Compelled by disparities in breast cancer outcomes, the Keck School of Medicine of USC’s Department of Population and Public Health Sciences and Novartis have joined forces in a pioneering collaboration to support medically underserved communities in Los Angeles County with the goal of eliminating barriers to screening and access. While Black women in the U.S. have higher screening rates for breast cancer than white women, the mortality rate for Black women with breast cancer is about 40% higher than white women —a disparity that is not yet fully understood but has been linked to a lack of access to timely, high-quality care and resources. Native American and Hispanic women also face significant disparities in breast cancer screening, often resulting in later-stage diagnoses compared to white women. The Keck School of Medicine of USC and Novartis bring complementary strengths to this collaboration, combining USC’s regional expertise in breast cancer health disparities and population sciences with Novartis’s experience and capabilities in advancing breast cancer care through collaboration and a passion for transforming patient care. The collaboration with Novartis will focus on the early detection of breast cancer, specifically reaching those in communities where access to breast cancer screening and quality care has been limited.USC’s researchers will examine the everyday obstacles that stand between women and timely care, including insurance coverage, language barriers, and access to reliable transportation.

A study published in Molecular Cell examines how immune cells control which antibody type they express to fight infectious diseases. MSU researchers employed a novel microscopy technique that allowed them to observe this process in real time as it occurred in live cells. With an additional NIH grant to continue research for four years, the researchers will build on the findings, which have implications for human health, including immune deficiencies and off-target mutations that can lead to cancer.

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer’s disease, and other potentially fatal conditions.

Researchers from the University of Waterloo developed the machine learning algorithm, called  RNovA, to detect changes in the proteins in human cells.