Tenocyte hypercellularity and vascular proliferation in a rabbit model of tendinopathy: contralateral effects suggest the involvement of central neuronal mechanisms
Bibliographic record
Abstract
OBJECTIVE: To determine whether there are objective findings of tendinosis in a rabbit tendinopathy model on exercised and contralateral (non-exercised) Achilles tendons. DESIGN: Four groups of six New Zealand white rabbits per group were used. The animals of one (control) group were not subjected to exercise/stimulation. INTERVENTIONS: Animals were subjected to a protocol of electrical stimulation and passive flexion-extension of the right triceps surae muscle every second day for 1, 3 or 6 weeks. MAIN OUTCOME MEASURES: Tenocyte number and vascular density were calculated. Morphological evaluations were also performed as well as in-situ hybridisation for vascular endothelial growth factor (VEGF) messenger RNA. RESULTS: There was a significant increase in the tenocyte number after 3 and 6 weeks of exercise, but not after 1 week, in comparison with the control group. This was seen in the Achilles tendons of both legs in experimental animals, including the unexercised limb. The pattern of vascularity showed an increase in the number of tendon blood vessels in rabbits that had exercised for 3 weeks or more, compared with those who had exercised for 1 week or not at all. VEGF-mRNA was detected in the investigated tissue, with the reactions being more clearly detected in the tendon tissue with tendinosis-like changes (6-week rabbits) than in the normal tendon tissue (control rabbits). CONCLUSIONS: There were bilateral tendinosis-like changes in the Achilles tendons of rabbits in the current model after 3 weeks of training, suggesting that central neuronal mechanisms may be involved and that the contralateral side is not appropriate as a control.
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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) | 0.000 | 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) | 0.002 | 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".