CB1 Agonism Alters Addiction-Related Behaviors in Mice Lacking Mu or Delta Opioid Receptors
Bibliographic record
Abstract
Opioids are powerful analgesics but the clinical utility of these compounds is reduced by aversive outcomes, including the development of affective and substance use disorders. Opioid systems do not function in isolation so understanding how these interact with other neuropharmacological systems could lead to novel therapeutics that minimize withdrawal, tolerance, and emotional dysregulation. The cannabinoid system is an obvious candidate as anatomical, pharmacological, and behavioral studies point to opioid-cannabinoid interactions in the mediation of these processes. The aim of our study is to uncover the role of specific cannabinoid and opioid receptors in addiction-related behaviors, specifically nociception, withdrawal, anxiety, and depression. To do so, we tested the effects of a selective CB1 agonist, arachidonyl-2-chloroethylamide (ACEA), on mouse behavior in tail immersion, naloxone-precipitated withdrawal, light-dark, and splash tests. We examined cannabinoid-opioid interactions in these tests by comparing responses of wildtype (WT) mice to mutant lines lacking either Mu or Delta opioid receptors. ACEA, both acute or repeated injections, had no effect on nociceptive thresholds in WT or Mu knockout (KO) mice suggesting that analgesic properties of CB1 agonists may be restricted to chronic pain conditions. The opioid antagonist, naloxone, induced similar levels of withdrawal in all three genotypes following ACEA treatment, confirming an opioidergic contribution to cannabinoid withdrawal. Anxiety-like responses in the light-dark test were similar across WT and KO lines; neither acute nor repeated ACEA injections modified this behavior. Similarly, administration of the Delta opioid receptor antagonist, naltrindole, alone or in combination with ACEA, did not alter responses of WT mice in the light-dark test. Thus, there may be a dissociation in the effect of pharmacological blockade vs. genetic deletion of Delta opioid receptors on anxiety-like behavior in mice. Finally, our study revealed a biphasic effect of ACEA on depressive-like behavior in the splash test, with a prodepressive state induced by acute exposure, followed by a shift to an anti-depressive state with repeated injections. The initial pro-depressive effect of ACEA was absent in Mu KO mice. In sum, our findings confirm interactions between opioid and cannabinoid systems in withdrawal and reveal reduced depressive-like symptoms with repeated CB1 receptor activation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".