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Record W4311702531 · doi:10.1083/jcb.202108091

The α-Catenin mechanosensing M region is required for cell adhesion during tissue morphogenesis

2022· article· en· W4311702531 on OpenAlexafffund
Luka Sheppard, Gerald Lerchbaumer, Katheryn E. Rothenberg, Rodrigo Fernández‐González, Ulrich Tepaß

Bibliographic record

VenueThe Journal of Cell Biology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsHospital for Sick ChildrenTed Rogers Centre for Heart ResearchUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsMorphogenesisCateninCell biologyCell adhesionCellBiologyWnt signaling pathwayGeneticsSignal transductionGene

Abstract

fetched live from OpenAlex

α-Catenin couples the cadherin-catenin complex to the actin cytoskeleton. The mechanosensitive α-Catenin M region undergoes conformational changes upon application of force to recruit interaction partners. Here, we took advantage of the tension landscape in the Drosophila embryo to define three different states of α-Catenin mechanosensing in support of cell adhesion. Low-, medium-, and high-tension contacts showed a corresponding recruitment of Vinculin and Ajuba, which was dependent on the α-Catenin M region. In contrast, the Afadin homolog Canoe acts in parallel to α-Catenin at bicellular low- and medium-tension junctions but requires an interaction with α-Catenin for its tension-sensitive enrichment at high-tension tricellular junctions. Individual M region domains make complex contributions to cell adhesion through their impact on interaction partner recruitment, and redundancies with the function of Canoe. Our data argue that α-Catenin and its interaction partners are part of a cooperative and partially redundant mechanoresponsive network that supports AJs remodeling during morphogenesis.

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 score0.147
Threshold uncertainty score0.546

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 studies0.0010.000
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 head0.015
GPT teacher head0.248
Teacher spread0.232 · 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

Citations31
Published2022
Admission routes2
Has abstractyes

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