Subchondral bone sclerosis in osteoarthritis: not just an innocent bystander
Bibliographic record
Abstract
Abstract Osteoarthritis (OA) is considered to be a complex illness in which the tissues of the joint play a significant role in the initiation and/or progression of the pathophysiology. We still do not completely understand what initiates the degradation and loss of cartilage. However, it has been suggested that increased catabolism due to elevated cytokines and growth factors in OA joints plays a significant role. Recent evidence suggests a key role for the subchondral bone tissue in the progression and/or initiation of OA. Indeed, the subchondral bone tissue produces a number of similar proinflammatory cytokines, and growth factors are involved in cartilage tissue remodeling. Interestingly, studies have shown the presence of clefts or channels in the tidemark that appears early in OA, indicating a possible way to traffic cytokines and growth factors from the subchondral compartment to the overlying cartilage. Therefore, it is possible that certain bone-derived products drive cartilage metabolism. Potential candidates include insulin-like growth factor-1 (IGF-1), transforming growth factor-β (TGF-β) interleukin 1β (IL-1β), and interleukin-6 (IL-6). Demonstrating that the subchondral bone plays a role in the initiation of OA would greatly contribute to furthering our knowledge of this pathology and provide new insights for therapeutic approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".