GERD

Ultrasound-assisted extraction for enhanced recovery and bioactivity of polyphenols from Tuber formosanum.

Tuber formosanum is a valuable edible and medicinal fungus, yet systematic research on the efficient and green extraction of its polyphenolic compounds remains limited. This study aims to establish an optimized ultrasound-assisted extraction (UAE) process for polyphenols from T. formosanum. UAE was conducted using a KS-700XDS power-adjustable ultrasonic bath at 50 kHz. Initially, UAE was validated...

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 mechanisms remain insufficiently characterized. PURPOSE: To elucidate the synergistic mechanisms of DSS in treating RA by integrating network pharmacology, machine learning, molecular docking, and dynamics simulations to identify core bioactive compounds a...

Multi-omics investigation of per- and polyfluoroalkyl substances in lung adenocarcinoma: comprehensive network toxicology, machine learning and molecular docking experiments.

Growing concerns regarding per- and polyfluoroalkyl substances (PFAS) as pervasive environmental contaminants have prompted increasing scrutiny regard...

Engineering the esophagus: advances, challenges, and translational pathways in esophageal tissue reconstruction.

Esophageal reconstruction is one of the most challenging procedures in gastrointestinal surgery. While conventional therapeutic approaches, such as ga...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...

Development and Validation of a Machine Learning Model for Predicting 30-Day Mortality and Early Endoscopic Hemostatic Intervention in Acute Upper Gastrointestinal Bleeding.

OBJECTIVE: Accurate pre-endoscopic risk stratification is essential in acute upper gastrointestinal bleeding (UGIB). Established scores predict mortal...

Global Research Trends and Thematic Evolution in Robotic Surgery for Obstructive Sleep Apnoea: A Bibliometric and Visualisation Study.

To systematically identify research trends, collaborative patterns, thematic developments and emerging areas of interest in the field of robotic surge...

Towards optimal valve prescription for transcatheter aortic valve replacement (TAVR) surgery: a machine learning approach.

Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a lif...

Mapping the scientific landscape of robotic hernia repair: a bibliometric and topic modeling analysis of thematic transitions.

Robotic hernia repair (RHR) has profoundly transformed modern surgery, yet it remains intensely debated. To understand this dynamic field, bibliometri...

Miniaturization in robotic surgery: a bibliometric and science mapping analysis of technological evolution and clinical translation (1996-2026).

Miniaturization has emerged as a major technological trajectory in robotic surgery, encompassing single-port systems, flexible endoscopic platforms, c...

Psychological adaptation to scaffolded generative AI use in higher education: SEM and thematic evidence from a private university's new media marketing course.

This study examines how students psychologically adapt to scaffolded generative artificial intelligence (GenAI) use in higher education. Drawing on th...

An Attention-Enhanced ViT-HLNN Hybrid Ensemble Framework for Multi-Class Gastrointestinal Disease Classification.

Gastrointestinal (GI) diseases such as polyps, esophagitis, and ulcerative colitis pose significant diagnostic challenges due to subtle visual pattern...

Large-scale transcriptomic data mining using explainable XGBoost and SHAP reveals shared biomarkers and molecular mechanisms between type-2 diabetes and triple-negative breast cancer for drug repurposing.

Type 2 diabetes (T2D) is considered as a risk factor of triple-negative breast cancer (TNBC). So, there is a significant chance of their co-existence....

Past, Present, and Future of Evaluating Diastolic Function.

The assessment of left ventricular diastolic function started with invasive pressure measurements and is currently primarily based on echocardiographi...

Automated extraction of colonoscopy quality indicators from free-text reports using a prompt-based large language model pipeline.

BACKGROUND AND AIMS: Artificial intelligence has increasingly enabled large-scale analysis of clinical documentation, offering new opportunities to im...

Integrated bioinformatics and machine learning for shared diagnostic genes and mechanisms between periodontitis and psoriasis.

BACKGROUND: Periodontitis and psoriasis are two prevalent conditions that are bidirectionally associated. However, the molecular basis remains poorly ...

Adaptive distribution-aware transformer for multi-scale visual representation learning on imbalanced and low-resolution data.

Deep learning models often struggle with class imbalance and low-resolution medical images, where critical spatial details and minority-class features...

Automated diagnosis of Helicobacter pylori infection from routine endoscopic images using deep learning: a development and validation study.

BACKGROUND: Real-time endoscopic diagnosis of Helicobacter pylori infection remains challenging and often requires biopsy-based testing, delaying trea...

Innovation and commercialization pathway in gastrointestinal endoscopy: a practical primer from American Society for Gastrointestinal Endoscopy.

Gastrointestinal endoscopy has undergone rapid technological evolution, yet many clinician innovators remain unfamiliar with the pathways required to ...

Advances in artificial intelligence for the evaluation of mitral regurgitation.

PURPOSE OF REVIEW: The diagnostic evaluation of mitral regurgitation (MR) is complex, time-intensive, and prone to significant interobserver variabili...