After a surprising discovery that overcomes a longstanding problem in fiber optics, MIT researchers demonstrated a biomedical imaging technique that is faster and more precise than other methods, which could help scientists and clinicians study new brain therapies.

In a new study, Duke Health researchers found that artificial intelligence tools can analyze routine electronic health records to accurately estimate a child’s risk of developing ADHD years before a typical diagnosis. By reviewing patterns in everyday medical data, the approach could help flag children who may benefit from earlier evaluation and follow-up.

The hippocampus is a key brain region involved in memory formation and spatial orientation. It transforms short-term memories into long-term ones, helping us retain and build upon our experiences. Researchers led by Magdalena Walz Professor for Life Sciences Peter Jonas at the Institute of Science and Technology Austria (ISTA) focus precisely on this area of the brain. Their latest study, published in Nature Communications, reveals how the central neural network in the hippocampus develops after birth.

Aging often brings metabolic troubles, and a new study in Engineering may explain why. Scientists found a special sugar-modified antibody called fucosylated IgG builds up in aging fat tissue. It worsens inflammation and scarring while weakening fat’s normal function. This discovery points to a new way to ease age-related metabolic problems by adjusting this antibody’s sugar structure, giving fresh hope for healthy aging.

B lymphoma remains tough to treat with current cell therapies due to high costs and limited antigen targeting. A new study in Engineering compares two live-cell glycocalyx engineering methods to boost immune cells against B lymphoma. By equipping NK and CAR-T cells with CD22-targeting glycans, researchers enhance tumor recognition and killing. This transgene-free strategy offers a practical, cost-efficient path to better adoptive cell therapies.

Chinese herbal medicines have given birth to many classic drugs, but their complex ingredients and unclear mechanisms slow new drug development. A new study in Engineering proposes phenotype–target coupled drug screening, combining phenotype-based and target-based discovery with AI, multiomics, and organ-on-chip models. This efficient framework helps locate active compounds, clarify targets, and boost success rates for herbal drug research and development.