A Quinoa Protein Hydrolysate Fractionated by Electrodialysis with Ultrafiltration Membranes Improves Maternal and Fetal Outcomes in a Mouse Model of Gestational Diabetes Mellitus
Bibliographic record
Abstract
Scope Quinoa intake exerts hypoglycemic and hypolipidemic effects in animals and humans. Although peptides from quinoa inhibit key enzymes involved in glucose homeostasis in vitro, their in vivo antidiabetic properties have not been investigated. Methods and results This study evaluated the effect of oral administration of a quinoa protein hydrolysate (QH) produced through enzymatic hydrolysis and fractionation by electrodialysis with ultrafiltration membrane (EDUF) (FQH) on the metabolic and pregnancy outcomes of Lepdb/+ pregnant mice, a preclinical model of gestational diabetes mellitus. The 4‐week pregestational consumption of 2.5 mg mL −1 of QH in water prevented glucose intolerance and improves hepatic insulin signaling in dams, also reducing fetal weights. Sequencing and bioinformatic analyses of the defatted FQH (FQHD) identified 11 peptides 6–10 amino acids long that aligned with the quinoa proteome and exhibited putative anti‐dipeptidyl peptidase‐4 (DPP‐IV) activity, confirmed in vitro in QH, FQH, and FDQH fractions. Peptides homologous to mouse and human proteins enriched for biological processes related to glucose metabolism are also identified. Conclusion Processing of quinoa protein may be used to develop a safe and effective nutritional intervention to control glucose intolerance during pregnancy. Further studies are required to confirm if this nutritional intervention is applicable to pregnant women.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".