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MICHAEL SHORT: All right, guys.

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

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00:00:27,620 --> 00:00:30,510
You actually are,
because, like I've said,

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00:00:30,510 --> 00:00:32,940
we've been teaching you
all sorts of crazy physics

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00:00:32,940 --> 00:00:34,500
and radiation biology.

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00:00:34,500 --> 00:00:36,870
We've taught you how
to smell bullshit,

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00:00:36,870 --> 00:00:39,000
taught you a little bit
about how to read papers

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00:00:39,000 --> 00:00:40,260
and what to look for.

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00:00:40,260 --> 00:00:42,635
And we're going to spend the
second half of today's class

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00:00:42,635 --> 00:00:43,680
actually doing that.

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00:00:43,680 --> 00:00:46,710
Well, we're going to have a
mini debate on whether or not

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hormesis is real.

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And you guys are going to
spend some time finding

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00:00:49,890 --> 00:00:52,038
evidence for or against it.

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Instead of just me telling
you this is what hormesis is

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00:00:54,330 --> 00:00:55,930
or isn't.

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00:00:55,930 --> 00:00:58,600
So just to finish up the
multicellular effects

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00:00:58,600 --> 00:01:00,130
from last time,
we started talking

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

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if a cell is
irradiated, and it dies

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00:01:05,560 --> 00:01:08,440
or something happens to it,
the other cells nearby notice.

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And they speed up
their metabolism,

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00:01:10,110 --> 00:01:12,520
their oxidative
metabolism, which

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can generate some of the
same chemical byproducts

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as radiolysis does,
causing additional cell

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00:01:17,642 --> 00:01:18,475
damage and mutation.

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00:01:21,270 --> 00:01:23,350
And there was an interesting--

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00:01:23,350 --> 00:01:26,440
yeah, I think I left-- we
left off here at this study,

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00:01:26,440 --> 00:01:28,090
where they actually
talked about most

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00:01:28,090 --> 00:01:31,300
of the types of mutations
found in the bystander

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cells were of different types.

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00:01:32,800 --> 00:01:35,890
But there were mutations
found, in this case,

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00:01:35,890 --> 00:01:38,710
as a result of what's called
oxidative-based damage.

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00:01:38,710 --> 00:01:40,690
This is oxidative
cell metabolism

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00:01:40,690 --> 00:01:44,590
ramping up and producing more of
those metabolic byproducts that

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can damage DNA as well.

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00:01:47,610 --> 00:01:50,320
What we didn't get
into is the statistics.

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00:01:50,320 --> 00:01:53,650
What do the statistics look
like for large sample sizes

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00:01:53,650 --> 00:01:57,525
of people who have been exposed
to small amounts of radiation?

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00:01:57,525 --> 00:01:59,150
I'm going to show
you a couple of them.

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00:01:59,150 --> 00:02:03,820
One of them is the folks within
3 kilometers of the Hiroshima.

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00:02:03,820 --> 00:02:06,510
So I want you to notice
a couple of things.

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00:02:06,510 --> 00:02:09,699
Here is the dose in gray,
maxing out at about two gray.

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00:02:09,699 --> 00:02:11,980
And in this case
this ERR is what's

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called Excess Relative Risk.

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00:02:13,755 --> 00:02:15,130
It's a little
different than odds

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ratio, where here an
excess relative risk of 0

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means it's like
nothing happened.

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00:02:21,820 --> 00:02:24,890
So anything above 0 means
extra excess relative risk.

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00:02:24,890 --> 00:02:28,120
So what are some of the features
you notice about this data?

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What's rather striking
about it in your opinion?

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Yeah?

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00:02:37,580 --> 00:02:38,420
Charlie?

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AUDIENCE: [INAUDIBLE]
so in the [INAUDIBLE]

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timeline from [INAUDIBLE]
timeline here.

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MICHAEL SHORT: This one?

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AUDIENCE: Yeah.

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

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Yep.

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What does it say here?

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Is it-- more than one
standard error Yeah.

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AUDIENCE: There's a
lot of variability?

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MICHAEL SHORT:
Yeah, I mean, look

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at the confidence in
this data at high doses.

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

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per amount of
radiation increases

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with decreasing dose, which
is the opposite of what

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you might think, our
confidence in that number

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goes out the window.

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

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to each of these data points?

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How many folks do you
think were exposed to gray

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versus milligray of radiation?

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

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

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I thought it was cold
and loud in here.

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

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And yet the error bars
are much smaller too.

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

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

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unless the effects themselves
and confounding variables are

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hard to tease out
from each other.

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If you then look at
another set of people,

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

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

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

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This would be from models.

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00:04:00,070 --> 00:04:01,990
It's not like folks had
dosimeters everywhere

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00:04:01,990 --> 00:04:03,280
in Japan in the 1940s.

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But this-- these
would be estimates

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00:04:05,140 --> 00:04:07,360
depending on where
you lived, let's

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00:04:07,360 --> 00:04:10,370
say in an urban,
suburban, or rural area,

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let's see, things
like milk intake

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right after the bomb, or
anything that would have given

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you an unusually high
amount of radiation,

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distance where the
winds were going.

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00:04:21,040 --> 00:04:24,540
This is the best you
could do with that data.

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00:04:24,540 --> 00:04:26,770
And now look at all
of the bomb survivors,

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00:04:26,770 --> 00:04:30,000
including the ones outside
3 kilometer region,

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but still got some dose.

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What's changed?

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00:04:38,000 --> 00:04:41,450
AUDIENCE: It seems like
they're less likely to get

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00:04:41,450 --> 00:04:43,290
more risk for less dose.

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MICHAEL SHORT:
Yeah, the conclusion

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00:04:45,170 --> 00:04:47,840
is almost flipped for
the low dose cases.

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00:04:47,840 --> 00:04:51,470
If you put them side by side,
depending on the folks living

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00:04:51,470 --> 00:04:54,740
within 3 kilometers of
the epicenter of Hiroshima

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00:04:54,740 --> 00:04:58,100
versus anyone exposed,
all the bomb survivors,

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you get an almost opposite
conclusion for low doses,

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00:05:01,160 --> 00:05:02,600
despite the numbers
being almost,

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00:05:02,600 --> 00:05:04,400
you know, within each
others confidence

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00:05:04,400 --> 00:05:06,710
intervals for high doses.

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00:05:06,710 --> 00:05:08,960
So what this tells us is
that the effects of high dose

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00:05:08,960 --> 00:05:12,200
are relatively easy to
understand and quite obvious

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00:05:12,200 --> 00:05:14,060
even with low sample sizes.

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00:05:14,060 --> 00:05:16,790
What is different between
these two data sets?

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00:05:23,910 --> 00:05:27,240
Well, it's the only difference
that's actually listed here.

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00:05:27,240 --> 00:05:29,167
Distance from the
epicenter, right?

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00:05:29,167 --> 00:05:30,750
So before I tell you
what's different,

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I want you guys to try
to think about what

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00:05:33,030 --> 00:05:35,400
could be different
about the folks living

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00:05:35,400 --> 00:05:38,220
within 3 kilometers of
the epicenter of Hiroshima

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00:05:38,220 --> 00:05:43,750
versus anyone else in the
city or the countryside?

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00:05:43,750 --> 00:05:44,380
Yeah?

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AUDIENCE: Would it
be like [INAUDIBLE]??

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00:05:46,210 --> 00:05:48,590
It seems like a the
closer, like, it

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

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So they're underestimating
[INAUDIBLE]..

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MICHAEL SHORT: Could be, yeah.

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

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00:06:01,990 --> 00:06:04,900
without necessarily
measuring it, right?

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00:06:04,900 --> 00:06:08,260
But what other major factors
or confounding variables

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00:06:08,260 --> 00:06:09,860
are confusing the data here?

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00:06:09,860 --> 00:06:10,944
Yeah?

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

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00:06:15,664 --> 00:06:18,690
like, not inside
the radiation, like,

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00:06:18,690 --> 00:06:24,118
the actual shockwave and heat
from the bomb [INAUDIBLE]??

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00:06:24,118 --> 00:06:26,660
MICHAEL SHORT: So in this case,
these are for bomb survivors.

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So, yes, that's true.

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

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00:06:30,260 --> 00:06:31,550
You get the pressure wave.

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

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would affect them in
addition to radiation.

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

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

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AUDIENCE: So if
they were injured,

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that could change how they
reacted to the radiation

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exposure.

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MICHAEL SHORT: Sure.

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Absolutely.

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And then the other
big one is, actually,

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00:06:52,710 --> 00:06:56,628
someone's kind of mentioned it,
but in passing, urban or rural.

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The environment that
you live in depends on

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

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00:07:01,630 --> 00:07:04,510
if you live in a city or
what sort of other toxins

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00:07:04,510 --> 00:07:06,190
or concentrated
sources of radiation

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00:07:06,190 --> 00:07:08,890
you may be exposed to by
living in a city that's

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endured a nuclear attack
or something else.

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00:07:11,558 --> 00:07:13,600
It could also depend on
the amount of health care

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00:07:13,600 --> 00:07:15,220
that you're able to receive.

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00:07:15,220 --> 00:07:16,850
If you show some
symptoms of something,

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00:07:16,850 --> 00:07:18,705
if you live way out
in the countryside,

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00:07:18,705 --> 00:07:20,080
and there weren't
a lot of roads,

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

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

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

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There's a lot more people.

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But anything from
like lifestyle,

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00:07:32,890 --> 00:07:36,160
to diet, to relative exposure,
think about the differences

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00:07:36,160 --> 00:07:38,830
in how folks in the city
and out in the countryside

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00:07:38,830 --> 00:07:41,320
may have been exposed
to the same dose,

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

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That's the best we can estimate.

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But would it matter
if you were to exposed

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00:07:49,150 --> 00:07:52,210
to let's say, alpha-particle
containing fallout

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00:07:52,210 --> 00:07:54,970
that you would
then ingest versus

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00:07:54,970 --> 00:07:58,830
exposed to a lot of gamma
rays or delayed betas.

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00:07:58,830 --> 00:08:00,570
It absolutely would.

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00:08:00,570 --> 00:08:04,722
So the type of radiation and the
route of exposure in the organs

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00:08:04,722 --> 00:08:06,930
that were affected are not
accounted for in the study

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00:08:06,930 --> 00:08:09,630
because, again, the
data is in gray.

189
00:08:09,630 --> 00:08:12,390
It's just an estimated
joules per kilogram

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00:08:12,390 --> 00:08:15,630
of radiation exposure, not
taking into account the quality

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00:08:15,630 --> 00:08:19,230
factors for tissue, the quality
factors for type of radiation,

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00:08:19,230 --> 00:08:21,730
the relative exposure,
the dose rate,

193
00:08:21,730 --> 00:08:23,250
which we've already
talked about.

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

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00:08:27,660 --> 00:08:29,940
So all these things
are quite important.

196
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And for all these
sorts of studies,

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00:08:32,049 --> 00:08:33,600
you have to consider
the statistics.

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So let's now look at a--

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

200
00:08:38,100 --> 00:08:40,470
where one might draw a
conclusion if the error

201
00:08:40,470 --> 00:08:42,830
bars weren't drawn.

202
00:08:42,830 --> 00:08:45,740
So based on this, can you
say that very low doses

203
00:08:45,740 --> 00:08:48,380
of radiation in
this area actually

204
00:08:48,380 --> 00:08:51,770
give you some increased
risk of, what do they say,

205
00:08:51,770 --> 00:08:52,760
female breast cancer?

206
00:08:55,560 --> 00:08:56,730
No.

207
00:08:56,730 --> 00:08:59,880
You can't be bold enough to
draw a conclusion from the very

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00:08:59,880 --> 00:09:04,218
low dose region from, let's
say, the-- the 1s to 10s

209
00:09:04,218 --> 00:09:06,510
of milligray, that whole
region right there that people

210
00:09:06,510 --> 00:09:08,550
are afraid of getting,
we don't actually

211
00:09:08,550 --> 00:09:13,300
know if it hurts or it has
nothing, or if it helps.

212
00:09:13,300 --> 00:09:16,585
That's a kind of weird
thing to think about.

213
00:09:16,585 --> 00:09:18,210
So the question is,
what do we do next?

214
00:09:18,210 --> 00:09:20,730
These are the actual
recommendations from the ICRP.

215
00:09:20,730 --> 00:09:23,130
And I've highlighted
the parts that

216
00:09:23,130 --> 00:09:26,460
are important, in my opinion,
for everyone to read.

217
00:09:26,460 --> 00:09:30,800
And the most important
one, probably we'll

218
00:09:30,800 --> 00:09:33,470
have to come to terms
with some uncertainty

219
00:09:33,470 --> 00:09:37,400
in the amount of damage that
little amounts of dose do.

220
00:09:37,400 --> 00:09:40,760
So this is the ICRP saying
to the general public,

221
00:09:40,760 --> 00:09:42,720
you guys should chill out.

222
00:09:42,720 --> 00:09:46,070
There's not much we can do
about tiny amounts of exposure.

223
00:09:46,070 --> 00:09:47,570
They happen all the time.

224
00:09:47,570 --> 00:09:50,000
You can either worry about it,
and get your heart rate up,

225
00:09:50,000 --> 00:09:51,800
and elevate your
own blood pressure,

226
00:09:51,800 --> 00:09:54,830
and have a higher chance
of dying on your own,

227
00:09:54,830 --> 00:09:57,710
or you can just chill
out because there is not

228
00:09:57,710 --> 00:10:00,170
enough evidence to say
whether a tiny little amount

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00:10:00,170 --> 00:10:03,470
of radiation, and we're talking
in the milligray or below,

230
00:10:03,470 --> 00:10:07,290
helps, or hurts, or does
nothing, which leads me

231
00:10:07,290 --> 00:10:11,850
into the last set of slides
for this entire course,

232
00:10:11,850 --> 00:10:14,250
they're not that long because
I want you guys to actually

233
00:10:14,250 --> 00:10:17,520
do a lot of the work here,
is radiation hormesis, real

234
00:10:17,520 --> 00:10:18,890
or not?

235
00:10:18,890 --> 00:10:21,920
There are plenty of studies
pointing one way or the other.

236
00:10:21,920 --> 00:10:26,330
And I want to show you a few of
them with some other examples.

237
00:10:26,330 --> 00:10:29,030
The whole idea here is that
a little bit of a bad thing

238
00:10:29,030 --> 00:10:31,370
can be a good thing,
much like vitamins,

239
00:10:31,370 --> 00:10:34,730
or, let's say, vitamin A in
seal livers, a little bit of it

240
00:10:34,730 --> 00:10:35,240
you need.

241
00:10:35,240 --> 00:10:36,980
It's a vital micronutrient.

242
00:10:36,980 --> 00:10:39,658
A whole lot of it can do
a whole lot of damage.

243
00:10:39,658 --> 00:10:42,200
You don't usually think of that
being the case for radiation.

244
00:10:42,200 --> 00:10:44,180
But some studies may have
you believe otherwise

245
00:10:44,180 --> 00:10:47,730
with surprisingly
high sample sizes.

246
00:10:47,730 --> 00:10:50,990
So the idea here is that if
you've got anything, not just

247
00:10:50,990 --> 00:10:53,660
element and diet, but
anything that happens to you,

248
00:10:53,660 --> 00:10:57,380
there's going to be some
optimum level where you could

249
00:10:57,380 --> 00:11:00,200
die or have some ill
effects if exposed

250
00:11:00,200 --> 00:11:02,390
to too much or too little.

251
00:11:02,390 --> 00:11:06,900
We all know that this happens
with high amounts of radiation.

252
00:11:06,900 --> 00:11:11,340
The question is, is
that actually happened?

253
00:11:11,340 --> 00:11:13,000
So let's look at
some of the data.

254
00:11:13,000 --> 00:11:15,570
In this case, I mentioned
selenium and actually

255
00:11:15,570 --> 00:11:19,910
have a fair bit of this
data that shows some,

256
00:11:19,910 --> 00:11:23,170
let's say, contradictory
results in this case, where

257
00:11:23,170 --> 00:11:25,540
a whole lots of
different people were

258
00:11:25,540 --> 00:11:28,120
exposed to a certain amount
of selenium accidentally.

259
00:11:28,120 --> 00:11:30,220
I don't think these were
any intentional studies.

260
00:11:30,220 --> 00:11:33,880
But some folks received
massive doses of selenium

261
00:11:33,880 --> 00:11:36,400
and tried-- folks tried
to figure out, well,

262
00:11:36,400 --> 00:11:38,890
what how-- oh, yeah, if you
want to see how much they got.

263
00:11:38,890 --> 00:11:44,050
Remember that you want about 5
micrograms per day on average.

264
00:11:44,050 --> 00:11:47,090
That's a pretty crazy
amount of selenium

265
00:11:47,090 --> 00:11:49,970
that ended up killing
this person in four hours.

266
00:11:49,970 --> 00:11:52,580
But let's look at a sort of
medium dose, something way

267
00:11:52,580 --> 00:11:55,250
higher than you
would normally get.

268
00:11:55,250 --> 00:11:58,640
Two different studies published
in peer-reviewed places--

269
00:11:58,640 --> 00:12:02,870
this one says, "taking
mega doses of selenium,"

270
00:12:02,870 --> 00:12:06,920
so enormous doses, "may
have acute toxic effects

271
00:12:06,920 --> 00:12:08,750
and showed no
decreased incidence

272
00:12:08,750 --> 00:12:13,550
of prostate cancer and
increased prostate cancer rates.

273
00:12:13,550 --> 00:12:15,350
35,000 people.

274
00:12:15,350 --> 00:12:18,770
The same supplements
greatly reduced

275
00:12:18,770 --> 00:12:22,717
secondary prostate cancer
evolution in another study."

276
00:12:22,717 --> 00:12:24,800
Kind of hard to wrap your
head around that, right?

277
00:12:24,800 --> 00:12:28,520
Both these studies were done
with, I'd say, enough people

278
00:12:28,520 --> 00:12:31,368
and came to absolutely
opposite conclusions,

279
00:12:31,368 --> 00:12:33,410
showing that there's
definitely other confounding

280
00:12:33,410 --> 00:12:35,660
variables at work here.

281
00:12:35,660 --> 00:12:37,790
So there's kind of two
solutions to this problem,

282
00:12:37,790 --> 00:12:39,530
increase your sample
size to try to get

283
00:12:39,530 --> 00:12:42,290
a most representative
set of the population

284
00:12:42,290 --> 00:12:45,430
or control for other
confounding variables.

285
00:12:45,430 --> 00:12:46,930
And then the question
is, how do you

286
00:12:46,930 --> 00:12:49,950
model how much is a
good thing to go over

287
00:12:49,950 --> 00:12:52,300
what these models mean.

288
00:12:52,300 --> 00:12:54,760
The one that's described
right now in the public

289
00:12:54,760 --> 00:12:56,920
is called the linear-no
threshold model.

290
00:12:56,920 --> 00:12:59,860
This means that if this
axis right here is bad

291
00:12:59,860 --> 00:13:02,410
and this is axis
right here is amount

292
00:13:02,410 --> 00:13:05,420
that any amount of
radiation is bad for you.

293
00:13:05,420 --> 00:13:07,420
What I think might be a
little bit more accurate

294
00:13:07,420 --> 00:13:09,720
is called the linear
threshold model.

295
00:13:09,720 --> 00:13:11,980
If you remember from
two classes ago,

296
00:13:11,980 --> 00:13:13,570
the ICRP recommends
that, I think,

297
00:13:13,570 --> 00:13:17,740
0.01 microsieverts is
considered nothing officially.

298
00:13:17,740 --> 00:13:19,990
That would mean there is
a threshold below which

299
00:13:19,990 --> 00:13:21,615
we absolutely don't care.

300
00:13:21,615 --> 00:13:22,990
And if there are
any ill effects,

301
00:13:22,990 --> 00:13:25,870
they're statistically
inseparable from anything else

302
00:13:25,870 --> 00:13:27,120
that would happen.

303
00:13:27,120 --> 00:13:29,963
And that would suggest here
this linear threshold model,

304
00:13:29,963 --> 00:13:31,630
where this control
line right here would

305
00:13:31,630 --> 00:13:35,740
be the incidence of whatever
bad happens in the control

306
00:13:35,740 --> 00:13:39,450
population not exposed to
the radiation, the selenium,

307
00:13:39,450 --> 00:13:40,700
the whatever.

308
00:13:40,700 --> 00:13:43,300
There's also a couple of other
ones like the hormesis model,

309
00:13:43,300 --> 00:13:46,090
which says that if
you get no radiation,

310
00:13:46,090 --> 00:13:49,788
you get the same amount of ill
effects as the control group.

311
00:13:49,788 --> 00:13:51,580
If you get a little
radiation, you actually

312
00:13:51,580 --> 00:13:54,460
get less ill effects.

313
00:13:54,460 --> 00:13:56,263
In this case, this
would be like saying

314
00:13:56,263 --> 00:13:58,180
getting a little bit of
radiation to the lungs

315
00:13:58,180 --> 00:14:00,730
could decrease your
incidence of lung cancer.

316
00:14:00,730 --> 00:14:03,935
Does anyone believe that idea?

317
00:14:03,935 --> 00:14:05,560
Getting a little bit
dose to your lungs

318
00:14:05,560 --> 00:14:08,670
could decrease lung cancer?

319
00:14:08,670 --> 00:14:09,470
OK.

320
00:14:09,470 --> 00:14:12,410
And then you reach some
point of crossover point

321
00:14:12,410 --> 00:14:16,260
where, yeah, a lot of
this thing becomes bad.

322
00:14:16,260 --> 00:14:19,540
And the question is,
is radiation hormetic?

323
00:14:19,540 --> 00:14:22,190
Does this region where
things get better actually

324
00:14:22,190 --> 00:14:28,090
lead all the way to x equals
0 as a function of dose?

325
00:14:28,090 --> 00:14:29,670
And I want to skip
ahead a little bit

326
00:14:29,670 --> 00:14:33,110
to some of the studies.

327
00:14:33,110 --> 00:14:36,410
No, I don't want to skip ahead.

328
00:14:36,410 --> 00:14:38,210
There are some non
hormetic models

329
00:14:38,210 --> 00:14:40,400
that have been proposed
in the literature.

330
00:14:40,400 --> 00:14:42,890
It's easy to wrap your head
around a linear model, right?

331
00:14:42,890 --> 00:14:44,030
It's just a line.

332
00:14:44,030 --> 00:14:44,920
More is worse.

333
00:14:44,920 --> 00:14:46,790
But the question is, how much?

334
00:14:46,790 --> 00:14:49,820
So folks have proposed
things like linear quadratic,

335
00:14:49,820 --> 00:14:52,130
where a little bit
of dose is bad.

336
00:14:52,130 --> 00:14:56,450
And then a lot more dose is
more bad as a function of dose.

337
00:14:56,450 --> 00:14:59,090
That's actually kind of what
we saw in the Hiroshima data.

338
00:14:59,090 --> 00:15:01,990
And I'll show you
again in a sec.

339
00:15:01,990 --> 00:15:05,380
So the history of this LNT,
or Linear No-Threshold model,

340
00:15:05,380 --> 00:15:07,450
states the following
four things--

341
00:15:07,450 --> 00:15:09,740
radiation exposure is harmful.

342
00:15:09,740 --> 00:15:13,582
Well, does anyone disagree
with that statement?

343
00:15:13,582 --> 00:15:16,052
I think we all know that
even large-- you know,

344
00:15:16,052 --> 00:15:18,630
at least large amounts of
radiation exposure is bad.

345
00:15:18,630 --> 00:15:21,630
It's harmful at all
exposure levels.

346
00:15:21,630 --> 00:15:23,930
That's the one you
have to wonder.

347
00:15:23,930 --> 00:15:26,570
Each increment of exposure
adds the overall risk,

348
00:15:26,570 --> 00:15:29,090
saying that it's an always
increasing function.

349
00:15:29,090 --> 00:15:30,860
And the rate of
accumulation exposure

350
00:15:30,860 --> 00:15:32,870
has no bearing on risk.

351
00:15:32,870 --> 00:15:34,730
The first one's easy.

352
00:15:34,730 --> 00:15:37,310
We know this is true
because you expose people

353
00:15:37,310 --> 00:15:38,750
to a lot of
radiation, bad things

354
00:15:38,750 --> 00:15:41,660
tend to happen,
deterministically.

355
00:15:41,660 --> 00:15:45,450
The second one, we
already know is false.

356
00:15:45,450 --> 00:15:49,110
If you look at large sample
sets of data, like, the data

357
00:15:49,110 --> 00:15:50,700
we showed before,
there's definitely

358
00:15:50,700 --> 00:15:54,180
a non-linear sort of
relationship going, where

359
00:15:54,180 --> 00:15:56,700
each incremental
amount of exposure

360
00:15:56,700 --> 00:15:59,470
has the same amount
of incremental risk.

361
00:15:59,470 --> 00:16:04,090
We know from a lot of studies
that's not typically true.

362
00:16:04,090 --> 00:16:09,000
Then the question is,
what about these two?

363
00:16:09,000 --> 00:16:10,750
So now it's going to--
we're going to find

364
00:16:10,750 --> 00:16:14,420
and who you some fairly
interesting studies.

365
00:16:14,420 --> 00:16:18,610
In this case, leukemia as a
function of radiation dose,

366
00:16:18,610 --> 00:16:21,430
what do you guys think
about this data set before I

367
00:16:21,430 --> 00:16:23,020
seed any ideas into your heads?

368
00:16:26,660 --> 00:16:29,180
So here is dose and
sieverts, not gray.

369
00:16:29,180 --> 00:16:33,410
And here is odds ratio, relative
risk of contracting leukemia.

370
00:16:38,480 --> 00:16:40,400
If you were to look at
the data points alone,

371
00:16:40,400 --> 00:16:42,389
what would you say?

372
00:16:42,389 --> 00:16:45,110
AUDIENCE: A little bit
of dose is good for you.

373
00:16:45,110 --> 00:16:46,960
MICHAEL SHORT: Yeah,
you might think that.

374
00:16:46,960 --> 00:16:48,418
But look at all
the different types

375
00:16:48,418 --> 00:16:50,520
of models you can draw
through the error bars.

376
00:16:50,520 --> 00:16:51,960
As you could draw
anything going,

377
00:16:51,960 --> 00:16:54,420
let's say, down and then up.

378
00:16:54,420 --> 00:16:57,150
You could draw a linear
no-threshold model,

379
00:16:57,150 --> 00:16:59,250
as long as it got through
this line right here

380
00:16:59,250 --> 00:17:01,530
or a linear quadratic model.

381
00:17:01,530 --> 00:17:04,470
So a study like
this doesn't quite

382
00:17:04,470 --> 00:17:07,760
give you any sort of
measurable conclusion.

383
00:17:07,760 --> 00:17:11,829
A study like this might,
especially considering

384
00:17:11,829 --> 00:17:14,260
the number of people involved.

385
00:17:14,260 --> 00:17:17,200
In this case, this
is the activity

386
00:17:17,200 --> 00:17:21,339
of radon in air as related
to the incidence of lung

387
00:17:21,339 --> 00:17:24,369
cancer per 10,000 people.

388
00:17:24,369 --> 00:17:28,329
Notice the sample size
here, 200,000 people

389
00:17:28,329 --> 00:17:32,620
from 1,600 counties that
comprise 90% of the population.

390
00:17:32,620 --> 00:17:36,310
Chances are you've then
passed the urban-rural divide.

391
00:17:36,310 --> 00:17:38,780
You've then passed any
region of the country.

392
00:17:38,780 --> 00:17:41,200
So by including such a
gigantic sample size,

393
00:17:41,200 --> 00:17:44,540
you do mostly eliminate
the confounding variables.

394
00:17:44,540 --> 00:17:48,700
So, location, you know,
house construction,

395
00:17:48,700 --> 00:17:51,880
urban versus rural,
age, anything else

396
00:17:51,880 --> 00:17:54,408
are pretty much smeared out
in the enormous sample size.

397
00:17:54,408 --> 00:17:55,450
And what do you see here?

398
00:17:59,772 --> 00:18:01,480
AUDIENCE: Looks pretty
good for low dose.

399
00:18:01,480 --> 00:18:03,440
MICHAEL SHORT: Yeah,
you see a fairly

400
00:18:03,440 --> 00:18:05,720
statistically-significant
hormesis

401
00:18:05,720 --> 00:18:08,690
effect, where, you know,
the route of exposure

402
00:18:08,690 --> 00:18:10,040
is very well-known.

403
00:18:10,040 --> 00:18:12,560
Everything else seems to
be controlled for by--

404
00:18:12,560 --> 00:18:15,050
I mean, we've included
something like almost 0.1%

405
00:18:15,050 --> 00:18:17,000
of the US population.

406
00:18:17,000 --> 00:18:17,690
That's not bad.

407
00:18:20,450 --> 00:18:24,770
Other ones for people that get
more specific, targeted dose,

408
00:18:24,770 --> 00:18:27,110
in this case, women who
received multiple x-rays

409
00:18:27,110 --> 00:18:30,680
to monitor lung collapse during
tuberculosis treatment, a group

410
00:18:30,680 --> 00:18:33,320
of people that can
be tightly controlled

411
00:18:33,320 --> 00:18:35,600
and followed very well.

412
00:18:35,600 --> 00:18:38,300
These are numbers with
one standard deviation.

413
00:18:38,300 --> 00:18:40,500
And that, right there so
you can see, is centigray.

414
00:18:40,500 --> 00:18:45,650
So this dose right here
is one gray worth of dose.

415
00:18:45,650 --> 00:18:47,750
That's a pretty toasty
amount of radiation.

416
00:18:47,750 --> 00:18:50,840
But below that,
again, statistically

417
00:18:50,840 --> 00:18:54,290
significant-looking data.

418
00:18:54,290 --> 00:18:56,650
I don't know how many
people were in the study

419
00:18:56,650 --> 00:18:58,400
because I didn't extract
that information.

420
00:18:58,400 --> 00:19:01,025
But it's something you might be
doing in the next half an hour.

421
00:19:03,302 --> 00:19:04,740
AUDIENCE: [INAUDIBLE]

422
00:19:04,740 --> 00:19:06,790
MICHAEL SHORT: Oh, it does.

423
00:19:06,790 --> 00:19:08,200
It says deaths per 10,000 women.

424
00:19:08,200 --> 00:19:10,590
But how many people
were in the study?

425
00:19:10,590 --> 00:19:12,340
The question is, what
is your sample size?

426
00:19:12,340 --> 00:19:15,450
So like in the last study,
it was just 200,000 people

427
00:19:15,450 --> 00:19:17,150
in the samples.

428
00:19:17,150 --> 00:19:19,400
That gives you some pretty
good confidence that you've

429
00:19:19,400 --> 00:19:21,620
eliminated confounding results.

430
00:19:21,620 --> 00:19:23,840
So I don't know how many
folks get tuberculosis

431
00:19:23,840 --> 00:19:27,345
these days in the US, or whether
this was even a US study,

432
00:19:27,345 --> 00:19:28,970
chances are the sample
size is smaller.

433
00:19:28,970 --> 00:19:32,090
So than even if the data
support your idea of hormesis,

434
00:19:32,090 --> 00:19:33,830
you have to call
into question, is

435
00:19:33,830 --> 00:19:36,740
this a large enough, and
a representative enough,

436
00:19:36,740 --> 00:19:39,542
sample size to draw
any real conclusion?

437
00:19:42,500 --> 00:19:43,700
So then let's keep going.

438
00:19:43,700 --> 00:19:45,940
More data needed.

439
00:19:45,940 --> 00:19:47,233
Evidence for a threshold model.

440
00:19:47,233 --> 00:19:49,150
This is probably the
most boring-looking graph

441
00:19:49,150 --> 00:19:51,460
that actually gives
you some idea of,

442
00:19:51,460 --> 00:19:53,770
should there be a threshold
for how much radiation

443
00:19:53,770 --> 00:19:55,000
is a bad thing?

444
00:19:55,000 --> 00:19:58,270
In this case, it's
very careful data.

445
00:19:58,270 --> 00:20:00,910
It's a very carefully-controlled
data set, lung cancer

446
00:20:00,910 --> 00:20:03,807
death from radon in miners.

447
00:20:03,807 --> 00:20:05,890
And folks that are going
down underground probably

448
00:20:05,890 --> 00:20:07,522
have a higher incidence
of lung cancer

449
00:20:07,522 --> 00:20:08,980
overall from all
the horrible stuff

450
00:20:08,980 --> 00:20:12,880
they're exposed to, whether
it's coal or, you know,

451
00:20:12,880 --> 00:20:13,950
if you're mining gypsum.

452
00:20:13,950 --> 00:20:16,130
Oh, there's lots of
nasty stuff down there.

453
00:20:16,130 --> 00:20:17,950
But there is an
additional amount

454
00:20:17,950 --> 00:20:20,620
of deaths responsible
from radon.

455
00:20:20,620 --> 00:20:23,230
Here's your relative
list risk level of 1

456
00:20:23,230 --> 00:20:25,400
and up to 10
picocuries per liter,

457
00:20:25,400 --> 00:20:31,490
which was around the
maximum of the last study.

458
00:20:31,490 --> 00:20:34,520
It's as boring as it
gets, which helps refute

459
00:20:34,520 --> 00:20:36,680
the idea of a linear
no-threshold model,

460
00:20:36,680 --> 00:20:40,190
because if there was a
linear no-threshold model,

461
00:20:40,190 --> 00:20:44,960
this dose versus risk would
be reliably and significantly

462
00:20:44,960 --> 00:20:46,720
going up.

463
00:20:46,720 --> 00:20:48,500
So there's data out
there to support this.

464
00:20:51,170 --> 00:20:53,640
And even-- even better
ones, lung cancer deaths

465
00:20:53,640 --> 00:20:54,720
from radon in homes.

466
00:20:54,720 --> 00:20:56,460
The study was
careful to look at.

467
00:20:56,460 --> 00:20:58,470
If you look at the
legend here, these

468
00:20:58,470 --> 00:21:02,870
are different cities ranging
from Shenyang in China,

469
00:21:02,870 --> 00:21:05,630
to Winnipeg in Canada, to New
Jersey, which is apparently

470
00:21:05,630 --> 00:21:08,990
a city, to places in Finland,
Sweden, and Stockholm,

471
00:21:08,990 --> 00:21:11,120
which are somehow
different places.

472
00:21:11,120 --> 00:21:11,690
Yeah.

473
00:21:11,690 --> 00:21:13,898
So when you see a study like
this where they actually

474
00:21:13,898 --> 00:21:15,560
control and check
to make sure they're

475
00:21:15,560 --> 00:21:18,080
not getting any
single locality as

476
00:21:18,080 --> 00:21:20,810
an unrepresentative
measurement, and the data just

477
00:21:20,810 --> 00:21:21,710
looked like a crowd--

478
00:21:21,710 --> 00:21:25,928
a cloud along relative
risk equals 1,

479
00:21:25,928 --> 00:21:28,220
this either refutes the idea
that there is no threshold

480
00:21:28,220 --> 00:21:29,600
or supports the
idea that there's

481
00:21:29,600 --> 00:21:34,710
got to be some threshold lying
beyond 10 picocuries per liter.

482
00:21:34,710 --> 00:21:37,610
So, again, to me, it supports
the ICRP's recommendation

483
00:21:37,610 --> 00:21:38,680
of chill out.

484
00:21:38,680 --> 00:21:41,180
You're going to have a little
bit of radon in your basement.

485
00:21:41,180 --> 00:21:43,310
But pretty big studies,
and quite a lot of them,

486
00:21:43,310 --> 00:21:46,670
show that a little bit isn't
going to add any risk to you.

487
00:21:46,670 --> 00:21:48,380
So if you're worried
about risk, they're

488
00:21:48,380 --> 00:21:53,020
statistically is none based on
quite a few of these studies.

489
00:21:53,020 --> 00:21:56,770
And in order to enable you to
find these studies on your own,

490
00:21:56,770 --> 00:21:59,090
I wanted to go through five
minutes of where to look.

491
00:21:59,090 --> 00:22:02,200
And the answer is not Google
because Google is not very

492
00:22:02,200 --> 00:22:04,360
good at finding every study.

493
00:22:04,360 --> 00:22:06,460
It also picks up a
whole lot of garbage

494
00:22:06,460 --> 00:22:09,800
that's not peer reviewed because
it just scrabbles the internet,

495
00:22:09,800 --> 00:22:10,300
you know?

496
00:22:10,300 --> 00:22:12,430
That's what it does really well.

497
00:22:12,430 --> 00:22:15,560
Instead, I want us to
take the next half hour,

498
00:22:15,560 --> 00:22:18,740
split into teams for
and against hormesis,

499
00:22:18,740 --> 00:22:20,660
and try and find
studies that confirm

500
00:22:20,660 --> 00:22:23,660
or refute the idea that
radiation hormesis is

501
00:22:23,660 --> 00:22:26,590
an actual effect.

502
00:22:26,590 --> 00:22:29,220
So how many of you have
some sort of computer device

503
00:22:29,220 --> 00:22:30,830
with you here?

504
00:22:30,830 --> 00:22:31,330
Good.

505
00:22:31,330 --> 00:22:34,670
Enough so that there is
equal amount in each group.

506
00:22:34,670 --> 00:22:37,132
I'd like to switch
now to my own browser.

507
00:22:37,132 --> 00:22:39,090
And I want to show you
guys the Web of Science.

508
00:22:46,040 --> 00:22:51,210
Web of-- yeah, [INAUDIBLE]
I use Pine on my phone.

509
00:22:51,210 --> 00:22:54,460
It's much better science.

510
00:22:54,460 --> 00:22:57,730
So if you just Google search Web
of Science, and you're at MIT,

511
00:22:57,730 --> 00:22:59,380
it will recognize
your certificates

512
00:22:59,380 --> 00:23:03,820
and send you into the actual
best scientific paper indexing

513
00:23:03,820 --> 00:23:05,002
thing out there.

514
00:23:05,002 --> 00:23:06,730
AUDIENCE: Better
than Google Scholar?

515
00:23:06,730 --> 00:23:08,630
MICHAEL SHORT: Oh, my god, it's
better than Google Scholar.

516
00:23:08,630 --> 00:23:09,460
Yeah.

517
00:23:09,460 --> 00:23:11,080
If you think you've
found everything

518
00:23:11,080 --> 00:23:13,538
by looking at Google Scholar,
you're only fooling yourself.

519
00:23:13,538 --> 00:23:15,190
You're not fooling anybody else.

520
00:23:15,190 --> 00:23:16,202
It's getting better.

521
00:23:16,202 --> 00:23:17,410
But it doesn't find anything.

522
00:23:17,410 --> 00:23:19,840
And Google Scholar is
really good at finding

523
00:23:19,840 --> 00:23:21,310
things that aren't
peer reviewed,

524
00:23:21,310 --> 00:23:24,040
self-published stuff,
things on archive, things

525
00:23:24,040 --> 00:23:25,690
that you can't
trust because they

526
00:23:25,690 --> 00:23:28,670
haven't passed the muster
of the scientific community.

527
00:23:28,670 --> 00:23:31,450
So instead, let's
say you would just

528
00:23:31,450 --> 00:23:33,900
do a simple search for
radiation hormesis.

529
00:23:33,900 --> 00:23:34,810
You can all do this.

530
00:23:34,810 --> 00:23:35,140
Don't worry.

531
00:23:35,140 --> 00:23:36,557
I'm not showing
you how to search.

532
00:23:36,557 --> 00:23:38,470
I'm showing you some
of the other features

533
00:23:38,470 --> 00:23:40,500
of Web of Science.

534
00:23:40,500 --> 00:23:43,450
And you end up with 534 papers.

535
00:23:43,450 --> 00:23:46,660
You can, let's say, sort
by number of times cited,

536
00:23:46,660 --> 00:23:51,190
which may or may not be a factor
in how trustworthy the data is.

537
00:23:51,190 --> 00:23:54,168
It might just correlate
with the age of the paper.

538
00:23:54,168 --> 00:23:55,460
It might also be controversial.

539
00:23:55,460 --> 00:23:58,510
So if people cite it as an
example of what to do wrong,

540
00:23:58,510 --> 00:23:59,920
it might be highly cited.

541
00:23:59,920 --> 00:24:02,830
You know, people have made
tenure cases and like careers

542
00:24:02,830 --> 00:24:04,330
on papers that ended
up being wrong.

543
00:24:04,330 --> 00:24:06,840
And all you see is 10,000
citations saying this person

544
00:24:06,840 --> 00:24:07,840
is an idiot.

545
00:24:07,840 --> 00:24:10,367
If the committee val-- you know,
judging you for a promotion

546
00:24:10,367 --> 00:24:11,950
doesn't read that
far into it, they're

547
00:24:11,950 --> 00:24:15,300
like, oh, my god,
10,000 citations, right?

548
00:24:15,300 --> 00:24:15,800
Boom!

549
00:24:15,800 --> 00:24:18,140
Tenure, that's all
you have to do.

550
00:24:18,140 --> 00:24:20,540
I think I have it
a little tougher.

551
00:24:20,540 --> 00:24:25,340
The important part is while
with a title like that, oh, man,

552
00:24:25,340 --> 00:24:27,110
the more-- the real
fun part though is you

553
00:24:27,110 --> 00:24:29,150
can see who has
cited this paper.

554
00:24:29,150 --> 00:24:31,700
So if you want to then go see,
why has this paper been cited

555
00:24:31,700 --> 00:24:35,540
260 times, you can instantly
see all the titles, and years,

556
00:24:35,540 --> 00:24:38,750
and number of additional
citations of the papers

557
00:24:38,750 --> 00:24:40,310
that have cited it.

558
00:24:40,310 --> 00:24:45,300
So this is how you get started
with a real research, research.

559
00:24:45,300 --> 00:24:46,850
Yeah, that's what
I meant to say,

560
00:24:46,850 --> 00:24:49,490
is starting from a paper and
a tool like Web of Science,

561
00:24:49,490 --> 00:24:52,700
you can go forward and
backward in citation time,

562
00:24:52,700 --> 00:24:55,430
backward in time to see what
evidence this paper used

563
00:24:55,430 --> 00:24:58,430
to make their claims,
forward in time to see what

564
00:24:58,430 --> 00:25:00,707
other people thought about it.

565
00:25:00,707 --> 00:25:02,040
So who wants to be for hormesis?

566
00:25:04,930 --> 00:25:07,830
All right, everyone, all you
guys on one side of the room,

567
00:25:07,830 --> 00:25:11,020
all you guys, other guys on
the other side of the room.

568
00:25:11,020 --> 00:25:12,570
And I'd like you
guys to try to find

569
00:25:12,570 --> 00:25:15,090
the most convincing
studies that you can

570
00:25:15,090 --> 00:25:16,950
to prove the other side wrong.

571
00:25:16,950 --> 00:25:19,830
I suggest using Web
Science, not Google Scholar.

572
00:25:19,830 --> 00:25:24,240
It's pretty easy to figure
out how to learn how to use.

573
00:25:24,240 --> 00:25:28,220
And let's see what
conclusion we come to.

574
00:25:28,220 --> 00:25:29,140
AUDIENCE: [INAUDIBLE]

575
00:25:29,140 --> 00:25:32,270
MICHAEL SHORT: Yep,
hormesis by the wall--

576
00:25:32,270 --> 00:25:34,350
yeah, anti-hormesis
by the window.

577
00:25:34,350 --> 00:25:34,850
There we go.

578
00:25:37,840 --> 00:25:40,800
And I'm going to hide this
because I don't want to give

579
00:25:40,800 --> 00:25:42,060
anyone an unfair advantage.

580
00:25:42,060 --> 00:25:46,060
AUDIENCE: So [INAUDIBLE].

581
00:25:46,060 --> 00:25:48,980
SARAH: So this is a graph
showing the immune response

582
00:25:48,980 --> 00:25:53,120
in the cells of mice showing
that after they were given

583
00:25:53,120 --> 00:25:58,010
doses from 0 to 2 gray,
or 0 to 7 on the right,

584
00:25:58,010 --> 00:25:59,480
the response of
the immune system.

585
00:25:59,480 --> 00:26:05,120
So at the lower doses below like
0.5 gray, which is in the range

586
00:26:05,120 --> 00:26:10,430
that we're looking at, well,
the immune system in the mice

587
00:26:10,430 --> 00:26:13,520
had a stronger response
at low doses of radiation

588
00:26:13,520 --> 00:26:15,410
and then very
quickly tapered off,

589
00:26:15,410 --> 00:26:19,720
supporting the claim the
low doses are good for mice.

590
00:26:19,720 --> 00:26:20,541
[LAUGHTER]

591
00:26:20,541 --> 00:26:21,624
MICHAEL SHORT: [INAUDIBLE]

592
00:26:22,124 --> 00:26:23,822
SARAH: I have another graph too.

593
00:26:23,822 --> 00:26:26,030
MICHAEL SHORT: So this
percentage change in response,

594
00:26:26,030 --> 00:26:30,116
I'm assuming 100
years is no dose.

595
00:26:30,116 --> 00:26:31,060
OK.

596
00:26:31,060 --> 00:26:32,620
SARAH: Yes.

597
00:26:32,620 --> 00:26:35,740
So at higher doses, the
response of the immune system

598
00:26:35,740 --> 00:26:39,370
was suppressed, which follows
with what all the other studies

599
00:26:39,370 --> 00:26:45,251
show about giving doses in
excess of like 1 gray to cells.

600
00:26:45,251 --> 00:26:47,510
MICHAEL SHORT: Cool.

601
00:26:47,510 --> 00:26:49,617
So anti-hormesis group.

602
00:26:49,617 --> 00:26:51,200
SARAH: Oh, I have
another graph, but--

603
00:26:51,200 --> 00:26:51,710
MICHAEL SHORT: Oh, you do?

604
00:26:51,710 --> 00:26:52,310
SARAH: Yeah.

605
00:26:52,310 --> 00:26:53,290
MICHAEL SHORT: Oh, I wasn't
going to call them out.

606
00:26:53,290 --> 00:26:54,950
I was going to have them
criticize what's up here.

607
00:26:54,950 --> 00:26:55,805
SARAH: Oh, no.

608
00:26:55,805 --> 00:26:56,680
I have another graph.

609
00:26:56,680 --> 00:26:58,013
MICHAEL SHORT: [INAUDIBLE] next.

610
00:27:00,122 --> 00:27:01,580
SARAH: I have two
of the same ones.

611
00:27:01,580 --> 00:27:03,740
No, I have another
one somewhere.

612
00:27:03,740 --> 00:27:05,660
I'll find it in a sec.

613
00:27:10,560 --> 00:27:13,930
This one.

614
00:27:13,930 --> 00:27:16,600
All right, so this
one is incidences

615
00:27:16,600 --> 00:27:23,170
of lung cancer based
on mean radon level

616
00:27:23,170 --> 00:27:24,430
and corrected for smoking.

617
00:27:24,430 --> 00:27:27,040
So you can't say that it was
just from people smoking.

618
00:27:27,040 --> 00:27:31,010
So for radon levels up to
7 picocuries per liter,

619
00:27:31,010 --> 00:27:35,710
the incidence of
fatal lung cancer

620
00:27:35,710 --> 00:27:39,190
actually decreased as
you had more radon.

621
00:27:42,070 --> 00:27:43,030
MICHAEL SHORT: Oh.

622
00:27:43,030 --> 00:27:43,530
AUDIENCE:

623
00:27:43,530 --> 00:27:44,518
SARAH: Yes.

624
00:27:44,518 --> 00:27:46,060
MICHAEL SHORT:
Anything else you guys

625
00:27:46,060 --> 00:27:50,700
want to show before we let the
anti-hormesis folks poke at it?

626
00:27:50,700 --> 00:27:52,133
SARAH: That's what I got.

627
00:27:52,133 --> 00:27:52,940
MICHAEL SHORT: OK.

628
00:27:52,940 --> 00:27:53,815
AUDIENCE: [INAUDIBLE]

629
00:27:53,815 --> 00:27:55,398
MICHAEL SHORT: What
are your thoughts?

630
00:27:55,398 --> 00:27:57,550
AUDIENCE: OK, could you
go back to the last one.

631
00:27:57,550 --> 00:27:58,720
SARAH: I will try, yes.

632
00:28:03,530 --> 00:28:06,420
AUDIENCE: Do you have
any other [INAUDIBLE]..

633
00:28:06,420 --> 00:28:08,460
AUDIENCE: [INAUDIBLE] response.

634
00:28:08,460 --> 00:28:10,570
AUDIENCE: So-- so
a mouse is twice--

635
00:28:10,570 --> 00:28:15,490
almost twice as effective
at fending off disease?

636
00:28:15,490 --> 00:28:19,378
OK, I-- I am not
a mouse biologist,

637
00:28:19,378 --> 00:28:24,238
but the smell test
makes me think that--

638
00:28:24,238 --> 00:28:26,190
that perplexed me.

639
00:28:26,190 --> 00:28:30,800
And I guess you didn't
do studies [INAUDIBLE]..

640
00:28:30,800 --> 00:28:32,740
SARAH: I am not personally
offended by this.

641
00:28:32,740 --> 00:28:33,470
So you're good.

642
00:28:33,470 --> 00:28:37,505
AUDIENCE: Enormous--
enormous change.

643
00:28:37,505 --> 00:28:40,820
And if radiation hormesis
has such a strong effect

644
00:28:40,820 --> 00:28:44,280
on these mice, then why isn't it
something everywhere as a thing

645
00:28:44,280 --> 00:28:44,780
now.

646
00:28:44,780 --> 00:28:48,600
Like, if radiation-- if
hormesis is responsible for 80%

647
00:28:48,600 --> 00:28:51,567
[? movement ?] in mice,
[INAUDIBLE] like where--

648
00:28:51,567 --> 00:28:53,400
SARAH: I don't know
that it was improvement.

649
00:28:53,400 --> 00:28:55,800
I think it was just in the
amount of response they saw.

650
00:28:55,800 --> 00:28:57,520
I don't know if
that means it's--

651
00:28:57,520 --> 00:28:59,062
well, that doesn't
always mean it was

652
00:28:59,062 --> 00:29:01,480
effective at doing something.

653
00:29:01,480 --> 00:29:01,980
Right.

654
00:29:02,530 --> 00:29:03,990
MICHAEL SHORT: [INAUDIBLE]
you guys have comments too?

655
00:29:03,990 --> 00:29:05,700
AUDIENCE: Additionally,
that's like an extremely small

656
00:29:05,700 --> 00:29:07,680
of a dose for such
a massive response

657
00:29:07,680 --> 00:29:13,000
in like a field that is
so based on probability.

658
00:29:13,000 --> 00:29:15,780
Like, how can something
like the dose range

659
00:29:15,780 --> 00:29:18,990
that small have that much
of an impact on mice?

660
00:29:18,990 --> 00:29:22,038
SARAH: Well, from 0 to half
a gray is pretty significant.

661
00:29:22,038 --> 00:29:23,080
AUDIENCE: But [INAUDIBLE]

662
00:29:23,080 --> 00:29:24,480
SARAH: [INAUDIBLE]

663
00:29:24,480 --> 00:29:27,973
AUDIENCE: --before you
get to the 0.6 gray.

664
00:29:27,973 --> 00:29:29,390
AUDIENCE: You're
also only looking

665
00:29:29,390 --> 00:29:33,010
at the cells from
[INAUDIBLE] it seems like.

666
00:29:33,010 --> 00:29:35,650
And it like looked
varied depending

667
00:29:35,650 --> 00:29:36,850
on the kind of tissue.

668
00:29:36,850 --> 00:29:39,655
So you can't do it for overall.

669
00:29:39,655 --> 00:29:41,030
MICHAEL SHORT:
OK, I want to hear

670
00:29:41,030 --> 00:29:42,700
from the pro-hormesis team.

671
00:29:42,700 --> 00:29:46,380
What makes your-- what makes
your legs a little shaky trying

672
00:29:46,380 --> 00:29:48,310
to stand and hold this up?

673
00:29:48,310 --> 00:29:49,270
AUDIENCE: [INAUDIBLE]

674
00:29:49,270 --> 00:29:50,062
MICHAEL SHORT: Aha.

675
00:29:50,965 --> 00:29:52,238
SARAH: Didn't read the study.

676
00:29:52,238 --> 00:29:53,134
[LAUGHTER]

677
00:29:54,463 --> 00:29:55,630
MICHAEL SHORT: I like this--

678
00:29:55,630 --> 00:29:56,800
I like this idea
that, yeah, you're

679
00:29:56,800 --> 00:29:58,990
only looking at one type
of cell, which may or may

680
00:29:58,990 --> 00:30:01,570
respond differently to
different types of radiation.

681
00:30:01,570 --> 00:30:03,230
There are no error bars.

682
00:30:03,230 --> 00:30:06,445
SARAH: No, not even
a whole mouse either.

683
00:30:06,445 --> 00:30:08,020
AUDIENCE: [INAUDIBLE]
in the mouse.

684
00:30:08,020 --> 00:30:11,040
MICHAEL SHORT: Oh, oh to
trigger an immune response.

685
00:30:11,040 --> 00:30:12,317
AUDIENCE: [INAUDIBLE]

686
00:30:12,317 --> 00:30:13,900
MICHAEL SHORT: It's
like-- there are--

687
00:30:13,900 --> 00:30:15,072
there's other cells nearby.

688
00:30:15,072 --> 00:30:16,780
But they're like, oh,
you're not my cell.

689
00:30:16,780 --> 00:30:17,822
I'm going to [INAUDIBLE].

690
00:30:17,822 --> 00:30:19,120
AUDIENCE: [INAUDIBLE] mice.

691
00:30:19,120 --> 00:30:19,953
MICHAEL SHORT: Yeah.

692
00:30:19,953 --> 00:30:21,550
So that's-- that's
a valid point.

693
00:30:21,550 --> 00:30:25,983
But, yeah, did it say
in the study how many?

694
00:30:25,983 --> 00:30:27,525
SARAH: Again, did
not read the study.

695
00:30:27,525 --> 00:30:28,233
[LAUGHTER]

696
00:30:30,070 --> 00:30:31,132
Read the conclusion.

697
00:30:31,132 --> 00:30:33,590
MICHAEL SHORT: The data alone,
just taken it at face value,

698
00:30:33,590 --> 00:30:36,470
make it look like hormesis is a
definite thing, Yeah, Kristin?

699
00:30:36,470 --> 00:30:40,157
AUDIENCE: I'm saying if
there is [INAUDIBLE]..

700
00:30:40,157 --> 00:30:40,990
MICHAEL SHORT: Yeah.

701
00:30:40,990 --> 00:30:41,490
SARAH: True.

702
00:30:41,490 --> 00:30:43,920
Nine mice cell samples.

703
00:30:43,920 --> 00:30:46,120
MICHAEL SHORT: Let's
go to the other study.

704
00:30:46,120 --> 00:30:47,830
SARAH: All right,
the-- the lung one?

705
00:30:47,830 --> 00:30:48,700
MICHAEL SHORT:
Yeah, it seems to be

706
00:30:48,700 --> 00:30:49,992
more controlled and more legit.

707
00:30:49,992 --> 00:30:50,950
SARAH: Yeah.

708
00:30:50,950 --> 00:30:52,130
This one has error bars.

709
00:30:52,130 --> 00:30:55,820
MICHAEL SHORT: Yeah, 1 has error
bars, 2, corrected for smoking.

710
00:30:55,820 --> 00:30:58,270
So let's see what
the caption says.

711
00:30:58,270 --> 00:31:01,840
Lung cancer fatality rates
compared with mean radon levels

712
00:31:01,840 --> 00:31:02,410
in the US.

713
00:31:05,520 --> 00:31:09,720
SARAH: And for multiple
counties because it

714
00:31:09,720 --> 00:31:11,260
talks about counties plural.

715
00:31:11,260 --> 00:31:11,760
So--

716
00:31:16,812 --> 00:31:18,270
MICHAEL SHORT: So
multiple counties

717
00:31:18,270 --> 00:31:22,510
helped control for
single localities, or--

718
00:31:22,510 --> 00:31:25,930
AUDIENCE: So the 0 level
there is theoretical.

719
00:31:25,930 --> 00:31:28,850
So the data that
you have down here,

720
00:31:28,850 --> 00:31:32,050
like, we don't know what
actually happens [INAUDIBLE]..

721
00:31:32,050 --> 00:31:32,830
SARAH: Past what?

722
00:31:32,830 --> 00:31:36,230
AUDIENCE: Like-- like below
1, the mean radon levels

723
00:31:36,230 --> 00:31:39,140
because everyone is
exposed to radon.

724
00:31:39,140 --> 00:31:41,920
SARAH: Well, it says average
residential level of 1.7.

725
00:31:41,920 --> 00:31:44,560
So I think that means maybe
some people have less, maybe

726
00:31:44,560 --> 00:31:45,640
some people have more.

727
00:31:45,640 --> 00:31:48,017
I don't know what the
minimum radon level is.

728
00:31:48,017 --> 00:31:49,600
MICHAEL SHORT: It's
not going to be 0.

729
00:31:49,600 --> 00:31:50,350
SARAH: It's not 0.

730
00:31:50,350 --> 00:31:51,910
MICHAEL SHORT:
Yeah, no one gets 0

731
00:31:51,910 --> 00:31:53,410
unless you live in
a vacuum chamber.

732
00:31:53,410 --> 00:31:55,452
SARAH: I don't know what
kind of scale that's on.

733
00:31:55,452 --> 00:31:56,430
AUDIENCE: Me too.

734
00:31:56,430 --> 00:31:58,010
MICHAEL SHORT: Yeah.

735
00:31:58,010 --> 00:31:58,510
Cool, yeah.

736
00:31:58,510 --> 00:32:00,220
So this-- this is
fairly convincing.

737
00:32:00,220 --> 00:32:02,120
If the point here
was to show there

738
00:32:02,120 --> 00:32:03,838
is the theory of
linear no threshold,

739
00:32:03,838 --> 00:32:06,130
and here's what's an actual
data with error bars shows.

740
00:32:06,130 --> 00:32:07,930
It does a pretty
good job in saying,

741
00:32:07,930 --> 00:32:11,020
the theory is not
right, in this case.

742
00:32:11,020 --> 00:32:12,410
Can you say that in all cases?

743
00:32:12,410 --> 00:32:13,330
It's hard to tell.

744
00:32:13,330 --> 00:32:16,750
In the first study you found
that was on the cellular level.

745
00:32:16,750 --> 00:32:18,700
Maybe the multicellular level--

746
00:32:18,700 --> 00:32:21,940
multicellular level, certainly
not the organism level,

747
00:32:21,940 --> 00:32:23,155
like we said, how many mice.

748
00:32:23,155 --> 00:32:24,280
This is just parts of mice.

749
00:32:24,280 --> 00:32:24,550
Just--

750
00:32:24,550 --> 00:32:25,995
SARAH: It could
be the same mouse.

751
00:32:25,995 --> 00:32:27,370
MICHAEL SHORT:
Some cells-- yeah.

752
00:32:27,370 --> 00:32:29,300
This one is definitely
at the organism level.

753
00:32:29,300 --> 00:32:32,380
It's for-- for gross amounts
of exposure, how many of them

754
00:32:32,380 --> 00:32:34,810
resulted in increased
incidence of lung cancer?

755
00:32:34,810 --> 00:32:36,640
The answer is pretty much none.

756
00:32:36,640 --> 00:32:39,400
They all showed a
statistically-significant

757
00:32:39,400 --> 00:32:43,053
decrease, which is
pretty interesting.

758
00:32:43,053 --> 00:32:43,720
So thanks a lot.

759
00:32:43,720 --> 00:32:44,220
Sarah.

760
00:32:44,220 --> 00:32:45,037
And the whole team.

761
00:32:45,037 --> 00:32:47,120
Now one of you guys come
up and find [INAUDIBLE]..

762
00:32:47,120 --> 00:32:48,260
SARAH: Carrying the team.

763
00:32:48,260 --> 00:32:50,925
AUDIENCE: [INAUDIBLE]

764
00:32:50,925 --> 00:32:52,550
MICHAEL SHORT: So
who wants to come up?

765
00:32:52,550 --> 00:32:54,140
Or does no one [INAUDIBLE]?

766
00:32:54,140 --> 00:32:55,590
SARAH: Let's throw down, right?

767
00:32:55,590 --> 00:32:57,697
Fixing to scrap.

768
00:32:57,697 --> 00:32:59,530
MICHAEL SHORT: OK, you
can just pull it out.

769
00:32:59,530 --> 00:33:00,840
SARAH: OK, Are you sure?

770
00:33:00,840 --> 00:33:01,673
MICHAEL SHORT: Yeah.

771
00:33:01,673 --> 00:33:03,570
SARAH: OK.

772
00:33:03,570 --> 00:33:05,472
I don't want to break things.

773
00:33:05,472 --> 00:33:07,180
MICHAEL SHORT: No,
pulling it out's fine.

774
00:33:07,180 --> 00:33:09,220
If you jam it in, you
can bend the pins.

775
00:33:09,220 --> 00:33:11,110
And that's happened here before.

776
00:33:11,110 --> 00:33:12,010
AUDIENCE: [INAUDIBLE]

777
00:33:12,425 --> 00:33:14,800
MICHAEL SHORT: Yeah, if you
want to take a minute to send

778
00:33:14,800 --> 00:33:16,740
each other the links, go ahead.

779
00:33:29,140 --> 00:33:31,350
No, I like this,
though, is you can--

780
00:33:31,350 --> 00:33:33,478
you can find a graph
that supports something.

781
00:33:33,478 --> 00:33:34,770
And you can cite it in a paper.

782
00:33:34,770 --> 00:33:36,070
And you can get that
paper published.

783
00:33:36,070 --> 00:33:37,710
But looking more
carefully at the data

784
00:33:37,710 --> 00:33:39,520
does sometimes call
things into question.

785
00:33:39,520 --> 00:33:40,260
AUDIENCE: Just like [INAUDIBLE].

786
00:33:40,260 --> 00:33:42,052
MICHAEL SHORT: Like,
I think you guys found

787
00:33:42,052 --> 00:33:44,160
a good example of
that mouse cell study

788
00:33:44,160 --> 00:33:45,870
that looks like it
supports hormesis,

789
00:33:45,870 --> 00:33:47,250
but you can't say so for sure.

790
00:33:56,180 --> 00:33:57,930
Make sure no one's
waiting for their room.

791
00:34:01,920 --> 00:34:02,920
No one's kicking us out.

792
00:34:16,620 --> 00:34:19,560
AUDIENCE: Have we got a
paper that I found here

793
00:34:19,560 --> 00:34:21,114
but we can't open up on there.

794
00:34:21,114 --> 00:34:22,239
MICHAEL SHORT: Interesting.

795
00:34:22,239 --> 00:34:24,035
Can you send me the link?

796
00:34:24,035 --> 00:34:24,910
AUDIENCE: [INAUDIBLE]

797
00:34:24,970 --> 00:34:26,553
AUDIENCE: Wait, that
wasn't an option.

798
00:34:26,553 --> 00:34:27,540
AUDIENCE: [INAUDIBLE]

799
00:34:27,540 --> 00:34:28,382
MICHAEL SHORT: Yeah.

800
00:34:28,382 --> 00:34:29,590
I mean, we can continue this.

801
00:34:29,590 --> 00:34:32,007
There's-- we're not-- since
we're not going to the reactor

802
00:34:32,007 --> 00:34:34,960
since that valve was
broken, let's keep it up.

803
00:34:34,960 --> 00:34:36,886
AUDIENCE: Hey,
[INAUDIBLE] workbook

804
00:34:36,886 --> 00:34:39,722
and [INAUDIBLE] put
it in the log book.

805
00:34:39,722 --> 00:34:40,889
AUDIENCE: That's your fault.

806
00:34:40,889 --> 00:34:41,764
AUDIENCE: [INAUDIBLE]

807
00:34:41,764 --> 00:34:43,560
AUDIENCE: I wasn't
even [INAUDIBLE]..

808
00:34:43,560 --> 00:34:44,484
AUDIENCE: [INAUDIBLE]

809
00:34:47,264 --> 00:34:48,686
Email us by name.

810
00:34:48,686 --> 00:34:50,108
AUDIENCE: [INAUDIBLE]

811
00:34:51,311 --> 00:34:52,478
AUDIENCE: It's not over yet.

812
00:34:52,478 --> 00:34:53,426
AUDIENCE: [INAUDIBLE]

813
00:34:54,137 --> 00:34:55,929
MICHAEL SHORT: Yeah,
actually, I like this.

814
00:34:55,929 --> 00:34:57,210
This will be a good--

815
00:34:57,210 --> 00:35:01,060
quite a good use of recitation.

816
00:35:01,060 --> 00:35:03,427
I'll keep my email
open in case folks want

817
00:35:03,427 --> 00:35:04,510
to send things to present.

818
00:35:06,865 --> 00:35:08,240
AUDIENCE: That's
the whole title.

819
00:35:11,570 --> 00:35:14,450
GUEST SPEAKER: So one--
one of the main problems

820
00:35:14,450 --> 00:35:16,850
that we had with
the hormesis effect

821
00:35:16,850 --> 00:35:19,940
was that all of the
studies that we've seen

822
00:35:19,940 --> 00:35:24,720
seem to cover a large
scope of like tissues,

823
00:35:24,720 --> 00:35:27,218
different effects, and
all sorts of things,

824
00:35:27,218 --> 00:35:28,760
like, yeah, there's
a lot of studies.

825
00:35:28,760 --> 00:35:29,760
There's a lot of trends.

826
00:35:29,760 --> 00:35:31,400
But, like, the
things in particular

827
00:35:31,400 --> 00:35:33,275
that they're studying
are all over the place.

828
00:35:36,370 --> 00:35:38,935
And a lot of the--

829
00:35:38,935 --> 00:35:41,670
a lot of the research
done, like these studies

830
00:35:41,670 --> 00:35:45,540
here, are not actually
meant to study hormesis.

831
00:35:45,540 --> 00:35:47,190
It's kind of like
recycled data that's

832
00:35:47,190 --> 00:35:49,260
used from some other study.

833
00:35:49,260 --> 00:35:52,680
And they're kind of like pulling
from multiple sources, which

834
00:35:52,680 --> 00:35:55,080
increases the uncertainty.

835
00:35:55,080 --> 00:35:57,300
Then, additionally,
we have conflicting

836
00:35:57,300 --> 00:36:01,170
epidemiological
evidence of low dosages.

837
00:36:01,170 --> 00:36:03,810
So we're, in one instance,
you may see a reduction

838
00:36:03,810 --> 00:36:05,430
in breast cancer mortality.

839
00:36:05,430 --> 00:36:08,915
You'll see excess thyroid cancer
in children, other, which is--

840
00:36:08,915 --> 00:36:11,290
MICHAEL SHORT: That's the same
study that was just shown,

841
00:36:11,290 --> 00:36:14,393
the Cohen 1995
residential radon study.

842
00:36:14,393 --> 00:36:15,226
GUEST SPEAKER: Yeah.

843
00:36:15,226 --> 00:36:16,674
AUDIENCE: [INAUDIBLE]

844
00:36:16,674 --> 00:36:17,757
MICHAEL SHORT: [INAUDIBLE]

845
00:36:18,257 --> 00:36:19,248
[LAUGHTER]

846
00:36:20,548 --> 00:36:21,840
GUEST SPEAKER: And so I think--

847
00:36:21,840 --> 00:36:25,350
we're not-- I don't think we're
trying to disqualify hormesis

848
00:36:25,350 --> 00:36:27,330
as, like, completely wrong.

849
00:36:27,330 --> 00:36:29,160
I think one of
the biggest issues

850
00:36:29,160 --> 00:36:33,000
that we're taking with it
is that it's a small effect,

851
00:36:33,000 --> 00:36:35,032
if anything.

852
00:36:35,032 --> 00:36:36,990
It's something that we
really don't know about.

853
00:36:36,990 --> 00:36:38,170
It's hard to quantify.

854
00:36:38,170 --> 00:36:42,000
And it's, at the end of the day,
really just not worth it, not

855
00:36:42,000 --> 00:36:45,900
worth looking into because
of all of the variable--

856
00:36:45,900 --> 00:36:47,680
variables that go into it.

857
00:36:47,680 --> 00:36:50,030
And the effects that, like,
we just don't know about.

858
00:36:50,030 --> 00:36:52,210
We don't understand it.

859
00:36:52,210 --> 00:36:53,790
So, yeah, fire away.

860
00:36:53,790 --> 00:36:54,580
MICHAEL SHORT: That's a a
great viewpoint, actually.

861
00:36:54,580 --> 00:36:55,700
Yeah, Monica?

862
00:36:55,700 --> 00:36:57,620
AUDIENCE: [INAUDIBLE]

863
00:37:00,500 --> 00:37:04,440
OK, so it says support for
radiation hormesis [INAUDIBLE]

864
00:37:04,440 --> 00:37:06,039
cell in animal studies, OK?

865
00:37:06,039 --> 00:37:09,838
And then it cites an example.

866
00:37:09,838 --> 00:37:12,280
Can you tell me how
that, like, you know,

867
00:37:12,280 --> 00:37:14,180
supports what you're saying?

868
00:37:14,180 --> 00:37:15,930
AUDIENCE: Can you just
highlight the part?

869
00:37:15,930 --> 00:37:17,938
MICHAEL SHORT: Oh,
right-- right up here.

870
00:37:17,938 --> 00:37:18,480
AUDIENCE: OK.

871
00:37:20,477 --> 00:37:22,310
GUEST SPEAKER: We haven't
seen it in humans.

872
00:37:25,256 --> 00:37:27,850
AUDIENCE: Well, often,
biological studies

873
00:37:27,850 --> 00:37:31,880
are done on rats because they
have similar effects to humans.

874
00:37:31,880 --> 00:37:36,980
But it's a lifespan of, like,
1/10 a human's lifespan.

875
00:37:36,980 --> 00:37:38,962
So, biologically,
that's accepted.

876
00:37:38,962 --> 00:37:40,420
GUEST SPEAKER:
Medicine also is not

877
00:37:40,420 --> 00:37:44,155
accepted until it works
on humans, not on animals.

878
00:37:44,155 --> 00:37:45,550
AUDIENCE: [INAUDIBLE]

879
00:37:45,550 --> 00:37:47,830
GUEST SPEAKER: So we can
cure cancer in rats all day.

880
00:37:47,830 --> 00:37:50,780
But, like, if it doesn't
work in like the human body,

881
00:37:50,780 --> 00:37:51,920
then it just--

882
00:37:51,920 --> 00:37:54,250
we still don't use
it, like, it needs

883
00:37:54,250 --> 00:37:57,280
to clear the hurdle
of human usefulness

884
00:37:57,280 --> 00:37:58,380
before we actually use it.

885
00:38:03,330 --> 00:38:05,965
MICHAEL SHORT: Let's actually
look at this paragraph.

886
00:38:05,965 --> 00:38:08,810
They relate to carcinogensis
in different tissues

887
00:38:08,810 --> 00:38:12,588
and the dose-response
relationships [INAUDIBLE]..

888
00:38:12,588 --> 00:38:14,130
AUDIENCE: So there's
a line that says

889
00:38:14,130 --> 00:38:15,880
the evidence for
hormesis in these studies

890
00:38:15,880 --> 00:38:18,127
is not compelling since
the data may also be also

891
00:38:18,127 --> 00:38:21,100
be reasonably interpreted to
support no radiogenic effect

892
00:38:21,100 --> 00:38:23,060
in the low dose range.

893
00:38:23,060 --> 00:38:24,760
MICHAEL SHORT: Oh,
that's interesting.

894
00:38:24,760 --> 00:38:27,610
Now, how would one interpret--
because you showed the Cohen

895
00:38:27,610 --> 00:38:28,940
data.

896
00:38:28,940 --> 00:38:33,490
So how would one interpret
that to mean no effect?

897
00:38:33,490 --> 00:38:35,760
I'm trying now
determine in this--

898
00:38:35,760 --> 00:38:38,237
are the claims of this paper
that you've been [INAUDIBLE]??

899
00:38:44,710 --> 00:38:46,590
And this brings up,
actually, another point.

900
00:38:46,590 --> 00:38:49,750
They do agree that there's been
hundreds of cell and animal

901
00:38:49,750 --> 00:38:50,800
studies.

902
00:38:50,800 --> 00:38:52,870
They cite three human studies.

903
00:38:52,870 --> 00:38:54,460
So since we have
the time, you guys

904
00:38:54,460 --> 00:38:58,033
may want to look for more
than three human studies, done

905
00:38:58,033 --> 00:38:59,200
at the time of this writing.

906
00:38:59,200 --> 00:39:03,420
It's not fair to take ones
that were done afterwards.

907
00:39:03,420 --> 00:39:04,980
AUDIENCE: [INAUDIBLE]

908
00:39:04,980 --> 00:39:05,920
GUEST SPEAKER: What?

909
00:39:05,920 --> 00:39:07,142
Let's find out.

910
00:39:07,142 --> 00:39:09,390
AUDIENCE: After 2000.

911
00:39:09,390 --> 00:39:11,890
MICHAEL SHORT: It might say at
the bottom of the first page.

912
00:39:11,890 --> 00:39:13,932
AUDIENCE: Oh, wait, in
the-- in the [INAUDIBLE]..

913
00:39:13,932 --> 00:39:16,590
MICHAEL SHORT: 2000, yep.

914
00:39:16,590 --> 00:39:17,090
Yeah.

915
00:39:17,090 --> 00:39:18,870
So if you want to
refute that point,

916
00:39:18,870 --> 00:39:22,910
you may want to find more
human studies pre 2000.

917
00:39:22,910 --> 00:39:25,880
It wouldn't be fair
to do otherwise.

918
00:39:25,880 --> 00:39:27,890
But, actually, I
liked what you said.

919
00:39:27,890 --> 00:39:30,770
So what you're proposing--

920
00:39:30,770 --> 00:39:36,087
if there's a mostly
blank board, is

921
00:39:36,087 --> 00:39:37,920
that most people should
adopt the model that

922
00:39:37,920 --> 00:39:40,930
looks something like this.

923
00:39:40,930 --> 00:39:44,880
This is the axis of
how much bad or that 0.

924
00:39:44,880 --> 00:39:46,770
And this is dose in gray.

925
00:39:46,770 --> 00:39:52,320
And whether your model does
this, or this, or this,

926
00:39:52,320 --> 00:39:54,600
it sounds to me like
you are defining a--

927
00:40:00,650 --> 00:40:03,550
like you're defining
a kill zone.

928
00:40:03,550 --> 00:40:05,348
[INAUDIBLE] maybe the--

929
00:40:05,348 --> 00:40:06,140
GUEST SPEAKER: Yes.

930
00:40:06,140 --> 00:40:08,930
MICHAEL SHORT: The point isn't
whether or not hormesis exists.

931
00:40:08,930 --> 00:40:11,300
The effect may be so
small that who cares.

932
00:40:11,300 --> 00:40:15,890
But the bigger discussion
is how much is that, not

933
00:40:15,890 --> 00:40:16,820
is a little bit good.

934
00:40:16,820 --> 00:40:18,112
Is that what you're getting at?

935
00:40:18,112 --> 00:40:21,620
GUEST SPEAKER: Yeah, the like,
maybe it does look like this.

936
00:40:21,620 --> 00:40:25,880
But the dip is small,
really not that

937
00:40:25,880 --> 00:40:29,695
different from the linear
threshold model, we noticed.

938
00:40:29,695 --> 00:40:31,070
MICHAEL SHORT:
Oh, so in addition

939
00:40:31,070 --> 00:40:33,770
to being a basic
science question,

940
00:40:33,770 --> 00:40:35,510
could the issue
of hormesis almost

941
00:40:35,510 --> 00:40:40,507
be a sidetrack in getting
proper radiation policy through?

942
00:40:43,090 --> 00:40:44,840
That's a point I hadn't
heard made before,

943
00:40:44,840 --> 00:40:46,123
but I quite like it.

944
00:40:46,123 --> 00:40:47,540
Because it's not
like you're going

945
00:40:47,540 --> 00:40:50,300
to recommend everyone smokes
three cigarettes a day

946
00:40:50,300 --> 00:40:52,527
or, you know,
everyone gets blasted

947
00:40:52,527 --> 00:40:55,110
by little bit of radiation once
a year as part of a treatment.

948
00:40:55,110 --> 00:40:56,725
I don't think anyone
would buy that.

949
00:40:56,725 --> 00:40:59,225
Even if it did help, I don't
think anybody would emotionally

950
00:40:59,225 --> 00:41:01,790
buy that.

951
00:41:01,790 --> 00:41:02,710
But by focusing on--

952
00:41:02,710 --> 00:41:04,460
you know, that-- there's
a nice expression

953
00:41:04,460 --> 00:41:07,160
is the most important thing is
make the most important thing

954
00:41:07,160 --> 00:41:08,270
the most important thing.

955
00:41:11,630 --> 00:41:14,060
It means don't lose sight
of the overall goal, which

956
00:41:14,060 --> 00:41:16,490
is if you're making policy
on how much radiation

957
00:41:16,490 --> 00:41:18,620
exposure you're
allowed, do you focus

958
00:41:18,620 --> 00:41:20,420
on saying, a little
bit is actually good,

959
00:41:20,420 --> 00:41:23,480
or do you focus on saying,
here's the amount that's bad?

960
00:41:23,480 --> 00:41:25,820
And anything below
that, we shouldn't

961
00:41:25,820 --> 00:41:29,540
be regulating or overregulating
because there's no evidence

962
00:41:29,540 --> 00:41:34,640
to say whether it's good or
bad outside the kill zone.

963
00:41:34,640 --> 00:41:36,180
I quite like that
point, actually.

964
00:41:38,960 --> 00:41:41,000
It means that the
supporters of radiation

965
00:41:41,000 --> 00:41:43,700
should chill out as well.

966
00:41:43,700 --> 00:41:46,947
Cool, all right, so any other
studies you want to point out?

967
00:41:46,947 --> 00:41:48,780
GUEST SPEAKER: We had
a couple of abstracts.

968
00:41:48,780 --> 00:41:49,430
MICHAEL SHORT: Yeah, let's see.

969
00:41:49,430 --> 00:41:50,597
GUEST SPEAKER: But I don't--

970
00:41:50,597 --> 00:41:52,190
I'm not sure.

971
00:41:52,190 --> 00:41:53,150
AUDIENCE: [INAUDIBLE]

972
00:41:55,550 --> 00:41:57,556
GUEST SPEAKER: OK.

973
00:41:57,556 --> 00:42:04,040
AUDIENCE: Some of the other ones
don't compare hormetic models.

974
00:42:04,040 --> 00:42:06,240
But they look at--

975
00:42:06,240 --> 00:42:08,202
they say [INAUDIBLE].

976
00:42:08,202 --> 00:42:09,030
It's like--

977
00:42:09,030 --> 00:42:09,770
GUEST SPEAKER: Do
you want to come up?

978
00:42:09,770 --> 00:42:11,562
AUDIENCE: Yeah, this
one says [INAUDIBLE]..

979
00:42:11,562 --> 00:42:12,603
GUEST SPEAKER: All right.

980
00:42:12,603 --> 00:42:13,580
AUDIENCE: [INAUDIBLE]

981
00:42:14,080 --> 00:42:15,650
AUDIENCE: [INAUDIBLE]

982
00:42:15,650 --> 00:42:17,920
AUDIENCE: It basically
compares threshold models

983
00:42:17,920 --> 00:42:23,962
with no-threshold
models in [INAUDIBLE]..

984
00:42:23,962 --> 00:42:25,435
AUDIENCE: [INAUDIBLE]

985
00:42:30,840 --> 00:42:33,373
So perhaps hormetic is
still better for you,

986
00:42:33,373 --> 00:42:39,289
but they-- the [INAUDIBLE] was
good enough with [INAUDIBLE]..

987
00:42:41,988 --> 00:42:43,905
MICHAEL SHORT: So what
they're saying is the--

988
00:42:43,905 --> 00:42:45,960
the choice of model
really doesn't

989
00:42:45,960 --> 00:42:48,690
matter, as long as it
fits through the data

990
00:42:48,690 --> 00:42:50,400
that we've got.

991
00:42:50,400 --> 00:42:53,070
And it seems to be, again, what
happens in the low-dose regime

992
00:42:53,070 --> 00:42:54,630
is less important, right?

993
00:42:54,630 --> 00:42:56,630
AUDIENCE: And it will--
they were satisfied when

994
00:42:56,630 --> 00:42:59,654
it fell from the [INAUDIBLE].

995
00:43:01,730 --> 00:43:04,230
MICHAEL SHORT: So they're saying
the best estimate of this--

996
00:43:07,750 --> 00:43:08,320
interesting.

997
00:43:08,320 --> 00:43:10,600
AUDIENCE: They prefer no
threshold [INAUDIBLE]..

998
00:43:10,600 --> 00:43:11,767
MICHAEL SHORT: That's funny.

999
00:43:11,767 --> 00:43:14,260
"If a risk model with
a threshold is assumed,

1000
00:43:14,260 --> 00:43:16,780
the best estimate
is below 0 sieverts.

1001
00:43:20,100 --> 00:43:22,290
But then how is their
confidence interval from--

1002
00:43:22,290 --> 00:43:23,990
oh, less than 0 to 0.13.

1003
00:43:23,990 --> 00:43:26,630
They don't quantify
how much lower

1004
00:43:26,630 --> 00:43:30,585
it goes because a negative
dose doesn't make sense.

1005
00:43:30,585 --> 00:43:31,085
No.

1006
00:43:40,280 --> 00:43:41,750
So, yeah, it's a
strong conclusion.

1007
00:43:41,750 --> 00:43:44,090
But it looks-- looks
fairly well supported

1008
00:43:44,090 --> 00:43:47,780
to say that we can't say with
those confidence intervals

1009
00:43:47,780 --> 00:43:52,470
that they give if there
is or isn't a threshold.

1010
00:43:52,470 --> 00:43:53,070
Interesting.

1011
00:43:53,070 --> 00:43:54,362
What do you guys think of this?

1012
00:44:00,020 --> 00:44:01,910
So what would you
delve into the study

1013
00:44:01,910 --> 00:44:04,865
to try to agree with
or refute this claim?

1014
00:44:17,260 --> 00:44:21,610
AUDIENCE: They use a linear
quadratic model only,

1015
00:44:21,610 --> 00:44:24,222
it looks like.

1016
00:44:24,222 --> 00:44:26,510
So they're not considering
any of the other proposed

1017
00:44:26,510 --> 00:44:27,710
models, which is a little--

1018
00:44:32,130 --> 00:44:34,150
maybe not sketchy,
but it just seems

1019
00:44:34,150 --> 00:44:36,560
like it'd be very easy
to consider other models

1020
00:44:36,560 --> 00:44:38,290
and why didn't they do that.

1021
00:44:38,290 --> 00:44:40,000
MICHAEL SHORT: Sure.

1022
00:44:40,000 --> 00:44:43,570
You know, what no study
has gotten into yet is,

1023
00:44:43,570 --> 00:44:47,260
what's the mechanism of, let's
say, ill effect acceleration.

1024
00:44:47,260 --> 00:44:50,500
This is something that, at
least at the grad school level,

1025
00:44:50,500 --> 00:44:52,460
we try to hammer to
everyone constantly

1026
00:44:52,460 --> 00:44:54,710
is not just what's the data,
but what's the mechanism.

1027
00:44:54,710 --> 00:44:59,330
What's the reason for an
acceleration of ill effects?

1028
00:44:59,330 --> 00:45:02,470
So if you guys had to think with
increasing radiation exposure,

1029
00:45:02,470 --> 00:45:05,920
let's say we wanted this linear
quadratic model idea, what

1030
00:45:05,920 --> 00:45:10,300
could be some reasons or
mechanisms for an increased

1031
00:45:10,300 --> 00:45:13,966
amount of risk per unit dose
as the dose gets higher?

1032
00:45:17,560 --> 00:45:18,060
Yeah?

1033
00:45:18,060 --> 00:45:21,140
AUDIENCE: Well, your
body [INAUDIBLE]..

1034
00:45:21,140 --> 00:45:24,120
But then-- so at some--
you get more dose--

1035
00:45:24,120 --> 00:45:25,756
you get more dosing [INAUDIBLE].

1036
00:45:25,756 --> 00:45:27,235
It just keep fixing itself.

1037
00:45:27,235 --> 00:45:28,878
And once you get
past a certain point,

1038
00:45:28,878 --> 00:45:32,165
then it can't [? fix itself ?]
[? fast enough. ?] The

1039
00:45:32,165 --> 00:45:37,588
additional damage keeps
snowballing events.

1040
00:45:37,588 --> 00:45:39,560
And they're giving
it more damage

1041
00:45:39,560 --> 00:45:43,504
to curb more radiation
because you would run out of--

1042
00:45:43,504 --> 00:45:45,772
of various [INAUDIBLE].

1043
00:45:45,772 --> 00:45:46,605
MICHAEL SHORT: Sure.

1044
00:45:46,605 --> 00:45:48,220
Works for me.

1045
00:45:48,220 --> 00:45:50,320
Yeah, I like that--
the idea there

1046
00:45:50,320 --> 00:45:52,630
was that you've got
some capacity to deal

1047
00:45:52,630 --> 00:45:54,700
with damage from radiation.

1048
00:45:54,700 --> 00:45:58,220
And then once you exceed that
capacity, you don't also--

1049
00:45:58,220 --> 00:45:59,980
with a higher dose,
you don't also

1050
00:45:59,980 --> 00:46:02,680
ramp up your capacity
to deal with that dose.

1051
00:46:02,680 --> 00:46:04,240
So in the linear
region, let's say,

1052
00:46:04,240 --> 00:46:08,170
you're somewhat absorbing the
additional ill effects of dose

1053
00:46:08,170 --> 00:46:11,380
by capacity to repair
DNA or repair cells.

1054
00:46:11,380 --> 00:46:13,390
Then once you exceed
that threshold,

1055
00:46:13,390 --> 00:46:16,310
you're beyond that point.

1056
00:46:16,310 --> 00:46:18,190
So that could be a
plausible mechanism

1057
00:46:18,190 --> 00:46:21,250
for why there could be a linear
quadratic model that could

1058
00:46:21,250 --> 00:46:25,420
be tested, certainly with single
cell or multi cell studies,

1059
00:46:25,420 --> 00:46:28,800
like these-- these radiation
microbeams or, you know,

1060
00:46:28,800 --> 00:46:30,550
injecting something
that would be absorbed

1061
00:46:30,550 --> 00:46:32,302
by one cell
[INAUDIBLE] irradiated,

1062
00:46:32,302 --> 00:46:33,760
and seeing what
the ones nearby do.

1063
00:46:33,760 --> 00:46:35,740
So you could count
that as number

1064
00:46:35,740 --> 00:46:38,230
of mutations, number
of cell deaths,

1065
00:46:38,230 --> 00:46:41,110
anything, something that could
be quantitatively tested.

1066
00:46:41,110 --> 00:46:42,620
So that's pretty cool.

1067
00:46:42,620 --> 00:46:44,770
I actually quite
like this study.

1068
00:46:44,770 --> 00:46:47,560
It's awfully hard
to poke a hole in--

1069
00:46:47,560 --> 00:46:49,690
in the logic used here.

1070
00:46:49,690 --> 00:46:51,260
The claims aren't outrageous.

1071
00:46:51,260 --> 00:46:53,260
They're saying, this is
what the data is saying.

1072
00:46:53,260 --> 00:46:57,850
If you change the model, you
can or not have a threshold

1073
00:46:57,850 --> 00:46:59,430
and still get an acceptable fit.

1074
00:47:02,350 --> 00:47:04,070
Can we actually look
in the study itself?

1075
00:47:04,070 --> 00:47:07,050
One thing I want to
know is, what sort of--

1076
00:47:07,050 --> 00:47:09,370
do they do meta
analysis, or did they--

1077
00:47:09,370 --> 00:47:13,820
yeah, so this was on the
Japanese atomic bomb survivors.

1078
00:47:13,820 --> 00:47:15,620
So did they analyze
previous data,

1079
00:47:15,620 --> 00:47:16,870
or did they get their own.

1080
00:47:16,870 --> 00:47:18,936
And then if so, what
was the sample size?

1081
00:47:27,368 --> 00:47:31,336
Somewhere it'll be,
like, yeah, [INAUDIBLE]..

1082
00:47:42,770 --> 00:47:44,400
So where [INAUDIBLE].

1083
00:47:47,945 --> 00:47:49,070
GUEST SPEAKER: Where am I--

1084
00:47:49,070 --> 00:47:51,390
where should I be
looking for this--

1085
00:47:51,390 --> 00:47:52,890
MICHAEL SHORT:
Probably further down

1086
00:47:52,890 --> 00:47:54,790
in any sort of
methodology section--

1087
00:47:54,790 --> 00:47:58,280
materials and
methods, here we go.

1088
00:47:58,280 --> 00:48:03,170
OK, here it is, 86,500
something survivors.

1089
00:48:03,170 --> 00:48:06,659
Oh, yes, with lots of follow up.

1090
00:48:06,659 --> 00:48:08,867
AUDIENCE: But how are you
able to determine the dose?

1091
00:48:08,867 --> 00:48:09,655
Like--

1092
00:48:09,655 --> 00:48:11,280
MICHAEL SHORT: That
is a good question.

1093
00:48:11,280 --> 00:48:12,697
AUDIENCE: Because
especially for--

1094
00:48:12,697 --> 00:48:15,900
if we're looking like low
dose, and you're estimating,

1095
00:48:15,900 --> 00:48:20,222
it's very easy to, like,
estimate wrong, or, like,

1096
00:48:20,222 --> 00:48:22,430
because then-- then it calls
into question you have--

1097
00:48:22,430 --> 00:48:24,080
[INAUDIBLE] modeling
they're using.

1098
00:48:24,080 --> 00:48:24,880
MICHAEL SHORT: Mhm.

1099
00:48:24,880 --> 00:48:26,430
So that's a great
question is, how

1100
00:48:26,430 --> 00:48:28,830
do they know what
those people die?

1101
00:48:28,830 --> 00:48:33,780
So how would we go about
trying to trace that?

1102
00:48:33,780 --> 00:48:35,670
This is when you
dig back in time.

1103
00:48:35,670 --> 00:48:37,728
They reference this,
the data appears et al,

1104
00:48:37,728 --> 00:48:38,520
whatever, whatever.

1105
00:48:38,520 --> 00:48:40,480
So if you can go
to Web of Science,

1106
00:48:40,480 --> 00:48:44,920
pull up this Pierce
et al Web paper.

1107
00:48:44,920 --> 00:48:46,120
Look at cited references.

1108
00:48:46,120 --> 00:48:47,770
Yeah, right there.

1109
00:48:47,770 --> 00:48:50,830
And look for that
1996 Pierce study.

1110
00:48:50,830 --> 00:48:52,180
Let's see if it has it.

1111
00:48:55,940 --> 00:48:58,566
You can just like control F
for Pierce, and we'll find it.

1112
00:49:02,040 --> 00:49:03,650
Pierce and [INAUDIBLE].

1113
00:49:03,650 --> 00:49:05,208
Yeah, 1996, that's the one.

1114
00:49:05,208 --> 00:49:06,083
GUEST SPEAKER: Where?

1115
00:49:06,083 --> 00:49:07,070
Which one?

1116
00:49:07,070 --> 00:49:08,092
This one?

1117
00:49:08,092 --> 00:49:09,390
MICHAEL SHORT: [INAUDIBLE].

1118
00:49:09,390 --> 00:49:10,500
This is the 1996 one.

1119
00:49:10,500 --> 00:49:13,240
Yep.

1120
00:49:13,240 --> 00:49:16,600
So let's see if we
can trace this back

1121
00:49:16,600 --> 00:49:19,512
and find out how they estimated
the dose of these folks.

1122
00:49:19,512 --> 00:49:21,220
GUEST SPEAKER: So I
just go to full text?

1123
00:49:21,220 --> 00:49:22,053
MICHAEL SHORT: Yeah.

1124
00:49:29,635 --> 00:49:31,120
AUDIENCE: How [INAUDIBLE].

1125
00:49:43,735 --> 00:49:44,485
MICHAEL SHORT: OK.

1126
00:49:54,900 --> 00:49:57,780
So interesting, this LLS cohort.

1127
00:49:57,780 --> 00:49:59,370
So there was some
life span study,

1128
00:49:59,370 --> 00:50:01,703
which was also referred to
actually in the lecture notes

1129
00:50:01,703 --> 00:50:05,380
as one of the original
studies, says,

1130
00:50:05,380 --> 00:50:10,025
who met certain conditions
concerning adequate follow up.

1131
00:50:10,025 --> 00:50:11,150
Although estimates of the--

1132
00:50:11,150 --> 00:50:12,700
OK, I want to see the next page.

1133
00:50:12,700 --> 00:50:14,075
Although we
estimate-- that might

1134
00:50:14,075 --> 00:50:15,424
be what we're looking for.

1135
00:50:18,180 --> 00:50:20,520
Number of survivors, let's see.

1136
00:50:24,975 --> 00:50:27,450
AUDIENCE: It's 92%.

1137
00:50:27,450 --> 00:50:29,870
MICHAEL SHORT: OK, here we
go, materials and methods.

1138
00:50:29,870 --> 00:50:32,810
The portion of the
LSS cohort used here

1139
00:50:32,810 --> 00:50:35,210
includes the same
number of survivors

1140
00:50:35,210 --> 00:50:38,340
for whom dose estimates
are currently available,

1141
00:50:38,340 --> 00:50:46,005
et cetera, with estimated doses
greater than 5 millisieverts is

1142
00:50:46,005 --> 00:50:47,660
[INAUDIBLE].

1143
00:50:47,660 --> 00:50:50,370
Table 1 summarizes the
exposure distribution.

1144
00:50:50,370 --> 00:50:54,672
So let's go find table 1 and
see where the data came from.

1145
00:50:58,109 --> 00:50:59,091
AUDIENCE: [INAUDIBLE]

1146
00:51:00,570 --> 00:51:04,030
MICHAEL SHORT: So it turns out
that this is specifically--

1147
00:51:04,030 --> 00:51:08,884
DS-86 weighted colon
dose in sieverts.

1148
00:51:08,884 --> 00:51:09,384
Interesting.

1149
00:51:09,384 --> 00:51:13,296
AUDIENCE: It [INAUDIBLE].

1150
00:51:13,296 --> 00:51:16,903
So how did they get that?

1151
00:51:16,903 --> 00:51:18,070
MICHAEL SHORT: I don't know.

1152
00:51:18,070 --> 00:51:22,700
But it sounds like we need to
find this LSS, this Just LSS.

1153
00:51:22,700 --> 00:51:25,180
So let's look at the things
that this paper cites.

1154
00:51:30,000 --> 00:51:31,095
Find this LSS.

1155
00:51:31,095 --> 00:51:33,720
So I'm walking-- what I'm doing
here is walking you through how

1156
00:51:33,720 --> 00:51:35,520
to do your own research.

1157
00:51:35,520 --> 00:51:38,460
And if someone comes to you
with some internet emotional

1158
00:51:38,460 --> 00:51:41,970
argument of, this and that
about radiation is wrong,

1159
00:51:41,970 --> 00:51:43,560
instead of yelling
back louder, which

1160
00:51:43,560 --> 00:51:46,480
means you lost the
argument, you hit the books.

1161
00:51:46,480 --> 00:51:48,604
And this is how you
do the research.

1162
00:51:48,604 --> 00:51:52,420
AUDIENCE: LSS-85, does that
mean it was [INAUDIBLE]..

1163
00:51:52,420 --> 00:51:54,750
MICHAEL SHORT: Probably.

1164
00:51:54,750 --> 00:51:57,040
Version of-- title
not available.

1165
00:51:57,040 --> 00:51:58,136
I hope it's not that one.

1166
00:52:00,372 --> 00:52:01,330
Can you search for LSS?

1167
00:52:05,520 --> 00:52:06,947
Nothing?

1168
00:52:06,947 --> 00:52:08,530
So let's go back to
the paper and find

1169
00:52:08,530 --> 00:52:11,450
what citation that was.

1170
00:52:11,450 --> 00:52:14,160
If you go up a little bit, I
think there was like a sup--

1171
00:52:14,160 --> 00:52:17,790
a superscript up to the
last page, I'm sorry.

1172
00:52:17,790 --> 00:52:20,286
There was a superscript
on LSS stuff.

1173
00:52:33,182 --> 00:52:34,670
AUDIENCE: So general
documentation

1174
00:52:34,670 --> 00:52:37,898
of the selection of LSS
cohorts [INAUDIBLE]..

1175
00:52:37,898 --> 00:52:38,940
MICHAEL SHORT: Thank you.

1176
00:52:38,940 --> 00:52:43,400
All right, let's find
references 9 and 10 in the--

1177
00:52:43,400 --> 00:52:44,150
yeah, [INAUDIBLE].

1178
00:52:44,150 --> 00:52:46,233
AUDIENCE: Can you click
one of the References tab?

1179
00:52:46,233 --> 00:52:48,260
MICHAEL SHORT: Oh, yeah,
up there, References.

1180
00:52:51,260 --> 00:52:53,010
Awesome!

1181
00:52:53,010 --> 00:52:54,440
9 and 10, OK.

1182
00:52:57,240 --> 00:53:00,102
Let's find them.

1183
00:53:00,102 --> 00:53:01,098
AUDIENCE: [INAUDIBLE]

1184
00:53:02,375 --> 00:53:03,750
MICHAEL SHORT: So
let me show you

1185
00:53:03,750 --> 00:53:05,640
quickly how to
use Web of Science

1186
00:53:05,640 --> 00:53:07,974
to get what you're looking
for if I could jump on?

1187
00:53:07,974 --> 00:53:10,460
GUEST SPEAKER:
[INAUDIBLE] up here?

1188
00:53:10,460 --> 00:53:12,720
MICHAEL SHORT: You
don't have to, yeah.

1189
00:53:12,720 --> 00:53:16,290
But thank you for being up here
for so long and running this.

1190
00:53:16,290 --> 00:53:17,580
So we're looking for--

1191
00:53:23,090 --> 00:53:25,730
where was-- the
article was here.

1192
00:53:28,610 --> 00:53:30,170
Went into references.

1193
00:53:30,170 --> 00:53:33,700
I guess that was like the last--

1194
00:53:33,700 --> 00:53:35,200
I don't want to
close all your tabs.

1195
00:53:35,200 --> 00:53:35,700
Here we go.

1196
00:53:35,700 --> 00:53:40,150
So GW, is that
Beebe and Usagawa.

1197
00:53:40,150 --> 00:53:43,930
So we'll go to Web of
Science, look for authors,

1198
00:53:43,930 --> 00:53:47,188
any paper with those authors.

1199
00:53:47,188 --> 00:53:48,730
So you can do a more
advanced search.

1200
00:53:48,730 --> 00:53:52,690
This is where things get really
interesting and specific.

1201
00:53:52,690 --> 00:53:53,850
So ditch the topic.

1202
00:53:58,180 --> 00:54:05,530
Search by Beebe and
add a field, Usagawa.

1203
00:54:05,530 --> 00:54:07,360
And then anything
with these two folks

1204
00:54:07,360 --> 00:54:10,300
in the author field that is
indexed by Web of Science

1205
00:54:10,300 --> 00:54:10,890
will pop up.

1206
00:54:13,848 --> 00:54:14,348
Nothing.

1207
00:54:19,745 --> 00:54:21,060
Did I spell anything wrong?

1208
00:54:21,060 --> 00:54:23,330
Usagawa, of course.

1209
00:54:36,500 --> 00:54:37,410
That's unfortunate.

1210
00:54:37,410 --> 00:54:39,630
Last thing to try
is Add Wild Cards.

1211
00:54:51,362 --> 00:54:52,294
Interesting.

1212
00:54:55,090 --> 00:54:57,310
This is actually one place
where I would use Google

1213
00:54:57,310 --> 00:55:00,010
to find a specific report.

1214
00:55:00,010 --> 00:55:02,530
So because you're not looking
to survey a field that's

1215
00:55:02,530 --> 00:55:04,840
out there, but you're
looking for any document

1216
00:55:04,840 --> 00:55:06,625
that you can confirm
is that document.

1217
00:55:09,970 --> 00:55:13,970
Let's head there.

1218
00:55:13,970 --> 00:55:16,858
Oh, it looks like
Stanford's got it.

1219
00:55:26,618 --> 00:55:28,420
That's something
that references it.

1220
00:55:28,420 --> 00:55:30,750
So at this point,
we've hit the maximum

1221
00:55:30,750 --> 00:55:32,508
that we can do on the computer.

1222
00:55:32,508 --> 00:55:34,050
But if you finally
want to trace back

1223
00:55:34,050 --> 00:55:38,670
to see how were the
Hiroshima data acquired,

1224
00:55:38,670 --> 00:55:41,880
take these citations,
bring it to one of the MIT

1225
00:55:41,880 --> 00:55:45,000
librarians like Christ Sherratt
is our nuclear librarian.

1226
00:55:45,000 --> 00:55:46,458
AUDIENCE: He's a
nuclear librarian?

1227
00:55:46,458 --> 00:55:49,110
MICHAEL SHORT: And we have
a nuclear librarian, yeah.

1228
00:55:49,110 --> 00:55:50,563
MIT libraries is pretty awesome.

1229
00:55:50,563 --> 00:55:52,230
So when you're looking
for anything here

1230
00:55:52,230 --> 00:55:54,680
in terms of research
or whatever,

1231
00:55:54,680 --> 00:55:56,280
there's actually
someone whose job

1232
00:55:56,280 --> 00:55:58,860
it is to help you find
nuclear documents.

1233
00:55:58,860 --> 00:56:00,668
And chances are, this
is a pretty big one.

1234
00:56:00,668 --> 00:56:02,210
So I wouldn't be
surprised if we have

1235
00:56:02,210 --> 00:56:03,990
a physical or electronic copy.

1236
00:56:03,990 --> 00:56:06,360
So we're now like one
degree of separation

1237
00:56:06,360 --> 00:56:08,850
away from finding the
original Hiroshima

1238
00:56:08,850 --> 00:56:13,400
data, where we can find out how
did they estimate that dose.

1239
00:56:13,400 --> 00:56:14,630
So I think this is fairly--

1240
00:56:14,630 --> 00:56:16,172
hopefully, this is
fairly instructive

1241
00:56:16,172 --> 00:56:18,950
to show you how do you go about
getting the facts to prove

1242
00:56:18,950 --> 00:56:22,250
or disprove something, knowing
the-- not just the physics

1243
00:56:22,250 --> 00:56:25,040
that you know, but how to
go out and find that stuff.

1244
00:56:25,040 --> 00:56:28,010
Now, I did see a
bunch of sources

1245
00:56:28,010 --> 00:56:31,360
from the pro hormesis team.

1246
00:56:31,360 --> 00:56:33,190
You still want me to show them?

1247
00:56:33,190 --> 00:56:34,120
AUDIENCE: [INAUDIBLE]

1248
00:56:35,430 --> 00:56:36,180
MICHAEL SHORT: OK.

1249
00:56:45,950 --> 00:56:48,760
Thanks.

1250
00:56:48,760 --> 00:56:51,940
All right, you just want to
hold this up while your--

1251
00:56:51,940 --> 00:56:54,580
let's go to your sources.

1252
00:56:54,580 --> 00:56:55,347
OK, here we go.

1253
00:56:55,347 --> 00:56:56,180
AUDIENCE: All right.

1254
00:56:56,180 --> 00:56:58,848
MICHAEL SHORT: So walk us
through what you found.

1255
00:56:58,848 --> 00:57:00,640
GUEST SPEAKER: I just
need to open them up.

1256
00:57:07,602 --> 00:57:09,060
AUDIENCE: Go through
them all, or--

1257
00:57:09,060 --> 00:57:11,410
MICHAEL SHORT: Yeah,
let's do them all.

1258
00:57:11,410 --> 00:57:13,036
GUEST SPEAKER:
There's not too much.

1259
00:57:13,036 --> 00:57:20,080
Kind of-- OK, so,
I unfortunately

1260
00:57:20,080 --> 00:57:23,680
was not able to find like too
many pretty graphs, or data,

1261
00:57:23,680 --> 00:57:25,330
or anything of the sort.

1262
00:57:25,330 --> 00:57:28,240
But if you look up, what
did I search for this?

1263
00:57:28,240 --> 00:57:31,510
I think I just looked
up radiation hormesis.

1264
00:57:31,510 --> 00:57:34,200
And this is one of the
articles that turned up.

1265
00:57:34,200 --> 00:57:36,190
And it seems to be
pretty well cited.

1266
00:57:36,190 --> 00:57:39,720
You can see it's
been cited 184 times.

1267
00:57:39,720 --> 00:57:42,760
And kind of the quick look
through the citations,

1268
00:57:42,760 --> 00:57:45,880
from what I saw, seemed
to be in support of it.

1269
00:57:45,880 --> 00:57:54,902
And if you actually look at the
abstract itself, where is it?

1270
00:57:54,902 --> 00:57:56,385
AUDIENCE: [INAUDIBLE]

1271
00:57:56,385 --> 00:57:58,260
GUEST SPEAKER: Yeah,
well-- the last sentence

1272
00:57:58,260 --> 00:58:01,620
is pretty excellent.

1273
00:58:01,620 --> 00:58:04,380
"This is consistent with
data both from animal studies

1274
00:58:04,380 --> 00:58:06,720
and human epidemiological
observations

1275
00:58:06,720 --> 00:58:08,640
on low-dose induced cancer.

1276
00:58:08,640 --> 00:58:10,590
The linear
no-threshold hypothesis

1277
00:58:10,590 --> 00:58:13,320
should be abandoned and
should-- and be replaced

1278
00:58:13,320 --> 00:58:15,600
by a hypothesis that is
scientifically justified

1279
00:58:15,600 --> 00:58:17,700
and causes less
unreasonable fear

1280
00:58:17,700 --> 00:58:20,332
and unnecessary expenditure."

1281
00:58:20,332 --> 00:58:21,540
MICHAEL SHORT: You know what?

1282
00:58:21,540 --> 00:58:25,600
I want to see what are the human
epidemiological observations

1283
00:58:25,600 --> 00:58:26,380
that they cite.

1284
00:58:26,380 --> 00:58:28,710
GUEST SPEAKER: Yeah, so
unfortunately, the MIT

1285
00:58:28,710 --> 00:58:31,080
libraries does not
have an electronic copy

1286
00:58:31,080 --> 00:58:31,800
of this article.

1287
00:58:31,800 --> 00:58:34,080
And I wasn't able to find one.

1288
00:58:34,080 --> 00:58:37,915
But going through some
of the citations for it--

1289
00:58:37,915 --> 00:58:39,540
MICHAEL SHORT: Before
you do, could you

1290
00:58:39,540 --> 00:58:40,530
go back to the article?

1291
00:58:40,530 --> 00:58:41,190
GUEST SPEAKER: Sure.

1292
00:58:41,190 --> 00:58:42,270
MICHAEL SHORT: I want
to point something out.

1293
00:58:42,270 --> 00:58:43,770
GUEST SPEAKER: Yes.

1294
00:58:43,770 --> 00:58:46,530
MICHAEL SHORT: Can you tell
if this was peer reviewed?

1295
00:58:46,530 --> 00:58:48,735
GUEST SPEAKER: I do not
know how to do that.

1296
00:58:48,735 --> 00:58:50,610
MICHAEL SHORT: It appears
to be a conference.

1297
00:58:51,155 --> 00:58:51,360
GUEST SPEAKER: OK.

1298
00:58:51,360 --> 00:58:54,060
MICHAEL SHORT: Not all
conferences require peer review

1299
00:58:54,060 --> 00:58:55,680
in order to present the papers.

1300
00:58:55,680 --> 00:58:58,320
So while conference
proceedings will typically

1301
00:58:58,320 --> 00:59:02,040
be published as a record of
what happened at the conference,

1302
00:59:02,040 --> 00:59:05,250
we don't know if this one
was peer reviewed and checked

1303
00:59:05,250 --> 00:59:07,292
for facts by an
independent party.

1304
00:59:07,292 --> 00:59:09,292
Could you go up a little
bit, and maybe there'll

1305
00:59:09,292 --> 00:59:11,530
be some information on that?

1306
00:59:15,410 --> 00:59:17,570
Oh, it did go in the British
Journal of Radiology.

1307
00:59:17,570 --> 00:59:18,580
OK, that's a good sign.

1308
00:59:18,580 --> 00:59:21,970
So conference proceedings,
you don't know.

1309
00:59:21,970 --> 00:59:24,880
But in order to publish
something in a journal,

1310
00:59:24,880 --> 00:59:27,130
you do because then in
order to get in the journal,

1311
00:59:27,130 --> 00:59:29,320
things have to be peer reviewed
to meet the journal standards,

1312
00:59:29,320 --> 00:59:31,815
regardless of whether they
came from a conference or just

1313
00:59:31,815 --> 00:59:32,690
a regular submission.

1314
00:59:32,690 --> 00:59:34,640
So, OK, that's good to see.

1315
00:59:34,640 --> 00:59:36,020
So, now, what else you got?

1316
00:59:36,020 --> 00:59:38,020
GUEST SPEAKER: And then
one of the key sentences

1317
00:59:38,020 --> 00:59:43,330
that I found right here,
adaptive protection

1318
00:59:43,330 --> 00:59:48,730
causes DNA damage prevention,
and repair, and immune system

1319
00:59:48,730 --> 00:59:50,350
or immune stimulation.

1320
00:59:50,350 --> 00:59:52,240
It develops with
a delay of hours,

1321
00:59:52,240 --> 00:59:55,240
may last for days to
months, decreases steadily

1322
00:59:55,240 --> 00:59:58,720
at doses above about
100 milligray to 200

1323
00:59:58,720 --> 01:00:00,580
milligray and is
not observed anymore

1324
01:00:00,580 --> 01:00:05,110
after acute exposures of more
than about 500 milligray.

1325
01:00:05,110 --> 01:00:06,880
That's all pretty interesting.

1326
01:00:06,880 --> 01:00:10,330
Like I said, unfortunately, I
couldn't find the actual paper.

1327
01:00:10,330 --> 01:00:12,640
So you can't really delve
into some of those claims.

1328
01:00:12,640 --> 01:00:16,930
But I tried to look at
some of the citations that

1329
01:00:16,930 --> 01:00:17,710
delved into them.

1330
01:00:17,710 --> 01:00:20,950
And this is where my
presentation gets a little bit

1331
01:00:20,950 --> 01:00:23,410
shakier because I'm
not particularly

1332
01:00:23,410 --> 01:00:27,430
good at parsing some of this
complex stuff very quickly.

1333
01:00:27,430 --> 01:00:28,930
MICHAEL SHORT: Let's
do it together.

1334
01:00:28,930 --> 01:00:29,972
GUEST SPEAKER: All right.

1335
01:00:34,530 --> 01:00:35,453
[INAUDIBLE]

1336
01:00:35,453 --> 01:00:37,620
MICHAEL SHORT: If you could
click Download Full Text

1337
01:00:37,620 --> 01:00:39,106
in PDF, it'll just be bigger.

1338
01:00:39,106 --> 01:00:39,856
GUEST SPEAKER: OK.

1339
01:00:42,675 --> 01:00:43,800
MICHAEL SHORT: There we go.

1340
01:00:47,155 --> 01:00:48,530
GUEST SPEAKER: So
it seemed to me

1341
01:00:48,530 --> 01:00:51,860
this one was more looking
through the statistics

1342
01:00:51,860 --> 01:00:53,730
of various studies.

1343
01:00:53,730 --> 01:00:55,700
I'm not entirely sure.

1344
01:00:55,700 --> 01:00:59,495
But I think the conclusion--

1345
01:00:59,495 --> 01:01:00,461
[INAUDIBLE]

1346
01:01:05,291 --> 01:01:08,680
There we go.

1347
01:01:08,680 --> 01:01:11,340
So the very last paragraph,
"the present practice

1348
01:01:11,340 --> 01:01:14,280
assumes linearity in assessing
risk from even the lowest dose

1349
01:01:14,280 --> 01:01:17,623
exposure of complex tissue
to ionizing radiation.

1350
01:01:17,623 --> 01:01:19,290
By applying this type
of risk assessment

1351
01:01:19,290 --> 01:01:21,330
to radiation protection
of exposed workers

1352
01:01:21,330 --> 01:01:24,900
and the public alike, society
may gain a questionable benefit

1353
01:01:24,900 --> 01:01:27,030
at unavoidably substantial cost.

1354
01:01:27,030 --> 01:01:28,710
Research on the p
values given above

1355
01:01:28,710 --> 01:01:30,690
may eventually
reveal the true risk,

1356
01:01:30,690 --> 01:01:33,960
which appears to be inaccessible
by epidemiological studies

1357
01:01:33,960 --> 01:01:35,260
alone.

1358
01:01:35,260 --> 01:01:36,802
MICHAEL SHORT: So
what are they going

1359
01:01:36,802 --> 01:01:39,930
on claiming [INAUDIBLE] versus
not being willing to claim it?

1360
01:01:39,930 --> 01:01:41,555
GUEST SPEAKER: So it
seems like they're

1361
01:01:41,555 --> 01:01:45,230
saying that at the current,
there's not really a problem--

1362
01:01:45,230 --> 01:01:48,750
a statistically
valid assertion of

1363
01:01:48,750 --> 01:01:51,540
the linear no-threshold
model and that the benefits

1364
01:01:51,540 --> 01:01:55,770
to society gained from that are
not worth the cost to society

1365
01:01:55,770 --> 01:01:56,760
from that assumption.

1366
01:01:56,760 --> 01:01:58,260
MICHAEL SHORT: So
what sort of costs

1367
01:01:58,260 --> 01:02:00,960
do you think society
incurs by adapting

1368
01:02:00,960 --> 01:02:04,390
a linear no-threshold
dose risk model?

1369
01:02:04,390 --> 01:02:06,890
GUEST SPEAKER: I mean, it could
pose unnecessary regulations

1370
01:02:06,890 --> 01:02:08,307
on like nuclear
power, which could

1371
01:02:08,307 --> 01:02:10,460
be arguably better for society.

1372
01:02:10,460 --> 01:02:11,330
MICHAEL SHORT: Sure.

1373
01:02:11,330 --> 01:02:14,650
Nuclear power plants
emit radiation, fact,

1374
01:02:14,650 --> 01:02:17,870
to use the old cell
phone methodology.

1375
01:02:17,870 --> 01:02:20,870
There's always going to be some
very small amount of tritium

1376
01:02:20,870 --> 01:02:21,800
released.

1377
01:02:21,800 --> 01:02:23,600
The question is, does it matter?

1378
01:02:23,600 --> 01:02:27,290
And if legislation is made
to say absolutely no tritium

1379
01:02:27,290 --> 01:02:28,790
release is allowed,
well, you're not

1380
01:02:28,790 --> 01:02:30,740
going be allowed to
run a nuclear plant.

1381
01:02:30,740 --> 01:02:33,410
That's not the question
we should be asking.

1382
01:02:33,410 --> 01:02:36,390
The question we should be
asking is, how much is harmful?

1383
01:02:36,390 --> 01:02:38,640
So I think that's what this
study is really getting at

1384
01:02:38,640 --> 01:02:41,300
is I'm glad to see someone
say, you may have a benefit.

1385
01:02:41,300 --> 01:02:45,000
But the cost is not
worth the benefit.

1386
01:02:45,000 --> 01:02:49,460
Like I-- I had a multiple
of the same arguments

1387
01:02:49,460 --> 01:02:51,890
with different people when
they were complaining, well,

1388
01:02:51,890 --> 01:02:56,120
how dare would you expose me
to any amount of radiation

1389
01:02:56,120 --> 01:02:57,620
at any risk that
I can't control.

1390
01:02:57,620 --> 01:02:59,560
I used to protest
outside Draper Labs

1391
01:02:59,560 --> 01:03:01,450
for 30 years protesting
nuclear power.

1392
01:03:01,450 --> 01:03:03,963
I was like, OK, how
did you get there?

1393
01:03:03,963 --> 01:03:05,960
They were like, oh, I drove.

1394
01:03:05,960 --> 01:03:07,070
What?

1395
01:03:07,070 --> 01:03:09,350
In a car?

1396
01:03:09,350 --> 01:03:12,140
Do you even know the risks per
mile of getting on the road,

1397
01:03:12,140 --> 01:03:14,610
let alone in Cambridge
specifically?

1398
01:03:14,610 --> 01:03:16,280
No?

1399
01:03:16,280 --> 01:03:18,950
Well, I was like, you
should really consider

1400
01:03:18,950 --> 01:03:21,410
where you put your effort?

1401
01:03:21,410 --> 01:03:25,257
It's-- again, it's
emotions versus numbers.

1402
01:03:25,257 --> 01:03:26,840
I'm going to go with
numbers because I

1403
01:03:26,840 --> 01:03:30,950
tend to make bad decisions
when I follow my emotions,

1404
01:03:30,950 --> 01:03:33,710
as do most people because
most decisions are

1405
01:03:33,710 --> 01:03:36,630
more complex than fight
or flight nowadays.

1406
01:03:36,630 --> 01:03:37,130
Yeah?

1407
01:03:37,130 --> 01:03:38,630
AUDIENCE: So a lot
of the discussion

1408
01:03:38,630 --> 01:03:43,795
just seems to be around
like expanding [INAUDIBLE]..

1409
01:03:43,795 --> 01:03:45,370
But a lot of the
arguments don't seem

1410
01:03:45,370 --> 01:03:50,363
to like really [INAUDIBLE].

1411
01:03:56,520 --> 01:03:58,720
But, yeah, like there's
a certain extent,

1412
01:03:58,720 --> 01:04:01,160
like, oh, you will
see [INAUDIBLE]..

1413
01:04:10,247 --> 01:04:11,080
MICHAEL SHORT: Yeah.

1414
01:04:11,080 --> 01:04:13,527
AUDIENCE: [INAUDIBLE]
are doing the same.

1415
01:04:13,527 --> 01:04:15,110
MICHAEL SHORT: You
make a great point.

1416
01:04:15,110 --> 01:04:18,090
That's why I like your--
your chosen idea so much

1417
01:04:18,090 --> 01:04:19,830
is, well, you didn't say chosen.

1418
01:04:19,830 --> 01:04:21,993
That's what I-- yeah.

1419
01:04:21,993 --> 01:04:23,910
Yeah, the question we
should be asking ourself

1420
01:04:23,910 --> 01:04:27,060
is not what is the dose-risk
relationship, but when should

1421
01:04:27,060 --> 01:04:28,238
we actually care.

1422
01:04:28,238 --> 01:04:30,030
It's like both sets of
studies have kind of

1423
01:04:30,030 --> 01:04:34,025
come to the conclusion
that, nah, right?

1424
01:04:34,025 --> 01:04:36,270
AUDIENCE: [INAUDIBLE] dose
doesn't really matter.

1425
01:04:36,270 --> 01:04:38,580
GUEST SPEAKER: Yeah, and
then I found this last one

1426
01:04:38,580 --> 01:04:40,050
is a little bit more assertive.

1427
01:04:40,050 --> 01:04:43,560
It's kind of just
hitting the same nail

1428
01:04:43,560 --> 01:04:47,740
on kind of the elimination of
the linear no-threshold model.

1429
01:04:47,740 --> 01:04:53,430
But then it does go on to make
some more powerful claim right

1430
01:04:53,430 --> 01:04:54,390
here.

1431
01:04:54,390 --> 01:04:56,520
"These data are examined
within the context

1432
01:04:56,520 --> 01:04:59,400
of low-dose radiation
induction of cellular signaling

1433
01:04:59,400 --> 01:05:01,740
that may stimulate
cellular protection

1434
01:05:01,740 --> 01:05:04,230
systems over hours to
weeks against accumulation

1435
01:05:04,230 --> 01:05:05,905
of DNA damage."

1436
01:05:05,905 --> 01:05:07,530
MICHAEL SHORT: Was
this the paper cited

1437
01:05:07,530 --> 01:05:09,953
in the other one that
actually said hours two weeks?

1438
01:05:09,953 --> 01:05:11,370
GUEST SPEAKER: I
believe so, yeah.

1439
01:05:11,370 --> 01:05:12,370
MICHAEL SHORT: OK, cool.

1440
01:05:12,370 --> 01:05:14,341
GUEST SPEAKER: And
then we can actually--

1441
01:05:14,341 --> 01:05:15,390
MICHAEL SHORT:
[INAUDIBLE] this one?

1442
01:05:15,390 --> 01:05:16,182
GUEST SPEAKER: Yes.

1443
01:05:16,182 --> 01:05:20,048
We can look up the full
text on Google Scholar.

1444
01:05:20,048 --> 01:05:21,090
MICHAEL SHORT: That's OK.

1445
01:05:21,090 --> 01:05:23,465
When you know what you're
looking for, you can verify it.

1446
01:05:23,465 --> 01:05:26,970
That's-- that's a useful thing
for Google is like to find

1447
01:05:26,970 --> 01:05:28,000
known content.

1448
01:05:28,000 --> 01:05:32,260
But if you're trying to
survey a field in Google, no.

1449
01:05:32,260 --> 01:05:34,242
GUEST SPEAKER: That's
not what I wanted.

1450
01:05:34,242 --> 01:05:35,200
MICHAEL SHORT: Not yet.

1451
01:05:35,200 --> 01:05:37,255
I'm sure-- I'm sure
they're working on it.

1452
01:05:37,255 --> 01:05:38,713
But they're not
Web of Science yet.

1453
01:05:43,150 --> 01:05:44,629
GUEST SPEAKER: All right.

1454
01:05:44,629 --> 01:05:45,615
AUDIENCE: [INAUDIBLE]

1455
01:05:49,080 --> 01:05:52,020
GUEST SPEAKER: Does anybody see
a Get The Full Paper button?

1456
01:05:52,020 --> 01:05:53,300
Oh, wait, right here, right?

1457
01:05:53,300 --> 01:05:54,120
MICHAEL SHORT: Yep.

1458
01:05:54,120 --> 01:05:54,620
That's it.

1459
01:05:54,620 --> 01:05:55,920
GUEST SPEAKER: OK.

1460
01:05:55,920 --> 01:05:56,700
Sign in?

1461
01:05:56,700 --> 01:05:59,760
MICHAEL SHORT: Sounds like
we don't subscribe to this.

1462
01:05:59,760 --> 01:06:02,100
GUEST SPEAKER: Oh, I was
able to get to it somehow.

1463
01:06:02,100 --> 01:06:03,065
Well, yeah.

1464
01:06:03,065 --> 01:06:05,690
AUDIENCE: I have another article
supporting this claim, though.

1465
01:06:05,690 --> 01:06:06,420
MICHAEL SHORT: OK.

1466
01:06:06,420 --> 01:06:07,628
GUEST SPEAKER: But this one--

1467
01:06:07,628 --> 01:06:09,880
AUDIENCE: Submit it, or
bring yours up, or whatever.

1468
01:06:09,880 --> 01:06:11,297
GUEST SPEAKER: And
then this one--

1469
01:06:11,297 --> 01:06:12,690
this one just had
some nice data.

1470
01:06:12,690 --> 01:06:14,148
If I'm going to
summarize, it had--

1471
01:06:14,148 --> 01:06:18,690
it was looking at the amount
of DNA damage instances

1472
01:06:18,690 --> 01:06:23,850
compared normal background dose
to like very, very low dose.

1473
01:06:23,850 --> 01:06:26,340
And the very, very low
dose was significantly less

1474
01:06:26,340 --> 01:06:28,380
than the normal background dose.

1475
01:06:28,380 --> 01:06:29,880
So that just kind
of shows that like

1476
01:06:29,880 --> 01:06:33,660
very low levels of radiation are
like no worse for you than just

1477
01:06:33,660 --> 01:06:35,580
background dose,
which is interesting.

1478
01:06:35,580 --> 01:06:36,413
MICHAEL SHORT: Cool.

1479
01:06:36,413 --> 01:06:37,300
GUEST SPEAKER: Yeah.

1480
01:06:37,300 --> 01:06:38,967
MICHAEL SHORT: I also
want to make sure,

1481
01:06:38,967 --> 01:06:41,955
do you guys have more
articles you want to show?

1482
01:06:41,955 --> 01:06:42,909
AUDIENCE: [INAUDIBLE]

1483
01:06:45,737 --> 01:06:47,570
MICHAEL SHORT: If you
want to send it to me,

1484
01:06:47,570 --> 01:06:49,432
I'll put it up here.

1485
01:06:49,432 --> 01:06:51,890
GUEST SPEAKER: All right, I
minimized because I didn't just

1486
01:06:51,890 --> 01:06:52,970
want to leave your email.

1487
01:06:52,970 --> 01:06:53,420
MICHAEL SHORT: Oh, I don't care.

1488
01:06:53,420 --> 01:06:54,140
There's nothing--

1489
01:06:54,140 --> 01:06:54,890
GUEST SPEAKER: OK.

1490
01:06:54,890 --> 01:06:56,432
MICHAEL SHORT: I'll
bring it back up.

1491
01:06:58,890 --> 01:07:00,550
So that's all the ones you sent?

1492
01:07:05,288 --> 01:07:07,256
Cool.

1493
01:07:07,256 --> 01:07:09,880
Actually, this one-- this
debate is turning out

1494
01:07:09,880 --> 01:07:12,880
a whole lot more interesting
than previously because,

1495
01:07:12,880 --> 01:07:14,290
well, because you're thinking.

1496
01:07:14,290 --> 01:07:16,070
It's actually really
nice to see this.

1497
01:07:16,070 --> 01:07:17,435
And this is the--

1498
01:07:17,435 --> 01:07:18,310
AUDIENCE: [INAUDIBLE]

1499
01:07:18,310 --> 01:07:19,685
MICHAEL SHORT:
I'm not surprised.

1500
01:07:19,685 --> 01:07:20,620
Don't worry.

1501
01:07:20,620 --> 01:07:23,140
It's just pleasant to have
a debate about something

1502
01:07:23,140 --> 01:07:25,480
controversial with a
whole group of people

1503
01:07:25,480 --> 01:07:28,390
who are thinking and
researching rather than shouting

1504
01:07:28,390 --> 01:07:30,116
and like throwing plates.

1505
01:07:30,116 --> 01:07:31,388
AUDIENCE: [INAUDIBLE]

1506
01:07:31,388 --> 01:07:33,430
MICHAEL SHORT: Oh, no, if
you want throw a chair,

1507
01:07:33,430 --> 01:07:34,645
but I might throw one back.

1508
01:07:34,645 --> 01:07:35,635
AUDIENCE: [INAUDIBLE]

1509
01:07:56,460 --> 01:07:58,920
MICHAEL SHORT: I wonder if
anyone's gone out recently

1510
01:07:58,920 --> 01:08:02,100
and has come up with all of the
pro and anti hormesis studies

1511
01:08:02,100 --> 01:08:04,380
and actually written
a paper that says,

1512
01:08:04,380 --> 01:08:06,870
that's not the point,
because, really, what we're

1513
01:08:06,870 --> 01:08:07,770
getting-- huh?

1514
01:08:07,770 --> 01:08:08,490
AUDIENCE: You could write that.

1515
01:08:08,490 --> 01:08:10,907
MICHAEL SHORT: No, I think you
could write that paper now.

1516
01:08:10,907 --> 01:08:13,173
AUDIENCE: Well, oh.

1517
01:08:13,173 --> 01:08:15,840
MICHAEL SHORT: It would make for
a pretty cool undergrad thesis,

1518
01:08:15,840 --> 01:08:17,189
actually.

1519
01:08:17,189 --> 01:08:18,335
Yeah?

1520
01:08:18,335 --> 01:08:19,710
Maybe I can tell
you a little bit

1521
01:08:19,710 --> 01:08:21,335
about what an undergrad
thesis actually

1522
01:08:21,335 --> 01:08:23,220
entails because the
seniors are all asking.

1523
01:08:23,220 --> 01:08:25,800
But it's good for you
to know ahead of time.

1524
01:08:25,800 --> 01:08:28,319
So the main requirement
for an undergrad thesis

1525
01:08:28,319 --> 01:08:30,112
is it's got to be your work.

1526
01:08:30,112 --> 01:08:31,529
That doesn't mean
you have to have

1527
01:08:31,529 --> 01:08:35,080
collected the data yourself,
like done an experiment.

1528
01:08:35,080 --> 01:08:37,590
But it has to be some
original thought, or idea,

1529
01:08:37,590 --> 01:08:39,870
or accumulation of yours.

1530
01:08:39,870 --> 01:08:43,920
So trying to settle this debate
and trying to figure out what

1531
01:08:43,920 --> 01:08:46,529
would be a proposed
chill region to say,

1532
01:08:46,529 --> 01:08:48,660
forget the linear
threshold or no threshold.

1533
01:08:48,660 --> 01:08:50,220
That's for the basic scientists.

1534
01:08:50,220 --> 01:08:53,310
If you are a government and
want to legislate something that

1535
01:08:53,310 --> 01:08:56,460
actually captures should
people be afraid or not,

1536
01:08:56,460 --> 01:09:00,149
defining that region would
be a pretty cool study to do

1537
01:09:00,149 --> 01:09:03,029
in the meta-analysis of
lots of other studies,

1538
01:09:03,029 --> 01:09:05,279
tracing back how worthy--

1539
01:09:05,279 --> 01:09:08,279
I mean, a lot of people
refer to the Hiroshima data

1540
01:09:08,279 --> 01:09:10,680
set because that's about
the biggest one we have.

1541
01:09:10,680 --> 01:09:13,350
In addition to folks with
radon or folks that smoke,

1542
01:09:13,350 --> 01:09:15,990
they were all exposed
to the same thing

1543
01:09:15,990 --> 01:09:17,410
in the relatively same area.

1544
01:09:17,410 --> 01:09:21,120
So it's a good control
group of people.

1545
01:09:21,120 --> 01:09:23,899
But how was-- how were
those doses estimated?

1546
01:09:23,899 --> 01:09:24,899
You have to dig that up.

1547
01:09:24,899 --> 01:09:27,600
And the act of digging
that up and then recasting

1548
01:09:27,600 --> 01:09:30,250
all of these new studies
in the basis of everything

1549
01:09:30,250 --> 01:09:32,250
we've learned since would
make for a pretty cool

1550
01:09:32,250 --> 01:09:34,240
undergrad thesis topic.

1551
01:09:34,240 --> 01:09:37,612
So as undergrad chair, I
wouldn't say no to that.

1552
01:09:43,020 --> 01:09:47,370
Threshold and other departures
from linear quadratic curvature

1553
01:09:47,370 --> 01:09:49,830
in the same data
set appears to--

1554
01:09:49,830 --> 01:09:53,189
is it the LSS data set?

1555
01:09:53,189 --> 01:09:54,490
Let's try to get the full text.

1556
01:10:00,310 --> 01:10:00,820
Awesome!

1557
01:10:00,820 --> 01:10:02,500
I think it's looking good.

1558
01:10:06,720 --> 01:10:07,220
Great!

1559
01:10:12,748 --> 01:10:14,040
Now I've seen that name before.

1560
01:10:16,970 --> 01:10:18,400
Interesting.

1561
01:10:18,400 --> 01:10:20,200
AUDIENCE: [INAUDIBLE]

1562
01:10:37,105 --> 01:10:38,230
MICHAEL SHORT: Interesting.

1563
01:10:38,230 --> 01:10:39,700
They propose
another model called

1564
01:10:39,700 --> 01:10:42,290
a power of dose, a power law.

1565
01:10:42,290 --> 01:10:44,835
And they say,
depending on this--

1566
01:10:44,835 --> 01:10:46,210
there's little
evidence that it's

1567
01:10:46,210 --> 01:10:49,180
statistically different
from one which

1568
01:10:49,180 --> 01:10:55,000
is a what do they call
one linear threshold

1569
01:10:55,000 --> 01:11:00,190
quadratic threshold or linear
quadratic threshold, OK?

1570
01:11:00,190 --> 01:11:03,350
So, again, it seems to be
yet another paper saying,

1571
01:11:03,350 --> 01:11:04,780
I don't think it matters.

1572
01:11:04,780 --> 01:11:07,000
Statistics says
it doesn't matter.

1573
01:11:07,000 --> 01:11:10,156
You could fit any
model to this data.

1574
01:11:18,730 --> 01:11:20,110
Let's get to the methods.

1575
01:11:20,110 --> 01:11:21,589
AUDIENCE: [INAUDIBLE]

1576
01:11:29,375 --> 01:11:30,500
MICHAEL SHORT: Interesting.

1577
01:11:37,560 --> 01:11:41,930
So dose response for
all non-cancer mortality

1578
01:11:41,930 --> 01:11:45,090
in the atomic bomb survivors.

1579
01:11:45,090 --> 01:11:48,020
So, also, in this case,
it's mortalities not

1580
01:11:48,020 --> 01:11:51,520
caused by cancer.

1581
01:11:51,520 --> 01:11:54,430
AUDIENCE: Like, caused
by radiation disease?

1582
01:11:54,430 --> 01:11:56,860
Or is that caused
by [INAUDIBLE]??

1583
01:11:56,860 --> 01:11:59,250
MICHAEL SHORT: So
this would be--

1584
01:11:59,250 --> 01:12:03,750
I think what they're getting
at is is there a response,

1585
01:12:03,750 --> 01:12:06,060
or is there a change in
the amount of mortality

1586
01:12:06,060 --> 01:12:08,980
not due to cancer and the--

1587
01:12:08,980 --> 01:12:09,930
the--

1588
01:12:09,930 --> 01:12:12,780
AUDIENCE: Health benefits other
than decreasing risk of cancer.

1589
01:12:12,780 --> 01:12:15,515
MICHAEL SHORT: Or in this
case, health detriments, right?

1590
01:12:15,515 --> 01:12:17,640
Because in this-- you know,
it never goes negative.

1591
01:12:17,640 --> 01:12:20,470
You can't really
tell in some cases.

1592
01:12:20,470 --> 01:12:20,970
Let's see.

1593
01:12:30,998 --> 01:12:33,040
Yeah, quite hard to tell,
especially considering.

1594
01:12:33,040 --> 01:12:36,160
And so at the low doses,
what would you guys

1595
01:12:36,160 --> 01:12:38,000
say for the low dose data?

1596
01:12:38,000 --> 01:12:39,250
AUDIENCE: That doesn't matter.

1597
01:12:39,250 --> 01:12:41,458
MICHAEL SHORT: I see a pretty
well-defined chill zone

1598
01:12:41,458 --> 01:12:43,860
right there, right?

1599
01:12:43,860 --> 01:12:44,998
AUDIENCE: Chill zone?

1600
01:12:44,998 --> 01:12:46,540
MICHAEL SHORT: We're
definitely still

1601
01:12:46,540 --> 01:12:49,360
in the chill zone at 0.4
sieverts of colon dose.

1602
01:12:49,360 --> 01:12:51,967
And that's a pretty
hefty amount of dose.

1603
01:12:51,967 --> 01:12:54,550
You know, we're talking eight
or nine times the allowed amount

1604
01:12:54,550 --> 01:12:57,490
that you're able to get in a
year from occupational safety

1605
01:12:57,490 --> 01:12:58,690
limits.

1606
01:12:58,690 --> 01:13:00,100
Once the doses
get higher, things

1607
01:13:00,100 --> 01:13:04,750
seem to get a little more
deterministic or statistically

1608
01:13:04,750 --> 01:13:07,030
significant.

1609
01:13:07,030 --> 01:13:09,430
But, yeah, look at all
the different models.

1610
01:13:09,430 --> 01:13:12,040
The linear threshold,
quadratic threshold,

1611
01:13:12,040 --> 01:13:14,770
linear quadratic
threshold, power of dose

1612
01:13:14,770 --> 01:13:17,860
all goes straight through not
just like in the error bars,

1613
01:13:17,860 --> 01:13:20,560
but almost straight through
most of the data points,

1614
01:13:20,560 --> 01:13:22,913
except for the
really far away ones.

1615
01:13:22,913 --> 01:13:24,580
So this is a pretty
neat study, showing,

1616
01:13:24,580 --> 01:13:26,080
like, hey, the
relationship does not

1617
01:13:26,080 --> 01:13:29,290
appear to matter for
doses of consequence.

1618
01:13:29,290 --> 01:13:32,320
I would call 2 sieverts
a dose of consequence

1619
01:13:32,320 --> 01:13:35,290
based on our earlier discussion
of biological effects.

1620
01:13:35,290 --> 01:13:37,307
Luckily, it doesn't go
much farther than that.

1621
01:13:37,307 --> 01:13:38,890
You don't want a lot
of people to have

1622
01:13:38,890 --> 01:13:42,580
received doses beyond 10 gray.

1623
01:13:42,580 --> 01:13:44,518
But this is pretty
compelling to me

1624
01:13:44,518 --> 01:13:46,810
to say, like, we can argue
about what the real model is

1625
01:13:46,810 --> 01:13:49,090
and what the underlying
mechanism is, but is

1626
01:13:49,090 --> 01:13:52,300
this a question we really
should be asking ourselves

1627
01:13:52,300 --> 01:13:54,415
when the total risk--

1628
01:13:54,415 --> 01:13:56,290
let's say, when the
total risk to an organism

1629
01:13:56,290 --> 01:13:59,830
reaches about 100%, once you
reach a a dose where it doesn't

1630
01:13:59,830 --> 01:14:03,010
even matter, then
is this a question

1631
01:14:03,010 --> 01:14:06,220
that we should really be
debating in the public sphere?

1632
01:14:06,220 --> 01:14:09,390
I love the outcome of
this particular debate.

1633
01:14:11,920 --> 01:14:14,870
Lots of statistics,
don't have time to parse.

1634
01:14:19,613 --> 01:14:21,530
Is there anything else,
Chris, that you wanted

1635
01:14:21,530 --> 01:14:24,708
to highlight in this study?

1636
01:14:24,708 --> 01:14:30,065
AUDIENCE: This appears
to [INAUDIBLE] comments

1637
01:14:30,065 --> 01:14:32,392
on Professor Donald
Pierce on [INAUDIBLE]..

1638
01:14:32,392 --> 01:14:33,600
MICHAEL SHORT: Oh, OK, well--

1639
01:14:33,600 --> 01:14:35,000
AUDIENCE: Do you think it
could be the same Pierce?

1640
01:14:35,000 --> 01:14:35,990
MICHAEL SHORT: Maybe.

1641
01:14:35,990 --> 01:14:37,940
It was a UK Pierce, I think.

1642
01:14:45,510 --> 01:14:47,940
That's pretty cool.

1643
01:14:47,940 --> 01:14:49,440
So anyone else have
any other papers

1644
01:14:49,440 --> 01:14:52,050
they want to show for or
against or for our sort

1645
01:14:52,050 --> 01:14:54,000
of collective new conclusion?

1646
01:14:56,605 --> 01:14:58,063
Which is that we
should just relax.

1647
01:15:02,230 --> 01:15:03,710
Cool.

1648
01:15:03,710 --> 01:15:04,710
Well, that went-- yeah?

1649
01:15:04,710 --> 01:15:05,210
Charlie?

1650
01:15:05,210 --> 01:15:06,960
AUDIENCE: I just had
had a question, like,

1651
01:15:06,960 --> 01:15:09,818
what would be like a
posed use of radiation

1652
01:15:09,818 --> 01:15:12,806
hormesis [INAUDIBLE]?

1653
01:15:12,806 --> 01:15:13,568
[INAUDIBLE]

1654
01:15:13,568 --> 01:15:15,110
MICHAEL SHORT: So
let's say you could

1655
01:15:15,110 --> 01:15:18,740
prove beyond a shadow of a doubt
that a little bit of radiation

1656
01:15:18,740 --> 01:15:20,480
exposure was a good thing.

1657
01:15:20,480 --> 01:15:22,670
You might then prescribe
radiation treatments

1658
01:15:22,670 --> 01:15:25,523
in order to reap the benefits.

1659
01:15:25,523 --> 01:15:27,440
I don't think there's
been a single study that

1660
01:15:27,440 --> 01:15:29,357
shows that there's like
deterministic benefits

1661
01:15:29,357 --> 01:15:30,842
from irradiating people.

1662
01:15:30,842 --> 01:15:32,300
Some of the studies
show that folks

1663
01:15:32,300 --> 01:15:35,390
that have gotten exposed
via various routes

1664
01:15:35,390 --> 01:15:37,250
do show a lower
incidence of cancer.

1665
01:15:37,250 --> 01:15:41,540
So you could almost think
of it like a vitamin, not

1666
01:15:41,540 --> 01:15:43,430
an injectable vitamin.

1667
01:15:43,430 --> 01:15:46,730
But-- so back-- there are
lots of pictures online

1668
01:15:46,730 --> 01:15:49,290
and stories of way up
in the north in Russia

1669
01:15:49,290 --> 01:15:51,530
and northern countries
that expose you

1670
01:15:51,530 --> 01:15:53,270
to ultraviolet
radiation to stimulate

1671
01:15:53,270 --> 01:15:55,670
the production of vitamin
D in your skin cells

1672
01:15:55,670 --> 01:15:59,120
because in the absence of an
ingestible source of vitamin D,

1673
01:15:59,120 --> 01:16:03,105
you make it naturally, but not
when there's eternal darkness.

1674
01:16:03,105 --> 01:16:05,480
So they'd actually have kids
stand in front of a UV lamp,

1675
01:16:05,480 --> 01:16:07,610
which does have ill effects.

1676
01:16:07,610 --> 01:16:09,650
That can cause
also skin cancers,

1677
01:16:09,650 --> 01:16:12,380
but the benefits of the
organism in generating

1678
01:16:12,380 --> 01:16:14,793
vitamin D that you need
for health are greater.

1679
01:16:14,793 --> 01:16:15,960
So that might be an example.

1680
01:16:15,960 --> 01:16:19,670
These-- these sorts of ideas
are not that far fetched.

1681
01:16:19,670 --> 01:16:22,220
If you put little kids
in front of UV lamps,

1682
01:16:22,220 --> 01:16:23,840
which you know
can do bad things,

1683
01:16:23,840 --> 01:16:26,270
but also does more good
things, then who's to say it

1684
01:16:26,270 --> 01:16:27,590
shouldn't happen for radiation?

1685
01:16:27,590 --> 01:16:29,600
Well, no one's to
say yet because we

1686
01:16:29,600 --> 01:16:34,070
have no real conclusive
proof that it is helpful.

1687
01:16:34,070 --> 01:16:35,824
But that was the-- yeah?

1688
01:16:36,324 --> 01:16:40,800
AUDIENCE: Have there been any
mechanisms that [INAUDIBLE]??

1689
01:16:40,800 --> 01:16:42,550
MICHAEL SHORT: You
mean in-- for radiation

1690
01:16:42,550 --> 01:16:43,690
or for something else?

1691
01:16:43,690 --> 01:16:44,690
AUDIENCE: For radiation.

1692
01:16:44,690 --> 01:16:47,065
MICHAEL SHORT: The mechanisms
of-- so that one study that

1693
01:16:47,065 --> 01:16:48,100
Chris showed that--

1694
01:16:48,100 --> 01:16:51,010
what was the idea?

1695
01:16:51,010 --> 01:16:52,750
That-- [INAUDIBLE].

1696
01:16:52,750 --> 01:16:54,988
The first one that you
showed, the mouse one,

1697
01:16:54,988 --> 01:16:56,530
and then the one
that Chris mentioned

1698
01:16:56,530 --> 01:16:58,210
where a little bit
of radiation dose

1699
01:16:58,210 --> 01:17:00,940
stimulated the immune system.

1700
01:17:00,940 --> 01:17:03,460
That might be a
potential good thing,

1701
01:17:03,460 --> 01:17:06,700
where the damage or
death of a few cells

1702
01:17:06,700 --> 01:17:10,510
may stimulate the nearby ones
to ramp up an immune response,

1703
01:17:10,510 --> 01:17:14,140
thus snuffing out any other
infection or problem that's

1704
01:17:14,140 --> 01:17:15,040
coming up.

1705
01:17:15,040 --> 01:17:16,720
That could be a use.

1706
01:17:16,720 --> 01:17:19,090
But we have to be proved
with much more confidence

1707
01:17:19,090 --> 01:17:20,356
than anything I've seen today.

1708
01:17:23,547 --> 01:17:24,630
So that's a good question.

1709
01:17:24,630 --> 01:17:25,963
Yeah, like how would you use it?

1710
01:17:25,963 --> 01:17:28,835
Use it like a vitamin, like
a UV lamp, like a SAD lamp.

1711
01:17:28,835 --> 01:17:30,210
Although, I don't
think SAD lamps

1712
01:17:30,210 --> 01:17:33,580
do anything bad, the
Seasonal Affective Disorder,

1713
01:17:33,580 --> 01:17:36,850
the most unfortunate
acronym in the world.

1714
01:17:36,850 --> 01:17:37,548
Yeah.

1715
01:17:37,548 --> 01:17:38,504
AUDIENCE: [INAUDIBLE]

1716
01:17:40,420 --> 01:17:42,970
MICHAEL SHORT: Yes.

1717
01:17:42,970 --> 01:17:45,250
I don't know if that
would be easy to swallow.

1718
01:17:45,250 --> 01:17:46,980
Yeah.

1719
01:17:46,980 --> 01:17:48,130
Cool.

1720
01:17:48,130 --> 01:17:52,035
All right, any other
thoughts from this exercise?

1721
01:17:52,035 --> 01:17:54,160
I think I'll do more
interactive classes like this.

1722
01:17:54,160 --> 01:17:57,256
It's good to hear you
guys talk for a change.

1723
01:17:57,256 --> 01:17:58,220
Cool.

1724
01:17:58,220 --> 01:17:59,770
OK.