Acute effects of pistachio consumption on postprandial glucose and insulin levels, oxidative stress, gut satiety hormone responses and endothelial function
Bibliographic record
Abstract
Background Nut consumption has been found to decrease risk of CHD, to improve control of type 2 diabetes and to promote healthy body weights, possibly related to their favorable fat, protein and antioxidant profiles. Previous studies have demonstrated that pistachios when included in meals decrease the postprandial glycemic response of carbohydrate foods. Methods 20 subjects, 40–65y, BMI>30kg/m 2 , with metabolic syndrome as defined by NCEP ATP III guidelines were recruited. Each subject participated in a total of 5 breakfast study meals over 5–10wks. Study meal order was randomized and were consumed after an overnight fast. Meal 1 was a control meal of white bread (50g available CHO). Meals 2 (white bread, butter and cheese) and 3 (white bread plus 3oz pistachios) had similar macronutrient profiles. Meals 4 (white bread) and 5 (3oz pistachios alone) had the same amount of available CHO (12g). Capillary finger‐prick and venous blood samples were taken and subjective satiety measures via a visual analogue scale were assessed along with endothelial function over the 3h study periods. Differences were assessed by least squares means with a Tukey adjustment for multiple comparisons.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".