Effect of milk protein composition and amount of β-casein on growth performance, gut hormones, and inflammatory cytokines in an in vivo piglet model
Bibliographic record
Abstract
The objective of this work was to better understand the effect of differences in milk protein composition, and specifically, a change in β-casein to total casein in a milk-based matrix, on growth performance and metabolic and inflammatory responses using a piglet model. Three formulas were optimized for piglets, with similar metabolizable energy, total protein content, and other essential nutrients. Only the protein type and ratio varied between the treatments: the protein fraction of the control diet contained only whey proteins, whereas 2 other matrices contained a whey protein to casein ratio of 60:40, and differed in the amount of β-casein (12.5 and 17.1% of total protein). Piglets fed formula containing whey proteins and caseins, regardless of the concentration of β-casein, showed a significantly higher average daily gain, average daily feed intake, and feed efficiency compared with piglets consuming the formula with only whey protein. Consumption of the formula containing only whey protein showed higher levels of plasma glucagon-like peptide-1 and ghrelin compared with the consumption of formula containing casein and whey protein. A positive correlation was observed between postprandial time and glucagon-like peptide-1 response. The intestinal pro-inflammatory cytokine tumor necrosis factor α increased significantly in piglets fed the whey protein/casein diet compared with those fed whey protein formula. All formula-fed piglets showed a lower level of IL-6 cytokine compared with the ad libitum sow-fed piglets, regardless of composition. No significant differences in the anti-inflammatory IL-10 concentration were observed between treatment groups. Milk protein composition contributed to the regulation of piglets' metabolic and physiological responses, with whey protein/casein formula promoting growth performance and a different immune regulatory balance compared with a formula containing only whey protein. Results indicated no differences between treatments containing different levels of β-casein.
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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 | 0.000 |
| 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 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".