Gastroenterology

Integrated multi-omics analysis identifies and validates endoplasmic reticulum stress and mitophagy-related biomarkers in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Growing evidence indicates that endoplasmic reticulum stress (ERS) and mitophagy play critical roles in MASLD progression. However, the specific mechanism by which ERS and mitophagy participate in MASLD is not clear, and there is still a lack of treatment strategies for t...

Semi-Automatic Assessment of Crohn's Disease Activity by Combined Analysis of Bowel Lesions and Creeping Fat.

PURPOSE: To develop and evaluate Crohn-BOOST, an open-source tool enabling semi-automatic segmentation of intestinal lesions and creeping fat on magnetic resonance enterography (MR Enterography), and to assess whether quantitative metrics derived from these segmentations relate to radiological disease activity scored with simplified MaRIA (sMaRIA) and Nancy indices. A fully annotated MR Enterograp...

Integrating spatial lymph node patterns and multimodal clinicopathological features to predict post-neoadjuvant recurrence in gastric adenocarcinoma: a machine learning nomogram.

Combining AI to reveal CCDC3-mediated pathways of colorectal cancer liver metastasis.

In colorectal cancer liver metastases, chromosomal instability (CIN) serves as a critical hallmark linked to tumor aggressiveness and poor prognosis. ...

Exploring the molecular mechanism of Shenling baizhu formula in the treatment of ulcerative colitis via the cGMP-PKG signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by symptoms such as persistent diarrhea....

Overcoming gastrointestinal mucosal barriers: Mechanistic innovations and technical advances in mucosal targeting strategies for animal oral vaccines.

Infectious diseases caused by pathogenic microorganisms (such as Escherichia coli, Avian influenza virus (AIV), Rotavirus, etc.) that primarily invade...

Artificial intelligence assistance improves endoscopist accuracy for gastric cancer dysplasia and intestinal metaplasia.

Prediction of Massage Force and Intra-abdominal Wall Deformation During Massage by a Digital Twin Model Based on an Abdominal Finite Element Model.

PURPOSE: Constipation is a prevalent disorder of the digestive system, and abdominal massage is commonly employed to alleviate its symptoms due to its...

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication after liver transplantation (LT). This study aimed to...

A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICCA) is a rare but highly lethal adenocarcinoma arising within the hepatic parenchyma. Diagnosis present...

Utility of augmented reality in endoscopic surgery for stones: European Association of Urology endourology up-to-date review.

PURPOSE OF REVIEW: The development of digital solutions has a direct impact on the modern understanding of the future of urology. Augmented reality is...

BCLC classification and AI-based image quantification: What is meant to be will come together - but how and when?: BCLC and AI-based image quantification.

The Barcelona Clinic Liver Cancer (BCLC) classification has been the mainstay for prognostic assessment and initial treatment selection in hepatocellu...

A noninvasive model for predicting intrahepatic venovenous shunts before HVPG measurement: a multiple cohort study.

OBJECTIVES: This study aimed to construct a machine learning (ML) model to facilitate non-invasive identification of moderate-to-severe intrahepatic v...

Machine-learning with multiomics for radiotherapy-induced acute rectal toxicities and survival outcome in patients with cervical cancer.

Automatic Hepatic Steatosis Quantification using Low-Dose CT with deep learning-based noise reduction and CT Fat Fraction Analysis Software.

OBJECTIVES: To evaluate the accuracy of CT-derived fat fraction (CDFF) software for quantifying hepatic steatosis at various radiation doses, using MR...

Impact of Deep Learning-Based Time-of-Flight PET Images of Small Tumors Using a Human Anatomic Phantom.

Time-of-flight (ToF) in PET improves image quality by enhancing the signal-to-noise ratio, and recent deep learning (DL)-based ToF (DL-ToF) methods fu...

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage.

Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face ...

Cell-free DNA fragmentomes for noninvasive detection of liver cirrhosis and other diseases.

Accessible liquid biopsies, including analyses of genome-wide cell-free DNA (cfDNA) fragmentation, are emerging for early detection of cancer but rema...

Cell-free chromatin state tracing reveals disease origin and therapy responses.

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues1,2. These fragments carry r...

Technology-enabled insights into SLC transporters in MAFLD: redefining the multi-hit pathogenesis and therapeutic landscape.

Recent advances in structural biology, functional genomics, and artificial intelligence (AI) have expanded understanding of the solute carrier (SLC) t...