Inhibitory properties of bambara groundnut protein hydrolysate and peptide fractions against angiotensin‐converting enzymes, renin and free radicals
Bibliographic record
Abstract
Abstract BACKGROUND An increased rate of high blood pressure has led to critical human hypertensive conditions in most nations. In the present study, bambara protein hydrolysates ( BPHs ) obtained using three different proteases (alcalase, trypsin and pepsin) and their peptide fractions (molecular weight: 10, 5, 3 and 1 kDa ) were investigated for antihypertensive and antioxidant activities. RESULTS Alcalase hydrolysate contained the highest amount of low molecular weight ( LMW ) peptides compared to pepsin and trypsin hydrolysates. LMW peptides fractions (<1 kDa ) exhibited the highest inhibitory activity against angiotensin‐converting enzyme ( ACE ) for all the enzymes hydrolysates. For renin inhibition, alcalase hydrolysate showed the highest inhibition at 59% compared to other hydrolysates and their corresponding membrane fractions. The antioxidant power of bambara protein hydrolysates and peptide fractions was evaluated through the inhibition of linoleic acid peroxidation and ABTS scavenging activity. Among the hydrolysates, alcalase exhibited the highest inhibition of linoleic acid oxidation. Furthermore, all BPHs were able to scavenge ABTS •+ to a three‐fold greater extent compared to the isolate. CONCLUSION BPH and LMW peptide fractions could potentially serve as useful ingredients in the formulation of functional foods and nutraceuticals against high blood pressure and oxidative stress. © 2016 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".