A newly developed AI tool can dramatically speed up the search for the genetic causes of rare diseases, a process that often takes years and frequently ends without answers. The tool analyzes how genes have evolved across many species to uncover hidden clues about which gene is responsible for a patient’s symptoms. In tests, it successfully identified the disease-causing gene in most cases, even when that gene had never previously been linked to a disease. This approach could significantly shorten the diagnostic journey and help guide doctors toward effective treatments much sooner.

LMU researchers show that the structure of DNA is organized to facilitate cell division at exactly the right moment in the cell cycle.

Using the American Heart Association’s recently developed PREVENT score to estimate a patient’s 10-year risk of cardiovascular disease, researchers found that women with the highest risk of cardiovascular disease were most likely to experience osteoporatic bone fractures. The findings could indicate that the PREVENT score may be valuable in identifying patients who could benefit from a bone density screening.