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  • MICHAEL SHORT: All right, guys.

  • So today I'm not going to be doing most of the talking.

  • You actually are, because, like I've said,

  • we've been teaching you all sorts of crazy physics

  • and radiation biology.

  • We've taught you how to smell bullshit,

  • taught you a little bit about how to read papers

  • and what to look for.

  • And we're going to spend the second half of today's class

  • actually doing that.

  • Well, we're going to have a mini debate on whether or not

  • hormesis is real.

  • And you guys are going to spend some time finding

  • evidence for or against it.

  • Instead of just me telling you this is what hormesis is

  • or isn't.

  • So just to finish up the multicellular effects

  • from last time, we started talking

  • about what's called the bystander effect, which says,

  • if a cell is irradiated, and it dies

  • or something happens to it, the other cells nearby notice.

  • And they speed up their metabolism,

  • their oxidative metabolism, which

  • can generate some of the same chemical byproducts

  • as radiolysis does, causing additional cell

  • damage and mutation.

  • And there was an interesting--

  • yeah, I think I left-- we left off here at this study,

  • where they actually talked about most

  • of the types of mutations found in the bystander

  • cells were of different types.

  • But there were mutations found, in this case,

  • as a result of what's called oxidative-based damage.

  • This is oxidative cell metabolism

  • ramping up and producing more of those metabolic byproducts that

  • can damage DNA as well.

  • What we didn't get into is the statistics.

  • What do the statistics look like for large sample sizes

  • of people who have been exposed to small amounts of radiation?

  • I'm going to show you a couple of them.

  • One of them is the folks within 3 kilometers of the Hiroshima.

  • So I want you to notice a couple of things.

  • Here is the dose in gray, maxing out at about two gray.

  • And in this case this ERR is what's

  • called Excess Relative Risk.

  • It's a little different than odds

  • ratio, where here an excess relative risk of 0

  • means it's like nothing happened.

  • So anything above 0 means extra excess relative risk.

  • So what are some of the features you notice about this data?

  • What's rather striking about it in your opinion?

  • Yeah?

  • Charlie?

  • AUDIENCE: [INAUDIBLE] so in the [INAUDIBLE]

  • timeline from [INAUDIBLE] timeline here.

  • MICHAEL SHORT: This one?

  • AUDIENCE: Yeah.

  • MICHAEL SHORT: Oh, yeah, these are the errors.

  • Yep.

  • What does it say here?

  • Is it-- more than one standard error Yeah.

  • AUDIENCE: There's a lot of variability?

  • MICHAEL SHORT: Yeah, I mean, look

  • at the confidence in this data at high doses.

  • And then while you may say, OK, the amount of relative risk

  • per amount of radiation increases

  • with decreasing dose, which is the opposite of what

  • you might think, our confidence in that number

  • goes out the window.

  • Now what do you think of the total number of people that led

  • to each of these data points?

  • How many folks do you think were exposed to gray

  • versus milligray of radiation?

  • AUDIENCE: A lot less for gray than [INAUDIBLE]..

  • MICHAEL SHORT: That's right, the sample size.

  • I thought it was cold and loud in here.

  • The sample size for the folks in gray is much smaller.

  • And yet the error bars are much smaller too.

  • That's not usually the way it goes, is it?

  • Usually, you think larger sample size, smaller error bars,

  • unless the effects themselves and confounding variables are

  • hard to tease out from each other.

  • If you then look at another set of people,

  • all of the survivor-- oh. yeah, Charlie?

  • AUDIENCE: How did they determine the-- the doses [INAUDIBLE]??

  • MICHAEL SHORT: This would have to be from some estimate.

  • This would be from models.

  • It's not like folks had dosimeters everywhere

  • in Japan in the 1940s.

  • But this-- these would be estimates

  • depending on where you lived, let's

  • say in an urban, suburban, or rural area,

  • let's see, things like milk intake

  • right after the bomb, or anything that would have given

  • you an unusually high amount of radiation,

  • distance where the winds were going.

  • This is the best you could do with that data.

  • And now look at all of the bomb survivors,

  • including the ones outside 3 kilometer region,

  • but still got some dose.

  • What's changed?

  • AUDIENCE: It seems like they're less likely to get

  • more risk for less dose.

  • MICHAEL SHORT: Yeah, the conclusion

  • is almost flipped for the low dose cases.

  • If you put them side by side, depending on the folks living

  • within 3 kilometers of the epicenter of Hiroshima

  • versus anyone exposed, all the bomb survivors,

  • you get an almost opposite conclusion for low doses,

  • despite the numbers being almost,

  • you know, within each others confidence

  • intervals for high doses.

  • So what this tells us is that the effects of high dose

  • are relatively easy to understand and quite obvious

  • even with low sample sizes.

  • What is different between these two data sets?

  • Well, it's the only difference that's actually listed here.

  • Distance from the epicenter, right?

  • So before I tell you what's different,

  • I want you guys to try to think about what

  • could be different about the folks living

  • within 3 kilometers of the epicenter of Hiroshima

  • versus anyone else in the city or the countryside?

  • Yeah?

  • AUDIENCE: Would it be like [INAUDIBLE]??

  • It seems like a the closer, like, it

  • would be a lot more instances where you get a higher dose.

  • So they're underestimating [INAUDIBLE]..

  • MICHAEL SHORT: Could be, yeah.

  • It might be harder to figure out exactly how much dose folks had

  • without necessarily measuring it, right?

  • But what other major factors or confounding variables

  • are confusing the data here?

  • Yeah?

  • AUDIENCE: Wouldn't a lot of people who lived closer,

  • like, not inside the radiation, like,

  • the actual shockwave and heat from the bomb [INAUDIBLE]??

  • MICHAEL SHORT: So in this case, these are for bomb survivors.

  • So, yes, that's true.

  • If you're closer, you get the gamma blast.

  • You get the pressure wave.

  • AUDIENCE: But like, even if you survive that, it still like

  • would affect them in addition to radiation.

  • Is it counting for people who got injured from that too?

  • MICHAEL SHORT: It should just account all survivors, yeah.

  • AUDIENCE: So if they were injured,

  • that could change how they reacted to the radiation

  • exposure.

  • MICHAEL SHORT: Sure.

  • Absolutely.

  • And then the other big one is, actually,

  • someone's kind of mentioned it, but in passing, urban or rural.

  • The environment that you live in depends on

  • how quickly, let's say, the ecosystem replenishes or not

  • if you live in a city or what sort of other toxins

  • or concentrated sources of radiation

  • you may be exposed to by living in a city that's

  • endured a nuclear attack or something else.

  • It could also depend on the amount of health care

  • that you're able to receive.

  • If you show some symptoms of something,

  • if you live way out in the countryside,

  • and there weren't a lot of roads,

  • then maybe you can't get to the best hospital,

  • or you go to a clinic that we don't know as much.

  • The point is, there's a lot of confounding variables.

  • There's a lot more people.

  • But anything from like lifestyle,

  • to diet, to relative exposure, think about the differences

  • in how folks in the city and out in the countryside

  • may have been exposed to the same dose,

  • because, again, dose is given in gray, not in sieverts.

  • That's the best we can estimate.

  • But would it matter if you were to exposed

  • to let's say, alpha-particle containing fallout

  • that you would then ingest versus

  • exposed to a lot of gamma rays or delayed betas.

  • It absolutely would.

  • So the type of radiation and the route of exposure in the organs

  • that were affected are not accounted for in the study

  • because, again, the data is in gray.

  • It's just an estimated joules per kilogram

  • of radiation exposure, not taking into account the quality

  • factors for tissue, the quality factors for type of radiation,

  • the relative exposure, the dose rate,

  • which we've already talked about.

  • How much you got as a function of time actually does matter.

  • So all these things are quite important.

  • And for all these sorts of studies,

  • you have to consider the statistics.

  • So let's now look at a--

  • I won't say, OK, a cellphone-like study

  • where one might draw a conclusion if the error

  • bars weren't drawn.

  • So based on this, can you say that very low doses

  • of radiation in this area actually

  • give you some increased risk of, what do they say,

  • female breast cancer?

  • No.

  • You can't be bold enough to draw a conclusion from the very

  • low dose region from, let's say, the-- the 1s to 10s

  • of milligray, that whole region right there that people

  • are afraid of getting, we don't actually

  • know if it hurts or it has nothing, or if it helps.

  • That's a kind of weird thing to think about.

  • So the question is, what do we do next?

  • These are the actual recommendations from the ICRP.

  • And I've highlighted the parts that

  • are important, in my opinion, for everyone to read.

  • And the most important one, probably we'll

  • have to come to terms with some uncertainty

  • in the amount of damage that little amounts of dose do.

  • So this is the ICRP saying to the general public,

  • you guys should chill out.

  • There's not much we can do about tiny amounts of exposure.

  • They happen all the time.

  • You can either worry about it, and get your heart rate up,

  • and elevate your own blood pressure,

  • and have a higher chance of dying on your own,

  • or you can just chill out because there is not

  • enough evidence to say whether a tiny little amount

  • of radiation, and we're talking in the milligray or below,

  • helps, or hurts, or does nothing, which leads me

  • into the last set of slides for this entire course,

  • they're not that long because I want you guys to actually

  • do a lot of the work here, is radiation hormesis, real

  • or not?

  • There are plenty of studies pointing one way or the other.

  • And I want to show you a few of them with some other examples.

  • The whole idea here is that a little bit of a bad thing

  • can be a good thing, much like vitamins,

  • or, let's say, vitamin A in seal livers, a little bit of it

  • you need.

  • It's a vital micronutrient.

  • A whole lot of it can do a whole lot of damage.

  • You don't usually think of that being the case for radiation.

  • But some studies may have you believe otherwise

  • with surprisingly high sample sizes.

  • So the idea here is that if you've got anything, not just

  • element and diet, but anything that happens to you,

  • there's going to be some optimum level where you could

  • die or have some ill effects if exposed

  • to too much or too little.

  • We all know that this happens with high amounts of radiation.

  • The question is, is that actually happened?

  • So let's look at some of the data.

  • In this case, I mentioned selenium and actually