Marek’s disease in chickens: a review with focus on immunology
Bibliographic record
Abstract
Marek's disease (MD), caused by Marek's disease virus (MDV), is a commercially important neoplastic disease of poultry which is only controlled by mass vaccination. Importantly, vaccines that can provide sterile immunity and inhibit virus transmission are lacking; such that vaccines are only capable of preventing neuropathy, oncogenic disease and immunosuppression, but are unable to prevent MDV transmission or infection, leading to emergence of increasingly virulent pathotypes. Hence, to address these issues, developing more efficacious vaccines that induce sterile immunity have become one of the important research goals for avian immunologists today. MDV shares very close genomic functional and structural characteristics to most mammalian herpes viruses such as herpes simplex virus (HSV). MD also provides an excellent T cell lymphoma model for gaining insights into other herpesvirus-induced oncogenesis in mammals and birds. For these reasons, we need to develop an in-depth knowledge and understanding of the host-viral interaction and host immunity against MD. Similarly, the underlying genetic variation within different chicken lines has a major impact on the outcome of infection. In this review article, we aim to investigate the pathogenesis of MDV infection, host immunity to MD and discuss areas of research that need to be further explored.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".