Marek's Disease Virus Influences the Expression of Genes Associated with IFN-γ-Inducible MHC Class II Expression
Bibliographic record
Abstract
Chickens infected with Marek's disease virus (MDV) become lifelong carriers regardless of their susceptibility to clinical disease. Therefore various viral immune-evasive mechanisms must play a role in MDV-host interactions. MDV has previously been shown to influence the expression of major histocompatibility complex (MHC) class II molecules. However, little is known about the underlying mechanisms of this phenomenon. In the present study, we studied the effect of MDV infection on the expression of several genes associated with IFN-γ-inducible MHC class II expression at 4, 7, 14, and 21 days post-infection (dpi). There was a significant (p ≤ 0.05) downregulation of MHC class II β chain expression throughout the experiment, while other components of the MHC class II heterotrimer (i.e., α chain and the invariant chain) were significantly downregulated only at 4 and 21 dpi. Furthermore, the expression of components of the IFN-γ-receptor complex was significantly downregulated at 4 dpi. In contrast, a number of other IFN-γ-signaling molecules, including signal transducer and activator of transcription 1 (STAT1), interferon-responsive factor 1 (IRF-1), and class II transactivator (CIITA) were significantly upregulated at most time points. The results of this study shed light on the possible mechanisms by which MDV may evade host immunosurveillance.
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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".