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Record W2767771270 · doi:10.3390/ijms18112344

G2/M-Phase Checkpoint Adaptation and Micronuclei Formation as Mechanisms That Contribute to Genomic Instability in Human Cells

2017· review· en· W2767771270 on OpenAlexafffund
Danî Kalsbeek, Roy M. Golsteyn

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Health SolutionsAlberta Cancer Foundation
KeywordsChromothripsisGenome instabilityMicronucleus testChromosome instabilityBiologyDNA damageG2-M DNA damage checkpointMitosisGeneticsCancer cellMicronucleusDNA repairCancer researchCancerCell biologyDNACell cycleCell cycle checkpointChemistryGeneChromosomeToxicity

Abstract

fetched live from OpenAlex

One of the most common characteristics of cancer cells is genomic instability. Recent research has revealed that G2/M-phase checkpoint adaptation-entering mitosis with damaged DNA-contributes to genomic changes in experimental models. When cancer cells are treated with pharmacological concentrations of genotoxic agents, they undergo checkpoint adaptation; however, a small number of cells are able to survive and accumulate micronuclei. These micronuclei harbour damaged DNA, and are able to replicate and reincorporate their DNA into the main nucleus. Micronuclei are susceptible to chromothripsis, which is a phenomenon characterised by extensively rearranged chromosomes that reassemble from pulverized chromosomes in one cellular event. These processes contribute to genomic instability in cancer cells that survive a genotoxic anti-cancer treatment. This review provides insight into checkpoint adaptation and its connection to micronuclei and possibly chromothripsis. Knowledge about these mechanisms is needed to improve the poor cancer treatment outcomes that result from genomic instability.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.457
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.056
GPT teacher head0.363
Teacher spread0.307 · 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
GenreReview

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

Citations85
Published2017
Admission routes2
Has abstractyes

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