Effect of acute fish oil and soy isoflavone supplementation on postprandial serum triglycerides and biomarkers of oxidative stress in overweight or obese, hypertriglyeridemic men
Bibliographic record
Abstract
Chronic intake of fish and fish oil (FO) high in omega‐3 fatty acids (n‐3PUFA) reduces triglycerides (TG) but increases oxidative stress (OXID), whereas chronic intake of soy isoflavones (ISO) may reduce OXID. Elevated serum TG and OXID are cardiovascular disease (CVD) risk factors, however the effects of acute n‐3PUFA and soy isoflavone supplementation are unknown. Ten overweight or obese males consumed a high‐fat, high‐fructose meal with four supplement combinations (ISOplacebo+FOplacebo; ISOplac+FO; ISO+FOplac; and ISO+FO) in a randomized, double blind, placebo‐controlled, crossover study. Blood was collected at baseline, 2, 4 and 6h post‐meal and analyzed for fatty acids, isoflavones, TG and OXID markers (oxidized‐LDL, lipid hydroperoxides and total antioxidant status). FO treatments significantly increased serum n‐3PUFA and ISO treatments increased serum isoflavones. The study meal significantly increased TG within all treatments but did not significantly affect any OXID biomarkers. There were no significant differences between treatments for TG or OXID. This study adds to limited research on the effects of acute doses of FO and ISO on postprandial biomarkers of CVD risk. Supported by the Hannam Soybean Utilization Fund, the Heart and Stroke Foundation of Ontario, Ocean Nutrition Canada and Archer's Daniel Midland Research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".