A quick, purification-free method was developed by researchers at Institute of Science Tokyo, to capture the detailed 3D structures of flexible sugar molecules. By growing crystals of galectin-10 protein using a cell-free crystallization process and soaking them in sugar solution, the researchers were able to trap and analyze the molecular arrangement of sugars and their interactions with the protein. This offers a powerful tool to accelerate research in drug discovery and molecular biology.

Researchers at Osaka Metropolitan University uncovered early hepatic changes associated with type 2 diabetes by analyzing primary hepatocytes from prediabetic Otsuka Long-Evans Tokushima Fatty rats.

A research group at The University of Tokyo has discovered a new principle by which helical chiral molecules acquire spin through molecular vibrations, enabling them to adhere to magnets. Until now, it was believed that chiral molecules could only exhibit magnetic properties when an electric current was applied. This discovery overturns that conventional understanding.

Heart failure (HF) has long been blamed on weakened heart muscle cells, but new research shows that support cells called fibroblasts may be a key factor. Researchers found that fibroblasts send harmful signals through the MYC–CXCL1–CXCR2 pathway, interfering with heart function. Blocking this pathway in mice improved their cardiac performance, with similar changes observed in human heart tissue. These findings highlight a new potential target for treating severe HF.

A new study from Ritsumeikan University found that a 12-day online gratitude journaling exercise significantly boosted work engagement among Japanese employees. Participants who daily noted things they were grateful for became more aware of colleague support, supervisor feedback, and opportunities to take initiative: reflecting greater recognition of job resources. These findings suggest that intentionally cultivating gratitude provides individuals and organizations with a low-cost, effective approach for enhancing workplace engagement through greater awareness of available resources.

Crystal structure prediction (CSP) of organic molecules is a critical task, especially in pharmaceuticals and materials science. However, conventional methods are computationally intensive and time-consuming. Now, researchers from Japan have developed a new workflow: SPaDe-CSP that accelerates CSP by machine learning-based prediction of most probable space groups and crystal densities and employing an efficient neural network potential for structure refinement. It achieved faster and more reliable CSP than conventional methods.