Scientists at the University of Connecticut have developed a handheld ‘pocket microscope’ that directly visualizes DNA and proteins in living cells without stains or labels. The system uses deep-ultraviolet light to map molecules with femtogram sensitivity, achieving 308-nanometer resolution across centimeter-wide areas. The device enables instant pathology diagnosis, identifies cancer cells, and maps brain neurons -- all while preserving samples’ natural state. This technology could transform medical diagnostics, from operating rooms to space missions.

New research from Australia highlights the need for artificial intelligence (AI) systems to complement –  not impede – worker safety and welfare in workplaces. 

While Australia has taken commendable first steps towards responsible governance of AI, its current regulatory apparatus lacks the legally binding and workplace-specific and mechanisms necessary to mitigate emerging risks, according to Future of Work expert Associate Professor Andreas Cebulla, from Flinders University.

A team led by Guoyin Yin at Wuhan University and the Shanghai Artificial Intelligence Laboratory recently proposed a modular machine learning framework using LoRA fine-tuning. This framework can not only accurately predict single organic reactions but also achieve the prediction of "one model handling multiple types of reactions." Even using only natural language to describe chemical reactions, the prediction accuracy is comparable to machine learning models based on expert experience. The article was published as an open access Research Article in CCS Chemistry, the flagship journal of the Chinese Chemical Society.