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 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 | 0.000 |
| 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".