Awakening the [delta]ormant receptor : interactions between [mu] and [delta] opioid receptors in vitro and in vivo
Bibliographic record
Abstract
Opioid drugs acting at the mu opioid receptor (muOR), such as morphine, represent the most commonly prescribed analgesics for the clinical management of moderate to severe pain. However, the clinical use of muOR agonists is limited by the occurrence of undesirable effects such as respiratory depression and the tendency to produce tolerance and/or dependence with repeated administration. delta opioid receptor (deltaOR) activation produces antinociception with reportedly less deleterious effects when compared to muOR activation. However, animal studies have revealed that deltaOR-mediated antinociceptive effects are modest compared to muOR-elicited ones. Thus, we studied the regulation of deltaOR trafficking in the rodent central nervous system with the intention of modifying the density of this receptor at the cell surface and thereby improve deltaOR agonist potency. Stimulation with morphine for 48 hours produced increased deltaOR cell surface density both in vitro in primary cortical neurons in culture and in vivo in neurons within the dorsal horn of the spinal cord of rodents. This enhanced deltaOR cell surface density was a trafficking event and was not due to an overall increase in deltaOR expression. In vivo, the increased deltaOR cell surface density was accompanied with enhanced antinociceptive potency of intrathecally administered muOR agonists and augmented internalization of a fluorescent deltaOR agonist in the dorsal horn. This effect was observed following pretreatment with various muOR agonists and was abolished in muOR knock-out mice, demonstrating that activation of muOR was critical for enhanced targeting of deltaOR to neuronal plasma membranes and the observed increased antinociceptive responses. These changes in deltaOR function and subcellular localization were not associated with the development of tolerance to muOR agonists and were reversed 48 hours after the cessation of treatment with morphine. This muOR-induced enha
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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".