Peptic Ulcer Disease

Tree-Guided Graph Neural Networks with Multilevel Optimization for Protein-Protein Interaction Prediction.

Predicting human-virus protein-protein interactions (PPI) is crucial for revealing viral infection and disease development. Graph neural networks serve as a powerful tool to identify potential PPIs. However, their performance is often compromised by topological disturbances caused by noise, which will reduce their ability to capture global and local pattern information. To address this limitation,...

Aspartame drives the continuous progression from MASLD to HCC.

BACKGROUND: Aspartame (APM), a widely used sweetener, has been linked to cancers, yet its molecular impact on metabolic dysfunction-associated steatotic liver disease (MASLD) and subsequent hepatocellular carcinoma (HCC) remains undefined. We integrated network toxicology, bulk RNA-seq and docking to map the mechanism. METHODS: APM targets were retrieved from ChEMBL, STITCH and SwissTargetPredicti...

Assessment of the accuracy and readability of artificial generative intelligence for patient questions on heavy menstrual bleeding.

OBJECTIVES: To evaluate the quality, patient-centeredness, clinician endorsement, and readability of generative artificial intelligence (AI) responses...

Is Nonpapillary Puncture a Feasible Alternative to Papillary Access in Percutaneous Nephrolithotomy? A Systematic Review and Meta-Analysis.

PURPOSE: Percutaneous nephrolithotomy (PCNL) is the gold standard for treating large and complex renal calculi, but puncture path selection (papillary...

Comparative diagnostic accuracy of image-enhanced endoscopy modalities and artificial intelligence-assisted endoscopy for gastric intestinal metaplasia and gastric dysplasia: protocol for a systematic review and diagnostic test network meta-analysis.

INTRODUCTION: Gastric intestinal metaplasia (GIM) and gastric dysplasia are critical precursors in the Correa cascade of gastric carcinogenesis. Altho...

Combined Effects and Potential Mechanisms of Multiple Metals Exposure on Coronary Artery Disease in the US Population: An Integrated Epidemiological and Network Toxicology Study.

Coronary artery disease (CAD) emerged as a major global health burden, but the relationship between multiple metals exposure and CAD and its toxicolog...

White cell - platelet ratio: A strong indicator for early mortality in liver cirrhosis patients with esophagogastric varices.

Esophagogastric varices (EGV) in liver cirrhosis patients within the intensive care unit (ICU) is a significant medical concern. This study aims to de...

Radiation scatter at fluoroscopy-guided endoscopic procedures: Building towards further optimization.

INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate...

Risk prediction models based on machine learning for emergence delirium in elderly patients undergoing spine surgery: development and validation study.

BACKGROUND: Emergence delirium (ED) is a common complication in elderly patients undergoing surgery for degenerative spinal disease (DSD) and is assoc...

Quinazolinone and Phthalazinone Inhibitors of the HDAC6/Ubiquitin Protein-Protein Interaction.

Histone deacetylase 6 (HDAC6) is a class IIb histone deacetylase that regulates diverse cytosolic acetylation through its two catalytic deacetylase do...

[A two-stage model for predicting postoperative pulmonary infection in esophageal cancer patients].

Postoperative pulmonary infection (PPI) after esophageal cancer surgery occurs frequently and severely impairs patients' prognosis. Most existing pred...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

State-of-the-art TinyML approaches for colorectal cancer detection: Current advances, challenges, and future directions.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with diagnostic disparities, particularly pronounced in resourc...

Implementation of a prospective video databank for artificial intelligence model development, validation and clinical outcomes research in gastrointestinal endoscopy.

BACKGROUND AND AIMS: High-quality, annotated datasets are fundamental to clinical research and artificial intelligence (AI) model development. Existin...

Integrated remote sensing and aeromagnetic datasets for mapping iron mineralization potential in the El-Bahariya depression in the Western Desert of Egypt.

The El-Bahariya depression in the Western Desert of Egypt is well-known for its iron ore deposits, with mineralization recorded in five well-known loc...

Artificial intelligence in endoscopic prediction of submucosal invasion in gastric neoplasms: systematic review and meta-analysis.

BACKGROUND: Accurate assessment of Submucosal (SM) invasion in gastric neoplasms is vital for curative endoscopic management, yet conventional endosco...

6PPD-quinone exposure and Alzheimer's disease: insights from integrative network pharmacology, transcriptomics, machine learning, and molecular docking.

OBJECTIVES: To systematically investigate the molecular associations between 6PPD-quinone (6PPD-Q), an environmental transformation product of the tir...

Intelligent Electrochemical Sensing: Machine Learning-Powered Multidimensional Fingerprinting for Simultaneous Detection of Six Antibiotics in Complex Matrices.

Antibiotic residues in environmental, food, and biological systems have become a serious global public health concern. Signal overlap occurs among str...

Combining Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation to Explore the Mechanism of Danggui-Shaoyao-San in treating Rheumatoid arthritis.

BACKGROUND: Danggui-Shaoyao-San (DSS) demonstrates clinical efficacy in rheumatoid arthritis (RA), but its bioactive constituents and molecular mechan...

Machine Learning-Based Prediction of Dental Caries in 12-Year-Old Adolescents: A Nationwide Cross-Sectional Study in Korea.

OBJECTIVE: We aimed to develop and evaluate machine learning models to support population-level risk stratification for dental caries in the permanent...