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Record W2064227389 · doi:10.4161/cc.9.19.13379

Controlled chaos: New insights into genetically programmed cell cycle asynchrony

2010· letter· en· W2064227389 on OpenAlexfundno aff
James Umen

Bibliographic record

VenueCell Cycle · 2010
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene Regulatory Network Analysis
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institute of General Medical SciencesMcGill University
KeywordsBiologyAsynchrony (computer programming)Asynchronous communicationCytoplasmCHAOS (operating system)Cell cycleCell biologyCellImage (mathematics)Computational biologyGeneticsArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Entry into and progression through mitosis critically depends on the activity of Cdk1 in complex with its non-catalytic subunit cyclin B. Conversely, in order to exit from mitosis the cyclin B-Cdk1 complex needs to be inactivated, which occurs through APC/Cdependent proteasomal degradation of cyclin B. This model is attractive in its simplicity and builds a foundation that explains multiple aspects of chromosome segregation.On first sight, it appears that the mitotic activity of Cdk1-cyclin B is constantly high until the metaphase-anaphase transition.Recent careful re-examination of Cdk1-cyclin B activity, however, revealed that even after entry into mitosis, the activity of Cdk1-cyclin B continues to rise. 1 More importantly, it appears that some events during mitosis require higher levels of Cdk1-cyclin B than others.Specifically, lowering Cdk1-cyclin B levels to an extent that just allows mitotic entry, causes defects in APC/C activation and spindle organization, two aspects of mitosis that are apparently dependent on high Cdk1-cyclin B activity. 1 These results indicated that maintaining and elevating Cdk1-cyclin B levels during mitosis is of critical importance to ensure genomic stability.One of the recently emerging proteins that is required to establish high levels of Cdk1-cyclin B activity during mitosis is the Greatwall kinase (GWL), as originally identified in Drosophila. 2 GWL mutant cells were initially described to display chromosome condensation defects as well as delayed progression through mitosis. 2 Subsequent analysis in Xenopus revealed that Greatwall kinase functions in a positive feedback loop with the maturation-promoting factor (MPF, which consists of CDK1 in complex with cyclin B) to promote mitotic entry. 3How exactly Greatwall exerts its effects is unclear, but biochemical Cell Cycle News & ViewsBuilding a great wall around mitosis: Evolutionary conserved roles for the Greatwall/MASTL kinases in securing chromosome stability

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.003
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 head0.004
GPT teacher head0.202
Teacher spread0.198 · 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
Published2010
Admission routes1
Has abstractyes

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