People with high blood pressure who take all their anti-hypertensive medication in one go at bedtime have better controlled blood pressure and a significantly lower risk of death or illness caused by heart or blood vessel problems, compared to those who take their medication in the morning, according to new research.

As little as a daily ping on your phone can boost physical activity, researchers from the Stanford University School of Medicine and their collaborators report in a new study. The finding comes by way of the first-ever entirely digital, randomized clinical trial, which sought to answer two overarching questions: Is it feasible to successfully run an entirely digital, randomized clinical trial?

Northwestern Medicine scientists have used patient-derived neurons to develop and test a new strategy to treat Parkinson's disease by mitigating the effects of harmful genetic mutations, as detailed in a study published today (Oct. 16) in Science Translational Medicine.

The more medications a patient takes, the greater the likelihood that interactions between those drugs could trigger negative side effects, including long-term organ damage and even death. Now, researchers at Penn State have developed a machine learning system that may be able to warn doctors and patients about possible negative side effects that might occur when drugs are mixed.

Researchers at the University of Illinois at Chicago are the first to identify the presence of a specific type of antibody, called anti-citrullinated protein autoantibodies, or ACPAs, in human tear fluid. They are also the first to demonstrate that patients with dry eye disease experienced reduced signs and symptoms of the condition in response to a new eye drop treatment - made from pooled human antibodies - that targets ACPAs.

A team led by a scientist at Scripps Research has invented a new genomics technique for tracking down the causes of rare genetic diseases. The technique, which the researchers report in Science, makes use of the fact that people inherit two copies or "alleles" of virtually every gene, one from the mother and one from the father.

An artificial intelligence/machine learning model to predict which scientific advances are likely to eventually translate to the clinic has been developed by Ian Hutchins and colleagues in the Office of Portfolio Analysis (OPA), a team led by George Santangelo at the National Institutes of Health (NIH). This work, described in a Meta-Research article published October 10 in the open-access journal PLOS Biology,