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Glycemic and insulinemic response to four different sweeteners in healthy individuals: A double blind, randomized controlled trial.

2013· article· en· W2560635302 on OpenAlexaff
Alexandra L. Jenkins, Kantha Shelke, Vladimir Vuksan, Thomas M.S. Wolever, Janice Campbell, Adish Ezatagha

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsGlycemic Index Laboratories
Fundersnot available
KeywordsPostprandialSucraloseErythritolSweetnessInsulinGlycemicSucroseFood scienceMealRebaudioside ACrossover studyMaltitolChemistryGlycemic indexSugarMedicineEndocrinologyPlacebo

Abstract

fetched live from OpenAlex

Background The non‐nutritive sweetener, erythritol, does not change postprandial glucose levels, whether this holds true for forms which are modulated to be more intensely sweet is not known. Objectives Comparison of the postprandial glucose and insulin responses of two erythritol products differing in sweetness intensity. Methods 15 healthy volunteers (6 M, 9F; 38±12 yr; 26.9±4.4kg/m 2 ) consumed 4 test meals consisting of 24g sucrose, 24g erythritol (Swerve ® Granular), 2.4g erythritol (Swerve ® 10x) and 3g sucralose (Splenda ® ) mixed with 200ml of water. All meals were matched for sweetness level. Capillary blood samples were taken fasting and at 15, 30, 45, 60, 90 and 120 min after the start of the meal. Results Postprandial glucose and insulin levels were significantly lower after the non‐nutritive sweeteners compared to sucrose at 15, 30 and 45 min. Glucose levels were also lower after both erythritol products compared to sucralose at 15 min. At 90 and 120min, glucose levels were significantly higher after the non‐nutritive sweeteners compared to sucrose (p<0.001). Incremental glucose and insulin areas were significantly lower after the three non‐nutritive sweeteners compared to sucrose (p<0.0001). Conclusions This study confirms that irrespective of sweetness level, consumption of erythritol does not raise postprandial blood glucose or insulin levels significantly.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.072
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.295
Teacher spread0.265 · 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 teacher head, 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
Published2013
Admission routes1
Has abstractyes

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