Inflammatory Bowel Disease

Fecal and colonic microbiota differ in composition, function, diagnostic utility and correlation with inflammatory cytokines in ulcerative colitis.

Fecal samples have been frequently used to investigate ulcerative colitis (UC)-related gut microbiota study due to their easy availability. However, whether fecal microbiota accurately represents the mucosal microbiome of UC patients remains controversial. This study aims to analyze the gut microbiota in feces and colonic tissue, and to demonstrate from different perspectives whether the gut micro...

Investigating Immune Microenvironment of Inflammatory Bowel Disease and the Mitochondrial Metabolism-Related Molecular Mechanisms: Combining a Multiomics Approach and Experimental Validation.

Inflammatory bowel disease (IBD) is a chronic and recurrent gastrointestinal disease, the pathogenesis of which has not been fully elucidated. Increasing evidence suggests that the disorder of mitochondrial metabolism is closely related to the pathogenesis of IBD, but its specific regulatory network and key genes remain to be further investigated. IBD-related transcriptome datasets (GSE3365 and GS...

Heterogeneous developmental trajectories and predictors of self-harm in early adolescence: A machine learning study.

BACKGROUND: Although prior studies have examined developmental trajectories of adolescent self-harm in terms of frequency and severity, a fundamental ...

Machine learning-based identification of a metabolic cell death gene signature for assessing disease activity and immunological landscape in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is characterized by a refractory, relapsing inflammatory state driven by a multifaceted and poorly understood interpl...

Investigation of the molecular network underlying PET-MPs-induced inflammatory bowel disease via integrated machine learning and molecular docking approaches.

Polyethylene terephthalate microplastics (PET-MPs), as environmental contaminants, have raised significant concerns due to their potential toxicity, l...

Machine learning prediction of childhood nephrotic syndrome outcomes.

BACKGROUND: Children with steroid-resistant, frequently relapsing, and steroid-dependent nephrotic syndrome experience high disease and treatment-rela...

Comments on "Artificial Intelligence in Colonoscopy Surveillance for Lynch Syndrome: Emerging Evidence, Lessons Learned From Average-Risk Populations, and Future Directions".

Identification of Novel Diagnostic Biomarkers and Host-Directed Drug Screening for Mycobacterium avium Infection: A Multi-Omics and Artificial Intelligence Study.

OBJECTIVE: The rising incidence of Mycobacterium avium (MAV) infection poses significant challenges due to diagnostic delays and refractory treatment....

Mathematic and Computational Models for Osseointegration in Titanium Dental Implants: A Systematic Review of Current Approaches and Future Directions.

PURPOSE: To identify, compare, and critically evaluate the main mathematic and computational models used to study osseointegration in titanium (Ti) de...

IBDome: An integrated molecular, histopathological, and clinical atlas of inflammatory bowel diseases.

BACKGROUND & AIMS: Multi-omic and multimodal datasets with detailed clinical annotations offer significant potential to advance our understanding of i...

Development and External Validation of a Transcriptome-Based Multivariable Prediction Model for Treatment-Free Remission in Chronic Myeloid Leukemia.

PURPOSE: Treatment-free remission (TFR) is a major therapeutic objective in chronic myeloid leukemia (CML). However, nearly 50% of patients relapse af...

Multi-omics reveals fibroblast subtypes with distinct roles in inflammatory bowel disease.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract involving complex interactions among epi...

A Novel Blood-Based Screening Test for Colorectal Cancer Using Raman Spectroscopy.

BACKGROUND: Label-free vibrational spectroscopic techniques (Raman spectroscopy) combined with machine learning (ML) methodologies have huge potential...

Artificial intelligence in inflammatory bowel disease: From current evidence, clinical translation, and the road to precision medicine.

Artificial intelligence (AI) is rapidly transforming healthcare, supporting disease management and enabling outcome prediction across multiple clinica...

Neuroendocrine basis of affective behavior: what we can learn from differences in sex development (DSD).

Steroid hormones influence affective behavior and its underlying neural networks. However, distinguishing between organizational and activational horm...

Deep learning layer-specific collagen quantification correlates with activity and is associated with outcomes in Crohn's disease.

BACKGROUND & AIMS: Intestinal fibrosis remains a major unmet need in inflammatory bowel disease (IBD). Although collagen deposition is the defining fe...

Metabolomic machine learning predictor for the diagnosis of alcohol-associated liver disease.

BACKGROUND: It is urgent to find novel non-invasive biomarkers that can accurately diagnose alcohol-associated liver disease (ALD). The objective of t...

Integrated multi-omics and experimental validation reveal CSK and FBLN1 as key targets of stanozolol in accelerating atherosclerosis.

BACKGROUND: Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanism...

Impact of Availability of Computer-Aided Detection Devices on Adenoma Detection During Colonoscopy: A Cluster Randomized Study.

BACKGROUND AND AIMS: Endoscopists' colonoscopy adenoma detection rates (ADR) are inversely associated with their patients' risk of post-colonoscopy co...

Atopic dermatitis.

Atopic dermatitis (AD) is the most common inflammatory skin disease and carries the highest disability-adjusted life-years burden, ranking 15th among ...