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.