I109. BONE MARROW LESIONS: CLINICAL OBSERVATIONS AND CORRELATION WITH TISSUE STUDIES
Bibliographic record
Abstract
Bone marrow lesions (BMLs) are well described in osteoarthritis (OA) and associate with pain but little is known about the structural and functional features of BMLs. Our primary aim was to evaluate BMLs using novel tissue analysis tools to gain a deeper understanding of how they mediate pain. We recruited 98 participants with advanced OA (n = 72) requiring total knee replacement (TKR), early OA subjects (n = 12) and non-OA controls (n = 14). Participants were assessed for clinical characteristics including pain and functional scores using the Western Ontario and MacMaster Universities Arthritis Index (WOMAC). Subjects were also evaluated for structural knee changes by knee magnetic resonance imaging (MRI) using a Philips 3T scanner. The degree of MRI structural damage was assessed by the MRI Osteoarthritis Knee Score (MOAKS). After full consent, knee joint tissue was harvested at the time of TKR for BML analysis using scanning electron microscopy (SEM), histology and tissue microarray. The mean (SD) WOMAC scores were advanced OA 1436.2 (471.6), early OA 797.4 (549.6) and controls 10.5 (12.6). SEM showed most normal bone marrow was adipocytic. Bone volume fraction was starkly reduced in BML areas, with marrow replaced by dense vascularized fibrous connective tissue, hyaline cartilage and fibrocartilage. Areas of aggressive resorption were found at the periphery of BML patches and regions of calcified cartilage formed deep within the bone. Infiltrates of amorphous tissue were also observed within BMLs. At the periphery of BMLs, there was evidence of new bone turnover with tidemark formation. Microarray of n = 24 samples from the OA BML group and controls showed 218 genes were significantly regulated compared with controls (p < 0.05). The most upregulated genes included genes involved in extracellular matrix turnover, neural development and wnt/Notch/catenin/chemokine signalling pathway molecules. Our study is the first to employ SEM and microarray techniques in one investigation to interrogate OA BMLs. BMLs demonstrated areas of high metabolic activity expressing neuronal, pain, extracellular matrix and pro-inflammatory signalling genes, explaining why they are strongly associated with pain. Disclosure statement: The author has declared no conflicts of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".