.860 you can tell who it came from because the protein 00:08:14.860 --> 00:08:17.100 profile was very different. So that was to start 00:08:17.100 --> 00:08:18.839 it off going, okay, before we even exercise, 00:08:19.019 --> 00:08:20.959 how different are they? Yep. Very different in 00:08:20.959 --> 00:08:23.720 both of those aspects. And then we looked at 00:08:23.720 --> 00:08:25.639 what happened after four weeks of high intensity 00:08:25.639 --> 00:08:28.519 training. So that was all on a bike and it was 00:08:28.519 --> 00:08:30.379 all monitored to make sure that they're going 00:08:30.379 --> 00:08:33.220 at a certain percentage of their BOT. max and 00:08:33.220 --> 00:08:34.720 a certain percentage of their lactate threshold 00:08:34.720 --> 00:08:37.919 and it was it is quite um like they're hard workouts 00:08:37.919 --> 00:08:39.940 but of course we also had people that came in 00:08:39.940 --> 00:08:42.159 with different training statuses so you could 00:08:42.159 --> 00:08:44.139 have been kind of an untrained individual to 00:08:44.139 --> 00:08:46.139 a pretty fit individual so that will also kind 00:08:46.139 --> 00:08:47.879 of you know it was a limitation within our study 00:08:47.879 --> 00:08:50.700 because it will increase the variability of our 00:08:50.700 --> 00:08:53.419 results and potentially impact the findings but 00:08:53.419 --> 00:08:56.320 in general you know we were able to control for 00:08:56.320 --> 00:08:58.860 their vo2 max level so that was kind of taken 00:08:58.860 --> 00:09:01.259 into consideration in our analysis but in any 00:09:01.259 --> 00:09:05.039 case what we found was that the proteins changed 00:09:05.039 --> 00:09:08.059 substantially after four weeks of training in 00:09:08.059 --> 00:09:10.419 the muscle, and they changed differently between 00:09:10.419 --> 00:09:12.500 males and females. So if you're a male, you know, 00:09:12.519 --> 00:09:14.740 those proteins changed in that direction. And 00:09:14.740 --> 00:09:16.740 if you're a female, then different proteins changed 00:09:16.740 --> 00:09:18.779 in different directions. So that's what we found 00:09:18.779 --> 00:09:21.940 with the proteins. And then with DNA methylation, 00:09:22.120 --> 00:09:24.779 what we found, which was surprising to me at 00:09:24.779 --> 00:09:27.139 the time, or not what I was expecting, was that 00:09:27.139 --> 00:09:31.039 there wasn't a huge effect of exercise training 00:09:31.039 --> 00:09:35.179 on the DNA methylation status. It was slight 00:09:35.179 --> 00:09:37.419 but not much and there was no difference between 00:09:37.419 --> 00:09:39.679 males and females. It's like yep it changed a 00:09:39.679 --> 00:09:41.799 little bit and what we can see looks the same 00:09:41.799 --> 00:09:44.100 for males and females. Okay so then I we got 00:09:44.100 --> 00:09:46.279 to thinking if that's what happens with four 00:09:46.279 --> 00:09:48.159 weeks which is you know a small amount of time 00:09:48.159 --> 00:09:50.259 to be training and we know you know what what 00:09:50.259 --> 00:09:52.519 adaptations lifelong training will bring are 00:09:52.519 --> 00:09:55.519 going to be a lot more robust then We wondered, 00:09:55.600 --> 00:09:58.320 what about the cardiorespiratory fitness of these 00:09:58.320 --> 00:10:00.639 individuals? Because we had such a range and 00:10:00.639 --> 00:10:03.259 everyone performed VO2 max tests before and after 00:10:03.259 --> 00:10:05.440 they started, then we kind of had a fitness level 00:10:05.440 --> 00:10:07.480 for each one of them, which indicates lifelong 00:10:07.480 --> 00:10:10.360 training, cardiorespiratory fitness, right? VO2 00:10:10.360 --> 00:10:12.460 max is a good measure of those. So we then used 00:10:12.460 --> 00:10:15.639 VO2 max to kind of give each individual a value, 00:10:15.759 --> 00:10:17.960 like this is how fit they are. The VO2 maxes 00:10:17.960 --> 00:10:21.539 ranged from about low 20s to we had some very 00:10:21.539 --> 00:10:24.259 fit individuals that were like mid 60s. We had 00:10:24.259 --> 00:10:25.919 quite a range and we had a lot of individuals 00:10:25.919 --> 00:10:29.460 as well. There were 20 females and 45 males. 00:10:29.559 --> 00:10:32.360 So for these muscle biopsy studies, which are 00:10:32.360 --> 00:10:34.679 kind of hard to get people to necessarily agree 00:10:34.679 --> 00:10:37.659 to give a piece of their muscle, it's relatively 00:10:37.659 --> 00:10:41.000 a decently sized study for this kind of endeavor. 00:10:41.179 --> 00:10:43.879 So yeah, what we found was that these fitter 00:10:43.879 --> 00:10:46.580 individuals, people with higher VO2 max, had 00:10:46.580 --> 00:10:50.179 a very different profile in DNA methylation than 00:10:50.179 --> 00:10:53.019 unfit individuals. So that indicated that... 00:10:53.360 --> 00:10:56.200 lifelong training or your cardiorespiratory fitness 00:10:56.200 --> 00:11:00.200 influenced the DNA methylation profile in the 00:11:00.200 --> 00:11:02.080 muscle. And it wasn't different between males 00:11:02.080 --> 00:11:03.919 and females, which again was very interesting 00:11:03.919 --> 00:11:06.600 to me. It was like, if you're fit, this is what 00:11:06.600 --> 00:11:08.440 your profile looks like. Doesn't matter if you're 00:11:08.440 --> 00:11:10.120 a male or female, even though there's baseline 00:11:10.120 --> 00:11:12.220 differences. And I can get to that in a second. 00:11:12.320 --> 00:11:14.980 And then what was also surprising to me is that 00:11:14.980 --> 00:11:17.220 we didn't find the same with protein. So in proteins, 00:11:17.299 --> 00:11:20.580 we didn't see any effect of lifelong training 00:11:20.580 --> 00:11:23.879 on the proteins. So that was an indication to 00:11:23.879 --> 00:11:27.679 us that doing, you know, an acute bout of training, 00:11:27.919 --> 00:11:31.039 right, four weeks will potentially. affects more 00:11:31.039 --> 00:11:33.860 the proteins right it has more of an acute effect 00:11:33.860 --> 00:11:36.919 but that lifelong training which is more you 00:11:36.919 --> 00:11:38.360 know everything that's happened in your whole 00:11:38.360 --> 00:11:40.960 life like your cardiorespiratory fitness is more 00:11:40.960 --> 00:11:43.919 affecting your dna methylation that acute training 00:11:43.919 --> 00:11:48.419 was having a more substantial effect on the proteins 00:11:48.419 --> 00:11:51.399 while the lifelong effect has more of an effect 00:11:51.399 --> 00:11:54.759 on dna methylation which is more of a of a stable 00:11:54.759 --> 00:11:57.360 process so proteins can really like fluctuate 00:11:57.360 --> 00:11:59.659 with depending on what you eat and what you do 00:11:59.720 --> 00:12:01.960 but that potentially the DNA methylation is more 00:12:01.960 --> 00:12:05.320 transient and takes more time to change. And 00:12:05.320 --> 00:12:07.340 so we were kind of able to see that in both ways 00:12:07.340 --> 00:12:10.460 because of what we saw after four weeks and because 00:12:10.460 --> 00:12:12.340 of what we saw when we looked at the association 00:12:12.340 --> 00:12:15.919 between VO2 max. So since then, I mean, it was 00:12:15.919 --> 00:12:17.820 a really interesting finding to me to think that, 00:12:17.820 --> 00:12:20.179 you know. your VO2 mocks or the training that 00:12:20.179 --> 00:12:22.360 you've done your whole life influences, you know, 00:12:22.360 --> 00:12:24.100 something really deep in the cell, you know, 00:12:24.100 --> 00:12:26.200 the DNA methylation of the cell, which it can 00:12:26.200 --> 00:12:31.509 change and is malleable, but... it's less transient 00:12:31.509 --> 00:12:35.009 than the proteins. And so since then, we've completed 00:12:35.009 --> 00:12:37.830 another study, which meta -analyzed other studies. 00:12:37.850 --> 00:12:40.870 So basically said, okay, we have our 65 individuals. 00:12:41.169 --> 00:12:43.669 We have some limitations in our studies. And 00:12:43.669 --> 00:12:45.490 since then, a lot of other studies had come out 00:12:45.490 --> 00:12:48.669 that had taken muscle biopsies and done VO2 max 00:12:48.669 --> 00:12:50.470 for those individuals. They didn't necessarily 00:12:50.470 --> 00:12:52.730 look for sex differences, but we were able to 00:12:52.730 --> 00:12:55.870 mine their data and meta -analyze it with ours. 00:12:55.950 --> 00:12:58.470 And we were able to confirm everything that we 00:12:58.470 --> 00:13:00.929 saw in our... study, which was, which is always 00:13:00.929 --> 00:13:03.129 comforting in science when what you found is 00:13:03.129 --> 00:13:05.710 replicable and, you know, you're not the only 00:13:05.710 --> 00:13:07.429 one who reached those conclusions. So being able 00:13:07.429 --> 00:13:10.049 to do that and replicated in those other cohorts 00:13:10.049 --> 00:13:12.549 really strengthened, you know, what we, what 00:13:12.549 --> 00:13:14.710 we saw, which is that, yeah, the differences 00:13:14.710 --> 00:13:16.830 between males and females were evident at some 00:13:16.830 --> 00:13:18.850 levels of gene regulation and not others. And 00:13:18.850 --> 00:13:21.509 that exercise training had a strong effect on 00:13:21.509 --> 00:13:24.269 the proteins early on, but later on with sustained 00:13:24.269 --> 00:13:26.690 training, more effect on the DNA methylation 00:13:26.690 --> 00:13:29.059 status and the muscle. were kind of our main 00:13:29.059 --> 00:13:32.039 findings. And microRNAs, we didn't go as much 00:13:32.039 --> 00:13:34.879 in depth as this, but we also found that the 00:13:34.879 --> 00:13:37.820 microRNAs changed differently between males and 00:13:37.820 --> 00:13:41.539 females after exercise. That was with an acute 00:13:41.539 --> 00:13:43.860 bout, not with the four weeks. It sounds like 00:13:43.860 --> 00:13:47.370 ventilation is important. And it's early in the 00:13:47.370 --> 00:13:50.710 process of a transcription. So potentially the 00:13:50.710 --> 00:13:54.590 impact is bigger, especially in the long run. 00:13:54.669 --> 00:13:57.210 This is something that the cell has to kind of 00:13:57.210 --> 00:14:00.389 plan in advance and put an effort to put methylation 00:14:00.389 --> 00:14:02.169 at the beginning of the process of transcription. 00:14:02.309 --> 00:14:04.850 And then things are happening. At the end, we 00:14:04.850 --> 00:14:08.450 have proteins. So with acute exercise, it seems 00:14:08.450 --> 00:14:10.730 like the end of the process can be manipulated 00:14:10.730 --> 00:14:13.750 pretty quickly. But the methylation part, maybe 00:14:13.750 --> 00:14:16.379 because it's... earlier in the process, maybe 00:14:16.379 --> 00:14:19.860 it requires more from the body to be put in place. 00:14:20.340 --> 00:14:23.259 That's why it's affected slower. Am I close? 00:14:23.580 --> 00:14:25.759 Yeah, I think that that's kind of the idea that 00:14:25.759 --> 00:14:28.139 I have in my mind is that it takes longer to 00:14:28.139 --> 00:14:32.080 have those effects because it's a more intricate 00:14:32.080 --> 00:14:34.840 process. With proteins, we know that you can 00:14:34.840 --> 00:14:36.820 break down, you know, you have protein degradation, 00:14:37.000 --> 00:14:39.059 your protein synthesis, it's like a quicker, 00:14:39.139 --> 00:14:41.399 faster acting process. With DNA methylation, 00:14:41.480 --> 00:14:43.960 it requires, you know, a bit more of kind of 00:14:43.960 --> 00:14:46.539 setup. by the other proteins in the cells that 00:14:46.539 --> 00:14:48.940 need to interact to then tag that on. And then 00:14:48.940 --> 00:14:50.899 it's going to take time until, you know, everything 00:14:50.899 --> 00:14:53.220 kind of flows downwards from that. I say time, 00:14:53.299 --> 00:14:54.919 everything in our cells happens pretty quickly. 00:14:54.960 --> 00:14:57.720 But yeah, essentially it is higher up the chain. 00:14:57.799 --> 00:15:00.220 It's like if you think about you have a boss 00:15:00.220 --> 00:15:03.379 at the top and if you want to get something happening 00:15:03.379 --> 00:15:05.899 and changing quickly at the bottom, if you get... 00:15:06.059 --> 00:15:08.980 to send a message to the boss and wait for how 00:15:08.980 --> 00:15:11.600 long it takes to get to the bottom of the chain, 00:15:11.659 --> 00:15:13.220 that's going to take a while. But if you tell 00:15:13.220 --> 00:15:15.480 the person at the bottom straight away, then 00:15:15.480 --> 00:15:17.840 that's going to be much quicker in its effect. 00:15:18.220 --> 00:15:21.159 Oh, I like it. Okay, so the methylation is important. 00:15:21.460 --> 00:15:23.980 I'm trying to gauge whether it's a good thing 00:15:23.980 --> 00:15:27.460 in relation to exercise and adaptation and performance. 00:15:27.740 --> 00:15:30.740 Is it a good thing or bad thing? Do we want more 00:15:30.740 --> 00:15:33.080 of it or less of it? Or is it just that it has 00:15:33.080 --> 00:15:35.299 to be in specific places? How should we think? 00:15:35.370 --> 00:15:37.850 about it yeah definitely in specific places so 00:15:37.850 --> 00:15:40.470 it's gotten really big now to look at the effect 00:15:40.470 --> 00:15:44.769 of aging for example on dna methylation there's 00:15:44.769 --> 00:15:47.129 it's a really hot topic right now and it's something 00:15:47.129 --> 00:15:49.389 that my previous lab worked was working on a 00:15:49.389 --> 00:15:51.210 lot as well and that i've been involved in and 00:15:51.210 --> 00:15:53.889 what we kind of see is that aging has one effect 00:15:53.889 --> 00:15:57.889 on dna methylation and exercise has the opposite 00:15:57.889 --> 00:16:01.509 effect on those same sites so it's like you have 00:16:01.980 --> 00:16:05.720 increases or decreases globally, yes, but it's 00:16:05.720 --> 00:16:08.500 more specific to the sites that it's at and it's 00:16:08.500 --> 00:16:10.940 having its effect. So there's some genes that 00:16:10.940 --> 00:16:13.840 increase with methylation with age and with exercise 00:16:13.840 --> 00:16:15.860 and others that decrease depending on the location 00:16:15.860 --> 00:16:18.850 in the gene. We know from from other studies 00:16:18.850 --> 00:16:22.009 that there will be differences in how resistance 00:16:22.009 --> 00:16:25.710 exercise or endurance exercise impacts our molecular 00:16:25.710 --> 00:16:28.450 profiles in our muscle. I don't think that there's 00:16:28.450 --> 00:16:30.549 been enough studies out there for us to have 00:16:30.549 --> 00:16:33.950 a very clear conclusion on what kind of changes 00:16:33.950 --> 00:16:36.990 are different if you do strength training or 00:16:36.990 --> 00:16:39.509 endurance training and how that impacts DNA methylation 00:16:39.509 --> 00:16:41.490 differently. Maybe there's something that's come 00:16:41.490 --> 00:16:43.549 out that I'm not aware of, but from what I know, 00:16:43.629 --> 00:16:46.350 there hasn't been a direct comparison to see 00:16:46.350 --> 00:16:48.750 the differences. between those two training modalities, 00:16:48.889 --> 00:16:52.129 whether frequency and duration. I mean, we know, 00:16:52.129 --> 00:16:53.850 you know, with exercise training adaptation, 00:16:54.149 --> 00:16:56.190 it's all about intensity, frequency and duration. 00:16:56.210 --> 00:16:59.399 So we can kind of presume given that. the changes 00:16:59.399 --> 00:17:02.200 that we were seeing were associated with VO2 00:17:02.200 --> 00:17:05.579 max, then that kind of has intensity, duration, 00:17:05.740 --> 00:17:07.779 and frequency within it, right? So the more that 00:17:07.779 --> 00:17:10.839 you exercise and the higher VO2 max is, that's 00:17:10.839 --> 00:17:13.259 where we saw that strong signature, that strong 00:17:13.259 --> 00:17:15.519 DNA methylation signature. So I would say, yeah, 00:17:15.579 --> 00:17:18.660 of course, it's the more intense and the higher 00:17:18.660 --> 00:17:20.039 that it is, the more that you're going to have 00:17:20.039 --> 00:17:22.299 this effect. And that's where we're seeing the 00:17:22.299 --> 00:17:24.660 impact on the DNA methylation. And whether there 00:17:24.660 --> 00:17:28.759 are other things that influence... our DNA methylation. 00:17:28.940 --> 00:17:32.059 Yeah, I mean, it's kind of a very blanket term 00:17:32.059 --> 00:17:35.079 to how our genes are interacting with the quote 00:17:35.079 --> 00:17:37.319 -unquote environment or their environment. So 00:17:37.319 --> 00:17:40.240 there's a lot of different molecules or factors 00:17:40.240 --> 00:17:43.519 that will float around in our cells and impact 00:17:43.519 --> 00:17:47.180 which genes are methylated higher or lower. And 00:17:47.180 --> 00:17:49.339 things like smoking have a really strong effect 00:17:49.339 --> 00:17:52.980 on DNA methylation. Like we said, exercise. I'm 00:17:52.980 --> 00:17:54.759 trying to think what other studies have shown. 00:17:55.200 --> 00:17:58.559 A strong cancer disease. the things that are 00:17:58.559 --> 00:18:01.420 happening in our cells are very much influencing 00:18:01.420 --> 00:18:04.259 our DNA methylation. And what's it to a pot? 00:18:04.569 --> 00:18:07.269 You asked what's impacting our DNA methylation 00:18:07.269 --> 00:18:09.849 in a positive way. I mean, define positive. If 00:18:09.849 --> 00:18:11.589 you want it to look more like exercise, is that 00:18:11.589 --> 00:18:13.930 positive? If you want it to look less like aging, 00:18:14.049 --> 00:18:16.329 is that positive? I think it gets a little bit 00:18:16.329 --> 00:18:19.769 of a cloudy in that sense. But yeah, we do know 00:18:19.769 --> 00:18:22.410 that the things that we do, the toxins we're 00:18:22.410 --> 00:18:24.950 exposed to also influence DNA methylation. But 00:18:24.950 --> 00:18:26.710 yeah, the main ones that have been studied and 00:18:26.710 --> 00:18:29.529 have been robustly shown are aging, smoking, 00:18:29.829 --> 00:18:34.819 cancer and disease, toxins. Now, yeah, exercise 00:18:34.819 --> 00:18:36.880 as well. I guess I could just add it wasn't in 00:18:36.880 --> 00:18:38.579 our study because it was already known that, 00:18:38.619 --> 00:18:40.400 yeah, I think I did mention it, but that there 00:18:40.400 --> 00:18:43.559 are thousands of genes that are at the mRNA level 00:18:43.559 --> 00:18:45.980 also different between male and female skeletal 00:18:45.980 --> 00:18:48.299 muscle. And there was a good made analysis that 00:18:48.299 --> 00:18:50.440 came out a few years ago that I can also link 00:18:50.440 --> 00:18:53.279 in the notes by another group that looked at 00:18:53.279 --> 00:18:55.539 all the studies out there that performed fossil 00:18:55.539 --> 00:18:58.299 biopsies and had males or females and trained. 00:18:58.420 --> 00:19:01.579 And they also saw that the mRNA were also changing 00:19:01.579 --> 00:19:04.170 differently after. exercise, whether you're male 00:19:04.170 --> 00:19:05.849 and female. And there, I think they did group 00:19:05.849 --> 00:19:07.809 on different exercise modalities, if I remember 00:19:07.809 --> 00:19:11.089 correctly. So that could be your previous question 00:19:11.089 --> 00:19:12.950 as well with comparing the different exercise 00:19:12.950 --> 00:19:15.250 modalities, at least at the mRNA level. We didn't 00:19:15.250 --> 00:19:17.329 look at the other, I don't know of other studies 00:19:17.329 --> 00:19:18.789 that have looked at the other levels, but they 00:19:18.789 --> 00:19:23.190 did compare how, jumped on another point of another 00:19:23.190 --> 00:19:25.589 important level of the central dogma, which is 00:19:25.589 --> 00:19:28.349 the mRNA, and that there have been a lot of studies 00:19:28.349 --> 00:19:31.890 on looking at the mRNA changes with exercise 00:19:31.890 --> 00:19:34.410 training. And there was a good meta -analysis 00:19:34.410 --> 00:19:35.910 that came out a few years ago that basically 00:19:35.910 --> 00:19:38.490 found all the studies that took muscle biopsies 00:19:38.490 --> 00:19:41.769 before and after training and looked and saw 00:19:41.769 --> 00:19:43.609 if there was a sex difference. And they did see 00:19:43.609 --> 00:19:45.730 that there were hundreds of genes that changed 00:19:45.730 --> 00:19:48.789 differently between males and females in muscle. 00:19:48.950 --> 00:19:51.230 So the mRNA level before and after training. 00:19:51.369 --> 00:19:53.349 And they did include different training modalities, 00:19:53.430 --> 00:19:55.309 I think. So they also had endurance and strength 00:19:55.309 --> 00:19:57.710 and made that direct comparison. So before what 00:19:57.710 --> 00:19:59.849 we talked about, we don't have a direct comparison 00:19:59.849 --> 00:20:02.170 from what I know of the DNA. and methylation 00:20:02.170 --> 00:20:04.769 changes and if they're different between strength 00:20:04.769 --> 00:20:08.029 and endurance. But we do know about mRNA levels 00:20:08.029 --> 00:20:10.369 changing differently depending on the training 00:20:10.369 --> 00:20:12.730 modality. And so, yeah, I can link that in the 00:20:12.730 --> 00:20:14.990 link. Send you that link as well if you want 00:20:14.990 --> 00:20:17.230 to put it in. That would be awesome. So is it 00:20:17.230 --> 00:20:20.650 that we can see if we take genetic material from 00:20:20.650 --> 00:20:23.789 skeletal muscle of a person, random person, we 00:20:23.789 --> 00:20:27.369 can guess whether they are athletes or not and 00:20:27.369 --> 00:20:30.230 potentially what type of sport they are doing? 00:20:30.759 --> 00:20:31.720 I thought you were going to ask about the male 00:20:31.720 --> 00:20:33.579 and female aspect because that part's super interesting. 00:20:33.680 --> 00:20:35.299 There's actually a really cool paper that found. 00:20:35.579 --> 00:20:38.079 That's my next question. Next one. So I'll answer 00:20:38.079 --> 00:20:39.940 that one first just because it's more definitive 00:20:39.940 --> 00:20:41.900 of an answer. And I think it's fascinating. But 00:20:41.900 --> 00:20:44.480 a paper that came out a few years ago tried to 00:20:44.480 --> 00:20:47.200 predict if we look at the mRNA in a tissue, can 00:20:47.200 --> 00:20:49.619 we predict if it's male or female? And they knew 00:20:49.619 --> 00:20:51.220 if it's male or female. So they could check if 00:20:51.220 --> 00:20:53.440 the prediction was right. And they found they 00:20:53.440 --> 00:20:55.160 looked at all the tissues, you know, 40 something 00:20:55.160 --> 00:20:58.299 tissues in the body. And it was with it's using 00:20:58.299 --> 00:21:00.000 what's called the GTEx portal. So it's. It's 00:21:00.000 --> 00:21:02.920 a large publicly available data set that has 00:21:02.920 --> 00:21:04.920 hundreds and hundreds of people that have donated 00:21:04.920 --> 00:21:07.799 their tissues after they've passed away. And 00:21:07.799 --> 00:21:10.259 so it's quite robust, the findings. And they 00:21:10.259 --> 00:21:12.740 found that besides breast tissue, skeletal muscle 00:21:12.740 --> 00:21:15.960 predicted sex the best out of any other tissue. 00:21:16.119 --> 00:21:19.660 So that just shows you, yeah, just how that's, 00:21:19.660 --> 00:21:21.400 you know, we call skeletal muscle one of the 00:21:21.400 --> 00:21:23.640 most sex -biased tissues in the sense that it 00:21:23.640 --> 00:21:26.539 really is differentiated between males and females 00:21:26.539 --> 00:21:29.079 compared to, you know, brain tissue, liver, kidney. 00:21:29.200 --> 00:21:31.740 any other tissue that was that was in there so 00:21:31.740 --> 00:21:34.259 yeah which makes sense giving given how hormone 00:21:34.259 --> 00:21:36.359 responsive it is and that the hormones will really 00:21:36.359 --> 00:21:37.859 differ between males and females and i had a 00:21:37.859 --> 00:21:40.380 whole bit i was gonna explain to you about hormones 00:21:40.380 --> 00:21:43.400 versus genetic yeah so that's to answer whether 00:21:43.400 --> 00:21:45.519 muscle can differentiate i mean we can differentiate 00:21:45.519 --> 00:21:47.299 based off of muscle if it's males and females 00:21:47.299 --> 00:21:50.480 and whether we can differentiate their training 00:21:50.480 --> 00:21:52.779 status that that's a really good question maybe 00:21:52.779 --> 00:21:55.319 that's a future paper that we work on absolutely 00:21:55.319 --> 00:21:57.559 because yeah there's lots of kind of machine 00:21:57.559 --> 00:21:59.849 learning algorithms out there to try to predict 00:21:59.849 --> 00:22:02.349 those things. And if we had the VO2 max of those 00:22:02.349 --> 00:22:04.970 individuals, if we were able to predict how fit 00:22:04.970 --> 00:22:06.650 they were. Yeah, that's an awesome question. 00:22:06.769 --> 00:22:09.069 I'm going to steal that. Let's see if there's 00:22:09.069 --> 00:22:10.890 a student that wants to work on that. That's 00:22:10.890 --> 00:22:13.930 awesome. We have to know if we can predict pretty 00:22:13.930 --> 00:22:17.730 robustly whether the tissue, the muscle tissue 00:22:17.730 --> 00:22:21.170 is from a female or from a male. Why? Why they 00:22:21.170 --> 00:22:24.009 are so different? What is happening from the 00:22:24.009 --> 00:22:26.930 genetic point of view and then through physiology? 00:22:27.630 --> 00:22:30.089 that we end up with so different tissues. So 00:22:30.089 --> 00:22:33.170 that's something that I tried very hard to answer 00:22:33.170 --> 00:22:36.609 during my PhD and in my thesis and was limited 00:22:36.609 --> 00:22:38.970 in my ability to answer that because typically 00:22:38.970 --> 00:22:43.150 females have XX sex chromosomes, so two X chromosomes, 00:22:43.269 --> 00:22:46.430 while males will have XY chromosomes. And that 00:22:46.430 --> 00:22:49.730 then sets up many differences in our cells, in 00:22:49.730 --> 00:22:52.410 our DNA. And what I mean by that is, so that's 00:22:52.410 --> 00:22:54.630 kind of the first difference that we see, you 00:22:54.630 --> 00:22:57.240 know, at day zero, at conception. The embryo 00:22:57.240 --> 00:22:59.660 is either XX or it's XY. And if everything goes 00:22:59.660 --> 00:23:02.819 kind of typically and there's no variations to 00:23:02.819 --> 00:23:05.220 the sex development process, which is the lab 00:23:05.220 --> 00:23:07.900 that I work in now, is very focused on sex development 00:23:07.900 --> 00:23:10.019 and on the different variations that happen to 00:23:10.019 --> 00:23:12.079 this process. And I can speak to how that kind 00:23:12.079 --> 00:23:14.900 of relates to my previous work as well. But those 00:23:14.900 --> 00:23:17.960 first differences are going to set you up for 00:23:17.960 --> 00:23:20.539 all the differences that come up. come downstream. 00:23:20.779 --> 00:23:23.680 So if you have XX or if you have XY, it basically 00:23:23.680 --> 00:23:26.059 takes your gonad development. So we start with 00:23:26.059 --> 00:23:28.019 a bi -potential gonad, which means it has two 00:23:28.019 --> 00:23:30.099 potentials. It can go on to be ovaries and it 00:23:30.099 --> 00:23:32.519 can go on to be testes. And you need to have 00:23:32.519 --> 00:23:35.480 a few key players present or absent in order 00:23:35.480 --> 00:23:37.740 to kind of go down those two pathways, one of 00:23:37.740 --> 00:23:41.220 those two pathways. And so having XX, if everything 00:23:41.220 --> 00:23:44.480 goes normally, will then develop into ovaries, 00:23:44.519 --> 00:23:46.680 which then means you have high estrogen, high 00:23:46.680 --> 00:23:49.180 progesterone, and lower testosterone levels. 00:23:49.359 --> 00:23:51.819 Or if you have XY, that typically will take you 00:23:51.819 --> 00:23:53.859 down the other pathway in which you develop testes 00:23:53.859 --> 00:23:56.099 and you have higher testosterone relatively and 00:23:56.099 --> 00:23:58.380 lower estrogen and progesterone. And so then 00:23:58.380 --> 00:24:01.819 there's kind of then thought of as two main drivers 00:24:01.819 --> 00:24:04.859 of the sex differences that we see. So everything 00:24:04.859 --> 00:24:06.700 that we talked about until now, the performance, 00:24:06.980 --> 00:24:09.160 the physiology, the proteins, the gene regulation. 00:24:09.359 --> 00:24:11.319 It's thought that those two are driven by those, 00:24:11.319 --> 00:24:13.200 that those things are driven by those two components. 00:24:13.240 --> 00:24:15.380 The difference, the fact that you have XX and 00:24:15.380 --> 00:24:17.579 XY and the fact that you now have different hormone 00:24:17.579 --> 00:24:19.390 levels for the rest of it. your life. And those 00:24:19.390 --> 00:24:22.130 two things will impact what goes on in the cell. 00:24:22.230 --> 00:24:25.150 And so it's kind of impossible to break apart 00:24:25.150 --> 00:24:27.309 those two drivers because they come together, 00:24:27.369 --> 00:24:29.130 right? If you have XX, you have that hormone 00:24:29.130 --> 00:24:31.109 profile. If you have XY, you typically have that 00:24:31.109 --> 00:24:33.450 hormone profile. So how will you say if the difference 00:24:33.450 --> 00:24:35.549 that you see is due to having different sex chromosomes 00:24:35.549 --> 00:24:37.509 or different hormone levels? Because while they 00:24:37.509 --> 00:24:39.390 come together, you can't break them apart. So 00:24:39.390 --> 00:24:41.250 that's what a big project that I'm currently 00:24:41.250 --> 00:24:43.849 working on in the lab that I'm in now, which 00:24:43.849 --> 00:24:46.670 is that the lab that I work in before I came 00:24:46.670 --> 00:24:49.230 in developed in collaboration with a couple labs 00:24:49.230 --> 00:24:51.970 in the U .S., what's called a four -core genotype 00:24:51.970 --> 00:24:55.269 model. So it's a model that's existed in mice, 00:24:55.430 --> 00:24:58.910 again, by our collaborator at UCLA for over 20 00:24:58.910 --> 00:25:01.289 years. And when I came in, they had just finished 00:25:01.289 --> 00:25:04.289 producing a rat version of this model. And what 00:25:04.289 --> 00:25:06.569 this model is and why it's called the four -core 00:25:06.569 --> 00:25:09.029 genotypes is that we end up having four genotypes. 00:25:09.250 --> 00:25:12.210 One that's, you know, a typical XY male, a typical 00:25:12.210 --> 00:25:16.930 XX female, but then we have XX males and XY females. 00:25:17.000 --> 00:25:19.240 And what that allows us to do is to break apart 00:25:19.240 --> 00:25:22.900 the impact of the sex chromosomes and the hormones, 00:25:23.200 --> 00:25:25.319 because now they're not linked together. Shani, 00:25:25.359 --> 00:25:28.880 just to make it clear. So when you say XX female, 00:25:29.099 --> 00:25:32.940 that's XX genetics and female hormonal profile. 00:25:33.059 --> 00:25:37.279 If you say XX male, you mean XX genetic profile, 00:25:37.480 --> 00:25:40.339 but hormonal profile is the profile of a male. 00:25:40.420 --> 00:25:43.640 Is that? Exactly right. Yeah. Yes. So when I 00:25:43.640 --> 00:25:46.740 say male or female here, it just is describing 00:25:46.740 --> 00:25:49.640 phenotypically or the gonads. The moment the 00:25:49.640 --> 00:25:52.299 gonads are testes, have high testosterone. The 00:25:52.299 --> 00:25:54.259 moment the gonads are ovaries, you have high 00:25:54.259 --> 00:25:57.640 estrogen. So yes. So yeah, that model has been 00:25:57.640 --> 00:26:01.420 used in mice for decades now to understand the 00:26:01.420 --> 00:26:03.859 drivers of a lot of different sex differences. 00:26:04.039 --> 00:26:06.240 So one, for example, is that what was found is 00:26:06.240 --> 00:26:10.079 that the X chromosomes are what strongly influence 00:26:10.079 --> 00:26:13.119 adiposity. So animals that had two X chromosomes, 00:26:13.400 --> 00:26:16.599 regardless of their hormone levels, were fatter 00:26:16.599 --> 00:26:18.980 and ate more. And so it was kind of a, you know, 00:26:18.980 --> 00:26:21.380 revelational in the sense that, you know, we 00:26:21.380 --> 00:26:23.799 see so many of the differences. It was commonly 00:26:23.799 --> 00:26:25.279 thought that so many of the differences that 00:26:25.279 --> 00:26:27.480 we see between males and females are due to hormones. 00:26:27.799 --> 00:26:30.160 And we know that hormones have such an influence 00:26:30.160 --> 00:26:34.119 on fat cells and on adipose tissue. But yeah, 00:26:34.200 --> 00:26:35.799 that study had kind of shown that there's also 00:26:35.799 --> 00:26:38.039 a role for the genes that are on the X and Y 00:26:38.039 --> 00:26:40.900 chromosomes that's been previously underappreciated. 00:26:40.940 --> 00:26:42.200 So there are a lot of studies. that have come 00:26:42.200 --> 00:26:44.460 out showing there's a specific gene on X or a 00:26:44.460 --> 00:26:47.559 specific gene on Y. that can influence a specific 00:26:47.559 --> 00:26:50.940 trait or a specific disease. And so, yeah, it's 00:26:50.940 --> 00:26:52.799 understanding that there's also now this level 00:26:52.799 --> 00:26:54.900 of, well, if you have two X chromosomes, it means 00:26:54.900 --> 00:26:57.900 that you have a different level of genes expressed 00:26:57.900 --> 00:27:00.200 in those chromosomes if you're a female. And 00:27:00.200 --> 00:27:02.579 if you have an X and Y, then you have different 00:27:02.579 --> 00:27:04.420 genes there as well in a male. So there's those 00:27:04.420 --> 00:27:06.819 inherent differences. So you asked, you know, 00:27:06.819 --> 00:27:08.240 to bring you back to the exercise adaptations 00:27:08.240 --> 00:27:11.279 and what we were seeing. I tried my best to answer 00:27:11.279 --> 00:27:13.400 that question with the human data that we had, 00:27:13.519 --> 00:27:15.140 which is, well, those two things are linked. 00:27:15.660 --> 00:27:18.099 can't really pull those components apart. We 00:27:18.099 --> 00:27:20.460 did as much as we could. And we did see that 00:27:20.460 --> 00:27:22.900 if you looked just within females, and we did 00:27:22.900 --> 00:27:24.640 have all their hormone levels measured in their 00:27:24.640 --> 00:27:27.980 blood, their testosterone, their estrogen levels, 00:27:28.140 --> 00:27:31.480 their SHBG, we all measured. And we did see that 00:27:31.480 --> 00:27:33.920 within females, because again, we couldn't compare 00:27:33.920 --> 00:27:37.420 males to females without. having those two things 00:27:37.420 --> 00:27:39.259 intertwined, right, the genetics and the hormones. 00:27:39.400 --> 00:27:41.880 But within females, we saw that hormones were 00:27:41.880 --> 00:27:44.460 impacting the DNA methylation level, so the level 00:27:44.460 --> 00:27:46.240 of hormones. And I mean, there's not a great 00:27:46.240 --> 00:27:48.079 variability in testosterone within the female, 00:27:48.200 --> 00:27:50.680 so that's not a huge finding. But with estrogen, 00:27:50.920 --> 00:27:53.039 you know, and it's really variable because it's 00:27:53.039 --> 00:27:55.579 changing throughout the cycle and it will be 00:27:55.579 --> 00:27:57.779 different between people. And while we did collect 00:27:57.779 --> 00:28:00.779 blood and muscle from people always in their 00:28:00.779 --> 00:28:02.759 early follicular stage, so the first seven days 00:28:02.759 --> 00:28:04.880 of their cycle, to try to minimize that variability, 00:28:05.079 --> 00:28:07.420 there will. inherently be variability because 00:28:07.420 --> 00:28:09.119 that wasn't also the goal of the study so it 00:28:09.119 --> 00:28:11.319 wasn't you know super tightly controlled as it 00:28:11.319 --> 00:28:13.140 could be it was just as tightly controlled as 00:28:13.140 --> 00:28:15.400 we kind of needed it for the bigger question 00:28:15.400 --> 00:28:17.859 but that yeah we do see that hormones influence 00:28:17.859 --> 00:28:20.920 the DNA methylation levels preliminarily from 00:28:20.920 --> 00:28:23.299 what we found but that further work is needed 00:28:23.299 --> 00:28:26.140 which is kind of what my lab is working on now 00:28:26.140 --> 00:28:28.279 in collaboration with with another lab is to 00:28:28.279 --> 00:28:30.700 understand what is driving the sex differences 00:28:30.700 --> 00:28:33.339 in the muscle and I can tell you what we found 00:28:33.339 --> 00:28:36.250 so far I'm still preparing that manuscript and 00:28:36.250 --> 00:28:39.369 don't have super firm conclusions yet. But what 00:28:39.369 --> 00:28:40.769 I'm finding so far that's really interesting 00:28:40.769 --> 00:28:44.710 is that there is a really strong effect of the 00:28:44.710 --> 00:28:46.970 gonadal hormones, so the testosterone, estrogen, 00:28:47.170 --> 00:28:50.170 progesterone, on the mRNA levels in the muscle 00:28:50.170 --> 00:28:52.849 of these rats. But there is still some component 00:28:52.849 --> 00:28:56.079 that's influenced. by the sex chromosomes. So 00:28:56.079 --> 00:28:57.539 we've kind of looked at a bunch of different 00:28:57.539 --> 00:29:00.160 tissues and tried to see, okay, what's having 00:29:00.160 --> 00:29:02.940 an effect in the mRNA levels in these different 00:29:02.940 --> 00:29:05.859 tissues? Is it the sex chromosomes or is it the 00:29:05.859 --> 00:29:09.220 hormones? And for most of the tissues, it's been 00:29:09.220 --> 00:29:11.920 the hormones, but not for all. And muscle is 00:29:11.920 --> 00:29:14.480 one of the ones that hormones seem to be having 00:29:14.480 --> 00:29:16.539 a much stronger effect. But again, that there 00:29:16.539 --> 00:29:18.279 is still some effect of the sex chromosomes, 00:29:18.500 --> 00:29:20.259 which is super interesting. And we're still going 00:29:20.259 --> 00:29:23.019 through kind of each gene, each mRNA and seeing, 00:29:23.119 --> 00:29:25.160 okay, what's... this one? What's its function? 00:29:25.380 --> 00:29:27.299 Why is this one driven by hormones? Why is that 00:29:27.299 --> 00:29:29.380 one driven by the sex chromosomes? So we're still 00:29:29.380 --> 00:29:31.440 kind of piecing that together. And the best that 00:29:31.440 --> 00:29:33.900 I could kind of do in my PhD with the human data, 00:29:34.019 --> 00:29:35.799 because again, that was rat data. The best I 00:29:35.799 --> 00:29:38.200 could do in my PhD with human data was to kind 00:29:38.200 --> 00:29:41.619 of see if there's hormone responsive sites around 00:29:41.619 --> 00:29:43.920 the DNA methylation differences we were seeing. 00:29:43.980 --> 00:29:46.759 And we did see the androgen receptor was nearby. 00:29:47.309 --> 00:29:50.470 those sites, which indicates that likely there's 00:29:50.470 --> 00:29:52.950 a kind of a hormonal explanation for some of 00:29:52.950 --> 00:29:55.640 the DNA methylation. differences that we were 00:29:55.640 --> 00:29:58.400 seeing in the human muscle. If we know that there 00:29:58.400 --> 00:30:01.079 are differences between females and males, and 00:30:01.079 --> 00:30:03.680 some of the differences are due to genetics, 00:30:03.779 --> 00:30:06.279 some of them are due to hormones. If there is 00:30:06.279 --> 00:30:09.240 any relation between how hormones influence genetics, 00:30:09.539 --> 00:30:11.720 I would be interested to know. Okay. Yeah. I 00:30:11.720 --> 00:30:13.519 mean, I think it's a fascinating topic, so I 00:30:13.519 --> 00:30:16.400 kind of had it in here. So how progesterones, 00:30:16.400 --> 00:30:20.140 estrogens, and testosterone work is there's kind 00:30:20.140 --> 00:30:22.759 of two signaling pathways, but I'll focus on 00:30:22.759 --> 00:30:24.819 the main one. and the one that's kind of the 00:30:24.819 --> 00:30:28.940 most canonical one is that hormones have receptors. 00:30:29.059 --> 00:30:31.559 We have testosterone that's floating around the 00:30:31.559 --> 00:30:34.299 cell, in the cell, and it needs to bind its receptor. 00:30:34.440 --> 00:30:36.819 That's how it exerts its action. And when it 00:30:36.819 --> 00:30:38.960 finds its receptor and they're together, they 00:30:38.960 --> 00:30:41.640 then enter the nucleus where the DNA is held. 00:30:41.759 --> 00:30:45.259 And that receptor can either directly or indirectly 00:30:45.259 --> 00:30:48.339 bind the DNA at specific sites. So there's specific 00:30:48.339 --> 00:30:50.380 what are called hormone responsive elements. 00:30:50.460 --> 00:30:53.059 So different sequences that will say, okay. We 00:30:53.059 --> 00:30:56.059 recognize when there's an androgen receptor and 00:30:56.059 --> 00:30:58.539 it will bind here and it will then directly impact 00:30:58.539 --> 00:31:03.019 which genes get transcribed. So which mRNA then 00:31:03.019 --> 00:31:06.180 come out from that interaction. So that's how 00:31:06.180 --> 00:31:08.900 hormones are really directly or, you know, we 00:31:08.900 --> 00:31:10.880 say indirectly because there's sometimes other 00:31:10.880 --> 00:31:13.339 proteins that are involved, but we can say directly 00:31:13.339 --> 00:31:17.480 or indirectly changing which genes are getting 00:31:17.480 --> 00:31:19.880 transcribed into mRNA. So that's kind of how 00:31:19.880 --> 00:31:23.619 hormones exert their effect. And yeah, so basically 00:31:23.619 --> 00:31:26.359 they're kind of seen as what we call transcription 00:31:26.359 --> 00:31:28.980 factors because they are a factor, right, in 00:31:28.980 --> 00:31:31.480 transcription. They can bind the DNA. The receptors 00:31:31.480 --> 00:31:34.579 can bind the DNA. What the future is bringing. 00:31:34.720 --> 00:31:37.000 Yeah, I think with every scientific question, 00:31:37.140 --> 00:31:38.700 the moment you answer it, you just kind of come 00:31:38.700 --> 00:31:40.519 out with more questions. So there's always more 00:31:40.519 --> 00:31:44.460 questions to answer. A few that I kind of had 00:31:44.460 --> 00:31:48.539 left after our work or with our work so far. 00:31:48.680 --> 00:31:51.200 A big one is the influence of the fiber types. 00:31:51.400 --> 00:31:53.859 So I didn't really, you know, I didn't go into 00:31:53.859 --> 00:31:55.460 this. I probably should have and is more interesting 00:31:55.460 --> 00:31:57.099 to your audience than all the molecular details 00:31:57.099 --> 00:32:00.000 that I gave. But I will add in that maybe you 00:32:00.000 --> 00:32:02.059 want to put it in earlier on, but it's not really 00:32:02.059 --> 00:32:04.220 a summary. It's something I meant to mention. 00:32:04.259 --> 00:32:07.599 I just realized. is that what we know about, 00:32:07.599 --> 00:32:10.440 and we talked about the differences physiologically 00:32:10.440 --> 00:32:12.460 between males and females, and we talked about 00:32:12.460 --> 00:32:14.720 how the fiber type, you know, fiber sizes are 00:32:14.720 --> 00:32:16.940 different, but also the proportions, right? And 00:32:16.940 --> 00:32:19.359 how those proportions then influence metabolism 00:32:19.359 --> 00:32:22.859 is huge. So if you have more type 2 fibers, which 00:32:22.859 --> 00:32:25.079 is what we see generally, again, in males, generally 00:32:25.079 --> 00:32:26.779 depending on training status, then you're going 00:32:26.779 --> 00:32:29.819 to have more glycolytic pathways, which is reliance 00:32:29.819 --> 00:32:32.240 more on carbohydrates. When you have more oxidative 00:32:32.240 --> 00:32:35.259 fibers or type 1 fibers in females, you're going 00:32:35.259 --> 00:32:40.059 to have more capacity to utilize fats as a fuel. 00:32:40.220 --> 00:32:43.960 So it has been shown multiple times that in endurance 00:32:43.960 --> 00:32:47.779 training, females will have a bit more of a reliance 00:32:47.779 --> 00:32:51.170 on fats as a fuel while males will have a bit 00:32:51.170 --> 00:32:53.950 more of reliance on carbs as a fuel of course 00:32:53.950 --> 00:32:56.490 they're both relying on both throughout training 00:32:56.490 --> 00:32:59.130 but the shift is a little bit different given 00:32:59.130 --> 00:33:02.269 that we have different fiber type proportions 00:33:02.269 --> 00:33:04.690 right type one versus type two within a male 00:33:04.690 --> 00:33:07.029 muscle or within a female muscle so that then 00:33:07.029 --> 00:33:11.039 is a huge question left to answer with what we've 00:33:11.039 --> 00:33:13.160 seen. So are all the differences that we're seeing, 00:33:13.279 --> 00:33:15.440 you know, in DNA methylation, in proteins, in 00:33:15.440 --> 00:33:19.200 mRNA, is that all partially or very largely driven 00:33:19.200 --> 00:33:21.680 by the fact that we actually have different distributions 00:33:21.680 --> 00:33:25.259 of type 1 and type 2 fibers? And again, I tried 00:33:25.259 --> 00:33:26.940 to answer that as best as I could because we 00:33:26.940 --> 00:33:29.599 did check for the fiber type proportions in all 00:33:29.599 --> 00:33:32.160 of the individuals, the 65 individuals that we 00:33:32.160 --> 00:33:35.359 had in our study. It's the data I was analyzing 00:33:35.359 --> 00:33:37.400 the night before my wedding. But anyways, no, 00:33:37.440 --> 00:33:39.400 I won't get into that. Yeah, so that's... a huge 00:33:39.400 --> 00:33:41.859 question left to answer is, you know, how much 00:33:41.859 --> 00:33:44.579 fiber types are influencing the molecular profiles 00:33:44.579 --> 00:33:46.519 that we see. And it's something that a colleague 00:33:46.519 --> 00:33:50.319 of mine did his PhD on after I completed my PhD. 00:33:50.460 --> 00:33:52.420 So he has some papers coming out on that. And 00:33:52.420 --> 00:33:54.960 that work is still ongoing. Preliminarily, or 00:33:54.960 --> 00:33:58.980 what he's finding so far is that there is a component 00:33:58.980 --> 00:34:03.880 of the proteins that is largely impacted by the 00:34:03.880 --> 00:34:05.880 fiber type differences between males and females, 00:34:06.000 --> 00:34:08.650 which is also what I was finding in DNA. that 00:34:08.650 --> 00:34:11.489 there's a really strong signature of DNA methylation 00:34:11.489 --> 00:34:15.250 in type 1 fibers or in type 2 fibers with, again, 00:34:15.369 --> 00:34:18.650 the limited ability of my study to answer that 00:34:18.650 --> 00:34:20.269 question because it wasn't designed for that. 00:34:20.389 --> 00:34:21.789 And there have been studies out there showing 00:34:21.789 --> 00:34:24.409 just how different the kind of molecular profiles 00:34:24.409 --> 00:34:26.670 are, right, the proteins and the DNA methylation 00:34:26.670 --> 00:34:28.309 and how they are different between type 1 and 00:34:28.309 --> 00:34:30.969 type 2 fibers. So that's a big part to take into 00:34:30.969 --> 00:34:33.750 consideration with things left to do. Another 00:34:33.750 --> 00:34:35.809 part, which is what we touched upon, which is 00:34:35.809 --> 00:34:38.309 what's driving those differences. which can be 00:34:38.309 --> 00:34:41.070 answered in multiple different ways. One is what 00:34:41.070 --> 00:34:43.289 we're trying to do with the RAP model. The other 00:34:43.289 --> 00:34:46.510 is using, indeed, gender -affirming hormone therapy 00:34:46.510 --> 00:34:48.429 individuals and seeing what hormones will do 00:34:48.429 --> 00:34:50.489 to their muscle. And yeah, there's kind of a 00:34:50.489 --> 00:34:52.130 few different ways we could try to answer that 00:34:52.130 --> 00:34:55.449 question. And the other thing is really just 00:34:55.449 --> 00:34:57.730 understanding the different levels of gene regulation, 00:34:57.909 --> 00:35:00.309 because that'll paint a bigger... kind of more 00:35:00.309 --> 00:35:02.849 comprehensive picture of what is happening with 00:35:02.849 --> 00:35:04.869 exercise adaptations. And, you know, if we were 00:35:04.869 --> 00:35:06.849 seeing differences between males and females 00:35:06.849 --> 00:35:09.550 on protein level, but not at DNA methylation, 00:35:09.710 --> 00:35:12.010 and we're seeing it at mRNA, what's happening 00:35:12.010 --> 00:35:14.670 with everything in between? Like what is the 00:35:14.670 --> 00:35:16.849 mechanism behind it? And while we tried to answer 00:35:16.849 --> 00:35:19.030 it, you know, in a few different ways, it's as 00:35:19.030 --> 00:35:21.949 we kind of hopefully alluded to is pretty complex. 00:35:21.989 --> 00:35:23.769 And there's a lot of different players. There's 00:35:23.769 --> 00:35:27.639 a lot of different. ways to regulate which proteins 00:35:27.639 --> 00:35:29.599 end up at the end of the day having their function. 00:35:29.719 --> 00:35:32.079 So kind of at which level is everything happening? 00:35:32.260 --> 00:35:35.039 Where is exercise exerting its effect? Where 00:35:35.039 --> 00:35:37.340 are the sex differences coming in? Are they earlier 00:35:37.340 --> 00:35:39.000 on? Are they later? Are they across the whole 00:35:39.000 --> 00:35:41.699 process? Yeah, just the complexity of the gene 00:35:41.699 --> 00:35:44.039 regulation, I think, is still a lot of questions 00:35:44.039 --> 00:35:45.920 left to answer there. That's awesome. Thank you 00:35:45.920 --> 00:35:49.159 so much for sharing what we know so far. Let's 00:35:49.159 --> 00:35:52.840 finish with some advice for coaches. So if you 00:35:52.840 --> 00:35:56.159 could bring it all together and compress it, 00:35:56.320 --> 00:35:59.719 would you have anything to say that coaches should 00:35:59.719 --> 00:36:02.059 know about the differences between female and 00:36:02.059 --> 00:36:04.340 male muscles? I think a better understanding 00:36:04.340 --> 00:36:07.719 of... what is going on in our bodies and our 00:36:07.719 --> 00:36:11.039 muscles, you know, contributes to a better understanding 00:36:11.039 --> 00:36:13.280 of kind of how to, how things work. I don't know 00:36:13.280 --> 00:36:16.139 how you want to think about. life and training. 00:36:16.320 --> 00:36:19.480 And I mean, other than the kind of basic ones 00:36:19.480 --> 00:36:21.300 that we know, which is, you know, females have, 00:36:21.380 --> 00:36:24.079 you know, greater relative lower body strength 00:36:24.079 --> 00:36:25.760 and upper body strength. And I don't know if 00:36:25.760 --> 00:36:27.760 that's something to take into consideration when 00:36:27.760 --> 00:36:30.980 you're planning, you know, your load and the 00:36:30.980 --> 00:36:33.300 rep, you know, the load that you're aiming to 00:36:33.300 --> 00:36:36.099 hit for your different reps. I think a lot of 00:36:36.099 --> 00:36:38.639 it also comes down to practice and to individual 00:36:38.639 --> 00:36:40.900 experience. And I think while, you know, every 00:36:40.900 --> 00:36:43.300 individual is going to be different, we're looking 00:36:43.300 --> 00:36:45.250 at males and females as a whole. But of course, 00:36:45.250 --> 00:36:47.650 there's so much individual variability as well. 00:36:47.710 --> 00:36:50.369 So it's hard to kind of have these concrete conclusions 00:36:50.369 --> 00:36:53.440 on this is what you now should do. But I think 00:36:53.440 --> 00:36:55.880 it's just the more we can understand what's happening 00:36:55.880 --> 00:36:59.699 molecularly, the more we can just get a bigger, 00:37:00.500 --> 00:37:03.440 more clear picture of, you know, what exercise 00:37:03.440 --> 00:37:05.519 adaptations are looking like. And, you know, 00:37:05.559 --> 00:37:09.119 what is that lactate burn at the end of 400 meters? 00:37:09.139 --> 00:37:11.000 You know, what does it mean on a molecular level? 00:37:11.059 --> 00:37:13.539 Yeah, regarding looking at males versus females 00:37:13.539 --> 00:37:16.179 and how to really take that into consideration. 00:37:16.880 --> 00:37:19.380 A few examples come to mind, like, you know, 00:37:19.380 --> 00:37:21.519 I think males tend to have a larger difference 00:37:21.519 --> 00:37:23.280 between their first and second lap in an 800 00:37:23.280 --> 00:37:25.019 meters. All right, you run and then you get really 00:37:25.019 --> 00:37:27.599 tired and continue running and you slow down 00:37:27.599 --> 00:37:29.619 a bit. Males tend to slow down more compared 00:37:29.619 --> 00:37:32.599 to females, which in my molecular mind makes 00:37:32.599 --> 00:37:35.800 sense, because if we know that females tend to 00:37:35.800 --> 00:37:38.679 rely more on fats and kind of have relatively 00:37:38.679 --> 00:37:43.000 enhanced endurance compared to males in the sense 00:37:43.000 --> 00:37:45.659 that, you know, they're able to. kind of rely 00:37:45.659 --> 00:37:49.000 on that process more then it kind of makes sense 00:37:49.000 --> 00:37:51.059 to me that they're able to run a more even pace 00:37:51.059 --> 00:37:54.039 right and more if you're relying on fats and 00:37:54.039 --> 00:37:56.920 your oxidation then you're relying more on your 00:37:56.920 --> 00:37:59.699 endurance capacity so you're going to be a bit 00:37:59.699 --> 00:38:02.659 more even when you're thinking about males in 00:38:02.659 --> 00:38:04.840 the 800 and if it if you're slowing down then 00:38:04.840 --> 00:38:07.199 you've relied a bit more on speed to get you 00:38:07.199 --> 00:38:08.940 there and then you've slowed down you know so 00:38:08.940 --> 00:38:11.340 it's kind of hard to put into I feel like I didn't 00:38:11.340 --> 00:38:13.360 explain that really well. But what I'm hearing 00:38:13.360 --> 00:38:17.119 is that females run slower in general than males, 00:38:17.380 --> 00:38:20.780 but they are able to keep the tempo better because 00:38:20.780 --> 00:38:23.119 they are slower, probably because of the same 00:38:23.119 --> 00:38:27.059 reasons that they are able to hold the pace. 00:38:27.139 --> 00:38:29.559 So the genetics are different. The muscle mass 00:38:29.559 --> 00:38:32.739 is different. The fueling is different. Exactly. 00:38:32.840 --> 00:38:35.559 And there are also some mental, you know, females 00:38:35.559 --> 00:38:37.579 and males mentally are a little bit different 00:38:37.579 --> 00:38:39.460 too. And there are some factors in the sports. 00:38:40.079 --> 00:38:42.840 that will benefit potentially from that too. 00:38:42.940 --> 00:38:47.619 So lots of things, very complex, but I get where 00:38:47.619 --> 00:38:49.900 you're going with it. Yeah, yeah. I think depending 00:38:49.900 --> 00:38:52.360 on the exercise that you're interested in or 00:38:52.360 --> 00:38:54.239 that you're doing or that you're involved in, 00:38:54.280 --> 00:38:56.199 you can potentially think about the different 00:38:56.199 --> 00:38:58.179 components of this in different ways. So my head 00:38:58.179 --> 00:39:01.599 goes to that and realizing that those are some 00:39:01.599 --> 00:39:03.280 of the differences we see in the 100 between 00:39:03.280 --> 00:39:05.400 males and females is the pacing. And that can 00:39:05.400 --> 00:39:07.599 kind of be explained by... the understanding 00:39:07.599 --> 00:39:09.500 of the metabolism and the molecular components 00:39:09.500 --> 00:39:11.699 of it. So yeah, depends on what you do. And then, 00:39:11.739 --> 00:39:13.099 you know, same with strength. If we're looking 00:39:13.099 --> 00:39:15.420 at upper versus lower body strength, then it's 00:39:15.420 --> 00:39:18.190 another. thing to understand yeah in that sense 00:39:18.190 --> 00:39:19.809 is the best way i can kind of think of how to 00:39:19.809 --> 00:39:23.630 relate this to practice beautiful two short questions 00:39:23.630 --> 00:39:25.590 to finish the first one is what is your favorite 00:39:25.590 --> 00:39:28.469 exercise you already said 800 yeah i was gonna 00:39:28.469 --> 00:39:30.710 say i don't think i should not stray away from 00:39:30.710 --> 00:39:32.730 that but yeah if you were to ask me like my specific 00:39:32.730 --> 00:39:36.010 the 800 is a delicate combination between endurance 00:39:36.010 --> 00:39:38.309 and strength so kind of get to do everything 00:39:38.309 --> 00:39:41.289 from speed training to speed endurance to endurance 00:39:41.289 --> 00:39:44.070 to to strength you know power strength training 00:39:44.070 --> 00:39:46.599 so a bit of everything which I love that aspect 00:39:46.599 --> 00:39:48.820 of it. Probably my favorite workouts is like 00:39:48.820 --> 00:39:51.420 200 meter hill repeats. There's just something 00:39:51.420 --> 00:39:53.639 to making it to the top of the hill. You know, 00:39:53.659 --> 00:39:56.000 you and your glutes are on fire and just you 00:39:56.000 --> 00:39:58.619 feel on top, you know? So yeah, it's probably 00:39:58.619 --> 00:40:01.860 my favorite workout. And the last question is 00:40:01.860 --> 00:40:04.599 where people can find you online if they want 00:40:04.599 --> 00:40:06.559 to follow your work and learn more. I'm not the 00:40:06.559 --> 00:40:09.099 most active. I do have LinkedIn. So if you just 00:40:09.099 --> 00:40:11.380 search my first name and last name, I'm the only 00:40:11.380 --> 00:40:15.460 one. But yeah, so I'm trying to post. more and 00:40:15.460 --> 00:40:19.599 get more exposure to our work. So through LinkedIn 00:40:19.599 --> 00:40:21.880 would probably be the best way. Thank you, Shani. 00:40:21.960 --> 00:40:22.440 It was a pleasure.