Role of lysophosphatidic acid in vascular smooth muscle cell proliferation
Bibliographic record
Abstract
Lysophosphatidic acid (LPA) is an important lipid molecule for signal transduction in cell proliferation. Although the effects of LPA on vascular smooth muscle (VSM) cell growth have been reported previously, the underlying mechanisms of its action are not fully understood. The present study was undertaken to investigate the effects of some inhibitors of different protein kinases and other molecular targets on LPA-induced DNA synthesis as well as gene expression in the aortic VSM cells. The DNA synthesis was studied by the [3H]thymidine incorporation method and the gene expression was investigated by the real-time PCR technique. It was observed that the LPA-induced DNA synthesis was attenuated by inhibitors of protein kinase C (PKC) (staurosporine, calphostin C, and bisindolylmaleimide), phosphoinositide 3-kinase (PI3K) (wortmannin and LY294002), and ribosomal p70S6 kinase (p70S6K) (rapamycin). The inhibitors of guanine protein coupled receptors (GPCR) (pertussis toxin), phospholipase C (PLC) (U73122 and D609), and sodium–hydrogen exchanger (NHE) (amiloride and dimethyl amiloride) were also shown to depress the LPA-induced DNA synthesis. Furthermore, gene expressions for PLC β1 isoform, PKC δ and ε isoforms, casein kinase II β isoform, and endothelin-1A receptors were elevated by LPA. These results suggest that the LPA-induced proliferation of VSM cells is mediated through the activation of GPCR and multiple protein kinases as well as gene expressions of some of their specific isoforms.
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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 | 0.001 |
| 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".