Anti‐inflammatory effects of continuous passive motion on meniscal fibrocartilage
Bibliographic record
Abstract
Motion-based therapies have been applied to promote healing of arthritic joints. The goal of the current study was to determine the early molecular events that are responsible for the beneficial actions of motion-based therapies on meniscal fibrocartilage. Rabbit knees with Antigen-Induced-Arthritis (AIA) were exposed to continuous passive motion (CPM) for 24 or 48 h and compared to immobilized knees. The menisci were harvested and glycosaminoglycans (GAG), interleukin-1beta (IL-1beta), matrix metalloproteinase-1 (MMP-1), cyclooxygenase-2 (COX-2), and interleukin-10 (IL-10) were determined by histochemical analysis. Within 24 h, immobilized knees exhibited marked GAG degradation. The expression of proinflammatory mediators MMP-1, COX-2, and IL-1beta was notably increased within 24 h and continued to increase during the next 24 h in immobilized knees. Knees subjected to CPM revealed a rapid and sustained decrease in GAG degradation and the expression of all proinflammatory mediators during the entire period of CPM treatment. More importantly, CPM induced synthesis of the anti-inflammatory cytokine IL-10. The results demonstrate that mechanical signals generated by CPM exert potent anti-inflammatory signals on meniscal fibrochondrocytes. Furthermore, these studies explain the molecular basis of the beneficial effects of CPM observed on articular cartilage and suggest that CPM suppresses the inflammatory process of arthritis more efficiently than immobilization.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".