0:00:01.230,0:00:03.055
One, because it's going to ruin our day,[br]alright?

0:00:03.055,0:00:09.780
So, uh, if you know anything special[br]about this paper, don't tell anybody.

0:00:09.780,0:00:13.385
What I really want you guys to do[br]is to not use the internet.

0:00:13.385,0:00:17.982
We're going to take a close look at this[br]paper, see what you guys think about it.

0:00:17.982,0:00:20.545
We're going to read it, I'm going to give[br]you about 20 minutes

0:00:20.545,0:00:23.253
to read this paper and discuss it.[br]Maybe half an hour.

0:00:23.253,0:00:24.717
Talk to your friends if you want to.

0:00:24.717,0:00:28.121
The idea is going to be to get through it[br]as fast as you can, and let's talk about

0:00:28.121,0:00:30.979
if we like this paper or not, alright?

0:00:30.979,0:00:33.433
Cool.

0:00:33.433,0:00:38.413
(crosstalk)

0:00:38.413,0:00:41.477
>> Put them up here.[br]>> Mia apparently doesn't staple papers

0:00:41.477,0:00:43.347
that she reads, so they're not stapled.

0:00:43.347,0:00:46.522
So it's just complete mayhem.

0:00:48.484,0:00:52.192
>> At least I got the job done.[br]>> No, not really.

0:00:53.015,0:01:13.725
(crosstalk)

0:01:37.136,0:01:39.976
>> Did anybody not get one?

0:01:41.230,0:01:44.838
(crosstalk)

0:01:49.838,0:01:51.501
>> Alright. I'll be back.

0:01:53.590,0:02:07.868
(crosstalk)

0:29:33.784,0:29:37.822
>> Alright, so, maybe read for about[br]five more minutes, and then maybe

0:29:37.822,0:29:40.800
discuss this for about five or[br]ten minutes.

0:29:45.026,0:29:49.792
So read for five more minutes,[br]then we'll discuss

0:29:49.842,0:29:53.418
for five or ten minutes, and then I'll[br]lead the discussion on the paper.

0:29:53.418,0:29:56.671
The discussion is really going to[br]center around what do you find convincing?

0:29:56.671,0:29:59.327
What do you like and dislike? Same kind of[br]discussions we've had, but sort of

0:29:59.327,0:30:03.775
a short version, just to kind of see if[br]maybe people will notice things

0:30:03.775,0:30:05.733
that other people didn't notice.

0:30:05.733,0:30:09.217
Does anyone know about this paper?[br]Anyone know what I'm talking about here?

0:30:09.217,0:30:12.244
Has anyone read this paper before?

0:30:12.244,0:30:14.212
Alright, good, we're all[br]on the same page.

0:30:14.212,0:30:17.534
Alright, read for a few more minutes, and[br]then when you're ready, start discussing

0:30:17.534,0:30:21.294
with whoever your neighbors - or[br]whoever you want to talk to about it.

0:30:21.294,0:30:23.451
Talk about this paper for[br]ten or fifteen minutes.

0:30:25.224,0:30:28.654
See what you think about it, see if you[br]can come up with a consensus.

0:37:36.675,0:37:59.618
(crosstalk)

0:44:50.319,0:44:58.191
>> Alright, okay, so uh, what do you[br]guys think of this paper?

0:44:58.191,0:45:00.943
>> Cool.[br]>> Yeah, super cool, huh?

0:45:00.943,0:45:04.203
Like really really good.[br]Yeah, I think you guys got it.

0:45:04.203,0:45:05.725
Yeah, and what do you think?

0:45:05.725,0:45:07.800
>> We have a theory[br]that it's all made up.

0:45:07.800,0:45:10.013
>> Ahh.[br](class laughing)

0:45:10.013,0:45:13.000
Anyone else think it's all made up?[br]>> I was convinced.

0:45:13.000,0:45:16.975
>> Based purely on the fact that you[br]told us that there was a retraction.

0:45:16.975,0:45:21.398
>> You can't find it, can you?[br]>> You also gave us the author manuscript,

0:45:21.398,0:45:23.363
so, yeah.[br]>> Yeah, yeah, no, no.

0:45:23.363,0:45:26.097
So, go do some Googling right now,[br]everybody pull up your laptop or your

0:45:26.097,0:45:29.564
phone and see what you think here,[br]because this is a really interesting

0:45:29.564,0:45:32.694
lesson in how to do this, right?

0:45:32.694,0:45:38.255
Yeah, yeah, yeah, no. But go see[br]what you can find about this paper.

0:45:38.255,0:45:41.079
It's a useful exercise.

0:45:41.079,0:45:46.085
A couple of minutes of your own[br]research by phone or laptop,

0:45:46.085,0:45:48.094
and then we'll have[br]a little more conversation.

0:45:50.439,0:46:06.354
(crosstalk)

0:48:27.216,0:48:30.474
>> All right. That's pretty amazing,[br]huh?

0:48:31.864,0:48:36.535
Okay, so not just the paper in "Cell,"[br]but also the paper in PNAS, right?

0:48:36.535,0:48:41.006
So two different papers had to be[br]completely retracted.

0:48:41.006,0:48:46.000
The retraction notice here in "Cell"[br]is good reading.

0:48:46.000,0:48:53.887
Let's see - where's the retraction[br]notice? Here's the retraction notice.

0:48:53.887,0:49:01.661
So, here we are.

0:49:01.661,0:49:04.027
Study reported the former family[br]blah, blah, blah.

0:49:04.027,0:49:06.885
Shortly after publication, a lab[br]with whom we had shared reagents

0:49:06.885,0:49:09.572
noticed that cell lines that were[br]supposed to be stably expressing

0:49:09.572,0:49:13.099
GFE-4 were not, we subsequently[br]found a western blot of the paper

0:49:13.099,0:49:14.127
had been inappropriately manipulated.

0:49:14.127,0:49:16.545
And that multiple cell lines were not[br]as reported.

0:49:17.641,0:49:20.160
When we constructed and validated[br]new cell lines and reagents,

0:49:20.160,0:49:23.963
our attempts to produce critical data[br]in the paper were unsuccessful.

0:49:23.963,0:49:30.925
This led to basically office -ORI,[br]is the Office of Research Integrity,

0:49:30.925,0:49:35.167
at the NIH, did a study, and[br]actually found that there were

0:49:35.167,0:49:38.595
fabrications in figures[br]two, three, five, six, seven,

0:49:38.595,0:49:41.860
and the majority of the supplement.[br]Alright?

0:49:41.860,0:49:50.748
Now, what's even more stunning -[br]what? Yeah, I'm getting there.

0:49:50.748,0:49:54.283
(crosstalk)[br]>> From the NIH? This is ridiculous.

0:49:54.283,0:49:56.341
>> Yeah, well, so, okay, right.

0:49:56.341,0:49:59.443
So an interesting thing to do[br]in these cases when you see retractions

0:49:59.443,0:50:04.103
is to read the ORI report, uh,[br]and the ORI report goes on for

0:50:04.103,0:50:09.218
pages and pages and pages of[br]all the things that were altered,

0:50:09.218,0:50:12.931
but the real meat of it is here.

0:50:14.033,0:50:17.010
This is for the "Cell" paper.

0:50:17.010,0:50:21.636
Results which did not originate from[br]experimental observations,

0:50:21.636,0:50:25.067
which did not originate from experimental[br]observation using selected regions

0:50:25.067,0:50:29.855
of the same original to represent the[br]control and the rescue.

0:50:29.855,0:50:34.696
Lying about whether they were 2.5[br]or 3.5 microliter channels,

0:50:34.696,0:50:36.921
not originating from experimental.

0:50:36.921,0:50:40.266
And then, what's particularly crazy[br]about this, is that there's a lot of

0:50:40.266,0:50:44.245
falsification data here, but almost[br]every single figure in here has the

0:50:44.245,0:50:46.582
end numbers exaggerated.

0:50:46.582,0:50:49.689
The error bar is mislabeled, etc.,[br]etc., right?

0:50:51.038,0:50:53.772
And so this is a relevant thing to[br]think about.

0:50:53.772,0:50:58.340
So this was a very talented scientist.[br]I saw her talk at

0:50:58.340,0:51:01.845
a Gordon research conference and[br]immediately asked her to apply to UT.

0:51:01.845,0:51:08.423
I said "You should apply for a faculty job[br]at UT," completely sold on the story.

0:51:09.393,0:51:12.308
So was UT Southwestern, who actually[br]offered her a job

0:51:12.308,0:51:13.832
as an assistant professor.

0:51:14.172,0:51:18.104
So was the Cancer Prevention and[br]Research Institute of Texas,

0:51:18.104,0:51:21.091
which offered her a two million dollar[br]recruitment grant.

0:51:22.361,0:51:26.174
All of which was of course rescinded[br]when this was discovered.

0:51:26.944,0:51:32.779
Turns out she had fabricated all the data[br]in a second paper in PNAS as well.

0:51:34.409,0:51:39.004
And so I think it's worth considering[br]these things and sort of paying attention

0:51:39.004,0:51:40.956
to what happens here, right?

0:51:40.956,0:51:44.840
So Claire Waterman, the senior author[br]on these papers is a very famous

0:51:44.840,0:51:48.121
cell biologist, who's been in the[br]business for 25 years,

0:51:48.121,0:51:49.479
at least as long as I have.

0:51:50.731,0:51:54.704
And is very well regarded, very[br]respected by all of her colleagues,

0:51:55.854,0:51:58.970
Obviously this puts her in[br]quite a bind, right?

0:52:00.640,0:52:02.009
And it's worth thinking about.

0:52:02.009,0:52:04.494
We've had faculty in this department[br]where this has happened, right?

0:52:04.494,0:52:08.603
This appears to be a case where[br]a very intelligent young scientist

0:52:08.603,0:52:12.782
somehow felt something about the[br]pressure of the job, needed to

0:52:12.782,0:52:15.942
make up all the data in two entire papers.

0:52:19.392,0:52:21.365
Then so one of the questions you ask is,

0:52:21.365,0:52:24.216
that you get asked a lot from[br]non-scientists is

0:52:24.216,0:52:27.404
"Well, why doesn't peer review find it?"

0:52:27.874,0:52:30.128
Right? How does this get through[br]peer review?

0:52:30.388,0:52:32.582
Did anyone see anything wrong[br]with this paper? If I had just given

0:52:32.582,0:52:35.598
you this paper, you'd have read[br]it and you'd have loved it, right?

0:52:36.047,0:52:40.058
Because if you're a smart person,[br]and you're a dedicated fraud,

0:52:40.588,0:52:42.574
it's very hard to get caught, right?

0:52:42.574,0:52:45.807
If you just make up numbers and put[br]them on a graph, and it looks good,

0:52:46.437,0:52:49.172
very hard to see that in peer review.[br]Right?

0:52:49.729,0:52:53.053
If you pick the part of the image that[br]shows what you want to show...

0:52:54.663,0:52:57.088
it's very easy to get away[br]with this actually.

0:52:59.675,0:53:02.557
>> The only thing I was suspicious about[br]in the whole paper was that

0:53:02.557,0:53:07.412
it all came together so perfectly,[br]and that's just like not how it should

0:53:07.412,0:53:08.550
ever happen with cancer cells.

0:53:08.550,0:53:10.493
>> Yeah, but it does sometimes, right?

0:53:10.493,0:53:13.931
Yeah, right, it does, and when you sit[br]there and you watch the data,

0:53:13.931,0:53:16.409
and it's from a good lab-- right?

0:53:17.079,0:53:20.597
It's very hard to say,[br]"Ah, it's too perfect."

0:53:20.597,0:53:23.803
You know, you wouldn't have said[br]"Oh, clearly you've made all of this up."

0:53:23.803,0:53:26.184
Right? Yeah, yeah, yeah. Right?

0:53:26.184,0:53:29.520
>> I don't - I was only suspicious[br]because I had thought already

0:53:29.520,0:53:31.029
that that's what happened with[br]this paper.

0:53:31.029,0:53:32.653
>> Yeah, yeah, yeah. No.

0:53:33.513,0:53:36.443
It's hard to do the exercise[br]any other way.

0:53:36.860,0:53:38.466
August had a question and[br]then Jifa.

0:53:38.466,0:53:42.496
>> No, just because we were quite -

0:53:42.496,0:53:47.755
you know, they made a little bit[br]far-fetched of a claim, but

0:53:47.755,0:53:52.538
at the same time we can see that,[br]yeah, the phenotype's right.

0:53:52.538,0:53:55.219
So I think...[br]>> Yeah, Jifa?

0:53:55.850,0:54:01.141
>> So, were the other scientists[br]here in on it, or was this like -

0:54:01.141,0:54:02.090
did she orchestrate it?

0:54:02.090,0:54:05.853
>> No, the Office of Research Integrity[br]puts it all on the one person.

0:54:06.563,0:54:09.281
Basically just a dedicated fraud[br]all the way through.

0:54:10.941,0:54:14.526
And again, it wouldn't be that[br]hard to do, right?

0:54:14.526,0:54:18.391
So probably the other authors[br]involved are the authors who

0:54:18.391,0:54:21.794
generated other reagents,[br]also possible that many of them

0:54:21.794,0:54:26.734
just generated reagents and gave[br]them to this person, to do work on,

0:54:26.734,0:54:29.662
and then she did experiments on[br]them and made up the results.

0:54:29.662,0:54:32.861
But actually in the entire[br]investigation, only one person

0:54:32.861,0:54:34.854
was found to be the root of all of this.

0:54:36.674,0:54:37.524
And so...

0:54:37.524,0:54:39.164
>> (inaudible).

0:54:39.164,0:54:39.914
>> Huh?

0:54:39.914,0:54:41.546
>> I said, it sucks for the other[br]authors of the paper.

0:54:41.546,0:54:43.237
>> Oh, it sucks for everybody,[br]absolutely.

0:54:43.947,0:54:51.823
>> I'm sorry, I just want to know,[br]how about the (inaudible)

0:54:52.249,0:54:54.465
>> I think we don't know. I think[br]someone will have to go back

0:54:54.465,0:54:56.109
and redo all those experiments, right?

0:54:56.109,0:55:03.818
So these are the findings of what[br]people said, but even those findings

0:55:03.818,0:55:10.183
in the first few figures, clearly the[br]numbers are inflated, right?

0:55:12.055,0:55:15.042
And so I think someone will have[br]to go back and start over.

0:55:15.395,0:55:20.525
>> I didn't read the summary at[br]the beginning because (inaudible),

0:55:20.525,0:55:25.955
so I just read the introduction, but I[br]feel like the titles are very attractive,

0:55:25.955,0:55:33.114
and then I read-- briefly go the the[br]introduction and read each figure.

0:55:34.010,0:55:40.080
I think they're basically true then you[br]gave us a little time so I went back

0:55:40.080,0:55:42.630
to read the summary.[br]>> Yup.

0:55:42.635,0:55:48.078
>> And I felt like some of the summaries[br]they were giving for the whole picture

0:55:48.078,0:55:53.710
of this paper, I felt like how could[br]it be so perfect, you know in

0:55:54.830,0:55:58.066
animal models, and the (inaudible)

0:55:58.066,0:56:00.243
>> Yeah, but every once in a while[br]you get lucky, right?

0:56:00.243,0:56:02.246
And so that's the thing with fraud, right?

0:56:02.246,0:56:07.419
If it's really consistent and you[br]stick to your guns, it's really hard

0:56:07.419,0:56:09.877
to catch. Now, the funny thing is

0:56:11.359,0:56:15.265
that surely she must have thought[br]someone would try to repeat -

0:56:15.265,0:56:18.358
I mean it's a cell paper. She was[br]on the job market, she gave

0:56:18.358,0:56:21.638
talks all over the country.[br]She must have known that

0:56:21.638,0:56:24.409
somebody was going to do[br]these experiments.

0:56:25.349,0:56:27.324
And so I just don't know.[br]August?

0:56:27.324,0:56:31.409
>> I'm pretty sure that Skau's[br]reputation is completely shattered,

0:56:31.409,0:56:34.415
but how is the reputation of[br]Clare Waterman?

0:56:34.415,0:56:38.176
>> I mean that's always a danger, right?[br]And time will tell, right?

0:56:38.176,0:56:41.189
It's the only time she's ever[br]been associated with it.

0:56:41.189,0:56:45.812
The independent investigation[br]found that it was all this one person.

0:56:46.712,0:56:48.662
So, time will tell.

0:56:49.965,0:56:51.941
But right now I would say[br]it's still very good.

0:56:51.941,0:56:53.416
>> Oh, okay.[br]>>Right? Yeah.

0:56:54.883,0:56:59.705
>> This makes me wonder like, what[br]is so terribly wrong with the system

0:56:59.705,0:57:01.658
that somebody (inaudible)

0:57:01.658,0:57:06.615
>> Sure. Right? I mean I think[br]that's one of the big questions,

0:57:06.615,0:57:09.272
and what's kind of related to[br]that that I think is a really

0:57:09.272,0:57:11.321
subtle point - I'll get to[br]your questions in a minute,

0:57:11.321,0:57:13.718
but I do want to make this point,[br]because it comes straight to this.

0:57:13.718,0:57:14.564
Right?

0:57:16.284,0:57:22.759
It's very easy to start believing[br]your own bullshit. Right?

0:57:23.859,0:57:31.051
And there's a big difference between[br]really making up entire papers

0:57:31.051,0:57:36.813
and not being honest with yourself,[br]but they all are part of the

0:57:36.823,0:57:40.158
same spectrum, and something you[br]have to guard against is

0:57:40.838,0:57:42.725
"Am I really doing this the right way?"

0:57:42.725,0:57:44.794
"Am I really seeing what[br]I think I'm seeing?"

0:57:44.794,0:57:46.443
"Am I really being completely honest?"

0:57:46.443,0:57:51.523
Because especially once you get halfway[br]into a paper, halfway into your PhD,

0:57:53.173,0:57:56.923
it gets, you know, there's[br]a lot of pressure.

0:57:58.063,0:58:01.440
And it's something you have to[br]fight against, right?

0:58:01.440,0:58:04.125
Especially when a project's[br]going south, right?

0:58:04.485,0:58:07.167
You've invested a lot in it,[br]and everything's starting to

0:58:07.167,0:58:10.816
fall apart, and so you've[br]got to be vigilant.

0:58:10.816,0:58:14.236
And again, I'm not saying that[br]you're likely to decide to just

0:58:14.236,0:58:17.003
make up all the data in the[br]last three figures of your paper.

0:58:18.073,0:58:21.245
But the system is stressful.

0:58:21.581,0:58:23.317
It's a very competitive system.

0:58:24.536,0:58:26.361
It's a very competitive world.

0:58:26.860,0:58:29.765
Is fraud any worse now than it used to be,

0:58:29.765,0:58:32.193
or can we just detect it better, right?

0:58:32.513,0:58:35.692
I don't actually know. My guess is that[br]we can detect it a lot better, right?

0:58:35.692,0:58:37.481
There's a lot better tools for it.

0:58:37.481,0:58:40.130
But there's also a lot more money[br]in science than there ever was before

0:58:40.130,0:58:44.305
at all levels, even in academia,[br]which puts a big incentive in

0:58:45.415,0:58:48.563
for people to be unethical.

0:58:49.517,0:58:52.804
But I mean these are serious concerns,[br]I think there's things that as

0:58:52.804,0:58:56.810
graduate students, you guys should[br]be thinking about and considering.

0:58:56.810,0:58:59.726
There were some hands up.[br]I can't remember who they all were.

0:59:00.389,0:59:01.283
Will?

0:59:01.996,0:59:04.907
>> I was just going to say that it's[br]crazy that it seems like the

0:59:04.907,0:59:07.260
way that she started to get caught[br]was that she sent

0:59:07.260,0:59:11.272
stably-transfected cell line, and it[br]wasn't actually stably-transfected.

0:59:11.272,0:59:13.202
>> Yup.[br]>> It seems so basic.

0:59:14.507,0:59:17.505
>> Yeah, I mean but once you're there,[br]right, they ask for the line,

0:59:17.505,0:59:18.347
what are you going to do?

0:59:18.880,0:59:22.764
>> That's also easy to hand away,[br]to be like "Oh, it might have..."

0:59:22.764,0:59:27.001
You know, you build these lines[br]and they fall apart, so I mean...

0:59:27.461,0:59:31.744
and if you're this confident in[br]falsifying data that ends up

0:59:31.744,0:59:35.999
in the "Cell" paper, you're probably[br]willing to think that you can

0:59:35.999,0:59:38.595
argue your way out of[br]something like that, right?

0:59:39.670,0:59:43.950
Do you see what I'm saying,[br]like the mental-- yeah, yeah.

0:59:44.322,0:59:48.898
>> Well but also at this level, you know[br]it's slid over into pathology, right?

0:59:48.898,0:59:54.138
I mean literally every single thing[br]in this paper has something

0:59:54.138,0:59:55.196
fraudulent about it.

0:59:56.110,0:59:58.881
Right, which is really evidence to me[br]that someone has gone

0:59:58.881,1:00:03.704
way past "Oh crap, I've got to just[br]save this one paper" into

1:00:03.704,1:00:04.724
"I'm invincible".

1:00:06.358,1:00:07.325
Right?[br]>> Yeah.

1:00:07.325,1:00:09.788
>> Yeah yeah yeah, I mean[br]I don't know, but yeah.

1:00:10.104,1:00:13.298
>> Yeah, so apart from the reputation[br]and embarrassment, what is the

1:00:13.298,1:00:15.794
punishment for such (inaudible)?

1:00:15.794,1:00:21.091
>> Right, so the punishment for her[br]is-- I mean, the punishment

1:00:21.091,1:00:23.975
is her entire scientific career[br]is completely ruined.

1:00:23.975,1:00:25.766
She'll never work in the[br]field again, right?

1:00:25.766,1:00:28.020
>> What about the taxpayer's money?[br]>> Right, right, right.

1:00:28.020,1:00:31.038
Taxpayer's money, there's nothing--[br]I mean, nothing done.

1:00:31.768,1:00:35.130
They have these voluntary settlements[br]here that you can read about it.

1:00:36.240,1:00:42.124
And these things are really built[br]around the assumption of

1:00:42.124,1:00:43.944
small amounts of fraud, you know?

1:00:44.178,1:00:49.670
You made a mistake, you're a savable[br]person as a scientist, then they

1:00:49.670,1:00:52.099
put a supervisory plan in place[br]where someone's really

1:00:52.099,1:00:55.050
looking a lot more carefully at your work,[br]and then for three years,

1:00:55.050,1:00:57.786
you're not allowed to work for the NIH[br]and these kinds of things.

1:00:58.436,1:01:01.294
But at this level, her reputation[br]is just destroyed, so there's--

1:01:01.294,1:01:03.505
we won't see her anywhere[br]in academic science again.

1:01:03.505,1:01:07.816
In terms of monetary, these kinds of[br]things, I don't know of any,

1:01:07.816,1:01:10.488
and there's much more-- there was[br]a big "New York Times" piece

1:01:10.488,1:01:14.588
about a cancer biologist at[br]Penn State who's apparently

1:01:14.588,1:01:19.248
been under investigation for fraud[br]like every other year for ten years,

1:01:19.248,1:01:22.545
and he still has millions of dollars[br]of research money and it just sort of

1:01:22.545,1:01:24.514
never comes home to roost, so.

1:01:25.074,1:01:27.770
You guys should educate yourself[br]about the fraud situation,

1:01:28.770,1:01:29.836
and what's there.

1:01:30.110,1:01:31.812
Did someone else have a hand up?

1:01:32.280,1:01:33.590
>> Can I same something quick?[br]>> Yeah.

1:01:33.590,1:01:37.906
>> I saw in the news, UT Southwestern[br]removed a million dollar grant from her.

1:01:37.906,1:01:40.300
>> Yeah yeah, that's the grant.[br]Yeah-- oh yeah, she--

1:01:41.127,1:01:44.330
the job was rescinded, the grant[br]was rescinded, so she's not

1:01:44.330,1:01:46.400
getting the grant, she didn't[br]get the job, she will absolutely

1:01:46.400,1:01:47.760
have to leave science.

1:01:48.316,1:01:50.911
As I understand it, she's like a[br]program officer at a foundation now

1:01:50.911,1:01:52.233
or something. Yeah.

1:01:52.233,1:01:55.716
>> But not just the monetary loss,[br]what about killing so many mice

1:01:55.716,1:01:59.570
and falsifying data? (inaudible).[br](laughter)

1:02:00.663,1:02:04.400
>> If you go down the road that[br]killing life is a problem,

1:02:04.400,1:02:05.989
then you're going to have[br]a real problem.

1:02:06.245,1:02:08.226
>> If you're doing science, doing[br]something productive,

1:02:08.226,1:02:10.554
it makes sense but if[br]you're falsifying data.

1:02:10.554,1:02:11.506
>> Yeah.

1:02:13.236,1:02:15.247
>> I was--[br]>> Hang on, you had a hand up.

1:02:15.766,1:02:18.982
>> How often-- obviously this one[br]seems like it was very intentional,

1:02:18.982,1:02:21.327
and so that's really-- but how[br]often do people get

1:02:21.327,1:02:23.493
caught up in this just because[br]they weren't careful enough

1:02:23.493,1:02:27.295
and they didn't force themselves[br]to be very thorough?

1:02:27.446,1:02:31.546
>> I mean mistakes get made in papers[br]all the time, right, and some papers

1:02:31.546,1:02:36.025
get retracted because we went back[br]and resequenced the mouse allele,

1:02:36.025,1:02:39.020
and it wasn't what we thought[br]it was, right?

1:02:39.424,1:02:42.183
But generally what happens is there's[br]a correction. Generally when that happens,

1:02:42.183,1:02:45.105
it's not like the entire paper's ruined,[br]"Oh, surprise, we mutated

1:02:45.105,1:02:46.859
totally the wrong gene".

1:02:46.859,1:02:50.570
Usually it's like "Oh we thought it was[br]exon 3, but in a frameshift,

1:02:50.570,1:02:53.362
but in fact it was something else."[br]Right?

1:02:53.367,1:02:54.093
>> Right.

1:02:54.093,1:02:59.272
>> And so you get a lot of corrections[br]in papers, and some retractions,

1:02:59.272,1:03:02.960
but generally, you know, you've[br]got to-- the whole paper

1:03:02.960,1:03:05.949
really has to be systematically[br]wrong to retract the entire paper.

1:03:05.949,1:03:09.135
>> So it's the dishonesty that[br]gets prosecuted.

1:03:09.135,1:03:13.287
>> Yeah, or I mean, it-- yeah, so the[br]dishonestly immediately you want to

1:03:13.287,1:03:16.015
retract the paper, because that's[br]also what the PI is going to

1:03:16.015,1:03:17.143
want to do.[br]>> Right.

1:03:17.143,1:03:21.286
>> Right? But if you just get it wrong,[br]you know, you get it wrong,

1:03:21.286,1:03:22.171
we're human, right?

1:03:22.171,1:03:25.959
If there was no-- and there have been[br]investigations where they find

1:03:25.959,1:03:29.247
"Oh, no, they weren't unethical,[br]they were just dumb."

1:03:29.247,1:03:29.867
(laughter)

1:03:29.867,1:03:31.776
No, seriously, right? And that can[br]happen, right?

1:03:31.776,1:03:34.379
And that's not a crime.

1:03:35.471,1:03:36.588
So, yeah.

1:03:37.454,1:03:40.570
>> Who does these investigations?[br]Is there like a secret service

1:03:40.570,1:03:42.074
for scientists, like--[br]>> Yeah.

1:03:42.074,1:03:44.461
The Office of Research Integrity[br]at the NIH, right?

1:03:44.461,1:03:45.274
>> At the NIH?

1:03:45.274,1:03:49.086
>> Yup, and then all universities will[br]have an office for research integrity,

1:03:49.086,1:03:52.956
so I'm sure that-- so if it happens at UT,[br]there's a UT office that will investigate,

1:03:52.956,1:03:56.364
but the NIH will also investigate[br]if it's NIH-funded research.

1:03:57.439,1:03:59.200
Yeah, so several differnet bodies.

1:03:59.200,1:04:00.775
And there's a...

1:04:01.845,1:04:02.993
Yeah.

1:04:04.578,1:04:06.925
>> Has anyone here read[br]the book "Bad Blood?"

1:04:07.475,1:04:08.527
>> "Bad Blood" what is that?

1:04:08.539,1:04:11.457
>> It's about the Theranos controversy[br]and (inaudible).

1:04:11.457,1:04:14.483
>> Oh, wow. No, is it good?[br]>> It's amazing.

1:04:14.483,1:04:16.275
>> Really? "Bad Blood."[br]>> Everyone should read it.

1:04:16.275,1:04:17.516
>> Okay.[br]>> It's really good.

1:04:17.516,1:04:19.478
>> The documentary on[br]HBO's pretty good.

1:04:20.138,1:04:21.534
>> Same title? Okay.

1:04:22.051,1:04:23.359
>> I think so.[br]>> Okay.

1:04:23.519,1:04:25.908
>> So lots of these[br]kinds of things existing.

1:04:26.271,1:04:27.009
>> Yeah (laughs).

1:04:27.009,1:04:28.357
>> Just like the...

1:04:29.731,1:04:33.264
I don't know how to[br]say that vitamin C is

1:04:33.264,1:04:37.675
for everything, and so now,[br]the (inaudible) for everything

1:04:37.675,1:04:39.903
and the (inaudible) can do everything,

1:04:39.903,1:04:41.799
and they just make money from that.

1:04:41.799,1:04:42.541
(laughter)

1:04:42.571,1:04:44.710
>> As long as they don't kill anyone,

1:04:44.710,1:04:47.855
they just sell the ideas[br]to the (inaudible).

1:04:48.027,1:04:50.641
>> Yeah, I mean that's the entire[br]supplement industry, right?

1:04:53.411,1:04:55.947
All right. Any other questions?

1:04:56.324,1:04:57.785
Thoughts, comments?

1:04:58.101,1:05:00.731
>> When is the next assignment due?

1:05:02.411,1:05:05.232
>> Next assignment is due[br]a week from Wednesday.

1:05:07.802,1:05:10.186
No, so nine days from now.

1:05:10.186,1:05:11.186
>> Nine days?

1:05:11.186,1:05:12.109
>> Nine days.

1:05:12.689,1:05:15.009
Whatever the date is here,[br]actually I have a calendar

1:05:15.009,1:05:17.587
in front of me.[br]>> It is the 6th so the 15th.

1:05:18.317,1:05:20.572
>> The 15th.[br]>> Ooh, I'm good at simple math.

1:05:20.934,1:05:24.088
>> It is as my calendar says,[br]'cause I have an 11 year old

1:05:24.088,1:05:26.633
girl at home, and "Riverdale"[br]season three starts.

1:05:26.633,1:05:27.693
(laughter)

1:05:27.694,1:05:29.843
But also your assignment is due,[br]so get it done before River--

1:05:29.843,1:05:31.161
>> "Riverdale" season three[br]already happened.

1:05:31.172,1:05:33.953
>> What?[br](laughter)

1:05:33.953,1:05:36.496
Oh, no, no, it comes out[br]free on Netflix. Yeah.

1:05:36.496,1:05:38.059
(laughter)

1:05:39.383,1:05:40.638
>> Judge me all you want.

1:05:40.638,1:05:42.358
>> I have a shared--[br]>> I know all of you

1:05:42.358,1:05:44.091
watch "Game of Thrones,"[br]and I don't, so.

1:05:44.091,1:05:46.145
>> No, no I don't either.

1:05:46.145,1:05:47.065
(crosstalk)

1:05:47.065,1:05:47.789
>> Jifa?

1:05:47.789,1:05:49.220
>> What's going on Wednesday?

1:05:49.506,1:05:51.996
>> Haven't decided yet. It's going to[br]be so much fun, though.

1:05:51.996,1:05:53.510
(laughter)

1:05:55.848,1:05:58.250
All right, cool. We're done.

1:05:58.250,1:06:00.633
(crosstalk)

1:06:07.721,1:06:11.911
>> I mean I sent in my paper[br]just last Friday afternoon.

1:06:11.911,1:06:13.891
>> Okay.[br]>> Was that too late, 'cause I--

1:06:13.891,1:06:16.260
>> It was too late, 'cause we[br]told you again and again and again--

1:06:16.260,1:06:19.233
>> Oh my--[br]>> All right, so anyway

1:06:19.233,1:06:20.990
>> Sorry about that.[br]>> Did you get your paper in today?

1:06:20.990,1:06:22.493
>> Yes. Yes, yes.[br]>> Okay. Great.

1:06:22.493,1:06:25.034
We will survive it.[br]>> Thank you, thank you.

1:06:25.034,1:06:26.676
>> All right.

1:06:26.676,1:06:28.372
(crosstalk continues)

1:06:28.372,1:06:29.617
>> Oh sorry, I wasn't (inaudible).

1:06:31.540,1:06:36.411
And on Wednesday-- I mean, this is[br]not about the class,

1:06:36.411,1:06:40.402
it's slightly about the class,[br]because (inaudible)--

1:06:40.402,1:06:43.107
invitation, having lunch--[br]>> With Roy Parker?

1:06:43.107,1:06:44.888
Yeah, you leave early[br]and go to that.

1:06:44.888,1:06:48.252
>> No no, not for that, but on[br]Wednesday afternoon,

1:06:48.252,1:06:51.650
I'm flying to (inaudible) to walk[br]in the commencement.

1:06:51.650,1:06:54.282
>> Oh okay. So you'll[br]miss this talk?

1:06:54.282,1:06:58.290
>> Yeah, I'll miss this talk likely,[br]and I'll be away for two weeks

1:06:58.290,1:07:00.526
because my parents are coming.[br]>> No problem.

1:07:00.526,1:07:03.683
So send your paper in before that.[br]>> So I was going to submit it

1:07:03.683,1:07:05.179
on Wednesday.[br]>> Great, no problem.

1:07:05.588,1:07:08.046
Okay, cool, good, it works.[br]>> Thank you.

1:07:08.046,1:07:08.683
>> You bet.

1:07:08.683,1:07:09.377
>> Mina?[br]>> Yeah?

1:07:09.377,1:07:12.399
>> So are you going to be in[br]your office right now, or?

1:07:12.399,1:07:15.057
>> Yeah yeah, I'll be here all day[br]doing experiments,

1:07:15.057,1:07:17.133
so if I'm not there, just leave it[br]on my desk.

1:07:17.133,1:07:17.838
>> Okay.

1:07:17.838,1:07:20.554
(crosstalk)