Rheumatology

Rheumatoid Arthritis

Latest AI and machine learning research in rheumatoid arthritis for healthcare professionals.

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Showing 1081-1100 of 4,318 articles

Cerebral Organoids Uncover Mechanisms of Neural Activity Changes in Epileptogenesis

Neurological disorders often originate from progressive brain network dysfunctions that start years before symptoms appear. How these changes emerge in the developing human brain remains elusive due to a lack of tractable model systems. Here, we show a cerebral organoid model of Tuberous Sclerosis Complex (TSC) that recapitulates hallmarks of epileptogenesis in vitro. We compare extracellular reco...

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with in vivo efficacy

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3D conformation and decent binding mode in the pocket. We introduce SE3-BiLingoMol, an SE(3)-equivariant Transformer for pocket-based 3D molecule generation, addressing two key limitations of existing language-model approaches. First, it uses Geometri...

Ultrastructural Analysis of Human Uncinate Fasciculus with Spectral-Focusing Coherent Anti-Stokes Raman Spectroscopy

Characterizing the ultrastructure of myelin in the human brain is key to understanding the neurobiology of both health and disease. In postmortem huma...

A deep learning approach for rational affinity maturation of anti-VEGF nanobodies

Nanobodies offer several advantages over conventional antibodies due to their lower immunogenicity, enhanced stability, and superior tissue penetratio...

Screening of Oyster Peptides for Anti-Muscle Atrophy Based on Machine Learning and Computer Simulation: Guided by Antioxidant Pathways

Muscle atrophy poses a serious threat to human health, with its primary pathogenic mechanisms closely linked to oxidative stress. This study focuses o...

Integrated analysis implicates novel insights of NMB into lactate metabolism and immune response prediction in primary glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...

Hierarchical Machine Learning Uncovers Topological Signatures of Autophagy Regulation by Oral Bacteria in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) progression has been increasingly linked to dysbiosis of the oral microbiome. We hypothesized that pathogenic vers...

GenVS-TBDB: A Target-Aware AI-Generated and Virtual-Screened Small-Molecule Library for Tuberculosis Drug Discovery

Tuberculosis (TB) remains a leading global health threat, with over 10 million new cases and 1.25 million deaths reported in 2023. Current TB therapie...

The FERM Guild: A Differentially Correlated Microbial Module Drives Hypertension via Metabolic Flux Perturbations

Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota composition and function being closely associated with...

Deep learning inference of universal dormancy pseudotime reveals the cellular targets of anti-cancer therapies

Controlled exit from and re-entry into the cell cycle is essential for multi-cellular life, while aberrant quiescent and senescent cell states have be...

Modeling and Design of Multi-layered Cylindrical Microcapsules for Intravitreal Controlled Release

Chronic diseases often require repeated oral or local administration, which can compromise patient compliance. In wet age-related macular degeneration...

Retinal vascularization rate predicts retinopathy of prematurity and remains unaffected by low-dose bevacizumab treatment

To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor...

Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences

Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial ...

Corr-A-Net: Interpretable Attention-Based Correlated Feature Learning framework for predicting of HER2 Score in Breast Cancer from H&E Images

Human epidermal growth factor receptor 2 (HER2) expression is a critical biomarker for assessing breast cancer (BC) severity and guiding targeted anti...

Early Prediction of Anti-PD-1 Therapy Response in Hepatocellular Carcinoma Using Gut Microbiota Biomarkers

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, and response rates to anti-PD-1 therapy are suboptimal. Previous m...

AI-detected tumor-infiltrating lymphocytes for predicting outcomes in anti-PD1 based treated melanoma

Easy and accessible biomarkers to predict response to immune checkpoint inhibition (ICI)-treated melanoma are limited. To evaluate artificial intellig...

Evaluating anti-LGBTQIA+ medical bias in large language models

Large Language Models (LLMs) are increasingly deployed in clinical settings for tasks ranging from patient communication to decision support. While th...

Adapting Biomedical Foundation Models for Predicting Outcomes of Anti Seizure Medications

Epilepsy affects over 50 million people worldwide, with anti-seizure medications (ASMs) as the primary treatment for seizure control. However, ASM sel...

Serum metabolic signatures are associated with anti-drug antibody development in rheumatoid arthritis patients treated with adalimumab

Development of anti-drug antibodies (ADAs) is a barrier to long-term efficacy of biologic therapies in rheumatoid arthritis (RA), but no biomarkers ex...

Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart

Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease ...

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