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Record W3082387403 · doi:10.1101/2020.09.01.278523

Spindle alignment is uncoupled with Kar9 symmetry breaking

2020· preprint· en· W3082387403 on OpenAlexafffund
Miram Meziane, Rachel Genthial, Jackie Vogel

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsAsymmetrySymmetry breakingMicrotubuleBilateral symmetrySpindle pole bodySpindle apparatusBudding yeastCompartment (ship)BiologySymmetry (geometry)PhysicsBiophysicsCell biologyCell divisionCellGeometrySaccharomyces cerevisiaeYeastEngineeringParticle physicsMathematicsGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Spindle positioning must be tightly regulated to ensure asymmetric cell divisions are successful. In budding yeast, spindle positioning is mediated by the asymmetric localization of microtubule +end tracking protein Kar9. Kar9 asymmetry is believed to be essential for spindle alignment. However, the temporal correlation between symmetry breaking and spindle alignment has not been measured. Here, we establish a method of quantifying Kar9 symmetry breaking and find that Kar9 asymmetry is not well coupled with early spindle alignment. We report the majority of asymmetric cells are not stably aligned. Rather, stable alignment, a state we define as perfect alignment, is correlated with Kar9 localization to the bud compartment, regardless of symmetry state. Our findings suggest that Kar9 asymmetry alone is insufficient for perfect alignment and reveal a possible role for Swe1 in regulating spindle alignment efficiency.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicMicrotubule and mitosis dynamics→French-language works237,207→