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Record W3092970864 · doi:10.3390/ijms21207602

A Common Kinetic Property of Mutations Linked to Episodic Ataxia Type 1 Studied in the Shaker Kv Channel

2020· article· en· W3092970864 on OpenAlexafffund
Juan Zhao, Dimitri Petitjean, Georges A. Haddad, Zarah Batulan, Rikard Blunck

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsShakerAtaxiaGatingXenopusBiophysicsMutationPotassium channelGeneticsChannelopathyMutantChemistryBiologyNeuroscienceGenePhysics

Abstract

fetched live from OpenAlex

gene encoding for the voltage-gated potassium channel Kv1.1. There have been many mutations in Kv1.1 linked to episodic ataxia reported and typically investigated by themselves or in small groups. The aim of this article is to determine whether we can define a functional parameter common to all Kv1.1 mutants that have been linked to episodic ataxia. (2) Methods: We introduced the disease mutations linked to episodic ataxia in the drosophila analog of Kv1.1, the Shaker Kv channel, and expressed the channels in Xenopus oocytes. Using the cut-open oocyte technique, we characterized the gating and ionic currents. (3) Results: We found that the episodic ataxia mutations variably altered the different gating mechanisms described for Kv channels. The common characteristic was a conductance voltage relationship and inactivation shifted to less polarized potentials. (4) Conclusions: We suggest that a combination of a prolonged action potential and slowed and incomplete inactivation leads to development of ataxia when Kv channels cannot follow or adapt to high firing rates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.042
GPT teacher head0.307
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2020
Admission routes2
Has abstractyes

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