Researchers at the Icahn School of Medicine at Mount Sinai have developed an artificial intelligence (AI) approach using data from wearable devices that can forecast upcoming periods of prolonged sitting in women with chronic pelvic pain disorders. The findings, published in the September 30 online issue of npj Women’s Health [DOI: 10.1038/s44294-026-00156-5], could inform personalized digital health tools that prompt the individual to move, such as by taking a short walk, at the right time while minimizing unnecessary alerts.

A research team led by an Oregon State University scientist has demonstrated in a mouse model a potentially better way of caring for women facing the life-threatening condition of ectopic pregnancy.

When learning a new motor skill, brain connections are reshaped to refine the timing of movements. However, scientists at MPFI have shown that rather than a brain-wide overhaul, synaptic changes in just a single class of neuron are needed to precisely adjust the timing of motor behavior. This finding suggests that with further research, scientists may be able to pinpoint specific learning deficits to precise neuronal cell types.