Under universal health coverage, allocating antidepressant benefits requires balancing health costs, clinical efficacy, and patient financial protection. We propose a dual societal–household disease-burden optimization framework and a triple-population cooperative particle swarm algorithm. Validated on real-world data from City S, China, the optimized reimbursement package cuts household out-of-pocket spending by up to 48.97% per unit treatment effect, offering a transferable decision-support tool for mental health financing and health equity in low- and middle-income countries.

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.

Traditional air quality models struggle with changing emissions, while pure AI systems operate as opaque "black boxes" that can break the laws of physics. To solve this, researchers developed ProNet, a framework that embeds AI directly into atmospheric equations. Tested across 338 cities, ProNet outperformed experienced human forecasters and accurately predicted extreme events—like severe dust storms—without producing "AI hallucinations." Crucially, it also acts as a scientific diagnostic tool, using routine hourly data to uncover and correct hidden flaws in existing chemical models.

Using satellite observations, researchers tracked water storage recovery after 468 severe droughts in large river basins worldwide. Most events were followed by recovery, but persistent deficits clustered in drylands and some inland basins. Recovery trajectories varied across basins and events, reflecting water availability after drought. Recurrent droughts and intensive human water use were associated with prolonged deficits.