Histopathological, biomechanical, and behavioral pain findings of Achilles tendinopathy using an animal model of overuse injury
Bibliographic record
Abstract
Animal models of forced running are used to study overuse tendinopathy, a common health problem for which clear evidence for effective and accessible treatments is still lacking. In these models, pain evaluation is necessary to better understand the disease, help design and evaluate therapies, and ensure humane treatment of the animals. Therefore, the main objective of this study was to evaluate pain and pathologic findings in an animal model of moderate Achilles tendinopathy induced by treadmill running. Air puffs, instead of electrical shocks, were used to stimulate running so that pain associated with stimulation would be avoided. Pressure pain sensitivity was evaluated in vivo using a new instrumented plier, whereas spinal cord peptides were analyzed ex vivo with high-performance liquid chromatography tandem mass spectrometry. Tendon histologic slides were semiquantitatively evaluated, using the Bonar score technique and biomechanical properties, using the traction test. After 8 weeks of treadmill running (2 weeks for adaptation and 6 weeks for the lesion protocol), the protocol was stopped because the air puffs became ineffective to stimulate running. We, nevertheless, observed some histologic changes characteristic of overuse tendinopathy as well as decreased mechanical properties, increased Substance P and dynorphin A peptides but without pressure pain sensitivity. These results suggest that air-puffs stimulation is sufficient to induce an early stage tendinopathy to study new therapeutic drugs without inducing unnecessary pain. They also indicate that pain-associated peptides could be related with movement evoked pain and with the sharp breakdown of the running performance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".