Target genes involved in antiproliferative effect of modified ginseng extracts in lung cancer A549 cells.

Lung cancer is the most common cancer and the leading cause of cancer-related deaths. Panax ginseng has long been used to treat cancer and other diseases worldwide. Most of the pharmacological actions of ginseng are attributed to a variety of ginsenosides, which are often metabolized by intestinal bacteria into more effective forms. In this study, we found that the antiproliferative activity of ginseng was increased after enzymatic processing of ginseng saponin (50% inhibitory concentration, >70 µg/ml). To elucidate the mechanism by which modified ginseng extract (MGX) induced cell death in human lung cancer cells, the gene expression profiles of A549 cells regulated by MGX were assayed using Agilent PrimeView Human Gene Expression Arrays. The expression of 17 genes involved in the regulation of cell signaling, cell metabolism, transport, and cytoskeleton-regulation was up-regulated, whereas the expression of 16 genes implicated in invasion and metastasis and cellular metabolism was down-regulated in MGX-treated A549 cells. Moreover, nuclear staining with 4',6-diamidino-2-phenylindole revealed that MGX clearly caused nuclear condensation and fragmentation which are observed in apoptosis cell. These results elucidate crucial anticancer mechanisms of MGX and provide potential new targets for the assessment of anticancer activity of MGX.

A novel patient-specific model to compute coronary fractional flow reserve.

The fractional flow reserve (FFR) is a widely used clinical index to evaluate the functional severity of coronary stenosis. A computer simulation method based on patients' computed tomography (CT) data is a plausible non-invasive approach for computing the FFR. This method can provide a detailed solution for the stenosed coronary hemodynamics by coupling computational fluid dynamics (CFD) with the lumped parameter model (LPM) of the cardiovascular system. In this work, we have implemented a simple computational method to compute the FFR. As this method uses only coronary arteries for the CFD model and includes only the LPM of the coronary vascular system, it provides simpler boundary conditions for the coronary geometry and is computationally more efficient than existing approaches. To test the efficacy of this method, we simulated a three-dimensional straight vessel using CFD coupled with the LPM. The computed results were compared with those of the LPM. To validate this method in terms of clinically realistic geometry, a patient-specific model of stenosed coronary arteries was constructed from CT images, and the computed FFR was compared with clinically measured results. We evaluated the effect of a model aorta on the computed FFR and compared this with a model without the aorta. Computationally, the model without the aorta was more efficient than that with the aorta, reducing the CPU time required for computing a cardiac cycle to 43.4%.