Researchers at the Indian Institute of Technology Gandhinagar (IITGN) have developed an adaptive charging strategy for lithium-ion batteries that could help Electric Vehicles (EVs) charge efficiently while reducing a major cause of battery degradation known as lithium plating. Published in the peer-reviewed Journal of Energy Storage, the study introduces a self-adjusting charging framework that dynamically protects batteries from internal degradation while optimising charging efficiency and time across varying temperature and health conditions.

Scientists at La Jolla Institute for Immunology (LJI) have discovered how T cells target paramyxoviruses, a viral family that includes measles virus and Nipah virus.

The Allen Institute, together with partner organizations, today launched the Brain Health accelerator (Brain Health): an ambitious global research initiative seeking to identify the specific brain cells and circuits affected in neurodegenerative disease and other brain disorders and use that knowledge to accelerate the development of new treatments.  

A new study from researchers at MUSC Hollings Cancer Center found that machine learning may help identify cancer patients at high risk of experiencing financial toxicity — the financial hardship and stress that often accompany cancer treatment. Using data from 793 patients, researchers tested six machine learning models and developed a web-based tool that can estimate a patient's likelihood of financial strain based on factors such as age, income, health status, treatment status and out-of-pocket costs. The best-performing model identified high-risk patients with 84% sensitivity and 75% specificity, offering a potential way for health care teams to intervene earlier with financial counseling and support services. The goal is to move financial toxicity screening from a reactive process to a proactive one, helping patients access resources before financial strain affects treatment decisions, quality of life or health outcomes.