Contribution of peripheral and central delta opioid receptors in the relief of migraine‐like headache in female and male rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Preclinical studies in mice highlight delta opioid receptors (DOPs) as a potential migraine treatment. Here, we examined their role in a rat model of migraine in both sexes. EXPERIMENTAL APPROACH: We assessed DOP distribution in the trigeminal ganglion (TG) using RNAscope, the action of the DOP agonist SNC80 on facial mechanical sensitivity using von Frey hairs and responses of trigeminal nucleus caudalis wide dynamic range (WDR) neurons using in vivo electrophysiology, in physiological conditions and a migraine model induced by isosorbide dinitrate (ISDN) injections. KEY RESULTS: In naive rats, DOP mRNA was expressed by large-diameter myelinated NF200-positive TG neurons predominantly and by some CGRP peptidergic neurons, but rarely by IB4-binding nonpeptidergic unmyelinated neurons, with no sex difference. Intravenous SNC80 inhibited WDR neuron responses to noxious mechanical stimuli equally in both sexes. In acute conditions, SNC80 inhibited ISDN-induced MH in a dose-dependent manner equally in both sexes, through peripheral and central DOPs. After chronic administration of ISDN, the distribution of DOP mRNA increased in the TG of females only, specifically in NF200-positive neurons. Subcutaneous SNC80 reversed the interictal and, more in females than in males, the chronic ictal cephalic mechanical hypersensitivity, by acting through peripheral DOPs in females and through central DOPs in males. CONCLUSION AND IMPLICATIONS: DOP-mediated antimigraine effect is stronger in female than male rats and appears to be mediated in chronic conditions through peripheral DOPs in females and central DOPs in males. The results strengthen the relevance of using DOP agonists to treat migraine.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".