Skip to content

Evaluation of TLR-2 Gene Expression and Its Association with Disease Activity in Iraqi Female Patients with Rheumatoid Arthritis

Oct 2026 · Israa University Journal for Applied Science · 0 citations
Rheumatoid Arthritis Research and Therapies

Abstract

Background: Rheumatoid Arthritis constitutes a long-lasting autoimmune inflammatory condition characterized by persistent synovial inflammation and progressive joint deterioration. Dysregulated immunological responses involved in the development and progression of the disease may be the result of a combination of hereditary predisposition and environmental variables, according to mounting evidence. Amis : This study set out to compare female RA patients to healthy controls in terms of Toll-like receptor-2 (TLR-2) mRNA expression and disease progression. Methods: From January to May of 2025, one hundred female participants took part in the study. Fifty of them were diagnosed with rheumatoid arthritis according to the 1987 American College of Rheumatology standards, and the other fifty were considered healthy controls. Laboratory tests and a rheumatological evaluation verified the clinical diagnosis. For the purpose of measuring TLR-2 transcript levels, blood samples were taken from each individual. RNA extraction, cDNA synthesis, and real-time PCR analysis were performed. Clinicopathological characteristics, including erythrocyte sedimentation rate (ESR), rheumatoid factor (RF), C-reactive protein (CRP), anti-cyclic citrullinated peptide (anti-CCP) antibody, and Disease Activity Score-28 (DAS28), were evaluated. Results: In contrast to controls, RA patients' TLR-2 gene expression was significantly upregulated (fold change: 2.52) compared to the former (1.01). A higher ESR, RF titer, CRP, anti-CCP antibody level, or DAS28 score was substantially linked to an increase in TLR-2 expression. Conclusions: There was a positive correlation between TLR-2 expression and inflammatory and disease activity indicators, and TLR-2 expression was considerably higher in RA patients. Based on these results, TLR-2 might be a useful biomarker for RA activity and development.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.