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Kv2.1 regulates insulin secretion in human islets independent of it's electrical function

2011· article· en· W3173867194 on OpenAlexaff
Patrick E. MacDonald, Xiao Qing Dai, Greg Plummer, Marina Casimir, Jocelyn Manning Fox

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExocytosisSecretionDepolarizationCell biologySyntaxin 3IntracellularChemistryGranule (geology)InsulinMembrane potentialInternal medicineEndocrinologyIsletSyntaxinBiologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

The voltage-dependent K+ (Kv) channel Kv2.1 mediates a major portion of the K+ current contributing to β-cell action potential repolarization, and also interacts with exocytotic SNARE proteins including syntaxin 1A. We now show that Kv2.1 modulates β-cell exocytosis and insulin secretion independent of its role in conducting K+. Expression of a non-conducting Kv2.1 pore mutant (W365C/Y380T) directly augmented the exocytotic response of human β-cells assessed by whole-cell capacitance. Acute intracellular dialysis, or transient expression, of an intracellular C-terminal fragment of Kv2.1 (C1; amino acids 412–633) which disrupts the channel interaction with syntaxin 1A inhibited the exocytotic response to membrane depolarization by 70–79% (p<0.001), whereas distal C-terminal (C2; aa 634–853) or N-terminal (aa 1–182) fragments had no effect. The Kv2.1-C1 fragment also inhibited glucose-stimulated insulin secretion from human islets, but did not affect secretory granule localization to the plasma membrane. These findings demonstrate a role for Kv2.1 in insulin secretion, by facilitating insulin granule exocytosis independent of its K+ conductance.

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 score0.003

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 communication0.0010.000
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 head0.029
GPT teacher head0.252
Teacher spread0.223 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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