Stream.Transcripts/twitch/1985683350 (2023-11-23) - Thanks Pieter but LNPs are not Magic --(23 Nov 2023)-- Gigaohm Biological High Resistance Low Noise Information Brief/1985683350 (2023-11-23) - Thanks Pieter but LNPs are not Magic --(23 Nov 2023)-- Gigaohm Biological High Resistance Low Noise Information Brief.vtt

WEBVTT

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testing one two I said 10 22 10 29 I don't think that worked out quite how I

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wanted to but we're gonna manage to make it work you can find me at giggle

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and biological.com you can also go to the soapbox link that you can find there

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which is also at giggle ohm.bio happy thanks giving everybody happy thanks

00:34.180 --> 00:40.920
giving Pamela Watcherby tense oral strain there's a click there that you can do

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to watch the show you can also download the stream deck starting next week we're

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gonna have the stream deck up I hope every time I do a stream at least every

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week stream and that means that you can start subscribing again if you'd like

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to get something like an email and a PDF of the show beforehand it might only

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be for Fridays or Wednesdays or whatever day we're gonna make it but

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someday at some point we're gonna start that PDF stuff again because these

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slides have started to become good enough that I think they're shareable

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and useful for people to start to really push these ideas out they haven't been

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there in a long time and so I think it's really nice for this to happen

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it is a little lonely in this crazy brainwashed world I'll tell you what it's

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very lonely my wife feels very lonely

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it's yeah it's tough thanks for coming tonight guys I didn't tweet it I didn't

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share it I didn't do anything I didn't have time it's Thanksgiving I just wanted

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to get a stream out there and keep the streak alive and keep the keep the

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sea warm keep the rig warm

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I yelled at the basketball team the other night my throat is still a little sore

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you schedule for 60 minutes next is going on French British Italian Japanese

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television people everywhere are starting to listen to him it's embarrassing yeah

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I'm gonna have to start with some more I'm gonna have to start with some more

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inspirational some more inspirational stuff in the beginning again I used to

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put a lot of work a lot more work into that beginning section of video so I

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just didn't think anybody was watching them but that one was a really good one

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keep in your arms straight

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so you know the drill you can look me up on PubMed and the name of the channel

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is derived from the resistance of the recordings that I used to make giga home

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resistance high-resistance low-noise information brief let's get this thing

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started

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I feel like my computer slowed down there for a minute hopefully you guys

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didn't lose anything yes happy Thanksgiving everybody good to see

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everyone here it's like we lost a few viewers see I told you I told you something

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poopy's going on they don't like it our information and our message is

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getting too sharp they don't like it at all

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yes yes truth bombs at dinner that's an understatement I bet at some of these

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places that we've been today thank you very much for joining me this is

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giga home biological a high-resistance low-noise information brief brought to

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you by a biologist if there's anything wrong with the timing or anything like

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that give me a shout out we are still here fighting against the same sort of

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nonsense you know the illusion of consensus the Scooby-Doo created by these

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people on social media I'm starting to really see what happened I know that

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there was this TV stuff and this stuff in Congress and whatever but I'm starting

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to understand how these people are all linked and it has a lot to do with these

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new social media and new communication platforms that came online during the

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pandemic and there's more than one there's actually about five or six and we can

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start to look back at when that was all happening when we were all scrambling

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during this during this censorship time in 2020 oh my goodness I can see it

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also clearly now I'm really excited as we break through some of this stuff on the

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18th and 19th of November in Bucharest Romania there was a COVID conference and

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some of our friends were at this COVID conference I'm gonna go over here

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pull myself down here and see if we can use my mouse to he has so just the

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prominent ones for now I'll pop my head down for a second Robert Malone was

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there Nick Hudson was there Brett Weinstein was there you can see this

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arrow right yeah and Denny Rancor was there among others which is kind of cool

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because as you know there is this there is this you know consensus that we're

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trying to battle against something and all of us are trying to work together

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towards some amorphous goal like health freedom or something like that and there

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is this faith in a novel virus this faith that millions of people were

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killed by it this faith that millions more were saved from it this faith that

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gain a function is real and possibly the source of it and therefore a virus will

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come again and this story is basically not been questioned by most of the

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people that we have been trying to look to for leadership in this in this fight

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to return to you know pre-2019 Western civilization which clearly we're never

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going to do the build back better the new normal this was all for real to make

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sure that we never thought we could have that back again and so in some ways it

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would be it should be somewhat curious if we can't find any leader on this

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playing board that doesn't want to say just simply well why don't we just go

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back to the way we were doing it about four years ago and start there and then

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we can repeat we can we can fix that but first of all we got to go back to that

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and everybody that through that out needs to be held to account

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everybody that just went against all those rules whence against all those

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norms went against all those expectations those people need to be held to

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account but that doesn't seem there doesn't seem to be anyone who's

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interested in that particular path and in fact yesterday I wanted to point that

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out and so that was one of the reasons why we went through that that video from

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Stockholm earlier this year so some more people were there that that definitely

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as far as I know aren't questioning the narrative that I really like Byron

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Bridal a lot and he's a great guy but he is not questioning there being a

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novel virus that spread around that's spreading still Jessica Rose hasn't

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questioned that even though she has done a selfie with Denny Rancor she has an

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acknowledge that that one of the main findings of Denny's data is that there's

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no evidence of spread of a novel deadly pathogen Harvey Reich is also another

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guy who I've talked to before and not on my show live but on a stream with with

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oh I'm not gonna remember her name and shoot that's really annoying Kathy

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something I believe I apologize for that if you're watching but it's a one of

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these private zoom calls so Harvey Reich is another guy who's not questioning

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the narrative there's Ryan Cole I'm not sure how much he's questioning the

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spread of a novel virus but I don't think that he's really there yet he's

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certainly not there yet with regard to promoting Denny Rancor's data and what

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Denny Rancor's data tends to you know it seems to show here's Jill Glasspool

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Malone and Meryl Nast you know that those two are also probably not pushing

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that narrative and then again what Brett Weinstein Nick and Robert and Denny

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Rancor so even if Denny Rancor is there and he presents to all these people and

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Robert Malone tweets it out he tweets out that 17 million people were killed

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by the vaccine and that he's never seen such shocking accounting of the 17

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million people around the world estimated to be killed by the vaccine but he's

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not at all shocked by the conclusion that there's no evidence of spread that

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the spread respected even borders of counties in the United States it has

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correlated much much better to to poverty and mental illness and income than it

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is to to like proximity of the previous cases or proximity of of of large

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incidences or events of all cause mortality I'm getting really good at

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not saying um when I'm doing these things but it's sometimes I have to pause

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for a second there um anyway and then I said okay this is all because these

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people have participated in this in this illusion of consensus and I don't know

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to what extent they were aware of this illusion before the start of the

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pandemic but most of them have to be aware of the illusion now because most of

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them have heard my my discussion of it our discussion of it over these

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this past year or so and most of them know what our contention is and they

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don't have a real meaningful argument because the only people that have

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tried to meaningfully argue with me are now blocking me on Twitter and no

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longer discussing it all and that's because again it really feels very very

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positive that that these these people are all involved in

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making sure that the worst case scenario of a pandemic caused by a gain of

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function virus is never out of your possibility space even if you don't

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believe that's what happened this time they need you to believe that that's

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what gonna happen next time or could happen next time or or eventually will

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happen they need you to believe that maybe in the

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same way that they needed us when we were children to really believe that

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the Russians had nine thousand warheads and we had six thousand warheads

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and they were on a on a hair trigger well two hair keys

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so i i don't you know i i have a hard time understanding

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anymore what history really is given the fact of all of things that i've

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learned over the last three years about how willing and able

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this apparatus is to govern us with lies in mythology

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and so i think that this illusion of consensus really needs to be inspected

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for this mythology and i suspect that we're going to find that it mostly is

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and that's why i think you need to think of this as a card game

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a card game with a rig deck a card game with a rig deck that a dealer is trying

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to steal your money so when you get the cards in order for you to have any

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meaningful chance of gambling with success

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you have to play knowing that the dealer is trying to get you

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to make a mistake so what would that mistake be

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how would they how would they communicate to those

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inside the game versus those outside the game

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what kinds of clues would there be that there's a game being played

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i think one of the clues that that Matt Crawford

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of rounding the earth pointed out about two years ago was this

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possibility that this covid is actually ovid

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ovid being this famous greek set of stories

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about various metamorphosis a lot of them are kind of like punishments or

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or or gods being vindictive but the point

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only being uh in this thing that this is a time of

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transformation and some of the the themes

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of ovid's metamorphosis in relation to the the fall of rome

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and the theme of let's say order being imposed on a world

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founded on chaos or based from or or growing from chaos

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an order is imposed on that and so in this story

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in this idea of covid it could be that in order to transform us into a new

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global government in order to transform us into a new global

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governance structure based on on digital currencies and digital

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IDs and no more national borders that mean anything

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they need to have a chaos they need to start from a chaos they can't

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have all of this order and then rearrange it

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or hope to usefully disassemble it at least that's what they think

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that's what they they think that's how how maybe that is how people have been

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governed through chaos and then imposed order

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and if that's the case then it does seem as though the people that are

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governing the globe that want to shift us to this new paradigm

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understand it as a necessity for us to go through some kind of chaos

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in order for this societal metamorphosis to take place

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and so i'm starting to make this argument that there's a fine line between an

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announcement and a warning and i want you to start to

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think about what people say on our side about where we're going and how we

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avoid going there and whether or not it's an

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announcement or a warning whether it's an announcement or a

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suggestion whether it's an alternative or

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an inevitability because i think it's very important it doesn't only have to be

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a guy like carol adebach the health guy from germany

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or jorston talking about these kinds of things and then for us to know that

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oh this is not really a warning or a complaint this is an announcement

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when when jorston says that we really need to crack down on misinformation

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and the press needs to do their job we understand that fully

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that they mean to crack down on misinformation they want us to beg for

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that but then when we hear robert melone say that he's been

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harassed on on the internet and it's not fun and you wouldn't like it and we've

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got to stop using violent speech or they're going to use it against us

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is that an warning or an announcement if somebody says we need to build new

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underground systems but doesn't ever advocate for us to take back the system

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that we have and and remodel it retake it back and use it

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the way it's supposed to be restore our republic no he says we need to build new

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underground systems it's not very different than what

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happened when we got censored back in 2020 and everybody ran to gab

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and to telegram

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and everybody went on signal and had all these secret groups where they chatted

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about i don't know

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well everything and everybody went to discord

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and how hard was it for these non-encrypted apps to

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actually be like honey traps for us in a way all the people that

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wanted to march around and be efficient you know or not efficient but uh

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evasive of the of the system they went away

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they went on gab they went on telegram i'm on signal now

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curiously who led us to gab who led us to telegram who led us to signal

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who led us to discord who led us to sub-stack

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if you hear somebody up on stage say we have a lousy society our children have

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been taught all the wrong values it's going to be okay that it all comes

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apart is that really a announcement

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a warning

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is that inevitability

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is that somebody trying to help us or is that somebody just trying to keep us

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walking down or riding numbly down this neon hallway

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covered in lies is that somebody who's pretending to be a part of the

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group of mimes stopping this drain it's a really important analogy

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try to imagine fooling a young group a group of young kids

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and try to see that this guy all by himself with his little chalk dish

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he can't fool a group of kids but if you got a bunch of crossfit athletes

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and then you fitted them with a bunch of uh

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machines that made a lot of noise with wheels and sparks

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i guarantee you you could fool a bunch of kids you might even be able to fool

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a bunch of teenagers and the more people that you lined up on the train with more

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elaborate props and a more elaborate coordinated effort

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the more people you could fool the more inspection

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they would pass the more the more scrutiny they could withstand

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in their act

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if you made it really complicated

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if you made it with smoke and heat so that people couldn't get very close to the

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train as these people stopped it

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if you made it really loud so that people were afraid to get near it

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the point that i'm trying to make is is that during the pandemic that's what

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all of these stories did to us

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they made it seem like there was nothing to guess or or wonder about

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these people were doing the best that they could to stop a national security

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priority a national security threat of never-before-seen proportions

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and potential the potential to kill a billion people and we don't have any

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treatment we don't know what will work

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the best we can do is hope that these people can put out enough pcr's and

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lateral flow tests so that we can at least keep track of when we're sick asymptomatically

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and so many people on social media seem to agree about this

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so many people on social media are arguing whether or not hydroxychloroquine or

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ivermectin are crazy or not

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and ivermectin and hydroxychloroquine did not save anyone from a ventilator did

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not save anyone from rendezivir did not save

22:26.380 --> 22:29.900
anyone from an opioid death

22:32.220 --> 22:36.540
financial incentives to declare covid didn't save anyone from the covid

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protocols it actually put more people on them

22:43.100 --> 22:47.660
sending people back with to elderly care homes with pneumonia

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and viral pneumonia without antibiotics didn't save anyone

22:53.500 --> 22:59.340
the dismissal of immunology 101 in october of 2020

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by a whole list of leaders including wollinski

23:03.820 --> 23:09.420
as in we don't know if our immunity will be good enough it could be like aids

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where we build antibodies and that's actually a sign of disease not a sign of

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immunity did you know that do you remember that

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giant contradiction thanks for reminding me of that pamela or

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pointing it out even the value of nutrition in

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america was dismissed a place where almost every grown

23:33.660 --> 23:37.900
adult has been malnourished for at least a decade

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and many children grow up malnourished over

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carbon carbohydrate over sugared over medicated over immunized

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they have been doing this train pulling and pushing act for three years

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and public health the public health apparatus would like to govern the

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world with this act

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public health apparatus needed to convert this pattern

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into something that they could declare was a pandemic of a novel virus

24:27.100 --> 24:30.460
and in order to convert this very distinct

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and reliable pattern this very distinct reliable pattern

24:35.740 --> 24:40.300
in pneumonia deaths into this very indistinct

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and novel pattern of pneumonia deaths it required protocols not a novel

24:45.340 --> 24:47.740
virus

24:48.540 --> 24:52.780
it required novel protocols like do not resuscitate people if they're having a

24:52.780 --> 24:56.140
heart attack at home or a stroke let them die

24:56.140 --> 25:00.620
don't bring them back to the hospital pronounce them dead

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if you do bring them into the hospital make sure you ventilate in my extra

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high pressure to make sure that the virus doesn't come out

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antibiotics don't work on viral pneumonia dumbass

25:12.780 --> 25:16.700
and steroids don't either

25:17.900 --> 25:23.180
remdesivir works though it's pretty good we should try it on everybody

25:23.740 --> 25:28.700
and opioid deaths well those people are just covid deaths

25:28.700 --> 25:33.340
we don't even need to talk about them i mean who who even cares about those

25:33.340 --> 25:37.420
people isn't it a waste to even use Narcan on them like

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they're just i wonder what people in san francisco would say

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death certificate fraud how far should this list go how much longer how much

25:48.380 --> 25:51.980
many more things can we think about they need to go on there

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the reason why i want this to happen is because i need you to see

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because i need you to see what because i need you to see

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what that was an echo there because i had that open

26:01.980 --> 26:05.740
yikes that was scary i need you to see that these people

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have really fooled us now this video is a video from one month ago

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by a professor

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of carny g melon and today i'll be talking mostly

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let me get my head out of the way for a second so i can rewind this

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and make sure it's all set up correctly

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1.5 so this is a video of

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a professor from carny g melon university so that's that's in pittsburgh

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and she gave this talk one month ago as part of a

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honoring peter colas series of lectures so it's about our ln

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lnp for r and a delivery which i thought already got the nobel prize

26:56.140 --> 27:03.980
which is usually when something has had you know like a decade of impact

27:03.980 --> 27:07.900
and so she's going to give a lecture about this but i want you to listen

27:07.900 --> 27:10.940
very carefully to the assumptions that she makes

27:10.940 --> 27:17.340
and the assumptions are are monumental

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she's going to say what we said at giga ohm biological they were going to do

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we said that in 2021 when everybody was all hot and bothered about the

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spiky spike being toxic

27:35.820 --> 27:41.260
we said it that they were going to blame the vaccine

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and it not working right because they chose the wrong protein or they're

27:44.620 --> 27:47.340
going to make some other excuse and otherwise

27:47.340 --> 27:52.300
otherwise we just proved that r and a and

27:52.300 --> 27:56.140
transfection in general works great in humans

27:56.140 --> 28:00.460
now this is a woman who just gave a talk a month ago and basically

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she's going to lead off with that in an extraordinarily aggressive way

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r and a's here to stay

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so today i wanted to speak with you about some of the work that we've been

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doing developing lipid nanoparticles for targets outside of the liver

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and i specifically wanted to focus on some of our data regarding delivery to

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the pancreas i'm not really sure i just want to

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talk to Moderna for a second modified r and a is not biological messenger r and a

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i'm not really sure why you're making that point because

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we understand that that coat we we recognize that codon optimization

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has certain implications and effects we've recognized that the chemical

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alterations have certain effects and we're calling it r and a

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are calling it transfections so you keep saying that but

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i've we've all acknowledged that this is modified r and a

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if we call it m r and a or r and a it doesn't really matter it's synthetic

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r and a so i mean you're you're making a semantic argument that doesn't

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it doesn't really matter if you listen to her talk and you assume that this is

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all synthetics then then it's really about what they

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can and can't do with them that is the point

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they can't control where they go and when they say that they inject you in the

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muscle to augment your immune system it's just

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absolutely absurd and that's that's what she's going to talk about here with

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cartoons so just a little bit about my lab in

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general and dr khalis had mentioned this in the introduction

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we work in a couple of different areas of drug delivery

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so we focus on oral delivery of protein medication so drugs like insulin that

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currently have to be injected and trying to find ways of delivering them

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in more patient-friendly forms so that might involve oral delivery for

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proteins the problem with proteins is that they're

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digested by our gastrointestinal tracts and so we're very interested in

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studying the transport of these large molecules across the

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gastrointestinal tract to facilitate these more patient-friendly means of

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delivering proteins. More recently my lab has taken interest in

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women's and infant health. I had my first pregnancy at this point about seven

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years ago and then another one shortly before the

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pandemic happened and there's nothing like firsthand

30:17.100 --> 30:21.100
experience to realize that the state of maternal medicine is rather poor

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and there are a lot of things that we can do to try to improve our

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understanding of transport processes during pregnancy

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to try to create medications that are safe that do not cross into the infant.

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And then finally the subject of today's lecture is in this area of RNA delivery

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where I've been working now on lipid nanoparticles for over 15 years

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and it's just been wonderful to see how far this field has come since I first

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started. My lab is especially interested in how manipulating the chemistry

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of these particles which are quite complex chemically.

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How those manipulations can affect their functionality in vivo

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both in terms of bio distribution where they're working well immunogenicity

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and toxicity. So I'll speak a bit more about that today.

30:57.580 --> 31:01.100
So as pretty much all of you probably know at this point these RNA therapies

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have gone from niche to mainstream so the first FDA approval of a lipid

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nanoparticle formulation and the first FDA approval of an RNA drug

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was back in 2018 by Al nylon and they developed this medication for a rare

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type of liver disease and this was wonderful and it brought to

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fruition decades of research on liposomal and lipid nanoparticle type

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materials but even then we still had a very small

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population of people who were benefiting from this type of technology

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and people were quite cautious about you know using these types of

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medications for larger patient populations. So then we had this awful

31:34.620 --> 31:37.740
occasion to need to put these materials to the test

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and I think all of us in the delivery field were absolutely delighted to see

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how well these materials and how well RNA therapies can work

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in you know huge. Was there ever a

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humanity or is this a stupid picture like what did they ever have this

31:51.500 --> 31:55.980
actually available or it was always the it was always Pfizer right

31:55.980 --> 32:01.340
it never came out with that I think this is BS right here

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anyway this is the statement that I'm trying to make

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this is you guys can all see it for what it is this is absolutely absurd

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the idea is very clear this was always the plan

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there was always going to be the plan it was always going to be

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throw the adenavirus under the bus so that we can point to the adenavirus

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as well obviously we took it off the market because

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it was causing clots and the mRNA doesn't cause clots.

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I mean duh the mRNA causes myocarditis but that goes away

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myocarditis is fine it only kills 50% of the people that

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they get it. It's it's really sad it's really sad

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because we said this we said it was going to happen two years ago we said

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they were going to do this and not one single person

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in that narrative control panel ever even bothered to think out loud that

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thought never mind actually speak the words or write a

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sub stack about it nobody and for two or three years

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almost three years really now that where we are

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it's almost three years oh my gosh it's going to be 2024

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we have been saying that they are going to blame

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some mistake in the methodology some mistake in the choice of protein some

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epitope they should have taken out

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and then they moved on to impurities then they moved on to

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process one versus process two and double stranded DNA and this sv40

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enhancer and promoter it's always been the same story

33:55.500 --> 34:00.620
these things work great but there were some problems with the rollout yeah sure

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but it was a rush job when we make these things like

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fine brewed beer this stuff is amaze balls

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that's the story that's the sales pitch that's the tv narrative that's what

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skilled tv watchers believe right now that's where we are at

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Thanksgiving 2023 just where i said we would be

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i'm not thankful for that

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which numbers of people and so now with this evidence and hundreds of millions of

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people at this technology works well this is really going to open the floodgates

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to all sorts of new therapies not just in vaccines but in protein replacement

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gene editing and otherwise so think about how naive that is think about

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how naive that is that she thinks that those two are equivalent because we

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used it for vaccination successfully even if even if

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even if

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replacing proteins hasn't worked

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curing cancer rarely works with mRNA

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putting these things in certain places doesn't work

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when you change their chemistry and they go places it's a fraction of it right

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these people would be very excited if they changed the lipid

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the lipid nanoparticle chemical composition and you went from 50 percent of it in the

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liver and 50 percent of it in the ovaries to 80 percent of it in the liver and 30 percent

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in the ovaries that would be a phd project that would be a very significant result

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that would allow them to stand in front of years of lecture halls

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saying that these results suggest that in a few years we can have really precisely targeting

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lipid nanoparticles based on the chemical alterations of and the properties that

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that emerge from those alterations blah blah blah blah blah blah

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and so let's listen to this lady explain what she plans to do and explain the

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sort of hand waving that she does look at this terrible cartoon already

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a protein is just a ball that comes from a comb

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I mean so for any trainees in the audience who are a little bit less familiar with this

36:36.940 --> 36:40.060
I wanted to just go through some of the basic molecular biology that

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underpins all this RNA work that we're doing so this is the central dogma of molecular biology

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that tells us that our permanent blueprint the DNA inside of ourselves this is transcribed

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into a temporary copy called messenger RNA which is then translated in the cell cytoplasm

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into proteins and so those arrows don't mean anything understanding the DNA polymerase

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doesn't mean anything like how it's copied understanding the RNA polymerase

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don't worry about that that's just an arrow understanding ribosomes

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mRNA protein that's just an arrow who cares about those things

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and now she's going to say that proteins are everything proteins are the motor as well

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ribosomes are RNA ribosomes are made of RNA and proteins in combination so it's a little

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hand wavy to say that proteins do everything when the most important thing the most important

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nanomachine that we almost know nothing about is the ribosome

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but that's okay you know just just keep us asking the wrong questions keep us focused

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on the wrong things instead of the arrows we'll focus on those funny shapes in blue

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genes are the doers in our body and because they're the molecules responsible for all function

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many diseases are caused by misregulated proteins so either the protein is non-functional

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either we have too much of a particular protein or too little and so to treat so a protein is

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non-functional we have too much we have too little it has nothing to do with the tertiary

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structure of the protein or the tertiary chemical alterations of it that's extraordinary and again

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you could say that this is being imprecise but she's talking to a really educated audience you

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would think that you'd want to hit this pretty pretty on the money you think you'd want to be

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with be pretty sharp with your biology but we're not we're not sharp right now this is one month

38:39.020 --> 38:44.620
ago ladies and gentlemen please we really need to manipulate protein expression such that it goes

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back to what it's supposed to be so that first FDA approved drug it contained short interfering

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RNA and it's short because it's about 21 base pairs in length as opposed to RNA mRNA which can

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be thousands long and it interferes with protein production so you can design this so it would

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be specific for a target gene of interest and then you can have reductions in that protein expression

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now i'm a little gonna object to the way that this is drawn because it looks like to me

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her si RNA is drawn as double-stranded but actually i think correct me if i'm wrong smart people in

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the audience but i think RNA is single-stranded and when you put small interfering RNAs in there

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they bind to the endogenous RNA and make a double-stranded RNA and that's why they get degraded

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because double-stranded RNA ain't allowed in our cells

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you see again it's just kind of imprecision you know like

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it's just kind of imprecise and it's annoying because these people get paid a crap ton of tax payer

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money to teach children to apprentice young biologists into this

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into this endeavor

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if we want to upregulate protein expression instead of downregulate that's where messenger RNA comes

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in and so we can design mRNA's that can for example give us more of a particular gene of or protein

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of interest and in the case of the vaccines it's just super cool we can ask our bodies to

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generate proteins that our bodies would never normally make so in this case it's generating

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the spike protein which is not native to mammalian cells so very powerful technology

40:36.780 --> 40:42.300
i wanted to speak very briefly on our news this week that the noble prize was given for the mRNA

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biology that underpinned the covid-19 vaccines so RNA therapeutics really require two parts

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so one is functional mRNA that once it goes inside the cell it can produce the protein of interest

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effectively and then the other is the delivery system which i think hasn't gotten quite as

40:57.260 --> 41:01.900
much press as the RNA itself but is equally important so today i'll be talking about the delivery

41:01.900 --> 41:07.500
system and the noble prize had to do with this mRNA biology so here are the two people who have

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just been awarded so koriko and weissmann who originally did the work at the university of

41:12.060 --> 41:16.940
pennsylvania in philadelphia so they um i like to just tell people they're both really terrific

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people i think they could be on a sitcom together or something the two videos that we watched of them

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i mean they were lovable people i mean definitely but in a you're not a nobel prize-winning kind

41:32.700 --> 41:37.980
of lovable way i think i think we don't always have um you know sometimes famous scientists aren't

41:37.980 --> 41:43.420
the best models of of collaboration it's been my privilege to collaborate with drew over the years

41:43.500 --> 41:48.700
when i was getting started in the mRNA field it was back in 2017 and RNA is quite expensive

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if you purchase it and i was giving a seminar at pen and drew was a stranger to me and we had a

41:53.500 --> 41:59.500
meeting and he offered to make me whatever mRNA i wanted and send it to me and people didn't believe

41:59.500 --> 42:03.100
too much in RNA therapies at that time there was still a lot of hesitation so i was taken aback

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and confused why a stranger would offer to help me in this way given the expense so it took me a

42:07.020 --> 42:10.940
couple of years to actually approach him and then when i did he was true to his work and he's provided

42:10.940 --> 42:15.980
me with with RNA since that time and has otherwise been a great collaborator i've also met

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katie koriko briefly and she's given me some nice advice so just such a pleasure to see good

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people um reward it for for their work so um in terms of what they did they discovered that

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base modifications of RNA are needed for protein translation and mammals so here is the molecule

42:31.980 --> 42:38.140
uridine which is one of those canonical nucleic acids that are present in RNA and the problem

42:38.140 --> 42:43.180
when we make RNA typically with these molecules such as uridine is that our cells recognize them

42:43.180 --> 42:49.500
as foreign and that's because our cells make RNA to incorporate some base modifications so if it

42:49.500 --> 42:54.220
sees RNA without base modifications it mounts a bit of an immune response that shuts down protein

42:54.220 --> 42:58.860
production so that's part of why nobody thought RNA therapies would become a reality because

42:58.860 --> 43:03.580
when we made RNA in lab and introduced it it just would not make protein so what they found was that

43:03.580 --> 43:09.740
they could make modifications to these different nucleobases and so here's um one version of this

43:09.740 --> 43:14.140
this is um n1 methyl pseudo uridine the ones that are used in the vaccines are just called

43:14.140 --> 43:19.420
pseudo uridine so i don't think this is i'm sorry i had to i had to put something in my ear and

43:19.420 --> 43:24.460
clean it from my i'm wearing my headphones again tonight i don't think this is right and i hope i

43:24.460 --> 43:32.060
don't so i don't care if i do it's it's thanksgiving and i'm streaming i i think that this is absolute

43:32.140 --> 43:38.380
nonsense i don't think that base modifications are necessary for protein translation in mammals i

43:38.380 --> 43:43.820
think they're necessary for sustained protein translation in mammals for them to get a signal

43:43.820 --> 43:53.020
that they can point to and say look it works but if you put non uh methyl pseudo uridine

43:53.820 --> 43:57.500
RNA in your lipid nanoparticle you'll get very transient expression

43:58.460 --> 44:08.860
very transient expression absolutely but that that's not quite right what they what this is is

44:10.460 --> 44:18.620
what this is is somebody who is i think over their skis saying what they've been told is right

44:19.740 --> 44:25.420
they probably practiced this talk and somebody said it's fine but essentially she's not saying

44:25.500 --> 44:33.580
this correctly i i really don't think so i know that we have base alterations in our RNA

44:34.860 --> 44:43.340
and they are used presumably for RNA regulation but for purposes of a

44:43.340 --> 44:53.900
transfection tool that's true for purposes of how RNA functions endogenously in your cells

44:54.620 --> 45:02.460
that's true to an extent because actually again the transient nature of RNA being degraded quickly

45:02.460 --> 45:08.060
in your cells is how protein expression is regulated at least as far as we guess

45:08.780 --> 45:15.260
and that's why small interfering RNAs that are complementary to your own

45:15.980 --> 45:21.500
mRNAs and circulation are an interesting way to interfere with protein expression

45:23.020 --> 45:27.020
somebody put in the chat that they're double stranded RNAs i'm going to look it up i'm not sure

45:27.660 --> 45:30.940
i think the mechanism is how i've described it though um

45:31.500 --> 45:37.980
um and so i think this is a bit of a hand-waving exercise to say that this is how it works but

45:37.980 --> 45:45.100
she's specifically talking about transfection not about about translation of proteins and

45:45.100 --> 45:49.820
endogenous proteins so we have these modifications and the cells are more willing to recognize these

45:49.820 --> 45:54.620
externally introduced RNAs as self and then they are willing to produce that protein so all the

45:54.620 --> 45:59.420
work that i'm showing you today is made with RNA that's been base modified so that it works well

45:59.580 --> 46:07.580
so that it works well see so so that it works well in its transfection excuse me so to go back to

46:07.580 --> 46:12.940
the delivery vehicle part of the equation RNA is large it's on the order of a hundred thousand

46:12.940 --> 46:17.180
grams per mole it's negatively charged and so it doesn't readily cross negatively charged cell

46:17.180 --> 46:21.340
membranes and if you were to inject it into the bloodstream it would be both degraded and

46:21.340 --> 46:25.260
negatively charged on the order of a hundred thousand delivery vehicle part of the equation

46:25.260 --> 46:30.460
RNA is large it's on the order of a hundred thousand grams per mole it's negatively charged

46:30.460 --> 46:34.060
and so it doesn't readily cross negatively i get to go back a little bit further and

46:34.060 --> 46:37.900
previous of delivery barrier it's been base modified so that it works well

46:39.100 --> 46:45.100
so in terms of delivery barriers excuse me so to go back to the delivery vehicle part of the

46:45.100 --> 46:50.780
equation RNA is large it's on the order of a hundred thousand grams per mole it's negatively

46:50.780 --> 46:54.940
charged and so it doesn't readily cross negatively charged cell membranes and if you were to

46:55.020 --> 46:59.500
inject it into the bloodstream it would be both degraded and quickly cleared from our system so

46:59.500 --> 47:04.220
we need a vehicle that's going to package it up and protect it and take it to the cells of interest

47:04.220 --> 47:11.020
wow so that's to me we've got to hear that for what she says it is right you got to hear it for

47:11.020 --> 47:16.620
what she says because that assumption is wrong listen carefully you inject it into the bloodstream

47:16.620 --> 47:21.740
it would be both degraded and quickly cleared from our system so if you injected it into the

47:21.740 --> 47:27.180
bloodstream it would be degraded and very quickly cleared did she mean that without lip

47:27.180 --> 47:32.700
and nanoparticle i think that must be what she means right because

47:34.060 --> 47:38.780
wow that that must be just naked RNA but we need a vehicle that's going to package it

47:38.780 --> 47:44.860
yeah okay and take it to the cells of interest so this diagram depicts a couple of barriers that

47:44.860 --> 47:49.100
it needs to overcome if we were to do IV injection so once it's injected into the bloodstream it

47:49.100 --> 47:53.580
needs to avoid clearance by macrophages once it exits the bloodstream it needs to

47:53.580 --> 47:57.980
it needs to avoid clearance by macrophages it also needs to avoid

47:58.940 --> 48:06.940
transfecting endothelial cells and avoid transfecting blood cells and as it goes through

48:06.940 --> 48:13.260
capillaries that will be more and more difficult because the then that's where this is all going

48:13.260 --> 48:16.140
to occur right that's where this size scale comes into play

48:19.180 --> 48:23.740
it's not going to happen in the big vessels it's going to happen in the capillaries and capillaries

48:23.740 --> 48:34.460
that this this size scale is wrong this cartoon is wrong and avoiding the transfection of endothelial

48:34.460 --> 48:42.460
cells is much harder than one might think diffuse through the tissue of the organ that you want to

48:42.460 --> 48:47.020
target it then needs to be up taken into the cell of interest and this happens through a

48:47.020 --> 48:50.940
process called endocytosis where the cell membrane reaches up and around that particle

48:50.940 --> 48:55.100
and it brings it inside and so at this point the nanoparticle is in this Waldorf compartment

48:55.740 --> 48:58.780
and the cell keeps it there because it's not sure what it is and it looks and says this is

48:58.780 --> 49:05.340
something I want to see that the the whole anytime a biologist anthropomorphizes the

49:05.340 --> 49:14.060
operations of a cell and I don't even know I don't think you can ever do that and if you do

49:14.060 --> 49:21.260
it you need to be very very careful in this case it's ridiculous it's held in an endosome until

49:21.260 --> 49:25.660
it does the cell decides what to do with it because it's not sure what it is

49:26.940 --> 49:32.700
are you kidding this is a chemical covered in other chemicals

49:33.260 --> 49:36.220
the hell is she talking about

49:39.180 --> 49:43.900
and typically a lipid nanoparticle is not on its wish list so the endosome begins to acidify

49:43.900 --> 49:47.820
and would otherwise degrade these lipid nanoparticles so part of the design of the chemistry behind

49:47.820 --> 49:51.980
these particles is that they need to mediate this process of endosomal escape and that's one of

49:51.980 --> 49:56.380
the most difficult parts of this process so once the RNA is into the cell cytoplasm that's when

49:56.380 --> 49:59.980
it can interface with the protein translational machinery and make our protein of interest

50:00.460 --> 50:06.300
so years ago we asked if we could develop a potent and degradable RNA delivery system

50:06.300 --> 50:10.700
potent for obvious reasons and degradable because many of these therapeutics will need to be

50:10.700 --> 50:18.220
repeat dose I mean seriously jittery and maker jason all of these arrows are pretty magical

50:18.220 --> 50:22.860
all of these arrows are pretty magical this arrows very magical this arrow what is this

50:22.860 --> 50:28.860
like is this an an electron going down from two different energy levels what the hell is this

50:30.540 --> 50:36.540
I mean did they take and are they trying to convert a photosynthesis diagram into a

50:41.900 --> 50:48.860
I mean even this is silly this part you know like okay now we have RNA I guess but it's

50:48.860 --> 50:55.180
double stranded or something what is this you know I don't I don't I don't I don't know what to say

50:56.140 --> 51:01.100
I don't know how to overcome this I mean could I get her to come to

51:01.820 --> 51:06.620
giga ohm biological and let me give her an hour lecture like this but then say completely

51:06.620 --> 51:17.820
the opposite what would she do it's shocking isn't it it's just shocking this B arrow this

51:17.820 --> 51:23.580
C arrow what is that the part of the design of the chemistry behind these particles is that they

51:23.660 --> 51:27.100
need to mediate this process of endosomal escape and that's one of the most difficult

51:27.100 --> 51:31.500
parts of this process so once the RNA is into the cell cytoplasm that's when it can interface

51:31.500 --> 51:36.140
with the protein translational machinery and make our protein of interest see if you can say all

51:36.140 --> 51:41.100
those words together that's when it can interface with the protein the cells protein machinery or

51:41.100 --> 51:48.140
whatever I mean that that doesn't make you a commander of this knowledge it doesn't make you

51:48.140 --> 51:53.260
understanding the way that this complex system manifests it's just a joke

51:55.900 --> 52:02.060
she was anthropomorphizing the cell as holding the liposome in an endosome because it didn't

52:02.060 --> 52:08.940
know what it was and it wasn't sure what to do with it that was her explanation for these other PhDs

52:09.260 --> 52:17.500
so years ago we asked if we could develop a potent and degradable RNA delivery system

52:17.500 --> 52:21.980
potent for obvious reasons and degradable because many of these therapeutics will need to be

52:21.980 --> 52:26.860
repeat dosed we will not necessarily create a cure but a treatment and we don't want this material

52:26.860 --> 52:32.620
building up over time so the materials that we work with in my lab they're lipid-like materials

52:32.620 --> 52:37.180
we call them lipidoids and they're a variation of the cationic lipids that have been used for

52:37.260 --> 52:41.340
decades at this point for different types of nucleic acid delivery first a lot of the work

52:41.340 --> 52:45.820
was done in the DNA delivery field so here's one of these cationic lipids if you were to put it

52:45.820 --> 52:50.940
into aqueous medium you would find that they would assemble into these liposomal structures

52:50.940 --> 52:57.660
where we have the hydrophilic head group on the outside of the aqueous media and then we would

52:57.660 --> 53:02.460
have these hydrophobic tails on the inside and you can load then hydrophilic drugs into the interior

53:03.020 --> 53:07.420
so we wanted to make something like this to hold on to our RNA and we also wanted to

53:07.420 --> 53:11.260
generate materials where we could look at a lot of different chemistries and try to understand

53:11.260 --> 53:17.420
I want you to see how how extraordinary it is that she talks as though we wanted to do we wanted to

53:17.420 --> 53:24.700
do we wanted to do like it's something you know it's almost like saying you know I wanted to put

53:24.700 --> 53:31.180
together a bunch of pages and I'm gonna call it a book and I really wanted to make a book so it was

53:31.180 --> 53:34.860
my idea to bunch a bunch of pages together and then bind them at the back

53:36.780 --> 53:45.660
she's talking about a a technology that she started her talk by saying that it had gone from

53:45.660 --> 53:54.060
niche to mainstream so what does she need to explain it for what's so special about hers

53:55.020 --> 54:01.580
and why does she need to explain it on this level she's giving a talk with Peter Coles in the

54:01.580 --> 54:09.260
background it's extraordinary I find this extraordinary it is the lack of

54:13.180 --> 54:19.820
appropriate audience I mean it's it's just oh it drives me crazy this is what used to drive me

54:20.220 --> 54:29.660
crazy about about neuroscience you could have a room full of people talking about supposedly

54:29.660 --> 54:34.940
about the highest level of discussion about our understanding of how micro circuits in the brain

54:34.940 --> 54:39.500
work and you could have somebody in the back room raise their hand and say I don't I don't

54:40.140 --> 54:43.420
could you briefly explain what a G protein coupled receptor is

54:43.980 --> 54:51.340
and you might have been talking about a type of receptor that is a G protein coupled receptor

54:54.780 --> 54:59.980
and you may have even given an introduction that was reasonable about G protein coupled

54:59.980 --> 55:04.380
receptors and this person would still have the audacity to raise their hand and ask that question

55:07.180 --> 55:08.380
only in biology

55:09.100 --> 55:10.620
you

55:10.620 --> 55:15.580
couldn't go into a physics lecture and say hey can you briefly explain to me what you mean by that

55:17.900 --> 55:25.100
I'm not sure I get it you couldn't go into an organic chemistry lab or lecture and say you know

55:25.100 --> 55:30.460
can you briefly explain to me what that category of molecule is I'm not really familiar with that

55:31.180 --> 55:38.860
but for some reason in biology everybody any any poser that wants to can go and join a lab

55:38.860 --> 55:41.340
and do a PhD project and there you go

55:45.580 --> 55:51.340
you did some programming as a PhD student and now you're up now you're going to do a postdoc in biology

55:53.180 --> 55:56.940
and since you did some T cell stuff I guess you're an immunologist now

56:00.540 --> 56:05.020
oh you put some silt bubbles and some RNA together and you followed the recipe

56:05.740 --> 56:10.780
and then you followed another recipe successfully and after following six recipes successfully that

56:10.780 --> 56:15.340
you basically adapted from other people's recipes you're a biologist now

56:18.860 --> 56:24.540
and the depth of your understanding of the concepts that you purport to wield is terrifying

56:25.420 --> 56:29.980
the chemistry of these lipidoids would affect their functionality and try to derive structure

56:29.980 --> 56:33.900
functional relationships from that so we use a high throughput type of chemistry called Michael

56:33.900 --> 56:38.940
addition in which we take an alkalamine so we need some combination and say primary means a

56:38.940 --> 56:43.580
secondary means and we would react them with alkal acrylate tails here it's an easy reaction

56:43.580 --> 56:46.940
you put the two together in a scintillation vial there's no solvent you can mix them for a

56:46.940 --> 56:50.780
couple of days at high temperature and out the other side comes something that's not too dissimilar

56:50.860 --> 56:55.900
from this cationic lipid up here so we can vary the chemistry of both this amine and the tail

56:55.900 --> 57:00.620
to generate large numbers of materials the degradability comes in from the use of these

57:00.620 --> 57:06.060
acrylate materials with which result in an ester in the final form of these lipids and those esters

57:06.060 --> 57:12.540
degrade under physiological conditions so these lipids are ionizable meaning that under reduced

57:12.540 --> 57:17.660
pH conditions as we form these particles they are going to have this nice electrostatic interaction

57:17.660 --> 57:21.980
with the negatively charged RNA which will help to catalyze the formation of these particles

57:22.700 --> 57:27.580
so the particles are made through a nanoprecipitation process in which we need rapid mixing

57:28.540 --> 57:33.820
so we have a rapid mixing of two streams to form our nanoparticles one of which is going to be

57:33.820 --> 57:39.020
RNA that's in a saline solution and then i do have to say that microfluidics is really cool

57:39.020 --> 57:44.380
they can do a lot of really cool things with microfluidic devices we have a variety of lipids

57:44.460 --> 57:48.700
that are dissolved in ethanol and they are rapidly mixed you can use microfluidic devices

57:48.700 --> 57:52.620
t-mixers and you can also use pipettes which are relatively straightforward

57:52.620 --> 57:55.820
pipettes are not appropriate for scale up or anything like that but they work well in the

57:55.820 --> 58:00.140
lab when you don't have a lot of money for microfluidic systems so you mix these two streams together

58:00.620 --> 58:05.580
and you get materials that you know you have you have lipids both on the exterior of the

58:05.580 --> 58:09.100
particle like we had with liposomes but you also have lipids throughout the material

58:09.100 --> 58:13.740
so in terms of the ingredients in these particles they include the ionizable lipid or lipidoid that

58:13.740 --> 58:18.300
i just told you about this tends to be where a lot of the IP is in the lipid nanoparticle space

58:18.300 --> 58:22.860
many labs or companies attempt to create their own chemistry and intellectual property with

58:22.860 --> 58:27.340
these synthetic materials they also contain helper lipids so these are often phospholipids that

58:27.340 --> 58:31.180
naturally occur in our cell membrane they can help with stability of the particles and also

58:31.180 --> 58:35.660
their ability to help with endosomal escape we have a lot of cholesterol in these particles

58:35.660 --> 58:40.220
which adds stability and prevents the particles from falling apart very similar to the way we

58:40.300 --> 58:43.900
have a lot of cholesterol in our cell membranes we would all be piles of boo if it were not for

58:43.900 --> 58:49.580
our cholesterol in our particles would be too then we have our polyethylene glycol lipid so the lipid

58:49.580 --> 58:53.420
anchor here will insert on the inside of the particle and then we have polyethylene glycol

58:53.420 --> 58:57.740
which is a hydrophilic polymer which decorates the outside of the particle it can quench that

58:57.740 --> 59:02.700
nanoparticle formation process so help us obtain particles of a nice size it can also improve

59:02.700 --> 59:06.460
stability and decrease the amount of unwanted immune cell uptake that we get

59:07.900 --> 59:12.700
unwanted immune cell uptake i thought you wanted immune cell uptake

59:14.700 --> 59:18.940
or maybe not for their maybe they're maybe they're not trying to do vaccines maybe they're trying

59:18.940 --> 59:23.340
to do something else so over the years we've made and screened thousands of these ionizable lipidoids

59:23.340 --> 59:27.900
for RNA delivery and we found a number that we really like and we've used them for numerous

59:27.900 --> 59:31.980
applications so here's one of our favorite lipidoids that we use in my lab

59:31.980 --> 59:35.500
it's a four-tailed lipidoid it has a couple of these nitrogen groups which help it

59:35.500 --> 59:40.620
protonate in the endosome and endosome doing endosomal escape we have our esters here for

59:40.620 --> 59:44.220
degradability and then these materials are interesting because they have these branch

59:44.220 --> 59:49.260
tails and the branch tails seem to change the structure of these lipids so that they can

59:49.260 --> 59:54.540
interface with endosomal membranes differently and aid that fusion and escape process so this

59:54.540 --> 59:58.940
is a great lipid and so the work i'm going to show you today all of it involves this ionizable lipid

59:59.820 --> 01:00:04.140
so standard nanoparticles where the state of the field is at this point is that we can achieve

01:00:04.140 --> 01:00:08.780
delivery to a couple of locations so the liver has been the easiest location i don't want to say

01:00:08.780 --> 01:00:13.420
it's easy but it's been the easiest because when you inject particles the liver is the organ that

01:00:13.420 --> 01:00:18.380
will naturally clear them from the bloodstream and so if it doesn't clear them from the bloodstream

01:00:18.380 --> 01:00:23.580
then those particles go elsewhere they go to any place they want to go they go to endothelial

01:00:23.580 --> 01:00:29.260
cells they go to the ovary they go to the testes they go to your brain they can go anywhere they

01:00:29.260 --> 01:00:37.740
want to if if you have perforated endothelial barriers so this concept that it can be

01:00:37.740 --> 01:00:45.180
it can be remain in the muscle and look how they label it immune cells and muscle now i'm sorry i'm

01:00:45.180 --> 01:00:51.660
not trying to be a creep here but the immune system isn't really organized to protect the

01:00:51.660 --> 01:00:58.540
interior of your deltoid there may be some resident immune cells there there may be a lymph

01:00:58.540 --> 01:01:07.340
vessel that runs through there the immune system is present but the immune system is

01:01:07.340 --> 01:01:12.620
oriented around barriers there is no question about it and barriers with the outside world

01:01:12.620 --> 01:01:17.340
there is a barrier with the outside world that runs through your body there's a barrier with

01:01:17.340 --> 01:01:22.860
the outside world that is in your lungs and there's a barrier in the outside world on the

01:01:22.860 --> 01:01:31.820
outside of your body and all three of these barriers are manned are our outward facing

01:01:31.820 --> 01:01:38.140
epithelial barriers epithelial cells are necessarily dividing barriers

01:01:38.300 --> 01:01:48.860
and the immune system is organized around them and so this assumption that she makes that we

01:01:48.860 --> 01:01:56.460
can inject it in in a muscle and it stays there and it's expresses protein and the immune system

01:01:56.460 --> 01:02:03.980
comes and it's not sure what to do but eventually it decides that what what the intention of this

01:02:04.060 --> 01:02:09.420
protein is is to make me make immune to a memory to it or something like this whenever they would

01:02:09.420 --> 01:02:15.580
talk through it and that first FDA approved product was to treat a liver condition and it's a to treat

01:02:15.580 --> 01:02:20.940
a liver condition because that's where the lipid nanoparticles go necessarily because the liver

01:02:20.940 --> 01:02:27.420
cleans your blood not because they're chemically altered to go to the liver but because that's

01:02:27.420 --> 01:02:31.900
where the majority of them go all of them don't go there

01:02:35.020 --> 01:02:40.060
the ones that don't transfect something else first get pulled out in the liver

01:02:42.620 --> 01:02:46.060
much of the transfection occurs at the liver

01:02:49.260 --> 01:02:54.700
and in fact it's very likely that when you get injected with an mRNA in your muscle and it leaks

01:02:54.700 --> 01:03:03.020
out the transfection occurs in the liver the transfection occurs in the capillaries of the heart

01:03:03.020 --> 01:03:06.940
the capillaries of the lungs maybe the capillaries of your skin

01:03:08.380 --> 01:03:13.340
I think we've seen it many many times where it's the capillaries of the skin where we get a massive

01:03:13.340 --> 01:03:21.980
transfection and therefore a massive inflammation a massive neutrophil attack on the endothelial cells

01:03:21.980 --> 01:03:28.700
we've seen this all around the world we've seen what happens we know this is what's going on

01:03:28.700 --> 01:03:38.940
there's no other biological alternative and these people know even as she disingenuously describes

01:03:39.580 --> 01:03:48.540
the nature of targeting the liver they called them liver targeting lipid nanoparticles because

01:03:48.540 --> 01:03:52.060
the liver pulls them out and the majority of them showed up there

01:03:59.180 --> 01:04:02.540
I mean I just hope you can see how disingenuous that is

01:04:07.180 --> 01:04:08.460
I just hope you can see it

01:04:09.340 --> 01:04:11.340
oops

01:04:13.260 --> 01:04:18.300
we also are capable of vaccination so delivery to the immune cells and the muscle cells within

01:04:18.300 --> 01:04:22.780
the muscle tissue to mount the immune response that we need but the question really is is we're

01:04:22.780 --> 01:04:28.220
thinking about the future of RNA therapies is how we will deliver these materials beyond the liver

01:04:28.220 --> 01:04:32.620
so as you can imagine most of the diseases in the body are outside of the liver and there are

01:04:32.620 --> 01:04:36.860
many different places we'd like to go so my lab works on delivering these materials to a couple

01:04:36.940 --> 01:04:41.020
of these particular organs and today I'll be talking mostly about our ability to deliver to

01:04:41.020 --> 01:04:47.580
the pancreas so for this work we're going to be focusing on swapping out the helper lipids

01:04:47.580 --> 01:04:52.540
in these particles and looking at how the influence of helper lipid charge in particular

01:04:52.540 --> 01:04:57.660
can direct these particles to different cell types so there have been a couple of people who

01:04:57.660 --> 01:05:03.100
have reported the influence of charge on the delivery process so Dan Seagard's lab was one

01:05:03.100 --> 01:05:07.660
of the first to show that changing the charge either cationic or negative compared to some of

01:05:07.660 --> 01:05:12.540
the neutral helper lipids can shift delivery from the liver to either the spleen or the lungs

01:05:12.540 --> 01:05:18.860
and we found something similar in our lab so in this case I'm showing you so DOPE is the standard

01:05:18.860 --> 01:05:23.340
phospholipid that we use in my lab it carries a net neutral charge and you can see if we look at

01:05:23.340 --> 01:05:27.900
organ distribution of protein expression so that's the blue and purple signal here you can see that

01:05:27.900 --> 01:05:32.380
we have expression in the liver and a bit in the spleen it's more it's more in the liver than the

01:05:32.380 --> 01:05:36.380
spleen just because the liver is larger so here's the quantified signal where we're looking at

01:05:36.380 --> 01:05:41.580
luminescence expression which is a model protein that we were trying to create so here we have

01:05:41.580 --> 01:05:46.700
mostly liver and a little bit in the spleen and then if we change our helper lipid to DOPS

01:05:46.700 --> 01:05:50.860
which is a negatively charged lipid you can see now that we have improved delivery in the spleen

01:05:50.860 --> 01:05:55.580
some shifts there whereas if we include a positively charged helper lipid now we have a

01:05:55.580 --> 01:06:00.380
significant shift shifts to the lung tissue so this is just evidence that the charge of these

01:06:00.460 --> 01:06:05.420
materials can be quite influential and this is just one of the the molecules out of four types of

01:06:05.420 --> 01:06:10.780
lipids that are present in these particles so we wanted to know if we could use a similar approach

01:06:10.780 --> 01:06:15.740
in our delivery to the pancreas so we're going to manipulate two parameters to try to get good

01:06:15.740 --> 01:06:20.460
delivery to the pancreas one is that chemistry so specifically the helper lipid and its charge

01:06:20.460 --> 01:06:24.620
and the other is the route of administration so you can imagine that depending on where you are

01:06:24.620 --> 01:06:28.860
injecting materials into the body you're going to go different places so we are going to swap out

01:06:28.940 --> 01:06:34.540
some of the typical IV injections for interperitoneal injections which is into the cavity that holds

01:06:34.540 --> 01:06:39.660
the liver and the pancreas and some other organs so for all of our experiments here that i'm going

01:06:39.660 --> 01:06:45.500
to show you today we're looking at the expression so interperitoneal would be like to lift the skin

01:06:45.500 --> 01:06:53.660
of your of your gut area and then poke through the skin but not poke into an organ and then squirt

01:06:53.740 --> 01:06:59.580
it in there it's like the space if you were to cut open the skin of your belly and open it up to

01:06:59.580 --> 01:07:05.420
see your intestines and then squirt it under there that that's the interperitoneal if you do that on

01:07:05.420 --> 01:07:12.620
a mouse or or a dog he would just pick up the skin of the belly and then put it into the triangle of

01:07:12.620 --> 01:07:18.860
skin that you have there and then you'd be in the space and you'd inject it in of a model protein

01:07:18.860 --> 01:07:23.900
so firefly vociferase and we're able to visualize protein expression if we have good delivery so

01:07:23.900 --> 01:07:29.260
our mRNA encodes firefly vociferase we'll put that into our particles we will deliver them into

01:07:29.260 --> 01:07:34.300
mice and then a few hours later we'll be able to take out their organs and to image them for

01:07:34.300 --> 01:07:39.660
luminescence so they take them out a few hours later you don't know where it goes after that you

01:07:39.660 --> 01:07:44.300
don't know if where it was is where it's going to stay you don't know anything that's the whole

01:07:44.380 --> 01:07:51.020
point of all of these experiments with mice is that there's necessarily an end point you're

01:07:51.020 --> 01:07:57.580
not going to cover all time lengths you're not going to cover all and then you're going to draw big

01:07:57.580 --> 01:08:06.540
conclusions and so imagine the extraordinary hubris that's going on here okay we already know

01:08:06.540 --> 01:08:11.180
they're safe because we tested them on three billion people so if they don't go everywhere we want

01:08:11.260 --> 01:08:14.940
them to all the time it doesn't matter because we know they're safe

01:08:18.460 --> 01:08:22.780
expressing proteins in the wrong place and the body doesn't cause any harm at all because we

01:08:22.780 --> 01:08:27.980
know they're safe from the vaccines don't you see otherwise we would know from the five billion

01:08:27.980 --> 01:08:37.180
shots that we rolled out don't you see we can target the liver because that's where they all go when

01:08:37.660 --> 01:08:45.260
you put them in as Mark said it's like a smart ball that when no matter which way you throw it

01:08:45.260 --> 01:08:52.220
it goes right back to the ground no matter what you inject in your body and into your blood it

01:08:52.220 --> 01:09:00.940
goes to your liver wow that's pretty brilliant you are so smart expression so here what i'm showing

01:09:00.940 --> 01:09:05.420
you first is if we take some of our favorite particles and we deliver them IV and this is

01:09:05.420 --> 01:09:09.260
with a neutral helper lipid and you can see as i showed you before that most of our expression

01:09:09.260 --> 01:09:14.860
is in the liver what my postdoc found when she quantified this was a very small amount of

01:09:14.860 --> 01:09:19.900
expression in the pancreas so note this is a exponential scale here so 10 to the 7th versus

01:09:19.900 --> 01:09:24.140
you know a couple of orders of magnitude more in the liver but she noticed there was a little

01:09:24.140 --> 01:09:28.060
something and she wondered if she could turn that little something into something more substantial

01:09:28.060 --> 01:09:31.660
so the first thought was okay let's change our route of administration and let's deliver

01:09:31.660 --> 01:09:36.540
these same particles intreparitinial injection and you can see here that we do have some shifts

01:09:36.540 --> 01:09:40.780
away from the liver and into the pancreas and if we quantify this here you can see the pancreas

01:09:40.780 --> 01:09:45.500
expression has jumped up in order of magnitude and we do see some reductions in the amount of liver

01:09:46.140 --> 01:09:52.060
i say give this woman a NIH grant i say payer for five more years right i mean that's

01:09:52.060 --> 01:09:58.140
hugely significant holy p-values Batman expression that we have and the overall efficacy is a bit

01:09:58.140 --> 01:10:01.900
lower this total bar is a bit lower but if our goal is to deliver to the pancreas that's not a

01:10:01.900 --> 01:10:07.340
problem so then she wondered about the charge of that helper lipid so here again are her data with

01:10:07.340 --> 01:10:12.700
the overall net neutral helper lipid which when she delivers it IP we have quite a bit in the

01:10:12.700 --> 01:10:18.060
pancreas then if she swaps this out for a negatively charged helper lipid we don't really see significant

01:10:18.060 --> 01:10:21.660
changes there there's certainly not more in the pancreas if anything there's a little less and

01:10:21.660 --> 01:10:26.300
then if she uses a positive helper lipid instead you can see something interesting happens so we

01:10:26.300 --> 01:10:29.980
we have the same amount of expression in the pancreas but what we've done is is to almost

01:10:30.700 --> 01:10:34.380
you know not completely but we've significantly reduced the amount of expression in the liver

01:10:34.380 --> 01:10:39.260
so where the hell does it go does she think it disappears it's degraded

01:10:40.300 --> 01:10:45.340
or is it in the endothelial cells or is it in the ovaries or is it in the brain

01:10:46.780 --> 01:10:52.300
there's only four organs listed here there's only four places they're looking

01:10:56.940 --> 01:11:03.180
and so this is really nice because ultimately if we want to do things in the pancreas you usually

01:11:03.180 --> 01:11:06.620
don't also want to manipulate protein expression in the liver so it's nice if we can do something

01:11:06.620 --> 01:11:12.380
more targeted so just to summarize what we've been able to do with these two different manipulations

01:11:12.380 --> 01:11:17.260
if we have IV injection of our neutral helper lipid we have less than 1% of signal in the pancreas

01:11:17.260 --> 01:11:22.300
if we change that to IP administration now we have 15% in the pancreas and if we then swap that

01:11:22.300 --> 01:11:25.900
neutral helper lipid out for something that's positively charged now we flip the ratio of

01:11:25.900 --> 01:11:31.660
pancreas to liver and we have about 60% and the rest we don't know what happens to who cares

01:11:31.660 --> 01:11:37.340
because you know we gave five billion shots to people and they're all fine so obviously it can't

01:11:37.340 --> 01:11:47.260
hurt holy balls i can't believe it so our next question was where in the pancreas was this

01:11:47.260 --> 01:11:52.300
expression occurring and what my postdoc found was that interestingly it's occurring in the

01:11:52.300 --> 01:11:57.020
eyelet cells so the eyelet cells are not a whole lot of the total tissue i forgot what it is but

01:11:57.020 --> 01:12:01.900
it's less than 10% of total pancreas tissue are these eyelets which contain both alpha and beta

01:12:01.900 --> 01:12:08.540
cells and so what she's trying to transfect the pancreas and it has two basic cell types and

01:12:08.540 --> 01:12:19.100
she's not even sure what the ratio is like i'm not an expert in the pancreas i'm not trying to

01:12:19.100 --> 01:12:25.340
transfect i'm not i'm not asking for grant money for the pancreas but if you don't know that ratio

01:12:25.340 --> 01:12:29.180
off the top of your head and you are supervising a postdoc doing a

01:12:33.660 --> 01:12:38.060
showing you here is some staining of luciferase expression so these are our control mice

01:12:38.700 --> 01:12:42.380
which have not received lipid nanoparticles and you can see that they don't have any brown

01:12:42.380 --> 01:12:46.540
signal which would correspond to luciferase expression and now this is the treated sample

01:12:46.620 --> 01:12:51.420
and you can see that the eyelets are expressing a lot of this luciferase there's also some

01:12:51.420 --> 01:12:57.500
outside here in the asinar tissue as well and if we quantify how important these beta cells are

01:12:57.500 --> 01:13:01.980
for protein expression we see that they are predominantly responsible for the protein

01:13:01.980 --> 01:13:06.460
expression so here if we look at wild type mice we have a certain amount of protein expression

01:13:06.460 --> 01:13:11.020
around 10 to the eighth and then if you treat these mice with stz which is a molecule that

01:13:11.020 --> 01:13:15.820
will deplete beta cells in the body you can see that we have about an order of magnitude reduction

01:13:15.820 --> 01:13:19.740
in the signal that we have in the animal suggesting that most of the protein expression

01:13:19.740 --> 01:13:26.460
is occurring in these beta cells so how on earth is this happening how are we transmitting these

01:13:26.460 --> 01:13:30.540
eyelets it's it would be very strange if the particles were penetrating the outer capsule

01:13:30.540 --> 01:13:34.620
of the pancreas my collaborator who's a pancreatic surgeon says you know that's quite unlikely

01:13:34.620 --> 01:13:40.220
so we wanted to understand more about how this was happening and what my postdoc did first is

01:13:40.220 --> 01:13:45.020
she looked at the bio distribution of these particles in the peritoneal cavity so she used

01:13:45.500 --> 01:13:50.860
fluorescently labeled mRNA so it was labeled with a red dye and she isolated different cell types

01:13:50.860 --> 01:13:55.980
so B cells T cells and macrophages and she looked at where these particles were accumulating and

01:13:55.980 --> 01:14:00.700
what she found was that they did not enter T cells but they were entering B cells and macrophages

01:14:00.700 --> 01:14:03.980
so this is not complete delivery we're not looking at protein expression here we're looking at

01:14:03.980 --> 01:14:09.260
which cells took up these particles so since both B cells and macrophages took up the particles

01:14:09.260 --> 01:14:13.900
she then asked if either one of these were involved in the process so here is an efficacy experiment

01:14:13.900 --> 01:14:18.940
in which she has wild-type mice and she compared the expression of luciferase here in our wild-type

01:14:18.940 --> 01:14:24.220
mice to mice in which those B cells have been depleted and what we see is no difference in

01:14:24.220 --> 01:14:28.460
expression so this suggests that the B cells are taking up the particles but they're not producing

01:14:28.460 --> 01:14:34.940
protein however we see something do you understand what she's testing here she she's testing whether

01:14:34.940 --> 01:14:45.260
the B cells the take-up protein are responsible for the signal that she saw on the spleen the liver

01:14:45.260 --> 01:14:52.300
or the lung or the pancreas and so she's depleting lymphocytes

01:14:54.700 --> 01:14:57.740
to show that there's no change in fluorescence

01:14:57.900 --> 01:15:09.260
to demonstrate that the fluorescence that she sees in her target organs is fluorescence that's

01:15:09.260 --> 01:15:15.580
not caused by these immune cells but it's caused by a transfection of those cells in those tissues

01:15:17.740 --> 01:15:23.740
now

01:15:24.140 --> 01:15:28.940
I just don't know what to say about this

01:15:30.860 --> 01:15:35.420
I don't know what it means I don't know what she's showing I don't know why she would call this

01:15:35.420 --> 01:15:40.860
an experiment that would answer that question but that's what she said that's what she explained

01:15:46.620 --> 01:15:50.780
and she's saying that if you deplete the macrophages that you get decreased

01:15:51.020 --> 01:15:57.260
efficacy of transfection decreased

01:16:01.260 --> 01:16:03.900
in different with the macrophages in the peritoneal cavity

01:16:03.900 --> 01:16:08.780
when we use a molecule that depletes these macrophages we see about an order of magnitude

01:16:08.780 --> 01:16:12.620
reduction in the expression that we're getting suggesting that macrophages are very important

01:16:12.620 --> 01:16:19.580
for this delivery process and as we dug a little bit deeper we wondered how macrophages were involved

01:16:19.660 --> 01:16:24.140
so there is some literature showing the process of or the concept of horizontal gene transfer

01:16:24.140 --> 01:16:27.260
by which cells in our body the macrophages in particular

01:16:27.260 --> 01:16:35.020
holy shit holy shit do you hear this what she does is she transfects the macrophages

01:16:35.020 --> 01:16:39.740
and the macrophages produce exosomes and she's calling them extracellular vesicles

01:16:39.740 --> 01:16:44.140
they are exosomes filled with that mRNA that they just got squirted with

01:16:44.860 --> 01:16:55.580
and those exosomes are then causing the transfection are you hearing this this is not facilitation

01:17:03.580 --> 01:17:07.340
I'm really I'm really I'm wow I don't even know what to say

01:17:07.340 --> 01:17:11.740
the type of communication to other cells that are nearby and we wondered if these extracellular

01:17:11.820 --> 01:17:16.220
vesicles might have some kind of role in this process so we did a rather complex experiment

01:17:16.220 --> 01:17:19.500
I'm going to try to walk you through it so again we have particles that are expressing

01:17:19.500 --> 01:17:24.300
our luciferase we're containing our luciferase mRNA we're going to inject them

01:17:24.300 --> 01:17:29.980
interparitoneally into mouse number one and then after a little bit of time goes past we're going

01:17:29.980 --> 01:17:34.620
to do a peritoneal wash so that's where you introduce some saline into the interparitoneal cavity

01:17:34.620 --> 01:17:38.460
and then you pull it out and it's going to contain the immune cells that are in that IP space

01:17:39.180 --> 01:17:43.980
so we'll take that wash and we'll put them into a cell culture dish and then we are going to

01:17:43.980 --> 01:17:48.620
allow these cells to produce extracellular vesicles which will bud off of them into the media

01:17:48.620 --> 01:17:54.460
and then we will collect them okay so now we have these EVs from the immune cells that are in mouse

01:17:54.460 --> 01:17:59.660
number one why are they calling them EVs when they're exosomes they're extracellular vesicles

01:17:59.660 --> 01:18:06.460
they are exosomes number one that have been treated with lmp's we take these EVs and we inject those

01:18:06.540 --> 01:18:10.780
interparitoneally into mouse number two so this mouse has not seen any lipid nanoparticles

01:18:10.780 --> 01:18:15.340
it's just seen these extracellular vesicles and then we do imaging to look at this luciferase

01:18:15.340 --> 01:18:20.220
expression and the results we found are quite interesting so we see that these EV treated mice

01:18:20.220 --> 01:18:25.020
so those are mouse or mice number two they do not have statistically significant differences

01:18:25.020 --> 01:18:29.660
in delivery compared to our lipid nanoparticle treated mice although the averages here are a bit

01:18:29.660 --> 01:18:35.100
we might have you know the averages about two times that of these EV treated mice so it's really

01:18:35.100 --> 01:18:39.020
very interesting that these EVs seem to be responsible for at least part of the delivery

01:18:39.020 --> 01:18:43.500
that we're seeing to the pancreas and as next steps we're going to try to figure out how exactly

01:18:43.500 --> 01:18:48.700
that's happening and why so finally I'll just share a little bit of safety data I always like to say

01:18:48.700 --> 01:18:53.580
when it comes to looking at immune responses and the toxicity there are lots of different ways

01:18:53.580 --> 01:18:57.980
that toxicity can happen and we've looked at only a subset of those measures and so more testing

01:18:57.980 --> 01:19:03.340
as well in this case we've looked at after our injections of these particles we look at some

01:19:03.340 --> 01:19:07.740
innate cytokines that can be expressed and we don't want to see significant differences there

01:19:07.740 --> 01:19:12.460
for the most part and certainly not elevation of these inflammatory cytokines then we also

01:19:12.460 --> 01:19:17.020
looked at antibody expression for IgG and IgM and we don't see any significance there

01:19:17.020 --> 01:19:24.700
after injection either what IgM and IgG antibodies would you be looking for what epitopes did you

01:19:24.700 --> 01:19:32.940
look for just serum IgG changes or what do you expect to see a serum IgG change

01:19:32.940 --> 01:19:38.620
that's a specific or was this specific for an epitope that's weird what a weird statement

01:19:38.620 --> 01:19:45.260
what a weird wow we also did some histology of all of these pertinent organs and compared to

01:19:45.260 --> 01:19:50.220
I mean then what does it mean like I don't understand does it activate the immune system then or not

01:19:50.220 --> 01:19:57.740
because how I guess it doesn't it only does it when they want it to they're so good at this

01:19:57.740 --> 01:20:03.580
wow it's impressive we also did some histology of all of these pertinent organs and compared to

01:20:03.580 --> 01:20:08.940
our PBS controls we don't see significant differences in the tissue or infiltration of

01:20:08.940 --> 01:20:13.500
immune cells so encouraging for now but as I said there's always more work so they were able to do

01:20:13.500 --> 01:20:21.020
histological inspection of the pancreas liver spleen heart kidney and lungs for immune

01:20:21.660 --> 01:20:28.060
infiltration and let's just think about this a second let's just think where are we here I'm

01:20:28.060 --> 01:20:39.420
going to look at the time the time is 33 19 okay so let's look let's just play shall we play a little

01:20:39.500 --> 01:20:47.340
bit of play where is that diagram where is that diagram well back here farther I guess

01:20:48.540 --> 01:20:55.900
where's the diagram there was a diagram where she told us the pro this the the the

01:20:57.180 --> 01:21:00.940
where she told us the actual experiment and how long was it going to take right here okay

01:21:02.220 --> 01:21:03.020
let's go back

01:21:03.020 --> 01:21:13.660
I want to go back because I want to hear how long they left the mice before they went looking for

01:21:13.660 --> 01:21:25.580
problems come on you demon don't mess with me demon come on later we'll be able to take out

01:21:25.580 --> 01:21:30.700
their organs and to image them for mice codes firefly with sipperase we'll put that into our

01:21:30.700 --> 01:21:35.980
particles we will deliver them into mice and then a few hours later we'll be able to take out

01:21:35.980 --> 01:21:42.860
their organs and to image them for luminescence expression so here what I'm showing you first a

01:21:42.860 --> 01:21:52.140
few hours later a few hours later that can't be when they did it for this one at 33 no way no way

01:21:52.460 --> 01:21:59.100
no way that can't be but you know that is it's the same

01:22:02.140 --> 01:22:03.420
they waited like an hour

01:22:04.860 --> 01:22:10.220
it's EV treated mice so it's really very interesting that these EVs seem to be responsible for at least

01:22:10.220 --> 01:22:14.220
part of the delivery that we're seeing to the pancreas and as next steps we're going to try

01:22:14.220 --> 01:22:19.420
to figure out how exactly that's happening and why so finally I'll just share a little bit of safety

01:22:19.420 --> 01:22:23.980
data I always like to say when it comes to looking at immune responses and and then of course we

01:22:23.980 --> 01:22:29.420
reviewed the safety data toxicity can happen and then of course we reviewed the safety data

01:22:29.420 --> 01:22:34.380
more testing is always needed in this case we've looked at after our injections of these particles

01:22:34.380 --> 01:22:39.100
we look at some innate cytokines that can be expressed and we don't want to see significant

01:22:39.100 --> 01:22:43.900
differences there for the most part and certainly not elevation of these inflammatory cytokines

01:22:43.900 --> 01:22:48.540
then we also looked at antibody expression for IgG and IgM and we don't see any significance

01:22:48.540 --> 01:22:53.660
there after injection either we also did some histology of all of these pertinent organs

01:22:53.660 --> 01:22:58.380
boy I'd like to know how long this was before they did it see significant differences in

01:22:58.380 --> 01:23:04.060
the tissue or infiltration of immune cells so after how many days there's always more work to be done

01:23:05.020 --> 01:23:09.500
so in summary what I've shown you today is that we can take our favorite ionizable lipid

01:23:09.500 --> 01:23:14.780
and we can formulate particles in which we tune both the helper lipid charge and the route of

01:23:14.780 --> 01:23:21.020
administration to deliver RNA to the pancreas and it seems that the eyelets are where most

01:23:21.020 --> 01:23:26.700
but it was mostly the the adjustment of where you injected it it had very little to do with

01:23:26.700 --> 01:23:31.820
what you did to the lipid did you notice that when you injected into the blood it didn't really

01:23:31.820 --> 01:23:35.580
change very much of where it went it was when you injected it into peritonealia and

01:23:35.900 --> 01:23:44.780
this is they didn't show it they didn't it's like this is so typical for an

01:23:44.780 --> 01:23:51.660
academy vision to say that these results are something because my p-values say it's something

01:23:54.300 --> 01:24:00.060
it's just unbelievable protein expression is happening and then we see that peritoneal

01:24:00.060 --> 01:24:04.300
macrophages are doing something very interesting to help in this process perhaps by engaging in

01:24:04.300 --> 01:24:10.540
this horizontal gene transfer mediated perhaps by engaging in horizontal gene transfer but the

01:24:10.540 --> 01:24:17.420
only thing they have as evidence that macrophages do something are this one figure

01:24:21.980 --> 01:24:29.900
this figure is not proof the difference between these six animals and these six

01:24:29.900 --> 01:24:36.220
animals right here is the proof that macrophages do something like horizontal gene transfer

01:24:38.140 --> 01:24:43.980
you understand that right this whole story with cartoons about macrophages

01:24:45.420 --> 01:24:46.300
at the end here

01:24:46.700 --> 01:24:54.140
the do something this cartoon hello it's me what what a horse no

01:24:58.860 --> 01:25:06.540
it's just unbelievable how how far this has gone how unbelievable it's it's it's totally harmless

01:25:08.700 --> 01:25:10.460
if you're doing experiments about

01:25:10.700 --> 01:25:17.340
soil microbes and just trying to figure out how that whole ecosystem works and you're never going

01:25:17.340 --> 01:25:22.780
to do any you know genetic manipulation and you're just measuring stuff and whatever that's great

01:25:23.980 --> 01:25:29.100
or if you work somewhere on some remote island on some interesting tuber

01:25:31.660 --> 01:25:36.940
but if you're making medical therapeutics if you're making biologics if you're making

01:25:36.940 --> 01:25:41.820
things that you intend to save the world with you better be freaking more complicated and more

01:25:42.460 --> 01:25:44.460
more humble in your biology than this

01:25:47.580 --> 01:25:52.540
you better have more command over the details than this you better get the details better than this

01:25:55.340 --> 01:26:03.180
this is terrible this is somebody with a very long narrow sliver of expertise

01:26:03.180 --> 01:26:11.900
a very long sliver of expertise that extends right to the edge of understanding of how

01:26:11.900 --> 01:26:20.300
lipid nanoparticles can be targeted to specific tissues but not nearly broad enough to understand

01:26:20.300 --> 01:26:29.020
how dumb a question it is if she had this kind of an understanding of biology she might understand

01:26:29.020 --> 01:26:34.060
how kind of ridiculous it is what she's trying to do if she had this broad of an understanding of

01:26:34.060 --> 01:26:43.820
biology she would not even be in this field a guy like me would have never found himself

01:26:43.820 --> 01:26:47.260
in this lab because this lab is even worse than

01:26:49.500 --> 01:26:57.500
wow someday i'm going to do like a a week on patch clamp physiology so that we can talk about

01:26:57.980 --> 01:27:02.140
what we can and can't do with it and more importantly we can talk about what we did with

01:27:02.700 --> 01:27:10.060
the mice before we did patch clamp experiments and how the in vivo manipulations of the behavior

01:27:10.060 --> 01:27:18.780
of the animal were read out in the the micro circuit i think i heard one member of the clown

01:27:18.780 --> 01:27:25.420
show talking the other day about how i might not know anything about anything because i've only

01:27:25.500 --> 01:27:33.660
ever worked in vitro and under a microscope a good majority of my work is under a microscope

01:27:33.660 --> 01:27:38.860
a good majority of my work in pitzburg was in a condor a confocal microscope a good majority of

01:27:38.860 --> 01:27:45.420
my work in trolenheim was and in the Netherlands was with live animals that were manipulated before

01:27:45.420 --> 01:27:52.780
the recordings were made either molecularly or behaviorally or both

01:27:52.940 --> 01:27:59.820
so i've got plenty of in vitro and in vivo experience and more importantly i've got that

01:27:59.820 --> 01:28:09.740
nice combination but you know it's these kind of limp-risted attacks that are happening all the

01:28:09.740 --> 01:28:17.020
time now and we're just not going to look backwards we're not going to look backwards in the cave

01:28:17.100 --> 01:28:20.380
we're not going to listen to the people saying hey wait for us

01:28:23.500 --> 01:28:32.140
we're out our flashlights are out pointed out we are climbing out we are actually probably

01:28:32.140 --> 01:28:39.500
outside of the hole helping other people out we're not climbing back in the cave

01:28:39.580 --> 01:28:48.220
let's see if there's any more for her let's see any more for her perhaps by engaging in this

01:28:48.220 --> 01:28:53.980
horizontal gene transfer mediated by extracellular vesicles so with that i'd like to thank all of

01:28:53.980 --> 01:28:57.740
the members of my group and particularly the people who were the most hands-on with this work

01:28:57.740 --> 01:29:02.380
so sam lakresti was the postdoc who looked at some of our initial charged helper-lifted work

01:29:02.380 --> 01:29:06.060
in the spleen and lungs and then the bulk of the work i showed you today was performed by

01:29:06.060 --> 01:29:11.420
jillian melamed who so this is jillian and this is sam and then our collaborator george

01:29:11.420 --> 01:29:14.940
get us who's at the university of pitzburg he's been a huge help he's a pancreatic surgeon and was

01:29:14.940 --> 01:29:19.820
able to assist us with some of our experiments um so uh then i'll just mention that i had the

01:29:19.820 --> 01:29:24.700
privilege of giving a ted talk a couple of years ago so if any of you want to see a lay version of

01:29:24.700 --> 01:29:29.100
some of what i've described here you can find that they're called fatballs for the purposes of

01:29:29.100 --> 01:29:35.420
uh psychom to lay audiences and then oh my gosh for the purposes of science communication they call

01:29:35.420 --> 01:29:43.020
them fatballs we almost should really look that that thing up right i i almost have to look at that

01:29:43.020 --> 01:29:51.580
that talk up um because you know it's going to be even worse than this um anyway uh who's the funders

01:29:52.300 --> 01:29:58.220
oh DARPA that's nice oh that's sweet isn't that nice then i age in DARPA good good good i mean

01:29:58.300 --> 01:30:06.700
what else you know what else what else could it be what else could it be it could only be that

01:30:09.260 --> 01:30:14.140
ladies and gentlemen sometime in 2019 they started telling us a story about a lab leak

01:30:14.140 --> 01:30:19.500
bat cave zoanosis maybe it came from a bat cave maybe it come from a laboratory maybe it came from

01:30:19.500 --> 01:30:24.140
the stitching done in the laboratory maybe they took it to the market after they sold animals

01:30:24.140 --> 01:30:30.220
there it doesn't matter this multi-colored rainbow of RNA covered the world the last three

01:30:30.220 --> 01:30:35.740
years and there is an illusion of consensus about this that the EUA and lockdowns were a bad idea

01:30:36.460 --> 01:30:41.340
but millions of people were killed by this novel virus and millions more were saved from it

01:30:41.900 --> 01:30:46.220
we should focus on regulating gain of function viruses because that's almost certainly where this

01:30:46.220 --> 01:30:55.020
came from and this faith in the fidelity of PCR and in the the lack of relevance of the

01:30:55.020 --> 01:31:03.260
protocols this is what we need to dismiss because the faith is a lie it was a conflated background

01:31:03.260 --> 01:31:14.460
signal or conflated background signals as my uh my my the clown car behind me said you know it's

01:31:14.460 --> 01:31:21.900
all clones now it wasn't all clones a year ago but it's all clones now the only real debate is

01:31:21.900 --> 01:31:29.420
whether clones spread or not which of course we've known that that's then the debate all along

01:31:29.420 --> 01:31:33.180
but these children are just catching up ladies and gentlemen so we're not going to look back

01:31:33.180 --> 01:31:35.980
we're not going to worry about it we're going to keep our arms straight we're going to keep

01:31:35.980 --> 01:31:41.500
our flashlights pointed forward and we are going to keep helping people find the way out

01:31:44.540 --> 01:31:48.460
because we are at a time point where our kids could end up enslaved

01:31:50.060 --> 01:31:55.820
and the way out is not to bug out the way out is not to get a cabin in the woods and don't look

01:31:55.900 --> 01:32:03.900
back or sign up for for Elon Musk satellite internet why would we do that

01:32:06.940 --> 01:32:11.420
I mean I almost feel like I have to start putting my money where my mouth is why would I do that when

01:32:11.420 --> 01:32:19.500
I could just take over Pittsburgh when everybody in Pittsburgh knows this immunology why would I

01:32:19.580 --> 01:32:26.620
have to leave when everybody at your church knows this immunology why would we need to leave

01:32:28.860 --> 01:32:33.580
when everybody knows this biology why would we need to leave

01:32:38.140 --> 01:32:43.580
making an underground network of bad of good guys is not going to solve the problem

01:32:43.580 --> 01:32:51.340
burning down the whole system is not going to solve the problem it's not fine if this whole

01:32:51.340 --> 01:32:58.780
thing falls apart because our kids were taught bad morals it's time for the adults to put their

01:32:58.780 --> 01:33:05.420
pants on and do the work that they should have been doing for the last 20 years it's time for

01:33:05.420 --> 01:33:12.620
people like you and me in our 50s to start doing the things that we should have been doing that our

01:33:12.620 --> 01:33:16.380
parents should have been doing but didn't do because we left it to Mitch McConnell

01:33:17.660 --> 01:33:21.580
and we left it to Nancy Pelosi and we left it to Joe Biden

01:33:25.820 --> 01:33:32.380
my dad could be president right now if he wanted to for the last 40 years but he certainly could have

01:33:32.380 --> 01:33:38.940
been a senator he certainly could have been a representative and he certainly would have had

01:33:38.940 --> 01:33:41.260
a hell of a lot better than some of the people that we've had

01:33:43.660 --> 01:33:47.900
it's a little weird talking from that way from Wisconsin because we did have Russ Feingold when

01:33:47.900 --> 01:33:52.220
I was a kid and when my dad would have been a senator and so that would have been a ridiculous

01:33:52.220 --> 01:33:56.620
person to run against because Russ Feingold was the last good guy we've had in Wisconsin

01:33:58.540 --> 01:34:03.580
I don't know about the the the young guy though he's pretty good Gallagher seems like a good guy

01:34:03.580 --> 01:34:07.500
stop all transfections and healthy humans please ladies and gentlemen because they are trying to

01:34:07.500 --> 01:34:12.460
eliminate the control group by any means necessary I don't know if this was a very good stream or

01:34:12.460 --> 01:34:19.180
not but I thought it was really important to show you how how far the assumptions have gone this is

01:34:19.180 --> 01:34:27.420
totally gone from niche to mainstream and that niche to mainstream is a lie because intramuscular

01:34:27.420 --> 01:34:31.820
injection of any combination of substances with the intent of augmenting the immune system is dumb

01:34:32.380 --> 01:34:38.940
and specifically transfection in healthy humans is criminally negligent viruses are not pattern

01:34:38.940 --> 01:34:46.220
integrity neither are exosomes neither are extracellular vesicles neither are lipid nanoparticles

01:34:46.220 --> 01:34:52.780
filled with mRNA none of them are patterned integrity and they all basically behave roughly the same

01:34:54.380 --> 01:34:59.260
let's just start to get this once you start to get this we're gonna get them we're gonna get them

01:34:59.260 --> 01:35:03.500
we're gonna win I assure you the book's not even out yet

01:35:06.220 --> 01:35:09.340
I know I sound like a broken record but man oh man

01:35:11.100 --> 01:35:12.620
holy p-values Batman

01:35:13.260 --> 01:35:15.260
hmm

01:35:18.700 --> 01:35:21.020
thanks guys I'll see you again tomorrow

01:35:21.020 --> 01:35:24.460
it's friday gotta keep working

01:35:42.620 --> 01:35:44.620
you

01:36:04.300 --> 01:36:09.820
are you from Wisconsin I'm from cadat up by Chippewa Falls good to see you thanks for joining

01:36:09.820 --> 01:36:12.460
see you tomorrow