Cannabidiol Exerts Anticonvulsant Effects Alone and in Combination with Δ9-THC through the 5-HT1A Receptor in the Neocortex of Mice
Bibliographic record
Abstract
Cannabinoids have shown potential in drug-resistant epilepsy treatment; however, we lack knowledge on which cannabinoid(s) to use, dosing, and their pharmacological targets. This study investigated (i) the anticonvulsant effect of Cannabidiol (CBD) alone and (ii) in combination with Delta-9 Tetrahydrocannabinol (Δ9-THC), as well as (iii) the serotonin (5-HT)1A receptor’s role in CBD’s mechanism of action. Seizure activity, induced by 4-aminopyridine, was measured by extracellular field recordings in cortex layer 2/3 of mouse brain slices. The anticonvulsant effect of 10, 30, and 100 µM CBD alone and combined with Δ9-THC was evaluated. To examine CBD’s mechanism of action, slices were pre-treated with a 5-HT1A receptor antagonist before CBD’s effect was evaluated. An amount of ≥30 µM CBD alone exerted significant anticonvulsant effects while 10 µM CBD did not. However, 10 µM CBD combined with low-dose Δ9-THC (20:3 ratio) displayed significantly greater anticonvulsant effects than either phytocannabinoid alone. Furthermore, blocking 5-HT1A receptors before CBD application significantly abolished CBD’s effects. Thus, our results demonstrate the efficacy of low-dose CBD and Δ9-THC combined and that CBD exerts its effects, at least in part, through 5-HT1A receptors. These results could address drug-resistance while providing insight into CBD’s mechanism of action, laying the groundwork for further testing of cannabinoids as anticonvulsants.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".