Dissociable effects of ultralow-dose naltrexone on tolerance to the antinociceptive and cataleptic effects of morphine
Bibliographic record
Abstract
Ultralow-dose opioid antagonists augment the antinociceptive effect of morphine and block the development of tolerance to repeated morphine injections in rodents, but the effects are not reliably reproduced in humans. One explanation for this discrepancy is that preclinical studies of ultralow-dose antagonism in rodents generally use reflex-withdrawal tests of antinociception, which may be affected by cataleptic effects of morphine. We tested this hypothesis by examining whether ultralow-dose naltrexone alters the cataleptic effect of morphine or the development of tolerance to morphine-induced catalepsy. Rats (N=56) were randomly assigned to saline, morphine (10 mg/kg), cotreatments of morphine plus naltrexone (molar ratios of 1,000,000 : 1; 500,000 : 1; 100,000 : 1), or naltrexone-alone groups. Rats were injected with drug for 7 consecutive days; on each day, catalepsy and antinociception were assessed 30 and 60 min postinjection, using the bar and tail-flick tests, respectively. Ultralow-dose naltrexone (500,000 : 1) extended the antinociceptive effect of morphine within a session and attenuated the development of tolerance to the antinociceptive effect of morphine across sessions. Naltrexone alone had no effect on either test. These data show that the paradoxical effect of ultralow-dose naltrexone on antinociception is not the product of morphine-induced catalepsy, pointing to an important role for agonist-antagonist combinations in the clinical treatment of 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) | 0.002 | 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".