In ovo feeding of probiotic lactobacilli differentially alters expression of genes involved in the development and immunological maturation of bursa of Fabricius in pre-hatched chicks
Bibliographic record
Abstract
Compelling evidence indicates that immunological maturation of the gut-associated lymphoid tissues, including the bursa of Fabricius, is dependent upon antigenic stimulation post-hatch. In view of these data, the present study investigated the impact of exposing the immune system of chick embryos to antigenic stimuli, via in ovo delivery of poultry-specific lactobacilli, on the expression of genes associated with early bursal development and maturation. Broiler line embryonated eggs were inoculated with 106 and 107 colony forming unit (CFU) of individual or a mixture of Lactobacillus species, including L. crispatus (C25), L. animalis (P38), L. acidophilus (P42), and L. reuteri (P43), at embryonic day 18 (ED18). The bursa of Fabricius was collected from pre-hatched chicks (ED20) to measure the expression levels of various immune system genes. The results revealed that L. acidophilus and the mixture of Lactobacillus species at the dose of 106 CFU consistently elicited higher expression of genes responsible for B cell development, differentiation, and survival (B cell activating factor (BAFF), BAFF-receptor (BAFF-R)), and antibody production (IL-10) and diversification (TGF-β). Similar expression patterns were also noted in T helper (Th) cell-associated cytokine genes, including Th1-type cytokines (interferon (IFN)-γ and IL-12p40), Th2-type cytokines (IL-4 and IL-13) and Th17 cytokine (IL-17). Overall, these results suggest that the supplementation of poultry-specific lactobacilli to chick embryos might be beneficial for accelerating the development and immunological maturation of the bursa of Fabricius. However, further studies are required to determine if the changes in gene expression are associated with the developmental trajectory and phenotypes of bursal cells.
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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 | 0.001 |
| 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".