Alterations in Ileal Mucosa Bacteria Related to Diet Complexity and Growth Performance in Young Pigs
Bibliographic record
Abstract
BACKGROUND: Evaluation of the prolonged impact of weaning diet on ileal mucosa bacteria and during periods of reduced and improved growth was conducted using 454 pyrosequencing. METHODOLOGY/PRINCIPAL FINDINGS: Weaned pigs were fed HIGH or LOW complexity diets, with or without antibiotics, for 6 weeks, followed by a common grower diet. Pigs were killed at 2 (n = 4 or 5) and 8 (n = 6) weeks post-weaning (periods of reduced and improved growth, respectively). Mucosal bacteria were removed; DNA was extracted and amplified using the V1-V3 region of the 16S rRNA gene. Mucosal bacteria clustered more closely by week post-weaning than diet but 44% of bacterial species did not change from week 2 to 8. There was no effect of diet complexity or antibiotic inclusion on indices of bacterial diversity. Firmicutes made up 91 and 96% of total reads at week 2 and 8, respectively. The proportion of Clostridium paraputrificum increased (P = 0.003) from week 2 to 8 in pigs fed LOW but didn't change in pigs fed HIGH; whereas Clostridium leptum decreased (P = 0.02) from week 2 to 8 in pigs fed LOW but didn't change in pigs fed HIGH. The proportion of Sarcina genus was 3-fold higher in pigs fed A+ compared to A- at week 2 and 5-fold higher at week 8 despite the lack of in-feed antibiotics at that time. CONCLUSIONS/SIGNIFICANCE: Shifts in mucosal bacteria populations may be related to dietary induced changes in growth performance during reduced and improved growth but further studies are required to confirm causative relationship. Weaning diet results in species specific prolonged alterations in mucosal bacteria, particularly where high levels of in-feed antibiotics are used. A considerable portion of ileal mucosal bacteria colonize early and remain stable over time despite changes in diet.
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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".