Prokineticin 2 and Cytokine Content in the Synovial Fluid of Knee Osteoarthritis and Traumatic Meniscal Tear Patients: Preliminary Results
Bibliographic record
Abstract
Knee osteoarthritis (OA) is a chronic degenerative inflammatory-based condition caused by a cascade of different intra-articular molecules including several cytokines. Among the cytokines, prokineticins (PKs) have recently been identified as important mediators of inflammation and pain. This observational study examined the potential involvement of PK2 in degenerative or traumatic knee disease. Fifteen patients presenting knee osteoarthritis (OA group) and 15 patients presenting a traumatic meniscal tear (TM group) were studied. Synovial fluid samples from affected knees were assessed for PK2, IL-10, and TNF-α using the ELISA method. At a long-term follow-up (minimum 5 years, mean = 6.1 years), patients in the TM group underwent clinical re-evaluation with PROMs (Tegner Activity Scale, IKDC, Lysholm, SKV); in addition, X-ray visualization was used to assess the presence of secondary OA. PK2 was detected in synovial fluids of both TM and OA patients and the levels were comparable between the two groups, while IL-10 levels were significantly greater in the OA group than those in TM patients. PK2 levels correlated with those of IL-10. PK2 levels were greater in blood effusions compared to clear samples, did not differ significantly between sexes, nor were they related to differences in weight, height, or injury (meniscal laterality, time since dosing). No correlation was found between PROMs and radiological classifications in patients in the TM group at final follow-up. These data are the first observations of PK2 in synovial fluid following traumatic meniscus injury. These findings suggest possible further prognostic indices and therapeutic targets to limit the development of secondary OA.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".