The type 1 cannabinoid receptor positive allosteric modulators GAT591 and GAT593 reduce spike-and-wave discharges in Genetic Absence Epilepsy Rats from Strasbourg
Bibliographic record
Abstract
Childhood absence epilepsy (CAE) is a non-convulsive seizure disorder primarily in children characterized by absence seizures. Absence seizures consist of 2.5–5 Hz spike-and-wave discharges (SWDs) detectable using electroencephalography (EEG). Current drug treatments are only partially effective and adverse side effects have spurred research into alternative treatment approaches. Recent research shows that positive allosteric modulation of the type-1 cannabinoid receptor (CB1R) reduces the frequency and duration of SWDs in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a model that recapitulates the SWDs in CAE. Here, we tested additional CB1R ago-PAMs, GAT591 and GAT593, for their potential in alleviating SWD activity in GAERS. In vitro experiments confirm that GAT591 and GAT593 exhibit increased potency and selectivity in cell cultures and behave as CB1R allosteric agonists and PAMs. To assess drug effects on SWDs, bilateral electrodes were surgically implanted in the somatosensory cortices of male GAERS and EEGs recorded for 4 h following systemic administration of GAT591 or GAT593 (1.0, 3.0 and 10.0 mg/kg). Both GAT591 and GAT593 dose-dependently reduced total SWD duration during the recording period. The greatest effect on SWD activity was observed at 10.0 mg/kg doses, with GAT591 and GAT593 reducing seizure duration by 36% and 34% respectively. Taken together, these results support the continued investigation of CB1R PAMs as a potential therapeutic to alleviate SWDs in absence epilepsy.
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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) | 0.001 | 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) | 0.002 | 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".