A team of heart researchers at Cleveland Clinic in Ohio has received expressions of concern for two papers in the Journal of Biological Chemistry, which says the images in the articles appear suspect.
The papers, both of which appeared in 2004, come from the lab of Subha Sen, a highly-funded scientist who has received millions in NIH grants over the past decade. Sen’s work also has drawn scrutiny on PubPeer, with comments cropping up on the site roughly three years ago for many of her papers.
As Retraction Watch readers know, reporting on the same data more than once — without notifying editors and readers — is bad for the scientific record and can lead to a retraction. Apparently, in the rush to publish findings about the coronavirus pandemic, some researchers are doing just that.
According to an editorial in JAMA today by editor in chief Howard Bauchner and two deputy editors, Robert Golub and Jody Zylke:
Last year, JAMA Ophthalmology published a study that claimed to find a link between using cholesterol-lowering drugs known as statins and a reduced risk of glaucoma. In a New York Times story on the paper, lead author
Jae H. Kang, an assistant professor of medicine at Brigham and Women’s Hospital in Boston, suggested that statins reduce pressure in the eye, help maintain good blood flow and may help protect the optic nerve.
But Kang came to realize, while reviewing the results for another study, that her research had a major error, as she writes in a letter accompanying the retraction and replacement of the study. Kang tells Retraction Watch:
On the surface, it would seem like a good thing when science undergirds policy decisions. But what if that science is deeply flawed? Craig Pittman, an award-winning journalist at the Tampa Bay Times and author of 4 books, writes that his new book Cat Tale: The Wild, Weird Battle to Save the Florida Panther is “a tale of raw courage, of scientific skulduggery and political shenanigans, of big-money interests versus what’s right for everyone.” In this excerpt, Pittman explains what happened — and what didn’t — after a group of scientists known as the Science Review Team (SRT) found serious problems in research used to support regulatory policies involving panthers.
In 2003, the SRT released a report containing its verdict. As you might guess, it ripped apart Maehr’s work, piece by piece, and yes, they called him out by name. They didn’t label him a fraud, but they made it clear that Dr. Panther had done some pretty shady things.
Because they were scientists, they didn’t scream out their findings in impassioned prose. They were cool and calm—but there was no mistaking what they were saying.
An Elsevier journal has denied the efforts of a group of researchers — well, most of them, anyway — to reverse a retraction after having agreed to the move in the first place.
The dispute centers on a 2018 paper in Preventive Medicine Reports titled “Association between low-testosterone and kidney stones in US men: The national health and nutrition examination survey 2011–2012” — which, as the title implies, found that:
Why is it so difficult to correct the scientific record in sports science? In the first installment in this series of guest posts, Matthew Tenan, a data scientist with a PhD in neuroscience, began the story of how he and some colleagues came to scrutinize a paper. In the second, he explained what happened next. In today’s final installment, he reflects on the editors’ response and what he thinks it means for his field.
In refusing to retract the Dankel and Loenneke manuscript we showed to be mathematically flawed, the editors referred to “feedback from someone with greater expertise” and included the following:
Why is it so difficult to correct the scientific record in sports science? In the first installment in this series of guest posts, Matthew Tenan, a data scientist with a PhD in neuroscience, began the story of how he and some colleagues came to scrutinize a paper. In this post, he explains what happened next.
Two years ago, following heated debate, a sports science journal banned a statistical method from its pages, and a different journal — which had published a defense of that method earlier — decided to boost its statistical chops. But as Matthew Tenan, a data scientist with a PhD in neuroscience relates in this three-part series, that doesn’t seem to have made it any easier to correct the scientific record. Here’s part one.
As it happened, I knew that paper, and I had also expressed concerns about it – when I reviewed it before publication as one of the members of the journal’s editorial board. Indeed, I was brought on to the editorial board of Sports Medicine because the journal had recently received a lot of bad press for publishing a paper about another “novel statistical method” with significant issues and I had been a vocal critic of the sports medicine and sport science field developing their own statistical methods that are not used outside of the field and validated by the wider statistics community.
