Researchers at The University of Texas MD Anderson Cancer Center and collaborating institutions in Texas developed an artificial intelligence (AI) model that helps explain how immune cells find their way to specific locations in the body and why they avoid others. The findings could help scientists better understand cancer, autoimmune diseases and treatment response.

With a new AI platform, patients communicate with medical devices in real time, receive alerts, ask questions, and better manage their condition.

Every online order sets off a complex chain of operational decisions, from choosing where items are fulfilled to picking, shipping and returns. A new review of 198 studies maps these decisions across the end-to-end B2C fulfillment process and shows how research is moving toward integrated, real-time and data- and AI-enabled decision-making, offering a roadmap for more efficient and responsive e-commerce operations.

The tumor-confined nano-activator (iCLAN_TSP-SAg) can drive localized expression of bacterial superantigens within tumors, enabling potent, antigen-independent T-cell activation while avoiding systemic toxicity.

Scientists have developed a simple yet powerful strategy to overcome a long-standing challenge in cancer phototheranostics—the trade-off between imaging brightness, therapeutic efficacy, and biological stability. By systematically replacing hydrogen atoms with deuterium (a heavier isotope) in a near-infrared fluorescent molecule, researchers achieved simultaneous improvements in all three critical properties. The optimized nanoparticles delivered 26% higher fluorescence brightness, 14% more reactive oxygen species for killing cancer cells, and 20% better stability in blood. In mouse models, a single treatment completely eliminated breast tumors, and fluorescence-guided surgery enabled precise removal of colorectal cancer remnants that were invisible under white light—extending survival from under 20 days to over 60 days. The strategy is broadly applicable and does not require redesigning the molecular backbone, offering a versatile platform for next-generation cancer theranostics.

Preeclampsia (PE) is a serious pregnancy complication characterized by hypertension and multi-organ dysfunction after 20 weeks of gestation, posing significant risks to both mothers and infants. Early identification of women at high risk enables timely preventive interventions, yet established screening protocols, such as the Fetal Medicine Foundation (FMF) clinical model, exhibit moderate sensitivity during the first trimester. Since routine laboratory tests reflect early metabolic and inflammatory changes associated with disease development, they may provide an accessible and cost-effective strategy for improving PE prediction.