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Record W2146021974 · doi:10.1128/mcb.01053-08

A Role for DEAD Box 1 at DNA Double-Strand Breaks

2008· article· en· W2146021974 on OpenAlexaff
Lei Li, Elizabeth A. Monckton, Roseline Godbout

Bibliographic record

VenueMolecular and Cellular Biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of Alberta
FundersCancer Research Institute
KeywordsBiologyDEAD boxRNA Helicase ARNARNA silencingRNase PMolecular biologyHelicaseDNACell biologyDNA damageNon-coding RNAGeneticsRNA interferenceGene

Abstract

fetched live from OpenAlex

DEAD box proteins are a family of putative RNA helicases associated with all aspects of cellular metabolism involving the modification of RNA secondary structure. DDX1 is a member of the DEAD box protein family that is overexpressed in a subset of retinoblastoma and neuroblastoma cell lines and tumors. DDX1 is found primarily in the nucleus, where it forms two to four large aggregates called DDX1 bodies. Here, we report a rapid redistribution of DDX1 in cells exposed to ionizing radiation, resulting in the formation of numerous foci that colocalize with gamma-H2AX and phosphorylated ATM foci at sites of DNA double-strand breaks (DSBs). The formation of DDX1 ionizing-radiation-induced foci (IRIF) is dependent on ATM, which was shown to phosphorylate DDX1 both in vitro and in vivo. The treatment of cells with RNase H prevented the formation of DDX1 IRIF, suggesting that DDX1 is recruited to sites of DNA damage containing RNA-DNA structures. We have shown that DDX1 has RNase activity toward single-stranded RNA, as well as ADP-dependent RNA-DNA- and RNA-RNA-unwinding activities. We propose that DDX1 plays an RNA clearance role at DSB sites, thereby facilitating the template-guided repair of transcriptionally active regions 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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.220
Teacher spread0.212 · 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 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

Citations108
Published2008
Admission routes1
Has abstractyes

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