Classical swine fever virus E<sup>rns</sup>glycoprotein antagonizes induction of interferon-β by double-stranded RNA
Bibliographic record
Abstract
Classical swine fever virus (CSFV) is capable of counteracting innate cellular antiviral responses by inhibiting type I interferon (IFN)-alpha/beta induction. A function associated with CSFV N(pro), with respect to the inhibition of IFN-beta production, has been clearly elucidated. In this study, we explored the role of CSFV E(rns) in IFN-beta induction by exogenous double-stranded (ds) RNA. Synthetic dsRNA (poly (IC)) was used as an exogenous stimulus to trigger IFN-beta induction. CSFV E(rns) inhibited IFN-beta promoter-driven luciferase activity induced by poly (IC) in different cell lines, and the inhibitory effect was dose-dependent. Moreover, E(rns) reduced IFN-beta mRNA synthesis and blocked IFN-alpha/beta production induced by poly (IC), suggesting that this inhibition occurs at the transcriptional level. Furthermore, E(rns) counteracted poly (IC)-mediated IFN-beta induction independent of its ribonuclease activity. In conclusion, CSFV E(rns) antagonizes extracellular dsRNA-mediated IFN-beta expression. These findings contribute to our understanding of the pathogenesis of CSFV.
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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".