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Record W1989465871 · doi:10.1093/nar/gkl408

RNA helicases and abiotic stress

2006· review· en· W1989465871 on OpenAlexafffund
George W. Owttrim

Bibliographic record

VenueNucleic Acids Research · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyHelicaseeIF4ARNA Helicase ARNARiboswitchAbiotic stressCell biologyGeneticsNon-coding RNAGene

Abstract

fetched live from OpenAlex

RNA helicases function as molecular motors that rearrange RNA secondary structure, potentially performing roles in any cellular process involving RNA metabolism. Although RNA helicase association with a range of cellular functions is well documented, their importance in response to abiotic stress is only beginning to emerge. This review summarizes the available data on the expression, biochemistry and physiological function(s) of RNA helicases regulated by abiotic stress. Examples originate primarily from non-mammalian organisms while instances from mammalian sources are restricted to post-translational regulation of helicase biochemical activity. Common emerging themes include the requirement of a cold-induced helicase in non-homeothermic organisms, association and regulation of helicase activity by stress-induced phosphorylation cascades, altered nuclear-cytoplasmic shuttling in eukaryotes, association with the transcriptional apparatus and the diversity of biochemical activities catalyzed by a subgroup of stress-induced helicases. The data are placed in the context of a mechanism for RNA helicase involvement in cellular response to abiotic stress. It is proposed that stress-regulated helicases can catalyze a nonlinear, reversible sequence of RNA secondary structure rearrangements which function in RNA maturation or RNA proofreading, providing a mechanism by which helicase activity alters the activation state of target RNAs through regulation of the reaction equilibrium.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
Research integrity0.0010.001
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 head0.073
GPT teacher head0.408
Teacher spread0.336 · 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.

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

Citations168
Published2006
Admission routes2
Has abstractyes

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