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Read the UC San Diego Today recap of the 2026 UC San Diego Women’s Health Symposium, featuring key moments, leadership insights, and poster research award winners.

Men with non-obstructive azoospermia may undergo microscopic testicular sperm extraction, or mTESE, without knowing whether sperm will be found. Speaking at the 2026 UC San Diego Women's Health Symposium, Kun Tan, Ph.D., of UC San Diego explains how molecular semen analysis could provide a noninvasive way to predict the procedure’s outcome. The assay uses stage-specific germ cell markers identified through single-cell RNA sequencing, then measures those markers in semen with qPCR. Because semen contains germ cells from different stages of sperm development, their molecular signals may reflect what is happening inside the testes. Tan shows how the assay predicts whether sperm retrieval was successful and can identify where sperm development may be blocked. The research could help couples planning IVF or ICSI avoid unnecessary surgery, reduce financial and emotional burdens, and receive more detailed information about male infertility before treatment.
Watch Kun Tan's WHS Presentation on UCTV

Alzheimer's disease can begin developing years before memory and thinking problems become noticeable. Iris Broce-Diaz, Ph.D., of UC San Diego is developing accessible, noninvasive, and cost-effective tools to help primary care physicians and neurologists identify people at higher risk earlier. Her models combine information from cognitive assessments, brain imaging, genetics, and PET scans to estimate the likelihood that mild cognitive impairment will progress within five years. Combining multiple measures improves the models' ability to separate higher- and lower-risk patients. Broce-Diaz also plans to add women-specific factors, including menopause history, hormone therapy, reproductive history, endocrine markers, and symptoms. The goal is to support better referrals, guide monitoring, and help eligible patients consider treatment sooner. Earlier risk assessment could also strengthen clinical trials and make dementia care more useful across different health systems.
Watch Iris Broce-Diaz's WHS Presentation on UCTV

Continuous glucose monitoring and wearable data are changing how researchers study pregnancy and women's health. Gladys (Sandy) Ramos, M.D., explains why glucose control is difficult during pregnancy and how CGM can reveal patterns that finger-stick testing may miss. She also describes research on CGM use in type 2 and gestational diabetes, labor, and behavior change. Ben Smarr, Ph.D., shows how wearable data can track changes in temperature, heart rate, activity, respiration, menstrual cycles, pregnancy, and aging. Together, the speakers discuss personalized care, participant engagement, patient-driven innovation, and access to these tools. The goal is to learn from continuous data while recognizing limits in evidence, interpretation, and equity.
Watch Ramos & Smarr’s Presentation on UCTV

Cardiovascular disease is a major threat to maternal health during pregnancy and the peripartum period, particularly for women with preexisting heart conditions. A UC San Diego cardiologist describes the development of a multidisciplinary cardio-obstetrics initiative designed to coordinate care for patients with congenital heart disease, heart failure, arrhythmias and coronary artery disease. The program brings cardiology and maternal-fetal medicine together with other specialties to establish consistent protocols, improve maternal and fetal outcomes, advance research and train future clinicians. As more people born with congenital heart disease survive into adulthood and consider pregnancy, the need for this specialized care continues to grow. Longitudinal surveillance is also helping researchers study outcomes and identify opportunities for better monitoring. Coordinated cardio-obstetrics care can help manage complex cardiovascular risks throughout pregnancy and delivery.
Watch Alshawabkeh's Presentation on UCTV

AI-powered cell imaging may help researchers identify biological differences that are difficult or impossible to see by eye. Yu-Hwa Lo, Ph.D., and Louise Laurent, M.D., Ph.D., describe a system that combines high-speed imaging, cell sorting, microfluidics, and artificial intelligence. The technology creates label-free images of cells, uses AI to classify them, and can isolate selected cells for deeper molecular analysis. Laurent explains how the team is applying the system to human trophoblast stem cells, which give rise to specialized placental cells involved in nutrient transport, hormone production, blood vessel remodeling, and immune regulation. Lo describes how AI can distinguish cell populations and identify features that may not be apparent to human observers. The researchers ultimately hope to connect imaging features with gene expression, proteins, and metabolism, allowing cell characteristics and behavior to be predicted from images alone.