Barley beta‐Glucan Consumption Decreases Serum Cholesterol Level and Increases 7 alpha‐Hydroxy‐4‐Cholesten‐3‐One Level in Hypercholesterolemic Adults
Bibliographic record
Abstract
Interrupting bile acid metabolism has been proposed as a possible mechanism of cholesterol‐lowering effects of barley β‐glucan in humans. Measuring bile acid intermediate 7α‐hydroxy‐4‐ cholesten‐3‐one (7αHC) provides an indication of bile acid synthesis rate. The aim of this study was to determine whether interruption of bile acid metabolism is responsible for the cholesterol‐lowering effect of barley β‐glucan. In a controlled, four phase crossover trial, mildly hypercholesterolemic subjects (n=29) were randomly assigned to receive breakfast containing 5g low molecular weight (MW), 3g high MW, 3g low MW barley β‐glucan or a control, each for 5 weeks. Serum total cholesterol levels were reduced 0.39mmol/l, 0.55 mmol/l and 0.48mmol/l and LDL levels were reduced 0.20mmol/l, 0.31 mmol/l and 0.25mmol/l from baseline by these three barley treatment diets, respectively (p<0.05). 3g high MW resulted in greatest reduction in serum cholesterol and LDL levels. 7αHC levels were increased by 18.3 %, 39.7% and 32.2% by these three barley treatments, respectively, compared with control (p<0.05). For between‐group differences, 3g high MW increased 7α HC significantly compared to control (44.1 mmol/l vs.39.0 mmol/l). In conclusion, high MW barley β‐glucan resulted in greater reduction in cholesterol levels and increased 7α HC levels compared to low MW. Interference of bile acid metabolism may be the mechanism of cholesterol lowering for barley β‐glucan. Increasing MW may increase the cholesterol‐lowering bioactivity of barley β‐glucan. Supported by Growing Forward Agriculture and Agri‐Food Canada
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".