Activated Chicken Gamma Delta T Cells Are Involved in Protective Immunity against Marek’s Disease
Bibliographic record
Abstract
Gamma delta (γδ) T cells play a significant role in the prevention of viral infection and tumor surveillance in mammals. Although the involvement of γδ T cells in Marek’s disease virus (MDV) infection has been suggested, their detailed contribution to immunity against MDV or the progression of Marek’s disease (MD) remains unknown. In the current study, T cell receptor (TCR)γδ-activated peripheral blood mononuclear cells (PBMCs) were infused into recipient chickens and their effects were examined in the context of tumor formation by MDV and immunity against MDV. We demonstrated that the adoptive transfer of TCRγδ-activated PBMCs reduced virus replication in the lungs and tumor incidence in MDV-challenged chickens. Infusion of TCRγδ-activated PBMCs induced IFN-γ-producing γδ T cells at 10 days post-infection (dpi), and degranulation activity in circulating γδ T cell and CD8α+ γδ T cells at 10 and 21 dpi in MDV-challenged chickens. Additionally, the upregulation of IFN-γ and granzyme A gene expression at 10 dpi was significant in the spleen of the TCRγδ-activated PBMCs-infused and MDV-challenged group compared to the control group. Taken together, our results revealed that TCRγδ stimulation promotes the effector function of chicken γδ T cells, and these effector γδ T cells may be involved in protection against MD.
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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".