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Record W2070950315 · doi:10.1042/bj20120385

Human cells enter mitosis with damaged DNA after treatment with pharmacological concentrations of genotoxic agents

2012· article· en· W2070950315 on OpenAlexafffund
Philip M. Kubara, Sophie Kernéis-Golsteyn, Aurélie Studény, Brittany B. Lanser, Laurent Meijer, Roy M. Golsteyn

Bibliographic record

VenueBiochemical Journal · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Lethbridge
FundersAlberta InnovatesAlberta Cancer FoundationUniversity of Lethbridge
KeywordsMitosisDNAGenotoxicityDNA damageCell biologyChemistryBiologyBiochemistryToxicity

Abstract

fetched live from OpenAlex

In the present paper, we report that mitosis is a key step in the cellular response to genotoxic agents in human cells. Cells with damaged DNA recruit γH2AX (phosphorylated histone H2AX), phosphorylate Chk1 (checkpoint kinase 1) and arrest in the G2-phase of the cell cycle. Strikingly, nearly all cells escape the DNA damage checkpoint and become rounded, by a mechanism that correlates with Chk1 dephosphorylation. The rounded cells are alive and in mitosis as measured by low phospho-Tyr(15) Cdk1 (cyclin-dependent kinase 1), high Cdk activity, active Plk1 (Polo-like kinase 1) and high phospho-histone H3 signals. This phenomenon is independent of the type of DNA damage, but is dependent on pharmacologically relevant doses of genotoxicity. Entry into mitosis is likely to be caused by checkpoint adaptation, and the HT-29 cell-based model provides a powerful experimental system in which to explore its molecular basis. We propose that mitosis with damaged DNA is a biologically significant event because it may cause genomic rearrangement in cells that survive genotoxic damage.

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)0.000
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
Metaresearch0.0000.000
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)0.0030.001

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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

Citations45
Published2012
Admission routes2
Has abstractyes

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