Flavanols are plant-derived compounds with an astringent taste, exhibiting pro- or antioxidant properties depending on the environment. Due to poor bioavailability, their health-promoting mechanism remains unclear. A new study identified their action via the brain-gut axis.  A single oral intake of flavanols stimulated brain regions involved in memory and sleep-wake regulation, and increased sympathetic nervous activity, a stress response. These findings may lead to future applications, such as the development of next-generation foods.

Low body weight in young women has been associated with various health concerns. Rising trends in the proportion of underweight women between the ages of 20 and 39 have been seen in Japan, raising concerns. In a first-of-its-kind study, Dr. Katsumi Iizuka and Dr. Hiroaki Masuyama from Japan have found that underweight Japanese women had a lower gut microbiota diversity and more inflammation-linked microbes. These findings suggest gut health is critical in weight control.

An Osaka Metropolitan University-led research team studied DNA interstrand crosslinks formation and its associated repair pathways to investigate whether colibactin-induced interstrand crosslinks play a crucial role in genotoxicity. 

As cities grow denser and hotter, creating space for greenery becomes increasingly difficult. To address this challenge, researchers from Chiba University developed a data-driven framework that integrates artificial intelligence and spatial analysis to map vertical greenery across Tokyo’s 23 wards. By analyzing over 80,000 street-view images, the team identified uneven distribution patterns and proposed a vertical greening demand index to guide future urban greening initiatives and climate-resilient urban planning.

Distribution-type membrane reactors are expected to be highly promising for carbon dioxide methanation reaction. In a recent breakthrough, a group of scientists from Shibaura Institute of Technology, Japan, has demonstrated the efficacy of these reactors and also examined the effect of membrane properties on reaction parameters. The present findings are a significant step towards a greener, cleaner, and more sustainable future.

Researchers at the RIKEN Center for Sustainable Resource Science (CSRS) in Japan have discovered that extended periods of high stress lead to iron deficiency and stunted growth in wheat crops. Experiments show reducing iron deficiency with a synthetic organic molecule called PDMA results in better growth and healthier plants. These findings are good news for farmers and consumers alike and could lead to treatments in the field that improve wheat production during prolonged periods of heat. The study was published in the scientific journal Nature Communications.

Researchers at University of Tsukuba have developed a technology for real-time estimation of the valence state and growth rate of iron oxide thin films during their formation. This novel technology was realized by analyzing the full-wavelength data of plasma emission spectra generated during reactive sputtering using machine learning. It is expected to enable high-precision control of the film deposition process.

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.

Pumpkins, squash, zucchini and their relatives accumulate soil pollutants in their edible parts. A Kobe University team has now identified the cause, making it possible to both make the produce safer and create plants that clean contaminated soil.

Researchers from SANKEN at The University of Osaka have successfully developed a groundbreaking “self-evolving” edge AI technology that enables real-time learning and forecasting capabilities directly within compact devices. This innovation, termed MicroAdapt, achieves unprecedented speed and accuracy. It processes data up to 100,000 times faster and achieves up to 60% higher accuracy compared to conventional state-of-the-art deep learning methods. This achievement represents a major advance toward next-generation real-time AI applications across manufacturing, automotive IoT, and medical wearables, addressing critical limitations of existing cloud-dependent AI.