Rheumatology

Artificial Intelligence Regulation in the United States: Current Landscape and Implications for Rheumatology.

Artificial intelligence (AI) is increasingly embedded in clinical tools used in rheumatology, including imaging interpretation, longitudinal disease monitoring, and electronic health record-based decision support. AI has moved from the periphery of biomedical research to an operational component of clinical care, increasingly embedded in electronic health records, imaging platforms, and decision s...

Adverse Pregnancy Outcomes in Women With Immune Abnormalities: Machine Learning Model Development and Validation Using First-Trimester Sonographic Features.

BACKGROUND: The maintenance and progression of pregnancy rely on immune homeostasis at the maternal-fetal interface. However, pregnancy complicated by autoimmune abnormalities can disrupt this balance and significantly increase the risk of adverse pregnancy outcomes (APOs). OBJECTIVE: This study aimed to (1) develop an interpretable predictive tool for APOs in patients with immune abnormalities an...

Recent advances in the molecular interactions of anti-cancer peptides with cellular targets.

Anti-cancer peptides (ACPs) selectively kill tumor cells through membrane disruption, intracellular target engagement, and immune activation. Recent s...

Tubulointerstitial Diseases: An Updated Framework for Diverse and Emerging Entities.

Tubulointerstitial diseases represent a heterogeneous group of kidney diseases with diverse causes and overlapping histopathologic and immunophenotypi...

E2F2 and TFDP1 as novel systemic lupus erythematosus (SLE) diagnostic markers and therapeutic targets based on machine learning and experimental study.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease influenced by multiple genetic and environmental factors.. This study u...

Ensemble learning-guided discovery of anti-tuberculosis phytochemicals: computational prediction and mechanistic insights.

Tuberculosis (TB) remains a major global health challenge driven by persistent Mycobacterium tuberculosis infection and increasing drug resistance. Ph...

State of the Art: Scapholunate Ligament Injuries.

ABSTRACT: Scapholunate ligament injuries are the most common ligamentous injuries of the wrist and typically result from high-energy trauma, most ofte...

Exploring anti-dengue activity with atomic-weighted vectors, class balancing and machine learning.

Dengue is a major mosquito-borne viral disease with no effective antiviral treatment currently available. This work introduces a machine-learning fram...

Piezochromic hydrogels for physically unclonable optical anti-counterfeiting with machine-learning assisted automatic identification.

Developing high-security anticounterfeiting with reliable authentication remains a significant challenge in preventing information leakage and economi...

NeuroPred-GMC: a dual-branch deep learning architecture for neuropeptide prediction based on gated dilated convolutional network and multi-scale convolutional network.

Neuropeptides are multifunctional signaling molecules in the nervous system. By modulating synaptic transmission and integrating physiological systems...

Deep learning-powered quantification of endocrine cells and CD3+ T cells in the natural history of type 1 diabetes.

AIMS/HYPOTHESIS: Histopathological analysis in type 1 diabetes presents challenges in achieving precise characterisation with cellular quantification ...

Prediction of SARS-CoV-2 exposure through T cell activation profiles.

In the ongoing effort to study the SARS-CoV-2 virus and COVID-19 disease, assessment of the T cell immune response has guided vaccine and therapeutic ...

Prognostic Imaging Biomarkers in Diabetic Macular Edema Treated with Anti-VEGF: A Multicenter AI Perspective.

INTRODUCTION: This study aimed to identify optical coherence tomography (OCT) biomarkers at baseline and after the loading phase (LP) of antivascular ...

Multimodal deep learning prediction of treatment response to anti-vascular endothelial growth factor in diabetic macular oedema.

OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth...

Cosine similarity analysis of venom proteomes of Indian cobras, Naja naja and Naja kaouthia reveals significant interspecies and geographic variations.

The Indian cobra (genus Naja) is one of the 'Big Fours' responsible for dreaded snakebite incidents in India. Immediate anti-snake venom (ASV) treatme...

Development and validation of a machine learning model to predict recurrence in polypoidal choroidal vasculopathy: a multicentre prospective study.

AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...

Imaging Biomarkers for Early Differentiation of Candida and Aspergillus Endogenous Fungal Endophthalmitis: Multicenter Optical Coherence Tomography-Based Analysis.

PURPOSE: Endogenous fungal endophthalmitis (EFE) is a rare, sight-threatening intraocular infection with heterogeneous clinical presentations. Candida...

Machine learning-based cardiovascular risk prediction in systemic lupus erythematosus: development and internal validation of a prognostic model.

BACKGROUND: Cardiovascular (CV) diseases are the leading cause of mortality in patients with systemic lupus erythematosus (SLE). While traditional ris...

Identification of COL5A1 and TGFBI as key basement membrane genes and their molecular mechanisms in gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, but the role of the basement membrane (BM) in GDM is not well understoo...

The melting properties of choline chloride in the representation of deep eutectic system phase diagrams.

Choline chloride (ChCl) is the cornerstone of deep eutectic solvents (DES), yet its melting properties remain an important source of uncertainty in th...