The combination of macleaya extract and glucose oxidase improves the growth performance, antioxidant capacity, immune function and cecal microbiota of piglets
Bibliographic record
Abstract
This study aims to investigate the effects of macleaya extract and glucose oxidase combination (MGO) on growth performance, antioxidant capacity, immune function, and cecal microbiota in piglets. A total of 120 healthy 28-day-old weaned piglets were randomly divided into two treatments of six replicates. Piglets were either received a basal diet or a basal diet supplemented with 250 mg/kg MGO (2 g/kg sanguinarine, 1 g/kg chelerythrine, and 1 × 106 U/kg glucose oxidase). The results showed that MGO supplementation increased average daily gain (ADG) and decreased feed:gain ratio (F/G) (p < 0.05). MGO increased serum superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activity, and immunoglobulin G (IgG) content (p < 0.05), but decreased malondialdehyde (MDA) and interleukin 1β (IL-1β) content (p < 0.05). The jejunal mRNA expression of nuclear factor erythroid 2-related factor 2 (Nrf2), glutathione peroxidase 1 (GPX1), and heme oxygenase 1 (HO-1) were increased in MGO group (p < 0.05), while that of kelch like ECH associated protein 1 (Keap1) was decreased (p < 0.05). The Firmicutes was significantly increased at phylum levels in MGO group (p < 0.05). In conclusion, 250 mg/kg MGO improved piglet growth, and regulated intestinal flora of piglets, which provided a theoretical basis for MGO as an alternative additive for antibiotics.
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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) | 0.001 | 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 | 0.000 | 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".