The influence of cholesterol and lipid metabolism on host cell structure and hepatitis C virus replication
Bibliographic record
Abstract
The hepatitis C virus (HCV) replicates on a membrane protein complex composed of viral proteins, replicating RNA, and altered cellular membranes. Small-molecule inhibitors of cellular lipid-cholesterol metabolism such as 25-hydroxycholesterol, cerulenin, lovastatin, and GGTI-286 all show a negative effect on HCV replication. Perturbation of host cell lipid and cholesterol metabolism can disrupt replication complexes by altering membranous structures where replication occurs. Changes in cholesterol and (or) lipid composition can have a general effect on membrane structure. Alternatively, metabolic changes can exert a more subtle influence over replication complexes by altering localization of host proteins through alterations in lipid anchoring. Here, we use Huh-7 cells harboring subgenomic HCV replicons to demonstrate that 25-hydroxycholesterol, cerulenin, lovastatin, and GGTI-286 do not disrupt the membranous web where replication occurs, whereas cholesterol-depleting agents such as beta-cyclodextrin do. Cellular imaging suggests that the HCV RNA can remain associated with subcellular compartments connected with replication complexes in the presence of metabolic inhibitors. Therefore, at least 2 different molecular mechanisms are possible for the inhibition of HCV replication through the modulation of cellular lipid and cholesterol metabolism.
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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 | 0.000 | 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) | 0.000 | 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".