Endocannabinoid‐related lipids are increased during an episode of cyclic vomiting syndrome
Bibliographic record
Abstract
BACKGROUND: The endocannabinoid system and the hypothalamic-pituitary-adrenal axis are important neuromodulators of nausea and vomiting. This led us to hypothesize that patients with cyclic vomiting syndrome (CVS) have lower serum endocannabinoids (eCBs) and higher salivary cortisol and alpha amylase. METHODS: Serum eCBs and related lipids, N-oleoylethanolamine (OEA) and N-palmitoylethanolamide (PEA), and salivary cortisol, and alpha amylase (index of sympathetic nervous system activity) were measured in 22 CVS patients (age 40 ± 11, female = 17) in the well and sick phases and 12 matched controls (age 37 ± 12, female = 10). KEY RESULTS: Contrary to our hypothesis, serum concentrations of the eCBs were not different among the study groups. However, serum concentrations of OEA and PEA were significantly higher during the sick than well phase in CVS patients (p = 0.001 and p = 0.04). There were positive correlations between serum PEA and nausea scores in the sick phase (Pearson's rho = 0.48, p = 0.036) and between serum OEA and poor sleep quality in patients (Pearson's rho = 0.7, p = 0.0005). Salivary cortisol and alpha amylase were not different between patients and controls, but subgroup analysis revealed that both were significantly higher in marijuana users compared to non-users during the sick phase (p = 0.04 and 0.03, respectively). CONCLUSIONS & INFERENCES: These data demonstrate that eCB-related lipids, OEA and PEA, are mobilized in the sick phase of CVS and are positively correlated with several of the symptoms of a CVS episode. These data also suggest the hypothesis that chronic marijuana use results in enhanced stress responses during CVS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".