1 00:00:01,480 --> 00:00:04,280 Speaker 1: Welcome to Stuff You Should Know, a production of I 2 00:00:04,360 --> 00:00:13,760 Speaker 1: Heart Radio. Hey, and welcome to the podcast. I'm Josh Clark, 3 00:00:13,800 --> 00:00:17,119 Speaker 1: and there's Charles W Chuck Bryan over there. Jerry is 4 00:00:17,200 --> 00:00:22,239 Speaker 1: persona non grata and that's that's stuff you should know, 5 00:00:22,320 --> 00:00:27,240 Speaker 1: of course, just the usual. Yeah, that's so stuff you 6 00:00:27,240 --> 00:00:32,320 Speaker 1: should know, stuff you should know regular mhm uh. So 7 00:00:32,560 --> 00:00:35,600 Speaker 1: can I say a couple of things here? Oh preamble 8 00:00:35,720 --> 00:00:40,559 Speaker 1: from Charles, let's hear it. So we're gonna be talking 9 00:00:40,600 --> 00:00:47,120 Speaker 1: today about the COVID vaccines, uh, specifically M in our 10 00:00:47,400 --> 00:00:52,640 Speaker 1: I'm sorry, oh boy episode m r NA vaccines a 11 00:00:52,760 --> 00:00:57,200 Speaker 1: k A Mr Nah. How I like to call him 12 00:00:57,240 --> 00:00:59,160 Speaker 1: head and picked up on that before. Now I can't 13 00:00:59,240 --> 00:01:03,840 Speaker 1: unsee it. Well that's because the M is little. Yeah yeah, 14 00:01:03,920 --> 00:01:06,360 Speaker 1: but still now I see it very clearly, the mr 15 00:01:06,440 --> 00:01:10,319 Speaker 1: NO vaccine. Uh. And just quickly, I wanted to say 16 00:01:10,360 --> 00:01:13,040 Speaker 1: that Josh put this together from whole cloth, from about 17 00:01:13,760 --> 00:01:17,400 Speaker 1: eight sources, and you did a great job. This is 18 00:01:17,440 --> 00:01:20,360 Speaker 1: a complicated thing that you did work your wonders on 19 00:01:20,400 --> 00:01:22,440 Speaker 1: and you're really good at this. Is that what you 20 00:01:22,480 --> 00:01:25,920 Speaker 1: wanted to say? Man, I wanted to say that, And 21 00:01:25,959 --> 00:01:29,880 Speaker 1: also our hopes here are that you can understand this. 22 00:01:29,920 --> 00:01:31,480 Speaker 1: I know we're kind of preaching to the choir a 23 00:01:31,480 --> 00:01:34,880 Speaker 1: bit with our our listenership, not not fully, there's plenty 24 00:01:34,880 --> 00:01:36,880 Speaker 1: of people. There's a lot of varying opinions among the 25 00:01:36,880 --> 00:01:39,520 Speaker 1: stuff you should know listeners, absolutely, but I think when 26 00:01:39,560 --> 00:01:42,520 Speaker 1: it comes to vaccine hesitancy, I think most of our 27 00:01:42,560 --> 00:01:44,720 Speaker 1: listeners are on board. And and our hope is that 28 00:01:44,760 --> 00:01:48,200 Speaker 1: you can understand this a little bit before Thanksgiving with 29 00:01:48,240 --> 00:01:51,960 Speaker 1: your weird uncle, so maybe you can say, hey, you know, 30 00:01:52,160 --> 00:01:55,720 Speaker 1: I know how these things work, and it's not something 31 00:01:55,760 --> 00:01:58,360 Speaker 1: to be feared. It's something to be like to stand 32 00:01:58,440 --> 00:02:01,520 Speaker 1: up from this turkey and a table and like applaud 33 00:02:02,640 --> 00:02:07,280 Speaker 1: with full no reservation and full like, what in the 34 00:02:07,360 --> 00:02:10,240 Speaker 1: world has science done? It's amazing? Yeah, it really is, 35 00:02:10,440 --> 00:02:13,680 Speaker 1: because it is. It's unbelievable that science has figured this 36 00:02:13,720 --> 00:02:17,160 Speaker 1: stuff out and they did it that quickly and that accurately. 37 00:02:17,440 --> 00:02:20,200 Speaker 1: I know it is. It's a triumph of modern science 38 00:02:20,240 --> 00:02:22,640 Speaker 1: for sure, um, one of the one of the biggest. 39 00:02:22,840 --> 00:02:25,119 Speaker 1: And we're gonna well, you know you it's an It's 40 00:02:25,160 --> 00:02:27,400 Speaker 1: impossible to talk about the M R and A vaccines 41 00:02:27,400 --> 00:02:30,400 Speaker 1: without talking about how it differs from traditional vaccines, and 42 00:02:30,440 --> 00:02:34,520 Speaker 1: it is a huge step forward in vaccine research and 43 00:02:34,600 --> 00:02:37,800 Speaker 1: vaccine production. Like, it's the future of vaccines. It's amazing 44 00:02:37,880 --> 00:02:41,800 Speaker 1: what what's just happened. But that's not to throw any 45 00:02:41,800 --> 00:02:45,480 Speaker 1: shade whatsoever on traditional vaccines, which we still need, which 46 00:02:45,520 --> 00:02:50,560 Speaker 1: we still use vaccines, yes, without which there would probably 47 00:02:50,639 --> 00:02:52,800 Speaker 1: be a great many of us who would not be 48 00:02:52,880 --> 00:02:56,440 Speaker 1: here because we hadn't survived, our parents hadn't survived, our 49 00:02:56,480 --> 00:02:59,760 Speaker 1: grandparents hadn't survived some disease that a vaccine was developed 50 00:02:59,760 --> 00:03:04,320 Speaker 1: to combat. So hats off to traditional vaccines. But m 51 00:03:04,400 --> 00:03:08,320 Speaker 1: RNA vaccines are are pretty astounding and what what science 52 00:03:08,360 --> 00:03:10,919 Speaker 1: has managed to come up with. Yeah, So we hope 53 00:03:10,960 --> 00:03:15,160 Speaker 1: to clear up some myths about what the COVID vaccines 54 00:03:15,240 --> 00:03:18,440 Speaker 1: are and are not. And hopefully by the end of 55 00:03:18,480 --> 00:03:21,120 Speaker 1: this you will agree that it's it's literally when I like, 56 00:03:21,400 --> 00:03:24,640 Speaker 1: there's some serious Nobel prizes coming in the future towards 57 00:03:24,680 --> 00:03:27,480 Speaker 1: these people, for sure. At the very least, we hope 58 00:03:27,520 --> 00:03:29,520 Speaker 1: that you hear this episode and are able to go, 59 00:03:29,800 --> 00:03:34,079 Speaker 1: huh so that's what's in me? Yeah, exactly, Well it's 60 00:03:34,080 --> 00:03:36,560 Speaker 1: not any anymore. We'll learn that too, that's true. Chuck 61 00:03:36,760 --> 00:03:41,520 Speaker 1: Nice Nice foreshadowing, So it is really it's it's really 62 00:03:41,520 --> 00:03:43,640 Speaker 1: hard to kind of overstate just how big of a 63 00:03:43,680 --> 00:03:47,120 Speaker 1: breakthrough it was for for m RNA vaccines and that 64 00:03:47,200 --> 00:03:51,400 Speaker 1: they do kind of read represent like this new path forward. 65 00:03:51,760 --> 00:03:54,280 Speaker 1: But to kind of understand how the whole thing works 66 00:03:54,280 --> 00:03:58,480 Speaker 1: and what makes it so magnificent as far as medical 67 00:03:58,520 --> 00:04:01,320 Speaker 1: breakthroughs go, you kind and I have to first understand 68 00:04:01,640 --> 00:04:04,920 Speaker 1: what m RNA actually is in what it does, don't 69 00:04:04,920 --> 00:04:08,080 Speaker 1: you agree? Yeah, I mean all this stuff is really new. 70 00:04:09,680 --> 00:04:13,360 Speaker 1: I mean, the quickest version of the history is that, uh, 71 00:04:13,400 --> 00:04:16,320 Speaker 1: this stuff was identified man a messenger RNA is what 72 00:04:16,360 --> 00:04:19,760 Speaker 1: we're talking about, identified in the nineteen sixties, and then 73 00:04:19,800 --> 00:04:23,240 Speaker 1: in nineteen eighty four the very first strand of m 74 00:04:23,440 --> 00:04:25,760 Speaker 1: r NA. I'm gonna say m n r A so 75 00:04:25,839 --> 00:04:31,560 Speaker 1: many times. You know that that m stuff and mr NAH, 76 00:04:31,600 --> 00:04:34,520 Speaker 1: the first strand of mr NAH was artificially produced in 77 00:04:34,520 --> 00:04:37,520 Speaker 1: a lab in nineteen eighty four, which in terms of 78 00:04:37,560 --> 00:04:40,800 Speaker 1: science is not that long ago. And since then they 79 00:04:40,839 --> 00:04:44,560 Speaker 1: have made leaps and bounds to the point where they 80 00:04:44,640 --> 00:04:51,120 Speaker 1: now can and did produce a COVID vaccine on a computer. Yeah, 81 00:04:51,200 --> 00:04:53,880 Speaker 1: I mean, that's basically what they're doing. These days is 82 00:04:53,880 --> 00:04:56,880 Speaker 1: is they're saying, Oh, I want I want a vaccine 83 00:04:56,920 --> 00:05:00,360 Speaker 1: that produces this little viral protein. I know that nomic 84 00:05:00,400 --> 00:05:02,919 Speaker 1: code of this little viral protein. It's something to taped 85 00:05:03,000 --> 00:05:05,640 Speaker 1: and tap tap tap, tap, tap tap, and then press 86 00:05:05,800 --> 00:05:09,560 Speaker 1: enter basically and the computer sets off some desktop machines 87 00:05:09,680 --> 00:05:13,520 Speaker 1: that produced that. That's that exact version of m RNA. 88 00:05:13,960 --> 00:05:18,640 Speaker 1: That is really really simplified version of what's going on. 89 00:05:18,800 --> 00:05:22,200 Speaker 1: But in a nutshell, it's basically where we've arrived now. 90 00:05:22,400 --> 00:05:25,560 Speaker 1: And like you were saying, that's that's in the last 91 00:05:25,640 --> 00:05:28,640 Speaker 1: thirty five years that we first very first time we 92 00:05:28,720 --> 00:05:32,320 Speaker 1: ever synthesized m RNA. And as easy as it sounds now, Chuck, 93 00:05:32,480 --> 00:05:39,080 Speaker 1: there were a lot of obstacles between and when the 94 00:05:39,160 --> 00:05:41,840 Speaker 1: very first m RNA vaccines ever in the history of 95 00:05:41,920 --> 00:05:46,839 Speaker 1: humanity came out just in time for the COVID pandemic. Yeah, 96 00:05:46,880 --> 00:05:48,440 Speaker 1: I mean there were a couple of big hurdles to 97 00:05:48,440 --> 00:05:54,480 Speaker 1: actually turn that like original miracle into boys about to 98 00:05:54,520 --> 00:05:59,320 Speaker 1: get so religious into fish to feed the masses. I 99 00:05:59,360 --> 00:06:03,120 Speaker 1: would have gone with water into wine. Okay, Hey, that 100 00:06:03,200 --> 00:06:05,680 Speaker 1: was a good one too. A couple of them being 101 00:06:05,720 --> 00:06:07,600 Speaker 1: in we're gonna get more into this you know, as 102 00:06:07,600 --> 00:06:10,360 Speaker 1: we go along. But uh, they learned how to that. 103 00:06:10,520 --> 00:06:12,960 Speaker 1: You know, m RNA is really fragile, so they learned 104 00:06:12,960 --> 00:06:15,640 Speaker 1: how to protect it by putting it in these little 105 00:06:15,720 --> 00:06:20,640 Speaker 1: tiny fat capsules called lipid nano particles. And so now 106 00:06:20,680 --> 00:06:22,680 Speaker 1: they've got a little sort of a little vehicle to 107 00:06:22,720 --> 00:06:26,000 Speaker 1: travel in that helps them get into a cell. Uh. 108 00:06:26,040 --> 00:06:29,000 Speaker 1: And then and I know we've talked about cytokine storms before, 109 00:06:29,120 --> 00:06:32,880 Speaker 1: when the when the human body has a really overblown 110 00:06:32,960 --> 00:06:36,840 Speaker 1: reaction uh and overblown immune response to the point where 111 00:06:36,880 --> 00:06:40,040 Speaker 1: it can actually kill somebody. Yeah, and those cytokine storms 112 00:06:40,080 --> 00:06:43,480 Speaker 1: just kept smacking down MR and A research over and 113 00:06:43,560 --> 00:06:46,200 Speaker 1: over again, because even when they finally did manage to 114 00:06:46,240 --> 00:06:48,360 Speaker 1: come up with a way to keep the fragile mr 115 00:06:48,400 --> 00:06:50,760 Speaker 1: and A from falling apart in the body, the body 116 00:06:50,800 --> 00:06:52,800 Speaker 1: would be like, what is this? Get this out of here. 117 00:06:53,160 --> 00:06:56,280 Speaker 1: I'm I'm going to just overblow so hard against this 118 00:06:56,279 --> 00:06:59,479 Speaker 1: this uh weird foreign invader that I'm gonna threaten to 119 00:06:59,560 --> 00:07:02,560 Speaker 1: kill my human which is not at all what you want. 120 00:07:02,600 --> 00:07:05,400 Speaker 1: And they finally figured out that if you use some 121 00:07:05,520 --> 00:07:09,560 Speaker 1: different nucleotides in place of other nucleotides, which are the 122 00:07:09,600 --> 00:07:13,120 Speaker 1: building blocks of life. Um, when you're building this mr 123 00:07:13,200 --> 00:07:16,160 Speaker 1: and A and then you really purify it, you get 124 00:07:16,280 --> 00:07:20,480 Speaker 1: like no slop whatsoever. You have a chance of um 125 00:07:20,520 --> 00:07:24,200 Speaker 1: making something that is that appears natural enough to full nature. 126 00:07:25,040 --> 00:07:28,440 Speaker 1: That's right, And we're able to really clean that stuff 127 00:07:28,520 --> 00:07:31,280 Speaker 1: up because it's not a live virus. Yes not, it's 128 00:07:31,320 --> 00:07:33,200 Speaker 1: not a living thing. And we'll get more into that, 129 00:07:33,280 --> 00:07:36,520 Speaker 1: and that's another big way how it differs from other vaccines. 130 00:07:37,200 --> 00:07:39,520 Speaker 1: But it's not a live virus, so you can you 131 00:07:39,560 --> 00:07:43,480 Speaker 1: can just dump a bunch of bleach on it basically essentially, 132 00:07:43,600 --> 00:07:46,720 Speaker 1: we'll say in a nutshell, but yes, it cuts down 133 00:07:46,760 --> 00:07:50,720 Speaker 1: on any type of contamination that you might get. Yeah, 134 00:07:50,720 --> 00:07:53,800 Speaker 1: and we have to thank for all of this, really 135 00:07:54,080 --> 00:07:58,720 Speaker 1: the Human Genome Project, because if not for that, which 136 00:07:58,760 --> 00:08:01,040 Speaker 1: started in the nineteen on these thanks to the U. S. 137 00:08:01,120 --> 00:08:05,320 Speaker 1: Government's um funding of that, we wouldn't have had any 138 00:08:05,320 --> 00:08:08,160 Speaker 1: of these breakthroughs to begin with. As far as reading 139 00:08:08,160 --> 00:08:10,760 Speaker 1: the genetic code, yes, it was a huge investment and 140 00:08:10,760 --> 00:08:13,640 Speaker 1: it really is paid off in multiple ways, and just 141 00:08:13,720 --> 00:08:18,600 Speaker 1: one of them is m RNA vaccines. Um. The the 142 00:08:18,600 --> 00:08:21,400 Speaker 1: whole thing that is just to me just amazing and 143 00:08:21,440 --> 00:08:24,880 Speaker 1: astounding and just confirms that we are living in some 144 00:08:24,920 --> 00:08:29,160 Speaker 1: sort of simulation that the breakthroughs that pushed this this 145 00:08:29,400 --> 00:08:33,320 Speaker 1: research for m RNA vaccines from basically a pipe dream 146 00:08:33,400 --> 00:08:35,240 Speaker 1: that we had no idea how we were ever going 147 00:08:35,280 --> 00:08:39,040 Speaker 1: to to get there. Two. Okay, we're ready to actually 148 00:08:39,559 --> 00:08:43,520 Speaker 1: create mRNA vaccines just in time for this pandemic that's 149 00:08:43,559 --> 00:08:47,080 Speaker 1: coming along. Um. They they all just kind of came 150 00:08:47,120 --> 00:08:53,000 Speaker 1: together in part because people were already working on coronavirus vaccines. 151 00:08:53,320 --> 00:08:56,680 Speaker 1: And what's really cool about mRNA vaccines is you can 152 00:08:56,720 --> 00:09:00,320 Speaker 1: plug and play different stuff. Thanks to the Human Genome ject, 153 00:09:00,600 --> 00:09:03,599 Speaker 1: we've learned to kind of read the genetic codes of 154 00:09:03,640 --> 00:09:07,240 Speaker 1: stuff and to write it and produce it. And because 155 00:09:07,280 --> 00:09:09,440 Speaker 1: of that, because we can do that on computers, now 156 00:09:09,720 --> 00:09:12,320 Speaker 1: you can say, I've got a template for a coronavirus, 157 00:09:12,480 --> 00:09:14,760 Speaker 1: let me get specific with it and make it as 158 00:09:14,760 --> 00:09:18,600 Speaker 1: stars COVID two coronavirus. Now that we've got the genetic code, 159 00:09:18,760 --> 00:09:22,000 Speaker 1: we can deploy a vaccine against it. And that's how 160 00:09:22,040 --> 00:09:24,319 Speaker 1: they were able to do it so quickly, that's right, 161 00:09:24,640 --> 00:09:29,520 Speaker 1: And they estimate that as of July this year, that 162 00:09:29,600 --> 00:09:32,600 Speaker 1: vaccine is saved almost two d and eighty thousand lives 163 00:09:33,600 --> 00:09:36,840 Speaker 1: UH and prevented about one point five million hospitalizations when 164 00:09:37,360 --> 00:09:42,040 Speaker 1: hospitals are overrun, and that's a really important thing. Um, 165 00:09:42,080 --> 00:09:45,720 Speaker 1: I'm gonna lobby for an early ad break here so 166 00:09:45,760 --> 00:09:49,760 Speaker 1: we can just get cooking and go uninterrupted and unmolested 167 00:09:50,840 --> 00:09:54,520 Speaker 1: until the second had break. That sound good? Yeah, a 168 00:09:54,600 --> 00:09:58,240 Speaker 1: lobbying approved. Okay, we'll be right back everyone and tell 169 00:09:58,280 --> 00:10:26,760 Speaker 1: you how all this stuff works right after this learning's 170 00:10:26,800 --> 00:10:37,320 Speaker 1: stuff with Joshua John. Okay, so, um, we should talk 171 00:10:37,360 --> 00:10:40,440 Speaker 1: about like I was saying, what mrn A does. Thank 172 00:10:40,480 --> 00:10:43,080 Speaker 1: you for swooping in and reminding me that, oh yeah, 173 00:10:43,160 --> 00:10:45,880 Speaker 1: this article that you wrote. You got the history part first, 174 00:10:45,960 --> 00:10:48,520 Speaker 1: let's start there. That makes it like he's skipping that. No, 175 00:10:48,679 --> 00:10:52,240 Speaker 1: he's not skipping. I was. My vision is blurry. I'm 176 00:10:52,280 --> 00:10:55,679 Speaker 1: so interested in this. Okay, So we're talking about m 177 00:10:55,760 --> 00:10:57,920 Speaker 1: r n A and m RNA is short for messenger 178 00:10:58,240 --> 00:11:05,600 Speaker 1: RNA and messenger RNA basically, UH is a. It's it's 179 00:11:05,640 --> 00:11:10,319 Speaker 1: a blueprint, right. It translates, it copies a little strip 180 00:11:10,559 --> 00:11:13,679 Speaker 1: of the blueprint that's encoded in your entire genome, in 181 00:11:13,720 --> 00:11:17,680 Speaker 1: your DNA, and it takes that little bit usually which 182 00:11:17,760 --> 00:11:20,440 Speaker 1: codes for like a protein or peptide which are really 183 00:11:20,520 --> 00:11:23,840 Speaker 1: important things. That are our body uses to do everything 184 00:11:23,920 --> 00:11:27,320 Speaker 1: from um contracting your muscles to making you feel hungry. 185 00:11:27,360 --> 00:11:30,679 Speaker 1: Like basically everything comes down to a protein or peptide, 186 00:11:30,960 --> 00:11:33,640 Speaker 1: and the instructions for building each of those proteins and 187 00:11:33,640 --> 00:11:37,640 Speaker 1: peptides are encoded in our DNA. And it's messenger RNA 188 00:11:37,800 --> 00:11:40,120 Speaker 1: that goes to the DNA says, Okay, we need some 189 00:11:40,160 --> 00:11:42,400 Speaker 1: more of this protein. I'm here to make a copy. 190 00:11:42,600 --> 00:11:44,960 Speaker 1: May I please make a copy? Here are some flowers. 191 00:11:45,000 --> 00:11:46,760 Speaker 1: They said, if I brought you some flowers, you'd be 192 00:11:46,760 --> 00:11:49,840 Speaker 1: cooler with this, And the DNA says proceed, And the 193 00:11:50,000 --> 00:11:54,640 Speaker 1: m RNA goes and produces itself as a copy and 194 00:11:54,880 --> 00:11:59,000 Speaker 1: leaves the nucleus. This is really important. M RNA goes 195 00:11:59,040 --> 00:12:01,640 Speaker 1: to the DNA, makes a copy and then leads to 196 00:12:01,760 --> 00:12:04,480 Speaker 1: nucleus and from that point on, the m RNA is 197 00:12:04,559 --> 00:12:08,920 Speaker 1: all about the cytoplasm. Right. Uh So, I kind of 198 00:12:08,960 --> 00:12:12,800 Speaker 1: like the and I've expanded upon the wonderful metaphor you 199 00:12:12,840 --> 00:12:17,120 Speaker 1: have of like a building site. Uh And I guess 200 00:12:17,120 --> 00:12:21,079 Speaker 1: I think we failed to mention that um, the amino 201 00:12:21,160 --> 00:12:23,959 Speaker 1: acids in the body is what's really carrying out the work, 202 00:12:25,040 --> 00:12:27,240 Speaker 1: like making your eyes blue. Let's say, yeah, Well, the 203 00:12:27,280 --> 00:12:30,320 Speaker 1: amino acids, they're the building blocks of proteins, of peptides. 204 00:12:30,360 --> 00:12:32,840 Speaker 1: If you arrange a certain set of amino acids in 205 00:12:32,880 --> 00:12:35,360 Speaker 1: a certain way, you've got a polypeptide and you've got 206 00:12:35,360 --> 00:12:38,720 Speaker 1: a protein. Right. So m n r A in this case, 207 00:12:38,720 --> 00:12:41,160 Speaker 1: if we're talking about this is like a job site. 208 00:12:41,559 --> 00:12:43,319 Speaker 1: Did I say n r A again? You said m 209 00:12:43,559 --> 00:12:48,360 Speaker 1: r A, mem ra, Well, that's the n r A 210 00:12:48,480 --> 00:12:51,360 Speaker 1: is just so like embedded in our that's just so sad. 211 00:12:51,720 --> 00:12:54,840 Speaker 1: I haven't said an r A once. I know it 212 00:12:54,920 --> 00:13:00,440 Speaker 1: sounds like it's so m r n A just like 213 00:13:00,480 --> 00:13:04,040 Speaker 1: black angus. Yeah, that one got a good reaction to. 214 00:13:04,280 --> 00:13:07,200 Speaker 1: That was good. So M and r chez m RNA 215 00:13:07,280 --> 00:13:10,640 Speaker 1: in this case would be like the architect showing up 216 00:13:10,640 --> 00:13:15,080 Speaker 1: with the blueprint wearing some like sensible like chinos, but 217 00:13:15,360 --> 00:13:17,840 Speaker 1: work boots. But they're really expensive work boots. You can 218 00:13:17,840 --> 00:13:20,080 Speaker 1: tell them there's not a scuff on them, okay, And 219 00:13:20,160 --> 00:13:22,520 Speaker 1: so it heads over to the work site, which is 220 00:13:22,559 --> 00:13:26,480 Speaker 1: the cytoplasm of the cell outside the nucleus, right. And 221 00:13:26,520 --> 00:13:30,400 Speaker 1: then I think in this case the ribosomes would be 222 00:13:30,440 --> 00:13:35,440 Speaker 1: the contractor sort of because the contractor maybe translates these 223 00:13:35,440 --> 00:13:41,480 Speaker 1: blueprints into I guess marching orders for the little workers 224 00:13:41,520 --> 00:13:45,760 Speaker 1: that are the amino acids. Yeah, the ribosome clears the 225 00:13:45,880 --> 00:13:49,120 Speaker 1: sandwich off of like the drafting table and spreads out 226 00:13:49,160 --> 00:13:51,240 Speaker 1: the mRNA blueprint is okay, let me see what we 227 00:13:51,240 --> 00:13:53,920 Speaker 1: got here, wipes his mouth, some crumbs away from his mouth, 228 00:13:54,320 --> 00:13:57,920 Speaker 1: and um gets to work taking that blueprint, taking that 229 00:13:58,040 --> 00:14:02,280 Speaker 1: messenger RNA and trans eating it into those amino acids 230 00:14:02,360 --> 00:14:04,840 Speaker 1: that get constructed in just a certain way to produce 231 00:14:04,880 --> 00:14:07,120 Speaker 1: a protein. And the m R and A says, do 232 00:14:07,120 --> 00:14:09,520 Speaker 1: it again, do it again, do it again. Let's keep going. 233 00:14:09,600 --> 00:14:12,240 Speaker 1: I'm feeling good. Let's keep this going for a little while. 234 00:14:12,880 --> 00:14:15,079 Speaker 1: That's right, For a little while, and it just happens, 235 00:14:15,160 --> 00:14:17,199 Speaker 1: you know, a certain number of times. It's not specific, 236 00:14:17,679 --> 00:14:21,160 Speaker 1: it varies, but it's limited. And then that m RNA 237 00:14:21,240 --> 00:14:24,960 Speaker 1: starts to break down. Nice going, you said, m R 238 00:14:25,040 --> 00:14:29,160 Speaker 1: n A. I know, and I'm really concentrated. Uh. And 239 00:14:29,200 --> 00:14:31,480 Speaker 1: then it's carried away from the cell and eventually out 240 00:14:31,480 --> 00:14:35,480 Speaker 1: of the body through the lymph nodes and it's disposed of. So, 241 00:14:35,920 --> 00:14:39,760 Speaker 1: like all jobs, eventually the contractor will disappear on you, right, well, no, 242 00:14:39,880 --> 00:14:46,920 Speaker 1: that was the architect out. Well, the architect disappears earlier. 243 00:14:46,920 --> 00:14:49,200 Speaker 1: I guess sure, I guess so. But you always want 244 00:14:49,200 --> 00:14:51,600 Speaker 1: the architect to come back sort of, Yes, well, the 245 00:14:51,680 --> 00:14:54,000 Speaker 1: architect is gonna come back. You'll you'll get another architect. 246 00:14:54,040 --> 00:14:56,320 Speaker 1: There's always more MR and A. The body is always 247 00:14:56,360 --> 00:14:58,720 Speaker 1: happy to produce more m R and A with sending 248 00:14:58,720 --> 00:15:01,560 Speaker 1: out blueprints in and instructions and go make this protein 249 00:15:01,680 --> 00:15:03,800 Speaker 1: right now, Man, I really screwed up. I thought the 250 00:15:03,840 --> 00:15:06,120 Speaker 1: contractor disappeared. How perfect would that have been. It would 251 00:15:06,120 --> 00:15:08,120 Speaker 1: have been pretty great, and you still got the joke in. 252 00:15:08,240 --> 00:15:12,680 Speaker 1: It was just wrong. And that's just wrong Jo scientifically. 253 00:15:12,880 --> 00:15:15,800 Speaker 1: But the thing about M R and A vaccines is 254 00:15:15,840 --> 00:15:19,920 Speaker 1: that researchers have figured out how to use this natural 255 00:15:20,000 --> 00:15:25,400 Speaker 1: process to help us vaccinate ourselves against diseases. And they 256 00:15:25,440 --> 00:15:28,400 Speaker 1: do that because we've reached a point where we can 257 00:15:28,920 --> 00:15:31,520 Speaker 1: Rather than having the the M R and A produced 258 00:15:31,640 --> 00:15:34,280 Speaker 1: in the nucleus of the celling going out into the cytoplasm, 259 00:15:34,680 --> 00:15:38,080 Speaker 1: vaccine researchers produced the MR and A outside of the 260 00:15:38,120 --> 00:15:40,760 Speaker 1: body and then injected into the body, and then it 261 00:15:40,800 --> 00:15:44,880 Speaker 1: goes into the cytoplasm from outside of the cell, and 262 00:15:44,920 --> 00:15:48,120 Speaker 1: then from that point on everything else follows the exact 263 00:15:48,120 --> 00:15:50,760 Speaker 1: same process. That is where we're at right now, and 264 00:15:50,840 --> 00:15:53,360 Speaker 1: that is where you're you can start to feel your 265 00:15:53,360 --> 00:15:57,040 Speaker 1: head opening up like a bloomin onion and out back. Yeah. 266 00:15:57,080 --> 00:15:59,840 Speaker 1: And I mean that in and of itself is remarkable. 267 00:16:00,000 --> 00:16:02,280 Speaker 1: It is that they said, you know what, this stuff 268 00:16:02,320 --> 00:16:05,040 Speaker 1: can actually go into a cell, even though and we'll 269 00:16:05,080 --> 00:16:06,760 Speaker 1: get a little bit more into this, even though it's 270 00:16:06,800 --> 00:16:10,000 Speaker 1: like can be up to ten thousand times too big 271 00:16:10,960 --> 00:16:14,240 Speaker 1: to permeate that cell, We'll figure that part out. And 272 00:16:14,360 --> 00:16:16,640 Speaker 1: they did. That's that's you know, courtesy of the of 273 00:16:16,680 --> 00:16:19,760 Speaker 1: the little fatty lipids. That's the vehicle that allows that 274 00:16:19,760 --> 00:16:22,480 Speaker 1: to happen. But just the notion that they thought, like, 275 00:16:22,560 --> 00:16:24,200 Speaker 1: I wonder if we can get the stuff to go 276 00:16:24,280 --> 00:16:27,520 Speaker 1: from the outside in, Yeah, was remarkable. It really is. 277 00:16:27,640 --> 00:16:30,480 Speaker 1: And it was just this contribution from hundreds of researchers 278 00:16:30,520 --> 00:16:34,160 Speaker 1: just building on one another's work, and um, that finally 279 00:16:34,280 --> 00:16:36,640 Speaker 1: led to the point where it's like it went from wow, 280 00:16:36,680 --> 00:16:39,120 Speaker 1: this is a really cool idea, to Okay, we're actually 281 00:16:39,160 --> 00:16:44,160 Speaker 1: preventing deaths in the pandemic things, to these things now right, uh, 282 00:16:44,200 --> 00:16:46,160 Speaker 1: and you know there are a couple of ways to 283 00:16:46,600 --> 00:16:49,600 Speaker 1: a few ways that you can immunize a person, like 284 00:16:49,680 --> 00:16:53,720 Speaker 1: literal techniques using m r N A. And it turns 285 00:16:53,720 --> 00:16:55,600 Speaker 1: out that we got I don't know if it's lucky 286 00:16:55,800 --> 00:17:00,520 Speaker 1: or just uh, you know, divine intervention smulation type stuff. 287 00:17:00,800 --> 00:17:03,520 Speaker 1: It turns out that the one that we that works 288 00:17:03,640 --> 00:17:06,240 Speaker 1: really well and that we're using for the COVID vaccine 289 00:17:06,240 --> 00:17:08,000 Speaker 1: turned out to be sort of the cheapest and the 290 00:17:08,040 --> 00:17:13,720 Speaker 1: easiest one, which means in vivo within the living So 291 00:17:13,840 --> 00:17:16,120 Speaker 1: in other words, you just get injected into your arm, 292 00:17:16,400 --> 00:17:18,560 Speaker 1: as opposed to like in vitro that's the other way, 293 00:17:18,600 --> 00:17:21,680 Speaker 1: which is it takes a lot longer, it's really complicated, 294 00:17:21,720 --> 00:17:24,439 Speaker 1: a lot more expensive. And they figured out, hey, we 295 00:17:24,440 --> 00:17:28,080 Speaker 1: can just do this with a shot in the arm. Uh, 296 00:17:28,160 --> 00:17:30,760 Speaker 1: And then it's a conventional m RNA as opposed to 297 00:17:31,200 --> 00:17:34,000 Speaker 1: something called self amplifying that we're not gonna sort of 298 00:17:34,000 --> 00:17:37,800 Speaker 1: get into now. But it's a conventional in vivo shot 299 00:17:38,040 --> 00:17:40,919 Speaker 1: that goes into your arm. Yeah, it's the most straightforward 300 00:17:41,000 --> 00:17:43,560 Speaker 1: it could possibly be at this point in our m 301 00:17:43,680 --> 00:17:47,560 Speaker 1: RNA vaccine technology, which like you said, is rather lucky. Yeah, 302 00:17:47,600 --> 00:17:48,919 Speaker 1: it didn't have to be that way. It could have. 303 00:17:48,960 --> 00:17:51,000 Speaker 1: It could have been the most expensive and the most 304 00:17:51,000 --> 00:17:54,000 Speaker 1: difficult in time consuming, and we'd be in a much 305 00:17:54,040 --> 00:17:57,879 Speaker 1: different spot right now, Yes, for sure. So um to 306 00:17:58,160 --> 00:18:01,040 Speaker 1: kind of explain how m RNA seems do their thing, 307 00:18:01,600 --> 00:18:03,280 Speaker 1: it helps to kind of view it as like a 308 00:18:03,280 --> 00:18:06,840 Speaker 1: metaphor for like a training session, like when you are 309 00:18:06,920 --> 00:18:10,920 Speaker 1: vaccinated against something. Your your immune system is being trained 310 00:18:10,960 --> 00:18:13,760 Speaker 1: to fight an invader. But it's like a training session 311 00:18:13,800 --> 00:18:17,560 Speaker 1: that uses like blank rounds, So it's much safer than 312 00:18:17,920 --> 00:18:21,240 Speaker 1: than say, like you know, capturing one of those enemies, 313 00:18:21,359 --> 00:18:24,320 Speaker 1: pushing them onto the field and giving everybody live ammunition. 314 00:18:25,080 --> 00:18:27,040 Speaker 1: Things can get messy in that sense. It's it's like 315 00:18:27,080 --> 00:18:30,560 Speaker 1: a military training session, I guess. So sure, yeah, all right, 316 00:18:30,720 --> 00:18:34,840 Speaker 1: I was thinking more SWAT team, but sure. So you know, 317 00:18:34,840 --> 00:18:37,560 Speaker 1: we mentioned a couple of times those lipid nanoparticles that 318 00:18:37,760 --> 00:18:40,680 Speaker 1: encase the m r N a uh, and that these 319 00:18:40,680 --> 00:18:43,040 Speaker 1: things are anywhere from a thousand to ten thousand times 320 00:18:43,080 --> 00:18:46,200 Speaker 1: too large for what normally could pass through the cell's membrane. 321 00:18:46,600 --> 00:18:50,480 Speaker 1: But the lipid coding basically opens that gate and says, 322 00:18:50,560 --> 00:18:53,320 Speaker 1: you know what, there with me, you love me. I'm 323 00:18:53,359 --> 00:18:57,159 Speaker 1: a little slippery fat cell and just just coming along 324 00:18:57,240 --> 00:18:59,360 Speaker 1: inside the cell with me and I'll shut the door 325 00:18:59,359 --> 00:19:02,040 Speaker 1: behind us. Yeah, which is really something because you know, 326 00:19:02,080 --> 00:19:04,560 Speaker 1: if the if any of the what are called toll 327 00:19:04,760 --> 00:19:07,600 Speaker 1: like receptors in the cell, which are always looking out 328 00:19:07,680 --> 00:19:10,119 Speaker 1: for something out of the norm, notice, like m rna, 329 00:19:10,280 --> 00:19:12,200 Speaker 1: what are you doing out here? You should be in there? 330 00:19:12,240 --> 00:19:15,000 Speaker 1: What's going on? Everybody? Hey, come quick, You've got a 331 00:19:15,080 --> 00:19:17,440 Speaker 1: big problem. And you would not be able to actually 332 00:19:17,720 --> 00:19:22,040 Speaker 1: successfully vaccinate somebody because you'd set off the alarm too early. Um, 333 00:19:22,040 --> 00:19:25,560 Speaker 1: there's something called interfere on that uh, it actually does 334 00:19:25,680 --> 00:19:29,199 Speaker 1: interfere with m rna from being transcribed. And so if 335 00:19:29,240 --> 00:19:32,600 Speaker 1: it's perfect name, so if it caught m rna out, 336 00:19:32,840 --> 00:19:37,040 Speaker 1: that interfere on would would come and and um prevent 337 00:19:37,080 --> 00:19:40,080 Speaker 1: the m rna from ever being transcribed into the viral protein. 338 00:19:40,280 --> 00:19:43,200 Speaker 1: That's a big one that that lipid coding helps protect. 339 00:19:43,520 --> 00:19:46,359 Speaker 1: So say, now we've got the m RNA showing up 340 00:19:46,400 --> 00:19:49,119 Speaker 1: in the cytoplasm again coming from outside the cell, but 341 00:19:49,160 --> 00:19:52,359 Speaker 1: now it's in the cytoplasm. Everything's cool, everything is normal, 342 00:19:52,560 --> 00:19:55,360 Speaker 1: and things can kind of proceed from there. That's right. 343 00:19:55,520 --> 00:19:57,760 Speaker 1: And it shows up with those blueprints rolled up under 344 00:19:57,800 --> 00:20:00,760 Speaker 1: their arm. It's got the little work order from from 345 00:20:00,760 --> 00:20:04,120 Speaker 1: the big boss, and it says, all right, ribosomes, you're 346 00:20:04,119 --> 00:20:06,240 Speaker 1: about to get a lot of work thrown your way. 347 00:20:06,600 --> 00:20:08,080 Speaker 1: Are you gonna be okay with that? You've got to 348 00:20:08,080 --> 00:20:11,080 Speaker 1: create all these different proteins that were coded for and 349 00:20:11,119 --> 00:20:13,440 Speaker 1: in this case where we want to stop a pandemic, 350 00:20:13,520 --> 00:20:16,880 Speaker 1: so it's coded uh for this virus. And we've got 351 00:20:16,920 --> 00:20:19,960 Speaker 1: just a tiny little bit of this virus's body. And 352 00:20:20,119 --> 00:20:22,760 Speaker 1: don't worry, you're not gonna get this person sick or 353 00:20:22,800 --> 00:20:27,920 Speaker 1: anything because, uh, my friend Josh Clark taught me, you 354 00:20:28,000 --> 00:20:32,240 Speaker 1: made another metaphor of like a piano player. Traditionally, if 355 00:20:32,280 --> 00:20:34,960 Speaker 1: you want to play the piano, you're gonna use at 356 00:20:35,000 --> 00:20:40,560 Speaker 1: least an arm and probably one of your ears traditionally, Uh, 357 00:20:40,920 --> 00:20:44,720 Speaker 1: but you really want both those arms in both those ears, yes, 358 00:20:44,840 --> 00:20:46,520 Speaker 1: and and like and the in a body to go 359 00:20:46,560 --> 00:20:48,400 Speaker 1: along with it. Like just an ear and an arm 360 00:20:48,440 --> 00:20:51,639 Speaker 1: can't play the piano. So just a little bit of 361 00:20:51,640 --> 00:20:55,080 Speaker 1: this virus isn't gonna make you sick, no, exactly, so 362 00:20:55,400 --> 00:20:57,040 Speaker 1: or let you spread it to someone else. That's a 363 00:20:57,080 --> 00:20:59,240 Speaker 1: big one. And that's what and that's what the m 364 00:20:59,359 --> 00:21:01,280 Speaker 1: R and A shows up coded for it's a little 365 00:21:01,320 --> 00:21:04,080 Speaker 1: piece of the virus that you're you want to immunize 366 00:21:04,119 --> 00:21:06,720 Speaker 1: the person against. And it says, hey, everybody, let's start 367 00:21:06,760 --> 00:21:09,760 Speaker 1: making this. Huh Hey everyone, Hey, we're here. Come make 368 00:21:09,800 --> 00:21:13,600 Speaker 1: this viral protein, which is called the anti antigen. And 369 00:21:13,640 --> 00:21:15,720 Speaker 1: so the body starts doing that because it has it 370 00:21:15,760 --> 00:21:17,600 Speaker 1: didn't know the m RNA was outside of the cell 371 00:21:17,720 --> 00:21:21,359 Speaker 1: or was ever created in a lab um and so 372 00:21:21,400 --> 00:21:25,240 Speaker 1: it starts transcribing the m rna and the viral proteins 373 00:21:25,280 --> 00:21:28,240 Speaker 1: start getting made. And the whole point to all of this, 374 00:21:28,400 --> 00:21:32,119 Speaker 1: if you want like a really good immune response, Chuck, 375 00:21:32,640 --> 00:21:36,520 Speaker 1: you want to trigger both of the two immune systems 376 00:21:36,560 --> 00:21:39,320 Speaker 1: that humans have. You've got the innate system and you 377 00:21:39,359 --> 00:21:42,920 Speaker 1: have the adapted system. Adapted systems, yes, you've got to 378 00:21:43,560 --> 00:21:47,240 Speaker 1: because you're a vertebrate. And um, if you can trigger 379 00:21:47,280 --> 00:21:50,200 Speaker 1: them both to to a large degree but not so 380 00:21:50,280 --> 00:21:52,080 Speaker 1: big a degree that you end up with a site 381 00:21:52,119 --> 00:21:55,040 Speaker 1: to a keen storm that can accidentally kill you, you've 382 00:21:55,080 --> 00:21:59,399 Speaker 1: got a good immunization going. That's right. Uh. And we 383 00:21:59,520 --> 00:22:02,639 Speaker 1: talked about out with Great Wonder and Marvel about the 384 00:22:02,680 --> 00:22:06,679 Speaker 1: human bodies immune system before, but as a refresher, we 385 00:22:06,720 --> 00:22:09,800 Speaker 1: do have two of them. We have the innate which 386 00:22:09,840 --> 00:22:12,760 Speaker 1: is the first line of defense. This is like, uh, 387 00:22:12,960 --> 00:22:16,440 Speaker 1: Sergeant Slaughter, you know, if foreign invaders come in and 388 00:22:16,440 --> 00:22:19,280 Speaker 1: and Sergeant Slaughter just wants to kill, kill, kill, kill 389 00:22:19,320 --> 00:22:22,480 Speaker 1: everything that comes in his in his little scope, and 390 00:22:22,560 --> 00:22:26,000 Speaker 1: that's the innate system. Just neutralize everything the second it 391 00:22:26,040 --> 00:22:27,719 Speaker 1: sees it. Be on the lookout for everything, and if 392 00:22:27,760 --> 00:22:29,960 Speaker 1: it looks weird, kill it. And that's like if you 393 00:22:29,960 --> 00:22:31,720 Speaker 1: get a skin on your knee or a cut on 394 00:22:31,760 --> 00:22:35,440 Speaker 1: your arm or something and it's mild, that inflammation around 395 00:22:35,440 --> 00:22:37,400 Speaker 1: the cut is that innate system. And if it's mild 396 00:22:37,480 --> 00:22:41,000 Speaker 1: enough and it doesn't get complicated or anything, that maybe 397 00:22:41,040 --> 00:22:44,119 Speaker 1: all you need for something like that, Sergeant slaughters an 398 00:22:44,680 --> 00:22:47,119 Speaker 1: that's all you need. But in this case, and with 399 00:22:47,160 --> 00:22:50,360 Speaker 1: anything a little more sophisticated, you're gonna want to engage 400 00:22:50,400 --> 00:22:54,159 Speaker 1: that adaptive system as well. Yeah, which if the innate 401 00:22:54,200 --> 00:22:57,920 Speaker 1: system is is activated on high enough alert, it's going 402 00:22:57,960 --> 00:23:01,680 Speaker 1: to basically go tell the adaptive system like, hey, there's 403 00:23:01,800 --> 00:23:04,440 Speaker 1: this is this is something more than just to cut 404 00:23:04,480 --> 00:23:06,640 Speaker 1: on the knee, like we we really need to pay 405 00:23:06,680 --> 00:23:09,480 Speaker 1: attention to this. And the adaptive system is made up 406 00:23:09,520 --> 00:23:13,640 Speaker 1: of specialized white blood cells and they basically are trained 407 00:23:13,680 --> 00:23:17,160 Speaker 1: to take a look at this weird new foreign invader, 408 00:23:17,320 --> 00:23:20,600 Speaker 1: which are called non self materials. Basically, anything that isn't 409 00:23:20,680 --> 00:23:22,880 Speaker 1: part of you, that comes from outside of your body, 410 00:23:22,960 --> 00:23:25,600 Speaker 1: it's called non self And so they look, I think 411 00:23:25,640 --> 00:23:30,679 Speaker 1: so too, Um, I see maybe Phil Collins final album 412 00:23:30,840 --> 00:23:33,719 Speaker 1: non self material. Yeah, but then it just be the 413 00:23:33,760 --> 00:23:36,600 Speaker 1: cover album, which is good. It's it's a great name 414 00:23:36,640 --> 00:23:39,919 Speaker 1: for standards, you know. Um. So they look at this 415 00:23:39,960 --> 00:23:42,480 Speaker 1: non self material and they say, okay, we got to 416 00:23:42,480 --> 00:23:46,439 Speaker 1: remember this. So they basically learn it, learn to recognize it, 417 00:23:46,920 --> 00:23:50,560 Speaker 1: catalog it, and then figure out how to produce antibodies 418 00:23:50,600 --> 00:23:55,119 Speaker 1: that specifically attack this virus or this antigen um, the 419 00:23:55,200 --> 00:23:58,120 Speaker 1: little bit of the virus that that can be infectious. 420 00:23:58,359 --> 00:24:00,920 Speaker 1: And then it remembers it and of the next time 421 00:24:01,440 --> 00:24:04,480 Speaker 1: that antigen or that virus comes into your body, your 422 00:24:04,520 --> 00:24:08,399 Speaker 1: body is ready because the innate system triggered the adapted system, 423 00:24:08,440 --> 00:24:12,439 Speaker 1: which memorized and cataloged antibodies to fight who used to 424 00:24:12,480 --> 00:24:16,560 Speaker 1: fight that virus? Yes, and it's it works great and 425 00:24:16,600 --> 00:24:19,840 Speaker 1: it works fast. Uh. There was a study that found 426 00:24:19,880 --> 00:24:25,040 Speaker 1: that the antibody producing cells can produce ten thousand antibodies 427 00:24:25,680 --> 00:24:30,200 Speaker 1: per hour, no, no, no per minute, no, no, ten 428 00:24:30,240 --> 00:24:34,320 Speaker 1: thousand anybody's per second. So like it literally just wants 429 00:24:34,359 --> 00:24:40,080 Speaker 1: to flood that site with with reinforcements, basically to kill 430 00:24:40,119 --> 00:24:43,960 Speaker 1: all this stuff in a very smart, strategic and pinpointed way. Yeah, 431 00:24:44,000 --> 00:24:46,240 Speaker 1: so you've got your innate system your adaptive system. You 432 00:24:46,280 --> 00:24:49,200 Speaker 1: want to set them both off. And so we're going 433 00:24:49,280 --> 00:24:51,960 Speaker 1: back into the cell. And by now, in this whole 434 00:24:51,960 --> 00:24:55,240 Speaker 1: time that we've been talking, the cell that took up 435 00:24:55,240 --> 00:24:57,480 Speaker 1: the m R and A that was injected into you 436 00:24:57,560 --> 00:25:01,200 Speaker 1: in the vaccine um has been making that viral protein, 437 00:25:01,280 --> 00:25:03,879 Speaker 1: the antigen, over and over again. It's like, I like this, 438 00:25:04,080 --> 00:25:05,359 Speaker 1: I don't know what to do with it. I'm gonna 439 00:25:05,359 --> 00:25:08,680 Speaker 1: just gonna start wearing it on the surface of my cell. 440 00:25:09,640 --> 00:25:12,639 Speaker 1: And the cell doesn't know any different. It thinks that, 441 00:25:12,680 --> 00:25:15,480 Speaker 1: you know, everything's going hunky dory, but it looks good 442 00:25:15,480 --> 00:25:19,520 Speaker 1: on me. Lucky exactly, but luckily. Um. We have some 443 00:25:19,640 --> 00:25:22,600 Speaker 1: kinds of immune cells, as innate immune cells, who are 444 00:25:22,600 --> 00:25:25,960 Speaker 1: on the lookout for anything weird. They're total fascists. They 445 00:25:25,960 --> 00:25:30,760 Speaker 1: don't truck any kind of a nonconformity or anything out 446 00:25:30,760 --> 00:25:34,240 Speaker 1: of the norm. And they look at this this new 447 00:25:34,440 --> 00:25:37,040 Speaker 1: same muscle cell, because that's what you get your your 448 00:25:37,119 --> 00:25:40,720 Speaker 1: vaccine injected into wearing all these weird viral proteins and 449 00:25:40,760 --> 00:25:43,680 Speaker 1: to say, come with me. And they overwhelmed that poor cell. 450 00:25:43,760 --> 00:25:47,359 Speaker 1: They take them out back and basically disassemble them. I 451 00:25:47,480 --> 00:25:51,120 Speaker 1: love that. I wonder it makes you wonder, like all 452 00:25:51,160 --> 00:25:53,800 Speaker 1: these cells are just doing the same thing, but like 453 00:25:53,920 --> 00:25:57,439 Speaker 1: some of them go, wait a minute, like you you 454 00:25:57,480 --> 00:26:00,240 Speaker 1: are very suspicious and you're coming with me. I'm going 455 00:26:00,280 --> 00:26:03,879 Speaker 1: to introduce you to my friend, the adaptive system. Like 456 00:26:03,960 --> 00:26:06,199 Speaker 1: do they know which cells or is it just a 457 00:26:06,320 --> 00:26:09,080 Speaker 1: random thing? What do you mean they know what cells? 458 00:26:09,280 --> 00:26:11,960 Speaker 1: You know? The cells that go that are more suspicious. 459 00:26:13,080 --> 00:26:16,560 Speaker 1: But I guess what they're saying is like, stop expressing yourself, 460 00:26:18,200 --> 00:26:22,120 Speaker 1: all right? Is that? Is that what you meant? Sort of? No, well, 461 00:26:22,119 --> 00:26:24,080 Speaker 1: I've got I just find it interesting that some of 462 00:26:24,119 --> 00:26:27,680 Speaker 1: them are just doing their thing and then some of them. 463 00:26:27,720 --> 00:26:29,880 Speaker 1: I mean they're the same kinds of cells. No, no, no, 464 00:26:29,920 --> 00:26:32,399 Speaker 1: they're different kinds of cells, so they are different. The 465 00:26:32,520 --> 00:26:36,560 Speaker 1: cells that are are suspicious, those are your innate immune cells. 466 00:26:36,560 --> 00:26:38,720 Speaker 1: They're constantly on lookout for something weird, and when they 467 00:26:38,760 --> 00:26:41,439 Speaker 1: find something weird, they just kill it. All right, and 468 00:26:41,640 --> 00:26:44,120 Speaker 1: the other cells are just they're yeah, they're just sitting 469 00:26:44,119 --> 00:26:46,080 Speaker 1: there like, not me. You don't look at me. I'm normal. 470 00:26:46,119 --> 00:26:48,840 Speaker 1: I'm normal. I've got I've got no weird proteins on 471 00:26:48,880 --> 00:26:51,520 Speaker 1: my surface. Okay, that makes sense now, Okay. So then 472 00:26:51,560 --> 00:26:54,800 Speaker 1: those cells that take the poor muscle cell that's been 473 00:26:54,800 --> 00:26:57,760 Speaker 1: creating this viral protein and thinks it looks pretty snazzy 474 00:26:57,960 --> 00:27:00,920 Speaker 1: and is now being disassembled, take some of those viral 475 00:27:00,960 --> 00:27:04,960 Speaker 1: proteins to the adaptive immune system, and that's where they say, hey, guys, 476 00:27:05,000 --> 00:27:06,840 Speaker 1: look at this. We don't know what this is, but 477 00:27:06,960 --> 00:27:09,199 Speaker 1: we think it's a problem. So you might want to 478 00:27:09,240 --> 00:27:12,200 Speaker 1: remember it and create some antibodies that you can deploy 479 00:27:12,240 --> 00:27:14,560 Speaker 1: against it if we ever see it again later. And 480 00:27:14,600 --> 00:27:18,320 Speaker 1: at that point, after all of that happens, you are 481 00:27:18,640 --> 00:27:22,920 Speaker 1: vaccinated against that. Yeah. And you know, here's the thing 482 00:27:23,000 --> 00:27:26,119 Speaker 1: that some other myths that people think that, uh, this 483 00:27:26,160 --> 00:27:28,160 Speaker 1: thing will live inside your body and who knows what's 484 00:27:28,160 --> 00:27:30,760 Speaker 1: going to happen in ten years. In ten years, we'll 485 00:27:30,800 --> 00:27:32,760 Speaker 1: all have horns growing out of our heads because of this. 486 00:27:33,640 --> 00:27:36,000 Speaker 1: That's not what happens. M r A. M r NA 487 00:27:36,200 --> 00:27:40,399 Speaker 1: leaves you. It's very fragile, like we mentioned, and different 488 00:27:40,440 --> 00:27:44,199 Speaker 1: studies have shown different results, but somewhere in the neighborhood 489 00:27:44,280 --> 00:27:46,720 Speaker 1: of a few days to a couple of weeks is 490 00:27:46,800 --> 00:27:49,600 Speaker 1: basically as long as that m r NA is going 491 00:27:49,640 --> 00:27:52,920 Speaker 1: to survive before it degrades and then leave your body 492 00:27:52,920 --> 00:27:55,960 Speaker 1: through the limp system. Yeah, and under normal circumstances, it's 493 00:27:56,000 --> 00:27:57,800 Speaker 1: just a few days, but they figured out how to 494 00:27:57,840 --> 00:28:00,159 Speaker 1: make it a little stronger because you wanted in a 495 00:28:00,160 --> 00:28:03,120 Speaker 1: little longer, because the more that your muscle cells are 496 00:28:03,119 --> 00:28:08,119 Speaker 1: producing this viral protein, the more of an innate response, 497 00:28:08,160 --> 00:28:10,399 Speaker 1: and then hence the more of an adaptive response you're 498 00:28:10,400 --> 00:28:12,840 Speaker 1: going to get. But no matter what they do, the 499 00:28:13,000 --> 00:28:14,880 Speaker 1: m r and A is going to go away. It's 500 00:28:14,920 --> 00:28:18,000 Speaker 1: going to follow all the normal processes for exiting the body. 501 00:28:18,320 --> 00:28:20,879 Speaker 1: Those cells that produced that viral protein are going to 502 00:28:20,960 --> 00:28:23,280 Speaker 1: be destroyed, and then those viral proteins are gonna be 503 00:28:23,359 --> 00:28:26,120 Speaker 1: taken up and taken to the lymph nodes where they're 504 00:28:26,160 --> 00:28:29,000 Speaker 1: shown to those um T and B cells that produce 505 00:28:29,080 --> 00:28:31,640 Speaker 1: the antibodies against them. All of that is a totally 506 00:28:31,680 --> 00:28:34,919 Speaker 1: normal process, and that is the point of vaccination because 507 00:28:35,000 --> 00:28:38,240 Speaker 1: during this process, maybe you're innate immune response makes you 508 00:28:38,280 --> 00:28:40,320 Speaker 1: feel like you get the flu for a few like 509 00:28:40,480 --> 00:28:43,960 Speaker 1: hours or half of a day, or maybe your arm 510 00:28:44,040 --> 00:28:47,480 Speaker 1: hurts really bad. That's that innate response. But you're not 511 00:28:47,600 --> 00:28:50,720 Speaker 1: going to get sick. You're not actually going to have 512 00:28:51,000 --> 00:28:57,520 Speaker 1: COVID because it's that live training with blanks to to 513 00:28:57,520 --> 00:29:00,720 Speaker 1: to to train your immune system how to recognize it, 514 00:29:00,800 --> 00:29:04,120 Speaker 1: so that when stars COVID two virus comes along and says, 515 00:29:04,400 --> 00:29:06,560 Speaker 1: I'll see what's going on here, he goes, Oh my god, 516 00:29:06,560 --> 00:29:09,360 Speaker 1: Oh no, somehow this thing, this this body has already 517 00:29:09,360 --> 00:29:11,600 Speaker 1: been trained to attack me. Now I'm dead and gone 518 00:29:11,600 --> 00:29:15,360 Speaker 1: and I can't possibly infect this person. That is the point, 519 00:29:15,600 --> 00:29:19,000 Speaker 1: and that's what's been done with MR and A vaccines. Yeah, 520 00:29:19,040 --> 00:29:21,200 Speaker 1: and I was about to describe this last part as 521 00:29:21,320 --> 00:29:24,320 Speaker 1: another miracle in this, but I think we're degrading the 522 00:29:24,640 --> 00:29:27,000 Speaker 1: hard work and research to describe it as a miracle. 523 00:29:27,680 --> 00:29:29,640 Speaker 1: It is hard work in research is what led to 524 00:29:29,680 --> 00:29:33,160 Speaker 1: this stuff. So I guess we'll call it a breakthrough. 525 00:29:33,240 --> 00:29:36,240 Speaker 1: One of the other biggest breakthroughs is that they had 526 00:29:36,280 --> 00:29:39,280 Speaker 1: to find the what you called the goldilocks zone, that 527 00:29:39,280 --> 00:29:44,080 Speaker 1: that perfect, perfect amount so this thing would work perfectly. 528 00:29:44,280 --> 00:29:47,400 Speaker 1: So we talked about the cytokine storms. You don't want that. 529 00:29:47,480 --> 00:29:50,280 Speaker 1: You don't want to overblow it and do too much, 530 00:29:50,760 --> 00:29:52,520 Speaker 1: so you had to dial it back a little bit. 531 00:29:52,880 --> 00:29:55,480 Speaker 1: But it can't be so weak that it doesn't even 532 00:29:55,560 --> 00:29:58,280 Speaker 1: notice the antigen to begin with. It's got a notice, 533 00:29:58,680 --> 00:30:01,280 Speaker 1: so it designs, says Annabi ease, so you have to 534 00:30:01,320 --> 00:30:04,320 Speaker 1: find the goldilocks zone in there. And then there's this 535 00:30:04,400 --> 00:30:07,720 Speaker 1: last bit of the fact that there's a basically an 536 00:30:07,720 --> 00:30:11,240 Speaker 1: early warning system in the body that prevents m RNA 537 00:30:11,480 --> 00:30:15,760 Speaker 1: from being translated. If it thinks like it's not built well, 538 00:30:15,880 --> 00:30:18,640 Speaker 1: if it's miss if it's misfolded or something, it can 539 00:30:18,680 --> 00:30:21,520 Speaker 1: really wreck the body system. So it's on the lookout 540 00:30:21,560 --> 00:30:24,720 Speaker 1: for that stuff, and it has to get past that 541 00:30:24,760 --> 00:30:28,760 Speaker 1: early warning system in order to make all this work anyway, 542 00:30:28,800 --> 00:30:31,320 Speaker 1: and they did it. They did all of those things. 543 00:30:32,160 --> 00:30:36,440 Speaker 1: It's pretty amazing. They made something that's natural enough to 544 00:30:36,720 --> 00:30:39,720 Speaker 1: full nature for for for all intents and purposes. Your 545 00:30:39,720 --> 00:30:42,200 Speaker 1: body is like, oh, I've made this mrn a cool, 546 00:30:42,320 --> 00:30:45,840 Speaker 1: let's listen to let's let's start translating it, which is astounding, 547 00:30:45,920 --> 00:30:49,400 Speaker 1: and then everything just kind of follows that process just perfectly, 548 00:30:49,760 --> 00:30:51,520 Speaker 1: and it really is like, hats off to those people. 549 00:30:51,560 --> 00:30:55,560 Speaker 1: Who made this stuff? You know, hats off, and I 550 00:30:55,600 --> 00:30:58,160 Speaker 1: think let's take a break. I think we did a 551 00:30:58,160 --> 00:31:01,840 Speaker 1: pretty good job there. Yeah, so too, and we're gonna 552 00:31:01,880 --> 00:31:05,320 Speaker 1: talk about how they make this stuff right after this 553 00:31:31,560 --> 00:31:41,720 Speaker 1: learn it's stop with Joshua Jos al Right, I love 554 00:31:41,760 --> 00:31:44,680 Speaker 1: how you put this so much in this uh in 555 00:31:44,720 --> 00:31:48,200 Speaker 1: this article, I'm gonna read it verbatim. Okay, to put 556 00:31:48,240 --> 00:31:53,720 Speaker 1: in a nutshell that's so oversimplified, it's basically wrong. Engineers 557 00:31:53,720 --> 00:31:57,160 Speaker 1: spell out the genetic code they want the m RNA 558 00:31:57,280 --> 00:32:00,120 Speaker 1: to carry, They add the ingredients, they press enter, and 559 00:32:00,160 --> 00:32:03,080 Speaker 1: the computer tells the lab equipment what chemical reactions to 560 00:32:03,080 --> 00:32:06,400 Speaker 1: carry out and for how long. I mean, that's kind 561 00:32:06,440 --> 00:32:10,200 Speaker 1: of it in a nutshell in the simplest like if this, 562 00:32:11,040 --> 00:32:13,000 Speaker 1: if you really need to tell your weird uncle at 563 00:32:13,000 --> 00:32:16,640 Speaker 1: Thanksgiving how it works, you may just want to start there, 564 00:32:17,520 --> 00:32:20,160 Speaker 1: right and see what his reaction is he goes they 565 00:32:20,200 --> 00:32:25,440 Speaker 1: press enter. That's my greatest fear, right, haven't you ever 566 00:32:25,440 --> 00:32:29,720 Speaker 1: seen war games? Right? But to start nice, to start 567 00:32:29,720 --> 00:32:32,080 Speaker 1: at the beginning, though, you have to understand what the 568 00:32:32,120 --> 00:32:35,600 Speaker 1: genetic code of this virus you're trying to fight. And again, 569 00:32:35,680 --> 00:32:39,440 Speaker 1: thank you Human Genome Project for pushing that along um. 570 00:32:39,480 --> 00:32:42,000 Speaker 1: And once you have the genetic code and you studied 571 00:32:42,000 --> 00:32:44,560 Speaker 1: the virus, you can figure out what it's achilles heel is. 572 00:32:45,000 --> 00:32:47,200 Speaker 1: And in the case of the covid vaccines, the to 573 00:32:47,760 --> 00:32:51,600 Speaker 1: um one from Maderna, uh and then one from bio 574 00:32:51,720 --> 00:32:54,920 Speaker 1: in Tech, and Visor can't forget to mention bio in Tech. 575 00:32:55,000 --> 00:32:57,360 Speaker 1: Basically they're the ones who actually came up with the 576 00:32:57,440 --> 00:33:01,200 Speaker 1: template for this vaccine, and Visor was like, hey, let's partner. 577 00:33:01,320 --> 00:33:04,040 Speaker 1: So it's it's wrong to just call it the Fiser vaccine. 578 00:33:04,440 --> 00:33:07,040 Speaker 1: And by the way, just announced today that they approved 579 00:33:07,040 --> 00:33:10,360 Speaker 1: mix and match. I heard that too, which is it's 580 00:33:10,400 --> 00:33:13,400 Speaker 1: it's awesome. I mean, everybody loves variety. It's a spice 581 00:33:13,400 --> 00:33:15,920 Speaker 1: of life. Well, I'm still gonna I got the Maderna 582 00:33:16,040 --> 00:33:18,160 Speaker 1: to begin with. I'm gonna get the Maderna booster. I'm 583 00:33:18,160 --> 00:33:20,120 Speaker 1: gonna I like variety, but I'm just gonna keep it, 584 00:33:20,280 --> 00:33:21,880 Speaker 1: keep it in the family. Now, that's my plan too. 585 00:33:22,040 --> 00:33:24,120 Speaker 1: I like the Maderna as well. And by the way, 586 00:33:24,200 --> 00:33:26,479 Speaker 1: this is so new and Maderna is such a new company. 587 00:33:26,520 --> 00:33:29,760 Speaker 1: I think they were organized in two thou the covid 588 00:33:29,840 --> 00:33:32,560 Speaker 1: vaccine that they make is the only product that they sell. 589 00:33:33,200 --> 00:33:35,760 Speaker 1: That's how new all of this stuff is. It's crazy. 590 00:33:35,800 --> 00:33:39,840 Speaker 1: But for the coronavirus vaccines, the covid vaccines, chuck um. 591 00:33:39,880 --> 00:33:43,440 Speaker 1: They figured out that the spike protein s protein is 592 00:33:43,480 --> 00:33:46,560 Speaker 1: what it's called. That that is the virus is Achilles heel. 593 00:33:46,880 --> 00:33:50,480 Speaker 1: It's the thing that gives the coronavirus that spiky appearance, 594 00:33:51,160 --> 00:33:54,080 Speaker 1: that crown. Yeah, and that is the thing that it 595 00:33:54,320 --> 00:33:58,040 Speaker 1: uses to fuse two a cell's membrane and then basically 596 00:33:58,080 --> 00:34:00,160 Speaker 1: coax it to open up so that it can bill 597 00:34:00,200 --> 00:34:03,040 Speaker 1: it's viral contents in there and make more and more viruses. 598 00:34:03,440 --> 00:34:05,680 Speaker 1: So it's the weakest point of the virus and that's 599 00:34:05,720 --> 00:34:08,440 Speaker 1: what they figured out how to target. But to understand that, 600 00:34:08,480 --> 00:34:10,920 Speaker 1: you have to know what the genome is so that 601 00:34:10,960 --> 00:34:13,000 Speaker 1: you can go in and say, here's the part of 602 00:34:13,040 --> 00:34:16,719 Speaker 1: the genetic code of the stars cove two virus that 603 00:34:16,800 --> 00:34:20,920 Speaker 1: makes that spike protein. Let's take this plug it into 604 00:34:21,400 --> 00:34:25,200 Speaker 1: a different um like a string of m rna, and 605 00:34:25,239 --> 00:34:28,680 Speaker 1: then we'll have that m rna that produces that spike 606 00:34:28,719 --> 00:34:30,759 Speaker 1: protein and we can use that in a vaccine. And 607 00:34:30,800 --> 00:34:34,080 Speaker 1: that's what they've done. It's it almost seems like a 608 00:34:34,160 --> 00:34:38,600 Speaker 1: Greek myth or something with the with the crown, because 609 00:34:38,600 --> 00:34:40,680 Speaker 1: I remember when we talked about the coronavirus and that 610 00:34:40,800 --> 00:34:44,400 Speaker 1: fancy crown and like, look at my fancy crown. And 611 00:34:44,440 --> 00:34:46,600 Speaker 1: it turns out is that that fancy crown is what's 612 00:34:46,600 --> 00:34:50,719 Speaker 1: going to drag it down and vanity, vanity, that's what 613 00:34:50,760 --> 00:34:54,360 Speaker 1: it is. We're playing a lot of human emotions. It's 614 00:34:54,239 --> 00:34:59,000 Speaker 1: it flew too close to the sun, that's right. Uh 615 00:34:59,040 --> 00:35:01,399 Speaker 1: So they identify I that little crown, like you said, 616 00:35:01,480 --> 00:35:03,560 Speaker 1: is the Achilles heel, and they got that little bit 617 00:35:03,560 --> 00:35:08,040 Speaker 1: of code and uh then the rest of this is 618 00:35:08,640 --> 00:35:10,920 Speaker 1: and this is sort of another one of the big breakthroughs. 619 00:35:11,200 --> 00:35:13,359 Speaker 1: I'm not gonna call it a miracle, is that they 620 00:35:13,480 --> 00:35:16,239 Speaker 1: again they figured out how to do this all outside 621 00:35:16,280 --> 00:35:19,279 Speaker 1: of the human body because they got ahold of plasmid 622 00:35:19,680 --> 00:35:23,160 Speaker 1: plasmid not plasma p L A S M I D 623 00:35:23,320 --> 00:35:27,239 Speaker 1: plasmid d na um usually from ecoli. But don't let 624 00:35:27,280 --> 00:35:29,560 Speaker 1: let that freak you out. It turns out it's really 625 00:35:29,560 --> 00:35:33,240 Speaker 1: helpful in this case. And this acts as like a template. 626 00:35:33,280 --> 00:35:36,239 Speaker 1: It's just like the working the working DNA that they 627 00:35:36,360 --> 00:35:38,960 Speaker 1: used to figure all this stuff out is standing in 628 00:35:39,000 --> 00:35:42,600 Speaker 1: for the humans own DNA, and it's in the uh, 629 00:35:42,680 --> 00:35:44,279 Speaker 1: it's in that it's on that work site, it's in 630 00:35:44,320 --> 00:35:49,800 Speaker 1: that cytoplasm. It's like almost extra bonus DNA that's outside 631 00:35:49,800 --> 00:35:52,640 Speaker 1: the nucleus, and so they're using that to stand in 632 00:35:52,760 --> 00:35:55,440 Speaker 1: for our own DNA. So we could figure, you know, 633 00:35:55,440 --> 00:35:57,799 Speaker 1: we could figure out how to make this stuff work together. Yeah, 634 00:35:57,840 --> 00:36:00,560 Speaker 1: it's almost like if you're looking at a piano keyboard 635 00:36:01,120 --> 00:36:05,480 Speaker 1: and the piano keyboard was plasmid DNA, and say it 636 00:36:05,840 --> 00:36:08,759 Speaker 1: coded for luminescence or something like that. If you went 637 00:36:08,840 --> 00:36:11,719 Speaker 1: along and took out some of the keys and put 638 00:36:11,760 --> 00:36:15,200 Speaker 1: in different keys, then now that it's coded for an 639 00:36:15,360 --> 00:36:18,239 Speaker 1: entirely different kind of protein. In this case, that the 640 00:36:18,280 --> 00:36:21,480 Speaker 1: antigen that you want, that spike protein. But the point 641 00:36:21,520 --> 00:36:24,400 Speaker 1: is it's like a structure. I keep using the piano 642 00:36:24,480 --> 00:36:27,440 Speaker 1: metaphor in different of thrilling ways, and I'm pretty happy 643 00:36:27,480 --> 00:36:30,000 Speaker 1: with that. But it's the backbone. It's the thing that 644 00:36:30,080 --> 00:36:34,080 Speaker 1: you use to hold the original code. Because remember m 645 00:36:34,239 --> 00:36:38,160 Speaker 1: R n A likes to go to DNA to make 646 00:36:38,200 --> 00:36:41,319 Speaker 1: a copy of that little code, that string of of 647 00:36:41,400 --> 00:36:44,479 Speaker 1: g's and teas and season as. That's how it's made, 648 00:36:44,600 --> 00:36:47,120 Speaker 1: and that's how it happens in the body. That's how 649 00:36:47,120 --> 00:36:48,759 Speaker 1: they do in the lab two. And to start that 650 00:36:48,800 --> 00:36:52,560 Speaker 1: means you have to have d N A okay, right, 651 00:36:53,320 --> 00:36:56,520 Speaker 1: But here's the thing. You can't just create that template 652 00:36:56,600 --> 00:36:59,640 Speaker 1: and then that's it. No bing bang boom bon joe. 653 00:36:59,719 --> 00:37:03,759 Speaker 1: You got transcribe that into the m RNA. And I 654 00:37:03,800 --> 00:37:07,279 Speaker 1: think in the nineteen eighties at Bruckhaba National Lab is 655 00:37:07,280 --> 00:37:12,440 Speaker 1: where they developed this really ingenious technique that use bacterial flages, 656 00:37:12,840 --> 00:37:15,800 Speaker 1: which are these viral parasites that uh and this is 657 00:37:15,840 --> 00:37:17,600 Speaker 1: where the E. Coli kind of comes back in that 658 00:37:17,640 --> 00:37:20,480 Speaker 1: infect bacteria like E. Coal I. And they have a 659 00:37:20,560 --> 00:37:24,359 Speaker 1: really really efficient RNA transcription engine, so they said, well, 660 00:37:24,400 --> 00:37:26,440 Speaker 1: let's just use that because it's already really good at 661 00:37:26,480 --> 00:37:29,279 Speaker 1: that yeah, which is pretty cool. And here's the other 662 00:37:29,320 --> 00:37:32,320 Speaker 1: thing too. If you're like, oh my god, equal I plasma, 663 00:37:32,400 --> 00:37:35,799 Speaker 1: d NA, bacterial flages that are viral parasites they're using 664 00:37:35,840 --> 00:37:40,000 Speaker 1: this together's it's like frankent signed stuff. Keep in mind 665 00:37:40,400 --> 00:37:45,400 Speaker 1: they're not harvesting like wild ecoli or wild bacteria floges, 666 00:37:45,800 --> 00:37:48,920 Speaker 1: like they're building those things from scratch in the lab, 667 00:37:49,680 --> 00:37:52,160 Speaker 1: and they're getting to the point. If they're not already there, 668 00:37:52,560 --> 00:37:54,560 Speaker 1: whether like, oh, we only need this part of the 669 00:37:54,600 --> 00:37:57,480 Speaker 1: plasma DNA, which again, by the way, does not create 670 00:37:57,520 --> 00:38:00,239 Speaker 1: equal like it creates an extra bit of some thing, 671 00:38:00,640 --> 00:38:03,200 Speaker 1: or we only need this part of the bacterial flage, 672 00:38:03,560 --> 00:38:05,839 Speaker 1: and so they just make those parts that they need 673 00:38:06,320 --> 00:38:10,800 Speaker 1: or increasingly just order them from from lab supply companies online. 674 00:38:11,280 --> 00:38:13,520 Speaker 1: Like that's the point that we're at now, because again, 675 00:38:13,520 --> 00:38:15,879 Speaker 1: these are all non living things that you can sterilize, 676 00:38:15,960 --> 00:38:19,439 Speaker 1: and they're in some cases not just parts of non 677 00:38:19,560 --> 00:38:24,719 Speaker 1: living things like plasmid DNA or bacteria flage. Yeah, I mean, 678 00:38:24,840 --> 00:38:27,920 Speaker 1: it's it's amazing. So they put this, uh, the plasma 679 00:38:28,040 --> 00:38:30,960 Speaker 1: DNA template. They take the bacteria flage and they put 680 00:38:31,000 --> 00:38:34,600 Speaker 1: it in a big soup kettle on the stove. They 681 00:38:34,600 --> 00:38:37,200 Speaker 1: add a little chemical go juice that says, all right, 682 00:38:37,239 --> 00:38:40,360 Speaker 1: get started, and then the bacteria flage says, wait a minute, 683 00:38:40,360 --> 00:38:43,160 Speaker 1: I know what I'm good at. I'm great at that transcription, 684 00:38:43,760 --> 00:38:47,040 Speaker 1: and so I'm gonna just start transcribing right now, and 685 00:38:47,080 --> 00:38:50,560 Speaker 1: I'm gonna transcribe that code in the plasma DNA and 686 00:38:50,600 --> 00:38:55,440 Speaker 1: I'm gonna produce a ton of m RNA strands. And 687 00:38:55,520 --> 00:38:58,080 Speaker 1: it doesn't it doesn't sound like a lot. But if 688 00:38:58,120 --> 00:39:01,440 Speaker 1: you have a an average production run, you're gonna get 689 00:39:01,440 --> 00:39:05,480 Speaker 1: about two grams of m RNA per leader. That's like 690 00:39:05,560 --> 00:39:09,319 Speaker 1: seven to ten coffee beans averagise coffee beans. Yeah, and 691 00:39:09,320 --> 00:39:10,839 Speaker 1: that's in a few days. And you might think, like 692 00:39:11,040 --> 00:39:12,640 Speaker 1: I thought, he said a lot. A couple of grams 693 00:39:12,719 --> 00:39:16,879 Speaker 1: is in a lot. These vaccines use, I think respectively, 694 00:39:16,960 --> 00:39:22,120 Speaker 1: Maderna and Fiser use a hundred and thirty micrograms per dose, 695 00:39:22,560 --> 00:39:25,400 Speaker 1: so that two grams ends up producing anywhere from two 696 00:39:25,480 --> 00:39:29,120 Speaker 1: hundred thousand to six hundred thousand actual vaccine doses. Yeah. 697 00:39:29,160 --> 00:39:31,319 Speaker 1: And also, don't forget we're talking about m rna, which 698 00:39:31,320 --> 00:39:34,400 Speaker 1: exists on the nano scale, and you're producing ten coffee 699 00:39:34,400 --> 00:39:38,840 Speaker 1: beans worth of that stuff in three days. They're talking small, yes, 700 00:39:39,080 --> 00:39:43,520 Speaker 1: very small. So they've got tons of m rna each 701 00:39:43,560 --> 00:39:46,560 Speaker 1: time they run one of these batches. And then they 702 00:39:46,600 --> 00:39:49,279 Speaker 1: take that m RNA that comes out and they purify it. 703 00:39:49,360 --> 00:39:52,839 Speaker 1: They get rid of any leftover nuclic materials from that 704 00:39:52,880 --> 00:39:56,760 Speaker 1: transcription process, clean up the slop, like I was saying, 705 00:39:57,560 --> 00:40:00,160 Speaker 1: and then they surround it with a lipid nanopartic goal 706 00:40:00,239 --> 00:40:02,200 Speaker 1: that packet of fats. It's gonna help it get into 707 00:40:02,239 --> 00:40:04,480 Speaker 1: the cell and protect it on its wild journey through 708 00:40:04,480 --> 00:40:06,960 Speaker 1: the body. And then they mix it with a few 709 00:40:06,960 --> 00:40:11,080 Speaker 1: other things, UM, usually a few kinds of um salts, 710 00:40:11,120 --> 00:40:15,200 Speaker 1: often to um to mimic the pH of the body 711 00:40:15,320 --> 00:40:18,239 Speaker 1: so that it's gets accepted a lot more easily. UM. 712 00:40:18,719 --> 00:40:22,319 Speaker 1: They use sugar to stabilize the whole thing. And that's 713 00:40:22,360 --> 00:40:25,319 Speaker 1: about it, and not even about it. That's it. Like 714 00:40:25,400 --> 00:40:27,960 Speaker 1: there there's some fats, there's the m R and a 715 00:40:28,040 --> 00:40:30,839 Speaker 1: salt and sugar, and then that's what you have in 716 00:40:30,880 --> 00:40:34,399 Speaker 1: your vaccine, whether it's the bio in tech Fighter or 717 00:40:34,480 --> 00:40:37,920 Speaker 1: the madernal one. That's right. And if weird uncle says, yeah, 718 00:40:38,000 --> 00:40:41,080 Speaker 1: but what else is really in there? Say, that's it 719 00:40:41,520 --> 00:40:43,879 Speaker 1: the salt and the sugar and what I just told 720 00:40:43,880 --> 00:40:47,400 Speaker 1: you about, dumb, dumb, And he'll say hopefully, well that 721 00:40:47,440 --> 00:40:52,040 Speaker 1: makes me hungry. Now sounds delicious from in my mouth. 722 00:40:52,800 --> 00:40:55,759 Speaker 1: It's like there's no butter in that, all right, Yeah, 723 00:40:55,760 --> 00:41:00,239 Speaker 1: there's lipidano particles. So we're gonna finish up talking little 724 00:41:00,239 --> 00:41:04,759 Speaker 1: bit about what differentiates this from traditional vaccines. Uh. The 725 00:41:04,800 --> 00:41:07,520 Speaker 1: biggest thing is that it's, like we've said before, it's 726 00:41:07,560 --> 00:41:11,879 Speaker 1: built from scratching a lab outside the human body, and 727 00:41:12,200 --> 00:41:15,080 Speaker 1: that's very different and it's non living, like we said, 728 00:41:15,080 --> 00:41:18,879 Speaker 1: And other vaccines are called viral vector vaccines, and they 729 00:41:19,000 --> 00:41:21,520 Speaker 1: either use like if you get a flu shot or something. 730 00:41:21,840 --> 00:41:24,879 Speaker 1: You're talking about either dead virus or a live one 731 00:41:25,360 --> 00:41:29,480 Speaker 1: that's been weakened, or proteins from a live virus. And 732 00:41:29,520 --> 00:41:32,839 Speaker 1: it takes a long time to produce these. Uh, it's 733 00:41:32,880 --> 00:41:36,319 Speaker 1: not like like this thing went at light speed, but 734 00:41:36,520 --> 00:41:39,120 Speaker 1: not in an unsafe way, in a in a truly 735 00:41:39,160 --> 00:41:42,960 Speaker 1: astounding applaudable way. Yeah. No, I was reading about the 736 00:41:43,000 --> 00:41:46,920 Speaker 1: Emergency Use Authorization project process and like the FDA did 737 00:41:46,960 --> 00:41:50,760 Speaker 1: not mess around like they they They definitely did double 738 00:41:50,840 --> 00:41:53,080 Speaker 1: time to to try to get these things out of 739 00:41:53,080 --> 00:41:54,600 Speaker 1: the door because they needed to, but they did not 740 00:41:54,719 --> 00:41:57,680 Speaker 1: cut corners on safety from anything I saw. It was 741 00:41:57,719 --> 00:42:00,880 Speaker 1: a really safe process and it but it was still 742 00:42:00,920 --> 00:42:04,560 Speaker 1: really fast, not because the FDA cut corners, but because 743 00:42:05,000 --> 00:42:08,960 Speaker 1: mRNA vaccines are able to be created really really fast, 744 00:42:09,480 --> 00:42:13,560 Speaker 1: and so I think bio and tech fiser Um had 745 00:42:14,000 --> 00:42:19,920 Speaker 1: emergency use approval within eleven months. Eleven months of developing 746 00:42:19,960 --> 00:42:25,000 Speaker 1: the vaccine, the second fastest of vaccine had ever been 747 00:42:25,640 --> 00:42:28,719 Speaker 1: developed before prior to m R and A vaccines is 748 00:42:28,840 --> 00:42:32,279 Speaker 1: four years. Yeah, I want to say a little bit 749 00:42:32,719 --> 00:42:34,799 Speaker 1: something else about that, because I think that's a big 750 00:42:34,840 --> 00:42:38,160 Speaker 1: reason for vaccine hesitancy, is the speed at which it 751 00:42:38,239 --> 00:42:41,319 Speaker 1: was approved and like there's no way they knew what 752 00:42:41,400 --> 00:42:44,239 Speaker 1: was going on. I read a lot about this over 753 00:42:44,640 --> 00:42:46,560 Speaker 1: not even for this, just like over the past year. 754 00:42:47,320 --> 00:42:50,680 Speaker 1: And how that process usually works is it's it's related 755 00:42:50,719 --> 00:42:53,560 Speaker 1: to funding. Like you're funded a certain amount of money 756 00:42:53,600 --> 00:42:57,080 Speaker 1: as a company to get approval for studies and stuff 757 00:42:57,120 --> 00:43:00,239 Speaker 1: like that, and you get funded that certain out and 758 00:43:00,280 --> 00:43:02,919 Speaker 1: you can only work within that amount of money. So 759 00:43:03,320 --> 00:43:05,440 Speaker 1: your study is and is only going to be of 760 00:43:05,480 --> 00:43:08,879 Speaker 1: a certain sample size and they're pretty big. And then 761 00:43:08,920 --> 00:43:10,760 Speaker 1: you also have to take a certain place in line. 762 00:43:11,360 --> 00:43:15,719 Speaker 1: With this vaccine, they had a sample size out of 763 00:43:15,760 --> 00:43:20,280 Speaker 1: the gate that was humongous because the entire world wasn't 764 00:43:20,360 --> 00:43:22,640 Speaker 1: getting infected with this stuff or not getting infected, but 765 00:43:23,040 --> 00:43:25,120 Speaker 1: you know, tons and tons of people were getting affected. 766 00:43:25,280 --> 00:43:28,040 Speaker 1: The entire world was on watch and on guard, and 767 00:43:28,080 --> 00:43:30,759 Speaker 1: so you had no problems with sample size, you had 768 00:43:30,880 --> 00:43:33,920 Speaker 1: no problem with funding, and you had no problem with 769 00:43:33,920 --> 00:43:36,120 Speaker 1: waiting in line, because they said, all right, you're immediately 770 00:43:36,160 --> 00:43:38,959 Speaker 1: at the front of the line, so it didn't get 771 00:43:39,360 --> 00:43:42,080 Speaker 1: approved because they just wanted to speed it through there 772 00:43:42,120 --> 00:43:44,440 Speaker 1: really quickly. It got approved because it jumped the line, 773 00:43:44,840 --> 00:43:46,960 Speaker 1: it had tons of money behind it, and it had 774 00:43:47,040 --> 00:43:51,400 Speaker 1: a ton of people in the getting you know, thankfully 775 00:43:51,600 --> 00:43:54,680 Speaker 1: volunteering to get jabbed early on for the tests, which 776 00:43:54,719 --> 00:43:59,160 Speaker 1: produced a ton of data that yeah, yeah, because they 777 00:43:59,160 --> 00:44:01,719 Speaker 1: have more participant as usual. That was everything I saw 778 00:44:01,800 --> 00:44:04,440 Speaker 1: as well too. It's so frustrating though, because they actually 779 00:44:04,480 --> 00:44:07,000 Speaker 1: got more data than they usually get. They just got 780 00:44:07,080 --> 00:44:11,279 Speaker 1: it a lot faster, and there's people still think that, 781 00:44:11,600 --> 00:44:14,080 Speaker 1: you know, there's just not enough information. It is because 782 00:44:14,080 --> 00:44:16,920 Speaker 1: because it didn't take as long. Yeah, because it is 783 00:44:17,000 --> 00:44:19,360 Speaker 1: very frustrating because people are like, I'm wary of that 784 00:44:19,400 --> 00:44:21,520 Speaker 1: because it was so fast, and it was so fast 785 00:44:21,600 --> 00:44:25,640 Speaker 1: because it was, uh, one of the biggest advances in 786 00:44:25,680 --> 00:44:28,759 Speaker 1: the history of medicine that's happening before very eyes. But 787 00:44:28,920 --> 00:44:30,920 Speaker 1: rather than just being like, oh my god, what an 788 00:44:30,920 --> 00:44:34,560 Speaker 1: amazing time to be alive, what an amazing accomplishment humanity did, 789 00:44:35,600 --> 00:44:37,719 Speaker 1: a significant portion of people are like, oh no, I 790 00:44:37,719 --> 00:44:39,800 Speaker 1: don't trust that they're trying to kill me. Your catalog 791 00:44:39,880 --> 00:44:42,400 Speaker 1: me or Bill Gates wants to keep tabs on on 792 00:44:42,560 --> 00:44:46,759 Speaker 1: me because Bill Gates cares what I'm doing. Yeah, we've 793 00:44:46,800 --> 00:44:48,799 Speaker 1: met Bill Gates, you guys a couple of times. He 794 00:44:48,840 --> 00:44:51,319 Speaker 1: doesn't care what you're doing. It's I hate to break 795 00:44:51,320 --> 00:44:54,640 Speaker 1: it to you, he does not care what you're doing. Uh. 796 00:44:54,680 --> 00:44:58,839 Speaker 1: And you know we mentioned before that we uh it's 797 00:44:58,840 --> 00:45:01,719 Speaker 1: almost like we were waiting of this, like we had 798 00:45:01,800 --> 00:45:05,480 Speaker 1: uh the m RNA vaccine sort of technology figured out 799 00:45:05,840 --> 00:45:09,120 Speaker 1: to a certain degree, and we were just waiting for 800 00:45:09,320 --> 00:45:12,560 Speaker 1: the Chinese government and the researchers to release that genetic code. 801 00:45:13,000 --> 00:45:15,200 Speaker 1: And once they did, they were like, all right, here 802 00:45:15,239 --> 00:45:19,080 Speaker 1: it is. It's open source in January twenty and everyone's like, great, 803 00:45:19,200 --> 00:45:21,600 Speaker 1: that's all we needed and we are ready to rock 804 00:45:21,640 --> 00:45:23,960 Speaker 1: and roll. And I think you did you say? It 805 00:45:24,000 --> 00:45:26,839 Speaker 1: was twenty five days later that they produced their first 806 00:45:26,840 --> 00:45:30,480 Speaker 1: successful batch, and then thirty nine days after that the 807 00:45:30,520 --> 00:45:33,960 Speaker 1: first phase of human trials were underway, which I mean, 808 00:45:34,000 --> 00:45:36,600 Speaker 1: that's just so fast. But to kind of go back 809 00:45:36,640 --> 00:45:38,440 Speaker 1: to that point to chuck, because I think a lot 810 00:45:38,520 --> 00:45:40,600 Speaker 1: of people are also suspicious about that, like, why were 811 00:45:40,600 --> 00:45:44,200 Speaker 1: they just waiting for this pandemic? It's pretty suspicious that 812 00:45:44,520 --> 00:45:47,480 Speaker 1: there were people who well at bio in Tech and 813 00:45:47,680 --> 00:45:51,319 Speaker 1: Maderna who already had like these templates ready. They were 814 00:45:51,320 --> 00:45:54,680 Speaker 1: working on mRNA vaccines and for a number of different fields. 815 00:45:54,880 --> 00:45:57,480 Speaker 1: And then there were other groups who were specifically working 816 00:45:57,480 --> 00:46:01,080 Speaker 1: on coronavirus vaccines because we've dealt with coronavirus is before 817 00:46:01,400 --> 00:46:05,399 Speaker 1: Mers Middle East Respiratory syndrome STARS, the original Stars, those 818 00:46:05,440 --> 00:46:08,960 Speaker 1: are both coronaviruses. Both of them share their spike protein 819 00:46:09,280 --> 00:46:13,760 Speaker 1: with Stars cove to the virus that that causes COVID 820 00:46:14,360 --> 00:46:17,120 Speaker 1: that's a coronavirus as well. They all have the spike protein, 821 00:46:17,320 --> 00:46:20,160 Speaker 1: so they had spike protein templates. So, like you said, 822 00:46:20,280 --> 00:46:23,719 Speaker 1: when Chinese researchers posted the genome of the Stars Cove 823 00:46:23,880 --> 00:46:27,080 Speaker 1: two virus, people were like, cool, let's take that, plug 824 00:46:27,120 --> 00:46:29,560 Speaker 1: it in and see what happens. And it worked. That's 825 00:46:29,600 --> 00:46:32,520 Speaker 1: why it was so fast. That can't say plug in 826 00:46:32,560 --> 00:46:36,560 Speaker 1: play enough. Yeah, I mean that's literally the situation because 827 00:46:36,840 --> 00:46:39,439 Speaker 1: in the future they might be able to solve things 828 00:46:39,480 --> 00:46:43,800 Speaker 1: like HIV and raybes and maybe even certain kinds of cancer. 829 00:46:43,960 --> 00:46:46,719 Speaker 1: Like it's it's a technology that can be applied to 830 00:46:46,760 --> 00:46:48,960 Speaker 1: a bunch of things, and they were just ready to 831 00:46:49,000 --> 00:46:51,680 Speaker 1: go for for this, Yeah, the cancer one. It's it's 832 00:46:51,960 --> 00:46:55,200 Speaker 1: I mean, that's just amazing there. Yes, but they're getting 833 00:46:55,239 --> 00:46:58,080 Speaker 1: to the point where they can say, Okay, you've got cancer. 834 00:46:58,160 --> 00:47:00,320 Speaker 1: Come in, we're gonna take a sample of your tumor. 835 00:47:00,360 --> 00:47:02,239 Speaker 1: We're gonna study it, we're going to figure out what 836 00:47:02,280 --> 00:47:05,200 Speaker 1: it's genome is. We're going to create a tailor made 837 00:47:05,280 --> 00:47:08,840 Speaker 1: vaccine to train your body to fight that cancer, and 838 00:47:08,880 --> 00:47:11,800 Speaker 1: we're going to vaccinate you against your own personal cancer. 839 00:47:12,040 --> 00:47:15,440 Speaker 1: Were a few years away from being able to do 840 00:47:15,480 --> 00:47:18,320 Speaker 1: that kind of thing. And then when that happens, if it, 841 00:47:18,400 --> 00:47:20,359 Speaker 1: if it, if we can do it, we will have 842 00:47:20,440 --> 00:47:23,120 Speaker 1: beaten cancer. That's what that's the next thing that m 843 00:47:23,239 --> 00:47:27,360 Speaker 1: RNA vaccines are about to do. It's amazing. It's a 844 00:47:27,400 --> 00:47:29,680 Speaker 1: reason to applaud science. Uh I, now you have a 845 00:47:29,719 --> 00:47:32,120 Speaker 1: little bit more that I didn't fully understand, and thankfully 846 00:47:32,160 --> 00:47:37,200 Speaker 1: you're gonna tell people about it. Well. The other I mean, 847 00:47:37,200 --> 00:47:39,000 Speaker 1: one of the other things, if I'm not mistaken that 848 00:47:39,239 --> 00:47:41,840 Speaker 1: it seems like vaccine hesitant people are worried about, is 849 00:47:41,880 --> 00:47:44,759 Speaker 1: that mRNA vaccines are going to embed themselves in your 850 00:47:44,960 --> 00:47:48,000 Speaker 1: d n A and alter it. And that's actually the 851 00:47:48,000 --> 00:47:52,160 Speaker 1: opposite of what mRNA vaccines do because, like we said, um, 852 00:47:52,239 --> 00:47:54,640 Speaker 1: they come from outside of the cell and they do 853 00:47:54,680 --> 00:47:57,239 Speaker 1: their work in the cytoplasm. They don't go anywhere near 854 00:47:57,280 --> 00:47:59,600 Speaker 1: your nucleus or interact with your d n A. They 855 00:47:59,600 --> 00:48:02,000 Speaker 1: don't need to. They've already got what they would have 856 00:48:02,040 --> 00:48:05,040 Speaker 1: needed from the DNA. And that the mrn A sense 857 00:48:05,080 --> 00:48:08,480 Speaker 1: shows up with the blueprints ready to be translated into 858 00:48:08,480 --> 00:48:11,480 Speaker 1: the proteins, right like, they can't. They can't get into 859 00:48:11,520 --> 00:48:14,200 Speaker 1: the nucleus, right No, I mean, as far as anybody knows, 860 00:48:14,320 --> 00:48:18,000 Speaker 1: they can't or they don't, there's no reason for them to. Uh, 861 00:48:18,040 --> 00:48:20,879 Speaker 1: there's no reason they should. And then even if they did, 862 00:48:21,200 --> 00:48:24,880 Speaker 1: that doesn't mean that they would be transcribed into your DNA. 863 00:48:25,480 --> 00:48:29,919 Speaker 1: Right The actual wild stars Covie two virus doesn't even 864 00:48:29,920 --> 00:48:32,960 Speaker 1: do that. A lot of viruses actually go in take 865 00:48:33,040 --> 00:48:37,120 Speaker 1: their RNA, reverse transcribe it into your DNA, and then 866 00:48:37,160 --> 00:48:39,840 Speaker 1: get your DNA to produce more viruses. That's how a 867 00:48:39,880 --> 00:48:42,640 Speaker 1: lot of viruses infect you. But the stars Covi two 868 00:48:42,680 --> 00:48:45,000 Speaker 1: virus is not like that. It's called a positive sense 869 00:48:45,120 --> 00:48:48,040 Speaker 1: RNA virus where it shows up and in much the 870 00:48:48,120 --> 00:48:51,000 Speaker 1: same way that the vaccine shows up with ready to 871 00:48:51,080 --> 00:48:54,799 Speaker 1: go mr NA, the stars covie two virus shows up 872 00:48:54,800 --> 00:48:57,800 Speaker 1: and says, here's some RNA, just start making more of myself. 873 00:48:58,000 --> 00:49:00,360 Speaker 1: And it has nothing to do with the d n 874 00:49:00,480 --> 00:49:03,280 Speaker 1: A in the nucleus. It just works in the cytoplasm 875 00:49:03,320 --> 00:49:05,920 Speaker 1: as well. So there's no reason to think or believe. 876 00:49:05,920 --> 00:49:08,920 Speaker 1: And there's no evidence, um that the stars Kvie two 877 00:49:09,000 --> 00:49:12,920 Speaker 1: virus imbeds itself in your d n A. And I 878 00:49:12,960 --> 00:49:15,839 Speaker 1: hate to say this, but even if it did, at 879 00:49:15,920 --> 00:49:19,120 Speaker 1: least eight percent of your d n A human being 880 00:49:19,719 --> 00:49:22,719 Speaker 1: is made up of ancient viruses DNA that has been 881 00:49:22,760 --> 00:49:27,040 Speaker 1: injected into humanity over the eons, and as much as 882 00:49:27,239 --> 00:49:31,720 Speaker 1: forty eight percent of your DNA is actually old viral DNA. 883 00:49:32,120 --> 00:49:36,480 Speaker 1: That's just junk DNA now, So UM, it doesn't do that. 884 00:49:36,520 --> 00:49:39,120 Speaker 1: It doesn't insert itself into your d NA. Even if 885 00:49:39,120 --> 00:49:42,880 Speaker 1: it does, basically you would be good at making ears 886 00:49:43,280 --> 00:49:48,120 Speaker 1: of coronavirus is for a while. Right. That's it. I 887 00:49:48,200 --> 00:49:51,320 Speaker 1: love it. So there you go. That's m RNA vaccines. 888 00:49:52,719 --> 00:49:55,160 Speaker 1: Nice work. Nice work to you too, man, Thank you 889 00:49:55,200 --> 00:49:57,919 Speaker 1: for doing this one. This is a great one, of course. Uh. 890 00:49:57,960 --> 00:50:00,040 Speaker 1: And if you want to know more about mr in 891 00:50:00,160 --> 00:50:03,200 Speaker 1: A vaccines, then just start researching. There's plenty of stuff 892 00:50:03,239 --> 00:50:06,200 Speaker 1: out there to explain this even further. And since I 893 00:50:06,239 --> 00:50:08,640 Speaker 1: said just start researching, that means, of course it's time 894 00:50:08,640 --> 00:50:13,640 Speaker 1: for listener mail. Uh. This is a quick one. I'm 895 00:50:13,640 --> 00:50:16,600 Speaker 1: gonna call this about the Church of the SubGenius is 896 00:50:16,600 --> 00:50:19,080 Speaker 1: a follow up. Good morning, fellas. I've been listening to 897 00:50:19,080 --> 00:50:21,400 Speaker 1: your podcast for several years. Some of my favorites include 898 00:50:21,600 --> 00:50:25,600 Speaker 1: how Soap Works and how sloths Work. I'm listening to 899 00:50:25,640 --> 00:50:28,759 Speaker 1: the Tale of the Church of the SubGenius episode as 900 00:50:28,800 --> 00:50:31,400 Speaker 1: I type, and I often google the topic you're enlightening 901 00:50:31,440 --> 00:50:34,719 Speaker 1: us with, and when I searched for Bob Dobbs. A 902 00:50:34,800 --> 00:50:39,840 Speaker 1: recent Twitter post from Bob Dobbs said this Earthlings of Earth, 903 00:50:40,360 --> 00:50:43,560 Speaker 1: you will be punished for the nineteen seventies. That is all. 904 00:50:46,600 --> 00:50:52,600 Speaker 1: Hashtag SubGenius, hashtag stark fists, hashtag Tuesday motivations. Uh. And 905 00:50:52,680 --> 00:50:56,400 Speaker 1: Chris from Arlington, Texas has hysterical. I love your podcast. 906 00:50:56,440 --> 00:50:59,280 Speaker 1: My wife and I have great conversations about your episodes 907 00:50:59,320 --> 00:51:03,839 Speaker 1: all the time. Uh. And again that is Chris from Arlington, Texas. 908 00:51:03,920 --> 00:51:06,319 Speaker 1: Very nice. Thanks a lot, Chris. That was a nice 909 00:51:06,320 --> 00:51:10,240 Speaker 1: little pick me up, and we love the nineteen seventies, 910 00:51:10,280 --> 00:51:13,920 Speaker 1: So screw you, sub genius. Agreed, Chuck, I'm glad somebody 911 00:51:14,000 --> 00:51:16,600 Speaker 1: said it. Well, if you want to give us a 912 00:51:16,640 --> 00:51:20,520 Speaker 1: pick me up like Chris, Chris right, Chris, like Chris did, 913 00:51:20,560 --> 00:51:23,600 Speaker 1: then you can send us an email to Stuff Podcast 914 00:51:23,880 --> 00:51:29,799 Speaker 1: at i heeart radio dot com. Stuff you Should Know 915 00:51:29,880 --> 00:51:32,680 Speaker 1: is a production of I Heart Radio. For more podcasts 916 00:51:32,760 --> 00:51:36,160 Speaker 1: my heart Radio, visit the i heart Radio app, Apple Podcasts, 917 00:51:36,239 --> 00:51:38,120 Speaker 1: or wherever you listen to your favorite shows.