Cyclophilins and Their Roles in Hepatitis C Virus and Flavivirus Infections: Perspectives for Novel Antiviral Approaches
Bibliographic record
Abstract
family, such as dengue virus (DENV) and yellow fever virus (YFV). Here, we discuss the roles of cyclophilins in HCV infection and provide a comprehensive overview of the mechanisms underlying the requirement for cyclophilins during HCV replication. Notably, cyclophilin inhibitor therapy has been demonstrated to be effective in reducing HCV replication in chronically infected patients. While the roles of cyclophilins are relatively well-understood for HCV infection, cyclophilins are more recently emerging as host factors for flavivirus infection as well, providing potential new therapeutic avenues for these viral infections which currently lack antiviral therapies. However, further studies are required to elucidate the roles of cyclophilins in flavivirus replication. Here, we review the current knowledge of the role of cyclophilins in HCV infection to provide a conceptual framework to understand how cyclophilins may contribute to other viral infections, such as DENV and YFV. Improved understanding of the roles of cyclophilins in viral infection may open perspectives for the development of cyclophilin inhibitors as effective antiviral therapeutics for HCV and related viruses.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".