Proteinase-activated Receptor-2 Gene Disruption Limits the Effect of Osteoarthritis on Cartilage in Mice: A Novel Target in Joint Degradation
Bibliographic record
Abstract
OBJECTIVE: Evidence indicates that proteinase-activated receptor (PAR)-2 participates in the degradative processes of human osteoarthritis (OA). We evaluated the in vivo effect of PAR-2 on articular lesions in a PAR-2-knockout (KO) mouse model of OA. METHODS: OA was surgically induced by destabilization of the medial meniscus of the right knee in C57Bl/6 wild-type (WT) and PAR-2 KO mice. Knee swelling was measured throughout the duration of the study (8 weeks postsurgery) and histologic evaluation of cartilage was done to assess structure, cellularity, matrix staining, and remodeling in the deep zone. Morphometric analysis of subchondral bone was also performed. RESULTS: Data showed significant knee swelling in the operated WT mice immediately following surgery, which increased with time (8 weeks post-surgery). Knee swelling was significantly lower (p ≤ 0.0001) in PAR-2 KO mice than in WT mice at both 4 and 8 weeks postsurgery. Cartilage damage was found in both operated WT and PAR-2 KO mice; however, lesions were significantly less severe (global score; p ≤ 0.05) in the PAR-2 KO mice at 4 weeks postsurgery. Operated WT mice showed reduced subchondral bone surface and trabecular thickness with significance reached at 4 weeks (p ≤ 0.03 and p ≤ 0.05, respectively), while PAR-2 KO mice demonstrated a gradual increase in subchondral bone surface with significance reached at 8 weeks (p ≤ 0.007). CONCLUSION: We demonstrated the in vivo implication of PAR-2 in the development of experimental OA, thus confirming its involvement in OA joint structural changes and reinforcing the therapeutic potential of a PAR-2 antagonist for treatment of OA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".