Comparative studies of microbial populations in the rumen, duodenum, ileum and faeces of lactating dairy cows
Bibliographic record
Abstract
AIMS: Understanding factors that influence the composition of microbial populations of the digestive system of dairy cattle will be key in regulating these populations to improve animal performance. Although rumen microbes are well studied, little is known of the dynamics and role of microbial populations in the small intestine of cows. Comparisons of fingerprints of microbial populations were used to investigate the effects of gastrointestinal (GI) segment and animal on community structure. METHODS AND RESULTS: Samples from four lactating dairy cows with ruminal, duodenal and ileal cannulae were collected. Terminal-restriction fragment length polymorphism (T-RFLP) comparisons of small subunit rRNA genes revealed differences in microbial populations between GI segments (P < 0.05). No significant differences in either methanogen populations or microbial community profiles between animals were observed. Quantitative PCR was used to assay relative changes in methanogen numbers compared to procaryote rRNA gene numbers, and direct microscopic counts were used to enumerate total procaryote numbers of the duodenal and ileal samples. CONCLUSIONS: T-RFLP comparisons illustrate significant changes in microbial diversity as digesta passes from one segment to another. Direct counts indicate that microbial numbers are reduced by eight orders of magnitude from the rumen, through the abomasum, and into the duodenum (from c. 10(12) to c. 3.6 x 10(4) cells per ml). Quantitative PCR analyses of rRNA genes indicate that methanogens are present in the duodenum and ileum. SIGNIFICANCE AND IMPACT OF THE STUDY: The contribution of microbial populations of the small intestine to the nutrition and health of cattle is seldom addressed but warrants further investigation.
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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 | 0.000 |
| 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) | 0.000 | 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".