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Record W2178489891 · doi:10.1083/jcb.201505056

Optical volume and mass measurements show that mammalian cells swell during mitosis

2015· article· en· W2178489891 on OpenAlexfundno aff
Ewa Zlotek-Zlotkiewicz, Sylvain Monnier, Giovanni Cappello, Maël Le Berre, Matthieu Piel

Bibliographic record

VenueThe Journal of Cell Biology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheInstitut national de la recherche scientifique
KeywordsMitosisBiologyCell biologyCytoplasmCell divisionCellCortex (anatomy)Mitotic indexBiophysicsBiochemistryNeuroscience

Abstract

fetched live from OpenAlex

The extent, mechanism, and function of cell volume changes during specific cellular events, such as cell migration and cell division, have been poorly studied, mostly because of a lack of adequate techniques. Here we unambiguously report that a large range of mammalian cell types display a significant increase in volume during mitosis (up to 30%). We further show that this increase in volume is tightly linked to the mitotic state of the cell and not to its spread or rounded shape and is independent of the presence of an intact actomyosin cortex. Importantly, this volume increase is not accompanied by an increase in dry mass and thus corresponds to a decrease in cell density. This mitotic swelling might have important consequences for mitotic progression: it might contribute to produce strong pushing forces, allowing mitotic cells to round up; it might also, by lowering cytoplasmic density, contribute to the large change of physicochemical properties observed in mitotic cells.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.232
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations245
Published2015
Admission routes1
Has abstractyes

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