High Rate of Joint Capsule Matrix Turnover in Chronic Human Elbow Contractures
Bibliographic record
Abstract
The joint capsule is a key component in posttraumatic joint contractures. The capsule is described as thickened, but little data exist supporting the observation. Our hypotheses were that mRNA levels of (1) collagen; (2) decorin and biglycan; (3) matrix metalloproteinases; and (4) tissue inhibitors of matrix metalloproteinases were significantly elevated in anterior joint capsules obtained from 11 patients having surgery for posttraumatic contractures when compared with nine elbows, from organ donors, that were free of contractures. Reverse transcription-polymerase chain reaction was used to evaluate mRNA expression normalized to a housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase. In the joint capsules of the patients with elbow contractures, relative mRNA levels were increased for: collagen Types I, III, and V (1.5-2.5 times); biglycan (1.5 times); and matrix metalloproteinases-1, -2, -9, -13, and -15 (1.6-3.9 times). In contrast, expression of tissue inhibitors of matrix metalloproteinases-1, -2, and -4 were decreased (1/3-3/4 times) in the capsules of patients with contractures. There was no difference between the groups in relative mRNA expression for decorin, matrix metalloproteinases-8, -14 and -16, and tissue inhibitor of matrix metalloproteinase-3. The results indicate that joint capsule matrix molecule mRNA levels are altered in the chronic stages of posttraumatic elbow contractures in humans, potentially creating an environment with high matrix turnover rates.
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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".