Supplementation of Conventional Therapy With the Novel Grain Salba (<i>Salvia hispanica L</i>.) Improves Major and Emerging Cardiovascular Risk Factors in Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To determine whether addition of Salba (Salvia hispanica L.), a novel whole grain that is rich in fiber, alpha-linolenic acid (ALA), and minerals to conventional treatment is associated with improvement in major and emerging cardiovascular risk factors in individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS: Using a single-blind cross-over design, subjects were randomly assigned to receive either 37 +/- 4 g/day of Salba or wheat bran for 12 weeks while maintaining their conventional diabetes therapies. Twenty well-controlled subjects with type 2 diabetes (11 men and 9 women, aged 64 +/- 8 years, BMI 28 +/- 4 kg/m2, and A1C 6.8 +/- 0.9%) completed the study. This study was set in the outpatient clinic of the Risk Factor Modification Center, St. Michael's Hospital, Toronto, Canada. RESULTS: Compared with the control treatment, Salba reduced systolic blood pressure (SBP) by 6.3 +/- 4 mmHg (P < 0.001), high-sensitivity C-reactive protein (hs-CRP) (mg/l) by 40 +/- 1.6% (P = 0.04), and vonWillebrand factor (vWF) by 21 +/- 0.3% (P = 0.03), with significant decreases in A1C and fibrinogen in relation to the Salba baseline but not with the control treatment. There were no changes in safety parameters including liver, kidney and hemostatic function, or body weight. Both plasma ALA and eicosapentaenoic polyunsaturated fatty acid levels were increased twofold (P < 0.05) while consuming Salba. CONCLUSIONS: Long-term supplementation with Salba attenuated a major cardiovascular risk factor (SBP) and emerging factors (hs-CRP and vWF) safely beyond conventional therapy, while maintaining good glycemic and lipid control in people with well-controlled type 2 diabetes.
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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) | 0.000 | 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 | 0.000 | 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".