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Record W2123810912 · doi:10.1152/ajpheart.00958.2010

The α-linolenic acid content of flaxseed can prevent the atherogenic effects of dietary <i>trans</i> fat

2011· article· en· W2123810912 on OpenAlexafffund
Chantal M.C. Bassett, Richelle S. McCullough, Andrea L. Edel, Amanda Patenaude, Renee LaVallee, Grant N. Pierce

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2011
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsCholesterolFood scienceChemistryLignanDietary fatCoronary heart diseaseInternal medicineBiochemistryMedicine

Abstract

fetched live from OpenAlex

Dietary intake of industrially hydrogenated trans fatty acids (TFA) has been associated with coronary heart disease. Dietary flaxseed can inhibit atherosclerosis induced by dietary cholesterol. The aim of this study was to determine whether supplementing the diet with flaxseed could protect against atherosclerosis induced by a diet enriched in TFA. Low-density lipoprotein receptor-deficient (LDLr(-/-)) mice were fed 1 of 14 experimental diets for 14 wk containing one of two fat sources [regular (pork/soy) or trans fat] at two concentrations (4 or 8%) and supplemented with or without dietary cholesterol (2%), whole ground flaxseed, or one of the components of flaxseed [α-linolenic acid (ALA), defatted fiber, or lignan]. Adding flaxseed to the diet partially mitigated the rise in circulating cholesterol levels induced by the cholesterol-enriched diet. Atherosclerosis was stimulated by TFA and/or cholesterol. Including milled flaxseed to an atherogenic diet significantly reduced atherosclerosis compared with the groups that consumed cholesterol and/or TFA. ALA was the only component within flaxseed that could inhibit the atherogenic action of cholesterol and/or TFA on its own. Dietary flaxseed protects against atherosclerotic development induced by TFA and cholesterol feeding through its content of ALA.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.003
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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

Citations55
Published2011
Admission routes2
Has abstractyes

Explore more

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