Effect of different concentrations of calcium chloride and potassium chloride on egg white proteins during isoelectric precipitation of ovomucin
Bibliographic record
Abstract
The effect of various concentrations of CaCl2 and KCl on egg white proteins during isoelectric precipitation of ovomucin was investigated in this study. At low concentrations of CaCl2 (<50 mM), lysozyme was the major contaminant in the precipitated ovomucin, whereas ovalbumin was the predominant one at high concentrations (>or=100 mM). At 50 mM CaCl2 concentration, the concentrations of both lysozyme and ovalbumin were moderate. Ovomucin with a purity of 97.3% was prepared using a 2-step method: egg white was first precipitated in the presence of 50 mM CaCl2 followed by a second 500 mM CaCl2 extraction. The concentrations of other proteins in the precipitate were 1.3% of ovalbumin, 1.1% of lysozyme, and 0.4% of ovomucoid. Unlike CaCl2-treated samples, ovotransferrin was found to be the second major contaminant in all KCl-treated precipitates. Compared with the control, adding KCl at the lowest concentration of 2.5 mM increased significantly the content of ovalbumin (from 7.6 to 68.0%) and reduced significantly the content of lysozyme (from 25.5 to 6.4%) in the precipitates; however, increasing the concentrations of KCl up to 500 mM did not affect the content of ovalbumin, but the content of lysozyme showed a general reduction trend. Although KCl was used widely in literature as the last step of ovomucin washing, our results show that KCl is not an efficient salt in purifying ovomucin.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".