Case studies in neuroscience: a novel amino acid duplication in the NH<sub>2</sub>-terminus of the brain sodium channel Na<sub>V</sub>1.1 underlying Dravet syndrome
Bibliographic record
Abstract
Dravet syndrome is a severe form of childhood epilepsy characterized by frequent temperature-sensitive seizures and delays in cognitive development. In the majority (80%) of cases, Dravet syndrome is caused by mutations in the SCN1A gene, encoding the voltage-gated sodium channel NaV1.1, which is abundant in the central nervous system. Dravet syndrome can be caused by either gain-of-function mutation or loss of function in NaV1.1, making it necessary to characterize each novel mutation. Here we use a combination of patch-clamp recordings and immunocytochemistry to characterize the first known NH2-terminal amino acid duplication mutation found in a patient with Dravet syndrome, M72dup. M72dup does not significantly alter rate of fast inactivation recovery or rate of fast inactivation onset at any measured membrane potential. M72dup significantly shifts the midpoint of the conductance voltage relationship to more hyperpolarized potentials. Most interestingly, M72dup significantly reduces peak current of NaV1.1 and reduces membrane expression. This suggests that M72dup acts as a loss-of-function mutation primarily by impacting the ability of the channel to localize to the plasma membrane. NEW & NOTEWORTHY Genetic screening of a patient with Dravet syndrome revealed a novel mutation in SCN1A. Of over 700 SCN1A mutations known to cause Dravet syndrome, M72dup is the first to be identified in the NH2-terminus of NaV1.1. We studied M72dup using patch-clamp electrophysiology and immunocytochemistry. M72dup causes a decrease in membrane expression of NaV1.1 and overall loss of function, consistent with the role of the NH2-terminal region in membrane trafficking of NaV1.1.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".