Taxonomic Identification of Commensal Bacteria Associated with the Mucosa and Digesta throughout the Gastrointestinal Tracts of Preweaned Calves
Bibliographic record
Abstract
Bacterial colonization in the gastrointestinal tracts (GIT) of preweaned calves is very important, since it can influence early development and postweaning performance and health. This study investigated the composition of the bacteria along the GIT (rumen, jejunum, ileum, cecum, and colon) of preweaned bull calves (3 weeks old) using pyrosequencing to understand the segregation of bacteria between the mucosal surface and digesta. Phylogenetic analysis revealed that a total of 83 genera belonging to 13 phyla were distributed throughout the GIT of preweaned calves, with the Firmicutes, Bacteroidetes, and Proteobacteria predominating. Quantitative PCR (qPCR) analysis of selected abundant bacterial genera (Prevotella, Bacteroides, Lactobacillus, and Faecalibacterium) revealed that their prevalence was significantly different among the GIT regions and between mucosa- and digesta-associated communities. Rumens contained the most diverse bacterial population, consisting of 47 genera, including 16 rumen-specific genera, followed by the large intestine and then the small intestine. Bacterial species richness was higher at the mucosal surface than in the local digesta, with the exception of the rumen. The majority of bacteria found on the rumen epithelial surface and within the small intestine could not be identified due to a lack of known genus-level information. Thus, future studies will be required to fully characterize the microbiome during the development of the rumens and the mucosal immune systems of newborn calves. This is the first study to analyze in depth the bacterial composition of the GIT microbiome in preweaned calves, which extends previous findings regarding early rumen colonization and bacterial segregation between mucosa- and digesta-associated microbial communities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".