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Many people don't realize that the trillions of bacteria, viruses, and fungi residing within the gastrointestinal tract --collectively called the gut microbiome -- are connected to overall health, and specifically to cancer.

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A change of instructions in a computer program directs the computer to execute a different command. Similarly, synthetic biologists are learning the rules for how to direct the activities of human cells.

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Vascular and interventional radiologists report the development of a new ionic liquid formulation that killed cancer cells and allowed uniform distribution of a chemotherapy drug into liver tumors and other solid tumors in the lab. This discovery could solve a problem that has long plagued drug delivery to tumors.

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A scientist and entrepreneur is working to use simple LED light to help determine if certain chemotherapy options will work for specific patients.

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In a groundbreaking new study, researchers have 3D printed unique fluid channels at the micron scale that could automate production of diagnostics, sensors, and assays used for a variety of medical tests and other applications.

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Researchers have created a new PET imaging agent that detects signs of inflammation. Such a tracer could aid diagnosis and study of diseases ranging from cardiovascular disease to cancer to COVID-19.

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A team has developed a class of light-switchable, highly adaptable molecular tools with new capabilities to control cellular activities. The antibody-like proteins, called OptoBinders, have potential applications including protein purification, the improved production of biofuels, and new types of targeted cancer therapies.

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NIBIB mourns the passing of molecular imaging pioneer and NIBIB Advisory Council member, Sanjiv “Sam” Gambhir, M.D., Ph.D.

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NIBIB-funded researchers at Stanford University have created an artificial neural network that analyzes lung CT scans to provide information about lung cancer severity that can guide treatment options.

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To counter drug resistance, scientists must engineer new drugs to kill mutated cancer cells or pathogens. Now, Penn State engineers have developed a new approach for predicting which mutation has expanded the most in a population and should be targeted to design the most effective new drug.