Making maps of gene activity easier to compare
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 3-Nov-2026 04:16 ET (3-Nov-2026 09:16 GMT/UTC)
KANAZAWA, Japan — Spatial transcriptomics can reveal where thousands of genes are active across a tissue, creating molecular maps at single-cell resolution. But comparing two such maps is difficult: thin slices of tissue may be rotated, stretched, or otherwise distorted, so equivalent regions do not automatically line up.
Researchers at Kanazawa University and Sapienza University of Rome have developed a computational method that aligns these maps directly from the individual measurement locations and their gene-activity values. Called Domain Elastic Transform (DET), it smoothly reshapes one digital map to match another without first converting the measurements into a regular grid of pixels.
The research, led by Osamu Hirose of Kanazawa University in collaboration with Emanuele Rodolà of Sapienza University of Rome, was published online in IEEE Transactions on Pattern Analysis and Machine Intelligence on September 15, 2026.
Satellite data could help governments decide where to build the data centres behind the growth of AI, by showing where renewable power, water and land are available and where drought and climate risks are highest, according to researchers at the University of Surrey.
The Southern California Environmental Health Sciences Center (SCEHSC) has received an $8 million grant from the National Institutes of Health (NIH) to advance research on the health effects of environmental exposures. SCEHSC, which is based at the Keck School of Medicine of USC and has been continuously funded by NIH for more than 30 years. The center has supported research on air pollution that has been highly influential in development of regulatory standards, on extreme heat and wildfires, per- and polyfluoroalkyl substances (PFAS) and on environmental effects on cardiorespiratory health, neurodevelopment and cognitive aging, kidney, liver and metabolic disease, and diabetes. The new grant ensures the center can continue backing these and other efforts through pilot funding, service cores providing expertise in exposure assessment, study design, biostatistics and data science, community engagement, research translation and science communication, and additional resources. Central to SCEHSC’s impact is its pilot program, which provides funding and support to help investigators turn promising ideas into established research programs. The program has generated a 30-to-1 return on its investments, with pilot funding helping researchers attract additional support, primarily from NIH. The new NIH funding will also allow SCEHSC to expand its work in two new areas in environmental health: artificial intelligence (AI) and cancer. SCEHSC is also expanding its work on environmental exposures linked to cancer in children and adults, in collaboration with the USC Norris Comprehensive Cancer Center.
Researchers in Szeged have developed MALVINA, a machine learning-based method that shows, cell by cell, how bacteria invade human cells, cause DNA damage, and change their behaviour in the presence of other bacteria or drugs. The method could help identify high-risk bacterial strains and support the development of therapies that not only kill pathogens, but also make them less harmful.