Cannabis vapor self-administration elicits sex- and dose-specific alterations in stress reactivity in rats
Bibliographic record
Abstract
RATIONALE: Cannabis users frequently report stress relief as their primary reason for use. Recent studies indicate that human cannabis users exhibit blunted stress reactivity; however, it is unknown whether this is a cause or a consequence of chronic cannabis use. OBJECTIVES: To determine whether chronic cannabis vapor self-administration elicits sex- and/or dose-dependent alterations in stress reactivity and basal corticosterone (CORT) concentrations, or whether pre-vapor exposure stress reactivity predicts rates of cannabis vapor self-administration. METHODS: -tetrahydrocannabinol (THC) at one of four extract concentrations (0, 75, 150, or 300 mg/ml) daily for 30 days. Half of the rats were then subjected to a second restraint stress challenge 24 h after the final self-administration session, while the other half served as no-stress controls. Plasma CORT concentrations were measured prior to stress and immediately post-stress offset. RESULTS: Female rats earned significantly more vapor deliveries than male rats. Pre-vapor stress reactivity was not a predictor of self-administration rates in either sex. Basal CORT concentrations were increased following vapor self-administration relative to pre-vapor assessment, irrespective of treatment condition. Importantly, cannabis self-administration dose-dependently reduced stress reactivity in female, but not male, rats. CONCLUSIONS: These data indicate that chronic cannabis use can significantly dampen stress reactivity in female rats and further support the use of the cannabis vapor self-administration model in rats of both sexes.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".