MétaCan
Menu
Back to cohort
Record W2036755369 · doi:10.1371/journal.pone.0009199

SIRT1 Negatively Regulates the Mammalian Target of Rapamycin

2010· article· en· W2036755369 on OpenAlexaff
Hiyaa S. Ghosh, Michael W. McBurney, Paul D. Robbins

Bibliographic record

VenuePLoS ONE · 2010
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversity of Ottawa
FundersU.S. Department of Defense
KeywordsPI3K/AKT/mTOR pathwaymTORC1mTORC2Sirtuin 1Cell biologyRPTORNutrient sensingResveratrolAutophagyTOR signalingTSC2Signal transductionP70-S6 Kinase 1NAD+ kinaseBiologyActivator (genetics)Mechanistic target of rapamycinTSC1ChemistryBiochemistryApoptosisDownregulation and upregulationReceptor

Abstract

fetched live from OpenAlex

The IGF/mTOR pathway, which is modulated by nutrients, growth factors, energy status and cellular stress regulates aging in various organisms. SIRT1 is a NAD+ dependent deacetylase that is known to regulate caloric restriction mediated longevity in model organisms, and has also been linked to the insulin/IGF signaling pathway. Here we investigated the potential regulation of mTOR signaling by SIRT1 in response to nutrients and cellular stress. We demonstrate that SIRT1 deficiency results in elevated mTOR signaling, which is not abolished by stress conditions. The SIRT1 activator resveratrol reduces, whereas SIRT1 inhibitor nicotinamide enhances mTOR activity in a SIRT1 dependent manner. Furthermore, we demonstrate that SIRT1 interacts with TSC2, a component of the mTOR inhibitory-complex upstream to mTORC1, and regulates mTOR signaling in a TSC2 dependent manner. These results demonstrate that SIRT1 negatively regulates mTOR signaling potentially through the TSC1/2 complex.

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)0.0020.001

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 head0.028
GPT teacher head0.239
Teacher spread0.211 · 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

Citations399
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicSirtuins and Resveratrol in MedicineFrench-language works237,207