Rabbit knee model of post‐traumatic joint contractures: The long‐term natural history of motion loss and myofibroblasts
Bibliographic record
Abstract
Our objective is to describe the natural history of motion loss with time and myofibroblast numbers in a rabbit knee model of post-traumatic joint contractures. Twenty-eight skeletally mature New Zealand White female rabbits had five-mm-squares of cortical bone removed from the medial and lateral femoral condyles of the right knee. A Kirschner wire (K-wire) was used to immobilize the knee joint in maximum flexion. A second operation was performed 8 weeks later to remove the K-wire. The rabbits were divided into four groups depending on the time of remobilization; 0, 8, 16 or 32 weeks. The average flexion contracture of the experimental knees in the 0-week and 8-week remobilization groups (38 degrees and 33 degrees, respectively) were significantly greater when compared with the values of the unoperated contralateral knees (8 degrees). The average flexion contractures of the experimental knees in the 16-week and 32-week remobilization groups were also greater than the unoperated contralateral knees, although they were not statistically significant. The average flexion contractures of the 16-week and 32-week groups were 19 degrees and 18 degrees, respectively, indicating a stabilization of the motion loss. Myofibroblast numbers in the posterior joint capsules were elevated 4-5x in the knees with contractures when compared to the contralateral knees. The initial decrease in severity followed by stabilization of motion loss and the association of motion loss with myofibroblasts mimics the human scenario of permanent post-traumatic joint contractures.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".