MétaCan
Menu
Back to cohort
Record W2003137732 · doi:10.1089/ars.2013.5736

DNA Repair Meets the RNA World

2013· article· en· W2003137732 on OpenAlexaff
Chow H. Lee

Bibliographic record

VenueAntioxidants and Redox Signaling · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsDNA repairBiologyAP siteRNABase excision repairDNADNA damageNucleotide excision repairComputational biologyDNA glycosylaseAP endonucleaseGeneticsGenome instabilityGeneCell biology

Abstract

fetched live from OpenAlex

The ability to repair damaged DNA and to maintain genome stability is the utmost importance for the survival of any species. Hence, it is not surprising to find that DNA repair mechanisms are evolutionarily conserved and are expected to evolve to maintain the existence of species. In the last few years, there has been an exponential increase in the evidence linking RNA processing with DNA repair programs. For instance, the well-studied DNA base excision repair (BER) enzyme apurinic/apyrimidinic endonuclease 1 can cleave RNA molecules, regulate mRNA levels, and associate physically with proteins involved in RNA processing. It is now clear that not only the expression of noncoding RNAs are changed upon DNA damage, they can modulate the expression of genes involved in the genome stability programs. The five reviews in this Forum provide the up-to-date knowledge on DNA repair, with a focus on BER, and a perspective on how the two ancient biochemical pathways are linked. The contributions demonstrate the complexity of such interactions, but also pointed out the opportunities for new therapeutic interventions. Future in vivo studies on the link between DNA repair processes and RNA metabolism should contribute to our basic understanding of physiology, disease, and treatment strategies.

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 score0.030
Threshold uncertainty score0.386

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAntioxidants and Redox SignalingSame topicDNA Repair MechanismsFrench-language works237,207