The glycemic index of pigmented potatoes is related to their polyphenol content
Bibliographic record
Abstract
Polyphenol extracts from coloured fruits and vegetables inhibit α-glucosidase in vitro, however it is not known whether this translates into an attenuation of blood glucose response in vivo. We examined this relationship in a GI study by feeding coloured potatoes to 9 healthy volunteers. We also examined the in vitro inhibitory activity of potato anthocyanin extracts on rat intestinal α-glucosidase. Potatoes (Purple Majesty; Red-Y38; Yukon Gold and Snowden) were fed with skin after cooking in a convection oven, using a random block design and 50 g available carbohydrate. Glucose was used as the standard and venous blood collected at 0, 15, 30, 45, 60, 90, 120 min. Areas under the curve (AUC) for glucose and insulin were calculated, and GI and Insulin Index derived. Neither AUC for blood glucose response nor insulin was significantly different among the various potatoes studied. Although the mean GI (±SE) values for the potato types varied (purple = 77.0 ± 9.0; red = 78.0 ± 14.0; yellow = 81.0 ± 16.0; and white = 93.0 ± 17.0), these differences were not significantly different. The mean (±SE) polyphenol content (mg GAE/100 g DW) was 234 ± 28; 190 ± 15; 108 ± 39; 82 ± 1 for purple, red, yellow and white potatoes, respectively. There was a significant inverse correlation between polyphenol content and GI of the potatoes (r = -0.825; p < 0.05; n = 4). In vitro, polyphenol extracts of red and purple potatoes inhibited α-glucosidase by 37.4 ± 2.2% and 28.7 ± 3.2%, respectively. The GI of coloured potatoes is significantly related to their polyphenol content, possibly mediated through an inhibitory effect of anthocyanins on intestinal α-glucosidase.
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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 | 0.001 |
| 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".