A new review was published in Volume 18 of Aging on September 19, 2026, titled “mTOR signaling in aging: from causality to geroprotective interventions and hallmark-level outcomes.”

Consumers are increasingly confronted with conflicting information surrounding how much protein they should have and which protein sources are healthiest, most sustainable, and best value for money. Cambridge research has uncovered the truth.

The mechanisms that cause the world’s most common chronic liver disease — Metabolic dysfunction-associated steatotic liver disease (MASLD) — to develop and progress are not still fully understood. Now, a study by the University of Barcelona has identified a new factor involved in the development of the disease: the protein ENT1, which allows the transport of small molecules essential for the functioning of liver cells into the cell. The results of the study, carried out with patients and animal models, open the door to exploring future therapies.

The International Society for Stem Cell Research (ISSCR) today opens its international symposium celebrating the 20th anniversary of induced pluripotent stem (iPS) cell technology, bringing together scientists, clinicians, and innovators from around the world to reflect on two decades of transformative discoveries and explore the future of stem cell research and regenerative medicine.

The three-day symposium, held Oct. 20–22 in Kyoto, Japan, is organized in partnership with the Center for iPS Cell Research and Application (CiRA) and co-sponsored by the Japanese Society for Regenerative Medicine (JSRM).

The extraordinary response to the symposium underscores the strength and momentum of stem cell science worldwide. Registration reached capacity twice, even after the ISSCR expanded the meeting to a larger venue to accommodate growing demand. This remarkable level of interest reflects both the profound impact of iPSC technology over the past two decades and the expanding opportunities ahead, from fundamental discoveries in human biology to advances in disease modeling, drug discovery, clinical translation, and the development of stem cell-based therapies.

Healthy soils are key to securing Europe's food, water, climate and biodiversity. Yet more than 60% of soils in the EU remain unhealthy, and the scientific knowledge that could help reverse the trend rarely reaches the people who write policy.

In the beginning of October, 15 partners from 10 European countries met in Nancy, France for the kick-off of PSOILICY, a new EU-funded project that will build the interfaces, hubs and tools needed to turn soil knowledge into evidence-based decisions.

Public biomedical databases such as NHANES, UK Biobank, FAERS, the Global Burden of Disease Study, and FinnGen have become a focus of the research-integrity debate, following a rapid rise in papers built from broadly accessible datasets. A correspondence published in Medicine Discovery argues that the quality of public database research rests on the study process, while the database name provides little information about scientific quality, and that treating a familiar database name as a marker of low quality risks confusing the infrastructure with the production model that exploits it. Citing a scientometric analysis of 36 health datasets — nine of which showed publication patterns consistent with rapid, formulaic expansion, producing 23,005 indexed publications in 2025 and an estimated excess of 11,577 publications above the prior trend — the authors argue that the same NHANES files support careful epidemiology, surveillance, and methods development as well as formulaic work, and that the recent surge emerged long after the survey architecture and its public documentation were established. They describe how generative AI has changed the economics of secondary data research, distinguishing researcher-directed assistance from more autonomous workflows that extend into question formulation and analytical planning, and warning of a plausible risk of automated hypothesis fishing. The correspondence proposes three actions for editorial policy: a short dataset-specific methods note for heavily reused resources; stronger transparency around analysis code, preregistration, and AI use; and editorial screening focused on study conduct rather than data provenance.