Optimization and Scale‐Up Preparation of Egg White Hydrolysate with Angiotensin I Converting Enzyme Inhibitory Activity
Bibliographic record
Abstract
Abstract Angiotensin I converting enzyme (ACE) plays an important role in regulation of blood pressure as it converts angiotensin I into angiotensin II (a potent vasoconstrictor). Food protein‐derived ACE inhibitory peptides have been considered as a safer alternative to antihypertensive drugs. In our previous study, three ACE inhibitory peptides were characterized from egg white ovotransferrin and their antihypertensive activity has been validated in spontaneously hypertensive rats. However, it is too costly to prepare these peptides from purified egg white ovotransferrin. The aims of the study were to determine the feasibility of preparing these peptides using egg white and then to optimize the conditions of preparing egg white hydrolysate. Taguchi's method was used to design experiments for optimization, which was established as follows: substrate %, pH of thermoase, time of thermoase digestion, ratio of pepsin to substrate, pH of pepsin, temperature of pepsin, and time of pepsin digestion were 7.5%, pH 8, 90 min, 1%, pH 2.5, 55 °C, and 180 min, respectively. The ACE inhibitory activity (IC 50 value) and peptide yield obtained under optimal condition were 30 ± 2 μg/mL and 77.5% ± 0.3%, respectively, which were comparable to the predicted values. Hydrolysate prepared at 150 L reactor showed comparable activity but low peptide yield. Results of this study demonstrated the feasibility of using egg white protein as the starting material to prepare a functional ingredient with potent ACE inhibitory activity.
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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 | 0.001 | 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".