Peptic Ulcer Disease

Machine learning identifies KRT8 dysregulation and endothelial remodeling in Moyamoya disease.

Moyamoya disease (MMD) is a rare occlusive cerebrovascular disease, and its pathological mechanism remains unclear at present. The abnormal vascular remodeling may be involved in vascular endothelial cells. In this study, RNA seq was performed on the superficial temporal arteries of 10 patients with MMD. Integrated analysis was conducted by combining validation set with training set. Key genes wer...

Association between prenatal exposure to per- and polyfluoroalkyl substances and blood pressure among preschool-aged children: The moderating effect of child-age and the mediating effect of inflammatory cytokine.

Our aim is to evaluate the association of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with offspring blood pressure (BP); examine the moderating effect of children's age; and the mediating effects of inflammatory cytokines. Data of 215 mother-child pairs were collected from the Guangxi Zhuang birth cohort. Levels of nine PFAS were measured during pregnancy, and offspring BP was...

Ultrahigh-Throughput Virtual Screening Strategies against PPI Targets: A Case Study of STAT Inhibitors.

In recent years, virtual screening of ultralarge (10) libraries of synthetically accessible compounds (uHTVS) became a popular approach in hit identif...

Evolving Role of Artificial Intelligence in Endoscopic Management of Inflammatory Bowel Disease: Diagnosis, Surveillance, and Assessment.

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, presents substantial diagnostic and management challenges because ...

Identifying features of prior hemorrhage in cerebral cavernous malformations on quantitative susceptibility maps: a machine learning pilot study.

Features of new bleeding on conventional imaging in cerebral cavernous malformations (CCMs) often disappear after several weeks, yet the risk of reble...

Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer.

The development of bladder cancer (BLCA) is associated with mitochondrial dysfunction and neutrophil extracellular traps (NETs); however, the relation...

eNCApsulate: neural cellular automata for precision diagnosis on capsule endoscopes.

PURPOSE: Wireless capsule endoscopy (WCE) is a noninvasive imaging method for the entire gastrointestinal tract and is a pain-free alternative to trad...

Predicting semantic segmentation quality in laryngeal endoscopy images.

Endoscopy is a major tool for assessing the physiology of inner organs. Contemporary artificial intelligence methods are used to fully automatically l...

A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions.

In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy (CE), with the goal of improving the efficiency of...

Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, environmental factors, and lifestyle choices. With t...

A novel artificial intelligence-based system for quality monitoring during esophagogastroduodenoscopy: a multicenter randomized controlled study.

Esophagogastroduodenoscopy (EGD) is the pivotal procedure for diagnosis of upper gastrointestinal (UGI) lesions. However, significant variation in EGD...

Human protein interaction networks of ancestral and variant SARS-CoV-2 in organ-specific cells and bodily fluids.

Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infection is essential for developing effective COVID-19 a...

Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning.

Early detection of lung nodules (LNs) is critical for prevention and treatment of lung cancer. However, current noninvasive diagnostic methods face si...

Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.

This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction mod...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized by high metastatic potential and recurrence rates....

Artificial Intelligence in Gastrointestinal Endoscopy: The Japan Gastroenterological Endoscopy Society Position Statements.

Research and development of artificial intelligence (AI) in the field of gastrointestinal endoscopy is progressing rapidly. In Japan alone, there are ...

Machine-Learning Prediction of Bleeding After Endoscopic Submucosal Dissection for Early Gastric Cancer: A Multicenter Study.

BACKGROUND: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer (GC); however, post-ESD bleeding remains...

Deep learning for classification of aggressive versus non-aggressive central giant cell granuloma using whole-slide histopathology images.

Microscopic images of aggressive and non-aggressive cases of central giant cell granuloma (CGCG) were analyzed by deep learning algorithms in order to...

Safety of nonselective nonsteroidal anti-inflammatory drugs in cardiac surgery: a historical cohort study.

PURPOSE: Pain management after cardiac surgery is imperative, as inadequate analgesia can increase the risk of myocardial ischemia, thromboembolism, a...

Photocatalytic microrobots for treating bacterial infections deep within sinuses.

Microrobotic techniques are promising for treating biofilm infections located deep within the human body. However, the presence of highly viscous pus ...