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Vaccins ARNm : ce que vos cellules sont réellement chargées de fabriquer — Transcript

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0:00Toxin's science show, Alexandre
0:04Cuniaval. Dear Toxin listeners, hello
0:10and welcome to a new edition of your
0:12scientific curiosity show on Toxin Plus
0:15. Today is October 8, 2026. Apparently,
0:19it's noon. You must like this first, or
0:23Roxan will yell at me; I don't want
0:26that, and neither do you. So give it a
0:29thumbs up, because it's really very
0:31important so that the show can be
0:33broadcast, known, relayed, and so on,
0:35so that it can continue to exist, so
0:37that we can receive guests as important
0:39as the ones I have today. I'll
0:44introduce them to you in a moment, but
0:45first, a word of introduction. Because
0:47as you know, dear listeners, there are
0:50shows that are lighter than others, and
0:52there are some where we have a little
0:54fun: we let our curiosity wander into
0:57areas that are not more or less serious
0:59, but that can sometimes amuse us a
1:02little. And here, we're going to return
1:06to a topic that amuses us much less,
1:07which is one of the reasons for the
1:09existence of this channel. Because the
1:13world changed over 5 years ago now,
1:16during the Covid era, and there is no
1:19serious retrospective analysis of this
1:22major crisis that has affected the
1:25world, the West in particular and,
1:28unfortunately for us, France and Europe
1:31. This assessment is made, it is made
1:35largely by this book ANM, the forbidden
1:38assessment under the direction of
1:40Patrick Stoco, whom I have the honor of
1:43receiving. Hello Patrick Stoco.
1:46>> Hello Alexandre. Hello everyone.
1:48>> So let me quickly introduce you, you
1:51are a biologist specializing in
1:53molecular virology and so you directed
1:55this book at RNM, the forbidden
1:57assessment and you asked Pierre
1:59Chaillot. Hello Pierre. Hello Alexandre
2:02>> to write a preface. So Pierre Chariot,
2:05I don't need to introduce him to our
2:07statistician listeners. He has already
2:09done us the honor of appearing several
2:11times on Toxin and already on my show.
2:13Thank you very much Pierre for coming
2:15back. So we're going to do an overall
2:18assessment in an hour, obviously, but
2:21on the occasion of the release of this
2:24very important book, let's take stock,
2:26this forbidden assessment. Uh, I wanted
2:30to start Patrick Stoco by asking you a
2:32question because you are, as I said, a
2:34specialist in molecular virology. What
2:36is molecular virology?
2:40>> Ah, so molecular virology is the part
2:43of science that deals with tinkering
2:47with viruses. To put it simply, if you
2:52like, since the 1980s, with the
2:54discovery of restriction enzymes, we
2:57have been able to take the genetic
3:00material of viruses, we have been able
3:04to analyze it, we have been able to cut
3:07it into small pieces, we have been able
3:10to reassemble these elements of the
3:14genetic material of viruses. And
3:18molecular virologists, in fact, that's
3:21their job. Their job is to mistreat
3:25these viruses, to tinker with them, and
3:27to also manufacture new ones. Because
3:30when you do research in molecular
3:33virology, you inevitably create new
3:35viruses for the purposes of the
3:38experiments you conduct. You create new
3:41viruses that are supposed to stay in
3:44the lab and not escape. So, as a lawyer
3:49, I have a question for you: when
3:51molecular virologists create new
3:54viruses, can they by any chance file
3:57patents on them? Absolutely. Of course.
4:03And that is precisely the whole point,
4:05because molecular virologists are also
4:08working on behalf of the pharmaceutical
4:10industry today. And when you create a
4:14new sequence, for example, which is
4:16exactly the case with messenger RNA,
4:19when you create a sequence that will
4:22then allow you to make a vaccine, you
4:25obviously take out a patent on that.
4:28And for example, for SARS-CoV-2, which
4:31is at the origin of the Covid crisis,
4:34we know that SARS-CoV-2 was the subject
4:37of three patents, which are now known.
4:41You can find the references for the
4:42three patents in the book that you have
4:44on the table. Patents that date back to
4:482002 and then two patents that date
4:52back to 2016. So this synthetic virus
4:56was patented.
4:59>> There you have it. So you have given me
5:01the opportunity with my big shoes to
5:03start. So this first piece of
5:06absolutely edifying information. You
5:09confirm to us that this virus that we
5:12knew about in 2019 and 2020 and then
5:14later contained sequences that were
5:17patented before. We agree with that
5:22>> completely. It is an artificial virus
5:25>> and this artificial virus has been
5:27patented. It has been the subject of
5:29three patents. Yes.
5:31>> So what I was telling you just before
5:33starting this program is that in this
5:36crisis, I don't even know what to call
5:38it, in this episode where so many
5:41things have been turned upside down,
5:43wherever you look, there is scandal. So
5:46here, we start with the fact that in
5:48reality, contrary to what we have been
5:50told, well yes, this virus is indeed
5:52artificial, it is a human creation with
5:54sequences that were previously leaked.
5:57Well, the question of whether the
6:00spread was intentional or not is
6:02another question, but in any case, here
6:04is the first lie that falls. You,
6:08Patrick Stoco, when you were tasked
6:10with writing this book with a team,
6:11could you perhaps tell us a little bit
6:13about who was on this team, by the way,
6:15RNM, the forbidden balance sheet. What
6:18exactly was the most important point,
6:21or perhaps the most salient one, that
6:24served as the primary motivation for
6:27you to write this book? So, listen,
6:31there are two elements. The first
6:34element is that a large part of this
6:36book, I'm thinking in particular of
6:38chapters 1 and 2, is made up of
6:40elements from my journal. As a
6:44biologist specializing in molecular
6:47virology since always, even well before
6:512020, I keep a journal and in this
6:54journal, of course, we find things that
6:57are not at all in line with the doxa of
7:00Covid. And so over time, I told myself
7:05that it would be a shame not to set in
7:08stone all the notes that I took over
7:11the years. All the notes I took over
7:15those years, that was, if you like, the
7:18primary motivation: to keep a record of
7:21what a specialist in molecular virology
7:24witnessed, and what he witnessed is not
7:27at all what the Doxa tells us. That's
7:31the first thing. And then the second
7:34thing is that as soon as these
7:36experimental gene injections were
7:38deployed, I explained to you earlier on
7:40air that these were not vaccines but
7:42experimental gene injections that do
7:45not work at all like vaccines. Well, we
7:50started counting the deaths and so from
7:542021 up to 2,000, well, up until today,
7:57the number of deaths that we have been
8:01able to count worldwide is absolutely
8:04phenomenal. I mean, Pierre, who is next
8:08to us, wrote a book in Pierre, your
8:11book on the victims, what was it? 25,
8:13huh? He wrote a book in 2025 where he
8:20already lists the number of deaths due
8:23to these injections in Europe. And I
8:27don't want to speak for you, Pierre,
8:29but for Europe, we have already reached
8:30roughly 300,000 deaths, just for Europe
8:32. And if you then count the deaths in
8:37the United States, if you count the
8:40deaths in the southern hemisphere, if
8:42you count the deaths in Japan, well,
8:45over the last five years, we arrive at
8:47a low range. I really want to keep this
8:53low range figure of around 4 million
8:57deaths. And so, why was it that I
9:01wanted to set this in stone? Well,
9:05because we are dealing here with the
9:07biggest catastrophe in the history of
9:10the pharmaceutical industry.
9:14>> So, hold on, Patrick Stoco, I'm going
9:17to turn to Pierre Chaillot because the
9:20figures you give us are, well, how can
9:23I say it, it's outrageous, it's almost
9:26deafening. We've never heard of figures
9:30of this magnitude. Pierre Chaillot, so
9:34you're confirming yourself, you're
9:36going to give us these figures again,
9:38perhaps with a geographical and
9:40temporal detail. So you're confirming
9:44this magnitude? So, the work that I
9:47conducted in the book that came out in
9:492025 focused on European data. So I
9:51didn't look at other data sources, but
9:53for Europe, yes, I can confirm. The
9:56calculation was carried out using two
9:58completely different methods. The first
10:01was to use the results of
10:02pharmacovigilance, that is to say,
10:04people who complained about adverse
10:05events related to vaccines in Europe.
10:09And using these results, we arrived at
10:11an estimate that the pharmaceutical
10:13industry considered low and minimalist:
10:15300,000 deaths. That is to say,
10:19according to the pharmaceutical
10:20industry, pharmacovigilance reports are
10:22extremely underestimated, and by taking
10:24the ratio used by the pharmaceutical
10:26industry to assess the adverse effects
10:28of their own products, we arrive at a
10:30figure of approximately 300,000 deaths
10:32in Europe.
10:33>> So 300,000 deaths on the European
10:35continent.
10:36>> Yes. Uh, and over what period?
10:38>> Regarding the period, I published my
10:41book in 2025, so we were looking at the
10:43period from 2021 to 2024, approximately
10:46. So, the deployment started timidly at
10:50the beginning of 2021. Let's say it was
10:53almost complete from mid-2021 until I
10:56wrote my book, let's say mid-2024,
10:58something like that. So over the space
11:01of 3 years. Wait,
11:03>> let me just say that, to me, this seems
11:05absolutely enormous. How can we
11:07establish these figures? You, Pierre
11:11Chaillot and Patrick Stoco, in your
11:13book, Le bilan interdit, tell us that
11:16we must distinguish between deaths with
11:18Covid and deaths from Covid. Do we
11:21agree with that? I
11:23>> have one more nuance, but if we're
11:25talking about vaccines, I'll just
11:27finish because I'm going to talk about
11:29the first of the two methods. The
11:32second method that I also developed was
11:34published in an international
11:36conference on bioinformatics and
11:37biostatistics with the Belgian
11:39researcher Patrick Meyer. We published
11:42our work on this in 2020 at the end of
11:44December 2025. The second method was to
11:47take the weekly number of deaths in all
11:49European countries by age group. These
11:51figures are available from Eurostat. So
11:53we have been monitoring the evolution
11:55of the number of deaths every week
11:57since we must have gone back to the
11:581980s or so. And we compare these death
12:01figures to the vaccination period and
12:03the number of vaccines that have been
12:05distributed. And we observe that during
12:08vaccination campaigns in all European
12:11countries by age group, there are
12:13increases in deaths during all European
12:15countries and for all age groups, we
12:18make this observation. So when we have
12:20an abnormal peak in deaths that appears
12:23in the observed mortality rate, people
12:25die every day in all European countries
12:27. Among the elderly, for example, there
12:29are peaks in deaths during each heat
12:30wave. There are peaks in deaths every
12:31winter. This can be seen in young
12:33people. The situation is rather flat.
12:35They are not very sensitive to
12:36temperature variations and to getting
12:38sick during temperature variations.
12:40Well, if we make this comparison, we
12:42notice peaks in deaths in all age
12:43groups that are abnormal and that
12:45appear like this in the calendar, we
12:47don't know why. And when we compare the
12:49number of vaccines received by this
12:51same population at the same time,
12:52everything seems to agree to show that
12:54there is a real correlation between the
12:56two. And this is what was the subject
12:58of a scientific publication with
12:59Patrick Meer. And so what this means is
13:02that with this method, since I notice
13:03that every time there is a vaccination
13:05campaign, there is a peak in mortality,
13:07I think that there is perhaps a link
13:09between the two. This link can go in
13:11both directions, as usual in statistics
13:12. Either we are vaccinating the dead,
13:14which would be strange, or we are
13:16vaccinating and the person dies
13:17afterwards. Which seems to be the most
13:20logical explanation. In doing so, we
13:22can estimate, I'll just finish with the
13:24estimate.
13:24>> Yes, please. If we consider that these
13:27peaks in deaths are possibly due to
13:29vaccination, we also arrive at the
13:31result of 300,000 deaths. Which means
13:33that we have two radically different
13:36methods. Pharmacovigilance on the one
13:38hand, and counting deaths on the other,
13:40which both arrive at the same estimate
13:42of magnitude of the number of deaths on
13:44the European continent. Which means
13:46that in my opinion, we are still quite
13:48reliable in being able to give an
13:49estimate. No, no, but listen Pierre,
13:53you answered what I wanted to ask you,
13:55it was clear that we had two distinct
13:56methods
13:58>> that lead us to the same result. So,
14:00it's an order of magnitude, I imagine,
14:01we're not going to be precise,
14:03>> but that being said, 300,000 deaths,
14:07well, we
14:09>> agree, we're talking about that,
14:11directly due to injections. And so
14:13Patrick Stoco, you're perhaps going to
14:16distinguish between vaccines and gene
14:18injections in a moment, but that's what
14:21we're talking about. 300,000 deaths
14:23directly due to injections, whatever
14:26they call them, over 4 years.
14:28>> In any case, 300,000 deaths perfectly
14:30correlated to injections. If you then
14:32have an explanation to tell me why
14:34people would die of another reason, I'm
14:36ready to hear it. But in any case,
14:38there is a correlation that is perfect.
14:41>> If I may...
14:42>> Yes, please.
14:44>> Allow me to add something. So,
14:47obviously Pierre, I quote Pierre in the
14:50book and I also base myself on his work
14:53, but he has a little rule of three. I
14:58think all our listeners are capable of
15:00doing a little rule of three in their
15:02heads. Basically, you have 500 million
15:06inhabitants in Europe. Out of 500
15:10million inhabitants in Europe, as
15:13Pierre just said, there could be
15:15300,000 deaths due to these
15:18experimental gene injections. We have
15:22vaccinated 5 billion people. So, that's
15:2710 times more. So there's no reason to
15:32imagine that in the United States,
15:35Japan, Australia or wherever, people
15:37are more resistant to these injections
15:40than they are in Europe. So if we get
15:45to 300,000 deaths in Europe for 500
15:48million inhabitants, well, for 5
15:50billion, you have 3 million deaths at
15:53the bottom. And so, I was telling you
15:59earlier that by doing a little more
16:03elaborate calculations, I have a low
16:07range of 4 million deaths worldwide
16:11over the last five years. And you see
16:15that we are there.
16:19>> Yeah, it's absolutely edifying. I would
16:23like us to review a vocabulary word
16:25because you talked about experimental
16:28gene injections and you clearly
16:30distinguish it from vaccines. So, I
16:32apologize for some who have already
16:33heard this distinction, but we'll go
16:35over it again, it doesn't matter. Why
16:37do you make this distinction and what
16:39does it mean?
16:41>> Because, uh, the WHO, uh, changed the
16:45definition of what a vaccine is
16:49precisely in order to justify the
16:52distribution of these gene injections.
16:58Basically, when you get a vaccine, you
17:00are injected with an antigen into the
17:02deltoid muscle. This antigen remains
17:07there and then your body makes
17:09antibodies against this antigen and
17:12then your immune system is, if you will
17:15, trained to fight against this antigen
17:18. But with experimental gene injections
17:21, it doesn't work like that at all.
17:24With experimental gene injections, you
17:26are injected with nanolipid particles
17:29that contain messenger RNA. These
17:33nanolipid particles go throughout the
17:36body, including the brain, including
17:39the heart, including the digestive
17:42system, including the eggs and so on.
17:46Uh, these nanolipid particles penetrate
17:49all the cells of your body and
17:52particularly into the inner epithelium,
17:55uh, of the blood capillaries. So
17:58>> excuse me, but the epithelium, I don't
18:00know what that is.
18:02>> Well, you have blood vessels everywhere
18:04. You have blood vessels in the brain,
18:06you have blood vessels throughout your
18:08body. Okay? And these blood vessels
18:13have an inner layer called the inner
18:16epithelium. It's a layer of cells, if
18:18you will, that's inside the blood
18:20vessels. And these nanolipid particles
18:25penetrate inside these cells and once
18:28they're inside the cells, they force
18:32these cells to produce spike proteins,
18:35which are toxic proteins. So your
18:42entire blood system, your blood
18:45capillaries, start producing proteins
18:52that are toxic to your body, including
18:55in your brain, your heart, and so on.
18:59And you can imagine that all of this is
19:02not without consequences. And so among
19:05the list of pathologies that are caused
19:08by these injections, well, there are
19:12obviously mainly pathologies of the
19:15cardiovascular system.
19:19>> So this is very important. I'm sorry.
19:22We're going to focus a little on this
19:23question of classification because in
19:25reality, in this crisis, this is what
19:26has happened all the time. The thing is
19:29that we changed the names of things or
19:31gave them names that didn't correspond
19:34in order to be able to implement
19:36policies that shouldn't have been
19:38implemented. And it seems to me that
19:41with a bit of hindsight that we're
19:43starting to have, that's perhaps the
19:46essential element of this moment. And
19:50Patrick Sto, then I'll turn to you.
19:52Pierre Chaillot,
19:53>> I don't want to monopolize the
19:54conversation. What happened, if you
19:57like, in 2020, is that the
19:59pharmaceutical companies already had
20:02the idea of marketing these mRNA
20:04vaccines, except that they were a
20:07little late and, instead of having
20:10these vaccines at the beginning of 2020
20:13, we had them at the end of 2020. They
20:16completely ruined all the preliminary
20:19studies. Anyway, Christine Coton showed
20:22this in her book. Rudolp Ster, who is
20:25the former chief toxicologist at Pizer,
20:28has just published a book also
20:30published by Marco Piéteur in which he
20:32explains in great detail all the flaws,
20:34uh, in the implementation, all the
20:37legal flaws, if you like, of the
20:39implementation of these injections. So,
20:43uh, these injections only arrived at
20:46the end of 2020. And so, we had to make
20:49people wait and make them believe that
20:52there was nothing else on hand other
20:54than these injections during the year
20:572020. When in fact, that was completely
21:00false. I show this in chapter 2 of the
21:03book. We had lots of early treatments
21:07that worked very well and that were
21:11banned outright in order to justify the
21:15deployment of these vaccines.
21:21>> Pierre Chaot.
21:22>> Yes, I completely agree with Patrick. I
21:25may have even added something
21:27additional, which is that we are faced
21:29with a new economic model for the
21:30pharmaceutical industry that has
21:32developed, which can be understood if
21:34we look at the Wikipedia page for
21:36Moderna. We see that it is an
21:38investment fund that was created, I
21:39think, in the early 2000s with the
21:41promise that we were going to move to a
21:43system, a new industrial system for the
21:45pharmaceutical industry, which is that
21:46of MNR vaccines, and which has been up
21:48against precautionary principles and
21:50ethical principles from the start
21:51regarding the fact that we should not
21:53use gene injections. And we should not
21:57do so, particularly because there were
21:59lots of trials in the 80s that were
22:01monumental disasters. With, well, glob,
22:03if I have to simplify things a little,
22:04with this type of injection, the only
22:06thing we managed to show is that it
22:07kills pigs very effectively and that,
22:09as soon as we moved on to humans, we
22:11had more or less the same result. So,
22:13that's why there were a whole bunch of
22:15trials in the 80s that were all
22:16disasters, and then they stopped, and
22:18there were a whole bunch of moratoriums
22:19that were put in place to say: "We
22:20shouldn't do that, we're stopping." But
22:23hey, uh, that didn't stop investment
22:24funds from getting involved, saying
22:26that it was extremely promising. Why is
22:28it extremely promising? That's where
22:30Patrick's job is extremely interesting.
22:33It's about simplifying all the
22:34processes, the fact that we can
22:36constantly develop products on the fly
22:38based on patents. We moved on to a new
22:41design. The concept of medicine has
22:43already changed over the last 200 years
22:44. We could talk about it for hours. But
22:47we have moved to an ultra-rapid concept
22:49, namely that to trigger a pandemic
22:51alert or to say that there was a new
22:53patient, all you need to do is find in
22:56an individual a genetic trace of
22:58something that you think shouldn't be
23:00there. We can call this element a virus
23:03if you like. There are people who would
23:05like us to change the vocabulary a
23:06little, but overall it is a genetic
23:07trace. We sequence this genetic trace
23:11and from this sequencing, which is just
23:13a list of computer letters, well, a
23:15list of letters that correspond to the
23:17sequence of this object, we can
23:19immediately create tests and then
23:21vaccines using molecular virology.
23:26Which means that we have moved from an
23:28old system where we studied patients to
23:30try to discover why they were sick. We
23:32conducted studies to try to perhaps
23:34find a pathogen. And then we studied
23:36this pathogen in the laboratory in a
23:37visible way. Uh, which took years, and
23:40then we tried to make a vaccine, all
23:42that went with it. We could discuss the
23:44effectiveness of all vaccines on this
23:46subject, uh, but with an ultra-rapid
23:47method where I find a sequence, click
23:49and then I can immediately make a test
23:51that I can sell on a large scale around
23:53the planet and earn billions. By the
23:55way, the tests have brought in much
23:57more than the vaccines, uh, in terms of
23:59pure money, and then I create vaccines.
24:02And so this technology, a question
24:04Pierre Cha, because I don't completely
24:06follow you on the reasoning, because
24:07from what I understood of what a
24:09vaccine is, but...I'm talking about
24:11under your control and especially under
24:13the control of Patrick Sto, that
24:15precisely for me, to get vaccinated, I
24:19had to generate antibodies. And if I
24:22just have a, how to say, a genetic
24:24sequence that I can, so I understand
24:26that I can test it because I can
24:28recognize it, that's right. But how can
24:31I immediately create a vaccine? I don't
24:36see the direct connection between the
24:38genetic sequence and the vaccine.
24:43>> The simple principle is to teach your
24:45body to recognize this sequence so that
24:48it can fight it more effectively. We
24:51can teach it either to recognize the
24:53sequence itself or to recognize a
24:54protein created by this sequence. In
24:57the idea of genetics, we have DNA that
24:59is supposed to produce RN and RN is
25:01supposed to create proteins. So,
25:04according to the theory of immune
25:06protection, we can teach you either to
25:08fight against a sequence or to fight
25:10against a specific protein linked to
25:11this sequence. And that's why you just
25:14need to have the sequence of the object
25:16to then create a vaccine that is based
25:18on, well, first a test to try to see if
25:21you have this sequence on you and then
25:23also a vaccine that is supposed to help
25:25your body fight against this sequence.
25:27Patrick, I'm not talking nonsense.
25:29>> Yes, if you don't mind, I'll just give
25:31you a little extra information. With
25:33traditional vaccines, we injected the
25:37protein that had been synthesized
25:40industrially. We injected it directly
25:43into the patient and then the patient
25:45produced antibodies against this
25:46protein. Except that producing proteins
25:50in very large quantities for hundreds
25:52of millions of people is very expensive
25:55. So the pharmaceutical industry had
26:00the idea of having you, your cells,
26:03produce the proteins that your body
26:06will fight against by producing
26:09antibodies. So now the factory that
26:14manufactures these antigens is you,
26:17you're the one who does the work,
26:19you're the one who's supposed to
26:22produce these Spike proteins, in this
26:25case for the MRENA vaccine, but you do
26:31the work of the manufacturers. Your
26:35body does the work of the manufacturers
26:37and then your body still has to figure
26:39out how to fight against the proteins
26:42that it produced itself. So that's
26:46pretty strong to
26:48>> see if I'm following you correctly. So
26:50in the RNA injection, I am injected
26:53with RNA sequences that will spread to
26:55all the cells in my body
26:59>> and then do the same thing as normal
27:02RNA, creating and synthesizing proteins
27:05in each cell of the body. And these
27:09proteins are designed to fight
27:12>> the intruder. No, these proteins, no,
27:16these proteins are toxic, so they will
27:19stimulate your immune system and your
27:22immune system is very likely to attack
27:25the cells, your cells that produce
27:28these toxic proteins.
27:31>> Oh yes. So in fact, there is something
27:33that completely escaped me. When you
27:35inject RNA, it is not to synthesize
27:38something that will fight the bad guy,
27:40so to speak. It is to synthesize the
27:44bad guy against whom I will create my
27:46own defense. And it is this defense
27:48that evolves infinitely.
27:50>> Exactly. So
27:52>> how long does RNA stay in the body
27:53afterwards? Well, you're going to
27:56synthesize nasty proteins, spike
27:58proteins, for 3 and a half years.
28:02>> You say that, Patrick, because we now
28:04have 3 and a half years of hindsight
28:05and we're still finding them.
28:06Absolutely.
28:07>> Yes, yes,
28:09>> but you see, I think that some of the
28:11listeners must be like me and who
28:12hadn't really understood this mechanism
28:14.
28:15>> Yes, that doesn't surprise me. So, well
28:19, listen, I understand better why you
28:21call it experimental gene injection and
28:24not a vaccine because in fact we're not
28:26talking about the same thing at all.
28:28>> Not at all. And so, it's much more
28:31serious than what I'm saying, as usual,
28:34because not only are you going to
28:36produce the toxic protein yourself, but
28:39you're going to produce lots of other
28:41proteins that we know absolutely
28:43nothing about, because the DNA, the
28:46mRNA that you've been injected with is
28:48an unstable mRNA, and your cells are
28:51going to produce not only the spike
28:53proteins that your body is going to
28:55fight against, but your body is also
29:00going to produce a certain number of
29:02ghost proteins which are proteins that
29:05we know absolutely nothing about and
29:07which are also potentially toxic
29:09proteins, uh, and that your body is
29:12going to have to defend itself against.
29:16And then, I'll just add one last thing
29:19for the record: in addition, this
29:21messenger RNA that's inside your cells,
29:24we now know that it's, uh, that it's
29:26likely to be retranscribed into DNA,
29:31and this DNA will be integrated into
29:35your genome without your knowledge. And
29:39integrating random DNA sequences into
29:42your genome is a process that is
29:45strictly carcinogenic.
29:49>> So, wait, let's go back to this
29:51sequence to stay in the DNA vocabulary.
29:55So, RNM, or messenger, is normally the
29:57messenger of DNA, these are small
29:58sequences that are then responsible for
30:00synthesizing proteins. Do we agree?
30:04Here, we forcibly inject RNA sequences
30:07into the body artificially and you say
30:09that they are retro-encoded. That means
30:12that it is the RNA that modifies the
30:13DNA, which is the same everywhere in
30:15all our cells. Do we agree?
30:17>> Not quite.
30:18>> Well, not quite. Well,
30:19>> not quite. No, but to do this,
30:22>> let's talk globally, but so this RNA
30:25comes back and modifies my DNA. There
30:29is a part, there is a part of this DNA
30:31that is degraded as the pharmaceutical
30:33industry hoped. Uh, there is a part, uh
30:36, we don't know what this part is in
30:39reality, what is the proportion that is
30:42truly degraded in 48 hours within the
30:44course. And what we do know is that
30:48there is a part of this messenger RNA
30:51that is in certain cell lines
30:54transcribed into DNA and this DNA is
30:57going to integrate into the nucleus of
31:00your cells and it completely disrupts
31:04the genetic functioning of your cells.
31:08And Nicolas Hulcher has just published
31:11a paper in the United States. You may
31:13have seen it, Pierre. They have just
31:16published a paper in the United States
31:19in which he shows that plasmid DNA from
31:22these injections was found in a
31:24carcinoma inside the heart of a patient
31:27who had died. So it's the smoking gun
31:30as he says. Uh, these sequences are in
31:34fact directly responsible for the
31:37development of turbocancer. Pierre Chau
31:45. No, I'm sorry but I'm really shocked,
31:48it's much worse than I imagined. So yes
31:51, yes, I'm just going back so that we
31:54don't lose track of what we just said
31:56at the beginning. This crisis has
31:59mainly allowed the pharmaceutical
32:01industry to launch a new process that
32:04has been validated. As we said at the
32:08beginning, this type of messenger RNA
32:10injection was prohibited because the
32:12trials had not been conclusive, which
32:14is an understatement so far. Billions
32:18were invested in certain funds like
32:20Moderna, but also in others to say that
32:22this was necessarily the technology of
32:23the future. And the Covid-19 crisis has
32:27allowed these new technologies to be
32:31authorized everywhere. And so in the
32:34book, R&M, the forbidden balance sheet,
32:37it doesn't just talk about virology, it
32:41also talks about law, philosophy, and
32:44ethics. And, uh, we can clearly see, uh
32:46, particularly in the second part of
32:48the book, all the mechanisms that have
32:50been put in place, so-called emergency
32:52mechanisms that are everywhere, that
32:54have allowed everything to pass, and
32:56everything is, and everything was, has
32:58been forced through in order to enter
33:00this pharmaceutical industry 2.0 zero,
33:02based on something that is completely,
33:05let's say, outside of reality, that is
33:07to say, I have a theoretical sequence.
33:10In fact, I try to annoy as much as
33:11possible all the time in order to have
33:13the rights to it and as soon as I can
33:15say, well, there is a new pathogen of
33:17this sequence that arrives, I will be
33:19able to immediately and industrially
33:20launch tests and vaccines. And so that
33:24really means we have entered a new era
33:26of so-called medical management or
33:28epidemic management. An era that is
33:32done extremely quickly. It is a real
33:34highway where in the future all we will
33:36have to do is file a sequence and say,
33:38"Here is a new pathogen." Well, that's
33:40great. I have it. I had patented it, so
33:42it's available and I'm starting
33:44industrial production of everything
33:45that goes with it. Uh, and so in my
33:47opinion, this is really the case. We
33:50have a complete paradigm shift that
33:52people may not have understood, but
33:54what happened during the Covid-19
33:56period is entirely reproducible
33:57indefinitely in the future with any new
33:59sequence that will be called viral,
34:01epidemic, problematic and that will
34:03have to be dealt with by force in the
34:05same way. For the pharmaceutical
34:09industry, developing a new vaccine with
34:12these technologies takes a week. And a
34:18test is the same. Developing a test to
34:21then create the epidemic of tests that
34:23we experienced and the epidemic of
34:25positive cases that we experienced
34:26takes a few days and so we are really
34:28in something that has become immediate.
34:31We have changed register. We are no
34:33longer in a medicine that was concerned
34:35with finding out if there were new
34:37patients somewhere, and that treated
34:39waves of patients like there are every
34:41winter, for example. So, a medicine
34:44that deals with the reality of what it
34:46has in front of it, a sick person or a
34:48healthy person, to a medicine based on
34:50something that is of the order, that is
34:52decorrelated from reality, that is
34:54based on tests where we consider that
34:56any person is a kind of potential
34:58murderer on foot who should be tested
35:00every day to find out if they are not
35:02vectors of a disease, to then be able
35:04to impose constraints on them, declare
35:06epidemics, and force them to receive
35:08injections. The paradigm shift that is
35:12denounced in this book goes far beyond
35:14the question that we talked about
35:16earlier, of the number of deaths linked
35:19to these particular injections. But
35:22really the idea is to become aware that
35:25we have radically changed the way we
35:27approach medicine, health care for
35:29populations, etc. Freedom, freedom of
35:31choice, is truly a colossal change.
35:35>> Absolutely. And that's what I was
35:37saying in the introduction, hence the
35:38importance of this program, but
35:40especially the work that you, Patrick
35:41Stoco and the team, have done. What I
35:44was telling you before the program is
35:47that it's still astounding that we
35:50don't have a documented public
35:52assessment, etc., of this period.
35:55Pierre Chaillot, you rightly said that
35:58this book is also interesting because,
36:03in addition to the virological and
36:05medical analyses, there is a whole
36:07section, as you said, of legal and
36:09philosophical analysis that
36:11particularly interested me. Especially
36:13the legal aspect. I'll just read you
36:16the introduction to the legal section
36:19of the book, which is short but has the
36:21merit of being effective. MNR
36:24injections against Covid-19 should be
36:26banned in Switzerland, I should point
36:28out, because the work concerns
36:30Switzerland. It is also very
36:32interesting because we have a different
36:34point of view than we French. So banned
36:36in Switzerland, not nuanced, not
36:38monitored more closely, not simply
36:40advised against for certain groups,
36:42banned because the medical, ethical and
36:45legal conditions for responsible mass
36:47prophylaxis are not and have never been
36:50met. Period. It deserves to be
36:53extremely clear and I am glad that we
36:56are speaking clearly like this, because
36:58on a legal level, it is true that
37:01nothing is working. But why? Because
37:05that is exactly what you were saying
37:07Patrick Sto, in fact the names have
37:08changed, the categories have changed.
37:11You said, we talked about gene
37:13injections instead of vaccines, we used
37:15protocols for others, but in law, in
37:17fact, we were arguing about an
37:18extraordinary situation. to attack
37:22head-on things that seemed absolutely
37:25normal. I'm thinking of patients 'free
37:28and informed consent to medical
37:30procedures. I'm thinking of freedom of
37:32conscience. I'm thinking of human
37:33dignity when people are forbidden from
37:36burying their dead. It's as old as
37:39civilization itself, I'm thinking of
37:40silly things like freedom of movement
37:42that seemed to go without saying, or
37:44free enterprise, and so on and so forth
37:45. In the end, all of that was thrown
37:48out the window with a snap of the
37:51fingers, without examining the most
37:53obvious conditions of proportionality,
37:56and without the institutions that are
37:58made for that reacting in any way.
38:03Obviously, the scale of the attacks on
38:05fundamental freedoms and fundamental
38:07rights would have merited this a priori
38:09control, but obviously it would have
38:11merited a posteriori control. And to my
38:14knowledge, this a posteriori control
38:16has not taken place. And what interests
38:19me, and here we each have our own
38:21perspective, is that whether it's you,
38:24Patrick Stoco, as a virologist, whether
38:26it's me as a lawyer or you, Pierre
38:28Chaillot, as a statistician, we see
38:30that there is a common point in this
38:32crisis: words have changed meaning, the
38:34objects that were being studied have
38:36changed categories. Do you share this
38:40feeling, Pierre Chaillot? Yes. Uh,
38:44mastery of language is what has indeed
38:46allowed us to enter into a discourse
38:48and not to leave it. Uh, the question
38:51of words is quite crucial, from my
38:53point of view in statistics since, uh,
38:56statistics is in fact counting
38:58something, uh, but to count something,
39:00you first have to define it. So you
39:03have to give a definition of an object
39:05and then provide the means to count
39:07this object. And so the person who
39:10decides on the definition of an object
39:12and the means to count it decides the
39:14final result. That's exactly what a
39:17statistic is. Well, if we take the
39:20example of the definition of COVID, we
39:22immediately created a vague and broad
39:25definition of a pathology that brings
39:27together a whole bunch of diverse and
39:30varied symptoms that are all included
39:32under the name COVID. You can still
39:36open your browser today, ask for all
39:38the possible symptoms and it will
39:40answer you, well, everything: fever,
39:41headache, difficulty breathing, intense
39:44fatigue, nausea, diarrhea or even
39:45nothing at all. And what makes it a bit
39:48annoying when we do statistics is to
39:50think that we have an object that we
39:52didn't define correctly initially, so
39:53we don't know how to count it. So what
39:56are we going to have as a result with
39:58an increase in the number of COVID
40:00cases? Just the fact that we started
40:03counting things and what we see in the
40:06statistics, particularly in hospitals,
40:08where we told people, "Look, we had
40:10incredible waves of patients who
40:12overwhelmed hospitals in 2020." We
40:14discovered later that hospitals had
40:16never been filled as quickly as they
40:18were in 2020. And we discovered that,
40:20for example, in terms of respiratory
40:23illnesses in France, 2020 was a
40:24perfectly normal year. Absolutely
40:27nothing happened, there is no trace of
40:29a new wave of patients appearing at any
40:32time since the start of this crisis. We
40:35can clearly see this notion of
40:36vocabulary. We created a new word, the
40:39word Covid, which we gave a definition
40:41that is not scientific, a variable
40:43definition, and we put a whole bunch of
40:45things in it. Secondly, there are the
40:49famous tests that have appeared to do
40:51COVID tests where we said, well, test
40:53yourself, you will know if you have
40:55Covid. There are different types of
40:58tests. We test, namely the PCR if you
41:00have a predefined piece of genetic
41:02sequence on you. That's it, you are
41:05considered positive with a PCR test. Or
41:07you have an antigen test where we check
41:08if you have this or that protein on you
41:10. Overall, that's pretty much it. Uh,
41:12and these traces said well if you have
41:14a positive test, you will be fine and
41:15in perfect health, well you are sick
41:17with Covid. Well, we have interesting
41:19statistical results where we can
41:21compare the fact of being sick with the
41:23fact of having a positive test and we
41:25realize for France in particular that
41:27there is no connection between the two.
41:29Which means that there is no connection
41:31between the fact of being sick and
41:32having a positive test. There just
41:34isn't one. It's quite easy to check.
41:38And so, once again, we've used a
41:40vocabulary where we've said that being
41:42sick is no longer having symptoms, but
41:45being sick is being subject to a
41:47positive test. I'll give an example for
41:51our listeners. Imagine, everyone knows
41:53what a pregnancy test is. A drawing,
41:56peeing on a test and that's it. If the
41:58test has two bars, it means you're
41:59pregnant. It's a test that's not
42:00perfect, right? It has failures in both
42:03directions. Imagine that we take all
42:05the little 9-year-old boys in Europe,
42:06there are about 5 million of them, and
42:07we make them all pee on the same day on
42:09a pregnancy test. You're going to get
42:10positive tests. There you go. What do
42:12you do with a little 9-year-old boy who
42:14looks at you with a positive pregnancy
42:15test? Well, you start him on a
42:18pregnancy test, an asymptomatic
42:20pregnancy test of course. Then, at nine
42:22months, you will take her to the
42:24delivery room. Well, no. And even if
42:27you see a woman who has a protruding
42:29belly with something moving inside, if
42:31she pees on a pregnancy test, the test
42:32is negative, do you deny her the
42:34accident of childbirth? No. The reality
42:38is the fact of being pregnant. Actually
42:40, the test can be measured; we can
42:41calibrate it. You calibrate your test
42:44by testing it on pregnant women to make
42:46sure it says yes as many times as
42:48possible. That allows you to test its
42:50sensitivity. And you calibrate your
42:51test by testing it on non-pregnant
42:53women or men and each time it tells you
42:54"Yes, it's pregnant, he made a mistake,
42:56right, he has to say no." And that
42:57allows you to calibrate the sensitivity
42:59of the test. Okay, the fact of being
43:01pregnant for the pregnancy test is what
43:03we call a standard goal, it's the
43:04reference. The reality is being
43:06pregnant. The test is a test. The
43:08reality is being pregnant. For Covid,
43:11you have a positive Covid test, what
43:13does that tell you? How do you compare
43:16it to the COVID symptoms? But since you
43:19haven't defined any initial symptoms,
43:20it looks like Covid, it makes green
43:22antennae grow on the head. Well, we
43:23would all agree to say that there is a
43:25new identifiable disease. But here, how
43:27do you calibrate your test on the
43:28disease? You don't have it. Which is
43:30why we changed our way of reasoning,
43:33even scientifically and in medicine. We
43:35said that the test is what proves it,
43:37and that's it. So, they put the cover
43:38in your face and then if it comes out
43:40positive, you are considered
43:41asymptomatically ill even if you have
43:43nothing, but that makes no sense from a
43:45medical point of view. So, we have
43:47monopolized the language on a generic
43:48word, or rather on something generic
43:50that we have called COVID and that we
43:52do not know how to properly identify.
43:54And then, we monopolized the language
43:56on Scare sick where it has become the
43:57result of a test and no longer a
43:59symptom. So, we have really changed the
44:01world. In which, we have a tangible
44:04reality which is initially: "I am sick
44:06and I need care", to something else
44:08which is this, we abandon it: "I am
44:10testing people to find out if I should
44:13consider them sick" and, moreover, we
44:15then make it known immediately, with
44:17coercion, forcing them to wear masks
44:19and stay at home, and so on and so
44:21forth. We have really completely
44:23changed the paradigm and words in
44:24particular have their importance in
44:25this. I completely agree.
44:28>> There is a category of language that is
44:31supposed to say something specific. We
44:34call it prophecy. And you talk about it
44:36, Patrick Stoco, at the moment of
44:38prophecy in the book. You talk about
44:41the prophets of the exponential, for
44:44example, with a man called Ferguson,
44:46well, a Ferguson model, but who comes
44:48from this gentleman. Can you finally
44:52tell us if this corresponds precisely
44:53to this crisis of language in the
44:55description of reality and possibly
44:57tell us a word about it? Yes, I will
45:00tell you a word about it, but if you
45:02allow me, I just want to
45:04>> add something to what Pierre just said.
45:08In the book, for those who are
45:10interested, in Chapter 1 that Pierre
45:12and I wrote together, in fact, in
45:15Chapter 1, we explain very simply and
45:17very precisely how PCR tests were
45:19poorly calibrated during the Covid
45:22period. So why were they poorly
45:25calibrated? For me, it's mainly because
45:28the health and political authorities
45:31panicked and, in their panic, misused
45:35these PCR tests. We knew since February
45:392020 that these tests were being
45:41misused. When I say we, I mean the
45:44virologists, we were in a bad position,
45:46we knew that these tests were being
45:48misused. But that allowed us to
45:51maintain fear and once again justify
45:54the development of experimental gene
45:56injections since December 2020. Now,
45:58I'm going to tell you a second thing
46:00about what Pierre just said. He talked
46:04about a paradigm shift. The paradigm
46:09shift for the pharmaceutical industry
46:11is actually much more serious than that
46:14because, up until a few years ago, the
46:16pharmaceutical industry manufactured
46:18drugs for the sick. However, the sick
46:23within any given society, regardless of
46:25the society, are a very small
46:27proportion. And in many cases, you have
46:33to manufacture drugs for a few sick
46:36people. So it costs a lot of money to
46:39develop these drugs. So it's not always
46:42profitable. I'm not going to start
46:45crying about the pharmaceutical
46:46industry's revenues. With Covid, they
46:49earned about 100 billion dollars. So it
46:52was a very good move. But why was it a
46:55good move? Because the paradigm shift
47:00with this technology consists of
47:03injecting something into healthy people
47:07who are not sick. However, in a society
47:12that includes 10 billion bipeds, to put
47:15it simply, well, the proportion of
47:17healthy people is much greater than the
47:20proportion of sick people. So from a
47:24marketing perspective, the
47:27pharmaceutical companies have something
47:30here that will allow them to make a lot
47:33of money by injecting products into
47:35healthy people and not into sick people
47:38. And so there is no need to explain
47:42this for very long to the
47:43pharmaceutical marketing department.
47:46They have understood that with this
47:49paradigm shift, there was, uh, a golden
47:55goose, it is common to all vaccinations
47:58in France. In Switzerland, it is a
48:00little different because you have
48:01freedom of conscience, it seems to me,
48:03total, whereas in Switzerland there is
48:05no right, there is no legal constraint
48:06on vaccinating even children. Which is
48:08something that there is not in France.
48:09In France, there are legal constraints
48:11where you can even withdraw children
48:12from parents who do not do it. Uh but
48:14there is in any case the history of
48:16vaccination with the, uh, it is this
48:18one, huh. In medicine, there is this
48:21problem of profitability for the
48:23industry, namely that in fact, the sick
48:25person is a rare occurrence in society.
48:28We only talk about it on TV. It seems
48:29common, but in reality, it is quite
48:31rare. That's it.
48:32>> In an epidemic, when we said flu
48:34epidemics in the winter when everyone
48:36is sick, it's cold, pollution is at its
48:38peak, and people have breathing
48:40difficulties, cough, and fever, etc. At
48:42the peak of the peak, at the maximum in
48:45France, there is one person in 1,000
48:47sick. Even when you have the impression
48:50that everyone around you is sick, at
48:51the same time, there is only one person
48:53in 1,000 sick. Which means that when
48:55you are at the head of an industry that
48:57is only interested in that part of the
48:58market, well, there is no great
49:00profitability. Whereas if you manage to
49:03convince the States that you are
49:05ultimately going to make a country's
49:07inhabitants captive, the number of
49:09sales you will be able to make will be
49:11colossal. Hence the test and the
49:13vaccine. With the test, everyone must
49:15get tested. With the vaccine, everyone
49:16must get vaccinated. But it's crazy, in
49:18terms of market power. And it's a
49:21captive market, there's almost no
49:23competition. Uh, it's the State that
49:24buys. So there's no risk for the
49:26pharmaceutical industry. People have
49:28the impression that it's free to go and
49:30get tested when in fact it's taken from
49:32the taxes that pay for it. So there's
49:34no longer any trust. It's free, it's
49:36the State that pays for it.
49:37>> Yes. Yes. If it's free, you get the
49:39product, right?
49:42>> I will now address your question
49:44regarding epidemiology, if that is
49:46alright with you. What we demonstrate
49:51in Chapter 5 is that all countries
49:54utilized various epidemiological models
49:57in order to predict what would unfold
50:00throughout the Covid crisis. And in the
50:05book, we examined the 10 most widely
50:08used epidemiological models in the
50:10world at that time. These are
50:14compartment models. I must honestly say
50:18that Pierre, who is a statistician, is
50:19better equipped than I am to answer
50:21this question. But basically, these
50:24compartment models are models into
50:28which we should enter reliable data at
50:32the outset so that the model can give
50:37us a reliable prediction of the
50:40evolution of the disease. Or, once
50:44again, that's exactly what happened in
50:472020. In the panic, we pushed all the
50:50parameters of each of these models to
50:52the extreme, saying, "Okay, let's take
50:55precautions, let's pretend that all the
50:59growth of these diseases in all
51:01countries is exponential and the worst
51:04possible." And let's see what happens.
51:09And when we analyze the use of these
51:11models in detail, we can clearly see
51:14that they all, absolutely all, gave
51:17predictions that were totally excessive
51:20, totally false, and that of course
51:22caused governments to panic, saying, "
51:25My God, the epidemiologists are telling
51:28us that there are going to be 100
51:31million, 20 million, 50 million deaths.
51:33" It's going to be worse than the
51:39Spanish flu of 1918. So let's take the
51:42maximum possible measures. So,
51:45mandatory experimental gene injections,
51:47non-pharmaceutical measures, lockdowns,
51:49etc., etc., etc. I won't go over the
51:51list again. It's in Chapter 2, but it's
51:56the keystone of this whole story, if
52:00you like, the misuse of epidemiological
52:05models in 2020. Epidemiologists didn't
52:11provide politicians with the right data
52:14that would have allowed them to make
52:16the right decisions. Well, I don't want
52:20to exonerate politicians because they
52:21didn't do anything.
52:23>> No, no, we shouldn't exonerate
52:24politicians, but I have the impression
52:25that you're going even further. You're
52:28saying that at one point models were
52:30used that had already been used and had
52:32already shown that they didn't work.
52:34>> Yes, absolutely. and the use, uh, I was
52:39going to say fraudulent, that's not
52:43quite the right term, but the misuse of
52:47these models, uh, was fueled by panic.
52:52Uh, and now on to the details of how
52:54these models work and why they were
52:56fueled by panic, excuse me Patrick Sto,
52:58but it's actually the opposite. That is
53:02to say, we put any data into models
53:04that didn't work because we knew, we
53:06had already used them, and that's what
53:08generated panic and was relayed by
53:10politicians and the media. We agree,
53:13right? Yes.
53:14>> Yes. Yes. But if you want, among all
53:16these models, we examined some with
53:19Stalder, who is the independent analyst
53:21with whom I worked on these models. We
53:23analyzed about ten of them, the 10 main
53:27models. So not all the models were bad.
53:30There were a certain number of models
53:33that could have functioned and could
53:35have provided reliable predictions had
53:38we successfully introduced into these
53:41models the specific parameters that had
53:43been gathered from the field. The
53:48problem is that we didn't use field
53:50data to feed these models. We fed them
53:54just any data whatsoever, and obviously
53:57the models then started saying anything
54:00at all.
54:02>> Pierre Chaillot, a word about these
54:04models.
54:06>> Yes, a model is just a, how do you say
54:09it? A mathematical object on which we
54:12put things as input, we say what
54:13algorithm should be done and then it
54:15produces something as output. So, maybe
54:18to understand, it's...we, basically,
54:19we're going to have a, yes, well, a
54:21model, as its name suggests, but we're
54:23going to say, uh, our virus, uh...if
54:24someone is contaminated, uh, they're
54:26going to contaminate, they're going to
54:27meet uh, uh, 10 people during the day,
54:29they're going to transmit it to three
54:31people, uh, and so on and so forth.
54:33That's more or less how it works.
54:34>> Yes, that's the principle of
54:36compartmental models, especially the
54:37most classic one, which we call the
54:39ones where we divide the population.
54:41But well, it is much the same principle
54:43. We say that there are people who are
54:45likely to be sick. So who are not sick
54:47but who are likely to be sick. That's
54:49the surrounding population. People who
54:50are infected, that's the i. And people
54:52who then either recover or die. So who
54:55are out of the field, who are more
54:56susceptible and who are not infected
54:58either, who are out of the equation. Uh
55:00, and then behind that, yes, there are
55:02a whole bunch of parameters of
55:03transmission principles, the
55:04probability of getting sick once you're
55:06infected, the probability of dying or
55:08getting established afterwards. There
55:10aren't that many parameters, and then
55:12based on these parameters, we run it
55:14and see what happens and we calibrate
55:16it on the known data. Well, there you
55:18have it, the number of deaths that
55:19there have been, the number of cases
55:21that, once again, with all the
55:22precautions that I mentioned earlier,
55:24where the level of knowledge is almost
55:25zero. And so, we put that into the
55:28model. Uh, and the model will take the
55:30assumptions that you give. In my first
55:33book, I included examples of models,
55:35examples that are published in major
55:36scientific journals and that promote
55:37lockdowns. If you read the model and
55:41you understand, the model says more or
55:43less, uh, the virus will spread
55:44everywhere and be deadly, so everyone
55:46will die unless we lock down. And so
55:49the lockdowns save millions of lives.
55:51Period. Then, they take the data, they
55:53see that not everyone died and that
55:55there are survivors, they conclude that
55:56they saved millions of lives. There you
55:58have it, that is to say that it is
55:59their initial hypothesis that is put
56:00into the equation and then at the end,
56:01they have the result that they put in
56:03the books, initial hypothesis. That's
56:04always what models are. I'll give
56:07another example with my friend Briochet
56:09in the first book too. We took the data
56:12of what is called COVID, so all the
56:14records, all that. And we calculated
56:17what is called the R0, so the fact of
56:19contaminating others with the virus
56:20based on the mortality data that we
56:22attributed to COVID and all that. So we
56:25calculated the properties of the virus
56:27and we calculated the reliability of
56:29our model because the data shows a bit
56:30of a strange face. We always have to
56:33lyse. And we have a correlation if you
56:36like, we evaluated the quality of our
56:38model if the result corresponds to the
56:40curve that we see. And we have a result
56:43that is not great, which is very good
56:45for epidemiology. I think we have 85%
56:47correspondence between us, what our
56:49model predicts and the final curve that
56:51is actually observed. And then, we did
56:53a second exercise. We took the deaths
56:55from the 2003 heat wave which also
56:57caused a big wave of deaths and we said
56:58the 2003 heat wave was due to a virus.
57:02It is not the heat; it is a virus
57:03killing people. And so we took an
57:05epidemiological model, we calibrated
57:08our model on the deaths in 2003 and we
57:10discovered a correspondence between our
57:13forecast curve and the final curve of
57:16more than 95%. Which means that saying
57:20that it was a virus that killed
57:21everyone during the 2003 cycle is much
57:23more reliable than saying that the
57:25deaths from Covid are due to a virus
57:27that spread. It works better. Uh, which
57:30means that in fact with models, we can
57:32say absolutely anything and that it's
57:33not because we have a model that seems
57:35to work that we are doing something
57:36true. The model simply puts the initial
57:39hypotheses back into equations and
57:41numbers, that is to say what we already
57:44claim to know. So there is no proof,
57:47ever, anywhere with any model. Which
57:49means that all the whistleblowers, the
57:51Fergusons and others, what they are
57:53doing is this. That is to say, a
57:55certain number of them, moreover, do
57:56not hide the fact that they are
57:57millenarians, that is to say that they
57:59predict the end of the world in the
58:00coming years because of a new virus
58:01that will ravage humanity. And as soon
58:04as they have the slightest signal, they
58:06throw their hypotheses into a model
58:07that will propose a curve where
58:09everyone dies and scare everyone with
58:11that. But the result of their model is
58:14just, let's say, the transcription of
58:17their own neurosis that they have
58:19translated into equations. Period.
58:21That's all. Nothing more to learn from
58:23models.
58:24>> And except that behind it, obviously,
58:26we have a problem because if I come up
58:28with a model like that and I tell you,
58:29well, in fact, I have a solution. We
58:32need to wear masks because it's very,
58:33very useful and we need to get
58:35vaccinated because it's very, very
58:36effective. Uh, and you're going to tell
58:38me, well yes, but in fact we had fewer
58:40deaths but it's because we were
58:41confined, we wore masks and we were
58:43vaccinated. So the proof is in the
58:44pudding, it's like the story of the
58:46magic cup, you know it, right?
58:47>> Yes, exactly. Don't
58:48>> you see a tiger there? It's because you
58:50have a magic cup that keeps tigers away
58:52.
58:52>> Yes, every morning, I put anti-elephant
58:53powder on my strawberries and no
58:55elephant has ever crushed my
58:56strawberries. I also think that this
58:57powder should be mandatory and
58:59reimbursed by social security. But it's
59:01exactly the same principle. So when
59:02they make models to claim that a
59:04certain object was effective, well,
59:05they're going to use that. Hence the
59:07fact that we try to free ourselves from
59:10models and that when we use data, we
59:12try not to create a model or really do
59:15a minimal one and compare raw data.
59:17When I compare the number of vaccines
59:19to the number of deaths, I compare them
59:21and I realize that it works all the
59:23time, my model is quite simple. It's
59:25just daily data that I compare. When I
59:29compare the number of doses of Rivotril
59:31that were distributed to people and I
59:33compare them with the number of deaths
59:35of people over 90 in March 2020, and I
59:37notice that they work perfectly
59:38together, I have another candidate for
59:40the death of these elderly people than
59:42the famous virus that would not
59:44circulate very well in the curves.
59:46There you have it. So, if you want to
59:48know the story of the model, it's
59:50something that is used when the data
59:52doesn't match well or when we say that
59:55it's a complex phenomenon. But the
59:57immediate problem is that we're going
59:58to talk nonsense and talk about
1:00:00whatever we want to talk about. We're
1:00:03going to
1:00:03>> talk nonsense. Look, that could be the
1:00:06gimmick of this show. Patrick Stoco, I
1:00:08asked you to speak for 10 minutes.
1:00:10You've been here for an hour. Before we
1:00:15conclude this show, if you want to draw
1:00:18our attention to one thing...the book
1:00:21is really big, there's a lot of stuff
1:00:23in it, so obviously we can't cover
1:00:26everything. But if there's a point that
1:00:29we haven't covered that you want us to
1:00:31highlight, now is the time. A point...
1:00:36Yes, well, I'm asking about the fourth
1:00:38book, whether or not we're dealing with
1:00:41the biggest disaster in the history of
1:00:43medicine. There's a question mark. So,
1:00:47maybe we could answer this question if
1:00:49you want.
1:00:50>> Oh well, let's go.
1:00:51>> So, if we look at all the disasters, I
1:00:54insist, that are linked to the activity
1:00:57of the pharmaceutical industry, I'm not
1:01:00talking about the Spanish flu of 1918,
1:01:03okay, we agree on that. Well, but if
1:01:07you take contaminated blood for example
1:01:10, well, between 1983 and 2003,
1:01:12contaminated blood caused about 1,000
1:01:15deaths. 1,000 deaths in 20 years. So,
1:01:18it's a story that we still talk about
1:01:21today, but proportionally, it didn't
1:01:23cause many deaths. The Mediator affair
1:01:26caused about 1,500 to 2,000 deaths. The
1:01:33tragedy of Talie de Mide, you remember
1:01:36in the 50s and 60s, between 10,000 and
1:01:3912,000 children were born with
1:01:41extremely serious malformations. No
1:01:45arms, no legs, and so on and so forth,
1:01:48not to mention the number of future
1:01:50inutero deaths. Viox caused about
1:01:5625,000 to 40,000 deaths in the USA. And
1:02:03then the biggest catastrophe that we
1:02:07know of today, apart from messenger RNA
1:02:11, was Oxyonain, which killed about
1:02:14500,000 people in the United States.
1:02:20That was before MRNA. Now, Pierre just
1:02:26told you that there were 300,000 deaths
1:02:28in Europe alone. I just told you that
1:02:33the low end was about 4 million deaths
1:02:36worldwide due to the deployment of
1:02:39these experimental gene injections. And
1:02:43you see that there are 10 times more
1:02:46deaths than the worst catastrophe we
1:02:49have ever experienced. That's all.
1:02:58>> I would also like to make another point
1:03:00, this will be my own conclusion and I
1:03:02will then let Pierre Chaillot also
1:03:04conclude. So now we have clearly
1:03:08understood, in terms of death, we can
1:03:10say that this is the greatest
1:03:12catastrophe in the history of medicine.
1:03:15But that's what I was saying earlier,
1:03:17there has also been a legal and
1:03:19civilizational upheaval that has never
1:03:22been seen before, at least in recent
1:03:24history. That is to say that from one
1:03:27day to the next, what seemed to us to
1:03:29be basic principles of law have been
1:03:31flouted, relegated far away. But above
1:03:39all, it has not returned, it has not
1:03:41returned to the situation we were in.
1:03:44All that has disappeared. Once these
1:03:47principles have been flouted, it's all
1:03:49over. And we can't go back because we
1:03:53can clearly see that the leaders who
1:03:55are responsible, well, are not
1:03:57accountable and they have not come to
1:03:59assess the exceptional measures they
1:04:01have put in place. Because, at the end
1:04:04of the day, we can understand that
1:04:05exceptional measures are put in place
1:04:06in the face of an exceptional situation
1:04:07. But then, we are accountable, we take
1:04:10stock, which is what you do, which they
1:04:11never do. We do this assessment after
1:04:15the fact, the assessment of the
1:04:17measures, whether proportionate or not,
1:04:19that have been put in place to deal
1:04:21with a threat. This assessment has not
1:04:23been done. Those responsible do not
1:04:25respond to what they have done. And so
1:04:28we have had a shift in civilization
1:04:30where the law no longer means anything.
1:04:32We have used words like emergency
1:04:34situations. You were also saying
1:04:36earlier, Patrick, Bosco Stoco, sorry.
1:04:39Uh, that's another one, that we had
1:04:42classified things as top secret. So
1:04:45obviously these things weren't
1:04:47classified top secret, and we gave them
1:04:49names that didn't correspond to reality
1:04:50at all. So we've largely transformed
1:04:54reality and we still haven't gotten out
1:04:56of this situation and therefore this
1:04:58catastrophe. So on the medical level,
1:05:01on the legal level, on the
1:05:02civilizational level, and I'll let
1:05:04Pierre Chaillot make a final word if he
1:05:06wants to as well. You're right, and
1:05:08let's point out that it's not for lack
1:05:10of asking for accountability in the
1:05:11book. He cited complaints filed in
1:05:14various places, notably in Switzerland
1:05:16against Suisse Médique; we see they
1:05:18drag on: they are either dismissed, or
1:05:20they just stall, with no progress. When
1:05:23the ECHR (European Commission on Human
1:05:25Rights) is called upon, it either
1:05:27sidesteps or validates all the
1:05:29exceptional measures that have been
1:05:31taken, or almost all of them, in any
1:05:33case those that are cited against the
1:05:35interests of the people who are
1:05:37requesting them. So, in effect, under
1:05:40the principle of fear, that is to say,
1:05:42we have succeeded in terrorizing people
1:05:45with an invisible object, the virus,
1:05:47which can be everywhere. So we have
1:05:49terrorized people and the law has
1:05:51collapsed. And unfortunately, it is not
1:05:54just the leaders, the people have also
1:05:56easily let their rights be taken away
1:05:58and only a minority of people have not
1:06:01accepted that their rights be taken
1:06:03away. This minority, and even a very
1:06:05small minority, has gone so far as to
1:06:08file complaints, appeals and so on. So,
1:06:11we do indeed have a fundamental problem
1:06:14which is, finally, a lack of law, a
1:06:16change in law and a passive acceptance
1:06:19by the population of having their
1:06:21rights taken away. I would like to
1:06:24conclude with a question so that
1:06:26everyone, uh, must have some
1:06:28introspection and ask themselves what
1:06:30they think is right and understand
1:06:32where we are at. I talked about it a
1:06:36little earlier, but with the new
1:06:38paradigm shift that we have, we are no
1:06:40longer individuals, uh, how should I
1:06:42say, who are free and equal and above
1:06:44all who are innocent by nature. With
1:06:48the new paradigm, we are all guilty and
1:06:51suspended. And the health authorities
1:06:55can at any time in this new paradigm
1:06:57ask us to justify our state of health.
1:07:01I was putting it on the basis of tests
1:07:03so that we have to prove that we are
1:07:05innocent and that we are not going to
1:07:07kill our neighbor by breathing in his
1:07:09nose. And that is an extremely profound
1:07:11change in terms of law. That is to say,
1:07:14we are basically considered guilty.
1:07:16That is what we call the law of
1:07:17suspects. Yes.
1:07:18>> And even when you have a positive test,
1:07:20I challenge you to find me the
1:07:22slightest study that would prove that a
1:07:25person, or even when you are sick with
1:07:27Covid, find me a study that would prove
1:07:30that we have succeeded in demonstrating
1:07:32the principle that the sick person
1:07:35makes their neighbor sick. From a
1:07:37scientific point of view, you will not
1:07:39find any. It is a principle that we
1:07:40accept and on which all the legislation
1:07:43is based to justify lockdowns, masks,
1:07:45etc., but we have no scientific studies
1:07:47that demonstrate it. We even have many
1:07:48studies showing the opposite, namely
1:07:50that we are failing. Which means that
1:07:53on the basis of a, how shall I say, a
1:07:55thought or a mental construct, we
1:07:57manage to put laws in place and
1:07:59suppress people's freedom on the basis
1:08:02of a suspicion of something that we do
1:08:04not know. And from a legal point of
1:08:07view, we are still on the presumption
1:08:09of innocence. That no matter what your
1:08:11state of health, no one can say that
1:08:13you are going to kill your neighbor by
1:08:15breathing in his face. In the end, we
1:08:17have internalized this and we accept
1:08:20the fact that there are restrictions
1:08:22and restrictions on freedom based on
1:08:24this simple suspicion. This is an
1:08:27extremely serious change in
1:08:28civilization. A sick person is
1:08:30initially someone who needs to be taken
1:08:32care of because they are not well. So,
1:08:34we are supposed to protect them and we
1:08:36have changed our paradigm. The sick,
1:08:38the test-positive, or the unvaccinated
1:08:40are extremely dangerous and harmful
1:08:42pieces of nuclear waste. And because of
1:08:46this, we must restrict their freedoms
1:08:48and consider them a danger to others.
1:08:51And I would like everyone to think
1:08:53about this and the implications it has
1:08:54for our everyday lives. Okay, and since
1:08:57I personally discovered that I couldn't
1:08:58find any studies that would allow me to
1:08:59see that my sick neighbor would make me
1:09:01sick, I send kisses to everyone in
1:09:02winter and I take care of you very well
1:09:03. Do the same. A quick word because I
1:09:06said, uh, it's the law of suspects and
1:09:08you specified it, Pierre Chaillot. The
1:09:10law of suspects, it's that moment
1:09:12during the French Revolution, during
1:09:14the terror when everyone is presumed
1:09:15guilty and you have to demonstrate your
1:09:17innocence. And there you extrapolate it
1:09:20, uh, to our situation, even medically.
1:09:23Uh, but it's very serious because
1:09:26there's a relationship to purity that
1:09:28seems to take us back to the darkest
1:09:31part of our history. Well, yes,
1:09:34>> with certain segregations that we've
1:09:36experienced and so on. But absolutely,
1:09:38but it's the same pseudo-genetic
1:09:40principle on which, in addition, the
1:09:41pharmaceutical industry is now being
1:09:43dosed with products that can be
1:09:44developed on a mass production line and
1:09:46paid for in cash. Patrick Stoco, any
1:09:50last words? No, I completely agree with
1:09:54Pierre, once again. And I simply hope
1:09:59that people will take the trouble to
1:10:01consult this document, which is
1:10:04designed for doctors, of course, who
1:10:07have not read the scientific
1:10:09publications of the last six years, but
1:10:12which is also designed for lawyers, to
1:10:15help lawyers defend the victims of
1:10:18these experimental gene injections that
1:10:21Pierre also described very well in his
1:10:24book.
1:10:26>> I confirm that it is well designed for
1:10:28lawyers. It can be taken as a manual.
1:10:30There are additional chapters
1:10:32specifically on legal matters and it is
1:10:36quite well done. There are summary
1:10:39conclusions at the end of each chapter,
1:10:41so if you just want to select a chapter
1:10:43and a conclusion, you can go straight
1:10:44to it. So that's very useful. Get this
1:10:48book ARNM, the forbidden report edited
1:10:50by Patrick Stoco, with a preface by
1:10:52Pierre Chaillot. My two guests today at
1:10:56Résurgence, and it's Marco Piéteur, I
1:11:02think the listener. Thank you both very
1:11:05much for accepting my invitation. Dear
1:11:07listeners, see you next time. But don't
1:11:09forget to give it a thumbs up, to pass
1:11:11it on, as you know, it's important.
1:11:13It's thanks to you and to this relay
1:11:15that these programs can exist. They are
1:11:17important and sometimes serious, like
1:11:19today. Thank you all and see you soon.
1:11:21Goodbye.
1:11:22>> So, all those people who trust us, well
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1:11:41>> link. There you go. uh
1:11:43toxin-media.fr/nouttxin-media.fr Oh no,
1:11:45yes if that's it uh slashnous, there
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1:11:50uh some people tell us "But and we
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1:11:54thank you very much to all those who
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1:12:25No, sorry.
1:12:26>> 2,500 because we only have 500. 2,500.
1:12:29But just for today, we could already
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1:12:42So, well, listen, thank you all for
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1:12:50with this toxin-media.fr/noz. Add
1:12:53something, Gu perhaps?
1:12:55>> Yeah, just recently, it's important to
1:12:57me, it's because Toxin was created, uh,
1:13:00to get your donations, uh, and it's not
1:13:02for a simple reason, it's because if we
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1:13:06serve you. That's really how we built
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1:13:13in my opinion, we're not better than
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1:13:25holding us back financially. We have no
1:13:27one,
1:13:28>> we don't have a hidden political agent.
1:13:30We don't have a
1:13:30>> hidden political agent. I'm the first
1:13:33one, those who saw me this summer know
1:13:35that. It's because I don't support
1:13:38anyone. I don't think I'm interested in
1:13:41the next presidential election at all.
1:13:44Why? Because in the short term, it's by
1:13:47organizing ourselves locally as a
1:13:48family that we'll get through this, and
1:13:50politically, the fruit will fall. But
1:13:53for me, politically, we work for 10
1:13:55years, 15 years, we don't work for 6
1:13:56months. So on top of that, obviously
1:13:59we're not affiliated, we're not
1:14:00affiliated with any party. Uh, I'd like
1:14:03to know which one, and it's this
1:14:05freedom that, once again, is an
1:14:08original choice. Uh, it's everything
1:14:12we've built together, we've built it,
1:14:14whether it's editorially, financially,
1:14:17in our entire way of doing things, to
1:14:19do it independently of everyone except
1:14:21you. So,
1:14:24>> we depend on you. That's also why we
1:14:26need you today. Toxin-media.fr/nous.
1:14:30I'm counting on you. I think G is
1:14:31counting on you. I think the team is
1:14:32counting on you. So thank you very much
1:14:34to all of you.

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