Study of the acute impact of polyphenols from brown seaweeds on glucose control in healthy men and women
Bibliographic record
Abstract
This study examined the acute impact of polyphenols from brown seaweeds on post‐load plasma glucose and insulin concentrations in healthy subjects. Twenty‐three participants (11 men, 12 women) aged 24–55 years were recruited in this double‐blind randomized placebo controlled study. The test product consisted of two 500mg capsules of InSea2™, a commercial mix of polyphenols from brown seaweeds with known inhibitory action on α‐amylase and α‐glucosidase activities. Polyphenol and placebo capsules were consumed on each occasion 30 minutes prior to consumption of 50 g of available carbohydrates from bread. Plasma glucose and insulin concentrations were measured over a period of three hours post carbohydrate ingestion at pre‐specified time points. Both treatments were separated by one week. Acute consumption of the seaweed polyphenol mixture was not associated with any adverse event. Compared with placebo, acute consumption of seaweed polyphenols was associated with a non significant 3.6% reduction in the area under the curve (AUC) of plasma glucose concentration (P=0.16), a 5.9% reduction in the insulin AUC (P=0.031) and a 6.9% increase in the Cederholm index of insulin sensitivity (P=0.047). Responses were similar in men and women. These data suggest that polyphenols from brown seaweeds may alter the acute glycemic and insulin response to carbohydrate ingestion. Funding: innoVactiv Inc.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".