In the late 1800s, newspapers ran alarming headlines about a dangerous new technology corrupting the nation’s youth. Books. Kids were sneaking off to libraries to read Horatio Alger, and parents were convinced it would ruin them. More than a century later, the medium has changed dramatically. But the fear, experts say, has not. The tension between panic and practicality was at the heart of a packed panel discussion Sept. 8 at UC Irvine, the third installment of the “Raising the Next Generation in the Age of AI” series. Co-presented by UCI’s School of Social Ecology, the Donald Bren School of Information and Computer Sciences, the Office of Research, the Connected Learning Lab, and CERES (Connecting the EdTech Research EcoSystem), the event brought together researchers, a tech industry leader and a youth advocate for a candid, research-grounded conversation about helping families navigate the challenges of raising children in an increasingly digital world.

The Family Heart Foundation, a leading research, education and advocacy organization, today announced the publication of a new peer-reviewed study in JACC: Advances demonstrating how its FIND Lp(a)^® Machine Learning Model can identify people with atherosclerotic cardiovascular disease (ASCVD) who are more likely to have high lipoprotein(a) — or Lp(a). The model has already been successfully deployed at five large U.S. healthcare systems participating in the FIND Lp(a) Program that aims to catalyze Lp(a) screening. The model’s high level of precision supports targeted Lp(a) screening as a practical approach for healthcare systems working toward implementation of guideline-recommended universal screening.

New review in Current Topics in Chemistry brings together decades of research on flavonoids isolated from Erythrina plants, a group long valued in traditional medicine and natural product chemistry.