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Record W2923606839 · doi:10.1002/1873-3468.13357

A readout of metabolic efficiency in arylamine <i>N</i>‐acetyltransferase‐deficient mice reveals minor energy metabolism changes

2019· article· en· W2923606839 on OpenAlexafffund
R Denis, Florent Busi, Julien Castel, Chloé Morel, Wenchao Zhang, Linh‐Chi Bui, Kim S. Sugamori, Stephenie D. Prokopec, Paul C. Boutros, Denis M. Grant, Fernando Rodrigues‐Lima, Serge Luquet, Jean‐Marie Dupret

Bibliographic record

VenueFEBS Letters · 2019
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Toronto
FundersUniversité Paris DiderotCentre National de la Recherche ScientifiqueChina Scholarship CouncilUniversity of Toronto
KeywordsNatMetabolismGluconeogenesisEnergy metabolismBiologyInternal medicineChemistryEndocrinologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Recent studies have revealed a possible link between the activities of polymorphic arylamine N-acetyltransferases (NATs) and energy metabolism. We used a Nat1/Nat2 double knockout (KO) mouse model to demonstrate that ablation of the two Nat genes is associated with modest, intermittent alterations in respiratory exchange rate. Pyruvate tolerance tests show that double KO mice have attenuated hepatic gluconeogenesis when maintained on a high-fat/high-sucrose diet. Absence of the two Nat genes also leads to an increase in the hepatic concentration of coenzyme A in mice fed a high-fat/high-sucrose diet. Our results suggest a modest involvement of NAT in energy metabolism in mice, which is consistent with the absence of major phenotypic deregulation of energy metabolism in slow human acetylators.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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.

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

Citations4
Published2019
Admission routes2
Has abstractyes

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