Rheumatology

SLA and DDX60L as potential diagnostic biomarkers for subclinical atherosclerosis in systemic lupus erythematosus: a transcriptomic and clinical validation study.

BACKGROUND: Systemic lupus erythematosus (SLE) patients face a 5-tenfold increased risk of atherosclerosis (AS), with subclinical lesions often progressing asymptomatically until life-threatening cardiovascular events occur. This study aimed to identify reliable molecular biomarkers for the early detection of SLE-associated AS. METHODS: Transcriptomic datasets (GSE154851 for SLE, GSE100927 for AS)...

Bufalin targets E2F2 to transcriptionally inhibit LINC01410 and suppress Wnt/β-catenin signaling in esophageal squamous cell carcinoma.

Bufalin, a main active monomer component extracted from the Traditional Chinese Medicine toad venom, exhibits potent anti-tumour activity across diverse malignancies. However, its specific molecular targets in Oesophageal squamous cell carcinoma (ESCC) remain unclear. Here, we demonstrate that bufalin suppresses ESCC growth and metastasis in a concentration-dependent manner both in vitro and in vi...

Dendrobine inhibits the growth and invasion of human breast cancer cells by regulating the NF-κB signaling pathway via the SLC6A9 target.

Dendrobine exhibits notable anti-tumor activity against breast cancer (BRCA). In this study, we integrated network pharmacology, bioinformatics, and e...

cGAS-STING pathway regulated by spatiotemporal heterogeneity of tumor microenvironment and precision therapy strategies in lung cancer.

The cGAS-STING pathway is a central regulator of innate immunity and exhibits a complex dual function in lung cancer: it can activate anti-tumor immun...

Remission, Relapse, and Thyroid-Related Parameters Measurement at Discontinuation of Low-Dose Anti-Thyroid Drugs in Graves' Disease.

BACKGROUND: This study aimed to elucidate the relationship between thyroid-related parameters and the prognosis of Graves' disease (GD). METHODS: This...

Artificial Intelligence-based Online Symptom Assessment Tools for Systemic Lupus Erythematosus (SLE) diagnosis: Patient Perspectives.

OBJECTIVE: The objective of this article is to identify perceptions of SLE patients regarding artificial intelligence (AI)-based online symptom assess...

Automatic choroid plexus assessment in SLE: a deep learning-enabled study.

PURPOSE: This study developed a deep learning model for automated choroid plexus (ChP) segmentation and examined its relationship with systemic inflam...

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...

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...