Ankle Joint Mobilization Decreases Hypersensitivity by Activation of Peripheral Opioid Receptors in a Mouse Model of Postoperative Pain
Bibliographic record
Abstract
OBJECTIVE: Investigate whether ankle joint mobilization (AJM) decreases hypersensitivity in the mouse plantar incision (PI) model of postoperative pain as well as to analyze the possible mechanisms involved in this effect. DESIGN: Experiment 1: PI male Swiss mice (25-35 g, N = eight animals per group) were subjected to five sessions of AJM, each lasting either 9 or 3 minutes. AJM movement was applied at a grade III as defined by Maitland. Paw withdrawal frequency to mechanical stimuli was assessed before realization of PI and before and after daily AJM sessions. Mechanical hypersensitivity was also assessed following systemic (intraperitoneal [i.p.]) and local (intraplantar) injection of naloxone (a nonselective opioid receptor antagonist; 1 mg/kg, i.p.; 5 µg/paw, respectively, experiment 2); and systemic injection of fucoidin (100 µg/mouse, i.p., an inhibitor of leukocyte rolling, experiment 3) in different groups of mice. RESULTS: Nine but not 3 minutes of AJM reduced mechanical hypersensitivity caused by PI, an effect that was prevented by systemic and local administrations of naloxone but not by fucoidin. CONCLUSIONS: Our results indicate that joint mobilization reduces postoperative pain by activation of the peripheral opioid pathway. However, antihypersensitivity induced by AJM is apparently not limited by the number of opioid-containing leukocytes but by opioid receptors availability in sensory neurons. A better understanding of the peripheral mechanisms of AJM could stimulate therapists to integrate joint mobilization with strategies also known to influence endogenous pain control, such as exercise, acupuncture, and transcutaneous electrical nerve stimulation to potentiate endogenous analgesia.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".