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Record W3015674834 · doi:10.1073/pnas.1916166117

Determining the correct stoichiometry of Kv2.1/Kv6.4 heterotetramers, functional in multiple stoichiometrical configurations

2020· article· en· W3015674834 on OpenAlexafffund
Lena Möller, Glenn Regnier, Alain J. Labro, Rikard Blunck, Dirk J. Snyders

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaFonds Wetenschappelijk OnderzoekGovernment of Canada
KeywordsConcatemerProtein subunitDimerStoichiometryPotassium channelChemistryBiophysicsCell biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

The electrically silent (KvS) members of the voltage-gated potassium (Kv) subfamilies Kv5, Kv6, Kv8, and Kv9 selectively modulate Kv2 subunits by forming heterotetrameric Kv2/KvS channels. Based on the reported 3:1 stoichiometry of Kv2.1/Kv9.3 channels, we tested the hypothesis that Kv2.1/Kv6.4 channels express, in contrast to the assumed 3:1, in a 2:2 stoichiometry. We investigate the Kv2.1/Kv6.4 stoichiometry using single subunit counting and functional characterization of tetrameric concatemers. For selecting the most probable stoichiometry, we introduce a model-selection method that is applicable for any multimeric complex by investigating the stoichiometry of Kv2.1/Kv6.4 channels. Weighted likelihood calculations bring rigor to a powerful technique. Using the weighted-likelihood model-selection method and analysis of electrophysiological data, we show that Kv2.1/Kv6.4 channels express, in contrast to the assumed 3:1, in a 2:2 stoichiometry. Within this stoichiometry, the Kv6.4 subunits have to be positioned alternating with Kv2.1 to express functional channels. The variability in Kv2/KvS assembly increases the diversity of heterotetrameric configurations and extends the regulatory possibilities of KvS by allowing the presence of more than one silent subunit.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.396
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.295
Teacher spread0.217 · 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 teacher head, 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

Citations42
Published2020
Admission routes2
Has abstractyes

Explore more

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