Receptor subtype-specific pronociceptive and analgesic actions of galanin in the spinal cord: Selective actions via GalR1 and GalR2 receptors
Bibliographic record
Abstract
Galanin is a 29-aa neuropeptide with a complex role in pain processing. Several galanin receptor subtypes are present in dorsal root ganglia and spinal cord with a differential distribution. Here, we describe a generation of a specific galanin R2 (GalR2) agonist, AR-M1896, and its application in studies of a rat neuropathic pain model (Bennett). The results show that in normal rats mechanical and cold allodynia of the hindpaw are induced after intrathecal infusion of low-dose galanin (25 ng per 0.5 microl/h). The same effect is seen with equimolar doses of AR-M1896 or AR-M961, an agonist both at GalR1 and GalR2 receptors. In allodynic Bennett model rats, the mechanical threshold increased dose-dependently after intrathecal injection of a high dose of AR-M961, whereas no effect was observed in the control or AR-M1896 group. No effect of either of the two compounds was observed in nonallodynic Bennett model rats. These data indicate that a low dose of galanin has a nociceptive role at the spinal cord level mediated by GalR2 receptors, whereas the antiallodynic effect of high-dose galanin on neuropathic pain is mediated by the GalR1 receptors. Thus, a selective GalR1 agonist may be used to treat neuropathic 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".