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Record W2290904775 · doi:10.1155/2016/2909210

n-3 Polyunsaturated Fatty Acid Supplementation Has No Effect on Postprandial Triglyceride-Rich Lipoprotein Kinetics in Men with Type 2 Diabetes

2016· article· en· W2290904775 on OpenAlexafffund
André Tremblay, Benoı̂t Lamarche, Jean‐Charles Hogue, Patrick Couture

Bibliographic record

VenueJournal of Diabetes Research · 2016
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsPolyunsaturated fatty acidTriglycerideChemistryInternal medicineApolipoprotein BPostprandialEndocrinologyLipoproteinCholesterolFatty acidDiabetes mellitusBiochemistryMedicine

Abstract

fetched live from OpenAlex

Dietary n-3 polyunsaturated fatty acids (PUFAs) have been proposed to modulate plasma lipids, lipoprotein metabolism, and inflammatory state and to reduce triglyceride (TG) concentrations. The present double-blind, randomized, placebo-controlled, crossover study investigated the effects of n-3 PUFA supplementation at 3 g/d for 8 weeks on the intravascular kinetics of intestinally derived apolipoprotein (apo) B-48-containing lipoproteins in 10 men with type 2 diabetes. In vivo kinetics of the TG-rich lipoprotein (TRL) apoB-48 and VLDL apoB-100 were assessed using a primed-constant infusion of L-[5,5,5-D3] leucine for 12 hours in a fed state. Compared with the placebo, n-3 PUFA supplementation significantly reduced fasting TG concentrations by -9.7% (P = 0.05) but also significantly increased plasma levels of cholesterol (C) (+6.0%, P = 0.05), LDL-C (+12.2%, P = 0.04), and HDL-C (+8.4, P = 0.007). n-3 PUFA supplementation had no significant impact on postprandial TRL apoB-48 and VLDL apoB-100 levels or on the production or catabolic rates of these lipoproteins. These data indicate that 8-week supplementation with n-3 PUFAs in men with type 2 diabetes has no beneficial effect on TRL apoB-48 and VLDL apoB-100 levels or kinetics.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.376
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.313
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

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