Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID affect large numbers of people, and constitute a substantial burden to the U.S. and global economies. The article by Eckey et al., in this issue of PNAS (1), adds to the growing evidence that the two illnesses have much in common. Moreover, the illnesses may represent just two examples of an even larger, recently recognized class of illness: post-acute infection syndromes (PAIS) (2).

cross-posted from: https://slrpnk.net/post/24826524

A report from French newspaper Le Monde paints a vivid portrait of the city’s evolving cycling culture, revealing a surge in two-wheeled activity that has captured the attention of cyclists and urban enthusiasts alike.

EDIT: This article is half a year old. Didn’t realise when posting sorry.

The appearance of thousands of formulaic biomedical studies has been linked to the rise of text-generating AI tools.

Data from five large open-access health databases are being used to generate thousands of poor-quality, formulaic papers, an analysis has found. Its authors say that the surge in publications could indicate the exploitation of these databases by people using large language models(LLMs) to mass-produce scholarly articles, or even by paper mills — companies that churn out papers to order.

Researchers have been sneaking secret messages into their papers in an effort to trick artificial intelligence (AI) tools into giving them a positive peer-review report.

The Tokyo-based news magazine Nikkei Asiareported last week on the practice, which had previously been discussed on social media. Nature has independently found 18 preprint studies containing such hidden messages, which are usually included as white text and sometimes in an extremely small font that would be invisible to a human but could be picked up as an instruction to an AI reviewer.