In an effort to greatly expand accessibility, this compact fluorescence-guided surgery system, evaluated in mice, is crafted from cost-effective and off-the-shelf components.

AI, specifically, machine learning, can help improve the quality of these MRI images, making it easier for doctors to diagnose patients. Machine learning involves training AI on a lot of data to recognize trends and make predictions on new data it receives. Source: Curious Science Writers

Rice University bioengineers have developed a new construction kit for building custom sense-and-respond circuits in human cells. The research, published in the journal Science, represents a major breakthrough in the field of synthetic biology that could revolutionize therapies for complex conditions like autoimmune disease and cancer. Source: Rice University News & Media Relations

Former NIBIB Director Dr. Roderic I. Pettigrew's viewpoint article in JAMA discusses the integration of medicine and engineering to transform how disease is prevented, diagnosed, and treated. JAMA

A new gene editing tool that helps cellular machinery skip parts of genes responsible for diseases has been applied to reduce the formation of amyloid-beta plaque precursors in a mouse model of Alzheimer’s disease, researchers at the University of Illinois Urbana-Champaign report. Source: University of Illinois Urbana-Champaign News Bureau

With the help of some of nature’s best engineers, NIBIB-funded researchers have developed technology to regrow damaged facial nerves.

Massachusetts Institute of Technology (MIT) engineers developed AI frameworks to identify evidence-driven hypotheses that could advance biologically inspired materials. Source: MIT News

Releasing a drug selectively in specific locations in the body, including the brain, has been challenging. Researchers at the University of Utah have tackled the problem by designing ultrasound-sensitive nanoparticles that release a drug at the targeted site when activated by focused ultrasound.

NIH has awarded more than $4 million in funds and support services to three diagnostic technology developers as part of RADx ® Tech’s Advanced Platforms for HIV Viral Load Monitoring program.