Acute Effects of Lentil Fractions on Satiety and Glycemic Responses Before and After a Meal in Healthy Young Men
Bibliographic record
Abstract
Aims Lentils are a rich source of nutrients and are high in protein, starch and dietary fiber, which promote certain health benefits, such as reducing post prandial glycemia and subsequent food intake (second meal effect). However, it remains unclear which component(s) are responsible for these effects. Therefore, the present study examined the effects of consuming lentil preparations of increased macronutrient content (fiber, starch and protein) on subjective appetite, blood glucose (BG) and insulin before and after a pizza meal, served either 30 or 120 min later, in healthy young men. Methods Two randomized, cross over, repeated measures experiments were conducted. Forty eight healthy males consumed iso‐volumetric (300 ml) tomato soup alone (control), or with the addition of 20 g of one of the following lentil preparations: lentil protein (75%) isolate, lentil protein (55%) concentrate, lentil starch (60%) or lentil fiber (55%). Treatment consumption was followed by a fixed‐energy pizza meal (12 kcal/kg body weight), served at either 30 minutes (exp‐1) or 120 minutes (exp‐2) later. Results In exp‐1, with the exception of the increase in pre‐meal BG after the lentil starch preparation (p<0.0001), there was no effect of treatment composition. The lentil protein isolate and concentrate, but not lentil starch or lentil fiber, treatments lowered post‐meal glycemia compared to the control (P<0.0001) without increasing blood insulin concentrations. No effects were seen on pre‐meal measures of satiety; however, in addition to post‐meal BG subjective appetite was also lower (P<0.05) after consumption of both lentil protein isolate and concentrate compared to the control. In contrast to exp‐1, lentil starch resulted in lower pre‐ and post‐meal subjective appetite compared to the control in exp‐2 (P<0.05); however, consumption of lentil starch also led to higher BG values. The post‐meal effects of the lentil protein preparations on lowering blood glucose were greater after the 120 min than 30 min meal. Conclusion Lentil protein is the macronutrient that contributes most to the low glycemic properties of lentils. Additions of these, or similar preparations, to high glycemic foods may aid in post‐prandial glucose control. Support or Funding Information This study was supported by Agriculture and Agri‐Food Canada (AAFC) and Saskatchewan Pulse Growers (SPG), Canada, Reference 497290
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 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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".