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Effect of an Optimized Savory Cluster on Glycemic and Insulinemic Responses in Healthy Individuals: a Randomized, Cross‐over Study

2016· article· en· W2962863051 on OpenAlexaff
Thomas M.S. Wolever, Alexandra L. Jenkins, Janice Campbell, Adish Ezatagha, Yang Pan, Mark Nisbet, L. J. Harkness-Brennan

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsGlycemic Index Laboratories
Fundersnot available
KeywordsPostprandialGlycemicMedicineFood scienceDiabetes mellitusGlycemic indexStarchCarbohydrateCluster (spacecraft)ObesityInsulinEndocrinologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Postprandial glycemia has been implicated in the development of chronic metabolic diseases such as obesity, type 2 diabetes mellitus and cardiovascular diseases. Foods with high contents of slowly digestible starch elicit lower glycemic responses have been proposed as better choices to help decrease postprandial glucose excursions and thus to improve glycemic control and health, For this reason, there is a growing interest in developing foods with slowly digestible starch, particularly for snacks. A low moisture, low temperature process was developed to produce a savory cluster snack (test‐cluster) containing nuts and grains and bound together with wheat starch and soluble fiber which is slowly digested in‐vitro . The objective of this study was to compare the glucose and insulin responses elicited by the test‐cluster to those of a control‐cluster made with ingredients commonly used in commercially available snacks or bars including oats, peanuts, puffed rice and corn syrup and an available‐carbohydrate matched portion of white‐bread in healthy subjects. Healthy men and women (n=25) were studied on 3 occasions using a randomized, cross‐over design. After 2 fasting finger‐prick blood samples, subjects consumed 1 serving (56g) of the test‐ or control‐cluster or 47g white‐bread and had blood glucose and serum insulin measured at intervals over the next 4 hr. Each serving of test‐cluster, control‐cluster and white‐bread, respectively, contained: 5, 5 and 4g protein; 12, 11 and 0.5g fat; 24, 33 and 24g available‐carbohydrate; and 10, 2 and 1g dietary fiber. The blood‐glucose peak‐rise and incremental area under the curve (AUC) after test‐cluster were significantly lower than those after both control‐cluster and white‐bread (mean±SEM; peak‐rise, 1.24±0.09 vs 2.27±0.13 and 2.27±0.16 mmol/L; AUC, 67±8 vs 117±10 and 114±9, respectively). The serum‐insulin peak‐rise and AUC after test‐cluster, 128±13 pmol/L and 6.10±0.73 nmol×min/L, were similar to those after white bread, 141±20 pmol/L and 6.47±1.11 nmol×min/L, but significantly less than those after the control‐cluster, 205±26 pmol/L and 9.60±1.31 nmol×min/L. It is concluded that a serving of test‐cluster elicits lower glucose and insulin responses than a serving of a similar control‐cluster. The results support the hypothesis that the carbohydrates in the test‐cluster are slowly digested and absorbed in‐vivo . Support or Funding Information This study is funded by PepsiCo, Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.317
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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