Modulation of Cell Death Pathways by Hepatitis C Virus Proteins in Huh7.5 Hepatoma Cells is a research paper published in International Journal of Molecular Sciences (2017). On theSindex it has a DataRank of 0.577. It has been cited 14 times, with 10 citing works in its 1-hop citation network.
The hepatitis C virus (HCV) causes chronic liver disease leading to fibrosis, cirrhosis, and hepatocellular carcinoma. HCV infection triggers various types of cell death which contribute to hepatitis C pathogenesis. However, much is still unknown about the impact of viral proteins on them. Here we present the results of simultaneous immunocytochemical analysis of markers of apoptosis, autophagy, and necrosis in Huh7.5 cells expressing individual HCV proteins or their combinations, or harboring the virus replicon. Stable replication of the full-length HCV genome or transient expression of its core, Е1/Е2, NS3 and NS5B led to the death of 20–47% cells, 72 h posttransfection, whereas the expression of the NS4A/B, NS5A or NS3-NS5B polyprotein did not affect cell viability. HCV proteins caused different impacts on the activation of caspases-3, -8 and -9 and on DNA fragmentation. The structural core and E1/E2 proteins promoted apoptosis, whereas non-structural NS4A/B, NS5A, NS5B suppressed apoptosis by blocking various members of the caspase cascade. The majority of HCV proteins also enhanced autophagy, while NS5A also induced necrosis. As a result, the death of Huh7.5 cells expressing the HCV core was induced via apoptosis, the cells expressing NS3 and NS5B via autophagy-associated death, and the cells expressing E1/E2 glycoproteins or harboring HCV the replicon via both apoptosis and autophagy.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.406
From this paper's citation signal
Citation Network Contribution
0.171
From 9 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 70% comes from its base citations and 30% from the citation network (9 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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