Plasma alkylresorcinol metabolites as potential biomarkers of whole-grain wheat and rye cereal fibre intakes in women
Bibliographic record
Abstract
It has been demonstrated that intact plasma alkylresorcinols (AR) and urinary AR metabolites could be used as biomarkers of whole-grain intake. Thereafter, we developed the method for the plasma AR metabolites, which is more convenient and requires less sample pretreatment than the analysis of intact plasma AR. The aim of the present study is to evaluate whether AR metabolites measured in plasma, in the same population, could also be considered as useful biomarkers of cereal fibre. Fifty-six women were recruited in a cross-sectional and observational study. Dietary intake (5-d record) and plasma AR metabolites (3,5-dihydroxybenzoic acid, DHBA; 3-(3,5-dihydroxyphenyl)-1-propanoic acid, DHPPA) were measured. The relationship between plasma AR metabolites and cereal fibre intake was examined using partial correlation and stepwise regression. Cereal fibre intake correlated significantly with plasma DHBA (r 0.411; P = 0.002) and DHPPA (r 0.463; P = 0.000) even after adjustment for BMI and age. Thus, plasma AR metabolites correlate with cereal fibre intake as noted with plasma intact AR and urinary AR metabolites. We observed that plasma DHPPA was the independent predictor of cereal fibre intake, explaining 18 % of the variance (adjusted r(2) 0.176; P = 0.002). In epidemiological screening, it might be easier to obtain and to collect plasma than urine samples. In addition, the plasma AR metabolites half-life seems longer than those of intact plasma AR, and their measurements are more convenient, and faster. Thus, sum of plasma AR metabolites and more specifically plasma DHPPA seems to be good and specific biomarkers of cereal fibre intake.
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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 | 0.000 | 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".