Human immunodeficiency virus enhances hepatitis C virus replication by differential regulation of IFN and TGF family genes
Bibliographic record
Abstract
HIV co-infection significantly impacts the natural history of hepatitis C virus (HCV) by increasing plasma HCV viral load, accelerating liver disease progression, and reducing rates of HCV clearance. Cytokines play an important role in regulating hepatic inflammation and fibrogenesis during chronic HCV infection, yet the impact of HIV on cytokine expression is unknown. In this study, an HCV continuous infection cell culture system was modified to permit co-infection with HIV to test the hypothesis that virus-induced disregulation of immune-response genes, particularly interferons and TGF-β, may create a permissive environment for the initial establishment of HIV/HCV co-infection in the host. CCR5-expressing Huh-7.5 hepatoma cells were transduced with human CD4 antigen to allow HIV infection in vitro. Co-infection of CD4⁺ Huh-7.5 cells with HIV and HCV or co-culture of HIV-infected CD4⁺ Huh-7.5 cells and HCV-infected Huh-7.5 cells increased the level of HCV RNA compared to HCV mono-infection. Quantitative gene expression analysis revealed HIV-induced up regulation of most tested IFN family genes when compared to HCV or co-infection. HCV infection induced up regulation of many TGF family genes that were subsequently down-regulated in the presence of HIV or HIV/HCV. Interestingly, co-infection resulted in down regulation of several IFN genes and significant up regulation of TGF-β genes leading to an overall enhancement of HCV replication. These data suggest that HIV infection may influence HCV replication in vitro by increasing levels of HCV RNA, possibly through the differential regulation of endogenous IFN and TGF family 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 | 0.000 |
| 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".