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Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition.
Brief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFThe diagnostic performance and optimal strategy of cone beam CT-assisted bronchoscopy for peripheral pulmonary lesions: A systematic review and meta-analysis.
Pulmonology
December 2025
Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Cone-beam computed tomography (CBCT) assisted bronchoscopy shows prospective advantages in diagnosing peripheral pulmonary lesions (PPLs), but its diagnostic value and potential influencing factors remain unclear. What is the clinical value and optimal strategy of CBCT-assisted bronchoscopy in diagnosing PPLs? The references were searched from PubMed, EmBase, and Web of Science. Studies reporting diagnostic yield and potential influencing factors of CBCT-assisted bronchoscopy were included.
View Article and Find Full Text PDFUsing Large Language Models to Detect and Understand Drug Discontinuation Events in Web-Based Forums: Development and Validation Study.
J Med Internet Res
January 2025
Department of Industrial and Systems Engineering, The University of Florida, GAINESVILLE, FL, United States.
Background: The implementation of large language models (LLMs), such as BART (Bidirectional and Auto-Regressive Transformers) and GPT-4, has revolutionized the extraction of insights from unstructured text. These advancements have expanded into health care, allowing analysis of social media for public health insights. However, the detection of drug discontinuation events (DDEs) remains underexplored.
View Article and Find Full Text PDFOvercoming Hesitancy and Barriers to Care with Integration of Telemedicine in a Free Student-run Health Clinic.
J Prim Care Community Health
January 2025
University of California, Davis, Division of Hospital Medicine, Sacramento, CA, USA.
Introduction: Nadezhda Clinic is a free student-run health clinic that provides culturally sensitive primary care services to the underserved Russian-speaking population of the greater Sacramento area. At the onset of the COVID-19 pandemic, the clinic suspended in-person services and solely offered telemedicine visits. Most patients were hesitant to utilize telemedicine due to poor technological literacy, privacy concerns, and a preference for in-person care.
View Article and Find Full Text PDFArgonaute-mediated dual recognition enables the detection of trace single-nucleotide-mutated fungicide-resistant fungal pathogens.
Chem Commun (Camb)
January 2025
Beijing Life Science Academy, Beijing 102206, China.
Detection of low-abundance mutations for the early discovery of fungicide-resistant fungal pathogens is highly demanded, but remains challenging. Herein, we developed a dual-recognition strategy, termed PARPA, involving s Argonaute (pfAgo)-mediated elimination of wild-type fungal genes and CRISPR/Cas12a-based amplicon recognition. This assay can detect fungicide-resistant at relative abundances as low as 0.
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