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WEBVTT
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You schedule for 16 minutes next is going on French British Italian Japanese television
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People everywhere are starting to listen to him. It's embarrassing
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And everybody knows when dry ice mixes with water it makes a real spooky fog show them Scooby
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Scooby Lou
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Good evening ladies and gentlemen this is legal and biological I resisted slow noise information brief brought to you by a biologist it is the 25th of October 2023. Thank you for joining me
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As usual tonight we are trying to break this limited spectrum of debate and this brilliant discussion within it
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And we're trying to turn it around a little bit I hope we're starting to become successful to a certain extent on that regard
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And I hope I'm starting to arm you with some of the basic arguments that you can take to your Thanksgiving dinner table
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It's it's going to be a long slog though we're not going to win this year or we're not going to win next year
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This may be the battle of our lifetime
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Because it is not a matter of what's true that counts but is what a matter is perceived to be true
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And I'm afraid that there has been a very concerted effort over many years to make sure that what is perceived to be true is indeed not the case
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It's not true at all
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And so that's where this you know don't take the bait on social media comes from
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They are they are controlling us by our urges and leading us by our noses
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And we have been fooled into solving this mystery about a gain of function virus that escaped or was released from somewhere in Wuhan, China
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And who's responsible for covering it up who funded it who lied about it
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And this is all one great big hoax
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But by accepting the challenge of solving it we have accepted its premises
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codified in the many books that have been released and will continue to be released
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Intramuscular injection of any combination of substances with the intent of augmenting the immune system is dumb
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And transfection is not immunization
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There is an illusion of consensus that has been created by people on the TV and behind the scenes people that purport to be
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dissidents and purport to be mainstream
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And I think the best way to describe what is being done to us at the moment
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Is to describe it as a sort of faith, a faith that is being protected by all these people
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It is a faith in a novel virus
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It is a faith in that millions have died
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And millions have been saved or could have been saved depending on which narrative you choose
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They could be saved by different things
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Gain of function is a real thing and a virus will come again
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And that's basically although these people have this wonderful diverse opinion
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And all these diverse opinions about what the most important thing to consider is
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None of them will challenge the tenets of this faith, none of them
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And when they are challenged to address any of the parts of the faith they walk around it
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All of them
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Because again it is not a matter of what it is true that counts
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But a matter of what is perceived to be true and their spectacular commitment to lies makes it very hard to see through
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Because it creates an illusion of consensus, a bunch of people
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A bunch of people that all agree about this one thing right here
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And if they all agree about this story and they all agree about this faith
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Then even though they seem to argue with one another, the show goes on
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And we are now about to move into a new phase of the show
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Where another aspect of the bifurcation is going to be brought together
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So first they split us up on pre-existing fault lines of political socio-economic division
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Based on this lab leak or natural virus narrative
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And now they are going to slowly bring us together
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With regard to the conclusion that some of the things that people said about the shots might have been correct
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I want to call your attention to the last couple of days of shows
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Because there were some pretty good home run shows with regard to Zuckerberg and Chan
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And the Huberman Show
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Talking about really how, sorry, how we are at this stage in our timeline
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When gathering the data now seems to be the imperative
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And so you can hear it all around the world, you can hear it from all these people all the time
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It is to get the data
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And so that's what Zuckerberg and Chan were talking about
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And what Huberman was seemed to be almost submitting to their superiority
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In terms of their vision and foresight into what shall come in the transgenic and trans-human future
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It was pretty disturbing but it's definitely worth watching
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And the reason why it's worth watching is because remember that Huberman is now part of this
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hierarchy of social media icons that includes Joe Rogan and Lex Friedman
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And Jordan Peterson and Brett Weinstein and Sam Cedar and Tim Poole
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And the list is endless basically
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And I have the feeling that eventually this guy Kevin McCurnan is going to go into that ecosystem
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And circulate this same claim
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Maybe he'll go on Joe Rogan next
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But a couple days ago he was on a CHD program with my colleague Brian Hooker and Mary Holland, the President
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And so I thought it would be useful to listen to this just to see what he presents
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And how he presents it
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And then I have a couple alternative videos that I wanted to watch
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Afterward from somebody else that you're kind of familiar with
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We might only watch one depending on how it ends up panning out
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So let's go into this first
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You can hear that my voice still needs quite a bit of rest
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There's still some what I would call loose material on my vocal cords or in my voice box
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That occasionally get in the way of breathing
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They also occasionally make my voice less projecting
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So I am working on getting a doctor's appointment
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Don't need to type or send a lot of emails or anything like that
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I'm definitely going to take care of my voice as soon as I can
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Because I think in the long term it might be good to have these vocal cords intact
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So let's get out of here and let's play this one
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I hope it's not too loud
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We're going to go a little forward here
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Oh, we're going to go a little forward here
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Powerful speakers like Bearish Arab
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Good morning children's health defense today is Tuesday October 24th
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And we have a very exciting guest with us today
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Kevin McCurnan, scientist who's going to be talking with us about the DNA contamination
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That's been discovered in COVID-19 vaccines
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Pfizer's but also others will be joined by our chief science officer Brian Hooker
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And we will be talking with Kevin
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Part of the context for this show is an article that defender published on Friday last week
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Regarding the fact that Health Canada, the main health agency in that country
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Has acknowledged the DNA contamination in Pfizer's COVID-19 shots
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This is the first time that a government has acknowledged this research
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This is very important because it suggests that now governments are on notice that they have to do something about this
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What Canada has said so far is they've looked at this and believed that the benefits still outweigh the risk
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But without any comprehension of the risks that seems rather specious
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It's our privilege to have Kevin here with us to talk specifically about his research
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Really one of the most dramatic elements of this is that inside this DNA plasmid contamination
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Our sequences from Simeon virus 40
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SB 40 was brought into the human population through the oral polio vaccine back in the 1950s
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Ironically today is world polio day
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And not in any way to diminish the significance of polio as a worldwide disease 50s
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Ironically today is
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World polio day
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And not in any way to diminish the significance of polio as a worldwide disease
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But the Simeon virus 40 now has robust science behind it
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Since the 1970s
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Proving that there's a very strong association between Simeon virus 40 and many forms of cancer and other diseases
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So with that, I'm very happy to go over to our conversation with Kevin McCurnan and Dr. Brian Hooker
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Welcome Dr. Kevin McCurnan and Dr. Brian Hooker
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I'm really thrilled to have both of you here with us
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So Brian, you're of course our science director here at Children's Health Defense
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On Kevin, you have an incredibly impressive background in science
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Would you just give us the quick highlights so that our viewers know how extensive your scientific credentials are?
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Certainly, well, I guess I'll shoot myself in the foot and tell you I dropped up a PhD program
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So I never got my doctorate
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But I have been working in the genomics field for 25 years now
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I started on the Human Genome Project down at with Eric Lander down at the White Institute at MIT
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Was managing the research and development team there through the scale up of the Human Genome Project
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And then after that spun a bunch of companies at least Adjunct Court is one company we spun out of MIT
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That built magnetic DNA purification tools which are made to play role in the story
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And we also built some PCR tests there and had a genome center
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That company got acquired by Beckman Coulter
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And then we spun another company out called Adjunct Court Personal Genomics
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That built the solid sequencer and that one got acquired by Applied Biosystems
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And I worked with Applied Biosystems for five years
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Building various DNA sequencers including some semiconductor systems
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So I'd have done some clinical sequencing
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We did a, they had a clean lab for a while that was doing sequencing of epilepsy and mitochondrial disease kids
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And that's kind of where I first ran into a lot of parents telling me about vaccine injuries
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And then we went into the cannabis arena where we were sequencing cannabis genomes
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Because many of the epileptic parents were looking for safe and effective cannabidiol
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Which was helping with seizures
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So we got interested in that field and somehow I ended up here sequencing a vaccine by mistake
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And found something that people seemed to be interested in
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So it's a long winding road to where I am now
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So tell us about this study that you did
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Where I think you were using these vials of the Pfizer and Moderna vaccines as controls
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Is that right? And you've stumbled on an incredible important finding
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Yeah, so we were doing, we're trying to sort out the pathology of a viroid
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That's devastating the cannabis field
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So we were doing RNA sequencing and the pipeline broke
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So if I wrote is a naked piece of RNA that is infectious in itself, it doesn't have any protein code around it
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So you can synthesize these and actually put them into plants and they create some RNA interference
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And there's some pathology that results from this
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So they don't affect mammals but they infect plants and they can be devastating
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And it's probably knocking down the yields in plants like 40% in this industry
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So everyone's trying to understand this 256 letter piece of sequence
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That's a pathology in plants at least in the cannabis plant right now
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So when we were sequencing the RNA of the cannabis genome to see what was happening when it got infected
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We started getting all this sequencing data back that didn't look like it was concentrated on genes
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And that's a sign that your RNA purification system might be broken
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So the way to solve that and figure that out is to spike in a pharmaceutical grade RNA
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To see if you find out where it's broken
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And I figured, well, these are probably pharmaceutical grade
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If they're injected into people, I'll use one of those
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It has a poly-A tag on it that should stick to our magnetic beads
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And it should tell us if we have an RNA problem or something else is wrong
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But I didn't expect to get out of the experiment was the contaminant that I then was pregnant with
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To tell the world about that, okay, it worked as a control
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It taught us that we had a DNA problem in our RNA sequencing pipeline
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But now I see there's a plasmid in here that I can't hide from
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And I've got to put it public as quickly as I can, as responsibly as I can
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And so we chose to do that by releasing all of these really rapid sub-stack articles
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Because you just couldn't see this getting through the peer review process in a timely manner given the political nature of it right now
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I'm ignorant, I'm not a scientist
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Walk us back a little bit, explain to our viewers what is a plasmid
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What did you find here, what does that mean for us?
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So when the clinical trials, I want to be clear, this is mostly pertaining to Pfizer
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We sequence Pfizer and Moderna, but there's different background to them
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So Pfizer's trial started by generating, you need to make this RNA
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In order to make this RNA, you need to feed a DNA template to read the RNA from
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So it's called an in vitro transcription reaction
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You present an RNA polymerase with a piece of DNA and it starts making RNA off of it
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It's kind of like, you know, it's the ink for your Xerox machine, if you will
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So they started the clinical trial with DNA that was amplified with PCR
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Which is really clean DNA, because when you amplify it, it raises the amount of DNA from background, a million full
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So there's no residual background, you get a really clean piece of DNA that you can make your RNA from
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That was what the trial was run out, it's called process one
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Resif Levy and Josh Goodscow have a good paper on this and the BMJ
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Then after the trial was done, they did a debate and switch and they changed the manufacturing process for scale-up
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By taking that piece of DNA that they use that they PCR'd and uses a template in process one
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They plugged it into a bacterial clasmid with such a circular piece of DNA
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That allows something that allows a bug like E. coli to replicate it every 30 minutes
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That means they can have an infinite supply of their DNA
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They just have to keep growing the E. coli day-to-day and they don't ever have to use PCR again
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So it's a real massive cost reduction for them
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But it comes with some additional risk is that you now have this DNA being replicated in the E. coli
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And it's not good to inject people with E. coli, so you have to get the DNA out of E. coli
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And the process of getting that DNA out of E. coli comes with inherent contaminants that weren't in the original trial
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The plasmid DNA is one of them, which is a large 7,800 base pair piece of DNA
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And there's also the potential for endotoxin to come through from the E. coli
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So there's a material difference between the trial and what people actually got
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And that's an important part of the story that everyone needs to know
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Now what we're trying to do is figure out what is the consequence of this plasmid DNA being in there
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They knew it was there, they tried to get rid of it by chewing it up with an enzyme
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But they didn't get rid of it completely, they got it halfway chewed up
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Why didn't they get rid of it completely?
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I mean, they use an enzyme called DNase and DNase breaks down DNA
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Why wouldn't that completely eliminate it? Two questions, why wouldn't that completely eliminate it?
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And why didn't FDA approve both processes?
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They're both a process for the proof of principle as well as the process for production
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Or were they involved in the second part?
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So I'll answer the second part first, which is that there was some discussion in the EMA
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I don't know what's happened at the FDA because we have less authority there
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There's some information at the EMA that I'm superimposing on the FDA in Health Canada
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Because I think similar things may occur there
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But at the EMA, they had an equivalency study that they were supposed to do
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Measuring 252 patients done with process 1 and process 2
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And as best we can tell that data was never matured and was never required for release
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They asked of it, but when Pfizer couldn't produce it, they kind of looked the other way
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So Josh has a good write up on that on Twitter
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And I'll point you to his work and Retsus Levy's work on this
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But your first question, which is why isn't the DNase killing this?
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It comes down to I think two reasons
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One, the way that they're measuring what's there has some blind spots
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And the second thing is they probably didn't anticipate that the modifications they made to the RNA
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Inhibit the DNase from doing its job
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So when they do this in vitro transcription reaction
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And they make this RNA, they put in a different nucleotide
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Notice N1 nucleosuduyridine
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So this altered nucleotide is actually what really got the attention of the Nobel Prize
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They put in a different nucleotide so that the RNA was less labile to an RNA's L that's in the human genome
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So the human body makes RNases that destroy RNA
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You know, the way RNA behaves is like your DNA, your DNA is like your hard drive
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Your RNA is like the task manager of all the programs that are opening and closing off that hard drive
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So the cell needs to have a system to not only turn a gene on, but to turn it off
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If it can't turn it off, then you have a problem
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So the way a lot of these get turned off is there are RNases that make sure that when a gene is expressed
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It's only expressed for a certain period of time that gets decayed
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But they put in this other base that stops that process from happening
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So that the RNA doesn't degrade, it's red or yes
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They put in something that turned off the off switch, is that correct?
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Yes, the RNA is harder to degrade
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And they wanted that so they ensured they got production of spike protein long enough to matter
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And there's a big debate as to whether it's too long right now
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Because we're finding this RNA stick around for way too long
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They thought it was only 48 hours, people can sequence out of plasma 28 days later, it's in breast milk now
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It's really a big train wreck in my opinion, they didn't need that
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But because of that base, that base also is published to radically change the melting temperature of DNA
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That means that it's much stickier, it's much harder to peel apart from DNA
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I think Colin Parr has a paper on this showing, if you just put four of these nucleotides into 25
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It raises the temperature 9C, the melting temperature, that's an enormous melting temperature
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For four bases of these things, yeah
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So that means that this RNA is extraordinarily sticky
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And that means it's very likely that it's making RNA DNA hybrid
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That when the RNA polymerase is copying the RNA off the DNA
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What you end up with is a triple helix, you end up with RNA kind of tangled up with DNA
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And a nucleus doesn't know how to get rid of the DNA in that context
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And this is really evident actually in Moderna's process
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Moderna, if you look at our paper, there's a hundredfold more spike DNA contamination than the plasma DNA
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The backbone that doesn't have any RNA similarity
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So that's a real clear set sign that the nucleus can destroy the DNA that doesn't have any complementary to RNA
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But it can't destroy the DNA that has complementary to the RNA that they're making
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So there's something I'd try to get rid of the DNA in that context
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And this is really evident actually in Moderna's process
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Moderna, if you look at our paper, there's a hundredfold more spike DNA contamination than the plasma DNA
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The backbone that doesn't have any RNA similarity
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So that's a real clear set sign that the nucleus can destroy the DNA that doesn't have any complementary
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to RNA, but it can't destroy the DNA that has complementary to the RNA that they're making
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So there's something I think they didn't see and anticipate because they changed this base
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They didn't realize the enzymes they typically used to get rid of this contaminant are no longer functional
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And so they now have to probably engineer different enzymes for this
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And DNase XT is a good idea, maybe T5, there's a host of these nucleases that might do a better job at this
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But I think with the Warp Speed program they didn't have time to really investigate this
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So that's one reason why the DNA is still there, there's a second reason
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The tools that you use to measure this differ based on the size of the DNA that's around
28:06.540 --> 28:15.540
So if you use something like barometry, this is a tool that uses a dye that is an intercalating dye that binds to like the minor groove of DNA
28:16.540 --> 28:20.540
These tools will measure DNA as small as like 5 to 10 bases
28:21.540 --> 28:25.540
It just has to be complementary at room temperature, that can be a 10 base pair piece of DNA
28:26.540 --> 28:29.540
You can get some cybergreen signal from it, a ribo green signal from
28:30.540 --> 28:33.540
QPCR needs at least 100 bases to amplify
28:34.540 --> 28:36.540
So all the DNA that's smaller than 100 bases, it can't see
28:37.540 --> 28:42.540
So they're using QPCR to monitor the DNA, they're using forometry to measure the RNA
28:43.540 --> 28:48.540
They're kind of playing some games there because they want to get really high RNA numbers and really low DNA numbers
28:49.540 --> 28:55.540
The EMA regulations aren't really a fixed amount of DNA, they're a ratio of how much RNA you have to how much DNA
28:56.540 --> 28:59.540
They're using two different processes to measure the DNA and the RNA
29:00.540 --> 29:06.540
But if I understand you correctly, they could be using one process for both or they could use both processes for both
29:07.540 --> 29:08.540
Absolutely, in fact
29:09.540 --> 29:17.540
That's absolutely right and I think anyone who's familiar with these bench tools knows the fact that they're deviating this is a game
29:18.540 --> 29:22.540
Because they had to make PCR primers to measure the spike DNA
29:23.540 --> 29:25.540
And all they have to do is change the polymerase to measure the RNA
29:26.540 --> 29:31.540
And they didn't do that, they opted to go get a whole other assay with a different instrument, with a different
29:32.540 --> 29:36.540
Forometry based readout to measure the RNA, they bent over backwards to measure the RNA differently
29:37.540 --> 29:42.540
They already had all the primers and tools, they needed to measure it with the PCR assay, they're using to measure the DNA
29:43.540 --> 29:45.540
You just swap the polymerase out and you get the answer the same day
29:46.540 --> 29:48.540
You did suggest gamesmanship, is that correct?
29:49.540 --> 29:50.540
And tend to deceive
29:51.540 --> 29:53.540
And tend to deceive, okay, got it
29:54.540 --> 29:58.540
And this data that you uncovered has been replicated around the world, is that right?
29:59.540 --> 30:04.540
Yes, many labs have now, so we put the primers public on our sub stack and in preprints
30:05.540 --> 30:08.540
And now people can just order those from IDT and make their own primers
30:09.540 --> 30:13.540
We have shipped Oslo primer lots that we have here when people didn't want to wait for IDT to remake these
30:14.540 --> 30:20.540
It can take IDT maybe a couple weeks sometimes to make these, so when people urgently want them, we'll ship them vials of our primers
30:21.540 --> 30:26.540
So Phillip Bockholz has confirmed this work by using our primers down in South Carolina
30:27.540 --> 30:30.540
He also went on to do Oxford Nanopore sequencing to confirm our work
30:31.540 --> 30:35.540
Just not to trust what we told him was working, he was doing what our primers were doing, he said alright
30:36.540 --> 30:38.540
Your primers clearly give me signal on my vaccine lots
30:39.540 --> 30:43.540
I'm now going to sequence them and make sure I can find the sequences of your primers inside my vials
30:44.540 --> 30:49.540
And he went and did that and confirmed that the DNA that he actually has in his vials matches the primer sequences we gave him
30:52.540 --> 30:56.540
Dr. Sin Lee did this at Milford molecular was saying our sequencing
30:56.540 --> 31:01.540
And he was doing what we were doing, we were doing what we were doing, we were doing what we were doing
31:02.540 --> 31:07.540
We were doing what we were doing, we were doing what we were doing, we were doing what we were doing
31:08.540 --> 31:11.540
Your primers clearly give me signal on my vaccine lots
31:12.540 --> 31:16.540
I'm now going to sequence them and make sure I can find the sequences of your primers inside my vials
31:17.540 --> 31:22.540
And he went and did that and confirmed that the DNA that he actually has in his vials matches the primer sequences we gave him
31:23.540 --> 31:29.540
I find that a very strange statement because why would you look for the primer sequences in the vial?
31:31.540 --> 31:36.540
If you're using nanopore, why wouldn't you just get all the sequences out of the vial?
31:38.540 --> 31:41.540
If you're using nanopore, I don't even know why you need to look what
31:45.540 --> 31:50.540
I don't know, the primers are supposed to be a very tiny probe for a longer sequence
31:52.540 --> 32:05.540
So I don't know how confirming that the primers are in the vial is any different than just confirming that there's DNA in the vial using nanopore without using his primers
32:08.540 --> 32:19.540
Or does he just mean that like as an extra control the actual primer sequence is actually in the bottle along with all the extended sequence that comes along with it, I assume?
32:20.540 --> 32:25.540
It seems like a weird statement, but you know, I'm not a molecular biologist. Maybe it makes more sense to somebody like Kevin
32:27.540 --> 32:32.540
Dr. Lynn, Dr. Sin Lee did this at Milford Molecular with Sanger sequencing
32:33.540 --> 32:40.540
He amplified, he made his own primers and he amplified, he emplied some large fragments to like 366 base pair of fragments to show that there's bigger fragments in there
32:41.540 --> 32:44.540
And Sanger sequenced those to prove that it's in fact in the vials
32:45.540 --> 32:53.540
And now the most recent study, I heard of one in Germany, I don't have a date of one in Germany, but Bridget Koenig claims to have found it in four vials out there as well
32:54.540 --> 33:08.540
And so what I'm interested in is the argument that I see forming here is PCR can find in theory a single molecule of DNA
33:09.540 --> 33:25.540
And so PCR may be able to find a very tiny amount of DNA which is lower than the agreement said
33:27.540 --> 33:35.540
And if we are essentially just saying, yeah, there's DNA in the vial and Pfizer can say, well, yeah, I guess there is some DNA in the vial but it's not too much
33:36.540 --> 33:41.540
Or they can say, well, yeah, but there's DNA in that stuff too and there's DNA in that stuff too
33:42.540 --> 33:49.540
So what difference does it make if there's a little DNA in this stuff? I mean, I understand the argument here that this shouldn't be there but
33:51.540 --> 34:02.540
We are being tempted to jump on this as if it's the magic answer to why everything went wrong and how we can now stick the knife in
34:03.540 --> 34:16.540
And we're putting all of our eggs in the basket of Kevin McCurnan that he's right that his measurements of vials are right
34:17.540 --> 34:31.540
And that nobody's gonna debunk this in a couple weeks by saying that, well, his primers weren't very specific or his PCR reaction doesn't isn't up to snuff because of this reason or because of that reason
34:33.540 --> 34:42.540
We have to be very, very careful here because there's a million reasons not to think that regular old transfection
34:43.540 --> 34:47.540
Regular old transfection was not a good idea now what
34:49.540 --> 34:51.540
This is a compounding problem
34:52.540 --> 35:01.540
And it's not being explained as a compounding problem although I did catch him a couple pages ago saying that the RNA stays around as a result of the
35:02.540 --> 35:09.540
N1 methyl pseudo uridine whenever the chemical alteration is and that he said that's a big train wreck
35:11.540 --> 35:14.540
Now I want you to think very carefully about this because
35:18.540 --> 35:27.540
It should really be a sum total story about what's wrong with transfection in healthy humans but even the
35:28.540 --> 35:37.540
Problem of the chemical alteration of the RNA which he came on my stream twice to talk about has almost completely been left out of this narrative
35:39.540 --> 35:42.540
Except characterized as a pretty big train wreck and we'll move on
35:48.540 --> 35:51.540
And there's a reason for that because this is a play
35:52.540 --> 35:58.540
And we have to be very careful about what the play is and who the bad guys are or who the people who know what the you know
35:58.540 --> 36:01.540
It could be that Kevin is just trying to do his best
36:02.540 --> 36:04.540
You know he was just trying just needed a
36:05.540 --> 36:07.540
Apolly a RNA
36:08.540 --> 36:11.540
Control to troubleshoot his problem
36:12.540 --> 36:15.540
And lucky for him somebody sent him a couple vials of
36:17.540 --> 36:19.540
Vaccine without ice buckets
36:20.540 --> 36:26.540
And he decided to use it as an RNA control which meant that it was going to get sequenced
36:27.540 --> 36:31.540
And as a result he found the plasmid
36:32.540 --> 36:37.540
And so he feels obligated to tell everybody I mean unfortunately you know he didn't mean to do it
36:40.540 --> 36:44.540
He's not an anti-vaxxer he just happened to find the DNA there
36:45.540 --> 36:51.540
So he feels the obligation to report it he did it pre-print because you know I mean how long is it going to take to go through peer review?
36:54.540 --> 36:59.540
But the RNA was chemically altered and codon optimized and that's a complete train wreck by the way
37:00.540 --> 37:02.540
I heard it
37:03.540 --> 37:07.540
There's a group in Japan Hiroshi, Arkawa I think maybe from Lincoln's name
37:08.540 --> 37:13.540
But they've been doing some work on this as well they've reassembled our data and been looking at some PCR protocols
37:14.540 --> 37:20.540
But the most recent one is out of David Speakers work out in Ontario where he's got the largest study to date
37:21.540 --> 37:27.540
He went through 27 vials and he even did some XBB 1.5s and those still have the DNA in them
37:29.540 --> 37:33.540
Now there's two different methods that we used in the paper with David just to try to emulate what Pfizer's doing
37:34.540 --> 37:38.540
As we measured it with QPCR in which case the DNA is under the limit on everything he looked at
37:39.540 --> 37:41.540
A couple of them are getting really close to the line
37:42.540 --> 37:44.540
That limit is somewhat arbitrary and we'll touch on that
37:45.540 --> 37:48.540
Then he also measured it with fluorometry to show that they're like a hundred foot over the line if you pick a different tool
37:49.540 --> 37:54.540
To really emphasize that this game of cherry picking different methods is a racket
37:55.540 --> 37:59.540
And that you can get vastly different numbers if you measure this thing with different tools
38:01.540 --> 38:07.540
But I think the interesting part of David's study is they took the vaccine lots sorted them based on DNA quantity
38:08.540 --> 38:16.540
And then Jessica Rose dug in to VAERS and showed that there are higher adverse events reported in VAERS
38:17.540 --> 38:19.540
The lots that have higher amounts of DNA
38:20.540 --> 38:22.540
It's a small data set, there's a lot of confounders there
38:23.540 --> 38:28.540
It's really just a hypothesis, we have to study more lots to make sure that there aren't other confounders that are skewing that association
38:29.540 --> 38:31.540
But it does seem to line up with Philips data
38:31.540 --> 38:35.540
He has numbers that are over the limit and have high adverse events
38:35.540 --> 38:37.540
We had numbers over the limit that have high adverse events
38:38.540 --> 38:43.540
And there's another lot that was recorded in some EMA documentation
38:44.540 --> 38:49.540
FL 0007 that has really high adverse events and has really high DNA as well
38:50.540 --> 38:54.540
So there's a couple other pieces of data that aren't in our paper because they were done at other laboratories
38:55.540 --> 38:59.540
That reconfirm at least with Pfizer more DNA is trending with more adverse events
39:00.540 --> 39:02.540
We're not seeing that with Moderna, which is interesting
39:03.540 --> 39:07.540
The correlation seems to go the other direction there and they are doing a better job getting rid of it
39:08.540 --> 39:10.540
They're probably at a log scale lower amounts of DNA
39:11.540 --> 39:15.540
So they may be below the amount that matters and something else is driving their adverse events
39:16.540 --> 39:22.540
We've found and confirmed in several different labs including Phil Buckholt's labs and Sinley's labs
39:23.540 --> 39:26.540
You've confirmed the presence of double-stranded DNA
39:27.540 --> 39:31.540
And sizable quantities, I mean we're talking about nanogram per milligram quantities
39:32.540 --> 39:35.540
Or hundreds of nanogram per milligram quantities of DNA
39:36.540 --> 39:41.540
First of all, what are the implications of just having double-stranded DNA in those vials
39:42.540 --> 39:46.540
And medically and then second of all, what is in that DNA?
39:47.540 --> 39:49.540
I mean, what is hiding in that DNA?
39:50.540 --> 39:52.540
You know, what elements do we need to be concerned about?
39:53.540 --> 39:58.540
Well, hiding is a good point because I do think there's been some intent to deceive here as well
39:59.540 --> 40:03.540
So, particularly on Pfizer's behalf, if you were to take the DNA sequence
40:04.540 --> 40:06.540
Which apparently they did give the sequence to regulators
40:07.540 --> 40:09.540
But they only annotated certain pieces of it and not others
40:10.540 --> 40:15.540
And that's very bizarre because if you take their sequence and plug it into a standard software tool like snap gene
40:16.540 --> 40:17.540
It will annotate everything
40:17.540 --> 40:22.540
So someone had to actually go and delete these annotations and then can something to the regulators
40:23.540 --> 40:25.540
And the piece that they deleted, I think, is the most controversial piece
40:26.540 --> 40:31.540
It's this SV40 promoter that is known to have a nuclear targeting sequence in this
40:32.540 --> 40:36.540
This is a tandem repeat of 72 bases, about 144 bases in size
40:37.540 --> 40:40.540
That binds transcription factors and drives any DNA attached to it into the nucleus
40:41.540 --> 40:44.540
This is in the answer of the SV40 promoter
40:44.540 --> 40:53.540
SV40 was used in the SV40 Ori, the promoter, and but they never reported the enhancer's presence, is that correct?
40:54.540 --> 40:56.540
They didn't report any of the SV40 components
40:57.540 --> 40:59.540
In fact, I can pull up what they did report here
41:00.540 --> 41:02.540
What you see on the right is what they presented to the EMA
41:03.540 --> 41:04.540
I suspect this is what went to Health Canada as well
41:05.540 --> 41:07.540
And there's somewhat shocked by this from the most recent email I saw from them
41:08.540 --> 41:13.540
But you'll notice it annotates the spike protein, the Ori, the kenamycin gene
41:14.540 --> 41:19.540
It has this five base pair cut site down here that linearizes the plasma
41:20.540 --> 41:21.540
A couple other small pieces
41:22.540 --> 41:25.540
If you take their sequence and just shove it into something known as snap gene
41:26.540 --> 41:28.540
It annotates all the stuff automatically over here
41:29.540 --> 41:30.540
It's SV40 just pops out
41:31.540 --> 41:33.540
I didn't find SV40, snap gene found it
41:34.540 --> 41:35.540
I'm going to pull this back
41:36.540 --> 41:41.540
So on the right, the Ori and the Kan are, and the S protein explained to us
41:42.540 --> 41:44.540
What is that showing us on the right?
41:45.540 --> 41:49.540
And then what did they have to take out to get to what you showed us through snap chain on the left?
41:50.540 --> 41:53.540
Okay, so the bacterial origin of replication is here in blue
41:54.540 --> 41:57.540
So when you put this in a coli, it will double with the coli
41:58.540 --> 42:00.540
It probably runs the copy number to 50 to 100 copies in the cell
42:01.540 --> 42:02.540
And then the cells double over 30 minutes
42:03.540 --> 42:04.540
So it's a great Xerox machine for DNA
42:05.540 --> 42:08.540
But to make that happen in a coli, you have to put a kenamycin resistance gene in there
42:09.540 --> 42:11.540
So that only the coli cells that have the plasma survive
42:12.540 --> 42:13.540
That way you knock out all the background
42:14.540 --> 42:15.540
So this is the kenamycin gene
42:16.540 --> 42:18.540
Now this kenamycin gene won't work on its own
42:19.540 --> 42:20.540
It needs a promoter that they've materially omitted here
42:21.540 --> 42:22.540
Oh, interesting
42:23.540 --> 42:24.540
That's missing
42:25.540 --> 42:26.540
The graph on the right seems very strange
42:27.540 --> 42:28.540
Because that kenamycin wouldn't work without a promoter
42:30.540 --> 42:31.540
Correct
42:31.540 --> 42:33.540
The other thing about the SV40 promoter is it is active in mammalian cells
42:34.540 --> 42:36.540
And you really don't want mammalian promoters in any injectable
42:37.540 --> 42:39.540
They don't need this because they have
42:40.540 --> 42:42.540
If you look very carefully here
42:43.540 --> 42:46.540
There's also an AMP-R promoter that's kind of obscured over here in the left
42:47.540 --> 42:49.540
That's what Moderna uses the drive to kenamycin gene
42:50.540 --> 42:52.540
Pfizer has it too, they just happen to also have this mammalian promoter
42:53.540 --> 42:54.540
That is superfluous and shouldn't be there
42:55.540 --> 42:57.540
And they know it because they deleted it from the annotation
42:58.540 --> 42:59.540
That's an intent to deceive, they actually
43:00.540 --> 43:01.540
I believe so
43:02.540 --> 43:04.540
Because any annotation tool that annotated this plasma
43:05.540 --> 43:06.540
That got down to T7 promoters
43:07.540 --> 43:08.540
It found the bacterial origin
43:09.540 --> 43:11.540
It found, I think this F1 origin down here
43:12.540 --> 43:13.540
It would have found the SV40 origin
43:15.540 --> 43:17.540
So this was deleted, this was deleted
43:18.540 --> 43:22.540
Let's just do a little background gentlemen on SV40
43:23.540 --> 43:25.540
Maybe Brian, can you give us a little bit of background in the
43:26.540 --> 43:28.540
Vaccine context of what SV40 really is
43:30.540 --> 43:32.540
And Kevin, correct me if I'm wrong
43:33.540 --> 43:41.540
But the SV40, Simeon Virus 40, was an artifact of the polio vaccine
43:42.540 --> 43:44.540
The oral, the live polio vaccine
43:46.540 --> 43:48.540
In the 1950s and 1960s
43:49.540 --> 43:53.540
And it is oncogenic SV40 itself
43:54.540 --> 43:59.540
As the virus is associated with certain tumors, certain forms of cancer
44:00.540 --> 44:02.540
Certain aggressive forms of cancer
44:03.540 --> 44:07.540
And that it was a contaminant in the oral polio vaccine
44:08.540 --> 44:10.540
The live virus polio vaccine for many, many years
44:11.540 --> 44:15.540
And so having these elements, including the SV40 promoter
44:16.540 --> 44:20.540
Would in itself, I believe, would be oncogenic
44:21.540 --> 44:26.540
And then that SV40 element, that 72 base pair element
44:27.540 --> 44:31.540
Has been shown to tie with other oncogenes in vivo
44:32.540 --> 44:36.540
And act as an enhancer, enhances its ability to form cancers
44:38.540 --> 44:40.540
So I'm very new to SV40
44:41.540 --> 44:43.540
I've been learning this just in this last year
44:43.540 --> 44:44.540
So what's going on in the field
44:45.540 --> 44:47.540
Now we don't have the whole SV40 virus, which is 5.2 kilobases
44:48.540 --> 44:51.540
We have about 420 bases or so of it
44:52.540 --> 44:53.540
Which consists of four pieces
44:54.540 --> 44:57.540
We have the SV40 origin, the promoter, the enhancer and the polyase signal
44:58.540 --> 44:59.540
That are in there
45:00.540 --> 45:04.540
In SV40, I think, instructs it to put a polyase signal on a messenger RNA
45:05.540 --> 45:07.540
For some reason, that's sitting in this vector as well
45:08.540 --> 45:09.540
I haven't studied as much in what the polyase signal
45:10.540 --> 45:12.540
Why they need the polyase signal in this vector, that seems to be
45:14.540 --> 45:17.540
I think that's needed, if they want to express these plasmids of a million cells
45:18.540 --> 45:20.540
It's good to have something that puts a polyase signal on it
45:20.540 --> 45:24.540
And so they put that on the F1 origin for other reasons
45:26.540 --> 45:29.540
So that being said, a lot of pushback is, hey, this doesn't have the T antigen
45:30.540 --> 45:34.540
The tumor antigen is what is deemed to be the carcinogen in SV40
45:35.540 --> 45:38.540
And so you guys are conflating SV40 with the virus
45:39.540 --> 45:41.540
You're spreading fear porn and all that
45:42.540 --> 45:46.540
I think an important thing to know is that a large portion of the population
45:47.540 --> 45:49.540
Is SV40 positive from the polio vaccine?
45:50.540 --> 45:51.540
So they presumably can make T antigen
45:52.540 --> 45:53.540
And why is that important?
45:54.540 --> 45:59.540
Well, T antigen is what actually initiates the DNA replication on the SV40 promoter that's in the vaccine
46:00.540 --> 46:02.540
So if a certain part of the population makes T antigen
46:03.540 --> 46:04.540
And you inject them with a lot of these promoters
46:05.540 --> 46:07.540
They're going to have the machinery to turn that promoter on
46:08.540 --> 46:09.540
Wherever it lands
46:10.540 --> 46:11.540
So there's
46:12.540 --> 46:13.540
I want other words
46:14.540 --> 46:20.540
Right, in other words, if you've been vaccinated with the oral polio or the live virus polio vaccine
46:21.540 --> 46:25.540
Then you could have the T antigen already in you
46:27.540 --> 46:29.540
Right, and that's something that I can't really
46:30.540 --> 46:34.540
I think right now we have data here that shows there's a legal problem here
46:35.540 --> 46:37.540
More so than we have evidence of a clinical problem
46:38.540 --> 46:39.540
The clinical problem we still need more data from
46:40.540 --> 46:42.540
We need to find out if this DNA is actually in other people
46:43.540 --> 46:45.540
Post vaccination and people who haven't been vaccinated to see
46:46.540 --> 46:48.540
Is it associated with a lot of this adverse events?
46:49.540 --> 46:50.540
Right now this is just hypothesis generation
46:51.540 --> 46:53.540
We don't we have that. We have a lot of reasons to believe this is a bad idea
46:54.540 --> 46:55.540
They don't need this DNA in there
46:56.540 --> 46:57.540
They didn't tell the regulators about it
46:58.540 --> 46:59.540
And it's inside of an LNP
47:00.540 --> 47:02.540
And it's going to get to the nuclear space and the sequence that's in there
47:03.540 --> 47:04.540
All right, so all of that is a train wreck
47:05.540 --> 47:07.540
If you're putting in 200 billion of these molecules per shot
47:08.540 --> 47:09.540
And you're doing them five times a year
47:10.540 --> 47:11.540
I don't know how many times people are taking them
47:12.540 --> 47:13.540
But if you think of your to schedule
47:14.540 --> 47:15.540
You should be past your fifth by now, right?
47:16.540 --> 47:18.540
So there's a cumulative dosing problem here
47:19.540 --> 47:21.540
There's a high number of these fragments in there
47:22.540 --> 47:24.540
Even though the nanograms might seem low
47:25.540 --> 47:27.540
The fragmentation of them makes them like buckshot
47:28.540 --> 47:30.540
And makes them much more potent as integration tools
47:31.540 --> 47:33.540
Because you have more active ends of DNA
47:34.540 --> 47:36.540
It's the ends of the DNA that have phosphates and hydroxyls
47:37.540 --> 47:38.540
That make them sticky
47:39.540 --> 47:41.540
Those are kind of like the Lego pieces of DNA, if you will
47:42.540 --> 47:44.540
So you'll see an FDA documentation on guidance documents
47:45.540 --> 47:47.540
So look at DNA that they base these nanogram limits
47:48.540 --> 47:49.540
Based on genomic DNA
47:50.540 --> 47:52.540
Ten nanograms of genomic DNA might be like twelve hundred copies of DNA
47:53.540 --> 47:54.540
But we're dealing with really small pieces
47:55.540 --> 47:56.540
Which means we have hundreds of billions of pieces
47:58.540 --> 48:00.540
And they even allude to the fact that if you were dealing with not
48:01.540 --> 48:02.540
The million cell contamination
48:03.540 --> 48:04.540
Which would be three giga-based genomes
48:05.540 --> 48:06.540
But you're dealing with viruses
48:07.540 --> 48:08.540
Well then the copy number is so damn high
48:09.540 --> 48:11.540
That you might need ventigram or adigram limits
48:12.540 --> 48:13.540
On the amount of DNA that could be around
48:14.540 --> 48:16.540
There's other guidance documents that also speak to the fact that
48:17.540 --> 48:18.540
The two hundred base paired limit is
48:19.540 --> 48:21.540
Maybe not really pertinent if you're dealing with promoters
48:22.540 --> 48:23.540
Maybe it should be down at seven bases
48:24.540 --> 48:26.540
Because seven bases could integrate and cause problems
48:27.540 --> 48:30.540
Even in like in a VDJ circumstance with certain parts of the genome
48:31.540 --> 48:33.540
So there are guidance documents
48:35.540 --> 48:37.540
And they put out guidance documents before LNPs were around saying
48:38.540 --> 48:39.540
We think there's going to be a million cell DNA
48:40.540 --> 48:41.540
We can tolerate this much of it
48:42.540 --> 48:43.540
Based on this copy number
48:44.540 --> 48:45.540
Based on us not knowing much about it
48:45.540 --> 48:47.540
But the moment you start getting into high copy number contaminants
48:48.540 --> 48:49.540
That have bioactive elements to them
48:50.540 --> 48:51.540
In their inside LNPs
48:52.540 --> 48:53.540
The whole game changes
48:54.540 --> 48:55.540
And it's really astounding
48:56.540 --> 48:58.540
You know when you when you look at these numbers
48:59.540 --> 49:01.540
It's really astounding
49:02.540 --> 49:04.540
When you look at these genomic insertion events
49:06.540 --> 49:08.540
And I've done genetic engineering before
49:09.540 --> 49:13.540
Primarily in genetically modified plants and bacteria
49:15.540 --> 49:17.540
It's like you're going to Vegas
49:18.540 --> 49:19.540
You're looking for the one in the million event
49:20.540 --> 49:22.540
But there are enough
49:23.540 --> 49:25.540
Aaron strands of DNA around there
49:26.540 --> 49:28.540
For that to actually happen, is that correct?
49:29.540 --> 49:31.540
Yeah, I mean Philip Buckholt put up an interesting paper
49:32.540 --> 49:33.540
And his Twitter recently about the rate
49:34.540 --> 49:35.540
When you do the million transfection like this
49:36.540 --> 49:37.540
The rate of integrative cells that's stabilized
49:39.540 --> 49:40.540
It was down below seven percent
49:41.540 --> 49:42.540
But seven percent is a huge number
49:43.540 --> 49:44.540
When you're dealing with billions of LNPs
49:46.540 --> 49:47.540
Right, right, so this is
49:48.540 --> 49:50.540
LNP is lipid nanoparticle, is that right Kevin?
49:51.540 --> 49:52.540
That's right, yeah, so these are
49:53.540 --> 49:54.540
packaged in these LNPs, we know that
49:55.540 --> 49:56.540
That was part of our most recent paper
49:57.540 --> 49:59.540
If you use a nucleation on the vaccine
50:00.540 --> 50:01.540
It won't get rid of the DNA that's there
50:02.540 --> 50:03.540
Because it's protected, it's inside this
50:04.540 --> 50:05.540
lipid nanoparticle
50:06.540 --> 50:08.540
So the guidance documents the FDA have for DNA contamination
50:09.540 --> 50:11.540
They are just ancient relics
50:12.540 --> 50:14.540
They're outdated, they actually started before the NCBIA
50:15.540 --> 50:17.540
Which is this National Childhood Vaccine Injury Act
50:18.540 --> 50:19.540
They were at ten p-grams back then
50:20.540 --> 50:22.540
After that act, they went up a thousand fold
50:23.540 --> 50:24.540
Over the course of ten years
50:25.540 --> 50:27.540
So, we're now at this stage
50:28.540 --> 50:29.540
We've tolerated a thousand times higher
50:30.540 --> 50:31.540
Now we're switching to LNPs
50:32.540 --> 50:33.540
That bring these things directly into cells
50:34.540 --> 50:35.540
With nuclear targeting sequences
50:36.540 --> 50:37.540
We were told that this would not target the nucleus
50:38.540 --> 50:40.540
We were told that this would not enter into the nucleus
50:41.540 --> 50:42.540
Is the nuclear targeting sequence
50:43.540 --> 50:44.540
Is that the SV40 enhancer?
50:46.540 --> 50:47.540
That is, it's actually
50:48.540 --> 50:50.540
It's been published as a great gene therapy tool
50:51.540 --> 50:53.540
Because it's so effective at bringing things to the nucleus in hours
50:54.540 --> 50:55.540
David Dean has great work on this
50:56.540 --> 50:57.540
Canada has just admitted that they found it
50:58.540 --> 50:59.540
It's in the vaccine
51:00.540 --> 51:01.540
So, all these arguments about our vials
51:02.540 --> 51:03.540
Are from dumpsters and everything
51:04.540 --> 51:06.540
Pfizer gave sequence to Health Canada
51:07.540 --> 51:08.540
That has it in there
51:09.540 --> 51:10.540
So, there's no more argument of it being in there
51:11.540 --> 51:12.540
So, let's move to the legal issue
51:13.540 --> 51:14.540
That you flagged for us Kevin
51:15.540 --> 51:16.540
So, Health Canada has acknowledged
51:17.540 --> 51:19.540
That this DNA contamination is in the vials
51:20.540 --> 51:21.540
So, we now have a major government
51:22.540 --> 51:23.540
Of the world acknowledging this
51:24.540 --> 51:25.540
And we published Children's Health
51:26.540 --> 51:27.540
Defense on Friday last week
51:28.540 --> 51:29.540
Published a story quoting Health Canada
51:31.540 --> 51:32.540
Is saying, Health Canada expects sponsors
51:33.540 --> 51:35.540
To identify any biologically functional DNA
51:36.540 --> 51:37.540
Sequences within a plasmid
51:38.540 --> 51:39.540
Such as an SV40 enhancer
51:40.540 --> 51:41.540
At the time of submission
51:42.540 --> 51:43.540
But we know that that didn't happen
51:45.540 --> 51:46.540
In our mind, as a scientist
51:47.540 --> 51:48.540
Who's long been involved in this area
51:49.540 --> 51:51.540
Should that be enough to now force
51:52.540 --> 51:53.540
All of the governments around the world
51:54.540 --> 51:55.540
To take these vials off the market
51:56.540 --> 51:57.540
Until they've been investigated
51:59.540 --> 52:00.540
I would think so if they don't do this
52:01.540 --> 52:02.540
What are they there for?
52:03.540 --> 52:04.540
I mean, this is like every time someone breaks a rule
52:05.540 --> 52:06.540
They just change the rule
52:07.540 --> 52:08.540
I mean, what do we need regulators for
52:09.540 --> 52:11.540
If they're not going to stick to these rules
52:12.540 --> 52:13.540
And guidelines they put forward
52:15.540 --> 52:16.540
In the same breath of that e-mail
52:17.540 --> 52:18.540
I think they reiterated the safe and effective
52:19.540 --> 52:20.540
Psalm, like, okay, we need
52:21.540 --> 52:22.540
But that's nonsense, as people say
52:23.540 --> 52:24.540
They say the risk benefit profile
52:25.540 --> 52:26.540
Continues to support the use
52:27.540 --> 52:29.540
But if they don't know, if they didn't know this
52:30.540 --> 52:31.540
And they don't acknowledge this
52:32.540 --> 52:33.540
Then how could they assess the risk benefit
52:34.540 --> 52:35.540
Profile? That seems just nonsensical
52:36.540 --> 52:37.540
It's circular, it's very circular for them
52:38.540 --> 52:39.540
To state that, you don't actually
52:40.540 --> 52:41.540
I mean an important point to that risk
52:42.540 --> 52:43.540
They waive the genotoxicity studies of the trial
52:44.540 --> 52:46.540
Right, right, right, they don't know that
52:47.540 --> 52:49.540
There's risk because the trials were never done
52:50.540 --> 52:53.540
And how can you get away with it?
52:54.540 --> 52:55.540
It seems like when you look at the
52:56.540 --> 52:57.540
Plasmid submission to the FDA
52:58.540 --> 52:59.540
There are unknown sequences
53:00.540 --> 53:01.540
There are big black boxes
53:02.540 --> 53:04.540
There's a big unknown where the SV40 promoter went
53:05.540 --> 53:07.540
Why did they tolerate this in the first place?
53:08.540 --> 53:12.540
You know, I don't know because there's other things in that sequence
53:13.540 --> 53:15.540
There's other points in that sequence that should have
53:16.540 --> 53:17.540
Wrong alarm bells
53:18.540 --> 53:20.540
If you turn on any sort of ore finding tool
53:21.540 --> 53:23.540
So to paint where the open reading frames are
53:24.540 --> 53:25.540
You can identify where the spike is
53:26.540 --> 53:28.540
But the thing that will blow your mind is that there's an
53:29.540 --> 53:30.540
Orp on the reverse strand of the spike
53:31.540 --> 53:32.540
That is 252 amino acids long
53:34.540 --> 53:35.540
Like that should have been a red flag
53:36.540 --> 53:38.540
So that tells me that no one opened this
53:39.540 --> 53:40.540
In a tool, they got the sequence
53:41.540 --> 53:43.540
And probably just said, pay your user fee
53:44.540 --> 53:45.540
And we'll put it in the file and move on
53:46.540 --> 53:48.540
What an Orp finder does is it looks for open reading frames
53:49.540 --> 53:50.540
And so if you turn it on, it will look for
53:51.540 --> 53:52.540
Star coat-ons and stop coat-ons
53:53.540 --> 53:54.540
And it instantly finds the spike protein
53:56.540 --> 53:57.540
If you ask this to look at
53:59.540 --> 54:01.540
On both strands of the DNA, it will find another Orp
54:02.540 --> 54:03.540
That runs the entire direction
54:04.540 --> 54:05.540
On the other strand of the spike protein
54:07.540 --> 54:08.540
For 1,252 amino acids long
54:09.540 --> 54:11.540
I don't have it visualized here because I've picked up the wrong screen here
54:12.540 --> 54:14.540
But I do have it on my sub-stack and people can see this
54:15.540 --> 54:16.540
Now anyone who's regulating this
54:17.540 --> 54:19.540
Would have, should have, put this into a
54:20.540 --> 54:21.540
Tool-like snap gene to say
54:22.540 --> 54:23.540
Show me what's in this plasma
54:24.540 --> 54:25.540
And it annotates all these pieces for you
54:26.540 --> 54:27.540
And it would have shown you that there is a mysterious
54:28.540 --> 54:30.540
Orp of unknown origin that encodes the entire opposite strand
54:31.540 --> 54:32.540
Of the spike protein
54:34.540 --> 54:36.540
Moderna doesn't have it, the virus doesn't have it
54:37.540 --> 54:39.540
It says Kevin, it's unknown, they don't know what it is
54:40.540 --> 54:42.540
I've blasted this thing against NCBI
54:43.540 --> 54:47.540
The only hits I can find in uniprot are to a gene that's
54:48.540 --> 54:50.540
Or protein that's in silk and in collagen
54:51.540 --> 54:53.540
And some other fibroin thing
54:55.540 --> 54:56.540
I don't know
54:59.540 --> 55:01.540
I guess I'm a little confused what he's saying
55:02.540 --> 55:03.540
He's saying that the
55:04.540 --> 55:06.540
On the complementary strand
55:07.540 --> 55:08.540
To the spike protein
55:10.540 --> 55:12.540
There is another open reading frame
55:14.540 --> 55:16.540
And the AI tool
55:17.540 --> 55:19.540
Recognizes that an open reading frame
55:20.540 --> 55:22.540
Because it finds the start codons
55:24.540 --> 55:25.540
My guess is
55:26.540 --> 55:27.540
Is that he is like
55:28.540 --> 55:30.540
Letting this software tool
55:31.540 --> 55:33.540
Tell him that there's a
55:34.540 --> 55:36.540
Origin of replication there
55:37.540 --> 55:39.540
And it's an open reading frame
55:40.540 --> 55:42.540
And then he's just saying, so I look and I try to find it
55:43.540 --> 55:44.540
But I can't find it anywhere
55:45.540 --> 55:46.540
Maybe because it isn't anything
55:48.540 --> 55:50.540
And it just has a start codon or something in the front
55:51.540 --> 55:53.540
That makes that automatic search system
55:54.540 --> 55:56.540
Identify it as an open reading frame
55:58.540 --> 56:00.540
I'm skeptical of that call right there
56:04.540 --> 56:06.540
I'm skeptical of that that doesn't really
56:07.540 --> 56:09.540
Sit right with me for some reason
56:10.540 --> 56:12.540
Just because this AI program or this
56:13.540 --> 56:15.540
This software tool
56:16.540 --> 56:19.540
Locates what it says is an open reading frame within
56:20.540 --> 56:23.540
With an origin of replication doesn't necessarily mean
56:24.540 --> 56:26.540
That that's going to be functional
56:28.540 --> 56:30.540
And in any other context
56:31.540 --> 56:33.540
I mean it's
56:34.540 --> 56:36.540
There's so much I've taken notes and I just want to keep it going
56:37.540 --> 56:39.540
And then I'll go back all the way to the beginning
56:40.540 --> 56:41.540
What this does
56:42.540 --> 56:44.540
But I know that this is an artifact of our codon optimization
56:45.540 --> 56:46.540
That should not be there and is a massive risk
56:47.540 --> 56:48.540
And they should get rid of it
56:49.540 --> 56:51.540
Because it's actually it's a massive
56:52.540 --> 56:54.540
Sedoco puzzle for someone to actually figure this out
56:55.540 --> 56:57.540
Like how do you get a 1,273 amino acid
56:58.540 --> 56:59.540
Open reading frame in strand
57:00.540 --> 57:02.540
And how do you get one on the other
57:03.540 --> 57:05.540
That doesn't have a stop codon anywhere
57:06.540 --> 57:07.540
That's scary
57:08.540 --> 57:09.540
What are the implications of having that
57:10.540 --> 57:11.540
And so the definition then it seems
57:12.540 --> 57:14.540
Of an open reading frame is just a very long sequence
57:15.540 --> 57:16.540
Without a stop codon
57:17.540 --> 57:19.540
Okay, maybe that's extraordinary
57:20.540 --> 57:23.540
Or maybe he's just making us ask the wrong question
57:24.540 --> 57:25.540
Like where did this come from?
57:26.540 --> 57:29.540
Or if you know that or if going into the opposite direction
57:30.540 --> 57:34.540
You know and then and then injecting that into humans
57:36.540 --> 57:37.540
I don't know if it's going to get expressed
57:38.540 --> 57:39.540
That's the thing
57:39.540 --> 57:40.540
Sure, yeah
57:41.540 --> 57:43.540
A waste pair of answer is a bidirectional promoter
57:44.540 --> 57:46.540
So presumably it makes our need both directions
57:47.540 --> 57:49.540
If for some reason it spans this poly A region
57:50.540 --> 57:52.540
In the plasmid it could go and start making RNA
57:53.540 --> 57:55.540
Over that unknown, that mysterious orb
57:56.540 --> 57:57.540
Good, good
57:58.540 --> 57:59.540
I don't know what that's going to do in the cell
58:00.540 --> 58:01.540
It could, there's a COSAC consensus sequence there
58:02.540 --> 58:03.540
It's very difficult to informatically screen
58:04.540 --> 58:05.540
For internal ribosomal entry sites
58:06.540 --> 58:07.540
So I can't tell you that ribosomes
58:08.540 --> 58:09.540
Definitely get to translate this thing
58:10.540 --> 58:11.540
But I can certainly tell you that if I were a regulator
58:12.540 --> 58:13.540
I would tell them to get rid of it
58:14.540 --> 58:15.540
Because it's risk with no gain
58:17.540 --> 58:18.540
Sorry
58:19.540 --> 58:20.540
There's no way they did
58:21.540 --> 58:23.540
If they looked at this, this would have run out to them
58:24.540 --> 58:25.540
It's clear to me, they didn't look
58:26.540 --> 58:28.540
I think they collected their user fee and put the thing in the file
58:29.540 --> 58:31.540
So the regulators were asleep on the job
58:32.540 --> 58:33.540
It sounds like what you're saying
58:34.540 --> 58:35.540
Because they didn't catch SV40
58:36.540 --> 58:37.540
That they could have easily caught through snap chain
58:38.540 --> 58:40.540
And they also didn't tell us about this open reading frame
58:41.540 --> 58:45.540
1220, 237 pair bases, base pairs
58:46.540 --> 58:47.540
Is that right?
58:48.540 --> 58:50.540
The open reading frame is 1273 for the spike
58:51.540 --> 58:53.540
And on the reverse side, there's like a 1252 amino acid
58:55.540 --> 58:56.540
Open reading frame
58:57.540 --> 58:58.540
And I could see someone writing an off
58:59.540 --> 59:00.540
Being like, oh, it's messenger RNA, it's going to be single stranded
59:01.540 --> 59:02.540
The reverse strand won't be there, what it's an RNA form
59:03.540 --> 59:05.540
But they didn't anticipate the DNA is going to come with it
59:06.540 --> 59:07.540
And so now we have both strands there
59:08.540 --> 59:10.540
And the other strand codes for something
59:11.540 --> 59:13.540
So if any of this stuff integrates, it's likely to be an open reading frame
59:14.540 --> 59:16.540
Of a foreign peptide that your immune system's not going to like
59:18.540 --> 59:22.540
The point is, it's a very open reading frame rich plasmid
59:24.540 --> 59:28.540
We've got millions and millions of lipid nanoparticles
59:29.540 --> 59:32.540
That are floating around physiologically
59:33.540 --> 59:36.540
And basically, and the lipid nanoparticles contain
59:38.540 --> 59:40.540
What appears to be transfection soup
59:41.540 --> 59:42.540
How do people not get transfected by this?
59:44.540 --> 59:46.540
I think the numbers are probably in the billions of trillions
59:47.540 --> 59:48.540
From what I've read on the L and P's
59:49.540 --> 59:50.540
A large number, but
59:52.540 --> 59:54.540
And yeah, they probably have the RNA and the DNA in them
59:55.540 --> 59:57.540
From the measurements we've made, they're packaged
59:58.540 --> 01:00:00.540
And they're the clearest resistant and they're ending up in cells
01:00:01.540 --> 01:00:03.540
What a lot of people push back is like, okay, any cell that gets transfected
01:00:04.540 --> 01:00:06.540
Is going to die, so who cares if this cargo's in there
01:00:08.540 --> 01:00:11.540
It's true because we see the spike protein and the spike sequence
01:00:13.540 --> 01:00:15.540
Persisting in least 28 days, people have sequenced
01:00:16.540 --> 01:00:18.540
mRNA or DNA, we don't know which one it was
01:00:19.540 --> 01:00:21.540
But they've got sequence of the vaccine 28 days later in plasmid
01:00:22.540 --> 01:00:24.540
They have found it in breast milk five or seven days later
01:00:25.540 --> 01:00:27.540
The protein itself, they have found Patterson
01:00:28.540 --> 01:00:30.540
Founded four months later on exosomes, I think
01:00:31.540 --> 01:00:34.540
Sorry, that was Bansal, Patterson found it like I think 200 days later in macrophages
01:00:35.540 --> 01:00:40.540
So cool thing is persisting, and I don't think every cell that gets transformed
01:00:41.540 --> 01:00:45.540
Is 100% killed instantly, there's something going on where people can't clear this
01:00:46.540 --> 01:00:48.540
And maybe it's hitting immune-privileged cells
01:00:49.540 --> 01:00:51.540
And that's why it sits around forever
01:00:52.540 --> 01:00:54.540
So I think it is a risk, if there's DNA floating around
01:00:55.540 --> 01:00:56.540
It's going to add to the persistence of this
01:00:57.540 --> 01:01:01.540
Because it could integrate and continually express these other foreign peptides
01:01:02.540 --> 01:01:06.540
Exactly, and what about, you know, what about the implications?
01:01:07.540 --> 01:01:10.540
When I think of DNA disrepair, I think of cancer
01:01:11.540 --> 01:01:14.540
And so, you know, I get very, very concerned about that
01:01:15.540 --> 01:01:19.540
Just not, you know, not specifically on
01:01:20.540 --> 01:01:22.540
Oh, we're making people into, you know,
01:01:23.540 --> 01:01:26.540
Genomically stable spike protein production factories
01:01:27.540 --> 01:01:32.540
But also just the other bits and pieces of DNA that are getting integrated into the genome
01:01:33.540 --> 01:01:34.540
And, you know, what are they doing?
01:01:35.540 --> 01:01:38.540
What are they enhancing, and what are they, you know, or what are they silencing?
01:01:40.540 --> 01:01:46.540
Well, what made me nervous is when we saw, so Phillips' work, I think, showed a couple billion of the
01:01:47.540 --> 01:01:51.540
Of the amplicons from just PCR, so PCR measures 100 base per amplicon
01:01:52.540 --> 01:01:54.540
And we have one that actually targets CSV 40 promoter
01:01:55.540 --> 01:01:58.540
So there's a billion copies of just that region in every injection
01:01:59.540 --> 01:02:02.540
That's kind of, that's carbon bombing a genome with a billion promoters
01:02:03.540 --> 01:02:05.540
Where are those lands, and what efficiency is an open debate
01:02:06.540 --> 01:02:10.540
But wherever they land, they're going to be active promoters of a million cells
01:02:11.540 --> 01:02:13.540
So I think that alone is an issue
01:02:14.540 --> 01:02:17.540
Because you're just dropping these things that make RNA into the genome randomly
01:02:18.540 --> 01:02:22.540
And if you happen to put one on a protoanco gene, or if, you know, right, right, a host of issues
01:02:23.540 --> 01:02:28.540
Now, there's other areas that genes that if you hyper express them, they can drive to sell excess cell growth
01:02:29.540 --> 01:02:32.540
They call them protoanco genes, and so it's an act of promoter for that
01:02:33.540 --> 01:02:34.540
Turns out it's not good
01:02:35.540 --> 01:02:38.540
The other thing that can happen is you can break a gene that slows down cancer, like P53
01:02:39.540 --> 01:02:41.540
P53 and Braca are these DNA repair enzymes
01:02:42.540 --> 01:02:44.540
And if you happen to put a different part of the plasma inside of those
01:02:45.540 --> 01:02:47.540
It could, it could disable those genes
01:02:48.540 --> 01:02:51.540
Then you don't have, you don't have this repair mechanism that you need
01:02:52.540 --> 01:02:55.540
Now, most people have two copies of all these genes
01:02:56.540 --> 01:02:58.540
So many people, you break one of them, maybe you're okay
01:02:59.540 --> 01:03:01.540
But there are subsets of people that have Braca mutations and P53 mutations
01:03:02.540 --> 01:03:05.540
And they're haploid, so they have like one bad copy and one good copy
01:03:06.540 --> 01:03:08.540
You come in with this vaccine, you can knock out the only other good copy
01:03:09.540 --> 01:03:14.540
And so this is a whole host of sort of rare genetics that you have
01:03:15.540 --> 01:03:18.540
I'm not sure how it inserts specifically to knock out a single enzyme
01:03:19.540 --> 01:03:21.540
So precisely among the entire human genome
01:03:22.540 --> 01:03:26.540
Wherever this small fragment of DNA is going to integrate
01:03:27.540 --> 01:03:30.540
If it's going to disrupt the Braca gene or disrupt the P53 gene
01:03:31.540 --> 01:03:35.540
It's going to have to insert exactly there and whatever chromosome it's in
01:03:36.540 --> 01:03:39.540
And then unless you have injected a pregnant woman
01:03:40.540 --> 01:03:44.540
And it's inserting into a developing fetus, which would be devastating
01:03:45.540 --> 01:03:50.540
Is it integrating into the genome of a liver cell that's going to die next week?
01:03:51.540 --> 01:03:58.540
Is it integrating into the cells of your kidney wall or you know what what
01:03:59.540 --> 01:04:02.540
And what happens if it does
01:04:03.540 --> 01:04:10.540
Again, I am trying to be devil's advocate here and try to emphasize
01:04:11.540 --> 01:04:17.540
That all these hypothetical scenarios where this DNA could in theory integrate
01:04:18.540 --> 01:04:22.540
And disrupt a gene, cause cancer, do whatever
01:04:23.540 --> 01:04:26.540
Are very low probability events
01:04:27.540 --> 01:04:36.540
Whereas the destruction of tissues which are expressing foreign proteins driven by this chemically modified RNA
01:04:37.540 --> 01:04:39.540
Not messenger RNA, but modified RNA
01:04:42.540 --> 01:04:44.540
Those consequences are going to be devastating
01:04:45.540 --> 01:04:50.540
Those consequences can include clotting and autoimmunity and the list is long
01:04:51.540 --> 01:04:54.540
And so if we're going to focus on what this DNA could do
01:04:55.540 --> 01:05:02.540
If it integrates and knocks out a cancer gene or the promoter integrates right next to an oncogene
01:05:03.540 --> 01:05:08.540
We're talking about what happens if I put all of my chips on 30 black
01:05:09.540 --> 01:05:13.540
And the ball hits 30 black, well then you're a millionaire
01:05:14.540 --> 01:05:18.540
And if some of this DNA goes into your grandma's
01:05:19.540 --> 01:05:25.540
You know already developing cancer and and juices it a little bit boy she could be dead
01:05:28.540 --> 01:05:33.540
But that kind of glosses over the fact that well if you transfect your grandma
01:05:34.540 --> 01:05:36.540
There's a million reasons why she might die
01:05:37.540 --> 01:05:40.540
And it has nothing to do with what the DNA integrates
01:05:41.540 --> 01:05:48.540
And it feels very much after he just you know casually went past the idea that the RNA is found everywhere
01:05:49.540 --> 01:05:52.540
And the spike protein is found everywhere and it doesn't go away like we thought it was
01:05:53.540 --> 01:05:54.540
And that's a train wreck
01:05:56.540 --> 01:05:58.540
We're focusing off a lot on this DNA then aren't we
01:06:01.540 --> 01:06:05.540
To consider this and perhaps why this may not be something you'd be seeing in all patients
01:06:06.540 --> 01:06:12.540
And there's another dimension of like which vaccine lots have more of this versus less of this like the Schmeling paper you look at has
01:06:13.540 --> 01:06:17.540
4% of the vaccine lots having a majority of the adverse events
01:06:18.540 --> 01:06:22.540
So we have a lot of VED diagrams here of things to consider
01:06:23.540 --> 01:06:25.540
There's a lot of people who probably took these and don't have any harm at all
01:06:26.540 --> 01:06:33.540
There's maybe a subset of people that take these bad lots that in fact have some genetic reason why they're more susceptible to the harm than others
01:06:34.540 --> 01:06:36.540
So you see there's a lot a little slippery language there
01:06:37.540 --> 01:06:40.540
There's probably a lot of people who took these vaccines and didn't have any harm at all
01:06:42.540 --> 01:06:48.540
There's probably a lot of people that took these vaccines and there's no harm at all
01:06:50.540 --> 01:06:54.540
There's probably a lot of people who took these vaccines and didn't have any harm at all
01:06:57.540 --> 01:07:00.540
There's probably a lot of people who took these vaccines and didn't have any harm at all
01:07:03.540 --> 01:07:07.540
And you mentioned, I think, to all of us.
01:07:07.540 --> 01:07:11.860
And so this is a whole host of sort of rare genetics
01:07:11.860 --> 01:07:13.060
that you have to consider in this.
01:07:13.060 --> 01:07:15.140
And perhaps why this may not be something you'd
01:07:15.140 --> 01:07:17.660
be seeing in all patients.
01:07:17.660 --> 01:07:20.060
There's another dimension of which vaccine
01:07:20.060 --> 01:07:21.900
lots have more of this versus less of this,
01:07:21.900 --> 01:07:23.300
like the Schmeling paper you look at
01:07:23.300 --> 01:07:27.060
has 4% of the vaccine lots having the majority
01:07:27.060 --> 01:07:28.700
of the adverse events.
01:07:28.700 --> 01:07:32.540
So we have a lot of VED diagrams here of things
01:07:32.540 --> 01:07:33.900
to consider.
01:07:33.900 --> 01:07:35.380
There's a lot of people who probably took these
01:07:35.380 --> 01:07:36.740
and don't have any harm at all.
01:07:36.740 --> 01:07:38.940
Maybe a subset of the people that take these bad lots
01:07:38.940 --> 01:07:42.460
that, in fact, have some genetic reason why they're more
01:07:42.460 --> 01:07:43.940
susceptible to the harm than others.
01:07:43.940 --> 01:07:48.140
Oh, so then even some people are lucky and not genetically
01:07:48.140 --> 01:07:50.620
susceptible to the DNA contamination,
01:07:50.620 --> 01:07:52.940
and they didn't have any problems.
01:07:52.940 --> 01:07:54.820
But then these other losers over there
01:07:54.820 --> 01:07:57.500
who just happened to have the wrong genes,
01:07:57.500 --> 01:08:00.220
they're extra susceptible, right?
01:08:00.260 --> 01:08:03.180
Stop lying.
01:08:03.180 --> 01:08:04.180
Others.
01:08:04.180 --> 01:08:06.260
Kevin, you mentioned, I think, harm at all.
01:08:06.260 --> 01:08:08.380
The majority of the adverse events.
01:08:08.380 --> 01:08:13.420
So we have a lot of VED diagrams here of things to consider.
01:08:13.420 --> 01:08:15.060
There's a lot of people who probably took these
01:08:15.060 --> 01:08:16.300
and don't have any harm at all.
01:08:16.300 --> 01:08:18.620
There's maybe a subset of people that take these bad lots
01:08:18.620 --> 01:08:21.700
that, in fact, have some genetic reason
01:08:21.700 --> 01:08:24.340
why they're more susceptible to the harm than others.
01:08:24.340 --> 01:08:27.500
Kevin, you mentioned, I think, today and in the past
01:08:27.500 --> 01:08:30.700
that this promoter, the SV40 promoter in particular,
01:08:30.700 --> 01:08:32.740
is used in gene therapy.
01:08:32.740 --> 01:08:35.940
And yet this was not reviewed as a gene therapy.
01:08:35.940 --> 01:08:37.460
It was reviewed as a vaccine.
01:08:37.460 --> 01:08:40.540
Is that an issue in your group?
01:08:40.540 --> 01:08:43.780
Yeah, I think that is actually a very serious legal issue.
01:08:43.780 --> 01:08:46.500
This here is the SV40 enhancer that
01:08:46.500 --> 01:08:49.300
is published to bind all of these transcription factors
01:08:49.300 --> 01:08:52.300
and drag this sequence into the nucleus.
01:08:52.300 --> 01:08:54.900
There's two of these copies of these 72 base pair pieces
01:08:54.900 --> 01:08:56.940
of DNA, and this is what they're putting
01:08:56.940 --> 01:09:00.700
in plasmids to get them to do perform gene therapy.
01:09:00.700 --> 01:09:03.620
So the sequence that they omitted
01:09:03.620 --> 01:09:06.460
is a bioactive sequence according to Health Canada,
01:09:06.460 --> 01:09:07.860
and it is used in gene therapy.
01:09:07.860 --> 01:09:09.380
There's just no debate anymore.
01:09:09.380 --> 01:09:12.660
The plasmids that are in there are gene therapy tools,
01:09:12.660 --> 01:09:15.060
and they're injected into beings and people.
01:09:15.060 --> 01:09:18.980
So not only was there no informed consent for anybody,
01:09:18.980 --> 01:09:20.980
and this was emergency news authorization,
01:09:20.980 --> 01:09:24.300
so they weren't by law.
01:09:24.340 --> 01:09:28.180
The question becomes, again, am I cracking yours?
01:09:28.180 --> 01:09:30.380
No, okay, it sounded like I was really loud.
01:09:30.380 --> 01:09:32.180
I don't think I'm actually that loud.
01:09:36.660 --> 01:09:39.700
The important thing to understand here is that
01:09:44.180 --> 01:09:45.020
yeah.
01:09:55.300 --> 01:09:58.300
I just, I, base pair pieces of DNA,
01:09:58.300 --> 01:10:00.300
and this is what they're putting in plasmids
01:10:00.300 --> 01:10:03.300
to get them to do perform gene therapy.
01:10:03.300 --> 01:10:06.300
So the sequence that they omitted
01:10:06.300 --> 01:10:09.300
is a bioactive sequence according to Health Canada,
01:10:09.300 --> 01:10:10.300
and it is used in gene therapy.
01:10:10.300 --> 01:10:12.300
There's just no debate anymore.
01:10:12.300 --> 01:10:15.300
The plasmids that are in there are gene therapy tools.
01:10:15.300 --> 01:10:17.300
And now the way that they assembled the plasmid
01:10:17.300 --> 01:10:19.300
was to look at all the fragments
01:10:19.300 --> 01:10:23.300
and then reassemble them into the plasma sequence.
01:10:24.300 --> 01:10:29.300
They found very few really long sequences of DNA
01:10:29.300 --> 01:10:31.300
because the DNA was digested.
01:10:34.300 --> 01:10:36.300
And so the argument on the other side
01:10:36.300 --> 01:10:39.300
is clearly going to be these fragments are tiny.
01:10:39.300 --> 01:10:41.300
Kevin makes the argument that tiny fragments
01:10:41.300 --> 01:10:45.300
have lots of active sticky ends,
01:10:45.300 --> 01:10:48.300
and so they're more likely to integrate.
01:10:48.300 --> 01:10:51.300
The regulators and other molecular biologists
01:10:51.300 --> 01:10:53.300
will say that the shorter the pieces are,
01:10:53.300 --> 01:10:55.300
the more likely that they won't integrate,
01:10:55.300 --> 01:10:56.300
that they won't be dangerous,
01:10:56.300 --> 01:10:58.300
that they will be cleaned up as noise.
01:11:02.300 --> 01:11:04.300
And so that's how they're going to argue
01:11:04.300 --> 01:11:06.300
that this is not really valid.
01:11:06.300 --> 01:11:08.300
If you use fluorimetry,
01:11:08.300 --> 01:11:10.300
you're finding these little tiny fragments
01:11:10.300 --> 01:11:12.300
that are a few base pairs long.
01:11:12.300 --> 01:11:14.300
I'm getting a GFP signal and claiming
01:11:14.300 --> 01:11:15.300
that's double-stranded DNA,
01:11:15.300 --> 01:11:18.300
but that's really not double-stranded DNA.
01:11:18.300 --> 01:11:20.300
That's not going to make RNA.
01:11:20.300 --> 01:11:23.300
It's not going to make protein.
01:11:23.300 --> 01:11:28.300
And if it integrates, it will be integrating where?
01:11:28.300 --> 01:11:31.300
Into the genome of a cell that's no longer using the genome,
01:11:31.300 --> 01:11:34.300
like an endothelial cell,
01:11:34.300 --> 01:11:36.300
or a liver cell,
01:11:36.300 --> 01:11:39.300
or an already differentiated cell in the body
01:11:39.300 --> 01:11:42.300
that really only uses a very sub-small subset
01:11:42.300 --> 01:11:45.300
of the total genome and its nucleus.
01:11:45.300 --> 01:11:48.300
And so if this small piece of DNA was
01:11:48.300 --> 01:11:50.300
to magically integrate the chances
01:11:50.300 --> 01:11:51.300
of it integrating somewhere
01:11:51.300 --> 01:11:54.300
that will have any impact on that cell,
01:11:54.300 --> 01:11:57.300
it seems to be quite vanishing.
01:11:57.300 --> 01:11:59.300
Certainly not just going to happen
01:11:59.300 --> 01:12:02.300
to stumble on Braco or stumble on P53
01:12:02.300 --> 01:12:04.300
because it's like a magnet for it.
01:12:07.300 --> 01:12:10.300
And so we seem to be creating these, you know,
01:12:10.300 --> 01:12:13.300
worst-case scenario is that it,
01:12:13.300 --> 01:12:15.300
your son drinks some whiskey,
01:12:15.300 --> 01:12:16.300
gets in the car,
01:12:16.300 --> 01:12:18.300
backs across the street,
01:12:18.300 --> 01:12:21.300
crashes into the house across the street.
01:12:21.300 --> 01:12:24.300
That's the worst-case scenario if you leave your son at home.
01:12:24.300 --> 01:12:26.300
The best-case scenario is you watch some Netflix
01:12:26.300 --> 01:12:28.300
and goes to bed on time.
01:12:30.300 --> 01:12:33.300
The best-case scenario or other scenarios
01:12:33.300 --> 01:12:36.300
that eats ice cream and you told him not to.
01:12:36.300 --> 01:12:38.300
But the worst-case scenario is, yeah,
01:12:38.300 --> 01:12:40.300
he drinks half a fifth of whiskey,
01:12:40.300 --> 01:12:41.300
drives the car across the street,
01:12:41.300 --> 01:12:43.300
crashes into the neighbor's house.
01:12:44.300 --> 01:12:46.300
But it's not very likely.
01:12:47.300 --> 01:12:50.300
In fact, I would argue it's vanishingly small,
01:12:50.300 --> 01:12:52.300
the probability that that's going to happen,
01:12:52.300 --> 01:12:54.300
even if I left a bottle of whiskey on the table
01:12:54.300 --> 01:12:57.300
next to the car keys, my son wouldn't do it.
01:12:58.300 --> 01:13:00.300
So it's a pretty bold statement to say
01:13:00.300 --> 01:13:03.300
that all this double-stranded little pieces of DNA
01:13:03.300 --> 01:13:07.300
and so it's highly likely because they were in lipid nanoparticles
01:13:07.300 --> 01:13:09.300
that they'll get into that nucleus
01:13:09.300 --> 01:13:12.300
and they'll interact with the two cancer-controlling enzymes
01:13:12.300 --> 01:13:14.300
called P53 in Braca.
01:13:17.300 --> 01:13:21.300
Why wouldn't they interact with one of the 100,000 other enzymes
01:13:21.300 --> 01:13:23.300
that are present in our cells instead,
01:13:23.300 --> 01:13:26.300
or one of the other 100,000 places
01:13:26.300 --> 01:13:29.300
that it could integrate and do nothing,
01:13:29.300 --> 01:13:32.300
or have no real effect,
01:13:34.300 --> 01:13:36.300
whereas transfection,
01:13:36.300 --> 01:13:38.300
expression of a foreign protein,
01:13:38.300 --> 01:13:40.300
activation of the immune system
01:13:40.300 --> 01:13:42.300
by the expression of a foreign protein,
01:13:42.300 --> 01:13:46.300
and the challenge of the immune system to clear that
01:13:46.300 --> 01:13:50.300
is obviously a non-physiological problem
01:13:50.300 --> 01:13:53.300
that you would not want to challenge a healthy human with,
01:13:53.300 --> 01:13:56.300
but let's focus on this DNA problem.
01:13:58.300 --> 01:14:00.300
That's where we are, ladies and gentlemen.
01:14:00.300 --> 01:14:02.300
That's where we are.
01:14:02.300 --> 01:14:07.300
That is the bamboozlement that's being brought upon us right now.
01:14:09.300 --> 01:14:11.300
Make no mistake about it.
01:14:11.300 --> 01:14:18.300
So it's a very, very nuanced trap
01:14:18.300 --> 01:14:20.300
that we are being lured into,
01:14:20.300 --> 01:14:24.300
and if we're not explicit and very careful
01:14:24.300 --> 01:14:26.300
about how we look at this,
01:14:27.300 --> 01:14:29.300
from the outside,
01:14:29.300 --> 01:14:33.300
from the perspective of people looking at us
01:14:33.300 --> 01:14:35.300
from the outside,
01:14:36.300 --> 01:14:39.300
it will be very easy for us to be brushed away,
01:14:39.300 --> 01:14:40.300
and you'll see in a minute.
01:14:40.300 --> 01:14:41.300
We'll watch the rest of this,
01:14:41.300 --> 01:14:44.300
then we're going to watch some debunk the funk,
01:14:44.300 --> 01:14:46.300
and they're injected into billions of people.
01:14:46.300 --> 01:14:50.300
So not only was there no informed consent for anybody,
01:14:50.300 --> 01:14:52.300
and this was emergency use authorization,
01:14:52.300 --> 01:14:55.300
so they weren't, by law,
01:14:55.300 --> 01:14:58.300
they weren't able to give truly informed consent,
01:14:58.300 --> 01:15:01.300
but it looks like this was a gene therapy,
01:15:01.300 --> 01:15:04.300
and people were not told that this was a gene therapy.
01:15:04.300 --> 01:15:05.300
Is that right?
01:15:05.300 --> 01:15:09.300
That's right, and now they may not have meant for it to be this,
01:15:09.300 --> 01:15:12.300
but they certainly, in my opinion, hit it.
01:15:12.300 --> 01:15:15.300
The fact that that SV-3 region is the only origin missing
01:15:15.300 --> 01:15:19.300
on the vector means whoever ran the annotation program there
01:15:19.300 --> 01:15:21.300
probably had three origins show up,
01:15:21.300 --> 01:15:23.300
the F1, the bacterial, and the SV-40
01:15:23.300 --> 01:15:24.300
and decided to remove the SV-40
01:15:24.300 --> 01:15:26.300
because it was an unpopular name,
01:15:26.300 --> 01:15:28.300
and they knew it was controversial.
01:15:28.300 --> 01:15:30.300
Incredible.
01:15:30.300 --> 01:15:33.300
There's a long literature in mainstream scientific
01:15:33.300 --> 01:15:35.300
journals about SV-40.
01:15:35.300 --> 01:15:36.300
Isn't that right, Brian?
01:15:36.300 --> 01:15:37.300
Absolutely.
01:15:37.300 --> 01:15:40.300
You know, it's such a strong promoter,
01:15:40.300 --> 01:15:42.300
and it's a mammalian active promoter,
01:15:42.300 --> 01:15:45.300
and so you would expect if you put that promoter,
01:15:45.300 --> 01:15:48.300
and especially if you have that 72 base pair
01:15:48.300 --> 01:15:51.300
enhancer region, that you're basically,
01:15:51.300 --> 01:15:55.300
you know, you've got a nuclear localization signal,
01:15:55.300 --> 01:15:57.300
and so that is its job.
01:15:57.300 --> 01:16:01.300
It basically will take a DNA sequence
01:16:01.300 --> 01:16:05.300
behind it, and it will deliver it into the nucleus.
01:16:05.300 --> 01:16:09.300
This is, it's absolutely incredible that this is there.
01:16:09.300 --> 01:16:12.300
It's absolutely incredible that this whole thing
01:16:12.300 --> 01:16:15.300
was hidden from view.
01:16:15.300 --> 01:16:19.300
Wouldn't that raise, you know, again,
01:16:19.300 --> 01:16:22.300
maybe I'm beating a dead horse,
01:16:22.300 --> 01:16:24.300
but just the absence of that information,
01:16:24.300 --> 01:16:27.300
wouldn't that raise some type of red flag
01:16:27.300 --> 01:16:31.300
with the EMA and the FDA?
01:16:31.300 --> 01:16:35.300
You would hope so, that they would feel deceived by this.
01:16:35.300 --> 01:16:36.300
Yeah.
01:16:36.300 --> 01:16:38.300
That this is something that is clearly in the rules
01:16:38.300 --> 01:16:40.300
that you need to declare these things,
01:16:40.300 --> 01:16:41.300
and now they find out, you know,
01:16:41.300 --> 01:16:45.300
years later that they weren't sure this information.
01:16:45.300 --> 01:16:49.300
So I don't know where it leads to.
01:16:49.300 --> 01:16:50.300
Right, right.
01:16:50.300 --> 01:16:53.300
You've been looking at this for quite a while now, Kevin,
01:16:54.300 --> 01:16:58.300
and so, you know, if you don't like the message,
01:16:58.300 --> 01:17:00.300
you shoot the messenger.
01:17:00.300 --> 01:17:03.300
So what's happening with you?
01:17:03.300 --> 01:17:05.300
Oh, well, I've already been character assassinated
01:17:05.300 --> 01:17:07.300
for my choice to get it into the cannabis field,
01:17:07.300 --> 01:17:10.300
so I'm kind of bulletproof from that standpoint.
01:17:10.300 --> 01:17:13.300
It's almost as bad as, you know, looking at vaccines.
01:17:13.300 --> 01:17:16.300
So his skin in the game is that he already threw away
01:17:16.300 --> 01:17:19.300
his career going into the cannabis industry, you know, so,
01:17:19.300 --> 01:17:22.300
I mean,
01:17:22.300 --> 01:17:23.300
he can't lose any.
01:17:23.300 --> 01:17:25.300
He can't be canceled anymore than that.
01:17:25.300 --> 01:17:26.300
In general.
01:17:26.300 --> 01:17:27.300
So yes.
01:17:27.300 --> 01:17:28.300
Yeah.
01:17:28.300 --> 01:17:29.300
Exactly.
01:17:29.300 --> 01:17:31.300
In the past, I want to point out that Kevin generously
01:17:31.300 --> 01:17:34.300
gave us a declaration in the case that we filed against
01:17:34.300 --> 01:17:37.300
coercive PCR testing of children in New York City schools,
01:17:37.300 --> 01:17:40.300
and we're very grateful for that.
01:17:40.300 --> 01:17:41.300
So, yeah.
01:17:41.300 --> 01:17:44.300
So, so you're not worried about the character assassination
01:17:44.300 --> 01:17:46.300
that goes along with this, Kevin?
01:17:46.300 --> 01:17:48.300
No, they already assassinated my character a decade ago
01:17:48.300 --> 01:17:50.300
when I decided to start studying cannabis.
01:17:50.300 --> 01:17:52.300
So they'll continue on that front.
01:17:52.300 --> 01:17:55.300
And yeah, we get harassed on Twitter and all the usual social media
01:17:55.300 --> 01:17:59.300
nonsense, but I don't think this is, I don't think it's very
01:17:59.300 --> 01:18:00.300
effective.
01:18:00.300 --> 01:18:02.300
And oftentimes, I think as a reverse effect,
01:18:02.300 --> 01:18:04.300
as people see who they're attacking.
01:18:04.300 --> 01:18:06.300
And I mean, you can see our preprint on Thursday.
01:18:06.300 --> 01:18:08.300
It's got like 72,000 downloads now,
01:18:08.300 --> 01:18:12.300
probably because a Streisand effect of everyone who's hating on us
01:18:12.300 --> 01:18:13.300
on Twitter.
01:18:13.300 --> 01:18:14.300
So.
01:18:14.300 --> 01:18:17.300
What's your sub stack so that we can have everybody follow?
01:18:18.300 --> 01:18:20.300
It's, it's a named after the count,
01:18:20.300 --> 01:18:22.300
the active compound and catnip.
01:18:22.300 --> 01:18:23.300
I'm a cat person.
01:18:23.300 --> 01:18:25.300
So it's, uh, it's a petalactone.
01:18:25.300 --> 01:18:28.300
Uh, so it's unfortunately really horrible to tell somebody in her
01:18:28.300 --> 01:18:32.300
to spell, but lactone is the last word, but a petalactone.
01:18:32.300 --> 01:18:35.300
If you ever get confused, just look up the active ingredient
01:18:35.300 --> 01:18:38.300
and catnip and it will give you that long winded name.
01:18:38.300 --> 01:18:41.300
I taught people how to take the Pfizer sequence as if they were
01:18:41.300 --> 01:18:44.300
given it as if they worked at the EMA or the health Canada.
01:18:44.300 --> 01:18:47.300
This is the tool that you would probably use to open it up and look
01:18:47.300 --> 01:18:48.300
at it.
01:18:48.300 --> 01:18:49.300
This is called snap gene.
01:18:49.300 --> 01:18:52.300
It's a free tool downloaded, opened the file,
01:18:52.300 --> 01:18:55.300
and it will instantly paint you the SV 40 regions.
01:18:55.300 --> 01:18:59.300
So this shows you that that someone had to go in and actively
01:18:59.300 --> 01:19:02.300
delete this because the standard tools in the industry paint this
01:19:02.300 --> 01:19:03.300
thing.
01:19:03.300 --> 01:19:06.300
So I don't get credit for finding SV 40 snap gene found it.
01:19:06.300 --> 01:19:08.300
It painted it the first time I loaded the sequence in,
01:19:08.300 --> 01:19:11.300
which is why I was really confused to see that it was not in
01:19:11.300 --> 01:19:15.300
Pfizer's plasma map because that told me somebody had to go
01:19:15.300 --> 01:19:16.300
and erase it.
01:19:16.300 --> 01:19:18.300
That's not an oops, I forgot it.
01:19:18.300 --> 01:19:22.300
That's a, I clearly wanted to deceive you type of move.
01:19:22.300 --> 01:19:23.300
Right.
01:19:23.300 --> 01:19:25.300
And this is just a picture of that second origin.
01:19:25.300 --> 01:19:27.300
Oh, I'm sorry, that second open reading.
01:19:27.300 --> 01:19:31.300
It's going in the opposite direction and teaches people how to go
01:19:31.300 --> 01:19:34.300
and look for these yourselves and some of the genes that that
01:19:34.300 --> 01:19:35.300
thing hits.
01:19:35.300 --> 01:19:38.300
They're not really strong hits, but I'm like, this is really weird.
01:19:38.300 --> 01:19:40.300
It says silk protein and silk.
01:19:40.300 --> 01:19:42.300
I'm not really strong hits.
01:19:42.300 --> 01:19:43.300
Stop saying that.
01:19:43.300 --> 01:19:47.300
And, um, and these not a very strong.
01:19:47.300 --> 01:19:50.300
Intervening sequences is SV 40 sequences.
01:19:50.300 --> 01:19:51.300
It's not just you.
01:19:51.300 --> 01:19:53.300
It's health Canada now, right?
01:19:55.300 --> 01:19:59.300
Yeah, they, they, they confirmed in that email that yes,
01:19:59.300 --> 01:20:02.300
we were given the sequence from the plasma, but we were not,
01:20:02.300 --> 01:20:06.300
we're not specifically annotated the SV 40 that was in that sequence.
01:20:06.300 --> 01:20:10.300
They, they annotated all those other pieces and just decided to not tell them
01:20:10.300 --> 01:20:12.300
about the SV 40 in the sequence.
01:20:12.300 --> 01:20:14.300
But they have some sequence to tell.
01:20:14.300 --> 01:20:17.300
A huge focus being a page in there and not telling them that he slips it in there.
01:20:17.300 --> 01:20:19.300
So they have the sequence themselves.
01:20:19.300 --> 01:20:20.300
They could have done it.
01:20:20.300 --> 01:20:23.300
They, they, they can, they can run snap gene just like anybody else.
01:20:23.300 --> 01:20:29.300
In theory, I suspect that they did until we published our work.
01:20:29.300 --> 01:20:30.300
Right.
01:20:30.300 --> 01:20:31.300
Oopsy.
01:20:31.300 --> 01:20:36.300
You've identified for us, Kevin, that, um, that the FDA and, and health Canada
01:20:36.300 --> 01:20:40.300
and the EMA potentially could allege that they were deceived.
01:20:40.300 --> 01:20:44.300
And perhaps they were deceived and that perhaps opens the door for them right now
01:20:44.300 --> 01:20:46.300
to take much more dramatic action.
01:20:46.300 --> 01:20:50.300
I think that's fair because if you look through the volume of data that
01:20:50.300 --> 01:20:55.300
Pfizer's handing over, it is, it's almost this drowned the regulator in materials
01:20:55.300 --> 01:20:57.300
so they can't possibly read it all.
01:20:57.300 --> 01:20:59.300
And that's really easy to do with sequence information.
01:20:59.300 --> 01:21:03.300
You hand them a file of 7,800 bases and unless they have the time that sets
01:21:03.300 --> 01:21:06.300
on a side and say, annotate this and look at this and tell me if there's
01:21:06.300 --> 01:21:07.300
something weird in it.
01:21:07.300 --> 01:21:11.300
They're, they're then also buried in all the PCR data, all the LPS data.
01:21:11.300 --> 01:21:15.300
They, they, they, you know, Pfizer even went out and engineered a new mass spec
01:21:15.300 --> 01:21:19.300
method of DNA sequencing to try to show them that their polyA signals were in,
01:21:19.300 --> 01:21:21.300
in the, in the vaccine were the right length.
01:21:21.300 --> 01:21:25.300
I mean, they did all of this work that I thought was fairly unnecessary and looked
01:21:25.300 --> 01:21:28.300
like a tactic of, of drowning regulators and data.
01:21:28.300 --> 01:21:31.300
That, that's probably what we're hearing here.
01:21:31.300 --> 01:21:32.300
They snowed them.
01:21:32.300 --> 01:21:34.300
Well, this is incredibly enlightening.
01:21:34.300 --> 01:21:37.300
Kevin, thank you so much for taking the time to explain this to us.
01:21:37.300 --> 01:21:41.300
I certainly have a much clearer picture and we can send people to your catnip,
01:21:41.300 --> 01:21:43.300
the pedal act tone.
01:21:43.300 --> 01:21:44.300
Is that right?
01:21:44.300 --> 01:21:48.300
New letter to get all the latest and look at it in greater detail again.
01:21:48.300 --> 01:21:49.300
Thank you both so much.
01:21:49.300 --> 01:21:50.300
Thank you.
01:21:50.300 --> 01:21:51.300
Thank you.
01:21:51.300 --> 01:21:52.300
Thank you.
01:21:52.300 --> 01:21:53.300
Thank you.
01:21:53.300 --> 01:21:54.300
Thank you so much, Kevin.
01:21:54.300 --> 01:21:56.300
And, and we look forward to your further research.
01:21:56.300 --> 01:21:57.300
Thank you for having us.
01:21:57.300 --> 01:21:58.300
Okay.
01:21:58.300 --> 01:22:06.300
So let me just summarize this really quickly and then let me give you my one minute
01:22:06.300 --> 01:22:10.300
summary about why I think we need to be careful about this.
01:22:10.300 --> 01:22:13.300
That was a lot of notes while he really went nuts there.
01:22:13.300 --> 01:22:25.300
So the big thing that seems to really impress Mary and, and Brian is that health
01:22:25.300 --> 01:22:32.300
Canada has decided to acknowledge that the SV40 enhancer and promoter sequences
01:22:32.300 --> 01:22:38.300
are there as evidence of double stranded DNA originating from the plasmid,
01:22:38.300 --> 01:22:44.300
which was used in process two manufacturing.
01:22:44.300 --> 01:22:49.300
Now, I find it a little interesting that Josh Getsko is the guy who kind of led
01:22:49.300 --> 01:22:57.300
the charge on the story of process one versus process two.
01:22:57.300 --> 01:23:01.300
He has been outspoken before about VAERS and other things.
01:23:01.300 --> 01:23:10.300
He seems to have auditioned quite early for participation in this on the team.
01:23:10.300 --> 01:23:14.300
And so being a part of that could mean that he's just a good guy who's been
01:23:15.300 --> 01:23:18.300
vigilant and working hard and pick this ball up and ran with it.
01:23:18.300 --> 01:23:23.300
And I hope that's the case.
01:23:23.300 --> 01:23:30.300
The Vyroid reference was interesting.
01:23:30.300 --> 01:23:35.300
That's naked RNA, which can infect plants.
01:23:35.300 --> 01:23:42.300
He was looking at trying to sequence Vyroids, and he needed an RNA polyA RNA control.
01:23:42.300 --> 01:23:53.300
And as he told me the story or told us the story on John Bodeman's St. Patrick's Day stream,
01:23:53.300 --> 01:23:59.300
he said that he sent out an all call to his network saying,
01:23:59.300 --> 01:24:03.300
hey guys, I need some polyA RNA for a control.
01:24:03.300 --> 01:24:05.300
Can anybody help me out?
01:24:05.300 --> 01:24:11.300
And then some random person sent him a box with three vials of the vaccine in it.
01:24:11.300 --> 01:24:14.300
That's the story that I remember.
01:24:14.300 --> 01:24:23.300
And so these were RNA samples that were not stored at the right temperature, shipped to him.
01:24:23.300 --> 01:24:28.300
And he was able to use them as controls, which also allowed them to get sequenced.
01:24:28.300 --> 01:24:34.300
And that's why we're here because then he found the plasmid DNA there.
01:24:34.300 --> 01:24:39.300
And remember that he would have assembled all kinds of little tiny fragments
01:24:39.300 --> 01:24:42.300
and then figured out that if you lined them up correctly,
01:24:42.300 --> 01:24:49.300
they reassembled into the original plasmid process, too.
01:24:49.300 --> 01:24:53.300
In case you're wondering, that's death on a unicorn there.
01:24:53.300 --> 01:24:59.300
It's for my daughter, kind of. She really likes unicorns.
01:24:59.300 --> 01:25:06.300
So he talked about PCR being used to produce the DNA for process one versus DNA plasmids
01:25:06.300 --> 01:25:09.300
plus bacteria to be used in process two.
01:25:09.300 --> 01:25:16.300
He did mention that the RNA being codon optimized
01:25:16.300 --> 01:25:20.300
and pseudoyuridine chemically altered made it stay around longer,
01:25:20.300 --> 01:25:23.300
was found in breast milk. He dropped a kind of all kinds of anecdotes there
01:25:23.300 --> 01:25:25.300
to finally say that it was a big train wreck.
01:25:25.300 --> 01:25:33.300
But that was about a 30 second, 15 second blip about the fact that the RNA is also bad.
01:25:33.300 --> 01:25:36.300
The RNA is also bad.
01:25:36.300 --> 01:25:44.300
Was briefly there, even though Kevin came on my stream twice in 2021 and 22
01:25:44.300 --> 01:25:51.300
to say many things about why the RNA itself was bad.
01:25:51.300 --> 01:25:58.300
And we know that the RNA could be reverse transcribed to DNA in theory.
01:25:58.300 --> 01:26:00.300
And so then you have DNA anyway.
01:26:00.300 --> 01:26:07.300
So again, we had that report earlier that there are places like in the liver
01:26:07.300 --> 01:26:11.300
where the line one enzyme is present and we can go backwards to DNA.
01:26:11.300 --> 01:26:14.300
And so then where are we? We're kind of in the same place again, right?
01:26:14.300 --> 01:26:22.300
So he talks about fluorometry versus PCR and using that to find double stranded DNA
01:26:22.300 --> 01:26:37.300
versus RNA. Many labs have now used his primers to find SV40 in these shots.
01:26:37.300 --> 01:26:41.300
Buck halter also used nanopore sequencing, but then only to look for his primer
01:26:41.300 --> 01:26:46.300
sequences, at least that's how he said it can't be true, but maybe it is.
01:26:46.300 --> 01:26:52.300
And then Sin Lee also used sanger sequencing to find, I don't think he went
01:26:52.300 --> 01:27:05.300
to look for the whole plasmid, but just for his little promoter sequences again, I think.
01:27:05.300 --> 01:27:11.300
So it's under the QPCR limit, which technically means then again that he didn't find a lot.
01:27:11.300 --> 01:27:14.300
And if you use fluorometry, then you're finding little tiny pieces
01:27:14.300 --> 01:27:19.300
and then you could call that being above the limit, but as he said, they're only concerned
01:27:19.300 --> 01:27:24.300
about longer pieces of DNA, and there's a reason for that.
01:27:24.300 --> 01:27:28.300
So him and Buck halter are making the argument that small pieces of DNA
01:27:28.300 --> 01:27:31.300
all have legatable ends, and so that makes them more dangerous.
01:27:31.300 --> 01:27:38.300
It's like a shotgun or a carpet bombing with the enhancer.
01:27:38.300 --> 01:27:43.300
But technically that's not true, I don't think, unless he's really found the enhancer
01:27:43.300 --> 01:27:49.300
intact, which I'm not really convinced that that's exactly what they found.
01:27:49.300 --> 01:27:55.300
They found lots of fragments that when you use an assembly program, you can find these things again,
01:27:55.300 --> 01:28:02.300
but I don't know how many intact segments of these enhancers and promoters are present.
01:28:02.300 --> 01:28:09.300
And I think that's part of the gray area there that's on purpose.
01:28:09.300 --> 01:28:17.300
And so then he talked a lot about the fact that the guidance documents surrounding these kinds of
01:28:17.300 --> 01:28:24.300
biologics are not up to date, and that the regulators therefore didn't really know how to regulate these things
01:28:24.300 --> 01:28:26.300
because they weren't up to date.
01:28:26.300 --> 01:28:31.300
So on top of the fact that the manufacturers tried to obfuscate what was there and how to look for it
01:28:31.300 --> 01:28:36.300
and whether they looked for it, the regulators themselves were also held back
01:28:36.300 --> 01:28:47.300
by their own out of date guidance documents.
01:28:47.300 --> 01:28:50.300
The genotoxicity studies were waived.
01:28:50.300 --> 01:28:55.300
He says, you know, it's pretty difficult to screen informatically for ribosome initiation sites.
01:28:55.300 --> 01:29:02.300
That's an interesting little slip there.
01:29:02.300 --> 01:29:10.300
And then the actual question is then, are these double-stranded DNA pieces actually integrating or not?
01:29:10.300 --> 01:29:14.300
Where are they integrating, how often, what are the odds, et cetera?
01:29:14.300 --> 01:29:18.300
And he zeroed in on one particular instance.
01:29:18.300 --> 01:29:29.300
And I noticed that this entire talk, this entire talk, this entire line, this entire talk, what did they not mention?
01:29:29.300 --> 01:29:43.300
When is the time when you would be most concerned about integration of genes, integration, or disruption of genes?
01:29:43.300 --> 01:29:48.300
When is the time when you would be most concerned about that?
01:29:48.300 --> 01:29:50.300
Would that be in an old person?
01:29:50.300 --> 01:29:52.300
Would that be in an adult?
01:29:52.300 --> 01:29:56.300
Would that be in a great big giant fat adult?
01:29:56.300 --> 01:29:59.300
Would that be in a teenager?
01:29:59.300 --> 01:30:02.300
What about a person who's already been through puberty?
01:30:02.300 --> 01:30:06.300
What about a pregnant woman with a fetus inside of her?
01:30:06.300 --> 01:30:10.300
Oh!
01:30:10.300 --> 01:30:12.300
So you don't want to mention that?
01:30:12.300 --> 01:30:25.300
You don't want to talk about that at all because gene integration into the fat cells of a 400 pound man who can't walk down the street and is 65 years old is not that dangerous.
01:30:25.300 --> 01:30:38.300
But injecting live-ended DNA with active mammalian promoters into pregnant women, now that might be a problem, ladies and gentlemen, we might need to back the truck up here.
01:30:38.300 --> 01:30:48.300
But of course we haven't mentioned that at all because we don't want to emphasize the part of the narrative which is about the malfeasance, the coercion.
01:30:48.300 --> 01:30:54.300
We want to emphasize the narrative about this ultra-complicated biology stuff.
01:30:54.300 --> 01:30:57.300
Not the really simple stuff.
01:30:57.300 --> 01:31:02.300
Like we didn't need to do this because people were not dying from a spreading respiratory disease.
01:31:02.300 --> 01:31:08.300
They were dying from ventilators and from remdesivir.
01:31:08.300 --> 01:31:12.300
You see where this went? How quickly this went off the rails?
01:31:12.300 --> 01:31:19.300
And it's because it's such a damn shiny object that nobody can stop looking at it.
01:31:19.300 --> 01:31:23.300
But if you understood the biology, it's actually not that shiny, okay?
01:31:23.300 --> 01:31:27.300
It's really not. I've got to get a new notebook here.
01:31:27.300 --> 01:31:32.300
I think that's number six.
01:31:39.300 --> 01:31:43.300
So look, here's the deal. Okay, I'm just going to make a list.
01:31:43.300 --> 01:31:48.300
This work.
01:31:48.300 --> 01:32:07.300
Okay, so first just understand this. Very simple fact, okay?
01:32:07.300 --> 01:32:24.300
Transfection is RNA. Transformation is DNA. If you use these processes to make proteins, you are transfecting or you are transforming your target.
01:32:24.300 --> 01:32:36.300
If you use an adenovirus carrying DNA to express the spike protein in a human, like in the J&J shot, you are transforming human cells.
01:32:36.300 --> 01:32:46.300
If you are using a lipid nanoparticle carrying an RNA to express spike protein in human cells, you are transfecting those cells.
01:32:46.300 --> 01:32:56.300
These two things have been products for sale as various methodologies for decades.
01:32:57.300 --> 01:33:10.300
And in the pandemic, we called these investigative vaccines.
01:33:10.300 --> 01:33:18.300
This is the story so far, okay? We know that transfection is RNA and transformation is DNA used to make proteins.
01:33:18.300 --> 01:33:29.300
And we know that we change the name of these processes, these methodologies without really significantly changing how they work and called them investigative vaccines.
01:33:29.300 --> 01:33:47.300
How do we know that's true? Because Peter Kullis told us that Peter Kullis, the great inventor of the LNP that was used to carry these transfections to our body's cells,
01:33:47.300 --> 01:33:57.300
told us that he burned five postdocs trying to learn how to target the LNP somewhere, and they failed.
01:33:57.300 --> 01:34:11.300
There's no more discussion. What do you need to talk about anymore? You don't need to burn biorum bridles, career anymore, you don't need to cite the Japanese paper, you don't need to cite the Japanese leak document.
01:34:11.300 --> 01:34:25.300
You can just cite the creator of the lipid nanoparticle who got screwed out of the Nobel Prize, who admitted it on camera in 2022.
01:34:25.300 --> 01:34:33.300
Almost in the same presentation that he said when I heard that the Pfizer data came out and was 95% effective, I opened a Scotch.
01:34:34.300 --> 01:34:51.300
Even though I knew in my head the lipid nanoparticle was going all over people's body and we couldn't control where it went and it maybe even went to their brain. But I had a Scotch anyway.
01:34:51.300 --> 01:35:20.300
The transfection in its purest form, so that would be best RNA, super pure, best top shelf LNP.
01:35:21.300 --> 01:35:34.300
And transfection in its purest form, it still doesn't work. It's a bad idea for healthy animals. That's the deal.
01:35:35.300 --> 01:35:42.300
Transfection in its purest form. But this wasn't transfection in its purest form.
01:35:42.300 --> 01:36:04.300
This was transfection with a foreign immunogen with human homology.
01:36:04.300 --> 01:36:22.300
Number one, number two, it was impure RNA that had been codon optimized.
01:36:22.300 --> 01:36:28.300
So that's misfolding.
01:36:28.300 --> 01:36:41.300
And it was also pseudoyuridine, which is premature stop.
01:36:41.300 --> 01:36:51.300
Plus, it's a wobble base, right? So it can be lots of different amino acids that it can code for when it goes through.
01:36:51.300 --> 01:37:03.300
It goes through the ribosome. And the LNP is a question for toxicity.
01:37:03.300 --> 01:37:15.300
And let's see, foreign immunogen, impure RNA, codon optimized, pseudoyuridine, LNP toxicity, protein fragments then, right?
01:37:15.300 --> 01:37:21.300
Because of these two things down here.
01:37:21.300 --> 01:37:39.300
And so even if transfection was in its purest form, super best RNA, super top shelf LNP, you'd still have the problem of you challenging your immune system to tell the difference between self and non-self when there are no signals related to viral infection.
01:37:39.300 --> 01:37:45.300
But then on top of that, you decided to use a foreign immunogen with human homologies.
01:37:45.300 --> 01:37:52.300
You decided to use an impure RNA rather than pure RNA. You decided to codon optimize it, which makes it misfold more.
01:37:52.300 --> 01:38:07.300
You decided to use pseudoyuridine to make it last longer, which also results in a wobble base and also results in premature stop codons, which results in protein fragments with unknown immunogenic quantity qualities.
01:38:07.300 --> 01:38:12.300
Plus the LNP toxicity is a big variable.
01:38:12.300 --> 01:38:22.300
And now on top of all of this, you have cDNA and endotoxin.
01:38:22.300 --> 01:38:36.300
And so the idea is, and I apologize, that my handwriting is very bad when I'm actually looking at the camera in here and I'm not really writing like I am on the other, I mean, just when I take notes, it looks really nice.
01:38:36.300 --> 01:38:39.300
But when you're watching me right, I don't write so well.
01:38:39.300 --> 01:38:52.300
The point is, again, I'm trying to make is that by focusing on the cDNA down here, we are ignoring that transfection in its purest form would suck.
01:38:52.300 --> 01:38:57.300
We're ignoring that the immunogen sucks. We're ignoring that the RNA sucked.
01:38:57.300 --> 01:39:06.300
We're ignoring that the codon optimization sucks. We're ignoring that the pseudoyuridine sucks, and we're ignoring that the LNP probably sucks.
01:39:06.300 --> 01:39:18.300
We're ignoring that these protein fragments make it suck even worse, and we're focused on this cDNA because we have this idea that maybe the regulators will finally act.
01:39:18.300 --> 01:39:26.300
And it's okay to think that way as long as we don't throw this list away.
01:39:26.300 --> 01:39:41.300
Because if we focus on the cDNA and put all of our eggs in the basket of Kevin McCurnan's observations, this is what's going to happen.
01:39:42.300 --> 01:39:45.300
Anti-vaxxers pretty much never come up with anything new.
01:39:45.300 --> 01:39:53.300
And recently, in dark, stinky corners of the internet, there have been claims about DNA contamination in COVID vaccines.
01:39:53.300 --> 01:39:55.300
This, again, is nothing new.
01:39:55.300 --> 01:40:01.300
It is recycled anti-vaccine garbage that has always been around for as long as vaccines have.
01:40:01.300 --> 01:40:05.300
Hey, I'm Dr. Wilson, I'm a PhD molecular biologist, and welcome to another COVID-demunking video.
01:40:05.300 --> 01:40:11.300
So, yeah, today I'm going to be tackling this claim that there is DNA contamination in COVID vaccines.
01:40:11.300 --> 01:40:15.300
But first, I want to cover some background on this topic.
01:40:15.300 --> 01:40:24.300
What you need to understand before learning why these claims are wrong is a little bit about how vaccines and other biologic drugs are made.
01:40:24.300 --> 01:40:30.300
All biological drugs, including vaccines, have a step in their manufacturing that uses cells.
01:40:30.300 --> 01:40:38.300
These can be mammalian cells, these can be bacterial cells, depends on the product, and what is needed.
01:40:38.300 --> 01:40:48.300
For example, to make insulin, which is needed to keep diabetics all over the world alive, you need bacterial cells that are genetically engineered to produce human insulin.
01:40:48.300 --> 01:40:56.300
Once the human insulin is made, all the bacteria and all the parts of the bacteria are separated away from the insulin, and the insulin is the drug product.
01:40:56.300 --> 01:41:04.300
Another example are polio vaccines. In order to get a polio vaccine, you need a virus, and the virus is grown in cells.
01:41:04.300 --> 01:41:09.300
But just like the insulin, the virus needs to be taken away from the cells and all the cells parts in order to make the actual vaccine product.
01:41:09.300 --> 01:41:17.300
Whatever the case may be, there are a slew of long-established tests that are done to ensure that your drug product has actually been removed from the cell's parts.
01:41:17.300 --> 01:41:22.300
There are tests that are designed to look for how much host cell DNA is left in the drug product after you have finished making it,
01:41:22.300 --> 01:41:26.300
same with host cell proteins, more bacterial endotoxin, and several other things.
01:41:26.300 --> 01:41:32.300
All of these tests are required by regulatory laws to be done on each and every lot of biological drug that goes out onto the market.
01:41:32.300 --> 01:41:37.300
And there are set limits as to how much residual material can be found in those drug products.
01:41:37.300 --> 01:41:40.300
These are very strict guidelines that pharmaceutical companies have to abide by.
01:41:40.300 --> 01:41:45.300
In addition to good manufacturing procedure, which is abbreviated GMP, we also have good documentation procedure and good lab procedures.
01:41:45.300 --> 01:41:47.300
All of this can be summarized as just GXP.
01:41:47.300 --> 01:41:50.300
So moving forward, I'll be referring to all of these guidelines as GXP.
01:41:50.300 --> 01:41:55.300
If any of those GXP guidelines are not met or there are deviations from their protocols, then that is a huge no-no,
01:41:55.300 --> 01:42:02.300
and it would result in a lot not even going out in the first place, or being recalled, or a number of other things, including fines and disciplinary actions against those responsible.
01:42:02.300 --> 01:42:05.300
So it's kind of a big deal, which is why there are many layers to these regulations.
01:42:05.300 --> 01:42:10.300
The pharmaceutical company itself is required to do in-house testing to show that their product meets all of these regulations,
01:42:10.300 --> 01:42:14.300
and the regulatory body, in this case for the US being the FDA, will double check those results,
01:42:14.300 --> 01:42:19.300
meaning that they can perform their own testing in their own labs, and furthermore, when those drugs go out to other countries,
01:42:19.300 --> 01:42:23.300
those other countries' own regulatory bodies will also do in-house testing on the products that they receive.
01:42:23.300 --> 01:42:28.300
Again, by the end of it, the levels of residual host cell protein, DNA, whatever, have to be below a certain set limit.
01:42:28.300 --> 01:42:31.300
Anything below that certain set limit is considered to be trace amounts.
01:42:31.300 --> 01:42:35.300
And in those trace amounts, these materials will not have a biological effect on whoever receives the drug.
01:42:35.300 --> 01:42:39.300
So in other words, if there is no biological effect being exerted by these materials in these trace amounts,
01:42:39.300 --> 01:42:42.300
then for all intents and purposes, they might as well not be there.
01:42:42.300 --> 01:42:46.300
So that's what we mean when we say, no, there is no contamination in these materials.
01:42:46.300 --> 01:42:56.300
So do you see how easy it would be for CHD to tie their ropes to Kevin McCurnan and start to fight on his behalf,
01:42:56.300 --> 01:42:58.300
maybe even give him a T-shirt?
01:42:58.300 --> 01:43:04.300
And then because we have put all of our eggs in the CDNA contamination basket,
01:43:04.300 --> 01:43:14.300
even if a very small fraction of what Dan Wilson says in this video is really dead on balls accurate,
01:43:14.300 --> 01:43:24.300
it's still going to be sufficient for the vast majority of his viewership to discard Kevin McCurnan as an anti-vaxxer.
01:43:24.300 --> 01:43:30.300
And as we watch this, you're going to see that a lot of the objections that he brings up are the same kind of objections
01:43:30.300 --> 01:43:37.300
that somebody sitting on the FDA board would bring up, same kind of objections that other people on Twitter bring up.
01:43:38.300 --> 01:43:47.300
And so unless we're really ready to go toe to toe with these people on the molecular biology, or Kevin is willing to do it,
01:43:47.300 --> 01:43:56.300
then we're setting ourselves up essentially to substitute and jump into the ring instead of Kevin.
01:43:56.300 --> 01:44:04.300
And instead of Kevin's co-authors, CHD is about to jump in front and say, well,
01:44:04.300 --> 01:44:11.300
health Canada says, and Kevin McCurnan says, so children's health defense says,
01:44:11.300 --> 01:44:19.300
and now debunk the funk, and a bunch of other people can accuse us of being completely wrong.
01:44:19.300 --> 01:44:25.300
Whereas if I think we stuck to this list I just put up, starting with the fact that
01:44:25.300 --> 01:44:31.300
transfection in its purest form is still a stupid idea in healthy people,
01:44:31.300 --> 01:44:35.300
we would have a lot stronger, solid ground to stand on,
01:44:35.300 --> 01:44:39.300
and by the time we got to complaining about the CDNA contamination,
01:44:39.300 --> 01:44:43.300
we would have already hit a home run or a grand slam.
01:44:43.300 --> 01:44:48.300
A couple people would have already crossed the plate, you know what I mean?
01:44:49.300 --> 01:44:57.300
And I'm very worried about this idea that we are being baited into accepting this as a whoa, this is great.
01:44:57.300 --> 01:45:01.300
And now the regulators will call it off the market for a few months,
01:45:01.300 --> 01:45:06.300
and then when a new one comes on the market and the regulators have really cracked down,
01:45:06.300 --> 01:45:11.300
and there's no more DNA in these shots,
01:45:11.300 --> 01:45:16.300
then everybody will be bamboozled again.
01:45:16.300 --> 01:45:23.300
Because transfection has been given a pass because of the CDNA contamination.
01:45:23.300 --> 01:45:27.300
He already believes transfection works great.
01:45:27.300 --> 01:45:35.300
Don't forget that half of the country doesn't know that transfection is a terrible idea.
01:45:35.300 --> 01:45:42.300
So it's not really a good idea to bring those people to the truth by first telling them an anecdote
01:45:42.300 --> 01:45:54.300
that, yeah, there's some contamination in there, and that might integrate into your genome.
01:45:54.300 --> 01:45:56.300
We've got to be very, very careful.
01:45:56.300 --> 01:45:59.300
Listen to the rest of this video just so you can see what I'm talking about.
01:45:59.300 --> 01:46:03.300
This is not funny.
01:46:03.300 --> 01:46:10.300
He's got a team of people, you know, he didn't do this all by himself.
01:46:10.300 --> 01:46:14.300
Other people seem to think that they've found differently, and it's quite a funny story, so let's get into it.
01:46:14.300 --> 01:46:18.300
So when it comes to COVID mRNA vaccines, some people who have a history of subscribing to anti-vaccine
01:46:18.300 --> 01:46:23.300
kind of deranged conspiracy theories claim to have found plasmid DNA in the mRNA vaccines.
01:46:23.300 --> 01:46:25.300
What is plasmid DNA, you might ask?
01:46:25.300 --> 01:46:29.300
Well, it comes from the manufacturing process used in making mRNA vaccines.
01:46:29.300 --> 01:46:31.300
A plasmid is a circular piece of DNA that can be taken up.
01:46:31.300 --> 01:46:34.300
You know what's most frustrating about this for me?
01:46:34.300 --> 01:46:48.300
That this whole story of using plasmid DNA in process two is exactly what I'm talking about when I say that they make infectious clones to study RNA viruses.
01:46:48.300 --> 01:46:54.300
It is exactly this process, and it is exactly as Kevin McCurnan said in that stream.
01:46:54.300 --> 01:46:58.300
They can make as much as they want.
01:46:58.300 --> 01:47:07.300
There's no limit. They have an infinite amount of plasmid. All they have to do is keep feeding the bacteria.
01:47:07.300 --> 01:47:24.300
That's why infectious clones can be used to create a pandemic, because you're not relying on some kind of magical RNA to be ridiculously high fidelity for three years and circulate the globe in a cartoon-like fashion.
01:47:25.300 --> 01:47:32.300
You're relying on brute force.
01:47:32.300 --> 01:47:40.300
RNA is a bit like paint. It doesn't replicate itself very well. It dilutes.
01:47:40.300 --> 01:47:51.300
So if I go outside of my garage and spill a bucket of paint on the ground, the only way it's going to spread is if people walk through it.
01:47:51.300 --> 01:47:58.300
And maybe if you were really careful, you could scoop up enough paint so that you could get some paint on the house next door.
01:47:58.300 --> 01:48:03.300
And you could argue that, wow, the blue paint is spreading everywhere.
01:48:03.300 --> 01:48:10.300
But to say that all the houses in Pittsburgh are because I dump paint in the backyard would be ridiculous.
01:48:10.300 --> 01:48:20.300
But if I had a giant truck full of blue paint, I could drive all around Pittsburgh and spread it all over the place and make it look like my paint had spread all over.
01:48:20.300 --> 01:48:29.300
But anybody who knows how paint works would be like, well, it couldn't have been Jay's fault for spilling it in his backyard that it got all over Squirrel Hill in Pittsburgh.
01:48:29.300 --> 01:48:34.300
That's impossible. Paint doesn't work like that.
01:48:34.300 --> 01:48:41.300
And there should be lots of biologists that are saying that RNA viruses don't pandemic.
01:48:41.300 --> 01:48:49.300
But infectious clones could be used to make it look like they was a pandemic.
01:48:49.300 --> 01:49:04.300
There should be hundreds, if not thousands, of biologists saying this just from a rudimentary understanding of the difference between double-stranded DNA and its copying versus single-stranded RNA and its copying.
01:49:04.300 --> 01:49:18.300
But instead, the moment I started talking about infectious clones as the ubiquitous way with which we study at RNA virology, Kevin McCernan himself got so tired of arguing about it
01:49:18.300 --> 01:49:24.300
that he blocked me on Twitter.
01:49:24.300 --> 01:49:37.300
This is not insignificant, ladies and gentlemen, that for process two and for making of the spike protein for all these different vaccines, it's fine to talk about recombinant DNA being replicated in a bacterial culture.
01:49:37.300 --> 01:49:46.300
But if I talk about how they do that with all coronaviruses all the time, and that barracks the guy who invented it and made it ubiquitous for everybody,
01:49:46.300 --> 01:49:58.300
and that's how they share these things, they send these clones around, all the stored viruses at the CDC are actually clones, and everybody got mad.
01:49:58.300 --> 01:50:02.300
Oh, no, you're an idiot. Don't listen to him.
01:50:02.300 --> 01:50:06.300
He's compromised.
01:50:06.300 --> 01:50:19.300
It is the standard technique by which they make all biologics. Do you hear it? It's the standard technique by which they make all biologics.
01:50:19.300 --> 01:50:26.300
That is the reason why the clone story is the answer.
01:50:26.300 --> 01:50:35.300
You can't make a little bit of an RNA virus and then let it loose and have it go change the world. That's not how RNA works.
01:50:35.300 --> 01:50:39.300
And these people all know it. They have to.
01:50:39.300 --> 01:50:45.300
Or they're participating in kind of a I don't want to know kind of thing.
01:50:45.300 --> 01:50:51.300
Because all you got to do is let your brain work. And this becomes basic biology.
01:50:51.300 --> 01:50:57.300
By things like bacteria and then expressed, meaning that the DNA can be read by cellular machinery and made into mRNA.
01:50:57.300 --> 01:51:02.300
Once the mRNA is made, the DNA is chopped up and the pieces are mostly removed from the final drug product.
01:51:02.300 --> 01:51:15.300
But this guy, a Mr Kevin McKernan, claims that he has gotten some vials of COVID mRNA vaccine and has found contamination of plasma DNA in the vaccine vials at levels orders of magnitude higher and the regulated limit.
01:51:15.300 --> 01:51:22.300
Wow, this should be good. He has written up his results and posted them on this regulation free preprint server, meaning that there's no safeguard, no peer review.
01:51:22.300 --> 01:51:27.300
We already go back to Kevin's talk and already preview what's going to happen here, right?
01:51:27.300 --> 01:51:35.300
The orders of magnitude statement comes from the fluorometry versus the QPCR.
01:51:35.300 --> 01:51:41.300
And in the discussion with Mary and Brian, Kevin was very clear.
01:51:41.300 --> 01:51:50.300
Using QPCR, they found levels of DNA lower than the minimum required or minimum allowed.
01:51:50.300 --> 01:51:57.300
But with using fluorometry, they found several orders of magnitude more than that.
01:51:57.300 --> 01:52:10.300
And so the argument that Dan is going to make is that fluorometry isn't an accurate representation of dangerous DNA because it's picking up all kinds of tiny little fragments.
01:52:10.300 --> 01:52:15.300
That's the exact argument that's going to happen here. Now, who wins that argument?
01:52:15.300 --> 01:52:18.300
What's the right answer there? Do you know?
01:52:18.300 --> 01:52:21.300
I thought this was just a home run.
01:52:21.300 --> 01:52:26.300
That even goes into what people can post on it, so it's not peer reviewed and it's not checked by anybody before it goes up.
01:52:26.300 --> 01:52:30.300
But that really doesn't even begin to describe the many problems with what he has presented here.
01:52:30.300 --> 01:52:38.300
So let's start with this. He writes that the COVID mRNA vaccine vials were sent to him anonymously in the mail without cold packs.
01:52:38.300 --> 01:52:43.300
Oh, wait, you serious? Let me laugh even harder.
01:52:43.300 --> 01:52:46.300
I could honestly end the video right here. That is really bad.
01:52:46.300 --> 01:52:49.300
This already violates the good documentation procedure of GXP guidelines.
01:52:49.300 --> 01:52:53.300
Not only do you have no idea who handled those vials before you receive them.
01:52:53.300 --> 01:52:58.300
Now, remember the story that he told Mary was that he didn't really mean to sequence the vials. It wasn't his intention.
01:52:58.300 --> 01:53:07.300
He just wanted a standard polyA RNA to control the experiment that he was doing.
01:53:07.300 --> 01:53:17.300
But look how inconvenient that aspect of the experiment is if someone from the other side can completely make fun of it.
01:53:17.300 --> 01:53:22.300
And it's not really that bad of a critique, right? I mean, it is.
01:53:22.300 --> 01:53:34.300
You should really probably start with a fresh vial, right? You should at least know where it was or how long it wasn't chilled like.
01:53:35.300 --> 01:53:38.300
But they're clearly not stored properly if they're not even sent on cold packs.
01:53:38.300 --> 01:53:41.300
Any self-respecting scientist would immediately recognize that this is not the right way to do this experiment.
01:53:41.300 --> 01:53:46.300
A competent and self-respecting scientist would make sure that they do the experiment right and actually have vials that have documentation
01:53:46.300 --> 01:53:52.300
so that they can show who handled them before they received them, but they were stored properly and make sure that there's no funny business going on with whatever you're testing.
01:53:52.300 --> 01:53:55.300
But we're not dealing with one of those people here and I'm not ending the video here.
01:53:55.300 --> 01:54:00.300
I'm going to be thorough and look at the results that they actually obtained with these mystery garbage vials.
01:54:01.300 --> 01:54:07.300
Let's go back to what I said earlier about there being tests to determine whether or not residual materials in your drug product are actually below the regulated acceptable limit.
01:54:07.300 --> 01:54:12.300
In order to demonstrate that tests are done to quantify the levels of residual materials in the drug product.
01:54:12.300 --> 01:54:16.300
So the obvious question is, I mean, you could even make the argument that the FDA would say the same thing, right?
01:54:16.300 --> 01:54:19.300
We don't know where these vials were. You got them in the mail, they were garbage.
01:54:19.300 --> 01:54:23.300
We're not going to take your word for these.
01:54:23.300 --> 01:54:26.300
They might even say to you that that was illegal.
01:54:26.300 --> 01:54:29.300
There's a law that these are the property of the government.
01:54:29.300 --> 01:54:34.300
You're not allowed to do anything with them except to inject them in people's arms or it's against the law.
01:54:34.300 --> 01:54:35.300
It's a federal law.
01:54:35.300 --> 01:54:37.300
They could even say that.
01:54:37.300 --> 01:54:40.300
That's where we are right now.
01:54:40.300 --> 01:54:48.300
Is CHD going to put their name on this and then get accused of doing something illegal or supporting the illegal something something?
01:54:48.300 --> 01:54:50.300
I don't know. I don't know that that's going to happen.
01:54:50.300 --> 01:54:51.300
I'm not a lawyer.
01:54:51.300 --> 01:55:05.300
I'm just saying it ain't so cut and dry as let's give Kevin McCurn in a sweatshirt and hat and get him on the team and give him a baseball bat and get him up to the plate.
01:55:05.300 --> 01:55:10.300
Here is did have here actually quantify the levels of plasma DNA in the vials.
01:55:10.300 --> 01:55:12.300
Well, he tried, but he didn't really.
01:55:12.300 --> 01:55:15.300
The key figure here in his blog post is this one.
01:55:15.300 --> 01:55:17.300
This is where he tried to make a standard curve.
01:55:17.300 --> 01:55:23.300
If you want to have a standard curve made up of known values so that you can compare your unknown samples against it and actually quantify a value.
01:55:23.300 --> 01:55:37.300
So this is his attempted standard curve where he just ran some known amounts of DNA on a PCR and then on a seemingly separate PCR assay ran his material from the vaccine vials and just compared the two separate assays, which not good.
01:55:37.300 --> 01:55:38.300
You don't want to do that.
01:55:38.300 --> 01:55:41.300
You ideally want to compare them within the same assay, but there's a lot more wrong here.
01:55:41.300 --> 01:55:43.300
So let's go right to the meat of what is wrong.
01:55:43.300 --> 01:55:45.300
There's a lot of analysis missing from this standard curve.
01:55:45.300 --> 01:55:51.300
He just reports that this certain value came up around cycle 20 and seems to be fine with just mentioning that.
01:55:51.300 --> 01:55:53.300
So I analyze the data for him.
01:55:53.300 --> 01:55:57.300
Whenever you make a standard curve in a quantitative PCR experiment, there are several basic things that you really should do.
01:55:57.300 --> 01:56:01.300
Two of those basic things is calculating the linearity and efficiency of your reaction.
01:56:01.300 --> 01:56:02.300
Again, he didn't do that here.
01:56:02.300 --> 01:56:03.300
So I did it for him.
01:56:03.300 --> 01:56:07.300
The linearity of his standard curve looks fine, but the efficiency of the reaction is where he run into a problem.
01:56:07.300 --> 01:56:11.300
In any PCR, the number of molecules present should double with each cycle.
01:56:11.300 --> 01:56:14.300
And the efficiency of a quantitative PCR reaction is measuring that.
01:56:14.300 --> 01:56:16.300
It's measuring how efficient the reaction was.
01:56:16.300 --> 01:56:23.300
Usually in GXP world and just across the board, a range of 90 to 110 percent efficiency is considered acceptable.
01:56:23.300 --> 01:56:25.300
Kev's efficiency here was around 70 percent.
01:56:25.300 --> 01:56:35.300
There could be many reasons that a PCR's efficiency would be low like this, but normally those reasons will be ironed out when you're actually qualifying your standard operating procedure for your assay, which Kev didn't do.
01:56:35.300 --> 01:56:45.300
Now, because he didn't actually post his mean cycle threshold values, I didn't have precise numbers to plug into this calculator, but I judged as best as I could, and I was even as generous as possible with the decimal points.
01:56:45.300 --> 01:56:48.300
But no matter how much I played with it, I couldn't get the efficiency above 75 percent.
01:56:48.300 --> 01:56:51.300
So let's be generous and say that the efficiency of the reaction was 75 percent.
01:56:51.300 --> 01:56:55.300
In a GXP experiment, that would invalidate the entire experiment.
01:56:55.300 --> 01:56:57.300
So essentially his assay failed, and his results are unusable.
01:56:57.300 --> 01:56:58.300
And there's good reason for this.
01:56:58.300 --> 01:57:04.300
If the efficiency is low, that means that the curves on this graph here are artificially shifted to the right, which means that you're not really making a difference.
01:57:04.300 --> 01:57:06.300
You're not really measuring accurate numbers at all.
01:57:06.300 --> 01:57:08.300
Just for comparison, here are data that I pulled from one of my experiments.
01:57:08.300 --> 01:57:11.300
You can see that the efficiency is well within range, and when the arity is pretty good.
01:57:11.300 --> 01:57:12.300
This is a passing assay.
01:57:12.300 --> 01:57:13.300
This is a failing assay.
01:57:13.300 --> 01:57:20.300
Kev is trying to criticize pharmaceutical companies' manufacturing processes while not being able to meet the standards of good manufacturing procedures himself.
01:57:20.300 --> 01:57:27.300
The theme from earlier when I talked about where the samples came from of just not taking the time to do this experiment the right way is very consistent throughout this whole thing.
01:57:27.300 --> 01:57:28.300
And yeah, there's more, it gets worse.
01:57:28.300 --> 01:57:33.300
So already he's failed the good documentation procedures, and now he has failed his actual assay, his experiment.
01:57:33.300 --> 01:57:37.300
But let's forgive that and move on and analyze the data further for tending like it's valid.
01:57:37.300 --> 01:57:42.300
Because remember, he claims to have found DNA in amounts that are orders of magnitude higher than what the regulatory limits set.
01:57:42.300 --> 01:57:44.300
So did he actually find that much DNA?
01:57:44.300 --> 01:57:46.300
Well, no, he didn't care ready for this one.
01:57:46.300 --> 01:57:49.300
In order to calculate how much DNA you actually have in your drug product, you have to do a few things.
01:57:49.300 --> 01:57:56.300
Once you have your standard curve and you're unknown plotted against it, it depends whether or not your standard curve is measuring copies or gram amounts.
01:57:56.300 --> 01:57:58.300
Kev's standard curve here is in gram amounts, and that's fine.
01:57:58.300 --> 01:57:59.300
We can work with that.
01:57:59.300 --> 01:58:03.300
And so I did, I put all the math involved here into a Google Excel sheet that you can access and look at yourself.
01:58:03.300 --> 01:58:04.300
It's in the description below.
01:58:04.300 --> 01:58:05.300
So go check that out.
01:58:05.300 --> 01:58:06.300
You want to check my math?
01:58:06.300 --> 01:58:18.300
But to make this as simple as possible, if I am as generous as possible, and I assume that all of the DNA copies that he has measured in this experiment are representing full-length intact plasmid, the total gram amount in a single dose of COVID vaccine would be 81 nanograms.
01:58:18.300 --> 01:58:21.300
So that's not orders of magnitude higher than regulatory limits.
01:58:21.300 --> 01:58:24.300
But we're not dealing with full-length intact plasmid here.
01:58:24.300 --> 01:58:30.300
Again, remember what I said about the manufacturing process, where after the mRNA is made, the DNA gets chopped up and mostly removed from the drug product.
01:58:30.300 --> 01:58:32.300
The DNA is going to be in pieces.
01:58:32.300 --> 01:58:36.300
So normally what people would do is look at the average length size of DNA in the final product.
01:58:36.300 --> 01:58:38.300
This can be done by doing what's called an electroph diagram.
01:58:38.300 --> 01:58:39.300
Kev actually did one.
01:58:39.300 --> 01:58:43.300
And he shows that most of the DNA in the vial is fragmented.
01:58:43.300 --> 01:58:44.300
In fact, it's very short.
01:58:44.300 --> 01:58:46.300
About 100 base pairs is the biggest peak that he gets.
01:58:46.300 --> 01:58:50.300
The full-length plasmid is going to be on the order of 15,000 bases.
01:58:50.300 --> 01:58:52.300
Okay, so this is a false argument, right?
01:58:52.300 --> 01:58:54.300
We also said this earlier.
01:58:54.300 --> 01:58:57.300
The idea that you need the whole plasmid is not the deal.
01:58:57.300 --> 01:59:12.300
The deal is that you need a meaningful size of DNA that's not supposed to be there, that it gives a potential for this integration or potential for mRNA production or potential for translocation to the nucleus.
01:59:12.300 --> 01:59:17.300
Some additional problem because of the DNA being there.
01:59:18.300 --> 01:59:25.300
So he's kind of, you know, making a crappy argument here that we can't find any full plasmid so it's no big deal.
01:59:25.300 --> 01:59:37.300
And this is kind of in parallel, but the flip side to Kevin and Buckhalter's argument that the smaller these pieces are, the more active ends there are, and that's kind of like carpet bombing the genome.
01:59:37.300 --> 01:59:40.300
Now, let's just listen.
01:59:40.300 --> 01:59:48.300
So while Kev's own results show that most of the DNA is fragmented, he doesn't show an average base pair length, which is what you would use to calculate how much DNA you actually have.
01:59:48.300 --> 02:00:00.300
So I looked at some historical data for similar biological products and similar electropharium curves, and I think 800 to 1,000 base pairs is a good average to estimate for average base pair length in this sample.
02:00:00.300 --> 02:00:04.300
I'll be generous and say 1,000 base pairs is the average length, so knowing that and knowing how many...
02:00:04.300 --> 02:00:12.300
That we know is wrong from Buckhalter's estimation. The smallest... the pieces are really much tinier than that, so this is wrong.
02:00:12.300 --> 02:00:20.300
This is definitely, at least from the perspective of trying to debunk Kevin and Buckhalter's work, this is wrong.
02:00:20.300 --> 02:00:38.300
And so you shouldn't be surprised. I'm not surprised that the debunk and his team or his helpers are going to get some of this incorrect, or at least represented disingenuously by saying that the average length of the double stranded plasma is 1,000 base pairs.
02:00:38.300 --> 02:00:49.300
I'm pretty sure Kevin didn't say that, and I'm pretty sure that Buckhalter actually measured them with the nanopore sequencing, and we could probably go back and look.
02:00:49.300 --> 02:01:00.300
But I think that I think that was also, they were much, much tinier, and that was Buckhalter's full argument was that they were so small, and that's what makes them not work.
02:01:00.300 --> 02:01:03.300
It's going to take me a while to find that. I'll just keep it plain.
02:01:03.300 --> 02:01:10.300
Because you measured in the actual QPCR reaction, you can calculate the nanogram amount of DNA, which comes out to five nanograms.
02:01:10.300 --> 02:01:13.300
That's about how much DNA Kev actually measured in this experiment.
02:01:13.300 --> 02:01:15.300
He keeps calling him Kev.
02:01:15.300 --> 02:01:18.300
He keeps calling him Kev. That to me is a little weird.
02:01:18.300 --> 02:01:22.300
I've never called him Kev, and I've actually had him on my stream.
02:01:22.300 --> 02:01:28.300
I had a good friend when I was a kid, though, Kevin. I used to call Kev a lot, but...
02:01:28.300 --> 02:01:35.300
On multiple levels, and was done on mystery vials with no documentation history, and he thought that this was a big find.
02:01:35.300 --> 02:01:40.300
Okay, so moving on a little bit, that five nanogram amount?
02:01:40.300 --> 02:01:47.300
Remember, that is me being as generous as possible with the numbers, and also ignoring the fact that his QPCR efficiency failed, which means that his standard curve is...
02:01:47.300 --> 02:01:52.300
Actually shifted to the left, which means that his samples are going to be an even lower gram amount on that standard curve.
02:01:52.300 --> 02:01:57.300
So, if this experiment was done the right way, you would probably get an even lower gram amount than what is shown here.
02:01:57.300 --> 02:02:02.300
So how do we know that Kev is wrong without even doing any of this analysis of his garbage data?
02:02:02.300 --> 02:02:06.300
We know because, again, regulatory bodies do this for us, and we've seen the results.
02:02:06.300 --> 02:02:10.300
For example, here's a summary of COVID vaccine batch release information from Australia.
02:02:10.300 --> 02:02:15.300
These vials were made by Pfizer, tested in-house by them, released by the regulatory body, and then went to Australia.
02:02:15.300 --> 02:02:19.300
And their regulatory body tested it themselves, and found that it passed all of the criteria.
02:02:19.300 --> 02:02:26.300
That means that all of the residual plasmid, the hostel DNA, the hostel proteins, the endotoxin, everything was below the acceptable limit, meaning that it was in trace amounts.
02:02:26.300 --> 02:02:28.300
In other words, practically nothing there.
02:02:28.300 --> 02:02:36.300
So either there's a global conspiracy among pharmaceutical companies and regulatory bodies all over the world, everyone's lying, or Kev just has no idea what he's doing.
02:02:36.300 --> 02:02:38.300
I think it's the latter.
02:02:38.300 --> 02:02:42.300
So you might think that that's the end of this video, but, oh no, there's more, it gets worse.
02:02:42.300 --> 02:02:47.300
So after blogging about these findings, Kev went on to say that these findings have health implications.
02:02:47.300 --> 02:02:57.300
He went on to claim that a promoter, which is a DNA sequence that sits in front of a gene on DNA and helps the DNA actually get read by cellular machinery, is somehow going to cause cancer.
02:02:57.300 --> 02:03:08.300
Yeah, he thinks that a promoter is somehow going to get into your cell nucleus and integrate itself into your DNA and just happen to integrate in front of a gene that, if misregulated, would contribute to cancer.
02:03:08.300 --> 02:03:11.300
And this is exactly what I just said.
02:03:11.300 --> 02:03:17.300
So parts he gets right, parts he gets wrong, parts he gets right again.
02:03:17.300 --> 02:03:20.300
It's exactly the bamboozlement.
02:03:20.300 --> 02:03:38.300
It's exactly how it always happens with Rogan, with Weinstein, with with Robert Malone and Steven Hadfield, with Rick Bright, with Tony Fauci, with EcoHealth Alliance, with Bobby Kennedy, with everyone.
02:03:39.300 --> 02:03:44.300
It's extraordinary how nobody can seem to get it straight.
02:03:44.300 --> 02:03:49.300
And they all make catastrophic errors when it comes to the faith.
02:03:49.300 --> 02:03:55.300
The faith in a novel virus, the faith in a million people dying and a million people could have been saved.
02:03:55.300 --> 02:04:02.300
The faith in the RNA and that it did something, the faith in gain of function and that a virus will come again.
02:04:03.300 --> 02:04:12.300
So let's argue about contamination of the shot with CDNA derived from the process to that they lied about.
02:04:17.300 --> 02:04:24.300
You know, this would be a pretty stupid idea if there were no evidence of random external promoters integrating themselves into your DNA.
02:04:24.300 --> 02:04:25.300
There isn't.
02:04:25.300 --> 02:04:30.300
It would be doubly stupid if we weren't regularly exposed to DNA viruses that have promoters in their genomes.
02:04:30.300 --> 02:04:36.300
We are just like anti-vaxxers who have come before him, who have tried to fear monger to the public about imaginary contaminations in vaccines.
02:04:36.300 --> 02:04:37.300
He's doing it again.
02:04:37.300 --> 02:04:38.300
And in a really bad way.
02:04:38.300 --> 02:04:44.300
So in summary, the experiments that claim to show DNA contamination in COVID vaccines are very sloppily done.
02:04:44.300 --> 02:04:47.300
Because they're so poorly done, they're not even considered valid by regulatory standards.
02:04:47.300 --> 02:04:49.300
And we actually analyze the invalid data.
02:04:49.300 --> 02:04:53.300
We see that it's actually consistent with the levels being below regulatory limits.
02:04:53.300 --> 02:04:56.300
And on top of all that, what Kev has done might be illegal.
02:04:56.300 --> 02:05:03.300
According to federal law, COVID vaccines are the property of the federal government and can only be used, administered, or handled by approved bodies.
02:05:03.300 --> 02:05:07.300
I don't think that Kev's lab is an approved body for handling federal property.
02:05:07.300 --> 02:05:09.300
So, yeah, it might be illegal.
02:05:09.300 --> 02:05:10.300
More on that later, maybe.
02:05:10.300 --> 02:05:11.300
Anyway, that's going to do it for this week's video.
02:05:11.300 --> 02:05:12.300
That was pretty fun for me.
02:05:12.300 --> 02:05:14.300
And thank you so much for watching.
02:05:14.300 --> 02:05:15.300
I really do appreciate it.
02:05:15.300 --> 02:05:19.300
If you've enjoyed this video, then don't forget to like it and subscribe so that you can catch me next week, where I'll be debunking some more.
02:05:20.300 --> 02:05:26.300
So, don't forget, there's another one because, of course, that was the first preprint.
02:05:26.300 --> 02:05:28.300
And now this is the second preprint.
02:05:28.300 --> 02:05:29.300
And he did it again.
02:05:29.300 --> 02:05:32.300
Yes, he did it again.
02:05:37.300 --> 02:05:40.300
Support what the author was claiming in the slightest.
02:05:40.300 --> 02:05:45.300
Now, there's another preprint by the same author claiming the same thing, that there's DNA contamination.
02:05:45.300 --> 02:05:47.300
And now he's got a Carnegie Mellon sweater.
02:05:47.300 --> 02:05:50.300
Are far above the allowable FDA limits.
02:05:50.300 --> 02:05:53.300
And it's just as wrong and sloppy as the first one.
02:05:53.300 --> 02:05:56.300
But a lot of you have been asking me to debunk it, so here we go.
02:05:56.300 --> 02:06:01.300
I will tell you exactly how this paper is so sloppy that it is practically useless, again.
02:06:01.300 --> 02:06:07.300
And I will tell you everything you need to know to understand why this story is wrong to begin with.
02:06:07.300 --> 02:06:09.300
Just for those who don't know, this is a preprint.
02:06:09.300 --> 02:06:11.300
That means it has not been peer reviewed.
02:06:11.300 --> 02:06:12.300
But that's not why it's wrong.
02:06:12.300 --> 02:06:14.300
So, let's get into what makes it wrong.
02:06:14.300 --> 02:06:19.300
Before we get to the data, I'm just going to jump the gun a little bit and tell you why this whole idea was wrong to begin with.
02:06:19.300 --> 02:06:26.300
Every single biologic or drug that uses biological materials in the manufacturing process needs to go through certain quality control standards in order to get FDA approval.
02:06:26.300 --> 02:06:30.300
And each subsequent batch that goes out to the public also needs to pass those same quality control standards.
02:06:30.300 --> 02:06:33.300
This is a whole regulatory area called good manufacturing practice, and it is global.
02:06:33.300 --> 02:06:39.300
Flashing across your screen right now are just some of the tests that each and every COVID mRNA vaccine batch had to pass before it went out to the public.
02:06:39.300 --> 02:06:44.300
This includes quantifying residual DNA left by the plasmid. That is used in the manufacturing process to make the mRNA.
02:06:44.300 --> 02:06:46.300
These tests are done both by the manufacturers and also by...
02:06:46.300 --> 02:06:48.300
That's funny. That's what you call contract research.
02:06:48.300 --> 02:06:49.300
That's funny.
02:06:49.300 --> 02:06:51.300
The results are then reviewed by regulatory bodies before the loss.
02:06:51.300 --> 02:06:58.300
The title of that one was proposed testing for prasmin DNA prior to release.
02:06:58.300 --> 02:07:02.300
It says proposed testing.
02:07:02.300 --> 02:07:05.300
So he's kind of misrepresenting this.
02:07:05.300 --> 02:07:09.300
Flying residual DNA left by the plasmid. That is used in the manufacturing process to make the mRNA.
02:07:09.300 --> 02:07:13.300
These tests are done both by the manufacturers and also by third parties, which are called contract research organizations.
02:07:13.300 --> 02:07:16.300
The results are then reviewed by regulatory bodies before the loss can go out to the public.
02:07:16.300 --> 02:07:17.300
Each test is qualified...
02:07:17.300 --> 02:07:18.300
There's an Australian...
02:07:18.300 --> 02:07:19.300
Is qualified in...
02:07:19.300 --> 02:07:21.300
Not sure that happened in America.
02:07:21.300 --> 02:07:30.300
The assay itself and the reagents take significant effort to demonstrate that they are actually measuring what the test is designed to measure and that it can demonstrate purity or contamination or lack thereof in whatever the context may be.
02:07:30.300 --> 02:07:32.300
The point is there is a lot of work that goes into this.
02:07:32.300 --> 02:07:34.300
A lot of people do these tests and a lot of regulatory bodies all over the world.
02:07:34.300 --> 02:07:35.300
Look at the results.
02:07:35.300 --> 02:07:40.300
So if these results are going to be overturned, then you need something of equal rigor to overturn them.
02:07:40.300 --> 02:07:43.300
And these preprints are nowhere near that level of rigor.
02:07:43.300 --> 02:07:54.300
It does really seem like the only thing he has to stand on is the idea that the SV40 promoter was removed from the EMA document that was submitted to Canada and to the European Union.
02:07:54.300 --> 02:08:01.300
And this allows them to title that video intent to deceive.
02:08:02.300 --> 02:08:06.300
Other than that, it doesn't seem as though there's a tremendous amount of evidence.
02:08:06.300 --> 02:08:18.300
They said that they were trying to correlate the amount of DNA in different lots to the outcomes, the VAERS outcomes.
02:08:18.300 --> 02:08:20.300
But we didn't see any of that data.
02:08:20.300 --> 02:08:22.300
We didn't hear any about that data.
02:08:22.300 --> 02:08:27.300
We didn't see how they quantified the difference between different lots.
02:08:28.300 --> 02:08:30.300
And how those quantifications were done.
02:08:30.300 --> 02:08:31.300
We didn't see that at all.
02:08:31.300 --> 02:08:36.300
He just mentioned that it happened that Jessica Rose did it.
02:08:36.300 --> 02:08:44.300
But that's a whole nother ball game quantifying the contamination across lots is very different.
02:08:44.300 --> 02:08:51.300
Apparently they had like 25 vials or something like that, right?
02:08:52.300 --> 02:08:55.300
I'm not sure they've been qualified as being of the quality of like an undergraduate project, to be honest.
02:08:55.300 --> 02:08:58.300
Anyway, let's now look at the preprints and what they show or what they claim to show.
02:08:58.300 --> 02:09:05.300
In this new preprint, again, what they're looking at are what they claim to be COVID mRNA vaccine vials, and they are testing the liquid inside of them for residual DNA contamination.
02:09:05.300 --> 02:09:11.300
They're doing this by using QPCR, which is the gold standard by which DNA and other nucleic acids are quantified in this context.
02:09:11.300 --> 02:09:13.300
But like the first preprint, there are still significant issues.
02:09:13.300 --> 02:09:17.300
If you haven't watched my previous video on this topic, I highly recommend you go check that out because I explain it all in much more detail.
02:09:17.300 --> 02:09:22.300
But in their first preprint, their QPCR reaction failed efficiency, which off the bat means it is totally invalid.
02:09:22.300 --> 02:09:27.300
And by the way, anybody who publishes QPCR reaction or tries to publish one, that failed efficiency is doing incredibly sloppy work.
02:09:27.300 --> 02:09:35.300
I can't stress that enough. It's a huge mistake that an undergraduate shouldn't make, let alone someone trying to publish a preprint that is trying to take down all of the pharmaceutical and regulatory industries.
02:09:35.300 --> 02:09:38.300
In any case, in this new preprint, their efficiency was much better. Very glad they learned that part.
02:09:38.300 --> 02:09:44.300
However, just like the first preprint, they are miscalculating the amount of DNA in their sample, and as a result, hugely overestimating how much DNA is there.
02:09:44.300 --> 02:09:48.300
Funnily enough, this overestimation still puts them below the FDA regulatory limit.
02:09:48.300 --> 02:09:52.300
Yeah, they admit and fully show that their measurements were below FDA regulatory limit.
02:09:52.300 --> 02:09:58.300
Anyway, the correct way to calculate how much DNA you have in your samples in this context is to use QPCR to get a copy number.
02:09:58.300 --> 02:10:04.300
Once you have a copy number of how many copies of DNA you have in your sample, you can then use that copy number to calculate a gram amount.
02:10:04.300 --> 02:10:09.300
But remember, as I explained in my previous video, any trace amounts of DNA that are going to be in the COVID mRNA vaccines are going to be in fragments.
02:10:09.300 --> 02:10:17.300
That's because the plasmid used for manufacturing is digested by enzymes called DNases, and then most of those fragments are removed away from the mRNA before it's made into the drug product.
02:10:17.300 --> 02:10:18.300
Because you have the copy number...
02:10:18.300 --> 02:10:26.300
How are they removed away? See, that's the argument that Buck Halter and McCurnan are making is that you can't remove them.
02:10:26.300 --> 02:10:35.300
They're just fragmented, and then they stay there. He's just hand-waving here, which is very interesting.
02:10:36.300 --> 02:10:45.300
But what I'm trying to set up for you is the idea that this is already ready to go, like within days.
02:10:45.300 --> 02:10:52.300
And so there is something happening here besides a sudden finding of DNA.
02:10:52.300 --> 02:10:56.300
It's possible that this DNA is harmless.
02:10:56.300 --> 02:11:00.300
It's possible that this DNA is meaningless.
02:11:00.300 --> 02:11:12.300
It's possible that it's just another piece of the nasty puzzle that is transfection is not a product that we can make suitable for healthy humans.
02:11:12.300 --> 02:11:17.300
And this is just one of the many details of that story.
02:11:18.300 --> 02:11:32.300
That when we emphasize it as the detail, when we emphasize it as the camels, you know, the straw that breaks the camel's back, we are actually overemphasizing its real significance, I think.
02:11:33.300 --> 02:11:46.300
And giving the door an opening to people like this who can kind of pounce on it and exaggerate that to the point where all of the other legitimate concerns get lost in this.
02:11:49.300 --> 02:11:57.300
It's 10.35. It's been two hours and ten minutes. I'm going to put this in the chat for you to watch if you want to.
02:11:57.300 --> 02:12:02.300
I'm not going to watch any more of this guy because I've already watched one and you get the idea of what he was doing.
02:12:02.300 --> 02:12:07.300
You get the idea of what he was trying to do.
02:12:07.300 --> 02:12:15.300
And I just want to finish up with a little summary really quick as long as my voice is still working.
02:12:15.300 --> 02:12:20.300
So thanks for watching that. This is a group of people that has been manipulating us.
02:12:20.300 --> 02:12:35.300
A couple of days ago, I watched a stream of somebody that I used to really enjoy named Huberman, who is a professor at Stanford, a neurobiologist, only to find out through my own loving wife that actually he's part of the intellectual dark web to and I was a dork for not knowing it.
02:12:37.300 --> 02:12:46.300
So they misled us about the potential for pandemics to be in the laboratory and that was that noise.
02:12:47.300 --> 02:12:53.300
That was on my microphone outside. It sounded like somebody jumped on it.
02:12:53.300 --> 02:12:57.300
And also the fact that we could stitch things together.
02:12:57.300 --> 02:13:04.300
But the illusion of consensus with regard to this, I hope you understand is very specific.
02:13:04.300 --> 02:13:15.300
The illusion of consensus is that the worst case scenario now or in the future is a gain of function laboratory bio weapon release leak.
02:13:16.300 --> 02:13:17.300
Accident.
02:13:19.300 --> 02:13:25.300
And so it's not only the illusion of consensus isn't that gain of function is real.
02:13:25.300 --> 02:13:32.300
The illusion of consensus is that gain of function is a potential source of a disaster.
02:13:33.300 --> 02:13:41.300
And that inside of that potential source of disaster are people who actually want to create the potential for that disaster.
02:13:42.300 --> 02:13:45.300
And there is a consensus across left and right.
02:13:46.300 --> 02:13:51.300
High in government secret meetings everywhere that this is the truth.
02:13:52.300 --> 02:14:08.300
And people like Kevin McCann and George Webb and Paul Cottrell were involved intimately in ceding this narrative in 2020 when it wasn't yet right to put it on television.
02:14:08.300 --> 02:14:26.300
When it wasn't yet right to put it on the intellectual dark web, there were people way, way out in the fringes that were already driven, promoted and encouraged to talk about the worst case scenario of 1 billion dead because of the release of a bio weapon.
02:14:27.300 --> 02:14:39.300
And that consensus was used as a seed to terrify people and to try and solve this mystery of where is the mystery virus.
02:14:40.300 --> 02:14:53.300
And the people on television and the people in social media and these people creating this illusion of consensus about the faith wants you to believe that excess death is the mystery virus.
02:14:54.300 --> 02:15:03.300
I mean a million 200,000 people so far have been killed in America by COVID means that all the excess deaths were due to COVID.
02:15:05.300 --> 02:15:14.300
And the magic trick, the enchantment that they are pulling there is that they are not doing the math correctly because if you want to know who the mystery virus killed, you've got to take the excess deaths.
02:15:15.300 --> 02:15:21.300
And then you've got to subtract the people that we didn't resuscitate in New York and elsewhere to prevent spread.
02:15:22.300 --> 02:15:26.300
You've got to subtract all the people that we ventilated to prevent spread.
02:15:26.300 --> 02:15:32.300
You've got to subtract all the people that we didn't give antibiotics to because antibiotics don't work on a viral pneumonia.
02:15:33.300 --> 02:15:39.300
You've got to subtract all the people that we didn't give steroids at the right time to because steroids are inappropriate for COVID.
02:15:40.300 --> 02:15:45.300
You've got to subtract all the people that got remdesivir, deteriorated and died from it.
02:15:46.300 --> 02:15:53.300
You've got to subtract all the opioid deaths that were extra because they were also roped in as part of the excess deaths.
02:15:55.300 --> 02:16:01.300
And you've got to subtract all the death certificate fraud that was driven by the PCR and driven by the financial incentives.
02:16:02.300 --> 02:16:04.300
And when you do that, there's nothing left.
02:16:05.300 --> 02:16:09.300
And that's why all the people that are preserving the faith don't do that math.
02:16:10.300 --> 02:16:19.300
That's why all the people who are preserving the faith don't talk about the PCR fraud, the lateral flow fraud, the variants and all the other crap about the virus because then you have to do the math.
02:16:24.300 --> 02:16:31.300
And if you do the math, you dispel this faith, the faith of a novel virus that millions died and were saved.
02:16:34.300 --> 02:16:36.300
The gain of function is real and a virus will come again.
02:16:37.300 --> 02:16:42.300
And that narrative is really, that's how they did it. That's what this faith is codified.
02:16:43.300 --> 02:16:51.300
The UN codified the faith of a novel virus in a PCR test with financial incentive in the US was ready to act on this plan.
02:16:52.300 --> 02:16:56.300
The only way that the molecular biology could be reels if they used an infectious clone.
02:16:57.300 --> 02:17:05.300
And the goal is the total surrender of individual sovereignty and enforcement of a global fundamental inversion from basic human rights to basic granted permissions.
02:17:07.300 --> 02:17:11.300
It's an illusion of consensus about this faith.
02:17:13.300 --> 02:17:25.300
An illusion of consensus that was started in 2019 with the intellectual dark web, including Brett Weinstein, Eric Weinstein, Sam Harris, Jordan Peterson, the whole nine yards.
02:17:26.300 --> 02:17:41.300
And then it was ceded with Rand Paul and Tony Fauci lying and fighting and that was ceded by the narratives and ceded by the proximal origin paper and the big dispute about what language they used and how dismissive they were.
02:17:42.300 --> 02:17:49.300
And then by the the Shenxi Lee science paper and then Omicron came out in South America and everybody thought it was a white hat and now we're here.
02:17:50.300 --> 02:17:55.300
And for three years, all the people that have been promoted on social media have never questioned the faith.
02:17:56.300 --> 02:17:58.300
Elon Musk has never questioned the faith.
02:17:59.300 --> 02:18:05.300
Peter Teals never questioned the faith. The Weinstein brothers have never questioned the faith. Sam Harris loves the faith.
02:18:06.300 --> 02:18:13.300
Tony Fauci is the priest. It's all people keeping us in this illusion of consensus of a mystery to solve.
02:18:14.300 --> 02:18:18.300
And by accepting the mystery and trying to solve it, you accept its premises.
02:18:19.300 --> 02:18:27.300
Once you've accepted its premises, then they can change your mind and give you an illusion of consensus that we don't know what's going on and then doctors behave stupid for three years.
02:18:28.300 --> 02:18:32.300
And now we have the excess deaths that we can invert and call a disease.
02:18:36.300 --> 02:18:37.300
That's what this was.
02:18:38.300 --> 02:18:47.300
We were solved into salt. We were fooled into solving the mystery and this mystery is really just a conflated background signal they lied.
02:18:49.300 --> 02:19:00.300
The faith is a lie. The diagnostics are lies. Their fidelity is a lie because it was an endemic background and it doesn't really matter what it was.
02:19:01.300 --> 02:19:07.300
But I think the best explanation is probably an infectious clone because the protocols were murder and transfection is not medicine.
02:19:08.300 --> 02:19:16.300
They might have transfected some people with something that wasn't an infectious clone, maybe just a spike protein or, you know, I don't know, anthrax or something like whatever you want to make up.
02:19:17.300 --> 02:19:23.300
But there are definitely, this is not the solution. It was a conflated background signal because the faith is a lie.
02:19:24.300 --> 02:19:29.300
That's kind of, that's kind of where I'm at. It's kind of how I feel.
02:19:30.300 --> 02:19:44.300
And I think that the players don't address the PCR fraud and all of the fraud about the virus and about replication competence and about transfection in general as we talk today specifically, and they never talk about natural immunity.
02:19:45.300 --> 02:19:53.300
I'm the only person, I don't want to toot my own horn, but I'm the only person who spent hours and hours talking about immunology.
02:19:54.300 --> 02:20:12.300
I'm the only person who has at least three five hour immunology streams under his belt in the last three years. Nobody else. Nobody else. Nobody else. Not one of these people. None of them.
02:20:15.300 --> 02:20:24.300
And that's because we are at a time point where they want your data. So they don't, there's no incentive to teach you this biology so that you understand its sacredness.
02:20:24.300 --> 02:20:34.300
The incentive is for you to think that it's just not even worth protecting or not even worth respecting. We're on the verge of cracking it.
02:20:35.300 --> 02:20:45.300
Ladies and gentlemen, intramuscular injection of any combination of substances with the intent of augmenting the immune system is dumb, transfection is not immunization.
02:20:45.300 --> 02:21:06.300
Thank you guys for joining me.
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It has been a pleasure to be here tonight. My voice held out pretty well. It feels pretty good. I guess I'm going to get a good night's sleep tonight.
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I don't know. It's been 50 in a row. If I make it to the doctor and the doctor says I can't talk for a while, then it's just going to stop.
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But the worst case scenario starting on November 2nd through November 5th, I will be off and back on November 6th.
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Just so you know, there is going to be a break to this 50. We're not going to get to 400 just yet, but the streak is alive and I will see you tomorrow. Thanks guys.
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Thank you so much for joining me.
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I'm going to have you on soon, Albert. I promise I'm going to have you on soon. Things are really busy behind the scenes, so I'm having no guests right now. It's nothing to do with you. I just need to clear my schedule.