Good afternoon and thank you very much for coming. I know it's Saturday. I know it's after 3 o'clock and there's still some people smiling So that's great. So thank you for being here. My name is Grisha today. I will be Moderating a session with a mentor and a colleague of the Christian here. We'll start with a Recorded session by dr. Inigo San Milan who is an exercise physiologist with a Special expertise in lactate metabolism, which makes him uniquely skilled at managing performance both in high level athletes one of his achievements is Training a repeat Tour de France winner and currently he I believe is in charge of athletic program at Atletico Bilbao a major soccer club in in Spain My second co-presenter will be dr. Adrian Christian here. He's a chair of cancer rehabilitation at Miami Cancer Institute I'm entering a colleague and he'll talk about his experience in building a population database and how that database can be used to drive decisions and In the midst of all that I will give a brief presentation on why every day should be a leg day Hello everyone, thank you for the invitation to this conference and for allowing me to talk I'm going to be speaking today about the role of The Warburg effect in cancer as well as mitochondrial function and how we can try to target cancer metabolism and cancer mitochondrial function through exercise, so I'm going to share my my screen and So, yeah before for many for many years I've been working with a leading and professional athletes and So I've been able to understand really well how a human Body works and understand perfection I always say say we cannot understand imperfection you wouldn't know perfection in the first place I've been lucky enough to be able to understand how those perfect Metabolisms those perfect machines work and this is what I've been doing But especially since my arrival to the world of academics 15 years ago. I started to encounter multiple diseases in which metabolism It was becoming a more and more important Player and this is why I'm trying to deploy the lessons that we have learned from eight athletes that we can apply To populations with chronic diseases, so I'm going to be speaking about the Warburg effect The Warburg effect it was discovered by a German physiologist Otto Warburg who received in 1933 a Nobel Prize. So what we know is like a differentiated cells Tissues they usually use glucose They produce pyruvate. I mean they degrade glucose to pyruvate. They oxidize it for mitochondrial transport of pyruvate and then production of ATP and they produce a little bit of lactate However, what we see in tumor cells and what Warburg discovered was that tumor cells They produce a lot of lactate and they do not oxidize a lot of pyruvate And this is what struck Warburg, lactate, right so it was called the Warburg effect and what Warburg What got struck was by by Lactate so this is the first research written in English in 1925 Although the Warburg effect was a hundred years old. It was in German Reading but this is the first written in English What he observed is that lactic acid appeared when when tumor cells were infused with different fuels different Substrates like my amino acids fatty acids or glucose Lactic acid appeared in the glucose experiments and then he saw that there was a large amount of entire weight of the Tumor cell in the form of lactic acid. That's how they usually Measure lactic acid in terms of weight. So it was very high and What would he the conclusion? What was that? There was like a very high glycolytic activity in this cancer cells and lactic production So this is how research was starting back in those days It was more at the metabolic level and understanding why that metabolic transformation of a normal cell into cancerous cell occurred so what we know is that glucose It's it's highly increased the uptake in cancer cells and glucose normally enters the cell and is converted to pyruvate and pyruvate should enter mitochondria for ATP production What were so is that there was a lot of glucose and uptake in those cancer cells but especially there was a lot of lactate production and this led Warburg to hypothesize that Cancer could be a mitochondria disease because in the moment where you cannot oxidize Pyruvate in mitochondria and you have to reduce it to lactate and produce largest amount of lactate It means that there is as Warburg described an injury to the respiration system, which is mitochondria Of course back in the days. We didn't know about he didn't know a century ago about DNA, right? but Warburg was trying to understand why This was happening, but the technology back in the days did not allow him to go farther and then in 1953 Watson and Crick discovered DNA and everything changed upon the arrival of genetics Cancer metabolism was buried and forgotten until very recently but the problem is that You know, even though you know, it's been in billions of dollars invested in the field of genetics genetics The field of genetics hasn't delivered all the expectations in the fight against cancer. This is the cover of Time magazine In genetics the future is now and it was really a hype and really very important topic, but this cover is from 1994 so this is almost a quarter of a century ago a long time ago So the future was never then through genetics and is definitely not now and who knows? Come to fruition. Although it has been helpful obviously in understanding cancer but in even if some treatments but not not to cure cancer now Watson who was the father of the human genome project very long process Which became that the famous human cancer genome atlas? The completion was in 2005 that led to then a new project which was called the pan cancer atlas Which was going to define once we know the human genome We were going to I mean the human genome once we know that we were going to understand every single cancer cell And all genetic makeup and the genetic mutations of each cancer if it's a tumor, right so the problem is that that was never the case because this concept called tumor heterogeneity and Each tumor has different cancer mutations and within a tumor We can see that if you take a biopsy to the left one centimeter to the left or even one centimeter to the right You're going to have different mutations as well So that led to a lot of uncertainty and anxiety among cancer research community And this is a paper from nature or genetics debate further focus should From sequencing genomes to analyzing the function right and even around that time Bert Borden Stein, he is the most cited cancer researcher in history. It was a brilliant issue and science where he described That there was a dark matter or there's something about all the genes, you know These oncogenes or other genes they were mutated but they needed a trigger that that mutations alone Were not enough and there's got to be something above that called According to dark matter now Johnson. I mean James Watson He's been quite controversial but at the same time Extremely influential because he discovered DNA and he's been the father of a human genome project He says now the target metabolism for cancer is it's a more promising Avenue, then gene cancer approaches Locating the genes that cause cancer has been remarkably unhelpful And if you were to do it all over again, you would go through by chemistry rather than my molecular biology that is you would go to cellular metabolism rather than genetics and and a very important thing that he said it's like we still don't know the reason of the Warburg effect and That you have to in these by chemistry and there's essentially no by chemistry left because everybody moved into DNA and there's the problem Upon their to discover a DNA and as I mentioned earlier all the work from auto war work was buried and everybody moved to genetics, so generations of oncologists and cancer researchers have grown with that understanding of Metabolism in cancer and the Warburg effect but these these these influential and controversial right remarks from Watson has led to like a renaissance in cancer metabolism So it's it's going almost back to a century and in a way it's a travel back to the future To understand the Warburg effect. These are the number of publications naming Warburg effect In cancer, which it was pretty much non-existent until the the first part of the of this century and is especially in 2015 we're starting to take off and we see like it's in the last ten years is remarkable And I mean this is already old for 2015 There are way more than that now every single pretty much every single cancer paper, whether it's a genetics paper or metabolism paper or clinical paper Already in the abstract or in the in first paragraphs of the introduction is naming the Warburg effect, right? So we need to understand it better. And this is what my colleague George Brooks from the University of Berkeley and myself We we came up with a hypothesis by which we believe that we could explain the Warburg effect and we believe we called it lactagenesis hypothesis, we believe that lactate is the Explanation and the purpose of the Warburg effect. You can read it in more detail But but these are things that we have learned from working with elite athletes Which we're going to say in the first sentence of the hypothesis lessons learned from exercise physiology metabolism Which can understand from these perfect machines as I mentioned earlier to understand faulty mitochondrial function and faulty metabolism in cancer cells Even some of these findings are going to media This is about a newspaper in Germany where we call about if the findings from working with elite athletes You know can help or lead to new therapeutic approaches for general population, maybe through the France would be even useful. So What we discovered or what we propose in our through our lactogenesis hypothesis We put the pieces of the puzzle together was that lactate is involved in Antigenesis is the main process in cancer as we all know immune escape, which is huge like Metastases as well and also the Self-sufficient metabolism the cancer cells have they're not efficient. Yeah, they're not You know, they they keep the cells alive not apoptotic, right? So anyways, these are the multiple steps Just at a glance that might happen. This is from a hypothesis You can read it in more with more time if you're interested, but then we decided is lactate an uncle metabolite So we see that You know, there are multiple Genes, there are driver genes there are dysregulated and they're going to lead to changes in different pathways as well as cell cycle and multiple changes they're going to fit ultimately transform a normal cell into a cancer cell and but as Orgenstein said That was like the dark matter. There's something above all these Driver genes in mutated genes in cancer, right? And so we believe that the answer or one of the dark matter Elements is lactate. So we published a few year I mean recently like three years ago a paper Where we showed for the first time that lactate is in fact a metabolite I mean an all come metabolite because it regulates the transcription activity of MCF-7 breast cancer cells where all those driver genes are significantly regulated as well as tumor suppressor in the wild form BC the BRCA gene It's a tumor suppressor, but it's overexpressed in some tumors and we know when it's when it's overexpressed It doesn't act as a tumor suppressor like when it is also under expressed so Around the same time the group from the University of Michigan led by Zhang And Zhao so what discover is what that the phenomenon called? histone lactylation So lactate travels to the nucleus of the cell and there what it does it increases histone lactylation So it exposes all the genes to be Expressed and this is what they discovered and then what we discover at the same time Is that that lactate travels to the nucleus but beyond? Exposing those genes and to be transcribed it does that we saw that lactate those mutated genes It really transcribes them or increases the expression as well And increase that expression by about 150 to 800 percent depending on those genes most of genes are driver genes are the main ones and Therefore is a major regulator later in cancer and without lactate those mutated genes have a hard time to be turned on So again, it's one of those dark matter that I've organized. I was saying we are Now we have another paper Under review where we are adding another line, which is a triple negative cancer cell length and we're having similar results And and so what we believe is that lactate that glucose that is You know, there's an exacerbation of glucose uptake by cancer cells Needs to lactate because there's some issues in mitochondrial function probably so that lactate There's some of that is used for energy purposes for the cell But the majority travels to the to the nucleus and over there It has Zhang and his group from Michigan discovered it expresses the genes and as we saw it acts as an outcome metabolite by Increasing the expression and of the genes main transcription factors and also Involved in cell division, you know Which are going to lead with that aberrant increase in cell division and decrease cell arrest typical of cancer But at the same time that lactate as we shown in our hypothesis is a major player in angiogenesis, immune scape Metastasis in the cell sufficient metabolism as well as that lactate is a major Responsible of the famous tumor microenvironment and now it's a it's a huge deal in cancer Research and and subject of further therapeutics So this is what we saw in that last experiment where we are It's under review right now, and we saw that lactate increases the expression of major genes but decreases also the expression of other ones both in ER positive G cancers as well as triple negative But then we also saw that increases not only the gene expression but the transcription into protein in both cells, so but this is an example of the EGFR, which is highly dysregulated in a large amount of cancers and Subject already for treatment and what we saw is that Lactate in we saw there was like a high expression under different Media conditions in experiment where lactate increases the expression of increases the expression that genetic expression, but also the protein expression so we decided to take this one step further and What we did is like we inhibited LDH. So LDH is the enzyme that converts Pyruvate to lactate therefore if you inhibit LDH, you're not going to find lactate So in fact through genetic engineering and short harping RNA when we inhibit lactate I mean LDHA, there's no lactate production and what we saw that there is no EGFR EGFR expression. It's not expressed And then this is the other the same experiment with the different conditions where we use control And when we have control and we have glucose There's plenty of expression of the EGFR, but when we use the short harping RNA, which inhibits LDHA We saw that under in both 24 and 48 hours. There is no EGFR expression. So we believe is an important finding because EGFR is the mother of Two major pathways that are dysregulated in pretty much the immense majority of cancers, which are the RAS-RAF Pathway as well as the PA3K-AQT-MTAR pathway which leads to aberrant cell growth and proliferation so and what we know with what we're fed again like glucose is that Enters the cell and it's oxidized to pyruvate, but that pyruvate cannot enter the cell properly. So it is oxidized I mean it's reduced to lactate and what we have shown is that lactate Increases both the gene expression and the protein expression of the EGFR and is this an experiment by decreasing or inhibiting LDHA. We increase with we inhibit also EGFR expression So normally if this is the mother The major regulator of the other pathways it should also decrease the expression of these pathways. It might be a great target for cancer growth and proliferation and restore cancer. So, but all these leads, all these molecular experiments and cellular experiments will lead to some form of translation research, right? So can we use what the term that I call metabolic rehabilitation to target cancer metabolism because we know exercise elicits important effects at the cellular level and the expression of multiple genes that are going to lead to an improvement in mitochondrial function and bioenergetics of the cell and general cellular metabolism, right? And we also know that exercise is the only medication to improve mitochondrial function, which is highly dysregulated in large amounts of cancers. Already, Wolfenstein, about 20, 20-something years ago, showed that in colorectal cancer, for example, about 70% of the cases of colorectal cancer showed also mitochondrial dysfunction, right? So this is a very, very important to me. It's the same, you know, paper with the exercising, the effects of cancer, I mean, of exercising cancer. This is a group of mice, this is a, sorry, there's a little lungs, and so they transfected cancer to these mice and this is the total volume of the tumor before exercise, I mean, in the control. And then after, I believe it was two months of exercise, random exercise, at the end of the day, mice, they run all day, right? So they show like a significant shrinkage of the tumor, which what we see here in the picture, it's significant. So this is, these are mice with no chemotherapy, no targeted therapy, nothing, just exercise, right? So this group went now to another paper and saying like the exercise from being just healthy stuff, right, that has been, and still thing, you know, people, ah, it's exercise, it's healthy. And most oncologists now, they're prescribing exercise because it's healthy, but actually, it could really be therapeutic because it can really target cancer metabolism, right? So this is what we're trying to do and with lessons learned from athletes, right, to first, how to prescribe exercise. So we need to understand the degree of metabolic and mitochondrial function in cancer patients so we can target a very specific exercise in the same manner that we do with world-class athletes. So we know, and so for that, I developed a methodology to indirectly, with my colleague, George Brooks, also, to indirectly measure mitochondrial function and this is by measuring fatty acids from the metabolic cart. In the metabolic cart, through stoichiometric equations, we can assess indirectly fat oxidation and we know that fat oxidation can only happen in mitochondria. And at the same time, here I am taking some lactate sample from the finger and we can see lactate in its capacity and we know that lactate can only be oxidized in mitochondria, therefore, both fatty acids and lactate are mitochondrial substrates and therefore, surrogates for mitochondrial function. And this is what we did then in different groups of populations, from elite athletes to moderately active individuals with populations with metabolic syndrome and this is a ramp test, an incremental test in power output and what's, these are lactate. So we know that the world-class athletes, they have an amazing lactate cleanse capacity and they do not accumulate blood lactate. Moderately active individuals, that should be our gold standard in metabolic syndrome, they have a very poor lactate cleanse capacity. This gap here doesn't seem very large but it is because we have the world-class athletes in context, which are people from a different planet almost but if we get rid of these athletes, the gap is significant here. Then we look at fat oxidation and we see that the same test and we see that world-class athletes have a huge significant amount of capacity for oxidizing fat, moderately active individuals, they're pretty good, that should be our gold standard and people with metabolic syndrome, they have a very poor lactate, I mean, fat oxidation. Then what I did is to cross them over, right? To look at fat oxidation and lactate cleanse capacity both in elite athletes, moderately active individuals in populations with metabolic syndrome and we saw that although the patterns are completely different, there's a very high correlation between fat oxidation and lactate, blood lactate using Bonferroni equation. So we know that this methodology can give us an idea, indirect idea of what's a mitochondrial function of a client, of a patient or of an athlete and therefore also, it gives us also a possibilities to prescribe exercise individually through this methodology. So without the necessity of doing biopsies and a very invasive methodology. So this, I have been doing this for almost 30 years with elite athletes where I develop what I call the metabolic map and we can understand what's going on at a metabolic level and therefore in the different substrates, fat oxidation, carbohydrate oxidation, lactate and therefore we can establish different training zones and in this case, I came up about 30 years ago with the zone two training that now is becoming quite popular. It's the exercise intensity at the one I've seen at first by trial and error but now in a more scientific way that is the exercise intensity at the one athletes as well as patients increase mitochondrial function the most. So therefore, this metabolic rehabilitation that I have coined can be utilized for cancer patients. The same concepts that we use with elite athletes we can do with populations with chronic diseases, right? So now, this is what the characteristics of cancer, this is from my hypothesis, is like a very high glucose utilization, poor mitochondrial function, right? And production of a lot of lactate. So it's a very glycolytic system. Now exercise and especially when you stimulate mitochondrial function through zone two, it increases mitochondrial function, aerobic capacity, which is going to decrease glycolysis, you're going to increase fat oxidation and increase lactate cleanse capacity, right? And then looking at a muscle as an organ is going to increase or improve the extra kinds of mitokines which is a very important concept that was developed by a group from Canada. This is from the first study where they were showing that the exosomes, they are released from the skeletal muscle and they could keep at bay many different diseases because they contain generic material and mRNAs, RNAs, enzymes, even sometimes DNA, and they can really keep at bay many diseases because skeletal muscle is a very healthy tissue if exercise is done properly, right? But we know that exosomes in exercise, in cancer, are a major contributors to metastasis. Exosomes represent everything that we see in the cancer cells of the phenotype and exosomes can travel to candidate organs from a primary tumor, penetrate that organ and release all the content and transform a normal cell into a cancer cell. And so exosomes are important. So can the exosomes from exercise, which are more oxidative, could be counteracting the glycolytic nature of exosomes produced by cancer cells? We don't know, but I think, I modestly think that this could be a way to explain why cancer, I mean, exercise can fight off cancer. And I'm just going to finish with this clinical case. This is Rob, stage four colorectal cancer, metastatic, diagnosed in 2015, 56 rounds of chemotherapy, no surgery, no targeted therapy, and he was in avid cycles before and he bite one or two, three hours religiously, but his training zones were not correct because he was training too high, very glycolytic as opposed to very oxidative. So these are the results with our methodology. So we saw that this is power output incremental test. His fat oxidation was not very good and his lactate was not very good at low power output. Now we saw that two months later, he had a significant improvement in fat oxidation and a significant improve in lactate cleanse capacity. So without a doubt, Rob's mitochondrial function improved significantly and therefore, his exosomes were more efficient probably than what he had before and could those exosomes fight off the exosomes from cancer and metastasis. So the fact was that two months later, Rob called me and he had done his PET scan and he had multiple metastasis everywhere and he said that he was free of cancer. He had no metastasis and he had done, the only intervention had been exercise. I'm not saying the exercise is going to cure cancer, but without a doubt, it can be used therapeutically in combination with a different therapy, specifically targeted therapies to understand cancer and target cancer. Rob remained remission for three years and he had a very good quality of life for those three years of cancer free, but unfortunately he came back and he passed away, but he taught us a lot. So yeah, really want to name here Rob as he was an amazing person. Anyways, thank you very much for your attention and thank you to my team and I appreciate the invitation to this conference. Thank you very much. All right, I hope this was a good overview for what we empirically already know, that we know that fit people die less by cancer and survivors tend to do better if they're quite functional. And so with this, we'll talk a little bit about why every day should be a leg day. As Dr. St-Milan pointed out, aerobic exercise of course is very important, but as we can all appreciate, there are multiple barriers to entry for aerobic exercise and poor leg strength is one of them. So I have nothing to disclose. Please feel free to share this as widely as you can. And so these are the objectives for the next 15 minutes or so. So we'll talk about who is Aunt Millie. We'll describe why leg power deficit is a problem, how we can accurately assess it, estimate it and what we can do about it. And at the end, I'll share some case examples of my recent practice. So who is Aunt Millie? Almost five years ago when I started a new gig, I was meeting with oncologists and one of the questions that I posed was, well, how do you know if your patient is fit to undergo treatment, transplant or big surgery? And the response was, well, we kind of look at them and we try to see, do they kind of look like Aunt Millie? Okay. And so, you know, there's one thing that I've learned over the years is that anyone can look good sitting in the chair. But if you think about this question on a population wide level, you know, in the United States of America, we have 50% of adult population who would have at least one chronic health condition and seven out of 10 chronic health conditions respond to exercise. We have half the population that do not meet the aerobic activity guidelines. We have two thirds of the population who are obese or overweight. We have 80% of population who do not meet resistance or aerobic exercise guidelines. And depending on how you define metabolic health, we have up to 88% of people in general population who are not metabolically healthy. So if you're thinking about this Aunt Millie or, you know, Uncle Sam sitting in a chair, chances are they're not doing that great. And so, you know, this of course is a problem not just for us in cancer rehabilitation world, but, you know, now these days we have more than 5% of United States population are cancer survivors. And, you know, these are the people who as was outlined earlier this year, up to 70% of cancer survivors have at least one functional deficit, which is compounded by the fact that more than 80% of them have some degree of sarcopenia, which is probably worth pointing out here. That's a population that is vastly more numerous than stroke survivors with disability, for example. So good thing is we're not gonna be out of job anytime soon. And so why is functional performance important? Of course, you know, if we objectively measure functional data, it's very clearly linked with mortality. And this is one of the good population level studies published almost 10 years ago. So these are the results of a short physical performance battery, which is an easily done panel. And basically what it showed is that the more able you are, the better you're going to do. And when the authors look at a separate analysis where they separated people with good walk speed versus bad walk speed, they noticed a pretty significant change in their survival, you know, as early as two years out. And so why is this important? How can we translate this into daily practice? So part of the short physical performance battery is doing a five times to stand test. And so what we could learn from this is something that is quite relevant. And this is how the basic science of it works. And I think it's pretty telling. So this is one of the earlier studies that looked at specific ways of estimating leg power from a sit-to-stand test. So this was a study of older Japanese adults. They were all healthy, and they were asked to perform 10 sit-to-stands as quickly as possible. Now, a number of metrics were taken, including the cross-sectional area of their thigh muscles using MRI as a gold standard, and also their leg strength was measured on a dynamometer. And what was found was that the number of repetitions that these patients were able to do didn't really correlate that strongly with the size of their thighs. And, sorry, the time that these patients were able to perform the 10 reps didn't really correlate that strongly with measured leg strength. And so this is why I think the standard repetition base measurement of sit-to-stand performance probably isn't as good as we can do. And so using basic principles that, you know, work is equal to force multiplied by distance, and that power is basically work per unit of time, we can actually approximate how much power leg muscles are producing. And so in this particular investigation, the metric was calculated as follows. So the distance traveled was basically measured as the length of the femur minus the height of the chair, which in that study was about 40 centimeters or 16 inches. Then the force, of course, was the patient's weight, which is body mass in kilogram times g, 9.81, then divided by time. And so once this calculation was done, it turned out that the calculated power correlated very strongly with the MR metric of the thigh size, and similarly correlated very strongly with the measured leg strength. So estimated power is a good, convenient metric. Now you could say what works in a lab study of healthy older Japanese adults may not necessarily translate into United States population, but it turns out that it actually does. So the same group that published the mortality data based on SPPB used this muscle quality index, which is basically the same calculation as the Japanese researchers did, and they basically found out the same thing. So in that study, they had a chair that was slightly higher, you know, 0.5 meters as opposed to 0.4 meters. They used the same metric for the force calculation, which was body mass times the free gravity acceleration. And they basically found out that if you separate people by quintiles, you find the same thing, that the ones who do worse on the calculated power do not tend to survive as well. And so in my practice, I noticed that I really couldn't do a standard sit-to-stand test for most patients because the chairs were just too low. So I started playing with the exam chair height, and these are the results that I can share with you today. So in my bone-net clinic, where I was able to collect data on about 200 patients, some of them were tested multiple times, the average chair height, as you can see, is closer to 20 inches. So they're quite high. And then similarly, in the heme clinic that I have slightly healthier population, you could say, at least by the chair height standard, still a good number of them required higher chairs to perform the test. And so, you know, then the next question is, if you vary the chair height, again, how do you compare the results? And so it turns out, you know, even in the large patient and varied patient population sample, if you vary the chair height and you include that variable chair height in calculation, your results are just as good as just as robust. And so this is a recent study of older Dutch folks where similar leg power calculation was carried out and then compared against hand group dynamometry, gait speed, and actual measured leg power extension. And it turned out that this calculated sit-to-stand power had the best correlation with maximal gait speed. And we all know that maximal gait speed is one of the ultimate prediction metrics for morbidity and mortality. And so this approach has been carried out in larger patient populations. And this, I think, is very cool. And so based on this thousands of patients studied, it was found that a lower, and not surprisingly, that lower calculated power cutoffs were correlated with much higher odds ratios of mobility limitations. And so, and this, I think, is a very good example of what we as a community can do to sort of, you know, get all of our numbers together and figure out where the cut-offs are, like what's the lowest power that we can tolerate to say, well, this patient, you know, might be okay with the next phase of treatment and whatnot. And so, now one thing which varied across all of the studies is how exactly they calculated the force, you know, which fraction of the weight. And so, you know, if you picture someone squatting all the way down, certainly you can say, yeah, you know, you can pretty much neglect the weight of their shins or, you know, say, well, maybe it's 90% of the body weight that goes up. However, in population that I work with, you know, the patients who require higher chair, probably a 70% of body mass portion is a better estimate. And there's been some work done by NASA engineers where they had, you know, space cosmonauts, astronauts, do some squats in the absence of gravity, and then they confirmed that, you know, 70% body weight is a better estimate than 90%. And so, using that 70% of body weight as the force, these are the power histograms that I kind of came up with in my population. And so, it looks like the patients with bone mets tend to produce less power than patients with hematologic malignancies. And I think what's important to point out here, both of these populations on average did worse than the most frail folks in those larger European studies that I showed. And so, now, of course, you know, my calculations are a little bit different than the ones presented previously, but I think if doing something like this, it's much more important to, you know, not overestimate the underperformance than underestimate the overperformance. In other words, if I have a patient who is pretty well off and, you know, I calculate their number to be slightly less than it normally is, it's probably not as big of a deal as if I overestimate the capacity of someone who is borderline frail, and then the oncologist next door is asking me, is this person good enough to go for transplant? And so, and with that, I'll segue into the way of, you know, trying to get the power a little bit better. So, I'm sure we've all enjoyed the Seidler lecture earlier today, and I think many of the same points I'm going to reiterate, that if you're going to have your patients do something, it should probably cost them nothing. It should be something that they can very easily relate to, and it should have practical relevance for their daily function. It should be something that's easy to implement safely, that intervention should be adaptable, so patients should be able to do it on a good day as well as on a bad day. It's ideally something that people should be able to do anywhere. And because we're in the business of trying to do good science, this intervention should be outcome-friendly, so we can, you know, share results and, you know, move the field forward. And so, with that, I would present to you that sit-to-stands are quite cheapo. And so, currently, this is what I do in my practice, is, you know, spend a little bit of time figuring out what the right height is, sort of this Goldilocks zone. Then we'll do a 30-second sit-to-stand test. For additional insurance, I also measure patients' heart rate before, after, and after the test in that one minute, just so that I have, you know, sort of my personal peace of mind that I'm not trying to give someone a heart attack, for example. And so, the way that I currently try to stratify my folks is the low performance, or the ones who can't manage too many reps, or the ones who need a really, really high chair, they're the sunrise and sunset group. And with those, we basically end up deciding that, you know, their bed usually is the highest surface that they have in their house, and therefore, it makes more sense to just practice when they're next to the bed, which is, you know, sunrise and sunset. And then, the vast majority of my folks are the breakfast, lunch, and dinner group, so I basically take their 30-second result, take 40 percent of that, round it down, and just ask them to start doing, you know, one set for breakfast, one set for lunch, and one set for dinner, and then increase by basically one rep from one day to the next. And the patients who are, you know, of the mindset where, no, I'm just going to do this one time, and I'm not going to, you know, bother with this three times a day, those are typically the higher performance, and they're the every-minute-on-the-minute group, they're the, you know, modified interval training folks. And this seems to work, but, you know, like I said, probably 95 percent of people are totally fine with the breakfast, lunch, and dinner approach. And so here are the case studies. So one of the first lessons that I learned from my patients was that, you know, it's very important to hold people accountable, and, you know, in the words of the patient who shared his experience with me here, you know, it's, you have to write things down, otherwise it won't happen. So this was a patient with severe GI graft-versus-hose disease, who was readmitted about one month after his transplant. This was an extremely protracted stay, about seven months long. There's multiple infections, multiple septic episodes, this patient became essentially wasted. You know, as you can appreciate from this x-ray, he didn't quite go into this experience with, you know, perfect musculoskeletal health, but this patient had a very definite goal. You know, his son was getting married, and he had to dance at a wedding in three months. So this is someone who is basically leaving a hospital, essentially in a wheelchair. And so he set up this system, you know, and he warned me that this is basically not for everybody. And, of course, not every patient is going to go through the trouble of measuring every single walkway in their house, and, you know, having a separate workout set for a different day of the week, but, you know, it gives you an idea. Now, at the same time, you can do something that's not quite as involved, and this is a filled-out sheet that I give to my patients in the clinic, which is basically just a simple table. And this is an example of an older gentleman who, you know, it was a fairly remote transplant, was admitted with recurrent pneumonias, also spent six months in the hospital, went home in a wheelchair, essentially tetraplegic, and at some point after his discharge, decided that he wanted to get a little stronger, so he asked, you know, can we do something? So this is what he did. In the span of two months, he was able to increase his sit-to-stand reps from three to the set to 14 to the set, and he was quite happy with it. Now, you know, the previous example, of course, as you can tell from all the numbers handwritten, shows someone with some degree of OCD, but, you know, you don't have to be OCD to make it work. This is a sheet shared, of course, with permission from an 85-year-old gentleman with prostate cancer, hypertension, osteoarthritis, stents with bilateral hip replacements, bad knees, and currently undergoing treatment for multiple myeloma. And so this patient started with, you know, doing it from time to time, and he kind of kept track of it, but what was really cool was I was actually able to measure him across multiple clinic visits, and his relative power improved almost 30 percent from first visit to the second, and even though he kind of fell off the wagon a little bit, it stayed quite good. You know, as you can see here, didn't quite go back to baseline. And so yet another patient that shared their progress with me was this. This is a fairly healthy guy. You could say he's a 56-year-old, about 10 years out of transplant, and he has this personal trainer type of occupation, and what was really bothersome to him is that even though he was able to recover strength and he was actually quite fit, he would still get short of breath trying to walk uphill. And so he decided he was going to pursue the interval training, you know, every minute on the minute type approach. And so this is what he's doing right now, and it seems to be working quite well. And so my takeaways that I'd like to share with you is that sit-to-stand testing is, of course, a cool way to, you know, do some very exact measurement, and I think patients who do it, they definitely see the utility of it, so it's much easier to, you know, try to get them to do stuff after that. The standard data on sit-to-stand, of course, is tied to a chair height, which it doesn't have to be, and so I think we can use the modified approach. And you know, best yet, this is something that does translate and definitely helps people. And so they say knowledge is power, and power is what, so I think we should all know what the what's are. And with that, I will pass the microphone to Dr. Christian. Why don't we take a quick minute just to stand up and stretch a little bit while we transition? I know it's the end of a long day, so everyone's tired. Okay, so it's an honor and a privilege to be up here talking to you today, and what I'm going to be talking about is kind of a segue from what my previous presenters have presented on. We went from a sort of a basic science approach to an individual approach in a clinic setting, and what I want to share with you is how to think about these things in a context of a population of cancer patients, and by that, it's through this Cancer Rehabilitation Physical Function Dashboard that we've started at our home institution, Miami Cancer Institute. My disclosures. So the learning objectives describe the MCI platform-based Cancer Rehabilitation Dashboard that tracks the physical function of cancer patients, reviews some of the physical function data that we've been able to gather from this dashboard, and discuss lessons learned and opportunities for design of future systems. So this is the Miami Cancer Institute. It's located in Miami, and we treat patients from all over South Florida, Latin America, Caribbean, as well as from other parts of the United States. It's a predominantly Hispanic population that we serve. We started the Rehabilitation Oncology Service back in January 2018, and currently we have two physiatrists, myself being one of them, and two nurse practitioners, and it's an outpatient rehabilitation practice, and we see all types of cancer patients of all ages and stages of cancer. So when we started this, our goal was really to integrate physical function in the language of a vital sign, and it should be an extension of our physical examination. It should be metrics to better understand the cancer populations that we serve and implement this new vocabulary and language into the clinical care of our cancer patients. And we decided on a multimodal approach to this using these several tools that you see here, two of which are self-reported, which is the PROMIS physical function and the PROMIS fatigue, and then four which are objective, a time-up-and-go test, a sit-to-stand test, a four-stage balance test, and grip strength. And as we know from the literature and even from clinical practice, there's a lot of significance to these tests. For example, the sit-to-stand can assess for leg strength, endurance, and balance, tug for the risk of falling and balance, grip for upper body strength as well as overall strength, balance, the four-stage balance test assessing for that, and then the self-reported physical function and fatigue metrics are also vitally important to us. So our process was to train our medical assistants in these physical function metrics, how to collect them effectively, we piloted them in our clinic, we developed a form to collect this data, and we worked with our IT folks on a power form in our electronic medical record system that can be used to collect the data for each patient visit, initial as well as subsequent. And then the physical function is entered into the patient's chart for new patients at every one of their follow-up visits as well. And this is what it looks like. So in this particular case, we have the medical assistant entering the information on a CERN or power form on a tablet, that information then gets translated into this cancer rehab flow sheet, and that data gets stored in an oncology data warehouse along with other important data for our patients at our institution, lab results, for example, genetic study results, imaging studies, and so forth. And then that data is then collected into this Tableau dashboard where we can look at it and think about it and look for trends in the physical function of our cancer patients. So this is what that cancer rehab flow sheet looks like. In this particular example, it's a prostate cancer patient, and each of these arrows points to a date when the patient was assessed, and those numbers correspond to those physical function metrics that I mentioned. What's nice about this is I can look at this with a patient in the room and see how the patient's done with respect to their physical function. Was there a change in their sit-to-stand score, for example, from 10 sit-to-stands in 30 seconds in April 5th to its most recent, October 13th, of 12 sit-to-stands. And that data then sits into this Tableau dashboard, which has multiple fields there we look at, which I'll quickly go through with you as well. And our clinicians have access to this. Right now, it's primarily myself and my colleague, Dr. Arata, as well as our nurse practitioners, but it's opened up to other practitioners in the institution as well, and I'm hoping to expand this even to our oncology service and so forth. So each of these tabs that we have on this dashboard has a legend. So anyone looking at it can look at the legend and kind of identify as to how we came up with the numbers, what's the definitions that we use for what is a unique patient, how many patient visits from when to when, what's our time frame, and so forth. But I think it's the filters that really give this dashboard a lot of meaning. And these filters were set up and developed with input from multiple stakeholders, including oncologists, psychiatrists, myself, obviously. And the filters, you can filter out the physical function data by date, by type of cancer, stage of cancer, gender, if they're in a clinical trial, are they a transplant patient, ECOG score, race, ethnicity, number of therapy visits, PT, OT, and speech, number of hospitalizations, psychiatric diagnosis, mortality, and even the cancer treatment, radiation therapy, and chemotherapy. And you could do this by different age groups. So whatever you're interested in, you can kind of look to see what is the physical function in these particular populations. And so, for example, if you're interested in a stage four lung cancer patient sit to stand, comparing that to a stage one lung cancer patient, or maybe looking to see is there a difference between sit to stand in breast cancer patients versus in lung cancer patients. And in this rather busy slide, you see these various metrics as they pertain over time. So what is the physical function? For example, self-report at first visit, second visit, fifth visit, and so forth. The red lines indicate that the person's values at the population level was how it correlated to a poor function versus green, which is a good physical function for that particular metric. And I just want to kind of look at this a little bit deeper dive. And this is the PROMIS self-report of a physical function. And what was really astonishing here is that almost 70% of the patients in this dashboard reported that the physical function level was quite good. Thank you very much. They're actually quite happy with the way that they're functioning. And there's no real problem for them. What was actually very interesting was when you're looking at the sit to stand for these patients, 53% of them had an impair sit to stand score. So there's an obvious mismatch between what the patients are self-reporting and what they're objectively doing. And I think that's a fascinating area to kind of delve into and kind of see why is that happening. And then we also looked at, for instance, the balance and grip scores in this dashboard. So I'm particularly interested in a third stage of a four-stage balance test, which is that sort of ability to stand with one foot in front of the other for 10 seconds. But you could look at grip strength data as well for both right and for left hand. And looking at grip strength, for instance, what was interesting here is that across all of our populations, about 50% had an impaired grip strength at that first visit when they saw us. So there is a pattern of certain types of physical function tests that seem to correlate more with impairment of physical function over time. In this particular tab on the dashboard, you can look to see what happens over time. Did the physical function improve, decline, or did not change for these various metrics? And this could be from that first time that we see them in clinic to the most recent time. And what's interesting here is that between 40% to 54% of patients referred to us showed an improvement in physical function metrics from that first visit to their most recent visit. When we look at something known as the ECOG score versus self-reported promise physical function, we want to see is there a correlation between these two. And again, you can look and kind of sift through the dashboard and see if you're interested in a lung cancer patient population versus a breast cancer patient population. We also have data on respect to body mass index that was mentioned before. About two-thirds, about 70% of our patients are either obese or overweight, and I think that has significant functional implications as well. We're looking at that as well. And this just kind of shows you that with this particular dashboard, you could actually look at various metrics. And for example, the sit-to-stand 30 seconds for us, if someone was good in a good category, they had an average of about 15 sit-to-stands, whereas if they're in the bad category, I would say they had about seven sit-to-stands in 30 seconds. So then, the nice thing about this dashboard, it gives you a bird's-eye view of physical function, and there are several advantages that I think that we've seen so far. And this is an evolving, it's a working progress for us. So right now, we're on the second and looking even the third editions of this dashboard as more practitioners become interested in knowing about the physical function of different cancer patients. One advantage is that the data can be modified as new research information becomes available. So if tomorrow we get something that says that the sit-to-stand normative data for men over 80 versus men over 70 is different, we can modify this in a dashboard, and that basically changes the entire dashboard to reflect this change is what's new in the literature. We can add new physical function metrics. For example, we're working with our pediatric oncology group to develop and integrate the pediatric physical function scores into the dashboard. Sarcopenia, the SARC-F, we also started using that. And once you identify this, the collection of this in the clinic space, it's very simple to just collect this information. So a patient comes in, they see the medical assistant. She or he does all these metrics very quickly in about five to 10 minutes. When I walk through the patient to the clinic space itself, I have the metrics in front of me. I could review this and I could, I've gotten to the point I could pretty much tell someone's physical function before I even enter the door, just looking at these metrics, because patterns do evolve over time for different types of cancer populations. The other thing is you can share this data with oncology clinicians at various team meetings. So for example, I report on this data on a fairly regular basis to all of our tumor boards and share with them what is the physical function of their population and are the specific trends there. And that has spawned actually cross-discipline collaboration on various QI and research projects, most recently with our pediatric group and our head and neck cancer group. Other advantages that it actually serves a dialogue with the patient. So you could share these metrics that initial visit and say, hey, you know, you sit the stand is 10, which is okay. And then when they come back and they've done, let's say rehab, now they're at 15, they could see that improvement there. So you could talk and teach them actually the language of physical function, and you could talk and have a conversation with them what it means to them for their own goals. And you can track these changes on individual patients over time and their functional status and share that with them. The other nice thing about this that you could look at functional data on rare types of cancers. So for example, how many in this audience see sarcoma patients on a regular basis? Maybe about three or four people. So the nice thing with this dashboard, our institution, we over, I guess, maybe an average year, we don't see that many, but over five and a half years, you actually start to see functional data on a very rare type of cancer populations. However, there are limitations that we're seeing so far. So some non-cancer rehab elements in EMR that are beyond our control include, for example, the oncologist and their staff don't enter a stage of a cancer or the ECOG scores or a type of cancer, we can't look at that data. And not all the cancer patients at our institution are referred to cancer rehab, so we can only infer on the data from the patients that are referred to us. The other thing that we're working on now is that, currently not doing, is that it's not differentiating between pre-cancer treatment physical function versus during active treatment or in survivorship, but that's in the works. Sometimes if the test is incorrectly administered and incorrectly entered data into the flow sheet, that can skew the data in its analysis. So it's important to train and periodically retrain multiple people to collect the data and periodically do spot checks that the tests are administered correctly by the staff. And then you have to work with IT to validate the data entered from time to time. The data has to make sense. So I'll give you an example. So one of these dashboard items, we had a huge spike, I mean, completely off the charts. I said, that doesn't make any sense. So we asked our IT folks, can you drill down into that particular patient's visit and see what's the story with their sit to stand? And when we did that, it actually turned out that it was entered that that person did 1,310 sit to stands in 30 seconds, which obviously is impossible. So what actually happened is that there was a faulty entry that basically the person's tug, the time up and go test was 13 seconds, which was a box just above, but it was 10 times that they did in 30 seconds. So you have to look for that periodically. It is essential to work with a biostation early on a regular basis to kind of sift through this and say, what do we see here? What makes sense? What doesn't make sense? And how can we use this information to then look at our programmatic side? How can we change the programmatic? How do we look at this and say, how can we improve the quality of care for our patients? So I wanna share with you a quick example of how we're currently using this in one population. So we do this with all the populations that we have at our cancer institute, but in one particular one I think is fascinating is that with our bone marrow transplant patients. So prior to transplant, they'll see me in the clinic. We collect this data that I just mentioned. And then during the actual transplant process, our physical therapists, occupational therapists, collect this data on the patient on a weekly basis. And we have a chart rounds on Friday afternoons. We didn't have it this past Friday. But we have it on Friday afternoons and we talk in the language of metrics. What was this person's sit to stand this week? What was their TUG score this week? How does that compare to prior to transplant? So the reason we're doing that is to pick up early changes in functional status. So if they have a dip, we don't wait a month to pick up on that. We calibrate the intensity of the rehab services, the intensity on a daily basis, the type of therapy, to minimize that drop in physical function, to catch it early. That's the idea behind it. So the goal obviously is to maintain or accept a slight, and the key word is a slight decrease in physical function metrics during the transplant process. However, this approach can be used for all cancer types. Identify applicable physical function metrics, incorporate the language of these metrics into the clinic workflow. So you talk the language of these metrics, sit to stand top and go grip strength. And then you initiate treatment plan using a tiered approach based on a severity impairments. You measure the effect of the interventions on these metrics, and then you look at different models to improve future interventions. And this I just, we just did a quick analysis of this just before I put this presentation together, looking at our dashboard from January 1st, 2018 to June 30th, 2023, 4,700 patients, to see is there a correlation between physical function and mortality using these metrics? And there is a statistically significant correlation between them across these metrics, including sit to stand. So I go back to sit to stand because when Dr. Shurkin and I started talking about this, we kind of independently were doing a similar thing, the sit to stand test. So it got me thinking about, well, what's the correlation between this and things that are important to us and also to oncologists, which is mortality and hospitalization rates. And there appears to be a associated with, a pair sit to stand test is associated with a high mortality and hospitalization for our patients. And this was kind of an interesting thing for us to look at. And this is still an evolving process and data analysis for us to think about what this means for us clinically. And this is the sit to stand mortality relationship. And what this basically says is that if someone could do more than 20 sit to stands in 30 seconds, the mortality probability is much lower than someone could basically do like two or three or four or five. So you might say, well, that kind of makes sense in some ways, but the really interesting thing is that you can use this information to educate the patient. You can use this information to educate the referring providers, but more importantly, you can design what I will call a multidisciplinary tiered approach to their care. So our team members here, and this could certainly be expanded, you see with the rehab nutrition cycle, social palliative care and so forth. But what's interesting, if someone is fit, they don't require a lot of services. So a lower intensity of services perhaps, but if they're pre-frail or frail, that has to change. A different kind of a rehab approach has to be delivered so it'd be the right intervention at the right time for that patient. So the idea, if we do this correctly, we should never ever see a patient come into our clinic in a wheelchair, barely able to stand up. In my mind, we could do better. Ideally, we see that patient that we know is a high risk GI lung cancer patient perhaps, we see them when they first get diagnosed. So that trajectory never gets to frail. If we do it correctly, we keep them maybe at that pre-frail state as long as possible. And that's the opportunity for us. So we wanna match the need with resources to maximize resiliency. So some future developments, and again, I keep going back to this because it's evolving. And as you think about maybe doing this at your institutions, how to think about this and learn from our pains and tribulations as well. But future developments are, can additional tools be of help? Patient apps, Fitbit data, step counters, mindfulness minutes, sleep, et cetera. They could be entered into this dashboard as another field. And once you enter it and start collecting it, over time, you can analyze that and see how does that make sense. You can incorporate musculoskeletal ultrasound measurements for sarcopenia, mid-thigh thickness, for example. Using maybe also bio-impedance spastroscopy data, which we have in our clinic. And a lot of you have heard from previous talks have access to SOZO machines and things of that nature. But something that's very interesting to me is very fascinating, something called a phase angle, which I think is an interesting thing to also include into a dashboard and kind of see what happens over time. What kind of data, what kind of information are we getting about our patients from this particular phase angle? So in conclusion, the CRD is a constantly evolving platform that provides an insight into the physical function of cancer patient using both self-reported and objective metrics. It can be customized to suit the interests of clinicians and researchers wishing to improve the quality of life of their patients. And as you could possibly imagine, there's no way one person can do all this. And I certainly have a lot of, I give a lot of credit to my colleagues who worked on this with us. And with that, I thank you so much for your time and attention. Thank you. Thank you very much, Dr. Christian. So we have five minutes left for questions, if anyone has any. Can you talk a little bit about upper extremity strengthening and how you guide patients to do that? And I know you're a leg man, but... Sure. Thank you. So the question is, how do you incorporate upper extremity strengthening into daily practice? And so what I basically tell patients to do is that, you know, they can do what they want to do. And most patients sort of have this idea that, yeah, if they just grip a dumbbell or a small water bottle and do some curls, it'll fit the bill, okay? In general, I encourage them to increase their daily activity. In other words, get engaged with things around the house. But if they ask for specific recommendations, I tell them, well, you need to be able to push, pull, and carry stuff, and just make that part of your day. So we focus on easy things like wall push-ups, for example, or for people who are a little stronger, we do counter-top push-ups, you know, and an advance is tolerated. A resistant band rows or resistant band pulls, I think, are quite useful. So thank you for the question. So my question's for Adrian. So the dashboard is obviously very impressive. I was wondering if you could comment on a couple things. One is, how long does it take for collection, and how much does that add to a particular patient's visit? And then the second is, how are you dealing with maybe data missingness and data integrity? So in other words, you know, if you see, you know, a hundred patients, how many of them do they refuse to complete all of the forms, particularly, for example, the patient-reported outcome forms, which some patients don't like to do? And then if someone can't perform one of the physical tests, how do you deal with that data in the dashboard? Is it a zero? Is it a not determined? And then how is that collated with other patients' data? Do you want me to repeat the questions? Yeah. So just for the recording purposes, there are three questions. Number one, how long does the data collection to the daily clinical visit in Dr. Christian's practice? Second question is, how do you deal with missing data? And the third question, I believe, was, how do you deal with super low performance? The data collection takes about five to ten minutes, and we chose those particular metrics because they're quick to do in our clinic. And you know, sometimes the medical system will help the patient to go through the form with them. So that's kind of time frame. If what was the second question again? Second question is integrity of data. So you know, in the dashboard, we only include the data that's collected. So if someone has empty fields, then we do not count that data in that. And if they can't complete something, we'll record it. It was, they couldn't do it. It was a zero. So that's how we interpret it currently. But if we don't have data on a particular field, we'll just exclude that patient at that time, that visit. So I guess, chances are, you probably have even better sensitivity for some of your metrics if you can find a statistical way to include those patients that are not completing those tests, right? Because they're the floor effect, and if you're not including them, then really you're looking at maybe a slightly higher functioning population. So we're not including them in this, but we still have access to the data. Because one of the things about the dashboard that's very nice is that you could do deeper dives into individual patients by MR numbers, and you could analyze those patients separately. So what we report in this is really just the ones that we have the data, but we can go into those particular patients' charts and kind of see what happened in that particular instance or case. So we have that capability to do it. And I'm preferring more to like, once you start to do descriptive analysis of certain cohorts, it'll be important to sort of combine those populations together, potentially, if you're talking about comparing different tests. Yeah. Yeah. So can I add to that? So in my practice, I collect the modified sit-to-stand data, but also hand-grip dynamometry. So between those two metrics, there are virtually no patients that you can't get some data out of, you know? And I imagine in the future, we can probably come up with a way to have some sort of a composite function, like some sort of a composite metric of, you know, kilograms or pounds of force in hand-grip and, you know, the watts per kilogram out of the leg strength testing. Yeah. And I would add to that that those particular tests, just about everyone can—we get some data on them. So grip strength, I think, is one wonderful thing. It's very simple to do. The sit-to-stand also, again, is something that's consistent. The forms, at times, it gets a little tricky because we have a Spanish population, we have Spanish forms, too, but then, you know, the patient might take longer because they can't read the questions, et cetera. So—but the objective tests, in my experience as well, fairly easy to collect. I think you might have just answered my question. I, too, work in a community with maybe not as much of a Hispanic population as you, but a fair amount, and you have Spanish, like official Spanish translations for all of the— Yes. Proms. Mm-hmm. Yeah. Okay. Thanks for your willingness to share your dashboard. I have two questions. The first question is, I've also seen that similar sort of disconnect between the patient-reported outcome measure and their objective performance. Why do you think that is, and how do you approach your discussion with the patient on that? And then, the second one is, especially with what you're starting to see with 30-second sit-to-stand and survival, have there been conversations with incorporating certain measures in the oncology clinics before they make it over to rehab? Yeah. So, great question. So, we definitely have that conversation with the oncologists as well. In respect to screening patients using the sit-to-stand test. So, what we're doing now is we're actually starting a program where we're going to use a sit-to-stand to screen for physical function in clinics because it's so simple. You don't require equipment. It's 30 seconds. You know, basically, it's—my general cutoff is 10. There's no logic to it, but I just think if they can't do sit-to-stands in 30 seconds, then we want to see them at every visit. So, that's the thing that we're going forward next with this. As far as that disconnect, I think it's a fascinating question. I think one thing that I've noticed is that very often, patients, when they get diagnosed with cancer and have a sort of a gradual descent, they sit more often. And the families and the patients themselves don't realize just how impaired they really are. But when you test them, then it becomes obvious. And I see that a lot with our neuro-oncology patients who are on steroids, high-dose steroids, and they get these steroid myopathies, and one day, basically, someone says, well, let's have you stand up a little bit, and they can't do it. So, but meanwhile, they're saying, yeah, I could do everything for myself, and so forth. So, I think that's a disconnect there. Another interesting thing that I find is that there's a sort of a level of physical function. If they're functioning at a very low level, it's very difficult for them to mount that, I guess, physiological reserve to get to a higher level of physical function. But if they are at a high functional level based on these metrics, they seem to be able to maintain that. So, I think that's an interesting concept. I don't have, I have some theories as to it, but right now, the advantage to this dashboard is it gives you an idea to look at things that you would never really kind of think about, and makes you think about them. And then the question is how to use that information to both screen for these patients, and how can you even have that conversation with an oncologist and say, listen, you may want to think about your stage four lung cancer patients differently when you're going to give them a new round of chemo or new treatment, because they may not be able to tolerate it. And these are some metrics you could look for. So, I spend a lot of my time educating our oncology colleagues in this language of physical function. So, I have colleagues now that basically know that if the standard of a patient is five, for instance, they got to call me or call our team. Thank you. So, to the second question from Dr. Oza, I think in my experience is that this disconnect between sort of patients feeling that they're okay when they're not probably comes from the discussions that they have with the oncology team. In other words, everyone who goes through treatment gets the standard, you know, the risks and the benefits. And everyone knows that things are probably not going to be so great. And I think patients sometimes won't, quote, embrace the suck when they probably shouldn't. So I guess we can call that a wrap. There are no questions in the online portal. Thank you so much.

Warburg effect

cancer metabolism

exercise in cancer treatment

lactate in cancer cells

gene expression regulation

mitochondrial function measurement

leg power measurement

mortality prediction

dashboard for tracking physical function

self-reported metrics

objective metrics

quality of life improvement