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Record W2508821115 · doi:10.1038/celldisc.2015.41

Temporal activation of XRCC1-mediated DNA repair is essential for muscle differentiation

2016· article· en· W2508821115 on OpenAlexafffund
Mohammad Al‐Khalaf, Leanne E Blake, Brian D. Larsen, Ryan A. V. Bell, Steve Brunette, Robin J. Parks, Michael A. Rudnicki, Peter J. McKinnon, F. Jeffrey Dilworth, Lynn A. Megeney

Bibliographic record

VenueCell Discovery · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health ResearchNational Cancer InstituteMach-Gaensslen Foundation of Canada
KeywordsXRCC1DNA repairCell biologyBiologyDNA damageMyocyteDNACellular differentiationBase excision repairProliferating cell nuclear antigenSkeletal muscleGeneGeneticsAnatomy

Abstract

fetched live from OpenAlex

Transient DNA strand break formation has been identified as an effective means to enhance gene expression in living cells. In the muscle lineage, cell differentiation is contingent upon the induction of caspase-mediated DNA strand breaks, which act to establish the terminal gene expression program. This coordinated DNA nicking is rapidly resolved, suggesting that myoblasts may deploy DNA repair machinery to stabilize the genome and entrench the differentiated phenotype. Here, we identify the base excision repair pathway component XRCC1 as an indispensable mediator of muscle differentiation. Caspase-triggered XRCC1 repair foci form rapidly within differentiating myonuclei, and then dissipate as the maturation program proceeds. Skeletal myoblast deletion of Xrcc1 does not have an impact on cell growth, yet leads to perinatal lethality, with sustained DNA damage and impaired myofiber development. Together, these results demonstrate that XRCC1 manages a temporally responsive DNA repair process to advance the muscle differentiation program.

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 score0.006

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 head0.007
GPT teacher head0.219
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

Citations41
Published2016
Admission routes2
Has abstractyes

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