Dose response effect of almond consumption on serum fatty acid profile and coronary heart disease risk: a randomized controlled crossover trial
Bibliographic record
Abstract
Background Consumption of almonds, has been associated with decreased risk of coronary heart disease (CHD), which may be related to their fatty acid (FA) composition. Methods 27 hyperlipidemic subjects consumed three iso‐energetic (mean 423 kcal/d) supplements in 1‐month phases: 1. full‐dose almonds (50–100g/d); 2. half‐dose almonds with half‐dose muffins; and 3. full‐dose muffins. Fasting blood was obtained at weeks 0 and 4 of each treatment and FA concentrations analyzed by TLC and GC. Results On both the half‐ and full‐dose almond supplements, the % oleic acid (OA) and monounsaturated FA (MUFA) increased in the triacylglycerol (TG) fraction (OA: P=0.003, P<0.001; MUFA: P=0.004, P<0.001, respectively) and in the free fatty acid (FFA) fraction (OA: P=0.01, P=0.12; MUFA: P=0.04, P=0.06). In both the TG and FFA fractions, MUFAs were positively associated with HDL‐C (P=0.03, P=0.003), OA and MUFA were inversely associated with ten year risk of CHD (OA: P=0.059, P=0.03; MUFA: P=0.048, P=0.01), while saturated FA were inversely associated with HDL‐C (P<0.05) and positively associated with 10 year CHD risk (P<0.05). Conclusion Almond consumption increased the OA and MUFA content in the serum TG and FFA fractions, which were inversely associated with CHD lipid risk factors and overall 10 year CHD risk. Supported by the Almond Board of California, Modesto, CA
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".