Inhibition of IκB kinase by thalidomide increases hepatitis C virus RNA replication
Bibliographic record
Abstract
Hepatic fibrosis is an integral element in the progression of chronic liver disease. Elevated hepatic interleukin (IL)-8 is an important contributor to fibrosis in patients chronically infected with the hepatitis C virus (HCV). Thalidomide has been used to reduce liver inflammation and fibrosis in HCV-infected patients, but its impact on HCV replication remains unclear. This study examined the effect of thalidomide on HCV replication in vitro. Results revealed that while thalidomide reduced IL-8 and nuclear factor kappa B (NF-κB) activity by 95% and 46% in Huh-7 cells, increasing concentrations of thalidomide correlated with a linear rise in HCV replication (17-fold at 200 μm). The NF-κB inhibitors, wedelolactone and NF-κB activation inhibitor-1, which mimic the actions of thalidomide by preventing phosphorylation and activation of IκB kinase (IKK) and hence block NF-κB activity, increased HCV RNA by 18- and 19-fold, respectively. During in vitro HCV replication in Huh-7 cells, we observed a 30% increase in IKKα protein and 55% decrease in NF-κB(p65)/RelA protein relative to cellular β-actin. Ectopic expression of IKKα to enhance the inactive form of IKK in cells undergoing virus replication led to a 13-fold increase in HCV RNA. Conversely, enhanced expression of NF-κB(p65)/RelA in infected cells resulted in a 17-fold reduction in HCV RNA. In conclusion, HCV RNA replication was significantly augmented by the inhibition of IKK activation and subsequent NF-κB signalling, whereas a restoration of NF-κB activity by the addition of NF-κB/RelA markedly reduced HCV replication. This study lends added importance to the role of the NF-κB signalling pathway in controlling HCV replication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".