The acute effect of commercially available pulse powders on postprandial glycaemic response in healthy young men
Bibliographic record
Abstract
Whole pulses (beans, peas, chickpeas and lentils) elicit low postprandial blood glucose (BG) responses in adults; however, their consumption in North America is low. One potential strategy to increase the dietary intake of pulses is the utilisation of commercial pulse powders in food products; however, it is unclear whether they retain the biological benefits observed with whole pulses. Therefore, the present study examined the effects of commercially prepared pulse powders on BG response before and after a subsequent meal in healthy young men. Overall, three randomised, within-subject experiments were conducted. In each experiment, participants received whole, puréed and powdered pulses (navy beans in Expt 1; lentils in Expt 2; chickpeas in Expt 3) and whole-wheat flour as the control. All treatments were controlled for available carbohydrate content. A fixed-energy pizza meal (50·2 kJ/kg body weight) was provided at 120 min. BG concentration was measured before (0-120 min) and after (140-200 min) the pizza meal. BG concentration peaked at 30 min in all experiments, and pulse forms did not predict their effect on BG response. Compared with the whole-wheat flour control, navy bean treatments lowered peak BG concentrations (Expt 1, P< 0.05), but not the mean BG concentration over 120 min. The mean BG concentration was lower for all lentil (Expt 2, P= 0.008) and chickpea (Expt 3, P= 0.002) treatments over 120 min. Processing pulses to powdered form does not eliminate the benefits of whole pulses on BG response, lending support to the use of pulse powders as value-added food ingredients to moderate postprandial glycaemic response.
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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) | 0.001 | 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".