Gastro-intestinal Digestibility of Processed Forms of Cow’s Milk Proteins under Simulated Infant and Adult Conditions Characterised by in vitro Methods
Bibliographic record
Abstract
Human digestion involves chemical, biochemical and fermentative processes integrated to achieve optimal nutrient absorption along the gastro-intestinal (GI) tract. In particular, efficient gastro-intestinal enzymatic digestion of proteins is critical for maximum upper intestinal protein absorption and may influence the distribution of dietary protein between the ‘host’ and microbiota. However, the relative efficiency of infant versus adult conditions of GI digestion of cow’s milk products have not been systematically studied. Conditions for in vitro GI enzymatic digestion, optimised for either infant or adult conditions, were applied to test pasteurised, skimmed milk, skimmed milk powder (SMP) and whey and casein protein fractions of cow’s milk. Research methods included digestion monitoring by o-phthaldialdehyde (OPA) derivitisation of peptides and free amino acids, and digestate analysis to characterise low mass ‘absorbing’ products (size exclusion chromatography) and larger non-absorbing products (700-3500 Da) by MALDI-TOF-MS. The results demonstrated significantly lower digestion efficiency for infant versus adult digestion conditions, particularly in the gastric phase. Digestibility of pasteurised milk and SMP were generally lower than either whey or casein protein fractions. Lower overall protein digestibility was associated with lower and higher proportions of ‘absorbing’ and ‘non-absorbing’ peptides, respectively. The higher yield of ‘non-absorbing’ peptides for infant digestion may permit strategic release of peptides with receptor-antagonistic bioactivity along the gut, and/or may promote supply of nitrogen for the microbiota. The favouring of digestion-resistant peptides to the colon due to processing requires further research to also investigate potential negative relationships with health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".