IFN regulatory factor 1 restricts hepatitis E virus replication by activating STAT1 to induce antiviral IFN‐stimulated genes
Bibliographic record
Abstract
IFN regulatory factor 1 (IRF1) is one of the most important IFN-stimulated genes (ISGs) in cellular antiviral immunity. Although hepatitis E virus (HEV) is a leading cause of acute hepatitis worldwide, how ISGs counteract HEV infection is largely unknown. This study was conducted to investigate the effect of IRF1 on HEV replication. Multiple cell lines were used in 2 models that harbor HEV. In different HEV cell culture systems, IRF1 effectively inhibited HEV replication. IRF1 did not trigger IFN production, and chromatin immunoprecipitation sequencing data analysis revealed that IRF1 bound to the promoter region of signal transducers and activators of transcription 1 (STAT1). Functional assay confirmed that IRF1 could drive the transcription of STAT1, resulting in elevation of total and phosphorylated STAT1 proteins and further activating the transcription of a panel of downstream antiviral ISGs. By pharmacological inhibitors and RNAi-mediated gene-silencing approaches, we revealed that antiviral function of IRF1 is dependent on the JAK-STAT cascade. Furthermore, induction of ISGs and the anti-HEV effect of IRF1 overlapped that of IFNα, but was potentiated by ribavirin. We demonstrated that IRF1 effectively inhibits HEV replication through the activation of the JAK-STAT pathway, and the subsequent transcription of antiviral ISGs, but independent of IFN production.-Xu, L., Zhou, X., Wang, W., Wang, Y., Yin, Y., van der Laan, L. J. W., Sprengers, D., Metselaar, H. J., Peppelenbosch, M. P., Pan, Q. IFN regulatory factor 1 restricts hepatitis E virus replication by activating STAT1 to induce antiviral IFN-stimulated genes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".