A Role for Hepatic Leptin Signaling in Lipid Metabolism via Altered Very Low Density Lipoprotein Composition and Liver Lipase Activity in Mice
Bibliographic record
Abstract
UNLABELLED: Obesity is highly associated with dyslipidemia and cardiovascular disease. However, the mechanism behind this association is not completely understood. The hormone leptin may be a molecular link between obesity and dysregulation of lipid metabolism. Leptin can affect lipid metabolism independent of its well-known effects on food intake and energy expenditure, but exactly how this occurs is ill-defined. We hypothesized that since leptin receptors are found on the liver and the liver plays an integral role in regulating lipid metabolism, leptin may affect lipid metabolism by acting directly on the liver. To test this hypothesis, we generated mice with a hepatocyte-specific loss of leptin signaling. We previously showed that these mice have increased insulin sensitivity and elevated levels of liver triglycerides compared with controls. Here, we show that mice lacking hepatic leptin signaling have decreased levels of plasma apolipoprotein B yet increased levels of very low density lipoprotein (VLDL) triglycerides, suggesting alterations in triglyceride incorporation into VLDL or abnormal lipoprotein remodeling in the plasma. Indeed, lipoprotein profiles revealed larger apolipoprotein B-containing lipoprotein particles in mice with ablated liver leptin signaling. Loss of leptin signaling in the liver was also associated with a substantial increase in lipoprotein lipase activity in the liver, which may have contributed to increased lipid droplets in the liver. CONCLUSION: Lack of hepatic leptin signaling results in increased lipid accumulation in the liver and larger, more triglyceride-rich VLDL particles. Collectively, these data reveal an interesting role for hepatic leptin signaling in modulating triglyceride 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".