The presence of blood cells in urine is a sign of bladder cancer. Because aspirin blocks platelets from forming harmful blood clots, the medication can cause mild bleeding or worsen existing bleeding in the urinary tract. Results from a study in the Journal of Internal Medicine suggest that this may prompt a clinician to run tests that uncover an asymptomatic bladder tumor.

Damon Runyon has awarded Quantitative Biology Fellowships to three outstanding young scientists applying computational approaches to persistent biological questions. Their projects will use machine learning, spatialomics, advanced network modeling, and other technologies to better understand breast cancer risk, improve response to immunotherapies, and identify new chromosomal drivers of cancer. Each postdoctoral scientist will receive independent funding ($240,000 total) to train under the joint mentorship of an established computational scientist and a cancer biologist.

Women with abnormal mammograms often have to wait for weeks to find out whether they have breast cancer.

 

Now, researchers at UC San Francisco and UC Berkeley have found a way to help reduce the wait and the worry by using AI to quickly identify those who are most likely to have the disease. By triaging these patients, the AI-guided workflow takes women with abnormal scans through the diagnostic process — from imaging to evaluation and sometimes even biopsy — in a single day. 

A UC Irvine-led study analyzed 3,511 cancer patients across six UC medical centers to examine infection-related side effects to antibody-drug conjugates, or ADCs.

Researchers found some ADC therapies were linked to dangerously low infection-fighting white blood cell counts and related complications, including hospitalization.

Led by pharmacy professor Alexandre Chan, the study highlights the need for closer monitoring and supportive care as targeted cancer therapies become more widely used.