Effect of Novel Maize-based Dietary Fibers on Postprandial Glycemia and Insulinemia
Bibliographic record
Abstract
BACKGROUND: Postprandial hyperglycemia has been associated with increased oxidative stress and the development of diabetes, heart disease and all-cause mortality. OBJECTIVE: To assess the effect of novel maize-based dietary fibers on postprandial glycemia and to assess the correlation between a rapid in vitro digestibility system and the blood glucose response. METHODS: In a clinical study, 12 healthy volunteers were fed seven test beverages containing maize-based fiber ingredients (25g total carbohydrate) along with 2 control meals on separate occasions in random order. Capillary blood samples were obtained and the relative glycemic and insulinemic responses were assessed by calculating the incremental area under the 2 h blood response curves. In vitro digestibility studies of the test fibers and control were also undertaken to determine if these correlated with the clinical findings. RESULTS: All test fibers resulted in significantly lower glycemic and insulinemic responses for the incremental area under the curve (iAUC) and at all time points compared with the control (P < 0.05). The in vitro digestibility curves were comparable to the cumulative in vivo iAUCs. In vitro data expressed as percent digestion correlated significantly with the in vivo iAUC for the first 30min of the test meal (P < 0.05). CONCLUSION: These novel maize-based dietary fibers all produce lower postprandial glycemic and insulinemic responses than the control. While further assessment is necessary in beverage and foods containing these fibers, they may be effective in applications for dietary strategies to control diabetes and other chronic diseases. In addition, the in vitro digestibility assay correlated well with in vivo data and may be useful in guiding product development.
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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) | 0.000 | 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".