Growth-promoting effects of caseinomacropeptide from cow and goat milk on probiotics
Bibliographic record
Abstract
Caseinomacropeptide (CMP), a 7-kDa phosphoglycopolypeptide fragment released from κ-casein during milk renneting, is heterogeneous with respect to post-translational glycosylation. Several studies have reported that CMP has growth-promoting activity on lactic acid bacteria belonging to the genera Bifidobacterium. The aim of this study was to evaluate the effect of glycosylation and sequence variations between bovine and caprine CMP on the growth of two probiotics: Lactobacillus rhamnosus RW-9595-M and Bifidobacterium thermophilum RBL67. The growth-promoting activities of CMP (mixture of glycosylated (gCMP) and non-glycosylated (aCMP) fractions), aCMP and gCMP were measured in a basal minimal culture medium using turbidimetric microplate assay at 37 °C. Supplementation of the culture media at 2 mg/ml significantly improved maximum growth by 1.5 to 1.8 times depending on the strain, the additive (CMP, aCMP, gCMP), and the bovine or caprine origin (P < 0.05). CMP preparations also decreased the time needed to reach the inflexion point of the growth curve and increase the cell density at that time (P < 0.05). The effects of CMP preparations were dose dependent and significantly superior to the effect of bovine β-lactoglobulin added to the culture media. As gCMP and aCMP were as efficient as bovine and caprine CMP (P > 0.1), it was concluded that the presence of oligosaccharides linked to CMP was not essential for growth-promoting activity of CMP.
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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 | 0.000 | 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) | 0.001 | 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".