A 2024 viewpoint led by researchers at Tohoku University’s AIMR reveals a strong correlation between hardness and ionic conductivity in NASICON-type solid electrolytes. By analyzing literature data, they identified relative density as a key factor, offering a practical strategy to enhance both properties for safer, high-performance sodium-ion batteries.

Researchers from The University of Osaka have used a miniature heater positioned over a nano-sized opening to gently unzip DNA’s double helix into a single strand for quick, efficient analysis. The device enables detection of longer DNA strands than before while using less power and improving accuracy. The technology could be used in handheld medical devices, helping doctors to diagnose disease and tailor treatments based on patients’ genes.

Using energy piles for geothermal heat exchange in buildings offers a sustainable alternative to traditional temperature regulators. However, designing these systems is often complex. Now, researchers from Shibaura Institute of Technology, Japan, have developed a simplified modeling framework to improve the design of energy pile systems. Using a combination of finite element modeling and field testing, they quantified the thermal interference between piles and soft clay soil—offering insights for quicker and enhanced geothermal performance.

People with diabetes often develop kidney disease without warning, leading to life-threatening complications. Now, researchers have discovered that two simple blood markers, estimated glomerular filtration rate difference and growth differentiation factor-15, can independently predict who is at an elevated risk of kidney function decline and early death. These findings could help doctors identify vulnerable patients sooner, paving the way for timely, personalized treatments that slow disease progression and improve outcomes for millions living with diabetes.

Hematopoietic stem cells (HSCs), which give rise to all blood cell types, are essential for regenerative medicine and gene therapy. However, predicting their long-term quality remains a challenge. Now, researchers from Japan have developed a novel system combining live-cell imaging and machine learning to predict HSC quality based on real-time behavior. This approach reveals hidden cellular diversity and enables accurate prediction of cell stemness and quality, advancing basic biology and offering promise for clinical applications.

A recent study by Associate Professor Takehisa Hirayama and Professor Osamu Kano from the Department of Neurology at Toho University School of Medicine has revealed a critical gap in the use of accessibility features among people living with Amyotrophic Lateral Sclerosis (ALS) and their caregivers. Though over 90% of ALS patients surveyed reported daily use of smartphones, tablets, or computers, many are unaware of the accessibility tools embedded in these devices—tools that could greatly enhance their quality of life as the disease progresses.