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Record W4298050976 · doi:10.17615/mwfg-0z70

aPKC Controls Microtubule Organization to Balance Adherens Junction Symmetry and Planar Polarity during Development

2020· article· en· W4298050976 on OpenAlexfundno aff
Tony Harris, Mark Peifer

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsAdherens junctionPolarity (international relations)PlanarMicrotubuleSymmetry (geometry)Balance (ability)Materials scienceCondensed matter physicsPhysicsCell biologyBiologyNeuroscienceComputer scienceMathematicsCadherinGeometryOperating systemGenetics

Abstract

fetched live from OpenAlex

Tissue morphogenesis requires assembling and disassembling individual cell-cell contacts without losing epithelial integrity. This requires dynamic control of adherens junction (AJ) positioning around the apical domain, but the mechanisms involved are unclear. We show that atypical Protein Kinase C (aPKC) is required for symmetric AJ positioning during Drosophila embryogenesis. aPKC is dispensable for initial apical AJ recruitment, but without aPKC, AJs form atypical planar-polarized puncta at gastrulation. Preceding this, microtubules fail to dissociate from centrosomes, and at gastrulation, abnormally persistent centrosomal microtubule asters cluster AJs into the puncta. Dynein enrichment at the puncta suggests it may draw AJs and microtubules together and microtubule disruption disperses the puncta. Through cytoskeletal disruption in wildtype embryos, we find a balance of microtubule and actin interactions controls AJ symmetry versus planar polarity during normal gastrulation. aPKC apparently regulates this balance. Without aPKC, abnormally strong microtubule interactions break AJ symmetry and epithelial structure is lost.

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 score0.041
Threshold uncertainty score0.553

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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