Effects of super-class cannabis terpenes beta-caryophyllene and alpha-pinene on zebrafish behavioural biomarkers
Bibliographic record
Abstract
Terpenes possess a wide range of medicinal properties and are potential therapeutics for a variety of pathological conditions. This study investigated the acute effects of two cannabis terpenes, β-caryophyllene and α-pinene, on zebrafish locomotion, anxiety-like, and boldness behaviour using the open field exploration and novel object approach tests. β-caryophyllene was administered in 0.02%, 0.2%, 2.0%, and 4% doses. α-pinene was administered in 0.01%, 0.02%, and 0.1% doses. As α-pinene is a racemic compound, we also tested its (+) and (-) enantiomers to observe any differential effects. β-caryophyllene had only a sedative effect at the highest dose tested. α-pinene had differing dose-dependent effects on anxiety-like and motor variables. Specifically, (+)-α-pinene and (-)-α-pinene had significant effects on anxiety measures, time spent in the thigmotaxis (outer) or center zone, in the open field test, as well as locomotor variables, swimming velocity and immobility. (+ /-)-α-pinene showed only a small effect on the open field test on immobility at the 0.1% dose. This study demonstrates that α-pinene can have a sedative or anxiolytic effect in zebrafish and may have different medicinal properties when isolated into its (+) or (-) enantiomers.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".