Cranberries improve postprandial glucose excursions in type 2 diabetes
Bibliographic record
Abstract
) (mean ± s.d.) = 39.5 ± 6.5; age (years) = 56 ± 6) revealed that postprandial increases in glucose were significantly lower in the cranberry vs. control at 2 & 4 h (p < 0.05). No significant differences were noted in insulin, insulin resistance evaluated by homeostasis model assessment, lipid profiles and blood pressure between the cranberry and control groups. Among the biomarkers of inflammation and oxidation, postprandial serum interleukin-18 and malondialdehyde were significantly lower at 4 h, and serum total nitrite was higher at 2 h in the cranberry vs. control group (all p < 0.05). No effects were noted on C-reactive protein or interlukin-6. Overall, dietary cranberries had notable effects in improving high-fat breakfast induced postprandial glucose and selected biomarkers of inflammation and oxidation in participants with T2DM. These findings provide evidence that adding whole cranberries to a high-fat meal may improve postprandial blood glucose management and warrant further investigation.
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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 | 0.000 |
| 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".