Association between changes in molecular biomarkers of cartilage matrix turnover and changes in knee articular cartilage: a longitudinal pilot study
Bibliographic record
Abstract
BACKGROUND: An early detection of Osteoarthritis is urgently needed and still not possible until today. The aim of the study was to assess whether molecular biomarkers of cartilage turnover are associated with longitudinal change in knee cartilage thickness during a 2 year period in individuals with increased risk of developing knee osteoarthritis. A secondary aim was to assess whether prior knee injury or subjective patient-reported outcomes at baseline (BL) were associated with articular cartilage changes. Nineteen volleyball players (mean age 46.5 ± 4.9 years, 47% male) with a 30-year history of regular high impact training were recruited. The serum biomarkers Cpropeptide of type II procollagen (CPII), cartilage oligomeric matrix protein (COMP), collagenase generated carboxy-terminal neoepitope of type II collagen (sC2C), cartilage intermediate layer protein 2 (CILP-2), and the urine biomarkers C-telopeptide of type II collagen (CTX-II) and collagenase-generated peptide(s) of type II collagen (C2C-HUSA) were assessed at BL and at 2 year follow up (FU). Femorotibial cartilage thinning, thickening and absolute thickness change between BL and FU was evaluated from magnetic resonance imaging. Subjective clinical status at BL was evaluated by the International Knee Documentation Committee Subjective Knee Form and the Short-Form 36 Physical Component Score. RESULTS: CILP-2 was significantly higher at FU and linearly associated with the absolute cartilage thickness change during the experimental period. Prior injury was a predictor of increased absolute cartilage thickness change. CONCLUSION: Measuring the change in the cartilage biomarker CILP-2 might be a valid and sensitive method to detect early development of knee osteoarthritis as CILP-2 appears to be related to cartilage thickness loss in certain individuals with increased risk of developing knee osteoarthritis. Prior knee injury may be predictive of increased articular cartilage thickness change.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".