Faculty Opinions recommendation of T-type calcium channel blockers that attenuate thalamic burst firing and suppress absence seizures.
Bibliographic record
Abstract
Absence seizures are a common seizure type in children with genetic generalized epilepsy and are characterized by a temporary loss of awareness, arrest of physical activity, and accompanying spike-and-wave discharges on an electroencephalogram. They arise from abnormal, hypersynchronous neuronal firing in brain thalamocortical circuits. Currently available therapeutic agents are only partially effective and act on multiple molecular targets, including γ-aminobutyric acid (GABA) transaminase, sodium channels, and calcium (Ca(2+)) channels. We sought to develop high-affinity T-type specific Ca(2+) channel antagonists and to assess their efficacy against absence seizures in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model. Using a rational drug design strategy that used knowledge from a previous N-type Ca(2+) channel pharmacophore and a high-throughput fluorometric Ca(2+) influx assay, we identified the T-type Ca(2+) channel blockers Z941 and Z944 as candidate agents and showed in thalamic slices that they attenuated burst firing of thalamic reticular nucleus neurons in GAERS. Upon administration to GAERS animals, Z941 and Z944 potently suppressed absence seizures by 85 to 90% via a mechanism distinct from the effects of ethosuximide and valproate, two first-line clinical drugs for absence seizures. The ability of the T-type Ca(2+) channel antagonists to inhibit absence seizures and to reduce the duration and cycle frequency of spike-and-wave discharges suggests that these agents have a unique mechanism of action on pathological thalamocortical oscillatory activity distinct from current drugs used in clinical practice. PMID: 22344687 Funding information This work was supported by: Canadian Institutes of Health Research, Canada Grant ID: 10677
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.345 | 0.206 |
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".