Effect of Novel Grains as a source of ù‐3 Fatty Acids and Functional food Components on Major and Emerging Risk Factors for Cardiovascular Disease in Type 2 Diabetes
Bibliographic record
Abstract
Grains of the plant Salvia hispanica alba (Salba) contain a high concentration of ù‐3 fatty acids in addition to being a rich source of vegetable protein, fiber, calcium, magnesium, iron and antioxidants. Objective To determine whether the addition of Salba to the conventional treatment for diabetes improves major and emerging CVD risk factors in type 2 diabetes. Participants Twenty participants with type 2 diabetes (11M:9F, age 64±8 years, BMI 28±4 kg/m 2 , A1c 6.8±0.9%), were included in the final analyses. Design and Intervention Using a randomized, single blind, crossover design, participants received either Salba or a matched control for 12 weeks separated by a 4‐week washout period. Main Outcome Measures Efficacy (A1c, blood pressure, fibrinolysis and proinflammatory markers), safety (liver, kidney and haemostatic function), and compliance (plasma fatty acids, returned supplements, diet records, body weight) were assessed.. Results Over 86% of Salba and control supplements was consumed, without adverse effects. Salba did not effect glycemic control. Compared to the control, Salba significantly reduced systolic blood pressure by 9.25±4 mmHg (p<0.001) and markers of body inflammation (hs‐CRP, 32±8%l, p<0.05) and fibrinolysis (Factor VIII, 23±7%, p<0.04; VonWillebrand factor 21±6%, p<0.02). Conclusions Salba grain added to conventional treatment in a high‐risk type 2 diabetic population attenuates major CVD risk factors such as blood pressure as well as emerging CVD risk factors such as body inflammation and fibrinolysis. Research support Salba Research and Development, Toronto.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".