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Cholesterolaemic effect of palmitic acid in relation to other dietary fatty acids

2002· article· en· W2117291993 on OpenAlexaff
Margaret A. French, Kalyana Sundram, M. Thomas Clandinin

Bibliographic record

VenueAsia Pacific Journal of Clinical Nutrition · 2002
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPalmitic acidLinoleic acidChemistryCholesterolInternal medicineEndocrinologyFatty acidFood scienceBiochemistryBiologyMedicine

Abstract

fetched live from OpenAlex

The effect of dietary intake of high palmitic acid levels in combination with other fatty acids in normal subjects was assessed. Palmitic acid (10% of energy) was fed in conjunction with decreasing levels of linoleic acid to determine if a threshold level of linoleic acid prevented palmitic acid from being hypercholesterolaemic. Healthy subjects received each of the diet treatments for 21 days, followed by washout periods of 7 days. In a second experiment, the effect of exchanging palmitic acid for trans fatty acids on plasma lipoprotein cholesterol levels and on rates for endogenous synthesis of cholesterol in normal subjects was investigated. Diet treatment lasted for 30 days. On day 30 of each diet treatment, a priming dose of deuterium was consumed, followed by a subsequent blood sample at 24 h. Blood cholesterol fractions were isolated and analysed by isotope ratio mass spectrometry to measure cholesterol fractional synthetic rates. In the first experiment, total plasma cholesterol levels increased as the percentage of linoleic acid decreased. The data indicated that high levels of palmitic acid were not hypercholesterolaemic if intake of linoleic acid was greater than 4.5% of energy. When the diet contained trans fatty acids plasma total and low-density lipoprotein-cholesterol increased and cholesterol synthesis increased with a decrease in high-density lipoprotein-cholesterol.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.388
Teacher spread0.325 · 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 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

Citations84
Published2002
Admission routes1
Has abstractyes

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