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Record W2040519360 · doi:10.1038/cddis.2014.305

miR-17 extends mouse lifespan by inhibiting senescence signaling mediated by MKP7

2014· article· en· W2040519360 on OpenAlexafffund
William W. Du, Weining Yang, Ling Fang, Jim W. Xuan, H Li, Azam Khorshidi, Shubham Gupta, X Li, Burton B. Yang

Bibliographic record

VenueCell Death and Disease · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsCell biologySenescenceBiologyAutophagyPsychological repressionPI3K/AKT/mTOR pathwayGene silencingTranscription factorCarcinogenesisSignal transductionApoptosisGeneticsCancerGeneGene expression

Abstract

fetched live from OpenAlex

Here we show that transgenic expression of miR-17 extends lifespan and inhibits cellular senescence. We propose that miR-17 acts as a critical regulator of cellular senescence and tumorigenesis. We demonstrate that miR-17 targets both ADCY5 and IRS1, upregulating the downstream signals MKP7, FoxO3, LC3B, and HIF1α, and downregulating mTOR, c-myc, cyclin D1, and JNK. Silencing either ADCY5 or IRS1 promoted autophagy and repressed cellular senescence and apoptosis. Repression of ADCY5 by miR-17 translocated membrane-bound RGS2 into the nucleus, promoting interactions of RGS2 with HIF1α and the MKP7 promoter, enhancing MKP7 transcription. ADCY5 repression by miR-17 also facilitated the translocation of EGFR and MKP7 from membrane into cytoplasmic and mitochondrial fractions. Importantly, we found that MKP7 inhibited senescence by dephosphorylating PRAS40 at Thr246 and mTOR at Ser2248, facilitating the interaction and loss of function of both molecules. Thus, the oncogenic miR-17 also acts pleiotropically to inhibit cellular senescence and extend longevity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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 teacher head, 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

Citations68
Published2014
Admission routes2
Has abstractyes

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