Hepatitis C virus induced up-regulation of microRNA-27: A novel mechanism for hepatic steatosis
Bibliographic record
Abstract
UNLABELLED: MicroRNAs (miRNAs) are small RNAs that posttranscriptionally regulate gene expression. Their aberrant expression is commonly linked with diseased states, including hepatitis C virus (HCV) infection. Herein, we demonstrate that HCV replication induces the expression of miR-27 in cell culture and in vivo HCV infectious models. Overexpression of the HCV proteins core and NS4B independently activates miR-27 expression. Furthermore, we establish that miR-27 overexpression in hepatocytes results in larger and more abundant lipid droplets, as observed by coherent anti-Stokes Raman scattering (CARS) microscopy. This hepatic lipid droplet accumulation coincides with miR-27b's repression of peroxisome proliferator-activated receptor (PPAR)-α and angiopoietin-like protein 3 (ANGPTL3), known regulators of triglyceride homeostasis. We further demonstrate that treatment with a PPAR-α agonist, bezafibrate, is able to reverse the miR-27b-induced lipid accumulation in Huh7 cells. This miR-27b-mediated repression of PPAR-α signaling represents a novel mechanism of HCV-induced hepatic steatosis. This link was further demonstrated in vivo through the correlation between miR-27b expression levels and hepatic lipid accumulation in HCV-infected SCID-beige/Alb-uPa mice. CONCLUSION: Collectively, our results highlight HCV's up-regulation of miR-27 expression as a novel mechanism contributing to the development of hepatic steatosis.
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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 | 0.001 |
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".