Another GlamourMag Data Faker is Busted by ORI

Apr 07 2015 Published by under Scientific Misconduct

In the Federal Register:

Ryousuke Fujita, Ph.D., Columbia University: Based on the report of an investigation conducted by Columbia University (CU) and additional analysis conducted by ORI in its oversight review, ORI found that Dr. Ryousuke Fujita, former Postdoctoral Scientist, Taub Institute for the Aging Brain, Departments of Pathology and Cell Biology and Neurology, CU Medical Center, engaged in research misconduct in research supported by National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), grant R01 NS064433 and National Institute of Aging (NIA), NIH, grant R01 AG042317.

ORI found that Respondent engaged in research misconduct by falsifying and fabricating data for specific protein expressions in human-induced neuronal (hiN) cells derived skin fibroblasts of Alzheimer's disease patients and unaffected individuals in seventy-four (74) panels included in figures in the following two (2) publications and one (1) unpublished manuscript:

Wow. 74 panels faked in a mere three papers? One wonders how many valid panels could possibly be left.

So what are the papers?

Nature. 2013 Aug 1;500(7460):45-50. doi: 10.1038/nature12415. Epub 2013 Jul 24.
Integrative genomics identifies APOE ε4 effectors in Alzheimer's disease.
Rhinn H, Fujita R, Qiang L, Cheng R, Lee JH, Abeliovich A. [PubMed]

Nature eh? Glamour number one. And I note that this busy bee faker is listed-second with a co-equal symbol. No evidence on the publisher site that this has been retracted that I can see.

Cell. 2011 Aug 5;146(3):359-71. doi: 10.1016/j.cell.2011.07.007.
Directed conversion of Alzheimer's disease patient skin fibroblasts into functional neurons.
Qiang L, Fujita R, Yamashita T, Angulo S, Rhinn H, Rhee D, Doege C, Chau L, Aubry L, Vanti WB, Moreno H, Abeliovich A. [PubMed]

Cell. Glamour two. In this case the retraction notices are all over the place. Once again, the faker is listed-second with a co-equal contributor symbol.

Fujita had a very impressive number of cheating techniques that were deployed. This seems slightly unusual...my memory suggests cheaters often focus on one or two strategies*.

Respondent inflated sample numbers and data, fabricated numbers for data sets, manipulated enzyme-linked immunosorbent assay (ELISA) analysis, mislabelled immunoflourescent confocal images, and manipulated and reused Western blot images.

h/t: Comradde PhysioProffe
__
*I could be wrong about this.

20 responses so far

  • MorganPhD says:

    The only way to make this behavior stop is to take a PI out with the cheating "trainee". Make an example of someone.

    As you said, 74 panels across 3 publications is an extraordinary amount of cheating, beyond the level that one might still contend the PI is blameless.

    This behavior is rewarded in both the job hunt and in the funding race. I have no doubt that some of those panels from the 2011 Cell or 2013 Nature paper ended up in an R01 application that was funded.

    But now the cheater is burned, but the PI gets to claim ignorance while reaping the benefits of the cheating in a few new R01's with fake data.

    It's like if I robbed a bank, gave the money to my wife, got arrested, and the government let my wife keep the Porsche she bought with my ill-gotten gains.

    I am, in no way, claiming that the PI of this group is an active participant in this crap and I am going to be clear that I don't know this particular situation. But let's be frank, we need to hold PI's more accountable for the data they put out in the world, or else this keeps happening.

  • drugmonkey says:

    Plausible deniability is a right bastige.

  • I'm sure that subsequent publications from other groups confirmed the main conclusions, so no harm, no foul.

  • Dave says:

    Yeh, conclusions are correct so no fucks given.

    As misconduct is clearly getting worse, or rather the detection is improving thanks to sites like Pubpeer, my main concern right now is how this affects funding. It's a lot easier to fudge figures and data in a grant application, which are hidden from the prying eyes of the winterweb.

  • MorganPhD says:

    So it's okay to make up data if your heart was in the right place?

  • DJMH says:

    Really good scientists don't need data, just intuition.

  • Dave says:

    Don't need no stinking data.

  • AcademicLurker says:

    Data is for the riff raff.

  • Masked Avenger says:

    When the NIH writes funding announcements asking for the impossible, they will damned well get the impossible, one way or another.

  • jmz4gtu says:

    So this is a field my lab works on, and, while I agree it's of broader significance that the paper was out there misleading the field and scamming funding, I personally know a poor grad student who tried to replicate that a$$hat's ELISA findings for almost 3 months, to no avail. That, more than anything else, I think, is what personally keeps me from putting data I'm not 100% about out there. The thought that some poor sap might end up wasting a part of her life trying to duplicate it. It's the one consequence of data fakery that can't be rationalized around.

    Sidenote: I wonder if this improves or diminishes her shot at getting her own paper on the same topic published (they're going to Cell). On the one hand, they actually do what these people claimed to. On the other hand, Cell's probably going to be extra vigilant about these things.

  • UCProf says:

    They should handle it the way they did in Iowa.
    http://www.desmoinesregister.com/story/news/crime-and-courts/2015/01/16/dong-pyou-han-iowa-state-university-aids-vaccine-fraud/21873849/

    Indict and prosecute for fraud. Make the university pay NIH back the money that was fraudulently obtained.

  • neuropop says:

    There were other papers from that lab that didn't pass muster.....

  • Juan Lopez says:

    UCprof, I really hope that what you say doesn't happen. The day a university has to send money out for this, they will implement the most ridiculous checks, double checks, forms, signatures and triple check system know to humanity, paid for by increasing indirects, of course. It will cut cheating and fraud, but it will take a huge toll on research as well.

    I much rather have the fraudster sunk without dragging everyone with them.

  • dsks says:

    The PI at least has some responsibility to ensure that, wherever possible, particularly compelling data is reproduced within the lab by more than one individual. Sure, that could be tricky if you have one postdoc with the skillz for a particular prep, but a lot of this fakery seems to involve fairly standard imaging and biochemistry techniques that probably should be bread and butter for anybody working in a given lab. During my postdoc, my PI and I would commonly cross-check our patch clamp data by repeating each others experiments. (I'd like to say it was because of our high moral standards, but not really; just a selfish desire not to publish something that's just plain wrong and end up looking like a bunch of fraudulent/incompetent monkeys to our colleagues).

    I think there has to be a question of due diligence with this sort of thing as far as the lab head is concerned. It's too convenient to throw staff under the bus and allow the PI to wring their hands and say, "Aw gee, I just had no idea..."

  • physioprof says:

    The PI at least has some responsibility to ensure that, wherever possible, particularly compelling data is reproduced within the lab by more than one individual.

    This is complete lunacy. What the PI has a responsibility to ensure is that she is creating an environment that (1) places a premium on rigor, honesty, and mutual- and self-criticism of data and (2) makes it clear that corners will not be cut and data "massaging" will not be tolerated and (3) makes it clear that primary data can be looked at by the PI and other lab members at any time (i.e.: no secrecy).

  • MorganPhD says:

    @dsks,
    here's a good (recently) example of your point about PI responsibility

    http://retractionwatch.com/2015/04/08/jci-retracts-stem-cell-paper-by-jacob-hanna-citing-figure-irregularities/

    The PI "blamed figure errors ... on the shoddy work of “medical trainees” who botched the job"

    @physioprof,
    So once you "make it clear", you're absolved of all responsibility? I bet you don't take credit by putting your name at the end of the paper either.

  • drugmonkey says:

    The PI at least has some responsibility to ensure that, wherever possible, particularly compelling data is reproduced within the lab by more than one individual.

    "whenever possible" is a nice weasel but you are being ridiculous. have another person run the 5-6 groups of 8-16 animals in behavioral studies that last months? right.

  • MorganPhD says:

    @drugmonkey and @physioprof,
    I don't think dsks suggested that every experiment needs to be independently validated by a second person in the lab or elsewhere. Rather, that common sense should prevail in the face of new and intriguing data.

    No one would expect you to rerun a 3 month mouse experiment, but perhaps you should have a second blinded observer for that behavior. It doesn't cost YOU (as a PI) anything to send grad student X down with postdoc Y to measure behavior the first time.

    In my experience, PI's only ask for independent replication when the data are negative or go against their preconceived notions. Person X can't show that Protein A and Protein B interact by IP, so I'll make Person Y try because Person X is stupid and doesn't have the "hands".

    It's always Person Y just showed something new and interesting, obviously they're right and I don't need to check because hooray for me, this paper can go to Cell now.

  • jmz4gtu says:

    "What the PI has a responsibility to ensure is that she is creating an environment that (1) places a premium on rigor, honesty, and mutual- and self-criticism of data and (2) makes it clear that corners will not be cut and data "massaging" will not be tolerated and (3) makes it clear that primary data can be looked at by the PI and other lab members at any time (i.e.: no secrecy)."
    -A good example of this is a lab I know of where all data that leads to a figure is put in a file on the lab server that anyone can access. It does two things, it makes people label their important data consistently and 2, makes data fakery highly unlikely.

  • mH says:

    "A good example of this is a lab I know of where all data that leads to a figure is put in a file on the lab server that anyone can access. "

    That's good, but "anyone" better include the PI 100% of the time. I wouldn't be able to sleep at night if I hadn't looked at (i.e. obsessed over) the data files underlying manuscript figures. It's your fucking job. I'm not saying a PI can't be fooled by a really motivated faker... but the stupidity and negligence of letting the kind of obvious shit that is uncovered by people glancing through the figures warrants consequences. And 7 times out of 10 on RW it is obvious the PI either never looked at a damn thing, which is barely better than being complicit.

Leave a Reply