Correlation of prostaglandin E2 concentrations in synovial fluid with ground reaction forces and clinical variables for pain or inflammation in dogs with osteoarthritis induced by transection of the cranial cruciate ligament
Bibliographic record
Abstract
OBJECTIVE: To evaluate the temporal pattern of prostaglandin (PG) E2 concentrations in synovial fluid after transection of the cranial cruciate ligament (CCL) in dogs and to correlate PGE2 concentrations with ground reaction forces and subjective clinical variables for lameness or pain. ANIMALS: 19 purpose-bred adult male Walker Hounds. PROCEDURE: Force plate measurements, subjective clinical analysis of pain or lameness, and samples of synovial fluid were obtained before (baseline) and at various time points after arthroscopic transection of the right CCL. Concentrations of PGE2 were measured in synovial fluid samples, and the PGE2 concentrations were correlated with ground reaction forces and clinical variables. RESULTS: The PGE2 concentration increased significantly above the baseline value throughout the entire study, peaking 14 days after transection. Peak vertical force and vertical impulse significantly decreased by day 14 after transection, followed by an increase over time without returning to baseline values. All clinical variables (eg, lameness, degree of weight bearing, joint extension, cumulative pain score, effusion score, and total protein content of synovial fluid, except for WBC count in synovial fluid) increased significantly above baseline values. Significant negative correlations were detected between PGE2 concentrations and peak vertical force (r, -0.5720) and vertical impulse (r, -0.4618), and significant positive correlations were detected between PGE2 concentrations and the subjective lameness score (r, 0.5016) and effusion score (r, 0.6817). CONCLUSIONS AND CLINICAL RELEVANCE: Assessment of the acute inflammatory process by measurement of PGE2 concentrations in synovial fluid may be correlated with the amount of pain or lameness in dogs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".