496 Effects of sodium metabisulfite (SMBS) and SMBS-containing lipid microparticles on the performance and intestinal barrier functions of weanling piglets challenged by deoxynivalenol-contaminated diets
Bibliographic record
Abstract
Abstract This study aimed to investigate the effects of sodium metabisulfite (SMBS) and SMBS-containing hydrogenated palm oil (HS) microparticles on the growth performance and intestinal barrier functions of weanling piglets challenged by deoxynivalenol (DON)-contaminated diets. Four corn-soybean-meal based diets were used: 1) negative control (NC, 0.00 mg/kg of DON); 2) positive control (PC, 3.3 mg/kg of DON); 3) SMBS (PST, 3.3 mg/kg of DON and 0.2% of SMBS); and 4) HS microparticles (HST, 3.3 mg/kg of DON and 0.45% of HS microparticles). Weaned piglets (n = 40) with similar body weights (BW; 8.22 ± 0.39 kg, 10 pigs/treatment) were fed for 28 d, including a 1-wk adjustment and 3 wk for exposure. Piglets subjected to the PC diet exhibited a noteworthy reduction in final BW by 13.3%, average daily gain (ADG) by 21.4%, and average daily feed intake (ADFI) by 20.1% compared with those on the NC diet (P < 0.05). Compared with the PC diet, the PST and HST diets increased by 6.76% and 4.31% in final BW (P < 0.05), 13.6% and 8.60% in ADG (P < 0.05), and 9.15% and 9.71% in ADFI (P < 0.05), respectively. No significant differences were detected in these values between the NC, PST, and HST diets (P > 0.05). There were no significant variations observed in the feed conversion ratio (FCR) among the four dietary treatments (P > 0.05). Feeding the PC diet to piglets led to a significant increase in the fecal score compared with the NC and HST diets (P < 0.05). No significant differences were detected in the mRNA expression levels of nutrient transporters and tight junction proteins among these four diets (P > 0.05). Additionally, compared with the NC diet, the PC diet significantly increased the mRNA abundance of Interleukin (IL)-6, IL-8, tumor necrosis factor (TNF)-α, and toll-like receptor 4 (TLR4; P < 0.05); however, a decreased mRNA abundance of IL-8 and TNF-α was observed in the pigs fed the HST diet (P < 0.05), indicating that the encapsulated SMBS from the HS microparticles could have the potential to mitigate the effects of DON. Overall, adding 0.45% of HS microparticles to a 3.3 mg/kg DON-contaminated diet in piglets could maintain the growth performance, and using the HS microparticles revealed some potential in DON detoxification by reducing the gene expressions of pro-inflammatory cytokines.
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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".