Effects of Chinese herbal plant extracts on diarrhea rate, intestinal morphology, nutrient digestibility, and immunity of weaned piglets
Bibliographic record
Abstract
This experiment aimed to establish the effects of Chinese herbal plant extracts compound (Astragalus root, Eucommia bark, Honeysuckle, and Quassic) to replace antibiotics on diarrhea rate, intestinal morphology, nutrient digestibility, and immunity of weaned piglets. In a 21 day experiment, 180 weaned piglets were randomly allocated to four dietary treatments, including a basal diet supplemented with 0 + 250 g/t oxytetracycline calcium and 50 g/t virginiamycin (control), 400 (T1), 500 (T2), and 600 (T3) g/t Chinese herbal plant extracts compound. The results showed that diets supplemented with Chinese herbal plant extracts significantly increased the number of Lactobacillus and Bifidobacterium in feces of weaned piglets, the villus height and ratio of villus height to crypt depth of jejunum and ileum, the levels of immunoglobulin G, immunoglobulin A, immunoglobulin M, interleukin-2, interleukin-4, total protein, albumin, tumor necrosis factor-α, and the apparent digestibility of energy, crude protein, crude fat, crude fiber, calcium, and phosphorus ( P < 0.05). Diets supplemented with Chinese herbal plant extracts significantly reduced the number of Escherichia coli in feces and the diarrhea index ( P < 0.05). In conclusion, dietary supplementation with Chinese herbal plant extracts compound preparation can improve intestinal morphology, feed apparent digestibility, and immunity and reduce diarrhea rate of weaned piglets.
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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 | 0.001 |
| 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".