The ileal microbiome and mucosal immune profiles in response to dietary supplementation of ultra-grinded Astragalus membranaceus in weaned goats
Bibliographic record
Abstract
Weaning goats are susceptible to diarrhea and have weakened immune functions due to physiological, dietary and environmental stresses. Astragalus membranaceus (A. membranaceus), a traditional Chinese medicinal herb, has been shown to improve growth performance and immunity in weaned ruminants. However, the influence mechanism of A. membranaceus on intestinal microbiota and mucosal immunity in weaned goats is still unknown. This study investigated the effects of ultra-grinded A. membranaceus (UGAM) on the immune function and microbial community in the ileum of weaned goats. Eighteen healthy weaned Xiangdong black goats (BW, 5.30 ± 1.388 kg) were used in a study of completely randomized block design with 28 days long. The animals were randomly assigned to either a basal diet supplemented with 10 g/d of milk replacer (CON, n = 9) or the CON diet supplemented with 10 g/head UGAM (UGAM, n = 9). Supplementation of UGAM increased (p < 0.05) the plasma concentrations of total protein and albumin. Meanwhile, the addition of UGAM reduced (p < 0.05) the relative mRNA expression of the IL-6 gene (a marker of inflammation), indicating the potential immunomodulatory effect of UGAM. Moreover, the relative abundances of Verrucomicrobiota and Mycoplasma were lower (p < 0.05) in the ileum of goats supplemented with UGAM than CON. These findings suggest that dietary supplementation of UGAM may have enhanced the ileum health of weaned goats by reducing inflammation factor expression and reducing the relative abundance of pathogenic microbes. The observed beneficial effects of ultra-grinded A. membranaceus on ileal mucosal immune and the community of ileal microbiota indicate its potential to be used as a viable option for promoting the well-being of weaned goats under weaning stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".