Ex Vivo Differential Responsiveness to Clostridium perfringens and Lactococcus lactis by Avian Small Intestine Macrophages and T Cells
Bibliographic record
Abstract
Tissue resident immune system cells in the chicken intestine play a significant role in the protection against pathogens. However, very little is known about these cells. The current study was conducted to further characterize chicken intestinal immune system cells. Furthermore, this study aimed to assess the immune modulatory action of a highly virulentClostridium perfringens, a commonly found chicken intestinal microbe, in comparison with a non-commensal,Lactococcus lactis, on intestine-derived immune system cells. The results demonstrated varying distribution of innate and adaptive immune cells along the avian gut-associated lymphoid tissue (GALT) in the duodenum, jejunum, ileum, and cecal tonsils. In addition, steady-state and tissue-specific presence of CD25+ cells among αβ and γδ T-cell subsets was assessed along the intestine.Ex vivostimulation withC. perfringensorL. lactisresulted in a significant increase in the frequency of CD25+ T cells (γδ and αβ T cells). In addition, significantly more cell death was observed inex vivostimulation withC. perfringens, which was indirectly correlated with a decrease in macrophage activation based on nitric oxide (NO) production with no effect on lymphoid cell responsiveness as per intracellular interferon (IFN)-gamma (γ) staining.Ex vivostimulation withL. lactisactivated γδ T cells and αβ T cells, based on intracellular IFN-γ staining, while it had limited effect on macrophages. However, the ability of γδ and αβ T cells to produce IFN-γ and the ability of macrophages production of NO was rescued in the presence ofL. lactis.These results demonstrate the potential application ofL. lactis, as a probiotic, against virulentC. perfringensinfection in chicken.
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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) | 0.001 | 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".