Genetic Influences on Joint Contractures Secondary to Immobilization
Bibliographic record
Abstract
The primary research question of this study queries whether, beyond environmental conditions, genetic factors affect the development of joint contractures. We hypothesized that intrinsic genetic factors influence the severity of joint contractures developing secondary to joint immobilization. Forty rats from four inbred rat strains had one leg immobilized in knee flexion for 4 weeks. The contracture was measured mechanically as the lack of range of motion to a standardized torque. Using the contralateral leg as a control, the average severity of the contracture could be calculated and compared between strains. All immobilized legs presented knee contractures after 4 weeks of immobilization. Two strains (Dark Agouti and Fisher 344) showed a larger mean knee contracture than those of the two other rat strains (Augustus Copenhagen Irish and Brown Norway). Environmental factors, such as immobility, are usually identified as a cause of a joint contracture. These results demonstrate that, in addition to mechanical factors in the environment of a joint, intrinsic genetic factors participate in the process leading to joint contracture. This demonstration has important consequences for directing future research and may lead to interventions to help patients at risk of developing 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 | 0.000 | 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".