A research team led by Haruyo Yamamoto, Chisa Nakashima, and Atsushi Otsuka from Department of Dermatology, Kindai University Faculty of Medicine, in collaboration with the Faculty of Engineering at Kindai University and other institutions, has developed a diagnostic system that uses artificial intelligence (AI) to accurately identify the type of facial pigmented lesions and support laser treatment decisions. A paper on this study was published online in Cureus, an international medical journal on June 5, 2025.

Michael Karin, PhD, has long been fascinated by what happens when inflammation—ideally a short-term burst of biological activity to promote healing or fight infection—turns chronic and potentially deadly.

CSHL Professor David Spector and graduate student Wenbo Xu have discovered that the long non-coding RNA LINC01235 helps promote the formation of triple-negative breast cancer. Their findings offer potential inroads to new and much-needed therapies for this deadly disease.

Researchers are pioneering a new approach to treating glioblastoma by targeting the gene MBLAC1 for the first time. This gene regulates copper levels and influences mitochondrial function—both essential to cancer cell survival. Disrupting MBLAC1 could impair tumor growth and open a new path for therapy. The study breaks new ground by revealing a molecular pathway that drives cancer through a gene tied to copper regulation and glioblastoma risk. Glioblastoma is a highly aggressive brain cancer with one of the highest mortality rates.

AI models have the potential not only to spot pancreatic cancer at an early stage, but also to predict the deadly disease’s prognosis, say scientists