Lack of Evidence for Antiatherogenic Effects of Wheat Bran or Corn Bran in Apolipoprotein E-Knockout Mice
Bibliographic record
Abstract
Epidemiological studies have suggested that intake of whole grains is inversely associated with coronary artery disease. The mechanisms, however, are not completely clear. We tested the hypothesis that intake of wheat bran or corn bran would (1) increase the plasma concentration of phenolic antioxidants and (2) reduce atherosclerosis in apo E-knockout mice. Apo E-knockout (E-KO) mice were fed for 18 weeks with a 0.1% cholesterol-supplemented diet in the absence of grain brans or the presence of 1.7% yellow dent corn bran or 3.3% hard red spring wheat bran. The concentration of antioxidant ferulic acid in plasma and urine was measured by HPLC to monitor the bioavailability of grain phenolics. Plasma lipoprotein profiles were determined by a combination of HPLC and online enzymatic methods. Urinary 15-isoprostane F(2t), an in vivo LDL oxidation biomarker, and atherosclerotic lesions were analyzed by ELISA and histological methods, respectively. Dietary supplementation with corn or wheat bran resulted in a 4- and 24-fold increase, respectively, in urinary excretion of ferulic acid. The urinary recovery rate of ferulic acid from the two brans in apo E-KO mice was approximately 1.9-2.9%. Dietary corn bran but not wheat bran also significantly increased the concentration of total ferulic acid in plasma. Nevertheless, the supplementation with either bran product for 18 weeks did not significantly alter the urinary excretion of 15-isoprostane F(2t), change the lipoprotein profiles, nor reduce the atherosclerotic lesion development in this animal model. The results suggest that phenolic antioxidants from the two types of bran may not be sufficient to reduce atherosclerosis in this animal model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".