The Skeptics Guide #1057 - Oct 11 2025

You're listening to the Skeptic's Guide to the Universe, your escape to reality.

Hello, and welcome to The Skeptics Guide to the Universe.

Today is Thursday, October 9th, 2025, and this is your host, Stephen Novella.

Joining me this week are Bob Novella.

Hey, everybody.

Kara Santa Maria.

Howdy.

And Jay Novella.

Hey, guys.

Evan is in phase two of Tax Hell.

He has the late deadline in mid-October, so he's doing

it.

Which, like, let's be honest, I think they just furloughed, like, half the IRS staff.

Well, yeah.

No, it's true.

IRS is

woefully understaffed now.

It's correct.

It's crazy.

Yeah, so he's doing that.

So you might notice we've started recording on Thursday instead of Wednesdays.

This is, I think, the second week we're doing that.

This is going to be our new normal.

And it's just a scheduling thing, mainly because Kara is starting a new job, and Thursday is going to be a lot easier for her than Wednesday.

Yeah, and I'm three hours behind you guys.

Yeah.

So it's different.

We're recording in the afternoon instead of the evening.

So So Jay's awake, right, Jay?

Yeah, I mean, we go till like 10:30 at night.

A lot of times at Eastern time.

And I'm just, you know, a million times sharper at one in the afternoon.

I love, too, that you guys are like, we're recording in the afternoon.

I'm like, it's 9 a.m.

Just have my.

Are you a morning person or an evening person, Kara?

I, well, I used to be an evening person.

I still am technically an evening person, but we've talked about this before.

Because I have a sleep disorder that makes me a very sleepy girl, I take this really intense intense medication and now I just wake up in the morning.

It's like the minute that the meds are done doing their thing, I'm just awake.

So that's how they work.

It's amazing.

Yeah.

So I wouldn't still call myself a morning person, but I'm much more of one than I ever was before.

I'm solidly a morning person.

You just like decline like this.

Well, I'm just very alert in the morning.

I get to do a lot of work.

Basically, from like 6 a.m.

to 2 o'clock in the afternoon is sort of my most productive hours.

And then I can function in the evening, but I get progressively sleepy in the evening.

Yeah.

Yeah.

I'd say I have more physical energy in the morning, so that's when I love to go to the gym.

That's when I love to

run errands.

And then I have a gym in the morning.

Yeah, and then I have

more mental energy at night.

I love staying up late to write or to read or to work on crafts.

Yeah, I can go to bed at 1 a.m.

No problem.

I don't do it as much as I used to, but midnight to me is just like 12:30.

I'll be like, yeah, I'll go up.

It's 12:30.

Yeah, I'm exactly the same way.

I usually wake up between 8 and 9.

I guess that's going to change when I start seeing patients again.

When I was working, I would wake up at 6 pretty much every morning or a little bit before.

Now my retirement time, I wake up at 7.

It's not much different.

It's just I can linger in bed until about 7.

Does your wife get up at the same time or do you always get up before her?

I always get up before her.

Even when she's working, because she works in the evening.

She teaches it.

Right.

She has evening classes.

She has meetings and stuff during the day, but she's rarely she's pressured to get up early in the morning.

So I generally wake up before she does.

Ah, what a life.

I love it.

So you guys know what time of year it is again.

Yes.

It is Halloween time.

Wait, no?

Nobel Prize time.

Oh, that's too.

That too.

But before we get to that, I have a quickie for you guys.

Just because this is, we can't pass this by.

I would absolutely be reporting on this if it weren't Nobel Prize week.

So we're just going to do a quick hit.

Researchers have implanted the first pig-to-human liver xenotransplant.

What?

So we've been talking about this for a while, this whole idea of where do you source organ transplants from and what's the wave of the future.

And I do think this is the most promising way.

So this is a pig, was the donor, and it was genetically modified.

They made 10 gene edits.

So xenoantigen knockouts, right?

So taking out genes for antigens that would activate the human immune system, and also human transgenes, putting in human genes for two basic reasons.

One is immunity, right?

Immune compatibility, and the other one is unique to the liver.

It is coagulation compatibility.

So, the liver, you may not realize this, right?

The liver is the biochemical factory of the body.

It detoxifies anything you eat, right?

There's always a first pass through the liver.

It doesn't do everything, but that's, you know, anything it can detoxify gets done through the liver.

The liver also does your glucose management, right, stores your glycogen and does that.

And the liver also produces your coagulation factors.

And so, and that's a complicated, what we call coagulation cascade, right?

So there's a complicated set of enzymes and proteins that are made in the liver that have to do with clotting your blood.

So that has to be compatible too.

This is what makes liver, xeno-liver transplants so challenging is because

it's not just the immune compatibility, you need the biochemical compatibility as well, right?

The pig liver has to do all the things that a human liver would do in the way that a human liver does.

And the big issue there is the coagulation compatibility.

So having said all that, this was done in China.

The recipient was a 71-year-old man with hepatitis B related cirrhosis and hepatocellular carcinoma.

He was not eligible for a resection or a liver transplant.

So they did this xeno,

it's called an auxiliary graft, which I mean, I think just means it did not replace the liver.

They just put it there in addition to the liver.

And he survived for 171 days, which is

a long time, right?

I mean, it's obviously not a cure, but that's for this technology.

That's pretty good.

And the big problem was

not rejection, it was the coagulation.

He eventually died of GI bleeds.

That's what I was doing.

So this still isn't where it needs to be.

It's still not where it needs to be.

Exactly.

So, I mean, 171 days is good, but that they have not dialed in all the changes they need to make yet in order to make this function.

So, I mean, obviously, this is a patient who, given his liver failure and his

liver cancer,

had a very short life expectancy anyway.

So, that's why you're able to do this kind of experimental treatment in somebody like that.

But this is a solid advance.

This is a solid step forward.

And we are seeing more of this, the xenotransplant from genetically modified, mostly pigs, at this point.

Remember, we talked about lung.

They're working on cardiac.

Cardiac is probably the easiest because it's just a pump.

There are some challenges with the lung lung because it does have a lot of immune function as well.

And it's challenging with the liver because of the biochemical compatibility.

I think pancreas is probably on the short list.

That could be like a cure for some types of diabetes.

And kidney, kidney is a filter.

That should be pretty easy to make compatible, more so than the liver or the lungs, which I think are going to be the real challenging ones.

If you guys are interested in reading about kind of what's on the horizon and in a really fun way, I highly recommend Mary Roach's new book, Irreplaceable You, because she talks about this in depth in it.

I had her on my podcast a couple of weeks ago.

Weeks ago.

Yeah, yeah, yeah.

And the book's fascinating.

It like just came out.

Awesome.

All right.

Now it's time to get to our Nobel Prizes.

Kara, you're going to start us off with physiology or medicine.

This year's Nobel Prize in Physiology or Medicine was awarded to Mary E.

Brunco from the Institute for Systems Biology in Seattle, Fred Ramsdell from Sonoma Biotherapeutics in San Francisco, and Shimon Sakaguchi from Osaka University.

They were awarded jointly the Nobel Prize in Physiology or Medicine, quote, for their discoveries concerning peripheral immune tolerance.

The kind of long and short of it is they discovered how the immune system is kept in check by a whole second system that a lot of people believed either wasn't there or they just didn't really, they were really skeptical about how it might work.

And so this is one of those stories of decades of research.

And I love this kind of science because it's like, this is how we know what we know.

But before I tell you more about their discoveries, I wanted to tell you like a kind of fun fact about how they were told that they received the Nobel Prize.

So the Nobel Prize Committee, they put, or Nobelprize.org, they do these great videos.

I don't know if you guys have seen them on YouTube, where they have an animation of the person who won, and then they have a phone call with somebody from NobelPrize.org talking to them about how they first found out.

And usually it's either a phone call or somehow it gets, I don't know, somebody finds out and tells them.

But my favorite is that Fred Ramsdell, he was hiking with his wife up near Yellowstone and didn't have service for days after they were released.

And so he only just found out about this.

Like the whole world knew before him, which I thought was absolutely hilarious.

And I don't know if you guys follow on Instagram, but one of my favorite accounts, Dr.

Lucky Tram, he's a science communicator.

He shared this like headline that says, Nobel Committee unable to reach prize winner who is quote living his best life hiking off grid.

So anyway, let's get into how they discovered this.

Okay, we know that there are T cells and B cells that help us

when we have a pathogen that enters our body and our immune system attacks those pathogens.

What the researchers in this year's Physiology or Medicine Prize, what they did is they really identified, I don't like to say discovered because we kind of knew the cells were there, but they identified these specific types of cells called regulatory T cells, which are really important for peripheral immune tolerance.

So let's kind of back up a little bit.

I mentioned we have T cells and B cells.

This year's prize really focuses on T cells, so that's what we're going to focus on.

But B cells have somewhat similar functions.

So there are T cells that are always patrolling the body and that sort of send downstream signals that say we need to attack when there's

a pathogen that enters the body, a virus, you know, bacteria, anything like that.

And then there's other types of T cells that actually bind to those cells and eradicate them.

So they attack body cells that have been infected.

And sometimes they also attack tumor cells, but sometimes they don't know to attack tumor cells.

All T cells have T cell receptors, right?

So they're these little things on the surface of the cells that understand or that recognize different pathogens.

And for a long time, there was a sort of one gene to one pathogen hypothesis.

And researchers quickly realize that there's just not enough actual DNA.

There's not enough coding regions of the DNA to have all the genes we would need to map for all the different pathogens that we are

exposed to.

So really, researchers a while back realized that a bunch of genes are randomly combined in different orders to come up with these special T cell receptors.

And the I think the number now is that there's possibly like 10 to the 15 different types of T cell receptors.

We're always able to recognize new pathogens.

It's basically everything.

Exactly.

Like we can combine our genes.

The genes can combine in such a way to produce new

receptors for anything that comes into the body.

And obviously, we don't recognize it at the beginning, and then we mount a stronger response.

We know that T cells are matured in the thymus, right?

Which is an endocrine organ in our body.

And

what sometimes happens is that a T cell that should be recognizing a pathogen actually attacks our own body cells.

We know this happens because people have autoimmune disease.

The thymus has this really cool system that helps it identify endogenous proteins, so the body's own cells, so that our T cells don't attack our own cells.

Basically, the thymus, there are cells in the thymus that have have endogenous protein fragments that they attach to, so that when the T cells are first matured, they sort of test them out and they say, Do you bind to me?

And if they bind to them, they go, Nope, you don't pass this test.

We're going to destroy you.

We're not going to release you into the body to go patrol viruses and protein, viruses, and bacteria because you're very likely going to attack body cells.

And that's not, no, no, no, we don't want that.

Yeah, so it's negative selection.

We make antibiotics against everything and then select out the self.

Exactly.

And so that is that central process that we talked about, right?

That is, these are the patrollers that are doing central immune tolerance.

After we discovered this, researchers said, okay,

probably there are also some that sort of are patrolled after this thymus test.

And a bunch of researchers started to do research in this field, and they very quickly made a bunch of discoveries.

But the problem was they made pretty big claims.

And And this happens, we see this a lot in the history of science, where big claims are made or, you know,

what we know is stated, but then, okay, but that means, you know, X means Y and Y doesn't pan out.

And so what ended up happening with this field of peripheral immune tolerance is that it sort of died because so many people made such big claims that they couldn't replicate that a bunch of researchers became really skeptical of the entire idea.

So Shimon Sakaguchi, who at the time was in the Aichi Cancer Center Research Institute in Nagoya, he was like, no, no, no, I still think there's something going on here, and this is why.

He did this really interesting experiment where they've removed the thymus altogether from newborn mice.

And they were like, okay, these mice are probably going to just make fewer T cells and their immune systems won't be good, right?

So they'll just get infections and they'll die.

But they found that if they removed it like three days or later after the mice were born, the opposite happened.

Their immune systems went haywire.

They were way too strong and they started attacking the mice's healthy cells.

They got this range of autoimmune diseases and they often died from that.

And so he was like, okay, this is interesting.

And it tells me that something is happening beyond this.

So he devised these cool experiments where he took these mice where the thymus had been removed that had an overactive immune system and he injected mature T cells from a healthy donor from a mouse that had a thymus intact and he found that they were protected.

So he was able to put mature T cells in after the fact and they were tested.

So what were these cells that he was putting in?

He knew they were mature T cells, but nobody knew what types they were.

So he was able to recognize that and maybe this requires going back, but remember how I said that they're the petrolling T cells, those have a protein called C D D4, and killer T cells, the ones that actually do the attacking, they have a protein on them called C D 8.

Well, he identified a protein called C D 25,

and he found that those patrolling T cells, they had both C D4 and C D 25

on their surface.

And he realized that if he added the C D 25 cells to the C D4 cells that were already in existence in the ultra kind of immune angry, you know, the hyperactive immune system cells, that's when they got healthy again.

So there was something about these C D25 receptors that was preventing these mice from attacking their own tissues.

And this was not only happening in the thymus, it was happening in somewhere in the periphery.

And so he was able to identify this new class of T cells.

They called them regulatory T cells.

And then this research sort of continued.

Okay, so here's where the story switches over to the other two researchers.

So now cut to a little bit later.

This was in the 90s that this research was happening.

So now we're going to cut to research that continued into the early 2000s.

At the time, Brunco and Ramsdell, Bronco, just to, as an aside, it's important to remember that

she is,

whoa,

only the 13th woman to have been awarded the Nobel Prize in Physiology or Medicine, only the 66th woman overall to receive the Nobel Prize.

So we're talking teeny, tiny percentages there.

So at the time, Bronco and Ramsdell were working together.

They were in a lab, they were at a biotech company called Celltech Chiroscience in Bothel, Washington.

They were really interested in the specific mutation called the scurfy mutation.

Scurfy.

They were using a model organism.

It was a mouse that was developed actually out of the Manhattan Project research.

So they were interested in how radiation sickness caused autoimmune problems.

So some of these mice that had this genetic mutation were born with scaly and flaky skin, large spleens, large lymph glands.

They lived for only a few weeks and they just were unhealthy.

And they were only male.

So people realized, researchers realized this had to be an X-link chromosome.

So only male mice got it because when female mice had the two X chromosomes, one of them could be healthy, but men, of course, or male mice, of course, only had one X chromosome.

And so if they carried the gene at all, they got really sick and they died.

So they started to go, like, okay, what's going on with these mice?

Why are they so sick?

And they realized that that these T cells were attacking the tissues of these mice.

So, Bronco and Ramsdell, this is where they enter because that was known.

They were like, okay, what's going on with these scurfy mice?

What is the mechanism underlying their disease?

Like, really?

Like, we know it's something with the T cells, but we want to understand exactly where on the genome this mutation is occurring.

And we've got to remember that this was before any of the modern technology that we have.

So, they had to do all of this kind of coding manually.

In order to understand where this gene was, they had to dig through like 170 million base pair nucleotides.

to figure this out.

It was bananas.

So they narrowed it down to about 500,000 nucleotides.

They mapped that whole area of the X chromosome, and they ultimately narrowed it down to 20 different potential genes.

And don't you love this?

Like your keys are always in the last place you look.

They looked through 20 genes and they found the mutation on the 20th one.

Oh my god.

Classic.

Yeah, it was a lot of work.

Let's have heard them when they found it on the 20th.

Yeah, serious.

A few curse words.

Probably, yeah, more than a few.

So they find this Scurfy mutation and they name it FOXP3 because it was similar to previously identified genes called forkhead box genes.

So they called them FOX genes.

So FOXP3,

they found, here's a kind of an interesting aside, but also very important

for their prize.

They realized that there was a human variant that was very similar to SCURFI in presentation, but they weren't sure if it was genetically similar.

But once they did this research, they realized the human equivalent of FOXP3 was responsible for a rare genetic disease called Ipex syndrome, which is immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome.

So this is an inherited immunodeficiency where, again, only male individuals develop early-onset autoimmune disease that's just really intense.

It presents with diabetes, enteropathy, so attack on the GI tract and a lot of kind of gut issues, rashes like eczema and psoriasis, and thyroid disease.

And these children often die very, very young.

So they were able to identify the actual gene responsible, which we now know with the tools that we have, we can start solving these problems where there's a specific genetic mutation.

Aaron Trevor Brandon, there is a clinical trial underway using CRISPR to treat iPads.

Amazing.

Yeah, amazing.

And so not only did they identify that, but they were able to basically look at the research that was previously done, you know, across the board, all the research that was done, but also the research that was done in Japan.

And everybody now was able to say, I mean, it wasn't just Shimon Sakaguchi at this point, but because he had done all of the work leading up to it, he was able to take that discovery of the FOXP3 gene and say, wait, that is what is actually controlling the development of those regulatory T cells that I identified.

So, I was able to find their function through these really interesting experimental techniques.

Now that I know where the gene is that controls it, we can, you know, do a lot of interesting things.

We can knock it out, we can boost it, we can, you know, try and understand exactly what's happening.

And so, all of this research together tells the story of this secondary immune tolerance, peripheral immune tolerance.

So, not just this pathway that occurs within the thymus, where the cells that are attacking healthy body tissue are sort of knocked out, but this whole secondary pathway where our body recognizes cells that attack healthy body tissue and potentially either gets rid of them or

weakens them.

Like there are so many different things we can do with autoimmune disease, right?

So, let's say, for example, that there's a disease where the body's own immune system is in hyperdrive, an autoimmune disease.

Like I have an autoimmune disease.

I have psoriasis.

That's my own body attacking my skin cells.

And it causes these like, you know, scaly patches.

And I have to take medicine for that in order to not have these patches on my elbows.

Some people have it severely over their whole body.

And there are a ton of autoimmune diseases.

If we can dial down those regulatory T cells so that they're not attacking healthy disease, or we can knock them out altogether, that would prevent autoimmune disease.

On the flip side of that, cancer cells, tumors, are especially good at recruiting.

Oh, no, they just recruit the T cells themselves.

Yeah, the T regulatory cells.

To suppress, to protect themselves from the immune system.

Exactly.

So they recruit the cells themselves.

And again, these T regulatory cells, this whole system, are what was discovered or at least identified by the people who, the three individuals who won the Nobel Prize.

So, tumor cells are really good.

That's how they're able to cloak themselves within the body, right?

They're able to say, like, we're just healthy body tissue, don't attack us, and then they grow and grow and grow.

And so, there's so much potential therapeutic benefit of continuing to develop drugs or treatments for these regulatory T cells to maybe be suppressed or turned off in the presence of tumors.

And we actually do have some pilot studies on that where patients are getting interleukin-2.

Interleukin-2 makes regulatory T cells thrive, so that's helping with the autoimmune disease and possibly even organ rejection after transplantation.

But then, as I mentioned, when it comes to the tumors, some researchers are like modifying the T cells, adding different antibodies on their surface so that they can be better recognized, or they can send out these sort of T cells to transplanted liver or kidney to help take care of of them.

And of course, dialing it down instead of, or sorry, dialing it up instead of down in cancer, in tumor biology, it would be a whole other application and probably so many more that we haven't even thought about.

So, once again, congratulations to doctors Mary E.

Bruckno from Seattle, or who is in Seattle now, Fred Ramsdell in San Francisco, and Shimon Sakaguchi in Osaka for their discoveries concerning peripheral immune tolerance.

It's another example also of how international, like global collaboration is involved in modern scientific research.

Like whenever you read about any of these Nobel Prizes, but also just any story like this, it's always multiple labs in different countries contributing different components to how things

unravel.

Yeah, which has

almost without fail.

I mean, that's what I'm constantly reading.

Multinational groups of researchers and labs.

And oh my gosh.

If you're doing research at at this level, it's like almost unavoidable.

It's like you have to.

And that not only has implications just for better science happening globally, but also it does have diplomatic implications.

Like science diplomacy is so important because we see this all the time where countries that are having geopolitical conflicts still come together with their scientific collaborators.

And yes.

The Trump administration just canceled all NIH subgrants to international collaborators.

Yeah, because it's like he wants us to be an island.

It's so short-sighted.

When you're an island, everything gets weird, as we know, from an evolutionary perspective, but also, yeah, from a collaborative perspective.

Like, our science is going to wither.

It's not going to grow if we cut ourselves off from the rest of the world.

All right, Bob,

you're going to go on and tell us about the prize in physics.

Yes, sir.

This year's Nobel Prize in Physics went to researchers who showed that the bizarre laws of quantum mechanics that I love so much don't quit when things get big.

Two Hallmark quantum effects, tunneling and energy quantization, show up even in macroscopic circuits that you can literally see.

This year's prize went to John Clark, Michael Dvore, and John Martinez for their foundational work in 1984 and 1985.

And that's right around the time, if you remember, right around the time that the mind flare was terrorizing those poor kids from Stranger Things, right?

Sorry, I've just, I've been bitching that show.

John Clark was professor of physics at the University of California, Berkeley at the time.

Now he's a professor emeritus at the university's graduate school.

Devore and Martinez are both professors of physics at the University of California, Santa Barbara.

If you're rusty, I haven't talked about it in a little while, quantum mechanics describes that counterintuitive and famously weird behavior of microscopic objects like atoms and electrons.

That weirdness of the quantum realm is not visible in the macroscopic world that we inhabit.

Those effects are still there, though, but they just kind of get averaged out by all the trillions of interactions that are happening in these huge, messy systems.

Like even like relativistic effects, the time that your head feels compared to the time that your feet are experiencing are slightly different, but it's so small, not even notice it.

So, what these guys did back in the 80s was to create electronic circuits made of superconducting loops where there's no resistance to flow.

Now within these circuits, they saw these two iconic quantum phenomena.

The first was quantum tunneling.

We've talked about that a little bit before.

This happens when a particle appears to move through a barrier, like an energy barrier, even when it doesn't have enough energy to do so.

I came across a theoretical physicist Stephen Gervin's take on this.

He likens this to, he uses an analogy comparing quantum tunneling to a car in neutral.

So imagine you're in neutral and you're approaching a hill.

If you don't have enough energy, you're not going to make it over that hill.

You just go up a bit, right?

And then you just kind of slow down, stop, and head back down.

Imagine that this is the case, but you still make it to the other side using this process called quantum tunneling.

It's about the analogy is there's a tunnel going through the hill rather than having to go all the way over the top of it.

I guess.

Yeah, yeah, you could, yeah, think of it that way, but it's just, yeah, but it's a metaphor, right?

We're not saying that that's what's actually happening, but it's just right, right.

You could think of it, yeah, think of it that way.

If you're interested in that, please read it, you know, go go online.

There's billions of websites talking about it, lots of ways to actually approach these topics.

Now, this has been shown to exist in the micro world, and it's actually so important that stars could not shine without engaging in quantum tunneling.

And many of the technologies that we use today just wouldn't happen

without this effect.

So, yeah, it's there, and it's critically important to life as we know it.

But quantum tunneling was never seen in the macro world in the way that Clark and Devore did in their experiment.

Now they did it specifically in this case by adding these what they call

Josephson junctions in their circuits, like an insulator that require tunneling to get past.

So that's how they kind of, that's what they did to the circuits to spot this.

The second quantum behavior was mainly fleshed out by Martinez.

This behavior is referred to as the quantization of energy.

It refers to the fact that subatomic particles can only gain or lose energy in fixed discrete amounts, right?

You guys have heard of that before.

In our world, energy is generally comparable to, say, a dial that can be turned by any amount, no matter how small.

It's continuous.

The quantum realm, however, only deals in very specific energies, more akin to a channel selector than a continuous dial.

So you can think of it that way.

Now, this was shown to happen in these large circuits by sending microwave photons into them and seeing how that energy was absorbed.

Specifically, they were looking at the absorption spectrum.

They saw that the energy was absorbed only at very specific frequencies.

And these frequencies were specifically predicted by theory, but it also had the bonus of actually being solid proof that even these large-scale circuits were experiencing this quantum energy quantization that we see in the quantum realm all the time, but not in

the macro scale world that we live in day to day.

All right, to sum up here,

what these researchers proved is that quantum behaviors can happen in things that are large enough for us to see.

It's not a phenomenon only for individual atoms or or particles.

In a real sense, these large circuits as a whole were behaving like atom-sized objects.

That means that the laws of quantum mechanics can also apply to macroscopic technologies.

That's the key right there.

But also, these weren't just some cool but obscure experiments that happened decades ago.

These discoveries that these gentlemen made, this was the foundation of a host of technologies that turned quantum physics essentially into engineering, right?

Allowing the creation of devices that were practical and controllable.

So this includes some things you might probably predict.

This includes some modern quantum computer platforms that are out there today, made by, I think it was like Google and IBM, but there's also quantum sensors and there's quantum amplifiers.

And also there's, I think, even newer than those things, there's these super precise measuring technologies like superconducting gravimeters.

And the list goes on and on, all essentially flowing from

this foundational research from decades ago.

So, who knows?

And also, I'd love to extrapolate a bit into the future.

So, who knows what amazing technology in the future can be traced back to this research from the time of the mind flayer in the 1980s?

Nice.

Yeah, that was

so many layers to this.

Yeah,

with quantum mechanics.

Yeah, I'm sorry.

Oh my gosh.

Yeah, it's nasty to cover because there's so many, like, well, you can't say that because that's misleading.

And no, that creates a mental image that's probably a minefield of

minefield is a great way to describe it.

All right, let's finish up with the Nobel Prize in Chemistry.

This one goes to, again, three researchers.

Susumu Kirigawa from Kyoto, Japan, Richard Robson from the University of Melbourne in Australia, and Omar Yagi from the University of California at Berkeley in the USA.

So again, international researchers contributing to this story.

And this has to do with something called metal organic frameworks, which we have definitely talked about on the show previously.

But I'm going to go back to 1974, is where, at least conceptually, this all begins.

But I'm going to first, Bob, ask you a question.

Do you remember back in high school when you and I believe it was Aaron, but you and somebody else got caught red-handed by Mr.

Koshan playing catch with those molecule models in the chemistry classroom?

Absolutely.

Right.

And I haven't thought about that in probably two decades, so thank you for that.

I remember that.

That guy had radar.

He did.

He had absolute radar.

Now, I was an innocent bystander because I had nothing to do with this, but Bob was my ride home.

And so I had to stay behind and help you reorganize all the drawers of rubber stoppers before we could go home as punishment.

Do you remember that?

I do.

Wow.

The rubber stopper thing was even more deeply buried than the throwing around the atoms and molecules.

Wow.

So I was reminded of that because this story begins with Robson, who in 1974 also was playing with these

model molecules, but that set him on a pathway not to reorganizing the rubber stopper drawers in the chemistry classroom, but the Nobel Prize.

Oh, if only we could have trembled that same path, Steve.

So, yeah, so

as a teacher back in the day, he would use, you know, but like the wooden ball and dowel kind of models that you build atoms out of.

And he would have to have the wood shop drill the holes in the wooden balls, and he had to tell them the specific angle at which to drill those holes, because that's the angle of the bonds

that those atoms make.

Accurate.

Yeah,

and then he realized that once you do that, like once you put the bonds at the correct angles, the molecules sort of automatically build themselves in the correct way, right?

The structure of the molecules sort of are automatic because it's built into how many bonds does like a carbon atom make and what angle are those bonds at, etc.

So he's like, huh, that's interesting.

I wonder if there's something there.

Ten years later, right, this idea percolates with him for 10 years.

Every year he's teaching his class, like looking at these chemical models, like there's something here.

And what he thought of is, I wonder if we can take this up one hierarchical level.

If the structure, right, the structure, three-dimensional structure of these molecules derives from the types of bonds that these atoms make,

I wonder if we could use bigger molecules to do the same thing, right?

So essentially, if you have a molecule that also has specific binding sites, could you use it kind of like a tinker toy to build bigger structures out of?

And so he combined copper ions.

Also, copper ions

like to make four bonds, right?

And he combined that with a four-armed

organic molecule.

Don't worry about what the long name is.

So then you have also a very similar tetrahedral type of structure, right?

For D and D players, it's like a D4, right?

So

and with four, the copper ions each able to make a bond.

And he's like, duh, this should behave kind of like a carbon atom, this giant molecule, right?

So he tried to build these bigger structures out of it, and it basically worked the exact same way.

He could build these larger structures out of

these metal organic sort of compounds that he had made.

Again, kind of like a chemistry tinker toy set.

Interestingly, because these were so big, the structure contained these large cavities.

If you could imagine that, like these are big molecules, you stick them together and it forms this bigger structure, but there's big voids, there's big empty areas in the structure, just because of the gangly molecules that you're connecting together.

So then he further thought, huh, I wonder what we could do with this, right?

So, how what kind of function would this serve?

Again, initially, he just wanted to see if he could do it.

But he started to play around with different structures to see if he could get them to do different things.

And he realized one thing is that that gas could flow into and out of these voids.

And you could also fill them with different kinds of ions.

And maybe they could serve as sort of a catalyst to drive chemical reactions.

And he started playing around building different structures that would do different things.

But there was a big problem with this technology.

And that is these structures were fragile.

They were not resilient, they would break down very quickly, and they could not resist high temperatures, and so they just weren't very practical or useful because of that.

They just weren't stable enough.

So now enter Kirigawa and Yagi.

They were not working together, they were working completely independently, right?

But they were sort of picking up from Robson's basic building blocks idea and experimenting with different ways of, again, not necessarily with any outcome in mind.

In fact, Kirigawa has a famous quote about the usefulness of useless, right?

Things which seem to be useless can turn out to have incredibly useful applications.

So you just never know.

So just following

your interest and the kind of just thinking outside the box and saying, ah, this is interesting.

I wonder if this would work, you know, and then worry about applications later yields incredibly useful things.

The quick version is that Kirigawa and Yagi, independently experimenting with this organic metal combination, these meta-structures that you're making using big molecules as building blocks, were able to make much more versions of them and found out how to make them much more stable.

And I think it was Yagi, in fact, in one of his papers that coined the term metal-organic framework for these kinds of structures.

That's basically the story.

At the end of the day, these three people were critical for the development of this chemistry technology of

developing these metal-organic frameworks, making them more stable, but also making them more flexible.

The reporting on this brings up the point that there were already other kinds of technologies like silicon dioxide and zeolites, right?

That where you could have similar functions.

So there wasn't a lot of interest in these early on.

It's like, eh, we can already do that with these other things.

These are fragile.

Who cares, right?

But the researchers kept pushing and they found out that, well, first of all, we can make them stable.

And secondly, we could make them do something that the zeolites can't do, and that is that they're flexible.

And what that means is they can change shape from when they're empty of stuff, whether it's a gas or other chemicals or whatever, to when they're full.

And that just expands the number of potential applications that they could potentially be used for.

So fast forward to today, where are we?

There are literally tens of thousands of metal organic frameworks that have been created.

And they have a wide range of potential applications.

We talked recently about harvesting water from the air in deserts.

Those are metal organic frameworks.

There's a lot of research looking at pulling carbon dioxide out of the air, right?

Carbon capture.

Those are metal organic frameworks.

Oh, cool.

There's a lot of metal organic frameworks that are

catalysts.

They make, because you're bringing different molecules together, you could then catalyze reactions.

You could make them happen more quickly.

The thing about the metal organic frameworks, and it's a framework, they're essentially programmable in a way.

Like you can design

the structure so that the voids are specific to whatever kind of molecules you want to fill them.

And now, with artificial intelligence, they can explore the potential design space of millions of metal-organic frameworks and say, yeah, find one for me that does this.

So, I think we're sort of poised for this technology to take off more.

One specific thing I thought of was: can this be used as a hydrogen storage medium?

No.

Right?

Because we're desperately looking for something that would store hydrogen.

And the short answer is it is being researched.

It is being researched, but it's not very promising.

And the reason for that is volumetrics.

Is that while

you can make metal-organic frameworks that store hydrogen, and they can be very mass efficient, have a low mass for the amount of hydrogen that you're storing.

They don't compress the hydrogen very well.

So they take up a lot of volume.

So that may be useful in some contexts, like any static storage need,

but wouldn't be good in a hydrogen fuel cell car.

You need to keep the weight and the volume under control for your hydrogen storage.

Doesn't mean that they won't eventually crack this problem, but that's where it is right now.

There's some major challenges.

So that's probably not going to be an early and maybe even a never application for MOFs, but there's so many other ones.

So this is just one of those, again, those technologies that facilitate other technologies.

It's also, this is the technology that's often behind the news item, right?

Like we were talking about the harvesting water from the air.

The technology behind that is the metal organic frameworks.

So keep your eye on this.

This will keep popping up in a lot of the news items that we talk about.

Cool, man.

All right.

I think there's three awesome Nobel Prizes for this year in the sciences.

And like is often the case with the Nobel,

I guess, announcements, when you first read it, you're like,

oh.

And then you dig into it and you're like, whoa,

this is such a big deal.

Yeah, absolutely.

All right, we have one non-Nobel news item.

Jay, tell us about some recent discoveries with long COVID.

Yeah, so many people with long COVID report this brain fog thing.

I mean, I think it's been in the news a lot.

It's definitely a term that has gotten out there.

A lot of people know about it.

But, you know, is it legitimate?

You know, what could potentially be causing it?

So a research team in Japan asked those questions.

You know, is there a measurable change in the brain chemistry that lines up with those that think they have these problems?

So they did.

They looked into it and they used a brain scan that can see one kind of communication receptor on neurons, and it's called the AMPA receptor.

Think of these receptors as tiny volume knobs that help neurons pass signals.

So the team scanned 30 adults that claimed to have long COVID symptoms who had ongoing cognitive complaints.

And what they did was they compared them with 80 healthy volunteers from a previous data set.

So

what they found on average was that people with long COVID showed a stronger AMPA signal across large parts of their brain.

And in simple terms, more of those volume knobs were visible on neuron surfaces.

They measured the test subjects' brains with a PET scan, and the tracer that they used, right, this is the thing that they typically will inject into somebody that will stick to the things that they're looking for, and they're able to locate that them sticking onto whatever it is they're looking for.

So, in this case, they want to find the receptors.

So, they used something called carbon-11K2, and this binds to the AMPA receptors.

And after the injection, the researchers were able to collect images during a 30 to 50-minute window.

I guess that's how long it was able to be traced.

And then they calculated a standard ratio that tells you how strong the tracer signal is in each brain region.

And they compared this against typical white matter as the reference.

Prior work from the same group supports the idea that this signal mainly reflects receptors on neurons, not on support cells.

And that matters because it ties the signal to synapses, Where this is where, of course, neurons talk to each other.

They also gave standard thinking tests to the people, and when they checked whether higher AMPA signal matched worse scores, two tests stood out.

And Steve, I'd like to hear what you have to say about this.

People with higher signal did worse on picture naming and on visual memory tasks that ask you to recall a figure, and those links showed up in the same brain areas that had the biggest group differences.

That connects the scan results to the real-world problems, like finding the right word or remembering what you just saw.

This is really interesting.

The AMPA receptors are excitatory, but they're also excitotoxic.

So, what that means is that they increase the firing of neurons, and they also cause some metabolic stress to those neurons, right?

They actually could kill them if there's enough of that stress.

So, what they think is happening is that it's just messing with the balance of signaling in these networks, right?

Just throwing off the network by having

excess excitatory signaling, too much excitation, and also too much stress on those neurons.

And

it can affect people's overall ability to maintain their focus and to think.

What's interesting is that this is probably a global effect, right?

This is not affecting one part of the brain.

But when there are global effects on the brain, there are certain canaries canaries in the coal mine, if you will.

There are certain symptoms that tend to be the first thing people notice.

And one of those is that just your ability to maintain concentration.

Because we take it for granted, but that's a very high energy functioning state of the brain.

The ability to focus your attention, maintain your attention,

divert your attention, filter out things you don't want to pay attention to.

We're all constantly doing that.

And when that's even a little sluggish, you really notice it.

Yeah, and a lot of people kind of experience it as something called brain fog.

Yeah,

they just can't think.

So, sorry if I missed this.

Are these people producing too much glutamate?

They didn't mention that as far as what I read.

This was a very, very long study.

Yeah, just I'm wondering if they're not going to be able to do that.

I don't think they know.

These receptors are more active.

I don't think they figured out why they're more active.

But AMP receptors are glutamate receptors, right?

So either they're making too much or too much is being left in the synapse, or there's something excitotoxic going on.

Yeah.

Yeah, okay.

They also conducted blood tests, and they found that there were two immune system signals.

You know, it moved with the brain scan result.

The blood tests don't prove cause and effect, though.

It's a pattern that suggests the immune system and synapses might be linked in these patients.

An important question here is: could this scan that they've created identify patients, right?

They were able to identify nine out of ten people who don't have it.

I know it seems backwards, but that's the way that their scan was working.

And these are, you know, these are early numbers.

It's a very small study, and these tests aren't even ready for clinical use.

They'd have to do much larger studies and really dig into that.

Yeah, but it's part of the process of going from a clinical diagnosis to a mechanistic diagnosis, right?

Your diagnosis is: I have brain fog, right?

Like it's just a symptom.

And maybe we could say you have brain fog and you don't have any abnormalities in your neurological exam that would explain it, right?

So that's typically how we make a clinical diagnosis.

You have some symptom and there's no obvious explanation.

So we're left with this syndrome.

Anytime we can go from that and say this subset of those people have this physiological thing going on, that not only helps us do more research, but design treatments for that subset of people.

Because usually there's more than one thing going on when we have just a vague clinical diagnostic category.

You know what I mean?

Unless it's really, really specific, which brain fog is not.

It's very, very non-specific.

Yeah, it's like feeling dizzy.

Yeah.

This study is a really good example of

the scientific process and the difficulty with a lack of funding in science.

So, for example, this is a good study.

You know, they found something that is actionable, that they need to look deeper in, and they need to do more horizontal studies to add up the body of knowledge, right?

It's from a small data set,

it needs to be replicated by other labs.

This is just the beginning of something that could take what, Steve, 10, 20 years to really get into

the point where you might even be able to treat it.

Yeah, I mean,

like with every one of these Nobel Prizes, when you look back, like when was the first kind of insight made about this?

It's usually like a 30-year delay to now we're having

researching actual applications.

yeah that translating basic science to

applicable science is 20 to 30 years is typical but it's important guys it's very important and we need to

the skeptic community i think needs to

we need to know this and we need to you know i don't know what could i even say here i've it's good to be able to advocate for basic science research with good arguments because it it's it's the first one of the first things to get attacked you know uh politically or when when

So it's easy to make fun of, for example, basic science research that has no obvious applications.

Like we're wasting money on doing researching like always like the sex life of French frogs or whatever.

But then when you trace, yeah, but that research led to curing this disease 20 years later.

The examples they choose are...

you know, if you actually trace that research, almost always lead to like really interesting discoveries and sometimes monumental applications.

It's important to know that connection and why you cannot use that argument.

Like, there's no obvious, immediate, direct application of this research, therefore it's useless.

That's a dumb argument, and it's ahistorical.

It's not true.

So, we have to just be patient and continue to sort basic science because we know that is the fuel that drives the engine of change, of progress of our economy.

You know what I mean?

It's so short-sighted to undermine the.

Totally.

And this is a point that has been made for for how many decades?

This was obvious decades ago, but no, you still have to remind people over and over again.

Basic science is critically important.

Oh my God.

Well, everyone, we're going to take a quick break from our show to talk about our sponsor this week, Quince.

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They have so many pieces from bedding to cookware.

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Yeah, I told you, like, my wife, we got her gold earrings.

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All right, guys, let's get back to the show.

All right, Jay, you're gonna keep going with Who's That Noisy?

All right, guys, last week I played This Noisy.

So what do you guys think that is?

Well, it's definitely an animal, right?

Bob, Cara.

Like a.

Yeah.

I would guess like a frog or something like that.

It's an animal or a toy.

Well, a listener named Michael Blaney wrote in.

He writes in quite a bit.

He says, hi, Jay, I'm guessing it's a duck.

That is all.

Yeah, it does have a little duck kind of situation there.

Another listener named Amanda Lee wrote in.

Hi, Jay.

I'm so excited to see you guys in Sydney next year.

Yes, we are going to Sydney, and I'm very excited.

I'm pushing that ball forward every day.

It's a lot of work, and I cannot wait until we get to go.

So she continues, I'm going to add my vote to what I'm sure must be an absolute legion of listeners, all identifying this week's noisy as some deep-sea diver sucking on a regulator connected to a tank with lots of nitrogen in it, and then laughing at how silly they sound.

Yeah, I mean, don't think you're crazy.

That's not that bad of a guess if you think about it, because because it has like a human kind of laughing rhythm to it, and it definitely is a higher-pitched thing.

So I like that one.

Chelsea B wrote in.

I think Chelsea B is going to start a rap group.

Chelsea B.

Hey, Jay, it's See Wee from Buffalo, New York.

First time writing in to say this week's noisy is another effing bird.

I included that one because it's not just funny, but it's just emblematic of the whole thing, right?

Because almost everything could be a bird.

Like, birds make every noise you can imagine.

So, it's always an okay guess to guess a bird.

I like that she didn't even pick a bird.

She's like, it's just a bird.

Gordy Swalm said, Hey guys, this week's noisy sounds like an evil mechanical duck doing his evil laugh, right?

So, there you have it.

This is the guess that a ton of people wrote in.

Thanks so much for doing what you do.

And then, guys, we actually have two winners this week.

They both submitted within a minute of each other.

So, I definitely wanted to give them both a shout-out.

So, the first one is Duncan Shaw.

Duncan said, Pay J Duncan Shaw from South Africa.

I've been listening since 2018 about my third time guessing.

The noise from this week's episode is a barking gecko, and it was newly discovered.

I heard it on Reddit, so I'm guessing one of many to get the correct answer this week.

And then the next person is Rachel Griffin.

She says, Hello, my guess for who's that noisy this week is the newly identified species of barking gecko recently found in the Namib Desert.

Is that Namib?

Namib, yeah.

Namib?

Like Namibia.

Namibia.

Okay, Okay, so Namib Desert.

Yeah, very cool.

So, yes, this is a newly identified species.

I knew we were in the herpetology zone somewhere.

So listen again.

The thing I find adorable, I did read this.

I'm not 100% true that the information is correct, but the person said this is basically the get-go saying, hey, like, get away from here.

I live here.

Like, stop bothering me.

Get away from me, kids.

You're bothering me.

It bothering me.

All right, guys, I got a new noisy this week from a listener named Von Contras.

Contreras.

Contreras.

Oh, contreras.

It's contreras.

Oh, okay.

Yeah.

All right.

I

have to say this.

I almost didn't play it because this is really weird, but I love it.

And I think if you listen to it a couple of times, you'll love it too.

Check it out.

And when you listen to it again, I noticed that this sounds a lot like

no, it sounds like

a song on Pink Floyd the Wall.

I can't remember the song, but it definitely has that

progression going on there.

So, if you think you know what this week's noisy is, or you heard something really cool, you got to email me at wtn at the skepticsguide.org.

steve yes we have things happening we do we've made some excellent progress on the political reality podcast we filmed a bunch of tick tocks we did and

we basically have all of the elements now decided on and we're just waiting on one thing to uh to begin and it's it is nothing that is within our control but it's all good because this is what it takes to to do what we're about to do very excited it's all there, and we will probably be launching this within a couple of weeks or

three weeks.

I think

we'll need to get the first episode out.

We are all going on an epic adventure,

and this adventure will include: we will all be going to LA and we will be doing a private show, and we will be doing an extravaganza.

And then we're going to fly to Sydney, and we'll be doing an extravaganza and probably a private show

and we're going to be doing a three-day conference in Sydney.

It's going to be not a con in Sydney and we're working of course with the Australian skeptics.

We're super excited.

This will be their 47th conference.

But we are taking over the conference because it's going to be 100% content that we create.

And it's going to be awesome because we've run this conference twice before.

We know exactly what we're doing.

It's going to be a ton of fun.

We have some awesome people joining us like Dr.

Carl.

He will be there.

I'm going to be hopefully communicating with him soon to see how

far in can I rope him, Steve?

I want him to do.

Will you chuggle for us?

Yeah, I just want him.

I want him to do

everything, basically.

If you can get him to sit in with us for two days, that would be fantastic.

Then, guys, we are going to be going to New Zealand.

And

I can say it now that we will be having a conference in New Zealand.

I can't give you any details.

It'll be the weekend after the conference in Sydney.

This is all happening, by the way, the weekend of July 23rd of 2026.

And then the following weekend will be the New Zealand conference.

I'll be giving you guys more details as they come out.

We're going to be selling tickets.

Hopefully, I mean, if I get my way, I'd like us to be selling tickets within a week or two.

I think it's possible, but I'm pushing very hard.

It'll happen.

And then, of course, all the details will have been completely finalized.

Bottom line is: we'd love to have you guys.

This is a really, you know, really big deal because, first of all, we're going to be going to two awesome countries that we love.

We're going to get to perform to a lot of people in the U.S.

and over in New Zealand and Australia.

We're hoping that we can bring Natakon to Australia and just absolutely blow them away, Steve.

Aren't you going to sing this time?

There's a small possibility that might happen, like 0.03%.

getting forward, by the way.

Dropping fast.

Guys, if you appreciate the work that we do and you want to help us keep this going and, again, like help us increase our footprint, which is what we're doing right now, you can become a patron.

You can go to patreon.com forward slash skepticsguide.

Any contribution is absolutely welcome, and we would really appreciate it.

Thank you, Jay.

All right, we have a great interview coming up with Professor David Kyle Johnson.

So let's go to that interview now.

We are joined now by David Kyle Johnson.

Kyle, welcome back to the SGU.

Hey, thanks, Steve.

It's great to be here.

And you are a professor of philosophy at King's College, and you are on our Rolodex, as we say, the virtual one, I guess, as our philosopher that we can turn to when we need to talk to a philosopher.

But you contacted us this time because we had a very quick, it wasn't really like

a formal part of the show, but

I think it was because of Evans.

It was the quote.

It was the quote.

The Joseph.

Yeah, if we had a brief conversation about inductive and deductive reasoning.

And I brought up Einstein, which was sort of

an example of a scientist who maybe had some issues in the past with inductive reasoning.

And of course, the real story is way more complicated than our brief discussion.

And since we're the SGU and this is logic, we're like,

let's do it.

Let's do a deep dive on deductive and inductive reasoning.

So that's why you're here.

Awesome.

I am very glad to do that.

I've been thinking about it all day prepping, and I'm trying to think about different ways to approach it and explain it all.

All right, so what's your elevator pitch kind of quickie version that you want people to walk away with?

What's the difference between those types of reasoning?

Okay, okay.

So here's the elevator pitch.

it is commonly thought that deductive and inductive reasoning are defined the following way.

Deduction is reasoning that goes from the universal to the particular, and induction goes from the particular to the universal.

That is incorrect.

That is a misconception that is borrowed from Aristotle, that comes from Aristotle, and it's not even a complete accurate representation of what Aristotle thought.

But the way that modern logicians understand deductive and inductive reasoning is deductive reasoning is reasoning that guarantees its conclusion, and inductive reasoning is reasoning that makes the conclusion probable.

It raises the probability or makes it more likely that the conclusion is true.

And that's how modern logicians understand those terms.

And all arguments fall under one of those two categories.

Okay, I get that.

But when you say that the general to the specific and specific to the general is not true, do you mean it's incomplete or it really is just absolutely wrong?

As an understanding of what deduction and induction is, even as Aristotle understood it,

it is inaccurate.

It's also incomplete in that, like, obviously, there's more arguments than just those two kinds of arguments.

But it is also the case that, like, as Aristotle understood it, and then as modern logicians understand it, that's not quite an accurate understanding of what deduction and induction is.

But would you agree?

Because this is, I get that, I get all that.

I knew that.

But I also thought that, well, part of the reason why that's the quickie summary is because if you do have, like if you take as a premise a general rule, you can make an absolutely must-be-true conclusion about that using deduction.

So that's where that relationship comes from.

Whereas induction, you can't, it's more about generating a hypothesis, so you cannot make a this 100% has to be true.

So there is still that relationship, right?

Yeah, kind of, except for when you said that induction is about generating a hypothesis, that is not necessarily the case either.

Like, it can.

It can, but not necessarily.

But not necessarily, right?

All right, so give us some more examples then.

Let's just talk about deductive reasoning.

So what would be some really good examples of deductive reasoning to help everybody understand what it is in its essence?

Okay, so

Aristotle kind of captures this when he says that he wants deductive reasoning to capture what he called syllogistic reasoning, which he defined defined as a discourse in which certain things being stated, something other than what is stated follows of necessity from them.

So he has kind of that in mind, he has that idea of an argument whose premises guarantee its conclusion.

So if A equals B and B equals C, A must equal C.

Yeah, that's an example.

That's an example of one, right?

So the problem is that whenever he, like he says, that's what deduction is, all of the examples he gives are just categorical, universal, to particular arguments.

They're all, if all A's are B's and X is an A, so X is a B, like, you know, all men are mortal, Socrates is a man, Socrates is mortal.

Like, those are the only kinds of, you know, examples he gives.

But as what you're asking for, right, there's lots of other examples of arguments that guarantee their conclusion.

So classic example is modus ponens.

If P, then Q, P, therefore Q.

Right.

And we can, you know, an argument can follow that form without following the universal to particular, you know,

gotcha.

Right?

Like, so, you know, if Biden won, then there'd be a male president.

Biden did win, therefore, there's a male president.

Like, that's modus ponens.

Those premises, if true, would guarantee that conclusion.

So, that's a deductive argument, right?

Either A or B, not A, therefore B.

That's called a disjunctive syllogism, right?

That is a deductive argument because if the premises were true, the conclusion would have to follow, right?

There's also like axiomatic or definitional arguments,

like that, you know, like all bachelors are unmarried or whatever.

That follows necessarily from the definition of bachelor.

All mathematical arguments are deductive in this way, right?

Yeah, I was going to say that it feels like math.

Deduction is basically math.

Yes, very much so, right?

And in fact, so

this is one of like, so one of the kind of important things to realize about this and why understanding this distinction is important or whatever is it like understanding that that under that that understanding articulation of what deduction is is incorrect, that the original understanding of universal to particular is incorrect, led to the modern understanding and that modern understanding led to like sentential and propositional logic and uh that eventually led to predicate calculus and it is upon that groundwork that like all modern computing is based on

makes sense right so like you can't make logic gates with universal to particular logic right like you you've got to have propositional logic and predicate calculus and that kind of stuff or whatever.

So it was like that development, that realization of updating or or changing, however, you define it, Aristotle's old understanding of deduction to this new understanding, which led to the development of the kind of formal logic, is what makes like all of computing possible.

So, like, it's really under, it's like it wasn't just a semantic, oh, we need to define it in a different kind of way kind of issue.

It was like really philosophically and you know, scientifically important in that kind of way.

It allowed for the kind of logical thinking that is necessary when programming a computer.

Exactly.

Exactly.

So, computers essentially follow deductive reasoning.

Yes.

That's a fair statement.

Yes.

Okay.

And then now let's tick over to inductive logic.

So give us some core examples of that.

Okay.

So inductive logic, again, is any kind of argument which raises the probability of its conclusion, right?

And so, of course, Aristotle's example of going from a particular to a universal, right, would fit under that category, right?

He would be like, I'm trying to figure, I forget what the exact names were, but like, you know, he had arguments like, I think I've got it here.

Person A is experienced and wise, and person B is experienced and wise, and person C is experienced and wise.

Therefore, all experienced people are wise, right?

Like that obviously follows that kind of classic articulation, right?

But there are a lot more ways to raise the probability of conclusions without engaging in that kind of particular to universal logic, right?

So analogies do this, right?

Thing one has properties A, B, and C.

Thing two has properties A and B.

So thing two probably has property C as well, right?

That's not particular to universal or anything like that, but clearly, right, if in the right conditions, that kind of logic is a pattern.

Yeah, it's a pattern, right?

It's an analogy, right?

You find similarities, you derive further similarities, right?

Inference to the best explanation, where you consider multiple hypotheses, compare them according to criteria that determine, you know, what good explanations should do, and you pick the best one, right?

You favor the best one.

That clearly does not always involve inference, you know, from particulars to your particulars to universals.

And certainly it is the case that those kind of conclusions aren't guaranteed, but they certainly raise the probability of,

that raise the probability of the conclusion.

In fact,

something that I think most philosophers of science agree with this, and something that I argue for in my book that I'm working on right now, which is called How, Why, and When to Think Scientifically,

argues that all of science is inductive.

No conclusion in science is ever 100% proven, 100% guaranteed.

Scientific arguments certainly can put the conclusions that they argue for beyond any possible reasonable doubt, right?

Like you'd have to be crazy in numerous ways to reject them, and you'd have to make ad hoc excuses and, you know, yada, yada, yada, but they'll never guarantee anything 100%.

And so all scientific reasoning is inductive.

In fact, in the book, I agree with Ernest McMullen that all scientific reasoning is actually inference to the best explanation.

Yes.

You can do other kinds of reasoning in service to that kind of like inference to the best explanation.

You can even use deduction when doing that.

And you can use different kinds of induction when doing an analogy and statistics

and, you know, obviously hypothetical inductive reasoning, right?

Like there's all different kinds of stuff that you can do, but it's all in service to trying to find the best explanation, which is an inductive form of reasoning.

And it sounds like that you can introduce new information when it's discovered into that and make a better conclusion as it reveals itself.

Yeah, right.

So this is something that was kind of was getting at your quote, Evan, where they were talking about like induction was guesswork, right?

And then when you mentioned Einstein, Einstein was kind of talking about, well, how do we derive the theories upon which science is based, right?

Is it this, you know, particular to universal kind of thing that we're doing or are we doing something else?

And what makes it even more confusing is Einstein said it's not inductive.

and he was by inductive, he meant the Aristotelian sense, from general to from specific to general, right?

From specific to universal.

He said it's deductive.

But when he said deductive, he didn't mean it in the Aristotelian way or in the modern logical way.

Oh, so he conflated kind of two different things from two different eras of understanding.

So dare you know that.

Well, that's what he says in his paper.

In his paper, he defines what he means by deductive reasoning.

And what he says is, when I mean deduction, what I mean is making up hypotheses.

We don't get it from looking at particulars or observations.

We like literally create them through artwork.

And then we deduce what would also be true if that hypothesis were true.

So you make a predictive inference, right?

And then you go off and test it to see if that, you know, if that prediction comes out to be true.

Right?

So he's the only way.

He wasn't using the jargon the way that philosophers use the jargon.

Correct.

Correct.

And in fact, technically speaking, what he's talking about there, you hypothesize, you make a prediction, you see if the prediction pans out.

That is actually inductive reasoning, right?

If P, like if my hypothesis is true, then I would expect this result.

If H, then R.

I do the experiment.

I get R.

Therefore.

the conclude the hypothesis is true.

That's inductive reasoning, or if it is deductive, it's invalid.

That's another kind of issue here.

Let me articulate that a little bit.

So something that's really interesting about this distinction is that we can't, modern logicians recognize that we can't simply say that an argument's deductive if the premises guarantee the conclusion.

Because if we say that, then there can't be invalid deductive arguments, right?

If the premises fail to guarantee the conclusion, well, then it's just automatically not deduction.

But we recognize that there are invalid deductive arguments, right?

Affirming the consequent, denying the antecedent are all examples of invalid deductive arguments.

So what

modern logicians usually do is say that, well, whether we count it as deductive or inductive depends on the intentions of the speaker.

If they think their premises guarantee their conclusion, then we consider it deductive.

And then we bring the appropriate logical, you know, apparatus to bear to figure out whether it actually does guarantee the conclusion.

And if they think it doesn't guarantee it, but only provides support for it, well, then we treat it as inductive and bring a different

logical apparatus to bear.

So what's interesting is that in some circumstances, if P, then Q, Q, therefore, P, can be invalid deductive reasoning, right?

If Biden is elected, if Biden is elected, then we'll have a male president.

We do have a male president, therefore Biden was elected.

Obviously, that argument doesn't work.

It's obviously deductive, but obviously it doesn't work.

But Einstein's reasoning, if my hypothesis is true, I would expect this result.

I did get this result, therefore my hypothesis is true, follows the same logical form, but I wouldn't call that deductive, and I certainly wouldn't say that it's like, you know, it's invalid, or I wouldn't dismiss it because it's technically invalid, right?

He recognizes, as all good scientists should, that seeing that result in the experiment is not a guarantee that the hypothesis is true.

But if the experiment's done correctly, well, there's pretty good evidence that the hypothesis is true, right?

And the more you do that kind of reasoning, the more experiments you kind of mount up or whatever.

That's more and more reasoning that the hypothesis is true.

None of it guarantees it, but but it provides good support.

And that's all inductive reasoning.

It's all inductive.

Science is inductive.

All right.

I have a couple questions.

Sure, sure.

The first is, it seems, therefore,

that

formal logical fallacies deal with deductive reasoning and informal logical fallacies deal with inductive reasoning.

Is that accurate?

The former, I believe, is accurate.

All formal logical fallacies are going to be dealing with deductive arguments.

Yes.

They're going to be invalid because they don't guarantee their conclusion.

they're supposed to and yada yada.

Informal logical fallacies, I don't think necessarily only deal with inductive arguments.

Probably it would be safe to say that they usually do, but it would be like begging the question, I would consider to be an informal logical fallacy, assuming the truth of what you're trying to prove.

And you could definitely do that

with a deductive argument.

Okay, but the symmetry is that formal logical fallacies, if you are committing them, your conclusion must be false.

Whereas with informal logical fallacies, if you're committing them, your conclusion does not have to be false.

It could still be true.

It's just not a good argument.

Is that fair?

Not quite.

So here's just a little distinction.

I don't know where you're coming from.

There's a little distinction here.

If you commit a law, if you commit a formal logical fallacy, what that means is that

your premises don't guarantee your conclusion.

The conclusion might still be true, right?

I could give you a bad argument for anything.

I could give you an invalid argument for anything, even if it happens to be true, right?

But it just means that the argument doesn't work to get you to that conclusion.

So, like, an example I was thinking of is that, well, you say if A equals B and B equals C, then A does not equal C.

That has to be wrong.

Right?

Yeah, because that's a formal logical fallacy.

So, but you're saying you could construct a formal logical fallacy that doesn't guarantee your conclusion is wrong.

Yeah, right.

So, yeah, I could definitely do it where it doesn't guarantee your conclusion is wrong.

So, see if I can come up with an example off the top of my head.

Oh, yeah, okay, here we go.

If I am in Denver,

then I am in Colorado.

I am in Colorado, therefore I'm in Denver.

I see.

That argument is invalid.

But you might be in Denver.

But if I give it while I'm in Denver, the premise is true, the conclusion, the premises are true, and the conclusion is true.

Even Even though the logic is not valid.

So I've given you an invalid logical argument, an argument that's deductive, and it's invalid, but it happens at the premise that

is it true that informal logical fallacies never prove that the conclusion is false?

Yeah, they know the informal logical fallacies will always,

an argument that commits an informal logical fallacy will always fail to provide adequate support for the conclusion.

But doesn't mean the conclusion must be false.

Right.

It doesn't mean the conclusion must be false.

Again, I can give you a prad argument for anything.

Yeah, got you.

Okay, that's good to know.

All right, my next question is this.

I took a course on Sherlock Holmes and logic and how that applied to actually medical diagnosis.

It was a very good course.

And one of the things I remember from that was that the kind of logic that

Sherlock Holmes used in

the literature is neither purely deductive or inductive, and that it's this his own kind of Holmesian induction.

A hybrid.

But it does sound like what he was doing was inference to the best explanation.

Yep.

Right?

So isn't that it?

So maybe, again,

my teacher was probably using an outdated version of what induction or deduction is.

Yeah, it is just inference to the best explanation, the best, the most probable explanation.

Yes, so

let me talk about this.

So this is great.

I'm so glad you brought this up.

So, first of all, right, like, you know, I was wondering if the quote from Star Trek where data is pretending to be Sherlock Holmes and he talks about like, I did deduction from, you know, from the general to the specific or whatever.

Like, like, that's the kind of like definition that floats around all the time, right?

And most people consider they call what Holmes did deduction.

But it's not, you're right, Steve.

It's inference to the best explanation, which can involve both inductive and deductive.

But at its core, it is inductive because the conclusions, the conclusion of his whole argument is never going to be guaranteed.

Right.

And one of, I teach a class on science, pseudoscience, and medical reasoning.

Yep.

And it is inspired by a paper that I wrote where I argue that what leads to medical, one of the things that leads to medical misdiagnosis is doctors misunderstanding what the nature of scientific reasoning is and the nature of diagnostic reasoning is.

They usually classify it as either system one or system two reasoning.

And if instead they recognized that it was inference to the best explanation, that would provide them a better understanding of what it is.

And then that would actually help them, not guarantee, but help them avoid diagnosis, you know, diagnostic errors.

Yeah, I agree.

And the

inference to the best explanation can use both system one and system two thinking.

Yes, 100%.

And for the audience, system one, I can't remember, I always forget which is which.

I think system one is an intuition.

Yeah, okay, so system one is basically like pattern recognition, pattern of intuition pattern recognition.

And system two reasoning is more like what people classically call the scientific method, which is you form a hypothesis, you make a prediction, you perform, you know, you do a task to see if the prediction turns out to be right, and then you revise or reject based on the results, which that's often called the scientific method.

Right.

I think that's better understood as the experimental method, and the scientific method is inference and best explanation.

Right.

And we call that in medicine, we call that system two analytical thinking.

Yeah.

And system one is the pattern recognition or intuitive, meaning it's like, I've seen this before, I recognize it.

You know, I just have a gut feeling that this is what it is.

But you have to back that up with analytical.

Like, I did a test, and the test has this probability, blah, blah, blah.

Then you do like real, you're crunching the numbers at the end of it.

Right, but even that is inductive, right?

It's inductive, analytical, but it's not.

It's all inference, yeah.

It's all inference.

You never know anything for sure in medicine.

Right.

But if we understood, if doctors better understood, like you do, that it's inference of the best explanation, I think diagnostic errors would be reduced.

And right, one of the things that I love the Holmes connection is that my understanding is that Sherlock Holmes was based on a medical doctor

that Arthur Conan Doyle knew.

And he saw

how he reasoned.

So he modeled Holmes' reasoning after this doctor.

And then ultimately, House MD's reasoning is based on Holmes because House is just a medical version of Sherlock Holmes.

Comes full circle, right?

I love that.

I love it.

Yeah, and Watson, of course, is a doctor.

He's an actual doctor.

Yeah, that character.

Right.

Okay, any nuance here that we haven't talked about yet?

So a couple of nuances here.

One is the reason I think it's important to understand this.

Like, it's not just semantic to get the definition of induction and deduction right.

Especially the point about like we need to understand that science is inductive.

Because one of the most common arguments of pseudoscientists, right,

is that like they'll say like, well, you can't 100% prove my pseudoscience false, therefore it's true.

Or they'll say like, can science 100% prove that global warming is really happen, whatever?

And then they'll use that as a reason to think that it's false.

Now, obviously, we all know that's an appeal to ignorance, right?

But what understanding the nature, the inductive nature of scientific reasoning allows us to do is really fully understand why that is a fallacy, why appealing to ignorance is not a good reason to dismiss science or accept pseudoscience.

Because when they are refusing to accept something because it hasn't been 100% proven, they're asking science to do something that by definition, by its very nature, it cannot and does not do.

Right?

Since it is inductive and doesn't prove anything 100%,

when we're thinking about what we should accept based on scientific reasoning, we have to do what Carl Sagan said, right, and numerous others have said this, right?

We have to proportion our belief to the evidence,

not hold out for 100% certainty, right?

And so this also,

and what this also lets us do when it's related to pseudoscience, is make us realize how widely applicable scientific reasoning is.

If it is inference to the best explanation, then it's not just experiment.

Experiment is extremely important in science, obviously, but it's not just, it's just not, it's not just scientific experiment.

When you're doing inference of the best explanation, you compare hypotheses according to criteria that, you know, that determine what good explanations should be.

And some of those explanations are simplicity or parsimony, right?

Scope or explanatory power, conservatism, does it align with things that we already have good reason to believe, right?

And I can think scientifically and weigh those by weighing those criteria even if I can't conduct an experiment.

So for example, if someone just tells me they saw a ghost in their room last night, I can't perform an experiment to like disprove or prove that hypothesis true, right?

But I can consider other possible explanations, like it was a waking dream, their perception fooled them or whatever, and realize, well, that's the much simpler, wider scoping, conservative explanation.

The Lockham's razor there.

That as the more likely explanation for what they saw.

And I'm doing, when I'm doing so, I'm thinking scientifically, even though I can't perform an experiment.

So once we realize that this is the nature of science and that science is, inference of the best explanation, science becomes a lot more widely applicable because you don't have to run an experiment to think scientifically.

Right.

And most people think that you have to do an experiment.

You're not doing an experiment, you're not thinking scientifically.

And you can definitely do that.

Kyle, I also learned the term in medical school, abduction.

Is that used by philosophers?

Yes.

So I'm so glad you asked, Steve.

I love this stuff.

So, okay, so here's the deal with abduction.

Abduction in its original form was

a term that was coined by C.S.

Peirce

and what he meant it to mean was hypothesis generation.

So abduction is the process by which we come up with hypotheses to then compare and figure out which one is the best, right?

Later, other people kind of adopt that term and use it as a shorthand for inference inference to the best explanation.

So in one of my favorite textbooks, Ted Schicks, How to Think About Weird Things, he uses the term that way.

Abduction is just the same thing as inference to the best explanation.

So by that understanding, abduction is a kind of information.

Yeah.

Right.

But technically speaking, abduction in its original form is the production of hypotheses, which I disagree with Einstein.

I love saying that.

He had it all wrong.

Yeah, we tried to get him on the show, but

so I think that he is wrong that classical Aristotelian induction, going from

specific, from particular to universal, can't generate hypotheses.

I think sometimes that can, but I also think he's right that sometimes that's not necessary.

You can just come up with them, right, in a kind of artistic way.

You get inspired or whatever, right?

And you can come up with them.

Of course, as you pointed out when you guys were talking about this before, you always just have to test them.

It doesn't matter where they come from or how you generate them.

You have to test them, right?

So it's

a get good confirmation for it.

But that's essentially what abduction is.

It's originally the production of hypotheses.

It kind of comes to be known as inference of the best explanation.

I try to not use it that way.

But that's basically what it is.

Gotcha.

Okay.

All right.

So, one more thing for you, Steve.

You can cut this out if you want to, but I know you love Bayes' theorem.

Yes, I do.

Right?

So, a really interesting philosophical problem is whether or not Bayes should be classified as deductive or inductive.

Yeah,

which vessel does it pour into?

I mean, my initial response was inductive just because it is a probabilistic statement.

It's just like, how much does this data change the probability of the hypothesis being true?

It all sounds inductive to me.

Exactly, right?

And that's kind of what I think too.

But the other side of the coin is it's all mathematical.

Yeah, that's true.

Right?

If all you're saying is this is the probability, that could be a deduction.

Exactly, right?

If I say, well, if the probability of A is 0.5 and the probability of B is 0.5, then it follows necessarily that the probability of A and B being true together is 0.25, right?

Like that follows, right?

That's mathematical, right?

So it's, I don't know.

I don't classify it as inductive, but it's not.

But can it be both at the same time?

Yeah, I was going to say, I think it's deduction in service to induction.

I like that.

I like that.

All right, good.

Yeah.

Just an interesting problem.

I just like,

yeah i don't know if anybody's spilled any ink on that whether how it should be classified i get the feeling there's like three people in the world who care about that problem

now subduction two of them are on this podcast right now subduction is something totally different right we don't talk about that

we'll talk about that on the geologic podcast right

all right kyle thank you so much for joining us and straightening us all out on logic yeah that was good oh thank you very much it's always a pleasure anytime

It's time for science or fiction.

Each week, I come up with three science news items or facts, two real and one fake.

Then I challenge my panelist skeptics to tell me which one is the fake.

Three regular news items.

Y'all ready?

Yep.

Yes.

Here we go.

Item number one: a recent analysis finds that oil and gas companies hold about 20% of the world's renewable energy assets.

Item number two, a new research finds that quitting smoking after a cancer diagnosis leads to improved survival, more than doubling survival time in patients with advanced stage cancer.

And item number three, a study of a backpack designed to increase airflow without supplemental oxygen increased avalanche burial survival time by at least five-fold.

Bob, go first.

Oil and gas companies hold 20% of the world's renewable energy assets.

Let's see.

I'm going to jump to three.

Backpack, that increases airflow, supplemental oxygen, five times, five-fold.

That's a lot, too.

But what's getting me, though, is quitting smoking, improved survival, more than doubling survival time.

That's just too huge to ignore right there.

I mean, if they can increase survival time by like 5% or 10%,

that's dramatic.

I mean, doubling survival time is just way just an outlier.

So I'm just going to have to say that that one's fiction.

Okay, Kara?

Hmm.

That's the one that feels the most like science to me.

Oh, your instincts.

Mine suck.

Yeah, like

you get a small cell.

Well, and it just says a cancer diagnosis.

It doesn't even necessarily

mean small cell long.

Yeah, so it could be any cancer that if you continue to smoke after your cancer diagnosis, you're just going to

massively shorten your your survival time there.

So I don't know.

I think that that one is

is science, but it makes me wonder what the well, yeah, more than doubling survival time, but like what's the baseline there?

I guess it depends.

If we're talking about advanced stage, different for different cancers.

I don't understand how a an avalanche backpack could increase your airflow without supplemental oxygen unless it like, I don't know, gives you like a tunnel to the outside world when you're buried somehow.

I don't know.

That sounds cool, though.

I don't really understand it.

And then oil and gas companies hold about 20% of the world's renewable assets.

I don't think I believe that.

I think that oil and gas companies have doubled down on oil and gas.

I think we do see greenwashing and we see a lot of talk about them entering the renewable space, but I think that probably other companies that are like renewable-only companies are dominating that space.

So, yeah, I think that one might be the fiction.

I bet you it's they don't have 20.

I don't think they have a fifth of the holdings.

Okay, and Chey.

Steve, with the last one with the backpack, yeah.

So they said it's it's designed to increase airflow.

Yes.

But I'm not clear what that means.

Like, is it I don't think he's going to tell us that.

I mean, airflow to the person's mouth?

So there's nothing in their mouth, right?

It's not like there's a tube in their mouth.

There's no mask or anything, and there's no supplemental oxygen.

It's just increasing flow to like the area of their front of their head.

Okay, so maybe this is like the kind of backpack

it's like the instant release like a

like in a car, like the airbag, like it could create a breathable space around the person's face.

Okay, that's the only thing I can think of.

And this technology exists, so I'm going to say that's science.

Second one is the one about if you quit smoking after a cancer diagnosis, this leads to improved survival.

I mean, I'd say that seems pretty obvious.

Yeah, I think

that one is definitely science.

I mean, quitting,

if you're not going to die specifically from lung cancer, say, you know, then they're going to give you surgery or do something to help mitigate the cancer, then sure, quitting smoking is going to help you.

So I think that one is science as well.

So

I'm agreeing with what Kara said.

Like, I don't think the oil and gas companies, companies, I mean, 20% of the world's renewable energy assets is a lot.

And if anybody would have the money to do it, it would be them.

But again,

for some reason, I just don't see these companies buying those assets because it's actually too smart of a thing to do.

Because they could have just slowly become these new sources of energy, particularly in the U.S., like we are like, the United States now is rejecting green energy.

So what Kara said is very, very true.

In my mind, I'm going to say that one's the fiction.

Okay, so you all agree with the third one.

So, we'll start there.

A study of a backpack designed to increase airflow without supplemental oxygen, increased avalanche burial survival time by at least five-fold.

You guys all think this one is science, and this one

is

science.

This is science.

Oh, neat.

Yeah.

So, this is like again, you wear a backpack, and then you just activate it, I guess, after you get buried in snow.

And it just takes advantage of the natural porosity of snow.

So again,

this is assuming somebody, they're trying to simulate an avalanche condition, right?

Where I guess where there's a lot of debris and stuff.

In that condition, it just circulates the air to the front of the person.

And they tested it, so they had people with the backpack that wasn't working compared to people with the backpack that was working.

They measured their pulse ox, right, basically their oxygen and their blood,

and the people could tap out whenever they wanted.

So

if their pulse ox hit 80 or lower, or if the person tapped out, they ended it.

And the study was for 35 minutes.

Basically, they would auto-end it at 35 minutes, even though the backpack is designed to last for 90 minutes.

In the treatment group, none of the subjects went below 80%

or tapped out.

So they basically all all made it to the 35 minutes, which was the end of the study.

And the people who did not have a functioning backpack lasted six to seven minutes.

And they were pulled, some because their oxygen dropped below 80%,

and some because they just couldn't take it anymore.

They tapped out.

So it might have been more than five times, right?

But that's when the study ended, right?

They didn't keep going.

And this is, so it's, you know, this is being presented as a potential way to increase survivability in you know in an avalanche situation if you have five minutes to dig yourself out versus thirty-five minutes or whatever to dig yourself out or that increases the amount of time until you can be found and rescued uh and so and most people who d who die they die of asphyxia right they just the CO two builds up in front of their face they have their oxygen tension drops and they pass out and they die right?

They go to cardiac arrest.

That's the most likely reason to die in that kind of situation.

So yeah, it seems like a simple idea.

Let's just move the air around and just so that they have less CO2 building up in front of their face and more oxygen and see if that allows them to survive longer.

And it does.

Works pretty well.

It's weird.

According to this one study, anyway.

All right, let's go backwards, I guess.

New research finds that quitting smoking after a cancer diagnosis leads to improved survival, more than doubling survival time in patients with advanced stage cancer.

Bob, you think this one is the fiction?

Jay and Carrie, you think this one is science.

So I guess the question here is the advanced stage cancer.

Is it possible that people are basically too far gone at that point to significantly increase their survival time through lifestyle measures like quitting smoking?

Or is there still room to alter their survival time,

even if they're advanced?

Or Or maybe it was beneficial, but only if you caught the cancer early enough.

Or maybe it wasn't beneficial at all.

What do you think, Bob?

You're the one who thought this one is fiction.

What do you think?

I think, yeah, I think it's late stage,

the fact that it's late stage and that it was such a dramatic improvement just seems like a non-start to me.

Yeah.

I also think that like if you're, okay, so advanced stage, if you're talking stage three or four, survival times are already, depending on the cancer, but they can be already low.

So when we're doubling an already low survival time, it may not be that big of a difference.

We could be talking six months versus 12 months or three months versus six months.

All right.

Well,

this one is

science.

This one is science.

It was surprising that the effect was most pronounced in the late stage,

the advanced stage cancers in this study.

They looked at a bunch of different cancers.

That's why I just said with a cancer diagnosis.

They didn't want to look at anyone specific.

They wanted to see just in general how do people do.

What they found was in the late stage cancer, stage three or four, those who kept smoking despite their diagnosis, 85% of them were alive after 210 days.

In the group that quit, 85% were still alive after 540 days.

And this is all cancers combined.

Yes, this is all cancers, but this is the stage three and four cancers.

This doesn't surprise me because, I mean, other than like radiation, like intense radiation, cigarettes are like one of the worst carcinogens we know about.

Like by far, it's just like a, if your body, if your cancer is already doing all the things cancer tries to do, spreading, recruiting blood vessels, doing all of that, and you just keep smoking on top of it, it's just going to do it faster, more intensely, more successfully.

Yeah, so this doesn't look at mechanism.

This is just seeing how long do they survive.

So that's one question.

It's also maybe people who don't smoke weather their chemo better, you know?

Oh, for sure.

Yeah, if you're smoking, you're also probably getting more like lung infections and

complications of all that is bad.

And it also might be a marker for because again, this is not a controlled trial.

They didn't say you smoke and you don't smoke.

You know, they couldn't do that.

So people who stop smoking may take care of themselves in other ways better as well.

So there's potential contributing factors.

But so but from a practical point of view, and this is why this study was done, because about like what percentage of people do you think are smoking at the time of their diagnosis?

Well, I mean, that's the same thing.

It's in the U.S., let's say U.S.

right now.

No, no, no, no.

At the time of any cancer diagnosis?

Oh, any cancer, not just lung cancer.

5 to 10%?

25%.

Yeah, that's 75%.

Oh, that's a lot.

25%.

So a little bit more than the background population, right?

Which makes sense because it's a risk factor for cancer.

And half of them about continue to smoke

despite the diagnosis.

Because they think what a lot of people think.

It's like, well,

it's too late now.

And in fact, unfortunately, some physicians might think that too.

They might think, well, am I going to really focus my efforts on trying to get them to quit after they get the cancer, like closing the barn door after the horse is gone?

So they said, well, but should we be ignoring this as a lifestyle intervention as part of their overall cancer treatment?

And this study supports the idea that, no, even

in late stage,

it still will improve improve your quality of life and your survival time if you quit smoking as part of the overall cancer treatment.

And this is not insignificant.

This is like almost a year of life.

You know, that's huge if you're.

That's better than some treatments.

Yeah, it is.

And so it would be really interesting to compare.

Like, this might be the single best thing you can do to increase survival.

Right to me, man.

Or it may be right there on par.

So imagine it combined with like, you know, first, or at this point, you're probably on second, third, fourth length.

So I should point out that there were previous studies which did not show much of a benefit, but again, they were looking at specific cancers and like and focusing on earlier stages.

And so this was a more comprehensive study, looked at more different kinds of cancers and later stages.

And that's, again, where the benefit was really the largest.

So that's probably why it was missed in the earlier studies.

But at the very least, this means don't neglect your smoking cessation intervention as part of cancer treatment because there's a good reason to think that it may have a significant benefit.

All right, all of this means that a recent analysis finds that oil and gas companies hold about 20% of the world's renewable energy assets is the fiction.

So, what's the percentage?

Because you're right, they talk a big game.

Lower.

They talk a big gain.

7%.

Yeah, I don't know, 5%, something like that.

1.42%.

It's negligible.

It's almost nothing.

Wow.

They've basically given up on this.

They talk a big game, but they're not doing it.

Nothing significant.

1.42% of renewable energy projects worldwide.

Okay, so what do you think that means?

They're not investing in wind and solar, even though they're like, you know, we're going to invest this money into the new green energy economy, whatever.

They're just not doing it.

They're investing in press.

How stupid and short-sighted is that?

What the hell?

I know.

Well, because they're still making money on oil and gas.

Trevor Burrus, Jr.: So, this included direct ownership also through subsidiaries or via acquisitions.

This is counting everything, not just like under Exxon.

This is like a subsidiary or an acquisition would still count.

It's still only 1.42%.

Did they,

oh, what was I going to say?

Did they include natural gas as oil and gas?

Yeah, yeah, it's definitely not great.

But they do that a lot too.

They love talking about how that's clean energy.

Yeah.

Right, but that doesn't count as renewable.

Now, 20% of the companies they studied had some renewable energy assets, but the total assets was only the 1.4%.

Yeah, so only 20% are doing anything.

80% don't have any

renewable assets.

Yeah, I would suspect this would get worse in the current climate.

Yeah.

Oh, yeah, the current climate?

Absolutely.

But geez.

The Biden era policies,

we passed two acts that

gave billions of dollars to develop renewable energy, was supposed to really turn the ship around, but now Trump is clawing a lot of that money back.

Yeah, it's terrible.

Well, good job, Jay and Kara.

Thank you.

Thank you.

Yeah, Jay.

Jay, you're going to give us a quote this week.

I am.

Science is the great equalizing force in the world.

Smart people, talented people, skilled people exist everywhere.

That's why we really should focus on unleashing their potential through providing them with opportunity.

You know who this is, Steve?

Yeah.

Omar Yagi!

That's the

one of the chemistry Nobel laureates from this year.

Yeah, that's a great quote.

I agree with that.

That's one of of the things I like about science in academia is that nothing's perfect, but it is pretty much a meritocracy.

And it is sort of a great equalizer.

Like everyone's on the same footing.

It's just a matter of how good is your ideas, how good is your scholarship, how good is the work that you do.

That's really the 90%er.

You know what I mean?

It is very powerful, you know, and something that we absolutely should be supporting, not only supporting, but making sure that everybody does have the opportunity to participate because anyone could be a great scientist, you know?

Yep.

Why limit our talent pool?

All right, well, thank you all for joining me this week.

You got it, brother.

Sure, man.

Thanks, Steve.

And until next week, this is your Skeptics Guide to the Universe.

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