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Coming up next. I've

2:00

got the kind of mind I

2:02

can't get enough. I wanna learn everything.

2:05

I wanna fill it all up

2:07

with new discoveries that happen every

2:09

day of the week. There's only

2:11

one place to go. science

2:33

to you Kiki! And

2:35

a good science to you too

2:37

Blair! out

2:40

there. Welcome to another episode

2:42

of This Week in Science.

2:44

We are back again with

2:47

so much more science! The

2:49

whole another week of science

2:51

has occurred while we were doing

2:54

whatever it is we do.

2:56

Were you the one scienceing

2:58

out there? If you were. Hi! Thanks

3:01

for science! Mm-hmm. Thanks

3:03

for bringing us this stuff

3:05

that we love talking about

3:07

and learning about. Justin is

3:09

still moving, doesn't have internet,

3:11

but hopefully next week we'll be able

3:13

to join us, but we'll see what

3:16

happens on that front. This is like

3:18

the best job opera ever. Yeah, he's

3:20

just hanging out on the ethereal plane.

3:22

You know, maybe he'll roll the right

3:25

number to get out of there, maybe

3:27

not. Just to wait for

3:29

his next turn. What can

3:31

you do? Roll the dice.

3:33

Hopefully they're like 21 sided.

3:35

Maybe 18. I don't know.

3:37

See what you got. Maybe some

3:40

dragons? I don't know. How

3:42

about I have stories this

3:44

week about the stellarator?

3:47

Love the stellarator. A possible disease

3:49

therapy and oxygen pill. More

3:51

memory. It's what I all

3:53

have, what we all need

3:56

maybe, and how not to

3:58

sleep better at night. What's

4:00

in the animal corner Blair?

4:03

I have some ideas about

4:05

how to not sleep better

4:07

at night. I could give

4:09

you one or 50. Really

4:12

just one I think. I

4:14

have, what did I even

4:16

bring? Oh, the AI emotions

4:18

that you mentioned before, friendly

4:21

and stressed macax and animal

4:23

consciousness. I was conscious of

4:25

that. Does it snakes? Does

4:27

it? No, I just had

4:30

trouble saying the word consciousness.

4:32

Say it three times fast,

4:34

everyone, and you'll feel just

4:36

like us. No. No. All

4:39

right, everyone, as we jump

4:41

in the show tonight, yes,

4:43

we're gonna up right in.

4:45

Yes. to this case of

4:48

the Science Wednesdays, no jumping

4:50

to conclusions. We're hopping into

4:52

the show. I want to

4:54

remind you that subscribing to

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But now, it's time for

5:42

the science! You

5:44

ready for the big

5:47

news? I'm ready for

5:49

you have for me.

5:51

Yeah, the stellarator Is

5:54

that in the latest

5:56

Rocky film or? No,

5:59

I mean, I just

6:01

really love it. They

6:03

call this this magnetic,

6:06

this fusion power device

6:08

like a Tokamak, except

6:11

a little twisty like

6:13

a pretzel, that this,

6:15

this, what's otherwise known

6:18

as the Wendelstein 7X,

6:20

that they call it

6:22

the stellarator. And they've

6:25

just published a paper,

6:27

this company. Proxima fusion,

6:30

which again, they've got

6:32

their names, all dialed

6:34

in, I love it,

6:37

infusion, engineering, and design,

6:39

entitled stalaris, a high-field

6:42

quasi-isodynamic stellarator for a

6:44

prototypical fusion power plant.

6:47

Oh, that kind of stellarator.

6:49

Got it. Yes, yes, yes.

6:51

Okay. So you, if you

6:54

are into the fusion news

6:56

thing, you might have heard

6:58

recently. Oh, wow. China, they

7:00

turned on their fusion, the

7:02

generator, nuclear fusion generator, and

7:04

they ran there for some

7:06

long period of time that

7:09

was really great. And then

7:11

there is a news. No,

7:13

no, eater, eater, the French

7:15

and European Union, they turned

7:17

theirs on, and they ran

7:19

it for longer than the

7:21

French. Yes, go, go, do

7:24

it, do it, yeah. Anyway,

7:26

that's really great, but this

7:28

Proxima fusion and their stellarator

7:30

that has been, they've been

7:32

working on it since they

7:34

first announced their prototype design

7:36

back in like 2007, the

7:39

Wendelstein 7X, W7X. For short,

7:41

this is in Germany. It's

7:43

out of the Max Planck

7:45

Institute for plasma physics and

7:47

the German federal government and

7:49

European Union has been funding

7:52

this design since its initiation

7:54

for over $1.3 billion in

7:56

funding to date. And so

7:58

this particular type of fusion

8:00

is based on the technology

8:02

being used in Tokamax. So

8:04

those are the donut plasma

8:07

fusion generators in which the

8:09

design, it looks like a

8:11

donut. It's a round donut

8:13

thing and they use magnets

8:15

around the outside to contain

8:17

energy and smoosh it. And

8:19

so it heats up and

8:22

it gets contained in plasmas

8:24

inside the Tokamac. plasma spins

8:26

around, kind of like how

8:28

you would imagine the plasma

8:30

doing those loopy whorls on

8:32

the top, on the, you

8:34

know, on the outbursts that

8:37

come from the solar flares

8:39

on the sun. So the

8:41

plasma is just getting heated

8:43

up and it's getting pressured.

8:45

It's really awesome. And if

8:47

you could keep it contained

8:49

and stable for a long

8:52

enough period of time, it

8:54

potentially could be the conditions

8:56

in which you could fuse.

8:58

ions and or atoms and

9:00

be able to actually create

9:02

power as opposed to just

9:04

use power to smush plasma.

9:07

Yes. The problem with Tokamax

9:09

that artificial intelligence has been

9:11

helping a lot to understand

9:13

there are instabilities in the

9:15

plasma and that they have

9:17

been having to put more

9:20

energy into the magnets. to

9:22

be able to control and

9:24

contain the plasma so that

9:26

the plasma is happy. Otherwise

9:28

it has outbursts and the

9:30

outbursts, hmm, it's not happy,

9:32

right? So the stellarator goes

9:35

at it from a little

9:37

bit different perspective. The stellarator,

9:39

because it is like a

9:41

twisty donut, what it's trying

9:43

to do is do all

9:45

the hard work in the

9:47

design phase as opposed to

9:50

in the magnet phase. And

9:52

so the design is actually

9:54

more following the path of

9:56

the magnetic whorals and what

9:58

the plasma wants to... do.

10:00

So the shape of the

10:02

stellarator is designed to be

10:05

more easier for the magnets

10:07

and the plasma to flow

10:09

through. So it's a lot

10:11

of upfront control, but then

10:13

less energetic control when you

10:15

actually get the plasma flowing.

10:17

Huh. Yeah. So

10:20

the exciting thing about these

10:22

the stellar and this article

10:24

about the stalaris is that

10:26

this is the first design

10:29

for a commercial. Stellarator fusion

10:31

plant and they have published

10:33

online and they are saying

10:35

that they will have their

10:37

pilot. plant in process and

10:39

creating energy by uh... two

10:41

thousand thirty one which is

10:44

six years away less than

10:46

and that it at that

10:48

point in time should be

10:50

ready for uh... for adoption

10:52

around the world so the

10:54

races on inertial fusion the

10:56

races on Whatever kinds of

10:59

fusion that you would like

11:01

to be using right now.

11:03

Oh good, you found a

11:05

great picture there Blair. Yeah,

11:07

I was looking around. So

11:09

there's a really clear compare

11:11

contrast of a Tokamak versus

11:14

a stellarator. Which the arrows

11:16

really do it for me.

11:18

Sometimes all it takes is

11:20

a really good diagram for

11:22

me to understand what's going

11:24

on. So you're doing a

11:27

great job explaining it, but

11:29

it's like such a it's

11:31

such an abstract thought for

11:33

me that so if I

11:35

can describe to the listener

11:37

basically it's showing that if

11:39

it's if it's going around

11:42

the donut in it kind

11:44

of a straight line there's

11:46

a lot of opportunity for

11:48

for the the particles to

11:50

wander. But it's not like

11:52

a school of fish. They

11:54

don't want to stay or

11:57

they don't want to stay

11:59

packed tightly together. They're like,

12:01

I'm going to go. I

12:03

have space. I'm going to

12:05

move around. And so it

12:07

destabilizes the plasma. It like

12:10

probably also messes with conserving

12:12

all the energy that you're

12:14

trying to use, right? Yeah,

12:16

it disrupts the whole thing,

12:18

which is bad. Yeah. And

12:20

so for some reason this

12:22

twisted pattern makes the. plasma

12:25

particles all feel the force

12:27

in the same way, so

12:29

they all go in the

12:31

same direction. Which, yeah, it

12:33

kind of makes sense. Like,

12:35

if you're on a water

12:37

slide, you're going in, and

12:40

it's kind of like twisting

12:42

to the left, it's not

12:44

going to be very easy

12:46

for you to be like,

12:48

oh, I'm going to go

12:50

over to the right instead.

12:52

No, like the force is

12:55

compelling you to twist around

12:57

and follow the water slide,

12:59

right? So. Yep. Yeah. It's

13:01

pretty cool. Yeah, and so

13:03

this is exciting because, you

13:05

know, I remember when the

13:08

stelator was first reported and

13:10

I was like, what is

13:12

this? Mushi twisted like, like

13:14

somebody in the chat has

13:16

said, Mobius strip of a

13:18

Tokamak. And the science behind

13:20

it is. just very interesting

13:23

and I've been wanting to

13:25

hear something for a while

13:27

so it's really interesting to

13:29

see the stelaris work become

13:31

a big player now within

13:33

this commercial fusion environment which

13:35

you know if fingers crossed

13:38

if they can actually get

13:40

commercial fusion power plants out

13:42

the door by the early

13:44

2030s I mean that is

13:46

I I wonder, nobody's gotten

13:48

close enough yet, but the

13:50

advancement is now, it's very

13:53

obvious as opposed to the

13:55

questions of the past as

13:57

to how these technologies would

13:59

work. Yeah, so

14:01

we'll see where it goes.

14:03

The structure will definitely continue

14:06

to be adapted and refined,

14:08

but this. their stellar radar

14:10

model coil demo magnet in

14:13

2027 proximate fusion is going

14:15

to what they say de-risk

14:17

its technology for stellarators the

14:20

company will demonstrate that stellarators

14:22

are capable of net energy

14:24

production with its demo stellarator

14:27

alpha in 2031 like I

14:29

said and lead to a

14:31

fusion energy in the grid

14:33

in the 30s. Well let's

14:36

see what will the roaring

14:38

30s be like for us

14:40

here on earth? We'll find

14:43

out. But it's very exciting

14:45

also that they've published their

14:47

design, published publicly, and that

14:50

they are putting the science

14:52

out there for everyone to

14:54

see, putting the engineering out

14:57

there as well, which I

14:59

think is great. So this

15:01

actually, this raises a really

15:03

interesting question I hadn't really

15:06

thought about. I'm calling my

15:08

own question interesting. It's funny.

15:10

Well, it probably is. Well,

15:13

I think it's interesting. Otherwise,

15:15

I wouldn't open my mouth

15:17

about it. Is there is

15:20

there copyright on the design

15:22

of the stellarator? They've released

15:24

it. Is it now something

15:27

that other people can build

15:29

or they have to kind

15:31

of have a payout to

15:33

these researchers if they build

15:36

a stellarator? I'm imagining that

15:38

this is intellectual property and

15:40

that there are... probably a

15:43

number of companies involved in

15:45

this already. So I'm imagining

15:47

that there are licensing and

15:50

intellectual property partnerships that are

15:52

already underway and that, you

15:54

know, by the time power

15:57

plants become an option, that

15:59

that that path will be

16:01

pretty clear. Right, because at

16:03

first I was like, man,

16:06

what is it? matter just

16:08

let people do the research

16:10

but that's why because if

16:13

fusion power happens they want

16:15

to be able to have

16:17

control over the money to

16:20

be made from that. Yeah,

16:22

so you've got you've got

16:24

German and EU investment, you've

16:26

got the Max Planck Institute,

16:29

so there's technology transfer out

16:31

of the university and government

16:33

holdings, and then you have

16:36

the technology transfer into those

16:38

partnerships that are probably constantly

16:40

being hashed out. I'm sorry,

16:43

I'm going way off target

16:45

here. That's okay. It's an

16:47

interesting question. I never really

16:50

looked at it from that

16:52

angle. Is that why fusion

16:54

is taking so long? Because

16:56

don't be sharing. No. That

16:59

is not why. Okay. I

17:01

just care. Because, you know,

17:03

maybe if everybody shared all

17:06

their homework, maybe it would

17:08

happen faster. No, everybody's been

17:10

sharing their homework. There are

17:13

certain types of fusion that

17:15

are advancing more quickly than

17:17

others, and what one type

17:20

of fusion learns from their

17:22

experiments and that they're willing

17:24

to share publicly in their

17:26

scientific writings and other ways,

17:29

then that knowledge can be

17:31

useful. to the other methodologies

17:33

and everybody trying these multiple

17:36

different solutions to the question

17:38

the problem of fusion is

17:40

hopefully getting us there faster

17:43

right it's divide divide try

17:45

all the things and then

17:47

see what works best you

17:50

know some might be better

17:52

than others We'll see I

17:54

mean ignition fusion is probably

17:56

just gonna stay really really

17:59

great at Designing and testing

18:01

nuclear warheads for a very

18:03

long time But there's Z-Pinch

18:06

fusion there with a company

18:08

up in Seattle, Zapp, and

18:10

then there's the inertial fusion,

18:13

which I think I reported

18:15

on Commonwealth being in Virginia,

18:17

state of Virginia, saying they're

18:20

going to be the first

18:22

commercial fusion plant in the

18:24

United States, but that's inertial

18:26

fusion. And then, you know,

18:29

we've got the... the Tokamax,

18:31

and then we've got the

18:33

stellarators, which are the plasma

18:36

fusion. So there are many

18:38

options. The end result is

18:40

how can we create a

18:43

reproducing and sustainable design to

18:45

fuse atoms together in a

18:47

way that gives us more

18:49

energy than we put in?

18:52

How can we do that?

18:54

Yeah. Interesting. And it's still

18:56

not there. So, you know,

18:59

this is exciting. I'm excited

19:01

because there's this progress, but

19:03

I mean, come on. NIF

19:06

said it was going to

19:08

have us having commercial power

19:10

plants by now. Everybody was,

19:13

we're going to totally be

19:15

doing it, everybody. Grain assault,

19:17

everyone, grain of salt. Oh,

19:19

and Blair, honestly, because there's

19:22

a study. I really wanted

19:24

to just, you know, throw

19:26

out here and get your,

19:29

well, du response on. Oh,

19:31

great. Okay, I'm ready. Yeah,

19:33

published in the journal Environmental

19:36

Research Communications, the researchers found

19:38

that in countries like the

19:40

United States and the United

19:43

Kingdom, far more land is

19:45

allocated to golf courses than

19:47

renewable energy facilities. Oh, well,

19:49

duh. The

19:52

amount of land spent on

19:55

golf courses is sickening. I

19:57

don't understand. Okay. It's the

19:59

part about... Mmm, I got,

20:02

the part of, this is

20:04

the one thing I will

20:06

say, and we can move

20:09

on. You got it. No,

20:11

golf courses strike a nerve

20:13

for me because they are

20:16

spaces that not only are

20:18

just a terrible use of

20:20

resources because it's all grass.

20:23

Right? Which needs? Water and

20:25

fertilizer and all these things.

20:27

But they are spaces that

20:30

historically have been designed to

20:32

exclude people. Yeah, be it

20:34

women, be it specific racial

20:37

groups, be it specific societal

20:39

groups, golf courses, and yes,

20:41

they take up space that

20:44

could be used. in ways

20:46

that benefit the entire community,

20:48

the environment, the neighborhoods around

20:51

it. Yep. Whoo! You'll leave

20:53

it! You're welcome Blair! Dr.

20:55

Jan Weinand, lead author of

20:58

the study, head of the

21:00

Integrated Scenarios Department. I love

21:02

that. I want to be

21:05

in an Integrated Scenarios Department.

21:07

This is the Institute Julek

21:09

Systems Analysis at Vorschung Zen

21:12

from Julek. It says, our

21:14

study does not advocate for

21:16

the direct conversion of golf

21:19

courses, but it highlights the

21:21

vast potential for renewable energy

21:23

on similarly large and underutilized

21:26

areas. It's crucial to consider.

21:28

I advocate for the conversion

21:30

of golf courses. Yeah, it's

21:33

crucial to consider how we

21:35

allocate land overall and especially

21:37

when significant space is dedicated

21:40

to activities that benefit only

21:42

a limited segment of the

21:44

population. Yep. Just like you

21:47

said. And the Reddit group,

21:49

the science group, the commentary.

21:51

the way it's fantastic everybody

21:54

says well I mean really

21:56

wouldn't it just add to

21:58

the game to have wind

22:01

turbines or to have you

22:03

know like out in the

22:05

rough your solar panels the

22:08

entire thing is rough but

22:10

it's like it's like it's

22:12

like it would be like

22:15

a pet golf course oh

22:17

no the feral king ran

22:19

away from with my ball

22:22

I don't know it could

22:24

be like mini golf in

22:26

gravity falls But like, yeah,

22:29

but it's big golf. So

22:31

it's like Maxie golf. Exactly.

22:33

Extreme golf, right? Yeah. Everybody's

22:36

into extreme sports. Let's take

22:38

it to the next level.

22:40

Extremely resourceful and sustainable golf.

22:43

All right Blair. Yes. Oh,

22:45

you want me to talk

22:47

now? My turn? Yeah, your

22:50

turn. Okay, I have a

22:52

story about AI, but it's

22:54

not really AI. AI can

22:57

be used to determine the

22:59

emotions of animals. It's not

23:01

really AI. Researchers from the

23:04

Department of Biology at the

23:06

University of Copenhagen, they trained

23:08

a machine learning model to

23:11

distinguish between positive and negative

23:13

emotions in seven different undulate

23:15

species, including cows, pigs, and

23:18

wild boars. By analyzing the

23:20

acoustic patterns of their vocalizations,

23:22

the model achieved an impressive

23:25

accuracy of 89.49% marking the

23:27

first cross-species study to detect

23:29

emotional valence using AI. So

23:32

of course, my first question

23:34

reading this press release was,

23:36

how do they know? Yeah.

23:39

So they're saying... It was

23:41

89% accurate. What are you

23:43

measuring? Budgeted by? Yes. So

23:46

I had to dig into

23:48

the actual paper, which I

23:50

was very lucky that actually

23:53

I didn't have to pay

23:55

to read. Thank you. So

23:57

the calls that they used.

24:00

from the longer list is

24:02

domestic and wild undulates including

24:04

cows, sheep, horses, per waltzki's

24:07

horses, which let's bookmark that

24:09

and come back to that

24:11

in a minute, pigs, wild

24:14

boars, and goats, they used

24:16

calls that were known already

24:18

for specific emotional states. So

24:21

they knew the emotional valence,

24:23

they knew the emotional state

24:25

of the animal at the

24:28

time. So then they were

24:30

able to say like, this

24:32

animal is scared. Let's feed

24:35

the scared sound into the

24:37

machine learning model. It identified

24:39

that that animal was scared.

24:42

And so that was validated

24:44

during previous studies based on

24:46

behavioral indicators. So there were

24:49

these larger studies done that

24:51

based on like based on

24:53

this. and this and this

24:56

we know that this animal

24:58

is excited or hungry or

25:00

like aggressive right and so

25:03

then when they make a

25:05

sound you can associate those

25:07

two things but This

25:10

doesn't even feel like that

25:12

complicated of a machine learning

25:14

model to me if I'm

25:16

being honest because it's really

25:18

just like an in-out machine

25:20

like it's really just matching

25:22

I feel like you don't

25:24

even need a machine learning

25:26

model to do that you

25:28

just need to be like

25:31

judge this against this right?

25:33

Yes you can I will

25:35

tell you having experienced not

25:37

this exact like valence judgments

25:39

for bird song, but the

25:41

identification of syllables in bird

25:43

songs by listening and then

25:45

based on like spectrometry and

25:47

the work that goes in

25:49

to trying to get individual

25:51

people to validate and to

25:53

actually create a methodology that's

25:55

repeatable and that is. as

25:57

accurate as possible is you

25:59

can't get as many data

26:01

points if you're having humans

26:03

verify all of the things

26:05

as if you're using the

26:07

machine learning. So yes, it

26:09

is in out. But in

26:11

terms of, I mean, I

26:13

certainly hope that programming and

26:15

creating this model and putting

26:17

it together was less work

26:19

than the other graduate students.

26:22

I went to graduate school.

26:24

Yeah, so I mean, you're

26:26

right. It's ultimately to make

26:28

things easier and instantaneous and

26:30

something that doesn't have to

26:32

be verified by a bunch

26:34

of different people. So you're

26:36

totally correct about that. And

26:38

so they say there's a

26:40

potential to revolutionize all sorts

26:42

of welfare, veterinary uses, livestock

26:44

management, conservation efforts. I know

26:46

that if you work with

26:48

a small set of animals

26:50

yourself, like people who work

26:52

in livestock, I would say,

26:54

a lot of them know

26:56

what these sounds mean already,

26:58

but that comes with experience,

27:00

right? And I think that

27:02

if you have, for example,

27:04

the thing that they talked

27:06

about in this press release

27:08

quite a bit, was about

27:10

having something monitoring real-time 24-7.

27:13

And that's the difference. You

27:15

don't have to go like,

27:17

oh! I don't think something's

27:19

wrong out there in the

27:21

field. You have your bot

27:23

listening and your phone goes

27:25

off. Ping, something... What's that,

27:27

Lassie? Oh, Jimmy's in the

27:29

well? Right, yes. So there's

27:31

real-time monitoring of animal emotions

27:33

that could revolutionize the way

27:35

that we care for animals,

27:37

study animals, working conservation, there's

27:39

lots of different things that

27:41

you could do with this.

27:43

Yeah, I mean thinking about

27:45

it from a zoo keeper's

27:47

perspective. How do you think

27:49

this kind of monitoring could

27:51

have helped with situations, say,

27:53

in the primate house or

27:55

in, with like the giraffes

27:57

who never talked? Well, they

27:59

do, remember? That was something

28:01

we talked about on TWIS.

28:04

So here's the thing. Primates.

28:06

Specifically the primates that I

28:08

worked with. If there's 20

28:10

of them. Is the machine

28:12

learning also going to tell

28:14

me that it's banana Sam

28:16

that's bothered at this moment?

28:18

Maybe. Maybe not. Sounds of

28:20

voices are different. And if

28:22

you train it up, I

28:24

mean, I have now a

28:26

note-taking AI that Marshall gave

28:28

me to use in my

28:30

Zoom calls that if you

28:32

train it, it will identify

28:34

every single person's voice. Every

28:36

time they come in without

28:38

having them have to identify

28:40

themselves. So you're absolutely right.

28:42

So that's I mean, that's

28:44

possible. I think that when

28:46

somebody's first entering into a

28:48

care area, it could be

28:50

really helpful. I think that

28:52

when you spend a long

28:54

time with animals, at least

28:57

while you're physically there, that's

28:59

what I'm saying. Like. very

29:01

specific animals if you spend

29:03

a lot of time around

29:05

them you definitely know what

29:07

those vocalizations mean inherently and

29:09

I don't know if you

29:11

could even put words on

29:13

it but it's it's almost

29:15

like an impulsive or a

29:17

or a your own emotional

29:19

response when you hear the

29:21

sounds you can you can

29:23

kind of get the vibe

29:25

from it that's like with

29:27

your cat or your dog

29:29

or your own animal that

29:31

you learn to or your

29:33

your animals train you You

29:35

train your animals. You learn

29:37

how to communicate, right? There

29:39

are sounds. Yeah. Yeah, but

29:41

I'm wondering for, I was

29:43

thinking, I'm wondering for conservation

29:45

if they could actually get

29:48

to a more accurate confirming

29:50

of, you know, how realistic

29:52

some of our zoos and

29:54

like public parks, public animal

29:56

parks are as opposed. to

29:58

the wild spaces that we're

30:00

trying to, you know, you

30:02

know, make something that, you

30:04

know, that it's like that,

30:06

you know, by, okay, we'll

30:08

listen to the animals in

30:10

this natural setting, we'll listen

30:12

to the animals in our,

30:14

you know, pseudo natural setting

30:16

and see how, see if

30:18

they make the same sounds.

30:20

Yeah, I think that's a

30:22

really interesting point. And this

30:24

actually plays into a story

30:26

I have for the animal

30:28

corner. So we'll bookmark some

30:30

of this. But I think

30:32

that there is a benefit

30:34

to knowing that stress is

30:36

part of an animal's day,

30:39

excitement is part of an

30:41

animal's day, you know, all

30:43

these kind of different things,

30:45

frustration is part of an

30:47

animal's day. Life gets very

30:49

boring without those things if

30:51

you just are thrown everything

30:53

that you need right to

30:55

your face all the time.

30:57

That's why like in Richmond

30:59

exists and stuff like that.

31:01

But it's not a one-to-one.

31:03

I would say animals that

31:05

are constantly in fear of

31:07

being predated upon don't need

31:09

that in their animal exhibits.

31:11

There's a famous story about...

31:14

I'm not going to get it

31:16

exactly right, but there was a

31:18

zoo that hired these architects to

31:20

build this North America region. And

31:23

they had this, they were like,

31:25

oh, this is a great idea.

31:27

We have a section for the

31:29

grizzly bears, we have a section

31:31

for the wolves, and we have

31:33

a section for the deer, right?

31:36

And then we'll rotate them through

31:38

because they want to have different

31:40

experiences all the time. And rotating

31:42

exhibits is a very common practice

31:44

in zoos, and it allows them

31:46

to kind of have a different.

31:49

scenery every so many days. Okay,

31:51

but what about the way they

31:53

smell or so there was I

31:55

don't recall from the story if

31:57

they actually got to production and

31:59

they actually this but I think

32:02

it got stopped after the the

32:04

blueprints were shared I'm not sure

32:06

but basically there was a whole

32:08

question of okay if we rotate

32:10

the deer into the wolf exhibit

32:12

they're gonna spend all day terrified

32:14

I know it's here I know

32:17

they're here I don't think so

32:19

yeah could you imagine you only

32:21

have like one herbivore and you've

32:23

got like two predator species and

32:25

the herbivore is just surrounded my

32:27

predators all the time Yeah.

32:30

So the other thing I thought

32:32

that was really interesting about this

32:35

is it can help us do

32:37

research on wild animals and social

32:39

dynamics. There's a lot of research

32:41

that's done on, for example, primates

32:44

in the wild, but they count

32:46

on just kind of mostly visual

32:48

cues of how relationships work and

32:50

how animals feel about things. More

32:53

on that later. But if they

32:55

had a speaker that was recording

32:57

calls and they could say, oh,

32:59

so and so feels such and

33:02

such way about this based on

33:04

the call, that is an extra

33:06

layer of information for social strategies

33:08

and dynamics when you're doing research.

33:12

So the long and short

33:14

of this was they did

33:16

this on a bunch of

33:18

different animals including Perwalski's horses,

33:21

which I said I would

33:23

mention They're an extremely endangered

33:25

animal that you should Google.

33:27

They're just a weird-looking horse.

33:29

That's it Just a weird-looking

33:32

horse. They are not a

33:34

horse. They are their own

33:36

species and I've seen them

33:38

in zoos a couple times.

33:41

They're really striking but they're

33:43

an endangered species regardless. All

33:45

these different undulate species, very

33:47

different, pigs and horses. The

33:49

machine learning model was able

33:52

to kind of universalize these

33:54

responses. They were common. They

33:56

were very similar. They're excited

33:58

sound versus they're scared sound.

34:00

So it is something that

34:03

is conserved amongst undulous. It's

34:05

a pretty big group of

34:07

animals. So that also has

34:09

some cool implications for using

34:12

a machine learning model like

34:14

this. I think it's really

34:16

cool. I think, you know,

34:18

it is a simple idea,

34:20

simplistic at his core, but

34:23

because of the, you know,

34:25

the, the amount of data

34:27

and the... the ways it

34:29

can be applied more easily

34:32

than people, then it might

34:34

actually be something that can

34:36

be used in these really

34:38

broad contexts. I'd like to

34:40

see it above 89% but

34:43

otherwise. Yeah, that'd be great.

34:45

A horse is a horse,

34:47

of course, of course, unless,

34:49

oh, especially if it's a

34:51

Prowalski's horse. Even if horse

34:54

is a horse, of course,

34:56

of course, even if it

34:58

looks like a per Ralski's

35:00

horse. Yeah, that song doesn't

35:03

work as well as I'd

35:05

like it too. Okay. Moving

35:07

on from your strange horses

35:09

and really, really cute wild

35:11

boar babies. Let's round out

35:14

the end of this part

35:16

of the show with a

35:18

story about... hopeful new transplant,

35:20

not transplantation, but new implantation

35:23

technology for type 1 diabetes.

35:25

Researchers just publishing in Science

35:27

Direct this last week reported

35:29

their work to to reverse.

35:31

They're really trying to reverse

35:34

type 1 diabetes and they

35:36

succeeded in doing so in

35:38

mice, but using human cells.

35:40

So one of the issues

35:42

with treating diabetes is a

35:45

type of cell within the

35:47

pancreas that is called the

35:49

islet cell, pancreatic islet cell.

35:51

It is the only human...

35:54

tissue that produces insulin, which

35:56

is needed to respond to

35:58

rising blood glucose levels, and

36:00

in type one diabetes, the

36:02

body goes, I don't like

36:05

you, islet cells, and destroys

36:07

them, and so then the

36:09

body cannot make its own.

36:11

insulin and becomes insulin deficient

36:14

so people end up having

36:16

to monitor their their blood

36:18

glucose their insulin and very

36:20

often will have insulin pumps

36:22

take insulin shots to be

36:25

able to manage their their

36:27

deficiency on their own. So

36:29

How do we get more

36:31

islets into the pancreas? How

36:33

can we reverse the process

36:36

of that degradation? One of

36:38

the problems is that the

36:40

islets, they just get it,

36:42

you put any transplanted islets

36:45

back in the pancreas and

36:47

the body just goes, no,

36:49

don't like you and they're

36:51

attacked. killed by the bodies

36:53

some more. There's also inflammation

36:56

that causes worse problems. So

36:58

it's just been really difficult

37:00

to get these islet cells

37:02

to survive and replicate this

37:05

part of the pancreas that

37:07

is that supports the islet

37:09

cells even that part of

37:11

the pancreas gets a lot

37:13

of inflammation in it. And

37:16

so it can't even just

37:18

support these newly transplanted cells.

37:20

So while Cornell medicine just

37:22

published their study, which they

37:24

They took human islet cells,

37:27

grew them in a dish

37:29

with, what did they grow

37:31

them in a dish with?

37:33

They grew them in a

37:36

dish with human pancreatic, they

37:38

took human pancreatic islet cells,

37:40

grew them in a dish

37:42

with blood vessel cells so

37:44

that the support tissue of

37:47

the blood vessels. that would

37:49

bring blood to the islet

37:51

cells and support them and

37:53

give them all of the

37:56

nutrients and keep them safe

37:58

and hopefully keep them from

38:00

being inflamed and angry, they

38:02

were... grown into a dish,

38:04

and then they were transplanted

38:07

into the skin of mice.

38:09

Now, the mice had been,

38:11

had type 1 diabetes induced

38:13

upon them, and when they

38:15

put this tissue that included

38:18

very healthy islet cells and

38:20

blood vessels into the skin

38:22

of the mice, they found...

38:24

that after transplantation, the islet

38:27

cells in the skin, they

38:29

survived and they produced insulin

38:31

and they were actually able

38:33

to reverse the effects of

38:35

type 1 diabetes on these

38:38

mice and the mice did

38:40

not have to have any

38:42

further modification or addition of

38:44

insulin to be able to

38:46

manage their insulin levels. So

38:49

the idea is that we

38:51

are taking the human cells

38:53

and putting them in mice

38:55

and one day instead of

38:58

maybe having an insulin pump

39:00

that is, you know, transplanted

39:02

into the surface of your

39:04

skin, maybe it's actually a

39:06

bunch of your own cells

39:09

that are able to be

39:11

there and manage your blood

39:13

glucose. So one step at

39:15

a time, they think they

39:18

are going to get there.

39:20

I think it's a very

39:22

exciting step forward here. Yeah,

39:26

that's awesome. Yeah. And what's interesting

39:29

to me also is that they

39:31

didn't, that this doesn't have to

39:33

be a pancreatic graft or transplant,

39:36

that the transplant isn't just into

39:38

this into the skin. It's on

39:40

the in the abdomen of the

39:42

of the mice. And so something

39:45

like this is something that could

39:47

easily be done in it with

39:49

in humans. It could be. it

39:52

wouldn't have to be a hugely

39:54

invasive surgery and it would also

39:56

be easily accessible should there be

39:59

any, you know, any issues moving

40:01

forward. But that said, again, years

40:03

and years of research to go.

40:05

Don't expect it to be like

40:08

right away. This is still in

40:10

mice, but it's a very, very

40:12

neat advancement. Getting just getting the

40:15

blood vessels and the pancreatic islet

40:17

cells to be happy together. And

40:19

then for them to be like,

40:21

we'll be happy in the skin

40:24

of a mouse. Yeah, that's great.

40:26

So, you know, hopefully it'll all

40:28

work really well moving forward. I

40:31

think a lot of people, it

40:33

would be, it would help out

40:35

a lot of people. Treatment for

40:38

type 1 diabetes is something that

40:40

could help to save a lot

40:42

of lives. Make a lot of

40:44

lives better for longer. Usually. Yes.

40:47

All right. This is

40:49

this week in science. I hope

40:51

that we make your lives better,

40:54

longer, that you come here for

40:56

your little science talking points, that

40:58

you can, or thinking points, you

41:00

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41:03

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41:05

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41:07

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41:10

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41:12

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41:53

Blair? I don't know. Get down

41:55

to the pool with your twist

41:58

stuff. That's right. You know. You

42:00

keep, you really do, everyone, you

42:02

keep. this show going. Blair, I

42:05

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42:07

everyone out there, we can't do

42:09

it without you. Thank you for

42:11

your support. All righty Blair. All

42:14

righty everyone out there. You know

42:16

what time it is? It's time

42:18

for us to go to sleep.

42:21

No, it's time for Blair's. They

42:23

have no more corner! With Blair!

42:34

What's you got Blair?

42:37

I'm so stressed out

42:39

Kiki! No! No, why?

42:42

Are you alive? No.

42:45

Japanese macacks are stressed.

42:47

Why? Because they have

42:50

to eat with their

42:53

mother. Previous research has

42:55

shown that primates exhibit

42:58

lower stress levels when

43:01

they are with close

43:03

relatives and important social

43:06

partners. Oh, you're being

43:08

in the kids table.

43:11

Previous research has shown.

43:14

Primates in general exhibit

43:16

lower stress levels when

43:19

they're with their close

43:22

relatives and important social

43:24

partners and higher stress

43:27

levels in presence of

43:30

dominant or unfamiliar individuals.

43:32

So known entities hanging

43:35

out with them, good.

43:38

However, in this study...

43:40

They studied 11 adult

43:43

females in a wild

43:46

group of Japanese macax

43:48

on Kinsican Island in

43:51

Meiji Prefecture. So they

43:53

looked at 205 hours

43:56

of observation. total. This

43:59

is one group in

44:01

one location. So that's

44:04

my big asterisk on this.

44:06

But they look at skin scratching.

44:09

So skin scratching or

44:11

first scratching is a sign

44:13

of stress in Japanese macax.

44:16

Not just parasites. Right.

44:18

And so they looked at

44:20

self-scratching activity as

44:22

a behavioral indicator

44:24

of stress throughout

44:26

these two hundred and five

44:29

hours. And they found that

44:31

wild female Japanese

44:33

macax, they exhibit

44:36

higher stress levels

44:38

when a closely

44:40

related female is

44:42

nearby, if they are

44:45

foraging. If they are resting,

44:47

anybody nearby is

44:49

great. So, during resting, the

44:52

frequency of self-scratching was higher

44:54

when no other individuals were

44:56

nearby compared to when they

44:58

were present, so they wanted

45:00

company when they were just

45:03

hanging out. But during foraging,

45:05

self-scratching was higher when a

45:07

related female, a mother or sister,

45:09

was proximate, then when a

45:11

non-related female was present.

45:13

And no effective kinship was

45:15

observed. So, huh. Being

45:18

around a mother or a

45:20

sister, it's just about the

45:22

suggests that co-feeding with a

45:25

related female might have to

45:27

do with foraging competition.

45:30

But just generally the point

45:32

of this study is that

45:35

it breaks. Yeah, sure. Maybe

45:37

you're not doing that right.

45:39

Hold the stick differently. Oh

45:42

boy. It provides a novel view

45:44

that... Social stress is more complicated

45:46

than previously thought. So basically, the

45:48

whole point of this study is

45:51

just to break that first expectation

45:53

based on a breadth of research

45:55

that has been done previously. That's

45:58

the whole point of the study.

46:02

I think that's good. Doesn't

46:04

that what we want? Right?

46:06

Like not everything we thought

46:09

in the old days is

46:11

going to be, is right.

46:13

We did a limited number

46:15

of studies and this is

46:18

what we assumed and let's

46:20

look at it differently. But

46:22

here is my problem with

46:24

this and I should have

46:26

opened the actual, let me

46:29

see if I can see,

46:31

do they have a family

46:33

tree for the group that

46:35

they looked at? Because they

46:38

looked at one group of

46:40

11. monkeys. And I don't

46:42

see a family tree. I

46:44

really want to see a

46:47

family tree for these 11

46:49

monkeys because is there one

46:51

mother? Right. Are there multiple

46:53

mothers? So related. Is this

46:56

one mother just really not

46:58

nice? Like there's so many

47:00

questions. group where mom stresses

47:02

everybody out. Is that the

47:05

norm or is that that

47:07

one mom? Well it did

47:09

say kin also be it

47:11

was like sisters too. Sisters

47:14

too. But that could be

47:16

a reflection of a stressful

47:18

mom. Yeah. What's

47:20

the order of the birth order

47:23

of the of the kin? What

47:25

is the? Yeah, what's the age?

47:27

What's the relatedness? What is, you

47:30

know, if it is a female

47:32

competition in a certain way, like,

47:35

have you shared a partner at

47:37

some point in the past or

47:39

is there, you know, how does

47:42

that go into foraging competition? What

47:44

does that have to do? There

47:47

are so many more questions to

47:49

answer here, but. Yeah, well and

47:51

is 11 a normal size for

47:54

Japanese macaques? Is it a larger

47:56

group? Is it a smaller group?

47:59

If it's a smaller group than

48:01

normal, did they just run into

48:03

their family way more? than other

48:06

Japanese macaques and they're like, huh,

48:08

you again. I know you. Or

48:11

did they spend a lot of

48:13

time really trying to stay away?

48:15

Right. Really? Mom, leave me alone.

48:18

No, I'm going to this tree.

48:20

Just leave me alone. It's one

48:23

group. It's one group over one

48:25

series of tests with one group

48:27

of individuals, right? So it's very

48:30

specific. But the point is. Not

48:32

big enough, but yeah. The point

48:34

is that just because you're around

48:37

related monkeys does not mean you're

48:39

inherently less stressed. I think that

48:42

is applicable. In the human primate

48:44

world as well. Right. Yeah. And

48:46

if you, I don't know if

48:49

you relate to those monkeys at

48:51

all. then you might find yourself

48:54

wondering how much in common you

48:56

might have with monkeys or with

48:58

ducks or with dogs. We're just

49:01

animals in general and so you

49:03

might wonder what is consciousness? Am

49:06

I conscious? Is it just so

49:08

often you've no idea of Blair?

49:10

and turn down the overhead and

49:13

hang up your beaded curtain, let's

49:15

talk about it. No, there's an

49:18

essay that was released this week

49:20

in science and it talks about

49:22

some potential methods for measuring consciousness

49:25

because until now it has been

49:27

an imperfect system and I... pause

49:30

it, it will continue to be

49:32

an imperfect system because I'm going

49:34

to argue pretty much everything's conscious

49:37

depending on how you want to

49:39

define consciousness, but I think everything's

49:42

kind of aware it exists. Some

49:44

people even argue that rocks... some

49:46

degree. I would argue that consciousness

49:49

is a quantum or... Right? Yeah.

49:51

There are people who argue that

49:54

with fervor, indeed. So... Not just

49:56

plants, but the phonges. Right, right.

49:58

Absolutely. Absolutely. So, you know, I

50:01

mean, does it matter? Here's why

50:03

it matters, actually. Let me answer

50:06

my own question. Last year, I

50:08

think I reported on it. I

50:10

don't recall. New York, there was

50:13

a New York declaration on animal

50:15

consciousness. And that demonstrated scientific backing

50:18

for consciousness among firstly all vertebrates

50:20

and then many invertebrates. And so

50:22

this kind of created the shock

50:25

waves in the scientific community because

50:27

if you address consciousness, that changes

50:30

how you can research on those

50:32

individual animals. Not to say that

50:34

scientists were upset about it, but

50:37

it just does change things. Right.

50:39

Scientists, they're going to debate, continue

50:42

to debate it. Right. And it

50:44

does make things more complicated. And

50:46

what if you applied for a

50:49

grant for a specific study and

50:51

now you can't perform that study

50:54

as you had applied to the

50:56

grant to do? Right. So there's

50:58

lots that could be implicated there.

51:01

There's lots to be considered, but

51:03

ultimately there was this kind of

51:06

sweeping declaration that all vertebrates are

51:08

conscious and many invertebrates are conscious.

51:10

And so... the question is how

51:13

do you test that? Yep. And

51:15

so this essay... posited a new

51:18

method called a marker method, which

51:20

essentially works to identify behavioral and

51:22

anatomical features associated with consciousness processing

51:25

in humans, and then you search

51:27

for similar properties and non-human. And

51:30

you don't just find one, because

51:32

you could find one pretty easily,

51:34

but you have to find multiples

51:37

and try to map them on

51:39

each other and make them follow

51:42

some sort of rhyme or reason

51:44

that is consistent with consciousness across

51:46

all. these different markers. So that

51:49

might be experiencing pain. or seeing

51:51

an object, things that you do

51:54

bodily to respond to that, doesn't

51:56

animal do that? Like if you're

51:58

in pain, do you pull your

52:01

hand away from the thing that's

52:03

causing pain? Does an animal do

52:06

that? Yes, absolutely. Does that mean

52:08

they're aware of their own body?

52:10

Unclear. So now you have to

52:13

stack these different markers, right? And

52:15

so they say the degree to

52:18

which a particular marker can increase

52:20

or decrease confidence in particular dimensions

52:22

of animal consciousness depends on the

52:25

context. So basically just depends. For

52:27

instance, linguistic behavior is a marker

52:30

of specific kinds of conscious thought

52:32

and emotion in humans. But as

52:34

demonstrated by large language models. that

52:37

simulate human conversation, linguistic behavior alone

52:39

is not strong evidence of consciousness

52:42

and non-human systems. So it is

52:44

a marker. So you have to

52:46

stack markers and go, I have

52:49

enough markers that I find consciousness.

52:51

So this is what was kind

52:54

of promoted here. And that's why

52:56

it's important. It's important to know

52:58

how we care for these animals,

53:01

how we do experiments on these

53:03

kinds of animals. Interesting. But it's

53:06

obviously just been kind of proposed

53:08

it hasn't even been tested yet

53:10

But I thought it was a

53:13

really interesting question because I know

53:15

we've talked a bunch about like

53:18

the dot test in the mirror

53:20

and whether that proves a sense

53:22

of self or consciousness And that's

53:25

really complicated because like you have

53:27

to understand how a mirror works

53:30

You have to understand that that

53:32

dot isn't supposed to be there

53:35

But then there's the question

53:37

also is, you know, like

53:39

this is getting at, is

53:41

there a distribution of complexity

53:43

of consciousness? Yeah, where there's,

53:45

you know, like minimally conscious,

53:47

right, a plant possibly, you

53:49

know, and then at very,

53:52

as you add different markers

53:54

together in different ways, there

53:56

are different kinds. of consciousness

53:58

maybe, similarly to intelligences and

54:00

maybe even, you know, I

54:02

don't know, I'm imagining a

54:04

Venn diagram, you know, you

54:06

know, multiple, multiple different domains

54:08

that can overlap or not.

54:10

Yeah, no, absolutely. Yeah. That's,

54:12

I immediately think about when

54:14

you're talking about the plants,

54:16

how, you know, I mentioned

54:18

the idea that you shy

54:20

away from pain or you

54:22

pull your hand away from

54:24

pain. Plans do do that.

54:26

It just takes a long

54:28

time. You have to be

54:30

patient. Except for the mimosa

54:33

pudica. Right. Oh, they're more

54:35

biased. mimosa. We'll always have

54:37

an important part in my

54:39

heart. Yeah, so I hope

54:41

to hear more about this

54:43

in the coming years. I

54:45

hope to hear some researchers

54:47

using the marker method so

54:49

that we can decide if

54:51

it's worth anything or not

54:53

from our armchairs over here.

54:55

it has to you have

54:57

to come up with the

54:59

idea before you can test

55:01

it right so yes absolutely

55:03

it maybe gives a method

55:05

a methodology for comparison across

55:07

various species is you know

55:09

to build it yeah because

55:11

that's one of the hard

55:14

parts is going how do

55:16

you know that this is

55:18

consciousness as opposed to just

55:20

sensory awareness and are they

55:22

really aware? I mean, is

55:24

it just a reflex? Is

55:26

it, you know, is it

55:28

that the animal is conscious

55:30

of what's going on or

55:32

the plant is conscious? Is

55:34

there an awareness of it

55:36

at any level? Does it

55:38

matter that it is only

55:40

a chemical signal or a

55:42

nervous signal that it happens?

55:44

Like when the doctor hits

55:46

your knee cap to make

55:48

the kick reflex? You're aware

55:50

of the kick having happened,

55:52

but you are not aware

55:55

of, you know, the things

55:57

that you, that that whole

55:59

process of the tendon on

56:01

your knee being tapped and

56:03

then your leg kicking out.

56:05

is not something that you

56:07

are in control of. So

56:09

there's, you know, I think

56:11

there, you look at it

56:13

and you go, oh, that's

56:15

interesting. And that felt strange.

56:17

Hmm. Higher consciousness looking at

56:19

lower nervous, oh, processes. And

56:21

are those nervous processes somehow

56:23

chemically aware of themselves? So

56:25

many layers layer. You open

56:27

one of my favorite boxes.

56:29

Let's pull it all out.

56:31

Keep it open. Yeah. Yeah,

56:33

like is planning for the

56:36

future is that consciousness, right?

56:38

Like if I'm a squirrel

56:40

and I'm hiding my acorns.

56:42

Am I aware? Or am

56:44

I following a kind of

56:46

an impulse? Yeah, exactly. Yeah.

56:48

If I'm a monarch butterfly

56:50

who only flies one way

56:52

and then dies of a

56:54

migration, am I aware of

56:56

what I'm doing or am

56:58

I just compelled to go

57:00

somewhere? And are you even

57:02

aware of that compulsion? You

57:04

know, it's just, yeah, just,

57:06

it happens, it's as if

57:08

it happens to you, in

57:10

a sense. Yeah, yeah, these,

57:12

I think these are very

57:14

fascinating questions, you know. I

57:17

think therefore I am. Am

57:19

I? So good. We am.

57:21

We am what we am.

57:23

My goodness. Yeah, it's interesting.

57:25

Squirrels, I don't know about

57:27

their storing behavior, but I

57:29

know in chickities and nut

57:31

hatches, they are from the

57:33

minute they're out of the

57:35

nest and they are like,

57:37

summer happens, they're like, summer

57:39

happens, they're like, I can

57:41

pick up little pieces, and

57:43

I'm gonna hide a bigger,

57:45

and I'm gonna hide things,

57:47

they're like, put them places.

57:49

But do they remember? where

57:51

it is, right? Some birds

57:53

do, some birds don't. Well

57:55

those birds, because that's what

57:58

they're, that's what they do.

58:00

They do remember. So squirrels

58:02

often forget, which is very

58:04

funny. We did a story

58:06

on the show about our

58:08

squirrels were hiding nuts in

58:10

Transformers and people were losing

58:12

power because squirrels kept hiding

58:14

nuts in the Transformers. Anyway,

58:16

a great place for a

58:18

larder, but you know. You

58:20

like smoked acorns? Yeah. I

58:22

love that electricity taste. Yes.

58:24

Yes. Oh, I like Ar

58:26

and Laura's comment in the

58:28

chat here. Squirrels don't hide

58:30

acorns. They dig holes and

58:32

sometimes come across a buried

58:34

acorn. Oh, you're talking about

58:36

ground squirrels, yes. That's wonderful.

58:39

Moving on from the animal

58:41

brain, let's stay with the

58:43

animal brain, the human brain.

58:45

Yeah, that's an animal. So

58:47

I was going to go

58:49

to an oxygen pill for

58:51

this next story, but since

58:53

you brought up brain stuff,

58:55

I figured, let's just let's

58:57

just go with the brain.

58:59

Let's do it. Publishing in

59:01

the open-axis journal E-Life, researchers

59:03

from Brown University this week,

59:05

have published a model, so

59:07

it's not actually looking at

59:09

an animal doing any... action.

59:11

It was creating a circuit,

59:13

a numerical simulation, a neural

59:15

network model of interactions between

59:17

prefrontal cortex and the basal

59:20

ganglia. And they were looking

59:22

at models of how these

59:24

circuits might work together to

59:26

do what they call implementing

59:28

adaptive resource allocation in working

59:30

memory. And so for those

59:32

of you who are involved

59:34

in programming or in circuitry,

59:36

you understand maybe the idea

59:38

of gating where it's the

59:40

and or on off. and

59:42

different circuits, different components in

59:44

the circuit can be turned

59:46

on or off and or

59:48

at various times in the

59:50

processing. And if you have

59:52

a neural network, it becomes

59:54

much more complex as they

59:56

start working together. And if

59:58

they respond in relation to

1:00:01

each other because of sort,

1:00:03

if this one's on, then

1:00:05

I should be off. Or

1:00:07

if this one's on, then

1:00:09

I need to do more

1:00:11

open or whatever. I don't

1:00:13

know. I'm making things up

1:00:15

right now. The question really

1:00:17

is, what are the limits

1:00:19

of working memory? And working

1:00:21

memory specifically is the amount

1:00:23

of memory that your brain

1:00:25

is using at any particular

1:00:27

time to make sure you

1:00:29

can keep going. It's the

1:00:31

six-digit number or seven-digit number

1:00:33

limit that we're supposed to

1:00:35

have for remembering phone numbers,

1:00:37

right? The working memory capacity

1:00:39

has been tested for a

1:00:42

very long time. It's like,

1:00:44

okay, that thing you can

1:00:46

hold in your head someone's

1:00:48

name, maybe if you're, you

1:00:50

know, don't have a significant

1:00:52

executive disfunction like some of

1:00:54

us. or the topic that's

1:00:56

being discussed. Or I'm listening

1:00:58

to you Blair and I

1:01:00

remember I want to ask

1:01:02

a question but I can't

1:01:04

be rude so please don't

1:01:06

just shout it out all

1:01:08

the time and wait my

1:01:10

turn and ask a question

1:01:12

like a polite person. You

1:01:14

know holding that question in

1:01:16

my head, part of the

1:01:18

resource allocation to do that

1:01:20

is working memory and I

1:01:23

have to keep listening to

1:01:25

the story that's being told

1:01:27

at the same time. So

1:01:29

I can be like, oh,

1:01:31

okay, all right, oh, how

1:01:33

do I put it, how

1:01:35

do I put it all

1:01:37

together? It's not short-term memory.

1:01:39

It's not long-term memory. It's

1:01:41

the memory that is the

1:01:43

operating system function that is

1:01:45

basically holding things together from

1:01:47

moment to moment. And so

1:01:49

how big is that? And

1:01:51

people are like, well, yeah,

1:01:53

it's the number of circuits,

1:01:55

right? It's how much is

1:01:57

in there. It's the size.

1:01:59

That's going to determine. how

1:02:01

much you can remember. But

1:02:04

these researchers, even though they

1:02:06

didn't look at actual animals,

1:02:08

and they did this neural

1:02:10

network, their question how and

1:02:12

why is working memory capacity

1:02:14

limited, their question they determined

1:02:16

based on the model that

1:02:18

they were putting that they

1:02:20

put together, that because of

1:02:22

how certain chunking of information,

1:02:24

so if you're remembering a

1:02:26

phone number. What

1:02:29

is it? What was it?

1:02:31

What was it? 86739. The

1:02:34

chunks, the three numbers at

1:02:36

the front and the four,

1:02:38

or 867. 53009. Your memory,

1:02:41

your working memory has chunked

1:02:43

that information into little groupings.

1:02:45

So the other. capacity of

1:02:48

it. So your brain is

1:02:50

using a compression strategy to

1:02:52

improve recall efficiency. They also

1:02:55

found that they put dopamine

1:02:57

instructions into their working memory

1:02:59

model and they also found

1:03:02

that learning shapes memory limits.

1:03:04

all told what they summarize

1:03:06

and what they what they

1:03:09

say is that working limitation

1:03:11

working memory limitations are more

1:03:13

from learning challenges. So do

1:03:16

you have executive dysfunction? Is

1:03:18

dopamine not working properly to

1:03:20

allow you to continue to

1:03:23

pay attention to something long

1:03:25

enough to be able to

1:03:27

get your working memory to

1:03:30

hold on to it? And

1:03:32

if your chunking is disorganized

1:03:34

or disordered, that doesn't allow

1:03:37

you to have a higher

1:03:39

resolution capacity for that working

1:03:41

memory. So you can get

1:03:44

into overload more quickly. chunking

1:03:46

that all these things potentially

1:03:48

work together and Now that

1:03:51

they're looking at this new

1:03:53

interpretation of working memory, difficulties

1:03:56

in patients, they can suggest

1:03:58

this, instead of this anatomical

1:04:00

limit, that people, really, we

1:04:03

just chunk more, manage your

1:04:05

dopamine, your working memories, just

1:04:07

you're fine, keep going everyone.

1:04:10

Keep your brain a workout,

1:04:12

is that what you're saying?

1:04:14

That's right. Or, you know,

1:04:17

as per a couple of

1:04:19

studies from this past week,

1:04:21

maybe go on a mobile

1:04:24

internet diet for a little

1:04:26

time. Smart. One study took

1:04:28

people away from mobile internet,

1:04:31

so they still had phone

1:04:33

calls and texting, so they

1:04:35

could stay in touch with

1:04:38

people, and for two weeks,

1:04:40

they found that people became

1:04:42

happier. and had better working

1:04:45

memory, and they had, and

1:04:47

they had better mood control.

1:04:49

Similar study, they took people

1:04:52

away from their mobile devices

1:04:54

entirely, mobile detox for 72

1:04:56

hours, and they found that

1:04:59

there were changes to the

1:05:01

dopamine circuitry in the stimulus

1:05:03

reward centers of the brain.

1:05:06

So I was just thinking

1:05:08

last night that I should

1:05:10

get myself one of those

1:05:13

cricket, or not cricket phones.

1:05:15

What are they called? The

1:05:17

kids phones, the ones that

1:05:20

are like, you can give

1:05:22

yourself parental control. Exactly. So

1:05:25

it has like the six

1:05:27

buttons on it. It's like,

1:05:29

this is my phone now.

1:05:32

Brian. Yeah. That's it. See

1:05:34

about that? Like, what if

1:05:36

I just turned my phone

1:05:39

into nothing about the phone

1:05:41

app and the text app?

1:05:43

What if that's all it

1:05:46

was? I think it would.

1:05:48

I think it would be.

1:05:50

I think it would be.

1:05:53

That would be great. It'd

1:05:55

be a good thing. It'd

1:05:57

be very, very, very great.

1:06:00

I held out so long

1:06:02

on getting a smartphone, so

1:06:04

long. But it's now, yes.

1:06:07

It's, you can't, everybody has

1:06:09

it now, it's just kind

1:06:11

of expected, and I don't

1:06:14

know, maybe, maybe the next

1:06:16

generation will be like, you

1:06:18

know, it's cool, flip phones.

1:06:21

I think they already are.

1:06:23

Yeah, I don't know. Yeah,

1:06:25

we don't need all of

1:06:28

the, we don't need all

1:06:30

the things. Neural networks, very

1:06:32

exciting stuff. you know if

1:06:35

you were feeling very tired

1:06:37

and like oh my gosh

1:06:39

I must be at like

1:06:42

high altitude or something and

1:06:44

I didn't do any like

1:06:46

pressure training for this hypoxia

1:06:49

I'm feeling or you know

1:06:51

maybe you are an individual

1:06:53

who has sickle cell anemia

1:06:56

or you are someone who

1:06:58

has a disorder of your

1:07:01

mitochondria Perhaps this new work

1:07:03

out of the Gladstone Institute

1:07:05

with mice with lay syndrome,

1:07:08

L-E-I-G-H-S syndrome, with a drug

1:07:10

called hypoxysat, maybe it might

1:07:12

be something that will interest

1:07:15

you if they ever get

1:07:17

it out to market, which

1:07:19

they hope to do. I

1:07:22

don't know. Hopefully sometime soon.

1:07:24

The idea though is that...

1:07:26

looking to work on the

1:07:29

problem of hypoxia, which is

1:07:31

the inability of oxygen to

1:07:33

be getting to the cells

1:07:36

of the body. And the

1:07:38

underlying issue with that very

1:07:40

often is an inability of

1:07:43

the hemoglobin to grab onto

1:07:45

oxygen within the blood. So

1:07:47

these Gladstone Institute researchers were

1:07:50

like, hey, not everybody who...

1:07:52

who has sickle cell anemia,

1:07:54

you know, can get the

1:07:57

treatments that they need and

1:07:59

in Lee syndrome this is

1:08:01

is a childhood mitochondrial disease,

1:08:04

the treatment is actually, they

1:08:06

have to go live at

1:08:08

high altitude because if they

1:08:11

live at areas where there's

1:08:13

a higher oxygen, saturated oxygen

1:08:15

concentration, then it's too much

1:08:18

oxygen and their mitochondria can't

1:08:20

handle it. So it's the

1:08:22

opposite. So anyway, they were

1:08:25

working on these issues of

1:08:27

mitochondrial disease and. hypoxia and

1:08:30

people, you know, you go

1:08:32

up to the mountains and

1:08:34

you're not ready for it

1:08:37

and you don't get enough

1:08:39

oxygen into your blood. You

1:08:41

can inhale more oxygen if

1:08:44

you get one of those

1:08:46

nice canned oxygen thingies. But

1:08:48

they found that they were

1:08:51

able to create a drug

1:08:53

that they call hypoxy stat

1:08:55

and it's a repurposed compound

1:08:58

that was initially designed for

1:09:00

an unrelated aspect of sickle

1:09:02

cell anemia. And when they

1:09:05

used it, the drug made

1:09:07

hemoglobin bind oxygen more tightly

1:09:09

than it normally does. And

1:09:12

so it's the remarkable thing

1:09:14

about it that I think

1:09:16

is just the... the glacier

1:09:19

on the top of the

1:09:21

mountain for this particular for

1:09:23

this particular study is that

1:09:26

it's a small molecule that

1:09:28

can be easily put into

1:09:30

a pill form so it

1:09:33

could potentially be an easily

1:09:35

given drug to treat hypoxia

1:09:37

and it works it works

1:09:40

super easily. And here I'm

1:09:42

going to see about sharing

1:09:44

this tab here with everybody.

1:09:47

So you can see the

1:09:49

pretty pictures that they came

1:09:51

up with for this concept

1:09:54

of hypoxysat, which is a

1:09:56

small molecule hypoxia therapy. And

1:09:59

it allows the oxygen to

1:10:01

be grabbed onto and and

1:10:03

moved around more readily than

1:10:06

the hemoglobin for these individuals

1:10:08

with the mitochondrial disorder. It

1:10:10

could also be a treatment

1:10:13

for people who actually have

1:10:15

hypoxia for whatever reason. And

1:10:17

so in its hypoxia over

1:10:20

time can lead to damage

1:10:22

to the organs and to

1:10:24

the body. this hypoxy stat,

1:10:27

this is the glacier on

1:10:29

the top of the mountain,

1:10:31

hopefully it won't melt away,

1:10:34

it treated the damage to

1:10:36

the brain. When they were

1:10:38

given this drug it actually

1:10:41

reversed damage to the body

1:10:43

and to the brain, not

1:10:45

just to whatever was acutely

1:10:48

happening at the time it

1:10:50

reversed damage. So can I

1:10:52

take that pill instead of

1:10:55

breathing? No, right? No, no,

1:10:57

it wouldn't be a replacement

1:10:59

for breathing, no. The first

1:11:02

thing I thought of was

1:11:04

oxygen gum, that's from something,

1:11:06

right? I'm like, oh, sounds

1:11:09

like something in doctor who,

1:11:11

no, I looked it up,

1:11:13

duck tails. It was the

1:11:16

reboot of duck tails, is

1:11:18

what it's from. Oxy, too.

1:11:20

and yeah oh man oxygen

1:11:23

gum like oxygen gum could

1:11:25

be possible based on this

1:11:28

oxygen gum could be possible

1:11:30

so the idea for in

1:11:32

space on a mountain underwater

1:11:35

oh not underwater wherever good

1:11:37

times we're had wherever not

1:11:39

enough oxygen is had potentially

1:11:42

this drug could be a

1:11:44

treatment that would be made

1:11:46

available. So I think it's

1:11:49

very exciting. Thanks a lot.

1:11:51

Researchers who are working on

1:11:53

these awesome treatments and thanks

1:11:56

for remembering Ducktail's Blair. Yeah.

1:11:58

I have one last story.

1:12:00

You went ready for... for

1:12:03

our last story for the

1:12:05

night. Oh yeah. Yes, everybody

1:12:07

ready to go get some

1:12:10

good sleep? Yes. Yes. Is

1:12:12

the story about sleep? Oh.

1:12:14

Well, it is, yeah. Do

1:12:17

you have a certain person

1:12:19

in your life who is

1:12:21

continuing to work night shift?

1:12:24

Not currently. So, going back.

1:12:26

But he did for... So

1:12:28

going back on night shift,

1:12:31

going back on night shift,

1:12:33

acclimating to the night shift

1:12:35

is really rough. So then

1:12:38

we've talked a lot about

1:12:40

the problems of metabolism, circadian

1:12:42

issues, when people do have

1:12:45

night shift work jobs and

1:12:47

the health detriment that come

1:12:49

as a result of that.

1:12:52

New study suggests you could

1:12:54

take melatonin. He

1:12:58

definitely tried that. All right.

1:13:00

Here's the here's the deal

1:13:02

for this study. Published in

1:13:04

BMJ British Medical Journal. The

1:13:07

researchers looked at melatonin supplementation

1:13:09

and oxidative DNA repair capacity

1:13:11

among night shift workers. This

1:13:13

was a randomized placebo controlled

1:13:16

trial. Basically they found. We're

1:13:18

using appropriate melatonin supplementation that

1:13:20

it improved oxidative DNA damage

1:13:22

repair capacity. So the damage

1:13:25

that we were talking about

1:13:27

that occurs, if melatonin is

1:13:29

taken, the intervention is taken

1:13:31

appropriately with the right quantity

1:13:34

and in the right timing,

1:13:36

that capacity can be improved

1:13:38

among night shift workers. And

1:13:40

they say further larger scale

1:13:43

trials are needed to evaluate.

1:13:45

varying doses of melatonin. And

1:13:47

also to look into questions

1:13:49

of long-term use of melatonin

1:13:52

supplements. But the commentary on

1:13:54

this is very much a

1:13:56

lot of, now people pop

1:13:58

a melatonin and think it's

1:14:01

going to make them sleepy.

1:14:03

And they're like, okay, I'll

1:14:05

be asleep in a half

1:14:07

an hour because I took

1:14:10

a melatonin and they're taking

1:14:12

like maybe a one milligram

1:14:14

or even a five milligran

1:14:16

melatonin. Like a half an

1:14:19

hour before you go to

1:14:21

bed. Well. the brain releases

1:14:23

melatonin approximately two hours before

1:14:26

you go to sleep. So

1:14:28

if you really want to

1:14:30

use melatonin for its purpose,

1:14:32

which is to entrain your

1:14:35

body clock, your circadian rhythm,

1:14:37

to a particular sleep and

1:14:39

light cycle, dark and light

1:14:41

cycle, if you take your

1:14:44

melatonin, which is released at

1:14:46

like 0.01 milligrams to 0.03

1:14:48

milligrams. per body weight. By

1:14:50

the body, by the brain,

1:14:53

a couple of hours, and

1:14:55

it is released a couple

1:14:57

of hours before you go

1:14:59

to sleep, that's the signal

1:15:02

that, oh, in the next

1:15:04

couple of hours, this is

1:15:06

going to start happening. Non,

1:15:08

hey, get sleepy in a

1:15:11

half an hour, go to

1:15:13

bed. Melatonin is not a

1:15:15

go-to-bed pill. It is a

1:15:17

train your clock. Interesting.

1:15:20

Treatment. And so as an

1:15:22

intervention, if you take it

1:15:25

at a good time period

1:15:27

and not too much of

1:15:29

a dose before you go

1:15:32

to sleep, you can set

1:15:34

your clock, but you need

1:15:36

to stick to your clock.

1:15:39

Because that's what it is.

1:15:41

That's what it's for. Oh,

1:15:44

I see Brian. Hi, Brian.

1:15:46

Who me? How come

1:15:48

doctors are prescribing it right

1:15:50

then? Is it just because

1:15:52

there hasn't been enough research?

1:15:54

And so this is some

1:15:56

of the stuff that now

1:15:58

is going to go on

1:16:00

a medical journal and now

1:16:02

doctors will start prescribing. it

1:16:04

differently? Hopefully, yeah, because people

1:16:06

learn, doctors learn, yes, melatonin,

1:16:08

it's good for getting sleep,

1:16:11

but maybe they forget, you

1:16:13

know, it's like, there are

1:16:15

specifications for how you're supposed

1:16:17

to take it, but yeah,

1:16:19

this is for sleep, right?

1:16:21

This is to help you,

1:16:23

you know, and it's not,

1:16:25

it's not something that is

1:16:27

addictive, it doesn't have like...

1:16:29

You know, it's not supposed

1:16:31

to have terrible side effects,

1:16:33

right? Well, it's over the

1:16:35

counter. It's over the counter.

1:16:37

You just buy it in

1:16:39

the supplement eye. There are,

1:16:41

you know, drinks that you,

1:16:43

little powder drinks, you take

1:16:45

a big old scoop, put

1:16:47

it in a cup. It's

1:16:49

like magnesium and melatonin and

1:16:51

who knows how much is

1:16:53

in there. You add water,

1:16:55

you drink it, go to

1:16:57

sleep. In honor of Justin

1:16:59

who is not here tonight,

1:17:01

I have to mention then

1:17:03

that a lot of melatonin

1:17:05

is packaged and sold by

1:17:07

supplement companies who are not

1:17:09

regulated. Great great points for

1:17:11

that. So is that melatonin

1:17:14

you're taking actually melatonin is

1:17:16

it actually the amount that

1:17:18

it says that it is?

1:17:20

Is there anything else in

1:17:22

there? Right. What else is

1:17:24

in there? As that, magnesium

1:17:26

is going to react, is

1:17:28

going to relax you as

1:17:30

well. How do all these

1:17:32

things work together? And if

1:17:34

the amount is so important

1:17:36

and we can't confirm that

1:17:38

each pill has the exact

1:17:40

milligrams that they say that

1:17:42

it has. That's exactly it

1:17:44

as well and how much

1:17:46

is going to be bio

1:17:48

available? So say it's a

1:17:50

one milligram. pill, but not

1:17:52

that much is actually bioavailable

1:17:54

by the time it gets

1:17:56

broken down and gets into

1:17:58

your body. Maybe it is

1:18:00

closer to point one or

1:18:02

point three. You know, that's

1:18:04

still, I think, more than

1:18:06

what your body's releasing, but

1:18:08

it's at least at least

1:18:10

closer by a couple of

1:18:12

factors of 10. Yeah, so

1:18:14

there are a lot of

1:18:17

things that I think that

1:18:19

yeah, the information and education

1:18:21

on how melatonin actually works

1:18:23

and how it how it

1:18:25

influences the entrainment of your

1:18:27

circadian rhythm. You know, that

1:18:29

is very important. But melatonin,

1:18:31

when used by shift workers,

1:18:33

it improves. there a capacity

1:18:35

to repair DNA oxidative damage

1:18:37

which suggests that there are

1:18:39

ways that if you're doing

1:18:41

regular work and you can

1:18:43

get yourself into the cycle

1:18:45

that you need to be

1:18:47

in that you can that

1:18:49

melatonin can be an intervention

1:18:51

to help to help with

1:18:53

that you know off-shift cycle.

1:18:55

Interesting. Yeah that's really not

1:18:57

how it's... advertised or

1:19:00

prescribed currently. So yeah, think

1:19:02

about the things that you

1:19:04

take over the counter. It

1:19:06

will help you sleep for

1:19:08

sure, but it's not, but

1:19:11

if you're taking it at

1:19:13

different times every day and

1:19:15

you're just using it as

1:19:17

a sleeping pill or a

1:19:19

sleeping aid that is not

1:19:22

how it should be used.

1:19:24

It's for your clock. It's

1:19:26

for your clock people. Your

1:19:28

internal clock. It would be

1:19:31

like. It's like you're supposed

1:19:33

to take that and then

1:19:35

when you wake up you're

1:19:37

supposed to take vitamin D,

1:19:39

right? So if you're a

1:19:42

shift worker. Mm-hmm. Yeah, I

1:19:44

was looking at those for

1:19:46

a whole spectrum UV light

1:19:48

to be able to stimulate

1:19:50

it. Yes. Because that's nice

1:19:53

and then it's also I

1:19:55

really like the idea of

1:19:57

waking up to a solar

1:19:59

light to that like gentle,

1:20:01

gentle, and gummies for

1:20:04

the yummy sugar. It's wonderful

1:20:06

in the winter. I mean,

1:20:08

those kinds of UV lights

1:20:10

when they come on like that

1:20:13

with your morning. It's like,

1:20:15

ah, you want like sleeping

1:20:17

beauty birds to be tweatling

1:20:20

at you? Yes. But on

1:20:22

that, uh, zombie Tom

1:20:24

Hanks. Don't eat melatonin

1:20:26

gummies for the yummy sugar.

1:20:28

As long as it's a

1:20:30

night, it's probably very little

1:20:32

in each gummy bear as it

1:20:34

is. We'll see about that. Make sure

1:20:37

you, we have no idea, who knows,

1:20:39

who made sure to quantify

1:20:41

that supplement that you got

1:20:43

over the counter. Who's regulating? This

1:20:45

is gummy bear, does not have

1:20:47

enough. This gummy bear has too

1:20:50

much. This gummy bear has too

1:20:52

much. This gummy bear. This gummy

1:20:54

bear has too much. This gummy

1:20:56

bear. This gummy bear. This gummy

1:20:59

bear. He's just right.

1:21:01

That's right. On

1:21:03

that note. We had

1:21:06

enough gummy bears,

1:21:08

Blair. Yeah, yeah. Those

1:21:10

gummy bears are

1:21:13

kicking in. I gotta

1:21:15

go! Well, don't leave

1:21:17

until we say a

1:21:20

whole bunch of thank

1:21:22

yous. Before we go, I do want

1:21:24

to say thank you so much to

1:21:27

everyone who's here watching the show live

1:21:29

with us as we are broadcasting. Thank

1:21:31

you to everyone in the chat room.

1:21:33

Thank you to our discorders. I know

1:21:36

I'm not in there today, but Blair

1:21:38

is. I will get my computers and

1:21:40

everything back up again to be able

1:21:42

to get into my discord. It's going

1:21:45

to happen one thing at a time.

1:21:47

Shout outs! Vada, thank you so much

1:21:49

for your time for the social media,

1:21:51

for the show notes, for all that you

1:21:53

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1:21:55

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1:21:57

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1:21:59

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1:22:02

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1:22:06

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as always, I really absolutely need

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