Rheumatology

Integrating machine learning-based molecular design with experimental validation for the discovery of EGFR inhibitors in lung cancer.

The emergence of drug resistance and off-target toxicities in epidermal growth factor receptor (EGFR) targeted therapies underscores the urgent need for novel inhibitor scaffolds. This study integrates artificial intelligence-driven generative models with experimental validation to discover novel, selective EGFR inhibitors. Utilizing REINVENT4, a reinforcement learning-based generative framework, ...

Phenotypic response surfaces in pharmacology: Mechanistic and translational perspectives on optimizing drug combination therapies.

Combination drug therapies are central to the treatment of diseases with multifactorial etiology, including cancer, infectious diseases, and autoimmune disorders. Despite their widespread use, optimizing drug combinations remains challenging because of complex pharmacokinetic and pharmacodynamic interactions and substantial inter-patient variability. Phenotypic Response Surfaces (PRS) have emerged...

Artificial intelligence literacy in fibromyalgia: The inverse gap between informed patients and unprepared clinicians.

A machine-learning-derived online screening tool for depressive symptoms in chronic digestive system diseases patients: a cross-sectional study with temporal validation from CHARLS.

Chronic digestive system diseases (CDSD) are common in older adults, and depressive symptoms are associated with poorer prognosis and quality of life....

Biofilm-mediated antibiotic tolerance in bacterial pathogens: Integrated molecular networks and novel therapeutic avenues.

The stable structure of biofilms and the characteristics of the bacteria within them make biofilms an important barrier for bacteria to resist externa...

Multi-cohort transcriptomic analysis with machine learning identifies interferon-related candidate genes in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with complex molecular mechanisms. Although transcriptomic studies have revea...

Comparing the Accuracy of ChatGPT-4o, DeepSeek-V3, and Gemini 2.5 Flash in Answering Frequently Asked Questions About Systemic Lupus Erythematosus: Quantitative Study.

BACKGROUND: Systemic lupus erythematosus (SLE) is a complex, fluctuating disease, creating a continuous need for reliable patient information. A prior...

A temporal-spectral dual-stream anti-noise bearing fault diagnosis model based on adaptive mode decomposition.

In recent years, deep learning-based bearing fault diagnosis models have achieved remarkable performance under ideal experimental conditions. However,...

Computational approaches for identifying quorum sensing inhibitors.

Quorum sensing (QS) is a critical cell-to-cell communication mechanism employed by microorganisms to coordinate their collective behaviors, including ...

Longitudinal serum uric acid transition patterns and their clinical, genetic, and dietary determinants: prospective prediction of incident hyperuricemia and gout in a Korean population-based cohort.

BACKGROUND: Longitudinal serum uric acid (SUA) transition patterns and their clinical, genetic, and dietary determinants remain poorly characterized. ...

An in-sensor communication electronic textile for imperceptible and ultrarobust silent speech.

Aphasiacs with impaired vocal organs suffer profound communication barriers, making silent speech decoding essential. Although audible speech is absen...

Clinical indicators associated with pericardial effusion in rheumatoid arthritis: a machine learning-based analysis.

BACKGROUND: Pericardial effusion (PE) is a frequent yet underdiagnosed complication of rheumatoid arthritis (RA), with substantial mortality risk. Nev...

Single-cell sequencing in systemic lupus erythematosus.

BackgroundSystemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by heterogeneous clinical manifestations and multi-organ in...

Integrating machine learning with QSPR for property prediction of anti-vertigo drugs.

Vertigo is a debilitating vestibular disorder affecting approximately 10-30% of the global population, yet no dedicated computational chemistry study ...

Bridging Generations: Leveraging Technology and Artificial Intelligence for Better Research, Outreach, and Daily Practice.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting hosted a workshop entitled "Bridging generatio...

EnAcrPred: A robust ensemble machine learning framework for identifying anti-CRISPR proteins.

The identification of anti-CRISPR proteins (Acrs) is crucial for understanding the regulation of CRISPR-Cas systems and their application in gene edit...

From Theory to Practice: Which Biomarkers Are Ready for Predicting Response in Advanced HCC?

Systemic therapies for advanced hepatocellular carcinoma (HCC) have expanded considerably with the advent of tyrosine kinase inhibitors, immune checkp...

Bioinformatics analysis identifies biomarkers associated with T-cell depletion in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects multiple organ systems. In SLE, T-cell subsets are closely associated ...

Identification of senescence-related biomarker for aortic dissection based on bioinformatics and machine learning algorithms.

Aortic dissection (AD) is a vascular surgical disease that seriously threatens human health. Due to a high misdiagnosis rate and unclear pathogenesis,...

A Multidimensional Integrated Strategy for Identifying Anti-thrombotic Quality Markers(Q-Markers) in Taohong Siwu Decoction through Combined Analysis of Chemical Profiling, Bioactivity, and Pharmacodynamic Efficacy.

ETHNOPHARMACOLOGICAL RELEVANCE: Taohong Siwu Decoction (TSD), originating from the Qing Dynasty medical text Gynecology Ice Mirror, is a representativ...