The environment is already under immense strain from global warming, and the rise of armed conflicts is compounding the crisis. Wars accelerate ecological destruction and the Iran–US war is emerging as the latest conflict to inflict severe environmental damage.

Preclinical study findings have revealed how estrogen loss may affect the aging female brain and could help explain why women are at higher risk for Alzheimer’s disease.

A new solar-powered desalination system developed at the University of Rochester can produce fresh water from seawater without chemical additives or brine discharge. At the same time, the process recovers salts and valuable minerals that would otherwise remain a difficult waste stream.

A recently published longitudinal study conducted at the northernmost region of Finland shows how the biomass of moths, which are a vital food source to insectivorous birds, has changed over the past few decades.

With an aim to expand its global peptide API capacity, Cordenpharma has plans to take over Ambiopharm, a U.S.-headquartered peptide API CDMO. Ambiopharm currently has two sites, one in in

The ‘Cardiocare’ project is focusing on a vulnerable group of patients – women over 65 with breast cancer at risk of cardiotoxicity from cancer treatment. The project is currently celebrating a series of major achievements that bring its ambitious vision closer to reality: smarter, more personalized and more patient-centered care for this patient group.

Researchers have developed a nanoscale carbon material derived from the fruit waste that is capable of efficiently removing 4-nitrophenol (4-NP), a persistent industrial pollutant, from water.

Azenta Life Sciences’ unique Acoustic tube technology offers faster, more efficient sample management in next-generation compound management and screening workflows.

Siemens Healthineers offers a quantitative Covid-19 test to measure neutralizing antibodies. The company has also submitted an application to the FDA under Emergency Use Authorization.

A new verification protocol developed at Binghamton University could help reduce hallucinations in AI-generated biomedical information. By combining retrieval-augmented generation with majority voting among seven large language models, the workflow produced matched medical terminology without unmatched or fabricated terms in more than 10,000 experiments.