Identification and Characterization of Gastrointestinal-Resistant Angiotensin-Converting Enzyme Inhibitory Peptides from Egg White Proteins
Bibliographic record
Abstract
Egg proteins are recognized as excellent sources of bioactive peptides, such as angiotensin-converting enzyme inhibitory (ACEi) peptides. Oral administration of a thermolysin-digested egg white hydrolysate (T-EWH) caused a significant blood pressure reduction in spontaneously hypertensive rats; a further ACEi assay implied that its ACEi activity was enhanced after in vitro gastrointestinal (GI) digestion. These results indicated that T-EWH contained ACEi peptides resisting GI digestion and/or being further released during GI digestion. Therefore, the objective of this study was to identify these responsible ACEi peptides from T-EWH. The conventionally activity-guided fractionation was applied, coupled with a synchronized GI digestion throughout, during which both peptide yield and ACEi activity before and after the GI digestion were measured. Finally, six ACEi peptides (LAPYK, LKISQ, LKYAT, INKVVR, LFLIKH, and LGHWVY) with good GI resistance were identified with IC 50 values <20 μM, especially LKYAT (0.09 μM). The structure–activity relationship of these peptides was discussed. The discovery of GI-resistant ACEi peptides could further support the application of egg white proteins as functional food ingredients.
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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) | 0.000 | 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 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".