Bioprocessing of common pulses changed seed microstructures, and improved dipeptidyl peptidase-IV and α-glucosidase inhibitory activities
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is a leading cause of death globally. T2DM patients experience glucose intolerance, and inhibitors of dipeptidyl peptidase IV (DPP-IV) and α-glucosidase are used as drugs for T2DM management. DPP-IV and α-glucosidase inhibitors are also naturally contained in foods, but their potency can be affected by the food matrix and processing methods. In this study, germination and solid-state fermentation (SSF) were used to alter pulse seed microstructures, to convert compounds into more bioactive forms, and to improve their bioaccessibility. Germination substantially modified the seed microstructure, protein digestibility, contents and profiles of phenolic compounds in all the pulses. It also increased DPP-IV and α-glucosidase inhibitory activities in chickpeas, faba beans and yellow peas. Compared to germination, SSF with Lactobacillus plantarum changed the content and the profile of phenolic compounds mainly in yellow peas and green lentils because of greater disruption of the seed cell wall. In the same pulses, heat treatment and SSF of flour increased DPP-IV and α-glucosidase inhibitory activities. The results of this study suggest that germination and SSF with L. plantarum are effective and simple methods for modulating phenolic and protein profiles of common pulses and improve the action on DPP-IV and α-glucosidase.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".