Effects of different satiety levels on the fate of soymilk protein in gastrointestinal digestion and antigenicity assessed by an <i>in vitro</i> dynamic gastrointestinal model
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Bibliographic record
Abstract
This study was designed to compare the effects of different satiety levels on the digestion and antigenicity of soymilk protein. The DIVRSD-II dynamic in vitro digestion model (DIVD) was employed to simulate different satiety degrees by changing the amount of food intake, namely full satiety (DIVD-FS), semi-satiety (DIVD-SS) and limited-satiety (DIVD-LS). A standardized static in vitro digestion method (SIVD) was used as a reference. Coupled with 60 min of gastric digestion and 120 min of intestinal digestion, the pH, particle size, soluble protein content, peptide content, gel electrophoresis, and antigenicity of soymilk digesta were monitored. The results showed that different satiety degrees altered soymilk protein digestive patterns in terms of gastric transit time, hydrolysis degree and antigenicity. The results of soluble protein content suggested that soymilk protein in DIVD-FS showed faster gastric transition than DIVD-SS and DIVD-LS. Gel electrophoresis and peptide content indicated that DIVD-FS digesta showed predominantly lower hydrolysis degrees in gastric and early intestinal stages. This further led to the persistence of major allergens at the early stage of intestinal digestion for DIVD-FS digesta. Soymilk protein digested using SIVD showed mostly intermediate values which indicated a good reference to the different satiety degrees of DIVD, although a descriptive result was obtained at early intestinal digestion. The results of this study showed for the first time the effect of different satiety degrees on hydrolysis kinetics, digestive degree and antigenicity of soy protein. The results suggested that the knowledge-base of soy protein digestibility depends on different satiety degrees and will be useful for guiding a healthy diet mode.
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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) | 0.000 | 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 it