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AI-powered CMBs provide a New Approach Methodology for precision oncology
AI-discovered cellular morphometric biomarkers in needle biopsy of prostate cancer predict neoadjuvant androgen deprivation therapy response and enable therapeutic targeting of mTOR in androgen deprivation therapy-resistant tumors Researchers at Berkeley Lab have led the development of an artificial intelligence-based biomarker that predicts neoadjuvant androgen deprivation therapy response in prostate cancer using standard histopathology images. The approach, termed a 13-cel
Hang Chang
Mar 251 min read


Invisible Exposure, Measurable Impact: How Genetics and AI Are Revealing the Hidden Health Risks of Thirdhand Smoke
Through initiatives such as Genesis AI, Berkeley Lab is helping to lead a new era of discovery in which advanced computational approaches can illuminate the biological consequences of environmental exposures and guide strategies to protect vulnerable populations. Environmental exposures often leave traces long after the original source disappears. One such exposure: thirdhand smoke (THS) , is increasingly recognized as a hidden but persistent threat to human health. Unlike se
Hang Chang
Mar 254 min read


GenomeOcean Leverages AI to Decode Nature’s Secret Language
GenomeOcean is a generative model available for researchers to analyze and create DNA sequences from microbial life. [Image: OpenAI] Unlocking the intricate details of life’s genetic blueprint has long been a significant challenge in genomics. Enter GenomeOcean, a powerful generative model now available to the global research community able to not just analyze but also create DNA sequences mimicking an array of microbial life. By leveraging massive user-generated datasets a
Hang Chang
Feb 275 min read


Advancing Cancer Research with Artificial Intelligence
Some members of the group involved in the research: (Left to Right) Hang Chang, Jian-Hua Mao, and Antoine Snijders. Researchers in the Biological Systems and Engineering (BSE) Division recently published two studies that will help oncologists more precisely understand the state of their patients’ disease or their risk for cancer relapse. As with many diseases, cancer can be challenging to predict and in some cases, impossible to treat. This work, however, is pushing the boun
Hang Chang
Feb 233 min read


Machine Learning Helps Link Chemical Exposure and Obesity
Some chemicals found in plastic bottles are hormone disruptors like the ones investigated in this study. (Credit: Mali Maeder/pexels.com) Obesity is a major health concern and chemical exposure is considered to contribute to this disease, along with genetic and lifestyle factors. However, real-world chemical exposure is complex and combinations of chemicals and their resulting interactions have not been studied fully. Scientists at Berkeley Lab and their collaborators develo
Hang Chang
Feb 231 min read


Genetic Background Influences Cancer Risk of Thirdhand Smoke Exposure
The harm caused by the chemical residues of tobacco smoke may vary with genetics. (Credit: John Graham/iStock; https://www.flickr.com/photos/grimages/4662858222/ ) A new study investigating the effect of thirdhand smoke (THS) in a mouse model system specially designed to mimic the genetic diversity of human populations has shed new light on how genetic predispositions contribute to an individual’s cancer risk. The study, published in the April Issue of Environment Internatio
Hang Chang
Feb 232 min read


Toward a Genetic Understanding of Variability in Radiation Sensitivity
Biological Systems and Engineering Division senior scientists Jian-Hua Mao and Antoine Snijders work with the X-ray machine at Potter Street. (Credit: Thor Swift/Berkeley Lab) More than half of all cancer patients receive some form of radiation therapy as part of their treatment. Advances in technology have enabled precision targeting of tumors, minimizing exposure of healthy tissues to radiation. Even so, acute and/or chronic injury to immune-system and blood-forming cells i
Hang Chang
Feb 234 min read
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