A recent comprehensive analysis highlights the transformative potential of Metal-Organic Frameworks (MOFs)—highly porous, tunable materials—in pharmaceutical research. The review concludes that MOFs can dramatically improve drug loading, enable targeted release to disease sites, and enhance the stability of delicate therapeutics, paving the way for more effective and precise treatments for conditions ranging from cancer to pulmonary diseases.

University of Utah epidemiologist Mary Jo Pugh leads efforts to better understand veterans’ health outcomes, especially for those with TBI, and how to improve them. Her team has documented several instances where veterans are at greater risk for negative outcomes, such as suicide, cancer,  cardiovascular disease and mental illness.

Single-cell sequencing provides great insights into the inner workings of cells – but making sense of the data requires advanced bioinformatics skills. Researchers at CeMM, Medical University of Vienna, and St. Anna Children’s Cancer Research Institute have now developed an artificial intelligence (AI) method and software tool that lets scientists explore such datasets through natural-language conversations – speaking English with the computer instead of having to learn a programming language. This study, published in Nature Biotechnology (DOI 10.1038/s41587-025-02857-9), illustrates how modern AI makes biomedical research more accessible and effective.

In a new Northwestern Medicine study, scientists have developed a more precise genetic risk score to determine whether a person is likely to develop arrhythmia, an irregular heartbeat that can lead to serious conditions such as atrial fibrillation (AFib) or sudden cardiac death.

Their approach not only improves the accuracy of heart disease risk prediction but also offers a comprehensive framework for genetic testing that, according to the scientists, could be applied to anything, including other complex, genetically influenced diseases like cancer, Parkinson’s Disease and autism.