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Record W4389934087 · doi:10.1152/physiol.00012.2023

Tracers and Imaging of Fatty Acid and Energy Metabolism of Human Adipose Tissues

2023· review· en· W4389934087 on OpenAlexafffund
André C. Carpentier

Bibliographic record

VenuePhysiology · 2023
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchNovo NordiskGovernment of CanadaEli Lilly and Company
KeywordsAdipose tissueBrown adipose tissueWhite adipose tissueLipid metabolismInsulin resistanceMetabolismBiologyFatty acid metabolismBeta oxidationEndocrinologyInternal medicineDiabetes mellitusMedicine

Abstract

fetched live from OpenAlex

White adipose tissue and brown adipose tissue (WAT and BAT) regulate fatty acid metabolism and control lipid fluxes to other organs. Dysfunction of these key metabolic processes contributes to organ insulin resistance and inflammation leading to chronic diseases such as type 2 diabetes, metabolic dysfunction-associated steatohepatitis, and cardiovascular diseases. Metabolic tracers combined with molecular imaging methods are powerful tools for the investigation of these pathogenic mechanisms. Herein, I review some of the positron emission tomography and magnetic resonance imaging methods combined with stable isotopic metabolic tracers to investigate fatty acid and energy metabolism, focusing on human WAT and BAT metabolism. I will discuss the complementary strengths offered by these methods for human investigations and current gaps in the field.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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)0.0000.000

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 head0.051
GPT teacher head0.359
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2023
Admission routes2
Has abstractyes

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