Metabolism-inspired hydrogels are redefining how soft materials function. Researchers have designed copolymer networks that enable hydrogels to mimic biological processes, such as self-oscillation and light-to-chemical energy conversion. By integrating multiple components step by step, these systems move beyond simple responses to achieve coordinated, life-like behavior. This approach marks a shift toward advanced bio-inspired systems, where polymer networks actively drive energy conversion and function, opening new possibilities for smart materials and sustainable technologies.

An Osaka Metropolitan University-led research group investigated the association between infertility and loss of the X chromosome (LOX) in women.

Language education plays a key role in helping foreign residents settle into society. However, Japan heavily relies on volunteers for it. New research conducted at Doshisha University investigates how volunteer-led Japanese classes function within national policies and local realities. Using policy analysis and on-field research, the study reveals that this reliance results in a “semi-professional” teaching environment that not only influences learning outcomes but may also limit the potential of volunteers and foreign residents.

Schizophrenia is a serious brain disorder that causes confused thinking, severe memory problems, and hallucinations. It affects about 23 million people worldwide, with cognitive dysfunction present in over 80% of patients. A research group led by scientists from Nagoya University in Japan tested a drug used to treat an immune disease to see if it could reduce schizophrenia-related symptoms in mice. The findings, published in Molecular Psychiatry, show that KD025 restored connections between neurons and significantly improved memory and visual recognition in mice, without causing the serious side effects common to current schizophrenia medications. 

Researchers from The University of Osaka found that the zinc finger proteins RLF and ZFP292 play redundant roles in stabilizing the CoREST corepressor complex at gene promoters in embryonic stem cells. Deleting both proteins allowed the cells to differentiate, suggesting that they could be useful targets for maintaining stem cell quality.

Lung cancer diagnosis relies heavily on interpreting complex computed tomography (CT) images, where accuracy can vary depending on physician’s experience. A new study introduces an artificial intelligence model that generates detailed, question-driven findings from chest CT scans instead of simple classifications. By combining structured medical data with visual question answering model, the approach enables interactive and interpretable diagnostic support. This method could improve consistency in reporting, assist clinical decision-making, and enhance training for medical professionals.