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Record W2035543709 · doi:10.1371/journal.pone.0001759

SirT1 Regulates Energy Metabolism and Response to Caloric Restriction in Mice

2008· article· en· W2035543709 on OpenAlexafffund
Gino Boily, Erin L. Seifert, Lisa Bevilacqua, Xiao He, Guillaume Sabourin, Carmen Estey, Cynthia Moffat, Sean A. Crawford, Sarah Saliba, Karen Jardine, Jian Ying Xuan, Meredith Evans, Mary‐Ellen Harper, Michael W. McBurney

Bibliographic record

VenuePLoS ONE · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of GuelphCanadian Diabetes Association
KeywordsCaloric theoryBiologyMetabolismMitochondrionRegulatorLipid metabolismNull alleleEnergy metabolismNull (SQL)GeneCell biologyAlleleGeneticsBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

The yeast sir2 gene and its orthologues in Drosophila and C. elegans have well-established roles in lifespan determination and response to caloric restriction. We have studied mice carrying two null alleles for SirT1, the mammalian orthologue of sir2, and found that these animals inefficiently utilize ingested food. These mice are hypermetabolic, contain inefficient liver mitochondria, and have elevated rates of lipid oxidation. When challenged with a 40% reduction in caloric intake, normal mice maintained their metabolic rate and increased their physical activity while the metabolic rate of SirT1-null mice dropped and their activity did not increase. Moreover, CR did not extend lifespan of SirT1-null mice. Thus, SirT1 is an important regulator of energy metabolism and, like its orthologues from simpler eukaryotes, the SirT1 protein appears to be required for a normal response to caloric restriction.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.200
Teacher spread0.180 · 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

Citations440
Published2008
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207