Three-dimensional cancer organoids and spheroids are powerful models for studying tumor biology, but current imaging methods limit their full potential. In this study, researchers introduce an AI-enhanced optical coherence photoacoustic microscopy (OC-PAM) system that enables high-resolution, label-free, and longitudinal imaging of 3D cancer models. The technology promises more physiologically relevant cancer research and accelerated translation of advanced in vitro models into drug discovery and precision oncology.

Spin density symmetry breaking in single-atom catalysts can significantly enhance the performance of hydrogen evolution reactions. Through interpretable machine learning and theoretical calculations, the research team quantified basic features into composite descriptors with well-defined structure-activity relationships, revealing a direct correlation between spin density symmetry breaking and catalytic activity, and offering new insights for the rational design of high-efficiency catalysts.

Formaldehyde is a common but unwelcome guest in many modern homes, leaking silently from furniture, flooring, and household products. While this colorless gas is a known respiratory irritant, cleaning it out of the air usually requires expensive or energy-heavy technology. Now, a research team from Vietnam National University has found a clever way to turn agricultural waste into a high-tech filter that breathes new life into indoor spaces.

Researchers at the University of Cincinnati developed a novel artificial intelligence to predict substance use defining behaviors with up to 83% accuracy and 84% accuracy to predict the severity of the addiction.

Researchers at Arizona State University and their international colleagues have developed a device that cuts sample consumption by as much as 97% while still producing high-quality structural data. The technology could accelerate drug discovery by showing how medicines interact with their protein targets in real time and help engineers design better enzymes for industry and biotechnology. It may also enable deeper insights into disease, enable the study of rare proteins that are difficult to produce, and unlock the full potential of next-generation X-ray laser facilities without excessive sample waste.