The Distribution of Fatty Acid Biomarkers of Dairy Intake across Serum Lipid Fractions: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort
Bibliographic record
Abstract
Circulating fatty acids (FA) derived largely from dairy consumption have most commonly been measured in total human serum or phospholipid (PL) fractions, and have been used as validated biomarkers of dairy intake in a growing number of epidemiological studies. Nevertheless, measurement and characterization of a wider spectrum of FA biomarkers of dairy across the four major serum lipid fractions is lacking. This study aimed to (1) quantify FA biomarkers of dairy in PL, triacylglycerol (TAG), cholesteryl ester (CE), and unesterified fatty acid (FFA) serum lipid fractions; and (2) identify potential demographic and metabolic factors that may modify the proportions of these FA across serum fractions. Baseline data from 444 adults in the PROMISE cohort were analyzed. FA biomarkers, 15:0, t16:1n-7, 18:2-c9,t11, and t18:1n-7 were quantified from serum. Dairy intake was estimated using the validated Canadian Diet History Questionnaire. Our results show that t18:1n-7 was the most abundant FA biomarker in all fractions except CE, where 18:2-c9,t11 was the most abundant. Positive correlations within fractions, and across FA in the PL, CE, and FFA fractions were found, however, TAG FA were negatively correlated with the other fractions. PL and CE FA were positively associated with dairy intake, and negatively associated with markers of dysmetabolism while, in contrast, these markers were predictors of higher TAG dairy FA. This study is the first to demonstrate distinct proportions of dairy FA in different serum lipid fractions. PL and CE FA marked dairy intake in this cohort, while TAG FA appeared to be markers of dysmetabolism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".