Egg proteins: fractionation, bioactive peptides and allergenicity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Eggs are an important source of macro and micronutrients within the diet, comprised of proteins, lipids, vitamins, and minerals. They are constituted by a shell, the white (containing 110 g kg −1 proteins: ovalbumin, ovotransferrin, ovomucoid, lysozyme and ovomucin), and the yolk (containing 150–170 g kg −1 proteins: lipovitellins, phosvitin, livetins, and low‐density lipoproteins). Owing to their nutritional value and biological characteristics, both the egg white and yolk proteins are extensively fractionated using different techniques (e.g., liquid chromatography, ultrafiltration, electrophoresis, and chemical precipitation), in which liquid chromatography is the most commonly used technique to obtain individual proteins with high protein recovery and purity to develop novel food products. However, concerns over allergenic responses induced by certain egg proteins (e.g., ovomucoid, ovalbumin, ovotransferrin, lysozyme, α ‐livetin, and lipoprotein YGP42) limit their widespread use. As such, processing technologies (e.g., thermal processing, enzymatic hydrolysis, and high‐pressure treatment) are investigated to reduce the allergenicity by conformational changes. In addition, biological activities (e.g., antioxidant, antimicrobial, antihypertensive, and anticancer activities) associated with egg peptides have received more attention, in which enzyme hydrolysis is demonstrated as a promising way to break polypeptides sequences and produce bioactive peptides to provide nutritional and therapeutic benefits for human health. © 2018 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.
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 it