Bioactive oat β-glucan reduces LDL cholesterol in Caucasians and non-Caucasians
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: There is increasing global acceptance that viscous soluble fibers lower serum LDL cholesterol (LDL-C), but most evidence for this comes from studies in Caucasians. To see if oat β-glucan lowers LDL-C in Caucasians and non-Caucasians we conducted a post-hoc analysis of the results of a randomized, controlled, double-blind, multi-center clinical trial whose primary aim was to determine if molecular-weight (MW) influenced the LDL-C-lowering effect of oat β-glucan. RESULTS: Caucasian and non-Caucasian subjects with LDL-C-C ≥ 3.0 and ≤ 5.0 mmol/L (n = 786 screened, n = 400 ineligible, n = 19 refused, n = 367 randomized, n = 345 completed, n = 1 excluded for missing ethnicity) were randomly assigned to consume cereal containing wheat-fiber (Control, n = 74:13 Caucasian:non-Caucasian) or 3 g high-MW (3H, 2,250,000 g/mol, n = 67:19), 4 g medium-MW (4 M, 850,000 g/mol, n = 50:17), 3 g medium-MW (3M, 530,000 g/mol, n = 54:9) or 4 g low-MW (4 L, 210,000 g/mol, n = 51:12) oat β-glucan daily for 4 weeks. LDL-C after 4 weeks was influenced by baseline LDL-C (p < 0.001) and treatment (p = 0.003), but not ethnicity (p = 0.74). In all subjects, compared to control, 3 H, 4 M and 3 M reduced LDL-C significantly by 4.8 to 6.5%, but 4 L had no effect. Compared to control, the bioactive oat β-glucan treatments (3H, 4M and 3M) reduced LDL-C by a combined mean (95% CI) of 0.18 (0.06, 0.31) mmol/L (4.8%, n = 171, p = 0.004) in Caucasians, a value not significantly different from the 0.37 (0.09, 0.65) mmol/L (10.3%, n = 45, p = 0.008) reduction in non-Caucasians. CONCLUSION: We conclude that oat β-glucan reduces LDL-C in both Caucasians and non-Caucasians; there was insufficient power to determine if the magnitude of LDL-C-lowering differed by ethnicity. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00981981.
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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 it