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Record W2290820108 · doi:10.1093/eurheartj/ehw001

Foxo3 circular RNA promotes cardiac senescence by modulating multiple factors associated with stress and senescence responses

2016· article· en· W2290820108 on OpenAlexafffund
William W. Du, Weining Yang, Yu Chen, Zhongkai Wu, Zhenguo Yang, Xiangmin Li, Burton B. Yang

Bibliographic record

VenueEuropean Heart Journal · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFOXO3SenescenceGene silencingCompeting endogenous RNATranscription factorEctopic expressionCell biologyRNATranscription (linguistics)Circular RNABiologyMolecular biologyLong non-coding RNAGeneticsGene

Abstract

fetched live from OpenAlex

AIMS: Circular RNAs are a subclass of non-coding RNAs detected within mammalian cells. This study was designed to test the roles of a circular RNA circ-Foxo3 in senescence using in vitro and in vivo approaches. METHODS AND RESULTS: Using the approaches of molecular and cellular biology, we show that a circular RNA generated from a member of the forkhead family of transcription factors, Foxo3, namely circ-Foxo3, was highly expressed in heart samples of aged patients and mice, which was correlated with markers of cellular senescence. Doxorubicin-induced cardiomyopathy was aggravated by ectopic expression of circ-Foxo3 but was relieved by silencing endogenous circ-Foxo3. We also found that silencing circ-Foxo3 inhibited senescence of mouse embryonic fibroblasts and that ectopic expression of circ-Foxo3 induced senescence. We found that circ-Foxo3 was mainly distributed in the cytoplasm, where it interacted with the anti-senescent protein ID-1 and the transcription factor E2F1, as well as the anti-stress proteins FAK and HIF1α. CONCLUSION: We conclude that ID-1, E2F1, FAK, and HIF1α interact with circ-Foxo3 and are retained in the cytoplasm and could no longer exert their anti-senescent and anti-stress roles, resulting in increased cellular senescence.

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 score0.001
Threshold uncertainty score0.005

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)0.0010.000

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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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

Citations768
Published2016
Admission routes2
Has abstractyes

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