Assessing the bioactivity of cannabis extracts in larval zebrafish
Bibliographic record
Abstract
BACKGROUND: Whole-plant cannabis extracts are consumed by the public for medical and non-medical ("recreational") purposes but are poorly researched compared to pure cannabinoids. There is emerging evidence that cannabis extracts comprising complex mixtures of cannabinoids may have different biological effects from that of pure cannabinoids. In the current study, we sought to assess the effect of whole-plant cannabis extracts produced from different chemotypes of cannabis on the normal behavior of zebrafish larvae. METHODS: Three cannabis plant chemotypes were used in this study that contained either high amounts of THC, high amounts of CBD, high but equal amounts of THC and CBD, or low but equal amounts of THC and CBD. Following solvent extraction, liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) was performed for the detection and quantitation of target cannabinoids. Larval zebrafish behavioral models were subsequently used to assess the effect of the four different whole-plant cannabis extracts on the normal larval behavior using the DanioVision behavioral tracking systems and software. To compare, changes in the behavior activity levels for 30 min periods were compared to controls using 2-way ANOVA with multiple comparisons followed by a Bonferroni post hoc test. RESULTS: It was found that the whole-plant extracts that contained high levels of THC had similar effects on larval behavior, while the high CBD and low THC:CBD extracts produced distinct effects on normal larval behavior. Exposure of larvae to concentration-matched levels of THC and CBD found in the extracts revealed that a subset of the cannabis extracts tested had similar behavioral profiles to the pure cannabinoids while others did not. CONCLUSIONS: To our knowledge, this is the first study to test and compare the bioactivity of different whole-plant cannabis extracts in larval zebrafish. This work will provide a framework for future studies of distinct cannabis extracts and will be useful for comparing the bioactivity of extracts from different cannabis chemotypes as well as extracts made through various heating processes. It will also act as the first stage of assessment before testing the extracts against zebrafish models of toxicity and disease.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".