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Bone & Joint Research
Vol. 10, Issue 8 | Pages 548 - 557
25 Aug 2021
Tao Z Zhou Y Zeng B Yang X Su M

Aims

MicroRNA-183 (miR-183) is known to play important roles in osteoarthritis (OA) pain. The aims of this study were to explore the specific functions of miR-183 in OA pain and to investigate the underlying mechanisms.

Methods

Clinical samples were collected from patients with OA, and a mouse model of OA pain was constructed by surgically induced destabilization of the medial meniscus (DMM). Reverse transcription quantitative polymerase chain reaction was employed to measure the expression of miR-183, transforming growth factor α (TGFα), C-C motif chemokine ligand 2 (CCL2), proinflammatory cytokines (interleukin (IL)-6, IL-1β, and tumour necrosis factor-α (TNF-α)), and pain-related factors (transient receptor potential vanilloid subtype-1 (TRPV1), voltage-gated sodium 1.3, 1.7, and 1.8 (Nav1.3, Nav1.7, and Nav1.8)). Expression of miR-183 in the dorsal root ganglia (DRG) of mice was evaluated by in situ hybridization. TGFα, CCL2, and C-C chemokine receptor type 2 (CCR2) levels were examined by immunoblot analysis and interaction between miR-183 and TGFα, determined by luciferase reporter assay. The extent of pain in mice was measured using a behavioural assay, and OA severity assessed by Safranin O and Fast Green staining. Immunofluorescent staining was conducted to examine the infiltration of macrophages in mouse DRG.


Bone & Joint Research
Vol. 9, Issue 10 | Pages 731 - 741
28 Oct 2020
He Z Nie P Lu J Ling Y Guo J Zhang B Hu J Liao J Gu J Dai B Feng Z

Aims

Osteoarthritis (OA) is a disabling joint disorder and mechanical loading is an important pathogenesis. This study aims to investigate the benefits of less mechanical loading created by intermittent tail suspension for knee OA.

Methods

A post-traumatic OA model was established in 20 rats (12 weeks old, male). Ten rats were treated with less mechanical loading through intermittent tail suspension, while another ten rats were treated with normal mechanical loading. Cartilage damage was determined by gross appearance, Safranin O/Fast Green staining, and immunohistochemistry examinations. Subchondral bone changes were analyzed by micro-CT and tartrate-resistant acid phosphatase (TRAP) staining, and serum inflammatory cytokines were evaluated by enzyme-linked immunosorbent assay (ELISA).


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.