CBD can be combined with additional cannabinoids for optimal seizure reduction and requires GPR55 for its anticonvulsant effects
Bibliographic record
Abstract
Abstract Background Cannabis has demonstrated anticonvulsant properties, and cannabis-based medicines are approved to treat pediatric patients with severe pediatric epilepsies that are particularly refractive to approved anti-epileptic drugs (AEDs). About thirty percent of epileptic patients do not have satisfactory seizure management with AEDs and could potentially benefit from cannabis-based intervention. Here we report the use of single and combined cannabinoids to treat Pentylenetetrazol (PTZ) induced convulsions in a zebrafish model, their effect on gene expression, and a simple assay for assessing their uptake in zebrafish tissues. These data provide novel insights as to the potential of treating epilepsy with cannabinoids. Methods Zebrafish larvae were treated with cannabinoids and their seizures measured through an optimized behaviour tracking method. Cannabinoid uptake was measured with a novel HPLC-UV method. Gene expression changes were assessed using quantitative PCR (qPCR), and chemical inhibitors of potential cannabinoid receptors were used to block activity. Results Treatment with cannabinol (CBN), cannabichromene (CBC) and cannabigerol (CBG) decreased seizure intensity at lower doses than CBD when accounting for the amount of cannabinoid recovered from exposed larvae. Δ 9 -tetrahydrocannabinol (Δ 9 -THC), Δ 8 -tetrahydrocannabinol (Δ 8 -THC) were effective at higher doses. Synergistic effects were observed between CBD and other cannabinoids such as Δ 9 -THC, Δ 8 -THC, and CBG. The reduction of PTZ induced seizures via CBD is partially mediated by the G-protein coupled receptor GPR55, as pharmacological inhibition of the receptor reduced the therapeutic action of CBD. Changes in expression of endocannabinoid system ( napepld, gde1, faah, ptgs2a ) and neural ( fosab, pyya ) genes in response to phytocannabinoid treatment were observed and highlight novel mechanisms of phytocannabinoid action. Conclusions CBD can be combined with additional cannabinoids for optimal reduction of seizure activity and requires the activity of GPR55. Changes in fosab regulation of gene expression and endocannabinoid signalling may influence the anticonvulsant effects of cannabis, however further investigation is required.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".