MicroRNAs play a central role in controlling gene expression, yet how cells select the active strand from each microRNA precursor has remained unclear. In this study, ASU researchers demonstrate that strand selection follows conserved structural and sequence-based rules rather than chance. Using a newly developed high-throughput assay and a machine-learning model trained on thousands of experimental measurements, the team shows that these rules apply across tissues, development, and evolution—from nematodes to humans. By establishing the first unified framework for predicting microRNA strand usage, the work reveals an unrecognized layer of gene regulation and underscores the power of artificial intelligence to uncover fundamental biological principles.

A team led by investigators at the Mass General Brigham Cancer Institute has discovered that a particular marker on tumor cells circulating in the blood indicates whether a patient with lung cancer will experience a lasting response to a newly approved immunotherapy called tarlatamab. The findings, which are published in Cancer Discovery, could allow clinicians to easily and noninvasively determine which patients should receive the drug.

Exposure to per- and polyfluoroalkyl substances (PFAS), a class of highly persistent environmental chemicals commonly referred to as “forever chemicals,” is associated with a higher risk of gestational diabetes mellitus and altered markers of insulin resistance and insulin secretion, according to a new systematic review and meta-analysis led by researchers at the Icahn School of Medicine at Mount Sinai.