Tokyo, Japan – Researchers from Tokyo Metropolitan University have developed a suite of algorithms to automate the counting of sister chromatid exchanges (SCE) in chromosomes under the microscope. Conventional analysis requires trained personnel and time, with variability between different people. The team’s machine-learning-based algorithm boasts an accuracy of 84% and gives a more objective measurement. This could be a game changer for diagnosing disorders tied to abnormal numbers of SCEs, like Bloom syndrome.

A team of agricultural and environmental scientists has developed a simple biochar based technology that can strip self toxic chemicals from pepper growing soils and restore healthy seed germination. The work offers a promising new tool to help farmers overcome “continuous cropping obstacles” that have long plagued high value capsicum production.

Artificial intelligence is quietly transforming how scientists monitor and manage invisible biological pollutants in rivers, lakes, and coastal waters, and a new review explains how this technological shift could better protect ecosystems and public health.

Earthworms could become unexpected allies in the global fight against antibiotic resistance, by helping farmers turn manure into safer, high-value organic fertilizer through a process called vermicomposting. Researchers report that this low energy, nature-based technology can remove antibiotic resistance genes far more consistently than conventional composting, while also improving soil health and supporting sustainable agriculture.

Shaun Gleason, director of the Partnerships Office at the Department of Energy’s Oak Ridge National Laboratory, has been appointed to Tennessee’s Artificial Intelligence Advisory Council. Council members are appointed by the governor and provide a collaborative source of knowledge, expertise and information sharing to advance the state’s use of AI technologies.