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Bone & Joint Research
Vol. 11, Issue 9 | Pages 639 - 651
7 Sep 2022
Zou Y Zhang X Liang J Peng L Qin J Zhou F Liu T Dai L

Aims

To explore the synovial expression of mucin 1 (MUC1) and its role in rheumatoid arthritis (RA), as well as the possible downstream mechanisms.

Methods

Patients with qualified synovium samples were recruited from a RA cohort. Synovium from patients diagnosed as non-inflammatory orthopaedic arthropathies was obtained as control. The expression and localization of MUC1 in synovium and fibroblast-like synoviocytes were assessed by immunohistochemistry and immunofluorescence. Small interfering RNA and MUC1 inhibitor GO-203 were adopted for inhibition of MUC1. Lysophosphatidic acid (LPA) was used as an activator of Rho-associated pathway. Expression of inflammatory cytokines, cell migration, and invasion were evaluated using quantitative real-time polymerase chain reaction (PCR) and Transwell chamber assay.


Bone & Joint Research
Vol. 12, Issue 2 | Pages 91 - 102
1 Feb 2023
Li Z Chen M Wang Z Fan Q Lin Z Tao X Wu J Liu Z Lin R Zhao C

Aims

Rheumatoid arthritis (RA) is a common chronic immune disease. Berberine, as its main active ingredient, was also contained in a variety of medicinal plants such as Berberaceae, Buttercup, and Rutaceae, which are widely used in digestive system diseases in traditional Chinese medicine with anti-inflammatory and antibacterial effects. The aims of this article were to explore the therapeutic effect and mechanism of berberine on rheumatoid arthritis.

Methods

Cell Counting Kit-8 was used to evaluate the effect of berberine on the proliferation of RA fibroblast-like synoviocyte (RA-FLS) cells. The effect of berberine on matrix metalloproteinase (MMP)-1, MMP-3, receptor activator of nuclear factor kappa-Β ligand (RANKL), tumour necrosis factor alpha (TNF-α), and other factors was determined by enzyme-linked immunoassay (ELISA) kit. Transcriptome technology was used to screen related pathways and the potential targets after berberine treatment, which were verified by reverse transcription-polymerase chain reaction (RT-qPCR) and Western blot (WB) technology.


Bone & Joint Research
Vol. 10, Issue 4 | Pages 285 - 297
1 Apr 2021
Ji M Ryu HJ Hong JH

Rheumatoid arthritis (RA) is an autoimmune disease characterized by symmetrical and chronic polyarthritis. Fibroblast-like synoviocytes are mainly involved in joint inflammation and cartilage and bone destruction by inflammatory cytokines and matrix-degrading enzymes in RA. Approaches that induce various cellular growth alterations of synoviocytes are considered as potential strategies for treating RA. However, since synoviocytes play a critical role in RA, the mechanism and hyperplastic modulation of synoviocytes and their motility need to be addressed. In this review, we focus on the alteration of synoviocyte signalling and cell fate provided by signalling proteins, various antioxidant molecules, enzymes, compounds, clinical candidates, to understand the pathology of the synoviocytes, and finally to achieve developed therapeutic strategies of RA.

Cite this article: Bone Joint Res 2021;10(4):285–297.


Bone & Joint Research
Vol. 9, Issue 8 | Pages 501 - 514
1 Aug 2020
Li X Yang Y Sun G Dai W Jie X Du Y Huang R Zhang J

Aims

Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method.

Methods

We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.


Bone & Joint Research
Vol. 9, Issue 9 | Pages 623 - 632
5 Sep 2020
Jayadev C Hulley P Swales C Snelling S Collins G Taylor P Price A

Aims

The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA).

Methods

Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.