1 00:00:07,120 --> 00:00:10,319 Speaker 1: Welcome to Creature Creature production of I Heart Radio. I'm 2 00:00:10,360 --> 00:00:14,160 Speaker 1: your host of Many Parasites, Katie Golden. I studied psychology 3 00:00:14,160 --> 00:00:19,720 Speaker 1: and evolutionary biology, and today on the show Annihilation eighteen. 4 00:00:20,120 --> 00:00:22,760 Speaker 1: Do you do you remember that movie with the Natalie 5 00:00:22,760 --> 00:00:25,560 Speaker 1: Portman and a bunch of other people and they go 6 00:00:25,640 --> 00:00:29,480 Speaker 1: to some like science explosion that makes all the animals 7 00:00:29,480 --> 00:00:33,280 Speaker 1: and plants turned into weird hybrid things. Anyways, the show 8 00:00:33,360 --> 00:00:36,760 Speaker 1: is not really about that. The show is about weird 9 00:00:37,120 --> 00:00:42,320 Speaker 1: genetic anomalies and what happens when you know, other nature 10 00:00:42,400 --> 00:00:45,960 Speaker 1: just gets a little bit funky. We're talking about plants 11 00:00:46,000 --> 00:00:50,479 Speaker 1: that look like a bad photoshop. We're talking about lobsters 12 00:00:50,520 --> 00:00:54,720 Speaker 1: that also actually look like a bad photoshop, and butterflies. 13 00:00:54,760 --> 00:00:57,840 Speaker 1: In fact, the common denominator throughout the whole episode is 14 00:00:57,920 --> 00:01:02,320 Speaker 1: this all looks like bad photoshop, but it's not. Discover 15 00:01:02,440 --> 00:01:05,319 Speaker 1: this and more as we answer the angel question, is 16 00:01:05,360 --> 00:01:09,040 Speaker 1: the reason dogs evolved so good because they're they're cute 17 00:01:09,040 --> 00:01:13,759 Speaker 1: widow eyeballs. Joining me today to talk about all things 18 00:01:13,880 --> 00:01:20,600 Speaker 1: genetically funky is comedian and scientists and all around cool 19 00:01:20,680 --> 00:01:26,680 Speaker 1: person Paula Vygnalin. Welcome, Hey, thanks for having me. Thank 20 00:01:26,720 --> 00:01:29,680 Speaker 1: you for coming on. I'm just talking about some genetic 21 00:01:29,760 --> 00:01:32,920 Speaker 1: mix ups on the show today. I love that. I'm excited. 22 00:01:33,160 --> 00:01:37,360 Speaker 1: These things look weird, but in a beautiful way, a 23 00:01:37,480 --> 00:01:41,400 Speaker 1: beautiful way. When I say weird, it's not a negative thing. 24 00:01:41,560 --> 00:01:45,440 Speaker 1: It's a beautiful thing. So have you ever heard of 25 00:01:45,560 --> 00:01:53,240 Speaker 1: a fasciation? Fasciation or maybe I think it's fasciation maybe 26 00:01:53,400 --> 00:01:56,920 Speaker 1: like fascia like the maybe, I don't know, I don't think, 27 00:01:56,960 --> 00:01:59,960 Speaker 1: so it's hard for me to pronounce this. I believe 28 00:02:00,000 --> 00:02:06,480 Speaker 1: its faciation. H So, like remember on old Windows computers 29 00:02:06,560 --> 00:02:09,880 Speaker 1: when it would crash and you would like drag your 30 00:02:09,919 --> 00:02:13,160 Speaker 1: cursor across the screen or like a window, and it 31 00:02:13,200 --> 00:02:16,080 Speaker 1: would just keep making copies of that over and over again. 32 00:02:16,120 --> 00:02:18,440 Speaker 1: So it would be yeah, yeah, just kind of like 33 00:02:18,480 --> 00:02:24,799 Speaker 1: the snaking window. This happens to plants in nature. Are 34 00:02:24,800 --> 00:02:27,000 Speaker 1: you saying they're a glitch in the matrix. I mean, 35 00:02:27,520 --> 00:02:31,959 Speaker 1: I'm pretty confident were a simulation, just based on the 36 00:02:32,000 --> 00:02:35,880 Speaker 1: probability that the universe is recursive. But it doesn't bother 37 00:02:35,960 --> 00:02:40,160 Speaker 1: me none, so you know, yeah that's fair. But yeah, no, 38 00:02:40,440 --> 00:02:43,280 Speaker 1: there is a glitch in the matrix if by matrix 39 00:02:43,360 --> 00:02:49,520 Speaker 1: you mean genetics. Uh, Anyways, imagine, like I meant a 40 00:02:49,560 --> 00:02:55,880 Speaker 1: Mendelian matrix. Yes, Mentellian matrix. That'd be great if the 41 00:02:55,919 --> 00:03:00,480 Speaker 1: new matrix is just like cool science and like we 42 00:03:00,600 --> 00:03:04,799 Speaker 1: had this pea plant bread with this pea plant and neils, like, oh, 43 00:03:04,840 --> 00:03:10,160 Speaker 1: I can't keep track of all these pea plants anyways. Uh, 44 00:03:10,400 --> 00:03:13,960 Speaker 1: imagine a daisy you got You got a daisy in 45 00:03:14,000 --> 00:03:17,640 Speaker 1: your head. It's uh, you know, flower, It's got some 46 00:03:18,040 --> 00:03:21,480 Speaker 1: petals and so on. And then imagine the daisy as 47 00:03:21,520 --> 00:03:24,680 Speaker 1: if someone just like smeared it, like took a clone 48 00:03:24,760 --> 00:03:28,640 Speaker 1: tool and smeared it across like I'm stretched daisy like 49 00:03:28,680 --> 00:03:32,000 Speaker 1: a limo, and then a stretched limo like daisy, and 50 00:03:32,080 --> 00:03:35,440 Speaker 1: a stretch daisy like the like the middle part looks 51 00:03:35,480 --> 00:03:40,640 Speaker 1: like a caterpillar. Yeah, yeah it does. It's it's it's 52 00:03:40,680 --> 00:03:45,520 Speaker 1: somewhat uncomfortable, but it's interesting. So it makes me feel 53 00:03:46,280 --> 00:03:49,720 Speaker 1: emotions that I can't really identify exactly. I kind of 54 00:03:49,760 --> 00:03:51,680 Speaker 1: want to eat it when I look at it, I'm like, 55 00:03:51,720 --> 00:03:55,520 Speaker 1: I just want to fold up this cal zone. It's 56 00:03:55,600 --> 00:04:00,480 Speaker 1: kind of like a daisy cannoli. Yeah. So typically a 57 00:04:00,600 --> 00:04:04,000 Speaker 1: plant part like a flower or branch or berry will 58 00:04:04,120 --> 00:04:07,960 Speaker 1: have a point of growth. So for a tree, a 59 00:04:08,040 --> 00:04:10,560 Speaker 1: branch will come out from a point of growth in 60 00:04:10,880 --> 00:04:14,560 Speaker 1: sort of a relatively uniform cylindrical pattern. Obviously it's not 61 00:04:14,800 --> 00:04:21,080 Speaker 1: exact exactly you've seen trees. What if I was like, no, no, actually, 62 00:04:21,440 --> 00:04:24,760 Speaker 1: I have not seen a tree, thank you, Yeah, I'm not. 63 00:04:24,880 --> 00:04:28,760 Speaker 1: I live in Hollywood, baby, They're all fake out of here, exactly. 64 00:04:28,920 --> 00:04:34,240 Speaker 1: I'm not familiar with your quote unquote tree trees. As 65 00:04:35,400 --> 00:04:41,120 Speaker 1: never seen a tree. Uh. Flower buds typically have a 66 00:04:41,160 --> 00:04:45,080 Speaker 1: point of growth from which is symmetrical. Flower blooms, either 67 00:04:45,320 --> 00:04:50,240 Speaker 1: radial symmetry like a daisy or bilateral symmetry like an orchid. 68 00:04:51,040 --> 00:04:56,919 Speaker 1: But in plants with fasciation, this point of growth becomes elongated, 69 00:04:57,360 --> 00:05:01,320 Speaker 1: so a normal looking daisy becomes a stretch daisy. And 70 00:05:01,520 --> 00:05:04,799 Speaker 1: strawberries instead of being this nice little tear drop shape 71 00:05:04,839 --> 00:05:08,839 Speaker 1: will like look like weird stretched strawberries. Like if you 72 00:05:08,960 --> 00:05:12,320 Speaker 1: took a strawberry and you put it into Blender or 73 00:05:12,360 --> 00:05:15,440 Speaker 1: some three D software and then just extruded it around 74 00:05:15,440 --> 00:05:19,239 Speaker 1: its space until the strawberry looks like a half circle 75 00:05:19,279 --> 00:05:23,360 Speaker 1: instead of a tear drop shape. Yeah, that's an eighty 76 00:05:23,400 --> 00:05:29,320 Speaker 1: degree strawberry, right, A hundred eight degrees strawberry experience. That's 77 00:05:29,360 --> 00:05:31,800 Speaker 1: so much strawberry. You could eat it like a watermelons, 78 00:05:31,839 --> 00:05:35,039 Speaker 1: like could you could? You could like shove it in 79 00:05:35,080 --> 00:05:38,680 Speaker 1: your mouth, uh, and choke. I guess that's not a 80 00:05:38,720 --> 00:05:42,680 Speaker 1: good I don't know I could. That's the new creature 81 00:05:42,760 --> 00:05:46,599 Speaker 1: feature motto, shove it in your mouth and choke. I 82 00:05:46,640 --> 00:05:51,280 Speaker 1: guess you're a creature feature. We care about the listener 83 00:05:51,320 --> 00:05:53,040 Speaker 1: and we want you all to shove it in your 84 00:05:53,040 --> 00:05:55,880 Speaker 1: mouth and choke. Yeah. I guess you could do that 85 00:05:55,920 --> 00:05:57,960 Speaker 1: with a lot of stuff. But yeah, this is a 86 00:05:58,240 --> 00:06:02,400 Speaker 1: it's a. It's a I would say I'm uncomfortable with 87 00:06:02,440 --> 00:06:06,840 Speaker 1: this strawberry, you know. Uh, it makes me like I 88 00:06:06,880 --> 00:06:10,400 Speaker 1: feel like that. That's not a tolerant of view. This 89 00:06:10,480 --> 00:06:13,600 Speaker 1: strawberry can't help how it looks. I need, you know. Yeah, 90 00:06:13,640 --> 00:06:15,840 Speaker 1: I guess I need to learn to be more understanding 91 00:06:15,880 --> 00:06:18,159 Speaker 1: of the strawberry before I stick it in a blender 92 00:06:18,279 --> 00:06:24,880 Speaker 1: and pulverize it into a tasty smoothie. Yeah. I think 93 00:06:24,880 --> 00:06:28,120 Speaker 1: it's good. It's it's a it's a bigger ratio of 94 00:06:28,120 --> 00:06:32,680 Speaker 1: of fleshy fruit to weird leafy talk. That is true. 95 00:06:32,760 --> 00:06:36,000 Speaker 1: That's a very good point. You're definitely getting more fruit 96 00:06:36,080 --> 00:06:39,480 Speaker 1: to leaf rach seo, Like, could you imagine dipping this 97 00:06:39,520 --> 00:06:43,839 Speaker 1: in some fond do be so good? It could hold 98 00:06:44,000 --> 00:06:46,960 Speaker 1: the chocolate like a platestead of having to be covered 99 00:06:47,000 --> 00:06:49,680 Speaker 1: in I could just use it as a shovel at 100 00:06:49,680 --> 00:06:53,159 Speaker 1: the chocolate fountain and just shovel that chocolate in your mouth, 101 00:06:53,200 --> 00:06:56,720 Speaker 1: because we all know that there's kind of a conceit 102 00:06:56,920 --> 00:06:59,599 Speaker 1: with chocolate strawberries. It's like, yeah, I really want the 103 00:06:59,640 --> 00:07:02,440 Speaker 1: straw b No, you just you just want the chocolate. 104 00:07:02,600 --> 00:07:08,960 Speaker 1: You're here for the chocolate. Yeah. So it also happens 105 00:07:09,040 --> 00:07:13,160 Speaker 1: to stems in plants, so like a dandelion stem that 106 00:07:13,240 --> 00:07:18,400 Speaker 1: is normally you know you've seen a dandelion, right me? Yes, 107 00:07:19,920 --> 00:07:22,400 Speaker 1: I don't know because you live in l A and 108 00:07:23,000 --> 00:07:26,320 Speaker 1: I'm not sure. Oh yeah, Well, the wheaty things grow 109 00:07:26,400 --> 00:07:32,800 Speaker 1: up between the sidewalks you mean sidewalk spangles. Yeah, I'm familiar. 110 00:07:33,600 --> 00:07:38,600 Speaker 1: But they have a thin stem. But dandelion stem that 111 00:07:38,840 --> 00:07:44,760 Speaker 1: undergoes fasciation becomes this like thick. It's a thick. It's 112 00:07:44,800 --> 00:07:49,119 Speaker 1: a big boy. It's a big, big old thick one 113 00:07:49,160 --> 00:07:53,080 Speaker 1: in it it looks like a broccoli like kind of 114 00:07:53,080 --> 00:07:55,440 Speaker 1: a thing. Like that's how thick it is. Yeah, yeah, 115 00:07:55,480 --> 00:08:00,080 Speaker 1: you could, uh you know, you could really have some 116 00:08:00,200 --> 00:08:03,480 Speaker 1: trouble picking this dand alone. I'll tell you what, did 117 00:08:03,520 --> 00:08:06,480 Speaker 1: that sound too actual? I hope not trying to keep 118 00:08:06,480 --> 00:08:09,360 Speaker 1: a clean I think this one is like weirder to 119 00:08:09,440 --> 00:08:12,560 Speaker 1: me because with dandelions usually people have that image of 120 00:08:12,600 --> 00:08:16,960 Speaker 1: like picking and like picking off the pedals, right, That's 121 00:08:16,960 --> 00:08:19,680 Speaker 1: how it's used, isn't that stuff that That's how dandelions 122 00:08:19,680 --> 00:08:22,960 Speaker 1: are used in media as people just like ripping them apart. Yeah, 123 00:08:23,000 --> 00:08:25,800 Speaker 1: I mean, you know we are here, but that's like 124 00:08:25,800 --> 00:08:31,160 Speaker 1: our favorite thing to do. That's true. I also shouldn't 125 00:08:31,200 --> 00:08:34,080 Speaker 1: complain given that that's most of my comedy style. Um, 126 00:08:34,120 --> 00:08:37,520 Speaker 1: but but it's also that image of like a thin 127 00:08:37,679 --> 00:08:40,720 Speaker 1: stem and people pulling the top part off. And this 128 00:08:41,000 --> 00:08:43,400 Speaker 1: is very like now it just looks clunkier, you know, 129 00:08:43,480 --> 00:08:49,880 Speaker 1: like this, you know, went to a gym. It's like 130 00:08:50,400 --> 00:08:54,679 Speaker 1: it's yeah, it's a CrossFit danielions, but it gives us. Yeah, 131 00:08:54,720 --> 00:08:57,000 Speaker 1: it's like that feeling you get when you like see 132 00:08:57,080 --> 00:08:59,520 Speaker 1: someone you knew from a while ago, and you know 133 00:08:59,520 --> 00:09:02,000 Speaker 1: they're like sort of standard size, but then they went 134 00:09:02,040 --> 00:09:05,480 Speaker 1: to a gym and got incredibly buff and bulky. This 135 00:09:05,600 --> 00:09:11,720 Speaker 1: is the camal nongiani flowers. Yes, this flower is prepping 136 00:09:11,800 --> 00:09:16,680 Speaker 1: to be included in the Marvel Universe cinematic use. Yes, yes. 137 00:09:16,960 --> 00:09:20,720 Speaker 1: And sometimes the fasciation is so severe that the flowers 138 00:09:20,760 --> 00:09:24,000 Speaker 1: will actually start to curl around the point of growth 139 00:09:24,160 --> 00:09:30,280 Speaker 1: just becomes so elongated that it like becomes a flower doughnut, which, yeah, 140 00:09:30,600 --> 00:09:33,680 Speaker 1: you know, it sounds like it tastes good, but it's 141 00:09:33,720 --> 00:09:37,720 Speaker 1: still just a plant. Unfortunately, it sounds like a powder donut, 142 00:09:37,760 --> 00:09:40,280 Speaker 1: but flower don't. Yeah, it sounds like, I don't know, 143 00:09:40,320 --> 00:09:42,280 Speaker 1: it kind of sounds like a health food that it's 144 00:09:42,320 --> 00:09:46,000 Speaker 1: like this is a flower doughnut, and you all right, 145 00:09:46,200 --> 00:09:48,920 Speaker 1: like is this But then it's like not that good 146 00:09:48,960 --> 00:09:50,920 Speaker 1: of a dessert, and it's also not that good of 147 00:09:50,960 --> 00:09:54,840 Speaker 1: a health food. So really nobody wins it went that that. 148 00:09:54,920 --> 00:09:56,880 Speaker 1: I feel like I have seen that in l a yeah, 149 00:09:58,200 --> 00:10:01,960 Speaker 1: health doughnut, Yeah, a healthy doughnut. Definitely seen that in 150 00:10:02,120 --> 00:10:06,280 Speaker 1: l Yeah. Yeah, no trees, but you do got health doughnuts. 151 00:10:07,280 --> 00:10:10,600 Speaker 1: It's a genetic defect that can happen in plants, and 152 00:10:10,679 --> 00:10:13,320 Speaker 1: so most plants can be affected by like even an 153 00:10:13,360 --> 00:10:18,959 Speaker 1: asparagus which turns into like an asparagus into an asparag No, 154 00:10:19,240 --> 00:10:24,439 Speaker 1: thank you, because I'm already weirded out by asparagus. It 155 00:10:24,480 --> 00:10:27,559 Speaker 1: would be in a it would be an a spare me, right, 156 00:10:28,400 --> 00:10:32,559 Speaker 1: thank you for correcting my joke. It was really I'm sorry, 157 00:10:32,640 --> 00:10:35,880 Speaker 1: no no, no, I mean because it was a bad joke. 158 00:10:36,000 --> 00:10:38,080 Speaker 1: It was real sickly. And then you came in and 159 00:10:38,120 --> 00:10:42,560 Speaker 1: you kind of got it, did some joke CPR on 160 00:10:42,600 --> 00:10:46,440 Speaker 1: and actually you coming out of the podcast, right, you 161 00:10:46,520 --> 00:10:49,640 Speaker 1: just used me to punch up, and then it's just 162 00:10:49,679 --> 00:10:52,480 Speaker 1: your gonna edit. This is the writer's room, right right, 163 00:10:52,480 --> 00:10:55,080 Speaker 1: I'm editing you out completely, and it's just gonna be 164 00:10:55,200 --> 00:10:58,120 Speaker 1: me having a conversation with myself, and like half of 165 00:10:58,160 --> 00:11:00,599 Speaker 1: the time I'm really funny and happens. I'm not that 166 00:11:03,240 --> 00:11:09,280 Speaker 1: this asparagus really does look like, um oh, what is 167 00:11:09,320 --> 00:11:11,520 Speaker 1: that movie with Robin Williams where he goes to hell 168 00:11:11,640 --> 00:11:14,760 Speaker 1: to find his wife? I have no idea? What dreams? 169 00:11:14,840 --> 00:11:20,840 Speaker 1: What dreams? And then the paint the paint sneers right, yeah, 170 00:11:21,200 --> 00:11:23,800 Speaker 1: it's like or like yeah, which is kind of like 171 00:11:23,840 --> 00:11:27,920 Speaker 1: the what's that Google deep dream? What Ai? It's like 172 00:11:27,960 --> 00:11:32,320 Speaker 1: an AI tried to do us an asparagus or like 173 00:11:32,360 --> 00:11:35,280 Speaker 1: when you take a panorama and your dog runs through. Yeah, 174 00:11:35,320 --> 00:11:38,520 Speaker 1: I love that, and then it gets all stretched out. 175 00:11:42,240 --> 00:11:46,800 Speaker 1: It's amazing. Yeah, yeah, it's it's it's a it is. 176 00:11:46,920 --> 00:11:50,520 Speaker 1: It is definitely a like you mentioned earlier glitch in 177 00:11:50,520 --> 00:11:52,640 Speaker 1: the matrix moment, though, it gives you that sort of 178 00:11:52,720 --> 00:11:56,120 Speaker 1: unsettling feeling of like, ah, this is I feel like 179 00:11:56,120 --> 00:11:58,320 Speaker 1: this asparagus would be really hard to cook because like 180 00:11:58,600 --> 00:12:02,800 Speaker 1: I feel like asparagus like they're like it takes a 181 00:12:02,840 --> 00:12:06,760 Speaker 1: while to like cook them all the way through, you know. Yeah, 182 00:12:06,800 --> 00:12:08,840 Speaker 1: And I feel like this one would burn on the 183 00:12:08,880 --> 00:12:11,760 Speaker 1: outside by the time you cooked. It looks like a 184 00:12:12,320 --> 00:12:19,719 Speaker 1: like a piece of toast made out of asparagus. Asparagus. 185 00:12:20,480 --> 00:12:23,199 Speaker 1: I bet it also makes your piece smell even weirder 186 00:12:23,280 --> 00:12:27,920 Speaker 1: than normal. What if it makes a smell good action, 187 00:12:28,679 --> 00:12:32,560 Speaker 1: that's great, Like we need to breed asparagus that whatever 188 00:12:33,000 --> 00:12:36,120 Speaker 1: the gene that like make messes with your urine makes 189 00:12:36,160 --> 00:12:41,400 Speaker 1: it smell great. Who this had to be some dude 190 00:12:41,440 --> 00:12:43,840 Speaker 1: being like, what does my pie smell like after I 191 00:12:43,880 --> 00:12:46,920 Speaker 1: eat only asparagus for three days? You know what I mean? Like, 192 00:12:47,200 --> 00:12:51,240 Speaker 1: sometimes not all scientists wear lab coats. Some are just 193 00:12:51,360 --> 00:12:53,679 Speaker 1: dudes and bachelor pads, you know what I mean. Like 194 00:12:54,000 --> 00:12:57,720 Speaker 1: I mean, I think like up until like the nineteen hundreds, 195 00:12:57,800 --> 00:13:01,440 Speaker 1: most of science was some dude like drinking his own 196 00:13:01,559 --> 00:13:06,360 Speaker 1: pea and seeing what life was like if he only 197 00:13:06,840 --> 00:13:10,320 Speaker 1: drank fluids and and put milk up his butthole. You know, 198 00:13:10,840 --> 00:13:14,920 Speaker 1: we gave a man an entire career because he only 199 00:13:15,120 --> 00:13:17,720 Speaker 1: ate McDonald's for a while, and we were like, sure, 200 00:13:18,040 --> 00:13:21,080 Speaker 1: let's just see what that looks like this he like 201 00:13:21,440 --> 00:13:24,640 Speaker 1: everybody nobody was like, dude, you should eat McDonald's for 202 00:13:24,720 --> 00:13:27,280 Speaker 1: a long time, and he's like he just he just 203 00:13:27,320 --> 00:13:30,680 Speaker 1: did it himself and then built a full career both 204 00:13:30,679 --> 00:13:34,959 Speaker 1: in nutrition and an entertainment off of that. It's incredible. 205 00:13:35,520 --> 00:13:41,559 Speaker 1: What when when Grimes just eats pasta for two years, 206 00:13:42,200 --> 00:13:47,640 Speaker 1: we call her a bad mother. And when I get 207 00:13:47,720 --> 00:13:54,160 Speaker 1: an excessive amount of chocolate's like that's unhealthy. Okay, It's like, oh, 208 00:13:54,200 --> 00:13:56,200 Speaker 1: I have to be on my period to eat a 209 00:13:56,200 --> 00:13:59,559 Speaker 1: bunch of chocolate. But Morgan what's his face can eat 210 00:13:59,600 --> 00:14:02,680 Speaker 1: a half emal for a year and that's like not 211 00:14:02,800 --> 00:14:06,679 Speaker 1: a midlife crisis. The Funyan's diet isn't getting a movie deal? 212 00:14:06,760 --> 00:14:14,000 Speaker 1: All right? Okay, fine, just another example of the patriarchy. 213 00:14:14,559 --> 00:14:19,200 Speaker 1: But uh so. Fasciation can be caused by a number 214 00:14:19,200 --> 00:14:26,160 Speaker 1: of factors, including random genetic mutation, hormonal imbalance, viral infection, 215 00:14:26,640 --> 00:14:32,440 Speaker 1: bacterial infection, chemical exposure, or parasites. But even in all 216 00:14:32,480 --> 00:14:35,520 Speaker 1: of these cases, the method of action is the same. 217 00:14:36,000 --> 00:14:40,400 Speaker 1: An abnormality occurs that affects the growing tip of the plant. 218 00:14:41,000 --> 00:14:44,360 Speaker 1: So the growing tip is called the maris stem, which 219 00:14:44,840 --> 00:14:48,520 Speaker 1: very much sounds like a little hobbit name or something 220 00:14:48,560 --> 00:14:52,560 Speaker 1: like Marris stem. Oh, I'm I'm stem and I'm going 221 00:14:52,640 --> 00:14:55,880 Speaker 1: with you, Mr Frodo to to protect the shy and 222 00:14:55,880 --> 00:14:59,040 Speaker 1: then he immediately gets eaten by a dragon or a 223 00:14:59,160 --> 00:15:03,640 Speaker 1: ring write or something thing I like, growing stem is 224 00:15:03,720 --> 00:15:09,600 Speaker 1: coming to borders near you. So yeah, the the Marris stem, 225 00:15:09,640 --> 00:15:14,760 Speaker 1: it's a cluster of undifferentiated cells. In a typical plant, 226 00:15:14,840 --> 00:15:18,560 Speaker 1: the marrow stem is a tidy little bump, but in 227 00:15:18,680 --> 00:15:22,320 Speaker 1: fasciation it goes bananas and there's this spread of the 228 00:15:22,320 --> 00:15:25,360 Speaker 1: Marris stem and thus a spread of cells that can 229 00:15:25,400 --> 00:15:31,080 Speaker 1: differentiate into new tissue. Uh So, uh sometimes we actually 230 00:15:31,200 --> 00:15:35,440 Speaker 1: deliberately breed flowers that have the genetic mutation for fasciation, 231 00:15:35,840 --> 00:15:40,920 Speaker 1: such as don't laugh Coxcomb I tried to keep really quiet. 232 00:15:41,000 --> 00:15:44,320 Speaker 1: You did, you did, which I'm glad when I say, like, 233 00:15:44,360 --> 00:15:47,240 Speaker 1: don't laugh now you take me seriously and don't actually laugh. 234 00:15:47,280 --> 00:15:49,280 Speaker 1: I I tried really hard. It was like it's like 235 00:15:49,320 --> 00:15:51,640 Speaker 1: a personal challenge, you know what I mean. Yeah, no, 236 00:15:51,800 --> 00:15:56,520 Speaker 1: I I saw, I saw just laughter trying to escape you. Definitely, 237 00:15:56,560 --> 00:15:59,840 Speaker 1: my mouth just like yeah, clamped down, yeah, yeah, unlike 238 00:16:00,000 --> 00:16:04,960 Speaker 1: And I have a coxcomb. So it's called a coxcomb 239 00:16:05,080 --> 00:16:08,320 Speaker 1: because it looks like a rooster's comb, you know, a rooster, 240 00:16:08,480 --> 00:16:12,880 Speaker 1: a cock. It's it's innocent. Fair So is this basically 241 00:16:12,920 --> 00:16:15,920 Speaker 1: this is kind of like flower cancer right because it's 242 00:16:17,120 --> 00:16:20,600 Speaker 1: but it's it's where is it not? It's so it's 243 00:16:20,680 --> 00:16:23,040 Speaker 1: sort of like that. I would say, it's more like 244 00:16:23,280 --> 00:16:29,120 Speaker 1: flower tumor. Ish. It's like it's like you're still so 245 00:16:29,160 --> 00:16:33,960 Speaker 1: the stem cells, the maristem of the plant having this 246 00:16:34,160 --> 00:16:40,480 Speaker 1: uncontrolled duplication sort of like a tumor. Fortunately for the plant, 247 00:16:40,720 --> 00:16:45,880 Speaker 1: it is a sustainable thing because it instead of being 248 00:16:45,960 --> 00:16:50,520 Speaker 1: like a tumor where it's basically non functional tissue that 249 00:16:51,160 --> 00:16:55,200 Speaker 1: you know, in malignant cases like steals your nutrients and 250 00:16:55,320 --> 00:16:57,920 Speaker 1: does nothing good for you except you know, hurts you. 251 00:16:58,480 --> 00:17:01,880 Speaker 1: In this case, it's just more of the plant, Like, hey, 252 00:17:02,040 --> 00:17:05,680 Speaker 1: there's just more of you. Enjoy that, which could be 253 00:17:05,920 --> 00:17:10,600 Speaker 1: could be problematic in some cases, I presume, but sometimes 254 00:17:10,400 --> 00:17:15,120 Speaker 1: it just works, like in coxcombs, where they just look 255 00:17:15,359 --> 00:17:18,200 Speaker 1: I guess, like you know, the rooster comb, and people 256 00:17:18,240 --> 00:17:20,400 Speaker 1: love that. People go nuts for it. They do look 257 00:17:20,440 --> 00:17:23,359 Speaker 1: really cool. These are fun. They look like a little purses. Yeah, 258 00:17:23,840 --> 00:17:28,600 Speaker 1: like fluffy little anemonies with Yeah, they do. They absolutely 259 00:17:28,680 --> 00:17:31,120 Speaker 1: do look like an enemy's maybe with like a weird 260 00:17:31,200 --> 00:17:34,480 Speaker 1: tongue attached to them. I'm into it. I'm into coxlick. 261 00:17:34,680 --> 00:17:39,000 Speaker 1: I like coxcomb. So in animals, when you have like 262 00:17:39,040 --> 00:17:43,320 Speaker 1: an oopsy goofer with undifferentiated tissue, this can often lead 263 00:17:43,359 --> 00:17:47,520 Speaker 1: to extra body parts, like supernumerary body parts, so like 264 00:17:47,720 --> 00:17:49,879 Speaker 1: an extra body part can occur when you have an 265 00:17:49,880 --> 00:17:54,760 Speaker 1: extra limb buds, So like in developing embryos, we have 266 00:17:55,040 --> 00:17:58,320 Speaker 1: limb buds. It's kind of like the maristem of a plant, 267 00:17:59,160 --> 00:18:01,320 Speaker 1: but instead of growing like a branch or flower, it 268 00:18:01,359 --> 00:18:05,439 Speaker 1: grows a limb like a leg or an arm. Uh. 269 00:18:06,200 --> 00:18:09,679 Speaker 1: And oh this is making this is making more sense 270 00:18:09,760 --> 00:18:14,280 Speaker 1: because like there are those stereotypes of in like some 271 00:18:14,400 --> 00:18:18,600 Speaker 1: underdeveloped areas where the children experience this right where they 272 00:18:18,720 --> 00:18:22,119 Speaker 1: have extra limbs or you know, are born with like 273 00:18:22,240 --> 00:18:25,520 Speaker 1: a tail or something you know, like uh so, but 274 00:18:25,560 --> 00:18:29,840 Speaker 1: if it's influenced by some environmental factors, that would make 275 00:18:30,000 --> 00:18:33,120 Speaker 1: a lot of sense. Absolutely it can be. Yeah, it's 276 00:18:33,200 --> 00:18:36,440 Speaker 1: something that can both be like a random genetic mutation 277 00:18:36,560 --> 00:18:40,119 Speaker 1: that's not necessarily environmental, but often it is environmental. And 278 00:18:40,119 --> 00:18:43,639 Speaker 1: you see that both unfortunately in humans, but you also 279 00:18:43,680 --> 00:18:46,719 Speaker 1: see it in frogs. So in areas where there's a 280 00:18:46,720 --> 00:18:50,640 Speaker 1: lot of pollution, you can get frogs with extra legs. 281 00:18:50,680 --> 00:18:53,520 Speaker 1: So like the intro to The Simpsons where we got 282 00:18:53,520 --> 00:18:58,120 Speaker 1: the fish with three eyes. Yeah, certainly. I don't think 283 00:18:58,240 --> 00:19:02,359 Speaker 1: three eyes is very common. It's usually like extra limbs that, 284 00:19:02,760 --> 00:19:08,440 Speaker 1: like multiple eye really unusual. I think like the sometimes 285 00:19:08,440 --> 00:19:11,240 Speaker 1: the only times like you get a third eye in 286 00:19:11,320 --> 00:19:14,679 Speaker 1: an animal or like a one eye or something is 287 00:19:14,720 --> 00:19:17,919 Speaker 1: when you have like a twin that doesn't split correctly. 288 00:19:18,680 --> 00:19:24,720 Speaker 1: So yeah, wow, but I don't interesting and I'm not 289 00:19:24,800 --> 00:19:27,000 Speaker 1: exactly sure why, but I think it has something to 290 00:19:27,040 --> 00:19:30,800 Speaker 1: do with the difference in how the eye develops versus 291 00:19:30,800 --> 00:19:34,720 Speaker 1: a limb develops. And now we are the extent to 292 00:19:34,800 --> 00:19:40,399 Speaker 1: which I know about um, but yeah, one question that 293 00:19:40,520 --> 00:19:42,879 Speaker 1: I had that I looked into it was like, why 294 00:19:43,080 --> 00:19:47,399 Speaker 1: don't animals have fasciation? So why can't I just grow 295 00:19:47,560 --> 00:19:53,840 Speaker 1: a mega arm that's like thick like that mega dandelion stem. Uh, 296 00:19:53,840 --> 00:19:57,520 Speaker 1: And I would I would guess it has something to 297 00:19:57,600 --> 00:20:01,440 Speaker 1: do with like the difference in growth of new tissue 298 00:20:02,160 --> 00:20:05,760 Speaker 1: in a plant's mare stem versus animal stem cells. So 299 00:20:05,840 --> 00:20:11,680 Speaker 1: like plant tissue is sort of more uh, it's kind 300 00:20:11,680 --> 00:20:18,040 Speaker 1: of more regularly structured. So yeah, it's simpler. Yeah, and 301 00:20:18,119 --> 00:20:20,879 Speaker 1: you have like so if you have you don't have 302 00:20:21,280 --> 00:20:24,679 Speaker 1: quite as many interacting organs. So like if you have 303 00:20:24,800 --> 00:20:29,920 Speaker 1: an arm, you have like a bunch of veins and bones, 304 00:20:29,960 --> 00:20:33,480 Speaker 1: and it's not all symmetrical inside your arm, Like your 305 00:20:33,600 --> 00:20:37,240 Speaker 1: arm does not have any radial symmetry, whereas like a 306 00:20:37,280 --> 00:20:41,280 Speaker 1: branch in a tree or or a stem or even 307 00:20:41,359 --> 00:20:44,640 Speaker 1: like a flower pedal, there's a lot of symmetry even 308 00:20:45,000 --> 00:20:48,119 Speaker 1: within each individual part of it. So if you have 309 00:20:48,320 --> 00:20:53,040 Speaker 1: this uh, genetic anomaly where it's just like it's like okay, 310 00:20:53,080 --> 00:20:56,399 Speaker 1: this but more of it, that will kind of work 311 00:20:56,400 --> 00:21:00,359 Speaker 1: out in the plant. That's why it's ironic that trees 312 00:21:00,400 --> 00:21:04,080 Speaker 1: don't exist in Hollywood because it is so symmetrical, it 313 00:21:04,320 --> 00:21:06,520 Speaker 1: should be able to make it in Hollywood, know what 314 00:21:06,520 --> 00:21:10,000 Speaker 1: I mean. Symmetry is so important when you're casting a tree, 315 00:21:10,040 --> 00:21:14,160 Speaker 1: like those trees and Wizard of Oz are really really 316 00:21:14,320 --> 00:21:17,359 Speaker 1: unfair standards for trees, like no real trees look like that, 317 00:21:18,240 --> 00:21:25,919 Speaker 1: No real trees look so um. There are really cool 318 00:21:26,680 --> 00:21:30,119 Speaker 1: mutations though, in animals that have to do with the 319 00:21:30,480 --> 00:21:34,679 Speaker 1: the like growing bud or limb bud and sometimes this 320 00:21:34,720 --> 00:21:39,359 Speaker 1: can actually work out great for animals. So uh, snakes 321 00:21:39,400 --> 00:21:44,560 Speaker 1: evolutionarily speaking, used to have legs. Uh and there so 322 00:21:44,640 --> 00:21:48,760 Speaker 1: their ancestors used to have legs. They didn't start out legless. 323 00:21:48,800 --> 00:21:52,280 Speaker 1: The so you know that that meme that's like the 324 00:21:52,320 --> 00:21:55,680 Speaker 1: first creature crawling out of the sea that people use 325 00:21:55,760 --> 00:22:00,280 Speaker 1: all the time. This would be like, yeah, the would 326 00:22:00,320 --> 00:22:07,600 Speaker 1: be in in reverse. Right, I'm tired of walking. This sucks, right, 327 00:22:07,720 --> 00:22:11,440 Speaker 1: let me just ride my body against the right. They 328 00:22:11,600 --> 00:22:16,600 Speaker 1: don't use legs. They use their abdominal muscle contractions to 329 00:22:16,840 --> 00:22:21,000 Speaker 1: smoothly glide along the ground. They have such a strong core. 330 00:22:21,160 --> 00:22:26,160 Speaker 1: They really I'm I'm out here jealous of snakes cores. 331 00:22:26,560 --> 00:22:29,919 Speaker 1: I'm jealous. I'm jealous of snakes and dolphins. Have you 332 00:22:29,920 --> 00:22:35,080 Speaker 1: ever seen the abs on a dolphin? Oh wow, yeah, yeah, 333 00:22:35,280 --> 00:22:37,879 Speaker 1: it's yeah, they do all that jumping out of water, 334 00:22:38,080 --> 00:22:42,040 Speaker 1: that huge amount of core strength. So yeah, snakes and 335 00:22:42,080 --> 00:22:50,320 Speaker 1: dolphins would laugh at your reps, just laugh. But yeah, 336 00:22:50,400 --> 00:22:53,720 Speaker 1: so uh yeah, snakes dropped the legs. They got a 337 00:22:53,760 --> 00:22:57,359 Speaker 1: more flexible skeleton that allows them to engorge themselves with 338 00:22:57,520 --> 00:23:01,760 Speaker 1: huge prey relative to their slender lot Boddie and h. 339 00:23:02,119 --> 00:23:05,639 Speaker 1: The gene that controls limb growth is actually called the 340 00:23:05,680 --> 00:23:10,920 Speaker 1: sonic hedgehog gene. Yeah, I'm familiar with this gene. Yeah, 341 00:23:10,960 --> 00:23:15,000 Speaker 1: it's a fun one. It's a fun it's fun fun naming, 342 00:23:15,160 --> 00:23:19,600 Speaker 1: you know. Sometimes you just gotta have fun with genes. Yeah, 343 00:23:19,760 --> 00:23:23,040 Speaker 1: like too many of these like z A B two 344 00:23:23,160 --> 00:23:26,680 Speaker 1: forty seven, blah blah blah, just call like sonic calle, 345 00:23:26,760 --> 00:23:30,719 Speaker 1: like Mario do a? Do you a bowser gene? You know? 346 00:23:31,640 --> 00:23:33,639 Speaker 1: Is that the gene for like where it's supposed to 347 00:23:33,680 --> 00:23:40,639 Speaker 1: be Italian but it's not. Yes that the Mario Chris 348 00:23:40,640 --> 00:23:45,520 Speaker 1: Pratt apparently has the Mario gene. Not really. I think 349 00:23:45,640 --> 00:23:48,120 Speaker 1: here's the thing I think everybody. I think people want 350 00:23:48,160 --> 00:23:52,000 Speaker 1: contradictory things from scientists. I think they want them to 351 00:23:52,040 --> 00:23:54,600 Speaker 1: be less uptight, but then when they are, they're like, 352 00:23:54,760 --> 00:23:57,639 Speaker 1: you're supposed to be the serious person in our society, 353 00:23:57,840 --> 00:24:01,720 Speaker 1: and they judge them for it. Yeah. Yeah, people really 354 00:24:01,800 --> 00:24:05,639 Speaker 1: knew that scientists were just like human and chill. I 355 00:24:05,680 --> 00:24:08,800 Speaker 1: think I feel like that they would they should be 356 00:24:08,840 --> 00:24:11,119 Speaker 1: able to relate to them more. But then they it 357 00:24:11,160 --> 00:24:14,040 Speaker 1: also concerns them. They're like, oh, these are people and 358 00:24:14,080 --> 00:24:18,280 Speaker 1: we're putting all this responsibility on Yeah. I think, yeah, 359 00:24:18,320 --> 00:24:23,680 Speaker 1: I think understanding that scientists are not just aliens that 360 00:24:23,840 --> 00:24:29,320 Speaker 1: don't aren't able to understand a social environment like outside 361 00:24:29,320 --> 00:24:32,200 Speaker 1: of a lab is would be nice, a nice trope 362 00:24:32,200 --> 00:24:36,000 Speaker 1: to get rid of, because yeah, I agree, like people 363 00:24:36,920 --> 00:24:39,080 Speaker 1: like this thing that this is a little bit of 364 00:24:39,119 --> 00:24:41,520 Speaker 1: a tangent. Sorry everyone, please don't give me a bad 365 00:24:41,520 --> 00:24:45,600 Speaker 1: review for tangents. But um, they're like I remember when 366 00:24:45,840 --> 00:24:49,480 Speaker 1: scientists were doing this like bird research on a bird calls, 367 00:24:49,520 --> 00:24:52,840 Speaker 1: and a lot of people are like like uh, and 368 00:24:52,920 --> 00:24:57,440 Speaker 1: it was there's some big controversy about like, oh, you're 369 00:24:57,840 --> 00:25:00,879 Speaker 1: you're spinning all this time, like researching ward calls, and 370 00:25:00,920 --> 00:25:03,480 Speaker 1: like that's that's so, you know, like you're supposed to 371 00:25:03,520 --> 00:25:06,439 Speaker 1: be doing real science. It's like, yeah, they did this 372 00:25:06,520 --> 00:25:10,240 Speaker 1: with like they did this with like beetle shells or something. 373 00:25:10,240 --> 00:25:12,320 Speaker 1: They're like I remember every once in a while, something 374 00:25:12,320 --> 00:25:14,760 Speaker 1: on Twitter or somebody you know will say something that's 375 00:25:14,800 --> 00:25:17,680 Speaker 1: like like, I can't believe scientists are wasting their time 376 00:25:17,680 --> 00:25:20,000 Speaker 1: and money on this thing instead of doing this thing. 377 00:25:20,040 --> 00:25:22,800 Speaker 1: And it's like you aren't a scientist and have no 378 00:25:22,920 --> 00:25:26,480 Speaker 1: idea the importance or the context of what they're studying. 379 00:25:26,960 --> 00:25:31,320 Speaker 1: And also science is just studying the world, so it's 380 00:25:31,359 --> 00:25:35,640 Speaker 1: still science even if you d prioritize it as necessary 381 00:25:35,760 --> 00:25:40,360 Speaker 1: for you. And everything is connected. Oops, I said everything 382 00:25:40,480 --> 00:25:45,080 Speaker 1: is connected, right, Like every like the Beatles shell will 383 00:25:45,240 --> 00:25:48,600 Speaker 1: like help with the design of cars, and like you 384 00:25:48,640 --> 00:25:52,280 Speaker 1: know what I mean, like everything is related. Um, but 385 00:25:52,320 --> 00:25:55,080 Speaker 1: I don't think people understand that. Yeah, I mean most 386 00:25:55,119 --> 00:25:59,399 Speaker 1: of our medical and technological advancements are based on scientific 387 00:25:59,440 --> 00:26:03,120 Speaker 1: research that you know, many many years of scientific research 388 00:26:03,160 --> 00:26:06,480 Speaker 1: that may not have that much apparently in common with 389 00:26:06,920 --> 00:26:10,200 Speaker 1: the end result of the research. But yeah, I mean, 390 00:26:10,200 --> 00:26:12,879 Speaker 1: like if we didn't like look at, you know, mouse 391 00:26:12,920 --> 00:26:15,199 Speaker 1: turds once in a while, we would probably not have 392 00:26:15,320 --> 00:26:19,120 Speaker 1: most of medicine. Uh, but we do that just for fun. 393 00:26:19,600 --> 00:26:22,480 Speaker 1: It's fun. Through mouse turds. Don't do it, don't get 394 00:26:22,480 --> 00:26:28,159 Speaker 1: haunt of virus. That yeah, sonic hedgehog gene. It's actually 395 00:26:28,240 --> 00:26:30,560 Speaker 1: Sonic hedgehog I think is the name, not Sonic the 396 00:26:30,680 --> 00:26:35,959 Speaker 1: Hedgehog science stupid sciences, But it's called that because of 397 00:26:36,000 --> 00:26:39,200 Speaker 1: its spiky appearance. And apparently one of the researchers who 398 00:26:39,240 --> 00:26:42,480 Speaker 1: discovered it had a daughter with a Sonic the Hedgehog 399 00:26:42,520 --> 00:26:47,360 Speaker 1: comic book, so that's cute like that. So a mutation 400 00:26:47,400 --> 00:26:52,159 Speaker 1: occurred in snakes that basically deleted activators for the sonic 401 00:26:52,200 --> 00:26:57,199 Speaker 1: hedgehog gene responsible for leg growth, but that gene for 402 00:26:57,359 --> 00:27:01,719 Speaker 1: legs is still technically there. Uh, it's just that the 403 00:27:01,800 --> 00:27:06,120 Speaker 1: activators that would switch that gene on are are not there. 404 00:27:06,160 --> 00:27:10,200 Speaker 1: So basically, when snakes start to develop as an embryo, 405 00:27:10,320 --> 00:27:12,919 Speaker 1: they start to like develop these little legs and then 406 00:27:12,920 --> 00:27:15,399 Speaker 1: they're like no, no, not just kidding, just kidding, No 407 00:27:15,560 --> 00:27:20,240 Speaker 1: legs for me, thank you? Oh weird? What do you think? 408 00:27:20,280 --> 00:27:22,520 Speaker 1: Like the first nake came out and was just like, 409 00:27:22,560 --> 00:27:28,320 Speaker 1: what the fuck are you kidding me? My whole family 410 00:27:28,400 --> 00:27:31,800 Speaker 1: has legs, and I have like I can't even go 411 00:27:31,880 --> 00:27:33,879 Speaker 1: to the grocery store with them because they don't know 412 00:27:33,880 --> 00:27:36,119 Speaker 1: how to handle me. Yeah, it's just like high five. 413 00:27:36,280 --> 00:27:42,720 Speaker 1: That is so insensitive. Uh, I mean I think that uh, 414 00:27:43,080 --> 00:27:47,680 Speaker 1: ruining your joke and taking it seriously. Uh, the first 415 00:27:47,720 --> 00:27:53,119 Speaker 1: snakes probably came from these lizards that have basically just 416 00:27:53,240 --> 00:27:57,080 Speaker 1: little nubs for legs, so the legs get kind of smaller, 417 00:27:57,280 --> 00:28:01,760 Speaker 1: more useless. And uh, I want I want everyone on 418 00:28:01,800 --> 00:28:05,359 Speaker 1: Twitter to take a moment and acknowledge what you just said, 419 00:28:05,960 --> 00:28:08,960 Speaker 1: ruining your joke and taking it seriously. Can you put 420 00:28:09,000 --> 00:28:11,239 Speaker 1: that at the front of every reply you send me 421 00:28:11,320 --> 00:28:18,040 Speaker 1: on Twitter, just people of Twitter, where you name this podcast, 422 00:28:18,200 --> 00:28:25,119 Speaker 1: ruining your joke by taking seriously? Yeah, this is uh, 423 00:28:25,320 --> 00:28:27,199 Speaker 1: you know, this is why I have comedians on the 424 00:28:27,240 --> 00:28:30,280 Speaker 1: podcast about science, so I can just be like, well, 425 00:28:30,359 --> 00:28:36,479 Speaker 1: actually you make a funny joke, but scientifically speaking, but yeah, no, 426 00:28:36,520 --> 00:28:40,360 Speaker 1: this is me at a party. I have so many friends, 427 00:28:40,640 --> 00:28:46,120 Speaker 1: so many friends. Um, but yeah, so so they did, 428 00:28:46,160 --> 00:28:49,920 Speaker 1: Like there are a lot of these sort of transitional species. 429 00:28:49,960 --> 00:28:52,440 Speaker 1: You could look at it and they're not necessarily direct 430 00:28:52,520 --> 00:28:55,360 Speaker 1: ancestors of the snakes, but when you you can see 431 00:28:55,400 --> 00:28:58,120 Speaker 1: like where you can see where they're coming from, Like 432 00:28:58,160 --> 00:29:02,400 Speaker 1: they there are these lizards that have these very teeny tiny, 433 00:29:02,520 --> 00:29:05,960 Speaker 1: nubby legs that uh, they don't really use that much. 434 00:29:06,000 --> 00:29:09,120 Speaker 1: And then probably one of them just kind of had 435 00:29:09,160 --> 00:29:12,560 Speaker 1: a gene deletion of these legs. And it's like, this 436 00:29:12,680 --> 00:29:16,080 Speaker 1: is fine. I'm fine with this. You know what, I 437 00:29:16,120 --> 00:29:20,760 Speaker 1: need your legs, all right. One day someone's gonna compare 438 00:29:20,800 --> 00:29:24,760 Speaker 1: me to Taylor Swift. Okay, you know what, this is 439 00:29:24,760 --> 00:29:29,280 Speaker 1: pretty great, Like you have your little legs and that's fine. 440 00:29:29,640 --> 00:29:35,239 Speaker 1: I don't judge you, but I don't actually need them. So, 441 00:29:35,720 --> 00:29:40,040 Speaker 1: you know, snakes are officially like that person who doesn't 442 00:29:40,080 --> 00:29:42,120 Speaker 1: have a TV. And you know that they don't have 443 00:29:42,200 --> 00:29:44,760 Speaker 1: a TV because they tell you about how much they 444 00:29:44,800 --> 00:29:49,320 Speaker 1: don't watch TV all the time. Yeah, it's like, yeah, 445 00:29:50,040 --> 00:29:54,719 Speaker 1: I mean TVs, like we get it. You read yeah, okay, 446 00:29:54,840 --> 00:29:57,080 Speaker 1: uh yeah, So snakes are out there like I don't 447 00:29:57,080 --> 00:30:00,440 Speaker 1: need legs. And actually I read Lussies and I thought 448 00:30:00,480 --> 00:30:15,400 Speaker 1: it was easy to read. They reads OLIVI do you 449 00:30:15,400 --> 00:30:20,240 Speaker 1: want to talk about lobsters? Obviously that's why I came here. 450 00:30:21,320 --> 00:30:25,440 Speaker 1: It's it's Lobster Wednesdays. Everybody gets your bib on and 451 00:30:25,520 --> 00:30:32,240 Speaker 1: get ready to enjoy some sun about lobsters. So lobsters 452 00:30:32,440 --> 00:30:36,440 Speaker 1: we love them, We love to eat them. Uh, they're 453 00:30:36,520 --> 00:30:41,920 Speaker 1: the cute little sort of Arthur pods the sea and 454 00:30:42,080 --> 00:30:48,560 Speaker 1: there they can have some really interesting and uh like 455 00:30:49,160 --> 00:30:54,960 Speaker 1: very fake looking genetic mix ups. So lobsters can have 456 00:30:55,600 --> 00:30:59,200 Speaker 1: a very rare mutation where they are bright blue instead 457 00:30:59,240 --> 00:31:03,479 Speaker 1: of brown. Now, just a quick reminder, lobsters in the 458 00:31:03,480 --> 00:31:07,920 Speaker 1: ocean aren't red. That's after you boil them as they 459 00:31:07,960 --> 00:31:11,400 Speaker 1: scream for mercy. Uh, they turn red. Oh my god, 460 00:31:12,000 --> 00:31:15,400 Speaker 1: but they're they're brown. I didn't even realize that. Yeah, yeah, yeah, 461 00:31:15,520 --> 00:31:19,440 Speaker 1: I mean, like, you know, it's some some chemical change 462 00:31:19,480 --> 00:31:26,160 Speaker 1: happens that I certainly know about chemistry. I'm so good 463 00:31:26,160 --> 00:31:28,280 Speaker 1: at chemistry. But yeah, it's when you boil them they 464 00:31:28,280 --> 00:31:31,320 Speaker 1: turn bright red. But in the ocean there's sort of 465 00:31:31,360 --> 00:31:37,320 Speaker 1: a muddy brown, all of kind of color. Uh. And 466 00:31:38,000 --> 00:31:42,760 Speaker 1: you know, but yes, sometimes they are bright bright blue, 467 00:31:42,920 --> 00:31:51,680 Speaker 1: like you know, I don't know how to describe this blue. Yes, yes, 468 00:31:52,280 --> 00:31:56,840 Speaker 1: this is this is a great wait, bust blue. What 469 00:31:56,920 --> 00:32:00,000 Speaker 1: did you say, I said, I I said best by, 470 00:32:00,280 --> 00:32:03,880 Speaker 1: But yeah, it might also be what is it megabus blue? 471 00:32:03,920 --> 00:32:05,320 Speaker 1: I don't know, I don't know, you know the blue 472 00:32:05,360 --> 00:32:09,560 Speaker 1: that it's the it's it's the blue of the nineties 473 00:32:09,800 --> 00:32:12,320 Speaker 1: that all the companies use. No, it's it's more the 474 00:32:12,320 --> 00:32:15,480 Speaker 1: blue of the early two thousand's where everyone decided blue 475 00:32:15,560 --> 00:32:19,720 Speaker 1: is the good color for stores in general, Walmart blue, 476 00:32:20,040 --> 00:32:25,320 Speaker 1: Best Buy blue. Uh, you know cool Ranch, Derito's blue. 477 00:32:25,760 --> 00:32:31,360 Speaker 1: It's it's bright, artificial looking blue. And uh, this is 478 00:32:31,400 --> 00:32:34,080 Speaker 1: said to be like a one in a million chance. 479 00:32:34,200 --> 00:32:38,560 Speaker 1: I wonder how this affects like they're how like predators 480 00:32:38,640 --> 00:32:40,800 Speaker 1: view them, and like how they're able to get away 481 00:32:40,840 --> 00:32:43,320 Speaker 1: from things. You know. Yeah, that's a good question because 482 00:32:43,440 --> 00:32:47,400 Speaker 1: with animals who have albin ism, we know, typically it's 483 00:32:47,400 --> 00:32:49,840 Speaker 1: a bad thing because it makes them a lot easier 484 00:32:49,840 --> 00:32:53,520 Speaker 1: to spot, so they don't typically survive as well. So 485 00:32:53,600 --> 00:32:57,720 Speaker 1: like albino squirrels often get picked off. Unfortunately, the same 486 00:32:57,760 --> 00:33:01,800 Speaker 1: thing with that. I've never seen an albino squirrel. I've 487 00:33:01,800 --> 00:33:04,800 Speaker 1: seen so many squirrels in my lifetime get picked off 488 00:33:04,800 --> 00:33:08,120 Speaker 1: by hawks pretty good. I mean, it's why melanistic squirrels 489 00:33:08,160 --> 00:33:11,400 Speaker 1: black squirrels are much more common than albino squirrels because 490 00:33:11,400 --> 00:33:14,920 Speaker 1: melanistic squirrels it's not so bad for them because you know, 491 00:33:15,000 --> 00:33:18,959 Speaker 1: they're they don't just like stand out like someone highlighted 492 00:33:19,000 --> 00:33:23,240 Speaker 1: them on, like, you know, this is like reverse white privilege. 493 00:33:25,400 --> 00:33:28,960 Speaker 1: This is what this is the only context, and yeah, 494 00:33:29,000 --> 00:33:33,800 Speaker 1: this is the squirrels of color are given an advantage. Yeah, 495 00:33:33,840 --> 00:33:36,840 Speaker 1: this is yeah. And yes, I know albinism can happen 496 00:33:36,880 --> 00:33:43,400 Speaker 1: to squirrels of colors. But yeah, that's a great question. 497 00:33:43,520 --> 00:33:45,880 Speaker 1: I don't know. I think that the lobsters are so 498 00:33:46,160 --> 00:33:51,040 Speaker 1: rare and they're typically only found during like commercial lobster fishing, 499 00:33:51,760 --> 00:33:54,600 Speaker 1: so I don't know like what that does for their 500 00:33:54,640 --> 00:33:58,320 Speaker 1: survival rates. I would imagine because it's blue and the 501 00:33:58,360 --> 00:34:03,000 Speaker 1: oceans kind of blue, maybe it's okay. It's a very 502 00:34:03,120 --> 00:34:09,840 Speaker 1: unscientific statement, but you know, it's like I think maybe 503 00:34:09,920 --> 00:34:14,400 Speaker 1: it's okay in any context is also a very uncientific statement, 504 00:34:14,480 --> 00:34:18,600 Speaker 1: given just a state of everything. I love reading a 505 00:34:18,640 --> 00:34:21,160 Speaker 1: paper in like the New England Journal of Medicine and 506 00:34:21,160 --> 00:34:26,279 Speaker 1: they're like, you know, smoking marijuana. I think maybe it's okay. 507 00:34:26,280 --> 00:34:31,320 Speaker 1: Maybe it's okay, bro. I don't know, dude, But blue 508 00:34:31,400 --> 00:34:35,600 Speaker 1: lobsters are not the only weird mutation that lobsters have. 509 00:34:35,960 --> 00:34:39,240 Speaker 1: They can also be bright orange, which is interesting because 510 00:34:39,239 --> 00:34:42,080 Speaker 1: when they're bright orange, they kind of look like the 511 00:34:42,120 --> 00:34:47,080 Speaker 1: color of a cooked lobster, but they're not. So it's 512 00:34:47,120 --> 00:34:49,279 Speaker 1: also a very rare mutation. You're not going to see 513 00:34:49,280 --> 00:34:53,959 Speaker 1: it typically, but they will be. It's that's like them 514 00:34:54,000 --> 00:34:56,640 Speaker 1: trying to hide before we cook them. They're like, no, no, 515 00:34:56,680 --> 00:35:00,560 Speaker 1: we're already cooking. Yeah, you don't out of throw me 516 00:35:00,640 --> 00:35:04,240 Speaker 1: in the pot. Yeah, but you know that's another protein 517 00:35:04,320 --> 00:35:08,480 Speaker 1: mutation that happens that gives them this bright orange coloration, 518 00:35:09,480 --> 00:35:13,440 Speaker 1: as is the blue coloration a protein mutation. But the 519 00:35:13,840 --> 00:35:18,440 Speaker 1: this is not even as wild as lobsters get. Uh, 520 00:35:18,480 --> 00:35:23,280 Speaker 1: they sometimes will look half and half, so they literally 521 00:35:23,320 --> 00:35:26,560 Speaker 1: look like you plopped a lobster and photoshop and like 522 00:35:26,640 --> 00:35:30,360 Speaker 1: selected exactly half of the lobster and changed the hue 523 00:35:31,160 --> 00:35:34,560 Speaker 1: down the middle, Yes, straight down in the middle, one 524 00:35:34,640 --> 00:35:39,120 Speaker 1: side being blue and one side being brown, or even 525 00:35:39,200 --> 00:35:42,800 Speaker 1: one side being orange and one side being brown or blue. 526 00:35:43,520 --> 00:35:47,160 Speaker 1: It's it doesn't look like it literally looks. It literally 527 00:35:47,200 --> 00:35:49,600 Speaker 1: looks like somebody laid painter's tape. But that line is 528 00:35:49,640 --> 00:35:52,960 Speaker 1: so clean all the way down. It's wild jealous of 529 00:35:53,000 --> 00:35:56,839 Speaker 1: these clean lines, just like I've never been able to 530 00:35:57,280 --> 00:36:01,400 Speaker 1: painting doing my nails. No, it's always always there's always 531 00:36:01,440 --> 00:36:03,759 Speaker 1: a point of like a bubble in the tape where 532 00:36:03,800 --> 00:36:06,080 Speaker 1: you peel it and then there's just like a little imperfection. 533 00:36:06,120 --> 00:36:09,480 Speaker 1: You're like yeah, and you're like, you know, who's the 534 00:36:09,520 --> 00:36:16,160 Speaker 1: best nail artist? Lobsters? Same thing, same thing, same thing 535 00:36:17,840 --> 00:36:23,600 Speaker 1: is a lobster. Uh So yeah, and it not only 536 00:36:23,640 --> 00:36:27,680 Speaker 1: looks mind blowing, but the explanation for it is also 537 00:36:27,719 --> 00:36:33,799 Speaker 1: really interesting. So uh. Most animals have some form of symmetry. 538 00:36:33,920 --> 00:36:37,200 Speaker 1: Some animals have radial symmetry, like a sea urchin or 539 00:36:37,239 --> 00:36:42,200 Speaker 1: a starfish, and some animals like humans and most mammals 540 00:36:42,280 --> 00:36:46,239 Speaker 1: and fish and lobsters have bilateral symmetry. So we each 541 00:36:46,280 --> 00:36:49,880 Speaker 1: have you know, uh, you know, half of our body 542 00:36:50,400 --> 00:36:54,760 Speaker 1: is relatively a mirror image of the other half. But 543 00:36:55,040 --> 00:36:58,759 Speaker 1: if something goes wrong, as the cells are splitting when 544 00:36:58,840 --> 00:37:03,719 Speaker 1: you're a blast assist developing into an embryo, uh, or 545 00:37:03,760 --> 00:37:07,239 Speaker 1: even a mistake when the chromosomes are dividing, you can 546 00:37:07,280 --> 00:37:10,160 Speaker 1: have an animal split down the middle with two different 547 00:37:10,200 --> 00:37:15,440 Speaker 1: colors and even two different sexes. So most two toned 548 00:37:15,560 --> 00:37:21,759 Speaker 1: lobsters are actually also gynandromorphs, So each side of the 549 00:37:21,800 --> 00:37:25,719 Speaker 1: lobster is a different sex So one side has testes 550 00:37:25,840 --> 00:37:30,279 Speaker 1: and the other has ovaries. So during early development and 551 00:37:30,360 --> 00:37:34,319 Speaker 1: during cell division or mitosis and air occurs where the 552 00:37:34,360 --> 00:37:39,239 Speaker 1: sex chromosomes don't split properly, so you have literally one 553 00:37:39,320 --> 00:37:42,520 Speaker 1: half is female and one half is male, and then 554 00:37:42,520 --> 00:37:46,800 Speaker 1: they're different colors. Uh, not necessarily, so male and female 555 00:37:46,840 --> 00:37:50,920 Speaker 1: lobsters aren't really different colors typically, but you can have 556 00:37:51,200 --> 00:37:55,120 Speaker 1: because one half has a different genome than the other half, 557 00:37:55,160 --> 00:37:57,759 Speaker 1: you could have a color mutation one half and not 558 00:37:57,880 --> 00:38:00,239 Speaker 1: in the other half. And so that's how you get 559 00:38:00,280 --> 00:38:03,239 Speaker 1: these like incredibly rare. Not only do they have a 560 00:38:03,280 --> 00:38:09,520 Speaker 1: color mutation, but they also have uh guyn andromorph mutation. 561 00:38:10,880 --> 00:38:14,319 Speaker 1: Can Andrew morph? Was that children's book series we read 562 00:38:14,440 --> 00:38:20,799 Speaker 1: as kids, that series. It's I did it for the 563 00:38:20,840 --> 00:38:26,040 Speaker 1: flip book though of the lobsters. So actually, last episode 564 00:38:26,040 --> 00:38:29,720 Speaker 1: we talked a little bit about how sex determination works 565 00:38:29,760 --> 00:38:32,400 Speaker 1: and how it can be different depending on the animals. 566 00:38:32,400 --> 00:38:35,839 Speaker 1: So not all animals are x Y like humans. So 567 00:38:36,160 --> 00:38:38,799 Speaker 1: you know, as humans you have like the x Y 568 00:38:38,960 --> 00:38:41,480 Speaker 1: chromosomes and x x and x y, but there there 569 00:38:41,520 --> 00:38:45,239 Speaker 1: are a lot of different variations in humans that can happen, uh, 570 00:38:45,320 --> 00:38:47,640 Speaker 1: and then in other animals that can be even like 571 00:38:47,640 --> 00:38:52,120 Speaker 1: like completely different systems like x oh where Uh, females 572 00:38:52,120 --> 00:38:54,520 Speaker 1: will have x X and males will have You tell 573 00:38:54,680 --> 00:38:58,520 Speaker 1: me there's a tic tac toe animals. There's tic tac 574 00:38:58,600 --> 00:39:05,120 Speaker 1: toe animals, some shrews, low spiders playing tic tac toe 575 00:39:05,640 --> 00:39:08,799 Speaker 1: much more much, which is the most fun kind of 576 00:39:08,880 --> 00:39:16,720 Speaker 1: sex system, I think. Uh so, if anyways, he's different. 577 00:39:17,280 --> 00:39:20,920 Speaker 1: There's also z W system and chickens, and well not 578 00:39:21,000 --> 00:39:23,839 Speaker 1: just chickens, I guess other birds too, but you know, 579 00:39:24,040 --> 00:39:27,759 Speaker 1: when you think bird, you think chicken. And actually the 580 00:39:27,840 --> 00:39:30,480 Speaker 1: z W system is kind of the mirror of X 581 00:39:30,640 --> 00:39:34,840 Speaker 1: Y system, because a female will have z W and 582 00:39:34,880 --> 00:39:37,239 Speaker 1: a male will have z Z and they actually can 583 00:39:37,280 --> 00:39:42,200 Speaker 1: have because males are boring. Wait, but that would mean 584 00:39:42,280 --> 00:39:45,480 Speaker 1: females are boring in other species. No, because we're not 585 00:39:45,680 --> 00:39:50,200 Speaker 1: z Z thing. I see, I get it. I am so. 586 00:39:50,400 --> 00:39:58,000 Speaker 1: I I appreciate comedy. I'm a comedy appreciator. Uh so, yeah, 587 00:39:58,080 --> 00:40:01,520 Speaker 1: And actually chickens can have interest things happen with their 588 00:40:01,600 --> 00:40:07,719 Speaker 1: sex determination system, where uh, males can like become females. 589 00:40:08,120 --> 00:40:10,640 Speaker 1: Uh And so there's a lot there's a lot of 590 00:40:10,640 --> 00:40:13,520 Speaker 1: cool shenanigans. If anyone tries to sell you the idea 591 00:40:13,640 --> 00:40:18,759 Speaker 1: that sex determination and chromosomes is simple, they're wrong, they're 592 00:40:18,880 --> 00:40:24,000 Speaker 1: uh yeah boom uh. So basically, what can happen during 593 00:40:24,000 --> 00:40:28,080 Speaker 1: cell dicivision. Let's take for example, the XO system XO 594 00:40:28,239 --> 00:40:32,560 Speaker 1: XO kiss kiss kiss um, where they say the cell 595 00:40:32,680 --> 00:40:37,359 Speaker 1: split and one cell gets two X chromosomes and then 596 00:40:37,360 --> 00:40:40,719 Speaker 1: the other cell only gets one X chromosome. Then, in 597 00:40:40,800 --> 00:40:42,880 Speaker 1: like a spider or a shrew or one of these 598 00:40:42,960 --> 00:40:47,719 Speaker 1: these creatures that have the XO system, one of them's 599 00:40:47,840 --> 00:40:50,640 Speaker 1: uh there, there's gonna be one organism where half is 600 00:40:51,040 --> 00:40:54,480 Speaker 1: male and half is female. And so this is actually 601 00:40:54,480 --> 00:40:58,719 Speaker 1: what can happen in butterflies. And when it happens in butterflies, 602 00:40:58,760 --> 00:41:02,840 Speaker 1: it's very striking. So now we're talking about color different 603 00:41:03,160 --> 00:41:05,920 Speaker 1: differences in two sides. That's not just because of some 604 00:41:06,080 --> 00:41:11,120 Speaker 1: interesting mutation like in lobsters where you have both gynandromorph 605 00:41:11,320 --> 00:41:15,839 Speaker 1: gynandromorphy and you have this color mutation. But in butterflies, 606 00:41:15,880 --> 00:41:20,560 Speaker 1: it's that male and female butterflies have different coloration even 607 00:41:20,600 --> 00:41:25,960 Speaker 1: when the typical sexual reproduction happens. So in a gynandromorph, 608 00:41:26,480 --> 00:41:29,279 Speaker 1: one half of the butterfly is male and has a 609 00:41:29,400 --> 00:41:32,399 Speaker 1: very different wing shape and color, and the other half 610 00:41:32,440 --> 00:41:36,120 Speaker 1: this female, and so not only are their wings different colors, 611 00:41:36,160 --> 00:41:39,359 Speaker 1: but they can be different shapes and sizes. It looks 612 00:41:39,400 --> 00:41:43,640 Speaker 1: like some psychopath cut butterflies in half and then glued 613 00:41:43,719 --> 00:41:49,759 Speaker 1: them back together. Um, God, sad about this hypothetical situation. 614 00:41:50,080 --> 00:41:53,520 Speaker 1: It like there's no way they can. They're flying in circles, right, 615 00:41:53,560 --> 00:41:57,080 Speaker 1: Like the wings are totally different sizes. They're probably not 616 00:41:57,160 --> 00:42:03,280 Speaker 1: flying great. It's probably not a probably not the best flyers, no, yeah, 617 00:42:03,320 --> 00:42:06,320 Speaker 1: because one side is like way bigger than the other. Yeah. Yeah. 618 00:42:06,480 --> 00:42:10,640 Speaker 1: And some species like where there's not as much sexual dimorphism, 619 00:42:10,760 --> 00:42:13,760 Speaker 1: that is, like there's not that as much difference between 620 00:42:13,760 --> 00:42:17,919 Speaker 1: males and females. They probably function all right in terms 621 00:42:17,960 --> 00:42:20,120 Speaker 1: of flying, but yeah, some of them, the difference is 622 00:42:20,239 --> 00:42:23,120 Speaker 1: very dramatic where the female is a lot smaller than 623 00:42:23,160 --> 00:42:26,759 Speaker 1: the male, or vice versa, and or the male like 624 00:42:26,840 --> 00:42:29,960 Speaker 1: sometimes you know, butterflies have those big those tails on it, 625 00:42:30,080 --> 00:42:32,560 Speaker 1: so like you have butterfly wing shape and then you 626 00:42:32,560 --> 00:42:34,800 Speaker 1: have sort of this tear drop shape coming off of 627 00:42:34,880 --> 00:42:37,200 Speaker 1: the bottom of the wing, and that's a that's like 628 00:42:37,239 --> 00:42:40,680 Speaker 1: a swallow tail. Butterfly has those, but it is only 629 00:42:40,680 --> 00:42:46,040 Speaker 1: in one sex. So when you have a gynandromorphe one 630 00:42:46,080 --> 00:42:48,480 Speaker 1: of the sides has that little tail and the other doesn't, 631 00:42:48,560 --> 00:42:52,239 Speaker 1: which is gonna make it real tricky for the butterfly. 632 00:42:52,920 --> 00:42:55,279 Speaker 1: So you have a good time flying, I guess the 633 00:42:55,320 --> 00:42:58,960 Speaker 1: butterflies like, um, okay, rest of the family, y'all go 634 00:42:59,040 --> 00:43:02,440 Speaker 1: out further for flowers and whatnot, and I'm just gonna 635 00:43:02,480 --> 00:43:06,880 Speaker 1: hang around in this circle like I'll just be at 636 00:43:06,920 --> 00:43:14,200 Speaker 1: home base. Yeah. Yeah, it's uh, it's it's like one 637 00:43:14,280 --> 00:43:16,640 Speaker 1: side of the butterfly is telling the other side of 638 00:43:16,640 --> 00:43:19,120 Speaker 1: the butterfly. Did you ask for directions? No, I'm not 639 00:43:19,120 --> 00:43:24,120 Speaker 1: going to ask get it, get it. It's it's at it. 640 00:43:25,440 --> 00:43:28,080 Speaker 1: I gotta explain something to the zoomers. Back in the day, 641 00:43:28,200 --> 00:43:31,879 Speaker 1: we used to have this joke where like men would 642 00:43:31,920 --> 00:43:35,600 Speaker 1: never ask for directions. Um, and that was this is 643 00:43:35,800 --> 00:43:41,640 Speaker 1: in dinosaur times actually when we have this joke, so 644 00:43:41,680 --> 00:43:45,400 Speaker 1: all the dinosaurs at Jurassic Park would ask for directions. 645 00:43:47,120 --> 00:43:49,920 Speaker 1: And then it's like like one dinosaur is like you 646 00:43:50,040 --> 00:43:53,160 Speaker 1: gotta You've gotta ask for directions, and it's like I 647 00:43:53,200 --> 00:44:00,920 Speaker 1: don't know, like I'll uh find a way MS park reference. 648 00:44:01,040 --> 00:44:04,879 Speaker 1: I feel like I'm wrap please every every word I say. 649 00:44:05,000 --> 00:44:11,600 Speaker 1: Another zoomer just like clicks pause and puts down. Al Right, 650 00:44:11,800 --> 00:44:14,920 Speaker 1: I think I think this episode is just as referential 651 00:44:15,040 --> 00:44:21,560 Speaker 1: as ulysses. Wow, that was that was so referential. To 652 00:44:21,920 --> 00:44:27,160 Speaker 1: being referential, I hurt in my brain. We're gonna take 653 00:44:27,160 --> 00:44:36,920 Speaker 1: a quick break. So sometimes when we talk about mutations, uh, 654 00:44:37,160 --> 00:44:41,080 Speaker 1: people get this idea that mutations are either good for 655 00:44:41,520 --> 00:44:44,960 Speaker 1: organism or bad. So, like it's often the topic of 656 00:44:45,120 --> 00:44:48,759 Speaker 1: conversation when we're talking about like COVID, like, oh, it 657 00:44:48,840 --> 00:44:51,040 Speaker 1: has a mutation, this must mean it's now like a 658 00:44:51,080 --> 00:44:55,760 Speaker 1: superpowered virus. But mutations are not intrinsically good or bad. 659 00:44:56,040 --> 00:44:59,959 Speaker 1: They're just a mutation, and whether or not it turns 660 00:45:00,000 --> 00:45:03,759 Speaker 1: out to be beneficial or bad for the organism, it 661 00:45:03,840 --> 00:45:07,799 Speaker 1: just depends on the selective pressures that the organism is 662 00:45:07,880 --> 00:45:13,759 Speaker 1: operating in. So sometimes these color mutations can in like 663 00:45:13,880 --> 00:45:19,960 Speaker 1: these interesting uh little genetic whoopsie doodles, can be maybe negative, 664 00:45:20,040 --> 00:45:23,520 Speaker 1: like we talked about the butterfly being half male and 665 00:45:23,560 --> 00:45:27,320 Speaker 1: half female and one side if the male and female 666 00:45:27,600 --> 00:45:32,680 Speaker 1: of that species have significant difference in size, they'll be 667 00:45:32,680 --> 00:45:35,319 Speaker 1: a little opsided and maybe flying circles a little bit. 668 00:45:36,160 --> 00:45:43,560 Speaker 1: But sometimes color mutations can completely shape the course of history. 669 00:45:43,600 --> 00:45:47,160 Speaker 1: For better or worse. So this one cool, weird eye 670 00:45:47,200 --> 00:45:51,120 Speaker 1: trick may have changed the course of human history. Doctors 671 00:45:51,120 --> 00:45:57,520 Speaker 1: hate it. So most primates have dark sclera, so that's 672 00:45:57,560 --> 00:46:02,160 Speaker 1: the eye tissue surrounding the iris is but in humans 673 00:46:02,200 --> 00:46:06,120 Speaker 1: this tissue is white or kind of off white. And 674 00:46:06,400 --> 00:46:10,360 Speaker 1: some research seems to indicate that by having this bright 675 00:46:10,840 --> 00:46:16,120 Speaker 1: white ish sclera, humans are better able to track eye 676 00:46:16,160 --> 00:46:20,799 Speaker 1: movement and gaze in each other. And some anthropologists have 677 00:46:21,040 --> 00:46:26,880 Speaker 1: a hypothesis that human cooperation and evolution was shaped by 678 00:46:27,000 --> 00:46:30,200 Speaker 1: our ability to see each other's gaze. And so this 679 00:46:30,280 --> 00:46:35,400 Speaker 1: is called the cooperative gaze hypothesis, which is like you know, 680 00:46:35,520 --> 00:46:38,440 Speaker 1: like when you're with which is like just June, right, 681 00:46:39,440 --> 00:46:46,680 Speaker 1: it's a bunch of cooperative gays. Uh see, I got 682 00:46:46,719 --> 00:46:51,520 Speaker 1: that one. I'm getting faster with it. But you know, 683 00:46:51,680 --> 00:46:54,520 Speaker 1: like when you're with someone and you can't like say 684 00:46:54,600 --> 00:46:59,240 Speaker 1: something out loud to them, but you're using your family 685 00:46:59,280 --> 00:47:02,959 Speaker 1: reunion weddings, right, You're like judging people. You're like, who's 686 00:47:03,000 --> 00:47:06,640 Speaker 1: that at the at stand up shows? Right, You're like 687 00:47:06,719 --> 00:47:09,520 Speaker 1: this is terrible, but with your eyes right, and like 688 00:47:09,640 --> 00:47:13,040 Speaker 1: all the zoomers who are left still listening to the show, 689 00:47:13,560 --> 00:47:16,640 Speaker 1: Like when you roll your eyes. If you didn't have 690 00:47:17,200 --> 00:47:20,440 Speaker 1: a white sclera, like, your parents would never know that 691 00:47:20,520 --> 00:47:27,799 Speaker 1: you hate them, which it's really important. They wouldn't get 692 00:47:27,840 --> 00:47:30,839 Speaker 1: the full sense of your disdain, which would really be 693 00:47:30,880 --> 00:47:34,719 Speaker 1: a tragedy. Part of phood, right, you have to let 694 00:47:34,760 --> 00:47:39,919 Speaker 1: them know that they're being so uncool right now. But yeah, So, 695 00:47:40,200 --> 00:47:45,399 Speaker 1: human babies follow eye gaze much more than primates, and 696 00:47:46,000 --> 00:47:49,840 Speaker 1: the ability to follow each other's gaze may have helped 697 00:47:49,920 --> 00:47:55,120 Speaker 1: human in collaboration or things like determining intent. So seeing 698 00:47:55,120 --> 00:47:58,640 Speaker 1: where someone's eye gazes can really help you understand like 699 00:47:58,680 --> 00:48:00,640 Speaker 1: what are they looking at? What are the focused on? 700 00:48:00,680 --> 00:48:03,239 Speaker 1: Are they looking at me or something else? Like are 701 00:48:03,280 --> 00:48:05,800 Speaker 1: they looking at the thing I have? So it can 702 00:48:05,840 --> 00:48:09,719 Speaker 1: both be protective for you, like of understanding, Okay, what 703 00:48:09,920 --> 00:48:12,919 Speaker 1: is this person interested in? And it can also help 704 00:48:12,920 --> 00:48:15,520 Speaker 1: you cooperate because like, if they keep looking at something 705 00:48:15,560 --> 00:48:17,759 Speaker 1: that's in your hands, it's like, oh, they may want 706 00:48:17,800 --> 00:48:20,000 Speaker 1: to see this, or they may want this, and so 707 00:48:20,560 --> 00:48:24,879 Speaker 1: I can figure out what someone wants before we even 708 00:48:24,960 --> 00:48:30,640 Speaker 1: maybe had language, So you know, having that sort of 709 00:48:30,800 --> 00:48:35,800 Speaker 1: non verbal accessory to communication may have been really really 710 00:48:35,800 --> 00:48:39,600 Speaker 1: helpful in our early development as a highly social species. 711 00:48:40,680 --> 00:48:45,120 Speaker 1: And uh it may have even helped our relationship with dogs, 712 00:48:45,320 --> 00:48:51,240 Speaker 1: which we co evolved with uh since very early history. Uh. 713 00:48:51,280 --> 00:48:53,920 Speaker 1: You know dogs used to be they had like a 714 00:48:53,960 --> 00:48:58,759 Speaker 1: wolf like ancestor, and they started to catch on that. Hey, 715 00:48:58,840 --> 00:49:01,719 Speaker 1: if I actually cue an Instagram wruble, I could have 716 00:49:01,760 --> 00:49:05,800 Speaker 1: a real qushy lifestyle next to humans. Unfortunately, they didn't 717 00:49:05,800 --> 00:49:10,200 Speaker 1: know like the extent to our obsession with making them 718 00:49:10,239 --> 00:49:14,600 Speaker 1: look real weird and cute. Uh and like breeding them 719 00:49:14,680 --> 00:49:18,560 Speaker 1: until they basically can't They can't breathe and they look 720 00:49:18,640 --> 00:49:23,080 Speaker 1: like a loaf of bread with eyeballs. But anyways, Uh yeah, 721 00:49:23,160 --> 00:49:28,000 Speaker 1: so dogs are able to follow our eye gays almost 722 00:49:28,040 --> 00:49:32,799 Speaker 1: as well as human infants. So having eyes that are 723 00:49:32,840 --> 00:49:37,440 Speaker 1: so easy to follow, dogs may have co evolved with us, 724 00:49:37,560 --> 00:49:41,359 Speaker 1: and we're better able to understand where our attention was 725 00:49:41,600 --> 00:49:46,120 Speaker 1: and able to cooperate with us. So if you've ever wondered, 726 00:49:46,160 --> 00:49:49,759 Speaker 1: like why your dog is so uncannily attuned to like 727 00:49:50,280 --> 00:49:52,919 Speaker 1: what you're looking at or or what you're interested in, 728 00:49:53,480 --> 00:49:56,240 Speaker 1: part of it could be that your dog is following 729 00:49:56,239 --> 00:50:01,920 Speaker 1: your eye gays. Now, my dog, I think needs dog glasses. 730 00:50:02,560 --> 00:50:06,160 Speaker 1: Her vision is not very good, so I can point 731 00:50:06,200 --> 00:50:09,000 Speaker 1: at a slice of cheese, and she goes like wandering 732 00:50:09,040 --> 00:50:13,319 Speaker 1: off like two feet away from the cheese. And so 733 00:50:13,520 --> 00:50:17,239 Speaker 1: I don't think she's noticing my eye movements as much 734 00:50:17,280 --> 00:50:22,319 Speaker 1: at all, although my dog, I think this might. I 735 00:50:22,360 --> 00:50:24,319 Speaker 1: don't know. I feel like maybe we're at the point 736 00:50:24,320 --> 00:50:27,000 Speaker 1: where we're wearing masks so much that our dogs are 737 00:50:27,000 --> 00:50:30,239 Speaker 1: even more tuned into our eyes. Because now when I 738 00:50:30,280 --> 00:50:32,719 Speaker 1: put in Now, when I put on a mask or 739 00:50:32,800 --> 00:50:35,319 Speaker 1: go to like I use paper towels to like open 740 00:50:35,360 --> 00:50:39,479 Speaker 1: the door knobs and stuff. She she um just because 741 00:50:39,520 --> 00:50:43,239 Speaker 1: people a building or gross, no kidding, um she uh. 742 00:50:43,440 --> 00:50:46,799 Speaker 1: She literally, she like starts freaking out immediately, like she's 743 00:50:46,920 --> 00:50:49,520 Speaker 1: very tuned into when I start moving. It's all like 744 00:50:49,719 --> 00:50:53,000 Speaker 1: embarrassing to Like when I put on pants, she freaks out, 745 00:50:53,040 --> 00:50:55,759 Speaker 1: which is like how much I don't wear pants in 746 00:50:55,920 --> 00:51:00,879 Speaker 1: my apartment. She's like, Oh, we're going outside. Now, were 747 00:51:00,880 --> 00:51:06,239 Speaker 1: you putting on pants? Ye, code pants, You're wearing a 748 00:51:06,320 --> 00:51:10,600 Speaker 1: broad pants. Something's happening, Something's happening. That's how my dog 749 00:51:10,680 --> 00:51:14,080 Speaker 1: is when I put on shoes, because it's it's a 750 00:51:14,200 --> 00:51:17,480 Speaker 1: fifty gamble for her. It could mean I'm going outside 751 00:51:17,560 --> 00:51:24,080 Speaker 1: with her or leaving forever forever and neglecting her for 752 00:51:24,120 --> 00:51:28,960 Speaker 1: an eternity, So I get it. Yeah, so she has 753 00:51:29,000 --> 00:51:34,040 Speaker 1: this expression of like dread and excitement that is really 754 00:51:34,040 --> 00:51:39,759 Speaker 1: pathetic and hard hard to watch honestly, But I like 755 00:51:39,840 --> 00:51:46,680 Speaker 1: that you just called your dog pathetic. I mean, somebody 756 00:51:46,760 --> 00:51:49,719 Speaker 1: kept me up all night whining about I don't know, 757 00:51:50,120 --> 00:51:52,000 Speaker 1: I have no idea what freaked her out on. But 758 00:51:52,080 --> 00:51:55,279 Speaker 1: imagine how anxious you would be if the person you 759 00:51:55,320 --> 00:51:58,480 Speaker 1: loved most in the world would just randomly leave at 760 00:51:58,600 --> 00:52:00,920 Speaker 1: times that you didn't understand end and you had no 761 00:52:01,000 --> 00:52:03,799 Speaker 1: idea if they were coming back it would be And 762 00:52:03,880 --> 00:52:05,600 Speaker 1: this is the person that you love most and are 763 00:52:05,600 --> 00:52:08,359 Speaker 1: also dependent on for food and shelter. I mean, I 764 00:52:08,440 --> 00:52:11,799 Speaker 1: get really sweaty palms if I'm left on red for 765 00:52:11,920 --> 00:52:15,879 Speaker 1: like two minutes. So oh yeah, I'm probably not want 766 00:52:15,960 --> 00:52:20,719 Speaker 1: to judge, but yeah, so so are the whites of 767 00:52:20,719 --> 00:52:25,240 Speaker 1: our eyes are really important maybe for even communicating with dogs, 768 00:52:25,280 --> 00:52:27,480 Speaker 1: and uh, you know, we know how important dogs have 769 00:52:27,560 --> 00:52:31,799 Speaker 1: been for our history and helping us with livestock and 770 00:52:31,840 --> 00:52:37,440 Speaker 1: agriculture and hunting, and so just this one cool little 771 00:52:37,520 --> 00:52:42,200 Speaker 1: genetic thing that happened with the sclera being white may 772 00:52:42,200 --> 00:52:47,719 Speaker 1: have had this like huge effect on evolution. Ah, and 773 00:52:47,800 --> 00:52:52,920 Speaker 1: in fact, you actually can get primates who have this mutation. 774 00:52:53,600 --> 00:52:58,560 Speaker 1: So there's this picture of a chimpanzee with the white sclera, 775 00:52:59,320 --> 00:53:02,960 Speaker 1: and it's a little uncanny because that first time you 776 00:53:02,960 --> 00:53:04,920 Speaker 1: look at it, you're like, oh, yeah, that's a chimpanzee, 777 00:53:04,960 --> 00:53:08,439 Speaker 1: and then you're like, it's this is it's a little 778 00:53:08,480 --> 00:53:10,560 Speaker 1: it's like an uncanny valley thing of like, this is 779 00:53:10,600 --> 00:53:13,480 Speaker 1: a little more human like than I'm used to seeing, 780 00:53:14,200 --> 00:53:16,320 Speaker 1: Like in the next Oh my god, I didn't even 781 00:53:16,520 --> 00:53:20,359 Speaker 1: realize that that was that's crazy. I had to look 782 00:53:20,440 --> 00:53:23,600 Speaker 1: up what a chimpanzee normally looks like in order to 783 00:53:23,680 --> 00:53:27,240 Speaker 1: remember that they didn't have the black in the eyes. 784 00:53:27,800 --> 00:53:31,359 Speaker 1: Is this? Oh is this? What's the ape world movie? 785 00:53:31,440 --> 00:53:34,240 Speaker 1: Planet of the Apes? Did they do that in Planet 786 00:53:34,239 --> 00:53:37,880 Speaker 1: of the Apes? A good question. Planet, Yeah, they have white, 787 00:53:37,960 --> 00:53:42,840 Speaker 1: they have sclera. They have white white sclera. That that's 788 00:53:42,880 --> 00:53:46,560 Speaker 1: what gave them more human expressions, right right, Yeah, that's 789 00:53:46,640 --> 00:53:50,359 Speaker 1: a that's a good point because he looks the one 790 00:53:50,440 --> 00:53:52,640 Speaker 1: the picture here looks like the main character from Rise 791 00:53:52,680 --> 00:53:55,960 Speaker 1: of the Planet of the Apes. Yeah. I mean, for 792 00:53:56,000 --> 00:54:00,759 Speaker 1: all we know, he could be um just retired now, 793 00:54:02,040 --> 00:54:05,359 Speaker 1: but like you know, I think that, yeah, because that's 794 00:54:05,360 --> 00:54:08,120 Speaker 1: the case in a lot of like maybe that's why 795 00:54:08,320 --> 00:54:11,799 Speaker 1: the Lion King live action thing was really lifeless. Did 796 00:54:11,800 --> 00:54:15,279 Speaker 1: they put whites in the eyes of the animals in 797 00:54:15,280 --> 00:54:20,640 Speaker 1: that movie or live action? Three D King? Live action? 798 00:54:20,920 --> 00:54:23,680 Speaker 1: Well they called it the live action ones, but it's 799 00:54:24,400 --> 00:54:26,879 Speaker 1: none of it. I don't think they did. I see. 800 00:54:27,040 --> 00:54:29,720 Speaker 1: I think that was a mistake. Yeah, definitely. It definitely 801 00:54:29,760 --> 00:54:32,600 Speaker 1: feels more human when they have the whites of the eyes, right, 802 00:54:32,719 --> 00:54:36,400 Speaker 1: that's crazy. Yeah, I really just thought that's what chimps 803 00:54:36,400 --> 00:54:37,840 Speaker 1: look like. I was like, why is this? Is this 804 00:54:38,000 --> 00:54:43,760 Speaker 1: just a funny picture? Katie included thing that's so wild? 805 00:54:44,160 --> 00:54:49,080 Speaker 1: How frequent is this is this mutation? It's very rare, 806 00:54:49,239 --> 00:54:52,000 Speaker 1: and it doesn't seem to actually like catch on. It's 807 00:54:52,080 --> 00:54:54,640 Speaker 1: not none of the chimps are really having it that 808 00:54:54,760 --> 00:54:58,800 Speaker 1: it's not a which I think is what's interesting about 809 00:54:58,840 --> 00:55:01,360 Speaker 1: it is that you think, like, oh, this is really 810 00:55:01,360 --> 00:55:05,840 Speaker 1: helpful and humans potentially, but it hasn't really taken hold. 811 00:55:06,600 --> 00:55:10,920 Speaker 1: It hasn't taken the chimp world by storm. And so 812 00:55:11,160 --> 00:55:14,879 Speaker 1: it's because I mean, when we think about chimpanzees, they're 813 00:55:14,920 --> 00:55:19,080 Speaker 1: not our ancestors. They are a cousin of ours like 814 00:55:19,160 --> 00:55:24,040 Speaker 1: on the evolutionary tree. And so the idea that like, oh, 815 00:55:24,320 --> 00:55:27,480 Speaker 1: chimpanzees are just like a hop, skip and a jump 816 00:55:27,520 --> 00:55:31,480 Speaker 1: away from evolving into humans is not really true because 817 00:55:32,239 --> 00:55:37,279 Speaker 1: primates like chimpanzees do not have the same use for 818 00:55:37,400 --> 00:55:42,040 Speaker 1: tracking eye gaze as early humans may have had. Uh So, 819 00:55:42,160 --> 00:55:47,160 Speaker 1: in fact, like there may be a detriment to having that. 820 00:55:47,239 --> 00:55:49,680 Speaker 1: I like, you may not be able to be as sneaky, 821 00:55:49,800 --> 00:55:51,880 Speaker 1: like if you if it's hard to see where your 822 00:55:51,920 --> 00:55:54,919 Speaker 1: gaze is, it's hard to see like where you're looking at, 823 00:55:55,080 --> 00:55:59,400 Speaker 1: and maybe it's makes it a little easier to be sneaky, 824 00:55:59,440 --> 00:56:01,000 Speaker 1: like if you see some food and you want to 825 00:56:01,040 --> 00:56:07,520 Speaker 1: grab it or something. Wait, so I'm reading up of 826 00:56:07,640 --> 00:56:11,239 Speaker 1: lowland gorillas possessed some degree of depigmentation, with eleven point 827 00:56:11,280 --> 00:56:14,360 Speaker 1: five percent of averted gazing eyes showing a completely white 828 00:56:14,360 --> 00:56:17,759 Speaker 1: scal sclera a lot of human Well, but this is 829 00:56:17,800 --> 00:56:21,160 Speaker 1: like this probably is from a sample of something. Um 830 00:56:21,200 --> 00:56:24,799 Speaker 1: that's just like a quick there's no way there, yeah, 831 00:56:24,880 --> 00:56:27,560 Speaker 1: there's well, this isn't guerrillas, but it's probably a specific 832 00:56:27,600 --> 00:56:32,440 Speaker 1: type of gorilla like lowland versus mountains. And also I 833 00:56:32,560 --> 00:56:35,040 Speaker 1: just like I literally was just googling it, so I 834 00:56:35,040 --> 00:56:37,560 Speaker 1: don't have the context at all, but it seems like 835 00:56:38,760 --> 00:56:43,160 Speaker 1: western Lowland and mountain gorilla faces were acquired. That's interesting. 836 00:56:43,200 --> 00:56:47,680 Speaker 1: I wonder if, like they have in their populations, they 837 00:56:47,719 --> 00:56:52,560 Speaker 1: have a specific kind of selective pressure that makes it 838 00:56:52,960 --> 00:56:56,359 Speaker 1: more beneficial for them to have be able to better 839 00:56:56,440 --> 00:56:59,240 Speaker 1: track their I gaze. Yeah, and it also is related 840 00:56:59,280 --> 00:57:03,239 Speaker 1: to direct says averted gazes or something. It looks like 841 00:57:03,680 --> 00:57:06,920 Speaker 1: that's this is so interesting. I'm fascinated by that, just 842 00:57:07,600 --> 00:57:11,640 Speaker 1: like gorillas with whites in their eyes, and it's uh, 843 00:57:12,760 --> 00:57:16,960 Speaker 1: I don't know, it's intense. It's an intense it really is. 844 00:57:17,200 --> 00:57:20,000 Speaker 1: Once you it's like the yel ship bricks. When you 845 00:57:20,040 --> 00:57:23,360 Speaker 1: see it, like when you realize that that's not normal, 846 00:57:23,480 --> 00:57:26,680 Speaker 1: you're like, oh my gosh. It actually brings me to 847 00:57:26,840 --> 00:57:30,520 Speaker 1: an article that says the scientific reason the Internet wants 848 00:57:30,560 --> 00:57:36,280 Speaker 1: to bang this handsome gorilla, Oh my god, and it's 849 00:57:36,600 --> 00:57:42,400 Speaker 1: they break it down into the fact that the uh 850 00:57:42,560 --> 00:57:46,200 Speaker 1: sclera are white or something. Yeah, okay, I mean I 851 00:57:46,200 --> 00:57:48,720 Speaker 1: guess so it looks more human. I guess it makes 852 00:57:48,760 --> 00:57:54,880 Speaker 1: gorillas sexier. All right, that's that's far. Japanese women go 853 00:57:55,040 --> 00:58:02,240 Speaker 1: ape over surprisingly handsome gorilla. This is from this is how, 854 00:58:02,360 --> 00:58:09,200 Speaker 1: this is how how desperate women are kidding. I'll check 855 00:58:09,240 --> 00:58:12,920 Speaker 1: this zoo. It's a. It's a. It's a bad sign 856 00:58:13,040 --> 00:58:17,000 Speaker 1: for bumble and tinder if people are just like pulling 857 00:58:17,080 --> 00:58:24,640 Speaker 1: up the zop Jesus. They made a pillow in the 858 00:58:24,680 --> 00:58:31,080 Speaker 1: shape of shabani for women to sleep with, so I 859 00:58:31,160 --> 00:58:34,960 Speaker 1: know to avoid it. What's the address? Well, this was 860 00:58:35,080 --> 00:58:38,240 Speaker 1: Japan Times. It was like an article about it. But 861 00:58:39,000 --> 00:58:41,360 Speaker 1: send me the links so I know never to go there. 862 00:58:43,600 --> 00:58:45,800 Speaker 1: You're like, yeah, send me the link. I don't want 863 00:58:45,800 --> 00:58:48,240 Speaker 1: to go there. I'm not going to get a body pillow. 864 00:58:48,360 --> 00:58:55,320 Speaker 1: How much does it cost? Um? Yeah, but in a 865 00:58:55,360 --> 00:59:00,080 Speaker 1: catered species in the canines like wild wolves coyote as 866 00:59:00,120 --> 00:59:03,520 Speaker 1: you can actually see as their eyes become have a 867 00:59:03,600 --> 00:59:08,080 Speaker 1: higher um contrast between their pupils and the rest of 868 00:59:08,080 --> 00:59:13,120 Speaker 1: their eyes. Is it tracts with the more social species. 869 00:59:13,160 --> 00:59:18,000 Speaker 1: So wild wolves and coyotes are both highly social. They 870 00:59:18,040 --> 00:59:21,600 Speaker 1: form packs, a lot of their survival depends on how 871 00:59:21,840 --> 00:59:25,000 Speaker 1: well they work as a team, and they actually have 872 00:59:25,240 --> 00:59:29,600 Speaker 1: much higher contrast eyes between their pupils and their irises, 873 00:59:31,000 --> 00:59:34,520 Speaker 1: which it's a similar function as the sclera. So instead 874 00:59:34,560 --> 00:59:37,880 Speaker 1: of having a white sclera like humans, they'll have like 875 00:59:37,920 --> 00:59:42,920 Speaker 1: a light yellow iris in a in a black pupil, 876 00:59:43,960 --> 00:59:46,920 Speaker 1: so their eye movement can be tracked. And among the 877 00:59:47,040 --> 00:59:51,280 Speaker 1: canid species, wolves and coyotes are the most social and 878 00:59:51,320 --> 00:59:56,840 Speaker 1: cooperative and so more solitary canids like you know, wild 879 00:59:56,920 --> 01:00:02,200 Speaker 1: dogs will have lower contrast eyes. That's so, that's so 880 01:00:02,280 --> 01:00:07,920 Speaker 1: wild that dogs are the less social, like not not 881 01:00:07,920 --> 01:00:11,360 Speaker 1: not like domesticated dogs. Yeah yeah, but like what but 882 01:00:11,440 --> 01:00:16,160 Speaker 1: what are what are our domesticated dogs descendants from wolves 883 01:00:16,280 --> 01:00:22,000 Speaker 1: or from the wild dogs ancestor, But wild dogs aren't 884 01:00:22,040 --> 01:00:26,760 Speaker 1: as closely related to domesticated dogs as it depends on 885 01:00:26,840 --> 01:00:30,360 Speaker 1: the type of wild dogs. So there are some highly 886 01:00:30,480 --> 01:00:35,200 Speaker 1: social wild dogs, and some wild dogs may actually come 887 01:00:35,480 --> 01:00:41,480 Speaker 1: from very early domesticated dogs. It's unclear, like dingoes maybe 888 01:00:41,680 --> 01:00:46,040 Speaker 1: came from early early domesticated dogs. Wild dogs look crazy, 889 01:00:46,080 --> 01:00:49,200 Speaker 1: like they look so weird. They look like they have 890 01:00:49,440 --> 01:00:53,880 Speaker 1: like these big circular ears, like huge circular ears compared 891 01:00:53,920 --> 01:00:57,720 Speaker 1: to their face and there there. Yeah, and their face 892 01:00:57,800 --> 01:01:00,600 Speaker 1: looks like almost like hyena, like you know, like the 893 01:01:02,000 --> 01:01:07,960 Speaker 1: hyenas often but they're another example of like canad because 894 01:01:08,080 --> 01:01:11,760 Speaker 1: wild dogs do actually like the African wild dog uh 895 01:01:11,920 --> 01:01:15,680 Speaker 1: does is pretty social because like they do have somewhat 896 01:01:15,760 --> 01:01:19,959 Speaker 1: high contrasting eyes, maybe not as much as wolves and coyotes, 897 01:01:20,000 --> 01:01:24,800 Speaker 1: but some other examples of like of canids that are 898 01:01:24,840 --> 01:01:31,160 Speaker 1: not that social. Foxes aren't as social. Main wolves aren't 899 01:01:31,160 --> 01:01:35,400 Speaker 1: as social. They will not necessarily have as high contrast 900 01:01:35,600 --> 01:01:40,400 Speaker 1: of an eye as wolves. A really wild looking canaid 901 01:01:40,560 --> 01:01:44,120 Speaker 1: species is the short eared dog. It does not look 902 01:01:44,680 --> 01:01:47,880 Speaker 1: like you would expect a canine to. Look what did 903 01:01:47,880 --> 01:01:51,840 Speaker 1: you say? Maned wolves? Main wolves are one of the 904 01:01:52,440 --> 01:01:57,360 Speaker 1: one of the canaid species. Uh, they're they're wild looking, 905 01:01:57,400 --> 01:02:02,040 Speaker 1: they have really long legs, stunt and then oh yeah, 906 01:02:02,080 --> 01:02:04,680 Speaker 1: those are the weird the weird legged ones. And what 907 01:02:04,760 --> 01:02:07,200 Speaker 1: was the one you just said to have that short 908 01:02:07,400 --> 01:02:12,520 Speaker 1: short eared dogs? Just just google Google and image of 909 01:02:12,560 --> 01:02:15,040 Speaker 1: short ear done. I'm like looking up all of these. 910 01:02:15,760 --> 01:02:21,400 Speaker 1: Oh my gosh, what what is that? It is not related? 911 01:02:21,800 --> 01:02:25,400 Speaker 1: Not this is an example of a wild Canada who 912 01:02:25,480 --> 01:02:31,160 Speaker 1: is not at all related to domesticated dogs. So this 913 01:02:31,280 --> 01:02:35,120 Speaker 1: is a u. I think this is the South American 914 01:02:35,960 --> 01:02:40,840 Speaker 1: uh candid species, and I think actually pretty, it's like 915 01:02:40,840 --> 01:02:44,200 Speaker 1: a pretty primitive species of Canada. But yeah they are, 916 01:02:45,160 --> 01:02:48,200 Speaker 1: they're pretty. They're mixed with like a with a pig 917 01:02:48,320 --> 01:02:53,080 Speaker 1: or something, yeah, or like a or like an ant eater. Yeah, yeah, 918 01:02:53,080 --> 01:02:56,280 Speaker 1: they're they're they're funny looking. But you if you look 919 01:02:56,320 --> 01:02:59,280 Speaker 1: at their eyes, you can see it's like you cannot 920 01:02:59,320 --> 01:03:02,919 Speaker 1: really see the pupil out well. They also there aren't 921 01:03:02,920 --> 01:03:07,360 Speaker 1: that many pictures of them either. Yeah, they're they're very rare. 922 01:03:07,400 --> 01:03:11,040 Speaker 1: They're hard to spot, very elusive, very interesting to see 923 01:03:11,040 --> 01:03:15,120 Speaker 1: how that tracks. And I wonder, like and dogs, like 924 01:03:15,280 --> 01:03:19,200 Speaker 1: even in sort of domesticated dogs, whether that affects because 925 01:03:19,200 --> 01:03:22,040 Speaker 1: like domesticated dogs have all sorts of different eye colors. 926 01:03:22,480 --> 01:03:25,600 Speaker 1: My dog has like brown eyes that almost like perfectly 927 01:03:25,640 --> 01:03:29,640 Speaker 1: blend with her pupils. It's really hard to see her 928 01:03:29,680 --> 01:03:33,160 Speaker 1: pupils unless you're like really staring deep into her eyes 929 01:03:33,200 --> 01:03:37,720 Speaker 1: like I do every day. Um, but I wonder because 930 01:03:37,720 --> 01:03:40,600 Speaker 1: she does not have a good relationship with other dogs. 931 01:03:40,880 --> 01:03:42,680 Speaker 1: I mean, part of that is she was attacked by 932 01:03:42,840 --> 01:03:45,720 Speaker 1: a couple of dogs and so she's just like she's done. 933 01:03:46,680 --> 01:03:51,840 Speaker 1: Um but I wonder if part of her, like because 934 01:03:51,920 --> 01:03:55,680 Speaker 1: she seems to have trouble with other dogs, even friendly ones. 935 01:03:56,680 --> 01:04:01,080 Speaker 1: And I wonder if like dogs with eyes that where 936 01:04:01,120 --> 01:04:03,840 Speaker 1: their eye gaze is harder to track. I wonder if 937 01:04:03,840 --> 01:04:07,280 Speaker 1: they ever have more problems socializing with other dogs because 938 01:04:07,400 --> 01:04:11,600 Speaker 1: the other dog can't read their body languages, which I 939 01:04:11,640 --> 01:04:15,400 Speaker 1: don't want my dog compassed right here. Who, I just 940 01:04:15,400 --> 01:04:18,720 Speaker 1: woke up from a nap. I'm sorry. Her eyes are 941 01:04:18,920 --> 01:04:22,080 Speaker 1: very dark and she also doesn't interact with other dogs 942 01:04:22,120 --> 01:04:24,360 Speaker 1: very much. But it's because she's more scared, I think, 943 01:04:24,720 --> 01:04:27,880 Speaker 1: you know. No, Yeah, Cookie is also scared. So we 944 01:04:27,960 --> 01:04:30,480 Speaker 1: have a sample size of two, which, as we know, 945 01:04:30,680 --> 01:04:39,120 Speaker 1: it to draw conclusions poppies science. Yeah, but I don't know, 946 01:04:39,200 --> 01:04:43,200 Speaker 1: because I I I should probably have looked into this 947 01:04:43,320 --> 01:04:46,040 Speaker 1: before I started recording him, just like maybe it's like this, 948 01:04:46,160 --> 01:04:49,200 Speaker 1: and maybe it's like this and I love science. Uh 949 01:04:50,480 --> 01:04:53,160 Speaker 1: but yeah, because we do. We do sound like Twitter, right, 950 01:04:53,280 --> 01:04:56,920 Speaker 1: I know, I know, just wild conjecture with no evidence, 951 01:04:57,000 --> 01:05:00,120 Speaker 1: just like I wonder if it's like this, but it 952 01:05:00,440 --> 01:05:04,000 Speaker 1: you know, I mean, because dogs use each other's body 953 01:05:04,120 --> 01:05:07,960 Speaker 1: language a lot, I think, much more than like facial expression, 954 01:05:08,000 --> 01:05:11,480 Speaker 1: other than like say, they're when they snarl and they 955 01:05:11,520 --> 01:05:14,960 Speaker 1: flash those white teeth, that's easy to see and that's 956 01:05:14,960 --> 01:05:18,120 Speaker 1: an easy expression in their ear position, but they also 957 01:05:18,520 --> 01:05:23,040 Speaker 1: look at each other's like body posture tail position like there, 958 01:05:23,040 --> 01:05:27,160 Speaker 1: whether their hair is up or down, just their overall 959 01:05:28,360 --> 01:05:32,360 Speaker 1: body language. It really helps dogs to communicate. But I 960 01:05:32,400 --> 01:05:35,280 Speaker 1: really do wonder about the eye gaze thing. I'm gonna 961 01:05:35,600 --> 01:05:40,360 Speaker 1: look into that wild how attentive um dogs are to 962 01:05:40,440 --> 01:05:45,160 Speaker 1: body language and how lacking men at clubs are language. 963 01:05:46,960 --> 01:05:49,560 Speaker 1: So like if you say, say, like men are dogs, 964 01:05:49,600 --> 01:05:52,760 Speaker 1: that would actually be a compliment because and they would 965 01:05:52,960 --> 01:05:56,200 Speaker 1: be like really paying attention to you and really toil 966 01:05:56,680 --> 01:06:01,040 Speaker 1: and yeah, like like you're you're a dog. But that's 967 01:06:01,080 --> 01:06:04,080 Speaker 1: good because like you're paying attention to the cues I'm 968 01:06:04,120 --> 01:06:13,000 Speaker 1: throwing out there. So, uh, before we go, I have 969 01:06:13,160 --> 01:06:18,440 Speaker 1: to reveal the answer to last week's mystery animal sound game, 970 01:06:18,680 --> 01:06:22,640 Speaker 1: which is a new thing I'm doing. And I've been 971 01:06:22,640 --> 01:06:27,480 Speaker 1: on the show before season three. Um wait season yeah, 972 01:06:27,520 --> 01:06:32,320 Speaker 1: season three. Don't worry, guys, I got this podcast in control. 973 01:06:33,200 --> 01:06:37,120 Speaker 1: And so every week I am playing a mystery animal 974 01:06:37,200 --> 01:06:43,160 Speaker 1: sound and people can guess from home, ask their coworkers, 975 01:06:43,240 --> 01:06:48,959 Speaker 1: their family, uh, call up your local library and try 976 01:06:49,000 --> 01:06:52,360 Speaker 1: to find out who is making that animal sound. So 977 01:06:52,640 --> 01:06:56,320 Speaker 1: first I want to reveal the answer to last week's sound. 978 01:07:05,080 --> 01:07:10,280 Speaker 1: So who do you think is talking there? Well, now, 979 01:07:10,320 --> 01:07:12,840 Speaker 1: that I've seen a shortier dog that sounds like something weird. 980 01:07:12,920 --> 01:07:18,240 Speaker 1: That dog, it just sounds like so when screaming with 981 01:07:18,280 --> 01:07:26,960 Speaker 1: their jaw like all the way open. Yeah, yeah, that's 982 01:07:26,960 --> 01:07:29,280 Speaker 1: how I wake up every morning. Actually, I just like 983 01:07:29,640 --> 01:07:37,360 Speaker 1: from deep slumber into the existential dread. Yes, So the 984 01:07:37,480 --> 01:07:43,600 Speaker 1: answer is actually the New Guineas Singing Dog. Congratulations to 985 01:07:43,640 --> 01:07:46,680 Speaker 1: everyone who gets the right answer. There is actually a 986 01:07:46,720 --> 01:07:48,960 Speaker 1: bit of a tie this week's We have four winners. 987 01:07:49,000 --> 01:07:54,400 Speaker 1: That is Shana, Jared Miller, Michael Daniels, and Instagram user 988 01:07:54,480 --> 01:07:58,400 Speaker 1: open Road before me. Great job you guys, great guesses. 989 01:07:59,080 --> 01:08:02,640 Speaker 1: So the New Guinea Singing Dog is a dog that 990 01:08:02,680 --> 01:08:06,800 Speaker 1: looks similar to a dingo, but is considered to be 991 01:08:07,000 --> 01:08:11,040 Speaker 1: a breed of domesticated dog and not its own species. 992 01:08:11,760 --> 01:08:15,200 Speaker 1: Oh my god, New Guinea singing Dog. It looks like 993 01:08:15,240 --> 01:08:19,080 Speaker 1: a dingo, but it's not a dingo, and it's so cute, 994 01:08:19,400 --> 01:08:24,240 Speaker 1: very cute. Uh. It has this really haunting call. It's 995 01:08:24,280 --> 01:08:27,040 Speaker 1: one of the rarest breeds of dogs in the world, 996 01:08:27,280 --> 01:08:30,920 Speaker 1: with an ancient lineage. It was in fact once thought 997 01:08:30,960 --> 01:08:34,680 Speaker 1: to be a separate species of canad but they are 998 01:08:34,720 --> 01:08:38,200 Speaker 1: in fact a breed of dog that has a segment 999 01:08:38,240 --> 01:08:42,120 Speaker 1: of its population, living fairly and often there. They like 1000 01:08:42,320 --> 01:08:46,000 Speaker 1: live cohabitate with humans, and instead of having a single owner, 1001 01:08:46,120 --> 01:08:50,920 Speaker 1: they live like in a village amongst humans um and 1002 01:08:51,240 --> 01:08:57,040 Speaker 1: so their howl, unlike other like wolf or doghowls, utilizes 1003 01:08:57,080 --> 01:09:01,720 Speaker 1: a pulsed, high frequency trill, which gives it that like 1004 01:09:02,040 --> 01:09:05,120 Speaker 1: rattling sound, like it's about to eat your face in 1005 01:09:05,120 --> 01:09:11,839 Speaker 1: a monster movie. That's wild. So onto our new mystery 1006 01:09:11,920 --> 01:09:16,360 Speaker 1: animal sound of the weak. Uh. Here is a hint. 1007 01:09:17,040 --> 01:09:20,120 Speaker 1: This may sound like a machine gun, but unless you're 1008 01:09:20,160 --> 01:09:23,120 Speaker 1: an insect, the only thing you'll really have to worry 1009 01:09:23,120 --> 01:09:26,120 Speaker 1: about is getting smacked in the face by its enormous tail, 1010 01:09:26,280 --> 01:09:29,320 Speaker 1: which is I guess a kind of specific hint. I 1011 01:09:29,360 --> 01:09:32,519 Speaker 1: hope it's helpful. Anyways, here's the sound. Well, that's my 1012 01:09:32,600 --> 01:09:36,840 Speaker 1: dog gets you. That sound, that's that's my dog Cookie. 1013 01:09:36,880 --> 01:09:40,240 Speaker 1: It's okay, I wasn't talking about you behind your back. 1014 01:09:40,920 --> 01:09:51,120 Speaker 1: I wasn't. I was okay, here we go. Nice. That 1015 01:09:51,280 --> 01:09:54,600 Speaker 1: definitely sounded like a machine gun. So if it's a 1016 01:09:54,640 --> 01:09:59,439 Speaker 1: machine gun, it's definitely American. And it's some kind of animal. 1017 01:10:00,120 --> 01:10:04,240 Speaker 1: That's that's another hint. Incredible, Yeah, it's it's not a gun. 1018 01:10:04,840 --> 01:10:07,439 Speaker 1: And it kind of sounds a little bit like not 1019 01:10:07,560 --> 01:10:10,200 Speaker 1: just like a gun, but like a computer game gun, 1020 01:10:10,280 --> 01:10:14,320 Speaker 1: you know what I mean. Yeah, we're like cartoony. Yeah yeah, 1021 01:10:14,360 --> 01:10:17,479 Speaker 1: do you have any guests this Polo? Oh? And he 1022 01:10:17,520 --> 01:10:22,280 Speaker 1: said it's so it has a tail. I'm sort of 1023 01:10:22,439 --> 01:10:26,960 Speaker 1: so is it some sort of lizard? That doesn't make sense? 1024 01:10:27,360 --> 01:10:32,400 Speaker 1: I don't know why I said that that makes a 1025 01:10:32,520 --> 01:10:36,559 Speaker 1: machine gun sound, that has a tail. I have no idea. 1026 01:10:36,680 --> 01:10:40,639 Speaker 1: I have no idea. Well, you can find out next 1027 01:10:40,720 --> 01:10:42,640 Speaker 1: week or maybe I'll tell you after the show, but 1028 01:10:42,720 --> 01:10:46,400 Speaker 1: you have to get a secret. Okay, okay, okay, next Wednesday, 1029 01:10:46,400 --> 01:10:49,960 Speaker 1: I'll reveal the answer. And if you think you the listener, 1030 01:10:50,000 --> 01:10:52,280 Speaker 1: think you may have an idea, a gift, or even 1031 01:10:52,320 --> 01:10:54,519 Speaker 1: if you have a question or a picture of your pet, 1032 01:10:55,000 --> 01:10:57,280 Speaker 1: you can write to me at Creature feature Pot at 1033 01:10:57,360 --> 01:11:00,479 Speaker 1: gmail dot com, Creature feature Pot on Instagram, I'm creat 1034 01:11:00,520 --> 01:11:04,880 Speaker 1: your feet pot on Twitter. That's eighteenth that is something 1035 01:11:04,960 --> 01:11:08,680 Speaker 1: very different plan. Where can the people find you? I'm 1036 01:11:08,720 --> 01:11:11,519 Speaker 1: at Polo Vignal and everywhere. P A l l A 1037 01:11:11,680 --> 01:11:14,439 Speaker 1: v I g U n A l A N. That's 1038 01:11:14,479 --> 01:11:18,120 Speaker 1: on Instagram, Twitter, Facebook, I'm on clubhouse now I do 1039 01:11:18,200 --> 01:11:21,559 Speaker 1: shows on Clubhouse. But yeah, just check me out. I 1040 01:11:21,560 --> 01:11:25,400 Speaker 1: put my my shows up on my website pologanland dot com. 1041 01:11:25,640 --> 01:11:29,439 Speaker 1: Check it out. It's very funny. And you'll never know 1042 01:11:29,479 --> 01:11:31,639 Speaker 1: it though, because I'm gonna edit her out and pretend 1043 01:11:31,640 --> 01:11:37,639 Speaker 1: like all of her jokes. Uh. And yeah, you can 1044 01:11:37,680 --> 01:11:42,240 Speaker 1: find me on Twitter at Katie Golden um. And let's 1045 01:11:42,280 --> 01:11:43,960 Speaker 1: see what else do I do at the end of 1046 01:11:44,000 --> 01:11:47,000 Speaker 1: these shows? Oh yeah, Uh, if you enjoyed the show 1047 01:11:47,040 --> 01:11:49,200 Speaker 1: and you want to give me a rating review, I 1048 01:11:49,280 --> 01:11:53,320 Speaker 1: really appreciate that. That really does help with the robots 1049 01:11:53,439 --> 01:11:56,120 Speaker 1: that go through the algorithm and they're like, hey, this 1050 01:11:56,160 --> 01:11:59,200 Speaker 1: show is good. Uh. And I read all of them 1051 01:11:59,479 --> 01:12:01,840 Speaker 1: and I really appreciate them. I mean, it warms my 1052 01:12:01,920 --> 01:12:04,400 Speaker 1: heart to see your feedback, even when you're like, hey, 1053 01:12:04,680 --> 01:12:07,639 Speaker 1: stop stop talking about how much you like to eat pizza. 1054 01:12:07,720 --> 01:12:11,439 Speaker 1: We get it. Uh. And thank you to the Space 1055 01:12:11,479 --> 01:12:15,920 Speaker 1: Classics for their super awesome song Exo Alumina. Creature features 1056 01:12:15,960 --> 01:12:19,519 Speaker 1: a production of I Heart Radio. For more podcasts like 1057 01:12:19,640 --> 01:12:22,200 Speaker 1: the one you just heard, visit the I Heart Radio app, 1058 01:12:22,240 --> 01:12:26,559 Speaker 1: Apple podcast, or Hey guess what anywhere anywhere you listen 1059 01:12:26,600 --> 01:12:30,599 Speaker 1: to podcasts, I don't judge you. I'm not the podcast police. 1060 01:12:31,479 --> 01:12:34,839 Speaker 1: I'm not. I'm not. I'm not watching you from the darkness. 1061 01:12:35,640 --> 01:12:37,680 Speaker 1: See you next Wednesday by