Technology Optimization, Antioxidant Activities and Characteristics of Peptide from Egg White
Bibliographic record
Abstract
In order to optimize enzymolysis technology for production of antioxidant peptides from egg white,the effects of enzyme activity,enzymolysis temperature,egg white content and pH were analyzed by orthogonal test with the scavenging rate of hydrolysate to DPPH radical as an index.Scavenging effects of the hydrolysate on hydroxyl radical,superoxide anion radical,lipid peroxidation and its total reduction capacity were investigated using ascorbic acid as controls,and its partial characteristics were also explored.Flavourzyme was screened out from four kinds of alkaline protease,neutral protease,trypsin and flavourzyme and enzymolysis time was 90 min.The optimum conditions were as follows:pH 5,enzymolysis temperature 45 ℃,egg white content 8% and enzyme activity 1 125 U.under such conditions,Scavenging rates of the hydrolysate on DPPH radical was 53.273%.Scavenging effects on hydroxyl(0.308 4～1.542 mg/mL) and superoxide anion radical(0.089～0.443 mg/mL) increased with its concontration,and their half inhibitory concentration(IC50) value was 0.092 mg/mL and 0.021 6 mg/mL for VC,1.24 mg/mL and 0.054 mg/mL for the hydrolysate,respectively.Inhibition effects of the hydrolysate to lipid peroxidation(0.667 ～10.667 mg/mL) decreased with increasing concentration,but it was activated within 0.667～10.667 μg/mL.Isoelectric point of the hydrolysate was about pH=3,scavenging effects of the hydrolysate on hydroxy radical decreased with increasing temperature,and its solubility increased linearly within pH 2～10.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".