Effect of milk protein composition of a model infant formula on the physicochemical properties of in vivo gastric digestates
Bibliographic record
Abstract
We investigated the effect of protein composition and, in particular, the presence of whey proteins or β-casein on the digestion behavior of a model infant formula using an in vivo piglet model. Three isocaloric diets optimized for piglets were prepared with the same concentrations of protein. For protein source, 1 diet contained only whey proteins and 2 contained a casein:whey protein ratio of 40:60 but differed in the amount of β-casein. To obtain the desired protein compositions, skim milk was microfiltered at 7 or 22°C, and retentates and permeates were combined with whey protein isolate. The diets were optimized to the nutritional needs of the piglets and fed to 24 newborn piglets for 18 d. Eight piglets were also fed ad libitum with sow milk and considered only as reference (not included in the statistical analysis). The study was carried out in 2 blocks, killing the animals 60 and 120 min after the last meal. All gastric contents, regardless of diet, showed a wide range of pH. Postprandial time did not affect the pH or physical properties of the gastric digesta. The digesta from whey protein-casein formulas showed significantly higher viscosity, a higher storage modulus, and a denser microstructure than digesta obtained from piglets fed whey protein formula. The β-casein:total casein ratio at the level used in this study did not significantly affect the physical and chemical properties of the stomach digestate. Although caseins showed extensive gastric hydrolysis, whey proteins remained largely intact at both postprandial times. The results indicate that the presence of different concentrations of milk proteins can be critical to the digestion properties of the food matrix and may affect the nutritional properties of the components.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".