 Everybody, today we are debating creationist genetics and we are starting right now. Ladies and gentlemen, we are thrilled to have you here for another epic debate. This is going to be a lot of fun, folks. Sometimes, our best debates have been just spur of the moment. This one was spur of the moment where our guests were like, hey, we'd love to do this. And Erica is going to be here. I promise. It's not false advertising. She's going to be here. Relax. So Erica, also known as YouTube's favorite daughter, she took a wrong turn as she was driving on a road trip that sounds like something like that. So she's going to be here a bit late and we are pumped for it as she will be co-monning tonight. And these gentlemen, though, they were originally going to do it on Erica's channel. It was a pleasant surprise that Erica was like, hey, it'd be cool to do a moderated debate. We can co-mon. So I was like, oh, that'd be a blast. So this is going to be a lot of fun. Want to let you know, though, if it's your first time here, consider hitting that subscribe button as we have a lot more debates coming up. So for example, it will be evolution on trial this Sunday as Standing for Truth and John Maddox are going to be facing Team Skeptic and Fight the Flat Earth. That should be an epic one for your Sunday afternoon. Hopefully we'll see you there. And want to let you know, I have linked our speakers in the description below. So if you're listening and you're like, I like that, there's plenty more where that came from. You can hear it by clicking on those links that I put down there for you. We are also going to have for today a fairly flexible kind of format. It's basically going to be like this, 15 minutes opening from each side, then a three minute rebuttal from each side, and then open conversation. And we're trying something different. We usually have all of our question and answer at the end. We may have some kind of concentrated Q&A at the end, but we're also going to take during the discussion. So not during the speeches, but during the discussion portion. As super chats or questions roll in, we'll actually be asking those during the discussion. I'll look for times that I can kind of like sneak into the conversation and say, hey, speaking of, can I ask a quick question from the audience? So it'll be a little bit more kind of dynamic as we're going. We've never tried this before. It should be fun. And last, we are, I think that's it actually, okay. So excited to have you guys here. This is actually, I'm thrilled to have you guys. So I just want to say thanks so much, Sal and Dan, for being with us. It's a true joy to have you guys with us. Thank you. This is, it's really cool to be here. And thank you, Sal, for doing this on such short notice and working around schedules and everything. So yeah, really excited to be here and talk about genetics. It's, I think about it all the time anyway. So this is great. Dan, would you like to introduce yourself? Oh, yeah, sure. Thank you. My name is Dan Stern-Cardinel. I'm an evolutionary biologist and a biology professor. I'm actually teaching evolutionary biology right now, just like this over Zoom, like everybody else is doing. And I've been following the evolution and creationism debate since 2005, actually, and kind of a funny aside, I've been reading Sal's work since then. So it is really cool to actually talk to Sal face to face. Likewise. And thanks, James, Erica, Dan. I'm a, I'm Salvador Cordova. I'm a former scientist and engineer in the aerospace industry, but presently do research and news reporting in the area of molecular biophysics. I work directly for World Famous Supply Geneticist and retired Cornell professor, John Sanford. I've also been detailed to work for various labs and professors around the country. Some of my, some of my work focused on the beta lactamase, nylonase family of enzymes and the post translational modifications of the topoisomerase family of enzymes and cancer research. I presently am doing computational work in structural biology and writing and am writing a book, which Dr. Sanford commissioned me to write. I have five science degrees, including an MS in physics from Johns Hopkins University and an MS equivalent in biology from my professional work. In addition to classes I've taken at the FAS graduate school at the National Institute of Health, where I got to study under evolutionary biologists. I used to believe in evolution. I no longer do. I self identify as a creationist. You bet. Well, thanks very much, gentlemen. This is going to be a lot of fun. So really again, we appreciate you being here. And with that, if I understand right, Dan, if I remember right, you'll be going first. And so the floor is all yours. And let me know if you'd like to use screen share. I can pull it up for the audience. Yeah, I'm going to screen share here and this will be a 15 minute opening. I have a clock here, but if either of you want to also keep time. So let me just pull up screen share here. This James, I'm not finicky about time. If yeah, I mean, if it's like a little bit, I'm not I'm not going. I'm easy to get along with. All right. So let me this is I should stipulate. This is my first debate of this format. I want to make sure that James and Sal, you can see this. Everything looks you can see PowerPoint full screen crystal clear. Great. OK. Well, in that case, let's get to it. So the first thing we have to address here is what on earth are we talking about tonight? We are going to talk about a concept called genetic entropy, which was first proposed by Dr. John Sanford in the book, Genetic Entropy and the Mystery of the Genome in 2005. The basic concept here of this book is that mutations build up within a population, it is declines and ultimately extinction of that population results. Sanford explains it like this. When selection is unable to counter the loss of information due to mutation, a selection arises called error catastrophe. If not rapidly corrected, this situation leads to eventual death of the species extinction. And I should note here that I'm quoting from I'll be quoting throughout from the third edition of genetic entropy here, because there are a handful of additions. So the big idea here is that this concept is all about survival and reproduction. Sanford is making an argument by contradiction. If genetic entropy is real, then evolutionary theory is fatally flawed. And there's a second part to that that he's pretty clear about, which is that if evolutionary theory is fatally flawed, then special creation is a better explanation for the origins of humanity than evolution. No, I'm mostly going to ignore that second part tonight. I'm going to mention it very briefly in a little bit. But what I want to do here is treat this as a scientific hypothesis and engage with it on those grounds. Now, in that regard, we have to treat it on the terms that Dr. Sanford uses in the context of evolutionary fitness. Evolutionary fitness means reproductive success. And there are a bunch of other components that go into that. Dr. Sanford, for example, in the book talks a lot about information in the genome. I know Sal, you like to talk about things like structural biology. All of that stuff is upstream of whether or not a population is able to propagate itself from generation to generation, or if it's degenerating to the point where it will go extinct. So the real crux of this matter is evolutionary fitness as it is correctly defined by the field of evolutionary biology, reproductive success. This book is really well thought out and has a number of specific components. Sanford is very particular about this argument. His argument says that virtually all mutations are inherently harmful, that these harmful mutations must accumulate and this must occur over generations. So it's not that a population gets slammed all at once with a bunch of bad mutations and goes extinct. It's a gradual decline over a long period of time. This is a constant ongoing process. And in fact, Sanford is very clear about the inevitability of this process. He picked the word entropy very purposefully. He wrote, mutational entropy appears to be so strong within large genomes that selection cannot reverse it. This makes extinction of such genomes inevitable. I have termed this fundamental problem genetic entropy and the emphasis there is in the original text. So he's very clear about drawing an analogy between the inevitability of genetic entropy and the second law of thermodynamics. He does that on purpose. So now let's talk about why this idea is wrong. I'm going to go through this in terms of the main errors as they relate to how populations actually evolve as mutations occur. One point I want to emphasize here is I'm going to point out a number of shortcomings in this hypothesis. If any one of them on their own is valid, then that's enough to invalidate the theory of genetic entropy. So with that said, let's get into these problems. The first problem is that fitness effects are context dependent on what Sanford says. He says it can very reasonably be argued that random mutations are never good. He doesn't provide any data for this claim. Instead, he misuses a single figure from a 1979 paper by a population geneticist in Motocomura, who is one of the most important population geneticists of the 20th century. Comura's focus was on neutral evolution. So the data, the figure that Sanford used was actually the parameters for a model that Comura developed to model neutral changes, changes that are not subject to natural selection. As such, it didn't include any beneficial mutations, anything on the right side of this graph. Now, Sanford modified that and called it the correct distribution by adding this teensy little curve here for beneficial mutations. But again, that's not based on data. That's just Sanford adding a little bit in terms of what he feels would be appropriate. Now, Comura actually explained why he designed his model that way, and Sanford just ignored that explanation. Sanford wrote he, Comura, obviously considered beneficial mutations so rare as to be outside of consideration. But Comura wrote in the actual paper that Sanford got the model parameters from, he said, we disregard beneficial mutants. This is an oversimplification. But a model assuming that beneficial mutations also arise at a constant rate independent of environmental changes leads to unrealistic results. And he goes on to elaborate that according to his simplified model, which just allows for a constant clock-like accumulation of mutations, that works really well for neutral variation that can't be selected. But if you allow beneficial mutations into that, you get runaway selection for beneficial mutations, which is not what happens in nature because you have fitness peaks in nature. You have genotypes that are optimal for a particular environment. So what Comura is saying is, my model is overly simplified because beneficial mutations would do too much work if I included them. And Sanford said that the explanation was the opposite, that they were too few to matter. But it's pretty clear from data and plenty of examples that beneficial mutations exist and the context in which a mutation occurs often matters. So for example, if anybody who's watching is lactose intolerant, I bet you think that lactase persistence is a beneficial mutation, the ability to digest lactose throughout your life. Other mutations depend on the context. The sickle cell allele, if present in two copies in an individual, causes sickle cell disease, which is very severe. But if present in one copy, it confers some degree of resistance to malaria, which is obviously very beneficial in many parts of the world. You could even look at this within a single small genome. So this figure shows different mutations present in influenza. One mutation confers resistance to tamiflu, but it comes at a fitness cost relative to the susceptible strain. But if that resistance mutation is present in the presence of another mutation, that cost is recovered. So the genetic context matters. And one more example, because it's fun and it makes me feel good about conservation biology, is elephants and a trait called tuskless. Being tuskless as an elephant is not super beneficial under normal conditions. But if the main selective pressure operating on elephants is people hunting you for your tusks, then being tuskless is a major benefit. And we see that trait rapidly spreading through elephant populations. So requirement number one, fixed negative fitness effects, that is false. The second problem is that harmful mutations cannot accumulate constantly. Sanford writes, as we will see, given these numbers, there is no realistic method to halt genomic degeneration. Now, this is a math problem for Sanford, because what he's claiming is going to happen is mathematically impossible. And consider a simple scenario. You have a genome and a mutation from state A to state B occurs, and that is a harmful mutation. Well, that mutation is now off the table and it can't occur in the future. But the reverse mutation from state B back to state A can occur. And according to Sanford's own logic of fixed fitness effects, that B to A mutation is necessarily beneficial. So over time, if we apply this to many mutations within a genome, over time, as mutations occur, the genome is going to approach an equilibrium. So this is a simplified representation of these dynamics. On the y-axis, we have mutation frequency. And on the x-axis, we have just number of mutations. And the two lines, red and blue, represent the frequency of two classes of mutations. Deleterious meaning harmful, not that they delete anything, but they hurt evolutionary fitness. And then beneficial plus neutral together, so things that don't hurt fitness. And according to Sanford, every mutation that occurs, no matter how many mutations have already occurred, approximately 100% of mutations are going to be harmful. But according to math, as deleterious mutations occur, the frequency of potential future deleterious mutations goes down. And the probability of the reverse mutations, beneficial mutations, goes up until eventually you're going to reach an equilibrium point within a given genome. Again, I want to be very clear here. This is not a biology problem. This is not a genetics problem. This is a math problem with Sanford's claims. So requirement number two, that harmful mutations accumulate constantly. That is also false. The third problem is that according to Sanford, mutations must inevitably occur over generations. And he's very specific about this. He even puts a number to it and describes an approximately linear accumulation of mutations to the tune of three additional deleterious mutations per person per generation as a minimum for humans. And he's also very clear that selection is unable to remove these mutations. So you have a population that is just accumulating tons and tons of mutations. This means that variation is increasing within that population because not everybody is going to get the same set of random mutations at the exact same time. This means that in terms of fitness, some individuals are going to be less bad than other individuals. You can follow Sanford's model and you definitely get, you could definitely model out a fitness decline, but you cannot model an equal fitness decline within a population. There's going to be some individuals that are better and some individuals that are worse. So just like before, we could show what happens graphically here because what happens is a situation called mutation selection balance. Now, in this figure, mutations are on the y-axis, just number of mutations and generations across the x-axis. The dotted line represents a threshold where if you get too many mutations and cross that threshold, you're no longer viable, meaning you're either dead or you're not reproducing. So your alleles, your variants of your genes are not going to be present in subsequent generations. Now, according to Sanford, mutations are going to accumulate in a population. Everybody is going to have exactly equal fitness cost to those mutations. So when you catch that threshold, when you accumulate mutations to where you hit that threshold, you continue to accumulate mutations despite the fitness cost associated with them because everybody is exactly equally bad and no better state can be selected over any other. But what actually happens is that mutations that do not immediately result in death or the inability to reproduce, we can call them tolerable mutations, those mutations are going to accumulate. And as that occurs, variation within that population is going to increase. That's what the thicker line represents at this point. This is increased variation. Now, it's not just going to magically stop at that threshold. Some individuals are going to experience mutations that put them over the threshold into inviability. Those intolerable mutations are going to get selected out of the population. And the remaining population is going to be free to continue to reproduce and experience mutations. So you end up at a balancing point where the rate of new mutations entering the population is that dynamic equilibrium with the rate of mutations being selected out of the population. This is called mutation selection balance. And at that point, genetic entropy cannot happen. That population is at equilibrium. Now, that's all very theoretical, but you don't have to take my word for it. This has been directly observed experimentally. And my favorite example of this is a paper by Springman at all published in 2010 called Evolution at a High Imposed Mutation Rate, Adaptation Obscures the Load. In this experiment, they treated a bacteriophage of virus called T7 with a mutagen and saturated the genome. And that just means they caused every possible mutation to be present within that population. In fact, many times over, they have the mutational load as well documented in that study. So every mutation is present. Every individual is just slammed with at least a dozen mutations. Some of them have over 100. They then directly measured the fitness of those viruses in terms of their growth rate. Now, according to Sanford, because virtually every mutation has a negative effect on fitness and you can never select out those harmful mutations because they're accumulating inevitably generation over generation. This population should have gone extinct. There's no way for the population in this situation to survive in light of genetic entropy. But what happened was the average fitness declined while the maximum fitness of that population actually increased. Those viruses by experiencing so many mutations, they actually found new beneficial genotypes that were not initially present. So these findings are explained by the occurrence of beneficial mutations and the selecting out of harmful mutations. In other words, a mutation selection balance. And these findings, a saturated population continuing on and in fact improving their maximum fitness, that is a direct experimental refutation of the genetic entropy hypothesis. So requirement number three, no selection over generations. That is also false. There's one more problem here. It's that genetic entropy is an example of the begging the question fallacy. That's when you sneak the conclusion of your argument into the premise of your argument. And John Sanford does this by assuming an optimal genome as the starting point. Evolution doesn't work that way. Evolutionary theory doesn't involve some perfect mutation free genome. But there is something else that starts that way that involves a perfect genome. Special creation involves a perfect starting state followed by degeneration. By framing his argument in terms of a perfect genome that subsequently degenerates, Sanford assumes his desired conclusion from the start. So it's no wonder he arrives at that conclusion by the end of his argument. But evolutionary theory doesn't work that way. And this alone is enough to invalidate his argument even if we put aside the science that I've just discussed. So I don't come up on my time here. I'll wrap this up in just a minute. So there is theory that we can talk about here, but we can also talk about observed evidence. Genetic entropy has never been observed. There is a well-known paper that Sanford co-authored with Dr. Rob Carter in 2012 looking at H1N1. And this paper is often used to claim that H1N1 experienced error catastrophe, but there are major flaws with that paper. And I hope we get to talk about that paper in some detail later on. There was also a review of the scientific literature in 2006 examining the theory of error catastrophe. Remember that term from Sanford earlier? And the authors in 2006 found that to that point, there had been no experimental demonstrations of this process. And I can tell you from my own work that since then there have still been no experimental demonstrations. We could also look at direct refutations. So we have experimental examples like the Springman paper I talked about earlier. And we have natural populations that if Sanford is right, should have gone extinct by now. Things like mice and HIV, but obviously they're not. And those are also direct refutations. So to summarize, genetic entropy is population extinction due to mutation accumulation and loss of fitness over generations. This is a flawed hypothesis because it begs the question. It assumes the conclusion from the start. But it's also flawed because fitness effects are context dependent. Harmful mutations cannot accumulate indefinitely within a population. And populations with variation experience selection and achieve a mutation selection balance. Plus we have direct observations, experimental and natural, that directly refute the genetic entropy hypothesis. So you put all that stuff together and this is an idea that has no support. It is a hypothesis without merit. So there's a whole lot of other things I hope we get to tonight. Things like the H1N1 paper, the idea of information in biology or structural biology, we'll probably talk about in code. So we probably won't get to all these topics, but these are just some of the things that I hope we get to. So thank you. And with that, I will turn the floor over to Sal. You bet. Thanks very much. Appreciate that. Can definitely tell that you've got speaking experience too, by the way. So do I remember right? Is it you teach at the high school level or college level? College level. Gotcha. College level. I teach my full-time gig is teaching the introductory biology class. So I get about 1,000 students a semester. Oh, that's right. OK, thanks that it's very clear that you do have that speaking experience. And we will kick it over. Thanks so much, Sal. Thank you. I appreciate that. Oh, absolutely. My pleasure. And Sal, we'll kick it over to you. And same thing. We'll have a flexible 15 minutes. And as mentioned, folks, we're doing something new tonight where as they have their open discussion, which will be after the rebuttals, so they will have three-minute rebuttals after the openings. But during the open discussion, we will kind of weave the superchat questions or comments into that open discussion section. So with that, Sal, the floor is all yours. Thanks as well for being here. Oh, I think let me check if you're on mute on Zoom really quick. Oh, that's right. Sorry about that. Thank you, Dan. And this is kind of one of the strangest debates where I actually hope that I'm wrong. And I'll explain why. The website, this website is under construction. And I hope to post... Is that showing right? I think I have a little problem there. I think you'll have to go back to share. Okay, I'll go back to share. Thanks, everyone, for bearing with me. And I'll go back to share. I'd like to thank the audience for bearing with my clumsiness. You're good. So this is probably one of the strange debates where I'm actually hoping my opponent is right for reasons that I'll explain. I'm hoping that he has really overturned the genetic entropy hypothesis. I'll briefly say that genetic entropy in terms of viruses, he defined a lot of it in terms of viruses, but that's not really the focus of Dr. Sanford's book. That's kind of more a peripheral issue, even though Dr. Sanford did talk about viruses. On some level, I wish my hypothesis tonight were wrong because it does not bode well for the human race, if I'm right. It would mean the human genome is deteriorating and suffering genetic entropy. Material tonight will be drawn from the writings of Ivy Lee creationists, a research professor at Cornell, and a PhD scientist trained at Harvard and MIT, and their picture there. The book Genetic Entropy was written by retired Cornell research professor John Sanford. He invented the gene gun, a sizable fraction of all genetically engineered organisms were through his patented gene gun process, which was used to feed starving billions. His invention is in the collection of the Smithsonian National Museum of American History. In 2017, Professor of Mathematics Emeritus, Bill Beister and John Sanford published an article on the Fundamental Theorem of Natural Selection. The article set a record for the number of downloads of any article in the journal's history, and is related to the hypothesis of genetic entropy. Those are some of the prints from there, from the paper, that's a section from it. As a result, in 2018, July, Bill Beister was keynote speaker at this international biology conference, and later in October, John Sanford was invited to the National Institutes of Health to give a presentation on genetic entropy. Respected science, here is a sample of respected scientists who are concerned that the human genome is deteriorating, starting with Nobel Prize winner Herman Mueller. And these are some of the references to their work. We don't have time to go into it right now. So I ask the rhetorical question, are there any respected scientists who think the human genome is improving naturally? I'm not aware of any personally. So how do I define genetic entropy? Genetic entropy claims that the human race is deteriorating genetically. In other words, we're getting sicker and dumber with each generation. Each generation on average will be a little less medically fit as the previous generation. There will be more heritable diseases and birth defects with each generation. The genetic entropy hypothesis has roots in the work of Nobel Prize winner Herman Mueller, who studied the effects of mutation on the human genome. This is before Watson Crick and the DNA Molecular Biology Revolution in 1953, which unwittingly justified Mueller's earlier concerns for the human genome. In Mueller's 1950 paper entitled Our Load of Mutations, Mueller put forward what I call the Mueller limit. It is the number of mutations per individual, per generation, that the human genome can tolerate, otherwise it'll start deteriorating. And that number, that limit is roughly 1.0 mutations per generation per individual. That Mueller limit was used by Susumu Ono to formulate what he called the junk, what has been known as the junk DNA hypothesis. That hypothesis says that 97% of the human genome is junk. But that was under the assumption that DNA's sole purpose was to code for proteins. It turns out DNA has multi-purposes. Ono's view has been shattered by developments at the NIH, such as the 4D Nucleome Project, which was a follow-on to the ENCODE project, which was a follow-on to the human genome project. It says, what they have discovered is DNA is not just a blueprint for proteins. It serves as a three-dimensional scaffold for molecular machines over time. DNA also serves as designated parking spaces for these molecular machines. To illustrate this, I'll show the human karyotype of the chromosomes here. And on chromosome 12 resides this DNA, the codes for what is called the hot air link RNA. And that is kind of the spelling of part of that link RNA, the hot air RNA. So from chromosome 12 emerges from transcription, the hot air link RNA, and it travels by the winds of Brownian motion to chromosome 2. How it gets there is an amazing problem in biophysics. So DNA actually serves as kind of a parking lot for the hot air link RNA. Once it gets there to chromosome 2, it somehow finds the Hawks cluster and assembles this complex here called the Polycomb Repression Complex 2. And here's the hot air link RNA that came from chromosome 12. These wires here are the DNA and they wrap around these little histones here. Histones are memory units. They're like little memory units of random access memory. So this complex will find the right histone on the right Hawks cluster. It'll find histone 3 and it's going to modify amino acid 27. This is a very precise process. So what does this result in? Well, that modification causes differences in the cells of the skin on the eyelid versus the feet. So all this computation, when you see how your organs are differentiating all your parts, there's all this computation going on in the DNA with machines like this. This is showing why ONO was wrong to think the prevailing view that DNA's main role is the code for proteins. It does a lot of computation and regulation. Furthermore, multiple genes can pull together molecular machines and chemicals in the process of DNA transcription and regulation. So these genes will come together and share molecular machines. This is really amazing and where the NIH is studying this is in the 4D nuclear project where we have multiple chromosomes like one section of chromosome 2, chromosome 15, chromosome 17, and chromosome X. They come together and co-regulate each other. This is induced by the fire link RNA, which resides on chromosome X. So we could see here, like what I said, is that the DNA is acting like scaffolds and parking spaces for these molecular machines. It is not solely dedicated to coding for proteins. And this is where it begins to increase the function. The problem is, so let me back up a little bit. So let me back up a little bit. DNA is part of a mind-boggling, intricate, four-dimensional, terrain-complete, chromatin-based, computational system, now the subject of the 4D nuclear project at the NIH, which is the follow-on of the ENCODE project. But as a result, the percentage of DNA that may be functional is far more than what Ono thought. But if this is the case, this would mean the human genome is already in violation of Mueller's limit and is headed toward destruction. So in addition to that, there's the E4 epitranscriptone project, which will probably find other uses for what we have called junk DNA. When they become RNA transcripts, they're involved in some really incredible things. It may even implement neural networks. It's just incredible. I just don't have time to go into it today. These developments, as we found more function in the genome, disturbed certain evolutionary biologists like this gentleman here, Dan Grower, the parent of the 4D nuclear project, ENCODE, speculated that most of the human genome is functional. And he said, he got really angry. He said, if ENCODE is right, evolution is wrong. The 4D nuclear project, which I just highlighted, is the successor to ENCODE, and it suggests that ENCODE is right. Therefore, evolution is wrong. So going back briefly to the Mueller limit of 1.0, and I'm going to cover this a little bit, it can be derived from a variety of mathematical methods. One is provided by Kamura in his 1966 paper with Maruyama, and it uses the Poisson distribution. We won't get no need to get into those details, but you'll see symbols like U or E to the U or E to the minus U. That was actually in Dr. Sanford's presentation at the NIH, and I'll highlight it there. You see it there. The reason I know that, I'm the one who go to dim into presenting this slide, and I wrote that part of the slide for him. Other biologists have used that, Iyer Walker and Keatley at E to the minus U. So I'm not going to give a formal proof of Mueller's limit in terms of the Poisson distribution, but most mutations, 99% of more are function compromising. There are a variety of literature on that. But to kind of give an idea of why, I'm going to go by the example of the potassium ion channel and the idea of spelling proteins. So this is a potassium ion channel. It has to fit perfectly as ions, has to be shaped perfectly in size perfectly so that it can pass specifically this potassium ion here. So this is the channel here, and the way it's constructed is it has to be spelled right. So that's how shapes and sizes are made in the molecular world. We can't do any milling. It has to be by spelling. And one analogy I'd like to say is that, you see how this nut fits the bolt? We can't change the size of the bolt very much, either making it larger or smaller without destroying the fit. It has pretty much, you can't improve, it already has a perfect fit. And that's a theme I'll echo more. And that justifies this distribution that Dan showed earlier on how most mutations are damaging, or maybe hopefully neutral at best. Maybe there's an improvement, which is very doubtful in certain cases. And that's why I love that picture of structural biology. Now, the dictionary of correct spellings in the English language, we have correct spellings by convention, but in biology, the correct spelling is according to physics and connectivity and performance considerations. Connectivity spelling is like nuts and bolts fitting together, like this one here. More difficult is performance spelling, is making systems that achieve certain performance characteristics like the optical ability of an eye to focus light according to optimal principles of geometric optics, or a bird to navigate thousands of miles according to magnetic principles. This is highlighted in William Bileck's book, Biophysics, and also his memorial lecture at Cornell, the Hans Beta Memorial Lecture. So there are far, far more ways to misspell than to spell, especially for proteins. So just to illustrate this with the English language, I have the ingredients list for tiramisu and one for a McDonald's bacon quarter double pounder with cheese. So can I evolve it by a mutation in selection? So I'll just take the ingredients list here, and we'll just call that the parent. And the parent will have children that are almost identical copies of it, except the children will have at least one mutation. I chose one because that's movers limit. Natural selection cannot remove these mutations. You'll see why. So we'll just pick one of the children. We'll say that that's the most fit. It's really like picking the best of the worst. And anyway, we'll just repeat the process. And the children inherit the mutations from the parent, and plus they get mutations of their own. And that's why if the process were to carry out, we just get a mess. And that was to illustrate intuitively movers limit without going all into the deep math. Now there is subtleties where movers limit can be bypassed based on Poisson distributions, namely females have to have more kids. So this is a table of that. Notice that each increase of just one mutation, more than triples the number of offspring needed per female to save the human race, not a lot of room for errors. And this resulted in something a little bit comical at John Sanford's talk at the NIH. He, Dan Grower was very angry at the end code because if end code were right, that would mean each female needs to bear 10 to the 35th offspring per mom. But Dr. Sanford pointed out, even if we use Dan Grower's own figures for mutation rates in humans, females would need to give 44,000 offspring. So this leads to the discussion of fitness. In the wake of their 2017 paper, which I consider very successful, I got recruited to work on Fischer's fundamental theorem of natural selection. And in the process, we began to see, we began to highlight problems with the definition of fitness. I'm hoping to post some of these things on my website that's still under construction. So God willing, in a few weeks, you'll get to see some of this. I'll talk about Fischer's fundamental theorem of natural selection. And some of these two papers that are very important, one by Lewington, the other by Grodd Wall. So this is the movie Dumb and Dumber. And this is Lloyd Christmas here, played, performed by Jim Carrey. I'm going to use him as an example of Dumb. In the evolutionary sense, fitness is defined by differential reproductive success. So if hypothetically someone like Einstein, had a bunch of dumb descendants like that, he would, these descendants would be considered evolutionary, evolutionarily fit. Even though in the common sense definition, this is devolution. You know, going from Einstein to Lloyd Christmas is a decrease in fitness, is devolution. That's in the medical engineering and common sense notion of fitness. And this is actually the argument that probably precipitated this debate. Dan was very curious, my counterpart, about this statement. So fitness increase in the medical engineering and common sense idea is more like, you know, Dumb going to very intelligent. Now, so there's confusion factors in the way fitness is defined. The engineering definition is not the same as the evolutionary definition. The medical definition is not the same as the evolutionary definition. That causes problems. So there may be devolution. And here is one of the papers. It says losses in general intelligence due to both selection and mutation. So selection is an agent of the destruction of our intellect. And that's it for now. And I'm sure we'll have plenty to talk about. And I'd like to thank Dan for showing interest in discussing this. Awesome. Well, folks excited to go into the rebuttal. So Dan will have three minutes for his rebuttal and we'll give some flexibility for that too if they need a little bit more or less. Totally okay. And then we'll do the same for Sal where he'll have a three minute rebuttal. Then we'll go into the open discussion. Also want to let you know, if you notice, folks, the studio, if the studio lights up red, it's not a red alert. I promise it's okay. It's basically if a super chat comes through, the studio lights up red. If a new subscriber comes through, the studio will light up green. So that's why you do see the flashes in my background sometimes. So with that excited, and we will kick it over to Dan. Thanks so much. Oh, I think you're still, let's see it. Let me check. It was me. Thank you. Yeah. Thank you for that Sal. Excellent. So I just have a couple of quick things I want to respond to. And the first thing is something we agree on that this is like, the way cells work is super complicated. This is like, it is not simple the way things like gene regulation works or anything like that. The way chromatin is structured in the nucleus and how different things get trafficked to different places in the cell. That stuff is, we agree that stuff is exceptionally complicated. And it also seems like we're not disagreeing super a lot on the genetics as I presented them. It seems like the problem where we're not agreeing on the outcome is not that the processes I described don't operate that way, but that the kind of the precision required for in particular the human genome is such that you don't get a chance to have things like natural selection operating. That everything is so tightly constrained that you don't have the flexibility to do that stuff. And I want to make sure I'm not straw manning your argument. So is that, am I understanding you correctly that the disagreement seems to be on things like the percentage of the genome that's functional and the degree to which changes in like non-coding DNA, non-translated, but transcribed RNAs, that kind of stuff is selected for a particular function within a cell and is very tightly constrained in terms of things like its structure and its sequence. I want to make sure I'm not misrepresenting your argument. Is that approximately right? We could probably talk about that. And I mean, I'm not trying to cut you off. I actually had to think about what you're trying to, how you're trying to characterize my arguments. And I think you're trying very hard to be fair and try to represent me accurately. So that's not a problem. And you could obviously tell that both of us focus on the idea from totally different angles. So that may be part of the problem. So I think we're not as far apart on the angles as it might seem from our respective intros. So for example, let's look at, let's look at encode for example because this is a place where we definitely disagree in terms of the percent functionality of the human genome because that has major implications here. If the genome is like 90% functional, then yeah, we definitely have a problem. But I just don't think there's any reasonable way to draw that conclusion based on the evidence. And we can look at that right here. Just very briefly here. Let's pull this up. Here we go. Those are going to full screen that. Now, the encode project for anyone who doesn't know was a survey of functionality within the human genome. I, Sal, you probably know better than me. The year it was originally, the original publication went out, the one that had like 100 authors on it. But this was a big survey of biochemical activity in the human genome, not function. And it was largely mis-recorded that it supported the conclusion that the genome was 80% functional. But it actually didn't do that at all because biochemical activity is rampant in the genome, but most of that stuff doesn't actually do anything. They've since revised the way they present their findings by breaking it up by biochemical activity into protein coding and non-coding regions. And the genetic evidence, whether it generates a phenotype or has been conserved to evolutionary history, there's a bunch of other stuff outside of those realms that is sometimes considered functional. But I don't think there's good evidence for that. So for example, if something is disease associated, that's not sufficient to call it functional because you could have a gain of function, GOF, that's a gain of function in a non-functional region that causes it to do something it shouldn't be doing. In like, for example, a transposable element that is supposed to be inactivated, but it reactivates, that could cause a problem, but that doesn't mean that region is functional. But this really comes down to, oh, that got all messed up. Look at that anyway. I don't know if you could see this. Can you see the PowerPoint slide there? Cool. So this is the correct format for this slide. This is what the genome is made of and we can quibble over what's functional and what isn't, but I think we would all agree that these are the components of the human genome. We've got about 44% are just dead transposable elements, things like retro transposons, another 8% are dead viruses called endogenous retroviruses, and then there's about 1% are pseudo genes. These are genes that are inactivated. Those are all degenerated. So like, you don't have a full transposon, you have like a little remnants of it. We can confidently say about 11% of the genome is functional, but almost 60% is certainly not. And then you could quibble about kind of the in-between range. But I think it's simpler to just look at this and say, okay, we're experiencing genetic entropy. Where is the cost of that in human reproductive output? Because again, this all has to come down to human reproductive output. If a population is going to go extinct, it could be because of structural constraints. It could be because of inactivated proteins due to mutations. But at the end of the day, reproductive output is going to fall off. And for species that's experiencing genetic entropy, I just don't see it in humans. I think that's a good place to stop for now. All right. I'll throw out this rhetorical question. If only 10% of the human genome of 3.3 gigabases is functional, that would imply if we take two bits for each nucleotide position and then eight bits for a byte, that would imply 80 megabytes is functional. Do we think 80 megabytes is enough to code something as complex as a human being? So that's more of a rhetorical, intuitive argument. People in computer science and engineers would think that's just too low to be able to even make something as complex as a human brain. I personally believe there is a lot of information outside of the DNA that's heritable and the glycone, but that's another story. I would disagree that the ERVs, the ALUs, had been demonstrated to be functionless. We know that in some of the transposable elements, they contain the CTCF binding motif, which ends up creating these loops that I was showing pictures of. And then the ERVs are also places where that act, if I could show, I'm gonna show a screen here. Maybe I could, I'm hoping maybe I could show this. See, do I have it? No. I don't have it immediately. Handy. But I could show where, when I showed earlier the polycomb repression complex docking on the hox cluster, there are similar complexes like the cap one complex that will dock on the ERVs. We actually don't know. They say that that suppresses it from transposing. That may not actually be just the only function. It may be doing, recruiting a lot of machines to do chromatin modifications. And we know that that's important in embryonic development. And who knows what else? There are trillion, there are 100 trillion cells and 100 trillion epigenomes with different chromatin states. We would have to test all of those to see if the ERVs have any role, same for the signs, signs and other transposons. Those transposons are very important to be able to create these CTCF binding motifs that create loops. They're almost like braces in a programming language. So you have to have a left brace in a statement and then 200 base pairs down, you have a right brace and that will form the loop. That seems to imply very careful design because as I was showing those transcription factories and those topologically associated domains, they can't be willy-nilly links and be able to co-regulate transchromosomaly. So I'm sorry, I'm throwing a lot of technical terms here, but this is where it's at if we're gonna debate at this level about the functionality of DNA. So with that, I'm open to taking a little break and taking audience questions. And I'd really like to thank Dan. You had a very strong opening and you gave me a lot of food for thought that I have to study. And I may not have a response to some of what you said today. And not that I'll have one anytime soon either because I think since your specialty is virology, what you conveyed is very much worthy of study. On the other hand, I thought I also made some pretty good points. And as I said earlier, there's a part of me that really hopes I'm wrong because this doesn't look good for humanity if I'm right. Thank you. Yeah, this is great so far. This is super fun. And it's great to hear from your arguments just directly. If I may, I'd love to just address this structural argument because this is really seems to be like a centerpiece of your argument here that we have these structural constraints that are so tight. One example you showed that I really like is the ion channel and it has to be exactly the right width so that a potassium ion can go through it, but a calcium ion can't. And if the long ion goes through, it just messes with nervous system and muscles and everything breaks. If I can just for just a minute, I want to hone in on this because it's absolutely true that there are very tight structural constraints but I'm going to go back to PowerPoint here. And I'm not going to full screen it. I'm just going to pull it up like this. But at the end of the day, the structural biology I think is a side. It's a distraction from the question of fitness but let's treat it like it's the critical thing. The linchpin of the whole argument is about structure. It doesn't support genetic entropy even if that was the case because sometimes we want structures that are super strong associations. So this right here, this triple helix, that's a collagen fiber. Collagen fibers are in our connective tissues are under our skin. And they basically hold everything in your body together. We don't want collagen fibers to be connected all really nearly. We want them to be really strong robust connections. And any mutations to those fibers that decrease the robustness of those connections is a big problem. Like connective tissue disorders are really bad. But there are lots of examples where a strong robust connection like that is also really bad. So for example, hydrogen bonds in the DNA, the double helix, the opposing strands fit together very precisely. But those H bonds that hold the A's and T's and C's and G's together, those are very easy to break and reform. And if you were having to separate them basically with like covalent bonds, for example, DNA replication just wouldn't work. It would be too costly. You could also look at my favorite example over here, hemoglobin. Hemoglobin, I think we would agree. And so you might, I don't want to put words in your mouth but I think you'd agree that the hemoglobin monomers are very well designed for their job of carrying oxygen throughout the body. But hemoglobin has a very low affinity for oxygen. That's why it works. It's not a pocket that perfectly fits the O2. It's a little sideways in there. And the result of that is that the O2 molecule can get in and get out really easily based on the gradients in the surrounding tissue. We know what happens when hemoglobin binds to things too robustly. That's carbon monoxide poisoning because carbon monoxide fits in that pocket perfectly and it doesn't let go. And then you can no longer carry oxygen. There's tons of examples like that through the body. Things like phosphorylation where you want to activate and then deactivate a protein or neurotransmitter reuptake at a synapse. Leaky ion channels where you want a slow leak of potassium out of the cell instead of a rush. Even the ribosomes, the way the large and small ribosomal subunits come together is relatively low affinity. So my point here is that the structural components are also context-dependent like the genetic components where there are situations where it's beneficial to have a very strong robust connection and you're going to be selected for that in that context. But there are other situations where a much looser connection is actually the optimal state and we see selection for that in a wide range of functions across lots of cells. Do you want to take that? Do you want to see what questions we can get through? Or do you want to respond by all means? Go ahead. I'd like to respond. I actually did have a picture of the... Let me see if I could pull it. First off, when I said it has to fit, I did... I was being very simplistic in saying it has to fit in a geometric sense. So thank you for that correction. What I meant is it has to be fit in the sense of even you use the correct word, optimal, optimal. The affinity has to be correct. The specificity has to be correct. Deviations from that are bad. I mean, that's exactly why I think... I think it's easy to see why variations will result in bad. That's why I like the structural biology argument. Now, one thing I'll point out, maybe a center piece of our disagreement is the definition of fitness. I also had a... See, I'm going to try to pull it up here and I have so many slides, Dan, that it's going to take me well to page through it. I don't know if you have the same problem as I have. I'm going to have for you. Okay, I'm going to show you that... I finally found that one of the ERVs and I have more with the signs. So, but let me just show this one here. I don't know if this one's showing... Is this showing the polycomb, honeycomb or is it showing the cap one? Cap one. Okay, so we were talking about ERVs. Crab, sink, finger, protein, which is also another protein I study. They often will dock on the endogenous retrovirus and they'll recruit a complex like this that will do all these chromatin modifications. Most of the literature will say that that's just suppressing the transposition of the ERV, but we really don't know. We really don't know. Any time we're modifying the chromatin here and for the audience's sake, these wires here, that's the DNA and it's wrapping around the histones. So there's a complex machine that is associated with ERV. I think the responsible thing to do is to say we don't know. It's a little premature to say it's junk. We've been... Some of the declarations of junk, like say for the transposons for ALUZE, has been just totally, I think pretty much eviscerated. It's too early to say that it's just junk and non-functional. So this whole thing about chromatin, and I was talking about the chromatin computation, it's mind-boggling that's involved in cell regulation and cell your differentiation. I think we underestimate the importance of that. So at the very least, it's too... It is really way too premature to say this is junk. And as I said, I don't know that I would feel comfortable saying that the human genome can be coated with only 80 megabytes and that's all our complexity. That just, to me, that just seems like too much a pill to swallow. Now, I wanted to show something here with the signs or transposons. DNA forms these regulatory loops and these create little parking lots for the molecular machines. So to create these loops, we have to have certain motifs. And these motifs are called CTCF binding motifs. And they have to be spelled one way on one part of the DNA and they have to be spelled backwards on the other part of the DNA and they have to match each other and it forms the loop of the right size. And where did these things reside? They reside on what we've been calling junk DNA, the transposons. So the reason I like this, if you see those regulatory loops, I'm going to show another picture, see if I could find it. And I apologize to the readers. This was from another presentation I had, but I just thought these had really cool pictures. So in a factory assembly line, you have these machines, these arms, and then you have the tools attached to the arms and it reaches in. But this looks a lot like, so I was talking about these loops. So you see these loops form, they have to be the right size and they have to position these molecular machines to service the gene. It does some sort of computation that tells us how much of something to make and that's really important. So we could see that the amount of spacer DNA, you can cut a little bit of it and it might still work. A little too much, it's just going to compromise the function. So how much is too much or too little? We know repetitive elements like the D4Z4 repeat. Humans have on average, say about 100 of this repeat. If we go down to about 11 repeats in an individual, they'll get muscular dystrophy. So there seems to be an optimal point and I'm glad you used the word optimal. I'm not saying an S to be, you know, that there's no give, but one direction or the other is not good. So I hope Erica's here. She's not here yet? Oh, bummer. She's not here yet. She said she'd be maybe an hour late, but it could be longer. So hopefully we have Erica joining us tonight. She is driving through the woods of western Virginia. Very embarrassing. I'm just kidding. I think she's fine. But one thing I was going to ask is, are we in the rebuttals still or have we jumped into open conversation? Yeah, this is just back and forth now. Okay, cool. When you're ready, I can ask maybe one or two super chats, but it doesn't have to be, if you guys are wanting it to be later, that's okay too. What do you think, Sal? I could use a break. I'd like to hear what the audience says. Yeah, sure. Bring them in. I think we probably pummeled them. With too much technical, too much geek speak. We need a little bit of relief here. Well, I am stoked to get into these super chats. Thanks for your questions, folks. And with that, A-A-A-A-A-A, many, many A's says, James, there is a ghost behind you. Careful, bro. If you're talking about Echo, I have a cat that sometimes wanders around here at the place I'm at. And she's terrific, but you'd love her. Jesus, let's see. Won't wear condoms. I'm confused, but by your username, but I appreciate your super sticker of two doves or one dove giving a thumbs up. Steven Steen, thanks for your super chat. Says, James's DNA sequence is alpha daddy. Thank you very much, Steven. Nasty guy, but we love him. Steven Steen also said, that's what she said. Did I tell you he's nasty? He's our local friendly troll. And stupid whore energy has entered the building. She's on the prowl. She says, what does the shape of ions and their channels have to do with genetic entropy? I'd be happy to take that one. That shows the precision of the parts have to be the right size and the right shape. And Dan used the word affinity. There's a point where something is just shaped just right. To be optimal to do the job. So when there are changes to our genome, this will change things like that ion channel. And if it shuts down, you're dead. So what I was trying to convey is that most changes, just like spelling, if you misspell a word, it's really especially a really long word. It's easy to misspell it. And the same is true in the spelling of proteins. The spelling of the protein makes things like that's how the ion channel will actually form. So I was trying to convey how the mutations will generally be bad. It's very hard to achieve something that's beneficial for something that's already working pretty much close to perfect. So if I can comment on that, is that okay? You bet. As long as I'll go over the original super chat was originally targeting, if they get the last word before we go into the open discussion. Gotcha. Okay, so the ion channel example, that's a protein. That's something that is within a protein coding region of DNA. So if you change the nucleotides in there, you potentially change the structure. And to change the structure, it might be better, it might be worse. Most of those, we know just from surveys of things, you can look at, you could do mutation accumulation experiments, and most of those changes don't have a detectable fitness effect. But then the thing where we're having a disagreement here is about the rest of the genome, the genome that's not protein coding. Now a lot of that is still going to be functional. There's a lot of stuff that's regulatory, like promoters, enhancers, silencers. These are things that turn on and off genes. There's even structural components, like telomeres and centromeres. These are parts of the chromosome that fold up in a very particular structure. There's even like spacer regions that need to be a certain length, but the sequence doesn't matter. As long as you have the right size, it's good, and all that stuff is very much constrained. But you add all that stuff up, it only gets you to about 11% of the genome, and the rest of it, we know what it is. It's, as Sal said, there's things called lines and signs. These are repeats from transposable elements. There's the viruses, the dead viruses. They're called endogenous retroviruses, if you want the long word for them. And those two things combined are like 55-ish percent of the genome, and we know what most of them are. And Sal, if you remind it, could you go back to that picture with the cap that binds to the region and the DNA? Because I think that actually illustrates the point of making here that those things are largely non-functional. Because that cap, I was going to talk while you're pulling it up, that cap is a protein. That's a part of your protein-coding DNA, which is only about 1.5% of your genome, 1.5% to 2% somewhere in there. And so that's a protein. We know that's functional. We have genes for that. What it does in that figure is it is doing two things. It's promoting methylation and deacetylation. And without going into the biochemistry of it, those things shut down a region of DNA and cause it to coil up very densely so it doesn't take up space. And what that indicates is that it's going into a form called heterochromatin. And heterochromatin is like the box of junk you pack into your basement as densely as you can without really regarding what's in it. You just need to get all this stuff out of the way and stick it in a corner. It's the DNA that's not doing anything. So we could say, okay, there's an affinity between the protein and that endogenous retrovirus sequence. But I think the function there is in the protein in terms of its affinity for that sequence. It's not the specificity of that box in the bottom left corner that matters there. It's the red and the blue proteins that matter that are providing the function. And what they're doing by methylating and deacetylating that region is shutting it down so it doesn't interfere with anything else. That's definitely an important function that those proteins are doing. But it indicates that that local region of DNA is non-functional and your cells just need to get it out of the way. Now, it's certainly true that mutations to that region can cause problems. But that doesn't mean it's functional. That means it should be doing one thing, sitting in a corner in a box. And if it's all spilled all over your basement floor, then you're going to trip over it and that's not good. So I don't think arguments like this that endogenous retroviruses have protein binding affinity that leads to biochemical changes in DNA. I don't think those on their base are strong arguments for the functionality of those regions. I think the specifics of those interactions matter. For example, if it was acetylation and demethylation, then it would be doing the opposite thing. Then it would be opening up that DNA so other enzymes and things could get in there. And then I'd be wondering what it's doing. But if it's being methylated, it's not doing anything. It's just being coiled up super tightly and thrown in a corner. So that, I think, is the answer to that argument that there's functions and there's activity. But those regions of DNA, like endogenous retroviruses, are not the functional components of that interaction. Over to you. Sorry, I need a way to say, like, that's the end. We'll give the last word down and then we had three new superchats that flew in in the meantime. And then there are topics I want to make sure we get to, things like the H1N1 paper, generating new information. I don't want to leave that stuff on the cutting room floor if we can. So I want to make sure we do get to those topics. Oh, I think you're muted yet, Sal. Let me unmute you. I can't unmute you on my side. Oh, OK. Am I unmuted? Yes. Thanks, moderator. You bet. Hi. I think that's something Dan and I are just going to disagree with. And I think the more that we discover, it's going to be important that things form into heterochromatin to be able to enable cellular differentiation. And there are other things that need, that that cat1 complex can be, might be doing. So I found that if we just wait around a few years, we're going to find things. And let's say even that the human genome is 10% functional. That's still too much functionality. It's still, it would still create a mutational load that's beyond muter's limit. And I think that's what we're facing. So we can argue about this, but it's still moot because 11% is still too much. So I think rather than boring the readers on this topic, we can say, OK, we disagree. And maybe more research in the future might be able to establish it one way or the other. And my intuition on this is again, just rhetorically, I said that 80 megabytes doesn't seem like enough to code a human being. And so I think that three-dimensional structure of DNA creates a lot, is a repository of more information. And so this stuff is very necessary as it changes the three-dimensional structure of the chromatin for regulation. So maybe it's not worth arguing because we're not going to settle it today. And I think we're going to permanently disagree and it's not worth the shouting match. So maybe we could take, would it be all right if we took some questions? Yeah, let's take another couple of questions. Then I really do want to make sure we cover information because Sanford really hammers that in the book as generating and maintaining information. So I don't want to leave that one on the floor. I want to make sure we get to that. OK, that'll be our next one after that. And then I want to talk about fitness after that, if that's OK. Absolutely. All right, so you'll get two shots and I'll get one. In the meantime, we'll take some super chats. You got it. Thanks for your super chat. Coming in fresh from General Balsak. Thanks for your super chat. Says, for Sal, where is the point that genetic entropy went over the line that, quote, de-evolution occurred? Was it right off the bat or was there a point in human history that it occurred? From the scientific standpoint, I think that is really hard to establish. What we do know is that the cranial capacity of human beings seems to have reduced just by the size of their brains. They're bones, so we have some archaeological evidence of this. The bones have lost bone density. It's been attributed to lack of exercise, but it could also be genetic. So the average person is probably way smarter than they are today. The average person way back was smarter and stronger, had healthier bones. So maybe I'm going to back up a little bit. How do we know that we're deteriorating? We're in a position we might find out. And as I said, there's no major geneticist that thinks we're improving. So maybe I'm going to pose that question to Dan. Does he think, in the medical sense, that we're improving? So I'm sorry that I don't have a scientific answer. Of course, I have my own personal belief, which is theological, and I used to believe in evolution. When I began to think that life was miraculously created, I began to accept Genesis literally. So to the viewer's question, I think that point happened when Adam and Eve fell. But that's something that's probably outside of science that we cannot directly establish. That is just my own personal belief. How we could do that scientifically, I don't know how we might be able to establish that. Dr. Sanford, Dr. Carter are working on that with mitochondrial DNA. So we might be able to work back some of the clocks, how far back it was. So I do think we did start off from a very good state, and we've been deteriorating since. And so if Dan doesn't want to take that question right now, I'm going to just put that later, because I actually did mean to ask him what he thought if he thinks the... I appreciate you asking. I just a quick note that does boil down, though, to an argument from authority that it's this group of famous geneticists, these well-regarded geneticists, say that we're in decline. Or, depending on your perspective, the Bible implies that we're in decline. And Sanford in the book, actually, I think there's a figure of ages going back to Noah and how the ages drop off over time, right? So whether it's using the Bible or just like all of these famous 20th century geneticists, it boils down to an argument from authority. But what we really need to see is the evidence in the genome. And I agree that right now humans are doing a better job of surviving in the face of genetic conditions compared to not just millennia or centuries ago, but 20 years ago. There's conditions that are survivable now that we're not in the 1990s and the 1950s, right? There's we've gotten better at dealing with this stuff. And that's a good thing. That is absolutely good. I don't think you can jump from that to say like the human gene pool is degenerating because we have these deleterious alleles in the population. A lot of the work that's been done in terms of allowing people affected by these various genetic conditions to live much more typical lives compared to decades ago also involves allowing them to have kids where in the past they wouldn't be able to. And a lot of that involves genetic testing that involves testing their offspring for those conditions so that they're not propagating those conditions to their offspring. So I think I can see what you're saying in terms of their more conditions are survivable now than were in the past. But I don't think you can jump from that to the conclusion that therefore the human genome due to modern medicine is in some kind of decline. I don't think that's a reasonable conclusion. And I think you need more than geneticists saying so I think there needs to be actual evidence in the genome in terms of like harmful alleles that are building up that we can document. And I don't think that evidence is there. I think the evidence is there and it's growing. I've talked to epidemiologists and there is there is concern for the rise of irritable diseases. And we're having a hard time ejecting things like juvenile diabetes for some of the reasons you mentioned but there are more and more of these rare diseases popping up. And we're not we're not able to clean it out. Natural selection has never cleaned out juvenile diabetes. It's kind of struck me that we see juvenile diabetes in all sorts of mammals. Why has selection not been strong enough to remove it? So rather than maybe arguing over that I appreciate you responding to my query and this is something we can study and talk about later. But I do have a follow up question and then I'll absolutely give you the last word but I do have a follow up question because the idea with genetic entropy is we're constantly bombarded with new mutations. And it's certainly true that genetic conditions that we've known of for a long time are are present and persisting in the human population. But as we've been being affected by genetic entropy I'm presuming that Dr. Sanford thinks it's an it's a continuous ongoing process in humans currently. And with 7 billion people we've experienced every possible mutation many times over in the human population. So with and just so everyone knows the math on that is approximately 100 new mutations per person per generation at 3 billion base pair bases base pairs in the human genome and 7 billion people we've got we've sampled all of the the single base mutations. So given that and given that this is the first time in human history that we've had a population this large there should be a lot of new genetic disorders that are popping up that we've never seen before. And that doesn't seem to be the case. There's certainly things like juvenile diabetes you know type on diabetes or sickle cell disease any number of genetic conditions. But what are the new conditions that genetic entropy predicts would be popping up in the human population? I don't think there are any that I could there aren't any that I can think of that are brand new in the last you know say 50 years or so of explosive post-World War II population growth. I'll give you the last word on that one. Oh thank you and if there's something I said that's objective objectionable we can revisit it again. And because I would like to get to our listeners who've patiently suffered through our geek speak nerd sit in. I think the figure you cited of the human genome sampling all mutations I would have to say that those are only single point mutations of the sort. We've not there's no way we could have sampled all the possible combinations. Dr. Brenda yeah Dr. Brenda Andrews did a lot of research with yeast because it's hard to do this research with humans on single and double knockout experiments. So there's a lot of things that are not expressed as deterioration until you have double knockouts because genomes are very very robust. So I think the argument that you put forward that we sampled all the mutations I I don't think that accurately reflects the possibility where we're you know we may have sampled all single mutations but we not anywhere sampled like combinations of two three four five six all the way up to hundreds or thousands and that's that would be significant. So but as I said I really do hope that things are not as grim as it may seem but there is a reason Dr. Sanford was invited to the NIH despite the fact he became a creationist. There are people there that are concerned about terrible diseases and the feedback we got is some of the people there that had a lot of sympathizers that said you know we need to be we need to recognize this we we think this is happening we have to deal with it. So if there's anything objectionable I said to that and you want to talk about it more we can say that. I'd like to go to the listeners for the next one. I also forgot a super chat so we'll jump into Nico blast super chat thanks for your patience Nico and Erica will hopefully be here I it sounded like she was hoping it would be an hour it might not it's possible it wouldn't be at all sorry folks but I promise her punishment will be swift and severe okay so uh no she's she's doing okay though she did send me a DM on Twitter and let me know that it's she's making her way but it's just kind of taking longer than expected but we will go to Nico blast super chat we appreciate it Nico and Nico asks what is the rate of entropy and when will all humans go extinct you should be able to predict these if what you claim is true the rate of entropy uh could I take that one Dan uh yeah go for it the uh the the word entropy in the colloquial sense not not the uh physics or engineering sense of uh the rate of entropy is determined by the mutation rate which we're arguing about so far some will say one mutation per individual per generation others are citing figures of closer to 80 to 100 until we have those figures it's going to be a little hard to make a prediction but what we can say is if we have mutation rates of a few hundred um we may not necessarily go extinct anytime soon but we're going to lose capability and we see that in the uh emergence of more and more birth defects so what is the prediction the prediction is and I cited the paper by uh one researcher who said our IQ levels are going to be going down with each generation by a certain fractional number of points uh at least if we extrapolate the figures we've had before so what are some of the things that are not working so optimally uh our eyesight we have lots of allergies so there's any number of things we we can put metrics on and we may expect that these things will increase we know that now we don't know how much the environment is affecting uh and it's kind of hard to factor that out we don't know why there's um so much autism going on could it be the environment the the chemicals or the food we don't know how much of that is tied to genetics but uh we do know that that um uh there are a lot of health concerns so i'm sorry i can't give you an exact figure but this is this is uh a concern one time when i was at the ENCO 2015 users conference uh one of the researchers there an epidemiologist uh was talking to me and she said what are you doing here and i said well you know i work for john sanford he thinks the human genome has an intolerable mutational load and that we're getting sicker and she she gave me this funny look she said you know what i i'm finding that in my research too we're finding a um she said i'm an epidemiologist i study cancer we're seeing an increase in the rise of juvenile juvenile cancer onset and it's it's it's really fast it's very disconcerting we don't know why so i've not heard i mean honestly i've not heard a single researcher that i've encountered it's that's saying we're improving that we're going to be smarter we're going to be stronger we're going to be healthier i've not met a single one and i i wish that were the case but i'm sensing that's just not the case that's that's why we're not hearing that may i ask a question yeah so if so this is an inevitable process um sanford's really clear on that that this is uh uh you know he specifically says large genomes but then he has the h1n1 paper so it's kind of ambiguous where that threshold is um so i'm just going to ask you um do you do you agree with sanford that that h1n1 is experiencing slash did experience uh genetic entropy in the 20th century like i the reason i'm asking is this is you know it's supposed to be an inevitable process and maybe human lifespans are too long to be able to see you know the the bending in that curve but there are things that are short-lived that should be susceptible um so like what's an example is h1n1 an example of that i i neither disagree or agree meaning um that's that's not something that i've studied um i actually cautioned john i said you know i think this is uh i mean you may be right but i don't think we have quite the strength of the argument that we do for i mean a virus is a virus it's not as complex as you carry out by any stretch of the imagination i said we our strongest case is with the human genome and that's the one that's the most well studied so um the thing with viruses they're they're parasites they can mutate a lot and uh you know the host will replicate them it's not quite the same thing with humans uh so i'm i'm sorry i'm not able to answer your question i think you raised some really good interesting things about h1n1 uh you also mentioned air catastrophe i talked to a population geneticist who's one of the tops in the world and i said what do you think about air catastrophe his name's joe felsenstein this is just kind of informal on the net and uh he said oh i think there are three definitions and they're not all in agreement i said great um it is definitely a crime that is misused very often is air catastrophe is a very specific definition and sanford actually gets it right sanford actually has the right definition that it's mutation accumulation over generations leading to extinction he actually so i don't so i don't think where i was headed with that i don't think viruses are a good model for uh for what will happen to humans just because they are parasites and they're not anywhere near as complex they can tolerate a tremendous amount of damage if we did that to the human genome we'd be dead so let's look at that actually let's look at that for a second um let's look at viruses versus humans here so uh i'm just going to share a slide here but not full screen it because that gets messy um we can look at factors that make you more likely to be susceptible to genetic entropy the g or air catastrophe depending on what word you want to use um you're going to be more susceptible if you have a dense genome which means you have a high percentage of sequence constrained uh nucleotides uh if you're haploid because you don't have redundancy and you talked about how in humans maybe we're missing a bunch of things because we're diploid and you need to have two defective copies okay um you need to have little or no homologous recombination because recombination gets around a lot of the problems that sanford identifies and just in general little or no redundancy functionally and we know that the human genome has a lot of redundancy so who's more likely to experience genetic entropy plus you layer on top of that mutation rates who's more likely to go extinct for mutation accumulation is it viruses with their very small very constrained very dense haploid genomes or is it humans or other mammals with our enormous genomes with lots of space between our genes and regulatory regions and I'm going to say again a lot of stuff that is whether we whether we disagree or not whether it's structurally constrained but we should be able to agree that it's not um sequence constrained there was a study just recently and I have it here I think let me find it in here uh that found that it was only eight ish percent yeah it was eight between eight and 15 percent of the genome is sequence constrained now for viruses that number is approaching 90 percent in many cases so viruses should be like the poster child for something that's going to experience genetic entropy but they don't uh which is weird um and I'll leave the h1n1 thing on the table for now but I do then we can talk about other eukaryotes because mice uh should be in the same boat as humans we have approximately the same mutation rate in terms of mutations per site per replication and mice should have a greater substitution rate which means they should have a greater accumulation of mutations over time and substitution rate is changes per site per year now they have a much shorter generation time than humans about 10 weeks versus 20 years but their substitution rate it's in the same order of magnitude but it's actually a little bit lower than humans according to a 2019 paper now that doesn't make any sense in the context of genetic entropy because they should be going extinct they should be suffering this cost faster than humans because they're accumulating they're experiencing mutations at a much faster rate due to their accelerated generation time compared to humans but just like in humans we can't find evidence of this in mice mice are obviously just chugging along just fine so we could throw viruses aside and say well they don't count I disagree oh my camera just died they uh I disagree that viruses don't count but if we want to talk about eukaryotes fine we could talk about other mammals and we have the same problem one sec I hate to interrupt guys so sorry about that um and pardon me I was trying to I was trying to stop your screen share Dan but I accidentally turned your camera off but I want to quick say well I am so sorry you guys I lost track of time is that I'm a I'm in a challenging spot where I can only host for about an hour and a half and we're we're sneaking up on that and so I know that you guys probably didn't expect that we would be thrilled to have you on for a second time because the audience has definitely enjoyed this we what we might need to do and I hate doing this guys but I just I I really have to and it's just because of my circumstances where I am sure is that what we should probably do is try to fly through these last few questions and then I would be honored to have you guys back for real and we could do it where we have at least two hours and I as I know an hour and a half is kind of a quick one so I if that's okay with you guys I can read through these and if we you if we're able to do like short and quicky and uh quick pithy answers yeah lightning round let's do it thanks for your patience guys and thanks for your super chat from she strikes again stupid horror energy asks if you find transposons in the same place in the genome it points to common descent because of all the places they could have jumped to some of them get co-opted to perform some function so what I think that's for you sal if those transposons have function to begin with then it's it probably means that they were created if one accepts creation the problem with just invoking random transposons moving especially certain kinds like the aloe elements it could be very could be pretty deadly we know a lot of diseases are associated with that so I I reject the idea that they can just uh willy-nilly go around the place and as I pointed out the transposons uh host the gene regulation it's very hard to do regulation uh and and be misregulating a system and then evolving it to be better so the idea of co-option probably is not going to work gotcha and just just if I may just a quick answer that that we have direct examples of co-option I mean there's a gene called syncyton that is required for placental development that mammals stole from a retro virus it's a case of horizontal gene transfer it's basically a stealth mode gene for your immune system and it facilitates embryo implantation it it prevents an inflammatory response to the uterus so we don't have to like hypothesize about whether or not that can happen we've got like concrete samples of that I want to give it a chance for Sal and then I hate to say it but we've got to go to the last question yeah I'm I'm afraid that's circular reasoning uh but thanks thanks for that point next up appreciate and I promise I know you've got another round in the chamber ready to go Dan I promise we would love to have you guys on next time and a lot of people in the chat are like you totally have to have these guys on again Cigar Frito Sarabi thanks for your super chat said Sal does DNA carry a template or info to create or does DNA pick up the info along the way when and how did the info get there if not by evolutionary processes spoken maybe or question mark I think definitely had to be created there um earlier my slide showed uh some of these Ivy League creationists like Change Tan and Rob Stadler they argue very effectively that a lot of the DNA had to be right there especially I mean there's no way we can evolve a bacteria to a eukaryote with all the transmembrane proteins and the translocan reformatting the creature would die that's why I don't believe in evolutionary theory the intermediate stages would just be too lethal it can't evolve there a lot has to be a lot of people think things that can evolve naturally and and just because we may see fossil sequences but if we look at the biochemistry it's very very very prohibitive even in simple things we might think like the microtubules and what looks like gene duplication if you didn't have the paralogs there the creatures be dead so I think it has to be there from the start that's evidence to me is of intelligent design and special creation that may be too big appeal for some people to swallow gotcha and with that I do have as I mentioned I think this is the last one I saw some new super chats come in but folks I promise we will host these exact same guys exact same topic we will read the other super chats beyond this last one that I'm about to read next time so I will save them no joke if you're really triggered by that idea just email me at moderatedbate.com at gmail.com I'll give you a I'll use Venmo or PayPal to give you a refund but Dave Gard thanks for your super chat for this the last one of the night said for both please discuss apoptosis apoptosis yeah thanks for that or control cell death in the context of genetic entropy micro level stuff here not a not at a population level so is this um the way I would interpret that is kind of how would that evolve and be maintained as a trait because the idea there is that within uh an organism right you have each of your cells has all of your DNA but very few of them are actually going to transmit that DNA to the next generation so it's it's an interesting evolutionary question of how do you evolve the trait of killing yourself as a cell which necessarily means you're not propagating the DNA that you contain that's a really interesting evolutionary question I think that the I really think that um dog and selfish gene idea gets at this and there's a there's a more there's a less scientific word that I really like that gets at this and the word is co-optition and that's how you could think of like multi-cellular organisms how all of your cells they're cooperating with each other but they're also competing with each other and alleles variants of genes that are going to promote cells dying under specific specific circumstances can be selected for and propagated and maintains in a population if on net the expression of those alleles facilitates the reproduction of the individual in which those program cell death cells exist and so I think that's a really good example of something that would seem to be a very difficult challenge for evolutionary theory it turns out if you just reduce it down to the gene level and just do the math and we don't have time right now to get into kin selection and and you know that kind of stuff but that's a whole that's like we could spend two hours just on that but you can get into the math and figure out that it is under certain conditions those types of alleles would actually be beneficial and that's how they'd be maintained over generations without you know cheaters or something exploiting the multi-cellular organism gotcha if you're willing to let me give Dan the last word on that cell just because I promise yes go ahead and have you guys back that's fine I want to say last of all thanks folks for being with us tonight the biggest thanks of all to our speakers as we really appreciate these guys this honestly people have really responded they've really enjoyed you guys so please do if you'd be willing to come back sometime the next week we'll do kind of the the last half of this debate and we'll do like at least an at least an hour and a half we'll shoot for two hours and we'll do we'll do no intros and we'll just we'll just go right into it oh that's fine with me Dan I thank you very much for being my counterpart in this discussion and thank you for suggesting that we meet and thanks James absolutely thanks Erica we got all this free advertising I think more people can because they she was she was scheduled to show up so we'll get her we'll get her here next time as well so it'll be the full house and but yeah definitely want to say folks if you've enjoyed listening to these speakers their links I have put in the description for you folks so you have a chance right now to click on those links and here are plenty more where that came from and last of all thanks so much new subscribers saw you pop up on the screen kango24 eye on anti-whiteism the faithless logician and npx Todd thanks for subbing excited to have you here as a part of the community so with that we'll be back tomorrow with two debates it's a busy busy week so should be a lot of fun and keep sifting out the reasonable from the unreasonable everybody and one last thanks to our guests as we really appreciated these guys thanks for being here guys thanks for having us thank you thank you thank you for hosting it was great yes thanks dan thanks james you bet take care folks see you to hopefully tomorrow