Исследование модуляции кристаллообразования биологической жидкости
Why this work is in the frame
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Bibliographic record
Abstract
The impact of high hydrostatic pressure (HHP) on protein digestibility of egg yolk and egg yolk granule was evaluated by static in vitro digestion using the standardized INFOGEST 2.0 method. The degree of hydrolysis (DH) and the phospholipid content were determined during digestion, and the protein and peptide profiles were characterized by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and reverse phase-high pressure liquid chromatography (RP-HPLC). The results showed that HHP induced protein aggregation in egg yolk and granule, mainly by disulfide bridges, which were not disrupted in the oral phase. Proteolysis during the gastric phase improved egg yolk and granule protein solubility, regardless of whether HHP was applied. However, the extent of the samples' digestibility was not affected, with DH values ranging from 15% to 20%. During the intestinal phase, the DH of egg yolk protein (∼40%) was higher than that of the granule (∼25%), probably due to the denser structure of the granule reducing the accessibility of intestinal enzymes. The DH, peptide, and protein profiles of control and HHP-treated egg yolk showed similar protein digestion behaviors for both gastric and intestinal phases. Among the different proteins, only the digestibility of β-phosvitin in HHP-treated granule was enhanced. Consequently, applying HHP to granules represents an interesting process that improves the digestibility of phosvitin with the potential to generate bioactive phosvitin-derived phosphopeptides. PRACTICAL APPLICATION: High hydrostatic pressure, mainly used as a preservation process, did not impair the nutritional quality of the egg yolk and granule proteins but improved the susceptibility of phosvitin (protein contained in egg yolk) proteolysis to produce bioactive phosphopeptides. Consequently, applying HHP to granules represents an interesting process that improves the digestibility of phosvitin.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it