Signaling Pathways Involved in Human Vascular Smooth Muscle Cell Proliferation and Matrix Metalloproteinase-2 Expression Induced by Leptin
Bibliographic record
Abstract
Accumulating evidence suggests that high concentrations of leptin observed in obesity and diabetes may contribute to their adverse effects on cardiovascular health. Metformin monotherapy is associated with reduced macrovascular complications in overweight patients with type 2 diabetes. It is uncertain whether such improvement in the cardiovascular outcome is related to specific vasculoprotective effects of this drug. In the present study, we determined the effect of leptin on human aortic smooth muscle cell (HASMC) proliferation and matrix metalloproteinase (MMP)-2 expression, the signaling pathways mediating these effects, and the modulatory effect of metformin on these parameters. Incubation of HASMCs with leptin enhanced the proliferation and MMP-2 expression in these cells and increased the generation of intracellular reactive oxygen species (ROS). These effects were abolished by vitamin E. Inhibition of NAD(P)H oxidase and protein kinase C (PKC) suppressed the effect of leptin on ROS production. In HASMCs, leptin induced PKC, extracellular signal-regulated kinase (ERK)1/2, and nuclear factor-kappaB (NF-kappaB) activation and inhibition of these signaling pathways abrogated HASMC proliferation and MMP-2 expression induced by this hormone. Treatment of HASMCs with metformin decreased leptin-induced ROS production and activation of PKC, ERK1/2, and NF-kappaB. Metformin also inhibited the effect of leptin on HASMC proliferation and MMP-2 expression. Overall, these results demonstrate that leptin induced HASMC proliferation and MMP-2 expression through a PKC-dependent activation of NAD(P)H oxidase with subsequent activation of the ERK1/2/NF-kappaB pathways and that therapeutic metformin concentrations effectively inhibit these biological effects. These results suggest a new mechanism by which metformin may improve cardiovascular outcome in patients with diabetes.
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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 | 0.000 |
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 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".