Shift of hindgut microbiota and microbial short chain fatty acids profiles in dairy calves from birth to pre-weaning
Bibliographic record
Abstract
This study aimed to characterize mucosa- and digesta-associated microbiota in the hindgut (cecum, colon and rectum) of newborn (NB, n = 6), day 7 (n = 6), day 21 (n = 6) and day 42 (n = 6) Holstein bull calves using amplicon sequencing. The hindgut microbiota was diverse at birth, and mucosa-attached microbial community had higher individual variation than that of digesta-associated community. In total, 16 phyla were identified with Firmicutes, Bacteroidetes and Proteobacteria being the dominant microbial taxa in the hindgut. Quantitative real-time PCR analysis showed a significant age effect on the proportion of mucosa-attached Escherichia coli, Bifidobacterium, Clostridium cluster XIVa and Faecalibacterium prausnitzii. Especially, high abundance of mucosa-associated Escherichia was detected during the first week of life, suggesting higher chance of the pathogenic infection during this stage. The relative abundances of predicted microbial genes involved in amino acid metabolism, carbohydrate metabolism and energy metabolism were enriched, indicating the importance of hindgut microbiota in fermentation during the pre-weaned period. Moreover, the significant correlation between short-chain fatty acid concentration and mucosa-attached carbohydrate utilizing (Coprococcus 1, Blautia, Lachnospiraceae NC2004 group, etc.) and health-related bacteria (Escherichia-Shigella and Salmonella) suggests the importance of hindgut microbiota in the fermentation and health of dairy calves during pre-weaned period.
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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".