Antioxidant activity and cytotoxicity of methanol extracts from aerial parts of Korean salad plants

The aim of this investigation was to determine the content of total phenolics, antioxidant activity and cytotoxicity of methanol extracts from the aerial parts of 11 Korean medicinal salad plants. The highest total phenolic content of the methanol extracts was found in Aster scaber (17.1 mg 100 g(-1)), followed by Ixeris dentate (16.4 mg 100 g(-1)), Aster yomena (12.0 mg 100 g(-1)) and Sedum sarmentosum (9.1 mg 100 g(-1)) of FW. Methanol extracts of Ixeris dentate and Aster scaber at 50 microg mL(-1) exhibited the highest DPPH radical scavenging activity by 86.4 and 83.3%, respectively. It was registered a dose-dependent increase of DPPH free radical scavenging activity. Total phenolic content of the studied plant extracts was correlated with the DPPH radical scavenging activity. It was found by means of MTT assay, that cytotoxicity of the methanol extracts was the highest against HCT-116. Methanol extracts from Petasites japonicus (IC(50)<25.0 microg mL(-1)) showed the highest activity against HCT-116, following by Angelica gigas (34.75 microg mL(-1)), Erythronium japonicum (44.06 microg mL(-1)), and Aster scaber (54.87 microg mL(-1)). In conclusion, the studied salad plants have high total phenolics content and high antioxidant activity. These plants dose-dependently increased DPPH free radical scavenging activity. The total phenolics level was highly correlated with the free radical scavenging activity. Most of the studied salad plants have potent cytotoxicity activity. The results of this investigation suggest that the extracts of studied salad plants could be an addition to basic medicine for some diseases.     

Structured polychotomous machine diagnosis of multiple cancer types using gene expression

MOTIVATION: The problem of class prediction has received a tremendous amount of attention in the literature recently. In the context of DNA microarrays, where the task is to classify and predict the diagnostic category of a sample on the basis of its gene expression profile, a problem of particular importance is the diagnosis of cancer type based on microarray data. One method of classification which has been very successful in cancer diagnosis is the support vector machine (SVM). The latter has been shown (through simulations) to be superior in comparison with other methods, such as classical discriminant analysis, however, SVM suffers from the drawback that the solution is implicit and therefore is difficult to interpret. In order to remedy this difficulty, an analysis of variance decomposition using structured kernels is proposed and is referred to as the structured polychotomous machine. This technique utilizes Newton-Raphson to find estimates of coefficients followed by the Rao and Wald tests, respectively, for addition and deletion of import vectors. RESULTS: The proposed method is applied to microarray data and simulation data. The major breakthrough of our method is efficiency in that only a minimal number of genes that accurately predict the classes are selected. It has been verified that the selected genes serve as legitimate markers for cancer classification from a biological point of view. AVAILABILITY: All source codes used are available on request from the authors.     

Quantitative determination of amygdalin epimers from armeniacae semen by liquid chromatography

D-amygdalin and its conversion product, neoamygdalin, were quantitatively analyzed on reverse-phase, high-performance liquid chromatography with an optimized eluent of 10 mM sodium phosphate buffer (pH 3.1) containing 8.5% acetonitrile. Linearity between concentrations and detector responses was obtained in the range from 0.05 to 0.5 mM. The detection limits for D-amygdalin and neoamygdalin were approximately 5 microM per injected amount. Armeniacae semen contains not only amygdalin but also emlusin, which is an enzyme that hydrolyzes amygdalin. When extracting amygdalin from a whole piece of armeniacae semen in boiling water, there was almost no influence of emulsin; which increased the extraction efficiency. However, conversion of d-amygdalin into neoamygdalin at high temperature was found. In this report, we solved this problem by using 4% citric acid as an extractant. This solution also prevented the extraction process from being affected by emulsin. In addition, the extraction efficiency remained the same as that when methanol was used as an extractant, regardless of the cutting size.