Region-specific establishment of bacterial communities in the small intestine of neonatal calves from birth
Bibliographic record
Abstract
Abstract Initial microbial colonization plays an important role in neonatal gut health. However, studies on gut microbial composition at birth are challenging, due to the limited access to accurate sampling. Here, we characterized the jejunal and ileal bacterial composition (epimural and luminal) of neonatal calves within 30 minutes after birth, and compared it with maternal (birth canal and rectum) and birth environments. RNA-based quantification along with amplicon sequencing revealed the colonization of active, dense (1.1–9.4 × 108 16S rRNA copy/g of sample), and diverse bacteria in the calf small intestine at birth. Pseudomonadaceae and Propionibacteriaceae dominated epimural communities, while Propionibacteriaceae, Prevotellaceae, Ruminococcaceae, and Lachnospiraceae dominated luminal communities. The composition of calf gut bacteria at birth was significantly different from maternal bacteria, especially for beneficial bifidobacteria. The bacterial communities of calf body habitats were similar to those of the birth environment, which was again divergent from gut microbiota. This study suggests an establishment of small intestinal-specific microbiota from birth, which is considerably deviated from maternal microbiota. In corollary, we further propose that small intestinal microbiota colonization could be mainly modulated by host selection.
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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 | 0.001 |
| 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".