Rising sea levels along coastlines not only threaten populations, but also pose a danger to agricultural crops, which may be damaged by surging amounts of saltwater. Researchers have, in response, sought to improve salt-tolerance in plants. An international team of scientists now reports the identification of cell traits that are critical to tolerating saltwater inundation—a finding that potentially offers new pathways for creating plants that can survive in harsh environments.

Researchers at Thomas Jefferson University have developed a groundbreaking automated machine learning (AutoML) model that can accurately differentiate between two common types of brain tumors using preoperative MRI scans, potentially improving surgical planning and patient outcomes.

The study, published in the December 2025 issue of Otolaryngology–Head and Neck Surgery, represents the first application of AutoML technology specifically trained to classify pituitary macroadenomas and parasellar meningiomas—two benign but challenging-to-distinguish brain tumors that require different treatment approaches.

A new study from the University of Maryland’s Jerin Tasnim, reveals that Virginia's current approach to managing septic system failures misses a critical factor: the time-varying relationship between hydrological stressors and septic system performance. This gap limits the state's ability to proactively identify and intervene in high-risk areas before failures occur—and before nitrogen pollution reaches the Chesapeake Bay. This study will be presented on December 8 at 10:30 A.M. ET at the Society for Risk Analysis Annual Meeting in Washington D.C.