Gut microbiota-mediated protection against influenza virus subtype H9N2 in chickens is associated with modulation of the innate responses
Bibliographic record
Abstract
Commensal gut microbiota plays an important role in health and disease. The current study was designed to assess the role of gut microbiota of chickens in the initiation of antiviral responses against avian influenza virus. Day-old layer chickens received a cocktail of antibiotics for 12 (ABX-D12) or 16 (ABX-D16) days to deplete their gut microbiota, followed by treatment of chickens from ABX-12 with five Lactobacillus species combination (PROB), fecal microbial transplant suspension (FMT) or sham treatment daily for four days. At day 17 of age, chickens were challenged with H9N2 virus. Cloacal virus shedding, and interferon (IFN)-α, IFN-β and interleukin (IL)-22 expression in the trachea, lung, ileum and cecal tonsils was assessed. Higher virus shedding, and compromised type I IFNs and IL-22 expression was observed in ABX-D16 chickens compared to control, while PROB and FMT showed reduced virus shedding and restored IL-22 expression to levels comparable with undepleted chickens. In conclusion, commensal gut microbiota of chickens can modulate innate responses to influenza virus subtype H9N2 infection in chickens, and modulating the composition of the microbiome using probiotics- and/or FMT-based interventions might serve to promote a healthy community that confers protection against influenza virus infection in chickens.
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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) | 0.000 | 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 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".