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Record W4393119439 · doi:10.1093/nar/gkae208

ARGLU1 enhances promoter-proximal pausing of RNA polymerase II and stimulates DNA damage repair

2024· article· en· W4393119439 on OpenAlexafffund
Scott Bachus, Nikolas Akkerman, Lauren Fulham, Drayson Graves, Rafe Helwer, Jordan Rempel, Peter Pelka

Bibliographic record

VenueNucleic Acids Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchResearch Manitoba
KeywordsBiologyDNA damageDNA repairTranscription (linguistics)RNA polymerase IIRNA splicingGene knockdownCell biologyMolecular biologyRNADNACancer researchPromoterGeneticsGene expressionGene

Abstract

fetched live from OpenAlex

Arginine and glutamate rich 1 (ARGLU1) is a poorly understood cellular protein with functions in RNA splicing and transcription. Computational prediction suggests that ARGLU1 contains intrinsically disordered regions and lacks any known structural or functional domains. We used adenovirus Early protein 1A (E1A) to probe for critical regulators of important cellular pathways and identified ARGLU1 as a significant player in transcription and the DNA damage response pathway. Transcriptional effects induced by ARGLU1 occur via enhancement of promoter-proximal RNA polymerase II pausing, likely by inhibiting the interaction between JMJD6 and BRD4. When overexpressed, ARGLU1 increases the growth rate of cancer cells, while its knockdown leads to growth arrest. Significantly, overexpression of ARGLU1 increased cancer cell resistance to genotoxic drugs and promoted DNA damage repair. These results identify new roles for ARGLU1 in cancer cell survival and the DNA damage repair pathway, with potential clinical implications for chemotherapy resistance.

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 score0.002
Threshold uncertainty score0.007

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.327
Teacher spread0.298 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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