Activation of CXCL‐8 Transcription by Hepatitis E Virus ORF‐1 via AP‐1
Bibliographic record
Abstract
Hepatitis E virus (HEV) is a small nonenveloped single-stranded positive-sense RNA virus and is one of the major causes for acute hepatitis worldwide. CXCL-8 is a small multifunctional proinflammatory chemokine. It was reported recently that HEV infection significantly upregulates CXCL-8 gene expression. In this study, we investigated the mechanism of HEV-induced CXCL-8 transcriptional activation. Using CXCL-8 promoter reporters of different lengths ranging from -1400 to -173, we showed that -173 promoter has the highest promoter activity in the presence of HEV genomic RNA, indicating that the -173 promoter contains sequences responsible for CXCL-8 activation by HEV. Ectopic expression of the ORF-1 protein can upregulate the -173 CXCL-8 promoter activity. In contrast, expression of the ORF-2 protein suppresses the CXCL-8 promoter activity and expression of the ORF-3 protein has no effect on the CXCL-8 promoter activity. We further showed that AP-1 is required for CXCL-8 activation because neither HEV genomic RNA nor the ORF-1 protein can upregulate the -173 CXCL-8 promoter in the absence of the AP-1 binding sequence. Taken together, our results showed that HEV and HEV ORF-1 protein activate the CXCL-8 promoter via AP-1. This novel function of HEV ORF-1 protein should contribute to our understanding of HEV-host interactions and HEV-associated pathogenesis.
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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 | 0.001 |
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".