Ursolic acid suppresses leptin-induced cell proliferation in rat vascular smooth muscle cells
Bibliographic record
Abstract
Accumulating lines of evidence indicate that high leptin levels are associated with adverse cardiovascular health in obese individuals. Proatherogenic effects of leptin include endothelial cell activation and vascular smooth muscle cell proliferation and migration. Ursolic acid (UA) has been reported to exhibit multiple biological effects including antioxidant and anti-inflammatory properties. In this study, we investigated the effect of UA on leptin-induced biological responses in rat vascular smooth muscle cells (VSMCs). A-10 VSMCs were treated with leptin in the presence or absence of UA. Intracellular reactive oxygen species (ROS) was probed by 2',7'-dichlorofluorescein diacetate. The expression of extracellular signal-regulated kinase (ERK)1/2, phospho-(ERK)1/2, nuclear factor-kappa B (NF-κB) p65 and p50, and matrix metalloproteinase-2 (MMP2) was determined by Western blotting. Immunocytochemistry and confocal laser scanning microscopy were also used for the detection of NF-κB. The secretion of MMP2 was detected by gelatin zymography. UA exhibited antioxidant activities in vitro. In rat VSMCs, UA effectively inhibited cell growth and the activity of MMP2 induced by leptin. These suppressive effects appeared by decreasing the activation of (ERK)1/2, the nuclear expression and translocation of NF-κB, and the production of ROS. UA appeared to inhibit leptin-induced atherosclerosis, which may prevent the development of obesity-induced cardiovascular diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".