0:00

This week in virology,

0:02

the podcast about viruses,

0:04

the kind that make

0:07

you sick. From Microbe

0:09

TV, this is Twiv,

0:12

this weekend virology,

0:14

episode 119, recorded

0:16

on the 7th of

0:19

February 2025. I'm Vincent

0:21

Rackin yellow and you're

0:24

listening to the

0:26

podcast all about

0:28

viruses. Joining me

0:30

today from Montreal

0:32

Canada, Angela Mingarelli.

0:34

Hello, how are you today? Is it

0:36

really cold there? Actually,

0:39

it's warm. I know this sounds

0:41

funny. Minus 4C is warm, but

0:43

because it's been minus 20 for

0:46

the last three weeks on and

0:48

off, minus 4, I actually had

0:50

my coat undone this morning. It

0:53

was just open. I was

0:55

like, it's not even cold.

0:57

So everything is. This is just

0:59

balmy. Also joining us from western

1:01

Massachusetts, Alan Dove. Good to be

1:03

here, and it's 35 Fahrenheit 2C

1:06

here, which is not too bad,

1:08

except that it's blowing a gale

1:10

out of the northwest. Wind is

1:13

whipping through here, and we had

1:15

some snow and sleet the other

1:17

day, and now, apparently, Saturday night,

1:20

we're getting another snowstorm. We don't

1:22

have any wind here in the

1:24

city. It's interesting. We certainly

1:26

have plenty here. picked once.

1:29

Oh yeah the global wind map that

1:31

should show it yeah we actually

1:33

have quite a bit of wind

1:36

in Montreal I think it comes

1:38

off the St. Lawrence like from

1:40

the river there's it's very

1:42

windy so it always feels

1:45

like five degrees colder than

1:47

it actually is. Hmm well if

1:49

you enjoy these programs you know

1:51

our main goal is to give

1:54

you science which is getting

1:56

increasingly hard. You

1:58

know the just

2:00

was published again after a

2:03

little hiatus and they censored

2:05

some stories on H5N1. They

2:07

pulled them out. This is

2:09

to me this is like

2:11

stunning that they would censor

2:13

science but that's the world

2:16

we are in anyway. We

2:18

can try and interpret for

2:20

you what's going on because

2:22

there are other sources of

2:24

information. And if you like

2:26

that, please support us. Help

2:29

us to do this. Microb.TV

2:31

slash contribute ASV, the American

2:33

Society for Virology, 2025 meeting

2:35

will be held in Montreal

2:37

at the Palais de Congre

2:39

de Montreal, July 14th or

2:42

17th, 2025. asv.org/ASV 2025. asv.org/ASV

2:44

2025. Check out the website

2:46

for the meeting schedule. It's

2:48

a bit different this year.

2:50

Under the program tab, you'll

2:52

see satellites on topics you

2:55

might want to sign up

2:57

for when you register like

2:59

emerging zoonoses, priority pathogens, plant

3:01

virology, a trainee satellite workshop,

3:03

only for trainees on culture

3:05

communication and mentorship, and a

3:08

satellite on next generation virology

3:10

technology, and conceptual frontiers. And

3:12

there will be a twift

3:14

too on Thursday of the

3:16

meeting. Everyone is coming, right,

3:18

Vincent? Or is anyone not

3:21

making it? I don't know

3:23

who's coming, actually. We can't

3:25

have everyone come because it's

3:27

too crowded. To be too

3:29

crowded. Yeah. We have to

3:31

have, I know that you

3:34

will be there, Angela, because

3:36

you live there. It's true.

3:38

It is on the way

3:40

to my lab, literally. If

3:42

you would like me to

3:44

come I can I can

3:46

easily get there. It's like

3:49

a three hour drive straight

3:51

up the highway That's true.

3:53

I don't want to I

3:55

don't want to show up

3:57

just to crowd the stage

3:59

So I think you'll probably

4:02

have plenty of people. Well, you

4:04

know, these days, not so many people show

4:06

up, as you know, to Alan. Yes, there

4:08

is that. So I don't know who's going

4:11

to come. But I will send out

4:13

a memo. How's that? Yes. I mean,

4:15

Montreal. I know right now it's

4:17

cold, but in July. It's beautiful

4:19

weather. It's sunny. Montreal is a

4:21

beautiful city in the summer. So

4:23

if I can entice anyone to

4:25

come. Okay,

4:28

a few news items. Yeah, so

4:30

I put a couple of these

4:32

in. I can go ahead

4:34

and probably. Yep, go ahead.

4:36

At least the first two.

4:38

First item is there

4:41

was a little accident

4:43

at a major supplier

4:45

of research monkeys in

4:47

South Carolina, and apparently

4:49

this is a facility

4:52

that has had some

4:54

other problems in recent

4:56

years. They apparently had

4:58

a piece of equipment

5:01

somewhere, a heater maybe

5:03

that was producing carbon

5:05

monoxide, killed 22 monkeys.

5:07

And the USDA report on

5:09

this cited it as a

5:11

critical violation of protocols for

5:14

animal care, but it

5:16

turns out they're not

5:18

actually going to do

5:20

anything about it. I don't

5:22

know why. This is, so I

5:24

linked to an article in science,

5:26

but a, just, you know, USDA

5:28

said, yep, this was a critical

5:30

violation. And, apparently. But these monkeys

5:32

bred there, do you know, or are they?

5:34

I think these may be, I think

5:36

McCax may breed in captivity. They, they

5:39

may be. I think it said it

5:41

was a breeder facility for most,

5:43

for scientific research, like that's where

5:45

then they send them to different

5:47

parts of the country. Yeah. And

5:50

this is the same place

5:52

where, just a little while

5:55

ago, they had 43

5:57

monkeys escape. Yeah, that's

5:59

right. It's like the

6:01

safest facility. Pretty significant

6:03

breach. They got most

6:05

of them I think,

6:07

right? Yeah, they got

6:09

them back, but this

6:11

seems like maybe there

6:13

are some more general

6:15

problems there. I don't

6:17

know what's going on.

6:20

All right. Now that

6:22

happened. Another item, the

6:24

animal and plant health

6:26

inspection service of the

6:28

USDA has been working

6:30

with state. animal veterinary

6:32

departments and they received

6:34

data from Nevada on

6:36

an avian influenza new

6:38

genotype D1.1 genotype. This

6:40

is an H5N1 flu,

6:42

but it's a genotype

6:44

that had not previously

6:46

been seen in cattle

6:48

in at least Nevada.

6:50

And probably if it's

6:52

in Nevada, it's going

6:54

to end up other

6:56

places too. So

6:59

Birdfloo is in the cattle

7:01

and I've linked to the

7:03

AFIS site on that. And

7:05

then in case AFIS goes

7:07

offline, I've also linked to

7:09

an NPR article on it.

7:11

And then we have a

7:13

couple of other stories that

7:15

I guess Amy put in

7:17

here. Yep. So we have

7:19

a Sidrap. Story, Argentina says

7:21

it too plans to pull

7:23

out of WHO by Stephanie

7:25

Sussieray. All right, good riddance.

7:27

yeah i was gonna say

7:29

you know this guy this

7:31

president oh you know they

7:33

screwed up the pandemic so

7:35

much do we really need

7:38

these super national organizations that

7:40

don't meet our needs i

7:42

think this is just unfortunate

7:44

when there is another pandemic

7:46

they will be very sorry

7:48

because it's not even if

7:50

people are just like oh

7:52

it's not going to happen

7:54

it's not if it's when

7:56

there is they will be

7:58

very very sad for pulling

8:00

out One hopes that it

8:02

is not in the next

8:04

four years. Okay, let me

8:06

just say that. Yeah, also.

8:08

Because it will be horribly

8:10

mismanaged. You will not get

8:12

any information about anything, except

8:14

to have, as far as

8:16

we can, wrestle it. So,

8:18

I mean, the WHO is

8:20

a good organization that helps

8:22

a lot of countries that

8:24

do not have the ability

8:26

to help themselves. This is

8:28

the altruistic model of humanity,

8:30

folks. you know, people help

8:32

other people and apparently the

8:34

US and Argentina now are

8:36

backing out. I didn't sign

8:38

up for that, that's for

8:40

sure. I grew up, I

8:42

was raised altruistically, you know,

8:44

and I don't agree with

8:46

people who think otherwise. But

8:48

you know, a lot of

8:50

people in this country are

8:52

altruistic, it's just, they got

8:54

out voted slightly. Yeah. Apparently

8:56

a lot of people sat

8:58

out to say, like, you

9:00

know, the problem, yeah, the

9:02

problem is not the majority

9:05

of Americans. The problem is

9:07

that just enough of a

9:09

population of people said, yeah,

9:11

you know, I'm not that

9:13

into Kamala. I'm not going

9:15

to bother to vote. Yeah,

9:17

now you get what you,

9:19

and now, you know, that's,

9:21

so if you're one of

9:23

those people, thanks. Another Sidrap

9:25

article, Lisa Schneering, Pejo, Pan

9:27

American Health Organization, warns of

9:29

rise of yellow fever in

9:31

the Americas. This is scary.

9:33

They said there were 61

9:35

cases reported. 30 of them

9:37

people died actually. Yeah. And

9:39

January, yeah. Which is pretty

9:41

unvaccinated. Typical fatality rates for

9:43

yellow fever. Most cases involve

9:45

unvaccinated people. the answer here

9:47

folks get vaccinated because these

9:49

are countries were made up

9:51

easy to get vaccinated. And

9:53

yeah I mean in this

9:55

case in vaccination we've talked

9:57

a little bit about the

9:59

yellow fever vaccine on twive

10:01

it's not this is not

10:03

a flu shot. This is,

10:05

it's a little more serious.

10:07

I think people over 60

10:09

are not supposed to get

10:11

it at all. Is that

10:13

right? Oh really? Yeah. Yeah,

10:15

like there's an age cut

10:17

off on it because it's

10:19

a highly effective vaccine, but

10:21

it can have a pretty,

10:23

you know, some bad outcomes

10:25

if your immune system, depending

10:27

on how it reacts and

10:29

apparently those odds go up.

10:32

as you get older and

10:34

so there are a lot

10:36

of people who shouldn't be

10:38

vaccinated and those who are

10:40

kind of can be a

10:42

rough ride. The real solution

10:44

here is mosquito control and

10:46

that's a hard problem but

10:48

it is one that is

10:50

addressable just needs to be

10:52

done so consistently. I mean

10:54

if they have access to

10:56

vaccines which I'm not saying

10:58

everyone in South America does

11:00

but if they did at

11:02

a young age I would

11:04

rather be sick for two

11:06

or three weeks than die

11:08

so 50% chance fatality rate

11:10

I would rather have a

11:12

even if it's a even

11:14

if it's two weeks of

11:16

you know flu-like symptoms or

11:18

even if it's severe flu-like

11:20

symptoms it's still better than

11:22

than dying if they can't

11:24

exactly if you're young enough

11:26

and you have access obviously

11:28

to the vaccine. Yeah but

11:30

there are also a lot

11:32

of mosquito-borne viruses-borne viruses-borne viruses

11:34

in... the same species and

11:36

mosquitoes that we don't have

11:38

vaccines for. So, you know,

11:40

a mosquito control program which

11:42

unfortunately is something that has

11:44

to be diligently managed and

11:46

funded year after year after

11:48

year and also ties into

11:50

things like making sure people

11:52

have adequate housing with screens

11:54

and, you know, the bugs

11:56

can't just fly in all

11:59

the time. all that together

12:01

is also an effective way

12:03

to manage it. It's why

12:05

we have low rates of

12:07

yellow fever in this country,

12:09

because in weather when these

12:11

these mosquitoes are all over

12:13

in the United States, but

12:15

in the weather when they're

12:17

out and about, we're charging

12:19

from an air conditioned car

12:21

to an air conditioned house

12:23

and... doesn't get to us.

12:25

All right, we have some

12:27

science for you today. Two

12:29

viruses we don't usually talk

12:31

about. Alan, you're going to

12:33

summarize that snippet for us.

12:35

Sure. So this first paper

12:37

is viral and immune dynamics

12:39

of genital human papaloma virus

12:41

infections in young women with

12:43

high temporal resolution. So it's

12:45

the viral and immune dynamics

12:47

that they're going to get

12:49

with high temporal resolution. The

12:51

young women do not have

12:53

high temporal resolution, as far

12:55

as I know. And the

12:57

authors are two co-first authors,

12:59

Nicholas Tessandier and Baptiste Ali,

13:01

and senior author is Samuel

13:03

Alizón. And boy are they

13:05

from a few different places.

13:07

There's the University of PSL

13:09

in Paris, University of Montpellier,

13:11

Swiss Tropical and Public Health

13:13

Institute in Basel, Institute of

13:15

genomic functional Montpellier, University of

13:17

Leige, Belgium, University of Manitoba,

13:19

Winnipeg, University of France Comte,

13:21

in Bézon. which is where

13:24

my grandfather was stationed in

13:26

World War I. That's the

13:28

only thing I knew about

13:30

Bézon before reading this. Central

13:32

Nationale Reference Papaloma virus, which

13:34

is in also Bézon Saint,

13:36

Paris-Clet... Wait, are we at

13:38

University of Paris-Clet, Paris-Clet, in

13:40

Orcet... C-H-U-D-N-N-N-N-N-N-F France, the Sorbonne

13:42

University of Oxford, UK. I

13:44

can pronounce that one. The

13:46

German Cancer Research Center in

13:48

Heidelberg and the Public Health

13:50

Agency of Canada. I think

13:52

I got all of them.

13:54

So this is a very

13:56

international team. And to summarize

13:58

this, I can... actually just

14:00

read the author's summary on

14:02

this paper. It's a plus

14:04

paper, open access, and the

14:06

author's summary is actually pretty

14:08

good. So they say, why

14:10

was this study done? Despite

14:12

human papaloma viruses, HPVs being

14:14

the most oncogenic viruses, we

14:16

know little about non-persistent infections

14:18

in young adults. Nearly one

14:20

out of five women of

14:22

age 25 has an HIV

14:24

genital genital infection, but more

14:26

than 90% of these clear

14:28

in less than two years.

14:30

The determinants of HDV genital

14:32

infection clearance are largely unknown.

14:34

In 2016, a longitudinal study

14:36

was initiated to monitor variations

14:38

in HDV virus loads and

14:40

the associated immune response. What

14:42

did the researchers do and

14:44

find? HDV virus load exhibits

14:46

a rapid increase, a long

14:48

plateau, and a steep decrease.

14:51

Infections are estimated to have

14:53

a medium median duration between

14:55

13 and 20 months. Immune

14:57

patterns are associated with HDV

14:59

infection, especially gamma delta T

15:01

cells and CXCL10 chemokine. And

15:03

variations in virus load are

15:05

primarily associated with HDV genotype

15:07

and variations in infection duration

15:09

with host differences. So what

15:11

are these findings mean? First

15:13

of all, HDV infection clearances

15:15

associated with the activation of

15:17

the immune response. Okay, makes

15:19

sense. Secondly, variations in virus

15:21

load can help to optimize

15:23

screening policies. Makes sense. And

15:25

finally, details of the immune

15:27

response can help identify biomarkers

15:29

and targets for immunotherapies. So

15:31

that's the basics. Chronic infections

15:33

by human papillomaviruses, they go

15:35

on your lifetime, cause cervical

15:37

cancers. and most anogenital cancers

15:39

and many oropharyngeal cancers, 83%

15:41

of HDV-induced cancers are cervical,

15:43

so women are most affected.

15:45

There are 630,000 HDV-induced cancers.

15:47

worldwide, at least in 2012.

15:49

A little behind on the

15:51

statistics there, folks. Yeah. Yeah.

15:53

13 years. And so these

15:55

are sexually transmitted infections. But

15:57

the good news is over

15:59

90% of these infections don't

16:01

go on for more than

16:03

two years. So they're acute

16:05

infections. They're not chronic infections.

16:07

And so why? Why not?

16:09

And if you can find

16:11

out why, maybe you can

16:13

get some clues about why

16:15

the ones. go on forever,

16:18

right? And we should mention

16:20

there is a highly effective

16:22

vaccine now against the oncogenic

16:24

HDV types that is now

16:26

routine in vaccination programs in

16:28

sensible countries around the world

16:30

for boys and girls as

16:32

they approach puberty and that

16:34

basically deals with this problem.

16:36

The issue is there's a

16:38

generation, actually there are a

16:40

couple of generations of people,

16:42

for whom that vaccine came

16:44

along too late, because after

16:46

you've been exposed to this

16:48

virus, after you've grown up

16:50

and become sexually active, you've

16:52

probably been exposed to this

16:54

virus, and then the vaccine

16:56

doesn't seem to be very

16:58

effective at all. All right,

17:00

so that's what this paper

17:02

attempts to do, really unique

17:04

study, I think. where they

17:06

say, you know, we have

17:08

done randomized clinical trials for

17:10

the vaccines, but they're limited

17:12

because the follow-up was not

17:14

all that frequent and we

17:16

didn't get samples that we

17:18

wanted to, cervical smears in

17:20

particular. So this study was

17:22

designed to investigate the immune

17:24

response, both in aid and

17:26

adaptive. to papaloma viruses in

17:28

women and then the the

17:30

viral load. They have a

17:32

very specific definition. Viral load

17:34

is the genome load, the

17:36

number of copies measured by

17:38

QPCR. And they normally... They

17:40

included that for us. They

17:42

normalize it to some human

17:45

gene in the sample, which

17:47

is the way you need

17:49

to do it, because every

17:51

sample is going to be

17:53

different quantity, right? And so

17:55

this is called the Papclear

17:57

cohort study taken... It was

17:59

done in Montelier, France. at

18:01

189 women, 18 to 25

18:03

years old, followed every two

18:05

months, either until the HDV

18:07

infection cleared or for 24

18:09

months, in which case they

18:11

said, okay, it's enough you

18:13

can go now. And this

18:15

is, so there are a

18:17

few reasons why this was

18:19

technically difficult and we're going

18:21

to talk about some of

18:23

the techniques they used. This

18:25

is not like a routine.

18:27

simple thing to sample and

18:29

figure out. So most of

18:31

the HDV infections are going

18:33

to be asymptomatic, which is

18:35

why they had to do

18:37

this cohort study and sample

18:39

the same population repeatedly over

18:41

time because you don't know

18:43

anybody's infected. The second problem,

18:45

and I didn't realize this,

18:47

but cervical smears apparently you

18:49

can't like... Just freeze them

18:51

and ship them off to

18:53

the lab FedEx. They've got

18:55

to be analyzed right away

18:57

because it's a fragile sample

18:59

And the sample has a

19:01

lot of keratinocytes which are

19:03

sticky and Auto fluorescent And

19:05

that's a big problem if

19:07

you're going to do fluorescence

19:10

activated cell sorting because usually

19:12

what you do is you

19:14

you label yourselves with some

19:16

Antibody against a surface marker

19:18

on something and you send

19:20

them through the cell sorta

19:22

in the ones that glow

19:24

or the ones you want

19:26

But if you got all

19:28

these other glowing cells in

19:30

there, then you can't really

19:32

do that. And that actually

19:34

is something that they spend

19:36

some time figuring out how

19:38

to deal with. But I

19:40

saw. that and I thought

19:42

it was interesting that like

19:44

I looked to see what

19:46

flow cytometer they used and

19:48

that they weren't using because

19:50

there's spectral flow cytometers and

19:52

then there's just like regular

19:54

like four laser that don't

19:56

use the actual spectral signature

19:58

of the fluorophores where every

20:00

floor for itself has a

20:02

very specific spectral signature. So

20:04

if you use the cell

20:06

type like the karastinocytes unstained

20:08

as you're just unstain control

20:10

it'll subtract all of that

20:12

fluorescence from the cells so

20:14

they're talking about how they

20:16

want to use cytof. But

20:18

I thought that that was,

20:20

it would be good, but

20:22

maybe using spectrophilocytomity and there's

20:24

also spectrophs orders. They might

20:26

reduce some of that like

20:28

fluorescent noise because we do

20:30

that. Like when I do

20:32

liver versus lung in my

20:34

control, I have an unstained

20:37

liver versus an unstained lung

20:39

because all of the cells

20:41

have auto fluorescence and you

20:43

use that to subtract from

20:45

your samples so that when

20:47

your actual fluorophores won't be

20:49

adding to that. It's still

20:51

cool because I know that

20:53

the material in a smear

20:55

is very very small as

20:57

well and they have very

20:59

few immune cells So the

21:01

fact that they did this

21:03

is actually very impressive. Yeah

21:05

Yeah, they And they had

21:07

to use a lot of

21:09

statistics because the numbers are

21:11

small and you know you

21:13

could look at Antibodies and

21:15

There's no clear if you

21:17

just look at the data,

21:19

there's no clear trend right

21:21

you have to put statistics

21:23

through them to get a

21:25

trend and even at that

21:27

they say it's a little

21:29

iffy but it's what they

21:31

could do. It's 974 visits

21:33

by all these people. That's

21:35

a lot of visits especially

21:37

for a pap smear between

21:39

all of those people. It

21:41

is not the most comfortable

21:43

thing to get done. Yeah.

21:45

Well it's very interesting that

21:47

last year I was in

21:49

Stockholm and did a twive

21:51

with a guy. who works

21:53

on HPVs and Sweden has

21:55

a goal to eliminate cervical

21:57

cancer in the next five

21:59

years. certainly cervical cancer is

22:02

caused by HDVs and nothing else.

22:04

So they've eliminated pap

22:07

smears in Sweden. It actually

22:09

happened during the pandemic when

22:11

people couldn't go. So they would

22:14

send them swabs and you would

22:16

self-swob and then they would

22:18

just do a PCR. And he said, if

22:20

it's negative, they would bring

22:23

you in and look to see if

22:25

there's a lesion. You know, if there's a

22:27

lesion they treat it, if there's no

22:29

lesion, there's nothing to do.

22:31

Hmm. So that simplifies it. Does he

22:34

mean? Sorry, Vincent. Sorry. No, no,

22:36

go ahead. No, just that like

22:38

there are other forms of maybe

22:41

not cervical, but I guess you

22:43

can't detect like uterine cancers, different

22:45

forms of uterine cancers. Those cells

22:47

would ever make it to the

22:50

cervix, maybe? Because pap smears you

22:52

can also detect infectious agents, right?

22:54

Just other infections that you could

22:57

potentially have that's not just.

22:59

He said the only agent, the only

23:01

thing that causes cervical cancer

23:03

is HDV. Nothing else. And in

23:05

fact, they even say that in this paper

23:08

somewhere. And so he said we don't

23:10

need to do pap smears anymore

23:12

because if there's no HDV,

23:14

there's no risk. If there is HDV,

23:16

then you have to look. and possibly,

23:18

you know, a blade, the lesion depending

23:21

on the size. But if it's negative,

23:23

and so he says, in Sweden, no more

23:25

pap smears. Can you imagine there?

23:27

That's kind of problematic, you

23:29

know, because like pap smear for HIV,

23:32

yes, to prevent cervical cancer, yes.

23:34

But pap smearing itself is not

23:36

only for like determining if the

23:38

person could have like mutated cells

23:40

or cancer cells or anything. It's

23:42

just overall looking to see if

23:44

there are external external lesions. on

23:46

the vagina, there could be other

23:48

things like it's a whole, because

23:50

then people aren't going to be

23:52

going to get like their, what do they

23:55

call it now, like just a checkup, like

23:57

a checkup, which is for women every two

23:59

years, includes it. And in that moment,

24:01

they also check for other signs

24:03

of like overall health. So there

24:05

could be other things wrong. So

24:07

if he's just saying no pap

24:09

smears. Well, they're presumably doing other,

24:11

I mean, they're presumably doing the

24:13

every two years get your exam.

24:15

I would, I would guess. So

24:17

Sweden's healthcare system is certainly up

24:19

to that. They're very good. Yeah,

24:21

I'm sure he's just referring to

24:23

maybe that part of it to

24:25

their saving on. That particular test

24:27

may not be. Anyway, listen

24:30

to the podcast. I was very

24:32

impressed. I thought it was made

24:34

a lot of sense. Yeah, cool.

24:36

All right. So here we- But

24:39

what are they, sorry to continue

24:41

the digression, but it's it's virology

24:43

still. So what about women who

24:45

are too old to have gotten

24:48

the HIV vaccine? Are they, if

24:50

they want to eliminate cervical cancer

24:52

in five years, it seems like

24:54

you're still going to have a

24:57

lot of people around who could

24:59

still get it. Right. Well, they.

25:01

do a PCR. Okay. Right. And

25:03

if you're positive, then they look

25:06

in and see if there's a

25:08

lesion. And if there's a lesion,

25:10

then they ablate it, right? Laser

25:13

ablation or something. Cryo ablation. But

25:15

yeah, they mean they do treatment

25:17

if there is a... Right. Okay.

25:19

So that's not eliminating cervical cancer.

25:22

That's... It's... In five years you

25:24

want to get to a point

25:26

where there's no serious cases of

25:28

it because you detected it early

25:31

enough. between the vaccine and the

25:33

screening. And in the other generations

25:35

you eliminate it. Right. If you

25:37

can, if you vaccinate early enough,

25:40

plus you do the screening for

25:42

everybody, then that, yeah, that makes

25:44

sense. Continuing that on the paper.

25:46

Yeah. So they, all right. So

25:49

they, I'm going to go through

25:51

the methods and then we're going

25:53

to go to the discussion for

25:56

the, for the conclusions, because the,

25:58

the, the methods, most of the

26:00

results is basically saying. how we

26:02

did this and the limitations and

26:05

so forth, but not what it

26:07

meant. So, as we said, they

26:09

want to characterize the local immune

26:11

response. They're getting pap smears, and

26:14

they use flow cytometry, and as

26:16

Alan said, keratinocytes are a problem.

26:18

So, they actually used software packages

26:20

to put cells into clusters into

26:23

clusters into clusters. based on the

26:25

fluorescence signal. And so does that

26:27

sound like a reasonable approach, Angela?

26:29

Yeah, you can do that even

26:32

in, there's a software called Flowjo

26:34

that we all use to analyze

26:36

flow cytometry data. And you can

26:39

put things into you map. Normally

26:41

you do it when you have

26:43

more than like 10 or 15

26:45

different markers. If you don't have

26:48

that many markers, it doesn't really

26:50

make like to do the clustering.

26:52

But yeah, people do this all

26:54

the time. That's very reasonable. Okay,

26:57

so they identify clusters of cells

26:59

in these samples, right? So initially,

27:01

all they have is the immune

27:03

data. They don't have the infection

27:06

data yet, so they can't make

27:08

any correlations, but they go through

27:10

it to tell you what. We

27:12

saw mostly granulocytes in terms of

27:15

white blood cells, and then we

27:17

try and make an association between

27:19

this cellular immune response and HDV

27:22

status. And so we get people

27:24

who are, had the same HDV

27:26

genotype doing two consecutive visits, so

27:28

they end up with a data

27:31

set of 145 HDV negative and

27:33

186 HDV focal flow cytometry samples.

27:35

All right. They also quantify secretions,

27:37

sorry, cytokines in these cervical samples.

27:40

using a package called Meso Scale

27:42

Discovery. And we're going to get

27:44

to what that means in a

27:46

bit. And then the of course,

27:49

the viral load kinetics. So there

27:51

were 76 people for whom at

27:53

least three samples had one HDV

27:56

genotype during their follow-up. They had

27:58

164 infections, including left, 66 left

28:00

censored infections. So weird. Yeah, so

28:02

they used this term. I saw

28:05

it in the abstract. I was

28:07

like, you know, many of the

28:09

infections were censored. What? I also

28:11

didn't know if they met. What

28:14

they and then I what they

28:16

mean is so some of these

28:18

women came in and they already

28:20

had an HIV infection at the

28:23

first time point. So that is

28:25

called a left censored infection because

28:27

you didn't see when it came

28:29

up. You don't know how long

28:32

that infection has been going on

28:34

and then you know it resolves

28:36

sometime later and you see the

28:39

resolution of it. If the opposite

28:41

happens if they get infected during

28:43

the study But it's toward the

28:45

end and then the study ends

28:48

and you don't see the ending

28:50

of that. That is a right

28:52

censored. And then they have some

28:54

that are double censored where they

28:57

came in with it and they

28:59

left with it and just through

29:01

the study they had the infection.

29:03

And then a complete infection, what

29:06

would that be? So that's they

29:08

came in without. infection, the first

29:10

time point. Got it. You saw

29:12

the virus come in, then you

29:15

saw the virus go away for

29:17

the end of the study. What

29:19

I found from this, it's interesting,

29:22

is that 41 of the participants

29:24

were co-infected by more than one

29:26

genotype. That's very interesting. So. I

29:28

would not have guessed that, but

29:31

people are multiply infected, so they

29:33

multiply transient. Or you have multiple

29:35

sexual partners. Actually, one of the

29:37

requirements for this study was you

29:40

had to have at least one

29:42

sexual partner in the previous 12

29:44

months. And so maybe if you

29:46

have more than one, you get

29:49

more than one serotype, right? Right,

29:51

because if you did this in

29:53

people who aren't... sexually active you're

29:55

not going to see anything. No

29:58

no yeah you don't want to

30:00

do that but that's where the

30:02

multiple infections could have a number

30:05

of different sources these viruses are

30:07

they they're durable they kind of

30:09

go everywhere they're very contagious it's

30:11

one of the more contagious SDIs

30:14

and since they're most of the

30:16

time asymptomatic I think it's not

30:18

uncommon for them to kind of

30:20

travel in little clumps. Do we

30:23

know if they travel, if people

30:25

can get multiple infections from one

30:27

sexual partner though? Has that been

30:29

shown? Like I don't know if

30:32

I don't know if we have

30:34

those data, but it's I was

30:36

I mean I had the reaction

30:38

like Vincent like whoa multiple infections

30:41

and I thought Actually that kind

30:43

of makes sense from what we

30:45

do know about HDV. You know,

30:48

it's also the I'm sure sex

30:50

workers are multiple multiple infected right?

30:52

Well, right they can they can

30:54

transmit I don't know how Right,

30:57

but I don't I don't think

30:59

you even need to invoke that.

31:01

I think it's just these these

31:03

viruses get around All right, so

31:06

the virus data and they also

31:08

have to apply statistics because If

31:10

you look at the raw data,

31:12

it's like figure four B. Oh

31:15

my gosh. Yeah. Oh my gosh.

31:17

It's like a kid took a

31:19

crayon and just scribble Yeah, I

31:21

don't know why yeah, and then

31:24

they have to apply statistics and

31:26

you know, they say we don't

31:28

have a lot of prior data

31:31

to give us some kind of

31:33

model for this. So they had

31:35

to do it themselves. So anyway,

31:37

what they end up finding is

31:40

very interesting. Infections last around 16

31:42

months. The plateau lasts about 14

31:44

months. So you get in fact

31:46

that you reach a plateau for

31:49

14 months. And then, interesting, the

31:51

median of two virus genome copies

31:53

per cell. And

31:55

what they also find it's interesting

31:58

is that most of the variants

32:00

in infection duration which is the

32:02

scribble on that graph is host

32:04

differences. It's interesting this plateau that's

32:06

that long and they refer to

32:09

it as like the immune system

32:11

like waiting but I think it's

32:13

more just that there's not I

32:15

guess it's in a mucousal surface

32:17

we know that it's not systemic

32:19

so it's kind of like isolated

32:22

there unless you have like actual

32:24

lesions getting into your bloodstream the

32:26

immune cells aren't gonna recruit as

32:28

much I guess but it's I

32:30

wonder how, like I don't know,

32:32

like the immune mechanisms, I guess

32:35

we don't really understand them, but

32:37

that it can be there for

32:39

that long. And I thought it

32:41

was, they've made it seem really

32:43

interesting that gamma delta T cells

32:46

were involved, like it was like

32:48

a new finding, but gamma delta

32:50

T cells are involved in most

32:52

mucousal surfaces, like in the gut

32:54

too, and in like other mucosal

32:56

infections, I think. Yeah.

32:59

Yeah. So in terms of

33:01

cytokines, they didn't see a

33:03

strong consistent increase or decrease

33:05

in the cervical area. And

33:08

there's a lot of inter-individual

33:10

variation among the site. So

33:12

it's very hard to get,

33:14

you know, any kind of

33:16

correlations with cytokines. Yeah. And

33:18

there's a lot of variation.

33:21

We're looking at figure four,

33:23

but figure three where they've

33:25

got graphs for 158 infections

33:27

and 76 women. And there's,

33:29

if you look at this,

33:32

it's not like, oh, here's

33:34

the pattern, you know, it's,

33:36

well, okay, this is kind

33:38

of that, and this is

33:40

kind of that, and this

33:42

one has this, and so

33:45

in all of these cases,

33:47

it's a lot of statistical

33:49

analysis to see if there

33:51

are any consistent patterns, and

33:53

then to figure out what

33:56

they might be. And I

33:58

think they only looked at

34:00

co-infections for HIV, but not

34:02

for other pathogens. because we

34:04

have so many, all of

34:06

these cytokines, if I have,

34:09

let's say, I don't know,

34:11

some other, like STI, sexually

34:13

transmitted infection, that is causing

34:15

inflammation, then I'm gonna have

34:17

increased now, one beta, or

34:20

I wanna, or whatever, and

34:22

then somebody else won't, but

34:24

those aren't necessarily related to

34:26

HDV, and they're only looking

34:28

at co-infections with HDV, not

34:30

with every other thing that

34:33

could be down there, If

34:35

you've got the flu, you're

34:37

probably going to have some

34:39

cytokines going all over the

34:41

place, which would maybe be

34:44

detectable in mucosa as well,

34:46

even though the virus is

34:48

not in a particular spot.

34:50

And they looked at viral

34:52

loads and antibodies, local immunity,

34:55

because they also look at

34:57

some cytokines. So basically, they

34:59

quantify circulating IGG and IGM

35:01

against. the six genotypes that

35:03

they have been following in

35:05

this study. And they detected

35:08

no correlations between the viral

35:10

load and serial conversion status.

35:12

So there's a lot of

35:14

people had no serial conversion,

35:16

but if you did, it

35:19

didn't really correlate with the

35:21

viral load. And the antibody

35:23

tighter. The one thing they

35:25

can say is. I

35:28

mean concentration of this chemokine

35:30

CXCL10 was negatively correlated with

35:33

viral load. That's the one

35:35

thing that they come up

35:37

with here. This gets a

35:40

strong signal. So this is,

35:42

let me summarize this for

35:45

you. These HDV infections, a

35:47

short, everything they conclude is

35:50

based on models, okay? HDV

35:52

infections have three phases of

35:54

short, a growth phase of

35:57

plateau, a long plateau. and

35:59

a short clearance phase. And

36:02

so that's the observation, which

36:04

is very interesting. Why that

36:07

is, we don't know, the

36:09

immunity studies don't really answer

36:11

that, but give you some

36:14

suggestions. This dynamics is contributed

36:16

to by the genotype and

36:19

the host. Both the genotype

36:21

and the host contribute to

36:24

that dynamic. Differences in the

36:26

dynamics, for example. They

36:29

find a role for granulocytes

36:31

in these patterns, which they

36:34

say others have been found,

36:36

and gamma-delta T cells, as

36:38

Angela said. They have three

36:41

distinct subpopulations with those cells.

36:43

They have a lower proportion

36:46

of CD4 T cells in

36:48

individuals with focal HDV infection

36:50

than an uninfected. individual. So

36:53

they say that it probably

36:55

doesn't have any role. Okay,

36:58

no role in controlling infection

37:00

locally. And then the dynamics

37:02

of local immunity, and again

37:05

they have clusters of innate

37:07

immune responses, and I said

37:10

already granular sites, increased in

37:12

frequency early in infection. And

37:14

they say this supports the

37:17

idea that the immune system

37:19

can detect HDV early on

37:22

and react to it. But

37:24

they say clusters associated with

37:26

the adaptive response increase in

37:29

frequency later. So there's not

37:31

there's not really antigen. I

37:34

guess they're like eliciting recruitment

37:36

of immune cells or adaptive

37:38

immune cells. But the whole

37:41

granulocyte thing I thought was

37:43

interesting. I guess they must

37:46

be limited. They were only

37:48

using CD16. They weren't like

37:50

differentiating what types of granulocytes

37:53

like neutrophils, xenophils, mass cells,

37:55

basophils, which all hang out

37:57

there anyway because they're protecting

38:00

the mucal. So I wonder,

38:02

and it didn't really look

38:05

that significant granulocytes between like

38:07

uninfected versus infected people

38:10

with HDB, unless I'm misinterpreting

38:12

the data, but it seemed

38:14

like there were already lots

38:17

of granulocytes there, and there

38:19

was a slight increase, which is

38:21

surprising that it's not more.

38:23

All right, so then they say, okay,

38:25

can we take these data and

38:28

interpret them? interpret how

38:30

infection could unfold. And

38:33

they say, okay, this striking

38:35

pattern is that CXCL10

38:37

is associated with milder

38:40

infections. And CXCL10

38:42

correlates with the innate

38:44

immune response. Yeah, the early.

38:47

And then they say, we

38:49

find immune cells

38:51

associated with adaptive

38:53

responses, peak later in

38:56

infection. Which makes sense?

38:58

Yeah. So they say one idea here

39:00

is that a fraction of

39:02

HDV infections evade the innate

39:04

response, like interferons,

39:06

and they establish a

39:09

persistent infection, and then the

39:11

adaptive response kicks in later,

39:14

and maybe that helps to

39:16

clear it, right? And these clusters

39:18

of cells that they're

39:20

observing, maybe they're involved.

39:22

So you can't really do any.

39:25

any experiments obviously we could do

39:27

is up is statistical predictions right

39:29

and I don't even know how

39:31

you would test any of this frankly

39:33

I mean I think the coolest thing from

39:35

this paper is showing this like plateau

39:37

phase that we didn't really know about

39:39

and the clearance at two years like

39:42

I mean I didn't know that maybe

39:44

this was already known but I think

39:46

that's pretty novel the 16-month average plateau

39:48

phase that's interesting yeah it definitely

39:50

is and I think that's not

39:52

something that people had looked at certainly

39:54

not in this level of detail

39:56

because again these are asymptomatic infections

39:58

nobody knew that had anything, nobody

40:01

is checking for this other

40:03

than through pap smears which

40:05

are only going to show

40:07

you if it's a, you

40:09

know, symptomatic. So I think

40:11

that is a novel finding

40:13

here. Yeah, that's cool. And

40:15

yeah, I mean, you've got,

40:17

it's going to end up

40:19

being a resolved infection, but

40:21

it sticks around for a

40:23

year and a half. That's

40:25

kind of weird. It is.

40:27

Can they actively transmit during

40:29

that time? I'm guessing yes,

40:31

do we know? Probably. There's,

40:33

well, there are virus genomes.

40:35

But it depends, like, how

40:37

much, it'd be interesting to

40:39

know if they were, if

40:41

they were potentially, like, if

40:43

they could transmit to another

40:45

individual. Well, I mean, it

40:47

has to be that these

40:49

are the people transmitting, right?

40:51

The ones who are infected

40:53

for. But every month but

40:55

I mean like closer to

40:57

the end like at what

40:59

time? That's a good question.

41:01

Would they be considered like

41:03

cleared versus not? Do they

41:05

have right? Do they have

41:07

those data like closer to

41:09

the end like as of

41:11

16 months on average or

41:13

18 months? I don't know.

41:15

Well, given the given the

41:17

crayon scribble variation in viral

41:19

loads, I'm sure there's going

41:22

to be a distribution of

41:24

people who are in that

41:26

plateau. But they're not really

41:28

contagious levels are low and

41:30

others who are in that

41:32

same plateau. You know, they've

41:34

got sky high virus levels

41:36

and maybe they're more contagious.

41:38

But given how hard it

41:40

was to even figure this

41:42

much out, I don't know.

41:44

You're going to need a

41:46

really big long invasive study

41:48

to figure that out, I

41:50

think. Even this is impressive.

41:52

That many people have been

41:54

very impressive. So the other

41:56

thing they did, they knew

41:58

who was vaccinated here. Yes.

42:00

And they did not see

42:02

any infections of vaccinated. people

42:04

with the same with the

42:06

with the genotypes that are

42:08

present in the vaccine and

42:10

so but they they say

42:12

any effect of vaccination on

42:14

which they did see on

42:16

infection duration or platovar alone,

42:18

is probably from cross immunity,

42:20

right? Which they did see

42:22

in vaccinated people. Good to

42:24

know. Get vaccinated if you

42:26

can. Yes. Yeah, their analysis

42:28

of candidates showed no association

42:30

with vaccination status. However, they

42:32

observed the trend for participants

42:34

being already sera positive. for

42:36

a genotype before infection by

42:38

this genotype, whether by vaccination

42:40

or prior infection, have smaller

42:42

viral load than those who

42:44

never sero-converted, converted. So if

42:46

you're already sero-positive, this genotype

42:48

for which you're positive by

42:50

vaccination or infection, it's a

42:52

smaller viral load. I don't

42:54

know what that means, frankly.

42:56

And then finally, weak evidence

42:58

for the mean IGG from

43:00

vaccinated individuals to be negatively

43:03

correlated with viral load, again,

43:05

because of cross-reactivity. I did

43:07

like how when they're talking

43:09

about this in the analysis,

43:11

they did not detect any,

43:13

they put it in quotes,

43:15

breakthrough. infection, meaning a focal

43:17

infection of a vaccinated participant

43:19

one by one, one of

43:21

the vaccine genotypes. I appreciated

43:23

the scare quotes around. They

43:25

must listen to twive. I

43:27

feel like these are, I'm

43:29

pretty sure these are twive

43:31

listeners. Well, they know that

43:33

it would be interesting to

43:35

study these kinds of infection

43:37

in the same way that

43:39

they've studied here, right? To

43:41

see people, it would be

43:43

really hard. You'd have to

43:45

have a huge. cohort I

43:47

think, but you say people

43:49

who have received these these

43:51

genotype vaccines and do you

43:53

see any infections and if

43:55

so what what's the immune

43:57

signature of that as well.

44:00

But they said this, this

44:02

makes this statement, natural immunity

44:04

may protect against HDV infection,

44:06

but not enough to prevent

44:08

it entirely. I find that

44:11

a weird sentence, right? May

44:13

protect against infection, but not

44:15

entirely. So this is where

44:17

people get into trouble, where

44:19

they say protecting its infection,

44:21

but they don't mean entirely

44:24

protected. They just mean partially

44:26

protected. So, but also what

44:28

does that mean? You still

44:30

get infected. So, potentially. So

44:32

what? Maybe you get a

44:34

shorter course of infection. You

44:36

get less virus production. Yeah.

44:39

Hmm. I mean, I'm interested

44:41

because I'd like to know

44:43

in vaccinated people, do you

44:45

ever see infection? They notice

44:47

in this study, which is

44:49

very small, they don't see

44:51

the same genotype. Right. But

44:54

they do see effects on

44:56

other genotypes. So I wonder.

44:58

If you did enough number,

45:00

if you had enough people

45:02

in the cohort, would you

45:04

see infections of the same

45:06

genotype as you were vaccinated

45:09

against? I don't see why

45:11

not, right? It's just, it

45:13

would not, maybe the infection

45:15

would be very brief, right?

45:17

Because you have antibodies or

45:19

whatever kind of immunity. Anyway,

45:21

I thought this is really

45:24

interesting because I don't really

45:26

think much about. You think

45:28

about people get HIV and

45:30

it's cleared and then you

45:32

have HIV chronic and you

45:34

get cancers. What about in

45:37

between, which is what this

45:39

is, you know, this acute

45:41

infection. And there's some hints

45:43

here about what's controlling it,

45:45

but there's still a lot

45:47

of work to do. Meantime

45:49

get vaccinated. Yeah, if you

45:52

can, if you're not too

45:54

old. Yeah. I mean you

45:56

could get you could get

45:58

HIV it's not like yellow

46:00

fever vaccine where you're worried

46:02

about you know some bad

46:04

outcome if you're too old

46:07

and get vaccinated it's just

46:09

it's too late. for a

46:11

lot of us. You know,

46:13

it's really unfortunate there's a

46:15

there's a big attack on

46:17

HDV vaccines in this country.

46:19

There are lots of lawsuits

46:22

coordinated by you know who.

46:24

Yep. There's a lot of

46:26

attack on a lot of

46:28

vaccines in your country even.

46:30

Yeah. Is any vaccine safe?

46:32

You know, there's no auto

46:34

immunity, there's no this or

46:37

that. But if you get,

46:39

if you can get into

46:41

a civil court, all you

46:43

need to do is convince

46:45

the jury, you don't even

46:47

have to convince them of

46:49

the science. You just say,

46:52

look at this person, they

46:54

got this after getting vaccinated,

46:56

and that's it. The jury

46:58

is likely to make an

47:00

award. And so the problem

47:02

is, right now, you know,

47:05

there's a vaccine compensation fund,

47:07

where if you claim you've

47:09

been injured, they review it,

47:11

and then, and then. for

47:13

HDV, they don't give awards

47:15

because there's no, there's no,

47:17

there's no, no documented harm.

47:20

There's no harm. Yet, when

47:22

it gets to civil court

47:24

and, you know, the head

47:26

of HHS can make a

47:28

difference in how often these,

47:30

these go to, it could

47:32

be that like what happened

47:35

in the 80s, many vaccine

47:37

manufacturers may drop out because

47:39

they can't afford this, the

47:41

costs of this litigation, right?

47:43

In the, in the, in

47:45

the 80s like. the manufacturers

47:47

of vaccines dropped precipitously until

47:50

Reagan signed into law the

47:52

Vaccine Injury Protection Act. And

47:54

so that could be gone,

47:56

you know, and so women

47:58

who benefit incredibly from HDV

48:00

vaccines may have trouble finding

48:02

them. So I'm very upset

48:05

about this. The whole politicization

48:07

of science and vaccineology in

48:09

particular is unacceptable. It's unacceptable.

48:11

It's unacceptable. It's unacceptable. And

48:13

you know, we got letters

48:15

from people who said, you.

48:17

better be political because that's

48:20

the only way that you're

48:22

going to be heard. Okay

48:24

another cool paper here P&AS

48:26

summary please. Yeah so let

48:28

me get to my summary

48:30

and my tabs open here.

48:33

Another virus that you get

48:35

it with age it can

48:37

also be very a little

48:39

bit more severe. Right. I

48:41

was just adding that. Right.

48:43

So Epstein bar virus, Balf

48:45

0 stroke 1, BALF 0

48:48

stroke 1, subverts the Kaviolan

48:50

and Arad pathways to target

48:52

B cell receptor complexes for

48:54

degradation is the title. This

48:56

paper is not open access,

48:58

unfortunately. The co-first authors are

49:00

Stephanie Pei-tung-U and Yiffay-Liao. Senior

49:03

author is Benjamin Givers. The

49:05

team is from Brigham and

49:07

Women's Hospital in Boston. So

49:09

I should say this is

49:11

an all Cambridge centered team.

49:13

So Brigham and Women's is

49:15

in Boston, Harvard graduate program

49:18

of virology in Boston, Broad

49:20

Institute of Harvard and MIT

49:22

in Cambridge, in Cambridge, UK.

49:24

So as a quick summary.

49:26

Somewhere north of 95% of

49:28

humans carry Epstein bar virus,

49:30

which can cause mononucleosis, it

49:33

can trigger multiple sclerosis, it

49:35

can also cause various cancers

49:37

in some people. It is

49:39

a herpes virus, and like

49:41

other herpes viruses, it has

49:43

two possible modes of infection

49:46

in a cell, litic and

49:48

latent. During the latent phase,

49:50

EBV hides out right in

49:52

the immune system in B

49:54

cells, which is... pretty gutsy.

49:56

This paper focuses on the

49:58

litic cycle where EBV reactivates

50:01

from latency and starts actively

50:03

infecting and killing cells again.

50:05

In order to do that,

50:07

it has to somehow prevent

50:09

the B cells in which

50:11

it lives from mounting an

50:13

immune response that would stop

50:16

it. Using a bunch of

50:18

cool proteomic and biochemical techniques,

50:20

these folks found that an

50:22

EBV-produced protein called Balf zero

50:24

stroke one, or Balf zero

50:26

one, I don't know what

50:28

we're going to call it,

50:31

targets to B- B-cell receptor

50:33

complexes and directs them to

50:35

the cell's proteasome for degradation.

50:37

Besides revealing potential targets to

50:39

intervene and stop E-B-B-B-B-B-B-E-R activation,

50:41

this also suggests a possible

50:43

new strategy for chemotherapies against

50:46

lymphomas that depend on B-cell

50:48

receptor signaling. So that's my

50:50

short version. There is a

50:52

E-B-V protein called barf. Barf.

50:54

Yeah, I was going to

50:56

say it was Balf and

50:58

barf because they also mentioned

51:01

them in the paper. Right.

51:03

Right. Very funny. Yeah, so

51:05

this is cool because you

51:07

get infected with EBV, you

51:09

know, 95% of adults are

51:11

infected early in life and

51:14

the virus infects epithelial cells

51:16

and then infects bee cells

51:18

and makes them into memory

51:20

bee cells. So they're... It's

51:22

quiescent sitting there with antibody

51:24

on their surface and the

51:26

genome is in there and

51:29

a couple of viral proteins

51:31

are made. It's a little

51:33

like a bank robber hiding

51:35

out at the police station.

51:37

It's very interesting. And these

51:39

B cells can hang out

51:41

anywhere they could be in

51:44

the bone marrow and then

51:46

periodically they reactivate, which means

51:48

they start making virus. There's,

51:50

as you'll see in the

51:52

paper, there's this idea that

51:54

somehow there's cross-linkingking of the

51:56

B cells, memory B cells

51:59

have. antibody on the surface,

52:01

right? Which, if it recognizes

52:03

its cognate antigen... will activate

52:05

the B cell so that

52:07

it starts cranking out antibody.

52:09

But if the antibodies are

52:11

cross-length, they will turn on

52:14

EBIV, LITIC cycle, make virus,

52:16

and then that virus will

52:18

go back to your epithelial

52:20

surfaces and reproduce out and

52:22

spread to somebody else. So

52:24

it's a very cool strategy

52:27

where B cells are essential.

52:29

You know, in herpes simplex,

52:31

neurons are essential for latency.

52:33

but for EBV it's B

52:35

cells. The cool thing is

52:37

that it makes them into

52:39

memory a B cell. So

52:42

as Alice said, how does

52:44

this, how does the virus

52:46

avoid this antibody on the

52:48

surface? Right, so some of

52:50

the B cells it infects

52:52

are going to be potentially

52:54

B cells that are responding

52:57

to EBV. Yeah, it turns

52:59

out there are a lot

53:01

of your B cells after

53:03

any BV infection or EBV.

53:05

Antibody positive, yeah, so that's

53:07

a problem, right? Yeah, so

53:09

how are you going to

53:12

get out of that? It's

53:14

always a way. There's yes.

53:16

This paper was very cool,

53:18

but some of the technique,

53:20

it was dense to get

53:22

through all their experiments, and

53:24

there's so much work in

53:27

this paper, it was very

53:29

impressive, but the amount of

53:31

experiments they did in Western

53:33

Blots. Wow, I would never

53:35

want to have to do

53:37

that many Westerns, but it's

53:39

really cool. So they call

53:42

this the B cell receptor.

53:44

The B cell has antibodies

53:46

on its surface. You can

53:48

also call those B cell

53:50

receptors. Right. But they're basically

53:52

antibody molecules stuck in the

53:55

membrane and they're specific for

53:57

one epitope. And if the

53:59

cell finds that epitope wherever,

54:01

it's going to get activated.

54:03

So they looked at interactions

54:05

among. viral and cell proteins.

54:07

And they find interactions between

54:10

the heavy chain of immunoglob.

54:12

and two Eppstein bar virus,

54:14

early Litic proteins, Balf and

54:16

barf. Balfo 1. What would

54:18

just call it Balf and

54:20

barf? And also with multiple

54:22

proteasome components and proteins involved

54:25

in transport. So this is

54:27

intriguing and they want to

54:29

know what's going on here.

54:31

So said the first question

54:33

they ask is, these two

54:35

proteins on their own, could

54:37

they? get rid of the

54:40

B cell receptor on the

54:42

surface of B cells. So

54:44

they make, they produce the

54:46

protein in cells and on

54:48

their own and only Balfe.

54:50

So the, on the surface

54:52

of these B cells, not

54:55

only is there antibody, the

54:57

B cell receptor, but there's

54:59

also C.D. 79 and another

55:01

C. C. D. 79A and

55:03

C. I think it was.

55:05

So when they put Balfin

55:07

these cells, it depletes 79B

55:10

and the antibody heavy chain.

55:12

So that's interesting that the

55:14

protein can do that. So

55:16

they ask whether both can

55:18

each target for degradation. And

55:20

either one, expression of either

55:23

one is actually enough to

55:25

deplete IGM and CD 79A.

55:27

Okay, so what is degrading

55:30

this? There's some interesting drugs

55:32

in this paper. Bortizomib. Bortizomib.

55:34

Who the heck would name

55:36

that? So it's a proteasomib.

55:39

So it's a proteasomib. People

55:41

who came up with comernity.

55:43

Comernity. Cels have a garbage

55:46

disposal called the proteosome. Big

55:48

protease in the cytosolus. that

55:50

are targeted for degradation by

55:52

a called ubiquitination, but they

55:55

also will chop up proteins

55:57

for loading onto MHC and

55:59

presentation and so forth. So

56:01

kind of important. Proteosome, they

56:04

have an inhibitor and when

56:06

they add this inhibitor to

56:08

cells that make valve, you

56:11

get more antibody on the

56:13

surface. So this is inhibiting

56:15

the removal of antibody from

56:17

the surface. And you know,

56:20

this is a paragraph with.

56:22

14 different experiments in it.

56:24

Oh my gosh. It's one

56:26

paragraph in the paper. It

56:29

was hard to keep track.

56:31

I had to read so

56:33

slowly. Then they have crisper

56:35

experiments, right, where they knock

56:38

out balf. And they show

56:40

that that is important for

56:42

down regulating the antibody from

56:45

the surface. And so they

56:47

conclude from all of this.

56:49

I'm not going to go

56:51

through it all. It's too

56:54

much. I want to give

56:56

you the bottom line here.

56:58

That balf. somehow associates with

57:00

these B cell receptors and

57:03

destabilizes them. How it does

57:05

that we're going to find

57:07

it? Excuse me, how it

57:10

does that we're going to

57:12

find out? So somehow the

57:14

mouth has got to take

57:16

the antibody from the plasma

57:19

memory and get it inside

57:21

the cell where it can

57:23

be chopped up, right? So

57:25

they're thinking, well, maybe some

57:28

kind of endocytosis. And there

57:30

are lots of kinds of

57:32

endocytosis. They use microscopy and

57:34

fluorescence to study which one.

57:37

And it looks like endocytosis

57:39

is involved in general, but

57:41

it's not clathrin mediated. So

57:44

endocytosis is defined based on

57:46

protein markers. One of them

57:48

is clathrin. And then it

57:50

was caviolar. You know Angelo,

57:53

it's I always think of

57:55

pasta when I think of

57:57

cavioli. about the exact same

57:59

thing, and I was like,

58:02

wow, I'm so Italian. And

58:04

I didn't think anybody else

58:06

would have thought of that.

58:09

Confitalian, yes. So the Marker

58:11

for Caviola endocytosis. Yeah, I

58:13

want to do that. Marker,

58:15

endocytosis is caviolin, which is

58:18

not to be a pasta,

58:20

right? It sounds like it.

58:22

Anyway, there's also inhibitors here.

58:24

So inhibitors of clathrin mediated

58:27

endocytosis do not block the...

58:29

the removal of antibody from

58:31

the cell surface. But they

58:33

have an inhibitor. And that

58:36

inhibitor, by the way, is

58:38

chloropromesine. Sounds familiar. There's a

58:40

cavioli inhibitor, genistine, that inhibits

58:43

the down regulation of the

58:45

antibody. Cavioli, basically it's just

58:47

like a shuttling system, no,

58:49

it'll take it like from

58:52

the cell, from the plasma

58:54

membrane, just to... So Cavioli,

58:56

you know, is interesting because

58:58

it brings it to the

59:01

ER, whereas Clafin mediated, just

59:03

brings it into the cytoplasm,

59:05

right? And they fused with

59:08

lysomes, but interestingly, Caviolin targets

59:10

the ER, so that's going

59:12

to become important here as

59:14

we will find out. They

59:17

also deleted Caviolin. the main

59:19

structural protein of cavioli. And

59:21

again, if you delete that

59:23

by CRISPR, you inhibit the

59:26

ability of Balfe to get

59:28

rid of antibodies from the

59:30

cell surface. So the conclusion

59:32

is Balfe triggers B cell

59:35

receptor internalization via the Caviolin

59:37

pathway. Right. Which that in

59:39

itself is so cool. Also

59:42

slightly horrifying but very cool

59:44

that the virus is internalizing

59:46

the BCR like to hide

59:48

itself from the immune system.

59:51

Yeah it's amazing. Taking the

59:53

sign quick so nobody literally.

59:55

Yeah bring down the flagpole

59:57

bring down the flag. So

1:00:00

then this is this confused

1:00:02

me for a long time

1:00:04

but I think I figured

1:00:07

it out. So if you

1:00:09

cross-length the antibodies on a

1:00:11

latently infected EBV cell it

1:00:13

will activate the litic cycle

1:00:16

and they want to know

1:00:18

is it the cross-linking that

1:00:20

is down regulating the antibody

1:00:22

or is it the the

1:00:25

actual litic cycle of EBV

1:00:27

itself? And it turns out

1:00:29

it's the litic cycle that

1:00:31

you need. It's not just

1:00:34

the cross-linking, but the induction

1:00:36

of the EBV litic cycle

1:00:38

induces internalization of these B

1:00:41

cell receptors into caviosomes. It's

1:00:43

cool, right? Yeah. All right.

1:00:45

So how does this get

1:00:47

the antibody degraded? Well, there

1:00:50

is what they're thinking is.

1:00:52

these antibodies, these B cell

1:00:54

receptors, are ending up in

1:00:56

the endoplasmic reticulum because this

1:00:59

is the caviolin pathway. And

1:01:01

there is a path, a

1:01:03

known pathway where misfolded proteins

1:01:06

are taken from the ER

1:01:08

to the proteasome. It's called

1:01:10

the ER associated degradation pathway.

1:01:12

I think that's in the

1:01:15

title ERAT. Yeah. Of the

1:01:17

paper. So basically if... Protheas

1:01:19

are misfolded in the ER,

1:01:21

which happens a lot. This

1:01:24

pathway will take them to

1:01:26

the proteasome where they're going

1:01:28

to be degraded, because they're

1:01:30

misfolded. You don't want them.

1:01:33

It sends them to the

1:01:35

shredder. It's like a quality

1:01:37

control. So now the virus

1:01:40

is like, oh, let's throw

1:01:42

these BCRs. We don't need

1:01:44

these. So basically we're going

1:01:46

to find out is that

1:01:49

the virus. It's spoiler. It

1:01:51

says it slips these BCRs

1:01:53

into this. So they do

1:01:55

a whole bunch of experiments

1:01:58

to prove this. There's this.

1:02:00

protein that's important

1:02:02

for erad function

1:02:05

and if they knock

1:02:07

it out it reduces

1:02:09

the degradation of the antibody.

1:02:12

They have an inhibitor

1:02:14

of erad called, oh

1:02:16

Eor, it's called Eor,

1:02:19

E-E-Y-A-Rastatin, wow,

1:02:21

that blocks the pathway

1:02:23

and that also

1:02:25

pairs degradation of

1:02:27

the... the cell receptor. And you

1:02:30

know, gosh, every paragraph is

1:02:32

like 20 experiments. It's just

1:02:34

remarkable. It is remarkable. I

1:02:36

mean, there are also controls,

1:02:38

which I'm not mentioning, which

1:02:40

are really important. But,

1:02:42

sure, the results started with, I

1:02:45

think. at least like a whole

1:02:47

page of just the supplemental to

1:02:49

get to figure one. I was

1:02:51

like, did I miss something? I

1:02:53

was reading and I was like, where

1:02:55

are they mentioning figure one? So

1:02:57

so much work was put into this.

1:03:00

All right, so now the ERAD pathways

1:03:02

involved. So now they have to say,

1:03:04

prove that the proteasome is

1:03:07

involved, okay? So the way that

1:03:09

things get targeted to

1:03:11

the proteasome is they have

1:03:13

to have ubiquitin. One way is

1:03:15

to have ubiquity. A little molecule

1:03:18

stuck on to them, covalently

1:03:20

linked, and that's like a

1:03:22

marker to go to the proteosome. And

1:03:24

so they find that they want

1:03:26

to know whether Balf is enough

1:03:29

to induce ubiquitination of these

1:03:31

B cell receptors, right?

1:03:33

And the answer is yes.

1:03:35

You can see they get

1:03:38

ubiquitinated. They have an inhibitor

1:03:40

of ubiquitination. first enzyme in

1:03:43

the pathway is called

1:03:45

ubiquitin, ubiquitin activating enzyme

1:03:47

E1 ligase. They can inhibit

1:03:49

that and that impairs

1:03:51

BCR degradation. And so

1:03:54

this proves, all these

1:03:56

experiments prove that Balfe uses

1:03:58

the ERAD pathway. I hate

1:04:00

to bring to get the

1:04:03

B cell receptor ubiquitinated. Remember,

1:04:05

it's now taken off the

1:04:07

cell surface. It's in the

1:04:10

ER. It's going to get

1:04:12

ubiquitinated and boom, going to

1:04:14

proteasomes. So that's the mechanism.

1:04:17

But how does this happen?

1:04:19

Like how does B cell

1:04:21

receptor on the cell surface?

1:04:24

All right, so they say,

1:04:26

let's look at the cytoplasmic

1:04:28

domains. So CD 79A and

1:04:31

B have long domain, 61

1:04:33

and 41 amino acids, and

1:04:35

immunoglobiones have three, and they

1:04:38

say, oh, it's got to

1:04:40

be the longer one. Nope,

1:04:42

it's not. They can deplete

1:04:45

CD 79 or 79B, and

1:04:47

it has no effect whatsoever

1:04:49

on the down regulation of

1:04:52

the B cell receptor, right?

1:04:54

It is down regulated along

1:04:56

with antibody, but it's not

1:04:59

important. It's a bystander because

1:05:01

if you get rid of

1:05:03

it, because I think the

1:05:06

valve is sticking to the

1:05:08

cytoplasmic tail of these proteins,

1:05:10

right? But no, it's not.

1:05:13

You don't need these proteins

1:05:15

at all. So so much

1:05:17

for that. So then they

1:05:20

turn to the antibody, which

1:05:22

is... got a three amino

1:05:24

acid cytoplasm. They go, well,

1:05:27

this must be important. So

1:05:29

they take out these three

1:05:31

amino acids, and guess what?

1:05:34

The antibody stays on the

1:05:36

surface. And they think these

1:05:38

are being, these are, they're

1:05:41

two lysines, and lysines are

1:05:43

typically ubiquitinated. So they think

1:05:45

maybe these are being ubiquitinated

1:05:48

eventually. But that's mouth. is

1:05:50

binding to this three amino

1:05:52

acid cytoplasmic domain. It's very

1:05:55

interesting. Okay, now this is

1:05:57

where it gets even cooler.

1:05:59

So when Epstein-Bar virus is

1:06:02

mature in the cell, so

1:06:04

the DNA reproduces in the

1:06:07

nucleus, and then it acquires

1:06:09

membranes and traverses the secretary

1:06:11

compartments on a way to

1:06:14

the plasma membrane, this is

1:06:16

the same pathway that antibodies

1:06:18

use to get to the

1:06:21

cell surface. So they're wondering.

1:06:23

It could be a problem

1:06:25

having antibody going in the

1:06:28

same vesicle, say, if it's

1:06:30

an antiviral antibody, that would

1:06:32

be not good, right? And

1:06:35

so maybe Balfe's function is

1:06:37

actually to also interfere at

1:06:39

that step, right, to make

1:06:42

sure that the antibody is

1:06:44

not binding to virus. And

1:06:46

so they do amazing numbers

1:06:49

of experiments. using a monoclonal

1:06:51

antibody against an epsine bar

1:06:53

virus protein, which will neutralize

1:06:56

virus infectivity. And if you

1:06:58

don't have a balf around,

1:07:00

you get much less infectious

1:07:03

virus produced compared to if

1:07:05

you have balf around. So

1:07:07

this balf is doing... a

1:07:10

couple of things is getting

1:07:12

antibody off the surface and

1:07:14

degrading it, but that is

1:07:17

probably so that it doesn't

1:07:19

interfere with virus production. And

1:07:21

they actually showed that this

1:07:24

valve prevents the incorporation of

1:07:26

the antibody into the virion

1:07:28

envelopes. Otherwise you would be

1:07:31

making virus particles with antibodies

1:07:33

stuck on destined to sail.

1:07:35

That's not going to work

1:07:38

well. No, yeah, already doomed,

1:07:40

right, because you have antibody.

1:07:42

I mean, the cell is

1:07:45

trying hard. It's doing its

1:07:47

best. Yeah. But there's always

1:07:49

a countermeasure from virus, and

1:07:52

his valve one is... Balf

1:07:54

protein is really important for

1:07:56

countering that. And there's a

1:07:59

very nice figure that, there's

1:08:01

one more really cool experiment,

1:08:03

but there's a very nice

1:08:06

figure showing you in B

1:08:08

cells with B-cells, the antibody

1:08:10

on the surface is taken

1:08:13

in and ubiquitinated and brought

1:08:15

to the proteasome and degraded.

1:08:17

Now, in those same cells,

1:08:20

E-B-V is being produced, right?

1:08:22

In the absence of B-F-1,

1:08:24

they would have antibodies stuck

1:08:27

on to them and they

1:08:29

would be the antibody would

1:08:31

go on the surface and

1:08:34

the virus would be stuck

1:08:36

to it and it would

1:08:38

never go anywhere. It's really

1:08:41

nice. All right, so it

1:08:43

turns out that certain cancers,

1:08:45

certain non-Hodgekin lymphomas need BCR

1:08:48

signaling to survive. So the

1:08:50

BCR is on the surface

1:08:52

of the B cell. These

1:08:55

are B cell cancers. These

1:08:57

are B cell cancers. they

1:09:00

need signaling to survive. So they're

1:09:02

thinking, hey, if we put Balfin,

1:09:04

going to get rid of the

1:09:07

BCR, there's not going to be

1:09:09

any signaling. What's going to happen?

1:09:12

So they did it and the

1:09:14

tumor cells die. Ask your doctor

1:09:16

about Balfe. So so cool, right?

1:09:19

Also, this is all in vitro.

1:09:21

Nothing has been done. So we

1:09:23

don't know what Balf would do

1:09:26

in an organism, in a mouse,

1:09:28

even in a human, let alone

1:09:30

a human. Now I'm pretty sure

1:09:33

you don't want this in all

1:09:35

your B cells. Yeah, still very

1:09:37

cool that it happened in vitro,

1:09:40

very cool, but what does that

1:09:42

mean and how can we use

1:09:44

that? They say we need a

1:09:47

model, we need an animal model

1:09:49

to test this. But it's cool

1:09:51

you put Balf in these cells

1:09:54

and it triggers cell death because

1:09:56

there's no more B cell. receptor-dependent

1:09:58

signal. A B cell receptor is

1:10:01

gone. Isn't that cool? Yeah. And

1:10:03

I don't think they said anything

1:10:05

about, like, did they measure, like,

1:10:08

interferons or anything? in the cells?

1:10:10

I don't think so, eh? No,

1:10:12

they didn't. They didn't at all.

1:10:15

Because I wonder if Balfin itself

1:10:17

is immunogenic, it must be. Like

1:10:19

what type of immune response, if

1:10:22

any, would it elicit? Yeah. I

1:10:24

don't know. They don't talk about

1:10:26

that at all. TBV when they

1:10:29

do it in a mice. So

1:10:31

this is cool, they say, as

1:10:33

a B cell tropic herpes, TBBV

1:10:36

must cope with large quantities of

1:10:38

immunoglolomulins. with this protein called Balfe

1:10:40

facilitates release of cells that express

1:10:43

antibody. So again these B cells

1:10:45

are making EBV, right? The litic

1:10:47

cycle is turned on. They're making

1:10:50

EBV. You can't have this antibody

1:10:52

in these cells because it's not

1:10:54

just on the surface. It's inside

1:10:57

the cell making its way up

1:10:59

and it's going to stick to

1:11:01

virus. So this is a brilliant.

1:11:04

That's why. the valve is there

1:11:06

so that these antibodies don't neutralize

1:11:08

virus infectivity. Because if you're going

1:11:11

to replicate the B cell, you

1:11:13

need to have the right equipment

1:11:15

to do that. Now, they say

1:11:18

here, these findings raise a question

1:11:20

of how frequently. does EBIV, in

1:11:22

fact a B cell that has

1:11:25

an antibody to one of its

1:11:27

proteins, right? You may think, ah,

1:11:29

that can't be very common. It

1:11:32

turns out they're germline encoded EBI,

1:11:34

antibodies, and they're more frequent than

1:11:37

you might think. And in fact,

1:11:39

well, at least for T cells,

1:11:41

20% of tonsular T cells can

1:11:44

be reactive with EBIV encoded peptides.

1:11:46

So they're thinking that there

1:11:49

are a lot of B

1:11:51

cells that could react with

1:11:54

with EBV. So this protein

1:11:56

has emerged to target just

1:11:58

this one aspect, which is

1:12:01

really important, of EBV production.

1:12:03

I'm just thinking, what if

1:12:06

you could make a vaccine

1:12:08

lacking this thing? Would that

1:12:11

be a good vaccine? I

1:12:13

don't know. Valve zero. Remember,

1:12:15

we've done this paper on

1:12:18

two of the EBV is

1:12:20

a risk factor for MS,

1:12:23

right? It's a trigger for

1:12:25

MS. It's quite clear. And

1:12:28

so we need to prevent

1:12:30

people from being infected somehow.

1:12:32

I don't know how you

1:12:34

do that. But anyway, cool,

1:12:36

right? Isn't that a cool

1:12:38

thing? Very cool. I like

1:12:40

that very much. A biphasic

1:12:42

life cycle. Now, there's a

1:12:44

lot of molecular biology here,

1:12:46

which is unusual for us

1:12:48

to do these days. We

1:12:51

used to do it pre-covin.

1:12:53

We used to do a

1:12:55

lot of these papers, but

1:12:57

I think. It's very cool.

1:12:59

It tells you basic fundamental

1:13:01

molecular biology of how virus

1:13:03

is reproducing evade. There you

1:13:05

go. EBV. Let's do some

1:13:07

email. Angela, can you take

1:13:09

the first one? Yes, one

1:13:11

second from Joseph. Joseph writes,

1:13:13

hello to a 15. I

1:13:15

would like to express my

1:13:17

sincere gratitude and sense of

1:13:20

honor to have our recent

1:13:22

paper on rotavirus and sp4

1:13:24

and intracellular calcium waves reviewed

1:13:26

on the TW podcast this

1:13:28

week. It was an excellent

1:13:30

summary of the paper particularly

1:13:32

delineating the intracellular versus the

1:13:34

intracellular calcium signals. You all

1:13:36

asked some really excellent questions

1:13:38

and I will work this

1:13:40

weekend to write up six-cent

1:13:42

answers to them both for

1:13:44

your own edification and in

1:13:46

case you get... questions from

1:13:48

two of listeners. As a

1:13:51

teaser, I am giving you

1:13:53

the plenary lectures on July

1:13:55

15th at ASV 2025. Some

1:13:57

of your questions will be

1:13:59

answered in that talk. Stay

1:14:01

tuned. Thank you all again

1:14:03

for your contribution to virology,

1:14:05

education, and communication. And thank

1:14:07

you for highlighting our work.

1:14:09

It's a huge compliment. Best

1:14:11

Joe. And Joe is a

1:14:13

PhD associate professor at Bayer

1:14:15

College of Medicine. Baylor, sorry.

1:14:17

It was a very nice

1:14:20

paper. Yeah. Yeah, that was

1:14:22

an easy one. Calcium waves.

1:14:24

All right, Fernando writes high

1:14:26

twive enquirers at the end

1:14:28

of 1189 Awesome episode with

1:14:30

the calcium waves you speculated

1:14:32

about how the deep snow

1:14:34

road trenches in Japan come

1:14:36

about as a twice delighted

1:14:38

Hokkaido deep powder skiing visitor

1:14:40

Let me enlighten you with

1:14:42

a YouTube video and he

1:14:44

sends a link and I

1:14:46

watched this And the answer

1:14:48

is it's a really really

1:14:51

big snowblower and it's really

1:14:53

cool. As is that's how

1:14:55

it's done. Our own California

1:14:57

Sierra Road and rail snow

1:14:59

plows are not far behind

1:15:01

and sends pictures or YouTubes

1:15:03

of those. Finally I wonder

1:15:05

if the choice of Hokusai's

1:15:07

great wave off Kanagawa as

1:15:09

the episode image was triggered

1:15:11

by the wave plus Japan

1:15:13

association. Was it? Not

1:15:16

consciously. So I was looking

1:15:18

for something of a wave,

1:15:20

right? And I searched for

1:15:22

a wave and did lots

1:15:24

of ocean, beautiful ocean waves.

1:15:26

And then I saw that,

1:15:28

which is a gorgeous piece,

1:15:31

right? And I said, I

1:15:33

have to do this. But

1:15:35

I must have been subliminal

1:15:37

because of the Japan. thing

1:15:39

with the snow, right? Yeah,

1:15:41

it's a famous Edo period

1:15:43

block print. Love it. Just

1:15:45

love it. Yeah. Yeah. Fernando

1:15:47

continues. I love digressions in

1:15:49

the midst of serious virology.

1:15:52

Always learning. Long time supporter.

1:15:54

Fernando, thank you. Back there's

1:15:56

a very good video. Who

1:15:58

is the famous, not Hokusai,

1:16:00

but. There's another artist of

1:16:02

the same era. Anyway, he

1:16:04

took a trip from Edo

1:16:06

to Kyoto, I think. So

1:16:08

Edo at the time was

1:16:11

the capital of Japan. Right.

1:16:13

And he took a trip.

1:16:15

And this was a trip

1:16:17

that the samurai used to

1:16:19

take all the time. So

1:16:21

he went with them along

1:16:23

on this trip. And he

1:16:25

stopped at all the little

1:16:27

places and made images, right.

1:16:29

And some very famous. images

1:16:32

came out of that. And

1:16:34

they look very much like

1:16:36

this. Same style. Yeah, same.

1:16:38

I love it. So yeah,

1:16:40

I love this style and

1:16:42

I think it probably the

1:16:44

wave and it was clearly

1:16:46

the best wave thing that

1:16:48

showed up. And it must

1:16:50

have been the snow also

1:16:53

that triggered it. Yeah, I

1:16:55

like that. Are John writes

1:16:57

the same thing. You probably

1:16:59

received more responses to how

1:17:01

the Japanese snow walls are

1:17:03

made, but in case here's

1:17:05

a short but clear description.

1:17:07

This one. is a website.

1:17:09

The snow walls, the snow

1:17:11

walls are made. The snow

1:17:14

walls of Tatiyama Kurobi. And

1:17:16

lots of maps and pictures.

1:17:18

And they're the big, lots

1:17:20

of heavy machinery. Yes. Look

1:17:22

at those things. The road

1:17:24

must be located under the

1:17:26

snow. They're using GPS to

1:17:28

map its exact location. A

1:17:30

bulldozer is used to scrape

1:17:32

off the top layers and

1:17:35

then these snowblowers start spitting

1:17:37

out. What a science, eh?

1:17:39

I mean, I guess they

1:17:41

want to have this road

1:17:43

open. Yep. Yeah. And the

1:17:45

highest it's ever been is

1:17:47

23 meters. Wow. That's pretty

1:17:49

high. I love it. Thank

1:17:51

you listeners. I love when

1:17:53

you get involved in our

1:17:56

stuff. Especially our off-road stuff.

1:17:58

Okay, back to you. Angela.

1:18:00

Yes, John writes, interesting about

1:18:02

why we don't vaccinate chickens.

1:18:04

Given the number of chickens

1:18:06

culled, is keeping some apparently

1:18:08

significant percent of the export

1:18:10

market still worth it not

1:18:13

to vaccinate. Numbers for how many

1:18:15

birds have been culled are all over

1:18:17

the place, but in trying to find

1:18:19

out, I learned that the US... the

1:18:22

USDA, compensates farmers for birds and eggs

1:18:24

lost. There are probably a lot of

1:18:26

underlying details there, but maybe that's why

1:18:28

there's little pressure against not vaccinating. But

1:18:31

I'm going to guess that the chickens

1:18:33

in the stores now are mostly from

1:18:35

vaccinated chickens and that the future supply

1:18:37

of chicks will come from that source

1:18:40

too. So here's an idea. label egg

1:18:42

cartons with in all caps, these eggs

1:18:44

laid by chickens vaccinated against H5N1

1:18:46

bird flu. That gets a further

1:18:48

message out there for vaccination and

1:18:51

it will also decrease demand a

1:18:53

bit from the anti-vaxers that won't

1:18:55

buy them, helping to ease the

1:18:57

upward pressure on price. Best regards

1:18:59

John. So I think wasn't the

1:19:01

reason they don't vaccinate because

1:19:04

it's a problem with export?

1:19:06

Well, yeah, exactly trade. traits and

1:19:08

also they can be asymptomatic infections.

1:19:10

There's so many things that you

1:19:12

can't control with animals like when

1:19:14

stamping out in like culling of

1:19:17

all the animals is very necessary

1:19:19

because you don't know if another

1:19:21

bird also that's flying in migratory

1:19:23

bird is then taking that virus

1:19:25

to then another you know down

1:19:28

the road to another chicken farm

1:19:30

and it's just people don't realize

1:19:32

how many secretions animals make and

1:19:34

how easily contempt like they can

1:19:36

transmit from one another like if you see

1:19:38

a chicken cage it's like 20 chickens in

1:19:40

a cage right next to it there's another

1:19:42

20 chickens right next to it there's

1:19:45

another 20 chickens if one of those

1:19:47

chickens are barely even in a cough

1:19:49

you won't even know that they're sick

1:19:51

until they're all infected with influenza and

1:19:53

then some of them might already be

1:19:55

going out to market or wherever and

1:19:57

then there's contaminated meat and then you're

1:19:59

sending like possibly contaminated meat to

1:20:01

another country exporting it. And well,

1:20:03

globally it's illegal. Like no other

1:20:05

countries will accept the meat if

1:20:07

the chickens aren't, like if they

1:20:09

were identified with bird flu and

1:20:11

then vaccinated against bird flu, it

1:20:14

makes no sense. They're just all

1:20:16

killed unfortunately. And we need to

1:20:18

just control the spread. Keep your

1:20:20

chickens inside. Don't let them get

1:20:22

near geese, migratory birds, water. So

1:20:24

you guys have, do you have

1:20:26

chicken culling in Canada? Of course,

1:20:28

yes, it's something that's done worldwide.

1:20:30

And it's not only chickens, it's

1:20:32

cows, it's pigs, it's any sort

1:20:35

of infectious disease that is, if

1:20:37

you do something called like stamping

1:20:39

out or like a cull, every

1:20:41

single animal has to be killed.

1:20:43

And like with the African swine

1:20:45

flu, for example, in Europe, it's

1:20:47

not even just your farm. It's

1:20:49

every farm within, I think it's

1:20:51

like a 30 kilometer radius or

1:20:53

something. It's that... There's different depending

1:20:56

on what country you live in.

1:20:58

There's X amount of kilometers from

1:21:00

where that infected point was, like

1:21:02

even with foot and mouth disease

1:21:04

it was like that for a

1:21:06

long time, that the radius around

1:21:08

your infected farm also had to

1:21:10

kill all of their animals to

1:21:12

assure that it hadn't spread. There's

1:21:14

also, so that that's an excellent,

1:21:17

thank you for that description of

1:21:19

the veterinary aspects of it. The

1:21:21

political and business context of this

1:21:23

also affects the process because agriculture

1:21:25

has ridiculously narrow profit margins. Chickens

1:21:27

in particular, if you're raising chickens

1:21:29

for eggs, you are just barely

1:21:31

getting by even if you've got

1:21:33

an enormous operation, maybe especially if

1:21:35

you've got an enormous operation. So

1:21:38

the cost of vaccinating all those

1:21:40

chickens is significant. You'd have to

1:21:42

go through thousands of chickens and

1:21:44

vaccinate them all, you'd have to

1:21:46

pay for the vaccine and on

1:21:48

and on and somebody skilled enough

1:21:50

to administer it. On the other

1:21:52

hand, every, basically every country in

1:21:54

the world, certainly every developed country

1:21:56

in the world, massively... subsidizes their

1:21:59

farmers. And the US is king

1:22:01

of this. I mean, we throw

1:22:03

billions of dollars at our farmers.

1:22:05

And I'm not objecting to that.

1:22:07

That's, well, I would object to

1:22:09

some aspects of it. But this

1:22:11

is an ongoing program. And as

1:22:13

this letter points out, the farmers

1:22:15

are compensated for the chickens they

1:22:17

have to call. And if they

1:22:20

have to call pigs and if

1:22:22

they have to call cattle, the

1:22:24

government's going to pay them for

1:22:26

those. So, on the one hand,

1:22:28

you could pay a lot of

1:22:30

your own money out of your

1:22:32

non-existent profit margin to vaccinate them,

1:22:34

or on the other hand, you

1:22:36

could take your chances and if

1:22:38

the virus comes, you just call

1:22:41

them all and you get reimbursed

1:22:43

and it's as good as a

1:22:45

sale. So, Angela, you have in

1:22:47

Canada H5N1 in chickens and they

1:22:49

have to be called or whatever

1:22:51

kind of bird, yes? Yes. You'd

1:22:53

have to get them called, yes.

1:22:55

The thing is, is the implementing-

1:22:57

But you don't have the cow

1:22:59

H5N1, I understand, right? Ours of

1:23:02

right now? I don't think so.

1:23:04

Yeah, yeah, yeah. But if we

1:23:06

did, the cows would have to

1:23:08

also get- Well, the US, we

1:23:10

don't call the cows because, I

1:23:12

don't know, they're not sick. And-

1:23:14

But then it's still transmitting to

1:23:16

the birds, possibly into other animals.

1:23:18

Oh my gosh, cows. I mean,

1:23:20

no, they don't call the cows

1:23:23

here. They just wait till they

1:23:25

stop until they stop. till they

1:23:27

stop. making virus and the milk

1:23:29

is clean again. And they pasteurized

1:23:31

the milk. Well, I think from

1:23:33

a producing cow, they wait until

1:23:35

the infection is over. But why,

1:23:37

so here in the US, egg

1:23:39

prices are going up, right? Why

1:23:41

not chicken prices? Why just eggs?

1:23:44

Does anyone know? Broiler, boiler farms

1:23:46

and egg farms are separate. I

1:23:48

see. They're not the same supply

1:23:50

chain. And there are other factors

1:23:52

in the egg supply demand. And

1:23:54

it's a little less so now

1:23:56

that we have more of our

1:23:58

flu vaccines being produced in cell

1:24:00

culture, but flu vaccine production, hundreds

1:24:02

of millions of doses of it,

1:24:05

uses a lot of eggs, traditionally.

1:24:07

Easter is coming up, believe it

1:24:09

or not. Egg consumption goes up

1:24:11

around Easter. And then throw into

1:24:13

it the fact that in the

1:24:15

US we have this highly consolidated

1:24:17

industry that's producing these at. massive

1:24:19

factory scale farms. My understanding is

1:24:21

that in Canada it's a much

1:24:24

more diversified industry, there are more

1:24:26

small suppliers feeding into it, and

1:24:28

so they're not as susceptible to

1:24:30

these shocks, you know, if one

1:24:32

farm gets hit, they call their

1:24:34

chickens, but the farm down the

1:24:36

road is still... tooling along. In

1:24:38

the US, if one farm gets

1:24:40

hit, it's, you know, a gazillion

1:24:42

chickens and that's a big chunk

1:24:45

of your egg supply gone. So

1:24:47

it's differences in the supply chain

1:24:49

in the two countries that have

1:24:51

led to the US having this

1:24:53

rather significant egg shortage. Yeah, overall

1:24:55

there's just been more chicken farms

1:24:57

affected in the US with higher

1:24:59

density of chickens, just more actual

1:25:01

chickens and implementing a vaccine in

1:25:03

poultry. takes a lot of money.

1:25:06

Apart from money, actually like Alan

1:25:08

was saying, like physically vaccinating the

1:25:10

chickens because most of the vaccines

1:25:12

in chickens are in embryo, like

1:25:14

the Newcastle vaccine and these things.

1:25:16

They're not, somebody's not like walking

1:25:18

around actually vaccinating the chicken most

1:25:20

of the time. It's all like

1:25:22

in the actual eggs. Having to

1:25:24

do that would take a lot

1:25:27

of manpower and then also, what

1:25:29

if you don't vaccinate them properly,

1:25:31

partial vaccination, then there's like escape

1:25:33

variants. There's so many things that

1:25:35

could happen that could happen that

1:25:37

I would not. necessarily, I wouldn't

1:25:39

want the influence, like, H5N1 being

1:25:41

vaccinated against, even though it's unfortunate

1:25:43

for the chicken's lives to, you

1:25:45

know, for them to die and

1:25:48

not to be consumed, because at

1:25:50

least they could be consumed. I

1:25:52

think it's for the best to

1:25:54

control. But nevertheless they vaccinate fish,

1:25:56

no problem, right? But for, well,

1:25:58

vaccinate fish against what? What do

1:26:00

you? Fish viral infections. They routinely

1:26:02

take the little, but those fish

1:26:04

viral infections we can't, they're not

1:26:06

necessarily going to spill over into

1:26:09

us or cause anything in humans

1:26:11

or other domesticated species that could

1:26:13

then have repercussions in our food

1:26:15

chain, etc. No, that's just to

1:26:17

protect the fish. so that they

1:26:19

can go to market, they don't

1:26:21

get infected. Yeah. But it is

1:26:23

doable. I mean, they have people

1:26:25

pulling the fish out of the

1:26:27

bucket. Oh, for sure. For sure,

1:26:30

if it's worth it. But in

1:26:32

this case, it's just too dangerous

1:26:34

to try to vaccinate. I understand

1:26:36

why we have to cull, but

1:26:38

this is crazy, right? Yeah. You

1:26:40

think we'd have a better way

1:26:42

or something else than wasting all

1:26:44

that protein. Yep. My gosh. That's

1:26:46

true. And those lives, because they're

1:26:48

all animals. I mean, in the

1:26:51

end, of course, we consume the

1:26:53

animals. And I'm not vegetarian, but

1:26:55

I still do empathize with the

1:26:57

animals that at least we would

1:26:59

be consuming them, having given their

1:27:01

lives for us, literally. And in

1:27:03

this case, they're just going in

1:27:05

the garbage and getting incinerated. And

1:27:07

it's terrible. There have been some

1:27:09

big culls of egg laying forms

1:27:12

in the US lately, like 2

1:27:14

million birds. And they said, the

1:27:16

problem is, if you order chicks

1:27:18

now, if you order chicks now.

1:27:20

To be popular, you're not going

1:27:22

to get him for a year.

1:27:24

Because it takes that long. Yeah.

1:27:26

I'm glad I'm not a chicken

1:27:28

farmer. Yeah, I mean, the corollary

1:27:30

to the egg shortage is you

1:27:33

get a chicken shortage. You mean

1:27:35

there's a chicken egg thing? Yes,

1:27:37

there's a chicken and egg problem

1:27:39

here. Okay. Well, let's see what

1:27:41

happens. One more, Alan. Sure. Anna

1:27:43

writes, hi all. I have been

1:27:45

a long time listener to Twiv

1:27:47

and a big fan of the

1:27:49

work you do in science communication.

1:27:51

You do in science communication. Like

1:27:54

many, I am very concerned with

1:27:56

the direction science funding is taking

1:27:58

in the USA and the global...

1:28:00

repercussions of obviously short-sighted decisions. I

1:28:02

have been part of one of

1:28:04

the laboratories in the WHO Global

1:28:06

Measles and Rubella Laboratory Network for

1:28:08

12 years now. It has been

1:28:10

an honor to work with so

1:28:12

many dedicated people that dedicate their

1:28:15

time and expertise to help making

1:28:17

the world a safer place. The

1:28:19

recent withdrawal of the USA from

1:28:21

the WHO will have a profound

1:28:23

impact in the Measles and Rubella

1:28:25

elimination program, as it will affect

1:28:27

vaccination diagnosis in the poorest countries.

1:28:29

WHO is not perfect, it is

1:28:31

made of humans after all, it

1:28:33

is the best we have though.

1:28:36

I came across this fundraiser for

1:28:38

WHO and thought I would share

1:28:40

it with you in case you

1:28:42

would like to give it the

1:28:44

twive bump. I cannot think of

1:28:46

a better informed audience for it

1:28:48

and links to this donor support

1:28:50

page for WHO with my best

1:28:52

wishes for every one of you.

1:28:55

Anna. Thank you Anna. Cool.

1:28:57

Yeah, Wjo is not perfect, but

1:28:59

it's what we have. Yes, indeed.

1:29:02

People need to, you don't quit,

1:29:04

you try and fix it, right?

1:29:06

If you quit, you can't do

1:29:08

anything about it. Yep. All right,

1:29:11

let's do some picks of the

1:29:13

week. Uplifting picks, with the week.

1:29:15

Angela, what do you have for

1:29:17

us? So mine is like really

1:29:19

cool, horrifying, but cool. So uplifting

1:29:22

for science to better understand how

1:29:24

cancer, you know, certain cancerous cells

1:29:26

are doing their thing, but once

1:29:28

again, also kind of horrifying. So

1:29:31

this is this paper in Nature,

1:29:33

let me just see the authors,

1:29:35

I have to click on the,

1:29:37

so there's a, there's a nature

1:29:40

paper, which is also has like

1:29:42

a news article. So the author,

1:29:44

last author is Togashi. We'll add

1:29:46

it to the show notes, you

1:29:49

guys can see, you guys can

1:29:51

see. and basically titled immune evasion

1:29:53

through mitochondrial transfer in the tumor

1:29:55

microenvironment. So this paper showed that

1:29:58

it's the first time anyone's ever

1:30:00

showed by directional exchange of mitochondria

1:30:02

between two cell types. And this

1:30:04

can, in this case, it was

1:30:07

tumor infiltrating lymphocytes, so called tils

1:30:09

and cancer cells. It's crazy. So

1:30:11

if you look at the news

1:30:13

article, which will also attach, they

1:30:16

have this very nice figure. You

1:30:18

can see a cancer cell and

1:30:20

a T cell. And the cancer

1:30:22

cell has, via these tunneling nanotubules

1:30:24

between the cells, connects it as

1:30:27

if like a little tube is

1:30:29

being connected to the T cell

1:30:31

and the cancer cell, siphons off

1:30:33

the mitochondria from the T cell

1:30:36

and then uses its mitochondria and

1:30:38

then gives the T cell, this

1:30:40

cancer mitochondria, so mutated, let's say,

1:30:42

mitochondria, that's also marked with USP30,

1:30:45

so that it will prevent degradation

1:30:47

inside of the T cell. Thus

1:30:49

causing the T cell to become

1:30:51

senescent and ineffective in killing tumor

1:30:54

cells. So that's like a lay

1:30:56

summary. This is crazy. So I

1:30:58

know these things happen, but when

1:31:00

you read them like that, literally

1:31:03

the tumor cell makes a tunnel

1:31:05

between itself and a T cell,

1:31:07

gives it really bad mitochondria that

1:31:09

it can't degrade that makes the

1:31:12

T cell not be able to

1:31:14

kill the cancer cells. And this

1:31:16

happens in this study that they

1:31:18

did in 15% of the T

1:31:21

cells. 15% of the details is

1:31:23

a lot, especially in the tumor

1:31:25

micro environment. That means that 15%

1:31:27

of them can now not kill

1:31:30

the cancer cells. So I thought

1:31:32

that this paper and like this

1:31:34

news article was just really interesting

1:31:36

because of this bidirectional exchange of

1:31:38

mitochondria and the implications. So it's

1:31:41

just scary like it's horrifying. Horrifying.

1:31:43

And this is, I mean, these

1:31:45

are cells in the body that

1:31:47

must have the tools to do

1:31:50

this for some evolutionary reason that

1:31:52

is not this. unclear exactly right

1:31:54

so this is a whole other

1:31:56

dimension of cell cell interaction that

1:31:59

we didn't know existed This could,

1:32:01