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Ultraviolet-C light kills coronavirus on N95 respirator masks, effectively decontaminating them so they can safely be reused, dermatology researchers at Henry Ford Health System and the University of Michigan announced Tuesday. A shortage of the medical-grade masks early in the COVID-19 pandemic drove the health systems to collaborate on a project to test whether a high dose of UV-C light — used to treat some skin conditions like vitiligo and psoriasis —  would kill virus particles but still preserve the integrity of the masks. (Shamus, 9/22)

Respirator masks made in China and purchased by U.S.-based healthcare systems often don't meet federal filtration standards, according to a new analysis by the not-for-profit patient safety organization ECRI. N95 respirator masks are used by healthcare personnel when interacting with suspected or confirmed COVID-19 patients. Shortages of these masks in the U.S. has forced some providers desperate for them during the COVID-19 pandemic to buy from suppliers that haven't received certification from the U.S. government, many of which are based in China. These masks tend to be called KN95. In an analysis of nearly 200 masks from 15 mask models manufactured in China, ECRI found 60% to 70% of the masks didn't filter 95% of aerosolized particles as their name suggests and is standard for N95 respirator masks in the U.S. (Castellucci, 9/22)

When you hear the word “bacteria,” you might think of germs or disease. But not all bacteria are harmful. Trillions of these microorganisms — also called microbes — live on our skin and inside our bodies, but they’re too tiny to see with the naked eye. Our microbes have important jobs, ranging from helping us digest food to protecting us from infections. The genetic material for the microorganisms — including bacteria, fungi and other microbes — that reside on or in our bodies is called the human microbiome. (Rich, 9/22)

In June, when MIT artificial intelligence researcher Regina Barzilay went to Massachusetts General Hospital for a mammogram, her data were run through a deep learning model designed to assess her risk of developing breast cancer, which she had been diagnosed with once before. The workings of the algorithm, which predicted that her risk was low, were familiar: Barzilay helped build that very model, after being spurred by her 2014 cancer diagnosis to pivot her research to health care. (Robbins, 9/23)

Today, PLOS Medicine published two large COVID-19 studies, one a meta-analysis of 79 international studies showing that most infected patients eventually have symptoms, and the other a study of 5.8 million US Department of Veterans Affairs patients revealing that blacks and Hispanics were more likely to be infected—but not to die within 30 days—than whites. (Van Beusekom, 9/22)