Half of people who die by suicide have no diagnosed psychiatric risk factors, such as depression. It was unclear whether this population was depressed and undiagnosed, or simply not depressed. Genetic research shows that this population is less likely to have genetic risk factors for depression, suggesting that what puts them at risk is meaningfully different.

Lehigh University researcher Hannah Dailey is leading a new international collaboration to improve predictions of how bone fractures heal. Supported by the U.S. National Science Foundation and the Swiss National Science Foundation, the four-year project partners with the AO Research Institute Davos (ARI) to develop computational models that combine mechanical factors—such as implant stiffness and loading patterns—with biological processes that vary from patient to patient. Using ARI’s extensive imaging library documenting fracture healing in sheep, the team will build probabilistic models capable of forecasting how recovery will progress. The models will ultimately be integrated into ARI’s online training platform to help surgeons understand how implant choices and rehabilitation strategies influence healing. Long term, the goal is to enable patient-specific simulations that help clinicians identify complications earlier and make more informed treatment decisions.

A research paper by scientists at Nankai University presents a monolithic synaptic device that replicates and integrates tactile sensing and neuromorphic processing functions for in-sensor computing.