Paradoxical modulation of the pain reducing properties of morphine
Bibliographic record
Abstract
Classic pharmacological theories predict that opioid antagonists should block the neurochemical and behavioural effects of opioids. Surprisingly, this relationship does not hold true when the antagonist is administered in very low doses (i.e., nanograms instead of milligrams/kg). Coadministration of ultralow doses of naltrexone (antagonist) and morphine (agonist) enhanced morphine’s analgesic effects, which have been attributed to the activation of mu opioid receptors. Morphine inducedcatalepsy, characterized by muscular rigidity and inhibition of postural support systems, is also mediated by mu opioid receptors and can be blocked by standard doses of naltrexone. Our study investigated the hypothesis that ultralow doses of naltrexone will enhance morphineinduced catalepsy. Rats (N = 56) were randomly assigned to six different groups: saline, morphine (10 mg/kg), cotreatments of morphine (10 mg/kg) plus naltrexone (molar ratios of 1 000 000:1, 500 000:1 or 100 000:1) or naltrexone alone. For seven consecutive days, rats were administered one injection daily. Each day, catalepsy and analgesia were assessed 30 and 60 min post injection using the bartest and tailflick test, respectively. Ultralow doses of naltrexone coadministered with morphine did not potentiate catalepsy or attenuate tolerance. In contrast, ultralow doses of naltrexone coadministered with morphine significantly and dosedependently attenuated tolerance to morphine’s analgesic effect in comparison to morphine alone. These data suggest that the enhancement of opioid analgesic effects and attenuated tolerance by ultralow doses of opioid antagonists are not the result of changes in morphineinduced catalepsy. (Funded by NSERC)
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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".