GERD

AI-guided integrative discovery of PD-1/PD-L1 interface inhibitors through multiscale modeling and experimental validation.

The PD-1/PD-L1 protein-protein interaction (PPI) is a critical immune checkpoint, and its inhibition represents a powerful strategy in oncology. Disrupting this macromolecular complex with small molecules remains a significant challenge. This study establishes a comprehensive pipeline for the discovery of novel in stock PD-1/PD-L1 inhibitors. We first developed a robust machine learning-based quan...

Cross-omics interpretable neural network for discovery of molecular markers in prostate cancer.

Determining molecular markers that mediate clinically aggressive phenotypes in prostate cancer is a significant challenge. While traditional linear models offer some interpretability, they often lack the precision needed for complex multi-omics data. Conversely, conventional deep learning methods provide robust predictions but typically remain opaque, hindering the identification of impactful mole...

Identification and validation of key autophagy-related genes in Lupus nephritis.

OBJECTIVES: Lupus nephritis (LN) is one of the most common complications of systemic lupus erythematosus. This study aimed to identify key autophagy-r...

Multi-omics integration identifies CACNG3 as a synaptic calcium channel regulator in Alzheimer's disease: Mechanistic insights and therapeutic implications.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and impaired daily functio...

AI Clinical Decision Tools in Multidisciplinary Team Discussions for Colorectal Cancer.

Multidisciplinary team (MDT) discussions have become a cornerstone of colorectal cancer (CRC) management, integrating the expertise of surgeons, oncol...

Shared inflammation in takotsubo syndrome and sepsis: Lipocalin-2 mediates neutrophil infiltration and cardiac damage.

BACKGROUND: Takotsubo syndrome (TTS) and sepsis often co-occur with poor outcomes, yet their underlying molecular mechanisms remain to be elucidated. ...

Targeting key proteins of pleural mesothelioma using plumbagin-indole-3-propionic acid ester: Insights from network pharmacology, molecular dynamics simulation and machine learning-based analysis.

This study explores the network pharmacology (NP) and molecular dynamics (MD) simulation analysis of pleural mesothelioma (PM) related enzymes. Throug...

Integrative machine learning reveals hidden and emerging co-regulatory gene networks for multi-phase glioblastoma outcome prediction.

BACKGROUND: Glioblastoma (GBM) is a highly prevalent and aggressive type of brain tumor characterized by profound molecular complexity and poor progno...

Label Noise in Pathological Segmentation Is Overlooked, Leading to Potential Overestimation of Artificial Intelligence.

Artificial intelligence (AI) has transformed medical imaging, notably in radiology and endoscopy. Semantic segmentation, a pixel-level technique cruci...

DSSA-PPI: enhancing binding affinity change prediction upon protein mutations using disentangled structure-sequence aware attention.

Accurate assessment of the effects of mutations on protein-protein interactions (PPIs) is crucial for understanding disease pathogenesis and the devel...

Same risk, different scales: outcome calibration and contour provenance in a 3D deep NTCP for dysphagia?

The global epidemiology of botulism outbreaks from open-source intelligence, 2017-2024.

BACKGROUND: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and ...

Identification of Individualised Aspiration Mechanisms in Post-Stroke Dysphagia: A VFSS-Based Interpretable Machine Learning Approach.

BACKGROUND: Post-stroke dysphagia (PSD) significantly increases the risk of aspiration-related pneumonia. While prior studies have linked abnormal tem...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Previous studies have reported comorbidity between M...

Interpretable machine learning for accessible dysphagia screening and staging in older adults.

Dysphagia in older adults causes serious complications, and efficient and scalable screenings are needed. This prospective multicenter study developed...

Artificial intelligence in endoscopy: a yet underused but promising tool in underserved settings.

Noninvasive detection and differentiation of gastric malignancy using cell-free DNA biomarkers.

INTRODUCTION: Gastric cancer remains a major global health burden, with high mortality driven by late-stage diagnoses that limit treatment options and...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close monitoring to guide therapy and evaluate treatment ...

Correction: Curriculum for safe and effective use of artificial intelligence in endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement.

Application of machine learning to create a prediction model for the need of aggressive nutritional intervention during head & neck cancer radiotherapy.

BACKGROUND: Curative-intent radiotherapy (RT) or chemoradiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC) frequently leads to mucosit...