https:/.../5-6-19+Low+Q_pt3.mp4

And so this is a relevant thing to
think about.

So this was a very talented scientist.
I saw her talk at

a Gordon research conference and
immediately asked her to apply to UT.

I said "You should apply for a faculty job
at UT", completely sold on the story.

So was UT Southwestern, who actually
offered her a job

as an assistant professor.

So was the Cancer Prevention and
Research Institute of Texas,

which offered her a two million dollar
recruitment grant.

All of which was of course rescinded
when this was discovered.

Turns out she had fabricated all the data
in a second paper in PNAS as well.

And so I think it's worth considering
these things and sort of paying attention

to what happens here, right?

So Claire Waterman, the senior author
on these papers is a very famous

cell biologist, who's been in the
business for 25 years,

at least as long as I have.

And is very well regarded, very
respected by all of her colleagues,

Obviously this puts her in
quite a bind, right?

And it's worth thinking about.

We've had faculty in this department
where this has happened, right?

This appears to be a case where
a very intelligent young scientist

somehow felt something about the
pressure of the job, needed to

make up all the data in two entire papers.

Then so one of the questions you ask is,

that you get asked a lot from
non-scientists is

"Well, why doesn't peer review find it?"

Right? How does this get through
peer review?

Did anyone see anything wrong
with this paper? If I had just given

you this paper, you'd have read
it and you'd have loved it, right?

Because if you're a smart person,
and you're a dedicated fraud,

it's very hard to get caught, right?

If you just make up numbers and put
them on a graph, and it looks good,

very hard to see that in peer review.
Right?

If you pick the part of the image that
shows what you want to show...

it's very easy to get away
with this actually.

>> The only thing I was suspicious about
in the whole paper was that

it all came together so perfectly,
and that's just like not how it should

ever happen with cancer cells.

>> Yeah, but it does sometimes, right?

Yeah, right, it does, and when you sit
there and you watch the data,

and it's from a good lab-- right?

It's very hard to say,
"Ah, it's too perfect."

You know, you wouldn't have said
"Oh, clearly you've made all of this up."

Right? Yeah, yeah, yeah. Right?

>> I don't - I was only suspicious
because I had thought already

that that's what happened with
this paper.

>> Yeah, yeah, yeah. No.

It's hard to do the exercise
any other way.

August had a question and
then Jifa.

>> No, just because we were quite -

you know, they made a little bit
far-fetched of a claim, but

at the same time we can see that,
yeah, the phenotype's right.

So I think...
>> Yeah, Jifa?

>> So, were the other scientists
here in on it, or was this like -

did she orchestrate it?

>> No, the Office of Research Integrity
puts it all on the one person.

Basically just a dedicated fraud
all the way through.

And again, it wouldn't be that
hard to do, right?

So probably the other authors
involved are the authors who

generated other reagents,
also possible that many of them

just generated reagents and gave
them to this person, to do work on,

and then she did experiments on
them and made up the results.

But actually in the entire
investigation, only one person

was found to be the root of all of this.

And so...

>> (inaudible).

>> Huh?

>> I said, it sucks for the other
authors of the paper.

>> Oh, it sucks for everybody,
absolutely.

>> I'm sorry, I just want to know,
how about the (inaudible)

>> I think we don't know. I think
someone will have to go back

and redo all those experiments, right?

So these are the findings of what
people said, but even those findings

in the first few figures, clearly the
numbers are inflated, right?

And so I think someone will have
to go back and start over.

>> I didn't read the summary at
the beginning because (inaudible),

so I just read the introduction,
but I feel like the titles are very attractive,

and then I read-- briefly go the the
introduction and read each figure.

I think they're basically true then you
gave us a little time so I went back

to read the summary.
>> Yup.

>> And I felt like some of the summaries
they were giving for the whole picture

of this paper, I felt like how could
it be so perfect, you know in

animal models, and the (inaudible)

>> Yeah, but every once in a while
you get lucky, right?

And so that's the thing with fraud, right?

If it's really consistent and you
stick to your guns, it's really hard

to catch. Now, the funny thing is

that surely she must have thought
someone would try to repeat -

I mean it's a cell paper. She was
on the job market, she gave

talks all over the country.
She must have known that

somebody was going to do
these experiments.

And so I just don't know.
August?

>> I'm pretty sure that Skau's
reputation is completely shattered,

but how is the reputation of
Clare Waterman?

>> I mean that's always a danger, right?
And time will tell, right?

It's the only time she's ever
been associated with it.

The independent investigation
found that it was all this one person.

So, time will tell.

But right now I would say
it's still very good.

>> Oh, okay.
>>Right? Yeah.

>> This makes me wonder like, what
is so terribly wrong with the system

that somebody (inaudible)

>> Sure. Right? I mean I think
that's one of the big questions,

and what's kind of related
to that that I think's a really

subtle point - I'll get to
your questions in a minute,

but I do want to make this point,
because it comes straight to this.

Right?

It's very easy to start believing
your own bullshit. Right?

And there's a big difference between
really making up entire papers

and not being honest with yourself,
but they all are part of the

same spectrum, and something you
have to guard against is

"Am I really doing this the right way?"

"Am I really seeing what
I think I'm seeing?"

"Am I really being completely honest?"

Because especially once you get halfway
into a paper, halfway into your PhD,

it gets, you know, there's
a lot of pressure.

And it's something you have to
fight against, right?

Especially when a project's
going south, right?

You've invested a lot in it,
and everything's starting to

fall apart, and so you've
got to be vigilant.

And again, I'm not saying that
you're likely to decide to just

make up all the data in the
last three figures of your paper.

But the system is stressful.

It's a very competitive system.

It's a very competitive world.

Is fraud any worse now than it used to be,

or can we just detect it better, right?

I don't actually know. My guess is that
we can detect it a lot better, right?

There's a lot better tools for it.

But there's also a lot more money
in science than there ever was before

at all levels, even in academia,
which puts a big incentive in

for people to be unethical.

But I mean these are serious concerns,
I think there's things that as

graduate students, you guys should
be thinking about and considering.

There were some hands up.
I can't remember who they all were.

Will?

>> I was just going to say that it's
crazy that it seems like the

way that she started to get caught
was that she sent

stably-transfected cell line, and it
wasn't actually stably-transfected.

>> Yup.
>> It seems so basic.

>> Yeah, I mean but once you're there,
right, they ask for the line,

what are you going to do?

>> That's also easy to hand away,
to be like "Oh, it might have..."

You know, you build these lines
and they fall apart, so I mean...

and if you're this confident in
falsifying data that ends up

in the "Cell" paper, you're probably
willing to think that you can

argue your way out of
something like that, right?

Do you see what I'm saying,
like the mental-- yeah, yeah.

>> Well but also at this level, you know
it's slid over into pathology, right?

I mean literally every single thing
in this paper has something

fraudulent about it.

Right, which is really evidence to me
that someone has gone

way past "Oh crap, I've got to just
save this one paper" into

"I'm invincible".

Right?
>> Yeah.

>> Yeah yeah yeah, I mean
I don't know, but yeah.

>> Yeah, so apart from the reputation
and embarassment, what is the

punishment for such (inaudible)?

>> Right, so the punishment for her
is-- I mean, the punishment

is her entire scientific career
is completely ruined.

She'll never work in the
field again, right?

>> What about the taxpayer's money?
>> Right, right, right.

Taxpayer's money, there's nothing--
I mean, nothing done.

They have these voluntary settlements
here that you can read about it.

And these things are really built
around the assumption of

small amounts of fraud, you know?

You made a mistake, you're a savable
person as a scientist, then they

put a supervisory plan in place
where someone's really

looking a lot more carefully at your work,
and then for three years,

you're not allowed to work for the NIH
and these kinds of things.

But at this level, her reputation
is just destroyed, so there's--

we won't see her anywhere
in academic science again.

In terms of monetary, these kinds of
things, I don't know of any,

and there's much more-- there was
a big "New York Times" piece

about a cancer biologist at
Penn State who's apparently

been under investigation for fraud
like every other year for ten years,

and he still has millions of dollars
of research money and it just sort of

never comes home to roost, so.

You guys should educate yourself
about the fraud situation,

and what's there.

Did someone else have a hand up?

>> Can I same something quick?
>> Yeah.

>> I saw in the news, UT Southwestern
removed a million dollar grant from her.

>> Yeah yeah, that's the grant.
Yeah-- oh yeah, she--

the job was rescinded, the grant
was rescinded, so she's not

getting the grant, she didn't
get the job, she will absolutely

have to leave science.

As I understand it, she's like a
program officer at a foundation now

or something. Yeah.

>> But not just the monetary loss,
what about killing so many mice

and falsifying data? (inaudible).
(laughter)

>> If you go down the road that
killing life is a problem,

then you're going to have
a real problem.

>> If you're doing science, doing
something productive,

it makes sense but if
you're falsifying data.

>> Yeah.

>> I was--
>> Hang on, you had a hand up.

>> How often-- obviously this one
seems like it was very intentional,

and so that's really-- but how
often do people get

caught up in this just because
they weren't careful enough

and they didn't force themselves
to be very thorough?

>> I mean mistakes get made in papers
all the time, right, and some papers

get retracted because we went back
and resequenced the mouse allele,

and it wasn't what we thought
it was, right?

But generally what happens is there's
a correction. Generally when that happens,

it's not like the entire paper's ruined,
"Oh, surprise, we mutated

totally the wrong gene".

Usually it's like "Oh we thought it was
exon 3, but in a frameshift,

but in fact it was something else."
Right?

>> Right.

>> And so you get a lot of corrections
in papers, and some retractions,

but generally, you know, you've
got to-- the whole paper

really has to be systematically
wrong to retract the entire paper.

>> So it's the dishonesty that
gets prosecuted.

>> Yeah, or I mean, it-- yeah, so the
dishonestly immediately you want to

retract the paper, because that's
also what the PI is going to

want to do.
>> Right.

>> Right? But if you just get it wrong,
you know, you get it wrong,

we're human, right?

If there was no-- and there have been
investigations where they find

"Oh, no, they weren't unethical,
they were just dumb."

(laughter)

No, seriously, right? And that can
happen, right?

And that's not a crime.

So, yeah.

>> Who does these investigations?
Is there like a secret service

for scientists, like--
>> Yeah.

The Office of Research Integrity
at the NIH, right?

>> At the NIH?

>> Yup, and then all universities will
have an office for research integrity,

so I'm sure that-- so if it happens at UT,
there's a UT office that will investigate,

but the NIH will also investigate
if it's NIH-funded research.

Yeah, so several differnet bodies.

And there's a...

Yeah.

>> Has anyone here read
the book "Bad Blood?"

>> "Bad Blood" what is that?

>> It's about the Theranos controversy
and (inaudible).

>> Oh, wow. No, is it good?
>> It's amazing.

>> Really? "Bad Blood."
>> Everyone should read it.

>> Okay.
>> It's really good.

>> The documentary on
HBO's pretty good.

>> Same title? Okay.

>> I think so.
>> Okay.

>> So lots of these
kinds of things existing.

>> Yeah (laughs).

>> Just like the...

I don't know how to
say that vitamin C is

for everything, and so now,
the (inaudible) for everything

and the (inaudible) can do everything,

and they just make money from that.

(laughter)

>> As long as they don't kill anyone,

they just sell the ideas
to the (inaudible).

>> Yeah, I mean that's the entire
supplement industry, right?

All right. Any other questions?

Thoughts, comments?

>> When is the next assignment due?

>> Next assignment is due
a week from Wednesday.

No, so nine days from now.

>> Nine days?

>> Nine days.

Whatever the date is here,
actually I have a calendar

in front of me.
>> It is the 6th so the 15th.

>> The 15th.
>> Ooh, I'm good at simple math.

>> It is as my calendar says,
'cause I have an 11 year old

girl at home, and "Riverdale"
season three starts.

(laughter)

But also your assignment is due,
so get it done before River--

>> "Riverdale" season three
already happened.

>> What?
(laughter)

Oh, no, no, it comes out
free on Netflix. Yeah.

(laughter)

>> Judge me all you want.

>> I have a shared--
>> I know all of you

watch "Game of Thrones,"
and I don't, so.

>> No, no I don't either.

(crosstalk)

>> Jifa?

>> What's going on Wednesday?

>> Haven't decided yet. It's going to
be so much fun, though.

(laughter)

All right, cool. We're done.

(crosstalk)

>> I mean I sent in my paper
just last Friday afternoon.

>> Okay.
>> Was that too late, 'cause I--

>> It was too late, 'cause we
told you again and again and again--

>> Oh my--
>> All right, so anyway

>> Sorry about that.
>> Did you get your paper in today?

>> Yes. Yes, yes.
>> Okay. Great.

We will survive it.
>> Thank you, thank you.

>> All right.

(crosstalk continues)

>> Oh sorry, I wasn't (inaudible).

And on Wednesday-- I mean, this is
not about the class,

it's slightly about the class,
because (inaudible)--

invitation, having lunch--
>> With Roy Parker?

Yeah, you leave early
and go to that.

>> No no, not for that, but on
Wednesday afternoon,

I'm flying to (inaudible) to walk
in the commencement.

>> Oh okay. So you'll
miss this talk?

>> Yeah, I'll miss this talk likely,
and I'll be away for two weeks

because my parents are coming.
>> No problem.

So send your paper in before that.
>> So I was going to submit it

on Wednesday.
>> Great, no problem.

Okay, cool, good, it works.
>> Thank you.

>> You bet.

>> Mina?
>> Yeah?

>> So are you going to be in
your office right now, or?

>> Yeah yeah, I'll be here all day
doing experiments,

so if I'm not there, just leave it
on my desk.

>> Okay.

(crosstalk)