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Record W3197892101 · doi:10.1073/pnas.2102036118

A second S4 movement opens hyperpolarization-activated HCN channels

2021· article· en· W3197892101 on OpenAlexafffund
Xiaoan Wu, Rosamary Ramentol, Marta E. Perez, Sergei Y. Noskov, H. Peter Larsson

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Calgary
FundersNational Institute of General Medical SciencesCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsHyperpolarization (physics)Movement (music)ChemistryPhysicsStereochemistryAcoustics

Abstract

fetched live from OpenAlex

channels, the fourth transmembrane segment S4 functions as the voltage sensor in hyperpolarization-activated HCN channels. But how the inward movement of S4 in HCN channels at hyperpolarized voltages couples to channel opening is not understood. Using voltage clamp fluorometry, we found here that S4 in HCN channels moves in two steps in response to hyperpolarizations and that the second S4 step correlates with gate opening. We found a mutation in sea urchin HCN channels that separate the two S4 steps in voltage dependence. The E356A mutation in S4 shifts the main S4 movement to positive voltages, but channel opening remains at negative voltages. In addition, E356A reveals a second S4 movement at negative voltages that correlates with gate opening. Cysteine accessibility and molecular models suggest that the second S4 movement opens up an intracellular crevice between S4 and S5 that would allow radial movement of the intracellular ends of S5 and S6 to open HCN channels.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.283
Teacher spread0.250 · 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

Citations18
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicIon channel regulation and functionFrench-language works237,207