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Record W2908303625 · doi:10.1073/pnas.1813161116

Conotoxin κM-RIIIJ, a tool targeting asymmetric heteromeric K <sub>v</sub> 1 channels

2018· article· en· W2908303625 on OpenAlexafffund
Sönke Cordeiro, Rocio K. Finol‐Urdaneta, David A. Köpfer, Anna Markushina, Jie Song, Robert J. French, Wojciech Kopeć, Bert L. de Groot, Mario J. Giacobassi, Lee S. Leavitt, Shrinivasan Raghuraman, Russell W. Teichert, Baldomero M. Olivera, Heinrich Terlau

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchNational Institute of General Medical SciencesGovernment of Canada
KeywordsHomomericIon channelProtein subunitBiophysicsChemistryPotassium channelConotoxinHeterologous expressionBiologyPopulationBiochemistryCell biologyPeptideRecombinant DNAReceptorGene

Abstract

fetched live from OpenAlex

Significance Most ion channels are multimeric (typically comprising 3–5 subunits). The subunits are encoded by homologous members of a gene family, generating an enormous set of possible heteromeric combinations. In this study, we provide evidence that the preferred target of conopeptide κM-RIIIJ is a heteromeric K v 1 channel consisting of three K v 1.2 subunits and one K v 1.1 or K v 1.6 subunit. We define the molecular interaction of κM-RIIIJ with these asymmetric K v 1 channels and show that in dorsal root ganglia (DRG) neurons, different κM-RIIIJ concentrations can distinguish discrete subpopulations of neurons. Our results highlight the potential of natural products and venom components, such as conopeptides, to generally elucidate native physiological roles of specific heteromeric ion channel isoforms at the cellular, circuit, and systems level.

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)0.001
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 score0.003
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.290
Teacher spread0.269 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicNicotinic Acetylcholine Receptors StudyFrench-language works237,207