Effect of almond consumption on the serum fatty acid profile: a dose response study
Bibliographic record
Abstract
Background Studies indicate that diets high in monounsaturated fatty acids (MUFA) can improve the blood fatty acid profile, by elevating oleic acid concentrations, and as such, relate to a decreased risk of coronary heart disease (CHD). Almonds are a good source of MUFA. Objective To assess the dose‐response effect of almonds compared to low‐fat muffins on the blood fatty acid profile and blood lipid risk factors of CHD in hyperlipidemic subjects. Design In a randomized controlled crossover study, 27 hyperlipidemic men and women consumed three iso‐energetic (mean 423 kcal/d) supplements in one‐month phases. The supplements consisted of full‐dose almonds (50–100g/d), half‐dose almonds with half‐dose muffins, and full‐dose muffins. Fasting blood was obtained at weeks 0 and 4 of each treatment. Results On both the half‐ and full‐dose almond supplements, there were significant increases in the oleic acid fraction of the blood lipid fractions. In addition, significant reductions were seen, respectively, for Total‐C (P=0.035; P=0.002), LDL‐C (P=0.021; P<0.001), Total:HDL‐C (P=0.003; P<0.001) and LDL:HDL‐C (P=0.002; P<0.001) with increases in HDL‐C (P=0.021; P=0.014). Conclusion Almond consumption significantly increased the oleic acid content of the blood lipid fractions and significantly improved blood lipid risk factors for CHD. (Funded by the Almond Board of California)
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".