Development of innate immunity in chicken embryos and newly hatched chicks: a disease control perspective
Bibliographic record
Abstract
Newly hatched chickens are confronted by a wide array of pathogenic microbes because their adaptive immune defences have limited capabilities to control these pathogens. In such circumstances, and within this age group, innate responses provide a degree of protection. Moreover, as the adaptive immune system is relatively naïve to foreign antigens, synergy with innate defences is critical. This review presents knowledge on the ontogeny of innate immunity in chickens pre-hatch and early post-hatch and provides insights into possible interventions to modulate innate responses early in the life of the bird. As in other vertebrate species, the chicken innate immune system which include cellular mediators, cytokine and chemokine repertoires and molecules involved in antigen detection, develop early in life. Comparison of innate immune systems in newly hatched chickens and mature birds has revealed differences in magnitude and quality, but responses in younger chickens can be boosted using innate immune system modulators. Functional expression of pattern recognition receptors and several defence molecules by innate immune system cells of embryos and newly hatched chicks suggests that innate responses can be modulated at this stage of development to combat pathogens. Improved understanding of innate immune system ontogeny and functionality in chickens is critical for the implementation of sound and safe interventions to provide long-term protection against pathogens. Next-generation tools for studying genetic and epigenetic regulation of genes, functional metagenomics and gene knockouts can be used in the future to explore and dissect the contributions of signalling pathways of innate immunity and to devise more efficacious disease control strategies.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".