Comparative efficacy of a novel Bacillus subtilis-based probiotic and pharmacological zinc oxide on growth performance and gut responses in nursery pigs
Bibliographic record
Abstract
Abstract In this study, we assessed the efficacy of a novel Bacillus subtilis probiotic in improving growth performance and gut responses in comparison to pharmacological zinc oxide (ZnO) in nursery pigs. A total of 96 piglets were randomly assigned to four groups: Negative control (NC), Positive control (PC, 3000 mg Zn /kg feed), B.subtilis low dose (BS9-L, 2 × 10 7 CFU/pig) and B.subtilis high dose (BS9-H, 2 × 10 9 CFU/pig). Growth performance, diarrhea rate, gut mucosal gene expression and fecal microbial populations were evaluated. B.subtilis administration did not improve piglet bodyweight. BS9-L showed (P < 0.05) higher average daily gain (ADG) in Period 2 (D14-D28). BS9 groups had (P < 0.001) lower feed conversion ratio (FCR) in Period 2 (D14-D28) and overall. Like the ZnO-group, BS9 groups had lower (P < 0.01) diarrhea rate. A significant reduction (P < 0.05) in fecal E. coli , total coliforms, and an increase in lactic acid bacteria and Bacillus spp. in BS9 groups was observed. BS9 group had reduced (P < 0.05) mRNA levels of intestinal IL-8 and higher levels of MUC-1 and occludin and TJP-1 compared to negative control. These findings suggest that probiotic BS9, may promote growth performance, and ameliorate various indicators of intestinal health in piglets. Hence, it may serve as a prospective alternative to ZnO growth promoter in commercial swine production.
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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".