Exploring the complexities of poultry respiratory microbiota: colonization, composition, and impact on health
Bibliographic record
Abstract
An accurate understanding of the ecology and complexity of the poultry respiratory microbiota is of utmost importance for elucidating the roles of commensal or pathogenic microorganisms in the respiratory tract, as well as their associations with health or disease outcomes in poultry. This comprehensive review delves into the intricate aspects of the poultry respiratory microbiota, focusing on its colonization patterns, composition, and impact on poultry health. Firstly, an updated overview of the current knowledge concerning the composition of the microbiota in the respiratory tract of poultry is provided, as well as the factors that influence the dynamics of community structure and diversity. Additionally, the significant role that the poultry respiratory microbiota plays in economically relevant respiratory pathobiologies that affect poultry is explored. In addition, the challenges encountered when studying the poultry respiratory microbiota are addressed, including the dynamic nature of microbial communities, site-specific variations, the need for standardized protocols, the appropriate sequencing technologies, and the limitations associated with sampling methodology. Furthermore, emerging evidence that suggests bidirectional communication between the gut and respiratory microbiota in poultry is described, where disturbances in one microbiota can impact the other. Understanding this intricate cross talk holds the potential to provide valuable insights for enhancing poultry health and disease control. It becomes evident that gaining a comprehensive understanding of the multifaceted roles of the poultry respiratory microbiota, as presented in this review, is crucial for optimizing poultry health management and improving overall outcomes in poultry production.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".