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Bone & Joint Research
Vol. 13, Issue 9 | Pages 513 - 524
19 Sep 2024
Kalsoum R Minns Lowe CJ Gilbert S McCaskie AW Snow M Wright K Bruce G Mason DJ Watt FE

Aims

To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design.

Methods

Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics.


Bone & Joint Research
Vol. 10, Issue 10 | Pages 677 - 689
1 Oct 2021
Tamaddon M Blunn G Xu W Alemán Domínguez ME Monzón M Donaldson J Skinner J Arnett TR Wang L Liu C

Aims

Minimally manipulated cells, such as autologous bone marrow concentrates (BMC), have been investigated in orthopaedics as both a primary therapeutic and augmentation to existing restoration procedures. However, the efficacy of BMC in combination with tissue engineering is still unclear. In this study, we aimed to determine whether the addition of BMC to an osteochondral scaffold is safe and can improve the repair of large osteochondral defects when compared to the scaffold alone.

Methods

The ovine femoral condyle model was used. Bone marrow was aspirated, concentrated, and used intraoperatively with a collagen/hydroxyapatite scaffold to fill the osteochondral defects (n = 6). Tissue regeneration was then assessed versus the scaffold-only group (n = 6). Histological staining of cartilage with alcian blue and safranin-O, changes in chondrogenic gene expression, microCT, peripheral quantitative CT (pQCT), and force-plate gait analyses were performed. Lymph nodes and blood were analyzed for safety.


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.