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Record W3019077374 · doi:10.1096/fj.201902947r

Chromosome dynamics and spindle microtubule establishment in mouse embryos

2020· article· en· W3019077374 on OpenAlexafffund
Angus D. Macaulay, Adélaïde Allais, Greg FitzHarris

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersInstitute of Human Development, Child and Youth HealthNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchFondation Jean-Louis Lévesque
KeywordsKinetochoreBiologyMitosisChromosome segregationCell biologySpindle apparatusMicrotubuleCentromereChromosomeMetaphaseMultipolar spindlesSpindle pole bodyEmbryoGeneticsCell divisionCellGene

Abstract

fetched live from OpenAlex

Chromosome segregation errors in mammalian embryos are common and jeopardize embryo health. Here, we perform for the first time 4-Dimensional imaging and tracking of chromosomes and centromeres through each preimplantation mitotic cell division in mouse embryos to define the normal dynamics of chromosome segregation. We show that a microtubule (MT)-dependent inward movement of chromosomes occurs at the time of nuclear envelope breakdown (NEBD), particularly in the earliest cell divisions, to position chromosomes prior to spindle assembly. Establishment of a rudimentary metaphase plate occurs immediately after NEBD, and is followed by a progressive alignment and biorientation of mitotic chromosomes. Stable end-on kinetochore-MT attachments form rapidly and attachment errors are uncommon. Altogether our data describe a rapid and efficient spindle assembly pathway that apparently minimizes the need for canonical MT attachment error correction in normally dividing embryos.

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 score0.008
Threshold uncertainty score0.419

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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

Citations8
Published2020
Admission routes2
Has abstractyes

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