Alexander Fedintsev | Biohacking - anecessary component of a strategy for radical life extension

12:49PM Sep 13, 2021

Speakers:

Keywords:

aging

biomarkers

radical life extension

interventions

experiment

drugs

people

called

cells

life expectancy

extracellular matrix

increase

markers

instance

question

years

pretty

accumulate

younger

maximum lifespan

Hi, everyone, welcome to forces by taking one constituent group sponsored by 100 plus capital. I am very thrilled to welcome all of you for I think what will be quite a special meeting to rate. It has taken me almost a year to set this up. And so I'm really, really happy to have Elisa mill join today, basically, around ng wieners compose previous presentation on plasma revolution, there was lots of interest in the group. As you explore this further, I then did some digging, and then over a few recommendations, found a Russian biohacker group and was been doing self experimentation on plasma evolution. But most of the stuff was in Russian, it was very hard for me to read, and I tried to contact them was very difficult. But then finally, someone who else in the group helped me reach out and that was half a year later. So he took me half a year to handy God bed connection. But now finally, we have Alexandra huge and little did we know he also proposed a 10th hallmarks of aging. So I'm going to share much more info on Alexander in the chat, but today he will be talking about biohacking as a necessary component of health extension. And really, really happy to have you here. I should also say he has been pre admitted to be a 2020 to four sec fellow. So you will be seeing much much more of him over the next year. With that, without further ado, Alexander will talk for a little while, then we may have some discussion that will be on the record. Some will be off the record. I will share more info on Alexander's work here. I'm super happy to have you here. Thank you so much for joining. You can't Yeah, it's hard for you to know how many people here in this group have been looking forward to this. So thanks a lot for joining and welcome to the group.

Thank you, Alison, for warm welcome. I'm happy to be here and I'm excited to talk about our work. I'm here on behalf of our group of enthusiasts. Our group is called RL e group, which is not surprisingly stands for radical life extension group there is simple but but through so and we basically tried to research and try out different on longevity, like interventions on ourselves and do many, many more things and I will tell about some of the products today. Yeah, let me share my screen. Alright, can you see can you see the slides possible? Alright, let's go forward. I would like to start my presentation with the words of brilliant scientists Nobel Prize winner Richard Fineman, who like who pointed out there's there is no like physical law that good limit our life like life longevity. Yeah. And this is basically what motivates us what drives us to to reach the radical life extension and how do we in our group define radical life extension, because of course, this is ambiguous term. Some people could define it as like 10% increase some some to define it is like 10,000 fold increase in life expectancy, but we defined as at least two fold increase in life expectancy, but the ultimate goal for us is of course, achieving longevity escape velocity, I hope that you are familiar with this term longevity escape velocity. And I actually proud that here, like we have here in the call person who, like advocated for this term. And basically, longevity escape velocity means that every year the progress in science and technology adds additional year for for the life expectancy. So, eventually this should be our goal. But let's let's see, how far are we currently from like from reaching this this scope? This ambitious goal? Yeah, in my presentation, I would like to answer three questions. Why biohacking is the basically the necessary component of a strategy for radical life extended how and how we do biohacking in our group. And what we have already achieved. So why we do biohacking first let's, let's try to analyze how far are we from achieving the longevity expected longevity escape velocity, right. And to do that, I have I have gathered the data from European public data banks and plotted the increase in life expectancy. On the graph. Here we have years on the x axis here on the y axis, we have life expectancy in different countries, I did regression, I made a regression lines here, and the slopes of this regression line lines tell us how many years we gain on average, like in particular country, how many years of additional life expectancy we gain every year. And we see that in some countries we gain like in Belgium 0.27 years every year, and so on, like very similar numbers in other bunkers. But on average, we gain 0.25 years, every year, this is life expectancy at birth. And it looks pretty okay. So like linear trend constant linear brand on increasing life expectancy. But in fact, this,

this slap expect this increase in life expectancy is not that big, because, for instance, if the grant will continue 30 year old can well can, you know, like half 50, additional 15 years, or 16 years to the current life expectancy. So, it's not a dramatic increase, even with this kind of progress like linear progress. But this is life expectancy at birth. And if we look at life expectancy at 65 years, we see that slope, now here became gentler. So, the life extension is not a uniform across age groups. And if we look at life expectancy at 85 plus years, it all like it flattens out almost completely. So, it means that the current progress in healthcare, it doesn't account for death deaths at Advanced ages, right that 85 plus years. So, basically, we can see that it doesn't, the current progress doesn't involve aging. So we don't have interventions against age aging itself, per se. And this infographics tells us that, okay, life expectancy at birth increases by every four years by one year, life expectancy and 64 years, 65 years, increases every 66 years. And life expectancy at 85 plus years old increases every 15 years. This means that many of the people, if not all, aged 8085 years or older, they are virtually doomed with the current progress of medicine, and maybe even like, younger younger people as well. So we can while we can clearly see this, from this graph from the scientific paper, which shows us clearly what's what's the what's the reason of that. Here we see two graphs, it's the these graphs are mortality rates on a logarithmic scale. So, in fact, these are exponents exponential functions. And the blue curve corresponds to the mortality rates of of so called poor people and like red curve is mortality rate. So what rich people and we see that the difference in mortality at 40 years is huge, but then it shrinks towards zero at Advanced ages. It means that the current current health care cannot actually prolong significantly a life of an old elder people. Like and this is this is when link the new medicine the new new healthcare and like new advances in science and technology should come into the, into the area. But what what is the current state of affair in, like in the longevity field in in the research field? So, it's also quite the study. It's, it's probably not the most optimistic because the study by Pedro de Magali is I don't know how to pronounce his surname correctly, so I'm sorry, if I'm Miss mispronouncing his surname showed that actually were the out of almost 30

Oh, life extending genetic manipulation in mice, only two of them showed signs of demographic aging rate retinal bation. So what does it mean in practice? What does it mean? Like demographic re demographic aging rate reservation? So let's take a look at these graphs, these graphs for called survivorship curves, and let's say that a yellow one yellow curve represents the control population control cohort a might maybe like people for instance. So, and the green curve represents the aging rate retardation, so, the intervention that actually decreases demographic rate of age, and we can see how dramatic is his maximum life lifespan improvement. So, all other cohorts have have already died out while like almost half of the green cohort are still alive. So this is what what happens when we influence the the aging per se. So the blue curve here represents what represents the intervention types that we have already discussed previous it's so the current health care. So it extends life in the in the beginning, so like version and no mortality here, but then two curves like converge, because because the like the mortality rate decrease here is pretty negligible. And this is not what we want, because we want to increase like the maximum lifespan as well. Luckily, we don't necessarily need right now to retard a aging rates to achieve like maximum life extension, maximum lifespan extension, we have so current genetic interventions in mice also extend maximum lifespan, but they do it via so called like parallel transfer of the survivorship curve. So they do not retard aged grade but still the DM demonstrate quite decent improvement in both median lifespan and maximum lifespan. And this is what we want to to develop. And this is we wanted to see from our big pharma. But what happens with Big Pharma, like we see that this process of adoption is is pretty pretty slow. On average, it takes like 2012 years to to like adopt a drug or intervention from preclinical trials to mark and there the failure rate is tremendous. Only one in 1000s of new drugs and up and up a ranking end up in like market one market. So the and currently there are not much anti aging drugs that are in developed and this is a Like said story, and this is why we need by hacking because boy hacking can can speed up the process of adoption of different already known interventions that dramatically, but only if by hacking is done right. And I will tell you how we do by hacking. Like, yes.

So by hacking done right, so we identify three main pillars of, like so called, we call it the correct barbed wire hacking or like intelligent bio hacking. So first, you use a mathematical framework for evaluation of potential interventions. So we need to understand how promising is the interventions, how many years on average, it can add to the to the lifespan? Is it worse, to even like to be even tested? Right? The second main pillar is to avoid typical experimentation mistakes, because experimentation and especial self experimentation is not an easy thing. It you can fool yourself easily if you do not do everything correct, from statistical point of view, and yeah. And the third main pillar is to do if you want to defeat aging, in the end, you must understand what is the underlying cause of aging, and we are also develop and doing theoretical progress in that direction. I will expand on this on this. And the next slides. So first of all, we developed a mathematical model that is able to convert risks of all cause mortality to add additional years of life. Because many studies that you can find on PubMed or other databases, they report, you know, like, relative risks of all cause mortality and something like that, or odds ratios or whatever. But these quantities are not intuitive. A you can like, basically, it's hard to tell whether a risk reduction of 10% worth it. So worse to test the drug or something like that, or like any other interventions, for instance, dietary interventions, okay, so some studies showed that they like consuming, I don't know, like, vegetables reduces risk of all cause mortality by 5% is a big increase in life expectancy. So it's small, people usually don't understand. And we we have developed a model that converts it, this risk reductions into the preceding two different easy quantity, additional years of life expectancy. And we have, you can, you can play with our demo of our, like the old power framework, which is very simplified, but reflects the concept. Alright, so this is enough about it. Let's talk about the experimentation mistakes. The first, experimentation mistakes in the first trap of self experimentation is that many biohackers do not account for the statistical phenomenon called regression to the mean, of regression to the mean. Like,

I can explain with a simple words, what does it mean? So, every like most of the biomarkers, especially in blood biomarkers, they'd have a natural, they're very variability. So the variety over the top and some markers, or many markers, actually, they ride pretty with high amplitude, and the parents pretty huge. And accidentally, if you take one measurement before the experiment, and after the experiment, before the experiment, you might actually accidentally measure your biomarker at the peak. And after the experiment, you can measure your biomarker at the trough of the natural their variants, and then you can run it To conclude, that the intervention led to the decrease in this biomarker of interest, but in fact, it is a mistake. So, it was just two natural parents over the variance of this marker. To avoid that, we first will try to beep markers that are that have quite small variance right. So, they are pretty robust stable and ideally monotonically increasing with age or nearly monotonic increase increasing with age. But for highly variety wearable markers, we do this the following procedure, we we have a history of measurements per person. So, we can we can plot the distribution, we can create a distribution of values, and we can say okay, this value seems to be an outlier, it is unlikely that it that it came from the distribution of previous values for that, like for the person, so we can say that it is unlikely that this value was was due to natural variants of this of this marker. Alright, the next experimentations taken how tackled the hacking. He typically by hackers, they do plan to, they measure plenty of markers at once. So the measure like panels of biomarkers were some by by hackers have like hundreds of biomarkers in their panels. And by just by pure probability theory, you can have like, due to random fluctuations, you can have several biomarkers like you can have, like statistically significant difference in at least several biomarkers, just due to due to lots of comparisons. And to avoid that, we apply simple sophisticated statistical methods in our experiments like Binyamin hope, their procedure for multiple comparisons correction and so. So this also helps helps this this is of course, not the silver bullet. It doesn't say automatically that our experiments are free of false discoveries, but at least it improves the chance that we will discover something meaningful, not not just random noise and the deep wonders then the third pillar is a deep understanding of the biology of aging. So we believe in the group that

current current view, our view of the aging process in the academia is is cells increasing, right so many of the laboratories like scientists, they focus on cells, they do epigenetic reprogramming the waker manipulates the NA deep loss levels, kill senescence cells whatever, but they completely overlook the the changes that are happening to the environment of these cells, namely extracellular matrix which is comprised of long leaving proteins like collagen, Alice Steen, and or like all of you probably know that these proteins undergo chemical modifications like glycation, and glycation leads to crossing formation to add new adducts formation and so on and so forth. And these actually, we have shown in the paper that these changes to long living molecules can lead to fire various mechanisms can lead to virtually all hallmarks of Asians so they can cause this hallmarks of aging. And the true underlying cause of aging might be just this damage to the extracellular matrix where our cells reside. And to give a bit more context, I have one I want to go here too deeply into details but I like would like to present some Some facts and hypothesis. So for instance, we can see here that that old stem cells, mesenchymal stem stem cells are planted like one place placed on a ni ECM extracellular matrix from younger mice are they expand like like young cells, so they preserve the traits of young cells on the younger matrix, while the younger cells like three months old cells, while being placed on on ECM from old mice, they display traits of old stem cells, so they divide less they have like specific biomarkers of old cells, and so on and so forth. And this is my hypothesis that I'm advocating for is like, what causes the cellular senescence phenomenon? Well, basically, it is not a surprise that it's not like something new that senescence cells are actually playing a role in wound healing even in the younger people. So these senescence cells are mainly like count direct fibrosis. And my hypothesis, the hypothesis like explains the accumulation of senescence cell the following then the following way. Since senescence cells like contract fibroids, then changes to extracellular matrix during the aging like stiffening like, matrix becomes resistant to collagenases and so on and so forth. It mimics the fibrosis and cells erroneously think that there is a fibrosis and can like turn into senescence cells and start doing their job to counteract the fibrosis. So, in a way you can cold call as like aging at CU to fibrosis. Yeah. So, this is my hypothesis, we were we are also working on experiments that will either confirm or deny this hypothesis, but yeah,

I would like to share this and we believe that the eventually what can lead us to radical life extension to like the longevity escape velocity is exactly the therapist that can rejuvenate this extracellular matrix, Mega deonna, again, like break down the the crosslinks new glycation currently it is it is problematic. So, we don't have any glucose pain breakers. But we still can do something to matrix and I will talk I will tell about it a bit later. So what we can do already now. Alright, so now let's discuss what we have, what you have already achieved and what we plan to do in the future. So, these four main areas of research and development that our team is focusing on. So first nine thing that So, like this is the first thing that we have tried in the beginning, when the group was formed is drug requisition. And so, we look for papers, where where different drugs are researched. And like where people you know, like, describe some anti aging properties of different drugs, we collect information we I we identify under wine pathways that these drugs, target and so on and so forth. We have also computational models, and we try try these drugs on ourselves, and I will later tell a bit our first about our first experiment, successful experiment was drug requisition. To test these drugs, we need something that we can measure and we Identify suitable biomarkers, we develop new biomarkers like composite biomarkers panel, so, biomarkers and so on and so forth mathematical modeling, I have already mentioned that and gene therapies. So, we started developing our own gene delivery system like recently in 2021. So, I will also cover this topic later and briefly what are our main focuses but we are not limited by that this is just what we are what we are targeting right now. So, musculoskeletal system to counteract circuits or capponi circulatory system, we are trying to remove the atherosclerotic blocks and increase elasticity of our blood vessels and cognitive function of course. So, this is a timeline with our progress. So, we have started as a group into sada in 2015. And then, in 2016, we conducted our first experiment. And in 2020, the, our probably most famous experiment happened, like therapeutic plasma exchange, research and in 2021, we continue with gene therapy development and more other smaller trials. Let's talk about about our history. So, in 2016, I worked on the data set analysis I had, I had huge table with lots of biomarkers for $1 billion journey during the logical center in Russian in Russia. And I was analyzing the data and found out that marker several markers of arterial health were, were strongly correlated with with like, actual age of people, and that I decided to like build a regression model to predict the basically age and I was surprised that the the model that I filled eventually,

it it likely, was not only the model property in chronological age, but it was also a pretty good predictor of overall health and the for instance, people with diabetes and hypertension, they have a significantly higher biological age. And this biological age was mainly driven by four factors, carotid intima, media thickness, pulse wave velocity, degree of stenosis and augmentation index. So, only four biomarkers give the error of six years and likely represent biological age estimation. And remarkably, the most significant biomarker in this in this index, carotid intima Media thickness, it happened to be a very, very robust biomarker, it was very stable, almost monotonically increasing with age. So, it was very hard to reverse. And there are very, very few drugs that could do this good rate other than like reduce the carotid intima Media thickness. And, but we have managed to find a drug combination that that exceeded our expectations. So we have found that drug combination belser accomplice, lovastatin reduces the carotid intima Media thickness homes to fall in both of our our volunteers and this are our co founders, Dennis slough and URI and the this reduction was pretty stable. It persisted for about a year which is remixing remarkable, I think, because I have I have I have seen lots of records about the progression of kerucut intima Media thickness and it's it's very stable biomarker. So, another biomarker very important biomarker, in this model is pulse wave velocity, which represents the reflects the the arterial stiffness It is it is pretty variable biomarker, or in our intake opposite to current intima Media thickness. And hence, we needed a device that could allow us to measure eat, like multiple times before the experiment after the experiment to like average our measurements and new, more statistically. Like statistically robust conclusions. But the there are few devices accurate that can accurately measure this despite marker on the market available on the market. And that's why we developed it ourselves. So we are biohackers. And then, so yeah, the first prototype we like he was already for our trials. We took our learnings from that, and we are working on a next version, which will, which will hopefully be out next year. So, yeah, looking forward for part of that. So another our achievement is basically the plasma Flores's, which is pretty famous in certain, like, yeah, and, like, pretty, pretty famous, I don't know, because other other our interventions are not that our experiments are not that famous. So we conducted this, we didn't, we didn't expect to observe like dramatic improvements in biomarkers that we can, like, treat as Super promising, and so on and so forth. We just wanted to basically understand how, how we can do that logistics like the logistics of the whole the whole process, because it was

so so you need to replace half of your plasma with the Celt selling, and like less albumin. And this is not a simple procedure. This is not a standard procedure. But we've managed to calculate how many, how many plasma you need to donate, at each, like visit to the doctor, and then how many albumin you need to replace. And we did this. And surprisingly, we have found some, like, pretty interesting changes in our biomarin biomarkers of this gentleman. We have found that, for instance, contrary to our expectations, for instance, cholesterol, it, it goes both directions. So it the bad LDL, bad considered as bad, it goes down and the HDL goes up, which is pretty interesting. But of course, we have like one or two data points. Now more of course. So we cannot draw conclusions out of that. And that's why our friends and colleagues members so far over the group. We have started a clinical trial and you have this identifier here. This clinical trial aims to compare plasma Flores's with album in and vote album, because it's interesting which role album and replenishment place and the whole procedure. So you can use the QR code to access the the article about the power experiment. Yes and next thing Yes, so here are smaller, smaller things that we have achieved we have tried various senolytics folks so for the Araya peptides are visiting other other drugs, our human volunteered to and but the thing is that even though they volunteer was like 57 years old, we haven't found that much senescence cell in his body and so we cannot see whether they work or not. So probably we need some someone older. Then we also created lentiviral vector for April, a one Milano gene delivery. We also tried microbial replacement experiments we can expand on what Later, it's pretty interesting stuff. Because we have a collection of microbial microbiota from Soviet cosmonauts. They are considered to be like, super healthy man. And we have a hypothesis that this might microbial microbial, like being transferred correctly can basically yield some very, very nice health improvements. Yeah. So what's next? Oh, here are several things that we are planning to deliver in the upcoming years. First of all, we are very intrigued by the article which showed that targeting the enzyme 15 PGD, ash, which basically basically, you're referred that muscular aging. So and we are very intrigued by that study and want to reproduce on ourselves. We also aiming for epigenetic rejuvenation of hematopoietic stem cells via targeting CDC 42 it's pretty also well known target, why it's all this is probably one example of cells that cannot be rejuvenated by place and by placing them in the younger environment. So, hematopoietic cells are or pretty reluctant to the changes like to reversing aging using this like methodology, but we can reduce their like, reduce their epigenetic age by targeting this enzyme or this protein. And but then, if they if they are in the old environment, they age again, they become senescent again, and so, we plan also to investigate how we can maintain the useful environment for this rejuvenated cells. So, this will be a very, very interesting one journey.

And the third, third point is actually very, very important. I've mentioned that there is something that we can do with h ECM already now, and this is targeting ls the janessa Celeste internet. So ellisdon is now considered to be one of the long longest living protein in our body, it basically it is there is a consensus in scientific community that last agenesis is limited to like early infancy, and then they have like all synthesize elastin like basically remains in our body and then it accumulates calcium also is degraded by enzymes and so on and so forth will lose these elastin and this leads to progressive progressive deterioration of different tissues, not on the blood vessels. Now, it is very, very important, but also skin, lungs and other like our ligaments, muscles, and all tissues lose their elasticity. And this is like crucial work not only for our appearance, but also for our functional and functional health, because for instance, rigid blood vessels, they lead lead to damage of organs because the blood they do not dampen the blood blood flow and that's why the the fast moving blood flow they damages sensitive capillaries in brain and kidneys and other organs. Also the of the fast this fast blood flow which is not dampened by the elastic order, it creates turbulence and the this turbulence puts an enormous load on left ventricle or power cord and this causes hypertrophy, cardiac hypertrophy, then hypertension is also can be caused by this outward extension and and so on and so forth. And we can try and we already have some drugs and other methods to increase production of elastin like in vivo, we will try and they force us Our main thing is development of anti aging gene delivery system. So, when this is actually what we have, what do we have tested already? So we have already experimented on on this animals to know how to Sorry, I forgot how to call this house in English. This is my bed. Sorry. But yeah, we have got our first promising results that might work actually, and we are developing this symbol and simple and safe gene delivery system that we aim to be used for delivering some anti aging genes and achieving on a pretty, pretty normal, I just hope that we will achieve with this gene therapy. Pretty impressive increase in life expectancy in the future. So our team, we are currently fifl was, yeah, but we're expanding. And you have developed in our efforts in in like, achieving radical life extension. Yeah, thank you for for your attention. It was a pleasure to present our stuff here. And ready for questions.

Thank you so much. Well, you have lots of questions here. And I will stop sharing your screen for just a second. Sure. A lot of information and you I will download the chat and send it to you because there's lots of detection on new work in it. And people have actually been going through the motion imposing most of the articles that you mentioned in the chat already. So that's great. And okay, let's see. So, oh, my God, we have lots of different questions. I guess, at let me know, in case I'm, I'm missing on someone, because usually I ask that you start them with the cue, but not everyone did this. I have one that is from deema. One from Alex Chen, and then I'll get back with a few others. So do you my your first?

Yeah, so, um, my question was regarding the, like, the progress you experienced so far, and when like whether it convinced you that biohacking can be impactful on I don't know, you can you can sort of claim as well if you think it was already impactful, and like why and at what point that you decided that it's kind of a worthy investment of time and money.

Yeah, well, basically, why interests to the life extension topic began in 2012. And at that time, I strongly believe that we will defeat aging with like, short within five years, but then then radical life extension was like steel very, very far away. And I like I started digging the material start started, are analyzing literature analyzing, trying to dig into these signaling pathways of age and trying to understand why why the progress is still there, why do Don't we have like this, you know, like rejuvenation therapists, and then then they infer, like critical mass of information accumulated and the the strategy of radical life extension like, emerged out of that. So we understood that actually, the cause of aging might be and likely to be in the ECM in the crosslinks location. And that will take 3d a long time to find ways of how to rejuvenate this vast majority of long living mt molecules, because it's not an easy task. And therefore, we need some ways. I like to mean some time before that, because it easily can take like two or three decades until we get to the point when we will have these age breakers or like other techniques that can basically rejuvenate our matrix, extracellular matrix. So I hope I at least partially answered the question, but but it's really hard because I can speak about it like ours. And we probably don't have so much time.

Well, I hope you can stay on for longer because we have lots of new questions. And next one up, we have Alex Chen. Okay, then we have makeup.

I got a few questions. I'll start with one to let someone else go after me. And then last by the ones after. Yeah. Do you have any ideas on how we can do better at educating potential biohackers about the common pitfalls you mentioned that started to the stock? Like how can we avoid other people who want to get into biohacking, kind of not making the same mistakes?

Well, that's a very good, good question. Basically, probably we want, we might start some initiative where we will accumulate best practices, create some some, you know, like, port, like, create some swab, where we will accumulate best practices, which will, which will, which will tell people how to avoid different mistakes, right? And how to be safe during this self experimentation. And probably maybe, even because it's a very, it's actually a very risky thing. And the biohackers are really brave men who try out new things, and many so called biomarkers, they just want to be like, I don't know, like, they probably do not realize what is by hiking, maybe it's like, something fancy they want to dry. But in fact, it's very risky thing, and it's probably a good thing to accumulate some knowledge somewhere and like, advertise this, this place where all the materials will be, which will basically say how, how cool is that? And on the other hand, how, how dangerous is biohacking and how to do it properly, like avoiding some statistical mistakes, and so on and so forth. So yeah, so we need probably a centralized place where we can accumulate all this information and then and then spread it over the internet. spread the knowledge on this website or something like that. Right, next one, we have Josh Alexander, my question was on how often

do you guys control for like confounding variables just in like lifestyle? Like, do you track your like sleep exercise and diet daily?

To make sure of course, we do we have like that, they are ables were wearables. Like, you know, like, like, Fitbit devices, right? So where we can see what was the distribution of activity back then bang before the experiment during the experiments on. But for instance, so what we think is that the control and control for confounders is especially important, when the effect size is very small. So then different confounding variables play play a huge role. But for instance, if you have like, a Alzheimer disease, right, and then you suddenly after invented intervention got like, a dramatic improvement in cognition. So it doesn't really mean what the lifestyle was, because it's the it has pretty limited influence on the, on the cognition, you're in this condition, right? So we are trying to pick up markers that are very, very stable and aren't, aren't easy that easily influenced by changes in lifestyle. So the to increase robustness of our findings. So this is the main idea to keep big up, like very, very stable markers, like I've mentioned, charactered, intima, media thickness, and so on and so forth. And of course, try to keep the same lifestyle as before. And we can of course, track track this by analyzing our activity data from variables. Yeah. This is thanks. Aaron with a short question. Yeah. Alex, how old are you? 34 this year, and turning in December. Okay, next up, we have john and sorry, I'll answer couple of words to the previous question. Unfortunately, I'm too young to like, do interventions myself and see the results. But still, I'm, I always try to take all the peel pills, all the drugs will make others do because I would like to test like safety or interventions. But I cannot see effect on me. Because I Borenstein car and have pretty pretty good biomarkers.

I Alexander Hello, sir. Hi, Alexander. I hope you can hear me. Okay, my internet connections a little bit unstable. You showed a nice chart of all cause mortality. And I wondered if you have access to some data that excludes things like accidents and injuries and war so that we can Yeah. War focus late on on age related diseases?

Yeah, I think it's, it's, it's already this status filtered. So it's like this from natural causes. By the way, are you that john john Ferber, who wrote a paper on like glucose and glucose pain breakers, like as a future therapeutic for, like, Asian? I am when I presented it a sense. So that I was I was also inspired by your work, and I cite your paper and I found it like, brilliant. Brilliant. Yeah. And that's arguments that, like, enzymes probably cannot do too much to crosslinks because they are too large and cannot fit between the collagen collagen. collagen strands. This is like, very, very smart. And I also share your concerns about that.

Well, I'm so glad that you got to see that I picked chapter 19 of the future eight, which is a book great be edited in 2010. Um, so Mike Knight thought once then maybe what we need to do is genetically engineer fibroblasts to do a better job of turning over the extra summoning matrix.

Yep. I totally agree with you, but it, but I think it will take a lot of time until we get to the working therapy on like, you know, speeding up the turnover of of the extracellular matrix, and we definitely need to win some time. You have to be able to preach this.

The Meanwhile, meanwhile, we do have a small molecule that is equal to take care of some of the crosslinked sandfly creation called Allah g berean.

Yeah, Lt. 711. Yeah. Yes. been?

I've been making that in my laboratory. So if people want to experiment, they can contact me.

decarb Big carbonio crosslinks?

That's correct. Yes. Okay, I thought it mostly didn't work except in dogs.

I was already clinical training. I am in a company that is not giving up. We can discuss this in another discussion.

Yeah, I would have a like I would be happy like to discuss it that really, really awesome.

This is the content of one of our presenting aging chapters is the story about Gabriel. I know. I think there's some reason Michael race chapter.

Well, we are going to do a follow up on this. So maybe that's a really good one to tie in to that one as well. Someone wanted to ask me a What are you doing personally, Alexander in terms of health extension? And then also, how do you avoid microplastics when doing plasma dilution?

Since I'm relatively young, I'm not doing anything special. Just physical exercise is trying to keep my diet more or less healthy. Yeah, and try to avoid like accidents. But other than that, I'm not doing like I'm not taking like supplements on a regular basis. Maybe. Maybe, yeah, I'm, I'm actually, I would like to point out for instance, I'm a fair I'm actually advocating For, for actually insulation. So like people avoid sun, but I think that it is incorrect. I will not, like, discuss this too deeply in this meeting, but I would like to maybe talk a bit about it later. Yeah. So regarding the second question, what was it, like microplastic during the plasma dilution? We don't do anything about that yet. So we will evaluate the importance of this factor in future. So we just tried this, like, as a pilot study, and we haven't really came up with the best way of doing plasma dilution yet. So we are still on the way of researching this. Thank you for the idea. But wait,

it was not for me. I am. Yeah, I'm I'm do, Michael. Yes. Next up, we have john. Alexander, it's very nice to know, this opportunity to hear about your more recent work. Likewise, thank you for your email. Yeah, I've been hearing your 2020 review, anybody who listened, I think it's very important in the companies here, fill down the aging. So with that in mind, you know, I'm very, very interested to see your third point on what's next. Regarding elasticity, again, I think is very important, of course, um, and you mentioned, you're really expressing lawston. But I'm wondering what the limitation is that or if you're not removing the old damaged last. Right, so do you, you know, you could even help make things worse, potentially, if you don't remove the old last. And that's correct. And cumulant demonstrates? So yeah, we're, I mean, what are your thoughts on Jad? And and more broadly about this type of approach for other, um, you know, molecules macromolecules, then accumulated stochastic colon damage over time. Yep,

that's correct. But there are studies that are promising in the in. So there are some types of drugs that, that increase the expression of troppo ellisdon gene, and actually see liked, and, like, suck new mice, or rats that, that took these drugs, they have more elastico worked through all the time, and the last one was properly organized. So this gives us hope. That's simply a stimulate and the expression might work. But of course, we want to take it first on ourselves food, probably tried on some animals. Yeah, and of course, trapo elastin expression is not the only thing that might, might be needed to restore the elastin network. Because the lesson is complex protein comprised of several, like, one of the years like, the end, the main structure, the main framework of the lesson is, is made up February. So we might also need to overexpress this this protein Yeah, it's a it's a very, very difficult to say in advance how it will turn out but we will see I this this is the only thing that I can tell right now. And for that, of course, we need when it lots of experiments, support and other stuff. But if we want to do it, nobody will

know because I'm glad you're going to trial. And there's also the you know, the collagens that accumulate damage over time exactly get turned over because of that damage.

Yes, exactly. So the big thing become less like less susceptible to calendula as a citizen, I'm pointed out but at least that a like at least on the skin, in the skin, we can try to apply some interesting methods. So but let's I will keep it fun for a while. Maybe if we will succeed. I will tell the big Well,

we will have to have egg for several occasions. Next up, we have David tovo.

Thank you Alexander, for your fine presentation, I appreciate it. Um, so we have many individuals who tend to come from the engineering or biological engineering background, who are 35 or younger, such as yourself, or are working on bio hacking. But it seems to me that the the right, the correct population to do this would be those where it would be clear whether a thing is actually having an impact or not whatever the thing is, and so that the focus of biohacking would be better focused in the 65 to 70. year age, where it seems to me and I can't prove this, that you have remaining normal functionality. Whereas No offense to anyone on this call 80 to 90 might be a little bit too late for some elements of our complement of humanity, or bodies. Um, and so I don't know, in your research, how many I'm interested in? How many of you have your folks doing biohacking using your protocols are in the 65 and older age range? And are they actually experiencing reversal of functional limitations?

That's very good question. And of course, like, our sample, so the majority of our Velen volunteers, like the members of our group, are of age 55, to 60. So it's very close to that ranged invention, maybe there are they are a bit young. But there's also a good thing because they can withstand, like, more negative influence, or if they like, the intervention will go wrong. So maybe, to older persons is not also a good idea to try things on. Yeah, that's, that's correct, that the effect will be more apparent on older persons. And we should aim for that. Let's, let's see. So the more experimentation, the more like, interest in this topic. Like, the more it grows, the more people it attracts, and maybe we'll find someone who is a bit older and wants salsa to participate in this study.

Let's see. So my question though, orient itself around the demonstration of regression of troubles, and therefore functional improvement, have you seen Not, not not biometric improvement, but actual functional improvement, like strength, gait speed, cognition rates, and so on.

Yeah, that's true. They functional improvements, for instance, will be apparent. For instance, in our experiment with this enzyme called 15, PGD, ash, which should rejuvenate muscles, right, and we expect to see the increased like muscle mass. And this is a beautiful experiment in the way that we can demonstrate this, like make it apparent, because we can, for instance, inject the drug into one sail leg, one reserves, and the other leg will be intact, or will be injected with selling. And then we can see the difference between two legs. And we will do like bilateral exercises. So both legs will have the same load. And then we can see how how things progress with time. And this will be probably the example of what you've mentioned, like the actual physical improvement, but of course it might fail. And this is totally fine because we're doing like science and we're exploring things.

Right. Now we have to on the record question and then a few of the record questions. And we will start with Mika.

So, as a biohacker What are your feelings on like? How do you feel about sharing like all your not only results, but also your personal bio data, just with the public? And also kind of on that you think other bio hackers also share that sentiment? Whatever that is, or do you think there's a diversity And privacy amongst biohackers? Well,

I'm not that familiar with the by hacker community, like, in general. So I can probably see, like, the preface for your team affairs there. But in our team, I think it depends, some biomarkers are okay to publish some Probably not, I wouldn't publish my, for instance, genetic data, I can probably like, in the open access, but some, like some, you know, like vascular H, or some logic that goes, I regularly do posts on Facebook like sharing, sharing my current results, so they don't see any problem with that. But some data I would like to keep private, like genetic data. For the

arterial stiffness sensor, can you give more details on how that works? Or is there a place online that we can go and read about it? Or is it published anywhere?

No, it's not published. So what is how does it work? It basically to photo polities demographic sensors in two locations in to like finger on Nandi, hand and finger on and the toe, on their on their feet. And then basically, that's it. So no big deal measures the time that pulse that it took for a pulse wave to travel a certain distance, and then you basically calculate pulse width, there was a Delta on that. The same principle that medical devices work, but it's

portable. Great, thanks. Okay, great. Well, we will close the we came up close to recording good. What is the most impressive achievement environment that your group has covered?

Well, we have observed like production, hein, atheromatous, atherosclerotic block and some older people. What do we don't really know? Like, we don't believe we are like a bit skeptical about it, because we want to that's why I'm not I was not mentioned in the presentation, because we need more data like to confirm because it's like too optimistic finding. Right? So what we should we should re examine ated multiple times because before saying to public that this is like a stable, reproducible achievement. So we would like to

what we did up so far, that you if you can read it reiterate, what data do you have so far for the evidence for removal of fo recurrences,

well, ultrasound examinations of patients, like basically corrupted characters artery scans, like before intervention, couple of subsequent scans. So yeah, but of course, as someone pointed out correctly, we have to ensure that there were no like environmental factors that can influence the results or maybe instrumental errors or whatever else. Because this, we're what yet so we need some more evidence in favor of this.

Just one more thing. Did you guys get a baseline fluctuation? like did you test for, like fluctuation of artery health in a normal healthy person with no intervention? Sure, sure.

I've mentioned that in the presentation before so we measure markers in a longitudinal fashion, right to have a distribution of values throughout the time. So we have like a pretty clear picture how markers there I like to what extent they can, they can, like diverged from a mean value. And that allows us to judge whether change was expected or unexpected, right? So for instance, I measure my pulse fate velocity every day for me, basically.

Okay, now we're going to turn the record up again. recommend the final question. We always ask is how can this help you work and can help further you work?

Well, one certain thing that everyone can do is to spread their awareness about the, like, the overlooked Hallmark or maybe even cause of aging. This is like damage to matrix to the SEM. So that can definitely speed up the progress in that direction. And I don't know like, if someone is, is willing to support us financially work by other means. So you're aware welcome, we need your help. If you think you can help us something, please do not hesitate to reach us at W e at Emily group.net. So this is our email. So please, probably Allison could paste these email somewhere in the description.

Yeah. We will do so. All right now our thank you again very efficiently from everyone. It was an honor to have you in the closet fellow next year. Thank you so so much for joining and this won't be the last time that we speak. I hope you have a lovely rest of the day. And I see most of you on September's 14 when we discuss cryonics Alright everyone, have a great rest of your day. Bye bye. Thank you. Bye bye.