Effect of an antibiotic and a probiotic on phage communities in the swine gut microbiota
Bibliographic record
Abstract
OBJECTIVE: The impact of dietary treatments on the phage community of porcine intestinal microbiota is not well understood. An antibiotic (tylvalosin), a probiotic (Pediococcus acidilactici), and a combination of these were given to six cannulated pigs in a double crossover design study. Samples of ileal digesta and feces were collected and whole genome shotgun sequencing was performed. The variations in phage and bacterial communities were compared for each treatment and sample type. RESULTS: The bacteriophages present in the gut microbiome exhibited greater variations in both α- and β-diversity between sample types (digesta, feces) than between treatments. β-diversity and differential abundance showed that the effect of the combined antibiotic and probiotic treatment was the same as with the antibiotic alone. However, the effects of the probiotic and antibiotic treatments were statistically significantly different in the fecal samples. β-diversity was different in those two treatments, and differential abundance analysis identified multiple phages as markers for each treatment. No significant variations in relative abundance were found in phage lifestyle (i.e., virulent, temperate) between treatments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".