Antiseizure effects of the cannabinoids in the amygdala‐kindling model
Bibliographic record
Abstract
Abstract Objective Focal impaired awareness seizures (FIASs) are the most common seizure type in adults and are often refractory to medication. Management of FIASs is clinically challenging, and new interventions are needed for better seizure control. The amygdala‐kindling model is a preclinical model of FIASs with secondary generalization. The present study assessed the efficacy of cannabidiol (CBD), ∆9‐tetrahydrocannabinol (THC), and a combination of CBD and THC in a 15:1 ratio at suppressing focal and secondarily generalized seizures in the amygdala‐kindled rat. Methods Fully kindled, male Sprague Dawley rats, with bipolar electrodes implanted in the right amygdala, were given either CBD (0–320 mg/kg), THC (0–40 mg/kg), or a combination of CBD and THC (15:1 ratio, multiple doses) intraperitoneally. Suprathreshold kindling stimulation was administered 1 h (THC) or 2 h (CBD) after drug injection, and outcomes were assessed using focal electroencephalographic recording and the Racine seizure scale. Results CBD alone produced a partial suppression of both generalized seizures (median effective dose [ED 50 ] = 283 mg/kg) and focal seizures (ED 40 = 320 mg/kg) at doses that did not produce ataxia. THC alone also produced partial suppression of generalized (ED 50 = 10 mg/kg) and focal (ED 50 = 30 mg/kg) seizures, but doses of 10 mg/kg and above produced hypolocomotion, although not ataxia. The addition of a low dose of THC to CBD (15:1) left‐shifted the CBD dose–response curve, producing much lower ED 50 s for both generalized (ED 50 = 26 + 1.73 mg/kg) and focal (ED 50 = 40 + 2.66 mg/kg) seizures. No ataxia or hypolocomotion was seen at these doses of the CBD + THC combination. Significance CBD and THC both have antiseizure properties in the amygdala‐kindling model, although THC produces suppression of the amygdala focus only at doses that produce hypolocomotion. The addition of small amounts of THC greatly improves the effectiveness of CBD. A combination of CBD and THC might be useful for the management of FIASs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".