Functional and spinal neuropeptidomic alterations in a new rat surgical model of osteoarthritic pain: A pilot study
Bibliographic record
Abstract
Background. Osteoarthritis is the leading cause of chronic joint pain, causing important productivity and economic losses. It is believed that peripheral and centralized sensitization play a role in the creation and maintenance of a chronic painful state. Different animal models have been employed for the investigation of pain mechanisms and evaluation of potential treatments, but none of them are ideal in terms of reproducibly, reliability and translational value. Methods. In the search for better animal model, this pilot study was performed with the goal of evaluating pain functional outcomes and spinal biomarkers between three surgical rat models of osteoarthritic pain, i.e. destabilization of the medial meniscus, cranial cruciate ligament transection and the combination of both, and comparing those results to the intra-articular injection of monosodium iodoacetate. Six rats were assigned to each model group and a Sham group. Static weight bearing, punctate tactile paw withdrawal threshold, and spinal neuropeptides (substance P, calcitonin gene-related peptide, bradykinin, and somatostatin) were evaluated for each group. Results. Both the monosodium iodoacetate and combination models induced functional alterations in static weight bearing and punctate tactile paw withdrawal threshold, the changes being more persistent in the combination group. Both also produced an increased release of pro-nociceptive and anti-nociceptive neuropeptides at different time-points. When surgical models were compared, the cranial cruciate ligament transection and destabilization of the medial meniscus models were less interesting, with temporary functional alterations, and no significant change in neuropeptides. Discussion. The surgical induction of osteoarthritis was accompanied by quantifiable neurophysiologic changes relating to non-physiologic pain. Comparison with the monosodium iodoacetate model showed that the interest of a surgical model, especially the combination of destabilization of the medial meniscus and cranial cruciate ligament transection, might reside in more persistent and progressive changes, a model that may represent better the human post-traumatic osteoarthritis.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".