Spinal administration of a δ opioid receptor agonist attenuates hyperalgesia and allodynia in a rat model of neuropathic pain
Bibliographic record
Abstract
Neuropathic (NP) pain is a debilitating chronic pain disorder considered by some to be inherently resistant to therapy with traditional analgesics.Indeed, l opioid receptor (OR) agonists show reduced therapeutic benefit and their long term use is hindered by the high incidence of adverse effects.However, pharmacological and physiological evidence increasingly suggests a role for dOR agonists in modulating NP pain symptoms.In this study, we examined the antihyperalgesic and antiallodynic effects of the spinally administered dOR agonist, D-[Ala 2 , Glu 4 ]deltorphin II (deltorphin II), as well as the changes in dOR expression, in rats following chronic constriction injury (CCI) of the sciatic nerve.Rats with CCI exhibited cold hyperalgesia and mechanical allodynia over a 14-day testing period.Intrathecal administration of deltorphin II reversed cold hyperalgesia on day 14 and dose-dependently attenuated mechanical allodynia.The effects of deltorphin II were mediated via activation of the dOR as the effect was antagonized by cotreatment with the d-selective antagonist, naltrindole.Western blotting experiments revealed no changes in dOR protein in the dorsal spinal cord following CCI.Taken together, these data demonstrate the antihyperalgesic and antiallodynic effectiveness of a spinally administered dOR agonist following peripheral nerve injury and support further investigation of dORs as potential therapeutic targets in the treatment of NP pain.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".