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Record W2136329025 · doi:10.1242/jcs.036970

Cx43 has distinct mobility within plasma-membrane domains, indicative of progressive formation of gap-junction plaques

2009· article· en· W2136329025 on OpenAlexaff
Jamie Simek, Jared M. Churko, Qing Shao, Dale W. Laird

Bibliographic record

VenueJournal of Cell Science · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsWestern University
Fundersnot available
KeywordsFluorescence recovery after photobleachingGap junctionPhotobleachingBiophysicsBiologyConnexinCell membraneCellCell biologyMembraneMembrane proteinFluorescenceIntracellularBiochemistry

Abstract

fetched live from OpenAlex

Connexin 43 (Cx43) is a dynamic molecule, having a short half-life of only a few hours. In this study, we use fluorescent-protein-tagged Cx43 variants to examine Cx43 delivery to the cell surface, its residency status in various cell-surface membrane domains and its mobility characteristics. Rapid time-lapse imaging led to the identification of Cx43 being delivered to cell-surface domains that lacked a contacting cell, and also to its localization within membrane protrusions. Fluorescence recovery after photobleaching (FRAP) was used to investigate the mobility state of cell-surface-localized Cx43. Cx43 mobility within clustered cell-surface profiles of Cx43 could be categorized into those with generally a high degree of lateral mobility and those with generally a low degree of lateral mobility. Cx43 mobility was independent of cluster size, yet the C-terminal domain of Cx43 regulated the proportion of gap-junction-like clusters that acquired a low Cx43 mobility state. Collectively, these studies show that Cx43 establishes residency at all cell-surface membrane domains, and progressively acquires assembly states that probably reflect differences in either channel packing and/or its interactions with Cx43-binding proteins.

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)0.000
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 score0.015
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.259
Teacher spread0.247 · 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

Citations45
Published2009
Admission routes1
Has abstractyes

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