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Record W4221074688 · doi:10.1073/pnas.2119381119

Cell size and polarization determine cytokinesis furrow ingression dynamics in mouse embryos

2022· article· en· W4221074688 on OpenAlexafffund
Lia Mara Gomes Paim, Greg FitzHarris

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsIngressionCytokinesisCleavage furrowCell biologyBiologyCell divisionCell polarityApical constrictionCytoplasmCellMorphogenesisGenetics

Abstract

fetched live from OpenAlex

Cytokinesis is the final step of cell division during which a contractile ring forms a furrow that partitions the cytoplasm in two. How furrow ingression is spatiotemporally regulated and how it is adapted to complex cellular environments and developmental transitions remain poorly understood. Here, we examine furrow ingression dynamics in the context of the early mouse embryo and find that cell size is a powerful determinant of furrow ingression speed during reductive cell divisions. In addition, the emergence of cell polarity and the assembly of the apical domain in outer cells locally inhibits the recruitment of cytokinesis components and thereby negatively regulates furrow ingression specifically on one side of the furrow. We show that this biasing of cytokinesis is not dependent upon cell–cell adhesion or shape but rather is cell intrinsic and is caused by a paucity of cytokinetic machinery in the apical domain. The results thus reveal that in the mouse embryo cell polarity directly regulates the recruitment of cytokinetic machinery in a cell-autonomous manner and that subcellular organization can instigate differential force generation and constriction speed in different zones of the cytokinetic furrow.

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 score0.012
Threshold uncertainty score0.153

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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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

Citations20
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicCellular Mechanics and InteractionsFrench-language works237,207