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Record W2008895037 · doi:10.1093/nar/gks039

DNA helicase and helicase-nuclease enzymes with a conserved iron-sulfur cluster

2012· review· en· W2008895037 on OpenAlex
Yuliang Wu, Robert M. Brosh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNucleic Acids Research · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health
FundersNational Institutes of Health
KeywordsHelicaseBiologyNucleaseRNA Helicase ADNA repairIron–sulfur clusterDNAGeneticsDNA replicationEukaryotic DNA replicationControl of chromosome duplicationBiochemistryCell biologyEnzymeGeneRNA

Abstract

fetched live from OpenAlex

Conserved Iron-Sulfur (Fe-S) clusters are found in a growing family of metalloproteins that are implicated in prokaryotic and eukaryotic DNA replication and repair. Among these are DNA helicase and helicase-nuclease enzymes that preserve chromosomal stability and are genetically linked to diseases characterized by DNA repair defects and/or a poor response to replication stress. Insight to the structural and functional importance of the conserved Fe-S domain in DNA helicases has been gleaned from structural studies of the purified proteins and characterization of Fe-S cluster site-directed mutants. In this review, we will provide a current perspective of what is known about the Fe-S cluster helicases, with an emphasis on how the conserved redox active domain may facilitate mechanistic aspects of helicase function. We will discuss testable models for how the conserved Fe-S cluster might operate in helicase and helicase-nuclease enzymes to conduct their specialized functions that help to preserve the integrity of the genome.

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.

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 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 score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.359
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