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Record W3166538734 · doi:10.1002/dvdy.381

Connexin 43 contributes to phenotypic robustness of the mouse skull

2021· article· en· W3166538734 on OpenAlexaff
Elizabeth Jewlal, Kevin Barr, Dale W. Laird, Katherine E. Willmore

Bibliographic record

VenueDevelopmental Dynamics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsWestern University
Fundersnot available
KeywordsSkullBiologyRobustness (evolution)MutantCraniofacialPhenotypeConnexinLoss functionWild typeGeneticsAnatomyGap junctionGeneIntracellular

Abstract

fetched live from OpenAlex

BACKGROUND: We compared skull shape and variation among genetically modified mice that exhibit different levels of connexin43 (Cx43) channel function, to determine whether Cx43 contributes to craniofacial phenotypic robustness. Specifically, we used two heterozygous mutant mouse models (G60S/+ and I130T/+) that, when compared to their wildtype counterparts, have an ~80% and ~50% reduction in Cx43 function, respectively. RESULTS: Both mutant strains showed significant differences in skull shape compared to wildtype littermates and while these differences were more severe in the G60S/+ mouse, shape differences were localized to similar regions of the skull in both mutants. However, increased skull shape variation was observed in G60S/+ mutants only. Additionally, covariation of skull structures was disrupted in the G60S/+ mutants only, indicating that while a 50% reduction in Cx43 function is sufficient to cause a shift in mean skull shape, the threshold for Cx43 function for disrupting craniofacial phenotypic robustness is lower. CONCLUSIONS: Collectively, our results indicate Cx43 can contribute to phenotypic robustness of the skull through a nonlinear relationship between Cx43 gap junctional function and phenotypic outcomes.

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)0.000
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 score0.060
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.006
GPT teacher head0.211
Teacher spread0.204 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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