A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence (AI) could significantly improve how doctors determine the best treatment for cancer patients—by enhancing how tumor samples are analyzed in the lab. The findings, published in the July 9 online edition of Nature Medicine, showed that AI can accurately predict genetic mutations from routine pathology slides—potentially reducing the need for rapid genetic testing in certain cases.

A new study, led by experts at the University of Nottingham, provides the strongest evidence to date that cancer is extremely rare in turtles, a finding that could offer valuable clues for preventing or fighting cancer in humans.

While previous research had hinted that cancer might be uncommon in turtles, the new analysis, published in BioScience, shows that only about 1% of individuals are affected, far less than in mammals or birds. The study was led by Dr Ylenia Chiari from the School of Life Sciences at the University of Nottingham, alongside Dr Scott Glaberman from the University of Birmingham, in collaboration with a team of researchers from zoos across the US, UK, and Europe.

The team analysed medical records and necropsies (autopsies) from hundreds of zoo turtles, including individuals from Chester Zoo in the UK.

Keck Medicine of USC is participating in a national, multisite clinical trial examining if a genetically engineered herpes simplex virus, when combined with immunotherapy, reduces or eliminates melanoma tumors.

A new, low-cost biosensing technology that could make rapid at-home tests up to 100 times more sensitive to viruses like COVID-19. The diagnostic could expand rapid screening to other life-threatening conditions like prostate cancer and sepsis, as well. Created by researchers at the University of California, Berkeley, the test combines a natural evaporation process called the “coffee-ring effect” with plasmonics and AI to detect biomarkers of disease with remarkable precision in just minutes.