Investigating the relationship between lentil carbohydrate fractions and in vivo postprandial blood glucose response by use of the natural variation in starch fractions among 20 lentil varieties
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Bibliographic record
Abstract
Consumption of pulses is associated with many health benefits by mechanisms that are not fully understood. This study sought to identify the starch component(s) in cooked lentils responsible for lowering postprandial glycemic response (PPGR). Rapidly digestible (RDS), slowly digestible (SDS) and resistant starch (RS) content of 20 varieties of cooked lentil were determined by in vitro methods and 8 varieties, representing a linear range of SDS, were chosen for a human trial with 10 participants to determine PPGR and glycemic index (GI). Among the 20 lentil varieties, RS accounted for 35% of the variation of in vitro area under the starch hydrolysis curve (SHAUC) (r = -0.587; p < 0.01), but RDS (r = 0.401; p = 0.080) and SDS (r = -0.022; p = 0.927) were not significantly related to SHAUC. Multiple linear regression of in vitro data resulted in an equation [SHAUCest = 30.9RDS - 63.6RS + 9680] that accounted for 70% of the variance in SHAUC, with SDS excluded due to collinearity. In the human trial all 8 lentils had low GI values (10 to 23). Neither GI nor area under the glucose response curve (AUC) was significantly related to RDS, SDS or RS (minimum p = 0.24). However, SHAUC and SHAUCest, respectively, were related to both GI (r = 0.704, p = 0.051; r = 0.773, p = 0.024) and AUC (r = 0.765, p = 0.027; r = 0.822, p = 0.012). These results confirm that lentils have low GI values, which is not reliably predicted by their RDS, SDS and RS contents when considered individually. However, in vitro SHAUC and a combination of RDS and RS may be predictive of the PPGR of lentils.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it