0:16

I'm I'm Joel Parker, and

0:18

this is Hell on Earth,

0:20

the Kagan U Today is Tuesday, December

0:23

31st, 2024.

0:25

2024. Coming up, a look

0:28

back up, of a look back

0:30

at some of from

0:32

science stories

0:34

from and computers

0:36

and artificial intelligence

0:39

to genetics and

0:41

pandemics. Well,

1:00

new year, How on Earth,

1:02

on Earth, friends. time of of can't

1:04

turn around without bumping into some

1:07

into some of the past year. the

1:09

past our last show on this

1:11

last day of the year. the

1:13

year, the How Earth Earth looks back at

1:15

a few of the science stories of

1:17

2024. of 2024. rather

1:19

than trying to compile

1:21

a consensus consensus top 10. We We

1:24

have a selection of just a

1:26

few stories our team pulled together that

1:28

they found interesting they hope you do

1:30

too. and are too.

1:32

to look back as

1:34

a reminder of the year

1:36

reminder of some might be

1:38

precursors of breakthroughs in the

1:40

future. in the future. University

1:57

of Colorado Boulder

1:59

Professor. and Nobel Prize winner

2:01

Tom Czech spoke with our

2:03

science show team about a

2:06

discovery he made that keeps

2:08

on giving. It involves small

2:10

segments of molecules within our

2:12

cells called ribonucleic acid or

2:15

RNA for short. It used

2:17

to be thought that all

2:19

big events in our cells

2:21

center on our impressively long

2:23

and complicated... DNA and that

2:26

the tiny RNA strands had

2:28

a menial job of carrying

2:30

messages between DNA and protein-making

2:32

factories inside ourselves. Tom Czech

2:35

has helped the world understand

2:37

that the lowly little RNA

2:39

actually works as a catalyst.

2:41

Not only can RNA carry

2:43

messages, R&A can also change

2:46

things throughout ourselves, so they

2:48

are catalysts, and he's written

2:50

a book about R&A titled

2:52

The Catalyst, R&A, and The

2:55

Quest to Unlock Life's Deepest

2:57

Secrets. Here's more from Tom

2:59

Czech, speaking to Shelley Schlander.

3:01

Many RNAs that we study

3:03

at C.U. Boulder are noncoding.

3:06

That means they don't even

3:08

care about transferring message from

3:10

DNA to the synthesis of

3:12

proteins, but they have other

3:15

functions in the cell. That

3:17

little tiny snippet. of is

3:19

it protein? It's not proteins,

3:21

you know, protein is a

3:23

different class of molecules. The

3:26

building blocks of R&A, like

3:28

those of DNA, are called

3:30

nucleotides, and there are just

3:32

four different flavors of these.

3:35

Their abbreviations are A, G,

3:37

C, and you, and so

3:39

you wouldn't think that something

3:41

as simple as that could

3:43

have such wondrous capabilities and

3:46

potential. With all

3:48

we need are

3:50

all bits of

3:52

information bits of

3:55

and zeros and

3:57

we can

3:59

do amazing we can

4:01

do bits of

4:03

information is

4:06

plenty to drive

4:08

a limitless

4:10

number of shapes

4:12

and functions

4:15

with instead of instead of

4:17

being just little messengers

4:19

that dutifully take. information from

4:21

DNA to the factories inside of

4:23

our cells that make the proteins

4:25

that make us us think... run do all

4:27

do all of the stuff that our bodies

4:29

can do. can do. You of talk

4:31

like like has a little mind

4:33

of its own. of its I

4:35

don't know if I

4:37

would say know if of its

4:39

own, but it certainly

4:41

is able to accomplish some

4:43

amazing tricks. If I I recall,

4:45

your Nobel Prize was not not

4:48

for... ribonucleic acid itself.

4:50

No, the the work that

4:52

we did in the early

4:54

that led to to the prize

4:57

in 1989 pond done

4:59

in a pond animal that

5:01

inhabits the world a throughout the

5:03

world, a little means it has

5:05

which means it has

5:07

little fuzzy projections that scoot

5:09

it around the pond. Its

5:11

name is tetra hymena. Is this

5:13

the one that you got from

5:16

the the Ponskum on varsity pond at CU Boulder? that

5:18

was actually yet a different

5:20

discovery by David Prescott, who

5:22

was a was a in the molecular

5:24

cellular Biology biology mean

5:26

you weren't the only one who was doing things

5:28

like looking one who weren't the only

5:30

ones, and looking at of wonders

5:33

of nature that you can

5:35

find of you look for that

5:37

you can find if you organisms to

5:39

study, right now it seems

5:41

pretty much limitless. limitless. more out there to

5:43

discover from the things that have figured out how

5:45

to be alive out how to be we don't know how they

5:47

figured it out they figured it out. They

5:49

figured it out in so many

5:51

different ways. mean, you go

5:53

to Yellowstone, you know, know, Park, and

5:55

you see organisms that are

5:57

giving these wondrous colors to the

5:59

morning... pool and these are living in

6:02

boiling temperatures often at extremely acidic

6:04

conditions and yet they found a

6:06

way to survive and to thrive

6:08

in what we would consider to

6:10

be a very hostile environment. So

6:12

you're curious about all these things

6:15

and how things are alive and

6:17

what exactly did you get that

6:19

Nobel Prize for then? We were

6:21

studying a process called RNA splicing

6:23

which we didn't discover had been

6:25

discovered. just a few years earlier

6:28

on the East Coast, where an

6:30

RNA molecule that is made as

6:32

a long RNA is cut and

6:34

pafed it together to form a

6:36

shorter RNA molecule. And why this

6:38

happens is still debated by scientists,

6:40

how this got started, but we

6:43

know that it's absolutely essential for

6:45

life. The analogy I like to

6:47

use is your favorite film. and

6:49

there's a commercial message and you

6:51

wouldn't you just like to be

6:53

able to cut that out snip

6:56

it out you know listen to

6:58

and watch the the good parts

7:00

without the commercial interruption so these

7:02

interruptions are rampant especially in RNAs

7:04

made from human genes Typically, every

7:06

one of our genes has about

7:09

10 such interruptions in it, and

7:11

the length of the commercial messages

7:13

is much longer than the length

7:15

of the useful parts of the

7:17

gene. Although every now and then

7:19

the supposedly advertising junk parts end

7:21

up being useful, but you think

7:24

these R&A snippeters... have figured out

7:26

what the really junkie stuff is

7:28

to get out there. Well, Shelley,

7:30

you make a good point that,

7:32

you know, nature is the great

7:34

opportunist and anything that starts out

7:37

as junk, if a biological system

7:39

can find a way to make

7:41

something useful out of it, that

7:43

happens. And we see that over

7:45

and over and over again. So

7:47

I wouldn't call these... junk, it

7:50

but it is

7:52

critical for making

7:54

a useful product

7:56

out of the

7:58

gene they they

8:00

be snipped out. that

8:03

that was the

8:05

process that we

8:07

were investigating when

8:09

we unexpectedly and

8:11

very curiously found

8:13

that the RNA

8:15

by itself was

8:18

capable of folding

8:20

up into a

8:22

complex three -dimensional

8:24

shape shape and splicing itself

8:26

of the larger

8:29

This was an was an

8:31

activity that had previously

8:33

been thought to be requiring

8:35

protein enzymes to accomplish. And

8:38

so we found that the

8:40

RNA was sufficient to power

8:42

its own splicing. And this

8:44

turned out to be the

8:46

first example of what we

8:48

call RNA catalysis. That

8:51

That was How on Earth

8:53

science show Show volunteer Shelley with

8:55

University of Colorado professor

8:57

and Nobel Prize winner and

8:59

an excerpt from our Tom Czech

9:01

in an Tom Cech's book 15th

9:04

show about Tom Czech's book The the

9:06

quest to unlock life's

9:09

deepest life's deepest

9:11

secrets Our

9:34

next pick is a story

9:36

about flu. flu. We

9:38

all recently have experienced

9:40

the of of a pandemic

9:42

with COVID, which which perhaps serve

9:44

as a cautionary tale for

9:46

how to monitor other

9:48

pathogens among animals and protect

9:50

from transmission to humans,

9:52

as Beth Bennett reports in

9:54

this update in a story

9:56

we aired in our

9:58

July 23rd 23rd show. Avian

10:01

has been in the news a lot this

10:03

year, but but around a lot longer. a lot longer.

10:05

Birds, especially waterfall, are are uniquely

10:07

afflicted by flu viruses because

10:09

they flock. Consequently, they

10:12

transmit readily to each other. other. They can They

10:14

can also infect other species because

10:16

they migrate, their droppings, loaded with

10:18

virus, land on on very... other animals.

10:20

Because Because domestic flocks are so

10:22

large, they're easily infected in

10:25

this way, this resulting in in mortality.

10:27

In In fact, previous outbreaks of H5N1

10:29

originated in domestic birds to spread

10:31

to wild ones, but this

10:33

variant of the virus has flipped

10:36

that scenario. scenario. A bit of of background,

10:38

the H&N refer to two types of proteins

10:40

found on the surface of the

10:42

virus. virus. There are 18 flavors of H, which

10:44

attach virus to a host cell, 11

10:46

and 11 of N, which releases

10:48

new virus from the infected cell. can

10:50

you can only imagine the possible

10:52

number of of combinations. A bird flu flu virus

10:54

can easily jump from one bird species

10:56

to another, but rarely jumps from birds to

10:58

birds to humans. As we've seen this year,

11:00

the H5N1 virus can infect cattle the

11:02

the close contact between dairy cattle and

11:04

the people who work with them. with them can

11:07

result in a relatively minor eye infection. Fortunately,

11:10

for us, us, it's still uncommon

11:12

for people to be directly infected

11:14

with the respiratory virus from

11:16

birds, and and even less common

11:18

is human -to -human transmission. transmission. When a a

11:20

person contracts H5N1, it can be

11:22

really severe, causing respiratory

11:25

distressed, pneumonia, and organ failure.

11:27

The the mortality rate for

11:29

human H5N1 infections has been

11:31

notably high, high, ranging from 50

11:33

to 60 reported cases. This makes

11:35

it makes it one of the deadliest

11:37

flu strains known. The big concern big

11:39

concern with H5N1 like other avian flu

11:41

viruses is its potential to evolve

11:43

into a strain that could sustain. human

11:46

to human transmission. the The

11:48

more people are infected, the more

11:50

chance for the virus to either

11:52

mutate or acquire genes from other

11:54

viruses, such as a cold virus,

11:56

present in an infected person would would

11:58

increase the ability of... in H5N1 to move

12:01

move between people. Once the Once the

12:03

virus can do this, the possibility of

12:05

a pandemic becomes real. In many other

12:07

In many other species, this prospect has

12:09

arrived. of of thousands

12:11

of migratory such as such as

12:14

cormorants, gulls, turns, and and pelicans have

12:16

succumbed to Raptors, such as bald

12:18

egos, that as on the sick prey on the

12:20

stick and water are are also being hit

12:22

hard. Even the Even the endangered

12:24

California is particularly vulnerable as

12:26

as a a feeder. feeder.

12:28

Federal wildlife officials have been

12:30

vaccinating the the condors. Marine mammals

12:32

Marine mammals have been contracting the virus probably

12:34

because they share habitat with with

12:36

infected seabirds. On South American

12:39

coasts, of sea lions and elephant

12:41

have been dying. dying. Sadly, on the

12:43

on the wildlife side, there's little to be done

12:45

except wait for the virus to work its

12:47

way through vulnerable populations. In

12:49

the the human world, however, testing and monitoring

12:51

of dairy and poultry farms is a

12:53

first step. step. in protecting us from

12:55

higher risks of severe illness

12:57

and transmission of a serious pathogen.

13:00

and transmission

13:02

of a serious

13:04

pathogen. Thanks to

13:06

Beth Bennet for

13:08

that story. Artificial

13:10

intelligence has been

13:12

a hot intelligence has

13:14

been a hot topic during the

13:16

past year, from its

13:19

social impact to its use in

13:21

technology and the arts, including

13:23

the music you are hearing

13:25

right now. right now, created

13:27

by the Bloom Generative Music

13:29

Program by Peter Eno

13:32

and In fact,

13:34

AI was the basis of

13:36

two Nobel Prizes this

13:39

year. year. In our 8th show, we

13:41

show, we mentioned that

13:43

the 2024 Nobel Prize in

13:45

Physics was awarded that

13:47

day to John and and

13:49

Jeffrey Hinton for foundational discoveries

13:51

and inventions that enable

13:54

machine learning with artificial neural

13:56

networks. Then, on the

13:58

the very next day, the Nobel Prize

14:00

in chemistry awarded to

14:02

three recipients for

14:05

for Protein Design protein

14:07

Structure for protein In

14:09

particular, two of

14:11

the particular, two of the

14:13

laureates, Demise used an

14:15

AI model called used

14:17

an AI model called predict

14:19

the structure of virtually

14:21

all of virtually all 200

14:24

proteins that researchers have

14:26

identified. The The

14:28

application of artificial intelligence

14:30

is wide -ranging, including

14:32

helping astrophysicists sift

14:34

through large and complex

14:37

sets and analysis tasks,

14:39

as discussed in

14:41

this excerpt from our

14:43

March show with Dr. Megan Ansdel,

14:45

Programmed scientist at NASA at

14:47

NASA in the Astrophysics Division, the

14:50

Planetary Science Division. Division.

14:52

What I What I presented on

14:54

in that session was a bunch

14:56

of different ways that AI is

14:58

used in astrophysics, a but

15:00

also a little bit about

15:02

how directorate is mission AI is using

15:04

AI within the So all the

15:06

divisions within the science mission

15:09

directorate, astrophysics, or planetary science,

15:11

Earth science, and physics, and biological

15:13

and physical sciences division. They all all have

15:15

representatives on a a science mission level working group

15:17

for AI and ML. AI and ML. So So

15:19

there's activities going all across at the science

15:21

mission directorate and they're all being coordinated

15:23

to a certain extent. being There's a higher

15:25

level sort of effort, but within There's a I'd

15:28

say sort of in a lot of ways

15:30

it's pretty typical to how I'd and ML

15:32

is being used in the other science divisions.

15:34

So you to the term ML, being what

15:36

is ML? the ML stands for machine ML

15:38

for machine learning. So you stands term ML.

15:40

intelligence, ML? so people like

15:42

to use learning and AI L

15:45

interchangeably. some of the things

15:47

that I was presenting on Okay. I I

15:49

started off with the Roman Space so this is

15:51

the next flagship astrophysics mission that'll be

15:53

launched, hopefully, in a couple of years.

15:56

in a it's doing a huge

15:58

survey of the sky for very... different

16:00

astrophysics research problems, but there's a

16:02

huge amount of data because it's

16:04

this large area wide field view

16:07

telescope and it's pretty agile so

16:09

it has surveying capabilities that are

16:11

unprecedented. So a lot of data

16:13

is going to come down. I

16:15

think they're expecting 20,000 terabytes of

16:18

observations during the five-year prime mission

16:20

and so AIML tools are going

16:22

to be really useful for sifting

16:24

through that and they did a

16:26

call for research and support participation

16:29

opportunities in the wide field science

16:31

campaign of Roman. And there was

16:33

a bunch of machine learning applications

16:35

and a bunch of machine learning

16:38

awarded research proposals as well. So

16:40

there's a lot of interest there

16:42

and it's really exciting. You talk

16:44

about the data volume here 20,000

16:46

terabytes. AI machine learning are probably

16:49

good for sifting through big data

16:51

as opposed to hiring hundreds of

16:53

grad students in postdocs to do

16:55

the work. For their entire life,

16:58

probably. Yeah. What does the

17:00

AI and ML do with that data

17:02

set, for example? Yeah, there's a bunch

17:04

of different things you can do with

17:06

it. There are ways you can look

17:09

for outliers. For example, outlier detection is

17:11

a thing. There's also ways that you

17:13

can do sort of physics informed machine

17:15

learning where you can use your understanding

17:18

of the physics of a situation and

17:20

pair that with machine learning to learn

17:22

even more physics. It depends on the

17:24

science case that you're looking at really.

17:26

But you know it's very useful when

17:29

you have so much data and you're

17:31

trying to either get an overall pattern

17:33

out of that data or to find

17:35

something very specific in that data. What

17:38

other examples do you have of use

17:40

cases in astrophysics? I think the Roman

17:42

Space telescope is, I don't know if

17:44

you can say machine learning is traditional,

17:46

but it's sort of the traditional machine

17:49

learning application in science. which is to

17:51

use it on the data analysis. So,

17:53

you know, the mission is already gone,

17:55

it's collecting data, and you're using mission

17:58

learning to sift through that data. The

18:00

The other mission I presented on was

18:02

the Habitable the Observatory, which is just a

18:04

mission concept, but it's the highest highest

18:06

flagship mission concept out of the recent of

18:08

the recent that was conducted. that was So it'll

18:10

be the next one after the the

18:13

Telescope to be launched. So it's

18:15

very early days. It's in very of mission

18:17

concept phase. sort of I'm the program scientist

18:19

for that at NASA program And one of

18:21

the things that I really want to do

18:23

is to start the application of want to do

18:25

learning now. So AI

18:27

if we're learning now. maturing the mission concept.

18:29

How How can machine learning help with that?

18:31

How can it how can it be used in

18:34

the well phase as well while the mission's

18:36

actually operating? know, when the data then down and use the data

18:38

comes down and use it in a more

18:40

traditional way of using it for science I'm

18:42

analysis. So I'm really excited to explore how

18:44

that can be done because it's something that

18:46

people have been really excited about and

18:48

really wanna do but haven't really yet had

18:50

the opportunity and and the support to do it. That

18:53

was Dr. Megan Ansdale,

18:55

program scientist at NASA

18:57

Headquarters in the Astrophysics

18:59

Division in the Planetary

19:01

Science Division, talking about

19:03

the application of artificial

19:05

intelligence in astrophysics. Did

19:19

you know that 40 years ago, desktop

19:21

computers were about the size

19:23

of a square square box because

19:25

the screen monitors had to be

19:27

so big. days, In those days,

19:29

if anyone mentioned the dream

19:32

of creating a screen display that

19:34

would take up less space and

19:36

be much lighter, most people

19:38

would have laughed the dreamer out

19:40

of the room. of the room. Fast

19:42

to today today screens

19:44

are key to

19:46

laptops and smartphones. phones. Well,

19:49

there's a similar breakthrough that

19:51

hasn't happened yet, yet, but our

19:53

Our prediction is that

19:55

in 2025 and forward, it

19:57

it will lead to

19:59

increasingly impressive... advances. Quantum state computers

20:02

are designed to have the

20:04

geeky concept of quantum entanglement.

20:06

Many researchers expect quantum computers

20:08

to someday operate incredibly faster

20:10

and solve tougher problems than

20:12

computers can today. For a

20:15

taste of this emerging technology,

20:17

let's listen to this excerpt

20:19

from our April 9th How

20:21

on Earth Show with Corbin

20:23

Tilliman Dick, who's with Maybell

20:25

Technology in Denver. Maybell, the

20:27

company, is named after the

20:30

Colorado town of Maybell, where

20:32

the coldest temperature in Colorado

20:34

was recorded. It was minus

20:36

61 degrees Fahrenheit. Maybell the

20:38

company makes desk-sized super-cold refrigerators.

20:40

Think minus 455 degrees Fahrenheit.

20:42

It does this to keep

20:45

quantum computers in calculations cold

20:47

enough to be quantum. For

20:49

more on this interesting technology,

20:51

here's Shelley Shlender talking with

20:53

Corbin Tillamondick. The noise of

20:55

the universe is really loud.

20:57

And if you want to

21:00

create, maintain, and manipulate these

21:02

fragile quantum states at room

21:04

temperature, it's kind of like

21:06

trying to assemble a puzzle

21:08

on a shaking table or

21:10

playing a sonata in a

21:13

hurricane, getting ultra-cold is usually

21:15

necessary to interact with these

21:17

quantum states in a meaningful

21:19

way. So you're telling me

21:21

that even though there are

21:23

some ways that we could

21:25

make room temperature quantum... We'd

21:28

still need to get it

21:30

super cold to get them

21:32

to talk to us. That's

21:34

how it appears today. Colorado

21:36

is being talked about as

21:38

a place where quantum applications

21:40

are likely to happen sooner

21:43

than there are many other

21:45

places. Is that just us

21:47

being proud of Colorado? No,

21:49

no, not at all. Colorado

21:51

is leading tech hub globally.

21:53

We have four Colorado scientists

21:55

who have received Nobel Prize.

21:58

for working quantum. It's

22:00

It's pretty unprecedented.

22:03

We've got more organizations working on quantum anywhere

22:05

else in the country, more than in California.

22:07

than That's not a per capita number. not a

22:09

That's a total number. That's a And there

22:11

are more quantum jobs here than anywhere else

22:13

in the world. Does this just mean

22:15

that quantum scientists really like to

22:17

ski quantum Now, I grew out of

22:19

work in the work in the 1940s, 1950s,

22:21

where the federal government wanted to make

22:23

sure that our most important secrets

22:25

were as far away from the Russians

22:27

as possible. as And so you had

22:29

Los Alamos and Sandia and here

22:32

in the middle of the country.

22:34

here in at middle you had something

22:36

extra and special, NIST which is

22:38

something extra between NIST and CU. is

22:40

Jilla, a joint of Standards that's just

22:42

down the street from our

22:44

radio station here in Boulder that's

22:46

also down the is on the CU

22:48

Boulder radio station here in a Nobel also

22:51

he a quantum guy would

22:53

you say? Boulder a quantum guy, yes. He

22:55

knows how to get things to be super Prize. does,

22:57

a quantum guy? Yes. missed

22:59

Angela meant that you

23:02

kind of had a

23:04

pathway for these deep deep

23:06

science. things that happened inside the

23:08

government lab. to escape the the lab

23:10

and become companies. now you have you

23:12

have things like the comes. That's a

23:14

Nobel Prize winning developed at NIST at a

23:16

company named named just got just got $200

23:19

in order to use it to

23:21

sense methane leaks all around the

23:23

country. that what they they can do

23:25

is instead of needing to put

23:27

a little sniffer on every single they

23:30

they can put up a tower and

23:32

they can sense a cal at the edge

23:34

of the horizon. It's an incredible technology

23:36

and it's quantum technology that's being deployed

23:38

at scale. being deployed at

23:40

scale today. Already? Cool. Cool.

23:42

My last question for last question

23:44

for you favorite your favorite music that speaks

23:47

quantum to you? Oh, I I have no

23:49

idea. Are Are you not a musical person? I

23:51

am, but not that

23:53

that I can think of that as quantum.

23:55

I mean, do mean, do you think

23:57

of quantum dips dips of sound? of sound?

24:00

Philip Glass? No,

24:02

I mean quantum

24:04

is symphonic, right?

24:06

It's about layering

24:08

these different signals

24:10

on top of

24:12

each other. It's

24:14

not little dips

24:16

and daps of

24:18

noise, not once

24:20

you get to

24:23

quantum advantage. It's

24:25

over tuna. big, powerful

24:27

music that is built

24:29

up from individual instruments

24:31

creating their own waveforms,

24:34

right? I mean, candidly,

24:36

the closest analogy in

24:38

the classical world to

24:40

entanglement is harmonics, right,

24:43

where you have these

24:45

different waveforms set combined

24:47

to create something more

24:50

than the underlying elements.

24:52

And so if you

24:54

think of, you know,

24:56

Parmenovarana, that's quantum to

24:59

me. Corbin Tilliman Dick

25:01

is the CEO of

25:03

Denver's Maybell Quantum. He's

25:05

an expert about and

25:08

a champion for the

25:10

symphony of quantum devices

25:12

and breakthroughs, being developed

25:14

by scientists in Colorado

25:17

and around the world.

25:19

In addition to founding

25:21

Maybell Technologies, Corbin Tilliman

25:24

Dick heads up Elevate

25:26

Quantum. a consortium of

25:28

over 85 quantum-focused organizations

25:30

in Colorado and the

25:33

Mountain West. So that

25:35

rounds out our New

25:37

Year's show, looking back

25:39

at some of the

25:42

science in 2024. Come

25:44

back and listen to

25:46

how on Earth every

25:48

Tuesday morning to discover

25:51

what science might make

25:53

our roundup next year.

25:55

Until then, happy new

25:58

year. It's

26:12

all for for this New Year's

26:14

Eve edition of How Earth, Earth?

26:16

Our our executive producer is

26:18

Shelley is Shelley This week's show

26:20

is produced by yours by Joel

26:22

Parker. Additional contributions by Shelley

26:24

Schlender and Beth Schlender Our

26:26

theme music was written and

26:28

produced by Josh Cutler. Additional

26:31

music from Cutler. Additional music from Cattleist, The Birds,

26:33

and Quantum. Quantum. Visit our

26:35

website at at how Earth .org to

26:37

find past episodes, extended interviews,

26:39

and you can subscribe to

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our can subscribe to our follow. us on

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through iTunes and follow us on Facebook

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or comments? Call the

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KGNU comment line at Call

26:49

the Cajun -9911. 3.447. For How

26:51

on Earth, the KGNU

26:54

Science News I'm Joel

26:56

Parker. Parker.