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A new imaging device at UT Southwestern is making complex aortic repairs safer for patients and operating room staff by dramatically reducing their exposure to radiation.

A gene that’s well known for its role in turning on tumor-suppressing genes when cells become stressed also keeps potential tumor-driving genes turned off, UT Southwestern researchers report in a new study.

The earlier individuals develop Type 2 diabetes or hypertension in life, the earlier they are likely to develop primary open-angle glaucoma (POAG), the leading cause of irreversible blindness worldwide, researchers from UT Southwestern reported in a recent study.

Leveraging its broad expertise in biomedical informatics, data sciences, and clinical sciences, UT Southwestern Medical Center is aggressively expanding its involvement in clinical informatics, which aims to harness the power of big data to improve patient care and public health.

In humans, virtually every cell stores fat. However, patients with a rare condition called congenital lipodystrophy, which is often diagnosed in childhood, cannot properly store fat, which accumulates in the body’s organs and increases the risk of early death from heart or liver disease.

In just a few hours, UT Southwestern scientists can tell which variant has infected a COVID-19 patient – a critical task that can potentially influence treatment decisions but takes days or weeks at most medical centers.

The rapid adoption of telemedicine and increased use of continuous glucose monitoring helped to attenuate the impacts of the COVID-19 pandemic on children with Type 1 diabetes.

A student group at UT Southwestern Medical School has been named the 2022 Chapter of the Year by the Texas Medical Association Medical Student Section.

The dominant form of heart failure worldwide appears to be caused by a strong, bidirectional interaction between the body’s response to metabolic stress and the immune system, according to a review article written by UT Southwestern researchers and colleagues.

Newly developed artificial intelligence (AI) programs accurately predicted the role of DNA’s regulatory elements and three-dimensional (3D) structure based solely on its raw sequence, according to two recent studies in Nature Genetics.