Cannabidiol Interferes with Establishment of Δ <sup>9</sup> -Tetrahydrocannabinol-Induced Nausea Through a 5-HT <sub>1A</sub> Mechanism
Bibliographic record
Abstract
Introduction: Cannabinoid hyperemesis syndrome (CHS) is characterized by intense nausea and vomiting brought on by the use of high-dose Δ 9 -tetrahydrocannabinol (THC), the main psychotropic compound in cannabis. Cannabidiol (CBD), a nonpsychotropic compound found in cannabis, has been shown to interfere with some acute aversive effects of THC. In this study, we evaluated if CBD would interfere with THC-induced nausea through a 5-HT 1A receptor mechanism as it has been shown to interfere with nausea produced by lithium chloride (LiCl). Since CHS has been attributed to a dysregulated stress response, we also evaluated if CBD would interfere with THC-induced increase in corticosterone (CORT). Materials and Methods: The potential of CBD (5 mg/kg, ip) to suppress THC-induced conditioned gaping (a measure of nausea) was evaluated in rats, as well as the potential of the 5-HT 1A receptor antagonist, WAY-100635 (WAY; 0.1 mg/kg, ip), to reverse the suppression of THC-induced conditioned gaping by CBD. Last, the effect of CBD (5 mg/kg, ip) on THC-induced increase in serum CORT concentration was evaluated. Results: Pretreatment with CBD (5 mg/kg, ip) interfered with the establishment of THC-induced conditioned gaping ( p =0.007, relative to vehicle [VEH] pretreatment), and this was reversed by pretreatment with 0.1 mg/kg WAY. This dose of WAY had no effect on gaping on its own. THC (10 mg/kg, ip) significantly increased serum CORT compared with VEH-treated rats ( p =0.04). CBD (5 mg/kg, ip) pretreatment reversed the THC-induced increase in CORT. Conclusions: CBD attenuated THC-induced nausea as well as THC-induced elevation in CORT. The attenuation of THC-induced conditioned gaping by CBD was mediated by its action on 5-HT 1A receptors, similar to that of LiCl-induced nausea.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".