Editorial: Emerging perspectives in sodium channelopathies
Bibliographic record
Abstract
Emerging perspectives in sodium channelopathiesRecent advances in molecular biology have greatly increased our understanding of ion channel structure and function.Cloning of genes encoding voltage-gated ion channels expanded the investigation of action potential signaling in neurons and muscle fibers.Gene sequences predicted the crucial role of positively charged residues in S4 segments as voltage sensors.Heterologous expression of channels, with mutagenesis, methane thiosulfonate reagent accessibility, and gating current experiments revealed details of the voltage-gating mechanism in sodium, potassium, and calcium channels.The identification of missense or truncation mutations in genes from patients with disorders of excitability, or channelopathies, led to their functional characterization, and expanded our understanding of the roles of diverse regions in channel function (reviewed by Cannon, 2006).The increasing number of channelopathy mutations identified and characterized as causing mixed gating defects, as well as channelopathies that promote mixed phenotypes, illustrates the challenge in the correlation of genotype to phenotype, and therefore the causality of dysfunction in channelopathy disorders.Prokaryotic sodium channels have yielded new insights into the mechanisms of channel function, with recent investigations providing detail into mechanisms of drug action and channelopathy dysfunction.Cystallographic and cryo-EM approaches have been increasingly important in the study of eukaryotic sodium channels, providing details of channel structure and enhancing computational approaches such as molecular dynamics.What has become clear is that there is no single mechanism of action for channelopathies and thus no one size fits all treatment for patients.Using diverse approaches to gain further understanding of specific genotype/phenotype relationships will facilitate more effective personalized treatment strategies that can greatly enhance patient outcomes.In this Research Topic issue, research articles on sodium channelopathies highlight advancements in our understanding of diseases of excitability, as well as the challenges inherent in bridging the gap in our knowledge of the relationship of genotype, channel dysfunction and patient phenotype.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.030 | 0.023 |
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".