Endocannabinoid signaling in stress, nausea, and vomiting
Bibliographic record
Abstract
BACKGROUND: Classical antiemetics that target the serotonin system may not be effective in treating certain nausea and vomiting conditions like cyclic vomiting syndrome (CVS) and cannabinoid hyperemesis syndrome (CHS). As a result, there is a need for better therapies to manage the symptoms of these disorders, including nausea, vomiting, and anxiety. Cannabis is often used for its purported antiemetic and anxiolytic effects, given regulation of these processes by the endocannabinoid system (ECS). However, there is considerable evidence that cannabinoids can also produce nausea and vomiting and increase anxiety in certain instances, especially at higher doses. This paradoxical effect of cannabinoids on nausea, vomiting, and anxiety may be due to the dysregulation of the ECS, altering how it maintains these processes and contributing to the pathophysiology of CVS or CHS. PURPOSE: The purpose of this review is to highlight the involvement of the ECS in the regulation of stress, nausea, and vomiting. We discuss how prolonged cannabis use, such as in the case of CHS or heightened stress, can dysregulate the ECS and affect its modulation of these functions. The review also examines the evidence for the roles of ECS and stress systems' dysfunction in CVS and CHS to better understand the underlying mechanisms of these conditions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".