Cannabidiolic acid methyl ester, a stable synthetic analogue of cannabidiolic acid, can produce 5‐HT<sub>1A</sub> receptor‐mediated suppression of nausea and anxiety in rats
Bibliographic record
Abstract
Background and Purpose The aim of this study was to compare the abilities of cannabidiolic acid methyl ester (HU‐580) and cannabidiolic acid (CBDA) to enhance 5‐HT1A receptor activation in vitro and produce 5‐HT1A‐mediated reductions in nausea and anxiety in vivo. Experimental Approach We investigated the effects of HU‐580 and CBDA on (i) activation by 8‐hydroxy‐2‐(di‐n‐propylamino)tetralin of human 5‐HT1A receptors in CHO cell membranes, using [35S]‐GTPγS binding assays, (ii) gaping by rats in acute and anticipatory nausea models, and (iii) stress‐induced anxiety‐like behaviour, as indicated by exit time from the light compartment of a light–dark box of rats subjected 24 h earlier to six tone‐paired foot shocks. Key Results HU‐580 and CBDA increased the Emax of 8‐hydroxy‐2‐(di‐n‐propylamino) tetralin in vitro at 0.01–10 and 0.1–10 nM, respectively, and reduced signs of (i) acute nausea at 0.1 and 1 μg·kg−1 i.p. and at 1 μg·kg−1 i.p., respectively, and (ii) anticipatory nausea at 0.01 and 0.1 μg·kg−1, and at 0.1 μg·kg−1 i.p. respectively. At 0.01 μg·kg−1, HU‐580, but not CBDA, increased the time foot‐shocked rats spent in the light compartment of a light–dark box. The anti‐nausea and anti‐anxiety effects of 0.01 or 0.1 μg·kg−1 HU‐580 were opposed by the 5‐HT1A antagonist, WAY100635 (0.1 mg·kg−1 i.p.). Conclusions and Implications HU‐580 is more potent than CBDA at enhancing 5‐HT1A receptor activation, and inhibiting signs of acute and anticipatory nausea, and anxiety. Consequently, HU‐580 is a potential medicine for treating some nausea and anxiety disorders and possibly other disorders ameliorated by enhancement of 5‐HT1A 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".