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Record W2580882546 · doi:10.1038/ncomms14146

Dietary fatty acid metabolism of brown adipose tissue in cold-acclimated men

2017· article· en· W2580882546 on OpenAlexafffund
Denis P. Blondin, Hans Christian Tingelstad, Christophe Noll, Frédérique Frisch, Serge Phoenix, Brigitte Guérin, Éric Turcotte, Denis Richard, François Haman, André C. Carpentier

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité LavalUniversity of OttawaCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGlaxoSmithKline
KeywordsBrown adipose tissueWhite adipose tissueAdipose tissueEndocrinologyInternal medicineMetabolismBiologyFatty acidSkeletal muscleFatty acid metabolismBiochemistryMedicine

Abstract

fetched live from OpenAlex

Abstract In rodents, brown adipose tissue (BAT) plays an important role in producing heat to defend against the cold and can metabolize large amounts of dietary fatty acids (DFA). The role of BAT in DFA metabolism in humans is unknown. Here we show that mild cold stimulation (18 °C) results in a significantly greater fractional DFA extraction by BAT relative to skeletal muscle and white adipose tissue in non-cold-acclimated men given a standard liquid meal containing the long-chain fatty acid PET tracer, 14(R,S)-[18F]-fluoro-6-thia-heptadecanoic acid (18FTHA). However, the net contribution of BAT to systemic DFA clearance is comparatively small. Despite a 4-week cold acclimation increasing BAT oxidative metabolism 2.6-fold, BAT DFA uptake does not increase further. These findings show that cold-stimulated BAT can contribute to the clearance of DFA from circulation but its contribution is not as significant as the heart, liver, skeletal muscles or white adipose tissues.

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: Observational · Consensus signal: none
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)0.0000.000
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)0.0020.000

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 head0.040
GPT teacher head0.355
Teacher spread0.316 · 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 designObservational
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

Citations150
Published2017
Admission routes2
Has abstractyes

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Same venueNature CommunicationsSame topicAdipose Tissue and MetabolismFrench-language works237,207