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Record W3115259887 · doi:10.3390/ijms22010330

Monounsaturated Fatty Acids in Obesity-Related Inflammation

2020· review· en· W3115259887 on OpenAlexaff
Gaétan Ravaut, Alexandre Légiot, Karl‐F. Bergeron, Cathérine Mounier

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsInflammationInflammasomeAdipose tissueContext (archaeology)EndocrinologyInternal medicineChemistryLipid metabolismMetabolic syndromeMediterranean dietBiologyObesityMedicine

Abstract

fetched live from OpenAlex

Obesity is an important aspect of the metabolic syndrome and is often associated with chronic inflammation. In this context, inflammation of organs participating in energy homeostasis (such as liver, adipose tissue, muscle and pancreas) leads to the recruitment and activation of macrophages, which secrete pro-inflammatory cytokines. Interleukin-1β secretion, sustained C-reactive protein plasma levels and activation of the NLRP3 inflammasome characterize this inflammation. The Stearoyl-CoA desaturase-1 (SCD1) enzyme is a central regulator of lipid metabolism and fat storage. This enzyme catalyzes the generation of monounsaturated fatty acids (MUFAs)-major components of triglycerides stored in lipid droplets-from saturated fatty acid (SFA) substrates. In this review, we describe the molecular effects of specific classes of fatty acids (saturated and unsaturated) to better understand the impact of different diets (Western versus Mediterranean) on inflammation in a metabolic context. Given the beneficial effects of a MUFA-rich Mediterranean diet, we also present the most recent data on the role of SCD1 activity in the modulation of SFA-induced chronic inflammation.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.041
GPT teacher head0.379
Teacher spread0.338 · 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
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

Citations247
Published2020
Admission routes1
Has abstractyes

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