Rheumatology

Research progress and clinical utility of multi-parameter orbital MRI in thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO), the most common orbital disease in adults, is a specific autoimmune condition closely associated with thyroid dysfunction, primarily affecting orbital fat and extraocular muscles. Multiparametric magnetic resonance imaging (MRI) holds unique value in diagnosing TAO, staging disease activity and progression evaluation by providing multidimensional informatio...

Strategy and efficiency-redefined discovery of novel nanomolar tyrosinase inhibitors: AI de novo molecular generation + expert-guided structural optimization.

Artificial intelligence (AI) has played an excellent supporting role in novel drug discovery and development. This study introduces a reinforcement learning (RL) model based on the Soft Actor-Critic (SAC) algorithm for AI-driven de novo molecular generation targeting tyrosinase. The model facilitates forward molecular generation design by integrating a chemical reaction template and a molecular bu...

The Role of Artificial Intelligence in Diagnosing and Monitoring Autoimmune Diseases: Can It Reduce the Disease Burden.

From Nutritional Epidemiology to Clinical Translation: Machine Learning Uncovers Antioxidant-Driven Prevention Strategies for Mitigating Cardiovascular-Arthritis Multimorbidity.

BACKGROUND: The aim of this study was to construct a machine learning (ML) model to predict the effect of dietary antioxidants on cardiovascular-arthr...

HERC5, IFI6, IFIT3, and OASL as potential diagnostic biomarkers for systemic lupus erythematosus: an integrated bioinformatics, machine learning and clinical validation.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a life-threatening autoimmune disorder causing multi-organ damage. Current diagnostic methods are hi...

A nomogram model integrating ultrasound-based multimodal radiomics features and clinical indexes for diagnosing significant hepatic fibrosis in AILD patients.

OBJECTIVE: To develop a prediction model combining radiomics features from 2D ultrasound (2D-US) and shear wave elastography (SWE) with clinical indic...

HGAlign: Biologically preserving batch correction and classification for metabolomics via heterogeneous graph alignment.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) is a powerful tool for profiling complex biological samples. However, large-s...

Exploring Patients' Profiles Associated With the Resolution of Acute Calcium Pyrophosphate Arthritis Treated With Colchicine and Prednisone: Post Hoc Analysis of a Randomized Controlled Trial.

OBJECTIVE: The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyr...

Identification of alkaline phosphatase as a putative biomarker of anti-NGF treatment-associated arthropathies: Machine learning-assisted analyses of clinical trial data.

OBJECTIVE: Nerve growth factor (NGF) inhibitors have been shown to provide pain relief in patients with osteoarthritis but are associated with adjudic...

Deciphering the rules of regulated cell death subroutines by in silico methods.

BACKGROUND: Regulated cell death (RCD) is essential for organismal development, as it plays key roles in organ formation, pathogen defense, and the ma...

Revealing the anti-tumor mechanisms of aromatic oil from Amomum villosum through integrated network pharmacology, bioinformatics, machine learning, single-cell sequencing, and cell experiments.

The dry fruits of Amomum villosum (Av) are a traditional Chinese medicine used for gastrointestinal disease. Aromatic oil has been reported to have an...

Amentoflavone from Ginkgo biloba inhibits EMT-driven lung cancer metastasis by targeting TGFBR2: Integrative network pharmacology, machine learning, and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: In non-small cell lung cancer (NSCLC), fatal outcomes predominantly result from metastatic dissemination, highlighting...

AI-generated patient education for ankylosing spondylitis: a comparative study of readability and quality.

OBJECTIVE: To evaluate and compare the quality and readability of patient education materials (PEM) related to ankylosing spondylitis (AS) generated b...

Multifactor machine learning models for predicting urinary tract infections: a pilot study.

PURPOSE: Vitamin D, a fat-soluble prohormone essential for calcium-phosphate homeostasis and bone health, also regulates innate and adaptive immunity ...

CoREST complex inhibition alters RNA splicing to promote neoantigen expression and enhance tumor immunity.

Epigenetic macromolecular enzyme complexes tightly regulate gene expression at the chromatin level and have recently been found to colocalize with RNA...

Integrating education-based interventions and machine learning for stunting prevention: A case study in East Lombok, Indonesia.

One of the regions in Indonesia that has the highest prevalence of stunting cases is West Nusa Tenggara, with a percentage of cases almost reaching 12...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, psoriatic arthritis, and systemic lupus erythematosus...

Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinical heterogeneity. Traditional single-analyte bi...

Deep learning based CT grading system for sacroiliitis: a multi-center studydemonstrating superior accuracy and efficiency compared to human readers.

BACKGROUND: To develop and validate a deep convolutional neural network (DCNN) for automated sacroiliitis grading in axial spondyloarthritis (axSpA) u...

Building a Quantitative Telemedicine Platform for Myasthenia Gravis: Augmenting the Physical Examination.

Myasthenia gravis (MG), a fluctuating autoimmune neuromuscular disease, presents unique challenges for remote assessment due to its reliance on detail...