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Record W2108499288 · doi:10.1152/ajpheart.00867.2006

Endoreduplication of human smooth muscle cells induced by 2-methoxyestradiol: a role for cyclin-dependent kinase 2

2006· article· en· W2108499288 on OpenAlexaff
Yu Gui, Hao Yin, Jia-Yin He, Songhua Yang, Michael P. Walsh, Xi‐Long Zheng

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2006
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEndoreduplication2-MethoxyestradiolCancer researchCell biologySmooth muscleCyclin-dependent kinase 4KinaseProtein kinase ABiologyCyclin-dependent kinase 2Internal medicineEndocrinologyMedicineCancerCell cycle

Abstract

fetched live from OpenAlex

Endoreduplication has been suggested to contribute to the development of hypertrophy of smooth muscle cells (SMCs) in hypertension. However, endoreduplication in vascular SMCs and the underlying molecular mechanisms are not clear. Treatment of human SMCs with 10 microM 2-methoxyestradiol (2-ME) for 24 h induces accumulation of cells with > or =4N DNA content, and some polyploid/aneuploid cells actively synthesize their DNA, suggesting the occurrence of endoreduplication. In addition, 2-ME treatment upregulates the expression of cyclin-dependent kinase 2 (Cdk2). The present study was designed to characterize endoreduplication of human SMCs and explore the potential roles of Cdk2 in endoreduplication induced by 2-ME. Treatment with 2-ME (10 microM) for 2-4 days not only caused increases in >4N cells and their reentry into S phase but also induced overduplication of chromosomes. Furthermore, 2-ME increased the kinase activity of Cdk2 and its interaction with cyclin E. Inducible overexpression of dominant-negative Cdk2 in human SMCs inhibited both DNA synthesis of >4N cells and the accumulation of >4N cells induced by 2-ME. We conclude that 2-ME induces endoreduplication of human SMCs and Cdk2 plays an important role in endoreduplication in response to 2-ME.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

Explore more

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