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Record W2140015697 · doi:10.1186/2041-9414-2-4

Fanconi anemia protein FANCD2 inhibits TRF1 polyADP-ribosylation through tankyrase1-dependent manner

2011· article· en· W2140015697 on OpenAlexfundno aff
Alex Lyakhovich, Marı́a José Ramı́rez, Andrés Castellanos‐Martín, María Castellà, Amanda M. Simons, Jeffrey D. Parvin, Jordi Surrallés

Bibliographic record

VenueGenome Integrity · 2011
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsnot available
FundersYork UniversityMinisterio de Ciencia e InnovaciónMedical Research CouncilCentre National de la Recherche ScientifiqueNational Cancer InstituteSchool of Medicine, New York UniversityNational Institutes of HealthGeneralitat de CatalunyaEuropean Commission
KeywordsFANCD2Fanconi anemiaTelomereDNA damageDNA repairBiologyGeneticsCancer researchCell biologyDNA

Abstract

fetched live from OpenAlex

BACKGROUND: Fanconi anemia (FA) is a rare autosomal recessive syndrome characterized by developmental abnormalities, progressive bone marrow failure, and predisposition to cancer. The key FA protein FANCD2 crosstalks with members of DNA damage and repair pathways that also play a role at telomeres. Therefore, we investigated whether FANCD2 has a similar involvement at telomeres. RESULTS: We reveal that FANCD2 may perform a novel function separate to the FANCD2/BRCA pathway. This function includes FANCD2 interaction with one of the telomere components, the PARP family member tankyrase-1. Moreover, FANCD2 inhibits tankyrase-1 activity in vitro. In turn, FANCD2 deficiency increases the polyADP-ribosylation of telomere binding factor TRF1. CONCLUSIONS: FANCD2 binding and inhibiting tankyrase-1PARsylation at telomeres may provide an additional step within the FA pathway for the regulation of genomic integrity.

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 score0.008

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.275
Teacher spread0.213 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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