Tracking Isoflavones in Whole Soy Flour, Soy Muffins and Plasma after Consumption of Muffins by Healthy Adults
Bibliographic record
Abstract
The cardio‐protective effect of soy may be related to isoflavones. Research is needed to determine how isoflavones change during processing and digestion from a raw food ingredient to the biological fluid in order to better understand the relationship between isoflavone form, the food matrix, and the health effects conferred. This study tracked the abundance and transformation of soy isoflavones in: de‐fatted whole soy flour; a baked soy muffin; and plasma after regular consumption of soy muffins in a human clinical trial. Isoflavones were identified and quantified in soy flour and muffins by HPLC, and in plasma by LC‐MS/MS after participants (n=162) consumed soy muffins at doses of either 12.5g or 25g soy protein daily for 6 weeks. Soy muffins were sampled from 7 different production days (n=14) and analyzed for individual isoflavone isoforms and total isoflavone. Mean (±SEM) isoflavone content was 4.14±1.29 mg/g (DW) in soy flour and 1.10±0.04 mg/g (DW) in soy muffins. Soy flour and muffins contained similar proportions of isoflavone isoforms, but soy muffins contained overall lower absolute isoflavone content. Median total plasma isoflavone concentrations at week 6 for the low dose soy and the high dose soy groups were 91.0 and 333.7 ng/mL, respectively. Baking soy flour does not result in major changes in the relative proportion of isoflavones isoforms. Regular consumption of soy results in a dose‐related increase in plasma isoflavones with an approximate 4‐fold increase with a doubling of the dose. Funded through the Government of Canada Growing Forward I Science substantiation Program (RBPI#1746).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".