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http://dx.doi.org/10.1103/PhysRevLett.72.1972 | DOI Listing |
Nat Commun
January 2025
The beta decay of the lightest charmed baryon provides unique insights into the fundamental mechanism of strong and electro-weak interactions, serving as a testbed for investigating non-perturbative quantum chromodynamics and constraining the Cabibbo-Kobayashi-Maskawa (CKM) matrix parameters. This article presents the first observation of the Cabibbo-suppressed decay , utilizing 4.5 fb of electron-positron annihilation data collected with the BESIII detector.
View Article and Find Full Text PDFJACC Adv
January 2025
Department of Surgery, Division of Transplant Surgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Background: Currently, there is no mathematical model used nationally to determine the medical urgency of patients on the heart transplant waitlist in the United States. While the current organ distribution system accounts for many patient factors, a truly objective model is needed to more reliably stratify patients by their medical acuity.
Objectives: The aim of the study was to develop risk scores (Colorado Heart failure Acuity Risk Model [CHARM] score) to predict mortality in adults waitlisted for heart transplant.
Cancer Cell
December 2024
The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK. Electronic address:
Pilot Feasibility Stud
November 2024
Headquarters Air Force A1Z (Integrated Resilience Directorate), Arlington, VA, USA.
Background: Sexual assault prevention is a priority for the military and is likely to be most effective when tailored to specific needs and individual experiences. Technology advances make it possible to integrate individualized programming into group education settings common to military training, but this approach is not without potential challenges. Prior to implementing and evaluating a novel prevention program, it is critical to conduct a feasibility study to assess the extent to which the program can be successfully implemented, is acceptable to participants, and can be rigorously evaluated.
View Article and Find Full Text PDFInt J Med Inform
January 2025
BioMedical Machine Learning Lab, School of Biomedical Engineering, UNSW Sydney, Randwick, NSW 2052, Australia.
Background: Early and reliable prognostication in post-cardiac arrest patients remains challenging, with various factors linked to return of spontaneous circulation (ROSC), survival, and neurological results. Machine learning and deep learning models show promise in improving these predictions. This systematic review and meta-analysis evaluates how effective these approaches are in predicting clinical outcomes at different time points using structured data.
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