Augmentation of spinal morphine analgesia and inhibition of tolerance by low doses of <i>μ‐</i> and <i>δ</i>‐opioid receptor antagonists
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Ultralow doses of naltrexone, a non-selective opioid antagonist, have previously been found to augment acute morphine analgesia and block the development of tolerance to this effect. Since morphine tolerance is dependent on the activity of micro and delta receptors, the present study investigated the effects of ultralow doses of antagonists selective for these receptor types on morphine analgesia and tolerance in tests of thermal and mechanical nociception. EXPERIMENTAL APPROACH: Effects of intrathecal administration of mu-receptor antagonists, CTOP (0.01 ng) or CTAP (0.001 ng), or a delta-receptor antagonist, naltrindole (0.01 ng), on spinal morphine analgesia and tolerance were evaluated using the tail-flick and paw-pressure tests in rats. KEY RESULTS: Both micro and delta antagonists augmented analgesia produced by a sub-maximal (5 microg) or maximal (15 microg) dose of morphine. Administration of the antagonists with morphine (15 microg) for 5 days inhibited the progressive decline of analgesia and prevented the loss of morphine potency. In animals exhibiting tolerance to morphine, administration of the antagonists with morphine produced a recovery of the analgesic response and restored morphine potency. CONCLUSIONS AND IMPLICATIONS: Combining ultralow doses of micro- or delta-receptor antagonists with spinal morphine augmented the acute analgesic effects, inhibited the induction of chronic tolerance and reversed established tolerance. The remarkably similar effects of micro- and delta-opioid receptor antagonists on morphine analgesia and tolerance are interpreted in terms of blockade of the latent excitatory effects of the agonist that limit expression of its full activity.
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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) | 0.002 | 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".