In a new segment on this site, I will start handing out “This Image Is Fine” awards for papers containing images of concern, but where the Editors do not think there is a problem. This first installment of the “This Image Is Fine” award will go to the Journal of the American College of Cardiology (JACC) for deciding that images containing large amounts of duplicated elements are not worth investigating.
I have based the name of the award on the Gunshow “On Fire” comic by artist KC Green. Two frames from the comic show a dog quietly sitting in a room on fire, saying “This is fine”. For those of you who are not familiar with this meme, an article on The Verge explains and shows the full comic. Like me, you can support the artist on his Patreon page.
Here, I will use the “This Image Is Fine” award for journals where I think an image is not fine, but where the Editor in Chief decides to not investigate because of one of many reasons, such as:
- the paper is too old/gets too many citations/is of interest for so many
- the original data is lost in a hurricane/flood/Windows update/viral pandemic
- one of the authors is a genius/friend/the Editor in Chief themselves
- the image looks fine to them/why would anyone photoshop an image
- the results have been confirmed by several other studies
- the allegations were sent in by a person with a lower h-index than the senior author or Editor
As usual, this post is not an accusation of misconduct. There might be a perfectly good biological or technical artifact explanation for the duplications that I am seeing, although I could not think of one. The senior author also could not give a good explanation. But if you can explain these repetitive elements, please let me know in the Comments below.
The paper that has deserved the first “This Image Is Fine” award was published in the Journal of the American College of Cardiology (JACC) in 2010, by researchers from Mercer University in Savannah and Emory University Atlanta, GA (USA). I won’t share the details of the paper or researchers here, but I have posted the images about a month ago on PubPeer. Today, the editors let me know that they won’t investigate the paper because the lab has been closed since the publication, the original data is no longer available, and a different set of Editors are now running the journal.
Here are three images from the JACC paper that appear to show repetitive elements within or between panels. Each panel represents a tissue slice from a differently treated rat, so each of the squares should be unique.
The colored boxes have been been added by me. Boxes of the same color and shape highlight areas that look similar to each other.
One of the authors of the paper contacted me and wrote that they had received an email from JACC. They wrote that the editors “have decided to keep the paper published in its current form due to the length of time to validate the concerns.”.
Upon receiving that email from the authors, I wrote to the journal to ask if that was true. They wrote that they had indeed decided to not investigate but for a slightly different reason.
The Editors won’t investigate because “(t)here is simply no pathway to validate the claims that three of the figures had panels with duplicative data, without the original data.”
I obviously think these images are of concern, and for that JACC has won the “This Image Is Fine” award. Here you go:
What do you think? Let me know in the comments below.
Update April 14, 2020: The journal replied on Twitter this morning that my statement that the journal would not investigate is false. They also sent me another email this morning saying that the investigation is still open. This email was sent after I posted this blog post and after I posted my concerns on Twitter.
This is puzzling and definitely a very different statement than the email they sent me yesterday. But it is great to hear they changed their mind after I took this to social media. I will keep you all posted.
Update June 30 2020: The paper has received a Correction stating that Figures 5, 6, and 7 are now removed.