1 00:00:01,120 --> 00:00:04,560 Speaker 1: Welcome to stuff you should know from how Stuff Works 2 00:00:04,600 --> 00:00:14,200 Speaker 1: dot com. Hey, and welcome to the podcast. I'm Josh Clark, 3 00:00:14,280 --> 00:00:18,400 Speaker 1: and there's Charles W. Chuck Bryant. It's just us. There's 4 00:00:18,440 --> 00:00:22,479 Speaker 1: no producer, there's no guest producer, there's no nothing, just 5 00:00:22,560 --> 00:00:25,400 Speaker 1: a ghost in the chair. Why is it whenever we're 6 00:00:25,400 --> 00:00:27,400 Speaker 1: in this room, just the two of us, I go 7 00:00:27,520 --> 00:00:30,840 Speaker 1: back to like elementary school or middle school and feel 8 00:00:30,880 --> 00:00:35,760 Speaker 1: like we should just start drinking whiskey or something. Isn't 9 00:00:35,760 --> 00:00:40,600 Speaker 1: that weird? Uh? Yeah, well, I guess Jerry kind of 10 00:00:40,640 --> 00:00:44,160 Speaker 1: provides like a teacher like presence, and I guess Nol 11 00:00:44,320 --> 00:00:46,919 Speaker 1: is kind of like a substitute teacher like presidents. So 12 00:00:47,479 --> 00:00:49,760 Speaker 1: I didn't ever have the urge to drink whiskey in 13 00:00:49,840 --> 00:00:52,879 Speaker 1: elementary school. But I can see where you're coming from. 14 00:00:52,920 --> 00:00:55,320 Speaker 1: It was eighth grade before that started from me. I 15 00:00:55,360 --> 00:00:57,320 Speaker 1: did drink to college. But I don't know. It's just 16 00:00:58,280 --> 00:01:00,760 Speaker 1: and neither one of the Jerry. No one would care. 17 00:01:00,840 --> 00:01:03,640 Speaker 1: Even it's just some weird thing about the teacher leaving 18 00:01:03,640 --> 00:01:07,119 Speaker 1: the room. After all these years, I'm still like, all right, 19 00:01:07,200 --> 00:01:10,520 Speaker 1: I need to act up right. My thing went more 20 00:01:10,560 --> 00:01:14,000 Speaker 1: towards paper airplanes than breaking out the pint bottle whiskey 21 00:01:14,040 --> 00:01:18,679 Speaker 1: I have in my sock. Again, I didn't even drink 22 00:01:18,760 --> 00:01:20,480 Speaker 1: until college, so of course I wasn't doing that. I 23 00:01:20,560 --> 00:01:23,640 Speaker 1: just probably started joking around. No, I know what you mean, 24 00:01:23,720 --> 00:01:28,880 Speaker 1: but today's Chuck, but hit the bottle right. Actually, today's 25 00:01:28,959 --> 00:01:31,920 Speaker 1: Chuck is all business. Because I hate to tell you this, buddy, 26 00:01:32,040 --> 00:01:35,920 Speaker 1: but you're doing your job right now. That's true. We 27 00:01:36,040 --> 00:01:39,360 Speaker 1: both are because this is our job to podcast. It's 28 00:01:39,360 --> 00:01:43,560 Speaker 1: funny during the the Emily and Chuck pre Oscar's Mini 29 00:01:43,560 --> 00:01:45,880 Speaker 1: Crush show, it was kind of dragging on. She's like, 30 00:01:45,920 --> 00:01:48,160 Speaker 1: this starting to feel like a job, and I was like, 31 00:01:48,400 --> 00:01:52,559 Speaker 1: this is my job. This is the job. The job 32 00:01:52,640 --> 00:01:54,720 Speaker 1: we we say. We talked about it like cops talk 33 00:01:54,760 --> 00:02:00,280 Speaker 1: about their jobs, good jobs. We're real, real podcasters that job. 34 00:02:00,960 --> 00:02:03,040 Speaker 1: Remember that show The Wire. Have you ever heard of it? 35 00:02:04,080 --> 00:02:07,360 Speaker 1: I'm just kidding. We've talked about it before. I remember 36 00:02:07,600 --> 00:02:12,000 Speaker 1: they called that one uh cop, real police, Yeah, real police. 37 00:02:12,160 --> 00:02:15,520 Speaker 1: I can't remember her name. Yeah, they said a lot 38 00:02:15,560 --> 00:02:18,680 Speaker 1: on that show. Yeah, but they mostly talked about one 39 00:02:18,960 --> 00:02:24,520 Speaker 1: officer in particular, police trying to think of Yeah, right, 40 00:02:25,400 --> 00:02:30,520 Speaker 1: there you go, So let's start real podcasting is this 41 00:02:30,560 --> 00:02:33,959 Speaker 1: one gonna be a stinker. No, it's not. Actually, it's 42 00:02:34,080 --> 00:02:38,160 Speaker 1: actually really do you know why, because it has the 43 00:02:38,200 --> 00:02:41,440 Speaker 1: hallmarks of a good episode, And I'm gonna I'm gonna 44 00:02:41,480 --> 00:02:43,639 Speaker 1: peel the curtain back a little bit for everybody, Chuck. 45 00:02:44,840 --> 00:02:47,320 Speaker 1: One of the hallmarks of a good episode, at least 46 00:02:47,360 --> 00:02:52,239 Speaker 1: of stuff you should know, is that there is controversy 47 00:02:52,400 --> 00:02:55,200 Speaker 1: associated with something even where there doesn't seem to be, 48 00:02:56,440 --> 00:03:00,200 Speaker 1: and that there are people who are either getting drew 49 00:03:00,240 --> 00:03:05,680 Speaker 1: it over, suffering, being neglected, being abused. There is some 50 00:03:05,880 --> 00:03:08,960 Speaker 1: group of people who the rest of the world aren't 51 00:03:08,960 --> 00:03:12,360 Speaker 1: really thinking of, um, who are who are suffering at 52 00:03:12,360 --> 00:03:15,400 Speaker 1: the hands of other people. And this this actually, this 53 00:03:15,440 --> 00:03:19,640 Speaker 1: episode has all that, all right, Surprisingly, I'll let you 54 00:03:19,680 --> 00:03:24,600 Speaker 1: guys guess where that stuff comes in. Alright, So we're 55 00:03:24,600 --> 00:03:30,360 Speaker 1: talking about false positives, and here's what that is. If 56 00:03:30,360 --> 00:03:33,120 Speaker 1: you've ever been to the doctor, I've had a medical 57 00:03:33,160 --> 00:03:39,480 Speaker 1: test done generally, well, not generally always, you will get 58 00:03:39,520 --> 00:03:43,040 Speaker 1: one of four results. Yeah, good point. You can get 59 00:03:43,040 --> 00:03:45,960 Speaker 1: a true positive. And remember, when you're getting a medical 60 00:03:45,960 --> 00:03:50,760 Speaker 1: test back, positive is negative. Yeah, usually means bad news. 61 00:03:51,000 --> 00:03:53,280 Speaker 1: Positive is not good. They don't say I have news, 62 00:03:53,760 --> 00:03:56,400 Speaker 1: I have good news. For you. Your results are positive, 63 00:03:57,680 --> 00:03:59,600 Speaker 1: it's a little bit of a mind trick that you 64 00:03:59,640 --> 00:04:04,920 Speaker 1: need to reform. But positive is you have this condition. Right. 65 00:04:05,000 --> 00:04:09,640 Speaker 1: It means that the the test that that searches for 66 00:04:09,840 --> 00:04:14,880 Speaker 1: a condition found a result. It is confirmed as yes. Right, 67 00:04:14,960 --> 00:04:18,159 Speaker 1: so that's it should say that's a true positive. Right. Yeah, 68 00:04:18,160 --> 00:04:20,280 Speaker 1: then you've got a true negative, which means you don't 69 00:04:20,320 --> 00:04:24,039 Speaker 1: have this. However, I feel like me or probably you 70 00:04:24,120 --> 00:04:27,479 Speaker 1: and most people, you say that's good news, but I 71 00:04:27,560 --> 00:04:30,040 Speaker 1: should like to get a confirmation on that. Yeah, how 72 00:04:30,040 --> 00:04:32,640 Speaker 1: do you know? How do you know? Doc? Then you 73 00:04:32,640 --> 00:04:34,479 Speaker 1: can get a false positive, which is what we're talking 74 00:04:34,480 --> 00:04:38,000 Speaker 1: about here, which is they say you have this condition, 75 00:04:38,080 --> 00:04:40,400 Speaker 1: like let's say you have cancer. I'm sorry to tell you, 76 00:04:40,640 --> 00:04:43,159 Speaker 1: but you don't, as it turns out later on, which 77 00:04:43,200 --> 00:04:46,919 Speaker 1: is great. False positives are kind of they should call 78 00:04:46,960 --> 00:04:50,640 Speaker 1: it the new lease on life result, right, the Dabney 79 00:04:50,640 --> 00:04:53,159 Speaker 1: Coleman out of time result. And then the worst of 80 00:04:53,200 --> 00:04:57,919 Speaker 1: all probably is the negative. Agreed. Man, I'm glad you 81 00:04:57,960 --> 00:05:00,800 Speaker 1: said that, because this this article just walks right past 82 00:05:00,839 --> 00:05:05,120 Speaker 1: that fact. That means results say you're fine, but it 83 00:05:05,120 --> 00:05:09,880 Speaker 1: turns out that you're not. Your your toast, so whatever 84 00:05:09,960 --> 00:05:12,640 Speaker 1: the lead and not even good avocado toast. You're bad 85 00:05:12,680 --> 00:05:16,880 Speaker 1: burnt toast right, exactly terrible stuff with that really cheap 86 00:05:16,920 --> 00:05:20,200 Speaker 1: sliced cheese that nobody would want to eat. What's what's 87 00:05:20,240 --> 00:05:24,120 Speaker 1: the opposite of a lease on life to result um 88 00:05:24,160 --> 00:05:28,640 Speaker 1: early death? Sudden early death out of the blue, Although 89 00:05:28,680 --> 00:05:30,839 Speaker 1: there is something to be said about that, about just 90 00:05:30,920 --> 00:05:34,200 Speaker 1: not knowing right just out of nowhere, bay up, you 91 00:05:34,400 --> 00:05:37,800 Speaker 1: just fall over dead. That's not necessarily the worst way 92 00:05:37,839 --> 00:05:39,839 Speaker 1: to go. Yeah, I guess I was thinking more in 93 00:05:39,880 --> 00:05:43,440 Speaker 1: the play on words of instead of a new lease 94 00:05:43,480 --> 00:05:46,960 Speaker 1: on life, something to do with renting in your landlord, 95 00:05:47,320 --> 00:05:53,039 Speaker 1: so an old and uh, we'll figure this one later 96 00:05:53,279 --> 00:05:55,440 Speaker 1: and dub it in Wait, what's it called when you 97 00:05:55,440 --> 00:06:01,239 Speaker 1: get kicked out of your apartment? An old eviction death? God, 98 00:06:02,440 --> 00:06:06,320 Speaker 1: we did it, chuck man. So those are if you 99 00:06:06,400 --> 00:06:08,360 Speaker 1: take a test at the doctor, those are the four 100 00:06:08,440 --> 00:06:12,440 Speaker 1: possible results you can get. What's really interesting here, and 101 00:06:12,480 --> 00:06:14,600 Speaker 1: this is something that you're going to want to remember. 102 00:06:14,720 --> 00:06:16,520 Speaker 1: And after you hear the rest of what we have 103 00:06:16,640 --> 00:06:19,279 Speaker 1: to say, you're really gonna want to remember this. But 104 00:06:19,440 --> 00:06:22,400 Speaker 1: when you hear something like this test that I'm about 105 00:06:22,440 --> 00:06:26,520 Speaker 1: to give you is accurate It doesn't mean that if 106 00:06:26,520 --> 00:06:29,320 Speaker 1: it comes back with a positive result that says you 107 00:06:29,400 --> 00:06:32,480 Speaker 1: have this thing. It doesn't mean there's a nine chance 108 00:06:32,560 --> 00:06:35,480 Speaker 1: that you have that. It just means that when they 109 00:06:35,480 --> 00:06:39,320 Speaker 1: say a test is accurate, that if if you do 110 00:06:39,520 --> 00:06:44,560 Speaker 1: have that disease, there's a chance that this test will 111 00:06:44,600 --> 00:06:50,200 Speaker 1: catch it. Okay, huge, huge difference between those two things. Okay, 112 00:06:50,600 --> 00:06:53,760 Speaker 1: that's step one. So really what this is saying is 113 00:06:53,800 --> 00:06:57,440 Speaker 1: that this test doesn't let very many false negatives get through. 114 00:06:58,200 --> 00:07:00,000 Speaker 1: And if you look at the numbers, this is how 115 00:07:00,040 --> 00:07:03,039 Speaker 1: that works out. If you have ten thousand people chuck, 116 00:07:04,279 --> 00:07:09,960 Speaker 1: and they take a test that's accurate. Uh and and 117 00:07:10,000 --> 00:07:13,600 Speaker 1: this is so ten thousand people and the them don't 118 00:07:13,640 --> 00:07:16,119 Speaker 1: have this and it's a ninety nine percent accurate test, 119 00:07:16,720 --> 00:07:20,680 Speaker 1: there's going to be one hundred that come back positive 120 00:07:21,120 --> 00:07:26,840 Speaker 1: out of ten thousand. Okay, nine of those positive results 121 00:07:27,000 --> 00:07:30,560 Speaker 1: are going to be true. One is going to be 122 00:07:31,080 --> 00:07:36,720 Speaker 1: a false negative. Okay, Okay, are going to be negative. 123 00:07:36,840 --> 00:07:40,880 Speaker 1: They're gonna come back negative. One are going to be 124 00:07:40,920 --> 00:07:46,280 Speaker 1: true negatives, but are going to actually be false positives. Right. 125 00:07:47,120 --> 00:07:48,840 Speaker 1: I know this is really mind bending, but if you 126 00:07:49,040 --> 00:07:51,320 Speaker 1: if you take the numbers like this, that means that 127 00:07:51,560 --> 00:07:55,200 Speaker 1: only one out of nine thousand, eight hundred and two 128 00:07:55,240 --> 00:07:58,640 Speaker 1: people had a false negative. So that's a big deal. 129 00:07:58,880 --> 00:08:01,040 Speaker 1: As you said, that's the big daddy, that's the one 130 00:08:01,040 --> 00:08:04,680 Speaker 1: you've got to really watch out for. But nine out 131 00:08:04,680 --> 00:08:09,760 Speaker 1: of a hundred are false positives, which means that this 132 00:08:10,800 --> 00:08:14,560 Speaker 1: accurate test has a fifty percent chance of giving you 133 00:08:14,600 --> 00:08:20,040 Speaker 1: a false positive if you come back positive. Should I 134 00:08:20,120 --> 00:08:22,200 Speaker 1: just not even have said any of that stuff now? 135 00:08:22,280 --> 00:08:25,440 Speaker 1: I think it's just funny that after ten years it's 136 00:08:25,520 --> 00:08:27,960 Speaker 1: done on me that you have to true talents. One 137 00:08:28,080 --> 00:08:32,800 Speaker 1: is explaining extremely complex things in a very easily digestible way, 138 00:08:33,800 --> 00:08:37,680 Speaker 1: and the other is completely confusing me with words that 139 00:08:37,720 --> 00:08:40,480 Speaker 1: come out. Well, this is very confusing stuff. I mean, 140 00:08:40,520 --> 00:08:43,360 Speaker 1: it's not just me, this is BAYSI and statistics. Basically, 141 00:08:44,240 --> 00:08:46,920 Speaker 1: the point of all of this is is that, first 142 00:08:46,960 --> 00:08:50,480 Speaker 1: of all, if you're accurate test comes back that says 143 00:08:50,480 --> 00:08:52,320 Speaker 1: you have something, it doesn't mean you have a ninety 144 00:08:52,360 --> 00:08:55,520 Speaker 1: nine chance of that you have it. Very important number one. 145 00:08:55,840 --> 00:08:58,440 Speaker 1: Number two, if it does say you have it, there's 146 00:08:58,440 --> 00:09:02,080 Speaker 1: a fifty chance that a test is wrong even if 147 00:09:02,080 --> 00:09:07,400 Speaker 1: it's accurate test. That's a big thing to remember that 148 00:09:07,520 --> 00:09:10,719 Speaker 1: if your doctor doesn't explain that to you, you punch him, 149 00:09:11,000 --> 00:09:13,079 Speaker 1: him or her in the arm and you say you're 150 00:09:13,120 --> 00:09:17,080 Speaker 1: not doing your job fully because I'm scared, buddy. Yeah, 151 00:09:17,080 --> 00:09:19,400 Speaker 1: I just got a positive test result and I'm scared 152 00:09:19,440 --> 00:09:22,000 Speaker 1: out of my mind. So if your doctor is not 153 00:09:22,040 --> 00:09:24,920 Speaker 1: going to come for you, hopefully Baysian statistics, well, and 154 00:09:25,000 --> 00:09:27,520 Speaker 1: don't listen to me, go look it up yourself, because 155 00:09:27,600 --> 00:09:29,960 Speaker 1: I'm sure someone else on the internet can explain it 156 00:09:30,000 --> 00:09:36,360 Speaker 1: better than I can. Perhaps Mr Billy Bays in his 157 00:09:36,720 --> 00:09:40,240 Speaker 1: whole statistical model. Was he a character of Melrose Place? 158 00:09:40,440 --> 00:09:44,600 Speaker 1: I think so. He's a pool cleaner? Um. Alright, So 159 00:09:45,320 --> 00:09:48,320 Speaker 1: with medical testing period, like you said, if your doctor 160 00:09:48,400 --> 00:09:50,439 Speaker 1: is not telling me that, with with any test that 161 00:09:50,480 --> 00:09:53,760 Speaker 1: you take, not all medical tests are created equally. Some 162 00:09:53,840 --> 00:09:57,960 Speaker 1: are really accurate, some aren't as accurate as a well 163 00:09:58,000 --> 00:10:00,160 Speaker 1: that's about say, so they could be. There's accurate as 164 00:10:00,200 --> 00:10:02,480 Speaker 1: they can be, which is to say, maybe not as 165 00:10:02,480 --> 00:10:04,800 Speaker 1: accurate as you would like it to be sure, but 166 00:10:05,160 --> 00:10:07,200 Speaker 1: you really need to talk to your doctor and hopefully 167 00:10:07,240 --> 00:10:10,959 Speaker 1: they're offering this up anyway, like, Hey, what's the deal 168 00:10:10,960 --> 00:10:13,600 Speaker 1: with this test? How reliable is this? Do I need 169 00:10:13,640 --> 00:10:17,600 Speaker 1: to get a second test? Because the whole thing with 170 00:10:17,640 --> 00:10:21,040 Speaker 1: false positives and false negatives and even true positives and 171 00:10:21,080 --> 00:10:26,360 Speaker 1: negatives is there's a bunch of different reasons why uh 172 00:10:26,400 --> 00:10:31,040 Speaker 1: follow up testing is both good and bad. Like sometimes 173 00:10:31,040 --> 00:10:34,040 Speaker 1: these procedures, like the follow up isn't like a pen prick. 174 00:10:34,679 --> 00:10:38,120 Speaker 1: Sometimes it's an actual surgical procedure that you may not 175 00:10:38,200 --> 00:10:40,360 Speaker 1: need a lot of times, and we'll get into these 176 00:10:40,400 --> 00:10:44,840 Speaker 1: more specifically, but there's expense involved. Um, a lot of 177 00:10:44,840 --> 00:10:48,520 Speaker 1: times you don't you didn't need to spend that money, 178 00:10:48,720 --> 00:10:50,760 Speaker 1: but you know, it's hard to say, because you should 179 00:10:50,760 --> 00:10:53,760 Speaker 1: be your own medical advocate and spend whatever money you 180 00:10:53,800 --> 00:10:57,920 Speaker 1: can to ensure that uh, the testing is is reliable. 181 00:10:58,720 --> 00:11:01,440 Speaker 1: And then there are things like the time that it 182 00:11:01,480 --> 00:11:03,800 Speaker 1: takes between these things, like all right, we'll see you. 183 00:11:04,080 --> 00:11:06,520 Speaker 1: We need to follow this up with another test, but 184 00:11:06,559 --> 00:11:08,720 Speaker 1: it's gonna take three months to get you in. And 185 00:11:08,720 --> 00:11:11,640 Speaker 1: in the meantime, in those three months, you're stressing out, 186 00:11:11,640 --> 00:11:14,600 Speaker 1: you're up all night, you can't sleep, your sex drive 187 00:11:14,679 --> 00:11:16,800 Speaker 1: is out the window. That sounds like a silly thing 188 00:11:16,840 --> 00:11:19,240 Speaker 1: to talk about, but it's a real thing, especially when 189 00:11:19,240 --> 00:11:24,480 Speaker 1: you're grown ups like us. Yeah, it's important, um, but 190 00:11:24,559 --> 00:11:27,400 Speaker 1: it's it's a here's a study from two thousand nine said, 191 00:11:27,400 --> 00:11:29,360 Speaker 1: granted this is a little old, but it's from the 192 00:11:29,360 --> 00:11:33,720 Speaker 1: Annals of Family Medicine, and when it came to test 193 00:11:33,760 --> 00:11:40,120 Speaker 1: for prostate long colorrectal and ovarian cancers, they found that 194 00:11:41,120 --> 00:11:47,000 Speaker 1: positive false positives. Uh, after four tests they did tests, 195 00:11:47,200 --> 00:11:50,680 Speaker 1: I think either four tests or fourteen test. After four tests, 196 00:11:51,120 --> 00:11:53,560 Speaker 1: you had about a thirty seven percent chance for men 197 00:11:54,040 --> 00:11:57,360 Speaker 1: in the chance for women for false positive. And then 198 00:11:57,360 --> 00:11:59,360 Speaker 1: the more test you got, the more that went up, 199 00:11:59,640 --> 00:12:03,280 Speaker 1: which is distressing. It is something like if you had 200 00:12:03,360 --> 00:12:07,680 Speaker 1: fourteen tests, all fourteen to the tests that they studied, um, 201 00:12:08,240 --> 00:12:11,240 Speaker 1: you had a sixty point four percent chance for men 202 00:12:11,280 --> 00:12:13,960 Speaker 1: and forty eight point eight percent chance for women of 203 00:12:14,040 --> 00:12:17,400 Speaker 1: coming back with a false positive. And again this isn't 204 00:12:17,440 --> 00:12:19,680 Speaker 1: just like it's yes, you have that new lease on 205 00:12:19,760 --> 00:12:22,840 Speaker 1: life on the other side, but studies have shown like these, 206 00:12:23,080 --> 00:12:26,160 Speaker 1: getting a false positive result from a test, it it 207 00:12:26,200 --> 00:12:29,760 Speaker 1: can be emotionally devastating and it can have an impact 208 00:12:29,840 --> 00:12:32,520 Speaker 1: on your finances if you're a Scrooge McDuck type who's 209 00:12:32,559 --> 00:12:35,120 Speaker 1: only moved by the idea of money, well and your 210 00:12:35,360 --> 00:12:38,600 Speaker 1: physical health because of stress. Yeah, because it's not like 211 00:12:38,640 --> 00:12:41,199 Speaker 1: you're not addicted demand which in the time just because 212 00:12:41,240 --> 00:12:44,440 Speaker 1: you're stress eating the whole time. So that's not good 213 00:12:44,480 --> 00:12:47,720 Speaker 1: for you. What was man? Which man? Which was a 214 00:12:47,800 --> 00:12:51,160 Speaker 1: canned sloppy joe starter. Okay, I know it's a meal, 215 00:12:51,520 --> 00:12:53,760 Speaker 1: and well it's more than a meal. A sandwich is 216 00:12:53,800 --> 00:12:56,200 Speaker 1: a sandwich, but a man which is a meal? Oh 217 00:12:56,240 --> 00:12:58,640 Speaker 1: that's right, I got it wrong. You're like, no, it's 218 00:12:58,679 --> 00:13:02,000 Speaker 1: more than a meal. Even it's even greater than the 219 00:13:02,080 --> 00:13:07,040 Speaker 1: ads per prophecies. Uh so the financial costs like you 220 00:13:07,040 --> 00:13:12,360 Speaker 1: were talking about Scrooge McDuck um forty. They did another 221 00:13:12,440 --> 00:13:15,560 Speaker 1: study of about a thousand people, and this was in 222 00:13:15,840 --> 00:13:19,319 Speaker 1: December of two thousand four and the issue of Cancer 223 00:13:19,559 --> 00:13:23,920 Speaker 1: Epidemiology bio Markers in Prevention that is a legit journal, 224 00:13:24,160 --> 00:13:27,320 Speaker 1: just by the title oh for sure, oh eight, and 225 00:13:27,320 --> 00:13:33,880 Speaker 1: then it says and and wakeboarding. More than participants had 226 00:13:33,880 --> 00:13:37,920 Speaker 1: at least one false positive. Of these people went on 227 00:13:38,000 --> 00:13:41,680 Speaker 1: to receive additional care at a cost of about a 228 00:13:41,720 --> 00:13:47,160 Speaker 1: thousand dollars for women and about eleven for men. So 229 00:13:47,600 --> 00:13:50,800 Speaker 1: that's not chump change. No, it's not um And a 230 00:13:50,840 --> 00:13:53,480 Speaker 1: lot of people say, well, who cares, I got insuredce, Well, 231 00:13:54,000 --> 00:13:56,520 Speaker 1: the health care spending is kind of a problem in 232 00:13:56,559 --> 00:13:59,960 Speaker 1: this country. There's apparently in two thousand five, the National 233 00:14:00,000 --> 00:14:03,959 Speaker 1: Academy of Sciences big shout out to them UM. They 234 00:14:04,000 --> 00:14:07,880 Speaker 1: found that there was thirty of healthcare spending was wasteful 235 00:14:08,040 --> 00:14:12,200 Speaker 1: in the United States in two thousand five, and the 236 00:14:12,240 --> 00:14:15,640 Speaker 1: idea of that gave rise to something. There's a campaign 237 00:14:15,640 --> 00:14:19,520 Speaker 1: called Choosing Wisely. Have you heard of that? Know? So 238 00:14:19,640 --> 00:14:21,840 Speaker 1: it's a campaign called Choosing Wisely. They have a site 239 00:14:21,840 --> 00:14:24,960 Speaker 1: called Choosing Wisely dot org. It's a joint effort between 240 00:14:25,040 --> 00:14:29,160 Speaker 1: the American Board of Internal Medicine, so it's physician based 241 00:14:29,760 --> 00:14:33,640 Speaker 1: and consumer reports, and they're basically saying, like, there are 242 00:14:33,680 --> 00:14:37,680 Speaker 1: a lot of unnecessary tests being performed out there that 243 00:14:37,720 --> 00:14:45,240 Speaker 1: are leading to these unnecessary surgeries, unnecessary expenses, unnecessary anxiety, 244 00:14:45,920 --> 00:14:48,360 Speaker 1: and we want to figure out what they are, and 245 00:14:48,400 --> 00:14:51,520 Speaker 1: we want to start advising people against them, or at 246 00:14:51,600 --> 00:14:55,240 Speaker 1: least advising doctors to advise their patients against them because 247 00:14:55,280 --> 00:14:59,280 Speaker 1: they might be unnecessary. And so this campaign UM has 248 00:14:59,320 --> 00:15:01,600 Speaker 1: really kind of had a big impact is we'll talk 249 00:15:01,640 --> 00:15:03,760 Speaker 1: about in a little bit. You know, the idea of 250 00:15:04,320 --> 00:15:08,680 Speaker 1: breast cancer screening has changed. The recommendations have changed from 251 00:15:08,680 --> 00:15:12,640 Speaker 1: what I understand from this Choosing Wisely campaign as UM 252 00:15:12,640 --> 00:15:16,880 Speaker 1: really kind of just shifted things from well, this over 253 00:15:16,920 --> 00:15:20,280 Speaker 1: abundance of caution can't be harmful to actually there are 254 00:15:20,400 --> 00:15:23,360 Speaker 1: some harms involved in an over abundance of caution. Let's 255 00:15:23,480 --> 00:15:27,480 Speaker 1: kind of UM streamline our caution and make it a 256 00:15:27,560 --> 00:15:31,840 Speaker 1: little more UM laser focused. Should we take a break? Yeah, 257 00:15:31,960 --> 00:15:34,880 Speaker 1: all right, we'll take a break, and I'll I'll hit 258 00:15:34,920 --> 00:15:36,440 Speaker 1: you with a stat right out of the gate when 259 00:15:36,440 --> 00:16:04,960 Speaker 1: we come back. All right, So before break, you were 260 00:16:04,960 --> 00:16:08,960 Speaker 1: talking about UM breast cancer and mammograms in particular, And 261 00:16:08,960 --> 00:16:10,720 Speaker 1: there was a study a few years ago in twenty 262 00:16:11,480 --> 00:16:20,080 Speaker 1: two zero about false positive mammograms and breast cancer over 263 00:16:20,720 --> 00:16:27,200 Speaker 1: diagnoses alone at four billion dollars a year billion. So 264 00:16:27,320 --> 00:16:32,880 Speaker 1: it's it's just such a fine line of uh, striking 265 00:16:32,880 --> 00:16:39,520 Speaker 1: the right note with preventative care and over diagnoses. Yeah, 266 00:16:39,520 --> 00:16:42,880 Speaker 1: and here's here's the problem. Like the tests, it's not 267 00:16:42,920 --> 00:16:46,240 Speaker 1: like they're not out there saving people's lives. Yeah, it's 268 00:16:46,240 --> 00:16:50,000 Speaker 1: not like the people like Dr Papa Nicolau who came 269 00:16:50,080 --> 00:16:53,120 Speaker 1: up with the pepsmere said, oh man, this is gonna 270 00:16:53,160 --> 00:16:56,080 Speaker 1: be like a cash register for Western medicine. That's not 271 00:16:56,120 --> 00:16:59,560 Speaker 1: what these tests were designed for. Unfortunately, they are used 272 00:16:59,560 --> 00:17:03,640 Speaker 1: in some circumstances like that, and probably more circumstances than that. 273 00:17:03,880 --> 00:17:06,520 Speaker 1: They're used again out of an over abundance of caution, 274 00:17:06,600 --> 00:17:09,719 Speaker 1: because no doctor wants to be responsible for missing something 275 00:17:09,760 --> 00:17:12,959 Speaker 1: and their patient um and and the leading to their 276 00:17:13,000 --> 00:17:15,639 Speaker 1: patient dying, so they're using this over abundance of caution. 277 00:17:15,920 --> 00:17:21,400 Speaker 1: The problem is that the tests aren't aren't infallible. They 278 00:17:21,440 --> 00:17:24,960 Speaker 1: do have um they do have accuracy problems, and some 279 00:17:25,040 --> 00:17:28,320 Speaker 1: tests are better than others, or another way to put it, 280 00:17:28,400 --> 00:17:30,480 Speaker 1: some tests are worse than others as far as false 281 00:17:30,480 --> 00:17:35,720 Speaker 1: positives go. And it takes the PEPs mirror in particular. UM. 282 00:17:35,760 --> 00:17:38,640 Speaker 1: With the PEPs mirror, it looks for pre cancerous cervical cells. Right, 283 00:17:39,320 --> 00:17:42,360 Speaker 1: three million, three million women in the United States get 284 00:17:42,440 --> 00:17:48,000 Speaker 1: a positive PEPs mirror result UM. From what I understand, 285 00:17:48,040 --> 00:17:52,040 Speaker 1: every year only three thousand of them have a deadly 286 00:17:52,119 --> 00:17:57,240 Speaker 1: cervical cancer and that of women will get a false 287 00:17:57,280 --> 00:18:01,560 Speaker 1: pepsmere in their lifetime. But is the thing. Four thousand 288 00:18:01,640 --> 00:18:04,959 Speaker 1: women who die in the US every year from cervical cancer, 289 00:18:05,200 --> 00:18:07,399 Speaker 1: most of them did not have a PEPs mirror or 290 00:18:07,480 --> 00:18:09,800 Speaker 1: hadn't gotten a PEPs mirror in the last five years. 291 00:18:09,840 --> 00:18:14,760 Speaker 1: So there's a really there's a there's a tough um 292 00:18:14,960 --> 00:18:20,200 Speaker 1: relationship between using the tests and and and overusing the tests. 293 00:18:20,240 --> 00:18:23,680 Speaker 1: And for every say, I think two thousand women who 294 00:18:23,760 --> 00:18:28,639 Speaker 1: undergo a mammogram, one woman's life is saved. Well, those 295 00:18:28,680 --> 00:18:31,880 Speaker 1: two thousand women, they didn't know whether it was gonna 296 00:18:31,920 --> 00:18:34,000 Speaker 1: be whether they were going to be the one whose 297 00:18:34,000 --> 00:18:36,199 Speaker 1: life was saved or not, so that to them or 298 00:18:36,240 --> 00:18:39,959 Speaker 1: to their doctor, it was worth it. Unfortunately, two hundred 299 00:18:40,040 --> 00:18:43,520 Speaker 1: of them will get false positives, and ten of them 300 00:18:43,520 --> 00:18:49,600 Speaker 1: will undergo unnecessary surgeries, painful, unnecessary surgeries to remove non 301 00:18:49,760 --> 00:18:56,000 Speaker 1: cancerous suspicious cells in their breasts. So there's this idea 302 00:18:56,040 --> 00:18:58,959 Speaker 1: where yes, we need to use these tests, and then 303 00:18:59,000 --> 00:19:01,120 Speaker 1: there's also this idea where we need to use these 304 00:19:01,119 --> 00:19:05,760 Speaker 1: tests better or come up with more accurate tests. Yeah, 305 00:19:05,800 --> 00:19:11,400 Speaker 1: I mean, in particular, mammograms UH and screening for colorectal 306 00:19:11,520 --> 00:19:14,480 Speaker 1: cancer are two of the big ones that can show 307 00:19:14,520 --> 00:19:16,640 Speaker 1: a lot of false positives, and they're sort of under 308 00:19:16,680 --> 00:19:21,000 Speaker 1: the microscope as to how we can correct this UH 309 00:19:21,160 --> 00:19:26,840 Speaker 1: moving forward. UM. For instance, mammograms UM correctly identifies breast 310 00:19:26,880 --> 00:19:31,239 Speaker 1: cancer of the time However, uh, if you're younger, if 311 00:19:31,240 --> 00:19:33,760 Speaker 1: you're a younger woman, or if you have very dense breast, 312 00:19:33,800 --> 00:19:36,840 Speaker 1: you're more likely to have a false positive. And so 313 00:19:37,119 --> 00:19:40,879 Speaker 1: because of this, over the past like even ten to 314 00:19:41,000 --> 00:19:46,760 Speaker 1: fifteen years, they've changed the recommended recommended age a few 315 00:19:46,800 --> 00:19:51,200 Speaker 1: times for who when when you should start getting these mammograms. 316 00:19:51,240 --> 00:19:55,360 Speaker 1: It's gone from I think in two thousand nine they 317 00:19:55,480 --> 00:19:59,080 Speaker 1: recommended between fifty and seventy four. Uh, then I think 318 00:19:59,119 --> 00:20:02,959 Speaker 1: it went down, but mean, um, I think it went 319 00:20:03,000 --> 00:20:05,520 Speaker 1: all the way down to forty. At one point, forty 320 00:20:05,640 --> 00:20:07,920 Speaker 1: was where it started, I think where it started, then 321 00:20:08,000 --> 00:20:10,840 Speaker 1: up to fifty and now I think this is the 322 00:20:10,920 --> 00:20:13,639 Speaker 1: latest as of a few years ago, the A c 323 00:20:13,800 --> 00:20:18,120 Speaker 1: American Cancer Society said if you are at average risk, 324 00:20:18,280 --> 00:20:20,119 Speaker 1: and this is probably how they should do it and 325 00:20:20,200 --> 00:20:23,240 Speaker 1: not just a sweeping age. But if you're an average risk, 326 00:20:23,359 --> 00:20:27,320 Speaker 1: you should start at forty five annually, but you could 327 00:20:27,400 --> 00:20:29,760 Speaker 1: begin as early as forty and I would guess that 328 00:20:29,800 --> 00:20:33,480 Speaker 1: means if it if it runs in your family, and 329 00:20:33,480 --> 00:20:37,960 Speaker 1: then after fifty five every other year, like Emily's mom 330 00:20:38,000 --> 00:20:41,399 Speaker 1: and my mom both went through breast cancer, so Emily 331 00:20:41,440 --> 00:20:45,719 Speaker 1: started getting mammograms. I think it maybe even at forty 332 00:20:46,320 --> 00:20:50,080 Speaker 1: because she was in the higher risk group. Yeah, and 333 00:20:50,080 --> 00:20:55,280 Speaker 1: they're no fun to go through, but she is. Uh. 334 00:20:55,400 --> 00:20:57,120 Speaker 1: I think Emily has a good head on her shoulders 335 00:20:57,119 --> 00:21:02,639 Speaker 1: as far as advocating for herself, but also um, not 336 00:21:02,800 --> 00:21:06,160 Speaker 1: going off the deep end. Yeah, that's simily like through 337 00:21:06,200 --> 00:21:08,480 Speaker 1: and through. Like she's not just gonna sit there and 338 00:21:08,520 --> 00:21:10,959 Speaker 1: be like, oh, whatever you say, doctor, and she's like 339 00:21:11,280 --> 00:21:13,639 Speaker 1: that actually doesn't sound quite right. She will stand up 340 00:21:13,640 --> 00:21:19,360 Speaker 1: for herself. Yea. Yeah, advocating for herself it's important. Um. 341 00:21:19,400 --> 00:21:22,640 Speaker 1: So with Mamma Graham's chuck, from what I've seen, nobody's saying, well, 342 00:21:22,680 --> 00:21:24,680 Speaker 1: this is a kind of X ray, so you don't 343 00:21:24,680 --> 00:21:28,160 Speaker 1: want to build up, you know, the radiation. That doesn't 344 00:21:28,160 --> 00:21:31,199 Speaker 1: seem to be the problem with overuse of mammograms. What 345 00:21:31,280 --> 00:21:33,840 Speaker 1: seems to be the problem is that they that well, 346 00:21:34,119 --> 00:21:36,280 Speaker 1: a Mamma Graham is an X ray, and the X 347 00:21:36,359 --> 00:21:39,600 Speaker 1: ray is handed off to a radiologist and they apparently 348 00:21:39,640 --> 00:21:43,960 Speaker 1: are like eight eighty four some high eighty percent effective 349 00:21:44,240 --> 00:21:48,600 Speaker 1: at finding cancerous tumors in breast. Just looking at an 350 00:21:48,640 --> 00:21:51,840 Speaker 1: image of a breast. This trained human being can say, yep, 351 00:21:51,960 --> 00:21:55,280 Speaker 1: there you go right there, circle it initially go follow 352 00:21:55,480 --> 00:21:59,600 Speaker 1: this up. The follow up UM is it results in 353 00:21:59,680 --> 00:22:04,040 Speaker 1: a a biopsy, usually a needle prick biopsy to remove 354 00:22:04,119 --> 00:22:07,320 Speaker 1: some of the cells. Those are examined, and if those 355 00:22:07,480 --> 00:22:10,879 Speaker 1: come back as suspicious, a doctor might say, we need 356 00:22:10,920 --> 00:22:14,080 Speaker 1: to get those cells out. Most of the time those 357 00:22:14,200 --> 00:22:19,280 Speaker 1: aren't actually cancer as cells, but they're still being removed surgically, 358 00:22:19,520 --> 00:22:24,160 Speaker 1: which is painful, costly, and can be a problem emotionally 359 00:22:24,480 --> 00:22:27,119 Speaker 1: to have to go through that surgical procedure to have 360 00:22:27,600 --> 00:22:30,600 Speaker 1: cells removed that you didn't need to have removed. That's 361 00:22:30,640 --> 00:22:34,200 Speaker 1: the that's the problem with with UM mammograms as far 362 00:22:34,240 --> 00:22:38,960 Speaker 1: as getting them frequently, and supposedly, between ages forty and fifty, 363 00:22:39,160 --> 00:22:41,480 Speaker 1: a woman has a fifty to sixty percent chance of 364 00:22:41,520 --> 00:22:44,680 Speaker 1: getting a false positive result from a mammogram. Yeah, man, 365 00:22:44,800 --> 00:22:48,520 Speaker 1: I mean a sixty chance. Yeah. And again, no one's saying, oh, 366 00:22:48,760 --> 00:22:51,600 Speaker 1: don't get mammograms. They're gonna just totally screw you up. 367 00:22:51,760 --> 00:22:55,520 Speaker 1: It's more like medical community, we need a better way 368 00:22:55,720 --> 00:22:58,639 Speaker 1: to to find to keep an eye on breast cancer. 369 00:22:59,240 --> 00:23:01,680 Speaker 1: I mean they're trying. I sure they are, of course 370 00:23:01,720 --> 00:23:04,919 Speaker 1: they are. In Colorectal cancer is a perfect example. UM. 371 00:23:04,960 --> 00:23:07,760 Speaker 1: It is the second leading cancer related death in the 372 00:23:07,880 --> 00:23:11,119 Speaker 1: US right now? Um was it? Say here? A hundred 373 00:23:11,200 --> 00:23:15,840 Speaker 1: thirty two thousand, seven hundred new diagnoses in two thousand fifteen. 374 00:23:16,680 --> 00:23:22,479 Speaker 1: And one of the big problems with colorectal cancer is 375 00:23:22,520 --> 00:23:24,720 Speaker 1: that not a lot of well, I'm saying a lot 376 00:23:24,720 --> 00:23:29,159 Speaker 1: of people, but I think about fifty of people don't 377 00:23:29,680 --> 00:23:37,440 Speaker 1: follow up on a recommendation to get a colonoscopy because 378 00:23:37,600 --> 00:23:40,960 Speaker 1: they don't want to get a colonoscopy. Yeah, so that's 379 00:23:40,960 --> 00:23:43,560 Speaker 1: a problem. Have you got one of those? Not yet? 380 00:23:43,960 --> 00:23:46,280 Speaker 1: You know not. I haven't either. I'm really really not 381 00:23:46,359 --> 00:23:49,200 Speaker 1: looking forward to it. And I was researching it today 382 00:23:49,400 --> 00:23:51,840 Speaker 1: and just almost fainted like three or four times while 383 00:23:51,880 --> 00:23:56,760 Speaker 1: I was reading the procedure. About the procedure, Yeah, it's hardcore, man. 384 00:23:56,840 --> 00:24:00,919 Speaker 1: There's like a finger with tube that they stick in 385 00:24:01,000 --> 00:24:05,000 Speaker 1: your anus, past your rectum up to your colon. The 386 00:24:05,240 --> 00:24:07,680 Speaker 1: c seesme I think it is, which is the top 387 00:24:07,720 --> 00:24:12,480 Speaker 1: of your colon, which is basically where the your rib 388 00:24:12,560 --> 00:24:17,520 Speaker 1: cage ends on your left side, that's your sesome. They 389 00:24:17,520 --> 00:24:19,520 Speaker 1: go all the way up there and it has like 390 00:24:19,560 --> 00:24:22,560 Speaker 1: a camera and a light on the end, and basically 391 00:24:22,560 --> 00:24:25,760 Speaker 1: what they're doing is visually inspecting the inside of your colon. 392 00:24:26,240 --> 00:24:28,720 Speaker 1: If they see something that they find suspicious, they can 393 00:24:28,760 --> 00:24:31,600 Speaker 1: put four steps through the tube and take a sample 394 00:24:31,640 --> 00:24:34,280 Speaker 1: of it and then just you know, come on back out. 395 00:24:34,720 --> 00:24:37,800 Speaker 1: Normally they'll they'll give you a sedative for this. UM. 396 00:24:37,840 --> 00:24:40,560 Speaker 1: They also give you I can't remember the name of 397 00:24:40,600 --> 00:24:44,560 Speaker 1: the drugs um, but it basically makes you forget that 398 00:24:44,640 --> 00:24:47,159 Speaker 1: it ever happened. Like you can prevent you from forming 399 00:24:47,200 --> 00:24:50,240 Speaker 1: memories during the procedure. But most people don't want to 400 00:24:50,280 --> 00:24:53,560 Speaker 1: go through this, even though it's extremely effective. It finds 401 00:24:53,600 --> 00:24:58,880 Speaker 1: like of um coal erectal cancer from what I understand, Yeah, 402 00:24:58,920 --> 00:25:02,680 Speaker 1: it's amazing, what like all the advances of medical science, 403 00:25:03,400 --> 00:25:06,760 Speaker 1: they're they're literally saying, like the best way is to 404 00:25:06,800 --> 00:25:09,879 Speaker 1: really just get on up in there and take a look. 405 00:25:10,240 --> 00:25:13,920 Speaker 1: Just jamming up there, you know, get up there. However, 406 00:25:14,080 --> 00:25:17,879 Speaker 1: they do have some because like we said about people 407 00:25:18,160 --> 00:25:21,959 Speaker 1: won't even get a colonoscopy when recommended. Uh, they have 408 00:25:22,200 --> 00:25:25,040 Speaker 1: other tests. Now they aren't as accurate, but at least 409 00:25:25,080 --> 00:25:29,520 Speaker 1: they're at least they're trying to get another test on 410 00:25:29,560 --> 00:25:33,199 Speaker 1: the table for people that are reticent to have the 411 00:25:33,240 --> 00:25:37,240 Speaker 1: two stuck up their butt, and some of them work. 412 00:25:37,320 --> 00:25:42,320 Speaker 1: There's this one called colon Guard from Germany. Yeah. They 413 00:25:42,359 --> 00:25:49,719 Speaker 1: they have accuracy rate of um no, no, no, this 414 00:25:49,760 --> 00:25:57,200 Speaker 1: one is oh well yeah, yeah, yeah, colon Guard. That's high. 415 00:25:57,280 --> 00:26:01,760 Speaker 1: Because I'm sorry, I'm miss spoke earlier. The the colonoscopy catches. 416 00:26:03,160 --> 00:26:05,600 Speaker 1: So this stuff that you just poop into a cup 417 00:26:05,640 --> 00:26:08,320 Speaker 1: and mail it in and some Porschemo tests it. Right, 418 00:26:08,840 --> 00:26:13,359 Speaker 1: that's that's really great. Well it's not not quite. It 419 00:26:13,520 --> 00:26:18,920 Speaker 1: showed of the cancers that a colonoscopy would uncover. Okay, 420 00:26:18,960 --> 00:26:22,359 Speaker 1: so that's not overall. Oh okay, I got it. But 421 00:26:22,440 --> 00:26:25,320 Speaker 1: it's still pretty good, right, But it has a high 422 00:26:25,480 --> 00:26:29,520 Speaker 1: high false positive rate, of which I mean if you 423 00:26:29,560 --> 00:26:32,959 Speaker 1: think a tube up your butt will make your rectum pucker, 424 00:26:33,240 --> 00:26:37,040 Speaker 1: so will a false positive of colorectal cancer. Yeah, the 425 00:26:37,119 --> 00:26:39,920 Speaker 1: German one, although that might be German two. But there's 426 00:26:39,920 --> 00:26:43,680 Speaker 1: another German. Uh actually this is a German study about 427 00:26:43,720 --> 00:26:47,000 Speaker 1: stool tests, and that's when you literally are just looking 428 00:26:47,000 --> 00:26:50,160 Speaker 1: at it trace amounts of blood in the stool. Well, 429 00:26:50,200 --> 00:26:53,119 Speaker 1: some do that had accuracy all over the place. That 430 00:26:53,200 --> 00:26:58,840 Speaker 1: was from which I mean, that's such a wild swing, 431 00:26:59,520 --> 00:27:01,600 Speaker 1: right that I don't know if I would opt for 432 00:27:01,640 --> 00:27:04,679 Speaker 1: that one of them. So one of them. Some of them, 433 00:27:04,720 --> 00:27:07,040 Speaker 1: I should say, probably most look for blood in the stool, 434 00:27:07,160 --> 00:27:11,440 Speaker 1: some some look for DNA or genetic material of cancer 435 00:27:11,560 --> 00:27:14,480 Speaker 1: in your stool, and another one looks for chemical changes 436 00:27:14,880 --> 00:27:17,760 Speaker 1: of a certain gene that's that could be present in 437 00:27:17,800 --> 00:27:20,160 Speaker 1: your stool. And by stool, of course, I mean poop 438 00:27:20,240 --> 00:27:23,520 Speaker 1: by the way, everybody um and they analyze them for this, 439 00:27:23,560 --> 00:27:26,399 Speaker 1: and again they're pretty good at catching the stuff, but 440 00:27:26,440 --> 00:27:30,200 Speaker 1: they're also pretty good at giving false positives. So I mean, 441 00:27:30,240 --> 00:27:32,680 Speaker 1: that's just a great the idea that we can catch 442 00:27:32,720 --> 00:27:37,840 Speaker 1: like colorectal cancers with colonoscopy, But people who need one 443 00:27:37,920 --> 00:27:40,639 Speaker 1: don't go get it because it's such an awful procedure that, 444 00:27:40,760 --> 00:27:43,000 Speaker 1: like you were saying at the outset, like that begs 445 00:27:43,040 --> 00:27:47,720 Speaker 1: for something new. You want to take another break, Yeah, 446 00:27:47,840 --> 00:27:52,359 Speaker 1: let's go prepare the finger with tubes. We'll talk about 447 00:27:52,480 --> 00:28:20,680 Speaker 1: drug testing right for this. Okay, all right, So we've 448 00:28:20,680 --> 00:28:24,399 Speaker 1: honed in on mostly medical testing up into this point. 449 00:28:25,240 --> 00:28:28,480 Speaker 1: But if anyone's ever taking a drug test, there is 450 00:28:28,520 --> 00:28:31,760 Speaker 1: always the risk of a weird false positive. You can 451 00:28:31,760 --> 00:28:35,280 Speaker 1: be a clean liver and still get a test that said, hey, 452 00:28:36,320 --> 00:28:39,080 Speaker 1: it says here that you smoked marijuana and you can 453 00:28:39,080 --> 00:28:42,360 Speaker 1: be like, dude, I don't and have never smoked marijuana, 454 00:28:43,240 --> 00:28:45,560 Speaker 1: and then you have to plead. Like basically every athlete 455 00:28:45,560 --> 00:28:49,240 Speaker 1: ever this test of positive for anything says I didn't 456 00:28:49,280 --> 00:28:52,240 Speaker 1: do it, man, this false positive. They're like whatever, stoner, 457 00:28:52,520 --> 00:28:55,640 Speaker 1: but it does. That's like the same thing with up 458 00:28:55,680 --> 00:28:59,720 Speaker 1: my Twitter account was hacked alright, Like really every time 459 00:28:59,800 --> 00:29:02,240 Speaker 1: some thing awful came out on your Twitter speed someone 460 00:29:02,280 --> 00:29:06,600 Speaker 1: hacked it. Yeah, but Twitter hacking does happen, and true 461 00:29:06,680 --> 00:29:10,320 Speaker 1: false positives and drug tests definitely happen. Yeah, it depends 462 00:29:10,400 --> 00:29:14,200 Speaker 1: on on what you've been doing. Like if you are 463 00:29:15,120 --> 00:29:19,640 Speaker 1: using a prescription medicine or even some over the counter medicines, 464 00:29:19,680 --> 00:29:21,480 Speaker 1: you can come up with the false positive on a 465 00:29:21,560 --> 00:29:25,400 Speaker 1: drug test. It says between seven and fifteen million people 466 00:29:25,440 --> 00:29:28,240 Speaker 1: a year in the United States get a false positive 467 00:29:28,280 --> 00:29:31,080 Speaker 1: drug test. That's a lot because think about it. When 468 00:29:31,440 --> 00:29:33,959 Speaker 1: you know, if you're applying for a job and you 469 00:29:34,000 --> 00:29:35,960 Speaker 1: go do the drug tests and you go home and 470 00:29:36,040 --> 00:29:38,040 Speaker 1: you hear that you got passed over for the job, 471 00:29:38,600 --> 00:29:40,760 Speaker 1: I don't know if they tell you that it was 472 00:29:40,800 --> 00:29:43,120 Speaker 1: because you failed your drug tests. And even if they do, 473 00:29:43,480 --> 00:29:46,120 Speaker 1: they're not going to be like, well, we want to 474 00:29:46,160 --> 00:29:49,040 Speaker 1: hear your side of the story. Mr Candidate number nine 475 00:29:49,520 --> 00:29:53,239 Speaker 1: twenty seven. You know they like you, just you just 476 00:29:53,280 --> 00:29:55,440 Speaker 1: lost out on a job because of a false positive. 477 00:29:55,560 --> 00:29:58,719 Speaker 1: You lost out on a sports scholarship, you lost out on, 478 00:29:59,360 --> 00:30:03,960 Speaker 1: UM don't know, getting to deliver meals on wheels, who knows, 479 00:30:04,000 --> 00:30:07,200 Speaker 1: But you're gonna miss out on something because of a 480 00:30:07,280 --> 00:30:09,719 Speaker 1: failed drug test when you didn't do anything. You've been 481 00:30:09,760 --> 00:30:12,160 Speaker 1: a straight air of your whole life. But again, you 482 00:30:12,200 --> 00:30:15,160 Speaker 1: did you You made the mistake of um not keeping 483 00:30:15,240 --> 00:30:18,880 Speaker 1: up with what prescription medicines can give you false positives. Yeah, 484 00:30:18,960 --> 00:30:22,240 Speaker 1: and here's the thing parents, if you drug test your kids, 485 00:30:23,400 --> 00:30:25,160 Speaker 1: I'm not weighing in on that one way or the other. 486 00:30:25,200 --> 00:30:27,120 Speaker 1: But if you drug test your kids and they return 487 00:30:27,160 --> 00:30:30,720 Speaker 1: a positive test from marijuana and they say, Mom, that's 488 00:30:30,800 --> 00:30:33,720 Speaker 1: because I was in the car with some people who 489 00:30:33,720 --> 00:30:39,720 Speaker 1: are getting stoned. That's how it showed up. Uh, it's 490 00:30:39,760 --> 00:30:41,880 Speaker 1: not true. I hate to break it to you, but 491 00:30:42,080 --> 00:30:44,880 Speaker 1: that is not You will not I don't think you 492 00:30:44,880 --> 00:30:47,600 Speaker 1: can ever get a false positive for a marijuana from 493 00:30:47,600 --> 00:30:50,080 Speaker 1: second hand smoke. Right. That's not your cue to burst 494 00:30:50,080 --> 00:30:52,440 Speaker 1: into tears and grab Todd and go oh Todd, I 495 00:30:52,480 --> 00:30:56,040 Speaker 1: knew you would never use drugs, And Todd's winking at 496 00:30:56,080 --> 00:30:57,880 Speaker 1: the camera and breaks the fourth while and winks at 497 00:30:57,880 --> 00:31:02,000 Speaker 1: the camera Ferris Bueller style. Yeah, stoked. It did kind 498 00:31:02,000 --> 00:31:03,880 Speaker 1: of remind me though, because it said here that cocaine 499 00:31:03,960 --> 00:31:07,640 Speaker 1: is one of the drugs that routinely do not come 500 00:31:07,680 --> 00:31:10,680 Speaker 1: back with a false positive or a false negative. Yeah, 501 00:31:10,720 --> 00:31:12,440 Speaker 1: it's kind of on the money. That means they have 502 00:31:12,480 --> 00:31:14,960 Speaker 1: a good test for it. Well yeah, but I kind 503 00:31:14,960 --> 00:31:17,920 Speaker 1: of that made me remember that old thing. I used 504 00:31:17,920 --> 00:31:20,640 Speaker 1: to hear that like whatever percentage of dollar bills has 505 00:31:20,680 --> 00:31:24,080 Speaker 1: cocaine on it, and I thought that's totally not true 506 00:31:24,120 --> 00:31:25,959 Speaker 1: and one of those things that you just here in school. 507 00:31:26,480 --> 00:31:31,000 Speaker 1: But I looked it up and apparently that is totally true. Uh. 508 00:31:31,040 --> 00:31:32,560 Speaker 1: There was a study just a few years ago in 509 00:31:32,600 --> 00:31:34,680 Speaker 1: New York City by n y U and they found 510 00:31:35,880 --> 00:31:38,560 Speaker 1: of dollar bills had trace amounts of cocaine. Yes, some 511 00:31:38,720 --> 00:31:42,720 Speaker 1: ridiculous amount of euros to too. Yeah, and not just cocaine, 512 00:31:42,760 --> 00:31:45,760 Speaker 1: It's like there was some morphine, heroin and meth and 513 00:31:45,880 --> 00:31:51,240 Speaker 1: lower quantities and then all manner of disgusting gross things 514 00:31:52,160 --> 00:31:55,520 Speaker 1: on on paper money, right, which apparently people were using 515 00:31:55,600 --> 00:31:59,040 Speaker 1: to roll into a tube and sticking into their nose 516 00:31:59,120 --> 00:32:02,600 Speaker 1: to ingest draw ugs with not were but kind of 517 00:32:02,640 --> 00:32:06,520 Speaker 1: always have. So so the idea that, um, you can 518 00:32:06,640 --> 00:32:10,680 Speaker 1: find drugs on money? Have you heard that? They're They're 519 00:32:10,760 --> 00:32:13,840 Speaker 1: like local laws around the country in the United States 520 00:32:13,880 --> 00:32:18,520 Speaker 1: that say that police can confiscate money as drug money 521 00:32:18,560 --> 00:32:20,640 Speaker 1: if they test it and it turns out that there's 522 00:32:20,720 --> 00:32:24,080 Speaker 1: drug residue on it. But it sounds like it's of money. 523 00:32:24,000 --> 00:32:28,560 Speaker 1: Yeah wow, yeah, not too cool. What are some of 524 00:32:28,560 --> 00:32:30,720 Speaker 1: the other things that can give you a false positive 525 00:32:31,840 --> 00:32:35,800 Speaker 1: aside from just jamming dollar bills in your nose? So 526 00:32:36,440 --> 00:32:39,280 Speaker 1: remember that Seinfeld where I think Elaine was supposed to 527 00:32:39,280 --> 00:32:41,640 Speaker 1: go on a j. Peterman trip but she got she 528 00:32:41,720 --> 00:32:45,360 Speaker 1: got disinvited because she turned up positive for heroin. But 529 00:32:45,440 --> 00:32:48,520 Speaker 1: it turns out that she was eating lemon poppy seed 530 00:32:48,600 --> 00:32:53,320 Speaker 1: muffins every day. That apparently is true, although this article 531 00:32:53,440 --> 00:32:57,440 Speaker 1: or how stuff Works article gets it wrong. So the 532 00:32:57,480 --> 00:33:02,200 Speaker 1: poppy seeds don't actually contain opium, but when you're harvesting 533 00:33:02,240 --> 00:33:06,680 Speaker 1: the seeds, opium can rub off onto the seeds and 534 00:33:06,720 --> 00:33:09,280 Speaker 1: depending from people, they were doing opium no no, no 535 00:33:09,360 --> 00:33:12,920 Speaker 1: from so like they're harvesting opium from the poppy and 536 00:33:12,920 --> 00:33:15,959 Speaker 1: then they're harvesting seeds later, and the seeds can come 537 00:33:16,000 --> 00:33:18,920 Speaker 1: in contact with opium residue from the poppy plant. And 538 00:33:18,960 --> 00:33:23,719 Speaker 1: then however, well they're processed or not processed by the 539 00:33:23,760 --> 00:33:26,080 Speaker 1: time you eat them, they they have they might have 540 00:33:26,120 --> 00:33:29,160 Speaker 1: a substantial amount of opium on the outside of the shell, 541 00:33:29,440 --> 00:33:32,680 Speaker 1: which will show up in a drug test. Seinfeld was 542 00:33:32,760 --> 00:33:38,200 Speaker 1: correct because I felt was correct. Apparently, ibprofen um can 543 00:33:38,320 --> 00:33:43,320 Speaker 1: come back with a positive from marijuana, barbiturates or Benny's 544 00:33:44,200 --> 00:33:48,600 Speaker 1: m Benny's and that was Jack Carouac's drug of choice, 545 00:33:50,360 --> 00:33:54,280 Speaker 1: one of several. Yeah, but he really, I mean I 546 00:33:54,320 --> 00:33:57,160 Speaker 1: remember him writing about the Bennies a lot. That's how 547 00:33:57,200 --> 00:34:00,080 Speaker 1: we wrote that book in like forty eight hours. He 548 00:34:00,160 --> 00:34:03,360 Speaker 1: write on like one long scrolling piece of paper. That's 549 00:34:03,360 --> 00:34:05,400 Speaker 1: what I've always heard. But last time I heard that, 550 00:34:05,440 --> 00:34:07,520 Speaker 1: I was like twenty years old, so I know it 551 00:34:07,560 --> 00:34:10,279 Speaker 1: looked into it since I think it's true, Well, I 552 00:34:10,320 --> 00:34:14,880 Speaker 1: think I've seen it. Jack Caroway clad us no, uh uh. 553 00:34:14,960 --> 00:34:20,000 Speaker 1: Some some OTC colden allergy medications apparently can result in 554 00:34:20,440 --> 00:34:24,560 Speaker 1: result in positive tests for like emphetamines. It's crazy. Yeah, 555 00:34:24,600 --> 00:34:27,920 Speaker 1: well you know that, like like if you're making bathtub crank. 556 00:34:28,040 --> 00:34:32,239 Speaker 1: You can use suda fed as like a precursor or 557 00:34:32,280 --> 00:34:35,719 Speaker 1: an ingredient in just crank. And that's why you're only 558 00:34:35,760 --> 00:34:37,960 Speaker 1: allowed to buy like one box at a time with 559 00:34:38,080 --> 00:34:41,359 Speaker 1: a driver's license. It such a seventies. Well yeah, if 560 00:34:41,400 --> 00:34:44,160 Speaker 1: you're using over the counter suda fed to make your 561 00:34:44,239 --> 00:34:50,120 Speaker 1: your meth, that's cranky. It's crank. Uh. And then tonic water. Surprisingly, um, 562 00:34:50,160 --> 00:34:54,680 Speaker 1: apparently quinine contains a little bit of the real quinine, 563 00:34:55,520 --> 00:35:00,319 Speaker 1: which is a drug. So here's the thing I looked 564 00:35:00,360 --> 00:35:03,440 Speaker 1: into this. I could not figure out why quinine would 565 00:35:03,760 --> 00:35:08,000 Speaker 1: result in the positive test for heroin. Here's why, Chuck, 566 00:35:08,040 --> 00:35:10,440 Speaker 1: you ready for this. I'm ready because you know gin 567 00:35:10,520 --> 00:35:13,320 Speaker 1: and tonics are my jam. Okay, well, just be careful 568 00:35:13,400 --> 00:35:17,120 Speaker 1: because gin or tonic water does contain sometimes like eighty 569 00:35:17,160 --> 00:35:20,840 Speaker 1: three milligrams of quinine in it, which was a malaria 570 00:35:20,960 --> 00:35:25,840 Speaker 1: drug right well back in the thirties, Supposedly heroin dealers 571 00:35:25,880 --> 00:35:30,759 Speaker 1: started adding quinnine to their heroin to combat malaria. That 572 00:35:30,840 --> 00:35:33,719 Speaker 1: was the urban legend. It turns out that's not the 573 00:35:33,760 --> 00:35:37,279 Speaker 1: case at all, but quinine actually interacts with heroin in 574 00:35:37,280 --> 00:35:39,680 Speaker 1: a way that kind of boosts it and it also, 575 00:35:39,840 --> 00:35:44,920 Speaker 1: more to the point, mimics heroin's bitter taste. So somebody 576 00:35:44,960 --> 00:35:49,160 Speaker 1: would taste the heroin and what they were tasting was quinine, 577 00:35:49,239 --> 00:35:51,440 Speaker 1: but they thought they had like some dynamite s gag 578 00:35:51,520 --> 00:35:54,120 Speaker 1: on their hands. So it was really just kind of 579 00:35:54,120 --> 00:35:57,560 Speaker 1: to take terrible junk and make it seem like it 580 00:35:57,600 --> 00:36:00,440 Speaker 1: was much better by adding quinine. Apparently this has been 581 00:36:00,440 --> 00:36:03,280 Speaker 1: going on for so many years that they that drug 582 00:36:03,360 --> 00:36:07,640 Speaker 1: tests test for quinnine because they consider that an indicator 583 00:36:07,840 --> 00:36:11,520 Speaker 1: of the presence of heroin. I think my big takeaway 584 00:36:11,640 --> 00:36:16,600 Speaker 1: is here, is it quinnine and not quinine? I've heard both. Okay, 585 00:36:16,920 --> 00:36:21,640 Speaker 1: that's your big takeaway. I was laying down gold. Well 586 00:36:21,719 --> 00:36:26,719 Speaker 1: here's my deal. As lately, I don't have been buying um. 587 00:36:26,760 --> 00:36:31,200 Speaker 1: I've been buying the real deal tonics. Yeah, like Feverit Tree. 588 00:36:31,320 --> 00:36:35,440 Speaker 1: I hate to use the word artisan tonics. You should, 589 00:36:35,600 --> 00:36:39,319 Speaker 1: but I've been buying the artisan tonics because they're delicious, 590 00:36:39,360 --> 00:36:44,960 Speaker 1: and I've really embraced bitter as a as a taste 591 00:36:45,040 --> 00:36:47,720 Speaker 1: that I can enjoy. Now Here in my late forties, 592 00:36:47,719 --> 00:36:51,040 Speaker 1: I've never liked bitter at all, but I'm kind of 593 00:36:51,160 --> 00:36:53,200 Speaker 1: have come around to it a little bit. Yeah. It 594 00:36:53,320 --> 00:36:56,520 Speaker 1: is like the definition of an acquired taste, isn't it. Yeah? 595 00:36:56,520 --> 00:36:58,239 Speaker 1: But now I really like it. And you know, these 596 00:36:58,360 --> 00:37:00,799 Speaker 1: these tonics that they make her like they're made from 597 00:37:00,840 --> 00:37:06,319 Speaker 1: the real Uh, what's the root the chincha? What is 598 00:37:06,320 --> 00:37:11,440 Speaker 1: it chinchilla? It's not chinchilla, chin shona? Is it chinchona? 599 00:37:11,640 --> 00:37:17,280 Speaker 1: I believe so. Yeah, And that's like the key ingredient, right, Yeah, 600 00:37:17,640 --> 00:37:20,560 Speaker 1: from what I understand it is the key ingredient tonic. 601 00:37:20,960 --> 00:37:26,239 Speaker 1: I'm not an artisan tonic making cinchona bark so as I. Yeah, 602 00:37:26,320 --> 00:37:28,279 Speaker 1: I don't know if that's the key ingredient or if 603 00:37:28,320 --> 00:37:30,800 Speaker 1: it's one of them. There's also like in white willow 604 00:37:30,920 --> 00:37:33,719 Speaker 1: or something in that like an ingredient, and aspirin is 605 00:37:33,760 --> 00:37:35,879 Speaker 1: also in to water. Yeah, I don't know. I enjoy 606 00:37:35,880 --> 00:37:37,560 Speaker 1: it though, And it's it's the thing is, you don't 607 00:37:37,680 --> 00:37:40,080 Speaker 1: use a ton of it. You just use like an 608 00:37:40,080 --> 00:37:43,480 Speaker 1: ounce and then some club soda or whatever. If you 609 00:37:43,560 --> 00:37:46,680 Speaker 1: have artisan soda water. Oh, I see what you're saying. 610 00:37:46,719 --> 00:37:50,000 Speaker 1: So you're using artisan like tonic, not with any kind 611 00:37:50,040 --> 00:37:53,960 Speaker 1: of fizz. You're using like the tonic tonic. Yes, oh wow, man, 612 00:37:54,000 --> 00:37:56,640 Speaker 1: that is that's hardcore. It's you know, it's like dark brown. 613 00:37:57,040 --> 00:37:59,600 Speaker 1: I got you, and then you pour that in. It's 614 00:37:59,600 --> 00:38:01,960 Speaker 1: like a couple blounces a gin an ounce of that 615 00:38:02,239 --> 00:38:04,759 Speaker 1: and then top it off with some soda water. Give 616 00:38:04,760 --> 00:38:07,479 Speaker 1: it a good shake. Man, that sounds great. It's really 617 00:38:07,480 --> 00:38:10,319 Speaker 1: good and it has a nice come over, come on over. 618 00:38:10,440 --> 00:38:13,879 Speaker 1: I think I started gin and tonic season early this year. 619 00:38:14,000 --> 00:38:18,600 Speaker 1: That's great, which is not good. No, it's great as well. Okay, yeah, 620 00:38:18,640 --> 00:38:22,680 Speaker 1: it's not good. It's great artisan tonic made from doomed goats. 621 00:38:22,840 --> 00:38:26,480 Speaker 1: They have some down They have a one kind downstairs 622 00:38:26,520 --> 00:38:32,680 Speaker 1: at the eighteen. Yeah, the bitterest place. Yeah, And I like, 623 00:38:32,800 --> 00:38:35,200 Speaker 1: there's okay. But then there's another one in Evandale, States 624 00:38:35,200 --> 00:38:37,600 Speaker 1: that I think. I like there's a little more so 625 00:38:37,760 --> 00:38:39,759 Speaker 1: is there like a specific tonic or just like the 626 00:38:39,800 --> 00:38:43,560 Speaker 1: general tonic that they have? Well, the one uh in Evandale, 627 00:38:43,600 --> 00:38:46,280 Speaker 1: States is one called dry Tonic and one called robust Tonic, 628 00:38:46,760 --> 00:38:48,600 Speaker 1: And I think the robust just has a little more 629 00:38:49,120 --> 00:38:55,239 Speaker 1: limp lime citrus. But they're they're both delicious this stuff, man, 630 00:38:55,680 --> 00:38:59,800 Speaker 1: Nice work, Chuck trying, yes, deer clear of the drug tests. 631 00:39:00,440 --> 00:39:02,839 Speaker 1: I'm pretty sure they're going to start instituting them at 632 00:39:02,880 --> 00:39:05,440 Speaker 1: stuff media any day. Now. You know, the only drug 633 00:39:05,440 --> 00:39:07,400 Speaker 1: test I ever had to take my entire life was 634 00:39:07,400 --> 00:39:10,919 Speaker 1: when I went through, uh the adoption process. Oh yeah, 635 00:39:10,960 --> 00:39:13,160 Speaker 1: I remember that. I never had to take one for 636 00:39:13,160 --> 00:39:16,600 Speaker 1: for work or anything. Uh, nor have I now that 637 00:39:16,760 --> 00:39:19,319 Speaker 1: you mentioned it. I think we're in the minority. You 638 00:39:19,360 --> 00:39:22,000 Speaker 1: never had to drive a Bobcat for work. I did, 639 00:39:22,000 --> 00:39:24,359 Speaker 1: but the guy I worked for couldn't have cared less. 640 00:39:26,000 --> 00:39:29,080 Speaker 1: Who's insured to the teeth? Before we go, Chuck, you 641 00:39:29,120 --> 00:39:30,960 Speaker 1: got anything else? You got nothing else? All right? So 642 00:39:31,040 --> 00:39:35,040 Speaker 1: before we go? I found um one test that is 643 00:39:35,280 --> 00:39:37,520 Speaker 1: just supposed to be. It just seems to me like 644 00:39:37,600 --> 00:39:40,400 Speaker 1: it's the gold standard for test. It's an HIV screen 645 00:39:41,040 --> 00:39:45,560 Speaker 1: and it's called the Enzyme linked immunos Orbit Essay or ELSA. 646 00:39:46,200 --> 00:39:48,359 Speaker 1: I think we talked about it in our HIV two 647 00:39:48,400 --> 00:39:52,279 Speaker 1: parter um. This is how this test is performed. So 648 00:39:52,400 --> 00:39:55,200 Speaker 1: you you get this one screen, the ELISIA screen. If 649 00:39:55,200 --> 00:39:58,840 Speaker 1: it comes back positive, a second ELISA screen is performed 650 00:39:59,040 --> 00:40:02,920 Speaker 1: if that's positive, of a separate test that uses an 651 00:40:03,040 --> 00:40:06,640 Speaker 1: entirely different technique is performed. All this is in the 652 00:40:06,719 --> 00:40:09,800 Speaker 1: lab before you ever hear your results. And that means 653 00:40:09,880 --> 00:40:12,960 Speaker 1: that one in the United States, one out of two 654 00:40:13,040 --> 00:40:17,319 Speaker 1: hundred and fifty thousand tests show a false positive. That 655 00:40:17,360 --> 00:40:21,640 Speaker 1: means that has a point zero zero zero zero zero 656 00:40:21,800 --> 00:40:25,960 Speaker 1: four percent chance of returning a false positive. That is 657 00:40:26,000 --> 00:40:30,399 Speaker 1: a bomb test. Yeah that's all I got. I got 658 00:40:30,400 --> 00:40:32,920 Speaker 1: nothing else. Go check out choosing wisely dot org. It 659 00:40:32,960 --> 00:40:36,320 Speaker 1: seems pretty interesting to me. Uh And in the meantime, 660 00:40:36,719 --> 00:40:41,319 Speaker 1: how about some listener mail. Yeah, I'm gonna call this 661 00:40:41,680 --> 00:40:46,600 Speaker 1: email from Mr Sweedman's class. All right, this is actually 662 00:40:46,640 --> 00:40:48,839 Speaker 1: from Mr Sweedman and on his class, but we're gonna 663 00:40:48,840 --> 00:40:51,239 Speaker 1: shout out his class and helps that he starts incorporating 664 00:40:51,320 --> 00:40:53,800 Speaker 1: this into his class. Hey, guys, love the show on 665 00:40:53,920 --> 00:40:57,880 Speaker 1: Walrus is wanted to chime in regarding reproductive isolation or 666 00:40:57,920 --> 00:41:01,600 Speaker 1: reasons why different species don't mate. I have taught biology 667 00:41:01,640 --> 00:41:05,160 Speaker 1: for several years and evolutionary biology is always my favorite unit. 668 00:41:05,800 --> 00:41:09,680 Speaker 1: Remember when we talked about reproductive isolation and yeah, what 669 00:41:09,719 --> 00:41:13,560 Speaker 1: other different types of like how that? How that would 670 00:41:13,600 --> 00:41:17,200 Speaker 1: manifest itself? I remember? So he says there are several 671 00:41:17,200 --> 00:41:21,240 Speaker 1: types of reproductive isolation, and geographic isolation is one of them. 672 00:41:21,280 --> 00:41:25,080 Speaker 1: And here's a little breakdown geographic isolation when species live 673 00:41:25,080 --> 00:41:31,440 Speaker 1: in different geographic reasons, sorry, regions, ecological like isolation, same region, 674 00:41:31,880 --> 00:41:37,759 Speaker 1: different habitat, Okay, okay. So so they're in the same 675 00:41:37,800 --> 00:41:39,359 Speaker 1: they're in the same big city, they just don't hang 676 00:41:39,360 --> 00:41:45,000 Speaker 1: out the same clubs, different neighborhoods, different neighborhoods. Behavioral behavioral. 677 00:41:45,120 --> 00:41:48,279 Speaker 1: I always have a trouble with that word isolation. One 678 00:41:48,360 --> 00:41:52,680 Speaker 1: species mating behavior won't work on another. For instance, a 679 00:41:52,719 --> 00:41:56,719 Speaker 1: peacock won't attract a chicken, right because the peacock can't 680 00:41:56,760 --> 00:42:01,520 Speaker 1: do chaw cockaw? No, what is the peacock say? Help? 681 00:42:01,800 --> 00:42:06,960 Speaker 1: That's right. Uh. Temporal isolation, same area, but breed at 682 00:42:07,000 --> 00:42:10,360 Speaker 1: different times, and that could be everything from the season 683 00:42:10,400 --> 00:42:13,240 Speaker 1: to literally the time of day. That's called two ships 684 00:42:13,239 --> 00:42:16,719 Speaker 1: passing in the night reproductive isolation. And that's like I 685 00:42:16,880 --> 00:42:18,759 Speaker 1: like morning sex and the other one's like, shut up, 686 00:42:18,800 --> 00:42:20,600 Speaker 1: I only like depth sex at night when I'm drunk. 687 00:42:22,640 --> 00:42:26,560 Speaker 1: Then there's gametic isolation. Mating can occur, but sperm and 688 00:42:26,600 --> 00:42:30,640 Speaker 1: egg won't mix. No, not you again, And he says 689 00:42:30,640 --> 00:42:32,440 Speaker 1: in this case it is usually the egg releases a 690 00:42:32,480 --> 00:42:37,439 Speaker 1: toxin that kills the sperm. Quid. That's right. Uh, And 691 00:42:37,520 --> 00:42:42,279 Speaker 1: finally has said, my student's favorite type of reproductive reproductive isolation, 692 00:42:42,920 --> 00:42:48,640 Speaker 1: mechanical isolation. That's when the parts don't fit, like just wait, 693 00:42:48,760 --> 00:42:51,160 Speaker 1: just hold, like, just give me a second. Wait, I 694 00:42:51,200 --> 00:42:56,200 Speaker 1: can do this and then nothing, he says, think square, peg, round, whole. Sure, 695 00:42:57,520 --> 00:42:59,200 Speaker 1: that's a really good way to put it, way better 696 00:42:59,239 --> 00:43:01,640 Speaker 1: than what I was. So there you have a guy's 697 00:43:01,640 --> 00:43:04,560 Speaker 1: all the types of reproductive isolation. Now you know, and 698 00:43:04,600 --> 00:43:08,040 Speaker 1: knowing is half the battle. G I, Joe, nice job. 699 00:43:08,440 --> 00:43:11,359 Speaker 1: Don't stop believing or whatever journey lyric guide your life. 700 00:43:11,880 --> 00:43:16,440 Speaker 1: That is from Mr Baird Swedman. Thank you, Mr schwed Man. 701 00:43:17,280 --> 00:43:20,719 Speaker 1: I's goot that you added at a h What is 702 00:43:20,760 --> 00:43:24,120 Speaker 1: it Swedman? It's just Swedman, but I like Mr Mr Schwedman. 703 00:43:24,480 --> 00:43:27,240 Speaker 1: I have to call him Schwedman. You know Mr Swedman 704 00:43:27,320 --> 00:43:30,919 Speaker 1: from PS right exactly. That's how I'm doing well. Thank 705 00:43:30,960 --> 00:43:33,840 Speaker 1: you very much, Mr Swedman. I'm sorry I got it 706 00:43:33,840 --> 00:43:36,440 Speaker 1: wrong in the first time, but Chuck said behavioral wrong, 707 00:43:36,640 --> 00:43:39,399 Speaker 1: so we're even. I could never say that right. If 708 00:43:39,440 --> 00:43:41,799 Speaker 1: you want to get in touch with us, especially if 709 00:43:41,840 --> 00:43:45,640 Speaker 1: you are one of the fine teachers instructing America's youth 710 00:43:45,800 --> 00:43:48,520 Speaker 1: or any youth of any country around the world, because 711 00:43:48,880 --> 00:43:52,000 Speaker 1: we think everybody's great. You can tweet to us where 712 00:43:52,239 --> 00:43:54,920 Speaker 1: s y s K podcast I'm at Josh Ouam Clark 713 00:43:55,200 --> 00:43:58,520 Speaker 1: Chuck's at Facebook dot com slash Charles W. Chuck Bryant. 714 00:43:58,680 --> 00:44:02,319 Speaker 1: He's also on Twitter at movie Crush. You can send 715 00:44:02,400 --> 00:44:04,880 Speaker 1: us all an email to Stuff Podcast at how stuff 716 00:44:04,880 --> 00:44:07,359 Speaker 1: works dot com and it's always Join us at our 717 00:44:07,360 --> 00:44:14,719 Speaker 1: home on the web stuffy sho dot com. For more 718 00:44:14,760 --> 00:44:17,080 Speaker 1: on this and thousands of other topics, is it how 719 00:44:17,120 --> 00:44:28,520 Speaker 1: stuff works dot com.