Ligamentous injury-induced ankle instability causing posttraumatic osteoarthritis in a mouse model
Bibliographic record
Abstract
BACKGROUND: This study aims to explore the relationship between surgically-induced ankle instability and posttraumatic osteoarthritis (PTOA) in a mouse model, and to provide reference for clinical practice. RESULTS: Ligamentectomy was performed on 24 eight-week-old male C57BL/6 J mice, which were divided into three groups. Both the anterior talofibular ligament (ATFL) and the calcaneofibular ligament (CFL) were severed in the CFL + ATFL group, while only the CFL was removed in the CFL group. The SHAM group was set as the blank control group. A wheel-running device was used to accelerate the development of ankle osteoarthritis (OA). Balance measurement, footprint analysis, and histological analysis were used to assess the degree of ankle instability and OA. According to the balance test results, the CFL + ATFL group demonstrated the highest number of slips and the longest crossing beam time at 8 weeks postoperatively. The results of gait analysis exhibited that the CFL + ATFL group had the most significant asymmetry in stride length, stance length, and foot base width compared to the CFL and SHAM groups. The OARSI score of the CFL + ATFL group (16.7 ± 2.18) was also much higher than those of the CFL group (5.1 ± 0.96) and the SHAM group (1.6 ± 1.14). CONCLUSION: Based on the mouse model, the findings indicate that severe ankle instability has nearly three times the chance to develop into ankle OA compared to moderate ankle instability.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".