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Record W2051088438 · doi:10.4161/cc.23051

MicroRNAs and DNA damage response

2012· review· en· W2051088438 on OpenAlexfundno aff
Yemin Wang, Toshiyasu Taniguchi

Bibliographic record

VenueCell Cycle · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchHoward Hughes Medical Institute
KeywordsDNA damageBiologymicroRNADNA repairGenome instabilityDNACell biologyRegulation of gene expressionGeneticsSOS responseGene

Abstract

fetched live from OpenAlex

The DNA damage response (DDR) pathways play critical roles in protecting the genome from DNA damage. Abrogation of DDR often results in elevated genomic instability and cellular sensitivity to DNA damaging agents. Many proteins involved in DDR are subjected to precise regulation at multiple levels, such as transcriptional control and posttranslational modifications, in response to DNA damage. MicroRNAs (miRNAs) are a class of small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. The expression levels of some miRNAs change in response to DNA damage. Some miRNAs, such as miR-24, 138, 96 and 182, have been implicated in DDR and/or DNA repair and affect cellular sensitivity to DNA damaging agents. In this review, we summarize recent findings related to the emerging roles of miRNAs in regulating DDR and DNA repair and discuss their potential in cancer therapy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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 designNot applicable
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

Citations99
Published2012
Admission routes1
Has abstractyes

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