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Record W2903987408 · doi:10.1242/jcs.224097

The connexin 30 A88V mutant reduces cochlear gap junction expression and confers long-term protection against hearing loss

2018· article· en· W2903987408 on OpenAlexafffund
John J. Kelly, Julia M. Abitbol, Stephanie Hulme, Eric R. Press, Dale W. Laird, Brian L. Allman

Bibliographic record

VenueJournal of Cell Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMutantCochleaHearing lossBiologyHair cellInner earCell biologyGap junctionGeneGeneticsAudiologyAnatomyMedicine

Abstract

fetched live from OpenAlex

ABSTRACT Mutations in the genes that encode the gap junction proteins connexin 26 (Cx26, encoded by GJB2) and Cx30 (GJB6) are the leading cause of hereditary hearing loss. That said, the Cx30 p.Ala88Val (A88V) mutant causes Clouston syndrome, but not hearing loss. Here, we report that the Cx30-A88V mutant, despite being toxic to inner ear-derived HEI-OC1 cells, conferred remarkable long-term protection against age-related high frequency hearing loss in Cx30A88V/A88V mice. During early development, there were no overt structural differences in the cochlea between genotypes, including a normal complement of hair cells; however, the supporting cell Cx30 gap junction plaques in mutant mice were reduced in size. In adulthood, Cx30A88V/A88V mutant mice had a reduction of cochlear Cx30 mRNA and protein, yet a full complement of hair cells. Conversely, the age-related high frequency hearing loss in Cx30+/+ and Cx30+/A88V mice was due to extensive loss of outer hair cells. Our data suggest that the Cx30-A88V mutant confers long-term hearing protection and prevention of hair cell death, possibly via a feedback mechanism that leads to the reduction of total Cx30 gap junction expression in the cochlea.

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 score0.007
Threshold uncertainty score0.384

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 head0.020
GPT teacher head0.269
Teacher spread0.248 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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