microRNA-27b regulates hepatic lipase enzyme LIPC and reduces triglyceride degradation during hepatitis C virus infection
Bibliographic record
Abstract
miRNAs are short, noncoding RNAs that negatively and specifically regulate protein expression, the cumulative effects of which can result in broad changes to cell systems and architecture. The miRNA miR-27b is known to regulate lipid regulatory pathways in the human liver and is also induced by the hepatitis C virus (HCV). However, the functional targets of miR-27b are not well established. Herein, an activity-based protein profiling method using a serine hydrolase probe, coupled with stable isotope labeling and mass spectrometry identified direct and indirect targets of miR-27b. The hepatic lipase C (LIPC) stood out as both highly dependent on miR-27b and as a major modulator of lipid pathway misregulation. Modulation of miR-27b using both exogenous miRNA mimics and inhibitors demonstrated that transcription factors Jun, PPARα, and HNF4α, all of which also influence LIPC levels and activity, are regulated by miR-27b. LIPC was furthermore shown to affect the progress of the life cycle of HCV and to decrease levels of intracellular triglycerides, upon which HCV is known to depend. In summary, this work has demonstrated that miR-27b mediates HCV infection by downregulating LIPC, thereby reducing triglyceride degradation, which in turn increases cellular lipid levels.
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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".