miR-130b is a potent stimulator of hepatic very-low-density lipoprotein assembly and secretion via marked induction of microsomal triglyceride transfer protein
Bibliographic record
Abstract
miR-130b is a microRNA whose expression is particularly elevated within adipose tissue and in the circulation in diabetic states. Hepatic miR-130b expression has been linked to hepatocellular carcinoma and changes in lipid metabolism. Here, we investigated the role of miR-130b in hepatic lipid homeostasis and lipoprotein export. We observed that overexpression of miR-130b-3p or -5p in HepG2 cells markedly enhanced the secretion of very-low-density lipoprotein (VLDL) particles, enhanced the secretion of [ 3 H]glycerol metabolically labeled triglyceride (TG), and significantly increased the number or the average size of lipid droplets (LDs), respectively. Overexpression of miR-130b also altered the expression of key genes involved in lipid metabolism and in particular markedly increased both mRNA and protein expression levels of microsomal triglyceride transfer protein (MTP). Conversely, the miR-130b inhibitor decreased mRNA levels of MTP and fatty acid synthase ( FAS) in HepG2 cells. However, dual-luciferase reporter assays indicated that MTP is not a direct target of miR-130b-3p. miR-130b overexpression did not alter de novo synthesized TG or the stability and secretion of apolipoprotein B 100. Interestingly, knockdown of phosphatase and tensin homolog ( PTEN) blocked the upregulation of MTP mRNA induced by miR-130b. Finally, miR-130b-induced stimulation of VLDL secretion was also observed in a second hepatocyte cell culture model, immortalized human hepatocytes, confirming the effects observed in HepG2 cells. Overall, these data suggest a potential role for miR-130b in promoting hepatic VLDL assembly and secretion mediated by marked stimulation of MTP expression and TG mobilization. Thus miR-130b overexpression corrects the defect in VLDL production in HepG2 cells.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".