Gastroenterology

Key molecular mechanisms of mitochondrial metabolic pathways in specific cell subpopulations of pancreatic cancer based on scRNA-seq and bulk RNA-seq.

BACKGROUND: Pancreatic cancer (PC) is a highly malignant tumor with increasing incidence, mortality, and a low five-year survival rate. Mitochondrial metabolic reprogramming plays a crucial role in tumor development, but the molecular mechanisms in different cell subpopulations of PC remain unclear. This study aims to integrate single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq to explore mit...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effects in complex co-exposure scenarios and toxicological mechanisms remain incompletely elucidated. This cross-sectional study quantified 54 urinary environmental pollutants via mass spectrometry among 1036 participants from the Yinchuan elderly cohort...

SAP18 drives vasculogenic mimicry in esophageal squamous cell carcinoma: a machine learning and multi-omics investigation.

Vasculogenic mimicry (VM), a novel endothelial-independent blood perfusion pathway, is linked to advanced stage and poor prognosis in esophageal squam...

AI-Powered Deep Visual Proteomics Reveals Critical Molecular Transitions in Pancreatic Cancer Precursors.

UNLABELLED: Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs governing early progression remain poorly def...

Spatially Resolved Proteomic Cartography Illuminates the Earliest Molecular Programs in Pancreatic Cancer Evolution.

Min, Schweizer, and colleagues use artificial intelligence-powered deep visual proteomics to generate a spatial proteomic atlas of pancreatic cancer p...

The Promise of Machine Learning-Based Population Screening for Hepatocellular Carcinoma.

Clusmann and colleagues developed PRE-Screen-HCC, an interpretable machine learning framework that leverages multimodal clinical data from 2 populatio...

Machine learning phenotypes and heterogeneous albumin effects in cirrhotic AKI: a causal inference study.

Current guidelines recommend albumin infusion as a first-line treatment for acute kidney injury (AKI) in patients with cirrhosis. However, recent larg...

Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction.

OBJECTIVE: To determine the optimal low-keV level using deep learning image reconstruction (DLIR) that maximizes lesion detectability, and to assess t...

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers, with survival rates influenced by a variety of factors, including earl...

Development and validation of the AI-predictive ParaScout In-Vitro Diagnostic (IVD) system for the microscopic detection of gastro-intestinal helminths in stool.

AbstractThe comprehensive method to detect gastrointestinal infections is still microscopic examination of stool specimens. However, manual microscopi...

Machine learning-based detection of missed inspiratory efforts using esophageal pressure during noisy pressure support ventilation.

BACKGROUND: Missed inspiratory efforts represent one of the most frequent and clinically relevant forms of patient-ventilator asynchrony during assist...

TCEP Induces Liver Injury Through Suppression of the PI3K/AKT Axis: Integrated Evidence from Epidemiology, Network Toxicology, and In Vivo Validation.

Tris(2-chloroethyl) phosphate (TCEP) is a widely used chlorinated organophosphate flame retardant, but its role in liver injury remains unclear. In th...

Deep learning classification of nasal anatomical variants on computed tomography for endoscopic sinus surgery.

Endoscopic sinus surgery (ESS) carries risks such as vision loss and intracranial injury due to the proximity of critical structures and unrecognised ...

Impact of artificial intelligence intervention on awareness of anatomical landmarks in laparoscopic gastrectomy: An exploratory study.

BACKGROUND: We have developed gastric cancer/gastrectomy artificial intelligence (gAI) that leverages the tacit knowledge of experienced surgeons to v...

Decision tree-based prediction of 5-year weight trajectories after bariatric surgery in adolescents and young adults: a retrospective cohort study from France and Sweden.

BACKGROUND: Metabolic-bariatric surgery is an efficient therapy in selected adolescents with severe obesity. However, predicting the postoperative wei...

Integrated analysis of single-cell and bulk-RNA sequencing data reveals drug therapeutic targets and prognostic biomarkers related to ribosome biogenesis in hepatocellular carcinoma.

BACKGROUND: Ribosome biogenesis is involved in the progression of hepatocellular carcinoma (HCC), but the specific mechanisms and diagnostic values of...

Deep Learning-Based Reconstruction Improves Image Quality in Canine Cranial Abdominal MRI: A Prospective Pilot Study.

The application of deep learning-based reconstruction (DLR) to magnetic resonance imaging (MRI) has been recently introduced in human and veterinary m...

Machine-learning prediction of affinity and epistasis in the bovine pancreatic trypsin inhibitor-chymotrypsin complex.

Protein-protein interactions (PPIs) are shaped by evolutionary pressures that fine-tune binding affinities and drive the epistatic relationships that ...

How Does Artificial Intelligence-Assisted Endoscopy Impact Upper Gastrointestinal Screening?

Deep learning-based dose prediction for MR-guided prostate SIB: Supporting rapid feasibility assessment and adaptive editing margin selection.

BACKGROUND: The template-based treatment planning workflow in the Unity magnetic resonance-guided linear accelerator (MR-Linac) helps facilitate the t...