1 00:00:00,160 --> 00:00:03,760 Speaker 1: This episode of Stuff You Should Know is sponsored by Squarespace. 2 00:00:04,000 --> 00:00:06,520 Speaker 1: Whether you need a landing page, a beautiful gallery of 3 00:00:06,600 --> 00:00:10,039 Speaker 1: professional blogger, an online store, it's all possible with the 4 00:00:10,119 --> 00:00:14,080 Speaker 1: Squarespace website. Go to squarespace dot com and set your 5 00:00:14,160 --> 00:00:18,840 Speaker 1: website apart. Welcome to you Stuff you Should Know from 6 00:00:18,880 --> 00:00:27,480 Speaker 1: House Stuff Works dot com. Hey, and welcome to the podcast. 7 00:00:27,480 --> 00:00:31,360 Speaker 1: I'm Josh Clark, and there's Charles W Chuck Bryant. This 8 00:00:31,520 --> 00:00:34,960 Speaker 1: is Stuff you Should Know the podcast, not the least 9 00:00:34,960 --> 00:00:40,199 Speaker 1: of which is membered by Jerry. That was exciting. I 10 00:00:40,320 --> 00:00:44,840 Speaker 1: have a bad cold. Yeah, my brain is not functioning 11 00:00:44,920 --> 00:00:47,280 Speaker 1: quite right. Yeah, but this is not the old days 12 00:00:47,360 --> 00:00:52,040 Speaker 1: where you have the six weeks of cold. Right, Hopefully 13 00:00:52,040 --> 00:00:55,760 Speaker 1: this will be just a couple of episodes, right, bear 14 00:00:55,800 --> 00:00:58,600 Speaker 1: with us, yeah, bear, But to make up for it, 15 00:00:58,800 --> 00:01:02,760 Speaker 1: I have all my teeth finally, right. It's just this 16 00:01:03,080 --> 00:01:06,480 Speaker 1: constant pendulum, that's right, swings from one of us to 17 00:01:06,520 --> 00:01:09,520 Speaker 1: the other. Got all toothed up yesterday, feeling good. The 18 00:01:09,560 --> 00:01:12,560 Speaker 1: eight months is over. Like, click your teeth together for everybody, 19 00:01:12,640 --> 00:01:16,440 Speaker 1: I'm afraid to Okay, you're like they're precious. Yeah, I 20 00:01:16,440 --> 00:01:18,959 Speaker 1: gotta treat them very carefully and I got fitted for 21 00:01:19,120 --> 00:01:21,000 Speaker 1: a bite guard, so I when I grind my teeth 22 00:01:21,040 --> 00:01:25,000 Speaker 1: at night doesn't keep happening. So things are looking good. 23 00:01:25,680 --> 00:01:29,039 Speaker 1: Everything's coming up, Chuck. That's funny. Jumy has a bike 24 00:01:29,080 --> 00:01:32,520 Speaker 1: guard too, from grinding her teeth. So two of the 25 00:01:32,520 --> 00:01:35,200 Speaker 1: most significant people in my life on their teeth, both 26 00:01:35,240 --> 00:01:37,320 Speaker 1: kind on their teeth. Did she bought her fingernaut? I don't. 27 00:01:39,480 --> 00:01:42,000 Speaker 1: Does she bought her fingers? Yeah? I take out my 28 00:01:42,040 --> 00:01:45,240 Speaker 1: stresses on my body. Yeah, those are short nails. Do 29 00:01:45,319 --> 00:01:48,760 Speaker 1: they hurt? Do they just ache? Because sometimes if I 30 00:01:48,800 --> 00:01:50,720 Speaker 1: overdo it, they do. If I when I cut my 31 00:01:50,800 --> 00:01:53,120 Speaker 1: nails and I file them a little too short, they 32 00:01:53,160 --> 00:01:56,440 Speaker 1: just ache for a day or so afterward. Yeah. To 33 00:01:56,480 --> 00:01:59,840 Speaker 1: have it, I've always done it. Yeah, like since you 34 00:02:00,000 --> 00:02:04,520 Speaker 1: can remember. Yeah, I wore that bitter polish for a 35 00:02:04,520 --> 00:02:06,600 Speaker 1: while when I was a kid to try and I 36 00:02:06,680 --> 00:02:08,680 Speaker 1: just cheered right through it. Yeah. It was like, oh, 37 00:02:08,760 --> 00:02:11,360 Speaker 1: it's so better. Still must bite if I kind of 38 00:02:11,360 --> 00:02:13,120 Speaker 1: like it in a weird way. Yeah, the part of 39 00:02:13,120 --> 00:02:17,079 Speaker 1: me that hates myself loves that taste. So weird. Well, Chuck, 40 00:02:17,120 --> 00:02:20,360 Speaker 1: Let's talk about another habit, a habit that humans have 41 00:02:20,480 --> 00:02:23,160 Speaker 1: had for a very long time. Uh. And that is 42 00:02:23,200 --> 00:02:28,520 Speaker 1: the habit of using animals as models for humans, as 43 00:02:28,600 --> 00:02:31,560 Speaker 1: stand ins for humans when we want to test new things, 44 00:02:32,240 --> 00:02:35,080 Speaker 1: find out new things about ourselves, like will this kill me? 45 00:02:35,280 --> 00:02:38,320 Speaker 1: Let's put it on an animal, right, does the heart 46 00:02:38,480 --> 00:02:41,880 Speaker 1: or the lungs actually pump blood around the body. Let's 47 00:02:41,880 --> 00:02:44,760 Speaker 1: cut a dog open and find out that we've been 48 00:02:44,760 --> 00:02:46,760 Speaker 1: doing it for a very long time. Yeah, And this 49 00:02:46,880 --> 00:02:51,840 Speaker 1: article came with its own own intro story, which was 50 00:02:51,960 --> 00:02:54,040 Speaker 1: pretty interesting. I thought, Yeah, we haven't done one of 51 00:02:54,040 --> 00:02:55,400 Speaker 1: those in a long time. They used to be like 52 00:02:55,440 --> 00:02:58,480 Speaker 1: a standard aspect of this. Yeah. Now we just babble 53 00:02:58,680 --> 00:03:02,000 Speaker 1: the yeah. Yeah, we just share what's going on in 54 00:03:02,000 --> 00:03:04,799 Speaker 1: our lives or day pretty much. Sorry, everybody. It must 55 00:03:04,840 --> 00:03:06,840 Speaker 1: be a real letdown that I think about it. Should 56 00:03:06,840 --> 00:03:10,120 Speaker 1: we do this though? All right, Well, let's go back 57 00:03:10,160 --> 00:03:15,080 Speaker 1: in time, back to seven and there was a company 58 00:03:15,120 --> 00:03:19,000 Speaker 1: called a pharma company called S. E. Matson Gil out 59 00:03:19,000 --> 00:03:23,280 Speaker 1: of Tennessee, and they had a great, I almost want 60 00:03:23,280 --> 00:03:27,639 Speaker 1: to say, wonder drug. Uh. There was an antibiot antibiotic 61 00:03:27,680 --> 00:03:31,240 Speaker 1: that worked really well in its powdered form, and people 62 00:03:31,280 --> 00:03:33,880 Speaker 1: started clamoring and said, we love this stuff, but sure 63 00:03:33,880 --> 00:03:36,320 Speaker 1: it would be great if we could put it as 64 00:03:36,360 --> 00:03:39,400 Speaker 1: a as a drop under my tongue instead. Right, I 65 00:03:39,440 --> 00:03:42,320 Speaker 1: like liquids. I'm not big on powders like that weirdo 66 00:03:42,760 --> 00:03:45,800 Speaker 1: Richard Petty who just takes goodies powder like me. Love 67 00:03:45,880 --> 00:03:49,839 Speaker 1: that dude. That's my go to. It's got caffeine. That's 68 00:03:49,920 --> 00:03:53,480 Speaker 1: what helps. Yeah, for migraines too. Really, caffeine is a 69 00:03:53,480 --> 00:03:55,760 Speaker 1: big one. Yeah, Emily can't do them, but that it's 70 00:03:55,800 --> 00:03:58,720 Speaker 1: my I couldn't either. It's my hangover cure. I see that, 71 00:03:58,840 --> 00:04:02,360 Speaker 1: I say that out loud. Did Yeah it works, wonders. 72 00:04:02,360 --> 00:04:05,400 Speaker 1: I thought, bloody Mary's where you're hangover again? I'm not. 73 00:04:05,560 --> 00:04:07,200 Speaker 1: I'm not a hair of the dogger. That's what it 74 00:04:07,280 --> 00:04:10,960 Speaker 1: was inventive for, you know. Yeah, all right, I'm getting 75 00:04:10,960 --> 00:04:14,760 Speaker 1: a self check. I apologis. Uh. So they decided we 76 00:04:14,800 --> 00:04:17,320 Speaker 1: need a liquid form of this. What was the name 77 00:04:17,320 --> 00:04:21,680 Speaker 1: of the drug, uh, sul fannel man. I just had 78 00:04:21,720 --> 00:04:26,440 Speaker 1: it sulfanlu minde yes or stulf vanillamide. I think sulfanla 79 00:04:26,520 --> 00:04:28,520 Speaker 1: mind Okay, that's how I would say it if I 80 00:04:28,560 --> 00:04:31,920 Speaker 1: were in nineteen thirties seven Tennessee, and well, uh, they 81 00:04:31,960 --> 00:04:34,159 Speaker 1: had a chemist named Harold Cole Watkins who went to 82 00:04:34,200 --> 00:04:36,600 Speaker 1: the lab and said, all right, let's dissolve this stuff 83 00:04:36,640 --> 00:04:41,560 Speaker 1: and something called uh dieth eileen glycolthlen that one I 84 00:04:41,600 --> 00:04:44,800 Speaker 1: know worked pretty well. So they added a little raspberry 85 00:04:44,839 --> 00:04:47,560 Speaker 1: flavoring to make it palatable, and they said, it smells 86 00:04:47,560 --> 00:04:50,800 Speaker 1: pretty good, tastes pretty good, looks pretty good. Let's sell it. Yeah, 87 00:04:50,839 --> 00:04:53,520 Speaker 1: and they did. They sold a bunch of it, and 88 00:04:53,640 --> 00:04:56,320 Speaker 1: just like one one month after mixing up a batch 89 00:04:56,400 --> 00:04:59,760 Speaker 1: of the stuff, they had six thirty three shipments all 90 00:04:59,800 --> 00:05:02,279 Speaker 1: over of the country because there was a huge demand 91 00:05:02,279 --> 00:05:05,279 Speaker 1: for this, I mean, like syl sylfanum I was already 92 00:05:05,400 --> 00:05:07,800 Speaker 1: an established drug. The idea of it being in some 93 00:05:07,880 --> 00:05:12,440 Speaker 1: sort of palatable form that was gangbusters. Everybody had syphilis 94 00:05:12,440 --> 00:05:14,039 Speaker 1: that they needed to take care of back then, and 95 00:05:14,040 --> 00:05:16,279 Speaker 1: this kind of thing would help and if it could 96 00:05:16,320 --> 00:05:19,080 Speaker 1: be a pleasant experience, well then great. And then uh 97 00:05:19,120 --> 00:05:21,600 Speaker 1: that was September when they made their first shipment. Right 98 00:05:22,400 --> 00:05:26,040 Speaker 1: by October, middle of October October eleventh, to be specific, 99 00:05:26,600 --> 00:05:29,640 Speaker 1: a group of doctors in Tulsa contacted the a m A, 100 00:05:29,839 --> 00:05:33,960 Speaker 1: the American Medical Association, and said, um, we think there's 101 00:05:34,000 --> 00:05:36,719 Speaker 1: something really wrong with this new mass and guild product, 102 00:05:36,760 --> 00:05:40,359 Speaker 1: which they called Sulfanila Mind Elixir or a lixer of 103 00:05:40,400 --> 00:05:43,880 Speaker 1: sulfanal of mind. Um, we think it's killing people actually 104 00:05:43,920 --> 00:05:47,440 Speaker 1: and killing them in one of the worst ways imaginable. Yeah, 105 00:05:47,480 --> 00:05:51,040 Speaker 1: it wasn't a just go sleepy time. Now, it was 106 00:05:51,080 --> 00:05:53,600 Speaker 1: a pretty bad death. Right. You're writhing in agony, you're 107 00:05:53,600 --> 00:05:57,040 Speaker 1: probably puking your guts up. You're just you're dying from 108 00:05:57,040 --> 00:05:59,680 Speaker 1: from being poisoned. So the A M A got ahold 109 00:05:59,680 --> 00:06:01,200 Speaker 1: of some off and they said, you know what, the 110 00:06:01,240 --> 00:06:05,680 Speaker 1: actual drug is fine, but this, uh, the solution we 111 00:06:05,800 --> 00:06:08,160 Speaker 1: mix it with is the culprit. It is pure poison. 112 00:06:09,080 --> 00:06:12,520 Speaker 1: Who knew? Nobody knew. And the reason why no one 113 00:06:12,560 --> 00:06:16,760 Speaker 1: knew was because mass and Gill and Cole Watkins. Um there, 114 00:06:16,800 --> 00:06:20,200 Speaker 1: Harold Cole Watkins and his his group of chemists were 115 00:06:20,200 --> 00:06:22,960 Speaker 1: not obligated to test this stuff out. Yeah, well people 116 00:06:23,000 --> 00:06:25,960 Speaker 1: knew though. That was the one frustrating thing is studies 117 00:06:26,000 --> 00:06:28,839 Speaker 1: out that said this stuff was poison, and I guess 118 00:06:28,880 --> 00:06:31,960 Speaker 1: they just didn't read them right. They didn't research the literature, 119 00:06:31,960 --> 00:06:35,480 Speaker 1: which is a big deal. Um, But they also didn't 120 00:06:35,520 --> 00:06:39,359 Speaker 1: test it out on human or animal ahead of time. Uh. 121 00:06:39,400 --> 00:06:41,960 Speaker 1: And they again they just looked at the tech or 122 00:06:42,080 --> 00:06:44,880 Speaker 1: the appearance, the smell, a little bit of the taste, 123 00:06:45,200 --> 00:06:47,279 Speaker 1: but no one took a full dose of this apparently, 124 00:06:47,920 --> 00:06:50,520 Speaker 1: and um, people died. I think a hundred people died 125 00:06:50,560 --> 00:06:53,279 Speaker 1: in fifteen states in about a month or so before 126 00:06:53,279 --> 00:06:57,320 Speaker 1: they could get um the shipment's back. Yeah. I think 127 00:06:57,320 --> 00:07:01,880 Speaker 1: the FDA, the barely born f D A. Um, this 128 00:07:01,920 --> 00:07:04,400 Speaker 1: is one of its first actions was going and getting 129 00:07:04,400 --> 00:07:08,039 Speaker 1: this stuff. Yeah. And the president of the company said, uh, 130 00:07:08,200 --> 00:07:10,360 Speaker 1: you know, we haven't broken any laws because I guess 131 00:07:10,400 --> 00:07:13,000 Speaker 1: there weren't laws on the books at the time. And 132 00:07:13,080 --> 00:07:17,960 Speaker 1: the head chemist, um, very sadly killed himself because of this. Yeah. Um, 133 00:07:18,000 --> 00:07:21,400 Speaker 1: like the story goes from bad to worse and um, 134 00:07:21,440 --> 00:07:25,080 Speaker 1: that was pretty Japanese of him. Yeah you know, yeah, 135 00:07:25,120 --> 00:07:27,680 Speaker 1: we did. We do a full episode on that on 136 00:07:27,840 --> 00:07:32,000 Speaker 1: suicide on I mean Hardy Cary. But it had another 137 00:07:32,080 --> 00:07:34,360 Speaker 1: name too, right, Yeah, did we do that or did 138 00:07:34,360 --> 00:07:36,760 Speaker 1: we just mention it? I'm sure we just mentioned okay, 139 00:07:37,200 --> 00:07:41,840 Speaker 1: um yeah, I think in the Japanese Stragglers and probably 140 00:07:41,920 --> 00:07:46,600 Speaker 1: the samurai Yeah, and the revenge one. Yeah. Boy, it's 141 00:07:46,560 --> 00:07:49,640 Speaker 1: sorry to keep track these days, yeah, really really is. 142 00:07:50,040 --> 00:07:53,400 Speaker 1: So this led to a night Congress in the US 143 00:07:53,840 --> 00:07:57,720 Speaker 1: enacted the FDA Cosmetic Act, which said that you know what, 144 00:07:57,840 --> 00:08:00,920 Speaker 1: you need to test these drugs on animals, and that 145 00:08:01,240 --> 00:08:05,120 Speaker 1: therein sort of started, at least in the US, the 146 00:08:05,160 --> 00:08:08,600 Speaker 1: official like decree that you can and should do this, right, 147 00:08:08,800 --> 00:08:10,800 Speaker 1: But it has been going on a long time before that, 148 00:08:12,480 --> 00:08:14,760 Speaker 1: or Buddy Galen who we've talked about before, well even 149 00:08:14,800 --> 00:08:19,400 Speaker 1: further back than galen Um, if you look at the Greeks, 150 00:08:19,240 --> 00:08:23,080 Speaker 1: at least as far back as about five c UM. 151 00:08:23,360 --> 00:08:28,480 Speaker 1: The ancient Greeks were using animals for testing, poking around 152 00:08:28,920 --> 00:08:32,640 Speaker 1: figuring out how to how the human body works, and 153 00:08:32,640 --> 00:08:35,120 Speaker 1: there was this idea that there was an analogy between 154 00:08:35,880 --> 00:08:39,520 Speaker 1: all animals that humans shared like a lot of the 155 00:08:39,559 --> 00:08:41,840 Speaker 1: same physiology of all animals. And there was a great 156 00:08:42,240 --> 00:08:46,880 Speaker 1: disagreement among the Greeks in particular about whether that was true. 157 00:08:47,160 --> 00:08:52,560 Speaker 1: But it didn't stop guys like Aristotle Um and uh Aerosistratus, yeah, 158 00:08:52,600 --> 00:08:58,360 Speaker 1: and Hippocrates as well from basically poking around inside live animals, 159 00:08:58,360 --> 00:09:02,760 Speaker 1: which is the the where the term for animal testing 160 00:09:02,800 --> 00:09:07,120 Speaker 1: came from. The other terms vivisection. Vivisection is cutting something 161 00:09:07,120 --> 00:09:11,120 Speaker 1: open while it's still alive. Yes, specifically an animal, right 162 00:09:11,200 --> 00:09:15,319 Speaker 1: or is that no, you can vivisect humans, yeah, because 163 00:09:15,360 --> 00:09:20,679 Speaker 1: dissection occurs after death. Vivisection is like cutting open I 164 00:09:20,720 --> 00:09:25,520 Speaker 1: think technically surgery would be. But the idea behind vivisection 165 00:09:25,600 --> 00:09:30,400 Speaker 1: is that there's this is just for experimentation actually not 166 00:09:30,520 --> 00:09:33,440 Speaker 1: like let me heal that oregan right there, right, which, 167 00:09:33,520 --> 00:09:35,800 Speaker 1: by the way, go back and listen to our human 168 00:09:35,840 --> 00:09:38,679 Speaker 1: experimentation episode. That was a great one. I remember that one. 169 00:09:39,440 --> 00:09:42,960 Speaker 1: Uh So flash forward a bit to second century Rome 170 00:09:43,000 --> 00:09:46,480 Speaker 1: where our friend Galen, who we just talked about him 171 00:09:46,720 --> 00:09:49,880 Speaker 1: in a podcast Our lives stuff in UK and Ireland, 172 00:09:50,160 --> 00:09:55,000 Speaker 1: that's right, which hopefully people will hear him. Yes. Uh, 173 00:09:55,000 --> 00:09:59,800 Speaker 1: he was a medical specialist and he said, you know what, 174 00:09:59,840 --> 00:10:01,600 Speaker 1: I going to do a demonstration in the public. I'm 175 00:10:01,640 --> 00:10:04,800 Speaker 1: gonna rent a hall. Yeah, basically, I'm gonna get this 176 00:10:04,840 --> 00:10:09,280 Speaker 1: pig and I'm gonna prove that we are all a 177 00:10:09,280 --> 00:10:12,640 Speaker 1: bundle of nerves by snipping certain nerves of this pig. 178 00:10:13,160 --> 00:10:15,800 Speaker 1: You want to see him not squeal anymore, watch me 179 00:10:15,840 --> 00:10:19,160 Speaker 1: snip this nerve. And uh, it was all planned in 180 00:10:19,160 --> 00:10:23,640 Speaker 1: this philosophers, pretty popular guy. He had punching cookies out. 181 00:10:23,720 --> 00:10:26,840 Speaker 1: He was really excited for this day. Philosopher that was 182 00:10:26,840 --> 00:10:32,560 Speaker 1: in attendance named Alexander. Uh Demascenus, Yeah, Demastinus, one of 183 00:10:32,600 --> 00:10:35,840 Speaker 1: those two. He Um said, you know what this is, 184 00:10:36,080 --> 00:10:39,880 Speaker 1: bs Um, doesn't prove a thing. And in fact, none 185 00:10:39,880 --> 00:10:43,000 Speaker 1: of these demonstrations prove anything, because that's a pig and 186 00:10:43,040 --> 00:10:46,760 Speaker 1: we're humans. Why are you bothering? Right? And apparently the 187 00:10:46,880 --> 00:10:50,480 Speaker 1: Romans had adopted from the Greeks the idea that empirical 188 00:10:50,480 --> 00:10:55,520 Speaker 1: evidence didn't really prove anything. If you saw something, it 189 00:10:55,559 --> 00:10:58,640 Speaker 1: doesn't mean it was true, right, which is a weird philosophy. 190 00:10:58,640 --> 00:11:00,920 Speaker 1: I'd like to understand a little more. I'm sure there's 191 00:11:00,960 --> 00:11:03,280 Speaker 1: a lot more to it than that, but that's just 192 00:11:03,320 --> 00:11:06,400 Speaker 1: like such a completely radically different paradigm from what we 193 00:11:06,440 --> 00:11:09,680 Speaker 1: have now. Um, the paradigm of science we're seeing is indeed, 194 00:11:09,720 --> 00:11:13,559 Speaker 1: believing that it requires empirical evidence. Used to be the opposite, 195 00:11:13,720 --> 00:11:16,800 Speaker 1: And that was Alexander's big objection, like, hey man, you 196 00:11:16,840 --> 00:11:20,400 Speaker 1: can cut that pig's nerve all day long, and sure 197 00:11:20,440 --> 00:11:22,120 Speaker 1: I saw it, and sure it had that effect, but 198 00:11:22,120 --> 00:11:25,319 Speaker 1: it doesn't prove anything. And Galen was like, I hate you, 199 00:11:25,600 --> 00:11:29,360 Speaker 1: I hate that idea, I hate Aristotle. I'm leaving because 200 00:11:29,400 --> 00:11:34,440 Speaker 1: Aristotle was apparently somebody who said, Yeah, I've I've poked 201 00:11:34,440 --> 00:11:36,720 Speaker 1: around in a pig or two in my time, and 202 00:11:36,760 --> 00:11:38,920 Speaker 1: I've concluded that the heart and that the brain is 203 00:11:38,960 --> 00:11:42,320 Speaker 1: the center. This idea that a nerve connected to the 204 00:11:42,360 --> 00:11:45,920 Speaker 1: brain could control anything is hogwash, if you'll forgive the punt. 205 00:11:46,360 --> 00:11:52,120 Speaker 1: Aristotle is just a big dummy, the dumbest of them all. So, um, 206 00:11:52,520 --> 00:11:54,760 Speaker 1: Galen did, in fact say I'm leaving. He said, I'm 207 00:11:54,800 --> 00:11:57,240 Speaker 1: taking my medical bag and I'm going home. And then 208 00:11:57,280 --> 00:11:59,480 Speaker 1: everyone there was like, boa, I really want to see 209 00:11:59,480 --> 00:12:04,000 Speaker 1: this pig get cut apart. Please don't leave. He said, okay, 210 00:12:04,240 --> 00:12:08,160 Speaker 1: you guys, I'll do it. You twisted my arm, came 211 00:12:08,160 --> 00:12:12,120 Speaker 1: back in. Uh, performed the experiment in the demonstration, and 212 00:12:12,200 --> 00:12:16,680 Speaker 1: this was the one of the first recorded um examples 213 00:12:16,679 --> 00:12:20,440 Speaker 1: of experimenting on animals for science. Yeah, so the ball 214 00:12:20,520 --> 00:12:25,360 Speaker 1: was rolling. Yeah, And um, I don't know if Galen 215 00:12:25,440 --> 00:12:27,840 Speaker 1: hadn't done it first. And he he obviously hadn't done 216 00:12:27,840 --> 00:12:29,520 Speaker 1: it first because he came a few hundred years after 217 00:12:29,559 --> 00:12:32,679 Speaker 1: Aristotle who had done that. But if Aristotle hadn't done it, 218 00:12:32,920 --> 00:12:36,200 Speaker 1: eventually somebody who was curious enough would have grabbed a 219 00:12:36,240 --> 00:12:38,240 Speaker 1: dog or a chicken or something and just cut it 220 00:12:38,280 --> 00:12:41,040 Speaker 1: open and started looking at what was inside. Yeah, you know, 221 00:12:41,600 --> 00:12:43,200 Speaker 1: like it would have happened, but these are the people 222 00:12:43,240 --> 00:12:46,400 Speaker 1: who are recorded doing it first. Uh. Go forward in 223 00:12:46,440 --> 00:12:48,480 Speaker 1: time a bit to the late nineteenth century, and there 224 00:12:48,520 --> 00:12:54,280 Speaker 1: was a microbiologist from Germany, Robert Coke, and he got 225 00:12:54,800 --> 00:12:58,640 Speaker 1: he got some some anthrax. He got some blood from 226 00:12:58,679 --> 00:13:01,840 Speaker 1: cows killed by anthrax. Started looking at it under a 227 00:13:01,840 --> 00:13:04,080 Speaker 1: microscope and said, you know what, something in there looks 228 00:13:04,080 --> 00:13:08,040 Speaker 1: funny to me. That might be the anthrax. So let 229 00:13:08,040 --> 00:13:10,240 Speaker 1: me take that and put it in a mouse and 230 00:13:10,320 --> 00:13:13,800 Speaker 1: see what happens. The mouse died, and he said, I'm 231 00:13:13,840 --> 00:13:17,640 Speaker 1: onto something here. I'm pretty sure that was the anthrax. Uh, 232 00:13:18,040 --> 00:13:20,480 Speaker 1: A big deal. It was a big deal. Again, using 233 00:13:20,480 --> 00:13:24,839 Speaker 1: an animal to experiment in order to further human understanding 234 00:13:25,400 --> 00:13:27,920 Speaker 1: and protect human health in life, that's right. And those 235 00:13:27,960 --> 00:13:31,760 Speaker 1: are the big eats that people have used animals for. Yeah, 236 00:13:31,760 --> 00:13:35,760 Speaker 1: and that was actual, like medically, let me try and 237 00:13:37,000 --> 00:13:40,240 Speaker 1: cure a disease. Yeah, not like the early guys like whoa, 238 00:13:40,320 --> 00:13:43,640 Speaker 1: what is this? To what happens if I sever this? Yeah? 239 00:13:43,640 --> 00:13:49,720 Speaker 1: But it it went on my ancient Greek impression Um. 240 00:13:49,880 --> 00:13:51,360 Speaker 1: The point I was trying to make, I guess was 241 00:13:51,520 --> 00:13:55,200 Speaker 1: later on in the nineteen fifties, people started, and notably 242 00:13:55,240 --> 00:14:01,960 Speaker 1: this Russian Dmitri h Bell Jeff, started using research on animals, 243 00:14:02,880 --> 00:14:09,679 Speaker 1: not necessarily for curing diseases, but to study behavior. Right. Yeah, 244 00:14:09,720 --> 00:14:13,040 Speaker 1: we talked about them in our Animal Domestication episode. Yeah, 245 00:14:13,040 --> 00:14:15,719 Speaker 1: so what he he had the great idea for these 246 00:14:15,760 --> 00:14:18,320 Speaker 1: cute little silver foxes. He's like, I might like one 247 00:14:18,360 --> 00:14:20,640 Speaker 1: of those is a pet. I have a niece who 248 00:14:20,720 --> 00:14:22,960 Speaker 1: would love one of those. Man, have you seen those 249 00:14:23,000 --> 00:14:26,520 Speaker 1: fox videos or then crying and walk around crying well 250 00:14:26,640 --> 00:14:28,800 Speaker 1: or calling or whatever. And they shake their little tail 251 00:14:28,800 --> 00:14:31,120 Speaker 1: when you scratch their belly, and I don't know if 252 00:14:31,120 --> 00:14:33,040 Speaker 1: I've seen that one. It's very cute. It makes sort 253 00:14:33,040 --> 00:14:38,040 Speaker 1: of like a little purring, little chirpy purr and wiggle 254 00:14:38,160 --> 00:14:40,880 Speaker 1: their tail and wag their tail, and it's just like, oh, man, 255 00:14:41,160 --> 00:14:43,920 Speaker 1: you're the perfect combination of dog and cats. Foxes are 256 00:14:43,920 --> 00:14:47,520 Speaker 1: pretty cute, so we want to team them. Well, that's 257 00:14:47,560 --> 00:14:50,200 Speaker 1: exactly what he did too, And he thought, I know 258 00:14:50,280 --> 00:14:54,240 Speaker 1: that domestication usually takes many, many, many years, but let 259 00:14:54,240 --> 00:14:56,960 Speaker 1: me see if I can do it in like years 260 00:14:57,560 --> 00:15:00,400 Speaker 1: and Chuck. Speaking of behavioral studies, one of the most 261 00:15:00,440 --> 00:15:04,040 Speaker 1: famous of all using animals was Pavlov's dogs, And I 262 00:15:04,080 --> 00:15:07,360 Speaker 1: was researching it and I had no idea. Pavlov didn't 263 00:15:07,400 --> 00:15:10,960 Speaker 1: just like bring a bell for his dogs to make 264 00:15:11,000 --> 00:15:15,040 Speaker 1: him salivate. He surgically altered his dogs. He went and 265 00:15:15,080 --> 00:15:18,000 Speaker 1: got their salivary glands and put them on the outside 266 00:15:18,440 --> 00:15:21,520 Speaker 1: of their faces so that he could collect saliva samples 267 00:15:21,520 --> 00:15:25,600 Speaker 1: more easily. And he created remember that cow in Athens 268 00:15:25,640 --> 00:15:28,720 Speaker 1: that had a porthole in it, same thing for the dogs, 269 00:15:29,120 --> 00:15:33,240 Speaker 1: so that he could collect gastric juices digestive juices for 270 00:15:33,320 --> 00:15:35,280 Speaker 1: samples as well. So what you're saying is that he 271 00:15:35,320 --> 00:15:40,200 Speaker 1: was a crazy madman. Yeah, yeah, I guess so. I 272 00:15:40,520 --> 00:15:43,560 Speaker 1: think the larger point here is that humans have been 273 00:15:44,280 --> 00:15:47,600 Speaker 1: just grabbing animals or even breeding animals, for the sole 274 00:15:47,680 --> 00:15:51,360 Speaker 1: purpose of using them to understand things a little more, right, 275 00:15:51,800 --> 00:15:55,080 Speaker 1: whether it be cutting them open to see how anatomy works, 276 00:15:55,480 --> 00:15:59,800 Speaker 1: to using them as um as for medical experiments, to 277 00:16:00,000 --> 00:16:03,640 Speaker 1: de termined that um anthrax is actually blood borne and 278 00:16:03,800 --> 00:16:07,480 Speaker 1: can kill you. Um two behavioral studies, right, And we 279 00:16:07,480 --> 00:16:09,360 Speaker 1: should point out that at work he was able to 280 00:16:11,040 --> 00:16:14,920 Speaker 1: weed out and by weed out, I mean coal, and 281 00:16:14,960 --> 00:16:17,520 Speaker 1: by col we mean kill, and by kill we mean 282 00:16:17,920 --> 00:16:21,440 Speaker 1: probably break their necks. Yeah. I think that's one of 283 00:16:21,480 --> 00:16:24,520 Speaker 1: the big problems with with this talking about this stuff 284 00:16:24,640 --> 00:16:28,920 Speaker 1: is so many euphemisms are used, like you just you 285 00:16:29,080 --> 00:16:32,600 Speaker 1: just demonstrated so Um. What he did was he was 286 00:16:32,640 --> 00:16:34,840 Speaker 1: able to weed out the foxes that weren't his tame, 287 00:16:34,960 --> 00:16:37,400 Speaker 1: and eventually he ended up with the fox that was, 288 00:16:37,840 --> 00:16:41,880 Speaker 1: by all accounts domesticated, a nice little pet. It said, Dmitri. 289 00:16:42,800 --> 00:16:46,640 Speaker 1: You and it's not just animals, um, that are cute 290 00:16:46,840 --> 00:16:50,760 Speaker 1: that we contame. Um. Animals and what most people would 291 00:16:50,800 --> 00:16:53,960 Speaker 1: say are roughly the lower end of the spectrum as 292 00:16:54,000 --> 00:16:57,360 Speaker 1: far as life is concerned, are very frequently used, like 293 00:16:57,520 --> 00:17:02,200 Speaker 1: um nematodes, fruit flies, UM. They come into use largely 294 00:17:02,240 --> 00:17:07,240 Speaker 1: because they have some similar processes. Like if you're studying 295 00:17:07,320 --> 00:17:11,040 Speaker 1: a very ancient process or a very ancient part of 296 00:17:11,080 --> 00:17:15,000 Speaker 1: the body like um insulin regulation, that you're gonna find 297 00:17:15,040 --> 00:17:18,119 Speaker 1: it throughout the animal kingdom. It's gonna be pretty widespread. 298 00:17:18,520 --> 00:17:21,920 Speaker 1: So the idea is, if you can track insulin regulation 299 00:17:21,920 --> 00:17:26,240 Speaker 1: and a fruit fly, you could conceivably extrapolate those findings 300 00:17:26,320 --> 00:17:30,560 Speaker 1: onto a human and a humans insulin regulation. And the 301 00:17:30,560 --> 00:17:32,879 Speaker 1: advantage of a fruit fly or a nematode is that 302 00:17:32,880 --> 00:17:36,760 Speaker 1: they're really easy to breed and they reproduce very quickly. 303 00:17:37,640 --> 00:17:41,320 Speaker 1: So if you're like Dmitri BALLETV and you're studying foxes, 304 00:17:41,720 --> 00:17:44,920 Speaker 1: it took him twenty five years to go through twenty generations, 305 00:17:45,520 --> 00:17:48,440 Speaker 1: it would take you roughly a month, I would guess 306 00:17:48,480 --> 00:17:51,000 Speaker 1: to go through about twenty generations of fruit flies. So 307 00:17:51,040 --> 00:17:55,919 Speaker 1: therefore you can track mutations much more quickly, much more inexpensively. 308 00:17:56,320 --> 00:18:00,840 Speaker 1: So UM, the fruit flies, the humatodes, other again lesser 309 00:18:01,080 --> 00:18:05,200 Speaker 1: life forms UM have been used extensively in medical testing 310 00:18:05,200 --> 00:18:07,600 Speaker 1: as well. And they and they count, they qualify. It's 311 00:18:07,640 --> 00:18:12,400 Speaker 1: a live organism that's being used for experimentation purposes. Yeah, 312 00:18:12,440 --> 00:18:14,840 Speaker 1: and uh, it kind of depends on what you're trying, 313 00:18:14,920 --> 00:18:17,399 Speaker 1: what your aim is, what your goal is, to what 314 00:18:17,560 --> 00:18:20,200 Speaker 1: animal you do use, because you can't just use any 315 00:18:20,240 --> 00:18:23,280 Speaker 1: animal for anything. UM. And here's a fun fact. I 316 00:18:23,320 --> 00:18:28,080 Speaker 1: did not know that the armadillo is an animal that 317 00:18:28,119 --> 00:18:31,000 Speaker 1: can actually get Hanson's disease a k A. Leprosy. We 318 00:18:31,080 --> 00:18:32,960 Speaker 1: knew that we talked about in the leprosy episode. I 319 00:18:32,960 --> 00:18:36,280 Speaker 1: don't remember mentioning the armadillo. I am scared to death 320 00:18:36,440 --> 00:18:38,960 Speaker 1: of armadillos now because of really oh yeah, when I 321 00:18:38,960 --> 00:18:41,159 Speaker 1: see it, I just look at him like leprosy. You 322 00:18:41,160 --> 00:18:43,600 Speaker 1: don't hug him on any longer, you know, and like 323 00:18:43,600 --> 00:18:45,280 Speaker 1: you'll see him on the side of the road, you know, 324 00:18:45,760 --> 00:18:48,000 Speaker 1: hit by a car or something like that. Texas, I 325 00:18:48,040 --> 00:18:51,400 Speaker 1: always double check, um. Well here in Georgia too, Yeah, 326 00:18:51,440 --> 00:18:54,200 Speaker 1: a little bit. Um. I always check to make sure 327 00:18:54,240 --> 00:18:56,960 Speaker 1: that my air recirculator is on when I pass them by. 328 00:18:57,040 --> 00:19:00,280 Speaker 1: That like the leprosy didn't waft into my car as 329 00:19:00,359 --> 00:19:04,560 Speaker 1: I drove past the roadkill that I was damaged by 330 00:19:04,600 --> 00:19:08,760 Speaker 1: the leprosy episode. Uh well, they actually have the perfect 331 00:19:08,800 --> 00:19:15,000 Speaker 1: body temperature to allow study on vaccines for leprosy. Um 332 00:19:15,040 --> 00:19:17,240 Speaker 1: And speaking of by the way, I'm sorry to interrupt you, 333 00:19:17,280 --> 00:19:21,720 Speaker 1: but I just found out last night that koalas Carrie 334 00:19:21,800 --> 00:19:25,840 Speaker 1: chlamydia really and transmitted sexually and can die from it. 335 00:19:26,040 --> 00:19:29,040 Speaker 1: Oh man, yeah, and are actually partially endangered in some 336 00:19:29,080 --> 00:19:33,320 Speaker 1: ways because they have chlamydia. M think about that next 337 00:19:33,359 --> 00:19:35,760 Speaker 1: time you want to hug from that cute little critter, 338 00:19:36,240 --> 00:19:39,800 Speaker 1: you know, well, they'll tear your face off too. Uh. 339 00:19:40,280 --> 00:19:43,040 Speaker 1: Should we take a little break here, all right, let's 340 00:19:43,040 --> 00:19:44,880 Speaker 1: take a break and we're kind of we're gonna come 341 00:19:44,880 --> 00:19:48,880 Speaker 1: back and talk more about the different animals used and 342 00:19:49,040 --> 00:20:10,040 Speaker 1: why Chuck. Before we get back to I want to 343 00:20:10,080 --> 00:20:13,720 Speaker 1: say this is UM this this episode and the other 344 00:20:13,760 --> 00:20:18,159 Speaker 1: one that's coming out Thursday. Yeah, and they're kind of 345 00:20:18,200 --> 00:20:22,240 Speaker 1: done in conjunction with these guys, UM Joe and Tim 346 00:20:22,320 --> 00:20:26,880 Speaker 1: who run a site called primer Stories dot com and 347 00:20:27,080 --> 00:20:31,560 Speaker 1: UM they do seasons. They're like animators, um web dudes, 348 00:20:32,400 --> 00:20:35,640 Speaker 1: and it shows they know what they're doing and they've 349 00:20:35,680 --> 00:20:38,800 Speaker 1: basically taken They'll they'll take essays. I wrote an essay, 350 00:20:38,960 --> 00:20:40,920 Speaker 1: then they take it and they break it up into 351 00:20:41,000 --> 00:20:43,720 Speaker 1: chunks and they animate it. Right, so as you're going 352 00:20:43,840 --> 00:20:48,880 Speaker 1: scrolling down, you're you're reading, but you're also experiencing, um, 353 00:20:49,800 --> 00:20:54,000 Speaker 1: the the art, the animation that really kind of brings 354 00:20:54,040 --> 00:20:57,679 Speaker 1: out the ideas of each one. It's really really neat site. 355 00:20:57,960 --> 00:21:02,920 Speaker 1: They they contacted us after our San Francisco show last year, 356 00:21:03,280 --> 00:21:06,080 Speaker 1: you know, early this year, and UM, they said, hey, 357 00:21:06,080 --> 00:21:07,879 Speaker 1: do you want to do one of these? And I 358 00:21:07,920 --> 00:21:10,840 Speaker 1: went and looked and I was amazed and said, yes, 359 00:21:10,960 --> 00:21:13,880 Speaker 1: I totally do. So you can go, UM check out 360 00:21:14,000 --> 00:21:16,560 Speaker 1: the s A I wrote at a primer stories dot 361 00:21:16,600 --> 00:21:18,840 Speaker 1: com slash s y s K and that one is 362 00:21:18,880 --> 00:21:22,240 Speaker 1: the one we're releasing after this one. Correct, Well, it 363 00:21:22,280 --> 00:21:24,679 Speaker 1: ties into both. It's it's kind of this essay about 364 00:21:25,119 --> 00:21:30,080 Speaker 1: UM humans changing attitude toward animal rights. But it was 365 00:21:30,080 --> 00:21:32,480 Speaker 1: fun to do and they're cool. They're cool dudes for sure, 366 00:21:32,480 --> 00:21:34,399 Speaker 1: and I like what they're doing. UM. This is the 367 00:21:34,560 --> 00:21:40,879 Speaker 1: fourth season, fourth season, nice plug, nice work. Thanks all right. 368 00:21:40,960 --> 00:21:44,960 Speaker 1: So we were talking about UM using different animals and 369 00:21:45,000 --> 00:21:49,439 Speaker 1: how if it's you know, fruit fly or a nematode, 370 00:21:49,520 --> 00:21:52,760 Speaker 1: people don't get their hackles up too much. No, it's true. UM, 371 00:21:52,800 --> 00:21:56,200 Speaker 1: if it is a rat or a mouse, people start 372 00:21:56,200 --> 00:21:59,320 Speaker 1: getting their hackles up a little more. UM and mice 373 00:21:59,400 --> 00:22:04,119 Speaker 1: are very famously used. A lot um of our genes 374 00:22:04,200 --> 00:22:08,399 Speaker 1: overlap with this mouse. UM specifically this one, which is 375 00:22:08,400 --> 00:22:15,000 Speaker 1: it mouse or amuse genus mice mices genus mice, So 376 00:22:15,040 --> 00:22:18,080 Speaker 1: that's the one that they use most often that has 377 00:22:18,119 --> 00:22:23,000 Speaker 1: the overlap UH, and their cell structure and organ organization 378 00:22:23,040 --> 00:22:27,160 Speaker 1: are basically the same as ours, so UM they do 379 00:22:27,200 --> 00:22:29,199 Speaker 1: a lot of testing with these mice as a result, 380 00:22:29,960 --> 00:22:34,240 Speaker 1: everything from you know, disease and stuff to genetics. Two 381 00:22:34,240 --> 00:22:38,280 Speaker 1: behavioral that they kind of run the gamut right on mice, Yeah, 382 00:22:38,280 --> 00:22:41,760 Speaker 1: for sure, and from that point up they tend to, 383 00:22:41,840 --> 00:22:43,720 Speaker 1: I think, run the gamut. Some are a little more 384 00:22:43,720 --> 00:22:47,879 Speaker 1: specific than others, like beagles apparently. Yeah, really come in 385 00:22:47,920 --> 00:22:54,680 Speaker 1: handy when you're testing prostate cancer um or muscular dystrophy both. Yeah. Um, 386 00:22:54,720 --> 00:22:58,960 Speaker 1: because they can contract those or develop those, so they 387 00:22:59,000 --> 00:23:03,200 Speaker 1: make great and mole models. Yeah. The these cats because 388 00:23:03,680 --> 00:23:07,080 Speaker 1: their site and they're hearing and their balance. I have 389 00:23:07,160 --> 00:23:11,600 Speaker 1: to ask, how are you feeling right now about this episode? Well, 390 00:23:11,640 --> 00:23:15,440 Speaker 1: what do you mean like about the topic? Uh? Because 391 00:23:15,440 --> 00:23:17,480 Speaker 1: you're holding it together really well? You mean I'm not 392 00:23:17,520 --> 00:23:22,760 Speaker 1: crying yet? Yeah? Yeah, I've checked my emotions out of 393 00:23:22,760 --> 00:23:26,800 Speaker 1: this one. I think this two parts sweet will get 394 00:23:27,359 --> 00:23:31,720 Speaker 1: points across. I'm just relying on that. I'll get weepy 395 00:23:31,800 --> 00:23:37,200 Speaker 1: later tonight. Do you remember the Secret of Nim? Yeah? Sure, 396 00:23:37,400 --> 00:23:39,440 Speaker 1: I had forgotten what the secret was, or I don't 397 00:23:39,440 --> 00:23:41,320 Speaker 1: think it ever dawned on me what the secret really 398 00:23:41,359 --> 00:23:43,400 Speaker 1: wasn't I went back and was reading about the those 399 00:23:43,400 --> 00:23:47,240 Speaker 1: were mice, right, there were rats and the secret of Nim. 400 00:23:47,320 --> 00:23:50,320 Speaker 1: Well we probably shouldn't say, would that be a spoiler? Yeah? 401 00:23:50,320 --> 00:23:53,000 Speaker 1: I think so it's like the spoiler, like that's in 402 00:23:53,040 --> 00:23:55,560 Speaker 1: the title. What if the secret of nim was that 403 00:23:56,200 --> 00:23:58,520 Speaker 1: Bruce Willis in the Sixth Sense was dead all along? 404 00:24:00,520 --> 00:24:02,280 Speaker 1: You know what I think was an even Wait is 405 00:24:02,280 --> 00:24:05,399 Speaker 1: that a spoiler? Yeah? I think it was. It was 406 00:24:05,520 --> 00:24:08,280 Speaker 1: years ago at least. If you haven't seen the sixth 407 00:24:08,320 --> 00:24:11,879 Speaker 1: Cents by now, t s for you go see the others, 408 00:24:11,920 --> 00:24:15,560 Speaker 1: though a lot of people haven't seen the others. Sixth Sense, 409 00:24:16,160 --> 00:24:19,200 Speaker 1: the one thing cool Kidman, that was good Man. That 410 00:24:19,320 --> 00:24:25,320 Speaker 1: was great, very atmospheric Moody film, that one. And the Orphanage. Yeah, yeah, 411 00:24:25,520 --> 00:24:28,840 Speaker 1: it's fantastic. The Orphanage is maybe even the better of 412 00:24:28,840 --> 00:24:34,840 Speaker 1: the two. Yeah. Yeah. Uh So monkeys primates, um, well, 413 00:24:34,920 --> 00:24:38,879 Speaker 1: non human primates, we should say, specifically, the maccaque monkey 414 00:24:38,960 --> 00:24:41,880 Speaker 1: is used a lot because there, uh there's a lot 415 00:24:41,920 --> 00:24:44,800 Speaker 1: of them, and they're widely distributed and uh have a 416 00:24:44,880 --> 00:24:48,680 Speaker 1: robust population. So you know, they made a lot of 417 00:24:48,720 --> 00:24:53,680 Speaker 1: advances into neuroscience thanks to the maccaque monkey. And then, um, 418 00:24:53,800 --> 00:24:57,000 Speaker 1: there's some animals that will just do because they contain flesh, 419 00:24:57,280 --> 00:25:00,320 Speaker 1: like pigs and goats are used a lot, and what's 420 00:25:00,359 --> 00:25:03,879 Speaker 1: called live tissue trauma training, which is exactly what it 421 00:25:03,920 --> 00:25:08,639 Speaker 1: sounds like. Um, it's used to train battlefield medics in 422 00:25:08,680 --> 00:25:13,719 Speaker 1: the military. Uh, and the Coast Guard apparently, and um 423 00:25:13,760 --> 00:25:19,439 Speaker 1: the animals innesthetized deeply to like surgical plane levels and 424 00:25:19,640 --> 00:25:26,800 Speaker 1: um shot or blown up or um just weird stuff 425 00:25:26,960 --> 00:25:30,879 Speaker 1: done to it to stimulate a battlefield trauma so that 426 00:25:31,480 --> 00:25:35,160 Speaker 1: medic can do live what it's called live tissue trauma training, 427 00:25:35,240 --> 00:25:37,560 Speaker 1: so they can save a life on the battlefield. Yeah, 428 00:25:37,600 --> 00:25:40,920 Speaker 1: but then they euthanize the they kill the animal afterward. 429 00:25:41,119 --> 00:25:43,600 Speaker 1: But yes, on the battlefield. That's the whole I mean, 430 00:25:43,640 --> 00:25:46,280 Speaker 1: that's the whole point there. And they're saying there's no 431 00:25:46,359 --> 00:25:50,000 Speaker 1: substitute for that, well, which is sort of the what 432 00:25:50,119 --> 00:25:54,080 Speaker 1: they scientists and doctors say. Well, well we'll get into 433 00:25:54,119 --> 00:25:57,400 Speaker 1: all that, okay. Uh. One thing we should mention though, 434 00:25:57,440 --> 00:26:00,600 Speaker 1: is that if you look for labels say this was 435 00:26:00,640 --> 00:26:03,560 Speaker 1: not tested on animals. Uh, it's sort of like the 436 00:26:03,600 --> 00:26:08,800 Speaker 1: whole free range chicken myth. Um, it's not exactly what 437 00:26:08,840 --> 00:26:12,399 Speaker 1: you think it is, right, Well, free range chickens, it 438 00:26:12,440 --> 00:26:15,200 Speaker 1: doesn't have to have like a porch attached to the structure. 439 00:26:15,320 --> 00:26:17,040 Speaker 1: They don't even have to have access to it, and 440 00:26:17,160 --> 00:26:19,399 Speaker 1: you just have to have the door open so they 441 00:26:19,400 --> 00:26:22,399 Speaker 1: can leave if they want. Um. But you have people 442 00:26:22,440 --> 00:26:24,919 Speaker 1: have images I think of these chickens running around the fields, 443 00:26:25,280 --> 00:26:28,040 Speaker 1: idyllic countryside. Yeah, but they don't they they're in the 444 00:26:28,080 --> 00:26:30,040 Speaker 1: barn where the food is and they kind of don't leave. 445 00:26:30,080 --> 00:26:32,320 Speaker 1: But the doors they are, so they're technically free range 446 00:26:33,400 --> 00:26:35,680 Speaker 1: unless something's changed. When I worked in the chicken industry, 447 00:26:36,040 --> 00:26:39,000 Speaker 1: those sad that sad year or whatever it was, I 448 00:26:39,040 --> 00:26:42,159 Speaker 1: would guess absolutely nothing's changed. Probably so, But if you 449 00:26:42,160 --> 00:26:45,119 Speaker 1: look for labels to say cruelty free or not tested 450 00:26:45,160 --> 00:26:48,240 Speaker 1: on animals, it may not mean what you think because 451 00:26:48,840 --> 00:26:52,560 Speaker 1: technically there's no oversight on a label like that, and 452 00:26:52,600 --> 00:26:56,359 Speaker 1: it could mean that we did not in the final 453 00:26:56,440 --> 00:26:59,959 Speaker 1: product of this cosmetic tested on animals. We didn't tell 454 00:27:00,040 --> 00:27:04,000 Speaker 1: us this rouge, but all the raw ingredients that went 455 00:27:04,080 --> 00:27:07,960 Speaker 1: into this from our suppliers were tested on animals. Or 456 00:27:08,200 --> 00:27:11,200 Speaker 1: back in the sixties or seventies, they tested these same 457 00:27:11,320 --> 00:27:13,919 Speaker 1: ingredients on animals, and there's no need for us to 458 00:27:13,960 --> 00:27:17,679 Speaker 1: test them again. So now we can say not tested 459 00:27:17,680 --> 00:27:21,400 Speaker 1: on animals even though these things, right, these things were 460 00:27:21,440 --> 00:27:25,480 Speaker 1: tested on animals years back. UM, And actually China has 461 00:27:25,560 --> 00:27:29,320 Speaker 1: changed things recently, as um, the West was getting further 462 00:27:29,359 --> 00:27:33,120 Speaker 1: and further away. I think the EU banned imports of 463 00:27:33,119 --> 00:27:38,240 Speaker 1: of anything that have been tested on animals cosmetics wise. Um, 464 00:27:38,280 --> 00:27:41,600 Speaker 1: and China has gone the opposite direction. It is mandated 465 00:27:41,920 --> 00:27:45,360 Speaker 1: that anything important into China cosmetics wise must have been 466 00:27:45,400 --> 00:27:49,119 Speaker 1: tested on animals. So kind of reset things here in 467 00:27:49,119 --> 00:27:51,239 Speaker 1: the West because there's a lot of Western companies like 468 00:27:51,840 --> 00:27:54,320 Speaker 1: I want in on that Chinese market, and China saying well, 469 00:27:54,320 --> 00:27:56,919 Speaker 1: you got to test your like, the whole thing on 470 00:27:57,160 --> 00:28:02,919 Speaker 1: animals before it comes in here. Interest thing. Uh So 471 00:28:03,040 --> 00:28:07,840 Speaker 1: here's the deal. Over the twentieth century, Um, we've made 472 00:28:07,840 --> 00:28:10,719 Speaker 1: a lot of medical advances. Life expectancy, this is kind 473 00:28:10,720 --> 00:28:14,280 Speaker 1: of a neat stat has gone up about three months 474 00:28:15,160 --> 00:28:19,240 Speaker 1: per year in the twentieth century, largely due to stuff 475 00:28:19,280 --> 00:28:23,800 Speaker 1: like this testing for disease. Well, yeah, people who are 476 00:28:23,840 --> 00:28:27,480 Speaker 1: advocates of animal testing say that would not have happened 477 00:28:28,040 --> 00:28:32,440 Speaker 1: maybe at all, had we not used animals. And life 478 00:28:32,480 --> 00:28:37,920 Speaker 1: expectancy was extended three months a year from I think 479 00:28:37,960 --> 00:28:40,600 Speaker 1: like eighteen forty to two thousand six or something like 480 00:28:40,640 --> 00:28:45,520 Speaker 1: that every year. UM. And and that was advanced by 481 00:28:46,280 --> 00:28:50,280 Speaker 1: finding things like antibiotics and vaccines, and all of the 482 00:28:50,360 --> 00:28:54,160 Speaker 1: things that um not just extend the human life, but 483 00:28:54,560 --> 00:28:59,720 Speaker 1: make the the extended years more enjoyable as well more healthy. UM. 484 00:28:59,760 --> 00:29:04,520 Speaker 1: And that's a huge rallying cry for people who point 485 00:29:04,560 --> 00:29:07,360 Speaker 1: to animal testing and say this is this is necessary 486 00:29:07,400 --> 00:29:09,760 Speaker 1: and has to continue. And actually there is a two 487 00:29:09,760 --> 00:29:13,720 Speaker 1: thousand eleven poll of biomedical researchers by Nature, which is 488 00:29:13,760 --> 00:29:16,480 Speaker 1: no slouch of a scientific journal, and they found that 489 00:29:17,320 --> 00:29:21,720 Speaker 1: agreed with the the sentence use of animals in research 490 00:29:21,880 --> 00:29:26,800 Speaker 1: is essential. There's two eleven. So that's not that sentiment 491 00:29:26,840 --> 00:29:30,640 Speaker 1: isn't going anywhere. No, I think that's probably pretty much accurate. Today. 492 00:29:31,520 --> 00:29:33,720 Speaker 1: On the other side of the coin, you have animal 493 00:29:33,920 --> 00:29:37,120 Speaker 1: rights activists and and even if you're not an activist, 494 00:29:37,200 --> 00:29:41,080 Speaker 1: just your average Joe on the street or Jane UM 495 00:29:41,280 --> 00:29:43,960 Speaker 1: might say, you know what, this is unethical. Uh does 496 00:29:44,040 --> 00:29:47,360 Speaker 1: a lot of harm, it's wasteful, and there are better 497 00:29:47,400 --> 00:29:49,920 Speaker 1: ways to do it. In fact, some people say it's 498 00:29:49,920 --> 00:29:53,320 Speaker 1: not even doing the job that it should be doing. 499 00:29:53,680 --> 00:29:56,960 Speaker 1: For instance, Uh, they can cure cancer and mice, and 500 00:29:57,040 --> 00:29:58,400 Speaker 1: we have been able to do this for a while, 501 00:29:58,840 --> 00:30:03,240 Speaker 1: can't cure it in humans. UM. Of the HIV AIDS 502 00:30:03,360 --> 00:30:08,240 Speaker 1: vaccines that were tested uh successfully on primates, they don't 503 00:30:08,240 --> 00:30:10,360 Speaker 1: work on humans, and one of them may have even 504 00:30:10,560 --> 00:30:15,320 Speaker 1: made humans more susceptible. Yeah yeah, so it's uh, you know, 505 00:30:15,360 --> 00:30:18,840 Speaker 1: there's two very strong sides to this argument. The f 506 00:30:18,960 --> 00:30:22,200 Speaker 1: d A has said that nine tenths of all drugs 507 00:30:22,200 --> 00:30:27,440 Speaker 1: and development don't work in humans after they worked in 508 00:30:27,480 --> 00:30:30,280 Speaker 1: animals because you just can't tell, right, And actually I 509 00:30:30,600 --> 00:30:32,760 Speaker 1: looked that up there. It's it's a little bit of 510 00:30:32,760 --> 00:30:38,200 Speaker 1: a fallacy. It's more like fail in clinical trials. But 511 00:30:38,800 --> 00:30:42,960 Speaker 1: that's all pre clinical trials that so not just animal 512 00:30:42,960 --> 00:30:46,000 Speaker 1: testing but also non animal testing where it passed that 513 00:30:46,160 --> 00:30:49,480 Speaker 1: the first stages when it made it to clinical trials, 514 00:30:49,480 --> 00:30:54,080 Speaker 1: of all drugs failed to work or actually harmed humans. 515 00:30:54,360 --> 00:30:56,640 Speaker 1: There's another side of the coin, though, too, Chuck, how 516 00:30:56,640 --> 00:30:59,080 Speaker 1: many sides are on this coin. There's it's like one 517 00:30:59,120 --> 00:31:01,200 Speaker 1: of those hundreds to die that you see a D 518 00:31:01,240 --> 00:31:04,360 Speaker 1: and D but never know how to use. Um. There 519 00:31:04,360 --> 00:31:08,360 Speaker 1: are probably a lot of drugs out there that harmed 520 00:31:08,400 --> 00:31:13,120 Speaker 1: animals and were shelved right then didn't make it into 521 00:31:13,120 --> 00:31:15,520 Speaker 1: clinical trials because the animals were harmed, that may not 522 00:31:15,600 --> 00:31:18,760 Speaker 1: have harmed humans that actually could have cured things. So 523 00:31:18,800 --> 00:31:20,960 Speaker 1: there's people saying no, we we we need to be 524 00:31:21,000 --> 00:31:25,120 Speaker 1: testing on humans because we're using this for humans. That's 525 00:31:25,200 --> 00:31:30,600 Speaker 1: that's what some some prob I guess protesters against animal 526 00:31:30,680 --> 00:31:33,960 Speaker 1: testing would say. And then, um, another thing that I 527 00:31:34,000 --> 00:31:37,080 Speaker 1: saw is that you you tend to think like, Okay, well, 528 00:31:37,480 --> 00:31:41,240 Speaker 1: it's advancing science, so I can't really get in the 529 00:31:41,280 --> 00:31:46,680 Speaker 1: way of that. But there are One of the critiques 530 00:31:46,720 --> 00:31:50,479 Speaker 1: of that argument is not all the science is is good, 531 00:31:50,640 --> 00:31:53,400 Speaker 1: that's being done and like a lot of animal lives. 532 00:31:53,400 --> 00:31:58,400 Speaker 1: If you agree that animal lives are are valuable, and 533 00:31:58,760 --> 00:32:01,920 Speaker 1: but that use seeing an animal life to advance scientific 534 00:32:02,000 --> 00:32:05,640 Speaker 1: understanding to protect human health and life is worthy, it's 535 00:32:05,680 --> 00:32:09,600 Speaker 1: a worthy use of an animal, then that you would 536 00:32:09,640 --> 00:32:12,520 Speaker 1: also probably agree with the idea that wasting the animal's 537 00:32:12,560 --> 00:32:17,240 Speaker 1: life and scientific testing is unforgivable. Right. So there was 538 00:32:17,280 --> 00:32:19,880 Speaker 1: a survey in two thousand nine p l OS one 539 00:32:20,240 --> 00:32:23,080 Speaker 1: Proceedings of the Library of Science one, the Journal of 540 00:32:23,080 --> 00:32:27,200 Speaker 1: two one Animal Studies. I found that forty one percent 541 00:32:27,360 --> 00:32:30,680 Speaker 1: failed to even state hypothesis are objective to the tests 542 00:32:31,560 --> 00:32:36,440 Speaker 1: umtent failed to describe the statistic methods used uh in 543 00:32:36,560 --> 00:32:41,840 Speaker 1: the study, didn't randomize scent, didn't use blinding, and those 544 00:32:41,840 --> 00:32:45,680 Speaker 1: are basic scientific efforts that you have to make in 545 00:32:45,760 --> 00:32:50,160 Speaker 1: any experiment, right, those are very basic um, which means 546 00:32:50,200 --> 00:32:53,000 Speaker 1: that those things were wasted, which means those animals lives 547 00:32:53,000 --> 00:32:56,440 Speaker 1: were wasted. And the suggestion is is that a lot 548 00:32:56,520 --> 00:33:01,160 Speaker 1: of publicly funded science is just not very good science 549 00:33:01,760 --> 00:33:05,200 Speaker 1: and it's wasting the lives of the animals involved. Well, 550 00:33:05,200 --> 00:33:08,560 Speaker 1: that's sad. I'm starting to get emotional. Okay, all right, 551 00:33:08,640 --> 00:33:11,280 Speaker 1: let's take a break then and we'll come back and 552 00:33:11,800 --> 00:33:14,480 Speaker 1: talk a little bit about our old buddy, Charles D 553 00:33:15,120 --> 00:33:38,040 Speaker 1: Chuck D. Darwin. Alright, so I teased everybody with Charles Darwin. 554 00:33:38,720 --> 00:33:40,840 Speaker 1: Oh is that who you're talking about? Which is what 555 00:33:40,880 --> 00:33:43,040 Speaker 1: I do every Halloween. I dress up as Charles Darwin 556 00:33:43,080 --> 00:33:46,360 Speaker 1: and tease the local teens. Oh what are you going 557 00:33:46,400 --> 00:33:48,800 Speaker 1: to dress up as for our show in d C 558 00:33:49,480 --> 00:33:52,400 Speaker 1: on October twenty night. I don't know, but I'm glad 559 00:33:52,400 --> 00:33:54,880 Speaker 1: you mentioned that, because we're doing a show at the 560 00:33:54,920 --> 00:33:58,200 Speaker 1: Lincoln Theater and we're turning it into a Halloween ball. 561 00:33:58,280 --> 00:34:02,040 Speaker 1: It's a Halloween bash, not even a ball. Yeah, it's 562 00:34:02,080 --> 00:34:06,440 Speaker 1: a wrong above the ball, including a reading of a 563 00:34:07,160 --> 00:34:09,399 Speaker 1: of a Halloween story like we do just for their 564 00:34:09,400 --> 00:34:12,160 Speaker 1: ears only. Yeah, Plus we'll be dressed up. We're encouraging 565 00:34:12,200 --> 00:34:15,000 Speaker 1: everyone who comes to be dressed up. Maybe I'll go 566 00:34:15,000 --> 00:34:16,719 Speaker 1: to Charles Darwin. And as far as I know, it's 567 00:34:16,719 --> 00:34:19,640 Speaker 1: an all ages show, but it could get spooky and 568 00:34:19,640 --> 00:34:22,360 Speaker 1: our shows do get a little blue. So just f y, 569 00:34:22,360 --> 00:34:25,520 Speaker 1: I you've been worn So Charles Darwin, who I made 570 00:34:25,600 --> 00:34:27,840 Speaker 1: dress up as I've got. I'm pretty sure I know 571 00:34:27,880 --> 00:34:30,920 Speaker 1: what I'm going as I'd rather not reveal it at 572 00:34:31,080 --> 00:34:33,960 Speaker 1: the time. Um, he was kind of in on this 573 00:34:34,000 --> 00:34:37,840 Speaker 1: game a long time ago, and he was he loved animals, 574 00:34:38,680 --> 00:34:42,319 Speaker 1: but he also wanted to study animals, but he also 575 00:34:42,360 --> 00:34:46,200 Speaker 1: wanted to treat them humanly while he studied animals. Sounds 576 00:34:47,200 --> 00:34:51,600 Speaker 1: sounds like Charles Darwin kind of approach. Yes. Uh So 577 00:34:51,719 --> 00:34:55,760 Speaker 1: there was a eight seventy four there was like people 578 00:34:55,800 --> 00:34:57,960 Speaker 1: were actually starting to get in trouble for some of 579 00:34:58,000 --> 00:35:01,200 Speaker 1: these things. Uh. In eighteen seven, any for these scientists 580 00:35:01,520 --> 00:35:04,920 Speaker 1: were actually put on trial for torturing dogs because they 581 00:35:04,920 --> 00:35:09,720 Speaker 1: wanted to see how absent and alcohol affected their nervous system. 582 00:35:09,760 --> 00:35:12,840 Speaker 1: So they cut them open and exposed them to these liquids. 583 00:35:12,920 --> 00:35:15,719 Speaker 1: They just dowsed them, And is what I what I'm 584 00:35:15,760 --> 00:35:18,640 Speaker 1: taking from I have no idea, I guess, so they're 585 00:35:18,640 --> 00:35:21,319 Speaker 1: actually acquitted. But um, it sort of brought things into 586 00:35:21,360 --> 00:35:26,040 Speaker 1: the UH in the front of everyone's minds and Darwin. 587 00:35:27,280 --> 00:35:28,880 Speaker 1: People were saying, let's not do this at all, and 588 00:35:28,960 --> 00:35:31,000 Speaker 1: Darwin stepped in and said he was a little more 589 00:35:31,000 --> 00:35:32,799 Speaker 1: moderate and said, you know what, let's craft a bill 590 00:35:32,880 --> 00:35:35,640 Speaker 1: here in the United Kingdom where you can do this, 591 00:35:36,360 --> 00:35:41,560 Speaker 1: but do it humanely. And that resulted in the Cruelty 592 00:35:41,600 --> 00:35:46,480 Speaker 1: to Animals Act of eight. It's pretty great. It was advancement, 593 00:35:47,440 --> 00:35:50,239 Speaker 1: it was, but the UK actually has long led the 594 00:35:50,239 --> 00:35:53,680 Speaker 1: way in the West for animal rights. Um, even even 595 00:35:53,760 --> 00:35:57,560 Speaker 1: before that, as we'll see, they they were trying to 596 00:35:57,600 --> 00:36:00,120 Speaker 1: protect animals, as we'll see in the next episod So 597 00:36:00,480 --> 00:36:03,520 Speaker 1: that's right. And then a little later in ur the 598 00:36:03,680 --> 00:36:07,239 Speaker 1: University's Federation of Animal Welfare said, let's get these two 599 00:36:07,320 --> 00:36:13,000 Speaker 1: dudes zoologist and a microbiologist, Russell and Birch, and just 600 00:36:13,160 --> 00:36:14,920 Speaker 1: do a lot of research, guys, and come back with 601 00:36:15,000 --> 00:36:18,719 Speaker 1: some findings that we can use. And boy did they. Yeah. 602 00:36:18,800 --> 00:36:22,560 Speaker 1: They they were like, there's a lot better that we 603 00:36:22,600 --> 00:36:27,480 Speaker 1: can do in protecting animals. They um, scientists are typically 604 00:36:27,560 --> 00:36:31,000 Speaker 1: dumb and can only remember things through a literation. So 605 00:36:31,080 --> 00:36:34,000 Speaker 1: these guys came up with the three RS, something that 606 00:36:34,040 --> 00:36:36,680 Speaker 1: could be put on a p s a poster um. 607 00:36:36,719 --> 00:36:39,239 Speaker 1: The three RS. I'm just teasing about the scientist thing, 608 00:36:39,680 --> 00:36:44,040 Speaker 1: our replacement, reduction and refinement. Right, yes, so your first 609 00:36:44,080 --> 00:36:48,720 Speaker 1: goal is to to find a replacement of the animal. 610 00:36:49,000 --> 00:36:54,640 Speaker 1: Is there any alternative to the animal in this experiment? Yeah, well, like, uh, 611 00:36:54,960 --> 00:36:57,520 Speaker 1: a sentient animal with a not like with a worm 612 00:36:57,560 --> 00:37:01,480 Speaker 1: perhaps instead of a mouse, or you know, if you 613 00:37:01,520 --> 00:37:05,879 Speaker 1: can find uh willing robot. Right, you know that it's 614 00:37:05,920 --> 00:37:09,440 Speaker 1: the bill. The second one's reduction. You want to reduce 615 00:37:09,520 --> 00:37:13,239 Speaker 1: the number of animals used to the absolute minimum. You 616 00:37:13,280 --> 00:37:16,720 Speaker 1: don't want to have any spare bang utangs hanging around. 617 00:37:17,200 --> 00:37:20,280 Speaker 1: You want to know how many you're gonna use, and uh, 618 00:37:20,640 --> 00:37:24,960 Speaker 1: those are the ones that you can kill. Correct and 619 00:37:25,000 --> 00:37:29,160 Speaker 1: then finally refine, which means and and this is you know, 620 00:37:29,480 --> 00:37:31,200 Speaker 1: sort of the opposite of what you were talking about 621 00:37:31,200 --> 00:37:34,920 Speaker 1: with those awful stats that you said, like, let's refine 622 00:37:34,960 --> 00:37:38,359 Speaker 1: this and at least get your technique down. Uh so 623 00:37:38,400 --> 00:37:42,240 Speaker 1: well that the suffering is minimized to its bare minimum 624 00:37:42,239 --> 00:37:46,200 Speaker 1: as well the waste is reduced. Yeah yeah, Um, and 625 00:37:46,360 --> 00:37:50,000 Speaker 1: that that uh, that was nine that Russell and Birch 626 00:37:50,120 --> 00:37:53,160 Speaker 1: released the three RS. This is two thousand nine. That 627 00:37:53,160 --> 00:37:59,000 Speaker 1: that one study I cited was conducted years later. So, uh, Peter, 628 00:37:59,680 --> 00:38:02,160 Speaker 1: you know the people for the Ethical Treatment of Animals, 629 00:38:02,200 --> 00:38:03,960 Speaker 1: We've talked about them quite a bit on the show. 630 00:38:04,520 --> 00:38:07,440 Speaker 1: They are down with the three RS, of course, but 631 00:38:07,600 --> 00:38:10,000 Speaker 1: they say, you know what, that's not enough, though. We 632 00:38:10,040 --> 00:38:13,040 Speaker 1: have a lot of studies that show that they're way 633 00:38:13,120 --> 00:38:17,360 Speaker 1: better ways of doing things these days than using animals 634 00:38:18,040 --> 00:38:20,920 Speaker 1: with the computer modeling that we have now and software 635 00:38:21,360 --> 00:38:25,440 Speaker 1: and humans. Yeah, and um, they're they've figured out techniques 636 00:38:25,560 --> 00:38:32,200 Speaker 1: using stem cells um to grow organs or organs cells 637 00:38:32,800 --> 00:38:37,040 Speaker 1: or like say, skin cells in vitro, and then exposing 638 00:38:37,040 --> 00:38:39,640 Speaker 1: them to the chemicals you want to test, and then 639 00:38:39,800 --> 00:38:43,719 Speaker 1: not only will you have your reaction or non reaction, 640 00:38:44,160 --> 00:38:47,480 Speaker 1: you'll also have it with like a human human cells. 641 00:38:48,200 --> 00:38:50,799 Speaker 1: So it's not like, oh, it messed this rabbits face 642 00:38:50,920 --> 00:38:53,919 Speaker 1: up pretty bad. Well, we'll just assume that it will 643 00:38:54,080 --> 00:38:56,320 Speaker 1: mess up a human skin as well. It's you know, 644 00:38:56,520 --> 00:38:59,440 Speaker 1: this stuff really burned through that that human skin tissue 645 00:38:59,480 --> 00:39:01,600 Speaker 1: that we sent the sized, So now we know for 646 00:39:01,680 --> 00:39:05,440 Speaker 1: sure not to give it to humans. There's also something 647 00:39:05,480 --> 00:39:08,759 Speaker 1: called because a big objection to that is well, that's 648 00:39:08,760 --> 00:39:10,959 Speaker 1: just a it's a skin. It's a group of skin 649 00:39:11,040 --> 00:39:14,160 Speaker 1: cells in vitro that doesn't really replicate you know, these 650 00:39:14,200 --> 00:39:18,280 Speaker 1: really intricate interplays that make up organs and systems of organs. 651 00:39:18,880 --> 00:39:21,279 Speaker 1: And there's a company out called um OH. I don't 652 00:39:21,280 --> 00:39:23,680 Speaker 1: remember what they're called, but their invention is organ on 653 00:39:23,760 --> 00:39:27,879 Speaker 1: a chip. It's amazing, dude. I watched this video about 654 00:39:27,920 --> 00:39:32,279 Speaker 1: it last night, which that's the only way it could 655 00:39:32,320 --> 00:39:34,560 Speaker 1: be better. It's if you could eat it afterwards, but 656 00:39:34,600 --> 00:39:37,040 Speaker 1: it'd be pretty messed up if you did so. It's 657 00:39:37,080 --> 00:39:41,520 Speaker 1: like a USB stick size module. That's the word I'm 658 00:39:41,520 --> 00:39:45,759 Speaker 1: going with. It's transparent and um say, the long on 659 00:39:45,880 --> 00:39:51,160 Speaker 1: a chip has some branching stuff, and inside there is 660 00:39:51,560 --> 00:39:57,080 Speaker 1: a layer of um lung cells and the that replicate 661 00:39:57,640 --> 00:40:02,120 Speaker 1: and simulate human lung So you have human lung cells 662 00:40:02,120 --> 00:40:04,360 Speaker 1: growing in the and arranged in the way that they 663 00:40:04,360 --> 00:40:07,520 Speaker 1: would in the human lung. And then the this device 664 00:40:07,600 --> 00:40:10,400 Speaker 1: allows you to pass air over the top and blood 665 00:40:10,400 --> 00:40:14,480 Speaker 1: over the top and introduce bacteria and introduce white blood 666 00:40:14,480 --> 00:40:18,480 Speaker 1: cells and study what they do. So you're replicating the 667 00:40:18,520 --> 00:40:23,160 Speaker 1: function of a human lung on this little thing, which 668 00:40:23,200 --> 00:40:26,680 Speaker 1: is all simulation. It is, but it's a real simulation, 669 00:40:26,800 --> 00:40:29,840 Speaker 1: Like it's it's using real lung cells and they're functioning 670 00:40:29,880 --> 00:40:33,040 Speaker 1: like a lung normally would, except you don't have to 671 00:40:33,320 --> 00:40:34,799 Speaker 1: you don't have to use it. You don't have to 672 00:40:34,800 --> 00:40:37,839 Speaker 1: say here and and inhale this. We'll just pass this 673 00:40:38,160 --> 00:40:42,000 Speaker 1: antibiotic across the lung cells and it will treat it 674 00:40:42,040 --> 00:40:46,200 Speaker 1: like the human lung would. It's amazing. And then yeah, 675 00:40:46,239 --> 00:40:48,399 Speaker 1: if you could eat it afterwards, eat the human lung 676 00:40:48,400 --> 00:40:52,640 Speaker 1: cells with some guacamali, you'd be like this, this is 677 00:40:52,800 --> 00:40:55,400 Speaker 1: the circle of life is complete. Well, that's sort of 678 00:40:55,480 --> 00:40:57,120 Speaker 1: one of the big points so that Peter and a 679 00:40:57,120 --> 00:41:00,440 Speaker 1: lot of organizations uses that we're we're so vans now 680 00:41:00,480 --> 00:41:03,720 Speaker 1: with our computer modeling and these simulations that they're actually 681 00:41:03,960 --> 00:41:08,080 Speaker 1: they are better ways than like it's sort of archaic 682 00:41:08,120 --> 00:41:11,000 Speaker 1: to experiment on an animal like these are not only 683 00:41:11,160 --> 00:41:15,120 Speaker 1: cruelty free, but it's smarter and better, Right, that's the 684 00:41:15,200 --> 00:41:18,479 Speaker 1: argument they make. Yeah, and I mean the statistics cut 685 00:41:18,560 --> 00:41:21,879 Speaker 1: both ways. Like if you look at Peter's stats, they're 686 00:41:21,920 --> 00:41:27,520 Speaker 1: like animal models are predictive. It's in this dismal range 687 00:41:27,840 --> 00:41:31,280 Speaker 1: right for you know, human outcomes, and then the people 688 00:41:31,280 --> 00:41:33,640 Speaker 1: who are in favor of animal testing stay, well, these 689 00:41:33,800 --> 00:41:37,000 Speaker 1: these computer models are actually the ones that have dismal results. 690 00:41:37,600 --> 00:41:40,360 Speaker 1: So both sides. I guess it's just too new, maybe 691 00:41:40,440 --> 00:41:43,840 Speaker 1: it's unproven. Yeah, but there does seem to be a 692 00:41:43,920 --> 00:41:48,839 Speaker 1: movement a foot in uh bio medicine to replace as 693 00:41:48,920 --> 00:41:54,600 Speaker 1: much as possible computer models with animals with computer models. Yeah. Uh. 694 00:41:54,760 --> 00:41:57,680 Speaker 1: Some of the other things that animal rights groups lobby for, 695 00:41:57,960 --> 00:42:01,120 Speaker 1: things like, well how about you do like CT scans 696 00:42:01,200 --> 00:42:03,760 Speaker 1: or m r s you're not actually harming the animal, 697 00:42:04,560 --> 00:42:08,040 Speaker 1: or this thing called micro dosing where you actually give 698 00:42:08,120 --> 00:42:13,080 Speaker 1: humans just very very small doses of these medicines that 699 00:42:13,600 --> 00:42:16,520 Speaker 1: won't be enough to hurt them if things don't work out, 700 00:42:16,840 --> 00:42:18,800 Speaker 1: but you could tell if it's going to be effective 701 00:42:18,880 --> 00:42:21,120 Speaker 1: or not. Yeah, it still produces that reaction on a 702 00:42:21,120 --> 00:42:23,440 Speaker 1: molecular level. It's just not going to have a system 703 00:42:23,520 --> 00:42:27,000 Speaker 1: wide toxic effect on it. That's pretty that's pretty neat. 704 00:42:27,800 --> 00:42:33,560 Speaker 1: Um and and they're there. There's some change, but at 705 00:42:33,560 --> 00:42:37,400 Speaker 1: the same time there's also um some digging in on 706 00:42:37,400 --> 00:42:39,839 Speaker 1: on both sides as well, Like, for example, with that 707 00:42:39,960 --> 00:42:44,000 Speaker 1: live tissue trauma training. Um, there was a there's a 708 00:42:44,040 --> 00:42:49,360 Speaker 1: movement to replace uh, any live animal with a dummy 709 00:42:49,520 --> 00:42:52,120 Speaker 1: or a mannequin or something like that. And the people 710 00:42:52,160 --> 00:42:55,080 Speaker 1: who are proponents of using animals and live tissue trauma 711 00:42:55,120 --> 00:42:58,200 Speaker 1: training say, man, there's something that can happen to a 712 00:42:58,200 --> 00:43:02,279 Speaker 1: battlefield medic during common at and that's called freezing. When 713 00:43:02,280 --> 00:43:05,959 Speaker 1: they're presented with a human being with you know, a 714 00:43:06,000 --> 00:43:09,200 Speaker 1: major trauma, they can just sit there and freeze and 715 00:43:09,239 --> 00:43:11,440 Speaker 1: freak out because this is the first time they've been 716 00:43:11,480 --> 00:43:14,360 Speaker 1: exposed to it. One of the aspects of you know, 717 00:43:14,520 --> 00:43:17,239 Speaker 1: blowing the leg off of a pig is that this 718 00:43:17,320 --> 00:43:19,239 Speaker 1: person is having to work on a pig. And yeah, 719 00:43:19,239 --> 00:43:21,320 Speaker 1: it's a pig, but it's a live pig. It's not 720 00:43:21,440 --> 00:43:25,920 Speaker 1: a right exactly, and maybe they made they made the 721 00:43:25,960 --> 00:43:27,920 Speaker 1: person care for the pig for like a week first, 722 00:43:27,920 --> 00:43:30,279 Speaker 1: so that it has even more Well, I just made 723 00:43:30,320 --> 00:43:32,319 Speaker 1: that up, but you could you could see how the 724 00:43:32,880 --> 00:43:35,720 Speaker 1: how that would like that would be tough to replace. 725 00:43:35,800 --> 00:43:38,319 Speaker 1: That's a tough one to argue with. But I think 726 00:43:38,440 --> 00:43:41,160 Speaker 1: ultimately the question is race chuck um, And this is 727 00:43:41,200 --> 00:43:44,239 Speaker 1: what we're gonna address in the next episode. Is is 728 00:43:44,239 --> 00:43:48,200 Speaker 1: probably the largest question of all and is do humans 729 00:43:48,239 --> 00:43:52,279 Speaker 1: have or have humans ever had the right to use 730 00:43:52,480 --> 00:43:57,239 Speaker 1: animals for our own means? And that's uh, we'll talk 731 00:43:57,280 --> 00:43:59,759 Speaker 1: about that one on the next episode. Boy, that's a 732 00:43:59,840 --> 00:44:03,319 Speaker 1: nice cliffhanger, I think, so too well done. Do we 733 00:44:03,480 --> 00:44:05,400 Speaker 1: have listener mail this one? Yeah? And you know what, 734 00:44:05,480 --> 00:44:07,879 Speaker 1: not only that, we have a two part listener mail 735 00:44:08,000 --> 00:44:11,400 Speaker 1: awesome that has its own cliffhanger. Man. All right, well, 736 00:44:11,480 --> 00:44:13,160 Speaker 1: let's get to it. So if you want to know 737 00:44:13,280 --> 00:44:16,440 Speaker 1: more about animal testing, you can type that word in 738 00:44:16,480 --> 00:44:18,480 Speaker 1: the search part how stuff works dot com and it 739 00:44:18,520 --> 00:44:21,879 Speaker 1: will bring up this excellent article. And since I said 740 00:44:21,920 --> 00:44:25,399 Speaker 1: search bar, it's time for part one of listener Mail. 741 00:44:27,440 --> 00:44:31,440 Speaker 1: That's right. This one was so robust. It's an unprecedented 742 00:44:31,480 --> 00:44:37,920 Speaker 1: to part from Evan, not Ivan, but Evan, will you 743 00:44:37,960 --> 00:44:40,960 Speaker 1: grow up to be a good man? I hope? So 744 00:44:41,080 --> 00:44:44,080 Speaker 1: now that's Levi on. Oh yeah, well the else silent 745 00:44:44,920 --> 00:44:47,440 Speaker 1: um and those were weren't the right words anyway, but 746 00:44:47,480 --> 00:44:52,280 Speaker 1: it's adorable. All right, here we go. First off, guys, 747 00:44:52,280 --> 00:44:54,520 Speaker 1: gotta say you're not only my favorite podcast, but you're 748 00:44:54,520 --> 00:44:57,840 Speaker 1: also my ten year old son's favorite podcast. Listen to 749 00:44:57,880 --> 00:45:01,680 Speaker 1: every episode at least twice how about that. And my 750 00:45:01,719 --> 00:45:03,839 Speaker 1: son is also a big fan of your TV show 751 00:45:03,880 --> 00:45:07,680 Speaker 1: and the animated shorts why they're in deep. However, my 752 00:45:07,719 --> 00:45:11,919 Speaker 1: beautiful fiance is not. In fact, there have been times 753 00:45:11,960 --> 00:45:15,160 Speaker 1: when I will be sitting next to her and she's 754 00:45:15,200 --> 00:45:17,680 Speaker 1: reading a book and I'll have my headphones listening to 755 00:45:17,719 --> 00:45:20,600 Speaker 1: the podcast so I don't disturb her, and I'll burst 756 00:45:20,640 --> 00:45:23,879 Speaker 1: out laughing like a crazy person. In her words, uh 757 00:45:23,920 --> 00:45:27,920 Speaker 1: this quote crazy end quote. Behavior of mine is directly 758 00:45:28,520 --> 00:45:31,799 Speaker 1: uh related to listening to you two, So thanks for 759 00:45:31,880 --> 00:45:34,360 Speaker 1: that anyway. One of the reasons are right is to 760 00:45:34,400 --> 00:45:37,600 Speaker 1: call your attention. You said on the Sugar It Powers 761 00:45:37,600 --> 00:45:41,880 Speaker 1: the Earth podcast, Chuck says, one day we're gonna rerecord 762 00:45:41,880 --> 00:45:44,560 Speaker 1: a show and not realize it, we're gonna hear about it. Well, 763 00:45:44,600 --> 00:45:46,919 Speaker 1: you managed to do it. You probably heard from someone 764 00:45:46,920 --> 00:45:49,120 Speaker 1: else by now. But you have covered the topic of 765 00:45:49,160 --> 00:45:54,480 Speaker 1: customs twice, the most recent one and all gets the 766 00:45:54,520 --> 00:45:57,920 Speaker 1: previous one in September. Don't get me wrong, both were great. 767 00:45:58,520 --> 00:46:01,440 Speaker 1: Honestly think that both of you legit only forgot. I 768 00:46:01,520 --> 00:46:03,320 Speaker 1: was waiting for either of you to acknowledge at the 769 00:46:03,360 --> 00:46:07,239 Speaker 1: second time, and that never came. And Ivan, you are 770 00:46:07,360 --> 00:46:11,800 Speaker 1: right on the money. Bou Josh emailed me and said, hey, buddy, 771 00:46:12,080 --> 00:46:16,440 Speaker 1: guess what we've done this. It finally happened, we released it, 772 00:46:17,080 --> 00:46:21,600 Speaker 1: and um, at first I was like shoot, but then 773 00:46:21,640 --> 00:46:24,200 Speaker 1: I thought, you know what, We've got a nice bit 774 00:46:24,200 --> 00:46:27,160 Speaker 1: of trivia. Now it was bound to happen, and now 775 00:46:27,760 --> 00:46:30,960 Speaker 1: people have. It's It's almost like an easter egg, right 776 00:46:31,440 --> 00:46:34,640 Speaker 1: that listeners and fans can say, like, you know which 777 00:46:34,640 --> 00:46:37,719 Speaker 1: one they did twice? You're a true fan, you know 778 00:46:38,160 --> 00:46:41,680 Speaker 1: you know it's weird. Though, UM, at no point during 779 00:46:41,880 --> 00:46:45,359 Speaker 1: the research and recording of the Customs episode was I like, 780 00:46:45,560 --> 00:46:49,720 Speaker 1: this sounds really familiar? Or did we talk about this nothing, 781 00:46:49,840 --> 00:46:52,520 Speaker 1: no point whatsoever. Nope. So that might make the first 782 00:46:52,560 --> 00:46:55,880 Speaker 1: Customs episode the least memorable episode we've ever done. Perhaps 783 00:46:56,600 --> 00:46:58,960 Speaker 1: so Part two you can look for in the second 784 00:46:59,000 --> 00:47:03,359 Speaker 1: part of this sweet coming out from Von wherein he 785 00:47:03,520 --> 00:47:06,359 Speaker 1: made a list of all of our band names over 786 00:47:06,400 --> 00:47:09,960 Speaker 1: the years. He also made a list of your puns. 787 00:47:10,400 --> 00:47:12,399 Speaker 1: I am not puny. I take issue with that. I'll 788 00:47:12,400 --> 00:47:14,840 Speaker 1: talk about it in the next episode. Great, that's a 789 00:47:14,880 --> 00:47:17,439 Speaker 1: great set up if you want to get in touch 790 00:47:17,480 --> 00:47:21,960 Speaker 1: with us, like lev On Evon and what is his 791 00:47:22,000 --> 00:47:24,600 Speaker 1: son's name? Did he say. He didn't say, but Evan 792 00:47:24,719 --> 00:47:28,320 Speaker 1: and son. Yeah, it'sund like a funeral home. Uh. You 793 00:47:28,360 --> 00:47:30,880 Speaker 1: can tweet to us at s Y s K podcast 794 00:47:30,960 --> 00:47:34,239 Speaker 1: or hang out with me at Josh um Clark. You 795 00:47:34,280 --> 00:47:36,839 Speaker 1: can hang out with us on Facebook at Facebook dot 796 00:47:36,840 --> 00:47:39,120 Speaker 1: com slash Stuff you Should Know and check out Chuck 797 00:47:39,200 --> 00:47:42,320 Speaker 1: at Charles W. Chuck Bryant and me it's super Josh 798 00:47:42,360 --> 00:47:46,560 Speaker 1: Clark both on Facebook. We're on Instagram. We're on social 799 00:47:46,600 --> 00:47:49,319 Speaker 1: media that hasn't even been invented yet. Plus, you can 800 00:47:49,360 --> 00:47:51,800 Speaker 1: send us an email to Stuff Podcast at how stuff 801 00:47:51,800 --> 00:47:53,880 Speaker 1: Works dot com and has always joined us at our 802 00:47:53,920 --> 00:47:56,959 Speaker 1: home on the web, the newly updated Stuff you Should 803 00:47:57,000 --> 00:48:04,480 Speaker 1: Know dot com. For more on this and thousands of 804 00:48:04,480 --> 00:48:12,440 Speaker 1: other topics, visit how stuff Works dot com. H