SGU Episode 990
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| SGU Episode 990 |
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| June 29th 2024 |
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An illustration of NOAA's GOES-U satellite in orbit above Earth. (Image credit: NOAA) |
| Skeptical Rogues |
| S: Steven Novella |
B: Bob Novella |
C: Cara Santa Maria |
J: Jay Novella |
E: Evan Bernstein |
| Quote of the Week |
Rarely do the advocates of cleanses explain what is meant by toxins. It is one of those nebulous pseudoscientific terms rolled out by people deliberately avoiding the specificity required for a science-based analysis. It's the modern-day equivalent of "evil spirits," vague enough to mean just about anything while retaining the ring of scientific legitimacy. |
Timothy Caulfield, Canadian professor |
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| Download Podcast |
| Show Notes |
| Forum Discussion |
Introduction, SkeptiCal and Skepardy, Murder Chic podcast
Voice-over: You're listening to the Skeptics' Guide to the Universe, your escape to reality.
S: Hello and welcome to the Skeptics' Guide to the Universe. Today is Wednesday, June 26th, 2024, and this is your host, Steven Novella. Joining me this week are Bob Novella...
B: Hey, everybody!
S: Cara Santa Maria...
C: Howdy.
S: Jay Novella...
J: Hey guys.
S: ...and Evan Bernstein.
E: Good evening everyone.
S: How's everyone today?
B: Doing good.
E: Not too bad.
S: Evan, you're still at the peak of sunlight, so you must be doing well.
E: Yes, I am. It's still light out, and I'm very happy about that.
B: But slightly less happy, though, right?
E: A little. Yeah, like I sent you a text the other day, Bob, on June 21st, saying I'm like one minute less happy than I was yesterday.
B: Yes.
S: We're on the downslope, but we're still in the upper half, so that's good.
E: Yeah, definitely.
B: Yeah, it's still like 7.50, and the sun has not set here.
E: I'll start to kind of feel it by August or so is when I'll start to really notice it for sure.
S: So I had a busy night last night. I did Skepperty for Skeptical.
B: Cool.
E: Skeptical. Cool.
S: A conference, 2024 Skeptical Conference, online July 19th to 21st. Part of that is basically Skeppardy, Skeptical Jeopardy. Although I have to say, we did Skeppardy first. We did it like 20 years ago, 25 years ago. It's kind of an obvious portmanteau, but yeah, we did it live. Remember that, guys? We did our live Skeppardy.
E: Yes, we do. Didn't we travel to Massachusetts to do it?
B: I don't even remember it.
E: Or was it an upper northern corner of Connecticut?
S: It was the Connecticut chapter of the Ness versus the Massachusetts chapter of the NESS.
E: Right, for bragging rights.
S: Yeah, for bragging rights.
E: Oh, yes. And what was her name?
S: Rebecca. It was not the Rebecca from the podcast, just another Rebecca.
E: Another woman named Rebecca. Was she... She was basically kind of running the Massachusetts Skeptics meetup group at that point. She was captain of the Massachusetts team. Well, let's just say it didn't go without controversy.
S: She got a little defensive when Connecticut triumphed Massachusetts, yeah.
E: Right, right. But as captain, if I recall, Rebecca was rather vociferous after the fact about certain things she perceived as being unfair. Or was it Becky?
S: Becky?
E: She wore gloves. I remember that.
S: The gloved one. Yeah.
E: Yeah.
C: The gloved one.
E: She wore gloves like 24-7. A bit of a character, I suppose.
S: Then I was on a true crime podcast. That was a lot of fun.
E: Oh, my gosh. Were you found innocent?
S: That was not the subject of it. So this is the Murder Sheet podcast with Kevin and Onya. And yeah, we talked for about an hour all about skepticism, really, conspiracy theories and just all skeptical topics. Because, apparently there's a lot of conspiracy thinking and pseudoscience in true crime.
B: Oh, really?
E: Oh, absolutely.
S: Yeah, because people come up with all these weird theories about what's really going on. In any investigation, there's going to be that, right, in any investigatory endeavour. And it's absolutely critical to follow strict logical procedure, follow rules of evidence. And we talked about a lot of basic principles like Occam's razor and, all that stuff. So it was fun. Well, yeah, as soon as it's published, we'll send the link around to it. But it was fun. Then, of course, right after that, we had our meeting, or I was late for it because I was doing these other things, but we had our meeting about the upcoming Chicago extravaganza shows.
E: Yes.
C: Exciting.
S: Well, let's move on to the show.
Quickie with Steve: Simulating Black Holes (3:45)
- [url_from_show_notes _article_title_] [1]
S: I want to start with a quickie. We've talked a lot about the taking of multivitamins, routine supplementation with multivitamins.
J: Yeah. What do you think about that, Steve?
S: Yeah. So there was a recent study, the largest study of its kind. No, it was an observational study. There wasn't a controlled trial, right? It was an observational study. But it followed over 40,000 participants for 20 years. So that's a long time.
E: That's a nice stretch.
S: It was up to 27 years, but it was a mean of 20-year follow-up.
E: Oh, Steve, a question, though. Did they start with 40,000 or did they end with 40,000? Because some of those people must be gone from the time they started.
S: That's what they started with. That's how many people were enrolled. Those were the people that they followed. The end point was death. So yeah, people over 20 years, yes, people died during the study. So the question was, do people who take multivitamins routinely, people who are healthy to begin with, right? So they didn't have a fatal illness at the beginning of the study.
E: And have access to good nutrition and right?
S: Well, they didn't say that. I think they controlled for those things, but they basically just only included people who were healthy at the beginning. But they would control for things like socioeconomic status and what was your eating habits and whatever. Do you smoke, all the usual stuff. And also like age, gender, and race, things like that. The usual demographic things that they control for. So what do you think they found?
E: No effect.
C: No difference.
S: Yep. No difference. None. There was no difference in the risk of mortality.
C: They were just slightly poorer because they spent money on supplements.
E: But Steve, I imagine none of these 40,000 participants had any vitamin deficiencies to begin with?
C: Well, they probably didn't know.
S: That's correct. Because that would have been excluded.
E: Right.
S: They probably did know because these were part of cohorts that have a lot of information that's collected about them over time.
C: Oh, nice.
S: So these were adults-
C: So they were looking at their blood work.
S: Yes. So yeah, that's why they were able to control for all these variables because they actually had that information. There was data from three different prospective cohort studies, right? Cohort studies when you identify a group of people and then you follow them over time. So they were able to pull them together into over 40,000 people total. So it's as good as you're going to get, basically, from this kind of study. So this has large numbers. They collected a lot of data about people. They followed them for a long time, right? So this is like the most robust study we have on this question. And they found no effect on mortality, so it did not make people live longer, which is consistent, obviously, with previous evidence, although previous evidence has been a little bit mixed because of the dependence. There's so many potential confounding factors. The two big ones are, do people who are sick take vitamins, so you have like a sick user effect versus do people who take vitamins also do other healthy things, things that are perceived to be healthy? Like, do they take better care of themselves overall? Is it a marker for good lifestyle choices, in other words? That's the healthy user effect. So it could cut both ways and the question is, which is a greater effect or do they come out in the wash? You have to control for them in order to be able to say that the vitamins themselves are having an effect because, again, not randomized, not controlled. It's an observational cohort study. So all you could do is, after the fact, try to control for these kind of demographic things. So definitely there's no big effect here, right? I mean, if there was a big effect, our study this robust probably would have seen a signal. So to follow up with what you're saying, Evan, obviously we need to treat vitamin deficiencies. And also vitamin supplementation has been shown to be effective in a number of disease conditions. I prescribe them all the time for migraines, for example. Magnesium, B2, Coenzyme Q10 have all been shown to be effective in migraines and people with migraines tend to be insufficient or deficient in them, right? But if you're healthy and you don't have any specific reason to take them just doing it for nutritional insurance or because you think more is better or that just vitamins are generally going to make you healthier, there's no reason to think that and there's no empirical evidence to support it. And this study is kind of a nail in the coffin on the idea that routine supplementation is a good idea.
News Items
GOES-U Satellites (8:10)
S: All right, Jay, tell us about the GOES-U satellites. Do you say it as an acronym, GOES-U?
J: That's how I've been saying it. I would imagine it's-
S: G-O-E-S-U?
J: Yeah. I would imagine that that's how it's pronounced.
B: Could you say the word acronym, Steve?
S: All right, from the top, let me give you guys some info about NOAA. The initials there are N-O-A-A. I'll be talking about them quite a bit here, so I want you to know who they are. So NOAA is the National Oceanic and Atmospheric Administration. And this is an agency within the U.S. government that's part of the Department of Commerce. Now, their goal is to understand and predict changes in climate, weather, oceans, and coasts. They want to share that knowledge and information that they find, and they want to conserve and manage coastal and marine ecosystems and resources. They're very important, particularly now when we have global warming punching as hard as it is. We need as much intel as we can get. So now that you know who they are, on June 25th, 2024, as we record this, that was yesterday, the GOES-U satellite successfully launched aboard a SpaceX Falcon Heavy. Who's surprised there? They launched from Kennedy Space Center in Florida. This launch marks the completion of NOAA's GOES-R series, which enhances both Earth and space weather monitoring capabilities. So let me get into some details here. You might have heard about the GOES satellites because they go back to 1975. I most certainly heard about them. So GOES stands for Geostationary Operational Environmental Satellites. And there's been a series of them throughout the decades. Versions of these satellites have provided a steady flow of really important information for almost 50 years. This is one of the best ways that we have to get information to predict the weather and to warn people about what's going on and what they should do. So not long ago in the 2000s, forecasting weather involved, and I was surprised to find out about this, but it involved hand-drawing maps and interpreting satellite data. You would think that we would have automated that and had it be all computer generated and everything a long time ago, but it really wasn't that long ago where they had to get down on a drawing board and map things out and actually do it with paper and pencil. So NOAA's weather satellites back then, they were efficient, but they were nothing compared to today's advanced technology that we have in orbit right now. So the GOES-R series, this began back in November 2016 with the launch of GOES-R. This revolutionized weather forecasting in a big way. So broadcast meteorologists rely on data from these satellites to provide life-saving information and give advanced warnings to millions of people across the United States and the Caribbean. So broadcast meteorologists, meaning the TV guy, you know what I mean? The people that we watch and talk about the weather, all of those meteorologists get their data from these satellites. There were some really significant advancements that went into the GOES-R series. So just for clarification, the GOES-R series of satellites is a total of four satellites. Three of them have been in orbit since 2016, and then the GOES-U satellite was the fourth one that just went up. Now these satellites significantly improved things like severe weather prediction, which includes thunderstorms and hurricanes. John Centineo from NOAA's National Severe Storm Laboratory said that meteorologists can now see the convection evolve in near real time. That's a really big deal because this gives them an eye inside the storm as it develops. They can see the severity level as it progresses, as it goes up and down, they can just see it happen right in front of them. This is a major step forward because it allows meteorologists to predict a storm's movement and changes, change in direction, change in intensity. Is it stalling? Is it going to be moving faster later on? They need to warn people with accurate information and that information has dramatically improved in the last decade. Another person named Ken Graham, who's a director of NOAA's National Weather Service, he added that the new series of satellites offer faster and more accurate data that's critical for estimating a storm's intensity, something called cloud top cooling, which has an effect on the overall storm, convective structures, and lightning activity. All of these things contribute to the shape and speed and size and everything of a storm. Instruments like the Advanced Baseline Imager and Geostationary Lightning Mapper, these are two very important modules that are aboard these satellites, they enhance the spectral channels and image quality and imaging speed and enabling around-the-clock monitoring of lightning and other weather phenomena. So again, this upgrade is very powerful, they really packed in an incredible amount of technology into these new satellites. Now while the GOES-U satellite is similar to the first three that have been up since 2016, the GOES-U satellite has some new features that are based on lessons that they learned from those three satellites, which is great. So its standout addition is something called a compact coronagraph. So this is a sensor that will monitor space weather events like coronal mass ejections. Very important to Earth's weather, it can do it because it's designed to block out the light from the sun, like if you think about the, the center part of the sun, the really bright part, you need, you have to have lenses and technology that can block that out so you can see the outer ring of the sun, which is called the sun's corona.
B: Yeah, the moon works too.
J: Yeah, absolutely, the moon works perfectly.
B: We saw it and it's beautiful.
J: The technology has become so good and so nuanced now that we really can see the corona now in a way that we couldn't before. And this, the instrument gives meteorologists near real-time information about what's going on with the sun's corona, with an eight-minute delay of course, because that's how long it takes the light to get here. This eliminates delays in, a delay in experience with previous instruments because previous instruments couldn't do anything like this. So it's really powerful. So it has a dramatic impact on Earth and space weather forecasting, like I said. So the GOES-U and the GOES-R satellites provide unprecedented weather surveillance across the Western Hemisphere. Unfortunately, it's not a global thing. I would imagine that other countries have similar things, maybe not up to the technological level that these guys are because they're very recent. But, this information dramatically helps researchers continue to develop new tools and methods that they'll be using to predict severe weather. So you've got to think about these satellites as sources of information, right? The information that they're giving us is way better. So engineers and meteorologists will get down to the drawing board and they'd be like, okay, now that we have this information, what can we do with it? And how can we manipulate it to help us in ways? They want to learn about predicting severe weather, getting more accurate, something called sea spray identification. They want to be able to monitor cloud motion. All of these things are all possible with the data that we're getting and they just have to write these little software modules to take the data and interpret it correctly, which will take time and everything, but the data is pouring in. So I'm really excited about that largely because we really need these satellites now, unfortunately, because of global warming. So we'll be able to really track what's going on. And this is a really great example of what excellent engineering and scientific research and scientific advancement can do for us.
S: How many are there? Did you say how many there are?
J: There's four in total.
S: Yeah.
J: Three of them were all launched by 2016 and the last one just went up, this week.
S: So this is the last one that's going to go up.
J: Yep. This is it. They only need four to get the coverage. China's Chang'e-6 capsule returned from the far side of the moon. That happened earlier this week on Tuesday. Luckily, it came back. Everything was great. The capsule delivered brand new lunar material from the far side of the moon. The capsule landed in Siziwang Banner, which is in Inner Mongolia, and the team recovered the capsule shortly after it landed. It was a 53-day mission and bottom line is we have brand new moon regolith that we're going to be studying and they might find out some interesting things about the far side of the moon because we have never seen a moon sample from there. We don't know anything about what's going on over there.
E: How different could it be?
J: Well, I mean, the scientists are very excited about it, Ev. They're saying that the material could provide insights into the differences between the near and far side of the moon. You just never know. They really don't know. So there is a future mission coming up in 2026 and in 2028. That's two other missions like, it's basically seven and eight version of these missions. I think it's great. I think that China should be working on a moon base and we need to, I think at some point we should be building a collective moon base where, they can do science together. It'd be great.
S: Yeah. All right. Thanks, Jay.
Risks of Cannabis (17:32)
S: Cara, tell us about the health effects of cannabis.
C: Yeah. So I came across two new studies this week that are interesting in that they, they sort of, I think, broaden the conversation that we've been having for quite some time, especially against the backdrop of the not just legalization of cannabis for medicinal purposes, but the legalization and free access to cannabis in several jurisdictions for recreational use. So in both of these studies, researchers in their way kind of say, the standard line that we're hearing very often is that cannabis is not as dangerous as cigarettes. Cannabis is not as dangerous as alcohol. And in some respects, cannabis is, can be healthful or can be good for your body. And in both of these studies, individuals say, I think we need to take a step back from that assertion. We need to say not so fast and we need to look at the evidence, which is, it's coming out in increasing numbers because historically when cannabis was schedule one, we weren't really doing a lot of research with this drug. So the first study I want to talk about is a study that was published in JAMA Network Open called Cannabis, Tobacco Use and COVID-19 Outcomes. And so in this study, researchers analyzed a ton of records. They looked at public hospitalization records for 72,501 patients across a period of time. These were researchers at Washington University School of Medicine in St. Louis, and they were looking at a major Midwestern healthcare system across two years of the pandemic. So spread across, I think, two or three states across two years of the pandemic, they looked at the health records of over 72,000 people. And they asked a very simple question to the individuals who came to the hospital with a COVID diagnosis. They said, do you use cannabis? They did not ask, do you use edibles versus smoke versus vape?
B: That's critical.
E: Yeah. Why wouldn't, yeah.
C: Because that's not what they wanted to know.
E: Okay.
C: You know, they weren't looking at route of administration. They weren't looking at anything other than, do you use cannabis? Oh, did you use cannabis in the previous year? They also did not ask how often, how likely. Remember, these are patients who showed up to the hospital with COVID during the peak of COVID. So they weren't giving them a survey, right? They wanted to do something quick and easy. Have you used cannabis in the previous year? Okay. Those who said yes to that question were 80% more likely to be hospitalized than those who did not. And 27% more likely to be admitted to the ICU. So for comparison, when they controlled for gender and age and ethnicity and other medical conditions like diabetes and heart disease and the use of other substances, tobacco smokers were 72% more likely to be hospitalized and 22% more likely to go to the ICU than non-smokers.
S: Those are similar numbers.
C: They're very similar numbers. The one area where there was a massive difference is that tobacco smokers were more likely to die. Cannabis did not seem to have an effect on the death rate from COVID in this study. So people who said they had used cannabis in the last year were more likely to require hospitalization, significantly more likely to require hospitalization, and also significantly more likely to have to be admitted to the ICU than those who did not. That's similar rates to those who smoke or to those who use tobacco. But those who use tobacco were much more likely to die. So the researchers do make the point that they don't know whether this is a function of literally smoking marijuana because, there is probably good face validity to the hypothesis that the physical act of smoking marijuana affects the lung tissue, right? The lining of the lungs, which could have downstream effects when it comes to a respiratory virus, but they cautioned very straight, they said, here's a quote, people were asked a yes or no question, have you used cannabis in the past year? They gave us enough information to establish that if you use cannabis, your healthcare journey will be different, but we don't, we can't know how much cannabis you have to use or whether it makes a difference, whether you smoke it or eat edibles. Those are questions we'd really like answers to, and I hope this study opens the door to more research on the health effects of cannabis. So when asked, when the researchers were asked, well, why would somebody who like eats cannabis be more likely to get sick? There's an interesting conversation here, because there is some research, some evidence that suggests that cannabis has like protective health effects. But most of that research is in vitro research. It's done in, petri dishes or it's animal research. There's also evidence that shows that cannabis affects your immune system negatively. And so it could be the case that even taking edibles, may still have a negative downstream effect. If somebody has something like COVID-19, it may undermine, the body's ability to kind of fight that viral infection off. And remember, during the peak of COVID, we did not have drugs for COVID, all that individuals had was supportive care. Okay, so big takeaways, hospitalization rates and ICU admissions significantly higher, comparable to tobacco, but those who use tobacco still much more likely to die from COVID. Okay, the next study was published in Psychological Medicine. And in this study, researchers were interested in investigating the relationship between cannabis use in young people and psychosis. Now this has historically been investigated. But there's been a bit of a change. So basically, this study showed that teenagers who use cannabis were 11 times more likely to develop a psychotic disorder like schizophrenia than those who did not. Historical studies have shown the association was there. But they were something like, like there was a meta-analysis done almost a decade ago now that looked at 10 different studies that found that that rate was about four times more likely. But there's a big difference between the studies that fed into that meta-analysis almost 10 years ago, and this study. And the two big differences are the age range that the researchers looked at. Can you guys think of another big one 10 years ago, cannabis use versus now?
B: Vaping?
C: Strength.
B: Oh.
C: The concentration.
B: Yeah, more than 10 years, isn't it? And over a long time, obviously. So there's a lot of different estimates, but the amount of THC, right, the concentration of tetrahydrocannabinol in marijuana and cannabis has risen significantly. Some estimates say that like between the 70s and 80s and, the teens and 2000s, upwards of like 20%, it's 20% stronger. And so this study looked at 1,560 adults in the UK. And they specifically were looking at these high-potency varieties of cannabis. And also, the other difference that I mentioned in this study versus previous analyses was that they looked at younger individuals. So they looked at adolescents aged 12 to 19. And they also looked at those in their early 20s. And this was all based on survey data, public health records in Ontario. So this actually was older data. It looks like between 2009 and 2012 up to 2018. And they kind of followed those public health records and really just looked, who's using cannabis, who is being diagnosed with schizophrenia. I think it was 1,500 plus individuals out of a big group of like 11,300. Interestingly, they found, again, like I said, that individuals who used high-potency cannabis were 11 times more likely, these are teens aged 12 to 19, to be diagnosed with schizophrenia or a related psychotic disorder versus those who did not. Many previous studies only asked about a psychotic episode. But in this study, they specifically look for a diagnosis, somebody who qualified for a diagnosis. So that's an important difference. And the interesting thing is they didn't see the same association when they looked at individuals between the ages of 20 and 33. Now we do know that schizophrenia and related disorders tend to pop up in late adolescence to early adulthood. So that range is appropriate. And what the researchers posit is that when we think about a diagnosis like schizophrenia, we very often think, like many mental health disorders, about the biopsychosocial model, right? The genetic predisposition, but then also the experiential, the social, the trauma-related or substance-related experiences in life that may exacerbate or that may heighten one's susceptibility to such a diagnosis. And so it's interesting that they noticed that in the younger people in this study, 12 to 19, that risk skyrocketed, but it didn't in the older individuals. So the worry here is that something is happening when young people use cannabis that's not causing them necessarily to develop a psychotic disorder, but that may be switching on or affecting that genetic predisposition for that psychotic disorder. So they do make an important statement. They say, not all teens, right? The vast majority of teens, here's a quote from a researcher in the study, the vast majority of teens who use cannabis will not develop a psychotic disorder. But according to these data, most teens who are diagnosed with a psychotic disorder likely have a history of cannabis use. So it's really, really interesting and also really interesting that, this study is about cannabis. I would be very interested in seeing with the exact same dataset, LSD or other sort of psychedelic drugs and its effects as well within this kind of population, especially of those who maybe already have or already are vulnerable to developing these disorders. But, I think both of these studies together, obviously they open up often more questions than answers and there's much more follow-up to be done, but they do signal that this narrative that cannabis is always safe, that cannabis is not as risky or dangerous or even potent as alcohol or other substances, I think that it's a naive narrative. And it's really important to remember that these types of drugs aren't done in a vacuum and individual risk factors vary greatly. And we're now identifying here two groups of people for whom cannabis use might be very, very risky, young people who have a predisposition to developing a psychotic disorder, as well as individuals who catch a COVID-19 virus.
S: Yeah, I think it's important not to get caught up in the politics of cannabis and just to look at it from a scientific evidence-based point of view. And it's a complicated combination of drugs, right? We wrote about this on Science-Based Medicine calling it the new herbalism because, again, there's a lot of talk about it like, oh, it cures cancer and it does this, whatever. It's like, yeah, going way beyond the evidence. Let's back up a little bit and let's actually study it. And also, as a drug delivery system, unless you're identifying and purifying individual components, it's not great. You talked about the risk of it, and you're right. Certainly I wouldn't recommend smoking marijuana as your drug delivery mechanism because-
C: Right. Nor would I.
S: Yeah. While it appears to be less carcinogenic than tobacco, that's not saying much, but it's not as bad as tobacco. It's still bad. It actually is associated with a higher risk of emphysema, so it's worse for the lungs, even though it's slightly less carcinogenic.
B: What about vaping it? I know there's a lot of news of vaping now that makes it seem a lot worse than we thought.
S: Vaping has a lot of the ... It doesn't have the ash in it. It doesn't have some of the particulate matter that smoking burning weed does, but it still has a lot of products that are not good for the lungs.
C: Right.
S: So, again, it's better, but not great.
C: Yeah, you're still inhaling a substance into your lungs.
S: It's less bad. You know what I mean?
B: It's not eating people.
S: Not the same as good.
C: And that's the important thing, too, is that then saying, okay, well, but if you eat it, it's completely safe. That's not necessarily true. Your body metabolizes it differently. Very often, it can be significantly stronger. It's harder to dose sometimes. Like you mentioned, Steve, which is, I think, a really important point, when we're talking about a substance that has a lot of different molecules in it, like THC is a very complex molecule, and then there's different CBDs, and there's all these different factors, right? There's a reason, for example, that in many hospitals, I can't speak for all, but in many hospitals, if somebody regularly uses THC, even in places where it is perfectly legal as part of their treatment regimen, they cannot imbibe that when they are inpatient in the hospital. It is not allowed. And very often, Marinol, which is a synthetic THC, is prescribed instead, simply because it can be dosed.
S: You know what dose is.
C: Yeah.
S: But definitely one thing is true. It needs to be studied a lot more. There's definitely some useful therapeutic molecules in cannabis, and they should be purified study, dosed, all that. But they're drugs, right? And like all drugs, they have risks versus benefits, and they have complicated actions, and you have to know exactly what you're doing, in what population, et cetera. It's not somehow this magical thing.
C: No. It's not a miracle.
B: Yeah.
S: That has no risks, or everything it does is good. That's the herbalism part, where it's just magical thinking and going way beyond the evidence. We have to treat it realistically. But having said that, it could be absolutely useful if done properly.
B: Yeah. It's ridiculous. It was Schedule 1 for so many decades, it's like, come on.
S: That was unfortunate.
B: Yeah. I think it's in the exact same category as heroin, sure.
Improved Enzymes (32:42)
S: All right, Bob, tell us about improving enzymes.
B: Oh, wait. That article?
S: Isn't that what you sent me?
B: That's exactly what I prepared.
J: You jerk.
E: Got us.
B: Enzymes, baby. Enzymes. Scientists have devised a method to improve enzymes by leveraging their evolutionary history. They call their technique information-based rational engineering, and could usher in dramatic benefits not only to human health, but many important industrial processes. This was published in the journal Nature Communications. The title is Simultaneous Enhancement of Multiple Functional Properties Using Evolution-Informed Protein Design. This is from researchers at the Broad Institute and Harvard Medical School. I think most everyone, certainly our listeners, have heard of enzymes, and a good chunk have at least a vague notion of what they do. Enzymes are proteins, first of all. They're proteins, strings of hundreds or more organic compounds called amino acids that fold up into very specific shapes, and that shape specifically allows them to perform their jobs. Now, enzymes are arguably the most important proteins, absolutely central to life. They speed up chemical reactions by offering another way for the chemical reaction to happen that takes less energy to get started. That's basically what they do. So what kind of chemical reactions are we talking about? You know, the not too important ones, the ones that are involved in eating, digesting, breathing, reproduction, and moving as well. It's involved in ATP. So yeah, critical chemical reactions. I'm going to focus a moment on digestion to show how important and also how underappreciated enzymes are. Do you guys remember that Love, Death, and Robots episode where the three robots after the apocalypse are describing how humans got their energy without using a fusion battery like they have? One of the robots says, expecting logic from beings who have internal vats of acid is a little much. Now, I can't disagree with that, and they kind of went off on the whole vat of acid thing. But do you know why we have this internal vat of acid, the hydrochloric acid, in our stomach?
J: Why we have it?
B: Yeah.
B: What does it do? What does it do? I used to think—
J: It breaks the food down. Ah, I used to think that too, Jay. I used to think that the stomach acid was there to break down food so that the intestines could do their job. And it makes sense because how many times have we seen people in movies get thrown in a vat of acid, and they just like disintegrate, like, yeah, that's what it does to food. It kind of breaks it up. But in fact, the main player in the stomach are enzymes. For the most part, stomach acid mainly creates the optimal environment, like pH-wise, right? It creates this optimal environment so that the digestive enzymes can work optimally at breaking down all the proteins and fats in that meatball that you just ate, right, Jay? So it's the enzymes that are the main player in terms of breaking down the food into bits that can then be processed and further digested and absorbed by the intestines. So without these enzymes speeding things up, get this, it would take years to digest our food, which of course doesn't make sense because then we'd be dead long before that.
J: That wouldn't work at all.
B: Yeah, it wouldn't work. So okay, Bob, I get it. Enzymes are important to life. I get it. But it's not just life. Many industries are flush with enzymes, if you will. Textiles, paper and pulp, pharmaceuticals, waste treatment, and many more all rely on enzymes to do what they need to do. Now imagine the impact on human health and industry if we could actually improve enzymes, making them even better.
J: What? The ones that we use in our body?
B: All of them. Imagine if we can improve enzymes.
E: How?
B: Making them better.
E: It's millions of years of evolution.
B: So yeah, we can't do any better than evolution.
E: Nope.
B: So gentlemen and lady, we can rebuild it. We have the technology. We have the capability to make the world's first bionic enzyme. Beta-lactamase will be that enzyme. Better than it was before, better, stronger, faster. Oh my God. I love the intro to the Bionic Man. I just watched it like four times, the show from the 70s. Watch the intro. It still is awesome.
E: Yeah, the rest of the show is unwatchable.
B: But please do not watch any episodes.
E: Especially the Sasquatch.
S: Sasquatch episodes, oh my gosh.
B: I repeat, do not watch any episodes because it will ruin your memory. I only saw one and it was enough.
J: It's terrible.
B: Holy crap.
J: It's terrible. The pacing is like nails on a chalkboard, man.
B: Oh my God.
E: It is unwatchable. It's unwatchable.
B: That said, I think I still want to go back and watch the episode with the other Bionic Man, the $7 million Bionic Man, I think he was. He had both legs and both arms, I think. I want to see that one again. It probably is going to be horrible.
E: Yeah, he was better, stronger, and faster.
B: Okay. So, guys, Evan, engineering enzymes with mutations is absolutely a thing and it has been for a while, but it has a problem. The problem though is that once you change the amino acid sequence, it almost always leads to a loss in activity. You know, it's just not like, ah. And worse, if you try to make additional mutations, it typically drops the performance and activity even more. So it's really, really hard. So one of their goals over the years then became being able to create multiple beneficial mutations in enzymes at the same time while also preserving the enzyme's activity, its function at the same time. So that's been one of their holy grails. And it's that goal that these researchers hoped to address using their evolution-informed models. So, okay, evolution-informed. In this context, that means that they're looking at enzymes from many, many different organisms. I mean, they didn't give a specific number, but they implied it could be hundreds. There's potentially 4,000 different organisms that could use the same enzyme, but not the same enzyme. It's the enzyme that share a common ancestor in the past. So each animal then, each organism has a different evolved variation of that enzyme, and they took a bunch of them and compared them. So the computational model that they use lines up all the different strings of amino acids from all these different enzymes with a common ancestor, and the program looks for subtle patterns in those amino acid strings. Now what this technique is doing here then is it's leveraging the evolutionary history of this enzyme to reveal the hidden relationships between the amino acids. These are the hidden relationships that would not be apparent if you're just looking at the sequence alone. You know, you need to look at it in the context of its evolutionary history, and then once you see those hidden relationships, they can reveal how the structure of an enzyme dictates its function. Once you have a better idea of how the structure of an enzyme dictates its function, then that helps us to design enzymes with tailored properties that are different, but also have the same structure and same function, but enhanced properties for biomedical uses or industrial applications. So that's what the goal was. Now the proof of the pudding is in the tasting, as they say, and they tasted the crap out of this. They modified this beta-lactamase enzyme using the predictions made by their model and their computations, and they were able to change a whopping 30% of the amino acids in this enzyme. That's huge. And even though they changed a dramatic amount, 30%, they were still able to maintain the same structure as the wild type of the enzyme as they refer to it, the one that's found in nature with all these different organisms. So on top of that, not only did their new enzyme preserve the structure, the new enzyme could also run 60 miles an hour, and it had telescopic vision. Oh, wait. Sorry. Those are my... I lied. The new enzyme... Not even a giggle from you, mofos. Just sit quiet and listen. The new enzyme had both improved activity and stability, and that's really dramatic. They were really interested in that because the researchers say in their paper, perhaps one of the most interesting results is the joint optimization of both stability and activity, which has often been viewed as an inherent trade-off in the protein engineering literature. So a lot of these researchers thought, man, you can't improve both stability and activity at the same time. They're kind of like, it's a trade-off. You're not going to get both, and that's exactly what they got. So I think a lot of these researchers were very, very surprised. Eve Napier is a PhD student at Trinity College, Dublin. She determined the 3D experimental structure, the new structure of this enzyme. She's the one that first saw that, wow, 30% of these amino acids have been changed. She said, overall, these studies reveal that proteins can be engineered for improved activity by dramatic jumps into new sequence space. So what does the future hold for this discovery? In the near future, the researchers say in their paper that they want to find out why this works so well and how can this be applied to other proteins. Then they say, we anticipate that this type of approach will be readily applicable to many protein classes as a means to enhance and design new industrial or therapeutic functions. Sweet. That's really sweet. What about further in the future? About that, they say, the work has wide-ranging applications in industry, processes that require enzymes for food production, plastic degrading enzymes, hello, and those relevant to human health and disease so that we are quite excited for the future possibilities. This has some amazing potential, it seems to me. Imagine being able to optimize not only enzymes, but proteins, just all proteins or many proteins as well. We are basically ugly bags of water and protein, right? That's a next generation quote there, Cara. Except for the protein bit I added myself. It's a little heady to imagine, but this could revolutionize so many things. Imagine therapeutic proteins, drug design, agriculture, biofuels, bioremediation, and on and on. It could have such an incredible impact. But beyond that, especially intriguing to me is using these evolution-informed techniques, we could potentially design novel proteins not found in nature, giving them customized functions and giving biologists toolkits that we can't even imagine right now.
J: Wow. That's amazing, Bob.
B: Yeah. This is so fascinating with so much potential. I hope they achieve even a third of what I'm imagining here. It would still be amazing. Steve, what do you think?
S: Yeah. I mean, obviously enzymes make biology function, right? It's how you control what happens. Because even though you think it speeds up reactions, but it makes them not happen to happen, right? Many reactions wouldn't happen at all without the right enzyme.
C: Yeah. They would take longer than you're alive.
S: Yes. Right.
B: Yeah. It would take you years to digest your meatball sandwich. I mean, years. I mean, basically digestion as we know it would not happen without enzymes.
S: And there are some diseases where we actually give people enzymes, like if your pancreas isn't working. So enzymes are already a treatment for certain diseases, and if they were more stable, whatever, that could improve certainly the effectiveness of those treatments. Otherwise, what are we talking about? Genetic engineering? You know, to get people to make better enzymes?
B: Yeah.
S: Yeah. Which is obviously not yet a ready for primetime technology in people, but potentially could be one day.
B: Yeah. And the key here is obviously you're taking these little evolved machines, these biological machines that are amazingly complicated. We are nowhere near being able to create these from scratch. I mean, we are so far away from doing that at this point. I remember a few decades ago thinking, man, we're going to have some amazing nanotechnology. Like now we're not. I mean, that's still quite a ways away. But what we are going to do is leverage the biological nanotechnology that has done billions of years of R&D already and just tweak them. I mean, you don't need to create this stuff de novo. Take these little machines and bacteria and archaea, take them and tweak them and just do even more amazing stuff than they're doing already with them.
S: Thanks, Bob.
Geopathic Stress (45:52)
S: All right, Evan, tell us about geopathic stress. What is that?
E: Yeah. What is that exactly. This is a headline I saw this week in a news item. What is geopathic stress and is it a threat to our health? Well, it certainly sounds like a threat to our health, but what is it? Geopathology, also known as geopathy, is a theory that links the Earth's inherent radiation with the health of humans, animals and plants. It rests on the idea that the Earth gives off a certain energy vibration that's disrupted by underground features, including, here's the shortlist, tunnels, sewers, geological faults, pipes, mineral deposits, utility lines, underground water, gophers, insect colonies, groundwater, rainwater runoff, large boulders, small boulders and dead bodies in graveyards. I may have added one or two of those for dramatic effect. According to this theory, living above any of these areas of energy disturbance can result in geopathic stress. That stress is said to cause a very large range of physical and physiological symptoms. This can create a pernicious effect on the health and behavior of all biological life. You know why that is? It's because just about everything on the planet lives above one or more of these things. It's nothing like trying to focus on the source of a "problem" by making the whole planet on which you live the problem itself. But hey, I guess it makes sense in the word, the word geopathic. What is it derived from? You guys know this, right? Geo means?
B: Geology.
J: George Hrab.
B: Pathology.
E: George Hrab. Yep. It's George's fault. Geo is earth. Pathology. Pathos and pathology. Pathos, right? Disease.
C: Disease, yeah.
E: Suffering, right? So geopathic. All right. Well, I tried to look up geopathic stress in the medical literature and you know what? I couldn't find any references to it.
C: Who would have thought?
E: I mean, why is that, Cara? You know what else I didn't find in the medical literature? The healing properties of unicorn blood and the health benefits of leprechaun charms. Makes you kind of wonder why that's the case too. While this is entirely ignored by medical science, correctly, it does seem though to have quite an understanding and a written background among a very certain group of specialists such as dowsers and water witchers and feng shui masters. Thank goodness for that. Without them, I would have no news item this week. So in a very selfish way, I'm grateful to those specialists. Now I'm going to read some of the highlights from this news article that came out this week. It focuses on a person named Peter Stott, S-T-O-T-T, who lost his first wife to cancer in 1998. Very sad. Her death, he believes, was due to geopathic stress, G-S for short, which are harmful energies that originate from the earth. And he said, Peter said, "I found out that the house where we had lived had a serious G-S problem." Now there's no exact description on how he found that the house had a G-S problem. And then he says the discovery prompted him to become a professional dowser, devoting his life to finding and managing geopathic stress. Yep. Nothing like an emotionally fragile state when making life decisions based on nonsense. Definitely. The article continues, although G-S might sound like B-S to some, it's worth noting that sewers and underground pipes, for example, can emit harmful gases and negatively impact a person's health. In particular, hydrogen sulfide in the fumes can be potentially fatal. OK, well, I'll agree with that statement, but it's kind of too bad that that's really not what this article is at all about. You know, the author is writing about G-S specifically. And that's a claim having to do with what energy fields, not gases. You can't wrangle in legitimate science concerns to validate the illegitimate science. It was a nice try, though, I think. Back to the article. Dowsing is also used to detect gases that aren't man-made, including methane seeps in wetlands and emissions from geothermal areas such as those found in volcanic regions. Dowsing, practitioners say, is a method used to detect the presence of various subtle earth energies and assess their nature and quality. They argue that some of these energies can be linked to geomagnetic anomalies caused by flowing underground water, dry faults, fissures, subterranean cavities or mineral and crystal deposits. OK. Yeah. They even argue that on top of that, you can find lots of things, dead bodies, lumps of gold, missing children, illegal narcotics, bombs, landmines and much, much more. Much like geopathy itself, which by definition occurs everywhere. Dowsers claim they can harness magic, in a sense, to find anything that naturally occurs or can be put into the ground. OK. So, the article goes on. How can one actually detect GS? Wow. That's a very good question. We're down to the nitty-gritty. Yep. It's dowsers, in fact. Dowsing is carried out by a dowser, practitioners who try to find the source of these energies using special tools such as pendulums, rods and bobbers, essentially sexed up tree branches. Their words, not mine. The person holds the tool, waiting for it to move or react, which they take as a sign that they've found what they're looking for. So, I'm going to actually interject here and help them out a bit with the definition of dowsing or the act of dowsing, right? The performance of dowsing, which I like to call it. It can be explained pretty much 100% of the time by what? The ideomotor effect. And if only I had a book that talked about, hey, look at that. The Skeptic's Guide to the Universe book says, the ideomotor effect, the subtle unconscious muscular movements people make resulting in the moving of objects. And noted parapsychology critic, Dr. Ray Hyman has written extensively about the ideomotor effect and he summarizes it as such, under a variety of circumstances, our muscles will behave unconsciously in accordance with an implanted expectation. What makes this simple fact so important is that we're not aware that we ourselves are the source of the resulting action. This lack of any sense of volition is common in many everyday actions. Very good, Dr. Hyman. Thank you again for your contributions to skepticism. We love you. Is it any wonder though, that the ideas of dowsing and geopathy go hand in hand, slight pun intended. Now, if you're really, if you're going to make a living using this sort of exercise in self-delusion that is dowsing, it makes sense to also call into existence a force that can't be measured using science and call it geopathy, right? Geopathy apparently does not affect everybody in the same way, according to this article. And that's true. Some of us use reality to ward off the effects. However, they go on. Cancer has been described as a disease of location. This is back to the subject of the article, Peter Stott. This is what he has to say now. Cancer has been described as a disease of location. And if there is a family history of cancer, as there was in my late wife's case, a person can be more susceptible to GS being a contributing factor in succumbing to the disease. The author of the article continues, Peter believes that GS impacts our immune system, depleting its resources and hindering its ability to function optimally. So much for the marijuana discussion there on the immune system. It's GS all the way. By eliminating GS from our surroundings, we allow our immune system to operate more efficiently, he contends. Our susceptibility to GS varies with some experiencing mild symptoms like sleep disturbances and fatigue, while others may face more severe health issues such as arthritis, multiple sclerosis and cancer. All right. Well, like I said earlier, I mean, go ahead and find for me any evidence that GS not just actually exists, first of all, but that it has an influence on anything like cancer or arthritis or any health effect whatsoever. It does not exist. And at least, OK, I'll give the author of this article credit. He writes next, however, data in support of this claim is sorely lacking. I think that's kind of like the first correct observation the article makes like towards the end. Peter believes it's also possible to carry a token or amulet on your person that's been imbued with the power of protection by someone who is proficient in dowsing. Yeah. So it kind of takes on all these levels of silliness after after a while. Fortunately, at the end, unfortunately, they put at the end, I think they should have put at the beginning. They did get a hold of Dr. Edzard Ernst, who they describe as a man who's dedicated years of his life to examining questionable science based claims. And yeah, he won't be enlisting the services of a GS specialist anytime soon. Here's what he told them. Geopathic stress cannot cause health problems for the simple reason that it does not exist. It is a sly invention of quacks who exploit gullible consumers. The methods to diagnose GS are as bogus as the ones that allegedly treat it, correct? But the quacks don't mind as long as the consumer pays. In response to that, Peter, the subject of the article, says, well, we're never going to change the minds of people like Dr. Ernst, who seem to focus exclusively on debunking anything for which there is not a scientific explanation. Moreover, science is moving on with research done into quantum physics, Bob, and the theory that everything in the universe is connected and is also accessible to everyone. You see, whenever what you're trying to push on people doesn't have a scientific explanations, you can always go to the margins of the quantum realm. And say, OK, it must exist there because we don't fully understand it. Scientists don't fully understand quantum physics yet, and therefore this is the true source of all this magic that's going on.
S: Yeah, it's quantum quackery, just invoking something they don't understand. Most people don't understand saying this is weird and it's things are connected in a weird way. So that explains my pseudoscience.
E: Exactly. Exactly. And I think Deepak Chopra, perhaps, is one of the most famous people, I think, for invoking the quantum realm in passing along the quackery. So there you go. Geopathic stress and dowsing. It seems like you cannot have one without the other. All right. Thanks, Evan.
E: Yep.
Using AI to Predict Alzheimer's (56:25)
- Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models [7]
S: So we'll do another quick one. This one is about using artificial intelligence to predict Alzheimer's disease. So this is not the first study looking at this. But this is basically they're using a large language model in order to look at speech patterns. And then trying to predict which patients are going to develop Alzheimer's disease based upon their speech patterns. So that in and of itself, that idea isn't new. One of the earliest signs of dementia is alteration in speech patterns. And it goes beyond just like the normal word finding difficulty that people get as they get older. They use fewer words. They use simpler sentence constructions. You know, they're less precise in their language. And that's actually highly predictive of early cognitive loss in dementia. So they were trying to see if AI could pick this out. So they followed a cohort of people for six years. They had examples of their speech throughout the study. And so they looked at 166 participants. And of those 166 participants, 90 of them, they all had minimal cognitive impairment at the beginning of this six year period. Minimal cognitive impairment basically means like normal ageing. You're not as not as sharp as used to be. You might have a little bit of difficulty remembering names, thinking of words. But you don't meet the criteria for dementia. You don't have dementia. You just have, you're not quite as cognitively sharp as you were. Minimal cognitive impairment. And that's that's the tricky category. Like we see patients all the time who have MCI. And the question is, is this normal ageing? Or is this early Alzheimer's disease? That's the $64,000 question that we get all the time. And this study is addressing that exact thing. So among those 166 participants, 90 of them went on to progress from MCI to dementia, or they had progressive cognitive decline. And 76 were stable. They did not progress at all over those six years. You know, they trained, the AI on the the speech of these participants. And they developed a model based upon that, based upon the speech data. They say that they achieved an accuracy of 78.5 percent and a sensitivity of 81.1 percent. So I assumed by accuracy they mean specificity. So, both specificity and sensitivity are around 80 percent, which is not great for a diagnostic test, actually. It sounds good. 80 percent. But it's pretty good, right? It's actually it's not bad, so it's not great, but it's not bad. And that's better than anything else we have in terms of the earliest stages of Alzheimer's, of Alzheimer's disease. Of like knowing who, which patient with MCIs is going to go on to develop dementia and who's going to remain stable over the next five to 10 years. This is increasingly important because we actually have treatments for Alzheimer's disease now, and they seem to work primarily if you start them in the earliest stages of the disease. So now there's this connection between being able to predict Alzheimer's as early as possible in the course of the disease and these emerging treatments that actually can alter the course of the disease, a slowdown progression. But again, they work way better if you start them very early on. So developing these kind of tools has a very immediate practical application. Identifying who should get treatment or not. And, we've talked about this, this idea of using AI diagnostically because a lot of diagnoses are basically pattern recognition. You know, something that large language models are very good at.
B: Oh, yeah.
C: And that's why we see a lot of the radiology stuff.
S: Yeah, exactly.
C: A lot of looking at films.
S: Yeah. And the other thing that the other way to look at it, they're good at pattern recognition. They're also good at identifying predictive features. You know, by that, I mean, like what aspects of whatever phenomenon they're looking at, predict some connection or some outcome or whatever. It makes some kind of prediction. And because that's an easy feedback loop to close. When you train the model, having an outcome to train it on. Like you're either correct or you're not correct. You know, that kind of thing, it's a lot easier to train the model if that's what you're looking at. So the AI gets very good at picking out what is it exactly about the speech pattern that's not just like it's a little off, but it's actually predictive, of progress in a future progression. And even when we don't necessarily like, like we as clinicians, we may have an idea of what that is. But, the AI can pick out things that we can't perceive, that humans can't perceive. And then even when it is trained and can make this prediction, we don't necessarily know how it's doing it. You know what I mean? It's just like it's seeing something in the pattern of speech that predicts progression to Alzheimer's disease. What I found impressive is how little data this was trained on. And how effective it was. And also the recordings were apparently very low quality because they were getting this as part of another database, not a database that was done for this study. They were just pulling people out of the Framingham Heart Study. A large database of people that were followed for many years. So that's why it's a convenient database to use. So I'd like to see is like a dedicated study where you get a cohort of, thousands of people in their 50s, 60s, 70s. You get baseline data. You train the model, even further. You train it on people who have MCI, who have, neurologically, healthy, who have Alzheimer's disease. And then, see, I bet you can get that predictive level much higher than what it is in this study. Again, hovering around 80 percent sensitivity and specificity. I do think that this is going to be huge diagnostically in medicine. It's just like a perfect application for it. Because there's so many moving parts diagnostically. And, as clinicians, we're just overwhelmed with data. Sometimes there are features that are what we call pathognomonic, right? Like if you have this feature, you have the disease. And so those are nice. Sometimes features are highly predictive and ones that we can hone in on, that are that are very good. But for a lot of things that we diagnose, it's just there's a lot of information. No one piece of information is definitive. And we're just using our judgement. And we're also doing a lot of intuitive pattern recognition ourselves. This smells like a heart attack. I've just seen it so many times. I kind of subconsciously almost recognize, just speaking like generically as a physician, you recognize the way things look, the way people behave or whatever. And you just sort of get, raises your radar for that diagnosis. But then, of course, you have to follow it up analytically, like you have to do the tests and, that with that have specific numbers attached to them in terms of their predictive value and their sensitivity and specificity. But even then, no test is 100 percent. Tests are they may be very good, but we're still just piecing together, the history, the exam and work and the findings on scans or findings on different different diagnostic tests. And then we put it all together and we make our our best assessment or we follow some kind of algorithm in terms of what we do. But we're making decisions with incomplete ability to make full use of all the data in front of us. It's just way too much data. It's way too complicated. There's way too many permutations and variables. And it's it's you know what I mean? It's impossible to say, like Spock would do or Data would do. This person has a ninety three point seven percent chance of having said, we can't do that in our head. That's just it's not it's beyond human capability. So we're always making sort of our best guess. This is a perfect application for AI because AI could be like Data or Spock and say and do can come up with much more precise, predictive algorithms in terms of just it gathers all the data. It runs it through its akinator like application and says, this is what this is, what the person has.
C: Do you know what comes to mind, Steve? Like what analogy I can't help but come up with as you say this is like, you know, when you're watching poker, there's the poker player. Who's pouring through the body language and how somebody's acted before and what the stakes are. And they're also trying to maybe count their outs or do some statistical analyses in their head. But mostly there's a million different reasons that they're deciding to act the way they act. But then when you're watching the game, you also see the overlay of the actual statistics and what would actually happen if they played, if they bet or they folded or they whatever. And it's sort of like both those things working together. It's what makes the play so fascinating to watch. And I feel like that in some ways is like what you're talking about with health care. Like you've got this physician who has all these different reasons to lean into this, but also having this A.I.
S: That would tell you.
C: That tells you the statistical whatever. And having both of those things combined means that you're bringing better patient care.
S: Absolutely. There's a huge potential here to improve the quality, to make diagnoses faster, to prevent unnecessary testing, for example. Like, sometimes we order tests to just to be sure, to cover the possibilities. And as opposed to this is the pathway, the quickest and most efficient pathway to making your clinical decision. Don't do this test first. Then depending on the results of that test, then you do this other follow up, whatever. Or you make this decision or this test will not help you. It feels like it would help. It's information and we feel good having that information. But statistically, it may not make a difference in terms of the patient outcome. So we try to think that way. But again, it's like there's way more information than you could actually use in a completely precise way. So, yeah, it's just medicines become way too complicated for the human brain to really handle it optimally. So there's a lot of headroom. There's a lot of room for improvement by having an A.I. assistant help you sort through massive amounts of information and navigate it optimally. It'll be like playing chess with a computer telling you what move to make in a way.
C: Totally.
E: Yeah. Yeah. Which, will destroy any human player ever.
S: Right.
B: Not a perfect analogy.
S: Not a perfect analogy. Because you still need the physician because there's a human element.
C: Yeah, that's why I think the poker analogy is better. It's the computer telling you these are your odds. These are your outs. If you do this, you have a 75 percent chance of winning. But you're still looking at your opponent and going, I don't know what he's going to do.
S: But I bet you if you trained an A.I. on those specific poker players, they would learn their tells.
C: Probably. Yeah. If you train them on the players.
S: Or their pattern of betting, it's like this guy's bluffing. I know, he's probably bluffing because this is the way he plays, because if you crunch or whatever, again, we wouldn't even might not be able to reverse engineer how it's doing it. Just the A.I. model would know like when they're bluffing and when they're not bluffing. Still on the steep part of this curve. There's studies like this coming out all the time. This one just caught my attention today. But this like when I was, reading through my dozens of science news items prepping for the show and for science and for science or fiction. I mean, there were dozens of A.I. studies, dozens of, you know. I mean, just today, it's happening so fast.
E: It's a wonderful tool for the toolkit.
S: Yeah. Yeah. I mean-
E: So versatile.
S: There's hype and there's pseudoscience surrounding it, too. But it is a legitimately powerful tool for what it does. Absolutely. All right.
Who's That Noisy? (1:09:46)
S: Jay, it's who's that noisy time.
J: Yes. All right, guys. Last week I played this noisy.
[Forest sounds in background, squeaking animal foreground]
You guys have any ideas?
S: It's a bird.
C: Superman playing with a dog toy.
E: It does have a dog toy squeak quality to it.
J: Yeah, it does. A listener named Joe Vanden said it's a dog with a squeaky toy stuck in his throat. Oh, and they signed it, Michelle. OK, that was from Michelle then. Sometimes people use other people's email addresses, I find.
E: Sure.
J: A listener named Victor Anderson said, Hey, Jay, I've been listening for 19 years and this is my first time submitting a guest for Who's That Noisy. I think this is the noisy that I have saved my phone, that I have saved to my phone that I wanted to submit from a different part of the video. Is this a donkey playing with a rubber chicken? No, it isn't. But I'm sure it sounds just like that because that's what a rubber chicken sounds like. That's what a rubber chicken sounds like. Visto Tutti says it's a bird, Jay. I think it's it may be the zebra finch. If you've seen pictures of zebra finches, they're tiny little cute birds. It is not a zebra finch. But I will- Another listener named Derek Reethans said, Hi, I think the noisy was two or more seagulls right about to steal your fries on the seaside. I've had seagulls steal French fries for me.
B: Really?
J: I have.
S: Oh, yeah.
J: On more than one occasion. They're really clever about it. Anyway, that is not correct. But, you're seeing kind of a pattern here, right? Birds. And Steve said it's a bird. And then people say squeaky toys. OK, I got a winner. I was very happy that we had a winner. I didn't think we were going to have one, but we do. This is from Lynn McCurdy. And Lynn said, I believe it is an alpaca's alarm call. You guys know what an alpaca is, correct?
S: Yeah. It's like a llama.
J: So, yeah. So when an alpaca detects a threat, it makes a call to the other alpacas to let them know that something sketchy is going on. And this is the sound that they make. [plays Noisy] Yep. They just scream like a squeaky toy.
B: Wow.
J: Yeah.
E: Neat.
S: That is an alpaca.
E: So I'm sure we have listeners who have alpaca. They must have heard that.
C: Is it alpaca or alpacas?
J: I don't know.
E: Yes.
J: I guess one alpaca is an alpaca and multiple is alpacas.
C: I don't know, because Evan just said, I'm sure we have listeners who have alpaca.
E: Alpaca, plural.
C: Fish and fishes.
E: It is alpacas.
C: All right.
J: OK, good. I'm glad.
C: So Evan clearly doesn't have alpacas.
E: Clearly, I would have gotten the noisy correct this week.
New Noisy (1:12:36)
J: So I have a new noisy for you guys this week. This noisy was sent in by a listener named Freya Brandl-Tanis. And here it is.
[Whooshing, chuffing, warbling animal sounds]
E: That's Jay at the meatball-eating contest.
J: That's like my digestion happening after a round of meatballs. (Bob laughs)
Announcements (1:13:39)
J: So, guys, we have a lot of fun stuff coming up.
E: Jay, I'm sorry, we have a correction, an instant correction. The plural of alpaca is alpacas or alpaca.
J: Good.
E: Both are appropriate. Back to you, Jay.
C: Vindicated.
S: It's usually it's usually like it's just like, is this a plural or is that the plural? The answer is usually yes. It's like octopus, octopi, octopuses. They're all acceptable.
B: Octopodes?
S: Except that one.
E: Go ahead, Jay.
J: So we got some fun stuff coming up here, guys. We have three shows that we will be doing in Chicago. Two of them are extravaganzas and one of them is a private show. The private show, guys, that's our one thousandth episode.
E: Finally.
J: It's a big number. It's a one with three zeros after it.
E: It's ten to the third power, right?
J: It's very cool. It's really cool that we that we lasted this long, 20 years, one thousand episodes, ton of hard work, largely done by Steve. But still, we all contribute. We will be doing our one thousandth episode live in front of a live audience. We will be doing a five hour show. So this show is very complicated because we will be having people that we will be bringing in virtually to say hi and people that have been reoccurring guests on the show and friends of the show. We will be having George Hrab there with us, who will be interviewing us, getting personal, asking us the hard questions, which he does really well. Definitely be revealing some inside stuff and just reminiscing about the last 20 years. We will be listening to snippets that have been recommended by listeners. These are moments that happen throughout the nine hundred and ninety nine previous episodes or, as many as we can get to. These will be funny moments. These will be crazy times. These will be offshoot conversations, profound statements, very insightful things, everything that's good in the show. I'm going to be picking the best of the best. It's going to be really cool. And then I will definitely compile some type of supercut of that, that I will be distributing to the patrons. We will also be recording an episode of SGU that that one thousandth episode will, that five hours will be reduced down into an hour and a half regular episode. But we will be talking about the past and the present and how, how things lined up. So, for example, Steve gave this as an example. We could be talking about what solar panels were like 15 years ago and what people were saying about them and where they are today. And just as an interesting marker that over the 20 years that we've done this podcast, lots of things have happened, lots of things have changed. We had an entire pandemic happen. I'm sure somebody will be talking about that to some degree. So anyway, it's going to be a really fun show. I'm really looking forward to it. We have done these, many multi hour shows before. We were talking. We had a meeting last night and we were all laughing that we actually don't need to prepare anything. Cara, because we can talk endlessly, particularly when we're in the same room with each other. We are preparing a lot, but we don't have to prepare because we could talk and talk and talk and talk. That's what we do. That's what we all love to do. But we're going to do our best to put on the best one thousandth show for you guys as we can. We have over 300 people attending right now. There is room for more. If you're interested, just go to theskepticsguide.org. That's our website. And you will have a button on there for the extravaganzas and for the one thousandth show. And lastly, we've been doing this for 20 years. If you think the work that we do is important, if you find it entertaining, insightful and helpful in any way, please consider becoming a patron of the SGU. Every dollar that you donate can help us do bigger and better things. So we'd love for you to join our list of patrons who are most of them are on discord chit chatting with each other every day. The conversations are happening 24/7. It's a wonderful group of people. And I think if you're looking for like minded skeptics out there, this is the place to go. You can go to patreon.com/SkepticsGuide for more information. And lastly, if you're interested, you can join our mailing list because we put out an email every week that highlights all the different content that the SGU has created over the previous week. Just got to go to theskepticsguide.org and there's a button on there. Y can join our mailing list.
S: Thank you, brother.
Questions/Emails/Corrections/Follow-ups
Email #1: The Pattern App (1:17:39)
S: So have you guys heard of the pattern?
J: No.
E: I like the zone or the secret or-?
J: It's scary. It sounds scary to me.
S: All right. Well, this is an email that comes from Matthews from Sweden.
E: Matthias.
S: Matthias? Matthias.
E: Cara, you?
C: I don't.
E: You're usually correct on these things.
C: I have no idea.
S: They write-
B: Definitely not the first thing you say.
C: It's probably not Matthews.
S: Yeah, probably Matthias or Matthias says, please debunk this very popular app. The pattern that is making tons of sensible persons believe in stupid astrology shit like the exact planet position combined with exact time of day of your birth somehow determines your personality. People use this to find partners. I don't believe in astrology, but this app is spot on for my friends. This is what he's quoting his other people now. It is not generic text I can read from. I can read my own conclusions into. This is science.
C: Oh, right.
S: Please. It's featured in Vanity Fair Time, Tech Crunch, Vogue, dot, dot, dot.
E: Of course.
C: Therefore, science.
E: Astrology is saturated in many cultures.
S: It's having a little renaissance, unfortunately. So I downloaded the app and I and I did my profile. Are you ready?
C: Yep.
S: Because I happen to know the actual minute of my birth, at least as close as they would record it in a hospital.
C: Me too.
S: So I put all that in. Can you tell me how accurate you think this is? You're meant to embrace your creative, fun, entertaining and playful side. You're learning to follow your curiosity and have a sense of humor about life. Don't be afraid to be flexible and pursue more than one interest at a time. Your mind moves incredibly fast and is constantly seeking stimulation. It's OK to own your need for freedom and independence.
C: Oh, my God, such a fortune cookie.
E: You know, more vague.
S: You may fear being-
C: This could not apply to more people?
S: You may fear being judged if you don't stick with tradition or put down roots and focus on being practical and responsible. However, if you overdo your irreverent traits, you can come across as immature and not taking anything seriously. In that case, you might act sarcastic or superficial and avoid depth and emotion like you're living life on the surface. So that has, I don't think, I don't see that it's having any relevance to me whatsoever. You know, I mean, this is no more accurate about me than it is about anyone or that any other generic reading would be about me. But you can it absolutely is what this person, what is quoting other people as saying it isn't. It is a generic text that you read your own conclusions into.
C: Yep.
S: Right? It's exactly what this is. It is an absolutely typical astrological cold reading.
E: Absolutely. This is explanation of astrology.
C: Right. It's that famous study. You guys remember that famous study where they gave everybody in the class the same?
E: Yeah, right.
C: Yeah, exactly.
E: Oh, my gosh. Crazy. But an app, sure. Oh, sure. There's a hundred thousand apps.
S: Yeah, yeah, yeah. So it's crap.
E: And Steve, you said it. Yeah, it has having somewhat of a resurgence. And I'm sure, obviously social media is responsible for that, among other things. Never, never went away. It's always been lurking.
S: Well, yeah, but the new generation becoming fascinated with it. So that's why we have to debunk these things over and over again. And now you have, young people who have not heard all the debunking and they fall for the same shtick all over again.
E: Yeah. I mean, but how many generations has astrology been around and around the world in various cultures?
S: it's been going on for thousands of years.
E: Thousands of generations.
S: Thousands of years.
E: Thousands of years, certainly.
S: Yeah. Hundreds of generations.
E: But why would we ever expect that this will ever go away? It never will. We just-
C: Because science?
B: It's apart of the human condition, it will never fully go away.
S: But Evan there's some kind of quantum connection, though.
E: Oh, that's right. We haven't figured out everything quantum yet. So therefore.
S: And just for the record, because we do a lot of drive by debunking of stuff, when people say, oh, well, instead of dismissing it, why don't you look at the evidence? OK, so this has been this has been looked at to death. This is again, this is a bit of a cumulative show. We're not new to astrology. We've talked about it before on the show. Just quickly, there's been, a score of studies looking at astrology and collectively they show that it doesn't work, right? There is nothing to it. There are no patterns that you can tie to astrological signs or meanings or whatever. There also isn't one astrology. There are different kinds of astrology and different astrologers don't even agree with each other on what stuff means. It's all metaphor and nonsense. But there's literally nothing to it. There's no mechanism either, like there's no plausible way that the alignment of planets and stars would influence your personality. You know what I mean? So it's just pure magical thinking. But it's a good example of a pretty classic pure pseudoscience. And, then the way that it the kind of readings that you get out of it is a classic cold reading. So it is good to to know about.
E: Oh, Steve. Yeah, I mentioned something?
S: Sure.
E: It's a bit of a tangent, but it is an app. And I saw it yesterday. And there's an app for throwing your phone into the air and measuring how far you can throw it into the air.
S: Oh, yeah? It sounds like a dangerous app.
E: I might say, right. But in a way, less dangerous than this astrology app. I don't know. I was just thinking that the other day. You know, like like what? OK, there's an app for everything. I mean, yeah, and even more than everything in some ways. That was my point.
S: All right. One more quick one.
Email #2: Processing Grief (1:23:25)
S: This one comes from Brendan, who writes, Hello, I am not sure if this qualifies as a critical thinking question. Long story short, someone I had an incidental relationship with died unexpectedly. I did not start crying until I saw the flowers left at the Garden of Remembrance. The thing I'm struggling with is why, with all the empirical evidence before the funeral, I was sad without crying. And then several days later, seeing the floral tributes had triggered the emotional response. I think I thought the data was enough. I am not a fan of flowers or tributes as someone who strives for science. I was shocked by my response. I knew the person was dead the whole time. Why did a bunch of dying flowers several days later push me over the edge to grief? Cara, you want to answer this question really bad.
C: That is the sweetest email. I don't I can't help but feel like did the person's are we not saying their name?
S: Brendan, just his first name.
C: Oh, Brendan, because you're human. You're a human being. You're not a robot. And we don't process our emotions following a scientific algorithm. It doesn't work that way. I wish it did. It would make life a lot easier to manage. But the truth of the matter is, when we talk about the things that we talk about on the show, when we talk about evidence based approaches to life, I think it's really dangerous to think that somehow thoughts and feelings and science and evidence are two different sides of the same coin or that you can utilize science and evidence to control your thoughts and feelings. You're having a grief reaction. Yes. If we were talking about a severe mental illness, if we were talking about diagnosable depression, diagnosable anxiety, bipolar, schizophrenia, there are tricks and tools that we can use in our toolbox to apply scientific principles to help increase emotion regulation, things of that nature. That's not what we're talking about here. You lost somebody and you tried really, really hard to use your cognitive skills, to intellectualize your reaction. But then you felt something authentic and grief doesn't follow a specific pattern. When we talk about the stages of grief, that you read about a lot. In some ways, it's kind of like talking about love languages. Like it's not very evidence based. Some people follow, utilize some of them. Some don't utilize any of them. The truth of the matter is there's no right way to mourn. There's no right way to grieve. It comes in fits and starts. Sometimes it's worse, sometimes it's better. And sometimes little things hit us at times we don't expect.
S: Yeah, you process grief, emotions differently than you process information, facts, logic. It's literally different parts of your brain. And there's different levels of conscious versus subconscious. And emotion is often processed on the subconscious. In fact, I think they would call it a process level. And it is that way. I remember, like after Perry died, it's the same thing. Like you don't necessarily cry right away, but then something triggers it. You know, for me, like a big trigger is always like when I have to talk to somebody else about it. Like if I have to, when I tell somebody, verbalizing it, absolutely brings it to the fore. And it's not like I didn't-
B: Me too.
S: Of course, I knew before then that the heart, like whatever, our father died or Perry died or whatever, like when we suffered this loss. I knew it intellectually. But it's just the emotion gets processed when you verbalize it or when you see a representation of it or whatever. You know, you don't realize that emotionally you might have been putting it at a little bit of a distance and then it comes crashing through because something.
C: It's why we use certain kind of pithy sayings in therapy sometimes. And obviously, this is not to be translated literally, but saying it out loud often makes it true. You know, obviously it was true and you knew it was true. But when you say it out loud, now you're confronting it with your whole brain. You're confronting it with your whole self. And the truth of the matter is you will continue to have those experiences. There will be anniversaries. There will be reminders. We often have these cycles of grief that come up on every single birthday, on every single death day. They can come back. They can be very difficult to process. That's natural. It's normal and it's human. And I think the one thing that maybe we didn't touch on, which is important, is that very often immediately after a death, we throw ourselves into cognitive experiences in order to mitigate or sort of temper the pain that we're feeling. And very often we're forced to do that if we are a family member or somebody who's responsible for plans. And when that happens, we are almost utilizing a coping mechanism where we're distancing ourselves from the feeling in an effort to survive in the day to day. But you can only do that for so long. And so it's not uncommon for some people that there's a delayed reaction where they get triggered because they've actually been trying not to feel those feelings fully because it's painful to do so.
S: Yeah, I think it's an evolved defense mechanism. You don't want to be overwhelmed all at once with all of the emotions of something. So your brain kind of gives you time to process it over time.
C: And it's cultural too, right? In some cultures, really going into it and wailing and letting all those feelings out is culturally prescribed. And in other cultures, I mean, we think about gender differences. We think about expectations within the family, religious expectations. All these things combine where you might have pressure to not have an outward expression or to not, be, quote, weak or to, quote, cry. I'm not endorsing any of those things, by the way. I'm just saying that they are the reality of what life is like for a lot of people.
S: All right. Let's move on with science or fiction.
Science or Fiction (1:29:24)
Theme: Technology news
Item #1: Researchers have achieved a new data rate record of 40 petabits (Pb) per second in a standard commercially available optical fiber.* [8]
Item #2: Scientists present a new gene editing system based on transposable elements that is 10 times more efficient than existing systems.[9]
Item #3: Engineers have made a thin film organic light harvesting system with 38% efficiency, a technique that can be utilized for photovoltaics.[10]* The National Institute of Information and Communications Technology (NICT) is Japan's primary national research institute for information and communications
| Answer | Item |
|---|---|
| Fiction | 40 Pb/s fiber data rate |
| Science | Gene editing 10x efficiency |
| Science | Photovoltaics light harvesting |
| Host | Result |
|---|---|
| Steve | swept |
| Rogue | Guess |
|---|---|
Jay | 40 Pb/s fiber data rate |
Bob | 40 Pb/s fiber data rate |
Evan | 40 Pb/s fiber data rate |
Cara | 40 Pb/s fiber data rate |
Voice-over: It's time for Science or Fiction.
S: Each week, I come up with three science news items or facts, two real and one fake. And then I challenge my panel of skeptics to tell me which one is the fake. We have three news items this week, but there is a theme. The theme is technology. Ready? All right. Here we go. Item number one. Researchers have achieved a new data rate record of 40 petabits per second.
B: A!
S: In a standard commercially available optical fiber. Number two, scientists present a new gene editing system based on transposable elements that is 10 times more efficient than existing systems. And item number three, engineers have made a thin film organic light harvesting system with 38 percent efficiency, a technique that can be utilized for photovoltaics. All right, Jay, go first.
Jay's Response
J: All right. This first one here, data rate record of 40 petabits per second in a standard commercially available optical fiber. Forty petabits per second. Compared to like what? What's the normal data transfer rate that we deal with on a day, you know?
E: Yeah. Depends on where you are.
S: That would be good to know.
B: Jay, what's your what's your fiber download?
J: It's like, like 500.
B: 500 megabit, right?
J: Yeah.
E: So this would be, oh man, petabits. That's way out there.
J: Yeah, it's phenomenal. I mean, for fiber optic. Yeah, I mean, with standard fiber optic cable, I mean, there's an incredible amount of bandwidth potential on a fiber optic cable because you could just use different frequencies of light. Yeah, maybe. Yeah. I mean, that might be possible. I don't know. I don't know what the I don't know. That's a tough one because I just don't know the what the limiting factors are today. I know that like the computers themselves cannot transmit and receive data that fast. You know, it's a limitation of how fast the processors can handle it. But the pipe itself, I mean, they're saying that they have a data rate record of 40 petabits per second. I don't know. OK, I mean, I think that's a maybe. All right. The second one, scientists present a new gene editing system based on transposable elements that is ten times more efficient than existing systems. That's OK. So it's ten times more efficient, order of magnitude more efficient than existing systems. I mean, I don't think that's crazy. I think, an order of magnitude increase in something like that seems very reasonable. The last one, engineers have made a thin film organic light harvesting system with a 38 percent efficiency, a technique that can be utilized for photovoltaics. Well, 38 percent efficiency is fantastic. That's the highest number I've ever heard for that type of thing. God damn, that's that'd be great if that was true. So I think the photovoltaic is true. It doesn't mean that it is scalable. But sure, I think that one's science. I think that they created that. Then between the first one, which is the 40 petabits and the second one, I think the 40 petabits is not correct. I think that that number is too high.
S: OK, Bob.
Bob's Response
B: Hang on. I'm doing some calculations in my head. Let's go with three thin film organic light harvesting system. 38 percent efficiency. Yeah. Wow. So, man, what are those numbers? Photovoltaic. I don't know. That's up there. But is that beyond the theoretical limit? Man, it's too close. I forget. Let's look at two gene editing based on transposable elements. 10 times more efficient. That would be wonderful because as great as CRISPR is. I mean, you can't do a lot. You know, you can't do big chunks of DNA updates with it. So that would be cool. And seems they could have found another technique beyond CRISPR. That would be wonderful. All right. So let's go to this first one here. 40 petabits per second. I mean, that's-
J: That's too damn high.
B: That's so high. That's that's something. I mean, I just did a quick mental calculation. I mean, that could potentially be 10,000 times better than conventional fiber. That's a hell of a leap. Yeah. But maybe they're just instead of going from, say, 500 gig gigabit, maybe they were already in the terabit range. In that case, it would be a couple of thousand, a few thousand times better. Still pretty intense. Ah, crap. I know I'm going to get busted on this one. I'll say that one's that one's fiction.
C: Which one?
S: The petabit.
B: Yeah.
S: OK. Evan?
B: I'm not confident.
Evan's Response
E: All right. Here's my reasoning. About the 40 petabits, and this is my problem because I refer to things I bring up or I did a news item in the past about. And then I have to kind of integrate it into this. And it usually leads me astray. However, here's what happened. Petabits. When I see petabits, I think of also petawatts. And when we did our special episode about the when we did it from the year 2035, we went into the future and record and record an episode. And my news item that in that episode had to do with a laser that generated a 50 petawatts or a series, right? 50 petawatts of power.
C: I don't remember that.
E: Yeah, it's weird because because, I don't know.
B: Petawatts are awesome.
E: The petabits that came up in this, in the science of fiction is now filed in the same file as that. They were just right. They live together in my brain now. And then I got into Cara. It goes even further. I got feedback from people on that news item, at least one, maybe two people who said that 50 petawatts in the year 2035, that will not even be a reality. You're you're you were too far off on your estimate. So I'm using that information to inform me here that the 40 petabits one is the fiction, because if petabits versus petawatts in some weird way line up, then 40 petabits now, not a chance. It would not it would not have happened. So that's my reason. Obscure as it is.
S: That's it, huh?
E: That's it.
S: OK, Cara?
Cara's Response
C: You think I'm going to part from the pack in something where I literally have no idea. Like when you read all of these, I was like, I don't. Why am I going last? You could have had me go anytime.
S: Being nice.
C: I'm going to go with the group. And my reasoning, Evan.
E: Yes, I want to hear.
C: And Jay and Bob is because when you read the first item and you said researchers have achieved a new data rate record of 40 petabits per second, Bob goes, ah, so I'm going to go with that is the fiction.
E: Cara, we need to play poker with Bob.
C: I know.
B: Yeah.
J: Bob's emotional reaction to these items is very telling.
B: If we're having if we're playing cards and I make that noise, somebody just put down six aces with no wild cards.
Steve Explains Item #3
S: I will. Let's start with the third one. Engineers have made a thin film organic light harvesting system with 38 percent efficiency, a technique that can be utilized for photovoltaics. You guys all think this one is science and this one is science. This one is science. So, yeah, this is a very interesting technology that they're dealing with here. So first of all, you know that we have multiple different types of photovoltaics. You have the silicon right now are, the industry standard. They're pretty high efficiency getting into like the mid 20s. They have great longevity, but they're rigid and they're heavy. You have the perovskite ones are coming, probably in combination with silicon. They have a potentially higher efficiency and they're lighter overall, but they're not that stable. They're not as stable as silicon. But they're working on that. They're working on the stability issue. And then there's the organic solar cells, which are a lot lighter. A lot thinner. Be easy to put them anywhere, but they have a lot lower efficiency. They're just getting north of 15 percent now. So they're starting to get to the point where they're commercially viable.
B: Damn, 38?
S: But this is doing now. How does it how does it achieve 30? It's first of all, what they weren't looking at a photovoltaic, which is why I had to say it could be applied to photovoltaics. The technique could be used in photovoltaics, but that wasn't the study that was done. They were looking at fluorescence, the brightness of fluorescence, which, from which is another way to measure how much light is getting absorbed. So that's why it's an energy. It's a light harvesting system. Now, what they do is they take four different dyes, four different colored organic dyes, and they arrange them. They fold them up into like one metastructure. The idea is that it will capture the full visible spectrum of light because you're using these different colored dyes. And because of the structure, it'll prevent light from leaking away or bouncing away, right? So it'll capture a much greater percentage of the light. So individually, like individually, they only capture less than three percent efficiency. But together they get up to 38 percent. So, again, this is sort of in the laboratory proof of concept stage. But hopefully this approach could be applied to designing a photovoltaic or an organic solar cell that has even if you get this, the organic solar cells into the 20s where it can compete with silicon. But again, it's a lot lighter, cheaper. You could sort of print this stuff. That could be a huge leap forward.
B: Oh my God, can you imagine print it and throw it willy nilly? Damn.
Steve Explains Item #1
S: So let's go back to number one. Researchers have achieved a new data rate record of 40 petabits per second in a standard commercially available optical fiber. You guys all think this one is the fiction, but let me give you some information about it before I reveal whether we be receiving the information. So let me tell you what the previous record was. The previous record by the same group was 300 terabits per second.
B: Oh, was it? Was it that high?
S: Yes.
J: Oh, wow.
S: 300 terabits. And so the thing is, this is this. That doesn't mean that you can hook up your fiber optic cable to your home and get that data rate, right? That's not, obviously, because as Jay pointed out, there's a lot of other elements to the system. What they're doing is figuring out how to use different bandwidths of light in these fiber optic cables in order to squeeze as much data throughput as possible. So these are like pushing the theoretical limits of fiber optic by using all these available channels. These who I'm getting the thunder here now, too.
B: So how many terabits was the previous?
S: So 300 terabits.
B: 300.
S: And they broke their record and they pushed it to 400 terabits. So I, yeah, I bumped it up a couple of orders of magnitude to make it fair.
E: Woohoo.
S: But yeah-
E: Thank you. Year 2035.
B: You lucked out, Evan, because comparing watts to bits.
S: That's totally specious. Yeah, very sketchy.
E: I get it.
S: Yeah. You backed into that one.
Steve Explains Item #2
S: All right. That means that scientists present a new gene editing system based on transposable elements that is 10 times more efficient than existing systems is science. This is the cool one here.
B: This is huge. I just read this 25 minutes ago. And I'm like, I'm talking about this next week. And now Steve probably won't let me because it's science or fiction.
S: Yeah, I'm talking about it right now.
C: You could do a deeper dive.
S: We will see. So basically, I mean, it's brilliant because like transposable elements, this is what they do, that they're basically little chunks of DNA that get inserted at specific locations in the DNA of a plant. For example. And so what they're doing is they're combining it with the like Cas9 system from like the CRISPR system. And what you end up with is this chunk of DNA or is it RNA?
B: It's RNA based.
S: It's RNA based, yeah. That it gets inserted with precision at a specific location in the plant's genome. So and it's 10 times as efficient as the just using the CRISPR. So, the problem with with CRISPR, again, it's fast, cheap. It's great for research, et cetera. But but for practical applications, the problem is that it has a very low percentage of getting, it's great at like making the cut where you want to make the cut, not not as great at getting, inserting the gene you want to insert where you want it to go. There's a lot of off target, effects. And you don't always get the gene in place. The efficiency of this system is much higher. It's an order of magnitude higher. So 10 times is great. So this could basically the application of this would be for GMOs, right? That would be like the real target application. Just, designer plants where you get much more quickly and precisely and inexpensively engineer plants with whatever alteration you want.
B: Yeah. And part of it, from what I gathered quickly, I don't know, a little while ago when I actually read it, was that it's the sheer quantity that you could do. I mean, you could like huge chunks of DNA you could you could you could add, which will help things with like, synthetic biology and creating, genomes from scratch. You could you could use this. And I would think that this has the potential. I kind of see in it with just a quick little read. I mean, CRISPR's days could be numbered. I mean, you couldn't just use this even if you want it for on a smaller scale because it's so much more precise.
S: Well, again, I think they'll have different applications that they're better designed for. My sense is this is specific to plants.
B: Oh, that wasn't my take. But I just did I didn't probably read as much as you did. But I don't I don't think it was just for plants.
S: Maybe it could be applied. But this is they're using a transposable elements that exist in plants. So I know that's what the research, that's what they were researching, whether or not they could apply this to other genomes. I don't know. But there's this is specific to plant genomes. But for now.
S: But yeah, there's multiple, multiple genetic manipulation tools now that I think are going to be mainly complementary. You know what I mean? Like there'll be different ones for different purposes. But yeah, just, you feel like we thought like CRISPR was a big advance and it was, but it was just the beginning, really, of our ability to to control genetic sequences with treatment and lots of different applications. So good job, guys.
E: Yes.
S: That was a fun one.
E: That was a fun.
J: Thank you. I'll take all the credit for that.
B: I got it. I got to make that noise strategically in the future when I don't want to throw you guys off.
S: No, don't do that. I will find some way to penalize you for doing it.
C: Now we know.
B: Yeah, I would never do that. But I want to re-listen to this episode to see if I could hear Steve cringing as I made that noise.
S: That's why I didn't matter what order you blew it. So I didn't matter what order.
C: Amazing.
S: There's no way Cara was going to not vote for that one is the fiction after you basically gave it away.
B: I couldn't help it. It was involuntary. My apologies.
S: My only hope is that I could get you to talk yourself out of it.
B: Yes. Which you are very good at doing. You bastard.
S: But I was hoping you will Steve put that there because he knew it would fool me.
B: Yeah, yeah. But cross my mind.
S: I thought maybe you were. Yeah, you were. You were flirting with that idea, but not enough. All right. Evan, give us a quote.
Skeptical Quote of the Week (1:45:57)
Rarely do the advocates of cleanses explain what is meant by toxins. It is one of those nebulous pseudoscientific terms rolled out by people deliberately avoiding the specificity required for a science-based analysis. It's the modern-day equivalent of "evil spirits," vague enough to mean just about anything while retaining the ring of scientific legitimacy.
– Timothy Caulfield (1963-present), Canadian professor of law
E: All right. Hey, you guys, we're going to be out at SciCon this year in October. October 24th through the 27th is SciCon. We're going to be out there. And here's a quote from one of the presenters who's going this year as well. "When I talk about information literacy, it's understanding what sources are more reliable than others. People have to understand their own biases and their own errors and understand that it interferes with their ability to use that information." Melanie Tresick King, associate professor of biology at Massasoit Community College, where she teaches a general education science course designed to equip students with empowering critical thinking, information, literacy and science literacy skills.
S: Awesome.
E: Very much looking forward to hearing her talk.
S: Absolutely. All right. Well, thank you all for joining me this week.
J: You got it brother.
C: Thanks, Steve.
Signoff
S: —and until next week, this is your Skeptics' Guide to the Universe.
S: Skeptics' Guide to the Universe is produced by SGU Productions, dedicated to promoting science and critical thinking. For more information, visit us at theskepticsguide.org. Send your questions to info@theskepticsguide.org. And, if you would like to support the show and all the work that we do, go to patreon.com/SkepticsGuide and consider becoming a patron and becoming part of the SGU community. Our listeners and supporters are what make SGU possible.
Today I Learned
- Fact/Description, possibly with an article reference[11]
- Fact/Description
- Fact/Description
References
- ↑ [url_from_show_notes _publication_: _article_title_]
- ↑ Space.com: How the GOES-U satellite will change Earth and space weather forecasts forever
- ↑ Neuroscience News: Cannabis Use Linked to Severe COVID-19
- ↑ ScienceAlert: Teen Cannabis Use Dramatically Raises Risk of Psychotic Disorders
- ↑ Nature Communications, via Trinity College Dublin: Scientists devise algorithm to engineer improved enzymes
- ↑ Metro UK: What is geopathic stress – and is it a threat to our health?
- ↑ Alzheimer's Association: Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models
- ↑ NICTNational Institute of Information and Communications Technology, Japan's primary national research institute for information and communications: World Record 402 Tb/s Transmission in a Standard Commercially Available Optical Fiber
- ↑ Nature: Transposase-assisted target-site integration for efficient plant genome engineering
- ↑ Cell: Panchromatic light-harvesting antenna by supramolecular exciton band engineering for heteromeric dye foldamer
- ↑ [url_for_TIL publication: title]
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