Transgenic milk containing recombinant human lactoferrin modulates the intestinal flora in piglets<sup>1</sup>This article is part of a Special Issue entitled Lactoferrin and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
Lactoferrin (LF) is a beneficial multifunctional protein in milk. The objective of this study was to determine whether bovine transgenic milk containing recombinant human lactoferrin (rhLF) can modulate intestinal flora in the neonatal pig as an animal model for the human infant. We fed 7-day-old piglets (i) ordinary whole milk (OM), (ii) a 1:1 mixture of OM and rhLF milk (MM), or (iii) rhLF milk (LFM). LFM provided better average daily mass gain than OM (P = 0.007). PCR-denaturing gradient gel electrophoresis and 16S rDNA sequencing analysis revealed that the LFM piglets exhibited more diversity of the intestinal flora than the OM group. Except for the colon in the LFM group, an increasing trend in microbial diversity occurred from the duodenum to the colon. Fecal flora was not different across different ages or different treatment groups, but a cluster analysis showed that the fecal flora of OM- and MM-fed piglets had a higher degree of similarity than that of LFM-fed piglets. Based on culture-based bacterial counts of intestinal content samples, concentrations of Salmonella spp. in the colon and of Escherichia coli throughout the intestine were reduced with LFM (P < 0.01). Concentrations of Bifidobacterium spp. in the ileum and of Lactobacillus spp. throughout the intestine were also increased with LFM (P ≤ 0.01). We suggest that rhLF can modulate the intestinal flora in piglets.
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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 | 0.001 |
| 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".