Wheat plants can do more than grow grain. Research shows that their roots release natural compounds that slow down soil microbes and keep nitrogen in the soil potentially cutting losses, greenhouse gas emissions and costs for farmers.

A collaborative team from Tsinghua University, UCAS, and University of Macau has published a comprehensive review on electroactive materials for bioelectronics and regenerative medicine. The article outlines mechanisms, interfaces, and applications of conductive, piezoelectric, triboelectric, thermoelectric, and photoelectric materials, and proposes a framework guiding next‑generation bioelectronic system design.

Researchers in Spain and Japan tested a broad range of pedestrians in varying group sizes to see whether there were any patterns to their turning behaviors, and what factors influence them if there are. It turns out that the vast majority of people have a preference for counterclockwise turning. Most factors such as culture or gender made little difference. Only age showed a noticeable but small change in that younger people followed this pattern more strongly. This area of research could impact our understanding of the brain, and fields like design, engineering and architecture. The original research, including the initial experiments and analysis, was conducted by the Department of Physics and Mathematics at the University of Navarra in Spain, with additional comparative experiments later carried out in Japan in collaboration with the University of Tokyo team. 

Wei Gao and his lab at Caltech have developed a flexible interface for medical sensing that moves with the body and a closed-loop therapeutic platform that can adhere to wet tissue.

Gestational diabetes is commonly viewed as a temporary complication of pregnancy. However, growing evidence suggests that its effects may extend far beyond pregnancy itself, influencing a child’s metabolic health before birth and increasing the risk of obesity, insulin resistance and diabetes later in life.

A review published in Frontiers in Endocrinology by researchers from Wroclaw Medical University and Wrocław University of Science and Technology examines how adipokines—hormones produced by adipose tissue—shape the metabolic environment of both mother and fetus during gestational diabetes.

The authors focus on leptin, adiponectin and markers of leptin resistance, including the Free Leptin Index (FLI) and Leptin-to-Adiponectin Ratio (LAR). These biomarkers may help identify metabolic disturbances associated with gestational diabetes and could eventually support early detection of children at increased risk of future metabolic disorders.

The review highlights the concept of metabolic programming, which proposes that conditions experienced during fetal development can have long-lasting effects on metabolism and disease susceptibility. According to the authors, the first 1,000 days of life—from conception to approximately two years of age—represent a critical window during which biological mechanisms linked to obesity, diabetes and other non-communicable diseases may be established.

The researchers emphasize that effective prevention begins with proper diagnosis and management of gestational diabetes during pregnancy. Improved monitoring, healthy nutrition, physical activity and multidisciplinary care may help reduce long-term metabolic risks for both mothers and their children.

The findings contribute to growing evidence that the origins of many metabolic diseases may be traced back to fetal life and support the development of earlier and more personalized prevention strategies.

“Robots that make judgments like humans are coming faster than we think.” A core technology that will accelerate the era where robots understand human intentions and choose the correct actions on their own has been developed in South Korea. KAIST researchers solved a key challenge in the commercialization of physical AI by developing a technology where AI learns human judgment criteria on its own with just a few videos. KAIST announced on June 10th that a research team led by Professor Chang D. Yoo from the School of Electrical Engineering has developed 'VOTP (Video-based Optimal TransPort Preference)' for the first time in the world, a new technology that allows AI to learn human intentions and judgment criteria using just a few preference videos instead of thousands to tens of thousands of human evaluation data points.