1 00:00:03,000 --> 00:00:05,880 Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff 2 00:00:05,880 --> 00:00:14,320 Speaker 1: Works dot com. Hey you welcome to Stuff to Blow 3 00:00:14,400 --> 00:00:17,240 Speaker 1: your Mind. My name is Robert Lamb and I'm Joe McCormick, 4 00:00:17,280 --> 00:00:19,960 Speaker 1: and we're back for part two of our discussion about 5 00:00:20,000 --> 00:00:23,239 Speaker 1: where's my eternal youth? Why can't I be young and 6 00:00:23,280 --> 00:00:27,040 Speaker 1: beautiful forever? Why do we age? I know that's the 7 00:00:27,120 --> 00:00:29,800 Speaker 1: It's the question we've always wondered. It shows up in 8 00:00:29,800 --> 00:00:35,840 Speaker 1: our philosophical writings, it shows up in our religion, our mythology. Uh. 9 00:00:36,120 --> 00:00:39,280 Speaker 1: In researching this topic, I kept thinking back to Genesis 10 00:00:39,320 --> 00:00:42,320 Speaker 1: six three. This is the King James version, and the 11 00:00:42,400 --> 00:00:45,479 Speaker 1: Lord said, my spirit shall not always strive with man, 12 00:00:45,960 --> 00:00:49,680 Speaker 1: for that he is also flesh. Yet his days shall 13 00:00:49,760 --> 00:00:54,520 Speaker 1: be a hundred and twenty years. So there's God putting 14 00:00:55,000 --> 00:00:58,800 Speaker 1: a limit on how old a human can become and 15 00:00:58,880 --> 00:01:02,480 Speaker 1: saying like, here's the aging process. Uh, these are the rules. 16 00:01:02,640 --> 00:01:05,640 Speaker 1: Obviously doesn't apply to Highlanders, that's right. Well, you know, 17 00:01:06,200 --> 00:01:08,200 Speaker 1: maybe they're they're part of the giants in the earth 18 00:01:08,319 --> 00:01:10,039 Speaker 1: or something. I don't know, Oh that could be. Yeah, 19 00:01:10,040 --> 00:01:13,440 Speaker 1: I guess they're not humans. So well, the spoiler for 20 00:01:13,520 --> 00:01:18,039 Speaker 1: Highlander too certain cuts they are not from Earth in 21 00:01:18,080 --> 00:01:20,840 Speaker 1: the good cuts. They're not from Earth yet again, we're 22 00:01:20,840 --> 00:01:23,720 Speaker 1: just trying to throw those seeds down. Highlander two episode 23 00:01:23,760 --> 00:01:26,640 Speaker 1: it's coming now. Speaking of parts one and two, this 24 00:01:26,720 --> 00:01:29,319 Speaker 1: episode is a part two. Yeah, so if you haven't 25 00:01:29,360 --> 00:01:31,039 Speaker 1: listened to part one yet, you should go back check 26 00:01:31,080 --> 00:01:34,280 Speaker 1: that out first. And that we explored the question of 27 00:01:34,360 --> 00:01:37,760 Speaker 1: why we age. We look at some animals that don't 28 00:01:37,800 --> 00:01:40,360 Speaker 1: really age in the same way that humans and other 29 00:01:40,400 --> 00:01:45,600 Speaker 1: similar mammals do, and we look at historical explanations people 30 00:01:45,640 --> 00:01:48,320 Speaker 1: have tried to come up with for why we age, 31 00:01:48,680 --> 00:01:51,200 Speaker 1: and we also explored some reasons to think that those 32 00:01:51,240 --> 00:01:54,120 Speaker 1: historical explanations were not correct. Today, we're going to try 33 00:01:54,120 --> 00:01:59,560 Speaker 1: to get into the modern evolutionary synthesis take on why 34 00:01:59,720 --> 00:02:02,440 Speaker 1: we age. What's happening and how do you solve this 35 00:02:02,560 --> 00:02:06,680 Speaker 1: paradox of the fact that aging is a decline over 36 00:02:06,760 --> 00:02:11,600 Speaker 1: time in our survival and reproduction fitness, and yet evolution 37 00:02:11,639 --> 00:02:15,840 Speaker 1: should be constantly optimizing our survival and reproduction fitness. Why 38 00:02:15,840 --> 00:02:18,400 Speaker 1: would it allow us to go into this period where 39 00:02:18,440 --> 00:02:21,520 Speaker 1: we tend to die and tend to get worse at 40 00:02:21,520 --> 00:02:25,320 Speaker 1: surviving and tend to not be able to reproduce anymore. Indeed, 41 00:02:25,360 --> 00:02:29,240 Speaker 1: because I certainly don't want to deify natural selection and 42 00:02:29,280 --> 00:02:34,200 Speaker 1: say that like natural selection produces perfect forms or ideal forms. 43 00:02:34,240 --> 00:02:36,840 Speaker 1: But look at the forms that natural selection has produced, 44 00:02:37,040 --> 00:02:41,640 Speaker 1: look at all the various engineering problems that that that 45 00:02:41,720 --> 00:02:44,600 Speaker 1: evolution has managed to solve. Why would there be this 46 00:02:44,880 --> 00:02:48,560 Speaker 1: be this huge, at least from our perspective, flaw in 47 00:02:48,600 --> 00:02:51,200 Speaker 1: the design. Yeah. Now, of course, today, as we often 48 00:02:51,200 --> 00:02:54,079 Speaker 1: do with evolution, just for the ease of communication, we're 49 00:02:54,080 --> 00:02:56,320 Speaker 1: going to be using a lot of metaphors that offer 50 00:02:56,360 --> 00:02:59,960 Speaker 1: a kind of like embodied view of evolution, as if 51 00:03:00,080 --> 00:03:02,760 Speaker 1: like it's making choices. What we, of course know is 52 00:03:02,800 --> 00:03:07,280 Speaker 1: that evolution is a is an optimization algorithm. It's not 53 00:03:07,360 --> 00:03:09,680 Speaker 1: a person, it's not a thing. It doesn't really have 54 00:03:09,840 --> 00:03:12,560 Speaker 1: desires of it of its own. It has a way 55 00:03:12,600 --> 00:03:15,240 Speaker 1: that it works, and the way that it works is 56 00:03:15,280 --> 00:03:19,919 Speaker 1: to optimize the success of genes that survived natural selection 57 00:03:19,960 --> 00:03:22,800 Speaker 1: and reproduce. Now, one of the answers we explored in 58 00:03:22,840 --> 00:03:26,640 Speaker 1: the last episode is one of the most common things 59 00:03:26,639 --> 00:03:28,560 Speaker 1: people are going to turn to when they're trying to 60 00:03:28,600 --> 00:03:31,320 Speaker 1: explain why we age. It's the thing that my brain 61 00:03:31,400 --> 00:03:35,000 Speaker 1: and immediately went to before I read anything on this subject, 62 00:03:35,480 --> 00:03:39,040 Speaker 1: I started to think, well, let's see, if everybody just 63 00:03:39,200 --> 00:03:44,800 Speaker 1: lived forever and nobody naturally aged out and died, then 64 00:03:44,920 --> 00:03:48,280 Speaker 1: you'd have way too much competition for resources, right, You'd 65 00:03:48,320 --> 00:03:51,200 Speaker 1: have way too many people trying to live on the 66 00:03:51,240 --> 00:03:53,600 Speaker 1: same landscape. You'd have too many people trying to eat 67 00:03:53,680 --> 00:03:57,160 Speaker 1: from the same food sources. You'd have overpopulation, and and 68 00:03:57,200 --> 00:04:00,120 Speaker 1: everybody would suffer for it. Overpopulation ties and to a 69 00:04:00,200 --> 00:04:02,880 Speaker 1: number of our different dystopian views of the future, as 70 00:04:03,040 --> 00:04:07,120 Speaker 1: does the possibility of immortality becoming an option at least 71 00:04:07,120 --> 00:04:09,840 Speaker 1: a certain privileged people in society. You know, you get 72 00:04:09,880 --> 00:04:14,960 Speaker 1: this sort of trope of the awful uh Methuselah of 73 00:04:15,000 --> 00:04:19,880 Speaker 1: the future, Right, some just dreary, old, greedy individual who 74 00:04:20,080 --> 00:04:23,159 Speaker 1: will not die and let go the reigns of life 75 00:04:23,440 --> 00:04:25,720 Speaker 1: so that others may grasp it. Right, Well, as much 76 00:04:25,760 --> 00:04:28,360 Speaker 1: as we don't personally want to grow old and die, 77 00:04:28,680 --> 00:04:31,520 Speaker 1: you can sort of recognize from an impartial standpoint, if 78 00:04:31,520 --> 00:04:34,080 Speaker 1: you just consider it in other people, that it seems 79 00:04:34,120 --> 00:04:37,640 Speaker 1: kind of unfair that people should live forever, right, Yeah, yeah, 80 00:04:37,720 --> 00:04:41,040 Speaker 1: unless it's me or someone that I'm investing, and there 81 00:04:41,160 --> 00:04:43,520 Speaker 1: they should put a limit on that stuff. Yeah, So 82 00:04:43,640 --> 00:04:46,960 Speaker 1: but these types of answers, while true, it is true 83 00:04:47,040 --> 00:04:49,840 Speaker 1: that it's good for the species that we should age 84 00:04:49,839 --> 00:04:53,559 Speaker 1: and die, and that it's good for future generations. Uh, 85 00:04:53,760 --> 00:04:56,320 Speaker 1: good of the species and good of the group based 86 00:04:56,360 --> 00:05:00,800 Speaker 1: explanations come under a lot of fire from evolutionary biologists. 87 00:05:01,400 --> 00:05:05,000 Speaker 1: There's some biologists to endorse kind of qualified versions of 88 00:05:05,000 --> 00:05:07,080 Speaker 1: of good of the group and good of the species 89 00:05:07,440 --> 00:05:10,400 Speaker 1: type explanations, but there I think many more who don't. 90 00:05:10,839 --> 00:05:13,400 Speaker 1: And here's an example to illustrate one of the big 91 00:05:13,480 --> 00:05:17,279 Speaker 1: problems in why these good of the group explanations failed 92 00:05:17,320 --> 00:05:20,479 Speaker 1: to hold up. Alright, hit me with it. Okay. Let's 93 00:05:20,480 --> 00:05:23,640 Speaker 1: imagine a pack of alien space wolves. Okay, and for 94 00:05:23,720 --> 00:05:27,119 Speaker 1: our Warhammer for fans out there, he's not talking about 95 00:05:27,120 --> 00:05:29,280 Speaker 1: space marines here. Wait, I don't know what space will 96 00:05:29,680 --> 00:05:31,720 Speaker 1: Is that a thing? Yeah, it's a faction of the 97 00:05:31,760 --> 00:05:36,160 Speaker 1: space marines in the Warhammer forty K universe that are wolves. 98 00:05:36,520 --> 00:05:39,479 Speaker 1: Well no, they well they wear wolf skins and they're 99 00:05:39,920 --> 00:05:43,280 Speaker 1: you know, genetically enhanced super soldiers. Okay, So it would 100 00:05:43,320 --> 00:05:46,800 Speaker 1: really complicate them the analogy you're making here, if if 101 00:05:46,839 --> 00:05:49,000 Speaker 1: we were to draw them into the discussion. Well, I 102 00:05:49,040 --> 00:05:51,280 Speaker 1: was just trying to make clear that this is a hypothetical, 103 00:05:51,440 --> 00:05:54,080 Speaker 1: not like real wolves on Earth. Okay, so alien space 104 00:05:54,120 --> 00:05:57,719 Speaker 1: wolves living on an asteroid somewhere in hunting space here. Now, 105 00:05:57,800 --> 00:06:00,920 Speaker 1: let's imagine this pack of alien space wolves has evolved 106 00:06:00,960 --> 00:06:03,599 Speaker 1: genes that cause them to grow old and become infertile 107 00:06:03,680 --> 00:06:06,320 Speaker 1: after about ten years of age, after which you know 108 00:06:06,360 --> 00:06:09,760 Speaker 1: they usually die within a couple of years. And let's 109 00:06:09,760 --> 00:06:13,000 Speaker 1: say that each female space wolf has an average of 110 00:06:13,120 --> 00:06:17,160 Speaker 1: one space wolf pup every year that she remains fertile. 111 00:06:17,600 --> 00:06:20,800 Speaker 1: So unless the space wolf is killed by injury or 112 00:06:20,920 --> 00:06:25,440 Speaker 1: disease or a marauding space explorer, um, the average space 113 00:06:25,480 --> 00:06:30,560 Speaker 1: wolf female has tin offspring in her life lifespan. Everybody's happy, right, 114 00:06:30,600 --> 00:06:32,720 Speaker 1: because they don't eat too many of the space dear, 115 00:06:32,760 --> 00:06:36,400 Speaker 1: they don't become overpopulated. It just works out pretty well. 116 00:06:36,920 --> 00:06:41,200 Speaker 1: But then suddenly one of these space wolves acquires a 117 00:06:41,279 --> 00:06:44,719 Speaker 1: mutation that allows her to stay fertile and survive for 118 00:06:44,839 --> 00:06:49,599 Speaker 1: twelve years instead of ten, So she has twelve of 119 00:06:49,720 --> 00:06:52,800 Speaker 1: space wolf pups, whereas all the other females in the 120 00:06:52,839 --> 00:06:56,080 Speaker 1: pack are still having ten, and half of her pups 121 00:06:56,120 --> 00:07:00,200 Speaker 1: carried this extended fertility and longevity gene, So those x 122 00:07:00,240 --> 00:07:03,919 Speaker 1: pups each have twelve pups, while non carriers of the 123 00:07:03,960 --> 00:07:06,480 Speaker 1: gene only have ten, and so on and so on 124 00:07:06,600 --> 00:07:11,000 Speaker 1: down the generations, and eventually this cheater gene for extended 125 00:07:11,080 --> 00:07:15,120 Speaker 1: life and extended fertility is going to proliferate, even if 126 00:07:15,160 --> 00:07:18,120 Speaker 1: it might be worse off for everybody in the long run. 127 00:07:18,200 --> 00:07:21,760 Speaker 1: Even if the long living, long reproducing animals have too 128 00:07:21,760 --> 00:07:25,600 Speaker 1: many offspring and consume too many resources and suffer die outs, 129 00:07:25,640 --> 00:07:30,200 Speaker 1: this won't really cause a reselection towards shorter lifespans, because 130 00:07:30,560 --> 00:07:33,960 Speaker 1: how would it. Instead, what it would do is optimize 131 00:07:34,000 --> 00:07:37,040 Speaker 1: for whatever genes are possessed by the survivors of those 132 00:07:37,120 --> 00:07:39,840 Speaker 1: die outs, and that would probably be like those that 133 00:07:40,040 --> 00:07:43,920 Speaker 1: store fat better, or hunt better, or can extract nutrition 134 00:07:44,000 --> 00:07:46,760 Speaker 1: from space moss in addition to meat. And this is 135 00:07:46,760 --> 00:07:49,600 Speaker 1: a really common type of argument against good of the 136 00:07:49,640 --> 00:07:52,960 Speaker 1: group and good of the species explanations and evolution, because 137 00:07:53,080 --> 00:07:57,600 Speaker 1: any mutation that cheats on the stasis you've created for 138 00:07:57,640 --> 00:07:59,880 Speaker 1: the good of the group will tend to start to 139 00:08:00,000 --> 00:08:03,400 Speaker 1: at an edge and then have more offspring than those 140 00:08:03,440 --> 00:08:06,560 Speaker 1: who don't cheat, and eventually that new gene will become 141 00:08:06,600 --> 00:08:08,600 Speaker 1: the norm. Right, Yeah, It's kind of like if you 142 00:08:08,680 --> 00:08:12,119 Speaker 1: have a you know, an academic environment where everybody's cheating 143 00:08:12,120 --> 00:08:15,240 Speaker 1: on the exam. Need the grading becomes that much harder 144 00:08:15,280 --> 00:08:18,840 Speaker 1: each and every time. It's true. Yeah, it's great. So 145 00:08:18,920 --> 00:08:21,280 Speaker 1: it's like you got a grade on a curve because 146 00:08:21,280 --> 00:08:25,680 Speaker 1: everybody's cheating, so everybody's grade goes down. Um. Yeah, And 147 00:08:25,760 --> 00:08:28,800 Speaker 1: so I just want to remind you, though, this doesn't 148 00:08:28,840 --> 00:08:31,000 Speaker 1: mean that there is not such a thing as the 149 00:08:31,040 --> 00:08:32,640 Speaker 1: good of the group and the good of the species. 150 00:08:32,679 --> 00:08:35,520 Speaker 1: Those things clearly are true. And it clearly is true 151 00:08:35,640 --> 00:08:39,000 Speaker 1: that it's good for the next generation that older generations 152 00:08:39,080 --> 00:08:41,880 Speaker 1: age out and die. I care about the survival of 153 00:08:41,920 --> 00:08:44,400 Speaker 1: the rest of my group. I care about members of 154 00:08:44,400 --> 00:08:47,640 Speaker 1: my species and about future generations. But I care because 155 00:08:47,640 --> 00:08:50,800 Speaker 1: I have a brain and I can recognize what's going on. 156 00:08:51,240 --> 00:08:54,320 Speaker 1: Magines don't care, and your genes don't care. They just 157 00:08:54,440 --> 00:08:59,000 Speaker 1: chemically proliferate themselves. They don't have a sentimental attachment or 158 00:08:59,120 --> 00:09:02,480 Speaker 1: or an idea that the next generation should get resources 159 00:09:02,520 --> 00:09:04,560 Speaker 1: to all right, So this just brings us back to 160 00:09:04,640 --> 00:09:09,640 Speaker 1: the question, though, why have we evolved to grow old? Right? 161 00:09:09,679 --> 00:09:13,439 Speaker 1: It's still unsolved. Why not live and reproduce forever, maintaining 162 00:09:13,520 --> 00:09:17,880 Speaker 1: perfect youth and vigor until something extrinsic happens, until we 163 00:09:17,920 --> 00:09:21,800 Speaker 1: get killed by a hemorrhagic fever or tractor accident. Alright, 164 00:09:21,800 --> 00:09:23,440 Speaker 1: we're gonna take a quick break and we come back. 165 00:09:23,559 --> 00:09:29,400 Speaker 1: We will answer that very question. Thank alright, we're back. 166 00:09:29,520 --> 00:09:31,960 Speaker 1: Al right. So, there are a number of modern, well 167 00:09:32,000 --> 00:09:36,080 Speaker 1: accepted scientific theories trying to answer the question of why 168 00:09:36,240 --> 00:09:39,760 Speaker 1: we evolved to age. And here's a starting point for 169 00:09:39,800 --> 00:09:42,040 Speaker 1: several of those theories. Let's go back to the wolves 170 00:09:42,080 --> 00:09:45,720 Speaker 1: for a second. Imagine the space wolves. Maybe a hypothetical 171 00:09:45,760 --> 00:09:48,560 Speaker 1: wolf species could breed and stay healthy until about the 172 00:09:48,600 --> 00:09:51,920 Speaker 1: age of ten. Like we said, why not twenty, Why 173 00:09:51,960 --> 00:09:55,520 Speaker 1: not thirty? Why not five hundred? Well, here are a 174 00:09:55,559 --> 00:09:59,840 Speaker 1: few things to consider. Wolves did not evolve in zoo 175 00:10:00,120 --> 00:10:04,320 Speaker 1: 's or as domestic pets, where they're guaranteed meals and 176 00:10:04,360 --> 00:10:09,240 Speaker 1: protection from violence and guaranteed access to veterinary care. The 177 00:10:09,360 --> 00:10:13,240 Speaker 1: landscape that created the wolf as it exists is one 178 00:10:13,240 --> 00:10:16,320 Speaker 1: in which there is a constant struggle to get enough 179 00:10:16,360 --> 00:10:19,640 Speaker 1: meat to survive and to not get sick and die, 180 00:10:19,720 --> 00:10:22,400 Speaker 1: and to not get injured and become unable to hunt, 181 00:10:22,440 --> 00:10:25,160 Speaker 1: so you starve. If you are a wolf living in 182 00:10:25,160 --> 00:10:28,079 Speaker 1: the wild, and you survive the first year of your life, 183 00:10:28,280 --> 00:10:32,200 Speaker 1: one of these things like injury or disease or starvation 184 00:10:32,960 --> 00:10:36,760 Speaker 1: very likely will kill you before you get a chance 185 00:10:36,800 --> 00:10:40,319 Speaker 1: to reach old age. These causes of death like disease 186 00:10:40,320 --> 00:10:43,840 Speaker 1: and injury, or what's known as quote extrinsic causes of death, 187 00:10:43,920 --> 00:10:47,200 Speaker 1: death caused by outside pressures and not by stuff that's 188 00:10:47,200 --> 00:10:50,200 Speaker 1: in your genes or by old age. And so we 189 00:10:50,240 --> 00:10:52,439 Speaker 1: can look at the real life example to see how 190 00:10:52,440 --> 00:10:55,800 Speaker 1: common this is. The actual gray wolf Canis lupus lives 191 00:10:55,840 --> 00:10:58,520 Speaker 1: somewhere around an average of six years or so in 192 00:10:58,559 --> 00:11:01,319 Speaker 1: the wild, but in captivity it can live for more 193 00:11:01,360 --> 00:11:05,680 Speaker 1: than fifteen years. So here's the first crucial bit to 194 00:11:05,840 --> 00:11:09,280 Speaker 1: use some more metaphorical language. If there are physical processes 195 00:11:09,320 --> 00:11:13,840 Speaker 1: that tend to render a wolf progressively less fit every 196 00:11:13,960 --> 00:11:18,120 Speaker 1: month after it's more than ten years old, evolution almost 197 00:11:18,200 --> 00:11:22,120 Speaker 1: never sees that. To put it in another metaphor, asking 198 00:11:22,160 --> 00:11:25,640 Speaker 1: why evolution allows the wolf to grow old to deteriorate 199 00:11:25,640 --> 00:11:28,360 Speaker 1: with old age is kind of like asking why we 200 00:11:28,480 --> 00:11:32,600 Speaker 1: don't have laws against time travel. The reason isn't that 201 00:11:32,640 --> 00:11:36,040 Speaker 1: our legislative bodies have considered and debated the issue of 202 00:11:36,120 --> 00:11:38,640 Speaker 1: time travel and in the end they concluded that time 203 00:11:38,640 --> 00:11:41,800 Speaker 1: travel is good, we better, we better allow it. That's 204 00:11:41,840 --> 00:11:45,880 Speaker 1: not what happens. What happens is the issue doesn't come up. Yeah, 205 00:11:45,920 --> 00:11:48,960 Speaker 1: it reminds me of some of these various programs that 206 00:11:49,720 --> 00:11:52,200 Speaker 1: informs you have to do to figure out how you're 207 00:11:52,240 --> 00:11:55,080 Speaker 1: saving your for your retirement, and they tend not to 208 00:11:55,160 --> 00:11:58,600 Speaker 1: cover the second century of your life because it's not 209 00:11:58,679 --> 00:12:02,199 Speaker 1: going to happen. That's perfect metaphor. Yeah, how come you're 210 00:12:02,240 --> 00:12:05,400 Speaker 1: not saving enough money for when you're two hundred years old. 211 00:12:05,800 --> 00:12:08,120 Speaker 1: It's not that you've decided it's better to be broke 212 00:12:08,200 --> 00:12:12,079 Speaker 1: when you're two hundred. It's just that the the situation 213 00:12:12,160 --> 00:12:14,520 Speaker 1: of being two hundred does not tend to come up 214 00:12:14,640 --> 00:12:18,880 Speaker 1: very often. Now, obviously it's not nearly that extreme because sometimes, 215 00:12:18,920 --> 00:12:21,600 Speaker 1: in some cases animals do live to old age and 216 00:12:21,640 --> 00:12:25,680 Speaker 1: they face biological sinescence under natural conditions. But for many 217 00:12:25,760 --> 00:12:29,560 Speaker 1: species it's pretty rare. For species of animals that tend 218 00:12:29,640 --> 00:12:32,840 Speaker 1: to die from one cause or another before they get 219 00:12:32,880 --> 00:12:36,840 Speaker 1: the chance to grow old evolution doesn't have many opportunities 220 00:12:37,120 --> 00:12:40,960 Speaker 1: to test what happens in old age, so it can't 221 00:12:40,960 --> 00:12:45,320 Speaker 1: optimize the animal for old age very efficiently, and compare 222 00:12:45,360 --> 00:12:48,440 Speaker 1: this to how strongly evolution tests and optimizes for the 223 00:12:48,480 --> 00:12:52,199 Speaker 1: effects of genes that manifest in early life. If something 224 00:12:52,240 --> 00:12:56,160 Speaker 1: affects how likely you are to survive at age twenty 225 00:12:56,320 --> 00:12:59,920 Speaker 1: or at age ten, evolution is going to be very strong, 226 00:13:00,040 --> 00:13:04,120 Speaker 1: only selecting four or against that gene. Okay, So this 227 00:13:04,200 --> 00:13:06,920 Speaker 1: is one part of the landscape of explanations today. Most 228 00:13:06,960 --> 00:13:11,160 Speaker 1: species that show significant aging evolved to their anatomically modern 229 00:13:11,200 --> 00:13:14,880 Speaker 1: condition in a situation where mortality was high and evolution 230 00:13:14,960 --> 00:13:17,800 Speaker 1: didn't get a lot of opportunities to see what happens 231 00:13:17,800 --> 00:13:21,120 Speaker 1: in old age, much less optimize it. Uh, let's introduce 232 00:13:21,120 --> 00:13:24,079 Speaker 1: another wrinkle into the explanation. Yeah, this one has a 233 00:13:24,080 --> 00:13:28,600 Speaker 1: wonderful title. This is mutation accumulation. Right, So we go 234 00:13:28,679 --> 00:13:32,320 Speaker 1: to the British biologist Peter B. Meadair. He was one 235 00:13:32,320 --> 00:13:35,320 Speaker 1: of the primary evolutionary thinkers credited with working out the 236 00:13:35,360 --> 00:13:38,480 Speaker 1: implications of this model of aging, where the force of 237 00:13:38,520 --> 00:13:42,880 Speaker 1: selection just declines with old age. So in several works 238 00:13:42,880 --> 00:13:45,800 Speaker 1: in the middle of the nineteen forties and the nineteen fifties, 239 00:13:46,280 --> 00:13:49,920 Speaker 1: UH he argued, based on similar logic, that natural selection 240 00:13:49,960 --> 00:13:52,840 Speaker 1: would often be blind to the effects of mutations that 241 00:13:52,880 --> 00:13:57,559 Speaker 1: cause negative effects laid in life after reproduction is mostly stopped. 242 00:13:57,559 --> 00:14:01,120 Speaker 1: So let's use another analogy. Imagine a mutation called the 243 00:14:01,160 --> 00:14:05,600 Speaker 1: twenty birthday surprise gene, which means that on the day 244 00:14:05,679 --> 00:14:09,360 Speaker 1: you turn twenty, carriers of this gene suddenly transform into 245 00:14:09,400 --> 00:14:12,320 Speaker 1: a bucket of fish heads and thus lose all ability 246 00:14:12,360 --> 00:14:16,080 Speaker 1: to reproduce. Now, this would mean that in order to 247 00:14:16,160 --> 00:14:19,520 Speaker 1: pass on this gene, a carrier would have to reproduce 248 00:14:19,680 --> 00:14:23,120 Speaker 1: before their twentieth birthday, So kids they have before they're 249 00:14:23,160 --> 00:14:26,680 Speaker 1: twenty years old could still carry this gene, but they 250 00:14:26,720 --> 00:14:29,160 Speaker 1: don't get the chance to have any kids after their 251 00:14:29,200 --> 00:14:31,480 Speaker 1: twenty years old, when plenty of other members of the 252 00:14:31,480 --> 00:14:35,680 Speaker 1: species would continue having children, All potential reproduction after twenty 253 00:14:35,800 --> 00:14:39,400 Speaker 1: is canceled, thus giving people with this gene significantly fewer 254 00:14:39,480 --> 00:14:41,920 Speaker 1: children on average than people without it, and so the 255 00:14:41,960 --> 00:14:46,080 Speaker 1: gene is unlikely to spread in the population. Now imagine 256 00:14:46,120 --> 00:14:49,680 Speaker 1: a similar gene. This is the hundredth birthday surprise gene. 257 00:14:50,360 --> 00:14:53,440 Speaker 1: Carriers of this gene, upon the day of their hundredth 258 00:14:53,440 --> 00:14:57,000 Speaker 1: birthday suddenly transform into a VHS copy of Highlander to 259 00:14:57,080 --> 00:15:00,440 Speaker 1: the quickening okay, and and and therefore becoming more No, 260 00:15:00,640 --> 00:15:03,680 Speaker 1: not quite No. The problem is, well, I guess you 261 00:15:03,680 --> 00:15:06,640 Speaker 1: you might get to live somewhat forever on a shelf, 262 00:15:06,640 --> 00:15:09,720 Speaker 1: but you don't. You definitely don't get to reproduce after that. Right, 263 00:15:09,760 --> 00:15:13,480 Speaker 1: there's very little sexual reproduction between copies of Highlander to 264 00:15:13,640 --> 00:15:18,200 Speaker 1: the quickening. But also it doesn't really matter, right because 265 00:15:18,240 --> 00:15:21,440 Speaker 1: do carriers of this gene have any fewer children the 266 00:15:21,600 --> 00:15:24,880 Speaker 1: non carriers of this gene? The answer is no, right, 267 00:15:24,920 --> 00:15:29,960 Speaker 1: because who's still having children at age one hundred? Almost nobody. 268 00:15:30,040 --> 00:15:32,520 Speaker 1: So even if you have this very unhelpful gene, you 269 00:15:32,560 --> 00:15:35,440 Speaker 1: don't like it that you transform into a VHS tape 270 00:15:35,440 --> 00:15:38,280 Speaker 1: on your hundredth birthday, that's not good for you. But 271 00:15:38,360 --> 00:15:40,920 Speaker 1: it doesn't matter to how many children you have. It 272 00:15:40,960 --> 00:15:43,840 Speaker 1: has no effect on that. So if you have this gene, 273 00:15:43,880 --> 00:15:46,440 Speaker 1: you can spread it to all your children, and they 274 00:15:46,440 --> 00:15:49,560 Speaker 1: can spread it to all of their children and so, 275 00:15:49,720 --> 00:15:52,120 Speaker 1: and they'll all have just as many kids and grandkids 276 00:15:52,120 --> 00:15:54,440 Speaker 1: as the neighbors who don't have it. You've already passed 277 00:15:54,480 --> 00:15:58,440 Speaker 1: it on by the time it matters, So this would 278 00:15:58,440 --> 00:16:01,080 Speaker 1: be the case. Though we we've we've used the Highlander 279 00:16:01,240 --> 00:16:04,640 Speaker 1: to transformation as as an example here, but even if 280 00:16:04,680 --> 00:16:09,320 Speaker 1: it were something seemingly beneficial, like say a gene made 281 00:16:09,320 --> 00:16:13,040 Speaker 1: you suddenly really excellent and talking to members of the 282 00:16:13,040 --> 00:16:17,440 Speaker 1: opposite sex at age one hundred, you know, like or 283 00:16:17,480 --> 00:16:20,560 Speaker 1: the opposite it made you terrible at a speaking to 284 00:16:20,600 --> 00:16:23,840 Speaker 1: the opposite sex at age one hundred, it would still 285 00:16:23,880 --> 00:16:27,040 Speaker 1: be the same case, right, yeah, unless the basically the 286 00:16:27,040 --> 00:16:29,040 Speaker 1: only thing that would matter would be if it's a 287 00:16:29,120 --> 00:16:32,560 Speaker 1: gene that suddenly makes you able to reproduce again. I mean, 288 00:16:32,600 --> 00:16:35,160 Speaker 1: if it did that, then that would probably matter. But 289 00:16:35,280 --> 00:16:38,320 Speaker 1: as long as you're past the age of reproduction and 290 00:16:38,400 --> 00:16:43,120 Speaker 1: you're not having any more children, mutations good or bad 291 00:16:43,280 --> 00:16:47,560 Speaker 1: are just going to sort of accumulate randomly without having 292 00:16:47,640 --> 00:16:51,520 Speaker 1: any effect Onesoever, natural selection just doesn't pay attention to 293 00:16:51,560 --> 00:16:54,400 Speaker 1: them because it never gets to notice them. Well. But 294 00:16:54,400 --> 00:16:56,000 Speaker 1: but then the other thing too, is that if you're 295 00:16:56,000 --> 00:16:57,800 Speaker 1: talking about something that would kick in so late in 296 00:16:57,920 --> 00:17:02,080 Speaker 1: life that even people with that gene might never experience it. Right. 297 00:17:02,160 --> 00:17:04,960 Speaker 1: It's like if you're playing a role playing game, video 298 00:17:05,000 --> 00:17:06,760 Speaker 1: game or what have you, and there's some sort of 299 00:17:06,760 --> 00:17:09,320 Speaker 1: like high level ability and you look at it. It It 300 00:17:09,400 --> 00:17:11,000 Speaker 1: looks great, but you know you're never going to play 301 00:17:11,040 --> 00:17:13,600 Speaker 1: the game long enough to get it. Yeah, so what's 302 00:17:13,640 --> 00:17:16,160 Speaker 1: the point. Yeah, the game might as well for you 303 00:17:16,400 --> 00:17:20,119 Speaker 1: not even have that thing in it. And apparently there 304 00:17:20,160 --> 00:17:22,560 Speaker 1: are going to be genetic mutations like that. And this 305 00:17:22,680 --> 00:17:24,959 Speaker 1: was Meta Wars insight. It came to be known, as 306 00:17:25,040 --> 00:17:30,159 Speaker 1: you said, as the mutation accumulation hypothesis. Whether reproduction stops 307 00:17:30,240 --> 00:17:33,160 Speaker 1: because you die of extrinsic causes. This was a big 308 00:17:33,160 --> 00:17:35,040 Speaker 1: thing Meta where had in mind. It's like we talked about, 309 00:17:35,080 --> 00:17:37,600 Speaker 1: you know, the wolf gets injured and can't hunt, the 310 00:17:37,640 --> 00:17:40,960 Speaker 1: wolf gets sick and dies, the wolf gets killed by something, 311 00:17:41,560 --> 00:17:44,720 Speaker 1: whether that happens or because you age out of your 312 00:17:44,760 --> 00:17:48,639 Speaker 1: reproductive stage of life for some other biological reasons. Genes 313 00:17:48,680 --> 00:17:52,840 Speaker 1: that have negative effects that show up mostly after reproduction 314 00:17:52,920 --> 00:17:56,040 Speaker 1: has stopped are not subject to the full force of 315 00:17:56,119 --> 00:17:59,600 Speaker 1: natural selection. So there's not much preventing the proliferation of 316 00:17:59,680 --> 00:18:02,440 Speaker 1: gene that harm you in old age because there's nothing 317 00:18:02,440 --> 00:18:05,240 Speaker 1: to weed them out, and they accumulate in the genome 318 00:18:05,320 --> 00:18:08,560 Speaker 1: over generations by what's known as genetic drift. And the 319 00:18:08,640 --> 00:18:12,480 Speaker 1: genetic drift is just the random dispersing of genes that 320 00:18:12,560 --> 00:18:15,880 Speaker 1: don't appear to have a very strong positive or negative effect. 321 00:18:16,280 --> 00:18:19,119 Speaker 1: So if you've got a mutation that you acquire for 322 00:18:19,280 --> 00:18:22,480 Speaker 1: a nasty surprise in old age, something bad that happens 323 00:18:22,520 --> 00:18:24,680 Speaker 1: to your body. And you could look at the process 324 00:18:24,720 --> 00:18:27,840 Speaker 1: of aging like this. It's just a large plethora of 325 00:18:27,920 --> 00:18:31,760 Speaker 1: genetic mutations that cause bad things to happen to your body. 326 00:18:31,880 --> 00:18:34,720 Speaker 1: Later on, you can still pass it on to your kids, 327 00:18:34,800 --> 00:18:37,400 Speaker 1: because you're you've had all your kids by the time 328 00:18:37,440 --> 00:18:40,720 Speaker 1: it starts affecting you. And so these genes can become 329 00:18:40,760 --> 00:18:43,680 Speaker 1: common in the gene pool of your species simply because 330 00:18:43,760 --> 00:18:46,800 Speaker 1: there's nothing stopping them. So simply put it in. The 331 00:18:46,840 --> 00:18:50,640 Speaker 1: force of selection declines with age. Mutations that are neutral 332 00:18:50,760 --> 00:18:54,400 Speaker 1: early in life when selection is strong, but negative later on, 333 00:18:55,080 --> 00:18:58,000 Speaker 1: they could accumulate in the population. I like to think 334 00:18:58,000 --> 00:19:00,280 Speaker 1: of this as the sack of kitty litter school things 335 00:19:00,280 --> 00:19:04,000 Speaker 1: in the closet scenario. What, okay, explain, but a friend 336 00:19:04,040 --> 00:19:06,560 Speaker 1: of mine, when I first met her, she had a 337 00:19:07,560 --> 00:19:09,760 Speaker 1: cat box, and then she would scoop the cat box 338 00:19:09,800 --> 00:19:13,040 Speaker 1: and it would accumulate in a garbage bag in the closet. 339 00:19:13,560 --> 00:19:16,440 Speaker 1: Accumulate me, you mean accumulate as and she would dump 340 00:19:16,440 --> 00:19:18,399 Speaker 1: it in a garbage bag in the close and it 341 00:19:18,440 --> 00:19:20,720 Speaker 1: was it was a lot cleaner than this makes it sound, 342 00:19:20,760 --> 00:19:22,280 Speaker 1: but it was. It was very much a sort of 343 00:19:22,359 --> 00:19:25,159 Speaker 1: kicking the can down a road scenario, like eventually you're 344 00:19:25,200 --> 00:19:28,199 Speaker 1: gonna have to take that bag of of of of 345 00:19:28,240 --> 00:19:32,919 Speaker 1: litter scoopings out, but you're not. The whole situation is 346 00:19:32,960 --> 00:19:35,120 Speaker 1: not built on what you're going to have to do tomorrow. 347 00:19:35,160 --> 00:19:37,640 Speaker 1: It's about what's happening to today. But what if you're 348 00:19:37,640 --> 00:19:39,520 Speaker 1: looking at that closet and you're saying, Oh, there's enough 349 00:19:39,560 --> 00:19:41,640 Speaker 1: space in here that I could keep scooping it into 350 00:19:41,680 --> 00:19:44,000 Speaker 1: the closet until I die of some of their cause, 351 00:19:44,480 --> 00:19:46,360 Speaker 1: and then I would never have to take it out. 352 00:19:46,400 --> 00:19:49,760 Speaker 1: It would be completely irrelevant. So it can accumulate forever, 353 00:19:49,920 --> 00:19:53,560 Speaker 1: just like these deleterious Janes can. Okay, So that's clearly 354 00:19:53,640 --> 00:19:56,760 Speaker 1: one part of the answer. One part is that stuff 355 00:19:56,800 --> 00:19:59,200 Speaker 1: that affects you late in life is just less likely 356 00:19:59,280 --> 00:20:02,040 Speaker 1: to get weeded out by natural selection. But what if 357 00:20:02,040 --> 00:20:05,879 Speaker 1: there's something more than that. What if maladaptive genes that 358 00:20:05,960 --> 00:20:09,199 Speaker 1: manifest in old age aren't just allowed to roam wild 359 00:20:09,320 --> 00:20:12,600 Speaker 1: by sort of the careless shepherd of natural selection. What 360 00:20:12,680 --> 00:20:17,200 Speaker 1: if they're positively selected for in some way, and that's 361 00:20:17,200 --> 00:20:19,439 Speaker 1: what we'll explore when we come back from this break. 362 00:20:20,160 --> 00:20:23,960 Speaker 1: Thank thank all right, we're back. So now it's time 363 00:20:23,960 --> 00:20:28,080 Speaker 1: to talk about antagonistic pleotropy. In a paper in N 364 00:20:28,840 --> 00:20:32,600 Speaker 1: seven and the journal Evolution, the American evolutionary biologist George C. 365 00:20:32,840 --> 00:20:37,320 Speaker 1: Williams had a breakthrough that made metoirs original hypothesis even 366 00:20:37,400 --> 00:20:40,480 Speaker 1: stronger and sort of complimented it. And so this was 367 00:20:40,520 --> 00:20:42,760 Speaker 1: a paper that I mentioned in part one. Actually it's 368 00:20:42,760 --> 00:20:46,960 Speaker 1: the paper called pleotropy, Natural Selection and the Evolution of sinescence. 369 00:20:47,720 --> 00:20:51,560 Speaker 1: Williams hypothesis for the evolution of aging came to be known, 370 00:20:51,640 --> 00:20:55,320 Speaker 1: as I said, as antagonistic pleotropy. And what this means 371 00:20:55,640 --> 00:20:59,240 Speaker 1: is that, well, pleotropy, the word comes from the Greek 372 00:20:59,600 --> 00:21:05,480 Speaker 1: roots meaning multiple turns or many effects. Pleotropy happens when 373 00:21:05,520 --> 00:21:11,040 Speaker 1: a single gene codes for multiple different phenotypic effects, meaning 374 00:21:11,080 --> 00:21:13,960 Speaker 1: effects on the body or effects on the behavior. So 375 00:21:14,000 --> 00:21:18,040 Speaker 1: if you had one gene that both gave you black 376 00:21:18,080 --> 00:21:22,560 Speaker 1: hair and gave you an extremely long, pinky fingernail, that 377 00:21:22,560 --> 00:21:25,040 Speaker 1: would be pleotropy. Or if you had a gene that 378 00:21:25,200 --> 00:21:29,840 Speaker 1: made you really tall and also made you better at 379 00:21:29,960 --> 00:21:33,640 Speaker 1: learning multiple languages, that would be pleotropy. And there are 380 00:21:33,680 --> 00:21:36,439 Speaker 1: lots of examples of this in animals in the real world. 381 00:21:36,760 --> 00:21:39,919 Speaker 1: Here's one in chickens. Robert, have you ever seen the 382 00:21:39,920 --> 00:21:42,560 Speaker 1: frizzle chickens? Who? I don't know. I've seen some pretty 383 00:21:42,560 --> 00:21:47,399 Speaker 1: funny looking chickens before chicken. I mean the ones that 384 00:21:47,520 --> 00:21:51,200 Speaker 1: have like the curly vegas outfits. Uh yeah, well yeah, 385 00:21:51,240 --> 00:21:54,000 Speaker 1: I have seen some of these. These these chickens that 386 00:21:54,040 --> 00:21:56,200 Speaker 1: have like a lot of extra feathers around their their 387 00:21:56,240 --> 00:21:59,560 Speaker 1: talents and all. The frizzle gene is is a gene 388 00:21:59,600 --> 00:22:02,800 Speaker 1: in chicken that causes the feathers to curl up instead 389 00:22:02,800 --> 00:22:07,840 Speaker 1: of lying flat. So you get these crazy looking, like awesome, beautiful, regal, 390 00:22:07,960 --> 00:22:11,399 Speaker 1: puffy chickens and they look really cool. But it turns 391 00:22:11,400 --> 00:22:14,840 Speaker 1: out this gene also controls several other phenotypic effects. So 392 00:22:14,960 --> 00:22:17,720 Speaker 1: if you are a chicken with the frizzle gene, you'll 393 00:22:17,760 --> 00:22:21,320 Speaker 1: also have a different metabolic rate and different body temperature 394 00:22:21,640 --> 00:22:24,520 Speaker 1: and lay a different number of eggs than the chickens 395 00:22:24,520 --> 00:22:26,919 Speaker 1: who don't have this gene. So if you want the 396 00:22:27,000 --> 00:22:29,920 Speaker 1: gene for the magnificent curl, you're going to be laying 397 00:22:30,040 --> 00:22:33,520 Speaker 1: fewer eggs, among other things. And these are examples where 398 00:22:33,760 --> 00:22:37,159 Speaker 1: the situation. It feels more like a trade off and 399 00:22:37,240 --> 00:22:41,120 Speaker 1: probably has more in common with some of our our myths, right, 400 00:22:41,280 --> 00:22:44,040 Speaker 1: because the gift of the god often comes with some 401 00:22:44,080 --> 00:22:48,120 Speaker 1: sort of consequence. Yeah exactly. So another one, just real 402 00:22:48,200 --> 00:22:51,399 Speaker 1: quick in cats, did you know about cats with white 403 00:22:51,440 --> 00:22:54,160 Speaker 1: fur and blue eyes are also deaf? I have heard 404 00:22:54,160 --> 00:22:58,240 Speaker 1: this one, yes, yeah, odd. So pleotropy can be like that. 405 00:22:58,359 --> 00:23:00,200 Speaker 1: It can come and it kind of mixed blessing form, 406 00:23:00,200 --> 00:23:02,120 Speaker 1: though I guess I don't actually know if blue eyes 407 00:23:02,160 --> 00:23:04,280 Speaker 1: are good for the cat. Maybe that's double bad. But 408 00:23:04,880 --> 00:23:07,040 Speaker 1: uh well you I mean, certainly, when you get into 409 00:23:07,119 --> 00:23:11,000 Speaker 1: the selective breeding of of a species, you get into 410 00:23:11,040 --> 00:23:14,879 Speaker 1: a situation where appearance has has has a survival advantage. 411 00:23:15,080 --> 00:23:19,679 Speaker 1: Yeah exactly. So pleotropy can go both ways. One effect 412 00:23:19,680 --> 00:23:22,360 Speaker 1: of a gene could be good while the other effect 413 00:23:22,440 --> 00:23:24,720 Speaker 1: could be bad. And here's where we get the idea 414 00:23:24,760 --> 00:23:29,879 Speaker 1: of quote antagonistic pleotropy, a pleotropy that's pulling in both directions, 415 00:23:30,280 --> 00:23:33,760 Speaker 1: but usually it'll pull a bit stronger in one direction 416 00:23:33,840 --> 00:23:37,320 Speaker 1: than another. So if the good effect outweighs the bad effect, 417 00:23:37,359 --> 00:23:39,800 Speaker 1: the gene will spread through the gene pool. But if 418 00:23:39,800 --> 00:23:42,159 Speaker 1: the bad effect outweighs the good effect, the gene will 419 00:23:42,200 --> 00:23:44,840 Speaker 1: tend to go extinct. That we should be clear again 420 00:23:44,920 --> 00:23:49,080 Speaker 1: what's meant by good and bad genes here, Because, for example, 421 00:23:49,119 --> 00:23:53,639 Speaker 1: a gene that caused the carrier to experience intense pain 422 00:23:53,760 --> 00:23:58,080 Speaker 1: and misery throughout life, but somehow also caused the carrier 423 00:23:58,359 --> 00:24:01,119 Speaker 1: to have more healthy children than the average member of 424 00:24:01,160 --> 00:24:05,320 Speaker 1: their species would also spread. So it's not optimizing for 425 00:24:05,440 --> 00:24:07,639 Speaker 1: like you to have a long life, for you to 426 00:24:07,720 --> 00:24:10,280 Speaker 1: have a fun life. It's optimizing for a number of 427 00:24:10,280 --> 00:24:15,120 Speaker 1: offspring and the success of those offspring. Now, William's theory 428 00:24:15,200 --> 00:24:19,440 Speaker 1: of antagonistic pleotropy picks up from this fact. He hypothesizes 429 00:24:19,520 --> 00:24:22,359 Speaker 1: that some of the genes that cause aging are selected 430 00:24:22,400 --> 00:24:26,720 Speaker 1: for because they have other separate effects that maximize fitness 431 00:24:26,720 --> 00:24:30,760 Speaker 1: and reproduction earlier in life, which, like metair showed, is 432 00:24:30,760 --> 00:24:34,080 Speaker 1: more strongly selected for in nature. The same genes that 433 00:24:34,160 --> 00:24:37,320 Speaker 1: make your skin sag and give you heart disease in 434 00:24:37,400 --> 00:24:42,080 Speaker 1: old age might also make you extremely reproductively competitive when 435 00:24:42,119 --> 00:24:45,480 Speaker 1: you're young. So here's a really broad example. How about 436 00:24:45,520 --> 00:24:50,159 Speaker 1: genes that control the rate of cell division. Yeah, so 437 00:24:50,160 --> 00:24:53,639 Speaker 1: a hypothetical gene might be selected for because it makes 438 00:24:53,680 --> 00:24:57,600 Speaker 1: cells divide more efficiently. And if cells divide more efficiently, 439 00:24:57,640 --> 00:25:00,840 Speaker 1: it means you can rejuvenate tissues and he wounds and 440 00:25:01,040 --> 00:25:04,480 Speaker 1: grow faster when you're young. But the same gene that 441 00:25:04,560 --> 00:25:09,120 Speaker 1: causes prolific cell division could potentially be a problem later 442 00:25:09,160 --> 00:25:11,600 Speaker 1: in life because what happens when cells are prone to 443 00:25:11,680 --> 00:25:15,160 Speaker 1: divide a whole lot you could be prone to cancer 444 00:25:15,240 --> 00:25:19,000 Speaker 1: cancer is runaway cell division. Cells that are not useful 445 00:25:19,040 --> 00:25:22,280 Speaker 1: for the body are suddenly being created in great abundance, 446 00:25:22,760 --> 00:25:24,800 Speaker 1: which brings us back to the Hadross or example that 447 00:25:24,840 --> 00:25:27,400 Speaker 1: we touched on earlier. Yeah, back in the first episode, 448 00:25:27,880 --> 00:25:30,240 Speaker 1: or you can think about something going exactly the reverse. 449 00:25:30,240 --> 00:25:33,720 Speaker 1: You could have a gene that could increase apoptosis signaling, 450 00:25:33,760 --> 00:25:37,240 Speaker 1: and apoptosis is programmed cell death, so a gene that 451 00:25:37,240 --> 00:25:41,000 Speaker 1: that causes cell lines to die off more frequently, and 452 00:25:41,119 --> 00:25:44,600 Speaker 1: this would help prevent runaway cell lines from turning into 453 00:25:44,640 --> 00:25:48,680 Speaker 1: cancer while you're young. Natural selection obviously would love this 454 00:25:48,800 --> 00:25:51,840 Speaker 1: because it would select against organisms that get cancer when 455 00:25:51,880 --> 00:25:55,399 Speaker 1: they're young and can't reproduce much. But the exact same 456 00:25:55,480 --> 00:25:59,400 Speaker 1: gene would cause tissues to deteriorate more with age because 457 00:25:59,400 --> 00:26:02,800 Speaker 1: they undergo more and earlier cell death, and in fact, 458 00:26:02,960 --> 00:26:06,000 Speaker 1: something like what I just described has actually been studied. 459 00:26:06,320 --> 00:26:09,720 Speaker 1: The example would be the gene at P fifty three. 460 00:26:10,040 --> 00:26:13,800 Speaker 1: The P fifty three gene has been implicated in antagonistic pleotropy, 461 00:26:13,800 --> 00:26:16,880 Speaker 1: and it's thought that P fifty three protects young animals, 462 00:26:16,880 --> 00:26:19,879 Speaker 1: including humans, but I think it's mostly been researched in mice. 463 00:26:20,960 --> 00:26:25,960 Speaker 1: It protects these young animals against cancer by interrupting cell proliferation. 464 00:26:26,040 --> 00:26:28,600 Speaker 1: It says, now, don't cells, don't divide too much now, 465 00:26:29,040 --> 00:26:31,399 Speaker 1: But in doing this it can also have the effect 466 00:26:31,440 --> 00:26:35,800 Speaker 1: of interrupting the proliferation of normal, non cancerous cells, like 467 00:26:35,920 --> 00:26:38,359 Speaker 1: stem cells, which are the cells the body uses to 468 00:26:38,400 --> 00:26:43,520 Speaker 1: rejuvenate tissues over time. So the same gene that plays 469 00:26:43,520 --> 00:26:46,520 Speaker 1: some role in helping protect against cancer when you're young 470 00:26:47,119 --> 00:26:50,600 Speaker 1: also helps play some role in the physical deterioration of 471 00:26:50,640 --> 00:26:53,760 Speaker 1: the body with age by preventing it from making new 472 00:26:53,800 --> 00:26:58,399 Speaker 1: cells and rejuvenating your tissues and detaining eternal youth. So 473 00:26:58,440 --> 00:27:01,480 Speaker 1: the takeaway from this obviously that anytime you see a 474 00:27:01,520 --> 00:27:04,760 Speaker 1: story about eternal youth in fiction or in a movie 475 00:27:04,840 --> 00:27:08,160 Speaker 1: or something like that, imagine these these characters who are 476 00:27:08,160 --> 00:27:11,800 Speaker 1: eternally youthful, riddled with cancer. It's not really not that 477 00:27:11,880 --> 00:27:14,680 Speaker 1: hard to imagine when you think about all the various 478 00:27:14,840 --> 00:27:18,280 Speaker 1: uh uh side effects and caveats that come with eternal 479 00:27:18,320 --> 00:27:20,680 Speaker 1: youth in most of our myths and legends. Right well, 480 00:27:20,800 --> 00:27:22,800 Speaker 1: I mean, yeah, you've got uh. I guess it's not 481 00:27:22,880 --> 00:27:25,880 Speaker 1: applicable in the Tiffannas story because he doesn't get eternal youth. 482 00:27:26,119 --> 00:27:28,760 Speaker 1: He wants to live forever. But you imagine the equivalent 483 00:27:28,800 --> 00:27:31,520 Speaker 1: of the Tiffanas story where you ask for eternal youth. 484 00:27:31,600 --> 00:27:34,080 Speaker 1: So Tiffanus asked for eternal life, or he doesn't ask 485 00:27:34,080 --> 00:27:37,840 Speaker 1: Aos asked for eternal life. For Tithness. He gets eternal life, 486 00:27:37,840 --> 00:27:40,280 Speaker 1: but not eternal youth. So it's the monkeys Paul coming 487 00:27:40,320 --> 00:27:42,840 Speaker 1: back to bite him. In this story. You would ask 488 00:27:42,880 --> 00:27:45,880 Speaker 1: for eternal youth and they say, okay, here's your eternal youth, 489 00:27:45,960 --> 00:27:48,479 Speaker 1: but you get lots of cancer with it. And I 490 00:27:48,480 --> 00:27:50,760 Speaker 1: think actually have read in the past that some of 491 00:27:50,800 --> 00:27:55,159 Speaker 1: these experimental youth extension techniques that people do research on 492 00:27:55,640 --> 00:27:59,119 Speaker 1: initially look promising but sometimes turn out to appear to 493 00:27:59,320 --> 00:28:02,960 Speaker 1: increase answer risk. Now here's another example of a potential 494 00:28:02,960 --> 00:28:07,359 Speaker 1: antagonistic pleotropy inflammation. So I want to cite one paper 495 00:28:07,440 --> 00:28:11,680 Speaker 1: from two thousand eight in Bioscience Trends by Makoto Godo, 496 00:28:12,080 --> 00:28:14,199 Speaker 1: and in this paper, the author explores the idea that 497 00:28:14,400 --> 00:28:17,520 Speaker 1: a lot of the signs of physical deterioration associated with 498 00:28:17,600 --> 00:28:22,320 Speaker 1: aging are driven by inflammation. But inflammation is a defense 499 00:28:22,359 --> 00:28:25,480 Speaker 1: mechanism for the body. It helps you survive the redness, 500 00:28:25,520 --> 00:28:28,399 Speaker 1: the swelling. It's not pleasant, but all that's part of 501 00:28:28,440 --> 00:28:32,320 Speaker 1: a primitive immune system response that protects you against antigens 502 00:28:32,320 --> 00:28:37,360 Speaker 1: and parasites. So inflammation responses can help you survive when 503 00:28:37,400 --> 00:28:41,440 Speaker 1: you're young, but later in life, inflammation related aging effects 504 00:28:41,440 --> 00:28:45,360 Speaker 1: cause widespread damage to the body, including all kinds of diseases, 505 00:28:45,400 --> 00:28:51,080 Speaker 1: from type two diabetes to rheumatoid arthritis. As the kind 506 00:28:51,120 --> 00:28:54,720 Speaker 1: of military reaction to invasion that is helpful for the 507 00:28:54,760 --> 00:28:58,120 Speaker 1: young organism can be a detriment to the older or 508 00:28:58,320 --> 00:29:01,959 Speaker 1: organism correct exactly right, And so it's believed now by 509 00:29:02,000 --> 00:29:04,520 Speaker 1: scientists that there are tons of things like this in 510 00:29:04,560 --> 00:29:09,160 Speaker 1: the body. There are genes that have these antagonistic pleotropy effects. 511 00:29:09,200 --> 00:29:11,360 Speaker 1: They're good for you when you're young. They help you 512 00:29:11,440 --> 00:29:15,160 Speaker 1: survive young adulthood and childhood, and help you have more 513 00:29:15,240 --> 00:29:19,880 Speaker 1: children early on. But the same very same genes having 514 00:29:19,920 --> 00:29:23,239 Speaker 1: the very same effects also cause you to age and 515 00:29:23,320 --> 00:29:27,320 Speaker 1: become sick and reduce your fitness later on in life, when, 516 00:29:27,400 --> 00:29:30,720 Speaker 1: as we established earlier, the force of selection is diminished. 517 00:29:31,160 --> 00:29:34,760 Speaker 1: So one more theory that is pretty similar to these 518 00:29:34,840 --> 00:29:39,280 Speaker 1: ones we've just discussed. We've got metairs mutation accumulation hypothesis, 519 00:29:39,320 --> 00:29:42,200 Speaker 1: which says, you know, uh, natural selection doesn't pay much 520 00:29:42,200 --> 00:29:45,760 Speaker 1: attention to what happens later in life, so negative mutations 521 00:29:45,800 --> 00:29:48,160 Speaker 1: can kind of just hang out there without really being 522 00:29:48,160 --> 00:29:51,960 Speaker 1: weeded out. Then you've got antagonistic pleotropy, which says that 523 00:29:52,280 --> 00:29:54,479 Speaker 1: some of the things that cause negative effects later in 524 00:29:54,520 --> 00:29:58,360 Speaker 1: life are positively selected for because those negative effects later 525 00:29:58,400 --> 00:30:01,440 Speaker 1: are much outweighed by positive of effects early in life 526 00:30:01,480 --> 00:30:04,960 Speaker 1: and uh, enhancing reproductive fitness early on. So there's a 527 00:30:05,040 --> 00:30:09,360 Speaker 1: very similar theory along the same lines called the disposable 528 00:30:09,480 --> 00:30:12,040 Speaker 1: soma theory, And this is a theory on the evolution 529 00:30:12,040 --> 00:30:14,800 Speaker 1: of aging that was put forward in nineteen seventy seven 530 00:30:14,840 --> 00:30:18,680 Speaker 1: by the English biologist Thomas Kirkwood. And this reframes it 531 00:30:18,720 --> 00:30:23,400 Speaker 1: as a question of resource investment in the body. Here's 532 00:30:23,440 --> 00:30:26,719 Speaker 1: the basic premise. The body has a finite amount of 533 00:30:26,800 --> 00:30:31,200 Speaker 1: resources that it can spend on various projects. And these 534 00:30:31,200 --> 00:30:35,440 Speaker 1: projects would include things like speeding up reproduction in the 535 00:30:35,480 --> 00:30:40,840 Speaker 1: youth and maintaining body tissues. And so if you've got 536 00:30:40,880 --> 00:30:43,360 Speaker 1: both of these things and you've got a limited budget 537 00:30:43,400 --> 00:30:46,960 Speaker 1: to spend on them, you're gonna need to make choices, right, 538 00:30:47,480 --> 00:30:49,960 Speaker 1: how much goes to each one, and indeed which one 539 00:30:50,040 --> 00:30:54,400 Speaker 1: is the most important for the biological mission at hand, right, 540 00:30:54,440 --> 00:30:56,840 Speaker 1: And so, drawing on the same logic we looked at earlier, 541 00:30:56,880 --> 00:30:59,680 Speaker 1: if you live in a scenario where you don't tend 542 00:30:59,760 --> 00:31:04,240 Speaker 1: to live to you know, your natural end of life age, 543 00:31:04,320 --> 00:31:06,880 Speaker 1: you tend to get weeded out by things happening to 544 00:31:07,000 --> 00:31:10,440 Speaker 1: you in the wild, you know, predation or starvation or 545 00:31:11,480 --> 00:31:15,600 Speaker 1: or a disease or injury, anything like that, it will 546 00:31:15,640 --> 00:31:18,640 Speaker 1: obviously look to your body like you need to invest 547 00:31:18,760 --> 00:31:22,640 Speaker 1: way more in those earlier stages in maximizing reproduction early on. 548 00:31:22,960 --> 00:31:25,240 Speaker 1: And so, drawing on metal war, evolution is going to 549 00:31:25,360 --> 00:31:30,640 Speaker 1: tend to favor pouring finite resources into early reproduction optimization 550 00:31:31,040 --> 00:31:36,400 Speaker 1: instead of maintaining tissues for an infinite natural lifespan. So 551 00:31:36,400 --> 00:31:39,720 Speaker 1: I'm trying to think of a human equivalent. Uh, it 552 00:31:39,880 --> 00:31:42,720 Speaker 1: sounds kind of silly, but basically like, should the body 553 00:31:42,760 --> 00:31:48,080 Speaker 1: spend its precious limited energy resources keeping your artery walls 554 00:31:48,240 --> 00:31:52,040 Speaker 1: from thickening over time or spending them on making you 555 00:31:52,120 --> 00:31:56,320 Speaker 1: super sexy? Well, you know, I God knows. I am 556 00:31:56,360 --> 00:31:59,600 Speaker 1: not an economist, but I find it when we discussed 557 00:32:00,120 --> 00:32:03,840 Speaker 1: cycles of organisms, or or life cycles of of stars, 558 00:32:03,920 --> 00:32:07,400 Speaker 1: even I think of companies and how they work. So 559 00:32:07,600 --> 00:32:09,520 Speaker 1: it comes down to a question as as say that 560 00:32:09,560 --> 00:32:12,360 Speaker 1: the CEO or even the founder of a company, are 561 00:32:12,440 --> 00:32:16,040 Speaker 1: you running the company like you want to retire from 562 00:32:16,040 --> 00:32:19,200 Speaker 1: it and watch it continue to prosper as you in 563 00:32:19,240 --> 00:32:22,479 Speaker 1: your retirement or are you running the company like you 564 00:32:22,520 --> 00:32:25,960 Speaker 1: intend to sell it? You know or we know what 565 00:32:26,000 --> 00:32:29,040 Speaker 1: the answer is. In most cases, yeah, you're you. In 566 00:32:29,200 --> 00:32:31,720 Speaker 1: many cases, you're running the company because in a in 567 00:32:31,760 --> 00:32:35,280 Speaker 1: a way that benefits the short term sale of the company, 568 00:32:35,440 --> 00:32:38,720 Speaker 1: or you're leaving this company for another company. Yeah. I 569 00:32:38,720 --> 00:32:41,240 Speaker 1: mean people like to have, you know, sort of like 570 00:32:41,360 --> 00:32:44,360 Speaker 1: long term investment type rhetoric. But a lot of people 571 00:32:44,800 --> 00:32:48,000 Speaker 1: have realized that the smart strategy for themselves is grab 572 00:32:48,040 --> 00:32:50,880 Speaker 1: and go, you know, optimize whatever you can get out 573 00:32:50,880 --> 00:32:53,720 Speaker 1: of a system for yourself as soon as possible, and 574 00:32:53,720 --> 00:32:56,320 Speaker 1: then be on your way, And that's the equivalent here 575 00:32:56,360 --> 00:32:58,440 Speaker 1: that this is to say that you can't even be 576 00:32:58,560 --> 00:33:00,800 Speaker 1: guaranteed that it will matter or whether you've got a 577 00:33:00,880 --> 00:33:05,719 Speaker 1: gene that optimizes against atherosclerosis or not. But if you 578 00:33:05,760 --> 00:33:09,239 Speaker 1: can optimize for being real sexy and having lots of 579 00:33:09,840 --> 00:33:13,880 Speaker 1: successful reproductive strategies early on in life, you're pretty much 580 00:33:13,880 --> 00:33:16,720 Speaker 1: guaranteed a better chance at having more children. And we 581 00:33:16,760 --> 00:33:18,960 Speaker 1: have so many different adages that back up this kind 582 00:33:19,000 --> 00:33:22,320 Speaker 1: of like personal philosophy and life. Right, you know, burn 583 00:33:22,320 --> 00:33:24,200 Speaker 1: it like you've stole it, I believe, not burn it 584 00:33:24,240 --> 00:33:27,480 Speaker 1: like you still drive it. Burn the candle at both ends. 585 00:33:27,560 --> 00:33:30,240 Speaker 1: That was combining the two there, you know. Or burn 586 00:33:30,280 --> 00:33:34,320 Speaker 1: it like you stole it, really like it's hot it 587 00:33:33,600 --> 00:33:36,120 Speaker 1: It behooves you to go ahead and burn it so 588 00:33:36,160 --> 00:33:38,680 Speaker 1: that they don't figure out you stole it. Yeah, sees 589 00:33:38,760 --> 00:33:42,080 Speaker 1: the day spend like there's no tomorrow exactly because sometimes 590 00:33:42,080 --> 00:33:45,200 Speaker 1: well sometimes there isn't, or there's there's a finite amount 591 00:33:45,200 --> 00:33:48,120 Speaker 1: of tomorrow. Sometimes a leopard will bite your face off. 592 00:33:48,440 --> 00:33:51,520 Speaker 1: You should just operate on the assumption that a leopard 593 00:33:51,600 --> 00:33:55,000 Speaker 1: might bite your face off, So spend what you've got today. Well, 594 00:33:55,040 --> 00:33:56,240 Speaker 1: that's good. I don't know if we'll fit that on 595 00:33:56,240 --> 00:33:58,920 Speaker 1: a bumper sticker, though. You now, what we've described so 596 00:33:59,040 --> 00:34:02,480 Speaker 1: far are I think, what's known as the classical theories 597 00:34:02,520 --> 00:34:05,040 Speaker 1: of aging. And in recent years we should point out 598 00:34:05,160 --> 00:34:08,520 Speaker 1: some scientists have proposed various kinds of updates to accommodate 599 00:34:08,640 --> 00:34:11,319 Speaker 1: new experimental findings. Maybe in the future we could come 600 00:34:11,360 --> 00:34:14,720 Speaker 1: back to this topic again and and explore the most 601 00:34:14,800 --> 00:34:18,759 Speaker 1: recent developments in in aging theory. But these are basically, 602 00:34:19,280 --> 00:34:21,759 Speaker 1: I would say, these classical theories are still pretty much 603 00:34:21,800 --> 00:34:25,160 Speaker 1: intact there. You know, you might need to modify them 604 00:34:25,239 --> 00:34:28,760 Speaker 1: in some ways to to update them for newest experimental findings. 605 00:34:28,760 --> 00:34:33,799 Speaker 1: But for example, an antagonistic pleotropy, people still basically think 606 00:34:33,840 --> 00:34:37,359 Speaker 1: that this is a good explanation for why a lot 607 00:34:37,400 --> 00:34:40,279 Speaker 1: of the aging effects we experience take place, and it 608 00:34:40,320 --> 00:34:44,120 Speaker 1: gives us room on which to build uh further analysis, Yeah, 609 00:34:44,120 --> 00:34:47,719 Speaker 1: of course, and it gives us room to say, if 610 00:34:47,719 --> 00:34:50,800 Speaker 1: we understand how a process happens and why it happens, 611 00:34:51,000 --> 00:34:54,719 Speaker 1: I wonder if it could be reversed or undone. And 612 00:34:54,760 --> 00:34:56,520 Speaker 1: of course there's a lot of that. There's a lot 613 00:34:56,560 --> 00:35:01,800 Speaker 1: of interest in this given that medical search is uniform 614 00:35:02,080 --> 00:35:07,719 Speaker 1: universally funded by mortals, right who and many of them 615 00:35:07,719 --> 00:35:12,319 Speaker 1: are are interested and possibly having more life to live 616 00:35:13,040 --> 00:35:16,319 Speaker 1: or if possible, you know, an infinite amount, right. So, 617 00:35:16,360 --> 00:35:19,160 Speaker 1: of course, because we don't want to age and grow 618 00:35:19,160 --> 00:35:22,880 Speaker 1: old and sag and wrinkle and and eventually die, scientists 619 00:35:22,920 --> 00:35:26,160 Speaker 1: are always working on ways to beat aging, and some 620 00:35:26,320 --> 00:35:30,480 Speaker 1: broad evolutionary mechanisms based on things like fruit fly research 621 00:35:30,560 --> 00:35:33,840 Speaker 1: are actually known. But unfortunately they're not the kind of 622 00:35:33,880 --> 00:35:38,040 Speaker 1: simple medical fixes that could like be ethically applied to humans. 623 00:35:38,080 --> 00:35:42,440 Speaker 1: They're they're evolutionary fixes that you couldn't really implement on purpose. 624 00:35:42,840 --> 00:35:45,360 Speaker 1: I mean you could in fruit flies, and researchers have, 625 00:35:46,000 --> 00:35:49,600 Speaker 1: so what are they Well, one would be low adult 626 00:35:49,680 --> 00:35:54,040 Speaker 1: mortality and high juvenile mortality if you get a bunch 627 00:35:54,080 --> 00:35:58,920 Speaker 1: of fruit flies and you create a scenario such that 628 00:35:59,040 --> 00:36:02,800 Speaker 1: adults tend to survive longer than they would in the wild, 629 00:36:03,360 --> 00:36:08,960 Speaker 1: while juveniles die very often. What actually happens is that 630 00:36:09,040 --> 00:36:12,759 Speaker 1: the life span and the reproductive lifespan of the fruit 631 00:36:12,800 --> 00:36:17,360 Speaker 1: flies increases over generations of evolution. And this kind of 632 00:36:17,400 --> 00:36:19,560 Speaker 1: makes sense, right if the if the mating pool is 633 00:36:19,680 --> 00:36:24,560 Speaker 1: limited to older individuals, genes that favor fitness in later 634 00:36:24,719 --> 00:36:30,480 Speaker 1: life will be selected for, and thus these would be 635 00:36:30,560 --> 00:36:33,600 Speaker 1: genes that prevent or delay aging, and they will become 636 00:36:33,600 --> 00:36:37,120 Speaker 1: more successful. Normally, evolution wouldn't care about those types of 637 00:36:37,200 --> 00:36:40,279 Speaker 1: genes very much. But of course we can't do this 638 00:36:40,320 --> 00:36:43,000 Speaker 1: to stop human aging unless we're prepared to like implement 639 00:36:43,000 --> 00:36:45,440 Speaker 1: a policy that only people over a certain age can 640 00:36:45,520 --> 00:36:49,160 Speaker 1: have children and then keep pushing the minimum age upwards. 641 00:36:49,160 --> 00:36:51,400 Speaker 1: Obviously we don't want to do that. Well, even in 642 00:36:51,480 --> 00:36:56,440 Speaker 1: scenarios like you know, periods of history in which there 643 00:36:56,520 --> 00:36:59,560 Speaker 1: is a high mortality rate for younger people, such as 644 00:36:59,640 --> 00:37:03,560 Speaker 1: during wars. Uh, it's still I don't think there's any 645 00:37:03,640 --> 00:37:05,440 Speaker 1: data to back of the idea that this would definitely 646 00:37:05,480 --> 00:37:09,640 Speaker 1: interfere with reproduction, because obviously there there are children that 647 00:37:10,000 --> 00:37:13,239 Speaker 1: grow up in the in the wake of war. Now 648 00:37:13,440 --> 00:37:18,359 Speaker 1: perhaps the father is not there anymore, but reproduction has 649 00:37:18,400 --> 00:37:21,040 Speaker 1: been initiated. But then that's a whole different area of study, 650 00:37:21,040 --> 00:37:24,280 Speaker 1: like the effects of war on reproduction and the health 651 00:37:24,360 --> 00:37:28,320 Speaker 1: of the resulting offspring. Um something we've touched on before 652 00:37:28,360 --> 00:37:31,080 Speaker 1: on the show, and we could easily revisit. Oh yeah, 653 00:37:31,080 --> 00:37:34,240 Speaker 1: that's all interesting stuff. Another thing to point out about 654 00:37:34,239 --> 00:37:37,000 Speaker 1: what I just mentioned about low adult mortality and high 655 00:37:37,040 --> 00:37:41,160 Speaker 1: juvenile mortality contributing to extended lifespans. We know this works 656 00:37:41,160 --> 00:37:45,640 Speaker 1: in fruit flies, but we can't predict other complicating factors 657 00:37:45,680 --> 00:37:49,160 Speaker 1: that might stop this from working another species. Though it 658 00:37:49,200 --> 00:37:52,200 Speaker 1: does appear to be pretty general that species that have 659 00:37:52,440 --> 00:37:57,719 Speaker 1: lower extrinsic mortality evolve longer lifespans. Like if you've got 660 00:37:57,760 --> 00:38:01,520 Speaker 1: good defense mechanisms against predators and disease, or if you 661 00:38:01,600 --> 00:38:04,000 Speaker 1: just happen to, say, end up on an island where 662 00:38:04,040 --> 00:38:07,760 Speaker 1: you don't have many predators or diseases, you will probably 663 00:38:07,880 --> 00:38:11,080 Speaker 1: evolve over a long period of time to breed longer 664 00:38:11,320 --> 00:38:14,840 Speaker 1: and live longer. Think about the great Wizzen tortoises of 665 00:38:14,840 --> 00:38:17,600 Speaker 1: the Galapagos. They've got a shell, they don't have really 666 00:38:17,880 --> 00:38:21,719 Speaker 1: natural predators, and they've got these long, long lifespans because 667 00:38:21,719 --> 00:38:25,040 Speaker 1: the adults and the old adults can just keep on breeding. 668 00:38:25,719 --> 00:38:27,640 Speaker 1: And they probably have, you know, a fair amount of moisture. 669 00:38:28,840 --> 00:38:32,839 Speaker 1: I think Aristotle was onto something. Yeah, no, they don't 670 00:38:32,840 --> 00:38:35,960 Speaker 1: have moisture at all. They look so dry. Those tortoises 671 00:38:35,960 --> 00:38:38,279 Speaker 1: are like the driest looking creatures I can think of, 672 00:38:38,360 --> 00:38:40,840 Speaker 1: But they live in a moist environment. Maybe that's it, 673 00:38:41,440 --> 00:38:44,640 Speaker 1: that is true, But okay, so looking at more like 674 00:38:44,719 --> 00:38:49,600 Speaker 1: potentially ethical medical fixes, are there things researchers are working 675 00:38:49,640 --> 00:38:52,400 Speaker 1: on in order to beat aging and humans? Well, the 676 00:38:52,400 --> 00:38:56,279 Speaker 1: answer is obviously yes. There are plenty of questions about 677 00:38:56,320 --> 00:39:00,640 Speaker 1: whether these projects are actually a good idea, and even 678 00:39:00,680 --> 00:39:02,840 Speaker 1: if they are a good idea, whether they could be 679 00:39:02,960 --> 00:39:06,759 Speaker 1: successful in principle, But there are plenty of people working 680 00:39:06,760 --> 00:39:09,120 Speaker 1: on it. One example, of course, is the gerontologist and 681 00:39:09,160 --> 00:39:11,560 Speaker 1: author Aubrey de Gray. He's made a whole career out 682 00:39:11,560 --> 00:39:14,440 Speaker 1: of the idea, going around promoting that we can and 683 00:39:14,480 --> 00:39:17,960 Speaker 1: should be trying to completely defeat the process of aging, 684 00:39:18,400 --> 00:39:22,160 Speaker 1: and that we can do it within the next few decades. Yeah, 685 00:39:22,320 --> 00:39:25,920 Speaker 1: he's everyone's probably seen images of de Gray before. He 686 00:39:25,920 --> 00:39:28,520 Speaker 1: has this big wizard's beard and he's resput and yeah, 687 00:39:28,560 --> 00:39:30,600 Speaker 1: he shows up in all sorts of he doesn't hate respute. 688 00:39:30,600 --> 00:39:33,719 Speaker 1: He shows up in various documentaries about this topic all 689 00:39:33,719 --> 00:39:37,560 Speaker 1: the time. Uh. And his his basic argument is, I think, 690 00:39:37,640 --> 00:39:40,880 Speaker 1: rather than genius, it's instead of viewing aging and death 691 00:39:41,000 --> 00:39:45,359 Speaker 1: as this unbeatable war, you know, this this unbeatable um 692 00:39:45,719 --> 00:39:49,280 Speaker 1: um problem, it's like, break it up into smaller battles, 693 00:39:49,360 --> 00:39:52,640 Speaker 1: smaller problems that you can win. You can solve. Yeah, 694 00:39:52,680 --> 00:39:56,000 Speaker 1: And I think this is the key appeal of his approach. 695 00:39:56,040 --> 00:40:00,200 Speaker 1: He says, aging is not one thing, it's maybe seven things. Us. 696 00:40:00,680 --> 00:40:03,080 Speaker 1: For instance, the problem might be cells die off and 697 00:40:03,120 --> 00:40:05,760 Speaker 1: are naturally replaced in the heart or in the brain, 698 00:40:06,040 --> 00:40:09,120 Speaker 1: and he says, well, use stem cell replacement for dying cells. 699 00:40:10,120 --> 00:40:12,759 Speaker 1: Or another example would be the body undergoes a proliferation 700 00:40:12,800 --> 00:40:15,400 Speaker 1: of unwanted cells, such as fat cells that replace muscle 701 00:40:15,440 --> 00:40:17,840 Speaker 1: and lead to diabetes. He says, we'll trick the problem 702 00:40:17,880 --> 00:40:21,399 Speaker 1: cells into self destruction through suicide, gene therapy, this sort 703 00:40:21,440 --> 00:40:25,360 Speaker 1: of thing. So it's it's taking taking the overall problem, 704 00:40:25,480 --> 00:40:28,479 Speaker 1: breaking it down into little individual problems that you could 705 00:40:28,480 --> 00:40:34,000 Speaker 1: potentially solve through medical intervention, genetic engineering, etcetera. Now, for 706 00:40:34,000 --> 00:40:37,000 Speaker 1: people who are interested in avoiding aging, obviously this message 707 00:40:37,080 --> 00:40:40,919 Speaker 1: is very appealing, Yes, but there are also we should 708 00:40:40,960 --> 00:40:45,360 Speaker 1: mention many researchers who find degrees program unrealistic, Like he 709 00:40:45,440 --> 00:40:48,319 Speaker 1: has plenty of critics. Well, on one level, it's kind 710 00:40:48,320 --> 00:40:52,239 Speaker 1: of the basic trans anti transhumanist argument, right like if okay, 711 00:40:52,280 --> 00:40:56,960 Speaker 1: if you break down essentially immortality into a number of 712 00:40:57,000 --> 00:41:00,839 Speaker 1: different treatment options that are available, then then who are 713 00:41:00,840 --> 00:41:04,320 Speaker 1: they available to who has access to these treatments. And 714 00:41:04,360 --> 00:41:08,160 Speaker 1: then it becomes this, uh, this this inequality situation where 715 00:41:08,360 --> 00:41:11,440 Speaker 1: you have the very dystopian idea of the super rich 716 00:41:11,440 --> 00:41:14,440 Speaker 1: individuals who can afford all of the various treatments that 717 00:41:14,440 --> 00:41:17,680 Speaker 1: that keep their unnatural lives going while the rest of 718 00:41:17,760 --> 00:41:20,160 Speaker 1: us simply live and die as always. I would say 719 00:41:20,160 --> 00:41:22,800 Speaker 1: the answer to that critique is not that you shouldn't 720 00:41:22,840 --> 00:41:26,040 Speaker 1: develop the medical technologies, but that you should find ways 721 00:41:26,080 --> 00:41:29,120 Speaker 1: to make them available to everyone. Then again, you do 722 00:41:29,200 --> 00:41:32,360 Speaker 1: have that intrinsic question of whether it's actually good to 723 00:41:32,480 --> 00:41:36,600 Speaker 1: allow any member of a species to be biologically immortal, uh, 724 00:41:36,640 --> 00:41:39,799 Speaker 1: to keep on living and consuming resources beyond what would 725 00:41:39,880 --> 00:41:43,120 Speaker 1: what would normally be allotted to them in a normal lifespan, Because, 726 00:41:43,600 --> 00:41:45,839 Speaker 1: as we talked about earlier on, there's this whole good 727 00:41:45,840 --> 00:41:48,279 Speaker 1: of the species argument. Your genes might not care about 728 00:41:48,280 --> 00:41:52,000 Speaker 1: the good of the species, but you should, right, we should. Well, 729 00:41:52,080 --> 00:41:54,080 Speaker 1: it's an easy argument for for for us to make. 730 00:41:54,120 --> 00:41:56,759 Speaker 1: But then again, we're not a hundred and fifty years 731 00:41:56,800 --> 00:41:59,640 Speaker 1: old and hooked up to the immortality machine. Right. Well, 732 00:41:59,680 --> 00:42:02,480 Speaker 1: once your time comes, you will probably change your tune. Right, 733 00:42:02,520 --> 00:42:04,440 Speaker 1: It's like, no, give me a little more. I just 734 00:42:04,480 --> 00:42:09,200 Speaker 1: need a little more one more yea um. But then again, yeah, 735 00:42:09,520 --> 00:42:11,640 Speaker 1: so that's like the question of whether we should be 736 00:42:11,680 --> 00:42:15,680 Speaker 1: trying to achieve biological immortality. There's also this question that 737 00:42:15,760 --> 00:42:18,480 Speaker 1: many scientists have have brought up, which is that his 738 00:42:18,560 --> 00:42:21,640 Speaker 1: program is unrealistic, not necessarily that it's a bad idea, 739 00:42:21,719 --> 00:42:25,680 Speaker 1: but that you you can't extend aging or not extend. 740 00:42:25,719 --> 00:42:28,800 Speaker 1: You can't extend youth forever. They're just gonna be hard 741 00:42:28,880 --> 00:42:31,960 Speaker 1: physical limits that you're gonna hit within the human body. 742 00:42:32,440 --> 00:42:35,000 Speaker 1: Just one example of that strain of thinking as a 743 00:42:35,040 --> 00:42:39,680 Speaker 1: paper that came out earlier this year in published by 744 00:42:39,680 --> 00:42:41,960 Speaker 1: the Proceedings of the National Academy of Science is called 745 00:42:42,280 --> 00:42:46,799 Speaker 1: Intercellular Competition and the Inevitability of Multicellular Agent. So this 746 00:42:46,840 --> 00:42:51,280 Speaker 1: study was conducted by UH scientists Joanna Massel and Paul Nelson, 747 00:42:51,760 --> 00:42:56,080 Speaker 1: and Massel and Nelson use mathematical models to argue that essentially, 748 00:42:56,120 --> 00:42:59,600 Speaker 1: no matter what you do, you will be faced with 749 00:42:59,719 --> 00:43:03,680 Speaker 1: one facet of aging or another, and the main tension 750 00:43:03,719 --> 00:43:09,040 Speaker 1: they highlight is tissue deterioration or cancer one or the other. 751 00:43:09,200 --> 00:43:12,680 Speaker 1: It's a mathematical inevitability. They say, if you find a 752 00:43:12,719 --> 00:43:17,280 Speaker 1: way to prevent cancer. Tissues deteriorate and cells become less efficient. 753 00:43:17,320 --> 00:43:20,200 Speaker 1: You get the body breaking down. If you find a 754 00:43:20,239 --> 00:43:23,920 Speaker 1: way to rejuvenate tissues, beef them up, make them youthful again, 755 00:43:24,280 --> 00:43:27,279 Speaker 1: you get cancer. Age is gonna get you one way 756 00:43:27,360 --> 00:43:30,480 Speaker 1: or another. It's like we're in that trolley car, right. 757 00:43:31,400 --> 00:43:35,279 Speaker 1: We have the tracks diverging to two unwanted fates in 758 00:43:35,280 --> 00:43:37,719 Speaker 1: a sense equally unwanted fates, and we have to try 759 00:43:37,760 --> 00:43:39,680 Speaker 1: and figure out, well, which way we're gonna go? What 760 00:43:39,719 --> 00:43:41,600 Speaker 1: are we going to plow into? I feel like this 761 00:43:41,600 --> 00:43:45,279 Speaker 1: should be reimagined as a myth, like going back to Tiffanus, 762 00:43:45,320 --> 00:43:50,480 Speaker 1: Like I want the gods gods that represent one represents 763 00:43:50,520 --> 00:43:54,960 Speaker 1: cancer and one represents the deterioration of body tissues, and 764 00:43:55,160 --> 00:43:57,960 Speaker 1: they're like at war and you have to choose between 765 00:43:58,000 --> 00:44:01,520 Speaker 1: your fate with one or the other. Uh I like that? Yeah, 766 00:44:01,600 --> 00:44:03,920 Speaker 1: this is this is where our modern day gods can 767 00:44:03,960 --> 00:44:07,080 Speaker 1: jump in and and provide us the story to make 768 00:44:07,120 --> 00:44:10,080 Speaker 1: sense of our our doom. Okay, well, I guess that 769 00:44:10,120 --> 00:44:12,600 Speaker 1: wraps it up for for part two of this episode 770 00:44:12,600 --> 00:44:16,120 Speaker 1: about why we age and why we can't have eternal youth. Yeah. Well, 771 00:44:16,160 --> 00:44:17,560 Speaker 1: and I don't want to leave it on too dark 772 00:44:17,600 --> 00:44:20,040 Speaker 1: of a note there with the whole doom talk, because 773 00:44:20,560 --> 00:44:26,040 Speaker 1: I mean, ultimately, I guess here's the here's the silver lining. Uh, Aging, 774 00:44:26,239 --> 00:44:29,880 Speaker 1: even dying, everybody does it. It couldn't be. It couldn't 775 00:44:29,880 --> 00:44:32,399 Speaker 1: be that much to it, right, look at the people 776 00:44:32,440 --> 00:44:34,520 Speaker 1: who do it. It It couldn't be. It couldn't be that difficult, 777 00:44:34,560 --> 00:44:36,440 Speaker 1: couldn't be that hard to go through. Well, I mean 778 00:44:36,800 --> 00:44:38,640 Speaker 1: it's easy to get down when you spend a lot 779 00:44:38,680 --> 00:44:41,520 Speaker 1: of time thinking about the inevitability of aging and death. 780 00:44:41,600 --> 00:44:45,040 Speaker 1: But um, I mean the thing to think about is, Yeah, 781 00:44:45,360 --> 00:44:47,480 Speaker 1: it comes to everybody. It's a part of life, and 782 00:44:47,560 --> 00:44:50,480 Speaker 1: there's a lot of life to love. Yeah, And it 783 00:44:50,600 --> 00:44:52,440 Speaker 1: bears reminding that there is a lot of stuff you 784 00:44:52,480 --> 00:44:55,520 Speaker 1: can do in the in the near future to make 785 00:44:55,560 --> 00:44:59,440 Speaker 1: your your far future a little more easy going. You know, 786 00:44:59,520 --> 00:45:03,399 Speaker 1: you can look after the body you have. You can uh, 787 00:45:03,440 --> 00:45:06,440 Speaker 1: you know, exercise and try to eat right. I think 788 00:45:06,480 --> 00:45:08,120 Speaker 1: I saw a study saying you need to eat a 789 00:45:08,120 --> 00:45:10,560 Speaker 1: bunch of chocolate to make it, and I think that's 790 00:45:10,600 --> 00:45:13,040 Speaker 1: what it was. Well, then that's the other side too, 791 00:45:13,160 --> 00:45:15,839 Speaker 1: is like you're gonna grow ahold, You're going to die. 792 00:45:15,920 --> 00:45:21,400 Speaker 1: You can't just spend your whole time worrying over that inevitability. 793 00:45:21,480 --> 00:45:23,480 Speaker 1: So you might as well have some chocolate. You might 794 00:45:23,520 --> 00:45:25,520 Speaker 1: as Oh no, I mean I was joking about those 795 00:45:25,600 --> 00:45:28,160 Speaker 1: articles that actually say chocolate will make you live longer. 796 00:45:28,280 --> 00:45:30,400 Speaker 1: Oh okay, not just the ones where there's like a 797 00:45:30,400 --> 00:45:33,840 Speaker 1: new study out that points to uh some beneficial quality 798 00:45:33,880 --> 00:45:37,560 Speaker 1: of like pure unsweetened chocolate. Uh yeah, I mean it's 799 00:45:37,640 --> 00:45:40,640 Speaker 1: it's always couched and like eat chocolate to be healthier. 800 00:45:40,760 --> 00:45:42,719 Speaker 1: Well if it's not couched in it. That's how I 801 00:45:42,719 --> 00:45:44,600 Speaker 1: think sometimes we interpret it. We read the study and 802 00:45:44,600 --> 00:45:46,680 Speaker 1: we're like, well, good, I like chocolate, or I like 803 00:45:46,719 --> 00:45:49,040 Speaker 1: red wine, or I like coffee, And now I can 804 00:45:49,080 --> 00:45:52,200 Speaker 1: just continue to enjoy the things that make my life 805 00:45:52,640 --> 00:45:55,239 Speaker 1: more bearable and uh and not worry about what they 806 00:45:55,320 --> 00:45:57,719 Speaker 1: might be doing too. Anytime you read an article about 807 00:45:57,760 --> 00:46:01,040 Speaker 1: the one silver bullet thing to eat or to drink 808 00:46:01,239 --> 00:46:05,400 Speaker 1: that will make you live forever, don't believe it. I agree, 809 00:46:05,600 --> 00:46:08,120 Speaker 1: unless that one silver bullet thing is the quickening which 810 00:46:08,160 --> 00:46:12,120 Speaker 1: will work. Can the quickening be transferred to another though 811 00:46:12,200 --> 00:46:16,360 Speaker 1: I'm a little shaky on on my my quickening science. 812 00:46:16,920 --> 00:46:18,480 Speaker 1: I don't know. We'll have to come back to that 813 00:46:18,640 --> 00:46:21,120 Speaker 1: what's the quickening conversion rate? I don't know. I think 814 00:46:21,120 --> 00:46:23,520 Speaker 1: you just have to be from the planet's ice, right remember? 815 00:46:25,200 --> 00:46:27,719 Speaker 1: All right, well there you go. Uh again, this was 816 00:46:27,760 --> 00:46:29,840 Speaker 1: a two parter. If somehow you made it through all 817 00:46:29,880 --> 00:46:31,960 Speaker 1: of part two without listening to part one, go back 818 00:46:32,000 --> 00:46:33,719 Speaker 1: and listen to part one. You will find it in 819 00:46:33,760 --> 00:46:35,759 Speaker 1: all other episodes of Stuff to Blow Your Mind at 820 00:46:35,800 --> 00:46:38,279 Speaker 1: Stuff to Blow your Mind dot Com, and you'll get 821 00:46:38,280 --> 00:46:41,640 Speaker 1: our moisture jokes. That's right. And hey, while you're stuff 822 00:46:41,640 --> 00:46:43,080 Speaker 1: to Blow your Mind dot Com, you will also find 823 00:46:43,160 --> 00:46:47,320 Speaker 1: links out to our various social media accounts such as Facebook, Twitter, Tumbler, 824 00:46:47,560 --> 00:46:49,560 Speaker 1: et cetera. And if you want to support our show, 825 00:46:50,000 --> 00:46:51,759 Speaker 1: you can visit that website and you can also just 826 00:46:52,160 --> 00:46:55,440 Speaker 1: leave us a rating, star rating, uh, textual rating, and 827 00:46:55,560 --> 00:46:59,080 Speaker 1: wherever you get your podcasts. 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