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SirT1 fails to affect p53‐mediated biological functions

2006· article· en· W2172011238 on OpenAlexaff
Christopher Kamel, Meena Abrol, Karen Jardine, Xiaohong He, Michael W. McBurney

Bibliographic record

VenueAging Cell · 2006
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversity of Ottawa
FundersNational Cancer Institute
KeywordsBiologySirtuin 1AcetylationEndogenyPhenotypeApoptosisGeneCell biologyGeneticsDownregulation and upregulationCancer researchEndocrinology

Abstract

fetched live from OpenAlex

The SirT1 gene encodes a protein deacetylase that acts on a number of nuclear substrates. p53 was identified as a SirT1 substrate whose transcriptional activity was reported to be negatively regulated by SirT1-dependent deacetylation. We set out to determine whether developmental defects and perinatal lethality observed in SirT1-null mice were caused by p53 hyperactivity by creating mice deficient for both SirT1 and p53. Animals null for both proteins were smaller than normal at birth, had eyelid opening defects and died during the late prenatal and early postnatal periods, a phenotype indistinguishable from mice deficient for SirT1 alone. Upon re-examination of the role of SirT1 in modulating p53 activity, we found that while SirT1 interacts with p53, the SirT1 protein had little effect on p53-dependent transcription of transfected or endogenous genes and did not affect the sensitivity of thymocytes and splenocytes to radiation-induced apoptosis. These findings suggest that SirT1 does not affect many p53-mediated biological activities despite the fact that acetylated p53 has been shown to be a substrate for SirT1.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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

Citations64
Published2006
Admission routes1
Has abstractyes

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