AI predicts patients likely to die of sudden cardiac arrest
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Dec-2025 10:11 ET (23-Dec-2025 15:11 GMT/UTC)
A new AI model is much better than doctors at identifying patients likely to experience cardiac arrest.
The linchpin is the system’s ability to analyze long-underused heart imaging, alongside a full spectrum of medical records, to reveal previously hidden information about a patient’s heart health.
Researchers at ETH have used nuclear magnetic resonance to find out what other atoms are bound to the platinum atoms in a single-atom catalyst and where they are spatially located.
The precise knowledge of the atomic environments can help produce single-atom catalysts that are more uniform, and thus more effective.
This also enables very efficient and resource-saving reaction accelerators for sustainable chemicals.
Amplification-free, highly sensitive, and specific nucleic acid detection is crucial for health monitoring and diagnosis. The type III CRISPR-Cas10 system, which provides viral immunity through CRISPR-associated protein effectors, enables a new amplification-free nucleic acid diagnostic tool. In this study, we develop a CRISPR-graphene field-effect transistors (GFETs) biosensor by combining the type III CRISPR-Cas10 system with GFETs for direct nucleic acid detection. This biosensor exploits the target RNA-activated continuous ssDNA cleavage activity of the dCsm3 CRISPR-Cas10 effector and the high charge density of a hairpin DNA reporter on the GFET channel to achieve label-free, amplification-free, highly sensitive, and specific RNA detection. The CRISPR-GFET biosensor exhibits excellent performance in detecting medium-length RNAs and miRNAs, with detection limits at the aM level and a broad linear range of 10-15 to 10-11 M for RNAs and 10-15 to 10-9 M for miRNAs. It shows high sensitivity in throat swabs and serum samples, distinguishing between healthy individuals (N = 5) and breast cancer patients (N = 6) without the need for extraction, purification, or amplification. This platform mitigates risks associated with nucleic acid amplification and cross-contamination, making it a versatile and scalable diagnostic tool for molecular diagnostics in human health.