Effect of Cocoa Bran on Low-Density Lipoprotein Oxidation and Fecal Bulking
Bibliographic record
Abstract
BACKGROUND: Legumes have reported benefits in terms of reduced risk for coronary heart disease and of colonic health. A novel legume fiber, cocoa bran, also may have favorable health effects on serum lipid levels, low-density lipoprotein (LDL) cholesterol oxidation, and fecal bulk. METHODS: Twenty-five healthy normolipidemic subjects (13 men and 12 women) (mean +/- SEM age, 37 +/- 2 years; mean +/- SEM body mass index [calculated as weight in kilograms divided by the square of height in meters], 24.6 +/- 0.7) ate cocoa-bran and chocolate-flavored low-fiber breakfast cereals for 2-week periods, with 2-week washout, in a double-blind crossover study. The cocoa-bran cereal provided 25.0 g/d of total dietary fiber (TDF). The low-fiber cereal (5.6 g/d TDF) was of similar appearance and energy value. Fasting blood samples were obtained at the start and end of each period, and 4-day fecal collections were made from days 11 through 14. RESULTS: High-density lipoprotein (HDL) cholesterol level was higher (7.6% +/- 2.9%; P =.02) and the LDL/HDL cholesterol ratio was lower (6.7% +/- 2.3%; P =.007) for cocoa-bran compared with low-fiber cereal at 2 weeks. No effect was seen on LDL cholesterol oxidation. Mean fecal output was significantly higher for cocoa-bran than for low-fiber cereal (56 +/- 14 g/d; P<.001) and equal to the increase seen in the same subjects with wheat fiber in a previous study. CONCLUSIONS: A chocolate-flavored cocoa-bran cereal increased fecal bulk similarly to wheat bran and was associated with a reduction in the LDL/HDL cholesterol ratio. In view of the low-fat, high-fiber nature of the material, these results suggest a possible role for this novel fiber source in the diets of normal, hyperlipidemic, and constipated subjects.
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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".