Low threshold<scp>T</scp>‐type calcium channels as targets for novel epilepsy treatments
Bibliographic record
Abstract
Low voltage-activated T-type calcium channels were originally cloned in the 1990s and much research has since focused on identifying the physiological roles of these channels in health and disease states. T-type calcium channels are expressed widely throughout the brain and peripheral tissues, and thus have been proposed as therapeutic targets for a variety of diseases such as epilepsy, insomnia, pain, cancer and hypertension. This review discusses the literature concerning the role of T-type calcium channels in physiological and pathological processes related to epilepsy. T-type calcium channels have been implicated in pathology of both the genetic and acquired epilepsies and several anti-epileptic drugs (AEDs) in clinical use are known to suppress seizures via inhibition of T-type calcium channels. Despite the fact that more than 15 new AEDs have become clinically available over the past 20 years at least 30% of epilepsy patients still fail to achieve seizure control, and many patients experience unwanted side effects. Furthermore there are no treatments that prevent the development of epilepsy or mitigate the epileptic state once established. Therefore there is an urgent need for the development of new AEDs that are effective in patients with drug resistant epilepsy, are anti-epileptogenic and are better tolerated. We also review the mechanisms of action of the current AEDs with known effects on T-type calcium channels and discuss novel compounds that are being investigated as new treatments for 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".