In Vitro Characterization of Fluted Pumpkin Leaf Protein Hydrolysates and Ultrafiltration of Peptide Fractions: Antioxidant and Enzyme-Inhibitory Properties
Bibliographic record
Abstract
fluted pumpkin leaf, protein hydrolysates, membrane ultrafiltration, antioxidant activity, antidiabetic activity, antihypertensive activity Hydrolysates were produced using Alcalase (AH), chymotrypsin (CH), pepsin (PH), and trypsin (TH), and also fluted pumpkin leaf protein isolate (FLI) as a substrate. AH had the lowest degree of hydrolysis (16.37%) but exhibited overall superior antioxidant and enzyme inhibitory properties. Therefore, it was fractionated by membrane ultrafiltration to give <1, 1-3, 3-5, 5-10, and >10 kDa peptide fractions. Gel permeation chromatography showed that the molecular weight of the FLI was 19.77 kDa and that of the hydrolysates was below 7.5 kDa. The hydrolysate peptides had a high content of hydrophobic amino acids but low levels of sulfur-containing amino acids, when compared to protein of FLI. Peptide sequence analysis showed that the hydrolysates consisted of dipeptides, tripeptides, and tetrapeptides with molecular weights below 500 Da. The hydrolysates were also stronger inhibitors of linoleic acid oxidation, -amylase, -glucosidase, and angiotensin converting enzyme (ACE) than FLI. Among the fractions, the <1 and 1-3 kDa were the most effective free radical scavengers and metal chelators in addition to their strong inhibitory activities against -amylase, -glucosidase, and ACE. We conclude that the AH and low molecular weight peptide fraction (<3 kDa) could find applications in formulating foods with various bioactive properties.
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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 | 0.000 |
| 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".