Coexpression of α<sub>2A</sub>‐adrenergic and δ‐opioid receptors in substance P‐containing terminals in rat dorsal horn
Bibliographic record
Abstract
Agonists acting at alpha(2)-adrenergic and opioid receptors (alpha(2)ARs and ORs, respectively) inhibit pain transmission in the spinal cord. When coadministered, agonists activating these receptors interact in a synergistic manner. Although the existence of alpha(2)AR/OR synergy has been well characterized, its mechanism remains poorly understood. The formation of heterooligomers has been proposed as a molecular basis for interactions between neuronal G-protein-coupled receptors. The relevance of heterooligomer formation to spinal analgesic synergy requires demonstration of the expression of both receptors within the same neuron as well as the localization of both receptors in the same neuronal compartment. We used immunohistochemistry to investigate the spatial relationship between alpha(2)ARs and ORs in the rat spinal cord to determine whether coexpression could be demonstrated between these receptors. We observed extensive colocalization between alpha(2A)-adrenergic and delta-opioid receptors (DOP) on substance P (SP)-immunoreactive (-ir) varicosities in the superficial dorsal horn of the spinal cord and in peripheral nerve terminals in the skin. alpha(2A)AR- and DOP-ir elements were colocalized in subcellular structures of 0.5 mum or less in diameter in isolated nerve terminals. Furthermore, coincubation of isolated synaptosomes with alpha(2)AR and DOP agonists resulted in a greater-than-additive increase in the inhibition of K(+)-stimulated neuropeptide release. These findings suggest that coexpression of the synergistic receptor pair alpha(2A)AR-DOP on primary afferent nociceptive fibers may represent an anatomical substrate for analgesic synergy, perhaps as a result of protein-protein interactions such as heterooligomerization.
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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 | 0.001 |
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".