Antihyperalgesic effects of δ opioid agonists in a rat model of chronic inflammation
Bibliographic record
Abstract
Opioid receptors in the brain activate descending pain pathways to inhibit the nociceptive response to acute noxious stimuli. The aim of the present study was to clarify the role of supraspinal opioid receptors in modulating the nociceptive response to persistent inflammation in rats. Subcutaneous administration of 50 microl of complete Freund's Adjuvant (CFA) into the plantar surface of the hindpaw induced a significant decrease in paw withdrawal latency to thermal stimuli (P<0.01) at 24 h post-injection. Intracerebroventricular (i.c.v.) administration of the mu opioid receptor agonists, DAMGO and morphine, and the delta opioid receptor agonists, deltorphin II and SNC80, significantly reversed the hyperalgesic response associated with peripheral inflammation in a dose-dependent manner (P<0.0001). The mu and delta agonists also significantly attenuated the antinociceptive response to acute thermal stimulation in rats (P<0.001). However, deltorphin II and SNC80 were less potent, and in the case of SNC80 less efficacious, in modulating the response to acute thermal nociception in comparison to hyperalgesia associated with persistent inflammation. These results indicate that mu and delta opioid receptors in the brain modulate descending pain pathways to attenuate the nociceptive response to acute thermal stimuli in both normal and inflamed tissues. The heightened response to delta agonists in the hyperalgesia model suggests that delta opioid receptors in the brain are promising targets for the treatment of pain arising from chronic inflammation.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".