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Acute Effects of Pea Fractions in Extruded Cereals on Glycemic and Insulin Responses in Adults

2017· article· en· W3158319906 on OpenAlexaffabout
Alie Johnston, Dianna Omer, Rebecca C. Mollard, Dylan MacKay, Nancy Ames, Julianne Curran, Danielle R. B̀ouchard, Peter J.H. Jones

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of New BrunswickManitoba Beekeepers' AssociationCargill (Canada)University of Manitoba
Fundersnot available
KeywordsPea proteinStarchGlycemicMealFood scienceCrossover studyWheat flourChemistryGlycemic indexDietary fibreInsulinBiologyMedicineBiotechnology

Abstract

fetched live from OpenAlex

The beneficial effects of consuming pulses on glycemic control are well established; however, research examining the effects of pulse fractions incorporated into extruded products is limited. The objectives of this study were to assess the effects of replacing oat flour with pea fractions in extruded cereals on post‐prandial glycaemia and insulin before and after a meal consumed at 120 min. In a randomized, repeated‐measures crossover trial, adults (n = 26) consumed cereals (35g) made with: 1) oat flour (control), 2) oat flour and pea starch (starch), 3) oat flour and pea protein (protein), 4) oat flour, pea starch and pea protein (starch+protein), 5) oat flour, pea fibre and pea protein (fibre+protein), and 6) pea fibre, pea starch and pea protein (fibre+starch+protein). Blood glucose (BG) and insulin incremental area under the curve (iAUC) was calculated pre‐meal (0– 120 min) and post‐meal (120–200 min). For pre‐meal overall mean BG, there was a time (p<0.0001), treatment (p<0.0001) and time‐by‐treatment effect (p<0.0001). During the pre‐meal period, the protein, fibre+protein and fibre+starch+protein cereals resulted in a lower (p<0.05) overall mean BG response compared to starch and control cereals. The starch+protein cereal also resulted in a lower (p<0.05) overall mean BG response compared to control. There was also a treatment effect on pre‐meal BG iAUC (p<0.0001); protein, fibre+protein and fibre+starch+protein cereals resulted in a lower (p<0.05) BG iAUC compared to control and starch cereals. Starch+protein also had a lower (p<0.05) pre‐meal BG iAUC compared to starch cereal. For post‐meal BG, there was a time (p<0.0001), treatment (p<0.05), but no time‐by‐treatment effect. There was also an effect of treatment on post‐meal iAUC (p<0.05). However, for both post‐meal BG overall mean and iAUC, posthoc testing did not identify differences between treatments. For pre‐meal overall mean insulin, there was a time (p<0.0001), treatment (p<0.0005), and time‐by‐treatment effect (p=0.001). During the pre‐meal period, fibre+protein led to a lower insulin response compared to control (p<0.05), starch+protein (p<0.05), and protein (p=0.001) cereals. Fibre+starch+protein also led to lower pre‐meal insulin compared to protein cereal (p<0.05). There was also a treatment effect on pre‐meal insulin iAUC (p<0.05); fibre+protein resulted in lower (p<0.05) insulin compared to control cereal. For post‐meal overall insulin (120–200 min), there was a time (p<0.0001), but no treatment (p=0.47) or time‐by‐treatment effect (p=0.52). There were no effects on post‐meal insulin iAUC. These findings indicate that benefits of replacing oat with pulse fractions in extruded cereals on BG and insulin are dependent on fraction type. The protein+fibre and fibre+starch+protein resulted in both decreased BG and insulin levels. Data support the use of pea fractions in extruded products designed to improve post‐prandial glycemic control. Support or Funding Information Saskatchewan Pulse GrowersAlberta Pulse Growers

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.288
Teacher spread0.268 · 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 designObservational
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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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