Bibliographic record
Abstract
Ovomucin, a key component in maintaining the viscous nature of egg white, is a glycoprotein contributing to 2-4% of the total egg albumin protein. Preparation of pure ovomucin remains a challenge due to the presence of coprecipitated proteins, mainly ovalbumin and lysozyme. The objectives of the study were to determine the effect of different salt concentrations on the extractability of ovomucin and to develop a simple method to purify ovomucin that could be adapted for further scale-up production. The protein compositions of ovomucin extracts were significantly affected by salt concentrations. The concentration of ovalbumin was increased, whereas that of lysozyme was decreased in the ovomucin extracts at increasing salt concentrations up to 500 mM; lysozyme was the major contaminant at low salt concentrations (<100 mM), whereas ovalbumin was the major contaminant at high concentrations (>or=200 mM). A 2-step method was developed for the first time to prepare ovomucin with a purity of greater than 90%. Egg white was first extracted in the presence of 100 mM NaCl at pH 6.0 to produce a precipitate containing moderate coprecipitated ovalbumin (14.6%) and lysozyme (15.9%); the contaminated proteins in the precipitate were further removed by using 500 mM NaCl. The yield of ovomucin was determined to be 400.2 mg/100 g of egg white. This 2-step method is simple, environmentally friendly, and easy for scale-up preparation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".