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Leveraging Old Hepatitis C Therapies.
N Engl J Med
December 2024
From West Virginia University College of Law, Morgantown (S.S.T.), the Institute of Human Virology, University of Maryland School of Medicine, Baltimore (S.K.), and the Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City (T.J.M.).
High-Throughput Screening of DPPIV Inhibitors Antagonizing GLP-1 Degradation Using an Enzymatic Activated Fluorescent Probe.
Anal Chem
December 2024
First Affiliated Hospital, College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian 116044, China.
Dipeptidyl peptidase IV (DPPIV, EC 3.4.14.
View Article and Find Full Text PDFGeometric deep learning improves generalizability of MHC-bound peptide predictions.
Commun Biol
December 2024
Medical BioSciences department, Radboudumc, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands.
Article Synopsis
- The interaction between peptides and MHC molecules is crucial for understanding autoimmunity and improving cancer immunotherapies.
- Recent advancements reveal that traditional sequence-based prediction methods have limitations, prompting the need for better approaches.
- The new structure-based methods, utilizing geometric deep learning and self-supervised learning, show improved accuracy and efficiency in predicting MHC-bound peptides, even outperforming conventional methods with significantly less data.
Prognostic Efficacy of the Albumin-Bilirubin Score and Treatment Outcomes in Hepatocellular Carcinoma: A Large-Scale, Multi-Center Real-World Database Study.
Liver Cancer
December 2024
Division of Liver Transplantation and Hepatobiliary Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Introduction: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality globally, with treatment outcomes closely tied to liver function. This study evaluates the prognostic utility of the albumin-bilirubin (ALBI) score compared to the traditional Child-Pugh (CP) grading, leveraging real-world evidence from a large-scale, multi-center database.
Methods: The Liver Cancer IN Korea (LINK) research network, a multi-center initiative, retrospectively collected electronic health records from three academic hospitals in South Korea, encompassing HCC patients diagnosed between 2015 and 2020.
An exploratory machine learning model for predicting advanced liver fibrosis in autoimmune hepatitis patients: A preliminary study.
Ann Hepatol
December 2024
Department of Dermatology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing 100700, China. Electronic address:
Introduction And Objectives: Advanced fibrosis is a crucial stage in the progression of autoimmune hepatitis (AIH), where fibrosis can either regress or advance. This study aims to leverage machine learning (ML) models for the assessment of advanced liver fibrosis in AIH patients using routine clinical features.
Patients And Methods: A total of 233 patients diagnosed with AIH and underwent liver biopsy were included in the discovery cohort.
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