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Record W1985077638 · doi:10.1155/2012/684684

Casein Kinase I<i>γ</i>2 Impairs Fibroblasts Actin Stress Fibers Formation and Delays Cell Cycle Progression in G1

2012· article· en· W1985077638 on OpenAlexafffund
Mathieu Latreille, Afnan Abu-Thuraia, Rossella Oliva, Dongmei Zuo, Louise Larose

Bibliographic record

VenueInternational Journal of Cell Biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchCanadian Diabetes Association
KeywordsCell cycleActinCell biologyCell cycle progressionCaseinKinaseCasein kinase 2MedicineCasein kinase 1FibroblastBiologyInternal medicineProtein kinase ABiochemistryCyclin-dependent kinase 2GeneticsCancerCell culture

Abstract

fetched live from OpenAlex

Actin cytoskeleton remodeling is under the regulation of multiple proteins with various activities. Here, we demonstrate that the γ2 isoform of Casein Kinase I (CKIγ2) is part of a novel molecular path regulating the formation of actin stress fibers. We show that overexpression of CKIγ2 in fibroblasts alters cell morphology by impairing actin stress fibers formation. We demonstrate that this is concomitant with increased phosphorylation of the CDK inhibitor p27(Kip) and lower levels of activated RhoA, and is dependent on CKIγ2 catalytic activity. Moreover, we report that roscovitine, a potent inhibitor of cyclin-dependent kinases, including Cdk5, decreases p27(Kip) protein levels and restores actin stress fibers formation in CKIγ2 overexpressing cells, suggesting the existence of a CKIγ2-Cdk5-p27(Kip)-RhoA pathway in regulating actin remodeling. On the other hand, we also show that in a manner independent of its catalytic activity, CKIγ2 delays cell cycle progression through G1. Collectively our findings reveal that CKIγ2 is a novel player in the control of actin cytoskeleton dynamics and cell proliferation.

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 score0.025
Threshold uncertainty score0.379

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 head0.006
GPT teacher head0.271
Teacher spread0.265 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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