Distinct commensal bacteria associated with ingesta and mucosal epithelium in the gastrointestinal tracts of calves and chickens
Bibliographic record
Abstract
The primary aim of this study was to determine whether distinct gastrointestinal tract (GIT) microbial communities are established within ingesta and on mucosal surfaces of dairy calves and chickens to evaluate whether the principle of microbial segregation is of broad biological significance. Multivariate analysis of the predominant bacterial PCR-denaturing gradient gel electrophoresis profiles and estimated bacterial populations were compared in rumen, jejunum, ileum, cecum, and colon ingesta and matching mucosal tissues. Samples collected from 3-week old (n = 8) and 6-month old (n = 8) calves revealed that the predominant mucosa-associated bacteria were distinct from those inhabiting ingesta, and bacterial diversity varied significantly among the GIT regions. The estimated bacterial populations displayed significant regional differences for bovine mucosal (P = 0.05) and for ingesta (P = 0.03) only at 6 months of age. This indicates an established segregation of the enteric bacterial population throughout the GIT in weaned calves. Analysis of ileal and cecal bacterial profiles in chickens confirmed that the segregation of commensal bacteria between ingesta and the mucosal tissue was a common biological phenomenon. Our study provides some fundamental understanding of the impact of sample type (mucosa vs. ingesta), region, and host age on commensal bacterial establishment and segregation throughout the GIT.
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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".