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Okay, everybody, welcome to today's meeting of Medical Doctors for COVID Ethics International

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on this Tuesday night, the 5th of November, London time, which is Wednesday morning, Australian

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New Zealand time, which is, which is midday, LA time on election day.

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In the US presidential election, 2024.

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Well, not only presidential, but all of the House of Representatives, Senate as well.

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So special day.

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And so this group was founded by Dr.

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Stephen Frost over three years ago with a desire to pursue truth, ethics, justice, freedom

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and health.

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Stephen has stood up against government and power over the years and has been a whistleblower

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and activist. His medical specialty is radiology.

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We remember another freedom warrior at this moment.

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And at all of our meetings is Rainer Formick, German and US lawyer who's unlawfully incarcerated

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in a German jail undergoing a German show trial.

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Please do what you can to highlight the outrageous behaviour of the German government in attacking

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Rainer Formick.

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It's clearly scared of Rainer's work as a freedom warrior.

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I'm Charles Covets, the moderator of this group.

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I'm Australasia's passion provocateur.

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And we love passionate people in these meetings.

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I practiced law for 20 years before changing career 31 years ago.

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And over the last 14 years, I've helped parents and lawyers to strategise remedies for vaccine

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damage and damage from bad medical advice.

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I'm also the chief executive of an industrial hemp company.

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We comprise lots of professions here and we're from all around the world.

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Many of us thought that vaccines were OK.

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Now, most of us know that vaccines have never been properly tested for safety and efficacy.

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And yes, I am a passionate anti-vaxxer.

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And please, I urge all of you to become passionate anti-vaxxers.

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God does not need help in producing healthy babies.

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If this is your first time here, welcome and feel free to introduce yourself in the chat.

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If you publish anything, put that in the chat as well.

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Most of us understand we're in the middle of World War 3 and that the medical science

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battle is only one of 12 battle fronts in this latest world war.

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And there's no time to be tired.

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I assess we're four and a half years into a seven year war.

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So look after your health.

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So you're up for the fight.

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Most of us understand the development of science and the science is never settled.

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And our presenter today is an expert in this space.

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Dr David Resnick, I'll introduce him in a moment.

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Some of us believe that viruses exist.

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Some of us believe that viruses are a hoax and some of us are on the fence.

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And most of us consider that debating the existence of viruses is a distraction from

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the real war that we are in.

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This meeting runs for two and a half hours normally, after which for those with the time,

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Tom Rodman runs a videotelegram meeting.

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Although today, because of the election, Stephen and I have discussed and will keep the meeting

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running for as long as people want to sit here to discuss what's happening in the election.

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It'll be a special deal.

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We will post this recording and we will keep the recording going.

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We won't publish that until unless something brilliant comes out of it.

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I point out that, yes, we'll talk about cloud up later.

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We will listen to Dr David Resnick for as long as David wishes to speak.

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And then we have Q&A.

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Stephen Frost, by long established tradition, asks the first questions for 15 minutes.

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This is a free speech environment with appropriate moderating.

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Free speech is crucially important in our fight to preserve our human freedoms.

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However, as occurred on Sunday night, we do not allow ad hominem attacks.

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You attack ideas. You don't attack the people not interested in your views about other

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people, whether they're, whether they are, whatever they are.

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No attacks on people, number one.

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And number two, appropriate moderating means we stick to the topic.

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Some people seem to think that because David Resnick might be presenting something, you can

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ask him what he thinks about stuff that's irrelevant to what he's been talking about.

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That's what appropriate moderating means.

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If you're offended by anything, be offended.

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We are lovingly not interested.

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We reject the offence industry that requires nobody to say anything that may offend another.

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We similarly reject the triggering industry.

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The triggering industry, both the offence industry and triggering industry are both

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free speech censorship attempts.

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We come with an attitude and perspective of love, not fear.

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Fear is the opposite of love.

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Fear squashes you, enslaves you.

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Love, on the other hand, expands you, liberates you.

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These twice weekly meetings are not just talk fest.

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An extraordinary range of actions and initiatives have been generated from linkages made by

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attendees in these meetings.

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It's just extraordinary.

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Like if it were, it would take us, it would take us an hour for Stephen and I to go through

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what's happened as a consequence of these conversations.

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If you have a solution or a product or links or resources that will help people put the

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details into the chat, the meeting is recorded and is uploaded on the Rumble channel.

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And now welcome to our guest presenter, Dr David Resnick.

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And we thank you, David, for giving us your time and wisdom and insights.

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David has presented to us previously.

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Let me tell you a little bit about David for the purposes of the recording.

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David received his PhD in chemistry from Georgia Tech in 1978.

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He worked 20 years in pharmaceutical biotech industry and founded four biotech companies.

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He developed inhibitors against the enzymes responsible for the tissue destruction caused

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by cancer, emphysema and arthritis.

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The same class of inhibitors are powerful anti-parasitic agents.

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They've left the pharmaceutical biotech industry in 1996 and joined UC Berkeley.

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And Professor Peter Juesberg's fight against the blatantly wrong dogma

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that HIV causes AIDS.

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And David's history on fighting against that fraud is similar to the fight that we're going

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through now on the COVID scam.

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David is former president of Rethinking AIDS, the group for the scientific reappraisal of

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the HIV hypothesis and former president of the International Coalition for Medical Justice.

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He was also a member of South African President Thabo Mwembeki's presidential AIDS advisory

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panel that met in 2000.

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Along the way, Peter Juesberg and Dave Rasnik proved the aneuploidy chromosomal imbalance

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theory of cancer.

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Since February 2020, similar time to many of us on this call, Dave has been working

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with people around the world fighting the COVID-initiated global coup d'etat.

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His full CV and four decades of information are available on his website, davidrasnik.com.

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And David, you introduced to us in your first presentation here Leopold Kaur's book,

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The Breakdown of Nations, written in 1957.

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And I have shared that with many people.

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I'm sure you'll tell us where you can find it on your website.

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It's a wonderful, wonderful book.

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And in the times that we're right now, we're in an election, the message of Leopold Kaur

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that the number one cause of all failures is bigness really resonates with me.

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I love that idea.

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So David, thank you so much for speaking to us again.

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And thank you, Stephen Frost, again, for creating this group and for organizing David to speak

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to us today.

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Well, I'm looking forward to presenting my cancer work today because it's something that

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I'm the most proud of as a scientist, scientific work.

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And it never would have come about had it not been for AIDS.

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That's when I joined up with Peter Duisburg just to support him for a little while.

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And I found wound up being with him for about 10 years.

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And when we weren't fighting the AIDS scandal, we'd take a breather and we'd work on cancer.

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And Peter ran out of, he couldn't get any grant support anymore.

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So right before he left to go on a sabbatical in Germany, the first one in his life, because he

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couldn't get any grant support anymore, financial support from the government because he

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challenged HIV.

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So he decided he's going to work on the chromosomal or chromosomal imbalance theory of cancer that

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Theodore Boveri produced back in 1914.

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And he went to Germany to do some experimental work on that.

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And I stayed in California and I went to the library to learn about chromosome, I knew about

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chromosomes, but about Boveri's work and about chromosomal imbalance.

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And it turns out that had it not been for AIDS, Peter and I would have not done our most important

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work that we did as scientists on cancer.

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And we got together and in a few years we proved Theodore Boveri's original theory that

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unbalanced chromosomes and only unbalanced chromosomes are what's behind cancer.

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And that's what I'm going to talk about today.

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Because I don't know how many opportunities you're going to get to hear this story, but I'm

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going to start right now by showing you, I need to share my computer if I can do that.

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Is there a share button on here someplace?

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Yes, there is.

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If you've got zoom, it's at the bottom of your screen.

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There's the green button that says share.

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Oh, I see it.

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I see it.

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Okay.

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And I want to share my screen.

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David, which state are you in?

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I think you said earlier, but...

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North Carolina.

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North Carolina.

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That's right.

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Okay.

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This is the screen.

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Let's say I want to, this is the one I want to share.

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Is that a picture of North Carolina behind you, David?

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No.

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All right.

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Okay.

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Tell me what you see.

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Yeah, we've got David Resnick PhD, your website, we can see.

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That's right.

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I wanted to start with this so people can see.

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If I click on the home screen, that's where we're at right now.

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We can see your desktop as well.

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Is that okay, David?

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Do you want that?

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Don't worry about that.

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All right.

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I've had problems doing this sort of thing over the past few years,

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and I think I haven't figured out well enough for today.

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Okay.

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So anyway, this is my website.

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And the stuff that I'm going to be talking about today...

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Let's see.

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Why don't they see, stop sharing?

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No, I want to share.

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Yeah.

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Why does that pop up?

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You are sharing.

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I don't want to stop sharing.

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Why doesn't this come forward?

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What do you want to see?

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Oh, it just disappeared.

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There was a little notification about that.

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I was sharing my screen.

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Move your mouse.

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Just move your mouse.

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Yeah.

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We've still got it.

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Okay, good.

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All right.

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Now, what I would like for people to do,

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I'm going to show you right now where you can go.

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Actually, I go too high and it brings this thing back down.

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But you can go up here to cancer.

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You see this where I'm going to go here?

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I'm going to click on this cancer tab.

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Yep.

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We can see that.

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Now you see the chromosomal imbalance theory of cancer.

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Yep.

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You can come down here.

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This book right here, I published it, I forget when.

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It was early 2000, I guess.

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It's the explanation of our chromosomal imbalance theory

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of cancer that Peter and I worked on.

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And this book, you can click on this image here

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and you can download my book.

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It's 358 pages.

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It's free.

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And you can go to that and read it.

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You can read it on the screen or you can download it

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and get it any way you want.

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The other thing is this is David Hansenman,

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this guy right here on the right, the second photo to the right.

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I'm going to be talking about him.

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I'm just showing you these things where you can go to

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and you can click on it and you can get his book.

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It's a biography of him for people who are interested.

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The same thing here with Theodore Boveri.

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Click, he's an important guy.

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You can click on it and you can download his book.

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It's only, let's see, 59 pages, but it's concerning

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the origins of malignant tumor.

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He published that in 1914 and he was absolutely right

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about unbalanced chromosomes.

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He explains in there how unbalanced chromosomes

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cause cancer and people can go to that if they want to.

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It's especially good for historical information.

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All these things, these are just examples,

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but these are the ones I want to talk about today.

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If you scroll down on the same thing here,

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down here at the bottom you see this cancer book.

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It's the biology of cancer by Weinberg.

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It's the second edition, it's published 2014.

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You can click on it and it's a very big book

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and you can download it and you get the gene mutation explanation

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of cancer, which is government dogma.

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All right, for those people who would like to compare

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the gene mutation stuff with the chromosomal thing

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or anything else they want to, and I just wanted to let you know

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that you can go to my website and you have access

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to any of this stuff that's on there.

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Okay, so if there's no questions about this,

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I'm going to go ahead with my presentation.

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Yep, go for it, David.

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That's well explained, Leah.

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Okay, let's get this done.

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Let's get this out of the way, get that out of the way.

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And here, let's see.

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Yeah, we can see that.

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Okay, everybody can see that.

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The essence of cancer, all right?

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What it really is, that's what I want to talk about today.

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It's basically a comparison of the chromosomal imbalance theory

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of cancer, which is government, I mean,

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what Peter and I have proved, Theodore Boveri came up with it.

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110 years ago this year, actually, versus the reigning gene

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mutation theory of cancer, the idea that there are cancer genes,

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that you have a normal gene, you get a mutation in it,

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and it turns into cancer, all right?

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That's untrue, and we're going to go through that today.

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So I'll move on to the next slide here.

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Okay, up here.

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There you go.

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Okay, this is that book I've mentioned that you can download if you want.

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It's The Hallmarks of Cancer, published by Robert Weinberg,

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originally in 2000.

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Oh, this is our, up the top is a paper that he published in 2000,

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where he says cancer biology and treatment will become a science

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with a conceptual and logical coherence

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that rivals that of chemistry and physics.

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And the whole pharmaceutical field industry that I was in there for about

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two decades is all about molecules, all about molecules.

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And it's very simple to understand that because that's what pharmaceutical

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companies do.

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They make molecules to target other molecules.

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And that's the only way they can conceive of any disease, including cancer.

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You find a gene, you make a drug, a molecular drug for that gene

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or whatever they think is the cause of a problem.

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And they can just keep going on forever like they have.

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Then totally, completely, abjectly a failure, an abject failure, this approach.

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All right, there's the Cancer Genome Atlas, which is part of the reason they have this.

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There was Nixon's war on cancer.

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It was like it was 1975 when he launched the war on cancer.

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And the gene mutation hypothesis became government dogma.

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And it led to the looking for gene mutations and they've cataloged over 10,000 different tumors,

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cancer tumors.

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And 10 million, actually more than 10 million now cancer-related in quotes,

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cancer-related mutations.

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In other words, they find these mutations in cancer cells, but they don't say they're

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actually cancer-causing.

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And each one of these cells, these cancer cells, has an average of 1,000 mutations per tumor,

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per tumor cell.

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I'm sorry, per tumor that has all these different cells in it.

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Now, for the folks who don't have a background in biology or biochemistry,

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you hear these things about gene mutations, about sequencing, about what is an oncogene.

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I'm going to help you a little bit for those who don't understand.

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The DNA is like, we'll be talking about this later, it's a biological dictionary.

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The genes are a biological dictionary.

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And they code those genes, the DNA and RNA code for amino acids, basically, sequences of them.

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And this normal here that you see lower down, that's a normal sequence of any protein,

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or any product of a gene.

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And the three-letter codes at the top, the code for these amino acids like lysine,

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histidine, leucine, glycine, those are amino acids.

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And the string of those make protein.

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And the AAA, the CAC, the TTG, the GGT, those are adenine,

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cytosine, thiamine, and guanine.

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Those are the four nucleotides.

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The different sequences of those nucleotides code for different amino acids.

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Now, this little yellow box that I have here shows a mutation.

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What they mean by a point mutation, you have your normal sequence up here,

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lysine, histidine, leucine, and glycine.

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And the histidine has the code of CAC.

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But that A now is going to be replaced with a G.

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That's a gene mutation, a point mutation right there.

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And now you have the code CGC, but it no longer codes for histidine,

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it codes for arginine, a completely different amino acid.

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0:19:18 --> 0:19:26
And they say down here that hypothetically, that the CGC,

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and this arginine replacement, now is responsible for turning that cell into a cancer cell,

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hence the red little cancer here.

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I want to emphasize repeatedly throughout this thing,

325
0:19:36 --> 0:19:38
that's never ever been demonstrated anywhere.

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But that's the hypothesis, that's the theory.

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But the vast majority of these mutations are totally irrelevant.

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I'll keep going here.

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Now, in spite of the National Cancer Institute dogma,

330
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leading cancer gene researchers know that mutant genes don't cause cancer.

331
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But they keep working on gene mutations because if anybody who

332
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goes against the government dogma, they can't get funding for that.

333
0:20:14 --> 0:20:19
But here, let's start back with this fellow back in 1994, Gerald Dermer,

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0:20:19 --> 0:20:22
his book, The Immortal Cell, Why Cancer Research Fails.

335
0:20:23 --> 0:20:28
Perhaps the most damning evidence against the oncogene or cancer gene theory

336
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is the fact that the supposed human oncogenes do not transform true normal cells,

337
0:20:34 --> 0:20:37
which have a normal set of chromosomes.

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0:20:38 --> 0:20:42
He said that they don't exist as of 1994.

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0:20:43 --> 0:20:48
It continues, there is absolutely no evidence from observations of human tumors

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to indicate that the mutation of any proto-oncogene,

341
0:20:53 --> 0:20:57
that means a normal gene before it's mutated into an oncogene,

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that these mutations of any kind is essential for cancer initiation.

343
0:21:05 --> 0:21:10
In fact, in many tumors, all of the supposed proto-oncogenes are normal

344
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and there are no oncogenes present.

345
0:21:13 --> 0:21:15
Now we go back to Weinberg.

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He, even though he published that book in 2014 that I already showed you folks about,

347
0:21:24 --> 0:21:33
the Molecular Biology of Cancer, and it was also in 2014, but he published in the journal Cell

348
0:21:33 --> 0:21:35
in the same year, these comments.

349
0:21:36 --> 0:21:41
He said, the actual course of research on the molecular basis of cancer

350
0:21:41 --> 0:21:42
has been largely disappointing.

351
0:21:43 --> 0:21:48
Rather than revealing a small number of genetic and biochemical determinants

352
0:21:48 --> 0:21:52
operating within cancer cells, molecular analyses of human cancers

353
0:21:52 --> 0:21:56
have revealed a bewildering complex array of such factors.

354
0:21:57 --> 0:22:03
Even within a given type of cancer, there were no uniform successions of genetic change.

355
0:22:03 --> 0:22:08
Instead, each tumor seemed to represent a unique experiment of nature,

356
0:22:08 --> 0:22:14
acquiring a unique set of mutant genes and in the unpredictable chronological order.

357
0:22:16 --> 0:22:22
The coupling between observational data and biological insight is frayed, if not broken.

358
0:22:22 --> 0:22:28
This is from one of the world's leading gene mutation supporters of that idea of cancer.

359
0:22:29 --> 0:22:31
Bruce Alberts, he's another heavyweight.

360
0:22:32 --> 0:22:36
This is from his book, a 2014 book, I guess 2014 was a big year.

361
0:22:37 --> 0:22:42
His book was Molecular Biology of the Cell, chapter 20, page 1094.

362
0:22:42 --> 0:22:44
You can see it's a very, very big book.

363
0:22:45 --> 0:22:52
This book is used in universities to educate upcoming scientists, molecular biologists,

364
0:22:52 --> 0:22:53
and that sort of thing.

365
0:22:53 --> 0:22:55
Here's what he has to say, it's very, very interesting.

366
0:22:57 --> 0:23:01
Human DNA has three billion nucleotides, that's those ATCs and Gs,

367
0:23:01 --> 0:23:03
we have three billion of those, all right?

368
0:23:04 --> 0:23:10
Every time a cell divides, there is about one uncorrected mutation per every one billion

369
0:23:10 --> 0:23:11
nucleotides.

370
0:23:12 --> 0:23:17
Thus, there are about three random mutations every time a cell divides.

371
0:23:17 --> 0:23:21
But I can tell you right now from a chemist, a scientist, anybody,

372
0:23:21 --> 0:23:26
that's an extraordinarily, extraordinarily stable and resilient system.

373
0:23:26 --> 0:23:31
When you have three billion nucleotides and you only have three mutations,

374
0:23:32 --> 0:23:37
and it could be anywhere on that genome, on the DNA.

375
0:23:38 --> 0:23:43
No scientist, nobody could do that, just only nature can be that precise, that accurate.

376
0:23:43 --> 0:23:51
But then he goes on, there are 10,000 trillion cell divisions during the course of a human life.

377
0:23:52 --> 0:24:00
Based on this, every single gene is likely to have undergone mutation about 10 billion

378
0:24:00 --> 0:24:04
separate occasions, 10 billion separate occasions, every gene in your body.

379
0:24:07 --> 0:24:15
Just by using that one mutation per billion nucleotides, but we have so many cell divisions,

380
0:24:15 --> 0:24:16
you get these mutations.

381
0:24:17 --> 0:24:21
From this point of view, the problem of cancer seems to be not why it occurs,

382
0:24:21 --> 0:24:23
but why it occurs so infrequently.

383
0:24:23 --> 0:24:24
That's absolutely right.

384
0:24:25 --> 0:24:33
If gene mutations cause cancer, and with this rate of mutation that happens in everybody,

385
0:24:34 --> 0:24:38
this rate of mutations happens in everybody, why don't we all have…

386
0:24:39 --> 0:24:40
Life would not even be possible.

387
0:24:43 --> 0:24:49
Bert Vogelstein is another big gene mutation guy, and this was in 2016.

388
0:24:49 --> 0:24:55
He said, the search for cancer-causing gene mutations is hindered by the lack of a gold standard.

389
0:24:55 --> 0:24:58
That is, bona fide driver gene mutations.

390
0:24:58 --> 0:25:06
In other words, there is not a single cancer gene or gene mutation anywhere in the world

391
0:25:06 --> 0:25:14
that has been demonstrated to turn a normal cell into a cancer cell or combination of these.

392
0:25:14 --> 0:25:20
There's no single gene or combination of gene mutations that anybody has ever been able to

393
0:25:20 --> 0:25:23
demonstrate that turns a normal cell into a cancer cell.

394
0:25:25 --> 0:25:37
Yet, that is the current dogma that virtually every researcher who's working on academics or

395
0:25:38 --> 0:25:43
any grant for the National Cancer Institute, they're all working under the assumption

396
0:25:44 --> 0:25:51
that gene mutations are the source of lots of problems, especially cancer.

397
0:25:56 --> 0:25:58
This is what they're facing.

398
0:25:58 --> 0:26:04
Any of the people who are here in the Zoom meeting today who are scientists or certainly

399
0:26:04 --> 0:26:09
a biological scientist, you've probably seen one of these metabolic or biochemical pathway

400
0:26:09 --> 0:26:12
charts on the hall in your lab somewhere.

401
0:26:12 --> 0:26:17
They just keep getting bigger and bigger and more amazing as the years go by.

402
0:26:18 --> 0:26:23
You see, these things take up a sizable fraction of the wall in a laboratory.

403
0:26:24 --> 0:26:30
There's no way in this slide that I could make it…

404
0:26:30 --> 0:26:35
I can't amplify it big enough right here, where you can even see a name of any one of these little

405
0:26:35 --> 0:26:41
genes or proteins or enzymes that are part of this network.

406
0:26:41 --> 0:26:47
This is a biological roadmap of life, basically.

407
0:26:47 --> 0:26:50
It's got oxidation in there, replication.

408
0:26:50 --> 0:26:56
It's got all kinds of stuff in this thing that people have mapped one gene at a time in a group

409
0:26:56 --> 0:26:56
of them.

410
0:26:57 --> 0:26:59
They've been doing this now for decades.

411
0:26:59 --> 0:27:01
They come up with these maps.

412
0:27:01 --> 0:27:06
They know a lot about the enzymes, the kinetics and everything, but they don't have a clue

413
0:27:06 --> 0:27:08
other than to map these things up.

414
0:27:08 --> 0:27:17
But they have no clue about how to change things other than just try it, have a hypothesis,

415
0:27:17 --> 0:27:21
make a molecule for it, inhibit or change this enzyme for that enzyme or whatever,

416
0:27:21 --> 0:27:22
which they can do.

417
0:27:23 --> 0:27:25
Usually, it's an utter failure.

418
0:27:25 --> 0:27:26
Nothing happens.

419
0:27:26 --> 0:27:28
Occasionally, something does happen.

420
0:27:30 --> 0:27:34
If they have a hypothesis like they do with cancer, even though they've never found a

421
0:27:34 --> 0:27:42
cancer-causing gene, they come up with these hypotheses from that atlas of oncogenes and

422
0:27:42 --> 0:27:45
tumor suppressor genes, a whole host of different names for them.

423
0:27:46 --> 0:27:52
The drug companies then or the academics will design inhibitors or some way to interact,

424
0:27:52 --> 0:27:57
a molecule or some way to interact with these hypothetical genes or molecules.

425
0:27:58 --> 0:28:02
Low and behold, it either causes havoc in the patient.

426
0:28:02 --> 0:28:04
It doesn't stop cancer.

427
0:28:04 --> 0:28:07
If anything, it can increase cancer.

428
0:28:08 --> 0:28:08
It's insane.

429
0:28:09 --> 0:28:10
These people know this.

430
0:28:11 --> 0:28:14
This is one of the points that I want to stress here.

431
0:28:15 --> 0:28:22
I'm not more brilliant than these people are that make these maps and do this stuff

432
0:28:22 --> 0:28:24
and write these grant proposals and everything.

433
0:28:25 --> 0:28:29
The people who have been doing this for a couple of decades at least, maybe even a decade,

434
0:28:30 --> 0:28:35
that's a shorter time, know that what they're doing doesn't make sense.

435
0:28:35 --> 0:28:39
But they keep doing it because if they want to keep their grant support, if they want to

436
0:28:39 --> 0:28:46
keep their little company going or the pharmaceutical industry, they have to just keep doing the

437
0:28:46 --> 0:28:50
insanity and how they live with it, I don't know.

438
0:28:50 --> 0:28:53
I know for a fact that they know this.

439
0:28:53 --> 0:28:55
It was just like with the AIDS stuff.

440
0:28:55 --> 0:29:04
The people at UCSF and also UC Berkeley during the 1980s with the AIDS stuff, and certainly

441
0:29:04 --> 0:29:10
in the 90s, most of those people knew that AIDS was not contagious and HIV did not cause AIDS,

442
0:29:10 --> 0:29:13
but they kept their mouths shut and they kept working on it.

443
0:29:14 --> 0:29:21
So the way the system is set up, it looks like people are making a lot of progress.

444
0:29:21 --> 0:29:25
Look at this map here, this map of all these biological interactions and everything.

445
0:29:25 --> 0:29:28
Oh, we really know something to be able to do a map like that.

446
0:29:28 --> 0:29:35
They don't have any idea of how to use it or what to make sense of it other than it's just

447
0:29:35 --> 0:29:36
kind of impressive to hang on your wall.

448
0:29:36 --> 0:29:37
Okay, I'll stop preaching.

449
0:29:37 --> 0:29:38
I'll keep going here.

450
0:29:38 --> 0:29:43
All right, this is a big point that I want to make.

451
0:29:44 --> 0:29:47
Our genome is not an instruction manual.

452
0:29:47 --> 0:29:49
A lot of people think it is.

453
0:29:49 --> 0:29:51
It's a biological dictionary.

454
0:29:52 --> 0:30:00
The best way to see this is that the genome of the mouse and humans, 99% of our genomes

455
0:30:00 --> 0:30:08
are the same, same genomes in mice and humans, and over half of our genes we share with the worm.

456
0:30:09 --> 0:30:13
You know, and there aren't really, really worm genes,

457
0:30:13 --> 0:30:16
there aren't really mouse genes, there aren't really human genes.

458
0:30:16 --> 0:30:17
It's like a dictionary.

459
0:30:17 --> 0:30:19
Think of the Oxford English Dictionary.

460
0:30:20 --> 0:30:25
You can, all of the, anything that's ever been written in English,

461
0:30:25 --> 0:30:28
you can find those words in the Oxford English Dictionary.

462
0:30:28 --> 0:30:33
But no matter how hard you look and you go through those 23 volumes of the Oxford English

463
0:30:33 --> 0:30:40
Dictionary, you cannot derive a novel or a lecture or a published paper or anything.

464
0:30:40 --> 0:30:41
No, those are just a little building blocks.

465
0:30:41 --> 0:30:47
They're just the bricks that you put together to make a sentence, an idea, or a book.

466
0:30:48 --> 0:30:51
The same thing is with the genes.

467
0:30:51 --> 0:30:52
That's what the genes are.

468
0:30:53 --> 0:30:59
They're just the little bricks that the whole intact organism or the cell puts together

469
0:30:59 --> 0:31:05
in a particular way and makes these proteins and these enzymes.

470
0:31:05 --> 0:31:07
And then you get something magical.

471
0:31:07 --> 0:31:10
Like with the same genes, same genes you can make a human.

472
0:31:12 --> 0:31:14
Not scientists can, but people can.

473
0:31:14 --> 0:31:15
Or you can make a mouse.

474
0:31:15 --> 0:31:17
A mouse can make a mouse, you see.

475
0:31:18 --> 0:31:24
And even though they're the same genes, so trying to find, looking for an oncogene,

476
0:31:24 --> 0:31:34
a cancer-causing gene, makes as much sense as looking for the human genes in humans

477
0:31:35 --> 0:31:37
to distinguish us from a mouse.

478
0:31:37 --> 0:31:38
It's not possible.

479
0:31:38 --> 0:31:39
It's not possible to do that.

480
0:31:39 --> 0:31:45
And yet that's the logic that is being used with cancer right now and all other

481
0:31:46 --> 0:31:51
major complex biological phenotypes or characteristics.

482
0:31:53 --> 0:31:54
Okay, part two.

483
0:31:55 --> 0:31:58
Carcinogens cause aneuploid chromosomes.

484
0:31:58 --> 0:32:01
Aneuploid means unbalanced chromosomes.

485
0:32:02 --> 0:32:05
Last week, I guess, I brought up the word aneuploidy.

486
0:32:05 --> 0:32:08
And most people hadn't heard about it before.

487
0:32:08 --> 0:32:11
Aneuploidy is the state of unbalanced chromosomes.

488
0:32:12 --> 0:32:14
All right, that's just a technical word for it.

489
0:32:14 --> 0:32:20
So aneuploid chromosomes cause cancer and only aneuploid cells cause cancer.

490
0:32:20 --> 0:32:25
And that's what Theodore Boveri understood 110 years ago.

491
0:32:25 --> 0:32:28
And he put it in that book that you can download from my website.

492
0:32:30 --> 0:32:36
One of the first guys, it was David Hanselman back in 1891.

493
0:32:36 --> 0:32:39
And he was a German guy, just like David Theodore Boveri.

494
0:32:40 --> 0:32:46
And he used microscopic analysis to examine cancer cells.

495
0:32:46 --> 0:32:48
And he looked at hundreds of cancer cells.

496
0:32:48 --> 0:32:53
And there's a book, like I said, you can go to my website and download this biography of him.

497
0:32:53 --> 0:32:58
There's also other articles that he's written that you can get too.

498
0:32:59 --> 0:33:06
And what he noticed was, is that all cancer cells have these abnormally called chromatin.

499
0:33:07 --> 0:33:10
And you can see these pictures of these cells.

500
0:33:10 --> 0:33:15
This number 10 down here looks like probably was a control cell lower right,

501
0:33:15 --> 0:33:19
where you have the chromosomes, the dark things,

502
0:33:19 --> 0:33:23
are chromosomes that are being pulled apart as the cells divide.

503
0:33:24 --> 0:33:27
The cancer cells, every one of them is different.

504
0:33:27 --> 0:33:30
The chromatin is unbalanced.

505
0:33:30 --> 0:33:34
The two cells, when they divide, they don't have the same chromatin or chromosomes,

506
0:33:34 --> 0:33:35
just the normal cells do.

507
0:33:36 --> 0:33:40
And he never found a cancer cell that was not like that.

508
0:33:40 --> 0:33:44
And the normal cells are very, very reproducible.

509
0:33:44 --> 0:33:46
No two cancer cells are alike.

510
0:33:47 --> 0:33:53
And the cell of a malignant tumor is a cell with a certain abnormal chromatin content.

511
0:33:53 --> 0:33:57
He said that before Boveri did, and he was absolutely right.

512
0:33:57 --> 0:33:59
Boveri and Hanselman actually knew each other.

513
0:34:01 --> 0:34:03
Now we'll go to Boveri.

514
0:34:03 --> 0:34:04
Here's the big guy.

515
0:34:05 --> 0:34:09
He formulated the aneuploidy theory of cancer in 1914.

516
0:34:09 --> 0:34:11
And that was that book that you can download.

517
0:34:12 --> 0:34:15
I think it's 59 pages, something like that.

518
0:34:15 --> 0:34:20
He said, the essence of cancer was a certain abnormal chromatin constitution,

519
0:34:20 --> 0:34:24
the way in which it originates having no significance.

520
0:34:24 --> 0:34:27
Each process which brings about this chromatin constitution

521
0:34:27 --> 0:34:30
would result in the origin of a malignant cancer.

522
0:34:30 --> 0:34:32
He was absolutely right about that.

523
0:34:32 --> 0:34:36
And now let's talk about these chromosomes.

524
0:34:36 --> 0:34:39
And he explained in his book, he explained how that would happen.

525
0:34:41 --> 0:34:44
Karyotype is just a fancy word, the technical word

526
0:34:44 --> 0:34:48
for a collection of species specific chromosomes.

527
0:34:48 --> 0:34:52
Remember, mice and humans share the same genes.

528
0:34:52 --> 0:34:54
99% of our genes are identical.

529
0:34:56 --> 0:34:58
But we don't have the same complement of chromosomes.

530
0:34:58 --> 0:35:02
In other words, it's like taking the Oxford English Dictionary.

531
0:35:02 --> 0:35:05
Standard, it comes in 23 different volumes,

532
0:35:05 --> 0:35:08
just like the human genome comes in 23 different volumes,

533
0:35:08 --> 0:35:09
23 different chromosomes.

534
0:35:11 --> 0:35:17
But the mouse has the same genes, but it only comes in 20 volumes, not 23.

535
0:35:18 --> 0:35:20
And these volumes are called chromosomes.

536
0:35:21 --> 0:35:27
And with sexually reproducing organisms like mammals,

537
0:35:27 --> 0:35:32
with sexually reproducing organisms like mammals,

538
0:35:33 --> 0:35:39
you get for your 46 chromosomes, 23 unique chromosomes come from the mother,

539
0:35:39 --> 0:35:45
23 unique chromosomes come from the father, the mother and the father,

540
0:35:45 --> 0:35:51
for a complement of 46 chromosomes in humans for a total of 20,000 genes.

541
0:35:51 --> 0:35:53
And with the mice, the male and the female,

542
0:35:53 --> 0:35:57
I do the same thing for a total of 20,000 genes.

543
0:35:57 --> 0:36:01
So they have backup, think of it like backup chromosomes,

544
0:36:01 --> 0:36:06
because the two copies are identical in terms of genes.

545
0:36:08 --> 0:36:10
They're duplicated, but it's very, very important

546
0:36:11 --> 0:36:13
that you have two copies to get into that.

547
0:36:13 --> 0:36:17
Now here is a modern way of looking at the chromosomes.

548
0:36:17 --> 0:36:19
On the left, we have human chromosomes,

549
0:36:20 --> 0:36:24
and they're using modern stains, which makes it much easier to identify the chromosomes.

550
0:36:25 --> 0:36:30
On the left, we have a human with 46 chromosomes, it's normal, it's euploid.

551
0:36:31 --> 0:36:37
It's male because it has one lower right, it has one X chromosome,

552
0:36:37 --> 0:36:40
and one Y chromosome is the male.

553
0:36:40 --> 0:36:48
And over here on the right, females, by the way, have two X chromosomes and no Y chromosome.

554
0:36:49 --> 0:36:52
On the right, you have cancer with its unbalanced chromosomes.

555
0:36:52 --> 0:36:57
You can see there's chromosome one up here, chromosome two is missing up here.

556
0:36:57 --> 0:37:03
You have three copies of chromosome three, you got two of four, you got one of five over here,

557
0:37:03 --> 0:37:07
and then you see these numbers are changing all along down here.

558
0:37:07 --> 0:37:10
And then down at the bottom, you see this whole array of different,

559
0:37:11 --> 0:37:14
they're stitched together chromosomes, they're called marker chromosomes.

560
0:37:15 --> 0:37:22
And no two cancer cells have the same complement of chromosomes.

561
0:37:22 --> 0:37:23
That's extremely important.

562
0:37:24 --> 0:37:30
All normal cells have the same complement of chromosomes, they're balanced.

563
0:37:30 --> 0:37:35
You can call them diploid for meaning two, their ploidy is diploid,

564
0:37:35 --> 0:37:38
or you can call them euploid for meaning it's normal.

565
0:37:39 --> 0:37:43
And euploid means they're unbalanced, they're abnormal.

566
0:37:43 --> 0:37:48
There's no two cancer cells that have the same complement of chromosomes.

567
0:37:48 --> 0:37:52
They have the same genes, but not the same complement of chromosomes.

568
0:37:52 --> 0:37:55
I emphasize that because it's so crucial, a lot of people don't know that.

569
0:37:57 --> 0:38:00
And here's some of the terminology, I've already been using it.

570
0:38:01 --> 0:38:04
Ploidy is just how many chromosomes do you have in your cell?

571
0:38:04 --> 0:38:08
Euploid means a balanced set of normal chromosomes.

572
0:38:08 --> 0:38:11
Humans, we have two copies of 23.

573
0:38:11 --> 0:38:16
One, half of them come from the mother, half comes from the father.

574
0:38:16 --> 0:38:22
For a total of 46, aneuploid means unbalanced chromosomes, for example, down syndrome.

575
0:38:22 --> 0:38:25
The down syndrome kids are actually aneuploid.

576
0:38:25 --> 0:38:30
They are born with the usual 46 chromosomes plus an extra chromosome 21

577
0:38:31 --> 0:38:34
for a total of 47 chromosomes.

578
0:38:35 --> 0:38:38
I don't have time to go into the consequences of that today,

579
0:38:38 --> 0:38:40
but we can in the discussion area if you want to.

580
0:38:42 --> 0:38:49
And then there's pseudodeploid, where you can have like this DLD1 cell line,

581
0:38:49 --> 0:38:53
it's an artificial cell line, which to use it in cell culture and laboratory.

582
0:38:54 --> 0:38:55
It's aneuploid.

583
0:38:55 --> 0:39:01
It has the right number of chromosomes, 46, but they have, for example,

584
0:39:01 --> 0:39:05
three copies of one of the chromosomes and only one copy of the other one,

585
0:39:05 --> 0:39:09
which makes it aneuploid, but the total is still 46.

586
0:39:12 --> 0:39:15
Now, this is what a pathologist looks at through a microscope.

587
0:39:15 --> 0:39:18
This is from the Pap smear that most everybody is familiar with,

588
0:39:19 --> 0:39:22
that George Papadikala developed back in the 50s.

589
0:39:23 --> 0:39:28
And they still use it to this day because it's the best cancer,

590
0:39:29 --> 0:39:34
as of right now, the best way to diagnose cancer is still with the Pap smear, the Pap test.

591
0:39:35 --> 0:39:40
And this is normal cervical cancer, normal cervical cells up here.

592
0:39:40 --> 0:39:46
They're stained with the cytoplasm green and the nucleus of these things are purple.

593
0:39:47 --> 0:39:49
And then they have 46 balanced chromosomes.

594
0:39:50 --> 0:39:53
And here is what the pathologist sees, for example.

595
0:39:53 --> 0:39:59
These are cancer cells that he sees along adjacent to the normal cells that happen to be

596
0:40:00 --> 0:40:04
in the Pap smear or on the cervix someplace.

597
0:40:04 --> 0:40:06
And you can see they're very, very different.

598
0:40:06 --> 0:40:09
They have between six, typically between 60 and 90 chromosomes.

599
0:40:09 --> 0:40:11
That's why they're so much larger.

600
0:40:12 --> 0:40:14
And the nuclei are much larger.

601
0:40:14 --> 0:40:18
That's one of the rules that pathologists use.

602
0:40:18 --> 0:40:25
They look for nuclei that are about three times larger than the normal cell has,

603
0:40:25 --> 0:40:28
as an indication that's possibly a cancer cell.

604
0:40:28 --> 0:40:32
And you can see that they're all different sizes and types of things,

605
0:40:32 --> 0:40:37
just like Hanselman, SAAW, and Bavaria.

606
0:40:37 --> 0:40:40
No two cancer cells look like each other.

607
0:40:42 --> 0:40:48
A theory of cancer must explain these and other features pathologists use to diagnose cancer.

608
0:40:48 --> 0:40:53
It must explain the time course of carcinogenesis, chromosomal instability,

609
0:40:53 --> 0:40:59
and other characteristics of cancer, such as drug resistance and abnormal metabolism,

610
0:40:59 --> 0:41:00
the Warburg effect.

611
0:41:00 --> 0:41:02
We're going to be talking about some of those things.

612
0:41:03 --> 0:41:03
Part three.

613
0:41:04 --> 0:41:08
How does chromosomal imbalance cause cancer?

614
0:41:09 --> 0:41:13
That's where Theodore Boveri came into, and he explained it.

615
0:41:13 --> 0:41:15
And Peter Duesberg and I proved it.

616
0:41:17 --> 0:41:22
For cancer to happen, the cells have to be able to divide.

617
0:41:22 --> 0:41:24
Cancer requires cell division.

618
0:41:24 --> 0:41:28
And let's just say we have a normal cell right here.

619
0:41:28 --> 0:41:31
It starts out with the normal 46 chromosomes.

620
0:41:31 --> 0:41:36
Before that cell has to divide, it has to double its chromosomes in order to,

621
0:41:36 --> 0:41:42
when it divides, such that each new cell, the two new cells that are a product of cell division,

622
0:41:42 --> 0:41:45
will both wind up having the balanced set of 46 chromosomes.

623
0:41:45 --> 0:41:48
That's what normally happens when cell division happens.

624
0:41:48 --> 0:41:52
The 46 chromosomes in one cell are duplicated to make 92.

625
0:41:52 --> 0:41:54
The cell divides.

626
0:41:54 --> 0:41:55
46 goes to the left.

627
0:41:55 --> 0:41:57
46 goes to the right.

628
0:41:57 --> 0:41:58
And you have two new cells.

629
0:41:59 --> 0:42:01
And right here we show a cell getting ready to divide.

630
0:42:01 --> 0:42:03
You can see the chromosomes here.

631
0:42:04 --> 0:42:09
And then they line up in preparation for that cell to divide.

632
0:42:10 --> 0:42:12
They line up with what's called the centromeres.

633
0:42:12 --> 0:42:16
That's where the proteins that pull the chromosomes apart.

634
0:42:16 --> 0:42:17
That's what they're called centromeres.

635
0:42:17 --> 0:42:18
That's where it's attached.

636
0:42:18 --> 0:42:25
They have to line up on what's called a metaphase plate and get lined up such that they can then

637
0:42:26 --> 0:42:31
get the forces balanced so that the cell, the chromosomes can be pulled apart.

638
0:42:31 --> 0:42:33
And here is the cell on the left.

639
0:42:34 --> 0:42:36
You see the chromosomes are starting to be pulled apart.

640
0:42:36 --> 0:42:39
The blue things are the chromosomes.

641
0:42:40 --> 0:42:44
And the spindle apparatus, or the red protein, so they're attached to the chromosomes.

642
0:42:44 --> 0:42:48
And they're pulling those chromosomes apart during cell division.

643
0:42:48 --> 0:42:54
If you rotate this image on the left, just 90 degrees, you see that what you're looking,

644
0:42:54 --> 0:42:55
it looks like a donut.

645
0:42:55 --> 0:43:00
That's what it looks like when you rotate that metaphase plate and you look at it head on.

646
0:43:00 --> 0:43:04
The thing on the left, the image on the left, is pulling the chromosomes left and right.

647
0:43:06 --> 0:43:09
The image on the right, the chromosomes are being pulled towards you

648
0:43:10 --> 0:43:13
and then away from you into your computer.

649
0:43:13 --> 0:43:16
And you can see that these are balanced.

650
0:43:16 --> 0:43:19
There's a symmetry here that's absolutely essential to balance the forces.

651
0:43:19 --> 0:43:21
It's a little donut.

652
0:43:21 --> 0:43:25
Right here, right in the middle where I'm moving my little cursor,

653
0:43:25 --> 0:43:27
that's where the centromeres are.

654
0:43:28 --> 0:43:33
And that's where the spindle apparatus are attached so they can pull those chromosomes apart.

655
0:43:34 --> 0:43:38
All right, now here's where we're going to generate some aneuploidy.

656
0:43:38 --> 0:43:43
Let's say there's some carcinogen or x-ray or cosmic rays or whatever happens.

657
0:43:44 --> 0:43:47
The cancer results from unbalanced cell division.

658
0:43:48 --> 0:43:55
So you had your 92 chromosomes all ready to go and something happens.

659
0:43:57 --> 0:44:02
Asbestos or something in your cytoplasm interfering with chromosomal separation.

660
0:44:02 --> 0:44:08
All carcinogens interrupt one way or another, normal cell division,

661
0:44:08 --> 0:44:11
and they cause an imbalance of forces.

662
0:44:12 --> 0:44:15
And then when they're, if they, most of these cells,

663
0:44:15 --> 0:44:18
once they have an imbalance in chromosomes, they die.

664
0:44:18 --> 0:44:20
They can't divide.

665
0:44:20 --> 0:44:23
But on the rare occasions that they do, they adjust these things,

666
0:44:23 --> 0:44:25
move them around or whatever to try to balance the forces.

667
0:44:25 --> 0:44:29
And if they are able to divide, then unbalanced division happens.

668
0:44:29 --> 0:44:33
Like moving to the left, there are 41 chromosomes.

669
0:44:33 --> 0:44:35
Moving to the right, there are 51 chromosomes.

670
0:44:35 --> 0:44:37
Now we have two aneuploid cells.

671
0:44:38 --> 0:44:38
All right.

672
0:44:40 --> 0:44:42
And then they're going to divide.

673
0:44:42 --> 0:44:44
And we have two new aneuploid cells.

674
0:44:44 --> 0:44:48
So when they divide, then they can either propagate or die.

675
0:44:48 --> 0:44:50
They usually die.

676
0:44:50 --> 0:44:51
Thank goodness.

677
0:44:51 --> 0:44:54
But if you have lots of exposure to carcinogen,

678
0:44:54 --> 0:44:56
you generate a population of these things.

679
0:44:57 --> 0:45:02
And at some point, some of them will figure out how to survive, unfortunately.

680
0:45:02 --> 0:45:04
But even those usually die.

681
0:45:04 --> 0:45:06
We'll get into that here in a little bit.

682
0:45:08 --> 0:45:10
OK, cancer phenotypes.

683
0:45:10 --> 0:45:13
Phenotype just means a characteristic or a property

684
0:45:13 --> 0:45:15
that you can look at under the microscope

685
0:45:15 --> 0:45:18
or it's like a physical something that you can measure

686
0:45:18 --> 0:45:20
and compare the good and the bad.

687
0:45:22 --> 0:45:26
So for example, large size and variable morphology

688
0:45:26 --> 0:45:28
that pathologists use, those are phenotypes.

689
0:45:28 --> 0:45:31
The appearance of tumor-associated antigens,

690
0:45:31 --> 0:45:34
that usually means like on the surface of a cell,

691
0:45:35 --> 0:45:38
that these proteins are on the surface of a cell,

692
0:45:38 --> 0:45:40
on cancer cells that are not present normal cells.

693
0:45:41 --> 0:45:43
You have high levels of secreted proteins

694
0:45:43 --> 0:45:47
that are responsible for invasiveness and loss of contact inhibition

695
0:45:48 --> 0:45:52
that allows cancers to progress and metastasize.

696
0:45:52 --> 0:45:54
And then, of course, there's the chromosomal instability

697
0:45:54 --> 0:45:58
that's responsible for progression and drug resistance.

698
0:45:58 --> 0:46:03
All of these things are due to aneuploidy and the overexpression of protein.

699
0:46:04 --> 0:46:06
Important observations.

700
0:46:07 --> 0:46:11
Aneuploid cancer cells have substantially greater amounts

701
0:46:11 --> 0:46:13
of DNA, RNA, and protein.

702
0:46:13 --> 0:46:20
The DNA, or the nucleotides, or those 3 billion nucleotides,

703
0:46:20 --> 0:46:24
the 20,000 genes that code for RNA,

704
0:46:24 --> 0:46:27
which leaves the nucleus, it goes out in the cytoplasm,

705
0:46:27 --> 0:46:30
it takes that coded information,

706
0:46:30 --> 0:46:32
goes into the cytoplasm of the cell,

707
0:46:32 --> 0:46:35
and it turns that coded sequence of RNA

708
0:46:35 --> 0:46:37
into a sequence of amino acids to make a protein.

709
0:46:38 --> 0:46:44
And so, the cancer cells, the aneuploid cancer cells,

710
0:46:44 --> 0:46:48
have substantially greater amounts of this DNA, RNA, and protein than normal cells.

711
0:46:48 --> 0:46:51
And that has dramatic consequences.

712
0:46:52 --> 0:46:56
This is most important of all for me personally,

713
0:46:56 --> 0:46:59
when I was trying to understand chromosomal imbalance

714
0:46:59 --> 0:47:02
and try to explain all the phenotypes.

715
0:47:02 --> 0:47:03
Of cancer phenotypes.

716
0:47:03 --> 0:47:08
And this is very crucial data that's important,

717
0:47:08 --> 0:47:10
it's been known for half my life

718
0:47:11 --> 0:47:15
that the relative proportions of DNA to RNA

719
0:47:15 --> 0:47:17
and RNA to protein are constant.

720
0:47:18 --> 0:47:21
In normal cells, the euploid cells, which are normal cells,

721
0:47:21 --> 0:47:24
and aneuploid cells, those relative proportions,

722
0:47:24 --> 0:47:29
in other words, if you increase the amount of DNA in a cancer cell,

723
0:47:30 --> 0:47:34
you automatically proportionally increase the amount of RNA and protein.

724
0:47:34 --> 0:47:40
And that has the profound biophysical consequences for these cells.

725
0:47:41 --> 0:47:45
Biophysical and biochemical consequences of aneuploidy.

726
0:47:47 --> 0:47:50
There's a 70% increase in the nuclear volume,

727
0:47:50 --> 0:47:53
that's why we saw those big nuclei in aneuploid cells.

728
0:47:53 --> 0:47:58
There's 70% increase in nuclear volume due to aneuploidy,

729
0:47:58 --> 0:48:04
produces only a 40% increase in the surface area of the nuclear membrane.

730
0:48:04 --> 0:48:06
Now those are out of balance.

731
0:48:06 --> 0:48:09
The physical properties of the membrane,

732
0:48:09 --> 0:48:11
which surrounds the chromosomes,

733
0:48:11 --> 0:48:13
now they're out of balance, they're disproportionate.

734
0:48:14 --> 0:48:17
And consequently, a change in the number of chromosomes

735
0:48:17 --> 0:48:21
alters the interactions between the chromosomes and the nuclear membrane.

736
0:48:22 --> 0:48:27
Cancer cells have a 10 to 100% more protein than euploid cells.

737
0:48:28 --> 0:48:34
The excess protein has even a greater consequence than the RNA.

738
0:48:34 --> 0:48:38
And the excess protein has profound consequences for the cancer cell

739
0:48:39 --> 0:48:41
because they're really big molecules.

740
0:48:42 --> 0:48:45
The consequences of extra protein.

741
0:48:45 --> 0:48:48
Biochemical changes are proportional.

742
0:48:48 --> 0:48:51
In other words, if you double an enzyme,

743
0:48:51 --> 0:48:53
the amount of an enzyme present,

744
0:48:53 --> 0:48:57
you double its activity, its ability to do work.

745
0:48:57 --> 0:49:00
That's the biochemical approach, all right?

746
0:49:00 --> 0:49:03
But the biophysical changes are exponential.

747
0:49:03 --> 0:49:08
They go up, they have much, much greater consequences than the biochemical.

748
0:49:08 --> 0:49:10
Here's some of the examples below.

749
0:49:10 --> 0:49:13
Says the effects of increased cellular protein.

750
0:49:13 --> 0:49:18
There's lots and lots of extra protein in cancer cells.

751
0:49:18 --> 0:49:21
The membrane-bound proteins, for example,

752
0:49:21 --> 0:49:23
we'll just talk about those right now.

753
0:49:23 --> 0:49:27
If you have a 10% increase in cellular protein,

754
0:49:27 --> 0:49:31
that's CP, you have a 100% increase in proteins

755
0:49:31 --> 0:49:33
that are bound to membranes, whether it's the nuclear membrane

756
0:49:34 --> 0:49:36
or the cellular membrane.

757
0:49:37 --> 0:49:39
And that has profound consequences.

758
0:49:39 --> 0:49:43
That explains a huge amount of things about invasiveness of cancer,

759
0:49:45 --> 0:49:47
just how the metabolism is all screwed up.

760
0:49:49 --> 0:49:52
And then the same thing with secreted proteins.

761
0:49:52 --> 0:49:57
If you have a 10% increase in the secreted protein,

762
0:49:58 --> 0:50:01
there is a 400% increase, or cellular proteins,

763
0:50:01 --> 0:50:04
or 400% increase in secreted proteins.

764
0:50:04 --> 0:50:08
And a 40%, you can see up here, a 40% increase in cellular proteins,

765
0:50:08 --> 0:50:12
the 3,100% increase in membrane-bound proteins.

766
0:50:13 --> 0:50:17
But there's typically a 70% increase in protein in cancer cells.

767
0:50:17 --> 0:50:18
And I don't know what those numbers are,

768
0:50:18 --> 0:50:21
but you can see how big these consequences are.

769
0:50:22 --> 0:50:24
Now, the Warburg effect, that has to do,

770
0:50:24 --> 0:50:27
the Warburg effect has to do with energy production.

771
0:50:28 --> 0:50:32
Aerobic glycolysis takes place in the mitochondria of the cells,

772
0:50:32 --> 0:50:36
the mitochondria of big organelles inside your cells

773
0:50:37 --> 0:50:41
that produce ATP, adenosine triphosphate,

774
0:50:42 --> 0:50:45
which is the energy molecule for most living things.

775
0:50:45 --> 0:50:49
Aerobic glycolysis in the mitochondria is much more efficient

776
0:50:49 --> 0:50:52
at producing the energy molecule, ATP.

777
0:50:52 --> 0:50:59
You get 32 molecules of ATP per one molecule of glucose by the mitochondria.

778
0:51:00 --> 0:51:07
Why then do cancer cells resort to the less efficient fermentation to produce ATP?

779
0:51:07 --> 0:51:09
Because that's where the Warburg effect.

780
0:51:09 --> 0:51:13
Instead of relying on mitochondria, now the fermentation comes in here.

781
0:51:15 --> 0:51:19
Increased production of ATP in the mitochondria of cancer cells

782
0:51:19 --> 0:51:23
is limited by crowding due to the extra chromosomes in protein.

783
0:51:24 --> 0:51:30
Mitochondria require five to 50 times more space than fermentation does,

784
0:51:30 --> 0:51:35
which happens in the cytoplasm, to produce the same amount of ATP.

785
0:51:35 --> 0:51:41
Fermentation produces ATP up to 200 times faster than the mitochondria,

786
0:51:41 --> 0:51:44
and it takes much less space to do it.

787
0:51:44 --> 0:51:45
And it does it in the cytoplasm.

788
0:51:46 --> 0:51:49
And as a consequence of this in cancer cells,

789
0:51:50 --> 0:51:53
many of the mitochondria shrink and die away.

790
0:51:53 --> 0:51:57
Mitochondria-like cells, I mean, they go away, they can reproduce, and they come back.

791
0:51:57 --> 0:52:03
But a large fraction of the mitochondria in normal cells disappear in cancer cells

792
0:52:03 --> 0:52:08
because they're just too big for the biophysics of all that aneuploidy.

793
0:52:09 --> 0:52:11
They're still there, but they're very, very reduced.

794
0:52:11 --> 0:52:14
And to make up for the lost ability to produce ATP,

795
0:52:14 --> 0:52:17
that's when fermentation comes in there,

796
0:52:17 --> 0:52:20
and it produces all the energy that cancer cells need.

797
0:52:20 --> 0:52:24
Those cancer cells turn to fermentation of glucose

798
0:52:24 --> 0:52:28
to provide the additional energy required for the synthesis of extra protein.

799
0:52:30 --> 0:52:31
Now, chromosomal instability.

800
0:52:31 --> 0:52:34
Chromosomal instability is absolute.

801
0:52:34 --> 0:52:37
If you don't have chromosomal instability, you don't have cancer.

802
0:52:37 --> 0:52:40
Without chromosomal instability, there is no.

803
0:52:40 --> 0:52:44
Once you get the aneuploid cell from a carcinogen,

804
0:52:44 --> 0:52:47
if there is no progression, you don't get cancer.

805
0:52:49 --> 0:52:52
There is no cancer, there's no metastasis,

806
0:52:52 --> 0:52:55
there's no drug resistance without chromosomal instability.

807
0:52:55 --> 0:52:58
That's the only way a cancer cell can progress

808
0:52:58 --> 0:53:03
is because unbalanced chromosomes are unstable and they're constantly changing.

809
0:53:03 --> 0:53:04
And we'll talk about that here.

810
0:53:05 --> 0:53:08
The evidence strongly suggests that the relationship

811
0:53:08 --> 0:53:11
between aneuploidy and chromosomal instability

812
0:53:11 --> 0:53:16
can be envisioned as a vicious cycle where one potentiates the other.

813
0:53:17 --> 0:53:20
The vicious cycle can lead to a rapid broadening of the karyotype.

814
0:53:20 --> 0:53:22
The karyotype is the collection of chromosomes.

815
0:53:24 --> 0:53:26
And it broadens the karyotype diversity,

816
0:53:26 --> 0:53:29
the variety of combinations of chromosomes,

817
0:53:29 --> 0:53:33
in a population providing the substrate for natural selection.

818
0:53:35 --> 0:53:36
I know that lady.

819
0:53:36 --> 0:53:39
In other words, as soon as you get an imbalance,

820
0:53:39 --> 0:53:43
you get progression, which leads to more imbalance, leads to more progression,

821
0:53:44 --> 0:53:48
up to a point until the cells just can't handle it more and they almost always die.

822
0:53:49 --> 0:53:52
Aneuploidy and chromosomal instability are inseparable.

823
0:53:52 --> 0:53:55
That's basically what she was talking about.

824
0:53:55 --> 0:54:01
Aneuploidy increases the complexity of managing all cellular activities.

825
0:54:01 --> 0:54:04
Chromosomal imbalance disrupts the mitotic machinery

826
0:54:04 --> 0:54:07
that separates the chromosomes during cell division,

827
0:54:07 --> 0:54:09
leading to chromosomal instability.

828
0:54:09 --> 0:54:12
Every time aneuploid cell divides,

829
0:54:13 --> 0:54:18
it's struggling to try to get the chromosomes lined up so it can separate

830
0:54:19 --> 0:54:21
and keep dividing.

831
0:54:21 --> 0:54:22
Almost always they fail.

832
0:54:24 --> 0:54:28
A single extra, an extra copy of a single chromosome

833
0:54:28 --> 0:54:32
is sufficient to produce chromosomal instability.

834
0:54:32 --> 0:54:34
Remember Down syndrome kids?

835
0:54:34 --> 0:54:38
They have one extra copy of the smallest human chromosome, chromosome 21.

836
0:54:38 --> 0:54:42
They have elevated risk of lots of different types of cancer

837
0:54:42 --> 0:54:44
that have nothing to do with cigarette smoking.

838
0:54:44 --> 0:54:47
They used to, they noticed that Down syndrome kids

839
0:54:47 --> 0:54:50
have much lower levels of lung cancer,

840
0:54:50 --> 0:54:52
head and neck, throat cancer and everything.

841
0:54:53 --> 0:54:56
That's restricted to people that smoke a lot basically.

842
0:54:56 --> 0:55:01
But they have elevated levels of all other kinds of cancer

843
0:55:01 --> 0:55:05
and don't have enough time to really talk about all those details right now.

844
0:55:05 --> 0:55:06
But they really do.

845
0:55:06 --> 0:55:09
They have hugely elevated levels of cancer,

846
0:55:09 --> 0:55:13
just because the extra copy of the smallest chromosome.

847
0:55:14 --> 0:55:18
The greater the imbalance of chromosomes, the greater the instability.

848
0:55:18 --> 0:55:22
The result is a heterogeneous population of aneuploid cells,

849
0:55:23 --> 0:55:26
leading to, once you have mature cancer,

850
0:55:26 --> 0:55:29
like in the solid cancer that takes decades to develop,

851
0:55:29 --> 0:55:32
once you have a tumor with all those cancer cells,

852
0:55:32 --> 0:55:35
no two cancer cells are identical.

853
0:55:35 --> 0:55:38
Every one of them has a different collection of chromosomes.

854
0:55:38 --> 0:55:42
Yet they have all the same genes, just a different collection of chromosomes.

855
0:55:42 --> 0:55:45
Aneuploidy always damages the cell.

856
0:55:45 --> 0:55:49
However, gaining chromosomes is more survivable than a loss.

857
0:55:50 --> 0:55:53
The survival advantage of cells with gained chromosomes

858
0:55:53 --> 0:55:58
plus chromosomal instability leads to the automatic progression of aneuploidy

859
0:55:59 --> 0:56:01
with an increase in chromosomes.

860
0:56:01 --> 0:56:04
That's why when you have aneuploid cells dividing,

861
0:56:05 --> 0:56:08
the ones that survive are the ones that have more chromosomes,

862
0:56:10 --> 0:56:14
than the ones that die off faster, the ones that have fewer chromosomes,

863
0:56:14 --> 0:56:16
compared to those that have more chromosomes.

864
0:56:16 --> 0:56:18
But they're generally dying off anyway.

865
0:56:20 --> 0:56:24
Here is just a schematic of the progression of cancer.

866
0:56:25 --> 0:56:28
Here you have a normal cell where its DNA index equals one,

867
0:56:28 --> 0:56:36
which means you divide the 46 chromosomes by 23 chromosomes,

868
0:56:36 --> 0:56:37
whichever way you want to look at it.

869
0:56:37 --> 0:56:42
The normal number of chromosomes by itself, that's the DNA index of one.

870
0:56:42 --> 0:56:46
In this case here, we have two copies of each chromosome,

871
0:56:46 --> 0:56:50
so you divide each one of these copies, two copies by two,

872
0:56:50 --> 0:56:52
DNA index of one, all along the border.

873
0:56:52 --> 0:56:53
That's normal.

874
0:56:53 --> 0:57:00
You come in and there's carcinogen, asbestos, radiation, whatever,

875
0:57:00 --> 0:57:05
you get an unbalanced cell, a cell with unbalanced chromosomes,

876
0:57:05 --> 0:57:07
and it starts trying to divide.

877
0:57:07 --> 0:57:14
You get these low level of chromosomes with DNA indices between 0.5 and 1.2.

878
0:57:15 --> 0:57:21
1.3, anywhere between 1.2 and 1.3 seems to be a barrier that cells

879
0:57:21 --> 0:57:24
have a very, very difficult time of progressing.

880
0:57:25 --> 0:57:28
That's why cancer is so rare.

881
0:57:28 --> 0:57:30
These cancer cells are wimpy.

882
0:57:30 --> 0:57:33
They die out in droves spontaneously.

883
0:57:33 --> 0:57:36
But if you keep getting doses and doses of carcinogens,

884
0:57:36 --> 0:57:41
and you keep feeding them, and keep doing this, and your health goes down,

885
0:57:41 --> 0:57:45
then eventually you're going to have some cells that are going to be able to survive.

886
0:57:45 --> 0:57:48
And then what they do is they have enough of them around,

887
0:57:49 --> 0:57:56
they do what's called chromosome doubling, where the tetraploidization,

888
0:57:56 --> 0:58:01
where the cells that have DNA index below 1.3, they can't divide.

889
0:58:01 --> 0:58:02
A lot of them can't divide.

890
0:58:02 --> 0:58:03
A lot of times they just die.

891
0:58:03 --> 0:58:08
But some rare occasions, some then just double their chromosomes again,

892
0:58:08 --> 0:58:13
and then they're able to get a balanced set of chromosomes, higher DNA index,

893
0:58:13 --> 0:58:16
and they pull the cells apart.

894
0:58:16 --> 0:58:18
They divide, pull the chromosomes apart.

895
0:58:18 --> 0:58:21
Then they get these cells that are called tetraploidization.

896
0:58:22 --> 0:58:24
They're much larger cells.

897
0:58:24 --> 0:58:27
They have roughly twice the amount of chromosomes available.

898
0:58:27 --> 0:58:31
But they're very, very unstable.

899
0:58:32 --> 0:58:35
Since they have extra chromosomes, they can afford to lose some.

900
0:58:35 --> 0:58:41
So as these progression goes along, there is a balance among these cells

901
0:58:42 --> 0:58:44
to lose them.

902
0:58:44 --> 0:58:45
They can afford to lose chromosomes.

903
0:58:46 --> 0:58:48
And it's better that they lose these chromosomes.

904
0:58:49 --> 0:58:56
It turns out nature has figured out a way to balance the survivability of aneuploid chromosomes.

905
0:58:57 --> 0:59:02
The DNA index that seems to be the most stable for these aneuploid cells

906
0:59:03 --> 0:59:11
is around a DNA index of 1.7, meaning they have 70% extra protein, 70% extra DNA.

907
0:59:11 --> 0:59:12
But it's wide.

908
0:59:12 --> 0:59:17
Varies from 1.5 to 1.9, but typically hovers around 1.7.

909
0:59:18 --> 0:59:20
And they can just keep dividing.

910
0:59:22 --> 0:59:25
So that's the progression part of this thing.

911
0:59:26 --> 0:59:30
Now into the quantitative theory of chromosomal imbalance.

912
0:59:31 --> 0:59:33
More details about this.

913
0:59:33 --> 0:59:36
Every one of these little subjects that I'm talking about, believe me,

914
0:59:36 --> 0:59:38
is an hour talking in its own right.

915
0:59:39 --> 0:59:41
But I'm just trying to give you the highlights here.

916
0:59:42 --> 0:59:44
And there's my book again.

917
0:59:44 --> 0:59:52
You can go to that book, my book on my website, and get more details.

918
0:59:52 --> 0:59:55
But this book was written for scientists.

919
0:59:55 --> 0:59:57
It's got a lot of technical jargon.

920
0:59:57 --> 1:00:01
But I tried to make it as much as possible in English.

921
1:00:01 --> 1:00:03
I've written another book for the general public.

922
1:00:03 --> 1:00:06
It's not published yet, but maybe it will this coming year.

923
1:00:06 --> 1:00:07
It's in the hands of the publisher right now.

924
1:00:07 --> 1:00:08
Thank goodness.

925
1:00:08 --> 1:00:14
So the phenotypes of cancer cells are determined by the fraction of the genome.

926
1:00:14 --> 1:00:20
This is another crucial feature about aneuploidy.

927
1:00:21 --> 1:00:29
It's the fraction of the chromosomes that are out of balance that determines cancer.

928
1:00:29 --> 1:00:33
The phenotypes of cancer cells are determined by the fraction of the genome phi.

929
1:00:33 --> 1:00:35
That's a Greek letter phi there.

930
1:00:35 --> 1:00:39
That is out of balance relative to the euploid cell.

931
1:00:40 --> 1:00:44
And that fraction is typically again about 50% to 70%.

932
1:00:45 --> 1:00:47
You see it's a large, large fraction right there.

933
1:00:49 --> 1:00:51
And here is just a diagram of this.

934
1:00:53 --> 1:00:58
It shows this is a plot of balanced, unbalanced phenotypes.

935
1:00:59 --> 1:01:03
The horizontal axis, the ploidy factor, just says,

936
1:01:03 --> 1:01:05
how many chromosomes do you have?

937
1:01:07 --> 1:01:10
Ploidy factor one means you have a DNA index of one.

938
1:01:11 --> 1:01:14
It means you have two copies of each chromosome.

939
1:01:14 --> 1:01:20
And then that's a little green thing down here on the x-axis, the horizontal axis.

940
1:01:20 --> 1:01:24
And then the cellular activity is arbitrarily designated one up here,

941
1:01:25 --> 1:01:29
just as your normal background phenotypes of your cell.

942
1:01:29 --> 1:01:35
Normal phenotypes of a cell are at this FD right here, flux.

943
1:01:36 --> 1:01:38
The F stands for flux.

944
1:01:38 --> 1:01:40
It's the activity or the output of a cell.

945
1:01:42 --> 1:01:46
Number one is just arbitrarily designated number here.

946
1:01:46 --> 1:01:50
And this just means that you have balanced chromosomes down here at one.

947
1:01:51 --> 1:01:57
These other things that I have up here are like we have cancer.

948
1:01:57 --> 1:01:58
That's why I have it in red right here.

949
1:01:59 --> 1:02:08
It has, like I said, a DNA index of around 1.7, which would be right about in here someplace.

950
1:02:09 --> 1:02:10
Or phi about 0.7.

951
1:02:10 --> 1:02:11
Here's 0.5.

952
1:02:12 --> 1:02:13
Then you have 0.2.

953
1:02:14 --> 1:02:16
And then down here we have this.

954
1:02:18 --> 1:02:21
This phi down here equal to 0.01.

955
1:02:22 --> 1:02:23
That's for down syndrome.

956
1:02:23 --> 1:02:27
That's like the kid that has the three copies of chromosome 21.

957
1:02:28 --> 1:02:30
It affects 1% of the genome.

958
1:02:30 --> 1:02:32
1% of the genome is affected.

959
1:02:33 --> 1:02:39
Now the seven gene mutation theory of cancer, that's this one over here.

960
1:02:40 --> 1:02:49
That little seven, that 0.00007, that's the phi of the seven gene theory of cancer.

961
1:02:49 --> 1:02:52
People early on, they thought it took seven gene mutations to cause cancer.

962
1:02:53 --> 1:02:57
Well, that's a very, very tiny fraction of the genome.

963
1:02:57 --> 1:03:03
And this dotted line right here shows you the effect of those genes.

964
1:03:03 --> 1:03:09
In other words, the phenotypic effect, that's what is measured here on this y-axis,

965
1:03:09 --> 1:03:11
on the vertical axis right here.

966
1:03:11 --> 1:03:12
It has no effect.

967
1:03:12 --> 1:03:19
The normal effect right here at this one down at the bottom and this one over here on the left.

968
1:03:19 --> 1:03:22
Right there is the normal cell number.

969
1:03:22 --> 1:03:23
Right there, it's at one.

970
1:03:23 --> 1:03:29
And look, this dotted line right here is the dotted line for the seven gene mutation.

971
1:03:29 --> 1:03:33
It has no effect on the phenotype of a cell.

972
1:03:34 --> 1:03:39
If you want to change the phenotype of a cell and all its properties like cancer cells,

973
1:03:39 --> 1:03:44
you have to change, you have to increase the fraction of the cell that is aneuploid.

974
1:03:44 --> 1:03:49
So here is 0.2 and then you get up here to 0.5.

975
1:03:49 --> 1:03:52
In other words, 50% of the chromosomes are out of balance.

976
1:03:52 --> 1:03:54
You're up here in the cancer zone.

977
1:03:54 --> 1:03:59
And typically they hover between 0.5 and 0.7.

978
1:03:59 --> 1:04:00
Somewhere in here is cancer.

979
1:04:01 --> 1:04:07
Then you have this here, this vertical, this straight line up here, phi equal to one.

980
1:04:08 --> 1:04:15
There's these three places up here where, I already talked about that one.

981
1:04:15 --> 1:04:17
Here you are for tetraploid cells.

982
1:04:17 --> 1:04:27
There are actually examples where the egg, a fertilized egg that divides,

983
1:04:27 --> 1:04:29
has four copies of every chromosome.

984
1:04:29 --> 1:04:32
Remember, your normal cell has two copies of every chromosome.

985
1:04:32 --> 1:04:40
But rarely some eggs will have, the fertilized eggs will have four copies of every chromosome,

986
1:04:40 --> 1:04:42
which means they're balanced.

987
1:04:42 --> 1:04:43
They're not out of balance.

988
1:04:43 --> 1:04:44
They're still in balance.

989
1:04:44 --> 1:04:48
And that's what this line, the straight line shows you.

990
1:04:48 --> 1:04:49
That's for balanced chromosomes.

991
1:04:50 --> 1:04:52
You can see these are infants.

992
1:04:52 --> 1:04:53
They're born dead.

993
1:04:53 --> 1:04:58
I couldn't find any of these tetraploid babies.

994
1:04:58 --> 1:04:58
But look at it.

995
1:04:58 --> 1:05:01
You can recognize them as a human being.

996
1:05:01 --> 1:05:04
Their phenotypes are normal because the chromosomes are balanced.

997
1:05:04 --> 1:05:08
But the physiological effects of having so, so much protein

998
1:05:08 --> 1:05:12
in their cells that can't survive and they're born dead.

999
1:05:12 --> 1:05:19
But then you also have the rare occasions where the child is born with three copies

1000
1:05:19 --> 1:05:21
of every chromosome in the cell.

1001
1:05:22 --> 1:05:24
And many of these are born alive.

1002
1:05:24 --> 1:05:27
Most of them aren't, but many of them are born alive.

1003
1:05:27 --> 1:05:31
And they can survive weeks to months, but they always die.

1004
1:05:31 --> 1:05:36
And you can see this is a typical example of one of these poor things.

1005
1:05:37 --> 1:05:37
These poor things.

1006
1:05:38 --> 1:05:41
So this illustrates balance.

1007
1:05:42 --> 1:05:46
Normal, if you have two chromosomes, two copies of each chromosome,

1008
1:05:46 --> 1:05:49
you get a healthy human being.

1009
1:05:49 --> 1:05:51
You get three copies of every chromosome.

1010
1:05:51 --> 1:05:53
You get the poor little kid like here.

1011
1:05:53 --> 1:05:58
And then the one that we had before, these have four copies.

1012
1:05:58 --> 1:06:02
But if you have unbalanced chromosomes, you get cancer cells.

1013
1:06:03 --> 1:06:04
And no two are alike.

1014
1:06:06 --> 1:06:07
Okay.

1015
1:06:08 --> 1:06:08
Right.

1016
1:06:08 --> 1:06:11
And then I know I'm talking a long time.

1017
1:06:11 --> 1:06:14
I know y'all are getting tired of hearing me, but I'm getting close to the end now.

1018
1:06:16 --> 1:06:21
Also, the theory of chromosomal imbalance are able to actually calculate the stability.

1019
1:06:21 --> 1:06:24
But all this stuff we're able to predict, by the way.

1020
1:06:24 --> 1:06:25
We have all these publications.

1021
1:06:25 --> 1:06:31
We're able to predict and advance this stuff based on the chromosomal imbalance theory of cancer.

1022
1:06:31 --> 1:06:35
And we can compare our theoretical calculations with the real world data

1023
1:06:36 --> 1:06:37
that other people did.

1024
1:06:37 --> 1:06:38
So we didn't do it.

1025
1:06:38 --> 1:06:41
So we weren't biased in terms of experimental stuff.

1026
1:06:42 --> 1:06:46
But here was an equation that I came up with and published it, I guess, was 90.

1027
1:06:48 --> 1:06:52
I can't remember if this was 1999 or 2000.

1028
1:06:52 --> 1:06:53
Came up with this equation here.

1029
1:06:53 --> 1:06:56
Stability index based on chromosomal imbalance.

1030
1:06:57 --> 1:07:02
And then it shows that the least stable cells down here, very, very low stability index right here.

1031
1:07:02 --> 1:07:03
One is the most stable.

1032
1:07:03 --> 1:07:06
Zero, of course, would be the least stable.

1033
1:07:06 --> 1:07:08
So as you go down, it's less and less stable.

1034
1:07:09 --> 1:07:14
And the curve shows the least stable cells have a DNA index of about 1.5.

1035
1:07:16 --> 1:07:20
But cancer typically has a DNA index around 1.7.

1036
1:07:20 --> 1:07:22
Right in here, your cancer cells.

1037
1:07:22 --> 1:07:23
Like, they vary.

1038
1:07:23 --> 1:07:24
They vary right in here.

1039
1:07:27 --> 1:07:31
So they're a little bit more stable than the ones at 1.5.

1040
1:07:32 --> 1:07:35
So the ones that are 1 or 2, aneuploid cells are still pretty stable.

1041
1:07:36 --> 1:07:43
Now here is, this is a comparison of real world data that was published by, I forget who it was.

1042
1:07:43 --> 1:07:44
I think it was one of the Vogelstein.

1043
1:07:44 --> 1:07:50
This was Vogelstein's data on cell lines from cancer cells.

1044
1:07:50 --> 1:07:51
Colon cancer cell lines.

1045
1:07:51 --> 1:07:52
Looked at a lot of different ones.

1046
1:07:53 --> 1:08:00
And what I did was I plotted Vogelstein's fraction of cell,

1047
1:08:00 --> 1:08:03
the fraction of cells down here on the left.

1048
1:08:04 --> 1:08:06
That's how stable the cells are.

1049
1:08:07 --> 1:08:10
And on the horizontal axis is a DNA index.

1050
1:08:10 --> 1:08:17
And you can see that the cells that have, that are close to the DNA index of 1,

1051
1:08:17 --> 1:08:19
these are aneuploid cells, though.

1052
1:08:19 --> 1:08:24
They're actually more stable than the ones that have a DNA index of about 40.

1053
1:08:25 --> 1:08:28
With 40 chromosomes instead of the 46.

1054
1:08:28 --> 1:08:31
And then when you have twice the number of chromosomes,

1055
1:08:31 --> 1:08:33
just as the stability index function shows,

1056
1:08:33 --> 1:08:36
these aneuploid cell lines, they're a lot more stable.

1057
1:08:36 --> 1:08:43
The least stable cells are the ones down here with the DNA index exactly halfway in between.

1058
1:08:43 --> 1:08:48
Just as this theory up here predicted that the least stable would be right about here,

1059
1:08:48 --> 1:08:51
DNA index of about 1.5.

1060
1:08:52 --> 1:08:56
And then as you go either side of the most stable,

1061
1:08:56 --> 1:08:58
then the stability drops off rapidly.

1062
1:08:58 --> 1:09:03
These are all real cell lines right here, real cancer cell lines.

1063
1:09:03 --> 1:09:05
And they follow the predictions exactly.

1064
1:09:10 --> 1:09:14
Okay, time course of carcinogenesis.

1065
1:09:14 --> 1:09:15
This is John Karens.

1066
1:09:15 --> 1:09:17
He's a critic of the gene mutation theory.

1067
1:09:17 --> 1:09:22
Clearly, we cannot claim to know what turns a cell into a cancer cell

1068
1:09:22 --> 1:09:26
until we understand why the time course of carcinogenesis

1069
1:09:26 --> 1:09:32
is almost always so extraordinarily long, like decades for solid cancer, for example.

1070
1:09:32 --> 1:09:33
So true.

1071
1:09:35 --> 1:09:36
Oh, here's the rates.

1072
1:09:39 --> 1:09:41
This is the 2000 paper I published.

1073
1:09:41 --> 1:09:44
This is the Auto-Catalyzed Progression Maneuploidy.

1074
1:09:44 --> 1:09:46
Explains the time course of human cancer.

1075
1:09:47 --> 1:09:50
I generated this equation here that I'm showing you right now.

1076
1:09:50 --> 1:09:52
And I applied it to real world data.

1077
1:09:53 --> 1:09:55
And I have highlighted here phi in the red.

1078
1:09:55 --> 1:09:56
Phi is the fraction.

1079
1:09:56 --> 1:09:59
Remember, the fraction of the genome is the important thing.

1080
1:10:00 --> 1:10:05
The closer the fraction is to one or two, the more stable the cells are.

1081
1:10:06 --> 1:10:11
The more further away you get, like we said, if you're halfway in between,

1082
1:10:11 --> 1:10:12
it's the most unstable.

1083
1:10:12 --> 1:10:17
But cancer cells tend to be around about 70% of the genome.

1084
1:10:17 --> 1:10:20
All right, so you can, I apply this to the genome.

1085
1:10:20 --> 1:10:28
I applied this data, this equation to real world data from Amortazh and Dole,

1086
1:10:28 --> 1:10:30
goes back to the 1950s.

1087
1:10:30 --> 1:10:33
And I did it to every one of the head, I forget how many.

1088
1:10:33 --> 1:10:38
Laura, they must have 20 or 30 different cancers that they plotted.

1089
1:10:39 --> 1:10:42
And they plotted the data.

1090
1:10:42 --> 1:10:44
And I just here just applied it to all of them.

1091
1:10:44 --> 1:10:47
But these are just representative examples.

1092
1:10:48 --> 1:10:51
Okay, so these are deaths per million.

1093
1:10:52 --> 1:10:56
That's the y-axis or the horizontal axis here, the deaths per million.

1094
1:10:57 --> 1:11:02
And the horizontal axis are age, it's in years.

1095
1:11:02 --> 1:11:07
All right, basically, what is the prospects if you have lung cancer?

1096
1:11:07 --> 1:11:12
You know, when do you expect to see deaths?

1097
1:11:12 --> 1:11:17
So like lung cancer in men, these circles, these little circles here,

1098
1:11:17 --> 1:11:19
are the real data from Amortazh and Dole.

1099
1:11:20 --> 1:11:26
The 7G mutation theory of cancer, that's the dashed line right here.

1100
1:11:26 --> 1:11:27
That one goes up that way.

1101
1:11:28 --> 1:11:32
This equation that I had back here, this is the solid line.

1102
1:11:32 --> 1:11:37
And you can see it fits the observational data of Amortazh and Dole.

1103
1:11:37 --> 1:11:40
It fits it for lung cancer in men.

1104
1:11:40 --> 1:11:42
It fits it for lung cancer in women.

1105
1:11:42 --> 1:11:43
It fits it for breast cancer.

1106
1:11:44 --> 1:11:47
It fits it for cervical cancer in women.

1107
1:11:47 --> 1:11:50
It fits it for prostate cancer in men.

1108
1:11:50 --> 1:11:52
And it fits it in colon cancer in men.

1109
1:11:52 --> 1:11:57
But notice that both the 7G mutation curve and the aneuploidy curve,

1110
1:11:58 --> 1:12:03
both fit the data, the same data for the colon cancer in men.

1111
1:12:03 --> 1:12:09
The reason is that most colon cancer in men usually survive it.

1112
1:12:09 --> 1:12:12
You know, something else kills them later in life.

1113
1:12:13 --> 1:12:17
And if they survive it, that's why it doesn't show this curve up here.

1114
1:12:17 --> 1:12:18
But I just wanted to show it.

1115
1:12:19 --> 1:12:20
Okay.

1116
1:12:20 --> 1:12:22
Almost done, everybody.

1117
1:12:22 --> 1:12:26
Aneuploidy is diagnostic of all stages of cancer.

1118
1:12:27 --> 1:12:30
This was a study, this was Bolton and colleagues.

1119
1:12:30 --> 1:12:36
They understood that aneuploidy was a very, very good thing to use to diagnose cancer.

1120
1:12:38 --> 1:12:40
This is all the way back in 1998.

1121
1:12:40 --> 1:12:44
And they were looking for a way of using chromosomes.

1122
1:12:44 --> 1:12:46
You can see on the right here, the lesion.

1123
1:12:46 --> 1:12:48
This is the old nomenclature.

1124
1:12:49 --> 1:12:53
When a pathologist, let's say, looks at a cervical cancer, they look at the normal cells.

1125
1:12:54 --> 1:13:01
Then they categorize the abnormal ones by CIN1, and increasingly worse, CIN2, CIN3,

1126
1:13:01 --> 1:13:03
invasive cancer.

1127
1:13:03 --> 1:13:06
Stands for cervical interepithelial neoplasia.

1128
1:13:07 --> 1:13:15
So you can see here that the cancers, the severity increases as you go down this list right here.

1129
1:13:16 --> 1:13:22
And that also increases with, here in these little, I put these little,

1130
1:13:22 --> 1:13:25
they used eight chromosomes that these guys looked at.

1131
1:13:26 --> 1:13:32
And then they looked at these four categories, normal CIN1, CIN2, CIN3, and invasive cancer,

1132
1:13:32 --> 1:13:34
for each one of these chromosomes.

1133
1:13:35 --> 1:13:39
So you have left to right here, this list going top to bottom.

1134
1:13:39 --> 1:13:45
And you can see that they're all, at some point, every one of the chromosomes is aneuploid,

1135
1:13:45 --> 1:13:46
or abnormal in these things.

1136
1:13:48 --> 1:13:54
Their hope was that they would get a different distribution in these chromosomes

1137
1:13:55 --> 1:13:59
for some chromosomes relative to others.

1138
1:13:59 --> 1:14:05
So they could use that distribution to characterize the differences between CIN1, CIN2,

1139
1:14:05 --> 1:14:06
CIN3, and invasive cancer.

1140
1:14:06 --> 1:14:10
All they can say is, up here, if you look at these chromosomes,

1141
1:14:10 --> 1:14:13
we can't tell whether you've got any of these things or not.

1142
1:14:14 --> 1:14:16
So they were a little disappointed.

1143
1:14:17 --> 1:14:23
It turns out that their idea was right, if you looked at the spread of the chromosomes.

1144
1:14:23 --> 1:14:25
But I don't want to get into that right now.

1145
1:14:25 --> 1:14:27
So they're a little disappointed.

1146
1:14:27 --> 1:14:32
But the main thing to notice here is, here's all the normal chromosomes down at the bottom.

1147
1:14:32 --> 1:14:33
These are cells, normal cells.

1148
1:14:33 --> 1:14:41
Normal cells had very reliable chromosomal counts of chromosomes.

1149
1:14:41 --> 1:14:47
And these little bars that are separating it just shows how well they varied from cell to cell.

1150
1:14:47 --> 1:14:50
Of course, up here are all of those different things.

1151
1:14:50 --> 1:14:54
The wide range, the chromosomal instability, they're all up here.

1152
1:14:54 --> 1:14:56
But there's this quantum leap.

1153
1:14:56 --> 1:15:01
There's this quantum leap from normal cells to all of these abnormal cells.

1154
1:15:01 --> 1:15:07
And the primary reason for that is that normal cells with those low level of aneuploidy,

1155
1:15:07 --> 1:15:12
like I say, if you have just a few chromosomes,

1156
1:15:13 --> 1:15:19
they're not readily distinguishable by eyeball with the PEP smear.

1157
1:15:19 --> 1:15:24
So everything below CIN1, it can still be aneuploid precursors to cancer.

1158
1:15:25 --> 1:15:28
But the pathologists can't detect it by eye with those stains.

1159
1:15:28 --> 1:15:31
It's just that the cells are just too normal.

1160
1:15:32 --> 1:15:34
But you can see all of them.

1161
1:15:35 --> 1:15:38
That explains why these things are all up here.

1162
1:15:38 --> 1:15:45
They had to have massive, they had to have already undergone that chromosomal doubling step.

1163
1:15:45 --> 1:15:50
They had to have already gone past that in order to get the level of chromosomes

1164
1:15:50 --> 1:15:53
that pathologists can easily detect.

1165
1:15:54 --> 1:15:57
Okay, so where, I'm almost done here.

1166
1:15:57 --> 1:15:58
I think that's it.

1167
1:15:58 --> 1:16:00
Where are the diploid cancers?

1168
1:16:00 --> 1:16:03
It goes all the way back to the little theater of Boveri in 1914.

1169
1:16:04 --> 1:16:08
This is what he said in his book concerning the origin of malignant tumors.

1170
1:16:09 --> 1:16:16
If it should turn out that an exactly diploid chromosome number was regularly found,

1171
1:16:16 --> 1:16:20
then our hypothesis, chromosomal imbalance hypothesis, must be false.

1172
1:16:20 --> 1:16:22
He's absolutely right.

1173
1:16:22 --> 1:16:26
But to this day, nobody has come up with diploid cancer.

1174
1:16:26 --> 1:16:27
The end.

1175
1:16:27 --> 1:16:28
Okay, everybody.

1176
1:16:30 --> 1:16:32
I know you're probably sick of hearing me talk, but...

1177
1:16:33 --> 1:16:36
No, David, it was very good.

1178
1:16:36 --> 1:16:38
So stop your share now.

1179
1:16:38 --> 1:16:40
Okay, stop the share.

1180
1:16:40 --> 1:16:41
I stopped share.

1181
1:16:42 --> 1:16:43
Okay, I stopped here.

1182
1:16:43 --> 1:16:43
Oh, good.

1183
1:16:43 --> 1:16:45
I can see you guys now.

1184
1:16:45 --> 1:16:45
Yes.

1185
1:16:45 --> 1:16:46
Anybody left?

1186
1:16:48 --> 1:16:50
Well, we're so happy we got left.

1187
1:16:52 --> 1:16:54
It was very good.

1188
1:16:54 --> 1:16:54
It was very good.

1189
1:16:54 --> 1:16:57
And the depth of your work is extraordinary.

1190
1:16:58 --> 1:17:05
And Stephen will go for 15 minutes with the first series of questions.

1191
1:17:07 --> 1:17:13
And, Dave, the question that I have for you while Stephen's gathering his thoughts is

1192
1:17:13 --> 1:17:19
you knew that the HIV virus, if it exists, didn't cause AIDS.

1193
1:17:19 --> 1:17:20
Yes.

1194
1:17:20 --> 1:17:22
As did Peter Duesberg.

1195
1:17:22 --> 1:17:29
And here you are seeing the same COVID scam going on.

1196
1:17:29 --> 1:17:36
And then, you know, Bobby Kennedy writes about AZT and all of that information that's available.

1197
1:17:36 --> 1:17:41
And yet the mass that most people go, oh, yes, HIV causes AIDS.

1198
1:17:42 --> 1:17:46
So how do you maintain your passion for finding the truth?

1199
1:17:46 --> 1:17:53
Because, you know, it's clear that you and Peter were right, as were a minority of others,

1200
1:17:53 --> 1:17:56
but it didn't change much, did it?

1201
1:17:56 --> 1:17:58
People weren't held to account for the fraud.

1202
1:17:58 --> 1:18:00
No, no, no.

1203
1:18:00 --> 1:18:05
And as you saw in my little bio, I've been fighting this for 40 years, basically.

1204
1:18:05 --> 1:18:06
Yeah.

1205
1:18:07 --> 1:18:08
And I've never stopped.

1206
1:18:09 --> 1:18:13
The thing, one reason why I really wanted to talk today and talk about cancer

1207
1:18:14 --> 1:18:17
is because of what happened with AIDS and the HIV.

1208
1:18:18 --> 1:18:24
There are a lot of us, a lot of scientists knew, even the mainstreamers that kept working on it

1209
1:18:24 --> 1:18:27
with HIV and everything, they knew the truth.

1210
1:18:27 --> 1:18:29
They knew HIV did not cause AIDS.

1211
1:18:29 --> 1:18:31
The older people certainly knew it.

1212
1:18:31 --> 1:18:35
That's why they were so mean to Peter.

1213
1:18:36 --> 1:18:39
Those people, you know, if they thought we were just wrong,

1214
1:18:40 --> 1:18:43
they would have ignored us, you know?

1215
1:18:43 --> 1:18:50
But the people that knew that we were right, which were a lot of people,

1216
1:18:50 --> 1:18:51
knew that we were right.

1217
1:18:51 --> 1:18:52
They couldn't have it.

1218
1:18:53 --> 1:18:57
And I've talked about this in other talks about AIDS.

1219
1:18:58 --> 1:19:00
And so they had to control the dogma.

1220
1:19:01 --> 1:19:06
The HIV dogma is what we were fighting.

1221
1:19:06 --> 1:19:09
Now Peter and I have been fighting the gene mutation dogma.

1222
1:19:09 --> 1:19:14
There's so many dogmas out there, so many dogmas.

1223
1:19:14 --> 1:19:16
Every profession has their own dogma.

1224
1:19:17 --> 1:19:21
And the people that if you go against it, you get punished.

1225
1:19:21 --> 1:19:24
You get fired or whatever, or you can't get grant support or anything.

1226
1:19:25 --> 1:19:31
And so one of the really remarkable things about this crazy thing that's

1227
1:19:31 --> 1:19:37
passed almost five years now is that we are now getting together as a group of people,

1228
1:19:37 --> 1:19:39
because we're so curious, we want to know what's going on.

1229
1:19:39 --> 1:19:42
We want to hear other people's story, you know?

1230
1:19:44 --> 1:19:50
And everybody has stories that other people need to know, you see?

1231
1:19:50 --> 1:19:53
And I have a story about AIDS and I have a story about cancer.

1232
1:19:53 --> 1:19:56
And I want to share that where the sharing is good.

1233
1:19:56 --> 1:20:02
Well, people are hungry to find this stuff and there's avenues for them to do it.

1234
1:20:02 --> 1:20:07
That's why so many of us go to your Zoom meetings and other Zoom meetings or whatever.

1235
1:20:07 --> 1:20:11
It's because we're so hungry for other people's stories, you know?

1236
1:20:12 --> 1:20:15
That's the way we solve problems.

1237
1:20:15 --> 1:20:16
That's the way human beings solve problems.

1238
1:20:18 --> 1:20:21
They don't appreciate it, but we are beginning to understand that.

1239
1:20:21 --> 1:20:29
I think that it's not a case of the science or logical thought.

1240
1:20:29 --> 1:20:32
It's a case of human beings getting together, sharing their stories,

1241
1:20:32 --> 1:20:37
and making sense of what has happened in the last five years in this case.

1242
1:20:37 --> 1:20:38
That's how I see it.

1243
1:20:38 --> 1:20:39
But...

1244
1:20:39 --> 1:20:43
Well, Stephen, the next 15 minutes are yours.

1245
1:20:43 --> 1:20:46
I go for it, Stephen, but David, we honour your work.

1246
1:20:46 --> 1:20:50
It's an extraordinary volume of work and I love your passion.

1247
1:20:50 --> 1:20:51
Stephen, over to you.

1248
1:20:52 --> 1:20:59
So, David, you know you were talking about the dogma of the HIV virus was the cause of AIDS.

1249
1:20:59 --> 1:21:03
And as I understand it, AIDS is a collection of symptoms and diseases.

1250
1:21:04 --> 1:21:07
It's not a disease as I can understand it.

1251
1:21:07 --> 1:21:17
But anyway, do you think that the defence of the dogma over AIDS was absolutely crucial

1252
1:21:18 --> 1:21:21
to the successful defence of that?

1253
1:21:21 --> 1:21:29
Was it absolutely crucial to the rise of virology and the possibility of 2020 happening?

1254
1:21:30 --> 1:21:31
Was that...

1255
1:21:32 --> 1:21:36
Do you think that they knew in the time of AIDS and HIV virus?

1256
1:21:37 --> 1:21:43
Do you think that they knew what they planned in the future, i.e. pandemics, you know?

1257
1:21:43 --> 1:21:49
Endless deadly pandemics which they could terrorise populations with so that

1258
1:21:51 --> 1:21:58
human beings would capitulate to world government, for example, that kind of thinking?

1259
1:21:59 --> 1:22:00
It was intentional.

1260
1:22:01 --> 1:22:02
I've talked about this.

1261
1:22:02 --> 1:22:04
I've talked about it was intentional.

1262
1:22:04 --> 1:22:09
Well, April 23rd, 1984, it was a press conference.

1263
1:22:09 --> 1:22:12
Margaret Heckler, Secretary of Health and Human Services,

1264
1:22:12 --> 1:22:13
they brought out...

1265
1:22:14 --> 1:22:16
I had a press conference out there, brought out Robert Gallo.

1266
1:22:17 --> 1:22:23
And it became government dogma that day that AIDS is contagious caused by Robert Gallo's virus.

1267
1:22:23 --> 1:22:25
Ultimately, it was called HIV.

1268
1:22:25 --> 1:22:31
It started in Africa, sexually transmitted, and is invariably fatal.

1269
1:22:32 --> 1:22:37
That was government set dogma to that day, on that day, April 23rd, 1984,

1270
1:22:37 --> 1:22:39
which continues to this day.

1271
1:22:39 --> 1:22:40
That was intentional.

1272
1:22:40 --> 1:22:52
Anthony Fauci was made director of the National Institute of Infectious Disease.

1273
1:22:52 --> 1:22:56
Infectious disease, I can't even think of it now.

1274
1:22:57 --> 1:22:59
But viral diseases, okay?

1275
1:23:01 --> 1:23:06
For the purpose of defending that dogma and pushing it,

1276
1:23:07 --> 1:23:09
National Institutes of...

1277
1:23:10 --> 1:23:11
Damn, I can't think of it now.

1278
1:23:11 --> 1:23:12
Also, this is gone.

1279
1:23:13 --> 1:23:20
Yeah, and he was brought in November of 1984 to push that program, that dogma.

1280
1:23:20 --> 1:23:21
It was intentional.

1281
1:23:22 --> 1:23:25
Allergy, infection, everything.

1282
1:23:25 --> 1:23:30
Every one of his viral pandemics since then, the first SARS, the MERS, the Ebola,

1283
1:23:30 --> 1:23:34
all of those were all of the same thing.

1284
1:23:34 --> 1:23:36
Prepare the way to do this.

1285
1:23:36 --> 1:23:42
And also, benefit the pharmaceutical companies and things because they make drugs,

1286
1:23:42 --> 1:23:45
I mean, make chemicals, sell them to people, whatever.

1287
1:23:45 --> 1:23:52
But it was basically part of a ploy to control the whole system.

1288
1:23:53 --> 1:23:54
Mm-hmm.

1289
1:23:54 --> 1:23:55
Yeah.

1290
1:23:55 --> 1:23:58
You look back at the history of it, it's clear.

1291
1:23:58 --> 1:24:01
So David, it was intentional, yes, but was it...

1292
1:24:01 --> 1:24:09
Do you think in the 80s, they were already planning a world where virology kind of took over

1293
1:24:09 --> 1:24:17
from immunology, if you like, where the immunologists could appreciate that human beings

1294
1:24:17 --> 1:24:20
and for that matter, other animals had incredible immune systems.

1295
1:24:20 --> 1:24:27
And it was highly unlikely that mere men, i.e. man, you know, the capital M,

1296
1:24:29 --> 1:24:33
were clever enough to improve on God's immune system, if you understand.

1297
1:24:35 --> 1:24:40
So do you think that they planned to control people in the future with the threat of deadly viral

1298
1:24:40 --> 1:24:41
pandemics?

1299
1:24:43 --> 1:24:47
Do you think they planned it then or do you think that came about later?

1300
1:24:47 --> 1:24:55
And it was intentional over AIDS, the deception, but do you think they knew in the 80s that they

1301
1:24:55 --> 1:25:02
were going to push virology to achieve, as a Trojan horse, for totalitarianism?

1302
1:25:03 --> 1:25:06
Well, I knew it was intentional to push it.

1303
1:25:07 --> 1:25:07
Absolutely.

1304
1:25:08 --> 1:25:16
Now, I don't know if it was designed to be the weapon of 2020, 2021.

1305
1:25:16 --> 1:25:17
I don't know.

1306
1:25:17 --> 1:25:23
But it definitely was pushed because all you got to do is look at everything they did during the

1307
1:25:23 --> 1:25:30
almost four decades of Anthony Fauci at the Institute of Allergy and Infectious Disease.

1308
1:25:30 --> 1:25:34
That's what he was the director of.

1309
1:25:34 --> 1:25:39
He had more money, more power than even the Secretary of Health and Human Services.

1310
1:25:39 --> 1:25:39
He did.

1311
1:25:40 --> 1:25:43
That was intentional to control that place.

1312
1:25:43 --> 1:25:45
What the goal was, you're asking the goal.

1313
1:25:45 --> 1:25:53
I don't know what the goal was other than to have massive control over this health and human

1314
1:25:53 --> 1:25:58
services, which the pharmaceutical industry was very, very big at this time.

1315
1:25:59 --> 1:26:05
And 70% of the FDA's money comes from the pharmaceutical industry.

1316
1:26:05 --> 1:26:12
And I'm sure they made hundreds of billions of dollars during this period that we're talking

1317
1:26:12 --> 1:26:12
about.

1318
1:26:13 --> 1:26:18
Incurable disease is what money is made of, like cancer and things like that.

1319
1:26:23 --> 1:26:23
I'm sorry.

1320
1:26:23 --> 1:26:24
Go ahead.

1321
1:26:24 --> 1:26:27
Did Fauci take over from Gallo, Robert Gallo?

1322
1:26:27 --> 1:26:31
No, Gallo was just at the National Cancer Institute.

1323
1:26:32 --> 1:26:35
It's not at the Institute of Allergy and Infectious Disease.

1324
1:26:37 --> 1:26:41
So he wasn't in charge of anything really big.

1325
1:26:41 --> 1:26:46
But he was a cancer virologist, Gallo was.

1326
1:26:51 --> 1:26:54
He was not the director of it or anything like that.

1327
1:26:54 --> 1:27:02
And he was originally found guilty of scientific misconduct and fired.

1328
1:27:02 --> 1:27:06
Started another facility later, but you never heard of it.

1329
1:27:06 --> 1:27:06
He just sort of disappeared.

1330
1:27:06 --> 1:27:07
So when was that?

1331
1:27:08 --> 1:27:09
Oh, Lord.

1332
1:27:10 --> 1:27:10
Oh, Lord.

1333
1:27:10 --> 1:27:12
That was in the 80s.

1334
1:27:12 --> 1:27:14
He was fired in the 80s.

1335
1:27:14 --> 1:27:18
Congress had some hearings on Gallo.

1336
1:27:18 --> 1:27:22
They found him guilty of lying scientific misconduct.

1337
1:27:23 --> 1:27:26
And of course, the government, it was the Reagan administration at the time,

1338
1:27:26 --> 1:27:31
they could not afford to have that embarrassment to come out.

1339
1:27:31 --> 1:27:37
The guy behind their policy of contagious AIDS and everything found guilty.

1340
1:27:37 --> 1:27:42
What they did was they dismantled that whole thing and they were going to require him to be

1341
1:27:43 --> 1:27:44
retried, so to speak.

1342
1:27:45 --> 1:27:49
And they realized the people that did it the first time, they found him guilty,

1343
1:27:49 --> 1:27:53
realized that the government, the powers that be, were not going to let him be guilty.

1344
1:27:54 --> 1:27:56
But they got rid of him.

1345
1:27:56 --> 1:27:58
They just had to get rid of him.

1346
1:27:58 --> 1:27:58
And that's what they did.

1347
1:27:59 --> 1:28:05
And subsequently, so Luke Montagnier won the Nobel Prize for Medicine in 2008

1348
1:28:05 --> 1:28:08
for the discovery of the AIDS virus.

1349
1:28:08 --> 1:28:09
Isn't that right?

1350
1:28:09 --> 1:28:10
That's right.

1351
1:28:10 --> 1:28:13
Not for the discovery that it caused for the virus.

1352
1:28:13 --> 1:28:13
Yes.

1353
1:28:13 --> 1:28:15
Sorry, for the HIV virus.

1354
1:28:15 --> 1:28:15
Sorry.

1355
1:28:15 --> 1:28:23
By the way, and Luke Montagnier later on acknowledged that that virus did not cause AIDS.

1356
1:28:24 --> 1:28:25
Exactly.

1357
1:28:25 --> 1:28:29
But that was pretty much, it was quite a lot later, wasn't it?

1358
1:28:29 --> 1:28:32
It was after 2020.

1359
1:28:32 --> 1:28:39
No, he actually, it was actually, it was 2000.

1360
1:28:39 --> 1:28:40
It was 2000.

1361
1:28:40 --> 1:28:42
I think it was 2000.

1362
1:28:42 --> 1:28:49
They had the AIDS conference, the big AIDS conference in San Francisco.

1363
1:28:49 --> 1:28:50
I was living there at the time.

1364
1:28:50 --> 1:28:54
And right downtown San Francisco.

1365
1:28:54 --> 1:29:00
Fauci, that was the first time he came out in opposition to HIV being the cause of AIDS.

1366
1:29:00 --> 1:29:07
And he introduced an alternative agent that was not a virus.

1367
1:29:07 --> 1:29:08
I forget what it was.

1368
1:29:10 --> 1:29:11
Just proposing it.

1369
1:29:12 --> 1:29:20
And then after, God, it was in the early 2000s when he and others and a bunch of Europeans

1370
1:29:20 --> 1:29:21
found HIV free AIDS cases.

1371
1:29:22 --> 1:29:26
And so it started to be a stampede away from HIV.

1372
1:29:27 --> 1:29:32
Anthony Fauci got on, I think it was Air Force Two, went all the way to wherever it was,

1373
1:29:32 --> 1:29:35
in England, I think it was, or France, or wherever it was.

1374
1:29:36 --> 1:29:41
And he shut that whole thing down about HIV free AIDS cases.

1375
1:29:41 --> 1:29:47
That's when they came up with HIV 2 or something like that, another retrovirus that caused these

1376
1:29:47 --> 1:29:51
other HIV 1 AIDS cases.

1377
1:29:52 --> 1:29:54
They had to keep the retrovirus thing going.

1378
1:29:55 --> 1:29:58
So they could not have a virus free AIDS cases.

1379
1:29:59 --> 1:30:04
And that's when, like I say, Anthony Fauci got on Air Force Two and flew out there very,

1380
1:30:04 --> 1:30:05
very quickly to shut that down.

1381
1:30:05 --> 1:30:06
And he did.

1382
1:30:08 --> 1:30:08
Yeah.

1383
1:30:10 --> 1:30:13
So who won the Nobel Prize in 2008 then?

1384
1:30:13 --> 1:30:16
Was that just Montagnier or was it Gallo Two?

1385
1:30:17 --> 1:30:17
Gallo No.

1386
1:30:18 --> 1:30:19
Gallo didn't get it.

1387
1:30:19 --> 1:30:20
No, exactly.

1388
1:30:20 --> 1:30:22
He wasn't happy about that, was he?

1389
1:30:22 --> 1:30:25
He thought he was going to get it instead of Montagnier.

1390
1:30:26 --> 1:30:26
Yeah.

1391
1:30:27 --> 1:30:28
So Montagnier, when he accepted...

1392
1:30:28 --> 1:30:31
He might have chained it with somebody, I don't know, but it wasn't with Gallo.

1393
1:30:33 --> 1:30:36
So Montagnier was awarded the Nobel Prize on his own for the...

1394
1:30:37 --> 1:30:38
I don't know.

1395
1:30:38 --> 1:30:41
I don't know if it was on his own or not, but it was not Gallo.

1396
1:30:41 --> 1:30:43
I think there was someone else, but I can't remember who it was.

1397
1:30:43 --> 1:30:49
But anyway, but the point was in 2008, Montagnier was probably aware

1398
1:30:50 --> 1:30:55
that the prize that he was being awarded was for something which he didn't believe was true

1399
1:30:55 --> 1:30:56
at that time.

1400
1:30:56 --> 1:31:02
He didn't get the prize for discovering the cause of AIDS.

1401
1:31:02 --> 1:31:07
He got the prize for discovery of the virus.

1402
1:31:08 --> 1:31:08
Absolutely.

1403
1:31:08 --> 1:31:09
That's exactly...

1404
1:31:09 --> 1:31:10
Yes, exactly.

1405
1:31:10 --> 1:31:13
Not given the Nobel Prize for discovering the cause of AIDS.

1406
1:31:13 --> 1:31:14
No.

1407
1:31:16 --> 1:31:16
Yeah.

1408
1:31:16 --> 1:31:17
I mean, that was weird.

1409
1:31:17 --> 1:31:18
It was very, very weird.

1410
1:31:18 --> 1:31:23
It was one of these politically engineered Nobel Prizes.

1411
1:31:24 --> 1:31:25
It's not the only one.

1412
1:31:26 --> 1:31:33
Maybe it was necessary to give Montagnier that to keep the false narrative going.

1413
1:31:33 --> 1:31:34
Yes.

1414
1:31:34 --> 1:31:35
Yes.

1415
1:31:36 --> 1:31:39
Because Montagnier was the biggest threat at the time, maybe?

1416
1:31:40 --> 1:31:43
Nobel Prize is a very powerful tool for propaganda.

1417
1:31:44 --> 1:31:45
Sure.

1418
1:31:45 --> 1:31:55
And Keri Mullis won the Nobel Prize for chemistry, which is your subject, in 1993 for the invention,

1419
1:31:55 --> 1:31:57
if you like, of the PCR technique.

1420
1:31:57 --> 1:31:57
PCR.

1421
1:31:57 --> 1:31:58
Is that right?

1422
1:31:58 --> 1:31:59
PCR, yeah.

1423
1:31:59 --> 1:32:01
Ten years earlier, yeah.

1424
1:32:01 --> 1:32:03
So all these names are all linked.

1425
1:32:03 --> 1:32:10
And it seems to me that Keri Mullis turned up in Paris and asked Montagnier when he was

1426
1:32:11 --> 1:32:12
surrounded by his colleagues.

1427
1:32:13 --> 1:32:14
And he said...

1428
1:32:15 --> 1:32:17
So he'd come up with a statement.

1429
1:32:17 --> 1:32:20
The HIV virus is the probable cause of AIDS.

1430
1:32:20 --> 1:32:26
So he asked Montagnier, because he couldn't find any justification for this statement,

1431
1:32:27 --> 1:32:31
and he asked Montagnier whether he could provide some references for him.

1432
1:32:31 --> 1:32:33
And Montagnier suggested a couple.

1433
1:32:33 --> 1:32:36
So I think this came directly from Keri Mullis's mouth.

1434
1:32:37 --> 1:32:41
And Keri Mullis said, no, that's not good enough.

1435
1:32:41 --> 1:32:43
And two suggestions.

1436
1:32:43 --> 1:32:48
And then Montagnier gave up and walked away, apparently, and left his colleagues, too.

1437
1:32:48 --> 1:32:50
And they were a little bit surprised.

1438
1:32:50 --> 1:32:52
So Keri Mullis said.

1439
1:32:52 --> 1:32:58
But Keri Mullis ended up, because he had a Nobel Prize, he was able to defend Peter Duisburg.

1440
1:32:58 --> 1:33:00
And I wonder whether you could tell us something about that.

1441
1:33:02 --> 1:33:03
To some extent.

1442
1:33:03 --> 1:33:08
After Keri talked with Montagnier, he was furious.

1443
1:33:09 --> 1:33:13
He was really, really furious, because he realized, man, this is a scam.

1444
1:33:14 --> 1:33:15
Total scam.

1445
1:33:15 --> 1:33:17
He sort of knew...

1446
1:33:17 --> 1:33:19
You don't think he knew beforehand or suspected it?

1447
1:33:19 --> 1:33:21
He suspected it, absolutely.

1448
1:33:21 --> 1:33:22
Oh, right.

1449
1:33:22 --> 1:33:22
Oh, yeah.

1450
1:33:23 --> 1:33:27
But he didn't get furious until he talked to Montagnier himself and asked him,

1451
1:33:27 --> 1:33:30
if Montagnier didn't know, who the hell does?

1452
1:33:31 --> 1:33:31
Yes.

1453
1:33:31 --> 1:33:38
So that was a very important story from Keri Mullis's point of view and also from human beings point of view.

1454
1:33:38 --> 1:33:47
But I think we ought to get that story sorted out in our minds so that we can...

1455
1:33:47 --> 1:33:53
Or you, maybe David, so you can explain to the public what, you know, in simple terms,

1456
1:33:54 --> 1:33:56
the connections in that story.

1457
1:33:57 --> 1:34:05
Because Keri Mullis ended up dying, in inverted commas, in August 2019 of pneumonia, as I remember him.

1458
1:34:06 --> 1:34:09
But of course, if you think about it, there's no way...

1459
1:34:09 --> 1:34:10
Because he was saying things like...

1460
1:34:12 --> 1:34:15
He hated Fauci, Anthony Fauci.

1461
1:34:15 --> 1:34:19
So he was saying things like, Keri...

1462
1:34:19 --> 1:34:21
I've actually heard it with my own ears.

1463
1:34:21 --> 1:34:25
Him saying that there's a video on the internet,

1464
1:34:25 --> 1:34:32
he's talking about Fauci and he says, he, Fauci, doesn't know anything about anything.

1465
1:34:32 --> 1:34:34
That's right. It's true.

1466
1:34:34 --> 1:34:37
And then he goes on to say, and I would say that to his face,

1467
1:34:37 --> 1:34:44
so this guy, Keri Mullis, had to be dead at the beginning of 2020.

1468
1:34:44 --> 1:34:50
He couldn't be around, they couldn't have done what they did at the beginning of 2020

1469
1:34:50 --> 1:34:53
with Keri Mullis around, in my opinion.

1470
1:34:53 --> 1:34:54
Or Montagnier.

1471
1:34:54 --> 1:34:56
It's very, very suspicious.

1472
1:34:57 --> 1:35:01
It's circumstantial at this point, but it did not escape my notice.

1473
1:35:02 --> 1:35:08
Keri Mullis died, and also, Luke Montagnier and Peter Duesberg had a stroke.

1474
1:35:09 --> 1:35:17
Those are the three most powerful, outspoken, credentialed opponents and critics

1475
1:35:18 --> 1:35:20
of Anthony Fauci in the world.

1476
1:35:20 --> 1:35:21
Those three people.

1477
1:35:22 --> 1:35:23
All right?

1478
1:35:23 --> 1:35:26
Two of them died, one of them had a stroke.

1479
1:35:26 --> 1:35:28
I mean, how fortuitous could that be?

1480
1:35:28 --> 1:35:35
Well, one of them died before 2020, but Montagnier died in February 22, I think.

1481
1:35:35 --> 1:35:36
Look at it this way.

1482
1:35:37 --> 1:35:37
Look at it this way.

1483
1:35:37 --> 1:35:39
They knew it was coming as a planned thing anyway.

1484
1:35:43 --> 1:35:46
They had the injections already in the vials before 2020.

1485
1:35:49 --> 1:35:49
Sure.

1486
1:35:50 --> 1:35:51
So is it true?

1487
1:35:52 --> 1:35:57
Because it came before, just because of 2019, that's beside the point.

1488
1:35:57 --> 1:36:00
It's all in the same time, you know?

1489
1:36:01 --> 1:36:02
Just too close.

1490
1:36:02 --> 1:36:03
Too close.

1491
1:36:03 --> 1:36:09
So David, is it true that Montagnier, one week before he died, he was in Milan?

1492
1:36:10 --> 1:36:13
So he was 94, was he, or something like that?

1493
1:36:13 --> 1:36:14
93?

1494
1:36:14 --> 1:36:15
He was an older fellow.

1495
1:36:15 --> 1:36:17
I mean, Keri was the youngest.

1496
1:36:18 --> 1:36:20
You know, Keri was old.

1497
1:36:21 --> 1:36:22
Peter was old.

1498
1:36:23 --> 1:36:26
I'm getting there myself.

1499
1:36:28 --> 1:36:36
Yeah, so Montagnier, apparently in the speech in Rome, he said, and I'm pretty sure I've got a

1500
1:36:36 --> 1:36:41
transcript somewhere, but whether I can find it or not is another matter, but he said that

1501
1:36:41 --> 1:36:44
the unvaccinated would save humanity.

1502
1:36:44 --> 1:36:45
Is that true?

1503
1:36:45 --> 1:36:46
And a week later he was dead.

1504
1:36:47 --> 1:36:48
Dead, I don't know.

1505
1:36:50 --> 1:36:50
Right.

1506
1:36:51 --> 1:36:55
So there ends the interrogation, David.

1507
1:36:57 --> 1:37:00
I could go on, but I'll bore people to death.

1508
1:37:00 --> 1:37:02
So Charles, are you there?

1509
1:37:04 --> 1:37:06
Thank you for answering those questions.

1510
1:37:08 --> 1:37:09
So these are really important names.

1511
1:37:10 --> 1:37:19
Luke Montagnier, Peter Duisburg, Keri Mullis, and they are really, really important.

1512
1:37:19 --> 1:37:23
There's a great story there that needs to be told, and it hasn't been told properly,

1513
1:37:23 --> 1:37:24
I don't think, so we should do that.

1514
1:37:24 --> 1:37:25
Get Celia Farber.

1515
1:37:25 --> 1:37:27
Invite Celia Farber.

1516
1:37:27 --> 1:37:28
You may have had her on before.

1517
1:37:28 --> 1:37:29
I think you have.

1518
1:37:29 --> 1:37:31
We have had her on, yeah.

1519
1:37:31 --> 1:37:32
She knows all these people.

1520
1:37:32 --> 1:37:35
She's very, you know, very, very tight.

1521
1:37:35 --> 1:37:37
She can answer a lot of your questions on the internet.

1522
1:37:38 --> 1:37:40
She can answer a lot of your questions that I can't.

1523
1:37:41 --> 1:37:47
I see you're not as au fait as her, you mean, on the stories?

1524
1:37:47 --> 1:37:50
I know about it, but I didn't dig into it like she did, you know?

1525
1:37:50 --> 1:37:51
Ah, yeah.

1526
1:37:51 --> 1:38:00
A journalist has a broader spectrum of views and questions than I do.

1527
1:38:01 --> 1:38:02
Yes, sure.

1528
1:38:02 --> 1:38:05
They can get the nuances and dig into things and ask the...

1529
1:38:05 --> 1:38:08
They can ask the kind of questions that you're asking me.

1530
1:38:10 --> 1:38:13
So I don't ask the same questions that Celia does.

1531
1:38:13 --> 1:38:14
I'm not a journalist.

1532
1:38:14 --> 1:38:17
Oh, about cancer, just one quick question I thought of,

1533
1:38:18 --> 1:38:20
which was about your presentation.

1534
1:38:20 --> 1:38:24
I'm sorry the questions I've asked now weren't really about your presentation,

1535
1:38:24 --> 1:38:26
but you do know stuff that...

1536
1:38:26 --> 1:38:34
So the cancer, the site of toxic drugs, which do they work?

1537
1:38:34 --> 1:38:39
And if they work, by what mechanism do they work?

1538
1:38:39 --> 1:38:44
And is it a kind of blunt instrument that kills everything and thereby cancer?

1539
1:38:45 --> 1:38:46
Or is it...

1540
1:38:47 --> 1:38:49
How finely tuned do you think it is as a chemist?

1541
1:38:50 --> 1:38:52
You mean the chemotherapy?

1542
1:38:52 --> 1:38:56
The site of toxic drugs, which are said to be wonder drugs, you know?

1543
1:38:56 --> 1:39:00
Oh, no, they should all be illegal.

1544
1:39:01 --> 1:39:01
All of them?

1545
1:39:02 --> 1:39:04
Yeah, I can't think of any...

1546
1:39:04 --> 1:39:07
There's no such thing as a cancer drug.

1547
1:39:07 --> 1:39:08
There isn't one.

1548
1:39:09 --> 1:39:12
Not in the sense of a pharmaceutical drug.

1549
1:39:16 --> 1:39:21
Remember the Warburg effect and the importance of glucose to...

1550
1:39:23 --> 1:39:27
Every cancer, I don't care, even though none of them have the same combination of chromosomes,

1551
1:39:27 --> 1:39:31
they're all absolutely dependent on fermentation of the cell.

1552
1:39:32 --> 1:39:38
The so-called Warburg effect because they have a requirement for energy.

1553
1:39:38 --> 1:39:41
They have a huge demand of energy, more than normal cells and tissues.

1554
1:39:42 --> 1:39:45
And that has to go through if you keep glucose out of your diet

1555
1:39:47 --> 1:39:48
and change it with something else.

1556
1:39:48 --> 1:39:50
I think they call them keto diets or whatever.

1557
1:39:50 --> 1:39:51
There are approaches.

1558
1:39:51 --> 1:39:55
There are approaches that take advantage that you can take advantage of.

1559
1:39:56 --> 1:39:57
One of them is the Warburg effect.

1560
1:39:57 --> 1:39:59
And a lot of people are doing that around the world,

1561
1:40:00 --> 1:40:03
primarily in Mexico and Europe, but especially Germany.

1562
1:40:04 --> 1:40:05
They know to...

1563
1:40:06 --> 1:40:07
They know diet.

1564
1:40:10 --> 1:40:14
Fasting, very serious medical monitor dieting.

1565
1:40:15 --> 1:40:16
The cancer cells...

1566
1:40:19 --> 1:40:24
Every component in my presentation, those little numbered areas there,

1567
1:40:24 --> 1:40:26
I could talk an hour on each one of those.

1568
1:40:27 --> 1:40:27
Like about the...

1569
1:40:27 --> 1:40:31
No, the cytotoxic drugs.

1570
1:40:31 --> 1:40:33
So this is really important in my...

1571
1:40:33 --> 1:40:35
They're carcinogenic, by the way.

1572
1:40:35 --> 1:40:39
I cannot think of a cancer, anti-cancer drug that is not carcinogenic.

1573
1:40:39 --> 1:40:40
Okay.

1574
1:40:40 --> 1:40:44
So, but most people believe that they work, these things.

1575
1:40:44 --> 1:40:45
Maybe they want to believe they work, but...

1576
1:40:47 --> 1:40:49
So they don't work, in your opinion?

1577
1:40:49 --> 1:40:50
They absolutely don't work.

1578
1:40:52 --> 1:40:54
Okay, let me answer the question this way.

1579
1:40:54 --> 1:40:57
There's no target, there is no genetic target.

1580
1:40:57 --> 1:41:00
The only metabolic approach that you could go after, like I said,

1581
1:41:00 --> 1:41:02
is the production of fermentation,

1582
1:41:02 --> 1:41:05
which no drug company goes after that because they can't, they don't know how.

1583
1:41:05 --> 1:41:07
It's a dietary thing.

1584
1:41:09 --> 1:41:10
But they...

1585
1:41:12 --> 1:41:13
Lost my...

1586
1:41:14 --> 1:41:15
So how do they...

1587
1:41:15 --> 1:41:16
I'll answer that question one more time.

1588
1:41:16 --> 1:41:17
I derailed it.

1589
1:41:17 --> 1:41:19
David, how do they produce the illusion that they work then?

1590
1:41:19 --> 1:41:21
How do these criminals...

1591
1:41:21 --> 1:41:22
The illusion, yes.

1592
1:41:26 --> 1:41:26
Okay.

1593
1:41:29 --> 1:41:30
They're all toxic.

1594
1:41:30 --> 1:41:30
And people...

1595
1:41:31 --> 1:41:35
Cancer cells are very, very wimpy cells.

1596
1:41:35 --> 1:41:37
They die on their own all the time, all the time.

1597
1:41:37 --> 1:41:38
Okay.

1598
1:41:38 --> 1:41:44
And one reason why it takes decades is because they're so wimpy for solid cancers, all right?

1599
1:41:45 --> 1:41:46
For these things to come along.

1600
1:41:47 --> 1:41:49
And we probably all have cancer cells in us.

1601
1:41:49 --> 1:41:52
Maybe even little micro tumors or whatever.

1602
1:41:52 --> 1:41:57
But our innate immune system takes care of it because a normal, a healthy person,

1603
1:41:57 --> 1:42:00
you're much more healthy than any aneuploid cell.

1604
1:42:00 --> 1:42:03
The aneuploid cells are not healthy at all.

1605
1:42:03 --> 1:42:05
They go, they come and they go and they disappear.

1606
1:42:05 --> 1:42:09
And we're exposed to carcinogens all the time.

1607
1:42:09 --> 1:42:12
And if you're healthy and you don't have so many carcinogens,

1608
1:42:14 --> 1:42:15
you're not going to die of cancer.

1609
1:42:16 --> 1:42:19
It used to be a very, very rare thing, cancer was.

1610
1:42:19 --> 1:42:23
Now, you know, cancer is now the second leading cause of death in the United States.

1611
1:42:23 --> 1:42:24
Second, it used to be third.

1612
1:42:24 --> 1:42:27
Now since they use these injections, it's number two.

1613
1:42:28 --> 1:42:31
And they're all toxic drugs.

1614
1:42:32 --> 1:42:35
Our cells, our normal diploid healthy cells,

1615
1:42:37 --> 1:42:40
they're so much healthier than any cancer cell.

1616
1:42:41 --> 1:42:44
What the chemotherapy does, it kills all the cancer drugs.

1617
1:42:44 --> 1:42:46
They kill the cancer cells.

1618
1:42:46 --> 1:42:48
Cancer cells always die faster than normal cells.

1619
1:42:49 --> 1:42:51
That's why they're so hard to culture.

1620
1:42:53 --> 1:42:56
Before the HeLa cells from Henrietta Lacks in the 50s,

1621
1:42:56 --> 1:42:59
nobody could culture a human cancer cell.

1622
1:42:59 --> 1:43:02
In fact, nobody could really hardly culture human cells, period.

1623
1:43:03 --> 1:43:07
But until Henrietta Lacks, the HeLa cell,

1624
1:43:07 --> 1:43:09
they're still going in the lab right now.

1625
1:43:10 --> 1:43:12
They're extremely difficult to grow.

1626
1:43:12 --> 1:43:14
And when you take a biopsy of a tumor,

1627
1:43:14 --> 1:43:18
it's always a mix of normal healthy cells and cancer cells.

1628
1:43:19 --> 1:43:22
And if you try to culture them, in no time at all,

1629
1:43:22 --> 1:43:25
all the cancer cells have died off in cell culture.

1630
1:43:25 --> 1:43:28
And the normal cells are the ones that keep going.

1631
1:43:28 --> 1:43:32
That's why people used to think that there was such thing as diploid cancers.

1632
1:43:32 --> 1:43:35
Because when they analyzed those cultured cells,

1633
1:43:35 --> 1:43:39
they were all diploid because all the diploid cancer cells had died off.

1634
1:43:39 --> 1:43:43
Now everybody knows there's no such thing as a diploid cancer cell.

1635
1:43:44 --> 1:43:45
All right.

1636
1:43:47 --> 1:43:52
So what happens is instead of keeping your much higher health,

1637
1:43:53 --> 1:43:55
that health difference, cancer is low, you're high,

1638
1:43:57 --> 1:44:00
the chemo and radiation and everything lower,

1639
1:44:00 --> 1:44:02
it kills the cancer cells faster than you,

1640
1:44:02 --> 1:44:04
but it's also destroying your health.

1641
1:44:05 --> 1:44:09
So that distance between you and cancer is getting smaller and smaller,

1642
1:44:09 --> 1:44:10
your health and the cancer cell.

1643
1:44:11 --> 1:44:16
And after therapy is done, your health now is way down here.

1644
1:44:17 --> 1:44:20
They do it to the point where they can't detect the cancer cells anymore,

1645
1:44:20 --> 1:44:21
but they're still there.

1646
1:44:21 --> 1:44:24
There are probably millions of them left, you know, low cancer cells.

1647
1:44:24 --> 1:44:26
And they're the ones that could survive all that,

1648
1:44:26 --> 1:44:30
but they have to take you off the drugs and the treatment before they kill you.

1649
1:44:31 --> 1:44:37
Every technique, every medical technique other than surgery, just pure surgery,

1650
1:44:37 --> 1:44:40
but if you use any chemotherapy or radiation,

1651
1:44:40 --> 1:44:44
they're killing you because they're your cells, it's just the cancer cells.

1652
1:44:44 --> 1:44:48
There's no target that a chemotherapy goes after,

1653
1:44:49 --> 1:44:52
that a cancer cell has a target that your normal cells don't have.

1654
1:44:52 --> 1:44:56
Remember they're your cells, your genes, the same thing.

1655
1:44:56 --> 1:45:01
They're targeting your normal cells at the same time they're targeting the cancer cells.

1656
1:45:01 --> 1:45:03
The cancer cells just die faster.

1657
1:45:03 --> 1:45:03
That's it.

1658
1:45:04 --> 1:45:10
Yes, but the point is, even if you are doubtful about that,

1659
1:45:12 --> 1:45:13
I'm certain of it.

1660
1:45:13 --> 1:45:20
If the cancer cells are killed off almost at the expense of the patient dying,

1661
1:45:20 --> 1:45:22
but not quite dying, and then the patient recovers,

1662
1:45:23 --> 1:45:30
and then they achieve a so-called, yeah, they've been cured of cancer eventually,

1663
1:45:30 --> 1:45:33
you know, after five years, whatever it is, allegedly.

1664
1:45:34 --> 1:45:39
Then you could argue that they've achieved their goal, even though they put their,

1665
1:45:39 --> 1:45:41
they didn't really know what they were doing.

1666
1:45:41 --> 1:45:46
They used a blunt instrument to kill off the cancer cells, which almost killed them.

1667
1:45:47 --> 1:45:48
Do you understand me?

1668
1:45:48 --> 1:45:50
But at least the patients have survived.

1669
1:45:50 --> 1:45:51
But most don't.

1670
1:45:51 --> 1:45:53
Most don't make five years.

1671
1:45:53 --> 1:45:54
Absolutely not.

1672
1:45:55 --> 1:45:56
Right.

1673
1:45:56 --> 1:45:58
So you think the whole thing with cancer drugs...

1674
1:45:58 --> 1:46:00
The cancer comes back and there's nothing they can do about it.

1675
1:46:00 --> 1:46:03
There's no therapy and it winds up killing them.

1676
1:46:04 --> 1:46:09
David, you think that the whole cancer treatment, that's a fraud too, do you?

1677
1:46:09 --> 1:46:11
So all the cancer research...

1678
1:46:11 --> 1:46:12
Absolutely, totally and completely.

1679
1:46:13 --> 1:46:14
Right. That's interesting.

1680
1:46:15 --> 1:46:18
So last question, very quickly, Charles.

1681
1:46:18 --> 1:46:20
Very quickly answers as well, David.

1682
1:46:20 --> 1:46:24
Was there a pandemic in 2020 or not?

1683
1:46:26 --> 1:46:27
A pandemic, a fraud?

1684
1:46:28 --> 1:46:29
Yes, exactly.

1685
1:46:30 --> 1:46:37
Did you know in the United States, fewer people died in 2020 than they did the previous five years?

1686
1:46:37 --> 1:46:40
Yeah. So do you think as I think, you don't have to agree with me,

1687
1:46:40 --> 1:46:48
but I think that it's highly possible, probable in fact, that pandemics can't occur because

1688
1:46:48 --> 1:46:51
a deadly virus, if you believe in viruses, kills its host.

1689
1:46:51 --> 1:46:53
Therefore it can't spread all around the world.

1690
1:46:53 --> 1:46:58
And so the whole thing about pandemics is a construct for these criminals

1691
1:46:58 --> 1:47:02
to use the Trojan horse for totalitarianism.

1692
1:47:03 --> 1:47:07
And the second question I have is, was there a disease called COVID-19?

1693
1:47:08 --> 1:47:08
No.

1694
1:47:09 --> 1:47:10
Absolutely.

1695
1:47:10 --> 1:47:13
All you got to do is look at the CDC, go to the CDC's own website.

1696
1:47:14 --> 1:47:16
They actually have it and I do it in my presentations.

1697
1:47:16 --> 1:47:23
I take an image of the CDC's website and they have a comparison of the symptoms of the flu

1698
1:47:23 --> 1:47:25
and the symptoms of COVID-19.

1699
1:47:25 --> 1:47:26
They're identical.

1700
1:47:27 --> 1:47:27
Absolutely.

1701
1:47:28 --> 1:47:28
Absolutely.

1702
1:47:29 --> 1:47:32
You know, so all they did was change the name.

1703
1:47:32 --> 1:47:37
There's two things and this came from the AIDS, HIV and AIDS started this.

1704
1:47:38 --> 1:47:46
The CDC knew as early as 1982 that the so-called AIDS defined, early AIDS defining diseases

1705
1:47:47 --> 1:47:56
were in gay men using chronic doses of nitrite inhalants and recreational drugs.

1706
1:47:56 --> 1:47:58
And the heterosexual IV drug users.

1707
1:47:58 --> 1:48:01
Those were the AIDS cases in the 70s and the early 80s.

1708
1:48:02 --> 1:48:09
And the CDC knew as early as 1982 that that was what was causing those symptoms that later

1709
1:48:09 --> 1:48:12
be called AIDS and they could be adding new symptoms for AIDS.

1710
1:48:12 --> 1:48:13
The definition is huge.

1711
1:48:14 --> 1:48:18
So to sum up David, AIDS was a false diagnosis and so was COVID-19.

1712
1:48:18 --> 1:48:19
It was a fraud.

1713
1:48:19 --> 1:48:21
It wasn't a false diagnosis.

1714
1:48:21 --> 1:48:22
I agree with you.

1715
1:48:22 --> 1:48:23
It was a scam.

1716
1:48:23 --> 1:48:24
They knew it.

1717
1:48:24 --> 1:48:35
They, I'm telling you right now that they decided in 1984, the federal government decided,

1718
1:48:35 --> 1:48:41
and that's when they hired Anthony Fauci to do this intentionally, was to lead the AIDS thing

1719
1:48:41 --> 1:48:47
as an uncurable viral disease that anybody could get.

1720
1:48:48 --> 1:48:50
And he killed any other.

1721
1:48:50 --> 1:48:56
Anthony Fauci would not allow anything else, any publications, any outspoken, anything.

1722
1:48:57 --> 1:48:58
That was by design.

1723
1:48:58 --> 1:49:02
They didn't care what it was, but they had this thing and they wanted to have this virus.

1724
1:49:03 --> 1:49:09
And they wanted to make a contagious disease because people are afraid of contagious diseases.

1725
1:49:10 --> 1:49:10
Absolutely.

1726
1:49:10 --> 1:49:12
They wanted to make a contagious disease lethal.

1727
1:49:13 --> 1:49:15
Yes, exactly.

1728
1:49:15 --> 1:49:15
Exactly.

1729
1:49:16 --> 1:49:20
Make it really an object of fear in the minds of human beings.

1730
1:49:21 --> 1:49:23
Lots of hands up.

1731
1:49:23 --> 1:49:25
One last point, Charles, just very quickly.

1732
1:49:26 --> 1:49:33
So in my opinion as a medical doctor, David, I think that it's highly probable that these

1733
1:49:33 --> 1:49:38
pandemics, the deadly viral pandemics, you know, which have caused, so we've got to do

1734
1:49:38 --> 1:49:41
something about the next pandemic and all this.

1735
1:49:41 --> 1:49:42
I don't think pandemics are possible.

1736
1:49:42 --> 1:49:44
No, we've agreed on that.

1737
1:49:44 --> 1:49:44
I think that's a con.

1738
1:49:45 --> 1:49:45
Come on.

1739
1:49:46 --> 1:49:47
I'm just trying to ram the point home.

1740
1:49:48 --> 1:49:50
You've rammed it beautifully.

1741
1:49:50 --> 1:49:51
I'm with you on that.

1742
1:49:52 --> 1:49:52
Good.

1743
1:49:52 --> 1:49:53
Very good, David.

1744
1:49:53 --> 1:49:54
Thank you so much.

1745
1:49:55 --> 1:49:55
All right.

1746
1:49:55 --> 1:49:56
Thank you, Stephen.

1747
1:49:56 --> 1:49:57
Lars.

1748
1:49:59 --> 1:50:00
Thank you, David.

1749
1:50:00 --> 1:50:01
That was fantastic.

1750
1:50:02 --> 1:50:04
I have two questions for you.

1751
1:50:04 --> 1:50:08
The first one is Thomas Seyfried in Boston.

1752
1:50:08 --> 1:50:11
He says that cancer is a metabolic disease.

1753
1:50:11 --> 1:50:13
Do you agree with him on everything he says?

1754
1:50:13 --> 1:50:15
Or do you have differences with him?

1755
1:50:15 --> 1:50:17
It is a metabolic disease.

1756
1:50:19 --> 1:50:24
That's the Warburg effect that I talked about and he talks about.

1757
1:50:24 --> 1:50:29
What they're doing, they're saying the thing where I absolutely disagree is that

1758
1:50:30 --> 1:50:36
they agree that aneuploidy is a big deal in cancer, but they say that the Warburg effect,

1759
1:50:36 --> 1:50:42
or this metabolic disease, leads to chromosomal imbalance.

1760
1:50:42 --> 1:50:44
It's the absolute opposite.

1761
1:50:45 --> 1:50:50
If that were true, there would be diploid cancers.

1762
1:50:50 --> 1:50:55
You'd have the fermentation leading to cancer without aneuploidy.

1763
1:50:55 --> 1:50:56
There's no example of that.

1764
1:50:59 --> 1:51:05
The question is, what causes this massive Warburg effect where you have these healthy cells

1765
1:51:05 --> 1:51:11
and all of a sudden they decided to go stop using mitochondria.

1766
1:51:11 --> 1:51:15
Much more efficient producing 32 ATP's per one glucose.

1767
1:51:16 --> 1:51:23
Why give that up and now start using fermentation to produce only two ATP's?

1768
1:51:23 --> 1:51:27
You see, the explanation is what I just said.

1769
1:51:28 --> 1:51:34
When you have this overabundance of protein, you have chromosomes, you have 70%, 50%, 60%,

1770
1:51:35 --> 1:51:38
80% extra protein in the cell.

1771
1:51:39 --> 1:51:44
It's called macromolecular crowding inside the cell.

1772
1:51:45 --> 1:51:49
It just changes the physics.

1773
1:51:49 --> 1:51:52
Like I said before, the phenotypic consequences,

1774
1:51:52 --> 1:51:56
the more biophysical consequences than biochemical.

1775
1:51:56 --> 1:51:59
The biophysical consequences go up exponentially.

1776
1:52:01 --> 1:52:03
Exponentially, like tenfold or more.

1777
1:52:05 --> 1:52:09
And that's what produces all of the phenotypes.

1778
1:52:09 --> 1:52:13
The membrane-bound proteins, the secreted proteins,

1779
1:52:13 --> 1:52:16
are a consequence of the overproduction of protein.

1780
1:52:17 --> 1:52:21
The only way you can get an overproduction of protein, you have to have a hell of a lot of ATP.

1781
1:52:23 --> 1:52:29
If you starve a cancer cell with ATP, you can't completely because you're generating the

1782
1:52:30 --> 1:52:32
fermentation in the cancer cell too.

1783
1:52:32 --> 1:52:39
But if you just really cut it down, the aerobic glycolysis,

1784
1:52:41 --> 1:52:44
not all of the mitochondria are destroyed in cancer cells.

1785
1:52:49 --> 1:52:52
Once you see it, it's obvious.

1786
1:52:52 --> 1:52:57
The metabolic thing, if you're talking about therapy, that's where you go to, I think.

1787
1:52:58 --> 1:53:01
Starve the cancer of glucose.

1788
1:53:03 --> 1:53:05
Starve it of ATP, but not the person.

1789
1:53:06 --> 1:53:08
Humans can live without glucose.

1790
1:53:09 --> 1:53:14
And David, Danny Dukoc, and others are saying precisely that in the chat.

1791
1:53:14 --> 1:53:15
Starve the cancer of glucose.

1792
1:53:15 --> 1:53:16
That's right.

1793
1:53:17 --> 1:53:18
Starve the cancer.

1794
1:53:18 --> 1:53:19
Yeah.

1795
1:53:19 --> 1:53:20
It's not toxic to people.

1796
1:53:20 --> 1:53:22
It's a non-toxic way to do it.

1797
1:53:24 --> 1:53:25
I have one more question, if I may.

1798
1:53:28 --> 1:53:31
A lot of cancer doctors talk about terrible cancer now.

1799
1:53:33 --> 1:53:39
In your view, what's the mechanism and is there anything people can do about it?

1800
1:53:40 --> 1:53:41
Don't get injected.

1801
1:53:43 --> 1:53:44
I don't know how you treat it.

1802
1:53:44 --> 1:53:47
I frankly, honestly, I don't know how you would do that.

1803
1:53:47 --> 1:53:48
Okay, I've answered this.

1804
1:53:48 --> 1:53:49
I've talked about it.

1805
1:53:49 --> 1:53:51
I put it in my new book, actually, too.

1806
1:53:51 --> 1:54:00
Knowing the chronology of the progression of cancer, it takes decades for solid tumors and

1807
1:54:00 --> 1:54:00
everything.

1808
1:54:01 --> 1:54:05
Because knowing the cancer cells, knowing the aneuploidy, how damaged these things are,

1809
1:54:06 --> 1:54:09
that your immune system is really just absolutely extraordinary.

1810
1:54:09 --> 1:54:11
Just get, if it sees them, it gets rid of them.

1811
1:54:13 --> 1:54:16
And if it can't get rid of them, it just like guards around it.

1812
1:54:16 --> 1:54:19
Now just sit there benign because they can't progress.

1813
1:54:20 --> 1:54:24
For example, you can have these partially progressed cancer cells, but if you go in

1814
1:54:24 --> 1:54:29
there and take a biopsy, on occasion, you'll free them up and then start dividing and progressing

1815
1:54:29 --> 1:54:30
and then turn into cancer.

1816
1:54:30 --> 1:54:34
It's rare, but a few percent, that happens even with just biopsy.

1817
1:54:36 --> 1:54:42
The turbo cancer, from my perspective, has to be, like I said, we all probably have these

1818
1:54:42 --> 1:54:45
little cancers and tumors in us to varying degrees.

1819
1:54:45 --> 1:54:49
I think it's the innate immune system that is just totally being destroyed.

1820
1:54:51 --> 1:54:55
I have no doubt that some of those things that they're injecting into people are carcinogens.

1821
1:54:56 --> 1:55:02
But if you had a functioning immune system, it would still take years to get a blood cancer

1822
1:55:02 --> 1:55:07
from scratch and decades to get a solid tumor from scratch by doing that.

1823
1:55:07 --> 1:55:07
You see?

1824
1:55:09 --> 1:55:15
So I'm convinced that these turbo cancers are those tumors that we have in our body.

1825
1:55:15 --> 1:55:19
They're in us already that are dormant, that you probably never ever know.

1826
1:55:19 --> 1:55:23
You probably survived it or whatever, or if it did show up, okay, or whatever.

1827
1:55:24 --> 1:55:30
But now once you've destroyed the innate immune system and you prevent that, you basically

1828
1:55:31 --> 1:55:35
with no immune system, you're turning people into petri dishes in the cell culture.

1829
1:55:36 --> 1:55:38
It's the tumor that is already there.

1830
1:55:39 --> 1:55:45
These aneuploid cells, like I said, they're very weak compared to normal healthy cells.

1831
1:55:45 --> 1:55:47
They don't have a prayer usually.

1832
1:55:49 --> 1:55:53
But as soon as you destroy the immune system, there's always a population.

1833
1:55:54 --> 1:55:56
Because no two of them have the same karyotypes.

1834
1:55:56 --> 1:55:59
There's always these different viruses, like bacteria.

1835
1:56:01 --> 1:56:04
Cancer is like a single cell organism, like bacteria.

1836
1:56:04 --> 1:56:07
The individual cells are on their own, really.

1837
1:56:08 --> 1:56:09
They can do what they want to.

1838
1:56:09 --> 1:56:16
You will always find an antibody-resistant bacterium in a population of bacteria.

1839
1:56:16 --> 1:56:19
Because you kill off all the ones that are susceptible to it, and you leave the ones

1840
1:56:20 --> 1:56:25
that just happen to be resistant to it, and then they repopulate the bacteria population.

1841
1:56:26 --> 1:56:31
Well, that's what I think is going on with the turbo cancer.

1842
1:56:32 --> 1:56:35
Every one of these cancer cells, remember, is unique.

1843
1:56:36 --> 1:56:37
Just like people are unique.

1844
1:56:37 --> 1:56:43
No two have the identical phenotype or karyotype or anything, like bacteria.

1845
1:56:46 --> 1:56:50
There's always going to be some that will take advantage of the environment.

1846
1:56:50 --> 1:56:53
You give them an environment with a weakened immune system.

1847
1:56:53 --> 1:56:58
Those that can proliferate will proliferate, like cell culture, like mad.

1848
1:56:59 --> 1:57:03
I think that is the explanation for the speed with which these things.

1849
1:57:04 --> 1:57:11
David Martin suggested that the pseudo-uridine downregulated interferon 1,

1850
1:57:11 --> 1:57:14
so that the immune system just couldn't handle it.

1851
1:57:14 --> 1:57:16
Does that make sense in your world?

1852
1:57:17 --> 1:57:19
I think it's more dramatic than that.

1853
1:57:19 --> 1:57:21
That's the molecular thing.

1854
1:57:21 --> 1:57:24
The interferon, or the cytokine, or that thing.

1855
1:57:24 --> 1:57:28
The immune system is at least as complex as our central nervous system, I think.

1856
1:57:28 --> 1:57:31
Everywhere you look, it's just so huge.

1857
1:57:31 --> 1:57:33
I think it's just in mass.

1858
1:57:35 --> 1:57:36
It's just being reduced.

1859
1:57:36 --> 1:57:37
One of the things that they've noticed with these,

1860
1:57:39 --> 1:57:42
have you heard of IgG4, immunoglobulin 4?

1861
1:57:42 --> 1:57:42
Yes.

1862
1:57:44 --> 1:57:46
That one, and I think too, but IgG4,

1863
1:57:46 --> 1:57:51
that's the one that's the least available antibody in our body.

1864
1:57:52 --> 1:57:57
When it proliferates, its function generally allows us to overcome allergies.

1865
1:57:58 --> 1:58:02
Like my brother had a lot of allergies, and they exposed him a lot of allergies when he was a kid.

1866
1:58:03 --> 1:58:09
Finally, his IgG4 came up there, and now he doesn't have these allergies anymore.

1867
1:58:10 --> 1:58:15
It basically shuts the immune system down to this, aspects of it.

1868
1:58:17 --> 1:58:25
But the IgG4 levels now have gone up 200, 500 fold, something like that, in these people.

1869
1:58:26 --> 1:58:36
And they have been exposed to these injections, and they're also getting used to these cancers.

1870
1:58:37 --> 1:58:42
If they have anything to do with cancers, they're going to stop the immune system from attacking

1871
1:58:42 --> 1:58:43
cancer cells.

1872
1:58:46 --> 1:58:47
I'm not an immunologist.

1873
1:58:48 --> 1:58:54
I don't know all the nuances because it's complex, complicated stuff.

1874
1:58:54 --> 1:58:58
But I know the general principles, and the general principles make perfect sense to me.

1875
1:58:58 --> 1:58:59
Thank you very much.

1876
1:59:00 --> 1:59:00
Thank you.

1877
1:59:00 --> 1:59:01
Thank you, Lars.

1878
1:59:02 --> 1:59:03
Zoe, good to see you again.

1879
1:59:09 --> 1:59:10
Sorry, I was on mute.

1880
1:59:10 --> 1:59:10
Can you hear me?

1881
1:59:11 --> 1:59:11
Yep.

1882
1:59:12 --> 1:59:12
Yes.

1883
1:59:19 --> 1:59:22
We could momentarily, but not now.

1884
1:59:22 --> 1:59:24
We've lost you now, Zoe.

1885
1:59:33 --> 1:59:35
And we can hear you now.

1886
1:59:35 --> 1:59:36
There we go.

1887
1:59:36 --> 1:59:36
Can you hear me now?

1888
1:59:37 --> 1:59:38
Yes.

1889
1:59:38 --> 1:59:39
I touched it.

1890
1:59:41 --> 1:59:41
Hello.

1891
1:59:41 --> 1:59:42
Thanks for having me.

1892
1:59:44 --> 1:59:46
Zoe, are you the medical coder?

1893
1:59:46 --> 1:59:47
Are you the medical coder?

1894
1:59:48 --> 1:59:49
That's me.

1895
1:59:49 --> 1:59:49
All right.

1896
1:59:53 --> 1:59:55
Can you put your email address in the chat?

1897
1:59:55 --> 2:00:01
Because I meant to invite you, but somehow you've slipped off the radar.

1898
2:00:02 --> 2:00:04
I sent an email to both you and Charles.

1899
2:00:05 --> 2:00:06
I think it was when Holland was on.

1900
2:00:06 --> 2:00:07
That's good.

1901
2:00:07 --> 2:00:08
Okay.

1902
2:00:08 --> 2:00:09
I'll look for it then.

1903
2:00:09 --> 2:00:10
So I hope it went through.

1904
2:00:10 --> 2:00:12
I have a proton mail address.

1905
2:00:12 --> 2:00:14
It's zoeSmith at protonmail.

1906
2:00:14 --> 2:00:17
So hopefully, I can send you another one.

1907
2:00:19 --> 2:00:19
Oh, that would be good.

1908
2:00:19 --> 2:00:20
Yeah. If you could do that.

1909
2:00:21 --> 2:00:21
Yeah.

1910
2:00:22 --> 2:00:31
So my question for Dr. Rasnik, it actually has to do with HIV, but it connects to COVID.

1911
2:00:32 --> 2:00:36
So my question, and this is in my book, because I used to work in a lab,

1912
2:00:37 --> 2:00:41
and there's an exposure protocol for anybody that works in a lab.

1913
2:00:41 --> 2:00:46
If you're exposed to a body fluid, you're supposed to go down to the ER,

1914
2:00:46 --> 2:00:53
and they will run a PCR test on you and see if you have HIV, and then they start you on

1915
2:00:53 --> 2:00:57
HIV prophylaxis if you've been exposed.

1916
2:00:57 --> 2:00:59
And I did not know what that drug was.

1917
2:01:00 --> 2:01:05
So for researching my book, I looked into it, and I can't remember the name off the top of my head,

1918
2:01:05 --> 2:01:07
the brand name.

1919
2:01:07 --> 2:01:12
But when I looked into the actual brand name and who makes it and what is the dose and

1920
2:01:13 --> 2:01:19
how are they prescribing this PrEP or prophylaxis treatment that they're giving to hospital

1921
2:01:19 --> 2:01:26
employees that are exposed to body fluids, it appeared to me it was AZT but in a reduced dose.

1922
2:01:27 --> 2:01:33
And what we know from HIV is that AZT was causing the AIDS symptoms and making it appear as though

1923
2:01:33 --> 2:01:37
there was an epidemic of HIV at the time.

1924
2:01:38 --> 2:01:43
And another thing that I talk about in the book is that there was this drug Remdesivir

1925
2:01:44 --> 2:01:49
in connection with the ventilators that were used to make everyone think that COVID-19 was

1926
2:01:49 --> 2:01:55
this massive respiratory failure disease, and that's how they got everyone to believe that there was

1927
2:01:55 --> 2:01:56
a pandemic happening.

1928
2:01:56 --> 2:02:00
It was actually the treatment in the hospital that was causing that.

1929
2:02:01 --> 2:02:05
So I'm finding this other parallel, and I'm just curious if you've discovered that,

1930
2:02:05 --> 2:02:12
if you knew that that was the treatment that hospital employees were given,

1931
2:02:13 --> 2:02:19
because I had always known, and I didn't know what the actual drug was that they were prescribing,

1932
2:02:19 --> 2:02:24
but everybody that worked in the lab that had ever, and I had a friend who actually did have

1933
2:02:24 --> 2:02:28
to do this treatment for two months because she was exposed to body fluids.

1934
2:02:30 --> 2:02:33
We all knew that it had these massive side effects, and I looked up what the side effects

1935
2:02:33 --> 2:02:35
were, and it was like two pages.

1936
2:02:35 --> 2:02:37
It includes death and organ failure.

1937
2:02:38 --> 2:02:45
I was definitely afraid of being exposed and having to be put on this protocol

1938
2:02:47 --> 2:02:53
in order to stay employed and come to find out there's this connection with AZT.

1939
2:02:53 --> 2:02:55
So I was interested in your perspective on that.

1940
2:02:55 --> 2:02:56
Yes.

1941
2:02:56 --> 2:02:56
If you could.

1942
2:02:56 --> 2:02:57
Happy to talk to you about that.

1943
2:02:58 --> 2:02:59
Yeah.

1944
2:03:00 --> 2:03:06
It's PREP and PEP, pre-exposure prophylaxis and post-exposure prophylaxis.

1945
2:03:07 --> 2:03:11
This came out in the end of the 90s, early 2000s, something like that.

1946
2:03:12 --> 2:03:18
It was the idea, it was a way to, you're right, they use these tests.

1947
2:03:18 --> 2:03:24
It's the same key here all the way through, antibody tests for HIV or PCR or something like that,

1948
2:03:25 --> 2:03:27
to label you with something.

1949
2:03:28 --> 2:03:34
Then they come up with the toxic thing to give you as a consequence of that.

1950
2:03:36 --> 2:03:39
The test, the PCR test, for example, is totally bogus.

1951
2:03:39 --> 2:03:45
Antibody test, PCR, it tells you in all of those tests, the PCR test for HIV,

1952
2:03:45 --> 2:03:51
the antialysate test and all that, it says in the package inserts that there's no reference

1953
2:03:51 --> 2:03:55
standards that these tests are not to be used to diagnose the presence of HIV

1954
2:04:00 --> 2:04:01
or the virus.

1955
2:04:02 --> 2:04:08
You cannot use it to diagnose AIDS or the presence of HIV.

1956
2:04:08 --> 2:04:12
Believe it or not, it says it in the package inserts that come with all those HIV tests.

1957
2:04:14 --> 2:04:17
But yet they're doing it anyway, and they're giving you these drugs.

1958
2:04:18 --> 2:04:24
Since they started using these things, the post-exposure prophylaxis and pre-exposure

1959
2:04:24 --> 2:04:29
prophylaxis, so many people were coming down with AIDS-defining diseases after that,

1960
2:04:32 --> 2:04:37
were killing a lot of people and keep adding these new diseases or consequences,

1961
2:04:38 --> 2:04:41
that they came up with another disease.

1962
2:04:41 --> 2:04:48
It was called immune reconstitution inflammatory syndrome.

1963
2:04:50 --> 2:04:54
Originally, it was immune reconstitution syndrome, IRS.

1964
2:04:55 --> 2:05:01
You come down with the same diseases as an AIDS person plus additional ones.

1965
2:05:03 --> 2:05:07
But if they show up only after you take the drugs, it's not called AIDS.

1966
2:05:07 --> 2:05:11
It's called IRS or immune, or IRIS.

1967
2:05:13 --> 2:05:14
That's what it is.

1968
2:05:14 --> 2:05:15
I've got posters.

1969
2:05:15 --> 2:05:16
I've talked about this.

1970
2:05:17 --> 2:05:19
They are causing more harm.

1971
2:05:20 --> 2:05:26
AIDS diseases plus a whole host, more than double the number of diseases that were associated

1972
2:05:26 --> 2:05:32
with AIDS are part of IRS and immune inflammatory reconstitution syndrome.

1973
2:05:35 --> 2:05:37
They're causing these diseases that they're trying to...

1974
2:05:37 --> 2:05:39
This has been going on since the late 90s.

1975
2:05:40 --> 2:05:42
Well, they're doing that with long COVID also.

1976
2:05:42 --> 2:05:44
They have a diagnosis for COVID.

1977
2:05:45 --> 2:05:50
After you've been given this test, they label you as COVID-19, and there's a diagnosis code for that.

1978
2:05:50 --> 2:05:54
But if you come in and you've been vaccinated and you have these long COVID symptoms,

1979
2:05:54 --> 2:05:58
they're calling them long COVID symptoms, they have specific diseases for that.

1980
2:05:58 --> 2:06:01
They're not categorized as vaccine injuries.

1981
2:06:01 --> 2:06:07
That's one reason that I titled my book what I did, because the COVID code, it actually

1982
2:06:07 --> 2:06:13
the code that I'm talking about when I refer to that, is the vaccine injury code that they

1983
2:06:13 --> 2:06:16
did not publish in the United States or in many other countries.

1984
2:06:16 --> 2:06:20
It was published on the WHO website, but they did not make it available

1985
2:06:21 --> 2:06:23
to report internationally as a code.

1986
2:06:24 --> 2:06:28
It was a way of burying a needle in the haystack, and they've recategorized...

1987
2:06:28 --> 2:06:33
Well, not only did they use the initial COVID diagnosis code to recategorize all the respiratory

1988
2:06:33 --> 2:06:38
symptoms that used to be flu, asthma, and all those things into COVID,

1989
2:06:39 --> 2:06:44
but they've also used this long COVID thing to categorize vaccine injuries as that.

1990
2:06:45 --> 2:06:45
Right.

1991
2:06:46 --> 2:06:51
So it seems to me in multiple levels, they use the HIV

1992
2:06:54 --> 2:06:57
fraud to parallel the COVID fraud.

1993
2:06:57 --> 2:07:02
They basically pulled the rules from the HIV scam and applied them to COVID.

1994
2:07:03 --> 2:07:06
Yeah. In fact, the AIDS thing was the blueprint.

1995
2:07:07 --> 2:07:10
When they kept that, that was the blueprint for everything since then.

1996
2:07:11 --> 2:07:14
I'm literally meaning everything since then.

1997
2:07:15 --> 2:07:21
I agree. So I was correct in the current treatment that they are still giving to

1998
2:07:21 --> 2:07:30
hospital employees and also marketing currently to gay people for as PrEP is AZT,

1999
2:07:30 --> 2:07:33
just a reduced dose. So it is continuing.

2000
2:07:34 --> 2:07:39
Absolutely. They're giving the anti-HIV drugs as prophylaxis.

2001
2:07:42 --> 2:07:47
Perfectly healthy. But if you had sex with somebody and you're afraid

2002
2:07:47 --> 2:07:51
that you might get HIV from them, then it's pre-exposure prophylaxis.

2003
2:07:51 --> 2:07:55
It's perfectly healthy. They give you the exact same AIDS drugs.

2004
2:07:55 --> 2:08:01
And if you come down with AIDS diseases or any of the other diseases, they don't call it AIDS,

2005
2:08:01 --> 2:08:06
even though you have the AIDS symptoms. They call it post-exposure prophylaxis.

2006
2:08:06 --> 2:08:10
I mean, immune reconstitution inflammatory syndrome. They just rename it.

2007
2:08:11 --> 2:08:13
Wow. Wow.

2008
2:08:15 --> 2:08:17
I think a lot of people are not aware of that.

2009
2:08:19 --> 2:08:21
They're not. That's why we have to share this stuff.

2010
2:08:21 --> 2:08:25
You know, and since you're a coder person, you could look that up.

2011
2:08:25 --> 2:08:27
Certainly with AIDS, you look at that.

2012
2:08:27 --> 2:08:35
So David, couldn't you and Zoe go to the equivalent of the police in the UK in America

2013
2:08:36 --> 2:08:39
or go to the sheriffs and tell them about this?

2014
2:08:41 --> 2:08:45
But you know, I don't go to people like that. They have to come to me

2015
2:08:45 --> 2:08:47
because I'm not a preacher. I can't convert anybody.

2016
2:08:48 --> 2:08:51
They have to look like moms and everything.

2017
2:08:51 --> 2:08:55
You know, they had to go through some horrible thing with their child,

2018
2:08:56 --> 2:09:00
to become a warrior and fight the horrible things that are going on.

2019
2:09:00 --> 2:09:01
That's what's going to happen with COVID.

2020
2:09:01 --> 2:09:06
They have to have enough people injured, whatever that is economically,

2021
2:09:09 --> 2:09:14
so they get so pissed off, they either give up or they die or they fight back.

2022
2:09:15 --> 2:09:18
I mean, look how long it took to talk about AIDS after all these decades.

2023
2:09:20 --> 2:09:24
But also, people like you, David and Zoe, working together,

2024
2:09:24 --> 2:09:30
could actually create a counter narrative which could destroy the false narrative of them.

2025
2:09:31 --> 2:09:36
So as you say, I'm happy to be sorry, all these people knew that.

2026
2:09:36 --> 2:09:39
Sorry. I'm eager to do it.

2027
2:09:39 --> 2:09:42
I would be happy to as well, whatever I can do.

2028
2:09:42 --> 2:09:52
I know in the United States, all the institutions down to the individuals that used any COVID

2029
2:09:52 --> 2:09:57
measure from the vaccine to the PCR tests are covered under the PREP Act.

2030
2:09:58 --> 2:10:03
So I don't think going to a sheriff would do any good in the United States because of that.

2031
2:10:04 --> 2:10:09
But anything that I can do, I'm happy to do, to fight back.

2032
2:10:10 --> 2:10:11
That's why I wrote my book.

2033
2:10:12 --> 2:10:18
And Dr. Rasnik, if I may, I'd like to send you an email later and maybe we could discuss this on

2034
2:10:18 --> 2:10:23
my sub stack and help get it out there more. By the way, everybody, I prefer Dave.

2035
2:10:23 --> 2:10:28
Zoe, I do think that- I don't like people that I don't like.

2036
2:10:28 --> 2:10:34
I come from the healthcare industry, so I'm programmed to show that kind of respect.

2037
2:10:34 --> 2:10:36
So thank you for being down to Earth, Dave.

2038
2:10:39 --> 2:10:40
Yeah, we'll do that.

2039
2:10:43 --> 2:10:47
So Zoe, I think there is a point in going to the sheriffs, even if they don't do anything,

2040
2:10:48 --> 2:10:55
because if you formally put a complaint in, a criminal complaint or whatever you call it in

2041
2:10:55 --> 2:11:02
America, then you know that you have told people, certain people, named people,

2042
2:11:03 --> 2:11:10
that what's going on and that you know that they knew then, at least so there's a marker

2043
2:11:11 --> 2:11:15
in the future. But if everybody says, oh, there's no point in going to the sheriff

2044
2:11:16 --> 2:11:22
and there's nothing recorded, then it's just all in the air, isn't it, in the future.

2045
2:11:22 --> 2:11:28
And that's not very- so I do think that notices of liability or whatever you want to call them,

2046
2:11:28 --> 2:11:33
you know, are very important because then in the future you can say this person,

2047
2:11:34 --> 2:11:41
this named person knew this then, two years ago, five years ago, whatever. But at the moment,

2048
2:11:42 --> 2:11:48
you know, HIV and AIDS has never been solved, I think because nobody's formally made these

2049
2:11:48 --> 2:11:56
complaints to anyone. Formally. Oh no, we tried. Listen, what happens, you get fired, you lose your

2050
2:11:56 --> 2:12:01
grants. I mean, if you know you're on the right track when somebody comes after you.

2051
2:12:01 --> 2:12:06
Absolutely, yeah. Your insolence is a testament to that.

2052
2:12:06 --> 2:12:13
It's far more important that Zoe and I and other people share the information so that we can

2053
2:12:13 --> 2:12:18
distribute it broadly. That's what I- Yes, very good.

2054
2:12:18 --> 2:12:22
All right. Thank you, Zoe. Glyn.

2055
2:12:22 --> 2:12:30
Hi, David. It's interesting, as a deep researcher, you've sort of done things in your own space and

2056
2:12:30 --> 2:12:38
all of these crazy ass hoaxes are all around you, which is, I think you've done a marvelous job of

2057
2:12:39 --> 2:12:48
describing it. And there's three primary ones here. The HIV hoax, the COVID hoax, and the

2058
2:12:48 --> 2:12:56
hoax and the pharma health correction industry hoax. Am I accurate in saying that?

2059
2:12:57 --> 2:13:05
I got it. But like I said, I got 40 years of that sort of stuff on my website. I mean, a lot of

2060
2:13:05 --> 2:13:12
stuff. And a lot of it- Okay, so what I would like to suggest is I think a lot of these are connected

2061
2:13:12 --> 2:13:19
and especially around who was the primary sponsor. So I want to name a number of other hoaxes and

2062
2:13:19 --> 2:13:24
see if you have an answer. So very quick answer, please. Just either say, yes, you think so and

2063
2:13:24 --> 2:13:30
you haven't, or I'm not sure. Just give me one or the other. The climate change hoax.

2064
2:13:35 --> 2:13:39
As who is the sponsor of the climate change hoax?

2065
2:13:39 --> 2:13:47
I don't know, but it's- Okay. Let me- the transsexual transformation improvement hoax.

2066
2:13:48 --> 2:13:54
I don't know, but I think they're all the same. The President Trump is a threat to democracy

2067
2:13:54 --> 2:14:04
hoax. I don't know the answer to these things. Okay. I'm just trying to- yeah. The women's lib

2068
2:14:04 --> 2:14:11
hoax. I'm glad for women's lib because I'm old enough to know when they didn't have a whole lot

2069
2:14:11 --> 2:14:17
of rights. Well, that's a- well, I won't go deep. That's a little deeper. Now, another one from you

2070
2:14:18 --> 2:14:24
having lived in California for a long time, the OJ Simpson murder trial hoax that he was the culprit.

2071
2:14:26 --> 2:14:32
He was definitely guilty. Oh, no, no, no, no. Oh, no, no, no, no. He was definitely not guilty.

2072
2:14:33 --> 2:14:40
In fact, she was killed. Both of them were killed by a mob who had held a very large loan out to

2073
2:14:40 --> 2:14:46
them and they weren't able to pay it back. So they were murdered for that mob action. I'd like to see

2074
2:14:46 --> 2:14:52
that evidence. And sure, if you want to get a hold of me. The reason I said he was guilty is because

2075
2:14:52 --> 2:15:00
I knew Celie Farber. You know, I know Celie Farber and she and I went down to LA. I drove her around

2076
2:15:00 --> 2:15:07
because I knew the area. She was going to interview him, OJ Simpson, about this thing.

2077
2:15:07 --> 2:15:16
And she's convinced he did it too. Well, he didn't and it was the mob and the people.

2078
2:15:16 --> 2:15:24
Let me just connect them all. Okay. So that happened to have been perpetrated by Bill Clinton,

2079
2:15:24 --> 2:15:31
who happens to be by bloodline a member of the Rockefeller family. The Rockefeller family is

2080
2:15:31 --> 2:15:38
behind the COVID hoax. They're behind the HIV hoax. They're behind the

2081
2:15:38 --> 2:15:41
pharma health industry all the way back to the early 1900s.

2082
2:15:41 --> 2:15:45
Well, the big ones, I think, are probably right. The big thing. It's OJ's thing, I doubt it.

2083
2:15:46 --> 2:15:51
Well, it's a quirky item, but that's why I brought it up because that's one I've been handed the

2084
2:15:51 --> 2:16:01
reality information. The hundreds of hoaxes of who killed JFK. That was LBJ and it was John D.

2085
2:16:01 --> 2:16:10
Rockefeller III. So my point in all of this is, you sort of wonder how did all these things happen?

2086
2:16:10 --> 2:16:16
All these, well, it's all a common cause. It's all connect the dots. It's all back to the Rockefeller

2087
2:16:16 --> 2:16:20
family. All right. So why was OJ Simpson involved in that?

2088
2:16:23 --> 2:16:33
So what happened was Bill Clinton needed something to take over the news chain.

2089
2:16:34 --> 2:16:40
And that trial lasted for nine months. And it was right while he was being impeached and

2090
2:16:40 --> 2:16:47
everything was going on with Monica Lewinsky. So that was all a frame up. I mean, where have you

2091
2:16:47 --> 2:16:53
ever seen trials that last that long? They intentionally made that trial last forever

2092
2:16:54 --> 2:16:57
as a diversion to what was going wrong with his presidency.

2093
2:16:58 --> 2:17:00
All right. Thank you. Let's get to it.

2094
2:17:00 --> 2:17:03
Why did OJ Simpson go along with it? Or you mean that he didn't go along with it?

2095
2:17:06 --> 2:17:09
What do you mean he went out? He defended himself as innocent.

2096
2:17:09 --> 2:17:13
Oh, I see. Why did they pick on him then?

2097
2:17:15 --> 2:17:21
He's a convenient, you know, it just, you know, that happened and they could use that as a diversion.

2098
2:17:21 --> 2:17:26
As soon as they spotted him, he became a huge patsy. He was a huge patsy.

2099
2:17:27 --> 2:17:31
Yeah. Okay. All right. Let's keep going. We're tight for time. We've got seven minutes to go

2100
2:17:31 --> 2:17:37
because the numbers here, Steven, are dropping. We've got 32 on the call. So Tom.

2101
2:17:37 --> 2:17:47
Tom. Okay. Thanks for the presentation. Yeah. I am Kui. JJ Kui does a lot of this biological

2102
2:17:47 --> 2:17:52
one-on-one kind of training and I pick up a little bit of, you know, my curiosity is,

2103
2:17:53 --> 2:17:59
you know, I'm trying to learn from you and kind of a neophyte in a lot of these areas, but

2104
2:18:00 --> 2:18:07
just the basic thing about the chromosomes and the X shape and then the X and the Y chromosome,

2105
2:18:07 --> 2:18:13
and then there's numbered chromosomes. You know, I find that interesting. And then there's the issue

2106
2:18:13 --> 2:18:23
of the DNA getting integrated, you know, the work by Kevin McKernan. So I'm hitting you just with a

2107
2:18:23 --> 2:18:33
bunch of different topics and you can comment on one or all or whatever. In your presentation,

2108
2:18:33 --> 2:18:41
there was a measurement that you used as a metric to determine, I think it was a DNA index or

2109
2:18:41 --> 2:18:47
something, the amount of, yeah, that seemed to be really fundamental. So I'm curious about how you

2110
2:18:47 --> 2:18:54
measured that. And as the cells divide, like one cell might have less chromatin, right? So,

2111
2:18:54 --> 2:19:00
and then the other has more. So that confuses me. It seems like the total, yeah, so let me see if

2112
2:19:00 --> 2:19:06
there's anything else. Oh yeah, your exponential functions and the math you did, that was kind of

2113
2:19:06 --> 2:19:13
interesting. And then maybe finishing up here, you said we all have this meme about the PCR being

2114
2:19:13 --> 2:19:20
faulty, but more people trust these grocery store lateral flow tests. And everyone knows,

2115
2:19:20 --> 2:19:28
I keep asking that question. Cui said, Cui has an answer, which is that had those tests existed back

2116
2:19:28 --> 2:19:34
in 2014, they would have had the same results. The background, you know, he has that whole argument

2117
2:19:34 --> 2:19:44
about the background noise and that those, so can you dismiss those tests as well? So yeah, those

2118
2:19:44 --> 2:19:52
are a few points. And that, well, maybe the last one is why do we have to have these chromosomes?

2119
2:19:52 --> 2:19:59
Is it just that the pack, if you concatenate all these base pairs at a certain point, you just need

2120
2:19:59 --> 2:20:05
to package them up in a chromosome. You know, what's, why did life do that? Oh man, we don't

2121
2:20:05 --> 2:20:17
have another two hours. Oh man, I don't know how to even respond to that. What's your number one

2122
2:20:17 --> 2:20:24
on top of the list? Well, yeah, to your presentation, then the DNA index and how you,

2123
2:20:24 --> 2:20:30
the DNA index. Yeah. It's easy. Okay. I got 10 fingers, you know, I got two hands,

2124
2:20:30 --> 2:20:43
a total of 10 fingers. And I define, I define my finger index, my normal finger index as 10

2125
2:20:43 --> 2:20:49
divided by 10. How many fingers do I have divided by the normal number? 10 divided by 10 is one.

2126
2:20:50 --> 2:20:57
Now I've been amputated, lost a finger. All right. Now I've got nine divided by 10. So the DNA index

2127
2:20:57 --> 2:21:08
is 0.9. You see, cause it got nine divided by 10 is 0.9. Okay. Now let's say some people are actually

2128
2:21:08 --> 2:21:15
born with more fingers than five. So now let's say I've got two little fingers or two thumbs

2129
2:21:15 --> 2:21:20
or whatever. Not let's say I've got three extra fingers. But okay, these are chromat,

2130
2:21:20 --> 2:21:27
are these chromosomes? Divided by 10, I have a finger index of 1.3. Now think of my fingers as

2131
2:21:27 --> 2:21:36
chromosomes. Right. So the big bundles of DNA. It's just a ratio. It's just a ratio of the number

2132
2:21:36 --> 2:21:42
of chromosomes present to the normal number of chromosomes. That's all it is.

2133
2:21:42 --> 2:21:52
Okay. And so going to the cancer cells are on average around 1.7. In other words,

2134
2:21:52 --> 2:21:58
they have roughly 70% more chromosomes, but it's very, very broad. You know, it's broad because

2135
2:21:58 --> 2:22:04
no two are alike, but they all over around 1.7. When one of those cancer cells that has an excess

2136
2:22:04 --> 2:22:11
number of chromosomes divides, it's another asymmetrical division, right? But because you

2137
2:22:11 --> 2:22:17
start from a, okay, you start from a big one, both pieces are still maybe greater than one.

2138
2:22:18 --> 2:22:25
Yeah. They never, yeah. They never, the thing is, is that the ones that have the fewer chromosomes,

2139
2:22:25 --> 2:22:30
you know, like, you know, always unbalanced. One will have more than the other. The one that

2140
2:22:30 --> 2:22:37
has more chromosomes has a survival advantage of the ones that have fewer. So there's a, there's

2141
2:22:37 --> 2:22:45
an advantage as an advantage. That's why the progression goes up. And that's why the 3.0 lived

2142
2:22:46 --> 2:22:56
maybe, right? That strange being. What was that again? There was a baby that was alive that

2143
2:22:56 --> 2:23:02
survived and wasn't that index like three or something? Oh yeah. Yeah. Yeah. Those are balanced.

2144
2:23:02 --> 2:23:08
Those are all balanced chromosomes. That's why it was a baby at all. So it had three copies

2145
2:23:08 --> 2:23:15
instead of two. And since it was balanced, that's why the cells were able to divide. And they kept

2146
2:23:15 --> 2:23:23
being balanced and they kept always being three copies instead of two. So that's not, that's not

2147
2:23:23 --> 2:23:32
aneuploid, but- No, aneuploid is unbalanced. Okay. That's called polyploid. Polyploid is if you have

2148
2:23:32 --> 2:23:37
more chromosomes than normal and that polyploid can either be aneuploid. In other words, they're

2149
2:23:37 --> 2:23:43
not balanced or they can be polyploid and balanced like the baby. If you have unbalanced chromosomes,

2150
2:23:43 --> 2:23:50
you get, you, except for like Down syndrome, you know, you, you can, you can be born and have

2151
2:23:50 --> 2:23:55
Down syndrome, but you know, they typically die in their fifties and they have lots of chance.

2152
2:23:56 --> 2:24:03
Try to be the last question. So the integration process wherein the plasmid, that's the other

2153
2:24:03 --> 2:24:10
issue, plasmid DNA and how the circular DNA compares to the chromosomal chromatin stuff.

2154
2:24:10 --> 2:24:18
But the integration process wherein the plasmids from the jab get integrated into the chromosome.

2155
2:24:18 --> 2:24:25
Can you discuss that a bit? And in terms of aneuploidy, it's irrelevant. In terms of it's

2156
2:24:25 --> 2:24:32
in the sense of the amount, the amounts are so small. The amounts of that are so small,

2157
2:24:32 --> 2:24:39
they're irrelevant. But if they may have a function where they, where they disturb normal operation

2158
2:24:39 --> 2:24:44
and they cause some sort of havoc, but it has nothing to do with their size. Like with the

2159
2:24:44 --> 2:24:51
aneuploidy thing, it has to do with the size of the genome. But you can go, go in and you can

2160
2:24:51 --> 2:25:00
disrupt, you can disrupt normal, normal genome by putting things in or changing their nucleotides,

2161
2:25:00 --> 2:25:05
like they do with those, those injections. You know, they forget, they take it, replace the

2162
2:25:05 --> 2:25:12
uracil or something else, or forget what it is. You know, and if you, a healthy cell would not,

2163
2:25:12 --> 2:25:16
could not survive with that substitution. But that's in the injections.

2164
2:25:18 --> 2:25:23
So you think they get cleaned up that Kevin McKernan stuff gets cleaned up pretty quickly?

2165
2:25:25 --> 2:25:32
I have no idea. I know what he did, but I don't know the details. That's not my field.

2166
2:25:32 --> 2:25:38
You know, they get down to the weeds and the minutia. I look at the big stuff.

2167
2:25:38 --> 2:25:41
All right. Thank you, Tom. Last question, Stephen.

2168
2:25:41 --> 2:25:48
Exactly, David. Well, actually, David, so, oh, you've disappeared now. You there?

2169
2:25:48 --> 2:25:52
He's there. He's there. He's doing something. Don't worry. He can hear you.

2170
2:25:52 --> 2:25:55
Oh, I did that by accident, I guess.

2171
2:25:55 --> 2:25:55
Oh, there you are.

2172
2:25:55 --> 2:25:57
So we lost you.

2173
2:25:57 --> 2:25:59
I'm back. I hadn't disappeared.

2174
2:25:59 --> 2:26:05
So David, you just said you like the big stuff and I'm exactly the same, but it's strange, you know.

2175
2:26:05 --> 2:26:12
So I've realised that not many people are like us who like the big picture, you know. So they have

2176
2:26:12 --> 2:26:17
all the information and they don't do anything with the information, it seems to me. And, and,

2177
2:26:17 --> 2:26:23
but you kind of assume that everybody thinks like you do, you're like we do, you know, and, but they

2178
2:26:23 --> 2:26:29
don't. And it seems to be quite rare that people want to join the dots of the information that they

2179
2:26:30 --> 2:26:36
have and then to seek other information. And I think that is your strength.

2180
2:26:36 --> 2:26:43
I'll tell you how I approach things. It has to do, a lot of it has to do with what we're confronted

2181
2:26:43 --> 2:26:51
with on a daily basis, all the way from school to jobs and everything. Scientists are like artists,

2182
2:26:52 --> 2:26:59
where you have this conception, you know, artists and scientists really start with the big thing,

2183
2:26:59 --> 2:27:05
the question. What is the question that you care about? It's usually trivial. I mean,

2184
2:27:05 --> 2:27:11
not trivial. If it's trivial, it's more engineering or technology. You know, it's how do I change this

2185
2:27:11 --> 2:27:16
to increase that twofold or whatever? You know, that's not science. Science is when you have a

2186
2:27:16 --> 2:27:21
question that nobody has an answer to and you're just driven by that question. The questions are

2187
2:27:21 --> 2:27:27
big. Then in the process of understanding it, you drill down and you know, you start with big and

2188
2:27:27 --> 2:27:33
then you go down into the details like I did with cancer. You know, I had this question about soon

2189
2:27:33 --> 2:27:39
as Peter Duesberg, he and I, we were at a coffee shop right before he went on the sabbatical in

2190
2:27:39 --> 2:27:45
1996 to Germany. We were talking about this aneuploid stuff and I had always been working

2191
2:27:45 --> 2:27:51
with single gene products, single enzymes, you know, for this disease or that disease or what are

2192
2:27:51 --> 2:27:56
making inhibitors for it. And then he was talking about all these chromosomes and everything. I was

2193
2:27:56 --> 2:28:03
saying, oh, jeez. And then I said, with cancer, I said, Peter, you mean it's just numbers? And he

2194
2:28:03 --> 2:28:11
said, yes. So then I started looking big, you know, about cancer, cancer big, aneuploid, then,

2195
2:28:11 --> 2:28:17
you know, then I get a big picture, big thing. Then I drill down on the details as my questions,

2196
2:28:18 --> 2:28:24
my focus was big, but my curiosity led me to sort of look at this detail, that detail, this detail,

2197
2:28:24 --> 2:28:28
for all of those little points and things that I were talking to you about, you know,

2198
2:28:29 --> 2:28:35
but most people in life think of it in school, your jobs or whatever, you're not allowed a big

2199
2:28:35 --> 2:28:41
picture. You're not even encouraged to have a big picture. Nobody respects the big picture, you know,

2200
2:28:41 --> 2:28:47
the details, you know, memorize this, do that, be able to calculate this, you know, and, you know,

2201
2:28:47 --> 2:28:50
you're not encouraged to look at the big stuff.

2202
2:28:52 --> 2:29:03
Exactly. So in the last five years, I've been really shocked as to what's happened on multiple

2203
2:29:03 --> 2:29:09
levels in many areas. And I wonder, what's the most shocked at whether you have been similarly

2204
2:29:09 --> 2:29:20
affected? And if so, was this last five years worse than the HIV AIDS era? And what's the most

2205
2:29:20 --> 2:29:23
shocking thing of all that's happened in the last 50 years? Say?

2206
2:29:24 --> 2:29:26
Most shocking thing? Well, what we're going through.

2207
2:29:26 --> 2:29:34
To you, to you. Not to you, not to what's happened to you, but to you, what is the most shocking

2208
2:29:34 --> 2:29:39
thing that's happened in the world in the last, in the scientific world or whatever in the last,

2209
2:29:39 --> 2:29:43
the fraud, if you like. Oh, oh, okay. Oh, I see what you're saying.

2210
2:29:43 --> 2:29:46
Oh, that's what you mean by shocking. I mean that, yeah.

2211
2:29:47 --> 2:29:49
Unacceptable. Correct.

2212
2:29:49 --> 2:29:53
Yeah, yeah, yeah. Okay. Oh, Lord. Anti-human, whatever.

2213
2:29:56 --> 2:30:01
God, I hadn't thought that way before. I can't answer your question.

2214
2:30:01 --> 2:30:05
For example, I don't think you were very impressed with the lockdowns,

2215
2:30:06 --> 2:30:12
you know, but also people talking about the science as if it never changes.

2216
2:30:12 --> 2:30:16
And there's no such thing as the science. Correct.

2217
2:30:16 --> 2:30:20
Yeah. So I just wonder, you know, sorry.

2218
2:30:25 --> 2:30:28
I know it's important to you, but I'm not getting it.

2219
2:30:28 --> 2:30:35
Oh, I understand. Yeah. So to me, I think the worst thing of all is the psychological torture,

2220
2:30:35 --> 2:30:38
deliberate psychological torture of human beings by their own governments.

2221
2:30:39 --> 2:30:47
It's outrageous. And the treason, the necessary treason. So yeah, I think it's just.

2222
2:30:47 --> 2:30:49
There's nothing new there, though. There's nothing new there. That's bad. I absolutely,

2223
2:30:49 --> 2:30:55
totally agree with you, but it's nothing new there. The scope, like World Wars and all that.

2224
2:30:56 --> 2:30:57
Oh, sure.

2225
2:30:57 --> 2:30:58
Racism.

2226
2:30:59 --> 2:31:05
But it completely blew my world apart. And I think it's blown many people's worlds

2227
2:31:05 --> 2:31:10
apart and they haven't recovered. No, you're right. I mean, look at my situation. You see,

2228
2:31:11 --> 2:31:17
I had my light bulb moment in 1985. You see, you never know when that light bulb moment's

2229
2:31:17 --> 2:31:22
going to happen. You're not looking for it. You know, other people are having it now.

2230
2:31:23 --> 2:31:30
They're a lot older, you know, and it's a thing that you can't forecast. It just happens,

2231
2:31:31 --> 2:31:33
you know, and you just have to be open to it.

2232
2:31:35 --> 2:31:38
Yeah. And once you've seen it, you can't unsee it.

2233
2:31:38 --> 2:31:44
That's right. And how do you respond? You see, so many people, professionals,

2234
2:31:45 --> 2:31:52
like other scientists and academics during the 80s, were confronted with what I was confronted with.

2235
2:31:53 --> 2:31:58
I knew there was a serious problem with the contagious HIV hypothesis in 1985. It didn't

2236
2:31:58 --> 2:32:03
make sense. But I didn't think it was a fraud or anything at that moment. You know, I just thought

2237
2:32:03 --> 2:32:10
well, they just got it wrong. Until I tried to discuss my reservations of problems with that

2238
2:32:10 --> 2:32:16
hypothesis with my colleagues at UCSF and UC Berkeley and places like that. They wouldn't talk

2239
2:32:16 --> 2:32:21
to me. You see, and that never happened before. You know, look how I love to talk.

2240
2:32:21 --> 2:32:27
Scientists used to love to talk, you know, and then when they stopped talking about something so big

2241
2:32:27 --> 2:32:32
and important, boy, that was a wake up call to me. There's something weird going on here. It's sick.

2242
2:32:33 --> 2:32:40
You know, and then that's what led me to delve into it. And I've been on that road ever since 1985.

2243
2:32:40 --> 2:32:47
Haven't gotten off of it. Good for you, David. It happens to most everybody at some point in

2244
2:32:47 --> 2:32:55
their life. It might be the last hour of their life. I don't know. So when you speak, David,

2245
2:32:55 --> 2:33:00
you have this great authenticity, which I think most human beings would recognize. And I don't

2246
2:33:00 --> 2:33:07
think many would disagree that, you know, I think it's very difficult for you. It would be very

2247
2:33:07 --> 2:33:12
difficult for you to lie, even if you were trying to lie. You know, you're just incapable of lying,

2248
2:33:12 --> 2:33:17
it seems to me. And so what you've said tonight, it just strikes me as so authentic and.

2249
2:33:18 --> 2:33:28
Yeah, there's so much more fun telling the truth. Absolutely. I mean, you know, it's just,

2250
2:33:28 --> 2:33:35
I don't know how you address that. I mean, people, it's funny if how open people are,

2251
2:33:35 --> 2:33:39
you know, when you're around people who are open, it's just sort of attracting, you know,

2252
2:33:39 --> 2:33:44
sort of attracted. And then you got the people that are closed up and tight. That's off putting.

2253
2:33:45 --> 2:33:49
Well, yeah, it's gas. Yeah, it feels like gaslighting when you're with them.

2254
2:33:50 --> 2:33:54
Anyway, thank you so much for David for coming on. And Charles, I don't know whether you want

2255
2:33:54 --> 2:34:00
to say anything. Thank you, David. Wonderful. We honor your great work. 40 years. May you keep

2256
2:34:00 --> 2:34:06
doing it for many years to come. And there are so we'll get this chat sent to you, but save the

2257
2:34:06 --> 2:34:11
chat as well, David, because it's a great conversation in there. And thank you, Stephen,

2258
2:34:11 --> 2:34:16
for organizing. Thank you, David. Thank you. I just I'd say one thing, David. I think that

2259
2:34:16 --> 2:34:23
Peter Duisburg, from the fact that he was so viciously attacked rather like an Andrew Wakefield,

2260
2:34:23 --> 2:34:28
you know, I think he was brilliant. I've never met the man, David, but I've just gathered that

2261
2:34:28 --> 2:34:34
he must have been brilliant. And obviously, you must be very, very talented. Otherwise,

2262
2:34:34 --> 2:34:40
you would not have been working with him. Yeah, well done to you. I'm just I consider myself

2263
2:34:40 --> 2:34:48
extremely lucky. All right. Yes, exactly. Thanks. Thank you, David. Thanks, everybody. Thank you so

2264
2:34:48 --> 2:34:55
much. Thank you. Bye bye. Don't forget to get it. Oh, it's gone now. Yeah. Oh, Charles,

2265
2:34:56 --> 2:34:59
Lee, can you leave it open for the election if people want to stay on?

2266
2:35:00 --> 2:35:04
No, there's only 25. Everyone's going, Stephen. Let them go to the Tom Rodman group,

2267
2:35:04 --> 2:35:08
and you should join the Tom Rodman group as well. You know how to do that?

2268
2:35:10 --> 2:35:16
No, I won't bother doing that. But anyway, I would have liked to keep it open so that people could

2269
2:35:16 --> 2:35:20
come back tomorrow as well. Charles, but you don't have to publish it, obviously.

2270
2:35:20 --> 2:35:26
Well, I'm going to stop this recording now. So, Pinter keeps