Inhibition of Intestinal Cellular Glucose Uptake by Phenolics Extracted from Whole Wheat Grown at Different Locations
Bibliographic record
Abstract
Whole grain consumption is associated with reduced risk of type 2 diabetes, and the underlying mechanism might be related to the actions of polyphenols. Dietary polyphenols contribute to low glycemic indices through inhibition of intestinal glucose transport proteins. This study has two objectives: (1) to evaluate how the contents of phenolic acids in wheat vary by genetic background and growth condition and (2) to evaluate how these changes translate into physiologic relevance by investigating cellular glucose transporter inhibitions. Phenolic acids were extracted from wheat varieties grown at different locations over two crop years. The degree of inhibition of glucose uptake into human Caco-2E cells was determined. Free and bound phenolic acid extracts of all wheat genotypes inhibited glucose uptake. Degree of glucose uptake inhibitions positively correlated with the contents of free and bound phenolic acids, and the correlation coefficients were R2=0.91 and R2=0.89 , respectively. Genotype and environment influenced the content of free and bound phenolic acids which linearly translated to the degree of glucose uptake inhibition in a model of intestinal absorption ( P<0.05 ). Results of this work mechanistically support the hypothesis that dietary phenols positively influence the glycemic index and therefore the health properties of whole grain consumption.
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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) | 0.000 | 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".