Differential Effects of Hepatitis C Virus JFH1 on Human Myeloid and Plasmacytoid Dendritic Cells
Bibliographic record
Abstract
Dendritic cells (DCs) are reported to be functionally deficient during chronic hepatitis C virus (HCV) infection. Differing results have been reported on direct effects of intact replicative-form HCV on DC function. To better understand the effect of HCV on DC function, we treated freshly purified human myeloid DCs (mDCs) and plasmacytoid DCs (pDCs) with HCV JFH1. We found that HCV upregulated mDC maturation marker (CD83, CD86, and CD40) expression and did not inhibit Toll-like receptor 3 (TLR3) ligand [poly(I:C)]-induced mDC maturation, a finding consistent with the phenotype of DCs from HCV-infected subjects. At the same time, HCV JFH1 inhibited the ability of poly(I:C)-treated mDCs to activate naive CD4 T cells. In contrast, although there was no direct effect of virus on pDC maturation, HCV JFH1 inhibited TLR7 ligand (R848)-induced pDC CD40 expression, and this was associated with impaired ability to activate naive CD4 T cells. Parallel experiments with recombinant HCV proteins indicated HCV core protein may be responsible for a portion of the activity. Furthermore, HCV-mediated mDC maturation was dependent upon CD81-E2 interaction and, in part, TLR2. Using UV-treated HCV, we show that HCV-mediated mDC and pDC maturation is virus replication independent and, using strand specific PCR, we found no evidence for HCV replication within DCs. Because these effects of HCV on DC subset maturation and function in part recapitulate direct ex vivo analysis of DCs in chronic HCV infection, the mechanisms described here likely account for a portion of the DC subset defects observed in vivo.
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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".