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Record W4380869725 · doi:10.1080/15476286.2023.2223466

Abasic RNA: its formation and potential role in cellular stress response

2023· review· en· W4380869725 on OpenAlexafffund
Tanya Prashar, Fernand De La Selle, Katalin A. Hudak

Bibliographic record

VenueRNA Biology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyRNAAP siteCell biologyDNA damageNucleic acidRibosomal RNAeIF4ARNA silencingMessenger RNADNANon-coding RNABiochemistryGeneRNA interference

Abstract

fetched live from OpenAlex

RNA is integral to gene expression as messenger RNA (mRNA), transfer RNA (tRNA) and ribosomal RNA (rRNA) each play roles to transmit information from DNA into synthesis of functional proteins. During their lifespan, these nucleic acids may be chemically modified by alkylation, oxidation and the removal of bases, which alters their activity. Though much research has been devoted to the detection and repair of damaged DNA, RNA is viewed as a short-lived molecule that is quickly degraded upon damage. However, recent studies indicate that RNAs that become modified, particularly during stress, function as important signalling molecules. In this review, we focus on the effects of abasic RNAs and the modifications that lead to the loss of a base, as RNAs that are initially methylated or oxidized often become abasic. We describe how these chemical changes occur and cite recent work showing that in addition to being indicators of damage, abasic RNAs function as signals that mediate downstream cellular responses to stress.

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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.030
GPT teacher head0.315
Teacher spread0.285 · 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

Citations10
Published2023
Admission routes2
Has abstractyes

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