Parkinson’s researcher Caroline Barwood pleaded not guilty to fraud-related charges in a Brisbane courtroom Monday.
According to 9News, Barwood is accused of three counts of fraud, and four instances of attempted fraud, which include trying to obtain approximately $700,000 (AUD) from various organizations between 2011 and 2013 for a study that never occurred. The case follows an investigation at her former institution, the University of Queensland (UQ), which resulted in three of her papers being retracted.
Crown Prosecutor Caroline Marco alleged that Barwood was also intimately involved with Bruce Murdoch, her former colleague at the UQ, who has pleaded guilty to 17-fraud related charges, and received a two-year suspended sentence earlier this year.
Marco also claimed that Barwood admitted that “she took no part in the study, had not even met a single patient,” the court heard, and relied on a study Murdoch claimed to have conducted, but was in fact never carried out.
It was also claimed that Barwood — who was granted bail in November 2014 — tried to pass off another researcher’s work as her own when applying for grant, fellowship, and travel funding, 9News reported.
When we contacted Barwood for a comment last week, she told us she is unable to comment on the ongoing proceedings.
Both Barwood and Murdoch left the UQ in 2013. In addition to her three retractions, Barwood also has a “reader alert” to her name; all four of the notices list Murdoch as an author. After the UQ investigation into 92 academic papers, Murdoch also notched a fourth retraction for a paper that is not co-authored by Barwood.
On two occasions, Barwood allegedly also tried to get almost $300,000 from the National Health and Medical Research Council through applications for an early career fellowship, 9News reported, but neither of her applications succeeded.
A UQ spokesperson told us last week that the university will send Retraction Watch a statement once the case concludes.
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As a biomedical researcher and someone recently diagnosed with Parkinson’s disease, this hits very close to home. Shame on these fraudsters.
How would people know that she fabricated the research data . I see most people in Pubpeer focus on the western blot images . is images the only way to find out about false research . Can we also point out wrong theories or conclusions regardless of the figures .Thank you
It does not take any particular skill to analyse Western blot images. It’s something that amateurs can do. What is the percentage of false positives being flagged on PubPeer?
@RSD: If one identifies image manipulation it is an obvious error right there. Other kinds of research misconduct, as never even showing negative data (as in “not supporting the claims made in the paper”), not allowing full access to all data obtained or simply coming to an abstruse conclusion is hard to proof. For the first two cases you would need a whistleblower, for the latter (in my anecdotal experience) scientists can simply justify that your interpretation could also be true and one can discuss this later.
Can we also point out wrong theories or conclusions regardless of the figures .
If I worked in that area, I would be reluctant to waste time “pointing out wrong theories or conclusions” — that is, explaining why someone else’s theory is internally contradictory or in conflict with the data or built on false assumptions — if the studies behind the theory never occurred.
So agree with you. I guess we get so obsessed with Western blots and immunoflourescence images manipulations that we set them at a gold standard. Have seen many papers with perfect figures but biologically impossible conclusions and interpretation and no one just seems to be bothered about them.
There’s a substantial difference between these two things:
1) Doing legitimate research and misinterpreting the results to draw incorrect conclusions.
2) Committing fraud and presenting phony results from research you didn’t actually conduct.
Clearly #2 is far more damaging than #1.
I strongly disagree that analysis of Western blot images takes no skill. I will urge all amateurs to refrain from doing so. Commenting haphazardly on images will cause unnecessary trouble, including career-altering consequences (even your own if you are wrong about your claims concerning someone else’s paper). No one should believe this claim by Anonymous. A thorough understanding of how image processing software works, including artefacts that can be induced by image compression software often contained in image processing software, is important so as to avoid making false claims about perceived patterns in images presented in scientific articles.
Beyond Western blot images, a proper application of statistics and knowledge of distributional patterns in numbers can detect highly suspect data presentations such as seen here;
https://pubpeer.com/publications/8DED35619357EB2A06497EB8DB7E02
https://pubpeer.com/publications/502F4441565400F69D21D2CBA8B5B6
However, identifying numerical statistical anomalies is no guarantee that a paper will be cleaned up or handled appropriately. Here the authors just change all the p-values to “p < 0.01" and they and the journal editors call it a day.
https://pubpeer.com/publications/C3A446E4B4A0A161DE9AEA4322FF2B
Of course you can discuss whether you find the interpretation of the data to have been inappropriately done, and the wrong conclusion drawn, should you have a well reasoned alternative conclusion prepared. There are plenty of such discussions on PubPeer and elsewhere.
How can we avoid this ?