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Record W2607158853 · doi:10.1016/j.ebiom.2017.04.027

Are SIRT1 activators another indirect method to increase AMPK for beneficial effects on aging and the metabolic syndrome?

2017· letter· en· W2607158853 on OpenAlexafffundabout
Rebecca J. Ford, Eric M. Desjardins, Gregory R. Steinberg

Bibliographic record

VenueEBioMedicine · 2017
Typeletter
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsAllosteric regulationResveratrolSmall moleculeActivator (genetics)ChemistryCalorie restrictionAMPKBiochemistryBiologyPharmacologyEnzymeEndocrinologyProtein kinase AReceptor

Abstract

fetched live from OpenAlex

The discovery that caloric restriction enhances lifespan and that sirtuins 1 (Sirt1) may mediate these effects ushered in a renaissance of research into the development of novel small molecule activators targeting this highly conserved family of deacetylases (Sinclair and Guarente, 2014). Subsequent findings that the polyphenol resveratrol, a substance enriched in the skin of red and purple fruits and most notably red wine, was a potent Sirt1 activator created further excitement around developing more specific agonists towards this new molecular target for anti-aging therapies (Sinclair and Guarente, 2014).

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.006

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 head0.319
Teacher spread0.299 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations10
Published2017
Admission routes3
Has abstractyes

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