175 Effects of dietary supplementation with xylanase and probiotics on growth performance and gut health of newly weaned pigs challenged with enterotoxigenic E. coli on d 7 post weaned
Bibliographic record
Abstract
Abstract This study was to investigate the effect of dietary supplementation with xylanase and probiotic on growth performance, and gut health of nursery pigs challenged with ETEC. Sixty-four weaned pigs (7.9 ± 0.4 kg) were allotted in a RCBD (2 x 2 factorial). ETEC (0, and ETEC, 6 x 109 CFU/mL) and synbiotic (0, and xylanase 10,000 XU/kg combined with Bacillus sp. 6 x 108 CFU/kg) were the factors. ETEC was orally inoculated on d 7. Growth performance were measured on d 7, 10, 15, and 21. On d 21, 48 pigs were euthanized for sampling to measure gut health parameters. Synbiotic increased (P < 0.05) ADG in P1 (53.5 to 96.0 g). Overall, ETEC reduced (P < 0.05) ADG (387.5 to 322.5 g) and G:F (0.810 to 0.706). ETEC increased (P < 0.05) fecal score from d 7 to 13, whereas synbiotic reduced (P < 0.05) it at d 9 and 11 in challenged pigs. ETEC increased (P < 0.05) MDA (0.259 to 0.818 μmol/mg), IL6 (2.96 to 4.30 pg/mg), ki-67+ (29.1 to 33.9%), and crypt depth (260 to 290 μm), whereas synbiotic tended to reduce TNF-α (1.05 to 0.87 pg/mg), protein carbonyl (3.13 to 2.51 nmol/mg), and IL6 (4.07 to 3.19 pg/mg); reduced (P < 0.05) crypt depth (290 to 260 μm), and ki-67+ (32.7 to 30.3%) and increased (P < 0.05) villus height (368.5 to 421.4 μm). ETEC reduced (P < 0.05) abundance of Veillonellaceae (7.11 to 3.02%), tended to reduce (P = 0.067) Clostridiaceae (1.1 to 0.55%), and Prevotellaceae (38.0 to 27.2%) and tended (P = 0.063) to increase Helicobacteraceae (34.5 to 49.5%). Collectively, ETEC reduced growth performance by affecting the microbiome, oxidative stress, and immune response. Synbiotic improve growth performance by enhancing gut health regardless of the challenge, whereas it reduced fecal score in challenged pigs.
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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) | 0.001 | 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 | 0.001 | 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".