#16 One Woman's Superpower: Detection __ Parkinson's Disease

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Speaker:
Hi, I'm Megan and I'm Debbie.
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We are real life scientists, and
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we want to share some sciencey
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stories that are surprising,
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smelly, and sometimes
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groundbreaking, but with an ad
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libs twist.
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You are listening to lab libs.
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I paused because I realized I
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gave away a lab lab's answer in
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my intro.
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Oh man.
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Well, I just like that.
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So many of your intros have a
question mark at the end.
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It's always the question.
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Always the question.
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I'm not sure.
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It's definitely groundbreaking,
but in a very strange way.
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Oh, okay.
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All right.
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Okay.
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I'm ready.
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You ready for an out of context
quote?
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That's right.
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Okay.
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This out of context quote is as
follows.
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We relate.
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A lot of people were there and I
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walked into the room and I
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thought, smell.
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I was already laughing like
before.
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Before you said smell.
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I was like, what is this?
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Like some narrative?
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Like, can you read it one more
time?
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We were late.
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A lot of people were there, and
I walked into the room and I
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thought, smell, smell.
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Okay.
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Joy Milne said that.
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Have you ever heard of her?
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All right.
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Nope.
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Well, no. Well, she's a nurse
with a doctor for a husband.
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Basically a normal woman,
honestly.
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Okay.
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And we'll get back to her later.
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Okay.
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So my story today centers around
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a certain neurodegenerative
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disease, which is your first lab
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libs.
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I always start out like the very
first sentence.
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Yeah, sometimes I do.
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The lab looms.
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so what did you say, miss?
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Right.
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Yeah.
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Isn't that.
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This is neurodegenerative, isn't
it?
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I think so, yeah.
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Okay.
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It's not that one.
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It's not that one.
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Um. Second guess.
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Oh. Lou Gehrig's.
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Nope.
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What's the one that.
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Oh. The Parkinson's.
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Yes.
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Oh, yeah.
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Okay.
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Yeah.
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Okay.
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third tries the charm or
whatever.
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Right?
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Let me just keep guessing until
I get it.
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Yeah, yeah.
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Yep.
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so I'm gonna give you a little
bit, a little bit of background
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information on Parkinson's
because I didn't really know
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much about it other than it
causes tremors, right?
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Do you know anything about it?
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yes and no. The only thing I
know is because my grandfather
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had it or got it, but he got it
when he was a lot older, which
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was good, you know?
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and really he just kind of, I
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mean, he shook a lot, but he
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also just kind of became
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non-verbal.
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Yeah.
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But that's all like my only
experience with it.
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Gotcha.
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Well, that we'll see that, late
diagnosis comes into play in the
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story a lot.
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All right.
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Cool.
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So Parkinson's disease is a
disease of the nervous system
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affecting mainly movement.
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Symptoms come on slowly and get
worse over time.
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Most of the time it starts with
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a tremor or sometimes a loss of
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balance.
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or just general stiffening and
soreness and stuff.
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And over time, it makes a lot of
things more difficult.
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Moving around in general even
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can affect your automatic
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movements like posture, blinking
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and moving your arms while you
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walk.
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Interesting.
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Yeah.
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Yeah.
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Wow.
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Later in the progression, it
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affects a lot more than just
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basic movements.
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it can affect your behavior,
memory, your overall thinking
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and reasoning even.
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Mhm.
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And it can cause a lot of
irritability and depression and
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changes in relationships.
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Yeah.
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Right now, there's not a cure.
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but there are methods to delay
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the progress if it's caught
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early.
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Mhm.
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Basically high intensity
exercise, often managing your
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sleep, stress and diet.
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There are some Medications and
cognitive engagement, with which
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these all sound like pretty
basic stuff that anyone would
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tell you, like do these things
to be healthy, right?
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For anything, particularly in
patients with the beginning
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stages of Parkinson's and all
stages, really, it actually does
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slow the progress significantly.
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Wow.
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Especially the often doing high
intensity exercise.
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Yeah.
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And just cognitive engagement
overall, like what you would
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imagine, like puzzles and
reading and learning things and
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keeping your mind active.
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Right, right, right through
everything.
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But since the symptoms come on
gradually, many people don't
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realize they have it until it's
already developed quite far.
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Globally, there are about ten
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million people with Parkinson's
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disease.
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It's the second most common
neurodegenerative disease, I
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think, after Alzheimer's.
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But I didn't look that up.
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But I assume that is the most
common.
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That common sounds, right?
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And it's growing faster than any
other neurodegenerative disease.
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This generation has two point
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five times increase than the
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previous generation measles
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vaccines.
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Is that what it is?
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What?
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Yeah, it's definitely just in
case y'all didn't know.
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We're apparently anti-vaxxers on
this podcast.
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Um, I'm just kidding.
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I'm going.
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Auntie, please don't call me.
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Oh, don't clip that, please.
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Uh, no, I don't know.
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We don't know why.
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Oh, we don't know why.
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Okay.
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there's a lot of new research
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that's been done to try to
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discover this mysterious cause
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or a cure or a prevention
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method, but we haven't found any
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of that.
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we have learned a lot, though.
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There's a lot of genetic risk
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markers that have been
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identified, okay, that they can
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screen for.
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And some environmental factors
have been found to be correlated
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with increased risk, like excess
use of caffeine or tobacco and a
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type of pollutant.
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Your next lab libs.
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So this type of pollutant
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there's actually two answers is
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an environmental factor that
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increases your risk of getting
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Parkinson's.
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You said something really
specific.
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I'm sorry.
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Tell us what you said.
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I said roundup weedkiller.
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Yep.
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Because I'm pro roundup these
days.
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You're pro roundup these days.
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You're using it in your lawn.
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I don't.
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I don't care about regulation or
anything like, get that crap
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back out there or somebody.
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So it's not round.
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There's just so much to clip in
this episode.
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Oh my God.
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Um, Debbie does her most
sarcastic episode thus far.
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actually.
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You're close.
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Yeah.
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Okay.
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What is it?
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There are two pollutants that
have been correlated with
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increased risk in Parkinson's.
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They are pesticides and some
water pollutants.
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Well, that is one problem with
the roundup was because it was
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polluting the water, right?
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Because people were using it on
their lawns and then it rains
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or, you know, whatever.
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And it was carrying Like the
pollutant away.
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Yeah.
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You know.
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Yeah, yeah.
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yeah, just to point out though,
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that doesn't necessarily mean
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that those things cause
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Parkinson's disease, but they do
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have a correlation with an
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increased risk.
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Okay.
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So correlation isn't the same as
causing something.
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It just could be that something
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else causes both of those things
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to be present in your life,
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right?
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But it is still.
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Important information towards
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learning more about what the
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cause is.
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So is it.
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Did they realize that because of
like, who was getting it?
240
00:08:44,090 --> 00:08:44,809
Speaker:
I don't know.
241
00:08:44,809 --> 00:08:47,539
Speaker:
I was just curious how they
would know.
242
00:08:47,539 --> 00:08:50,740
Speaker:
Maybe there's some sort of
243
00:08:50,740 --> 00:08:56,059
Speaker:
surveys being done that ask a
244
00:08:56,059 --> 00:08:57,659
Speaker:
bunch of questions about what
245
00:08:57,659 --> 00:08:59,059
Speaker:
you've been exposed to over your
246
00:08:59,059 --> 00:09:00,580
Speaker:
life, or what other conditions
247
00:09:00,580 --> 00:09:02,139
Speaker:
you have, that they ask all
248
00:09:02,139 --> 00:09:03,419
Speaker:
these questions to people with
249
00:09:03,419 --> 00:09:05,940
Speaker:
Parkinson's disease, or it might
250
00:09:05,940 --> 00:09:09,139
Speaker:
be larger demographic surveys
251
00:09:09,139 --> 00:09:11,039
Speaker:
where you can just list what
252
00:09:11,039 --> 00:09:13,139
Speaker:
disorders you have, and they can
253
00:09:13,139 --> 00:09:14,580
Speaker:
correlate that information with
254
00:09:14,580 --> 00:09:15,759
Speaker:
other questions They've asked
255
00:09:15,759 --> 00:09:16,139
Speaker:
you.
256
00:09:16,139 --> 00:09:16,980
Speaker:
Yeah.
257
00:09:16,980 --> 00:09:17,220
Speaker:
Okay.
258
00:09:17,220 --> 00:09:20,220
Speaker:
It might not even be specific to
Parkinson's where they're
259
00:09:20,220 --> 00:09:21,980
Speaker:
getting that information.
260
00:09:21,980 --> 00:09:23,539
Speaker:
MM. I'm not sure.
261
00:09:23,539 --> 00:09:24,299
Speaker:
MM. Okay.
262
00:09:24,299 --> 00:09:26,419
Speaker:
So we know some things about
263
00:09:26,419 --> 00:09:28,419
Speaker:
what's correlated with risk for
264
00:09:28,419 --> 00:09:30,259
Speaker:
Parkinson's as well as genetic
265
00:09:30,259 --> 00:09:31,460
Speaker:
markers.
266
00:09:31,460 --> 00:09:34,580
Speaker:
And we have some idea of what's
267
00:09:34,580 --> 00:09:36,860
Speaker:
going on in the brain with
268
00:09:36,860 --> 00:09:38,580
Speaker:
people that have Parkinson's,
269
00:09:38,580 --> 00:09:40,230
Speaker:
even though we're not sure what
270
00:09:40,230 --> 00:09:41,750
Speaker:
the mechanism is that's causing
271
00:09:41,750 --> 00:09:42,950
Speaker:
these things, like why it's
272
00:09:42,950 --> 00:09:43,669
Speaker:
happening, right?
273
00:09:43,669 --> 00:09:45,509
Speaker:
But we know what is happening,
right?
274
00:09:45,509 --> 00:09:48,590
Speaker:
We know that there are these
clumps of proteins called Lewy
275
00:09:48,590 --> 00:09:52,470
Speaker:
bodies that are present in
brains with Parkinson's disease.
276
00:09:52,470 --> 00:09:55,190
Speaker:
And other changes happen in the
brain too.
277
00:09:55,190 --> 00:09:57,470
Speaker:
Particularly there's changes in
278
00:09:57,470 --> 00:10:00,470
Speaker:
the mitochondria structure that
279
00:10:00,470 --> 00:10:02,789
Speaker:
cause cell damage, that
280
00:10:02,789 --> 00:10:04,950
Speaker:
mitochondria start not working
281
00:10:04,950 --> 00:10:07,769
Speaker:
properly and that causes cell
282
00:10:07,769 --> 00:10:08,830
Speaker:
damage.
283
00:10:08,830 --> 00:10:09,629
Speaker:
Interesting.
284
00:10:09,629 --> 00:10:13,070
Speaker:
And as everybody knows,
mitochondria is the powerhouse
285
00:10:13,070 --> 00:10:14,110
Speaker:
of the cell.
286
00:10:15,710 --> 00:10:18,370
Speaker:
So if you if you've taken by a
287
00:10:18,370 --> 00:10:21,490
Speaker:
powerhouse, if you've taken bio
288
00:10:21,490 --> 00:10:23,870
Speaker:
one, then ever in your lifetime,
289
00:10:23,870 --> 00:10:25,070
Speaker:
that's the only thing you
290
00:10:25,070 --> 00:10:27,429
Speaker:
remember anything.
291
00:10:27,429 --> 00:10:29,149
Speaker:
We all know the powerhouse.
292
00:10:29,149 --> 00:10:30,350
Speaker:
Yeah.
293
00:10:30,350 --> 00:10:32,370
Speaker:
So we've learned a lot, but
294
00:10:32,370 --> 00:10:33,990
Speaker:
there's still a lot we don't
295
00:10:33,990 --> 00:10:34,629
Speaker:
understand.
296
00:10:34,629 --> 00:10:35,509
Speaker:
Okay.
297
00:10:35,509 --> 00:10:38,309
Speaker:
In walks Joy Milne to the case.
298
00:10:38,309 --> 00:10:39,070
Speaker:
All right.
299
00:10:39,070 --> 00:10:39,870
Speaker:
To the scene.
300
00:10:39,870 --> 00:10:40,470
Speaker:
Mhm.
301
00:10:40,470 --> 00:10:43,669
Speaker:
Joy and her future husband, Les
Milne.
302
00:10:43,669 --> 00:10:45,789
Speaker:
Have a beginning to their story.
303
00:10:45,789 --> 00:10:48,309
Speaker:
That is so normal.
304
00:10:48,309 --> 00:10:49,750
Speaker:
It's cliche.
305
00:10:49,750 --> 00:10:50,029
Speaker:
Right?
306
00:10:50,029 --> 00:10:52,029
Speaker:
They were high school
sweethearts.
307
00:10:52,029 --> 00:10:55,549
Speaker:
They met in the late nineteen
sixties when she was sixteen and
308
00:10:55,549 --> 00:10:57,190
Speaker:
he was seventeen.
309
00:10:57,190 --> 00:11:01,429
Speaker:
Joy transferred to Les's school,
where he was on the swim team.
310
00:11:01,429 --> 00:11:05,269
Speaker:
And oddly enough, she remembers
noticing a nice trait about him.
311
00:11:05,269 --> 00:11:07,070
Speaker:
One of your five senses.
312
00:11:07,070 --> 00:11:08,330
Speaker:
Your next lab libs that I've
313
00:11:08,330 --> 00:11:09,750
Speaker:
given away several times over in
314
00:11:09,750 --> 00:11:10,750
Speaker:
this episode.
315
00:11:10,750 --> 00:11:12,990
Speaker:
All right, but you got it right
anyways.
316
00:11:12,990 --> 00:11:14,029
Speaker:
Yeah, I got it right.
317
00:11:14,029 --> 00:11:15,549
Speaker:
You said smell, which it is.
318
00:11:15,549 --> 00:11:17,830
Speaker:
Like she said he smelled good.
319
00:11:17,830 --> 00:11:18,629
Speaker:
Yeah, yeah.
320
00:11:18,629 --> 00:11:20,909
Speaker:
Okay, so Joy has hypersomnia,
321
00:11:20,909 --> 00:11:22,269
Speaker:
which means she has a
322
00:11:22,269 --> 00:11:24,070
Speaker:
genetically increased sense of
323
00:11:24,070 --> 00:11:24,590
Speaker:
smell.
324
00:11:24,590 --> 00:11:29,269
Speaker:
Oh, and she noticed right away
that he had a really nice smell.
325
00:11:29,269 --> 00:11:32,639
Speaker:
And she said he had a lovely
male mask.
326
00:11:32,639 --> 00:11:33,360
Speaker:
Okay.
327
00:11:36,360 --> 00:11:37,759
Speaker:
They fell in love.
328
00:11:37,759 --> 00:11:39,919
Speaker:
Yeah, they fell in love.
329
00:11:39,919 --> 00:11:42,200
Speaker:
They had several children.
330
00:11:42,200 --> 00:11:43,759
Speaker:
They had successful careers.
331
00:11:43,759 --> 00:11:44,840
Speaker:
She's a nurse.
332
00:11:44,840 --> 00:11:46,240
Speaker:
He's a doctor.
333
00:11:46,240 --> 00:11:49,279
Speaker:
They rarely fought peaceful
marriage.
334
00:11:49,279 --> 00:11:50,799
Speaker:
They were both generally quiet,
335
00:11:50,799 --> 00:11:51,980
Speaker:
and they appreciated each
336
00:11:51,980 --> 00:11:53,159
Speaker:
other's humor.
337
00:11:53,159 --> 00:11:54,960
Speaker:
Pretty average, right?
338
00:11:54,960 --> 00:11:55,519
Speaker:
Mhm.
339
00:11:55,519 --> 00:11:56,279
Speaker:
Sounds nice.
340
00:11:56,279 --> 00:11:57,240
Speaker:
Yeah.
341
00:11:57,240 --> 00:12:01,480
Speaker:
Then one day in nineteen seventy
five, around then I had to piece
342
00:12:01,480 --> 00:12:04,120
Speaker:
together all the the dates here.
343
00:12:04,120 --> 00:12:06,000
Speaker:
But I thought it it helped
344
00:12:06,000 --> 00:12:07,960
Speaker:
understand how long this is
345
00:12:07,960 --> 00:12:09,600
Speaker:
happening over.
346
00:12:09,600 --> 00:12:14,000
Speaker:
So they're in their thirties
now, nineteen seventy five ish.
347
00:12:15,000 --> 00:12:17,039
Speaker:
She notices that he starts to
348
00:12:17,039 --> 00:12:18,960
Speaker:
smell bad no matter what he
349
00:12:18,960 --> 00:12:19,759
Speaker:
does.
350
00:12:19,759 --> 00:12:25,080
Speaker:
Really, no one else, including
les himself, can smell it.
351
00:12:25,080 --> 00:12:26,799
Speaker:
No matter what he does.
352
00:12:26,799 --> 00:12:29,500
Speaker:
She tells him, you need to
shower more.
353
00:12:29,500 --> 00:12:34,259
Speaker:
Buys different detergent, all
kinds of things, because she can
354
00:12:34,259 --> 00:12:39,139
Speaker:
smell this musty, yeasty,
unpleasant odor coming from him.
355
00:12:40,139 --> 00:12:42,179
Speaker:
Well, no one else can smell it.
356
00:12:42,179 --> 00:12:43,179
Speaker:
Yeah, yeah.
357
00:12:43,179 --> 00:12:46,179
Speaker:
No, I mean, what I'm saying,
like, yeah, she's probably like,
358
00:12:46,179 --> 00:12:48,100
Speaker:
okay, obviously I'm losing it.
359
00:12:48,100 --> 00:12:48,779
Speaker:
Right?
360
00:12:48,779 --> 00:12:50,220
Speaker:
Yeah, yeah.
361
00:12:50,220 --> 00:12:53,720
Speaker:
And, he starts getting annoyed
about it, tells her, stop
362
00:12:53,720 --> 00:12:54,360
Speaker:
bringing that up.
363
00:12:54,360 --> 00:12:55,320
Speaker:
I suppose, you know.
364
00:12:55,320 --> 00:12:55,840
Speaker:
Yeah.
365
00:12:55,840 --> 00:12:58,080
Speaker:
So I get it.
366
00:12:58,080 --> 00:13:00,919
Speaker:
Like no one likes to be told
like, you fucking smell bad.
367
00:13:00,919 --> 00:13:01,919
Speaker:
Yeah.
368
00:13:01,919 --> 00:13:03,519
Speaker:
And especially totally normal.
369
00:13:03,519 --> 00:13:04,519
Speaker:
One person like.
370
00:13:04,519 --> 00:13:06,559
Speaker:
Yeah, that is a weird thing,
right?
371
00:13:06,559 --> 00:13:12,679
Speaker:
So eventually she just moves on
and really she just deals with
372
00:13:12,679 --> 00:13:14,480
Speaker:
it that he smells bad.
373
00:13:14,480 --> 00:13:16,759
Speaker:
I thought you meant she left him
when you said she moved.
374
00:13:16,759 --> 00:13:19,080
Speaker:
No, no, I was like, yeah, that
was it.
375
00:13:19,080 --> 00:13:20,399
Speaker:
That was the final straw.
376
00:13:20,399 --> 00:13:21,000
Speaker:
Wow.
377
00:13:21,000 --> 00:13:23,720
Speaker:
No, she she gets over it, okay.
378
00:13:23,720 --> 00:13:25,440
Speaker:
And they live on and whatever.
379
00:13:25,440 --> 00:13:28,100
Speaker:
Unfortunately, over the years,
380
00:13:28,100 --> 00:13:30,080
Speaker:
les changes in a bunch of other
381
00:13:30,080 --> 00:13:30,960
Speaker:
ways.
382
00:13:30,960 --> 00:13:34,159
Speaker:
He becomes moody, intolerant,
less thoughtful.
383
00:13:34,159 --> 00:13:37,240
Speaker:
She says, more argumentative.
384
00:13:37,240 --> 00:13:40,600
Speaker:
And one night he starts
attacking her in her sleep.
385
00:13:41,840 --> 00:13:45,639
Speaker:
He's clearly acting out a
nightmare, screaming, shaking
386
00:13:45,639 --> 00:13:49,480
Speaker:
her, but he's unaware of
anything that he's doing.
387
00:13:49,480 --> 00:13:51,720
Speaker:
But still, he's violently
attacking her.
388
00:13:51,720 --> 00:13:52,279
Speaker:
Yeah.
389
00:13:52,279 --> 00:13:53,600
Speaker:
So she insists that they go to
390
00:13:53,600 --> 00:13:54,840
Speaker:
the doctor and figure out what's
391
00:13:54,840 --> 00:13:55,759
Speaker:
wrong.
392
00:13:55,759 --> 00:13:56,399
Speaker:
And he.
393
00:13:56,399 --> 00:13:57,320
Speaker:
He was diagnosed with
394
00:13:57,320 --> 00:13:58,679
Speaker:
Parkinson's that year at age
395
00:13:58,679 --> 00:13:59,600
Speaker:
forty five.
396
00:13:59,600 --> 00:14:00,279
Speaker:
Oh, wow.
397
00:14:00,279 --> 00:14:02,639
Speaker:
So now we're in around nineteen
ninety five.
398
00:14:02,639 --> 00:14:04,919
Speaker:
Oh, my gosh, that's so young.
399
00:14:04,919 --> 00:14:05,679
Speaker:
I know.
400
00:14:05,679 --> 00:14:09,080
Speaker:
So twenty years goes by of them
401
00:14:09,080 --> 00:14:11,240
Speaker:
working through Les's worsening
402
00:14:11,240 --> 00:14:12,360
Speaker:
symptoms, living with his
403
00:14:12,360 --> 00:14:14,000
Speaker:
diagnosis.
404
00:14:14,000 --> 00:14:19,039
Speaker:
And one day they go to a type of
meeting, an in-person meeting,
405
00:14:19,039 --> 00:14:23,340
Speaker:
which is your next lab libs that
I asked you to guess.
406
00:14:23,340 --> 00:14:25,539
Speaker:
What do you think kind of
meeting they went to?
407
00:14:25,539 --> 00:14:27,059
Speaker:
Yeah, you said a type.
408
00:14:27,059 --> 00:14:29,980
Speaker:
A type of in-person meeting.
409
00:14:29,980 --> 00:14:31,419
Speaker:
And I said round table.
410
00:14:31,419 --> 00:14:35,259
Speaker:
Because I did not have any clue
what you were asking me.
411
00:14:36,580 --> 00:14:39,059
Speaker:
But I thought just like any kind
of meeting that you would go to.
412
00:14:39,059 --> 00:14:41,539
Speaker:
Well, I just thought King
Arthur's.
413
00:14:41,539 --> 00:14:41,899
Speaker:
Yeah.
414
00:14:41,899 --> 00:14:42,379
Speaker:
Yeah.
415
00:14:42,379 --> 00:14:44,940
Speaker:
I thought that's where they
probably went.
416
00:14:44,940 --> 00:14:46,220
Speaker:
They went to the Renaissance
Fair.
417
00:14:46,220 --> 00:14:48,419
Speaker:
They went to a support group.
418
00:14:48,419 --> 00:14:48,779
Speaker:
Yeah.
419
00:14:48,779 --> 00:14:49,580
Speaker:
They did.
420
00:14:49,580 --> 00:14:50,980
Speaker:
They went to a support group.
421
00:14:50,980 --> 00:14:51,620
Speaker:
Mhm.
422
00:14:52,779 --> 00:14:54,820
Speaker:
This is sometime around twenty
twelve.
423
00:14:54,820 --> 00:14:56,899
Speaker:
At this point, as far as I could
gather.
424
00:14:58,059 --> 00:15:00,340
Speaker:
Joy remembers being a little
late.
425
00:15:00,340 --> 00:15:02,820
Speaker:
So there were a lot of people
there already.
426
00:15:02,820 --> 00:15:03,620
Speaker:
Sound familiar?
427
00:15:03,620 --> 00:15:04,500
Speaker:
Yep.
428
00:15:04,500 --> 00:15:04,940
Speaker:
Right.
429
00:15:04,940 --> 00:15:06,580
Speaker:
So this is where you're out of
context.
430
00:15:06,580 --> 00:15:07,259
Speaker:
Quote.
431
00:15:07,259 --> 00:15:09,299
Speaker:
She walks into the room.
432
00:15:09,299 --> 00:15:11,460
Speaker:
The support group for
Parkinson's disease.
433
00:15:11,460 --> 00:15:11,779
Speaker:
Right?
434
00:15:11,779 --> 00:15:15,259
Speaker:
And she thinks smell.
435
00:15:15,259 --> 00:15:18,399
Speaker:
So she was smelling that smell
436
00:15:18,399 --> 00:15:20,149
Speaker:
in that room with all the
437
00:15:20,149 --> 00:15:20,750
Speaker:
people?
438
00:15:20,750 --> 00:15:21,750
Speaker:
Yep.
439
00:15:21,750 --> 00:15:27,549
Speaker:
So the smell that she's been
smelling for thirty five, forty
440
00:15:27,549 --> 00:15:29,149
Speaker:
years at this point, right?
441
00:15:29,149 --> 00:15:31,110
Speaker:
She's a bloodhound.
442
00:15:31,110 --> 00:15:32,429
Speaker:
The Parkinson's bloodhound.
443
00:15:32,429 --> 00:15:37,629
Speaker:
She's Parkinson's bloodhound,
so.
444
00:15:37,629 --> 00:15:39,830
Speaker:
Oh, my God, she.
445
00:15:39,830 --> 00:15:40,389
Speaker:
Yeah.
446
00:15:40,389 --> 00:15:42,629
Speaker:
So she walks into the room.
447
00:15:42,629 --> 00:15:44,509
Speaker:
She smells strongly
448
00:15:44,509 --> 00:15:47,429
Speaker:
overpoweringly the smell that
449
00:15:47,429 --> 00:15:48,509
Speaker:
she's been smelling on her
450
00:15:48,509 --> 00:15:49,029
Speaker:
husband.
451
00:15:49,029 --> 00:15:49,909
Speaker:
Right.
452
00:15:49,909 --> 00:15:52,429
Speaker:
Since they were in their early
thirties.
453
00:15:52,429 --> 00:15:54,029
Speaker:
Yeah.
454
00:15:54,029 --> 00:15:59,990
Speaker:
And she looks at her husband,
tells him they immediately being
455
00:15:59,990 --> 00:16:03,870
Speaker:
medical professionals, both of
them knew that this could be
456
00:16:03,870 --> 00:16:05,909
Speaker:
something big, big breakthrough.
457
00:16:05,909 --> 00:16:07,149
Speaker:
Yeah, yeah, yeah.
458
00:16:07,149 --> 00:16:10,389
Speaker:
She reached out to Tilo Kunath,
459
00:16:10,389 --> 00:16:12,350
Speaker:
which is what I'm going with for
460
00:16:12,350 --> 00:16:13,350
Speaker:
the pronunciation.
461
00:16:13,350 --> 00:16:14,389
Speaker:
Sure, that sounds right.
462
00:16:14,389 --> 00:16:17,789
Speaker:
A neuroscientist at the
University of Edinburgh.
463
00:16:18,909 --> 00:16:19,750
Speaker:
Is that right?
464
00:16:21,309 --> 00:16:23,070
Speaker:
Tell me again.
465
00:16:23,070 --> 00:16:24,429
Speaker:
Well, wow.
466
00:16:24,429 --> 00:16:26,509
Speaker:
Debbie knows how to pronounce
something.
467
00:16:26,509 --> 00:16:31,429
Speaker:
This is the problem with it is
that for us, this word doesn't
468
00:16:31,429 --> 00:16:34,350
Speaker:
really get pronounced like this.
469
00:16:34,350 --> 00:16:38,590
Speaker:
But we say like burrow, okay.
470
00:16:38,590 --> 00:16:44,470
Speaker:
But in Scotland I believe they
don't make it two syllables.
471
00:16:44,470 --> 00:16:46,190
Speaker:
It's Edinburgh.
472
00:16:46,190 --> 00:16:47,129
Speaker:
Edinburgh?
473
00:16:47,129 --> 00:16:48,009
Speaker:
Yes.
474
00:16:48,009 --> 00:16:49,049
Speaker:
Perfect.
475
00:16:49,049 --> 00:16:51,570
Speaker:
So he's at the University of
Edinburgh.
476
00:16:51,570 --> 00:16:53,009
Speaker:
Mhm.
477
00:16:53,009 --> 00:16:57,490
Speaker:
Um, she meets him at a charity
event for Parkinson's disease.
478
00:16:57,490 --> 00:16:58,690
Speaker:
Okay.
479
00:16:58,690 --> 00:17:03,210
Speaker:
And tells him, you know, what
happened, how she believes that
480
00:17:03,210 --> 00:17:07,049
Speaker:
she smelled this smell off of
people with Parkinson's.
481
00:17:07,049 --> 00:17:07,289
Speaker:
Right?
482
00:17:07,289 --> 00:17:08,009
Speaker:
Right, right.
483
00:17:08,009 --> 00:17:11,250
Speaker:
He writes them off at first.
484
00:17:11,250 --> 00:17:12,609
Speaker:
Of course he says.
485
00:17:12,609 --> 00:17:13,890
Speaker:
I just dismissed it.
486
00:17:13,890 --> 00:17:16,890
Speaker:
I have to say, it just didn't
seem possible.
487
00:17:16,890 --> 00:17:19,410
Speaker:
You wouldn't think
neurodegenerative conditions
488
00:17:19,410 --> 00:17:20,450
Speaker:
would have an odor.
489
00:17:20,450 --> 00:17:21,730
Speaker:
I mean, he's not wrong, right?
490
00:17:21,730 --> 00:17:23,650
Speaker:
That is really weird thing.
491
00:17:23,650 --> 00:17:24,049
Speaker:
Yeah.
492
00:17:24,049 --> 00:17:25,490
Speaker:
Just some random person at a
493
00:17:25,490 --> 00:17:26,589
Speaker:
charity event to come to you
494
00:17:26,589 --> 00:17:28,410
Speaker:
with, right?
495
00:17:28,410 --> 00:17:34,450
Speaker:
It's just such an odd like sense
to for it.
496
00:17:34,450 --> 00:17:35,329
Speaker:
You know what I mean?
497
00:17:35,329 --> 00:17:41,329
Speaker:
Like you don't normally compare
like diseases with I could smell
498
00:17:41,329 --> 00:17:43,930
Speaker:
the disease on you, you know
what I mean?
499
00:17:43,930 --> 00:17:45,900
Speaker:
But later that year, he heard
500
00:17:45,900 --> 00:17:48,460
Speaker:
about another study that was
501
00:17:48,460 --> 00:17:50,319
Speaker:
about dogs being able to smell
502
00:17:50,319 --> 00:17:51,779
Speaker:
cancer.
503
00:17:51,779 --> 00:17:55,019
Speaker:
And he thought, maybe she has
some merit.
504
00:17:56,500 --> 00:18:03,259
Speaker:
So he got back in contact with
Joy and les, and he decided that
505
00:18:03,259 --> 00:18:08,180
Speaker:
there was only one way to
confirm her claims.
506
00:18:08,180 --> 00:18:09,220
Speaker:
Right.
507
00:18:09,220 --> 00:18:13,660
Speaker:
So it was straight out of a type
508
00:18:13,660 --> 00:18:15,500
Speaker:
of middle school competition in
509
00:18:15,500 --> 00:18:16,980
Speaker:
my mind.
510
00:18:16,980 --> 00:18:19,500
Speaker:
Your next lab lives.
511
00:18:19,500 --> 00:18:20,420
Speaker:
What do you think?
512
00:18:20,420 --> 00:18:22,619
Speaker:
A middle school competition.
513
00:18:22,619 --> 00:18:24,180
Speaker:
You said chess.
514
00:18:24,180 --> 00:18:26,220
Speaker:
You think they had a chess match
about it?
515
00:18:26,220 --> 00:18:27,259
Speaker:
A chess tournament.
516
00:18:27,259 --> 00:18:29,420
Speaker:
I'm thinking that sounds.
517
00:18:29,420 --> 00:18:31,059
Speaker:
No, that's not even close.
518
00:18:31,059 --> 00:18:32,259
Speaker:
But give me a second.
519
00:18:32,259 --> 00:18:33,099
Speaker:
Let's see.
520
00:18:33,099 --> 00:18:34,660
Speaker:
It's not a spelling bee.
521
00:18:34,660 --> 00:18:36,579
Speaker:
No, it's a spelling bee.
522
00:18:36,579 --> 00:18:37,740
Speaker:
A spelling bee?
523
00:18:37,740 --> 00:18:38,380
Speaker:
Yep.
524
00:18:38,380 --> 00:18:39,259
Speaker:
That's it.
525
00:18:39,259 --> 00:18:40,619
Speaker:
No, I don't know what.
526
00:18:40,619 --> 00:18:41,819
Speaker:
Like a science fair?
527
00:18:41,819 --> 00:18:42,299
Speaker:
Oh, yeah.
528
00:18:42,299 --> 00:18:42,960
Speaker:
Okay.
529
00:18:42,960 --> 00:18:44,559
Speaker:
It's straight out of a science
fair.
530
00:18:44,559 --> 00:18:46,079
Speaker:
Okay.
531
00:18:46,079 --> 00:18:47,759
Speaker:
They provided my experience.
532
00:18:47,759 --> 00:18:49,160
Speaker:
Yeah, I feel like I can.
533
00:18:49,160 --> 00:18:51,240
Speaker:
I can almost see the trifold
534
00:18:51,240 --> 00:18:53,140
Speaker:
board full of pictures and data
535
00:18:53,140 --> 00:18:54,119
Speaker:
tables.
536
00:18:54,119 --> 00:18:54,599
Speaker:
Okay.
537
00:18:54,599 --> 00:18:56,160
Speaker:
Hypothesis.
538
00:18:56,160 --> 00:18:59,480
Speaker:
So they provided joy with twelve
539
00:18:59,480 --> 00:19:02,000
Speaker:
shirts, six worn by people
540
00:19:02,000 --> 00:19:03,700
Speaker:
diagnosed with Parkinson's, six
541
00:19:03,700 --> 00:19:04,759
Speaker:
worn by people without
542
00:19:04,759 --> 00:19:05,880
Speaker:
Parkinson's.
543
00:19:05,880 --> 00:19:08,960
Speaker:
I put them each in a Ziploc bag
and everything.
544
00:19:08,960 --> 00:19:09,880
Speaker:
I gotta be honest.
545
00:19:09,880 --> 00:19:11,799
Speaker:
I thought she was gonna smell
people.
546
00:19:14,039 --> 00:19:15,720
Speaker:
She has a line of people walk
up.
547
00:19:15,720 --> 00:19:17,000
Speaker:
That's what I thought.
548
00:19:17,000 --> 00:19:18,799
Speaker:
I mean, they have to control
variables, right?
549
00:19:18,799 --> 00:19:23,440
Speaker:
They have to make sure she's
only smelling this one person.
550
00:19:23,440 --> 00:19:23,680
Speaker:
Right?
551
00:19:23,680 --> 00:19:24,519
Speaker:
So they.
552
00:19:24,519 --> 00:19:25,680
Speaker:
I think they even went through
553
00:19:25,680 --> 00:19:27,559
Speaker:
some process of like freezing it
554
00:19:27,559 --> 00:19:29,079
Speaker:
right after so that they could
555
00:19:29,079 --> 00:19:30,539
Speaker:
make sure the smell was like,
556
00:19:30,539 --> 00:19:32,759
Speaker:
oh, interesting fresh stuff and
557
00:19:32,759 --> 00:19:33,200
Speaker:
stuff.
558
00:19:33,200 --> 00:19:37,640
Speaker:
So they go through all of the
process and, but it basically
559
00:19:37,640 --> 00:19:42,170
Speaker:
boils down to she gets twelve
shirts, six from people with.
560
00:19:42,170 --> 00:19:42,890
Speaker:
With six.
561
00:19:42,890 --> 00:19:43,490
Speaker:
Without.
562
00:19:43,490 --> 00:19:43,890
Speaker:
Okay.
563
00:19:43,890 --> 00:19:47,609
Speaker:
She has one hundred percent
accuracy.
564
00:19:47,609 --> 00:19:48,250
Speaker:
Oh my God.
565
00:19:48,250 --> 00:19:52,730
Speaker:
Minus one person that she said
has Parkinson's disease.
566
00:19:52,730 --> 00:19:55,609
Speaker:
But actually he didn't have
Parkinson's disease.
567
00:19:55,609 --> 00:19:58,769
Speaker:
But less than a year later, he
568
00:19:58,769 --> 00:19:59,930
Speaker:
was he was diagnosed with
569
00:19:59,930 --> 00:20:00,769
Speaker:
Parkinson's disease.
570
00:20:00,769 --> 00:20:03,890
Speaker:
I was gonna say, yeah, but maybe
they don't know that yet.
571
00:20:03,890 --> 00:20:04,529
Speaker:
Yep.
572
00:20:04,529 --> 00:20:06,650
Speaker:
Oh my God.
573
00:20:06,650 --> 00:20:10,130
Speaker:
So once you account for the one
that she got, quote unquote
574
00:20:10,130 --> 00:20:12,289
Speaker:
wrong, that was actually right.
575
00:20:12,289 --> 00:20:14,650
Speaker:
She has she had one hundred
percent accuracy.
576
00:20:14,650 --> 00:20:15,009
Speaker:
Wow.
577
00:20:15,009 --> 00:20:16,410
Speaker:
Of being able to identify them.
578
00:20:16,410 --> 00:20:17,609
Speaker:
Now, granted, that's a very
579
00:20:17,609 --> 00:20:21,369
Speaker:
small sample size, but it's very
580
00:20:21,369 --> 00:20:23,289
Speaker:
unlikely that she would get all
581
00:20:23,289 --> 00:20:24,089
Speaker:
twelve correct.
582
00:20:24,089 --> 00:20:25,130
Speaker:
By random chance.
583
00:20:25,130 --> 00:20:25,529
Speaker:
Right.
584
00:20:25,529 --> 00:20:26,250
Speaker:
Right.
585
00:20:27,490 --> 00:20:30,529
Speaker:
So Kunnath and his team
586
00:20:30,529 --> 00:20:31,970
Speaker:
published the paper on this
587
00:20:31,970 --> 00:20:34,450
Speaker:
experiment in ACS Central
588
00:20:34,450 --> 00:20:36,329
Speaker:
Science in twenty nineteen, and
589
00:20:36,329 --> 00:20:37,680
Speaker:
they listed Joy Milne as a
590
00:20:37,680 --> 00:20:38,509
Speaker:
co-author.
591
00:20:38,509 --> 00:20:39,069
Speaker:
Wow.
592
00:20:39,069 --> 00:20:39,470
Speaker:
Yeah.
593
00:20:39,470 --> 00:20:40,990
Speaker:
Nice.
594
00:20:40,990 --> 00:20:43,910
Speaker:
So isn't that crazy?
595
00:20:43,910 --> 00:20:46,089
Speaker:
First of all, that she can smell
596
00:20:46,089 --> 00:20:48,670
Speaker:
Parkinsons just fucking
597
00:20:48,670 --> 00:20:49,430
Speaker:
randomly.
598
00:20:49,430 --> 00:20:54,710
Speaker:
And she she smelled it for so
long because that's why I wanted
599
00:20:54,710 --> 00:20:55,509
Speaker:
to go through the timeline.
600
00:20:55,509 --> 00:20:58,029
Speaker:
Because she started smelling it
when they were thirty one.
601
00:20:58,029 --> 00:21:00,869
Speaker:
He was diagnosed when he was
forty five.
602
00:21:00,869 --> 00:21:04,910
Speaker:
They didn't go to that support
group until twenty years later.
603
00:21:04,910 --> 00:21:06,230
Speaker:
So she's been smelling this
604
00:21:06,230 --> 00:21:09,410
Speaker:
smell for thirty five years at
605
00:21:09,410 --> 00:21:11,509
Speaker:
least way before he was
606
00:21:11,509 --> 00:21:12,349
Speaker:
diagnosed.
607
00:21:12,349 --> 00:21:12,869
Speaker:
Wow.
608
00:21:12,869 --> 00:21:16,230
Speaker:
Can you imagine being her and
being finally validated?
609
00:21:16,230 --> 00:21:16,710
Speaker:
Right?
610
00:21:16,710 --> 00:21:18,809
Speaker:
And also figuring out that like,
611
00:21:18,809 --> 00:21:21,450
Speaker:
you knew on some level that,
612
00:21:21,450 --> 00:21:21,910
Speaker:
right?
613
00:21:21,910 --> 00:21:24,109
Speaker:
He had this before anyone could
614
00:21:24,109 --> 00:21:25,589
Speaker:
reasonably know that he had
615
00:21:25,589 --> 00:21:26,670
Speaker:
this, right.
616
00:21:26,670 --> 00:21:27,309
Speaker:
Wild.
617
00:21:27,309 --> 00:21:27,869
Speaker:
Yeah.
618
00:21:27,869 --> 00:21:28,829
Speaker:
Very wild.
619
00:21:28,829 --> 00:21:29,910
Speaker:
Mhm.
620
00:21:29,910 --> 00:21:32,670
Speaker:
So based on this original study,
621
00:21:32,670 --> 00:21:34,119
Speaker:
many of the compounds
622
00:21:34,119 --> 00:21:36,250
Speaker:
responsible for the smell have
623
00:21:36,250 --> 00:21:38,769
Speaker:
been found to be increased in
624
00:21:38,769 --> 00:21:40,789
Speaker:
this oily substance on the skin
625
00:21:40,789 --> 00:21:41,849
Speaker:
of people with Parkinson's
626
00:21:41,849 --> 00:21:42,210
Speaker:
disease.
627
00:21:42,210 --> 00:21:43,130
Speaker:
Oh, really?
628
00:21:43,130 --> 00:21:43,569
Speaker:
Okay.
629
00:21:43,569 --> 00:21:43,809
Speaker:
Yeah.
630
00:21:43,809 --> 00:21:45,170
Speaker:
It's called sebum.
631
00:21:47,130 --> 00:21:48,049
Speaker:
Yeah.
632
00:21:48,049 --> 00:21:48,650
Speaker:
Gross.
633
00:21:48,650 --> 00:21:49,490
Speaker:
Sounds gross.
634
00:21:49,490 --> 00:21:50,289
Speaker:
It is gross.
635
00:21:50,289 --> 00:21:53,809
Speaker:
It's like the oily stuff on your
skin.
636
00:21:53,809 --> 00:21:56,849
Speaker:
And it collects in certain
places that are like.
637
00:21:56,849 --> 00:22:00,210
Speaker:
Not to say that anyone isn't
washing their body, but there
638
00:22:00,210 --> 00:22:02,450
Speaker:
are just certain places that are
harder to reach.
639
00:22:02,450 --> 00:22:04,750
Speaker:
So you end up scrubbing them
640
00:22:04,750 --> 00:22:07,490
Speaker:
less and washing them generally
641
00:22:07,490 --> 00:22:07,890
Speaker:
less.
642
00:22:07,890 --> 00:22:11,690
Speaker:
Like on the back, on the upper
back area somewhere.
643
00:22:11,690 --> 00:22:14,170
Speaker:
Yeah, like back of your neck and
stuff.
644
00:22:14,170 --> 00:22:18,450
Speaker:
I thought it was gonna be like
she was smelling whatever those
645
00:22:18,450 --> 00:22:22,930
Speaker:
things in the brain like, but
like, that'd be crazy.
646
00:22:22,930 --> 00:22:24,569
Speaker:
Plaque or Lewy bodies?
647
00:22:24,569 --> 00:22:25,250
Speaker:
Yeah.
648
00:22:25,250 --> 00:22:27,130
Speaker:
They're like, that's what I was
thinking.
649
00:22:27,130 --> 00:22:29,329
Speaker:
I was like, is she smelling like
that?
650
00:22:29,329 --> 00:22:30,569
Speaker:
That change.
651
00:22:30,569 --> 00:22:31,250
Speaker:
But.
652
00:22:31,250 --> 00:22:32,740
Speaker:
Well, I don't know.
653
00:22:32,740 --> 00:22:33,819
Speaker:
It could be.
654
00:22:33,819 --> 00:22:35,660
Speaker:
There could be some connection.
655
00:22:35,660 --> 00:22:37,720
Speaker:
We're still doing research to
656
00:22:37,720 --> 00:22:39,059
Speaker:
figure out what the connection
657
00:22:39,059 --> 00:22:39,259
Speaker:
is.
658
00:22:39,259 --> 00:22:40,859
Speaker:
It seems to be that there are.
659
00:22:40,859 --> 00:22:45,259
Speaker:
A bunch of differences in lipid
metabolism.
660
00:22:45,259 --> 00:22:46,019
Speaker:
Okay.
661
00:22:46,019 --> 00:22:48,059
Speaker:
For people that have Parkinson's
disease.
662
00:22:48,059 --> 00:22:52,859
Speaker:
So the way that they metabolize
fats and lipids is different.
663
00:22:52,859 --> 00:22:54,500
Speaker:
And that's causing different
664
00:22:54,500 --> 00:22:57,000
Speaker:
stuff to be in their oily
665
00:22:57,000 --> 00:22:58,420
Speaker:
secretions.
666
00:22:58,420 --> 00:22:59,579
Speaker:
Oh yeah.
667
00:22:59,579 --> 00:23:01,740
Speaker:
This is this is fun.
668
00:23:02,859 --> 00:23:06,480
Speaker:
Anyways, and she can smell it,
which is even worse.
669
00:23:06,480 --> 00:23:07,519
Speaker:
That's really weird.
670
00:23:07,519 --> 00:23:08,200
Speaker:
Yeah.
671
00:23:08,200 --> 00:23:09,920
Speaker:
And why does it smell cheesy?
672
00:23:09,920 --> 00:23:10,759
Speaker:
It smells bad.
673
00:23:10,759 --> 00:23:12,200
Speaker:
It's like yeast.
674
00:23:12,200 --> 00:23:13,640
Speaker:
Oh, musty.
675
00:23:13,640 --> 00:23:15,759
Speaker:
I thought, I thought unpleasant.
676
00:23:15,759 --> 00:23:18,200
Speaker:
That's how she would try to
describe it.
677
00:23:18,200 --> 00:23:19,759
Speaker:
Yeah, yeah.
678
00:23:22,579 --> 00:23:24,220
Speaker:
So there's many different
679
00:23:24,220 --> 00:23:26,099
Speaker:
research groups studying this
680
00:23:26,099 --> 00:23:27,759
Speaker:
topic now, and they're each
681
00:23:27,759 --> 00:23:29,059
Speaker:
finding different types of
682
00:23:29,059 --> 00:23:30,660
Speaker:
compounds that are unique in
683
00:23:30,660 --> 00:23:32,559
Speaker:
Parkinson's Patients in their
684
00:23:32,559 --> 00:23:33,619
Speaker:
sebum.
685
00:23:33,619 --> 00:23:34,500
Speaker:
Mhm.
686
00:23:34,500 --> 00:23:40,619
Speaker:
One of Cunard's original team
members, Perdita Barran, is a
687
00:23:40,619 --> 00:23:44,339
Speaker:
certain type of scientist, which
is your next lab libs.
688
00:23:44,339 --> 00:23:45,259
Speaker:
Come on.
689
00:23:45,259 --> 00:23:47,619
Speaker:
You did me so dirty this time.
690
00:23:47,619 --> 00:23:48,460
Speaker:
I did.
691
00:23:48,460 --> 00:23:49,059
Speaker:
Yeah.
692
00:23:49,059 --> 00:23:50,660
Speaker:
I'm not getting anything right.
693
00:23:50,660 --> 00:23:52,299
Speaker:
You got smell right?
694
00:23:52,299 --> 00:23:55,099
Speaker:
I did, oh, and I got you got
roundup.
695
00:23:55,099 --> 00:23:56,700
Speaker:
Weed killer kind of right?
696
00:23:56,700 --> 00:23:57,380
Speaker:
Kind of.
697
00:23:58,460 --> 00:23:59,140
Speaker:
Okay.
698
00:23:59,140 --> 00:24:02,059
Speaker:
The type of scientist is the
category you gave me.
699
00:24:02,059 --> 00:24:03,940
Speaker:
And I said an entomologist.
700
00:24:03,940 --> 00:24:04,829
Speaker:
Probably not that.
701
00:24:04,829 --> 00:24:06,269
Speaker:
Not gonna be that.
702
00:24:06,269 --> 00:24:08,829
Speaker:
Okay, so, so far we've got a
neuroscientist.
703
00:24:08,829 --> 00:24:10,230
Speaker:
Well, they're kind of
scientists.
704
00:24:10,230 --> 00:24:11,150
Speaker:
Do you think now that, you know,
705
00:24:11,150 --> 00:24:15,630
Speaker:
we're talking about this oily
706
00:24:15,630 --> 00:24:16,069
Speaker:
stuff?
707
00:24:16,069 --> 00:24:18,430
Speaker:
I think, I guess dermatologists
708
00:24:18,430 --> 00:24:20,309
Speaker:
could be, but that's a good
709
00:24:20,309 --> 00:24:20,670
Speaker:
guess.
710
00:24:20,670 --> 00:24:22,170
Speaker:
I don't know what.
711
00:24:22,170 --> 00:24:24,009
Speaker:
Who would specialize in that?
712
00:24:24,009 --> 00:24:25,049
Speaker:
A chemist.
713
00:24:25,049 --> 00:24:25,529
Speaker:
Oh, okay.
714
00:24:25,529 --> 00:24:26,250
Speaker:
Just a chemist.
715
00:24:26,250 --> 00:24:26,609
Speaker:
Yeah.
716
00:24:26,609 --> 00:24:26,849
Speaker:
Okay.
717
00:24:26,849 --> 00:24:27,930
Speaker:
Okay.
718
00:24:27,930 --> 00:24:30,769
Speaker:
So she's a chemist at the
University of Manchester.
719
00:24:30,769 --> 00:24:31,410
Speaker:
She's gonna.
720
00:24:31,410 --> 00:24:34,410
Speaker:
Does Manchester have a weird
secret pronunciation?
721
00:24:34,410 --> 00:24:35,250
Speaker:
No, you nailed it.
722
00:24:35,250 --> 00:24:36,730
Speaker:
Okay.
723
00:24:36,730 --> 00:24:37,450
Speaker:
Okay.
724
00:24:39,250 --> 00:24:41,369
Speaker:
she's been working on a skin
725
00:24:41,369 --> 00:24:44,089
Speaker:
swab test to detect the scent by
726
00:24:44,089 --> 00:24:45,569
Speaker:
mass spectrometry.
727
00:24:45,569 --> 00:24:48,170
Speaker:
By mass spectrometry?
728
00:24:48,170 --> 00:24:49,609
Speaker:
Aha.
729
00:24:49,609 --> 00:24:50,130
Speaker:
Right.
730
00:24:50,130 --> 00:24:52,690
Speaker:
Spectrum spectrometry.
731
00:24:52,690 --> 00:24:53,450
Speaker:
Is that right?
732
00:24:53,450 --> 00:24:54,569
Speaker:
That sounds wrong.
733
00:24:54,569 --> 00:24:56,490
Speaker:
No, I think it's got too many
R's.
734
00:24:56,490 --> 00:24:56,769
Speaker:
Yeah.
735
00:24:56,769 --> 00:24:57,589
Speaker:
No, I think it's right.
736
00:24:57,589 --> 00:24:57,829
Speaker:
Yeah.
737
00:24:57,829 --> 00:24:58,230
Speaker:
That's right.
738
00:24:58,230 --> 00:24:58,670
Speaker:
Okay.
739
00:24:58,670 --> 00:24:58,950
Speaker:
Yeah.
740
00:24:58,950 --> 00:25:00,269
Speaker:
They put it in like a chamber
741
00:25:00,269 --> 00:25:01,990
Speaker:
type thing and it smells
742
00:25:01,990 --> 00:25:03,029
Speaker:
basically.
743
00:25:03,029 --> 00:25:04,789
Speaker:
Not really.
744
00:25:04,789 --> 00:25:10,349
Speaker:
You put any kind of chemical
compound that is an unknown
745
00:25:10,349 --> 00:25:12,470
Speaker:
thing in there.
746
00:25:12,470 --> 00:25:18,190
Speaker:
And it uses a bunch of sensors
to measure all the different.
747
00:25:18,190 --> 00:25:20,029
Speaker:
Wavelengths.
748
00:25:20,029 --> 00:25:24,950
Speaker:
Oh. When you put the light
through each type of man.
749
00:25:24,950 --> 00:25:29,109
Speaker:
I'm reaching deep into my mind
for like my college chemistry
750
00:25:29,109 --> 00:25:34,670
Speaker:
classes, it like uses a
wavelength of light that that
751
00:25:34,670 --> 00:25:39,549
Speaker:
puts through the chemical that
that is unknown, right?
752
00:25:39,549 --> 00:25:45,789
Speaker:
And then based on how the light
bounces back and what they know
753
00:25:45,789 --> 00:25:49,589
Speaker:
about light and known chemicals,
they can say, what is this
754
00:25:49,589 --> 00:25:51,029
Speaker:
chemical made of?
755
00:25:51,029 --> 00:25:51,519
Speaker:
Okay.
756
00:25:51,519 --> 00:25:52,960
Speaker:
like what individual like can
757
00:25:52,960 --> 00:25:54,359
Speaker:
give you like sort of recipe,
758
00:25:54,359 --> 00:25:56,680
Speaker:
but it comes out like a colorful
759
00:25:56,680 --> 00:25:59,539
Speaker:
lines graph to represent like,
760
00:25:59,539 --> 00:26:00,720
Speaker:
right.
761
00:26:00,720 --> 00:26:02,000
Speaker:
What each of the chemical
762
00:26:02,000 --> 00:26:03,460
Speaker:
compounds are in this unknown
763
00:26:03,460 --> 00:26:04,039
Speaker:
thing.
764
00:26:04,039 --> 00:26:04,559
Speaker:
Yeah.
765
00:26:04,559 --> 00:26:10,079
Speaker:
They use it to also determine
what chemicals are in planets.
766
00:26:10,079 --> 00:26:13,599
Speaker:
When they're looking at a planet
in the telescope, they can use
767
00:26:13,599 --> 00:26:18,319
Speaker:
spectrometry to tell what is in
the atmosphere of the planets.
768
00:26:18,319 --> 00:26:19,359
Speaker:
Are you serious?
769
00:26:19,359 --> 00:26:20,039
Speaker:
Yeah.
770
00:26:20,039 --> 00:26:20,440
Speaker:
Wow.
771
00:26:20,440 --> 00:26:23,000
Speaker:
So, yes, they're using mass
spectrometry.
772
00:26:23,000 --> 00:26:23,759
Speaker:
Okay.
773
00:26:23,759 --> 00:26:28,700
Speaker:
To determine what is exactly in
this oily stuff so that they can
774
00:26:28,700 --> 00:26:33,599
Speaker:
swab your skin and say, yes, you
have these things in your oil or
775
00:26:33,599 --> 00:26:34,339
Speaker:
no, you don't.
776
00:26:34,339 --> 00:26:38,339
Speaker:
I feel like it's not going to be
that easy, but well, nothing is
777
00:26:38,339 --> 00:26:38,980
Speaker:
ever that easy.
778
00:26:38,980 --> 00:26:42,619
Speaker:
No. Basically, they did a study
779
00:26:42,619 --> 00:26:44,680
Speaker:
to see if her skin swab test
780
00:26:44,680 --> 00:26:46,180
Speaker:
works.
781
00:26:46,180 --> 00:26:47,539
Speaker:
They had a slightly larger
782
00:26:47,539 --> 00:26:49,220
Speaker:
sample size than Joy Milne's
783
00:26:49,220 --> 00:26:52,059
Speaker:
twelve t shirts, but not that
784
00:26:52,059 --> 00:26:52,460
Speaker:
large.
785
00:26:52,460 --> 00:26:57,740
Speaker:
Still, she compared seventy nine
people with PD.
786
00:26:57,740 --> 00:27:01,740
Speaker:
That's Parkinson's disease and
seventy one people without it.
787
00:27:01,740 --> 00:27:02,380
Speaker:
Okay.
788
00:27:02,380 --> 00:27:05,539
Speaker:
To find a set of large lipids
789
00:27:05,539 --> 00:27:08,220
Speaker:
that are present only in the PD
790
00:27:08,220 --> 00:27:09,740
Speaker:
patients.
791
00:27:09,740 --> 00:27:12,160
Speaker:
And then they can transfer the
792
00:27:12,160 --> 00:27:16,079
Speaker:
sebum from a blotting paper into
793
00:27:16,079 --> 00:27:19,619
Speaker:
the machine analyzer in just a
794
00:27:19,619 --> 00:27:20,420
Speaker:
few minutes.
795
00:27:20,420 --> 00:27:22,220
Speaker:
So Theoretically, if it's
796
00:27:22,220 --> 00:27:24,200
Speaker:
accurate, this test could be
797
00:27:24,200 --> 00:27:25,440
Speaker:
super helpful for quick
798
00:27:25,440 --> 00:27:26,440
Speaker:
diagnosis.
799
00:27:26,440 --> 00:27:28,240
Speaker:
Right now, the other diagnosis
800
00:27:28,240 --> 00:27:29,759
Speaker:
test is a blood test, which
801
00:27:29,759 --> 00:27:31,240
Speaker:
takes a lot longer to process
802
00:27:31,240 --> 00:27:32,279
Speaker:
the results.
803
00:27:32,279 --> 00:27:33,940
Speaker:
And it involves a lot more
804
00:27:33,940 --> 00:27:36,460
Speaker:
people to like, interpret all
805
00:27:36,460 --> 00:27:37,019
Speaker:
those results.
806
00:27:37,019 --> 00:27:37,500
Speaker:
Right?
807
00:27:37,500 --> 00:27:37,900
Speaker:
Right.
808
00:27:37,900 --> 00:27:41,460
Speaker:
So her research is unpublished
so far.
809
00:27:41,460 --> 00:27:46,019
Speaker:
She's still going about this
test to see how accurate it is.
810
00:27:46,019 --> 00:27:46,500
Speaker:
Mhm.
811
00:27:46,500 --> 00:27:50,259
Speaker:
but she claims as so far that
812
00:27:50,259 --> 00:27:51,759
Speaker:
it's reaching up to ninety
813
00:27:51,759 --> 00:27:53,119
Speaker:
percent accuracy.
814
00:27:53,119 --> 00:27:53,720
Speaker:
Wow.
815
00:27:53,720 --> 00:27:56,119
Speaker:
Now, we don't know if it's
giving false positives or false
816
00:27:56,119 --> 00:27:59,500
Speaker:
negatives because she hasn't,
published the information yet,
817
00:27:59,500 --> 00:28:01,420
Speaker:
but that is pretty promising.
818
00:28:01,420 --> 00:28:05,779
Speaker:
And she's working with clinical
settings and hospitals to figure
819
00:28:05,779 --> 00:28:09,500
Speaker:
out what would be the most
efficient ways to go about doing
820
00:28:09,500 --> 00:28:11,420
Speaker:
this test as she perfects it.
821
00:28:11,420 --> 00:28:12,259
Speaker:
Right?
822
00:28:12,259 --> 00:28:14,140
Speaker:
Yeah, that's what I was going to
say.
823
00:28:14,140 --> 00:28:22,220
Speaker:
Like, are they like swabbing a
particular spot or seems to be
824
00:28:22,220 --> 00:28:25,299
Speaker:
that they're swabbing that like
back of the neck where, where
825
00:28:25,299 --> 00:28:28,220
Speaker:
the collar of your shirt would
they think like the most common
826
00:28:28,220 --> 00:28:32,710
Speaker:
spot that it would be traceable
on that area.
827
00:28:32,710 --> 00:28:33,309
Speaker:
Okay.
828
00:28:33,309 --> 00:28:37,410
Speaker:
a simple test for early
diagnosis is truly the key to
829
00:28:37,410 --> 00:28:39,190
Speaker:
more effective treatments.
830
00:28:39,190 --> 00:28:43,109
Speaker:
Many people have symptoms that
they don't notice or they don't
831
00:28:43,109 --> 00:28:47,750
Speaker:
process as being red flags
because some of those symptoms
832
00:28:47,750 --> 00:28:51,509
Speaker:
you wouldn't really think to pay
attention to necessarily like,
833
00:28:51,509 --> 00:28:55,730
Speaker:
am I blinking enough or, or my
arm's moving when I walk right?
834
00:28:55,730 --> 00:28:57,490
Speaker:
My blinking as much as I used
to.
835
00:28:57,490 --> 00:28:58,970
Speaker:
Is this a tremor?
836
00:28:58,970 --> 00:29:01,130
Speaker:
My just nerves.
837
00:29:01,130 --> 00:29:03,849
Speaker:
And yeah, you know, oh, I had
too much coffee.
838
00:29:03,849 --> 00:29:04,410
Speaker:
Right?
839
00:29:04,410 --> 00:29:04,970
Speaker:
Exactly.
840
00:29:04,970 --> 00:29:05,930
Speaker:
Because it doesn't it's not
841
00:29:05,930 --> 00:29:07,529
Speaker:
always consistent, your symptoms
842
00:29:07,529 --> 00:29:08,369
Speaker:
either.
843
00:29:08,369 --> 00:29:08,970
Speaker:
Yeah.
844
00:29:08,970 --> 00:29:12,849
Speaker:
And it could be some stuff
that's under seems completely
845
00:29:12,849 --> 00:29:14,490
Speaker:
unrelated from each other.
846
00:29:15,529 --> 00:29:20,049
Speaker:
Like your mood and your
irritability can have something
847
00:29:20,049 --> 00:29:22,210
Speaker:
to do with your blinking, right?
848
00:29:22,210 --> 00:29:23,829
Speaker:
You know, or other types of
849
00:29:23,829 --> 00:29:24,829
Speaker:
movement, things like you might
850
00:29:24,829 --> 00:29:26,069
Speaker:
not put that together for a long
851
00:29:26,069 --> 00:29:26,630
Speaker:
time.
852
00:29:26,630 --> 00:29:30,190
Speaker:
if you keep brushing it off as
this little thing happen or that
853
00:29:30,190 --> 00:29:34,710
Speaker:
little thing happen, then that
does delay the diagnosis Right.
854
00:29:34,710 --> 00:29:37,750
Speaker:
It's not like a one step
solution to the problem.
855
00:29:37,750 --> 00:29:38,309
Speaker:
Yeah.
856
00:29:38,309 --> 00:29:43,190
Speaker:
No, it would be easier to screen
people of a certain age or that
857
00:29:43,190 --> 00:29:45,269
Speaker:
have certain genetic factors.
858
00:29:45,269 --> 00:29:45,710
Speaker:
Oh yeah.
859
00:29:45,710 --> 00:29:46,230
Speaker:
That's true.
860
00:29:46,230 --> 00:29:47,470
Speaker:
It would be easier to screen
861
00:29:47,470 --> 00:29:50,910
Speaker:
them early without having to do
862
00:29:50,910 --> 00:29:52,869
Speaker:
all these weird testing or
863
00:29:52,869 --> 00:29:55,210
Speaker:
tracking to see maybe if this is
864
00:29:55,210 --> 00:29:56,430
Speaker:
a symptom or that's maybe a
865
00:29:56,430 --> 00:29:57,029
Speaker:
symptom.
866
00:29:57,029 --> 00:29:57,549
Speaker:
Yeah.
867
00:29:57,549 --> 00:29:58,769
Speaker:
that's true.
868
00:29:58,769 --> 00:30:00,730
Speaker:
Maybe it would be even routine
869
00:30:00,730 --> 00:30:02,140
Speaker:
that everybody gets screened for
870
00:30:02,140 --> 00:30:02,779
Speaker:
it.
871
00:30:02,779 --> 00:30:03,940
Speaker:
If it was so easy.
872
00:30:03,940 --> 00:30:04,259
Speaker:
Right?
873
00:30:04,259 --> 00:30:05,099
Speaker:
lots of people.
874
00:30:05,099 --> 00:30:09,539
Speaker:
It could take twenty years
before they get a diagnosis, but
875
00:30:09,539 --> 00:30:12,220
Speaker:
they can think back and think
twenty years ago.
876
00:30:12,220 --> 00:30:13,779
Speaker:
These symptoms may have started.
877
00:30:13,779 --> 00:30:15,700
Speaker:
Oh my gosh.
878
00:30:15,700 --> 00:30:18,140
Speaker:
So after les died in twenty
879
00:30:18,140 --> 00:30:20,880
Speaker:
fifteen, Joy said to Scientific
880
00:30:20,880 --> 00:30:23,220
Speaker:
American, my husband suffered
881
00:30:23,220 --> 00:30:25,019
Speaker:
from Parkinson's for twenty one
882
00:30:25,019 --> 00:30:26,819
Speaker:
years after his diagnosis, but
883
00:30:26,819 --> 00:30:28,359
Speaker:
he had it many years before
884
00:30:28,359 --> 00:30:29,019
Speaker:
that.
885
00:30:29,019 --> 00:30:30,539
Speaker:
I would like to see.
886
00:30:30,539 --> 00:30:32,180
Speaker:
It almost makes me cry.
887
00:30:32,180 --> 00:30:33,460
Speaker:
I would like to see that people
888
00:30:33,460 --> 00:30:34,519
Speaker:
don't suffer the way he
889
00:30:34,519 --> 00:30:35,220
Speaker:
suffered.
890
00:30:35,220 --> 00:30:36,940
Speaker:
Yeah.
891
00:30:36,940 --> 00:30:37,460
Speaker:
Yeah.
892
00:30:37,460 --> 00:30:41,700
Speaker:
there's actually a huge backlog
of people waiting to be tested
893
00:30:41,700 --> 00:30:43,339
Speaker:
for Parkinson's disease.
894
00:30:43,339 --> 00:30:44,940
Speaker:
Like with the blood tests?
895
00:30:44,940 --> 00:30:46,099
Speaker:
Yes.
896
00:30:46,099 --> 00:30:47,940
Speaker:
In certain places where there
897
00:30:47,940 --> 00:30:51,099
Speaker:
are only a few specialized
898
00:30:51,099 --> 00:30:54,160
Speaker:
medical institutions that can
899
00:30:54,160 --> 00:30:56,000
Speaker:
test you and give you your
900
00:30:56,000 --> 00:30:58,259
Speaker:
results and write walk you
901
00:30:58,259 --> 00:30:59,480
Speaker:
through the treatments and
902
00:30:59,480 --> 00:31:00,319
Speaker:
stuff.
903
00:31:00,319 --> 00:31:03,680
Speaker:
I suppose there's a backlog of
thousands of people.
904
00:31:03,680 --> 00:31:09,940
Speaker:
I suppose they do more of
diagnosis by symptoms like.
905
00:31:09,940 --> 00:31:14,180
Speaker:
They might start treating
somebody with something based on
906
00:31:14,180 --> 00:31:18,440
Speaker:
the symptoms and everything,
even before they were able to
907
00:31:18,440 --> 00:31:21,980
Speaker:
get a blood test, you mean
they're starting treatment in
908
00:31:21,980 --> 00:31:23,220
Speaker:
the meantime, right?
909
00:31:23,220 --> 00:31:23,380
Speaker:
Yeah.
910
00:31:23,380 --> 00:31:28,279
Speaker:
Especially because it's mostly
lifestyle changes anyways that
911
00:31:28,279 --> 00:31:30,400
Speaker:
are healthy regardless.
912
00:31:30,400 --> 00:31:30,880
Speaker:
Right.
913
00:31:30,880 --> 00:31:31,720
Speaker:
That's true.
914
00:31:31,720 --> 00:31:32,759
Speaker:
Yeah.
915
00:31:32,759 --> 00:31:33,559
Speaker:
Yeah.
916
00:31:33,559 --> 00:31:34,559
Speaker:
So if they could get through
917
00:31:34,559 --> 00:31:37,240
Speaker:
that backlog with a skin swab,
918
00:31:37,240 --> 00:31:38,480
Speaker:
that can be done in just a few
919
00:31:38,480 --> 00:31:41,420
Speaker:
minutes and analyzed by machine,
920
00:31:41,420 --> 00:31:42,920
Speaker:
then that would be a big
921
00:31:42,920 --> 00:31:43,599
Speaker:
benefit.
922
00:31:43,599 --> 00:31:45,920
Speaker:
Yeah, that's pretty incredible.
923
00:31:45,920 --> 00:31:49,619
Speaker:
So, the University of Manchester
has continued the line of
924
00:31:49,619 --> 00:31:51,900
Speaker:
research as well.
925
00:31:51,900 --> 00:31:55,259
Speaker:
And they are in collaboration
926
00:31:55,259 --> 00:31:57,460
Speaker:
with this program called Medical
927
00:31:57,460 --> 00:31:59,549
Speaker:
Detection dogs.
928
00:31:59,549 --> 00:32:00,910
Speaker:
Oh, yeah.
929
00:32:00,910 --> 00:32:03,710
Speaker:
They're trying to develop
training programs to determine
930
00:32:03,710 --> 00:32:05,430
Speaker:
if dogs can smell this odor.
931
00:32:05,430 --> 00:32:05,950
Speaker:
Okay.
932
00:32:05,950 --> 00:32:10,029
Speaker:
That Parkinson's disease has
that joy can smell.
933
00:32:10,029 --> 00:32:12,829
Speaker:
they ended up putting this is
934
00:32:12,829 --> 00:32:14,309
Speaker:
your next lab libs coming up
935
00:32:14,309 --> 00:32:15,150
Speaker:
here.
936
00:32:15,150 --> 00:32:19,309
Speaker:
They put through ten dogs into
this initial training program.
937
00:32:19,309 --> 00:32:19,789
Speaker:
Okay.
938
00:32:19,789 --> 00:32:21,390
Speaker:
How many of the pups do you
939
00:32:21,390 --> 00:32:23,289
Speaker:
think, got through the training
940
00:32:23,289 --> 00:32:25,910
Speaker:
program to be good enough to, do
941
00:32:25,910 --> 00:32:26,230
Speaker:
it?
942
00:32:26,230 --> 00:32:29,789
Speaker:
Well, I said to, I said a number
one through five.
943
00:32:29,789 --> 00:32:31,869
Speaker:
So it wasn't all of them.
944
00:32:31,869 --> 00:32:34,509
Speaker:
Yeah, I think two sounds good.
945
00:32:34,509 --> 00:32:35,869
Speaker:
Yeah, it was two.
946
00:32:37,670 --> 00:32:38,990
Speaker:
What kind of dogs?
947
00:32:38,990 --> 00:32:39,549
Speaker:
You don't know?
948
00:32:39,549 --> 00:32:42,349
Speaker:
I don't know, it didn't say it
didn't say.
949
00:32:42,349 --> 00:32:44,349
Speaker:
I just wonder if it's like
bloodhounds, right?
950
00:32:44,349 --> 00:32:47,190
Speaker:
Like if they're particularly
good sniffers.
951
00:32:47,190 --> 00:32:47,589
Speaker:
Yeah.
952
00:32:47,589 --> 00:32:48,990
Speaker:
This type of dog, maybe.
953
00:32:48,990 --> 00:32:52,410
Speaker:
Well, two dogs got through the
training program out of ten.
954
00:32:52,410 --> 00:32:53,849
Speaker:
And they're not one hundred
955
00:32:53,849 --> 00:32:55,250
Speaker:
percent accurate because they're
956
00:32:55,250 --> 00:32:56,329
Speaker:
just puppies, because they're
957
00:32:56,329 --> 00:32:57,009
Speaker:
babies.
958
00:32:59,529 --> 00:33:01,309
Speaker:
But they were well above pure
959
00:33:01,309 --> 00:33:03,289
Speaker:
chance on accuracy somewhere
960
00:33:03,289 --> 00:33:05,769
Speaker:
between seventy to ninety
961
00:33:05,769 --> 00:33:06,170
Speaker:
percent.
962
00:33:06,170 --> 00:33:07,289
Speaker:
Correct.
963
00:33:07,289 --> 00:33:07,809
Speaker:
Okay.
964
00:33:07,809 --> 00:33:09,930
Speaker:
Depending on the day and
depending on the dog.
965
00:33:09,930 --> 00:33:10,609
Speaker:
Right?
966
00:33:10,609 --> 00:33:12,089
Speaker:
Yeah.
967
00:33:12,089 --> 00:33:13,170
Speaker:
And there's only two of them.
968
00:33:13,170 --> 00:33:17,089
Speaker:
So there's gonna be like, you
know, high variability, right?
969
00:33:17,089 --> 00:33:19,650
Speaker:
In this study, it's a terrible
sample size.
970
00:33:19,650 --> 00:33:20,289
Speaker:
Yeah, yeah, yeah.
971
00:33:20,289 --> 00:33:21,730
Speaker:
But you know, we're just, we're
972
00:33:21,730 --> 00:33:23,089
Speaker:
starting out, we're trying some
973
00:33:23,089 --> 00:33:24,170
Speaker:
stuff here.
974
00:33:24,170 --> 00:33:25,869
Speaker:
I mean, So yeah, there's,
975
00:33:25,869 --> 00:33:28,230
Speaker:
they're well above pure chance
976
00:33:28,230 --> 00:33:29,710
Speaker:
on accuracy.
977
00:33:29,710 --> 00:33:31,349
Speaker:
So they're doing something.
978
00:33:31,349 --> 00:33:31,750
Speaker:
Yeah.
979
00:33:31,750 --> 00:33:35,630
Speaker:
but one of the main goals of
this study with the dogs wasn't
980
00:33:35,630 --> 00:33:41,650
Speaker:
necessarily to like use the dogs
to smell people clinically and
981
00:33:41,650 --> 00:33:45,609
Speaker:
diagnose them, but The main idea
for the study was more.
982
00:33:45,609 --> 00:33:49,970
Speaker:
To do experiments on figuring
out what they're smelling like.
983
00:33:49,970 --> 00:33:54,049
Speaker:
Maybe if they could smell this
odor, then we can give them
984
00:33:54,049 --> 00:33:58,130
Speaker:
different odors that we think
might be related.
985
00:33:58,130 --> 00:34:01,049
Speaker:
Like here's what we think is
causing that odor.
986
00:34:01,049 --> 00:34:03,430
Speaker:
do they go towards that in a
similar way?
987
00:34:03,430 --> 00:34:04,150
Speaker:
Okay.
988
00:34:04,150 --> 00:34:05,970
Speaker:
that makes sense.
989
00:34:05,970 --> 00:34:06,569
Speaker:
Yeah.
990
00:34:06,569 --> 00:34:11,989
Speaker:
So we would use that information
to develop more accurate
991
00:34:11,989 --> 00:34:13,929
Speaker:
diagnosis tools, right?
992
00:34:13,929 --> 00:34:17,289
Speaker:
There's a bunch of crazy stuff
happening all over the world
993
00:34:17,289 --> 00:34:20,929
Speaker:
based on this one woman's
ability to smell.
994
00:34:20,929 --> 00:34:21,929
Speaker:
Really.
995
00:34:21,929 --> 00:34:26,809
Speaker:
in China, they're developing a
new type of technology to your
996
00:34:26,809 --> 00:34:27,650
Speaker:
next lab libs.
997
00:34:27,650 --> 00:34:31,409
Speaker:
What do you think is the new
type of technology that China is
998
00:34:31,409 --> 00:34:34,690
Speaker:
using to tackle this idea?
999
00:34:34,690 --> 00:34:37,409
Speaker:
I said AI, which I suppose it
1000
00:34:37,409 --> 00:34:40,010
Speaker:
could be, but I'm gonna tell you
1001
00:34:40,010 --> 00:34:41,530
Speaker:
the other word that I hear a lot
1002
00:34:41,530 --> 00:34:42,130
Speaker:
of that.
1003
00:34:42,130 --> 00:34:45,250
Speaker:
I have no idea what it is.
1004
00:34:45,250 --> 00:34:45,929
Speaker:
Tell me.
1005
00:34:47,130 --> 00:34:48,210
Speaker:
Technology.
1006
00:34:49,570 --> 00:34:51,050
Speaker:
It could be nanotechnology.
1007
00:34:51,050 --> 00:34:51,889
Speaker:
Could you imagine?
1008
00:34:51,889 --> 00:34:54,369
Speaker:
No, because I don't know what
that means.
1009
00:34:54,369 --> 00:34:59,170
Speaker:
I think it's like tiny, tiny,
tiny, tiny microscopic robots.
1010
00:34:59,170 --> 00:35:00,889
Speaker:
It's tiny technology.
1011
00:35:00,889 --> 00:35:04,570
Speaker:
I'm pretty sure it's microscopic
robots.
1012
00:35:04,570 --> 00:35:04,969
Speaker:
Robots.
1013
00:35:04,969 --> 00:35:06,449
Speaker:
Little tiny robots.
1014
00:35:06,449 --> 00:35:06,849
Speaker:
Little tiny.
1015
00:35:06,849 --> 00:35:07,730
Speaker:
Is it AI?
1016
00:35:07,730 --> 00:35:08,769
Speaker:
Yeah, it's AI AI.
1017
00:35:08,769 --> 00:35:16,349
Speaker:
Okay, so in China, they're
developing an AI nose, which you
1018
00:35:16,349 --> 00:35:18,849
Speaker:
guessed earlier, you were like,
you could put it in there.
1019
00:35:18,849 --> 00:35:21,630
Speaker:
When I was talking about the
spectrometer, You were like, you
1020
00:35:21,630 --> 00:35:24,190
Speaker:
can put it in there like a
little like machine nose And I
1021
00:35:24,190 --> 00:35:26,110
Speaker:
was like, oh, there it is.
1022
00:35:26,110 --> 00:35:26,829
Speaker:
Yes.
1023
00:35:27,869 --> 00:35:28,190
Speaker:
Yeah.
1024
00:35:28,190 --> 00:35:30,429
Speaker:
So China, is trying to do that.
1025
00:35:30,429 --> 00:35:30,789
Speaker:
Huh.
1026
00:35:30,789 --> 00:35:31,150
Speaker:
Okay.
1027
00:35:31,150 --> 00:35:34,349
Speaker:
Currently, you need to have a
gas spectrometer to read any
1028
00:35:34,349 --> 00:35:39,789
Speaker:
results from this sebum skin
test swab test thing.
1029
00:35:39,789 --> 00:35:43,389
Speaker:
And those are bulky and very
expensive machines.
1030
00:35:43,389 --> 00:35:49,389
Speaker:
But researchers in China Lu and
Zheng Chen.
1031
00:35:49,389 --> 00:35:50,989
Speaker:
Mhm.
1032
00:35:50,989 --> 00:35:51,590
Speaker:
Mhm.
1033
00:35:52,630 --> 00:35:54,550
Speaker:
And and their colleagues are
1034
00:35:54,550 --> 00:35:56,429
Speaker:
building a portable and cheap
1035
00:35:56,429 --> 00:35:58,349
Speaker:
system to do the task in a more
1036
00:35:58,349 --> 00:36:00,389
Speaker:
accessible way, like nano
1037
00:36:00,389 --> 00:36:01,909
Speaker:
technology.
1038
00:36:01,909 --> 00:36:08,750
Speaker:
No. Like nasal technology?
1039
00:36:08,750 --> 00:36:09,150
Speaker:
Yes.
1040
00:36:09,150 --> 00:36:10,269
Speaker:
That's what it is.
1041
00:36:10,269 --> 00:36:11,070
Speaker:
Mhm.
1042
00:36:11,070 --> 00:36:12,590
Speaker:
They've combined the gas
1043
00:36:12,590 --> 00:36:15,670
Speaker:
spectrometer device in a more
1044
00:36:15,670 --> 00:36:16,789
Speaker:
simplified way.
1045
00:36:16,789 --> 00:36:17,670
Speaker:
Right.
1046
00:36:17,670 --> 00:36:21,480
Speaker:
With a surface acoustic wave
sensor.
1047
00:36:21,480 --> 00:36:22,199
Speaker:
Aha.
1048
00:36:22,199 --> 00:36:22,599
Speaker:
Right.
1049
00:36:22,599 --> 00:36:24,199
Speaker:
That's because that's what I was
gonna say.
1050
00:36:24,199 --> 00:36:28,440
Speaker:
I think is that they can put
1051
00:36:28,440 --> 00:36:31,000
Speaker:
something that is smelly and is
1052
00:36:31,000 --> 00:36:34,260
Speaker:
giving off waves of smelly odor,
1053
00:36:34,260 --> 00:36:34,920
Speaker:
right?
1054
00:36:34,920 --> 00:36:37,079
Speaker:
Chemicals that cause an odor.
1055
00:36:37,079 --> 00:36:37,400
Speaker:
Right?
1056
00:36:37,400 --> 00:36:42,320
Speaker:
And the machine can sense that
just from the air inside of it,
1057
00:36:42,320 --> 00:36:44,679
Speaker:
like a nose would smell.
1058
00:36:44,679 --> 00:36:45,039
Speaker:
Right?
1059
00:36:45,039 --> 00:36:45,519
Speaker:
Right.
1060
00:36:45,519 --> 00:36:49,679
Speaker:
It's quote unquote, sniffing the
air in some way.
1061
00:36:49,679 --> 00:36:50,599
Speaker:
Right, right, right.
1062
00:36:50,599 --> 00:36:51,960
Speaker:
I think that's what that means.
1063
00:36:51,960 --> 00:36:52,960
Speaker:
Huh?
1064
00:36:52,960 --> 00:36:55,320
Speaker:
I don't know because those are a
lot of words.
1065
00:36:55,320 --> 00:36:56,639
Speaker:
Sounds right.
1066
00:36:56,639 --> 00:37:01,079
Speaker:
but yeah, and they've also
combined that with machine
1067
00:37:01,079 --> 00:37:08,559
Speaker:
learning algorithms to be able
to smell odors released in this
1068
00:37:08,559 --> 00:37:10,719
Speaker:
gaseous scent wave, right?
1069
00:37:10,719 --> 00:37:12,519
Speaker:
And use the algorithms that
1070
00:37:12,519 --> 00:37:14,320
Speaker:
they've programmed to match the
1071
00:37:14,320 --> 00:37:16,150
Speaker:
compounds from the test sample
1072
00:37:16,150 --> 00:37:19,159
Speaker:
to known samples who have PD or
1073
00:37:19,159 --> 00:37:20,619
Speaker:
samples from people who are
1074
00:37:20,619 --> 00:37:21,619
Speaker:
healthy, right?
1075
00:37:21,619 --> 00:37:24,340
Speaker:
So it's taking out the process
1076
00:37:24,340 --> 00:37:26,780
Speaker:
of people trying to match those
1077
00:37:26,780 --> 00:37:30,059
Speaker:
compounds up, and is teaching a
1078
00:37:30,059 --> 00:37:31,619
Speaker:
machine learning algorithm to do
1079
00:37:31,619 --> 00:37:33,820
Speaker:
it, which this is actually a
1080
00:37:33,820 --> 00:37:35,260
Speaker:
task that machine learning is
1081
00:37:35,260 --> 00:37:35,739
Speaker:
good at.
1082
00:37:35,739 --> 00:37:37,320
Speaker:
This is what we should be using
1083
00:37:37,320 --> 00:37:39,420
Speaker:
AI for, not fucking Google
1084
00:37:39,420 --> 00:37:41,420
Speaker:
searches, right?
1085
00:37:41,420 --> 00:37:47,139
Speaker:
No, no, I agree there are like
some really, really good uses
1086
00:37:47,139 --> 00:37:48,860
Speaker:
for humanity, you know?
1087
00:37:48,860 --> 00:37:52,019
Speaker:
So their device they claim has
1088
00:37:52,019 --> 00:37:54,699
Speaker:
reached nearly eighty percent
1089
00:37:54,699 --> 00:37:55,659
Speaker:
accuracy.
1090
00:37:55,659 --> 00:37:57,820
Speaker:
They actually have published a
study about it.
1091
00:37:57,820 --> 00:37:58,340
Speaker:
Okay.
1092
00:37:58,340 --> 00:38:02,420
Speaker:
Unlike the skin swab people,
woman people.
1093
00:38:02,420 --> 00:38:07,280
Speaker:
It's not just her, but, she, I'm
sure doing also fine research.
1094
00:38:07,280 --> 00:38:08,324
Speaker:
It just hasn't been published
1095
00:38:08,324 --> 00:38:13,610
Speaker:
yet, but the AI knows has had
1096
00:38:13,610 --> 00:38:15,710
Speaker:
some false positives just like
1097
00:38:15,710 --> 00:38:16,650
Speaker:
the dogs.
1098
00:38:16,650 --> 00:38:17,809
Speaker:
That was also their problem.
1099
00:38:17,809 --> 00:38:19,050
Speaker:
They'll say something is
1100
00:38:19,050 --> 00:38:21,050
Speaker:
Parkinson's when it's actually
1101
00:38:21,050 --> 00:38:21,769
Speaker:
not.
1102
00:38:21,769 --> 00:38:25,730
Speaker:
Yeah, that's what you don't
want, right?
1103
00:38:25,730 --> 00:38:27,250
Speaker:
You don't want that call.
1104
00:38:27,250 --> 00:38:32,409
Speaker:
I mean, technically a false
positive is sort of better than
1105
00:38:32,409 --> 00:38:36,289
Speaker:
a false negative because it's on
the side of caution.
1106
00:38:36,289 --> 00:38:39,210
Speaker:
It's more stressful to say like,
hey, you got this disease, but
1107
00:38:39,210 --> 00:38:39,889
Speaker:
you actually don't.
1108
00:38:39,889 --> 00:38:43,170
Speaker:
But in a way, it's better than
saying, nope, you don't have it.
1109
00:38:43,170 --> 00:38:46,489
Speaker:
You're all good, all good, but
then you actually do have it.
1110
00:38:46,489 --> 00:38:48,170
Speaker:
Then clinically, that would be
1111
00:38:48,170 --> 00:38:49,690
Speaker:
worse because then you're not
1112
00:38:49,690 --> 00:38:51,829
Speaker:
taking the steps needed to avoid
1113
00:38:51,829 --> 00:38:52,849
Speaker:
things, right?
1114
00:38:52,849 --> 00:38:53,650
Speaker:
Whatever.
1115
00:38:53,650 --> 00:38:55,829
Speaker:
False positives are also bad
1116
00:38:55,829 --> 00:38:57,530
Speaker:
though, so we want it to be
1117
00:38:57,530 --> 00:38:58,090
Speaker:
accurate.
1118
00:38:58,090 --> 00:39:01,750
Speaker:
The research team that's working
on this have been trying to
1119
00:39:01,750 --> 00:39:06,010
Speaker:
improve its accuracy by testing
it on more people to improve the
1120
00:39:06,010 --> 00:39:08,170
Speaker:
AI knowledge base.
1121
00:39:08,170 --> 00:39:11,210
Speaker:
They also said They're
considering race and other
1122
00:39:11,210 --> 00:39:15,210
Speaker:
variables for the model to
improve accuracy worldwide.
1123
00:39:15,210 --> 00:39:19,489
Speaker:
Okay, now a question I had
throughout this whole research
1124
00:39:19,489 --> 00:39:24,690
Speaker:
journey is are there other
people who can smell this?
1125
00:39:24,690 --> 00:39:26,170
Speaker:
It can't just be.
1126
00:39:26,170 --> 00:39:27,409
Speaker:
Joy Milne right.
1127
00:39:27,409 --> 00:39:28,690
Speaker:
I wondered the same thing.
1128
00:39:28,690 --> 00:39:30,130
Speaker:
Like if that if that was a
1129
00:39:30,130 --> 00:39:31,389
Speaker:
condition that other people
1130
00:39:31,389 --> 00:39:31,909
Speaker:
have.
1131
00:39:31,909 --> 00:39:32,630
Speaker:
Right.
1132
00:39:32,630 --> 00:39:35,989
Speaker:
Like it can't just be there's
other people with hypersomnia.
1133
00:39:35,989 --> 00:39:37,510
Speaker:
That's what I'm saying that have
1134
00:39:37,510 --> 00:39:38,750
Speaker:
increased sense of smell
1135
00:39:38,750 --> 00:39:39,309
Speaker:
genetically.
1136
00:39:39,309 --> 00:39:41,150
Speaker:
Like, yeah, there must be other
1137
00:39:41,150 --> 00:39:42,469
Speaker:
people who can smell this
1138
00:39:42,469 --> 00:39:43,750
Speaker:
Parkinson's odor.
1139
00:39:43,750 --> 00:39:44,230
Speaker:
Yeah.
1140
00:39:44,230 --> 00:39:44,909
Speaker:
That's true.
1141
00:39:44,909 --> 00:39:47,909
Speaker:
Now, I tried searching to see if
1142
00:39:47,909 --> 00:39:53,039
Speaker:
there was some sort of call from
1143
00:39:53,039 --> 00:39:54,760
Speaker:
research teams on the internet,
1144
00:39:54,760 --> 00:39:58,480
Speaker:
like a call to say, hey, I think
1145
00:39:58,480 --> 00:40:01,480
Speaker:
I have this, can I contact you
1146
00:40:01,480 --> 00:40:02,639
Speaker:
for research?
1147
00:40:02,639 --> 00:40:04,239
Speaker:
And it seemed that I was not the
1148
00:40:04,239 --> 00:40:06,639
Speaker:
only one looking for that, but I
1149
00:40:06,639 --> 00:40:10,019
Speaker:
could not find a place that was
1150
00:40:10,019 --> 00:40:12,960
Speaker:
taking submissions.
1151
00:40:12,960 --> 00:40:16,360
Speaker:
For lack of a better word of
people saying, I think I can
1152
00:40:16,360 --> 00:40:17,400
Speaker:
smell this thing.
1153
00:40:18,960 --> 00:40:21,719
Speaker:
Google AI said that.
1154
00:40:21,719 --> 00:40:25,639
Speaker:
Like when I when I googled it,
the AI answer said that
1155
00:40:25,639 --> 00:40:28,880
Speaker:
researchers are looking for
other super smellers.
1156
00:40:28,880 --> 00:40:29,159
Speaker:
Yeah.
1157
00:40:29,159 --> 00:40:30,039
Speaker:
Of course.
1158
00:40:30,039 --> 00:40:32,079
Speaker:
but I couldn't find a source for
1159
00:40:32,079 --> 00:40:34,079
Speaker:
the claim, so I don't know if it
1160
00:40:34,079 --> 00:40:35,199
Speaker:
was just making stuff up or
1161
00:40:35,199 --> 00:40:35,599
Speaker:
what.
1162
00:40:35,599 --> 00:40:36,199
Speaker:
Mhm.
1163
00:40:36,199 --> 00:40:38,840
Speaker:
I would think that they're
looking for more people.
1164
00:40:38,840 --> 00:40:39,320
Speaker:
Right?
1165
00:40:39,320 --> 00:40:41,960
Speaker:
I would think that would have
been joy.
1166
00:40:41,960 --> 00:40:42,599
Speaker:
Poor joy.
1167
00:40:42,599 --> 00:40:44,719
Speaker:
She's like eighty something
years old now.
1168
00:40:44,719 --> 00:40:50,139
Speaker:
Like I got the dogs scenario and
everything, but the original
1169
00:40:50,139 --> 00:40:55,860
Speaker:
thing that was able to detect it
was a human right.
1170
00:40:55,860 --> 00:40:59,780
Speaker:
So you would think trying
humans.
1171
00:40:59,780 --> 00:41:01,619
Speaker:
Would be a thing.
1172
00:41:01,619 --> 00:41:03,980
Speaker:
And I could find plenty of
people saying they think they
1173
00:41:03,980 --> 00:41:04,460
Speaker:
can smell it.
1174
00:41:04,460 --> 00:41:05,380
Speaker:
They have the.
1175
00:41:05,380 --> 00:41:05,980
Speaker:
Mhm.
1176
00:41:05,980 --> 00:41:06,460
Speaker:
Yeah.
1177
00:41:06,460 --> 00:41:09,099
Speaker:
So maybe they are out there
looking for people, but maybe
1178
00:41:09,099 --> 00:41:12,860
Speaker:
they're doing it more like
targeted way than just letting
1179
00:41:12,860 --> 00:41:15,500
Speaker:
people submit online or
something, I don't know.
1180
00:41:15,500 --> 00:41:15,940
Speaker:
I don't know.
1181
00:41:15,940 --> 00:41:18,460
Speaker:
I expected to find more things
1182
00:41:18,460 --> 00:41:19,659
Speaker:
about other people who could
1183
00:41:19,659 --> 00:41:21,699
Speaker:
smell this, but I didn't find
1184
00:41:21,699 --> 00:41:23,300
Speaker:
any other like much other
1185
00:41:23,300 --> 00:41:25,579
Speaker:
studies saying we found other
1186
00:41:25,579 --> 00:41:26,940
Speaker:
super smeller, we found this or
1187
00:41:26,940 --> 00:41:27,900
Speaker:
whatever.
1188
00:41:27,900 --> 00:41:31,980
Speaker:
But I did find an interesting
Facebook post by some random guy
1189
00:41:31,980 --> 00:41:36,820
Speaker:
named Henry, on a support group
page for Parkinson's.
1190
00:41:36,820 --> 00:41:42,219
Speaker:
Okay, that he said his wife
smelled his Parkinson's odor
1191
00:41:42,219 --> 00:41:46,079
Speaker:
years before his diagnosis, and
that he has tried contacting the
1192
00:41:46,079 --> 00:41:47,920
Speaker:
researchers in Manchester.
1193
00:41:47,920 --> 00:41:51,119
Speaker:
The ones I was talking about
with no response because this
1194
00:41:51,119 --> 00:41:53,320
Speaker:
whole thing went pretty viral
when it happened.
1195
00:41:53,320 --> 00:41:54,079
Speaker:
Like really?
1196
00:41:54,079 --> 00:41:54,840
Speaker:
Okay.
1197
00:41:54,840 --> 00:41:56,079
Speaker:
Like, especially in the
1198
00:41:56,079 --> 00:41:57,219
Speaker:
neuroscience community, of
1199
00:41:57,219 --> 00:41:58,239
Speaker:
course.
1200
00:41:58,239 --> 00:42:01,360
Speaker:
but in the Parkinson's community
too, right.
1201
00:42:01,360 --> 00:42:02,519
Speaker:
Everybody was talking about the
1202
00:42:02,519 --> 00:42:03,980
Speaker:
woman who can smell Parkinson's,
1203
00:42:03,980 --> 00:42:04,519
Speaker:
right?
1204
00:42:04,519 --> 00:42:09,139
Speaker:
A lot of comments on his post of
other people saying that they or
1205
00:42:09,139 --> 00:42:12,800
Speaker:
their partners can also smell it
and people saying they could
1206
00:42:12,800 --> 00:42:16,039
Speaker:
smell it and no one else has,
like no one else around them can
1207
00:42:16,039 --> 00:42:17,159
Speaker:
smell it, right?
1208
00:42:17,159 --> 00:42:18,400
Speaker:
That they can smell it on their
1209
00:42:18,400 --> 00:42:19,840
Speaker:
shirts of the people around
1210
00:42:19,840 --> 00:42:21,199
Speaker:
their neck.
1211
00:42:21,199 --> 00:42:25,119
Speaker:
They describe it as musky or
oniony or foul.
1212
00:42:25,119 --> 00:42:28,440
Speaker:
Lots of people saying their
doctors were dismissive of this.
1213
00:42:28,440 --> 00:42:30,000
Speaker:
Even after the study on Joy
1214
00:42:30,000 --> 00:42:32,760
Speaker:
Milne came out, they were still
1215
00:42:32,760 --> 00:42:33,730
Speaker:
dismissive.
1216
00:42:33,730 --> 00:42:34,409
Speaker:
right?
1217
00:42:34,409 --> 00:42:36,409
Speaker:
That that that their partner
1218
00:42:36,409 --> 00:42:38,110
Speaker:
could smell their Parkinson's
1219
00:42:38,110 --> 00:42:39,130
Speaker:
odor.
1220
00:42:39,130 --> 00:42:40,050
Speaker:
Right.
1221
00:42:40,050 --> 00:42:42,329
Speaker:
Then I found this study from
1222
00:42:42,329 --> 00:42:45,570
Speaker:
Germany, um, where they used
1223
00:42:45,570 --> 00:42:47,369
Speaker:
young women.
1224
00:42:47,369 --> 00:42:48,369
Speaker:
This is how they said it.
1225
00:42:48,369 --> 00:42:50,889
Speaker:
They used young women as
sniffers.
1226
00:42:50,889 --> 00:42:51,889
Speaker:
Okay.
1227
00:42:53,010 --> 00:42:55,489
Speaker:
now, these people have been
1228
00:42:55,489 --> 00:42:57,969
Speaker:
previously familiarized with the
1229
00:42:57,969 --> 00:42:59,090
Speaker:
Parkinson's disease.
1230
00:42:59,090 --> 00:42:59,730
Speaker:
Smell.
1231
00:42:59,730 --> 00:43:00,610
Speaker:
Okay.
1232
00:43:00,610 --> 00:43:02,889
Speaker:
And now they were doing a study
1233
00:43:02,889 --> 00:43:04,329
Speaker:
to see if they could identify
1234
00:43:04,329 --> 00:43:06,530
Speaker:
it, like blindly in the same
1235
00:43:06,530 --> 00:43:07,050
Speaker:
way.
1236
00:43:07,050 --> 00:43:07,329
Speaker:
Right?
1237
00:43:07,329 --> 00:43:10,329
Speaker:
With the t shirts and
everything, basically very
1238
00:43:10,329 --> 00:43:13,369
Speaker:
similar test to the one Joy did
in her experiment.
1239
00:43:13,369 --> 00:43:17,070
Speaker:
They gave t shirts to fifteen
people with PD and nineteen
1240
00:43:17,070 --> 00:43:20,289
Speaker:
healthy people, told them to
wear it for a night, and then
1241
00:43:20,289 --> 00:43:23,690
Speaker:
they put it in the Ziploc bags,
just like the original study.
1242
00:43:23,690 --> 00:43:28,230
Speaker:
And they gave those to twenty
six women to rate the scent in a
1243
00:43:28,230 --> 00:43:29,550
Speaker:
couple of different ways.
1244
00:43:29,550 --> 00:43:35,269
Speaker:
First, they asked them to
qualitatively describe it, what
1245
00:43:35,269 --> 00:43:41,329
Speaker:
it smelled like, and then they
also quantitatively asked them,
1246
00:43:41,329 --> 00:43:44,190
Speaker:
does this person have the
Parkinson's disease or not?
1247
00:43:44,190 --> 00:43:44,909
Speaker:
Right, right.
1248
00:43:44,909 --> 00:43:46,869
Speaker:
So they had a couple different
data points about it.
1249
00:43:46,869 --> 00:43:49,230
Speaker:
They also gave them a third set
1250
00:43:49,230 --> 00:43:51,670
Speaker:
of odors, which was an
1251
00:43:51,670 --> 00:43:54,730
Speaker:
artificial Parkinson's disorder,
1252
00:43:54,730 --> 00:43:59,230
Speaker:
an artificial PD odor made from
1253
00:43:59,230 --> 00:44:02,190
Speaker:
mixing four volatile organic
1254
00:44:02,190 --> 00:44:02,789
Speaker:
compounds.
1255
00:44:02,789 --> 00:44:05,150
Speaker:
That's the that's what they're
called VOCs.
1256
00:44:05,150 --> 00:44:05,869
Speaker:
Okay.
1257
00:44:05,869 --> 00:44:09,010
Speaker:
They mix these four VOCs,
1258
00:44:09,010 --> 00:44:10,710
Speaker:
scents, basically volatile
1259
00:44:10,710 --> 00:44:11,590
Speaker:
organic compounds.
1260
00:44:11,590 --> 00:44:13,989
Speaker:
That's like a scent, right?
1261
00:44:13,989 --> 00:44:17,750
Speaker:
into a bottle to make this
artificial PD thing.
1262
00:44:17,750 --> 00:44:19,349
Speaker:
To see if they could recreate
1263
00:44:19,349 --> 00:44:21,429
Speaker:
the smell with the known
1264
00:44:21,429 --> 00:44:22,989
Speaker:
compounds that they know are
1265
00:44:22,989 --> 00:44:25,559
Speaker:
common in this oily sebum from
1266
00:44:25,559 --> 00:44:26,239
Speaker:
the people.
1267
00:44:26,239 --> 00:44:29,119
Speaker:
That's basically what they
thought were causing the smell.
1268
00:44:29,119 --> 00:44:33,840
Speaker:
These four most common like most
increased compounds.
1269
00:44:33,840 --> 00:44:34,480
Speaker:
Gotcha.
1270
00:44:34,480 --> 00:44:38,039
Speaker:
So these twenty six women who
1271
00:44:38,039 --> 00:44:39,960
Speaker:
knew what the smell was from
1272
00:44:39,960 --> 00:44:40,760
Speaker:
before.
1273
00:44:40,760 --> 00:44:41,400
Speaker:
Yeah.
1274
00:44:41,400 --> 00:44:44,960
Speaker:
Can identify PD also.
1275
00:44:44,960 --> 00:44:46,000
Speaker:
Wow.
1276
00:44:46,000 --> 00:44:46,880
Speaker:
Crazy, right?
1277
00:44:46,880 --> 00:44:50,960
Speaker:
And these are not necessarily
women that have that disorder.
1278
00:44:50,960 --> 00:44:54,719
Speaker:
No, they're not people with
hypersomnia or whatever.
1279
00:44:54,719 --> 00:44:55,000
Speaker:
Right?
1280
00:44:55,000 --> 00:44:55,920
Speaker:
Like they don't have any
1281
00:44:55,920 --> 00:44:57,559
Speaker:
increased sense of regular
1282
00:44:57,559 --> 00:44:57,840
Speaker:
people.
1283
00:44:57,840 --> 00:44:59,760
Speaker:
They're just regular people.
1284
00:44:59,760 --> 00:45:00,480
Speaker:
Wow.
1285
00:45:00,480 --> 00:45:01,239
Speaker:
Right.
1286
00:45:02,360 --> 00:45:02,719
Speaker:
Wow.
1287
00:45:02,719 --> 00:45:03,599
Speaker:
That's crazy.
1288
00:45:03,599 --> 00:45:04,280
Speaker:
Yeah.
1289
00:45:04,280 --> 00:45:05,199
Speaker:
It's wild.
1290
00:45:05,199 --> 00:45:08,519
Speaker:
they described the real PD odor
1291
00:45:08,519 --> 00:45:10,699
Speaker:
as strong, sweaty, musty and
1292
00:45:10,699 --> 00:45:11,739
Speaker:
unpleasant.
1293
00:45:11,739 --> 00:45:15,340
Speaker:
And then the odors that were
from the artificial PD
1294
00:45:15,340 --> 00:45:19,360
Speaker:
combination and the healthy
people, They described those
1295
00:45:19,360 --> 00:45:22,840
Speaker:
both as natural, neutral,
subtle, even clean.
1296
00:45:22,840 --> 00:45:25,039
Speaker:
Sometimes even though they were
1297
00:45:25,039 --> 00:45:27,199
Speaker:
still from, like Parsons dirty t
1298
00:45:27,199 --> 00:45:28,320
Speaker:
shirt, right?
1299
00:45:28,320 --> 00:45:32,659
Speaker:
so it seems that it's more than
just the four compounds.
1300
00:45:32,659 --> 00:45:36,219
Speaker:
I thought it was going to be
because that didn't trick them.
1301
00:45:36,219 --> 00:45:37,619
Speaker:
They didn't think those were.
1302
00:45:37,619 --> 00:45:38,059
Speaker:
Yeah.
1303
00:45:38,059 --> 00:45:40,139
Speaker:
They haven't recreated that
smell yet.
1304
00:45:40,139 --> 00:45:40,539
Speaker:
Right?
1305
00:45:40,539 --> 00:45:41,019
Speaker:
Right.
1306
00:45:41,019 --> 00:45:43,619
Speaker:
these women were pretty
accurate.
1307
00:45:43,619 --> 00:45:45,500
Speaker:
How accurate do you think they
were?
1308
00:45:45,500 --> 00:45:48,539
Speaker:
Your next lab lab's between
fifty and one hundred percent.
1309
00:45:48,539 --> 00:45:50,019
Speaker:
How accurate were they?
1310
00:45:50,019 --> 00:45:51,940
Speaker:
Um, I said sixty nine.
1311
00:45:51,940 --> 00:45:52,579
Speaker:
Obviously.
1312
00:45:52,579 --> 00:45:53,340
Speaker:
Nice.
1313
00:45:55,900 --> 00:45:59,619
Speaker:
I mean, that's sounds pretty
okay.
1314
00:45:59,619 --> 00:46:00,980
Speaker:
Maybe lower.
1315
00:46:00,980 --> 00:46:02,300
Speaker:
No, it's higher than that.
1316
00:46:02,300 --> 00:46:02,820
Speaker:
It's higher.
1317
00:46:02,820 --> 00:46:03,579
Speaker:
What?
1318
00:46:03,579 --> 00:46:05,340
Speaker:
What is it, eighty to ninety.
1319
00:46:05,340 --> 00:46:05,820
Speaker:
Wow.
1320
00:46:05,820 --> 00:46:07,079
Speaker:
Oh, okay.
1321
00:46:07,079 --> 00:46:08,679
Speaker:
Up to ninety percent accurate.
1322
00:46:08,679 --> 00:46:08,840
Speaker:
Wow.
1323
00:46:08,840 --> 00:46:11,880
Speaker:
And like I said, the artificial
PD didn't trip them up.
1324
00:46:11,880 --> 00:46:13,519
Speaker:
So the odor must be coming from
1325
00:46:13,519 --> 00:46:14,639
Speaker:
more than just those four
1326
00:46:14,639 --> 00:46:15,800
Speaker:
compounds, huh.
1327
00:46:15,800 --> 00:46:22,059
Speaker:
so it may be that many women or
many other many people can
1328
00:46:22,059 --> 00:46:23,739
Speaker:
differentiate the smell.
1329
00:46:23,739 --> 00:46:25,019
Speaker:
Maybe all those people in the
1330
00:46:25,019 --> 00:46:26,500
Speaker:
Facebook comments really can
1331
00:46:26,500 --> 00:46:26,699
Speaker:
smell.
1332
00:46:26,699 --> 00:46:27,300
Speaker:
It really can't.
1333
00:46:27,300 --> 00:46:32,460
Speaker:
No, it's not as rare, but this
one person just happened to be
1334
00:46:32,460 --> 00:46:35,539
Speaker:
the one that put two and two
together about it, right?
1335
00:46:35,539 --> 00:46:38,360
Speaker:
I was going to say it just
happens to be the one that got
1336
00:46:38,360 --> 00:46:40,219
Speaker:
actually like tested.
1337
00:46:40,219 --> 00:46:41,420
Speaker:
Yeah, you know what I mean?
1338
00:46:41,420 --> 00:46:41,659
Speaker:
Yeah.
1339
00:46:41,659 --> 00:46:44,139
Speaker:
Taken seriously by the medical
community, right?
1340
00:46:44,139 --> 00:46:46,980
Speaker:
And you know, they were both
medical professionals.
1341
00:46:46,980 --> 00:46:48,860
Speaker:
So that probably gave them some
1342
00:46:48,860 --> 00:46:50,280
Speaker:
credibility, some credibility,
1343
00:46:50,280 --> 00:46:50,699
Speaker:
right?
1344
00:46:50,699 --> 00:46:53,820
Speaker:
Or even networking.
1345
00:46:53,820 --> 00:46:55,539
Speaker:
They knew who to talk to and
stuff.
1346
00:46:55,539 --> 00:46:56,059
Speaker:
Probably.
1347
00:46:56,059 --> 00:46:56,500
Speaker:
Yeah.
1348
00:46:56,500 --> 00:46:57,019
Speaker:
Yeah.
1349
00:46:57,019 --> 00:46:59,309
Speaker:
This is really gonna change how
1350
00:46:59,309 --> 00:47:00,389
Speaker:
we not only think about
1351
00:47:00,389 --> 00:47:02,010
Speaker:
diagnosing Parkinson's, but
1352
00:47:02,010 --> 00:47:03,190
Speaker:
other neurodegenerative
1353
00:47:03,190 --> 00:47:04,949
Speaker:
disorders.
1354
00:47:04,949 --> 00:47:11,750
Speaker:
And it's kind of a nod to a
medicine from long past.
1355
00:47:11,750 --> 00:47:16,070
Speaker:
Like in the past, it was not
uncommon for physicians to use
1356
00:47:16,070 --> 00:47:20,829
Speaker:
things like breath tests and
scent signaling in diagnosis of
1357
00:47:20,829 --> 00:47:22,630
Speaker:
diseases in general.
1358
00:47:22,630 --> 00:47:25,989
Speaker:
So maybe this is a lesson that
even when we come up with new
1359
00:47:25,989 --> 00:47:29,869
Speaker:
fancy tests and medicine, that
there are still kind of older
1360
00:47:29,869 --> 00:47:34,989
Speaker:
methods, sometimes simple
methods that still hold a lot of
1361
00:47:34,989 --> 00:47:37,829
Speaker:
importance right now.
1362
00:47:37,829 --> 00:47:40,010
Speaker:
Like I said earlier, les died in
1363
00:47:40,010 --> 00:47:41,829
Speaker:
twenty fifteen from Parkinson's
1364
00:47:41,829 --> 00:47:44,989
Speaker:
disease, but before he died, he
1365
00:47:44,989 --> 00:47:47,349
Speaker:
and Joy spent a few hours each
1366
00:47:47,349 --> 00:47:48,949
Speaker:
day for the last six weeks of
1367
00:47:48,949 --> 00:47:49,949
Speaker:
his life, writing about
1368
00:47:49,949 --> 00:47:51,289
Speaker:
everything that had happened to
1369
00:47:51,289 --> 00:47:53,110
Speaker:
him between the time that she
1370
00:47:53,110 --> 00:47:55,429
Speaker:
smelled his weird odor, to the
1371
00:47:55,429 --> 00:47:57,150
Speaker:
time that he was diagnosed,
1372
00:47:57,150 --> 00:47:57,730
Speaker:
right?
1373
00:47:57,730 --> 00:48:00,090
Speaker:
They thought that since she
1374
00:48:00,090 --> 00:48:02,010
Speaker:
smelled it on him so early that
1375
00:48:02,010 --> 00:48:03,690
Speaker:
maybe he was showing symptoms
1376
00:48:03,690 --> 00:48:05,730
Speaker:
that we don't even know are
1377
00:48:05,730 --> 00:48:06,730
Speaker:
symptoms.
1378
00:48:07,730 --> 00:48:10,650
Speaker:
So they spent time thinking
about their life.
1379
00:48:10,650 --> 00:48:12,889
Speaker:
They said it was kind of
cathartic also.
1380
00:48:12,889 --> 00:48:13,329
Speaker:
Yeah.
1381
00:48:13,329 --> 00:48:14,929
Speaker:
And nice to like, talk again
1382
00:48:14,929 --> 00:48:16,789
Speaker:
about everything that they've
1383
00:48:16,789 --> 00:48:17,369
Speaker:
been through.
1384
00:48:17,369 --> 00:48:19,750
Speaker:
Um, to try to help others to
1385
00:48:19,750 --> 00:48:21,969
Speaker:
find the disease sooner than
1386
00:48:21,969 --> 00:48:22,570
Speaker:
they did.
1387
00:48:22,570 --> 00:48:24,050
Speaker:
Yeah.
1388
00:48:24,050 --> 00:48:27,690
Speaker:
So, and Joy is still working on
this field of research even into
1389
00:48:27,690 --> 00:48:28,610
Speaker:
her eighties now.
1390
00:48:28,610 --> 00:48:29,130
Speaker:
Yeah.
1391
00:48:29,130 --> 00:48:30,449
Speaker:
Oh my gosh.
1392
00:48:30,449 --> 00:48:33,889
Speaker:
She's trying to determine if she
has the power to smell other
1393
00:48:33,889 --> 00:48:39,409
Speaker:
diseases like Alzheimer's or
cancer and see if they can help.
1394
00:48:39,409 --> 00:48:45,510
Speaker:
If that can help them figure out
other diagnostic tools or other
1395
00:48:45,510 --> 00:48:47,730
Speaker:
causes of these disorders.
1396
00:48:47,730 --> 00:48:48,329
Speaker:
Wow.
1397
00:48:50,650 --> 00:48:55,099
Speaker:
Her husband's final words to her
were, You won't let this go.
1398
00:48:55,099 --> 00:48:56,420
Speaker:
You will do it, won't you?
1399
00:48:56,420 --> 00:48:58,019
Speaker:
You promise?
1400
00:48:58,019 --> 00:49:00,579
Speaker:
And she's definitely kept her
promise.
1401
00:49:00,579 --> 00:49:01,340
Speaker:
Yeah.
1402
00:49:01,340 --> 00:49:03,820
Speaker:
She sounds pretty amazing.
1403
00:49:03,820 --> 00:49:04,139
Speaker:
Yeah.
1404
00:49:04,139 --> 00:49:04,820
Speaker:
Honestly.
1405
00:49:04,820 --> 00:49:06,099
Speaker:
Yeah, totally.
1406
00:49:06,099 --> 00:49:08,480
Speaker:
And like I said, even to,
1407
00:49:08,480 --> 00:49:11,159
Speaker:
because, you know, she felt
1408
00:49:11,159 --> 00:49:11,880
Speaker:
crazy.
1409
00:49:11,880 --> 00:49:12,639
Speaker:
You know it.
1410
00:49:12,639 --> 00:49:14,559
Speaker:
And she was like, everybody and
1411
00:49:14,559 --> 00:49:16,320
Speaker:
herself were gaslighting her her
1412
00:49:16,320 --> 00:49:17,980
Speaker:
whole life telling her, no,
1413
00:49:17,980 --> 00:49:20,000
Speaker:
you're smelling this imaginary
1414
00:49:20,000 --> 00:49:20,559
Speaker:
smell.
1415
00:49:20,559 --> 00:49:23,400
Speaker:
I know no one else can smell it
like you would.
1416
00:49:23,400 --> 00:49:26,079
Speaker:
You would definitely question it
yourself.
1417
00:49:26,079 --> 00:49:26,599
Speaker:
Mhm.
1418
00:49:26,599 --> 00:49:26,880
Speaker:
Yeah.
1419
00:49:26,880 --> 00:49:28,079
Speaker:
Pretty incredible.
1420
00:49:28,079 --> 00:49:30,679
Speaker:
It's opened up this whole field
of.
1421
00:49:30,679 --> 00:49:31,000
Speaker:
Yeah.
1422
00:49:31,000 --> 00:49:32,360
Speaker:
That's awesome.
1423
00:49:32,360 --> 00:49:33,480
Speaker:
That's really cool.
1424
00:49:33,480 --> 00:49:35,280
Speaker:
Yeah, very, very cool.
1425
00:49:35,280 --> 00:49:38,239
Speaker:
Thank you for sharing that with
me.
1426
00:49:38,239 --> 00:49:39,280
Speaker:
Yep.
1427
00:49:39,280 --> 00:49:40,800
Speaker:
That's a that's like cutting
1428
00:49:40,800 --> 00:49:42,739
Speaker:
edge, some cutting edge shit
1429
00:49:42,739 --> 00:49:43,360
Speaker:
there.
1430
00:49:44,400 --> 00:49:49,619
Speaker:
Well, I fell down this very
smelly rabbit hole.
1431
00:49:49,619 --> 00:49:53,619
Speaker:
Tell me about the rabbit hole
you fell down this week.
1432
00:49:53,619 --> 00:49:58,659
Speaker:
Okay, so, as you know, I have no
time for anything, ever.
1433
00:49:58,659 --> 00:50:00,340
Speaker:
Because I have so much stuff
1434
00:50:00,340 --> 00:50:02,579
Speaker:
going on, so I don't get to fall
1435
00:50:02,579 --> 00:50:02,780
Speaker:
down.
1436
00:50:02,780 --> 00:50:05,219
Speaker:
Very many like rabbit holes on
1437
00:50:05,219 --> 00:50:07,340
Speaker:
my own, so I have to research my
1438
00:50:07,340 --> 00:50:08,420
Speaker:
rabbit holes.
1439
00:50:08,420 --> 00:50:09,019
Speaker:
Yeah.
1440
00:50:09,019 --> 00:50:11,039
Speaker:
From like something that I've
1441
00:50:11,039 --> 00:50:13,920
Speaker:
been interested in before or
1442
00:50:13,920 --> 00:50:16,179
Speaker:
I've seen, but I didn't really
1443
00:50:16,179 --> 00:50:18,019
Speaker:
research it much or it's
1444
00:50:18,019 --> 00:50:19,780
Speaker:
something like that I thought
1445
00:50:19,780 --> 00:50:21,500
Speaker:
about for the show, but it just
1446
00:50:21,500 --> 00:50:24,099
Speaker:
wasn't the right fit for our
1447
00:50:24,099 --> 00:50:24,460
Speaker:
show.
1448
00:50:24,460 --> 00:50:28,380
Speaker:
You purposefully research and
plan to fall down the rabbit
1449
00:50:28,380 --> 00:50:29,619
Speaker:
hole, is what you're saying?
1450
00:50:29,619 --> 00:50:35,960
Speaker:
Yeah, but the way that this
actually started was I saw
1451
00:50:35,960 --> 00:50:42,800
Speaker:
something in passing about the
exact amount of length about
1452
00:50:42,800 --> 00:50:47,519
Speaker:
marathons are okay and why they
are the length that they are.
1453
00:50:47,519 --> 00:50:51,320
Speaker:
Because they are twenty six
point two miles.
1454
00:50:51,320 --> 00:50:51,760
Speaker:
Okay.
1455
00:50:51,760 --> 00:50:55,480
Speaker:
I'm yeah, if I'm getting that
correctly.
1456
00:50:55,480 --> 00:50:59,280
Speaker:
And I was like, oh, let me so I,
1457
00:50:59,280 --> 00:51:00,880
Speaker:
I looked at that a little bit,
1458
00:51:00,880 --> 00:51:02,960
Speaker:
but then it triggered like
1459
00:51:02,960 --> 00:51:04,920
Speaker:
another memory of mine, of
1460
00:51:04,920 --> 00:51:06,199
Speaker:
something that I thought was
1461
00:51:06,199 --> 00:51:06,840
Speaker:
really wild.
1462
00:51:06,840 --> 00:51:10,099
Speaker:
But I will give you information
on marathon real quick because
1463
00:51:10,099 --> 00:51:12,440
Speaker:
it's pretty, pretty incredible.
1464
00:51:12,440 --> 00:51:15,639
Speaker:
In nineteen oh eight in the
1465
00:51:15,639 --> 00:51:21,210
Speaker:
Olympic Games in London, In the
1466
00:51:21,210 --> 00:51:21,710
Speaker:
course.
1467
00:51:21,710 --> 00:51:25,789
Speaker:
I believe it was twenty five
miles originally.
1468
00:51:25,789 --> 00:51:26,269
Speaker:
Okay.
1469
00:51:26,269 --> 00:51:33,650
Speaker:
But for this certain Olympics,
they extended it to accommodate
1470
00:51:33,650 --> 00:51:35,909
Speaker:
the British royal family.
1471
00:51:39,309 --> 00:51:42,070
Speaker:
Queen Alexandra requested that
1472
00:51:42,070 --> 00:51:44,150
Speaker:
the race start on the lawn of
1473
00:51:44,150 --> 00:51:48,550
Speaker:
the Windsor Castle and finish in
1474
00:51:48,550 --> 00:51:50,429
Speaker:
front of the Royal box at the
1475
00:51:50,429 --> 00:51:51,670
Speaker:
Olympic Stadium.
1476
00:51:51,670 --> 00:51:55,469
Speaker:
Oh, that distance just happened
1477
00:51:55,469 --> 00:51:57,570
Speaker:
to be twenty six point two
1478
00:51:57,570 --> 00:51:58,150
Speaker:
miles.
1479
00:51:58,150 --> 00:51:59,510
Speaker:
So we've just kept that ever
since.
1480
00:51:59,510 --> 00:52:01,269
Speaker:
And then we just stuck with
that.
1481
00:52:01,269 --> 00:52:01,590
Speaker:
Yeah.
1482
00:52:01,590 --> 00:52:02,750
Speaker:
That's funny right?
1483
00:52:02,750 --> 00:52:03,309
Speaker:
I like that.
1484
00:52:03,309 --> 00:52:04,389
Speaker:
Yeah, it's pretty cool.
1485
00:52:04,389 --> 00:52:05,429
Speaker:
Just one.
1486
00:52:05,429 --> 00:52:07,110
Speaker:
She's just a girl.
1487
00:52:07,110 --> 00:52:08,070
Speaker:
She's just a girl.
1488
00:52:08,070 --> 00:52:11,230
Speaker:
And she just wanted it to start
from her house.
1489
00:52:11,230 --> 00:52:13,590
Speaker:
And and ever since then.
1490
00:52:13,590 --> 00:52:17,070
Speaker:
And her stadium and her stadium.
1491
00:52:17,070 --> 00:52:18,039
Speaker:
Yeah.
1492
00:52:18,039 --> 00:52:18,559
Speaker:
Wow.
1493
00:52:18,559 --> 00:52:19,280
Speaker:
That's funny.
1494
00:52:19,280 --> 00:52:20,639
Speaker:
She's just a girl, and she
1495
00:52:20,639 --> 00:52:22,000
Speaker:
controlled how long marathons
1496
00:52:22,000 --> 00:52:22,199
Speaker:
are.
1497
00:52:22,199 --> 00:52:22,639
Speaker:
Forever.
1498
00:52:22,639 --> 00:52:23,239
Speaker:
Right?
1499
00:52:23,239 --> 00:52:24,119
Speaker:
For forever.
1500
00:52:24,119 --> 00:52:25,920
Speaker:
Yeah, exactly.
1501
00:52:25,920 --> 00:52:26,559
Speaker:
Um.
1502
00:52:26,559 --> 00:52:26,840
Speaker:
Wow.
1503
00:52:26,840 --> 00:52:32,420
Speaker:
So that led me to remember
something, and I was curious if
1504
00:52:32,420 --> 00:52:35,159
Speaker:
you've ever heard about.
1505
00:52:35,159 --> 00:52:36,159
Speaker:
Okay.
1506
00:52:36,159 --> 00:52:38,639
Speaker:
The nineteen oh four Olympics.
1507
00:52:38,639 --> 00:52:40,760
Speaker:
Not off the top of my head.
1508
00:52:40,760 --> 00:52:44,159
Speaker:
Okay, well, that's exciting for
you.
1509
00:52:44,159 --> 00:52:45,760
Speaker:
I can see it in your face.
1510
00:52:45,760 --> 00:52:51,139
Speaker:
Let me just tell you a little
bit about the wild and crazy
1511
00:52:51,139 --> 00:52:55,280
Speaker:
shit that went on in the
nineteen oh four Olympics.
1512
00:52:55,280 --> 00:52:57,800
Speaker:
I'm so excited in Saint Louis.
1513
00:52:57,800 --> 00:52:59,920
Speaker:
the first weird thing about it
1514
00:52:59,920 --> 00:53:03,039
Speaker:
is that it lasted like six
1515
00:53:03,039 --> 00:53:04,679
Speaker:
months.
1516
00:53:04,679 --> 00:53:05,519
Speaker:
The Olympics.
1517
00:53:05,519 --> 00:53:06,599
Speaker:
Yes.
1518
00:53:06,599 --> 00:53:10,139
Speaker:
It started in like March or
1519
00:53:10,139 --> 00:53:12,159
Speaker:
April maybe, and finished in
1520
00:53:12,159 --> 00:53:13,000
Speaker:
November.
1521
00:53:13,000 --> 00:53:14,940
Speaker:
doesn't seem normal, right?
1522
00:53:14,940 --> 00:53:15,699
Speaker:
Exactly.
1523
00:53:15,699 --> 00:53:16,980
Speaker:
So that's not normal.
1524
00:53:16,980 --> 00:53:19,340
Speaker:
The Olympics have been going on
for a long time, right?
1525
00:53:19,340 --> 00:53:20,739
Speaker:
Like hundreds of years.
1526
00:53:20,739 --> 00:53:21,099
Speaker:
Yeah.
1527
00:53:21,099 --> 00:53:26,260
Speaker:
I think it kind of goes back to
like Romans, right?
1528
00:53:26,260 --> 00:53:27,400
Speaker:
I don't know, let's move on.
1529
00:53:27,400 --> 00:53:27,960
Speaker:
Okay.
1530
00:53:27,960 --> 00:53:29,139
Speaker:
Anyway, this is a rabbit hole.
1531
00:53:29,139 --> 00:53:30,019
Speaker:
We don't have time for that.
1532
00:53:30,019 --> 00:53:32,500
Speaker:
Yeah, we don't have time to
research this.
1533
00:53:32,500 --> 00:53:33,340
Speaker:
Okay.
1534
00:53:33,340 --> 00:53:35,940
Speaker:
I'm gonna start with Who who was
1535
00:53:35,940 --> 00:53:37,719
Speaker:
there and who was, able to
1536
00:53:37,719 --> 00:53:38,619
Speaker:
compete.
1537
00:53:38,619 --> 00:53:39,139
Speaker:
Okay.
1538
00:53:39,139 --> 00:53:43,099
Speaker:
Okay, so Travel to Saint Louis
1539
00:53:43,099 --> 00:53:45,159
Speaker:
was difficult for many
1540
00:53:45,159 --> 00:53:47,039
Speaker:
international athletes.
1541
00:53:47,039 --> 00:53:49,619
Speaker:
and also political tensions
1542
00:53:49,619 --> 00:53:52,000
Speaker:
abroad also kind of limited
1543
00:53:52,000 --> 00:53:53,900
Speaker:
participation.
1544
00:53:53,900 --> 00:53:56,860
Speaker:
So as a result of that, the
1545
00:53:56,860 --> 00:53:59,139
Speaker:
games had far less international
1546
00:53:59,139 --> 00:54:01,300
Speaker:
representation.
1547
00:54:01,300 --> 00:54:06,780
Speaker:
And out of roughly six hundred
competitors, five hundred and
1548
00:54:06,780 --> 00:54:08,179
Speaker:
eighty were Americans.
1549
00:54:08,179 --> 00:54:09,579
Speaker:
No.
1550
00:54:09,579 --> 00:54:10,260
Speaker:
Yeah.
1551
00:54:11,619 --> 00:54:14,340
Speaker:
They couldn't get anybody from
other countries.
1552
00:54:14,340 --> 00:54:17,019
Speaker:
This was the American Olympics.
1553
00:54:18,539 --> 00:54:19,900
Speaker:
Oh my God.
1554
00:54:19,900 --> 00:54:20,980
Speaker:
Oh, God.
1555
00:54:20,980 --> 00:54:23,019
Speaker:
Wouldn't that be funny if that
happened now?
1556
00:54:23,019 --> 00:54:24,460
Speaker:
So funny because the Olympics
1557
00:54:24,460 --> 00:54:25,880
Speaker:
are going to be in LA in twenty
1558
00:54:25,880 --> 00:54:26,619
Speaker:
twenty eight.
1559
00:54:26,619 --> 00:54:27,260
Speaker:
Oh, true.
1560
00:54:27,260 --> 00:54:27,980
Speaker:
Yeah.
1561
00:54:27,980 --> 00:54:29,380
Speaker:
Wouldn't that be hilarious if
1562
00:54:29,380 --> 00:54:30,659
Speaker:
everyone was like, we're not
1563
00:54:30,659 --> 00:54:31,260
Speaker:
coming?
1564
00:54:31,260 --> 00:54:31,860
Speaker:
I mean.
1565
00:54:31,860 --> 00:54:34,659
Speaker:
It just sounded like so familiar
the way you said it.
1566
00:54:34,659 --> 00:54:36,780
Speaker:
I was like, this could be
happening right now.
1567
00:54:39,019 --> 00:54:40,780
Speaker:
Okay, so the marathon.
1568
00:54:41,780 --> 00:54:46,659
Speaker:
The race was batshit okay.
1569
00:54:46,659 --> 00:54:52,280
Speaker:
From what I have read and looked
into, it was dusty, dirty.
1570
00:54:52,280 --> 00:54:55,099
Speaker:
There were cars still like
1571
00:54:55,099 --> 00:54:57,539
Speaker:
exhaust fumes, everything was
1572
00:54:57,539 --> 00:54:58,699
Speaker:
freaking insane.
1573
00:54:58,699 --> 00:55:01,400
Speaker:
So, the race was run in extreme
1574
00:55:01,400 --> 00:55:04,300
Speaker:
heat on dusty roads with no
1575
00:55:04,300 --> 00:55:05,559
Speaker:
water stations.
1576
00:55:05,559 --> 00:55:10,699
Speaker:
No. They're gonna kill these
American Olympians.
1577
00:55:10,699 --> 00:55:14,059
Speaker:
Only fourteen of the thirty two
runners finished.
1578
00:55:14,059 --> 00:55:14,860
Speaker:
Oh my God.
1579
00:55:14,860 --> 00:55:15,380
Speaker:
Yeah.
1580
00:55:15,380 --> 00:55:17,619
Speaker:
And then the guy that ended up
winning.
1581
00:55:17,619 --> 00:55:20,179
Speaker:
His name was, Frederick Lortz.
1582
00:55:20,179 --> 00:55:23,659
Speaker:
he had actually written in a car
for eleven.
1583
00:55:25,340 --> 00:55:26,699
Speaker:
Shut up!
1584
00:55:27,739 --> 00:55:31,059
Speaker:
He had ridden in a car for
eleven miles.
1585
00:55:31,059 --> 00:55:34,980
Speaker:
No wonder he won and jumped back
out at the end.
1586
00:55:36,099 --> 00:55:38,019
Speaker:
Oh, wow.
1587
00:55:38,019 --> 00:55:40,900
Speaker:
But they still, like, gave him.
1588
00:55:40,900 --> 00:55:44,179
Speaker:
No no no no no. Okay, let me
tell you about the second one.
1589
00:55:44,179 --> 00:55:45,059
Speaker:
That one.
1590
00:55:45,059 --> 00:55:48,179
Speaker:
Oh, his name is, um, Thomas
Hicks.
1591
00:55:48,179 --> 00:55:54,500
Speaker:
And he was basically collapsing
almost to the finish line.
1592
00:55:54,500 --> 00:56:00,579
Speaker:
Oh. Because he was given by his
trainers as a stimulant.
1593
00:56:00,579 --> 00:56:01,179
Speaker:
Oh, God.
1594
00:56:01,179 --> 00:56:01,940
Speaker:
I'm nervous.
1595
00:56:01,940 --> 00:56:06,139
Speaker:
Strychnine and brandy and egg
whites.
1596
00:56:06,139 --> 00:56:07,099
Speaker:
Excuse me.
1597
00:56:08,260 --> 00:56:09,860
Speaker:
That's not a stimulant.
1598
00:56:09,860 --> 00:56:15,380
Speaker:
Oh, well, apparently it is
brandy and running that won him
1599
00:56:15,380 --> 00:56:17,260
Speaker:
that race, didn't it?
1600
00:56:17,260 --> 00:56:21,389
Speaker:
That reminds me of those weird
marathons where you, like, chug
1601
00:56:21,389 --> 00:56:24,230
Speaker:
a beer or eat a donut every so
often or something.
1602
00:56:24,230 --> 00:56:25,150
Speaker:
Have you heard of those?
1603
00:56:25,150 --> 00:56:26,590
Speaker:
Yeah, yeah, yeah.
1604
00:56:26,590 --> 00:56:27,710
Speaker:
That's true.
1605
00:56:27,710 --> 00:56:28,070
Speaker:
Yeah.
1606
00:56:28,070 --> 00:56:30,510
Speaker:
I had a shot of brandy.
1607
00:56:30,510 --> 00:56:30,949
Speaker:
Brandy.
1608
00:56:30,949 --> 00:56:31,989
Speaker:
Every couple of miles.
1609
00:56:31,989 --> 00:56:33,030
Speaker:
That'll help.
1610
00:56:33,030 --> 00:56:34,150
Speaker:
Oh my God.
1611
00:56:34,150 --> 00:56:35,070
Speaker:
Oh my God.
1612
00:56:35,070 --> 00:56:36,150
Speaker:
I mean, it did.
1613
00:56:36,150 --> 00:56:37,550
Speaker:
It worked, I guess.
1614
00:56:37,550 --> 00:56:39,590
Speaker:
I suppose so.
1615
00:56:39,590 --> 00:56:44,630
Speaker:
So, um uh, so imagine they did
1616
00:56:44,630 --> 00:56:45,750
Speaker:
that now at the Olympics, just
1617
00:56:45,750 --> 00:56:46,630
Speaker:
like in the middle, they were
1618
00:56:46,630 --> 00:56:48,030
Speaker:
like, let me have a shot really
1619
00:56:48,030 --> 00:56:48,590
Speaker:
quick.
1620
00:56:50,550 --> 00:56:53,409
Speaker:
Okay, I got, I got a new, event.
1621
00:56:53,409 --> 00:56:54,409
Speaker:
Okay.
1622
00:56:54,409 --> 00:56:58,210
Speaker:
It's called plunge for distance.
1623
00:56:58,210 --> 00:57:01,289
Speaker:
Plunge for distance.
1624
00:57:01,289 --> 00:57:02,210
Speaker:
That's right.
1625
00:57:03,369 --> 00:57:08,849
Speaker:
So what, what you do is please
tell me it's not a plunger.
1626
00:57:08,849 --> 00:57:11,730
Speaker:
You dive into the water, okay?
1627
00:57:11,730 --> 00:57:16,550
Speaker:
And you have to float motionless
under the water.
1628
00:57:16,550 --> 00:57:20,969
Speaker:
And depending on how long you
stayed under and how far you
1629
00:57:20,969 --> 00:57:22,150
Speaker:
drifted, you won.
1630
00:57:22,150 --> 00:57:24,070
Speaker:
Oh, okay.
1631
00:57:24,070 --> 00:57:24,789
Speaker:
Mhm.
1632
00:57:27,710 --> 00:57:28,469
Speaker:
Interesting.
1633
00:57:28,469 --> 00:57:30,389
Speaker:
I'm a winner in nineteen oh
four.
1634
00:57:30,389 --> 00:57:32,670
Speaker:
he went sixty feet without
moving.
1635
00:57:32,670 --> 00:57:35,630
Speaker:
Oh, so that's good.
1636
00:57:35,630 --> 00:57:36,469
Speaker:
Good for him.
1637
00:57:36,469 --> 00:57:39,909
Speaker:
Ah, I thought that was pretty
great.
1638
00:57:39,909 --> 00:57:40,630
Speaker:
Okay.
1639
00:57:41,630 --> 00:57:43,070
Speaker:
Yeah.
1640
00:57:43,070 --> 00:57:48,469
Speaker:
in the eighties, there was an
Olympic sport of ski dancing,
1641
00:57:48,469 --> 00:57:52,389
Speaker:
and it was like they would do,
like, flips and tricks, like ice
1642
00:57:52,389 --> 00:57:54,710
Speaker:
skating, but they were on skis.
1643
00:57:54,710 --> 00:57:55,429
Speaker:
That's cool.
1644
00:57:55,429 --> 00:57:55,789
Speaker:
Yeah.
1645
00:57:55,789 --> 00:57:56,750
Speaker:
Yeah.
1646
00:57:56,750 --> 00:58:00,550
Speaker:
I forgot to mention that it was
also this.
1647
00:58:00,550 --> 00:58:02,750
Speaker:
What made it even more wild?
1648
00:58:02,750 --> 00:58:04,250
Speaker:
the nineteen oh four Olympics.
1649
00:58:04,250 --> 00:58:05,530
Speaker:
The nineteen oh four Olympics.
1650
00:58:05,530 --> 00:58:09,889
Speaker:
It was in conjunction with the
World's Fair.
1651
00:58:09,889 --> 00:58:13,530
Speaker:
Oh, wait, wait, wasn't the world
1652
00:58:13,530 --> 00:58:14,610
Speaker:
fair in, like, Chicago or
1653
00:58:14,610 --> 00:58:15,289
Speaker:
something?
1654
00:58:15,289 --> 00:58:16,610
Speaker:
Not in nineteen oh four.
1655
00:58:16,610 --> 00:58:19,489
Speaker:
Oh, that was another one that we
talked about.
1656
00:58:19,489 --> 00:58:20,849
Speaker:
Another one that I nineteen oh
eight.
1657
00:58:20,849 --> 00:58:22,170
Speaker:
That's what I feel.
1658
00:58:22,170 --> 00:58:28,449
Speaker:
It feels like nineteen oh eight
to me that maybe someone please
1659
00:58:28,449 --> 00:58:31,170
Speaker:
correct us in the comments and
tell us her wrong kind of right,
1660
00:58:31,170 --> 00:58:33,210
Speaker:
but like not.
1661
00:58:33,210 --> 00:58:35,769
Speaker:
Um, so.
1662
00:58:37,730 --> 00:58:46,210
Speaker:
The, the one thing that I heard
about way back in the day about
1663
00:58:46,210 --> 00:58:53,360
Speaker:
this was since it was also the
world's fair and, They had, uh,
1664
00:58:53,360 --> 00:58:54,900
Speaker:
how shall I say?
1665
00:58:56,860 --> 00:59:02,019
Speaker:
Enclosed displays of, um,
indigenous peoples.
1666
00:59:02,019 --> 00:59:04,980
Speaker:
Oh, you know what?
1667
00:59:04,980 --> 00:59:09,340
Speaker:
Enclosed displays of indigenous.
1668
00:59:09,340 --> 00:59:14,820
Speaker:
Oh. I hate that a lot.
1669
00:59:14,820 --> 00:59:16,659
Speaker:
I hate that a lot.
1670
00:59:16,659 --> 00:59:17,699
Speaker:
Wow.
1671
00:59:17,699 --> 00:59:23,840
Speaker:
so organizers had indigenous
people and other groups who were
1672
00:59:23,840 --> 00:59:25,920
Speaker:
part of like the.
1673
00:59:25,920 --> 00:59:26,840
Speaker:
I'm sorry.
1674
00:59:26,840 --> 00:59:30,239
Speaker:
Um, I, I didn't say the right
words.
1675
00:59:30,239 --> 00:59:34,280
Speaker:
They were called cultural
exhibits.
1676
00:59:34,280 --> 00:59:35,880
Speaker:
Oh, that's so much better.
1677
00:59:35,880 --> 00:59:36,400
Speaker:
Yeah, yeah.
1678
00:59:36,400 --> 00:59:37,039
Speaker:
That's fine.
1679
00:59:37,039 --> 00:59:39,280
Speaker:
Then that was at the World's
Fair.
1680
00:59:39,280 --> 00:59:42,179
Speaker:
So they thought, oh, cool cool,
cool.
1681
00:59:42,179 --> 00:59:45,019
Speaker:
ones also had them compete in
the Olympics.
1682
00:59:45,019 --> 00:59:46,619
Speaker:
Oh, God.
1683
00:59:46,619 --> 00:59:49,380
Speaker:
Or against their will?
1684
00:59:49,380 --> 00:59:50,940
Speaker:
I don't know.
1685
00:59:50,940 --> 00:59:51,860
Speaker:
I don't know.
1686
00:59:51,860 --> 00:59:52,380
Speaker:
Wow.
1687
00:59:52,380 --> 00:59:55,860
Speaker:
What was and wasn't against
their will like I do know.
1688
00:59:55,860 --> 00:59:58,099
Speaker:
I'm assuming it's against their
will like that.
1689
00:59:58,099 --> 00:59:59,699
Speaker:
They had no say in it at least.
1690
00:59:59,699 --> 01:00:02,019
Speaker:
Probably not a whole lot of say.
1691
01:00:02,019 --> 01:00:02,860
Speaker:
I would imagine.
1692
01:00:02,860 --> 01:00:05,199
Speaker:
But I also think that a lot of
1693
01:00:05,199 --> 01:00:07,219
Speaker:
the indigenous peoples that were
1694
01:00:07,219 --> 01:00:10,139
Speaker:
in these type of exhibits and
1695
01:00:10,139 --> 01:00:11,340
Speaker:
stuff, because this is not the
1696
01:00:11,340 --> 01:00:13,059
Speaker:
only one.
1697
01:00:13,059 --> 01:00:18,920
Speaker:
I think they're coerced in some
way, shape or form or fashion,
1698
01:00:18,920 --> 01:00:19,860
Speaker:
like, you know.
1699
01:00:19,860 --> 01:00:21,699
Speaker:
Oh, God help you.
1700
01:00:21,699 --> 01:00:23,420
Speaker:
I'll feed you.
1701
01:00:23,420 --> 01:00:24,699
Speaker:
So yuck.
1702
01:00:24,699 --> 01:00:27,300
Speaker:
White humans, white people suck.
1703
01:00:27,300 --> 01:00:29,260
Speaker:
We do like we're just really
bad.
1704
01:00:29,260 --> 01:00:29,980
Speaker:
Yep.
1705
01:00:29,980 --> 01:00:30,860
Speaker:
Historically.
1706
01:00:30,860 --> 01:00:32,980
Speaker:
So. And organizers did that
1707
01:00:32,980 --> 01:00:35,019
Speaker:
because they wanted to compare
1708
01:00:35,019 --> 01:00:37,219
Speaker:
the athletic ability between
1709
01:00:37,219 --> 01:00:41,010
Speaker:
cultures And, Oh, yeah, I hate
1710
01:00:41,010 --> 01:00:41,610
Speaker:
it.
1711
01:00:43,369 --> 01:00:48,050
Speaker:
And as you can imagine, it's
widely criticized today.
1712
01:00:48,050 --> 01:00:50,210
Speaker:
Well, I hope so.
1713
01:00:50,210 --> 01:00:52,170
Speaker:
The rabbit holes are supposed to
be fun.
1714
01:00:52,170 --> 01:00:54,769
Speaker:
I know, I don't like this.
1715
01:00:54,769 --> 01:00:55,730
Speaker:
This is so fucked.
1716
01:00:55,730 --> 01:00:56,889
Speaker:
It's really fucked.
1717
01:00:56,889 --> 01:00:58,369
Speaker:
It's really, really, really
fucked.
1718
01:00:58,369 --> 01:00:59,889
Speaker:
That's devastating.
1719
01:00:59,889 --> 01:01:00,289
Speaker:
Yeah.
1720
01:01:00,289 --> 01:01:01,849
Speaker:
So sorry about that rabbit hole.
1721
01:01:01,849 --> 01:01:02,530
Speaker:
Sheesh.
1722
01:01:02,530 --> 01:01:09,050
Speaker:
But needless to say, the
nineteen oh four Olympics were a
1723
01:01:09,050 --> 01:01:11,650
Speaker:
complete and utter shit show.
1724
01:01:11,650 --> 01:01:16,690
Speaker:
Yeah, starting from how freaking
long they were and how they were
1725
01:01:16,690 --> 01:01:18,329
Speaker:
not very global.
1726
01:01:19,530 --> 01:01:21,289
Speaker:
They were way too long.
1727
01:01:21,289 --> 01:01:22,050
Speaker:
You add in the.
1728
01:01:22,050 --> 01:01:25,190
Speaker:
human rights atrocities, right?
1729
01:01:25,190 --> 01:01:26,590
Speaker:
You throw that in there.
1730
01:01:28,949 --> 01:01:32,190
Speaker:
I thought this was going to be
about the length of a marathon.
1731
01:01:32,190 --> 01:01:36,650
Speaker:
I told you about the length of a
marathon that wasn't related to
1732
01:01:36,650 --> 01:01:38,090
Speaker:
this at all.
1733
01:01:38,090 --> 01:01:41,489
Speaker:
I mean, so wait, I have one
question about that, though.
1734
01:01:41,489 --> 01:01:42,130
Speaker:
Okay.
1735
01:01:42,130 --> 01:01:43,730
Speaker:
This was the nineteen oh four.
1736
01:01:43,730 --> 01:01:44,969
Speaker:
They did the weird marathon
1737
01:01:44,969 --> 01:01:46,250
Speaker:
length in nineteen oh eight,
1738
01:01:46,250 --> 01:01:47,170
Speaker:
right?
1739
01:01:47,170 --> 01:01:47,809
Speaker:
Yeah.
1740
01:01:47,809 --> 01:01:49,650
Speaker:
So did they have a marathon in
nineteen oh four?
1741
01:01:49,650 --> 01:01:50,849
Speaker:
Was it twenty five miles?
1742
01:01:50,849 --> 01:01:55,730
Speaker:
I don't know how long it was,
but I do know that the almost
1743
01:01:55,730 --> 01:02:00,809
Speaker:
winner rode in a car for eleven
miles of it.
1744
01:02:00,809 --> 01:02:03,489
Speaker:
Oh gosh, there's so much more.
1745
01:02:03,489 --> 01:02:05,530
Speaker:
I encourage people to look up
1746
01:02:05,530 --> 01:02:06,889
Speaker:
some of the events and how
1747
01:02:06,889 --> 01:02:08,570
Speaker:
things played out when they were
1748
01:02:08,570 --> 01:02:09,369
Speaker:
there.
1749
01:02:09,369 --> 01:02:13,570
Speaker:
Oh my gosh, it was just, I'm
like, who planned this?
1750
01:02:13,570 --> 01:02:14,889
Speaker:
What are you doing?
1751
01:02:14,889 --> 01:02:15,730
Speaker:
Wow.
1752
01:02:15,730 --> 01:02:16,969
Speaker:
Yeah.
1753
01:02:16,969 --> 01:02:18,409
Speaker:
So that's fun.
1754
01:02:18,409 --> 01:02:19,730
Speaker:
Not fun at all.
1755
01:02:19,730 --> 01:02:21,610
Speaker:
No, it's not that fun.
1756
01:02:21,610 --> 01:02:24,989
Speaker:
This is what I'm talking about
when people are like, oh, I was
1757
01:02:24,989 --> 01:02:26,710
Speaker:
born in the wrong time.
1758
01:02:26,710 --> 01:02:29,150
Speaker:
Like I wish I was born in the
1759
01:02:29,150 --> 01:02:30,710
Speaker:
olden days when everything was
1760
01:02:30,710 --> 01:02:31,070
Speaker:
good.
1761
01:02:31,070 --> 01:02:32,309
Speaker:
Everything was not good.
1762
01:02:32,309 --> 01:02:33,550
Speaker:
Yeah, things were not good.
1763
01:02:33,550 --> 01:02:37,849
Speaker:
You see things like that and
you're like, oh no, no, no,
1764
01:02:37,849 --> 01:02:39,230
Speaker:
these are not good now either.
1765
01:02:39,230 --> 01:02:40,750
Speaker:
But things were not good before.
1766
01:02:40,750 --> 01:02:41,349
Speaker:
All right.
1767
01:02:41,349 --> 01:02:45,230
Speaker:
Well, that being said, we will
be back.
1768
01:02:45,230 --> 01:02:45,590
Speaker:
Wait.
1769
01:02:45,590 --> 01:02:46,269
Speaker:
One more thing.
1770
01:02:46,269 --> 01:02:46,909
Speaker:
Yeah.
1771
01:02:46,909 --> 01:02:50,289
Speaker:
I don't know if anybody watched
the Olympics a few weeks ago or
1772
01:02:50,289 --> 01:02:51,349
Speaker:
whenever it was.
1773
01:02:51,349 --> 01:02:55,650
Speaker:
but I just want to talk about a
couple of, sports that I think
1774
01:02:55,650 --> 01:02:57,329
Speaker:
are totally insane.
1775
01:02:57,329 --> 01:02:58,010
Speaker:
Okay.
1776
01:02:58,010 --> 01:02:59,250
Speaker:
Oh, I'll play this game.
1777
01:02:59,250 --> 01:02:59,690
Speaker:
Okay.
1778
01:02:59,690 --> 01:03:00,170
Speaker:
Yeah.
1779
01:03:00,170 --> 01:03:01,309
Speaker:
because I don't usually watch.
1780
01:03:01,309 --> 01:03:02,150
Speaker:
I love the Olympics.
1781
01:03:02,150 --> 01:03:05,329
Speaker:
That's one thing about me is I
get really into sports,
1782
01:03:05,329 --> 01:03:07,030
Speaker:
particularly for the Olympics.
1783
01:03:07,030 --> 01:03:08,909
Speaker:
Yeah, but mostly I like the
summer Olympics.
1784
01:03:08,909 --> 01:03:10,210
Speaker:
I like I don't care about.
1785
01:03:10,210 --> 01:03:12,530
Speaker:
I don't get patriotic about it
like I do watch.
1786
01:03:12,530 --> 01:03:16,050
Speaker:
I like the American gymnasts and
ice skaters and stuff, but
1787
01:03:16,050 --> 01:03:17,849
Speaker:
honestly, I don't care who wins.
1788
01:03:17,849 --> 01:03:19,849
Speaker:
Like, I'm not like gung ho for
1789
01:03:19,849 --> 01:03:21,130
Speaker:
America to get the most medals
1790
01:03:21,130 --> 01:03:21,690
Speaker:
or anything.
1791
01:03:21,690 --> 01:03:24,650
Speaker:
I just like the Olympics a lot.
1792
01:03:24,650 --> 01:03:28,530
Speaker:
And now you can watch all of the
Olympics on demand.
1793
01:03:28,530 --> 01:03:28,929
Speaker:
Practically.
1794
01:03:28,929 --> 01:03:29,809
Speaker:
You can watch anything.
1795
01:03:29,809 --> 01:03:30,289
Speaker:
Yeah.
1796
01:03:30,289 --> 01:03:32,909
Speaker:
So starting in the Summer
Olympics a couple of years ago,
1797
01:03:32,909 --> 01:03:33,889
Speaker:
I got really into it.
1798
01:03:33,889 --> 01:03:34,889
Speaker:
I watched a bunch of wild
1799
01:03:34,889 --> 01:03:36,170
Speaker:
things, and this is the first
1800
01:03:36,170 --> 01:03:38,010
Speaker:
time I've really been into the
1801
01:03:38,010 --> 01:03:39,010
Speaker:
Winter Olympics.
1802
01:03:39,010 --> 01:03:40,210
Speaker:
Yeah, so I did.
1803
01:03:40,210 --> 01:03:40,849
Speaker:
Me too.
1804
01:03:40,849 --> 01:03:43,250
Speaker:
I even know a lot of these weird
sports.
1805
01:03:43,250 --> 01:03:43,690
Speaker:
Like.
1806
01:03:43,690 --> 01:03:44,369
Speaker:
Yeah.
1807
01:03:44,369 --> 01:03:46,050
Speaker:
Like skeleton.
1808
01:03:46,050 --> 01:03:47,050
Speaker:
Have you ever heard of that?
1809
01:03:47,050 --> 01:03:49,170
Speaker:
Oh, I am very familiar.
1810
01:03:49,170 --> 01:03:50,889
Speaker:
What the hell?
1811
01:03:50,889 --> 01:03:52,929
Speaker:
There's skeletons too fast.
1812
01:03:52,929 --> 01:03:55,170
Speaker:
They're going way too fast.
1813
01:03:55,170 --> 01:03:57,210
Speaker:
And head first.
1814
01:03:57,210 --> 01:03:58,489
Speaker:
Face first.
1815
01:03:58,489 --> 01:03:58,969
Speaker:
Yep.
1816
01:03:58,969 --> 01:03:59,849
Speaker:
It's too much.
1817
01:03:59,849 --> 01:04:04,730
Speaker:
What's the one that's like
skiing, but also rifles.
1818
01:04:04,730 --> 01:04:07,099
Speaker:
Oh, I saw that one.
1819
01:04:07,099 --> 01:04:09,019
Speaker:
It's like mountaineering or
something.
1820
01:04:09,019 --> 01:04:09,940
Speaker:
I saw that one.
1821
01:04:09,940 --> 01:04:12,980
Speaker:
Was not expecting that
combination up in the mountains.
1822
01:04:12,980 --> 01:04:15,300
Speaker:
And I was like, are those guns?
1823
01:04:15,300 --> 01:04:18,539
Speaker:
Yeah yeah yeah yeah, yeah.
1824
01:04:18,539 --> 01:04:22,780
Speaker:
Curling is still obviously a
whole mystery to me.
1825
01:04:22,780 --> 01:04:25,659
Speaker:
It is a mystery and people love
it.
1826
01:04:25,659 --> 01:04:27,219
Speaker:
People love it so much.
1827
01:04:27,219 --> 01:04:28,539
Speaker:
They love it so much.
1828
01:04:28,539 --> 01:04:29,980
Speaker:
I think my biggest question,
1829
01:04:29,980 --> 01:04:32,139
Speaker:
because it's so mysterious, my
1830
01:04:32,139 --> 01:04:35,079
Speaker:
biggest question is, where the
1831
01:04:35,079 --> 01:04:38,340
Speaker:
fuck do you go to learn fucking
1832
01:04:38,340 --> 01:04:40,059
Speaker:
curling?
1833
01:04:40,059 --> 01:04:41,300
Speaker:
Hell if I know.
1834
01:04:41,300 --> 01:04:43,659
Speaker:
Like, who goes, you know what I
1835
01:04:43,659 --> 01:04:45,179
Speaker:
think I'm thinking about getting
1836
01:04:45,179 --> 01:04:46,300
Speaker:
into curling.
1837
01:04:46,300 --> 01:04:47,659
Speaker:
I'm gonna go down the street.
1838
01:04:47,659 --> 01:04:50,019
Speaker:
Well, I learned something when I
was watching the Olympics.
1839
01:04:50,019 --> 01:04:53,059
Speaker:
I don't know about curling, but
I know that for things like
1840
01:04:53,059 --> 01:04:58,099
Speaker:
skeleton and the other, um,
types and everything.
1841
01:04:58,099 --> 01:04:58,699
Speaker:
Sports.
1842
01:04:58,699 --> 01:04:59,219
Speaker:
Yeah.
1843
01:04:59,219 --> 01:05:04,920
Speaker:
Um, you don't start off in that
sport because there are so few.
1844
01:05:04,920 --> 01:05:07,840
Speaker:
facilities that have tracks.
1845
01:05:07,840 --> 01:05:11,440
Speaker:
There's only several in the
world, so you don't just start
1846
01:05:11,440 --> 01:05:16,320
Speaker:
from age five and say, I'm going
to go be a skeleton.
1847
01:05:16,320 --> 01:05:17,599
Speaker:
I'm going to be a loser.
1848
01:05:17,599 --> 01:05:22,480
Speaker:
You know, you actually most of
them start in track and field.
1849
01:05:22,480 --> 01:05:26,639
Speaker:
And then right at some point
they transfer to one of these
1850
01:05:26,639 --> 01:05:28,679
Speaker:
other specialized sports.
1851
01:05:28,679 --> 01:05:29,360
Speaker:
Yeah.
1852
01:05:29,360 --> 01:05:32,199
Speaker:
In their career, I think I may
have heard that a little bit.
1853
01:05:32,199 --> 01:05:33,800
Speaker:
So maybe start off doing
1854
01:05:33,800 --> 01:05:35,840
Speaker:
something else and then it's
1855
01:05:35,840 --> 01:05:36,360
Speaker:
just weird.
1856
01:05:36,360 --> 01:05:38,639
Speaker:
You take your crack at curling.
1857
01:05:38,639 --> 01:05:39,559
Speaker:
For some reason.
1858
01:05:39,559 --> 01:05:43,880
Speaker:
So what other ones do you not
understand being a sport?
1859
01:05:43,880 --> 01:05:45,199
Speaker:
Do you have any other ones?
1860
01:05:45,199 --> 01:05:47,360
Speaker:
I also think some of there's too
1861
01:05:47,360 --> 01:05:49,639
Speaker:
many of the I'm on a snowboard
1862
01:05:49,639 --> 01:05:51,380
Speaker:
or I'm on skis and I jump real
1863
01:05:51,380 --> 01:05:52,320
Speaker:
big.
1864
01:05:52,320 --> 01:05:53,320
Speaker:
There's too many.
1865
01:05:53,320 --> 01:05:54,760
Speaker:
Like we don't need all of the.
1866
01:05:54,760 --> 01:05:57,880
Speaker:
Like, we could just have a
couple of those, you know.
1867
01:05:57,880 --> 01:05:58,280
Speaker:
Sorry.
1868
01:05:58,280 --> 01:06:02,139
Speaker:
And I will die on this snow
covered hill.
1869
01:06:02,139 --> 01:06:02,900
Speaker:
Okay.
1870
01:06:04,300 --> 01:06:07,179
Speaker:
The what I call we.
1871
01:06:07,179 --> 01:06:08,900
Speaker:
It's not a sport.
1872
01:06:08,900 --> 01:06:10,139
Speaker:
Are you talking about ski
jumping?
1873
01:06:10,139 --> 01:06:11,900
Speaker:
Where they go, they just go.
1874
01:06:11,900 --> 01:06:12,460
Speaker:
Yes.
1875
01:06:12,460 --> 01:06:13,940
Speaker:
Like a flying squirrel.
1876
01:06:13,940 --> 01:06:14,260
Speaker:
Yes.
1877
01:06:14,260 --> 01:06:16,300
Speaker:
All they do is go off a big
1878
01:06:16,300 --> 01:06:18,360
Speaker:
cliff and pose like a flying
1879
01:06:18,360 --> 01:06:19,260
Speaker:
squirrel.
1880
01:06:19,260 --> 01:06:21,219
Speaker:
And that's supposed to be
impressive.
1881
01:06:21,219 --> 01:06:23,539
Speaker:
You heard about the penis
injections in that sport, right?
1882
01:06:23,539 --> 01:06:26,860
Speaker:
No. Okay, we're going on a
rabbit hole inside the rabbit
1883
01:06:26,860 --> 01:06:27,539
Speaker:
hole right now.
1884
01:06:27,539 --> 01:06:29,699
Speaker:
But really quickly.
1885
01:06:29,699 --> 01:06:31,219
Speaker:
Oh, really quickly.
1886
01:06:31,219 --> 01:06:31,900
Speaker:
And ski jumping.
1887
01:06:31,900 --> 01:06:32,860
Speaker:
That's the sport you're talking
about.
1888
01:06:32,860 --> 01:06:33,380
Speaker:
Where they go.
1889
01:06:33,380 --> 01:06:33,900
Speaker:
We.
1890
01:06:35,059 --> 01:06:35,739
Speaker:
Yeah.
1891
01:06:35,739 --> 01:06:38,579
Speaker:
There are like many jumping
1892
01:06:38,579 --> 01:06:40,059
Speaker:
sports in the Olympics, but this
1893
01:06:40,059 --> 01:06:41,440
Speaker:
one in particular, they do that
1894
01:06:41,440 --> 01:06:42,619
Speaker:
motion right.
1895
01:06:42,619 --> 01:06:43,860
Speaker:
They're not doing a trick
really.
1896
01:06:43,860 --> 01:06:46,300
Speaker:
They're just going for distance
1897
01:06:46,300 --> 01:06:49,860
Speaker:
and apparently a little bit of
1898
01:06:49,860 --> 01:06:51,739
Speaker:
extra fabric in your suit,
1899
01:06:51,739 --> 01:06:54,260
Speaker:
particularly in the front
1900
01:06:54,260 --> 01:06:55,820
Speaker:
region.
1901
01:06:55,820 --> 01:06:56,179
Speaker:
Huh.
1902
01:06:56,179 --> 01:06:58,719
Speaker:
Um, if you have just a little
1903
01:06:58,719 --> 01:07:00,804
Speaker:
bit more material there, you fly
1904
01:07:00,804 --> 01:07:02,889
Speaker:
way farther for some reason
1905
01:07:02,889 --> 01:07:04,610
Speaker:
because of the drag or I don't
1906
01:07:04,610 --> 01:07:05,670
Speaker:
know, physics, but for some
1907
01:07:05,670 --> 01:07:07,510
Speaker:
reason I'm gonna call bullshit
1908
01:07:07,510 --> 01:07:08,989
Speaker:
and I'm going to say that
1909
01:07:08,989 --> 01:07:10,309
Speaker:
they're patting their crotches
1910
01:07:10,309 --> 01:07:12,570
Speaker:
because of the way the camera
1911
01:07:12,570 --> 01:07:13,670
Speaker:
looks at them when they're
1912
01:07:13,670 --> 01:07:14,590
Speaker:
doing.
1913
01:07:14,590 --> 01:07:16,110
Speaker:
Listen, listen.
1914
01:07:16,110 --> 01:07:22,030
Speaker:
They inject their penis with
some sort of acid.
1915
01:07:22,030 --> 01:07:24,710
Speaker:
It was like it was something
crazy, like hydrochloric acid or
1916
01:07:24,710 --> 01:07:27,190
Speaker:
something ridiculous to make.
1917
01:07:27,190 --> 01:07:30,909
Speaker:
Make it all swollen when they go
get fitted for the suit.
1918
01:07:30,909 --> 01:07:31,750
Speaker:
Okay.
1919
01:07:31,750 --> 01:07:36,349
Speaker:
And the swelling lasts for just
a couple of months.
1920
01:07:36,349 --> 01:07:37,710
Speaker:
So by the time they get their
1921
01:07:37,710 --> 01:07:39,510
Speaker:
suit back and go compete in the
1922
01:07:39,510 --> 01:07:40,989
Speaker:
Olympics, it's just a little bit
1923
01:07:40,989 --> 01:07:43,710
Speaker:
looser than when they got fitted
1924
01:07:43,710 --> 01:07:44,230
Speaker:
for it.
1925
01:07:44,230 --> 01:07:44,909
Speaker:
Right?
1926
01:07:44,909 --> 01:07:46,510
Speaker:
But it's not a substance that
1927
01:07:46,510 --> 01:07:48,469
Speaker:
can be tested for in the like,
1928
01:07:48,469 --> 01:07:50,269
Speaker:
drug testing.
1929
01:07:50,269 --> 01:07:54,710
Speaker:
Oh. Um, so they end up with like
a couple of inches.
1930
01:07:54,710 --> 01:07:58,829
Speaker:
And it's like something like for
every inch of extra material in
1931
01:07:58,829 --> 01:08:00,090
Speaker:
the crotch of their suit.
1932
01:08:00,090 --> 01:08:02,170
Speaker:
They fly like nine feet farther.
1933
01:08:02,170 --> 01:08:02,849
Speaker:
Really?
1934
01:08:02,849 --> 01:08:03,289
Speaker:
Yeah.
1935
01:08:03,289 --> 01:08:03,690
Speaker:
Wow.
1936
01:08:03,690 --> 01:08:06,570
Speaker:
So it was this huge controversy
in ski jumping this year.
1937
01:08:06,570 --> 01:08:07,969
Speaker:
Are they the penis?
1938
01:08:07,969 --> 01:08:10,010
Speaker:
And there was a whistleblower of
1939
01:08:10,010 --> 01:08:12,650
Speaker:
of someone anonymously told the
1940
01:08:12,650 --> 01:08:14,690
Speaker:
Olympic Committee that there
1941
01:08:14,690 --> 01:08:16,329
Speaker:
were these men doing penis
1942
01:08:16,329 --> 01:08:17,329
Speaker:
injections.
1943
01:08:17,329 --> 01:08:18,130
Speaker:
Unbelievable.
1944
01:08:18,130 --> 01:08:18,569
Speaker:
Yep.
1945
01:08:18,569 --> 01:08:19,729
Speaker:
Unbelievable.
1946
01:08:19,729 --> 01:08:20,850
Speaker:
Unbelievable.
1947
01:08:20,850 --> 01:08:23,289
Speaker:
But that being said, that one
1948
01:08:23,289 --> 01:08:25,250
Speaker:
just seemed the dumbest to me
1949
01:08:25,250 --> 01:08:25,930
Speaker:
this year.
1950
01:08:25,930 --> 01:08:27,529
Speaker:
I was just like, yeah, bro.
1951
01:08:27,529 --> 01:08:29,369
Speaker:
You're literally just getting,
1952
01:08:29,369 --> 01:08:31,970
Speaker:
like, shot off of this big
1953
01:08:31,970 --> 01:08:32,569
Speaker:
cliff.
1954
01:08:32,569 --> 01:08:34,090
Speaker:
Like come on.
1955
01:08:34,090 --> 01:08:38,529
Speaker:
Did you see the moguls with the
knees that your knees hurt when
1956
01:08:38,529 --> 01:08:39,569
Speaker:
you were watching it?
1957
01:08:39,569 --> 01:08:40,890
Speaker:
No, I didn't see the mogul.
1958
01:08:40,890 --> 01:08:41,130
Speaker:
Okay.
1959
01:08:41,130 --> 01:08:42,210
Speaker:
They're on skis.
1960
01:08:42,210 --> 01:08:42,649
Speaker:
Yeah.
1961
01:08:42,649 --> 01:08:44,369
Speaker:
With their legs real bent.
1962
01:08:44,369 --> 01:08:44,890
Speaker:
Okay.
1963
01:08:44,890 --> 01:08:47,770
Speaker:
And there's all these hills,
moguls.
1964
01:08:47,770 --> 01:08:49,250
Speaker:
There's all these hills in the
snow.
1965
01:08:49,250 --> 01:08:50,250
Speaker:
They're called moguls.
1966
01:08:50,250 --> 01:08:50,649
Speaker:
Yeah.
1967
01:08:50,649 --> 01:08:51,850
Speaker:
Oh, you know what that is, then?
1968
01:08:51,850 --> 01:08:53,770
Speaker:
I know what moguls are.
1969
01:08:53,770 --> 01:08:54,210
Speaker:
Yeah.
1970
01:08:54,210 --> 01:08:54,689
Speaker:
Okay.
1971
01:08:54,689 --> 01:08:56,130
Speaker:
Well, that's what the event is
called too.
1972
01:08:56,130 --> 01:08:58,220
Speaker:
And they have to go back and
forth and your skis.
1973
01:08:58,220 --> 01:09:00,859
Speaker:
But every time they do it, you
can see their knees like.
1974
01:09:02,899 --> 01:09:07,859
Speaker:
Yeah, I always like wonder about
these people that do the same.
1975
01:09:07,859 --> 01:09:09,420
Speaker:
Like a sport that puts you in.
1976
01:09:09,420 --> 01:09:11,380
Speaker:
Like, like hockey players.
1977
01:09:11,380 --> 01:09:15,000
Speaker:
the goalies that they're like
bending over a lot.
1978
01:09:15,000 --> 01:09:17,359
Speaker:
The whole time, you know what I
mean?
1979
01:09:17,359 --> 01:09:21,399
Speaker:
Like they've gotta get like back
and hip issues.
1980
01:09:21,399 --> 01:09:25,960
Speaker:
Like, there's no way that you
can be in a certain pose for
1981
01:09:25,960 --> 01:09:29,640
Speaker:
hours and hours and hours and
not get issues.
1982
01:09:29,640 --> 01:09:32,520
Speaker:
They must like, look at even the
ice skaters.
1983
01:09:32,520 --> 01:09:32,920
Speaker:
Yeah.
1984
01:09:32,920 --> 01:09:36,880
Speaker:
They jump up and land with like
thousands of pounds of force.
1985
01:09:36,880 --> 01:09:37,319
Speaker:
That's true.
1986
01:09:37,319 --> 01:09:38,359
Speaker:
Onto one foot.
1987
01:09:38,359 --> 01:09:39,359
Speaker:
That's true.
1988
01:09:39,359 --> 01:09:41,039
Speaker:
I didn't think about that.
1989
01:09:41,039 --> 01:09:44,720
Speaker:
But that being said, the ice
skating is my favorite Oh so
1990
01:09:44,720 --> 01:09:46,399
Speaker:
beautiful it was.
1991
01:09:46,399 --> 01:09:48,239
Speaker:
Yeah, they're pretty incredible.
1992
01:09:48,239 --> 01:09:48,579
Speaker:
Yeah.
1993
01:09:48,579 --> 01:09:50,500
Speaker:
Alysa Liu is my favorite person
on planet earth.
1994
01:09:50,500 --> 01:09:53,819
Speaker:
Yeah, she was pretty
spectacular.
1995
01:09:53,819 --> 01:09:57,539
Speaker:
I think that before I knew
1996
01:09:57,539 --> 01:10:01,460
Speaker:
anything about her, like I just
1997
01:10:01,460 --> 01:10:03,180
Speaker:
like when I first saw her
1998
01:10:03,180 --> 01:10:06,020
Speaker:
perform like that, she was just
1999
01:10:06,020 --> 01:10:06,859
Speaker:
having fun.
2000
01:10:06,859 --> 01:10:07,300
Speaker:
Yeah.
2001
01:10:07,300 --> 01:10:09,579
Speaker:
She was she wasn't taking it
2002
01:10:09,579 --> 01:10:12,659
Speaker:
like the competition, like of it
2003
01:10:12,659 --> 01:10:13,100
Speaker:
all.
2004
01:10:13,100 --> 01:10:15,859
Speaker:
She was just like, I'm gonna go
out there and kill it.
2005
01:10:15,859 --> 01:10:16,180
Speaker:
Yeah.
2006
01:10:16,180 --> 01:10:17,020
Speaker:
And she did.
2007
01:10:17,020 --> 01:10:18,060
Speaker:
Yeah.
2008
01:10:18,060 --> 01:10:18,819
Speaker:
Well, anyways.
2009
01:10:18,819 --> 01:10:19,260
Speaker:
All right.
2010
01:10:19,260 --> 01:10:24,180
Speaker:
Well, we'll be back in a couple
of weeks, in a couple of weeks.
2011
01:10:24,180 --> 01:10:25,979
Speaker:
And we love you guys.
2012
01:10:25,979 --> 01:10:29,819
Speaker:
And you can find all the sources
in our show notes.
2013
01:10:29,819 --> 01:10:30,739
Speaker:
Yeah.
2014
01:10:30,739 --> 01:10:33,859
Speaker:
And lab libs you can play along.
2015
01:10:33,859 --> 01:10:34,979
Speaker:
Yeah.
2016
01:10:34,979 --> 01:10:37,020
Speaker:
That's a fun thing for you to
try.
2017
01:10:37,020 --> 01:10:40,939
Speaker:
If you haven't noticed that
existing yet in the show notes
2018
01:10:40,939 --> 01:10:42,659
Speaker:
before you click play.
2019
01:10:42,659 --> 01:10:44,659
Speaker:
You try to guess all the lab
libs.
2020
01:10:44,659 --> 01:10:45,420
Speaker:
That's how you do.
2021
01:10:45,420 --> 01:10:46,340
Speaker:
That's right.
2022
01:10:46,340 --> 01:10:50,505
Speaker:
and like, subscribe, whatever.
2023
01:10:50,505 --> 01:10:52,585
Speaker:
Just let, let us know you're out
there.
2024
01:10:52,585 --> 01:10:53,465
Speaker:
Yeah, yeah.
2025
01:10:53,465 --> 01:10:54,704
Speaker:
you can always find us on
2026
01:10:54,704 --> 01:10:58,385
Speaker:
Instagram too at underscore
2027
01:10:58,385 --> 01:10:59,545
Speaker:
podcast.
2028
01:10:59,545 --> 01:11:00,265
Speaker:
Oh yeah.
2029
01:11:00,265 --> 01:11:02,864
Speaker:
There's a lot of really cool
stuff on there now.
2030
01:11:02,864 --> 01:11:03,824
Speaker:
Yeah, yeah there is.
2031
01:11:03,824 --> 01:11:07,704
Speaker:
We're even suggesting other
podcasts you might like.
2032
01:11:07,704 --> 01:11:08,545
Speaker:
Mhm.
2033
01:11:08,545 --> 01:11:09,984
Speaker:
So give us a listen.
2034
01:11:09,984 --> 01:11:13,225
Speaker:
Give them a listen and we will
talk to you guys later.
2035
01:11:13,225 --> 01:11:14,385
Speaker:
Bye bye.