Poxvirus Immunomodulatory Strategies: Current Perspectives
Bibliographic record
Abstract
Successful transmission by viruses in the face of vigorous innate and acquired host immunity requires the ability to evade, obstruct, or subvert critical elements that mediate host antiviral responses. To that end, viruses with larger genomes, such as poxviruses, encode multiple classes of immunomodulatory proteins that have evolved specifically to inhibit such diverse processes as apoptosis, the production of interferons, chemokines, and inflammatory cytokines, and the activity of cytotoxic T lymphocytes (CTLs), natural killer (NK) cells, complement, and antibodies. Often, the evolutionary origins of these virus-encoded immunomodulatory proteins are difficult to trace. The obvious sequence similarity between some immunomodulatory poxvirus genes and the cDNA versions of related cellular counterparts suggests that they were once captured by ancestral retrotranscription and/or recombination events and then reassorted into individual virus isolates during coevolution with vertebrate hosts. However, other poxviral immunomodulators have no known cellular counterpart or have putative functions that cannot be predicted based on similarity to known cellular proteins. The origins of these orphan regulators may be obscure, but their potential for immune subversion can be profound.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".