A quantum mechanics approach to artificial intelligence can improve cancer outcomes
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Updates every hour. Last Updated: 27-Jun-2026 07:15 ET (27-Jun-2026 11:15 GMT/UTC)
A new study from the Icahn School of Medicine at Mount Sinai shows that social determinants of health—including environmental conditions, health behaviors, access to resources, and social well-being—can play an equally important or even greater role than genetics in predicting a person’s risk of developing common diseases. Published in the June 22 online issue of The American Journal of Human Genetics [DOI: 10.1016/j.ajhg.2026.05.014], the study, titled "Integrating Social Determinants of Health and Genetic Risk in Disease Risk Models," examined how inherited genetic risk and social, behavioral, and environmental factors interact to influence disease risk across diverse populations.
A newly published review article in Photonix Life provides one of the most comprehensive guides to date on Raman microscopy for biological imaging. Led by researchers at the University of California San Diego, the review systematically covers spontaneous and coherent Raman techniques, bio-orthogonal probes, biomedical applications ranging from cancer to neurodegenerative disease, and emerging frontiers including quantum-enhanced imaging and AI-driven diagnostics. By organizing technical advances along four parallel performance axes and evaluating the trade-offs of each approach, the review offers a practical decision-making resource for biologists considering Raman methods and for spectroscopists seeking impactful biological applications.
Strange “chimeric” RNA once thought to be the product of cancer is actually an important controller of women’s health, including influencing their susceptibility to infectious disease and autoimmune disorders, new research suggests.