Optogenetic and Potassium Channel Gene Therapy in a Rodent Model of Focal Neocortical Epilepsy
Bibliographic record
Abstract
Neocortical epilepsy is frequently drug-resistant. Surgery to remove the epileptogenic zone is only feasible in a minority of cases, leaving many patients without an effective treatment. We report the potential efficacy of gene therapy in focal neocortical epilepsy using a rodent model in which epilepsy is induced by tetanus toxin injection in the motor cortex. By applying several complementary methods that use continuous wireless electroencephalographic monitoring to quantify epileptic activity, we observed increases in high frequency activity and in the occurrence of epileptiform events. Pyramidal neurons in the epileptic focus showed enhanced intrinsic excitability consistent with seizure generation. Optogenetic inhibition of a subset of principal neurons transduced with halorhodopsin targeted to the epileptic focus by lentiviral delivery was sufficient to attenuate electroencephalographic seizures. Local lentiviral overexpression of the potassium channel Kv1.1 reduced the intrinsic excitability of transduced pyramidal neurons. Coinjection of this Kv1.1 lentivirus with tetanus toxin fully prevented the occurrence of electroencephalographic seizures. Finally, administration of the Kv1.1 lentivirus to an established epileptic focus progressively suppressed epileptic activity over several weeks without detectable behavioral side effects. Thus, gene therapy in a rodent model can be used to suppress seizures acutely, prevent their occurrence after an epileptogenic stimulus, and successfully treat established focal 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".