Yaba Monkey Tumor Virus Encodes a Functional Inhibitor of Interleukin-18
Bibliographic record
Abstract
Interleukin-18 (IL-18) is a critical proinflammatory cytokine whose extracellular bioactivity is regulated by a cellular IL-18 binding protein (IL-18BP). Many poxviruses have acquired variants of this IL-18BP gene, some of which have been shown to act as viral virulence factors. Yaba monkey tumor virus (YMTV) encodes a related family member, 14L, which is similar to the orthopoxvirus IL-18BPs. YMTV 14L was expressed from a baculovirus system and tested for its ability to bind and inhibit IL-18. We found that YMTV 14L bound both human IL-18 (hIL-18) and murine IL-18 with high affinity, at 4.1 nM and 6.5 nM, respectively. YMTV 14L was able to fully sequester hIL-18 but could only partially inhibit the biological activity of hIL-18 as measured by gamma interferon secretion from KG-1 cells. Additionally, 17 hIL-18 point mutants were tested by surface plasmon resonance for their ability to bind to YMTV 14L. Two clusters of hIL-18 surface residues were found to be important for the hIL-18-YMTV 14L interaction, in contrast to results for the Variola virus IL-18BP, which has been shown to primarily interact with a single cluster of three amino acids. The altered binding specificity of YMTV 14L most likely represents an adaptation resulting in increased fitness of the virus and affirms the plasticity of poxviral inhibitor domains that target cytokines like IL-18.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".