Cataracts affect 25 million people in the U.S. and over 65 million people globally.

These numbers are expected to rise as populations age, and life expectancy increases.

NIH-supported work offers new insight into the earliest steps of cataract formation at the molecular level.

Georgia Tech has been awarded up to $21.8 million from the Advanced Research Projects Agency for Health (ARPA-H) to develop a first-of-its-kind therapy for lymphatic disease, a condition that has long lacked effective treatment options. Led by Woodruff Professors Susan Napier Thomas and J. Brandon Dixon, the project aims to move beyond symptom management and address the disease itself, offering hope to patients who often experience chronic pain and disfigurement. Funded through ARPA-H’s GLIDE program, the initiative will focus on advancing the therapy toward initial human trials, including for rare pediatric conditions. The award highlights Georgia Tech’s leadership in engineering-driven healthcare innovation and its commitment to improving care for underserved patient populations.

About The Study: Among metabolic and bariatric surgery (MBS)-eligible patients in a national sample, semaglutide and tirzepatide prescriptions increased dramatically between 2018 and 2025, whereas MBS use rates declined substantially beginning in 2023. Stratification by procedure type and body mass index (BMI) category suggests that recent shifts in MBS use may be more pronounced in certain patient subgroups (e.g., those seeking sleeve gastrectomy or with lower BMIs).

About The Study: In this cross-sectional study of 62,685 participants from the All of Us Research Program, loneliness partially mediated the association between anxiety symptoms and suicidal ideation as well as depressive symptoms and suicidal ideation. Targeting and reducing loneliness may present a transdiagnostic approach to arrest the progression from anxiety and depressive symptoms toward suicidal ideation. 

About The Study: Compared with usual care, use of the PETRUSHKA tool increased the number of patients still taking their antidepressant at 8 weeks and improved depressive and anxiety symptoms at 24 weeks. However, lack of a double-blind design and the large amount of missing data limit the validity of these results. The PETRUSHKA tool is a web-based clinical decision-support system combining clinical and demographic predictors with patient preferences to personalize antidepressant treatment. 

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease. Scientists used their tool, named Merlin, to assess 3D abdominal computed tomography (CT) scans, accomplishing tasks as simple as identifying anatomical features to as complex as predicting disease onset years in advance. Despite being developed as a general-purpose CT model, Merlin surpassed a gauntlet of similar automated tools in tasks they were specifically built to handle.