Role of voltage-gated calcium channels in epilepsy
Bibliographic record
Abstract
It is well established that idiopathic generalized epilepsies (IGEs) show a polygenic origin and may arise from dysfunction of various types of voltage- and ligand-gated ion channels. There is an increasing body of literature implicating both high- and low-voltage-activated (HVA and LVA) calcium channels and their ancillary subunits in IGEs. Cav2.1 (P/Q-type) calcium channels control synaptic transmission at presynaptic nerve terminals, and mutations in the gene encoding the Cav2.1 alpha1 subunit (CACNA1A) have been linked to absence seizures in both humans and rodents. Similarly, mutations and loss of function mutations in ancillary HVA calcium channel subunits known to co-assemble with Cav2.1 result in IGE phenotypes in mice. It is important to note that in all these mouse models with mutations in HVA subunits, there is a compensatory increase in thalamic LVA currents which likely leads to the seizure phenotype. In fact, gain-of-function mutations have been identified in Cav3.2 (an LVA or T-type calcium channel encoded by the CACNA1H gene) in patients with congenital forms of IGEs, consistent with increased excitability of neurons as a result of enhanced T-type channel function. In this paper, we provide a broad overview of the roles of voltage-gated calcium channels, their mutations, and how they might contribute to the river that terminates in 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".