Dietary inclusion of mushroom (<i>Flammulina velutipes</i>) stem waste on growth performance and immune responses in growing layer hens
Bibliographic record
Abstract
BACKGROUND: Medicinal mushrooms contain biologically active substances that can be used as an immune-modulating agent in poultry. The present study aimed to investigate the effects of Flammulina velutipes mushroom waste (FVW) on performance, immune response and serum immunity in growing layer hens. RESULTS: No significant differences (P > 0.05) were observed with respect to average daily feed intake, body weight gain and feed conversion ratio among the experimental groups during the entire study period (1-70 days). Antibody titers against Newcastle disease and infectious bronchitis were higher (P < 0.05) in the FVW fed groups than in the control and antibiotic groups. On day 28, serum immunoglobulin (Ig)A and IgG were higher (P < 0.05) in the 6% FVW group than in the control and antibiotic fed groups. On day 70, serum IgA was higher (P < 0.05) in FVW fed groups than in the control group; IgG was higher (P < 0.05) in the FVW groups than in the control and antibiotic groups. However, IgM was higher (P < 0.05) in both the 4% and 6% FVW groups than in the control and antibiotic groups for both experimental periods. Serum cytokine interleukin (IL)-2 and tumor necrosis factor-α concentrations were significantly higher (P < 0.05) in both the 4% and 6% FVW grousp than in the control and antibiotic groups; IL-4 was significantly higher (P < 0.05) in the FVW groups than in the control group; and IL-6 was significantly higher (P < 0.05) in the 6% FVW group than in the control and antibiotic groups. CONCLUSION: FVW at the 6% level can be used as a potential phytogenic feed stuff in growing layer hen rations with respect to improving the immune response without affecting normal weight gain. © 2018 Society of Chemical Industry.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".