Thermoase‐hydrolysed pigeon pea protein and its membrane fractions possess in vitro bioactive properties (antioxidative, antihypertensive, and antidiabetic)
Bibliographic record
Abstract
Enzymatic hydrolysis can liberate bioactive peptides from protein materials, thus, pigeon pea was hydrolysed using thermoase. Crude hydrolysate (PPHT) was subjected to ultrafiltration using different molecular weight cutoffs to collect <1, 1–3, 3–5, 5–10, and >10 kDa peptide fractions. Fractions were analysed for in vitro antioxidative, antihypertensive, and antidiabetic properties. The peptide fractions had stronger DPPH• scavenging and renin inhibition when compared to PPHT. In contrast, ACE inhibition was stronger for the PPHT and <1 kDa peptide fraction while activity decreased as peptide size increased. The <1 kDa peptide also showed significantly stronger ferric reducing antioxidant power, OH• scavenging and inhibition of linoleic acid oxidation when compared to PPHT. α-amylase and α-glucosidase were inhibited by all the peptide fractions, though the 3–5 and >10 kDa had higher values. We conclude that the PPHT and peptide fractions could serve as potential ingredients to formulate antihypertensive and antidiabetic functional foods and nutraceuticals. Practical applications Oxidative stress promotes the generation of free radicals, which have a significant impact in the pathogenesis of human chronic diseases such as cardiovascular impairment, cancer, and diabetes. Peptides generated from enzymatic hydrolysis of proteins have been identified to impart beneficial health effects. In this work, we showed that a thermoase digest of pigeon pea protein as well as the fractionated peptides had strong antioxidant properties in addition to exhibiting inhibitory activities against renin and angiotensin converting enzyme, the main therapeutic targets for antihypertensive agents. The peptide products also inhibited α-amylase and α-glucosidase activities, providing potential ingredients that can be used to formulate antidiabetic functional foods.
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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".