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Genistein is a major component of soybean isoflavone and has multiple functions resulting in antitumor effects. Prostate cancer is 1 of the targets for the preventive role of genistein. We examined the effect of genistein on human prostate cancer (LNCaP and PC-3) cells. Proliferation of both cell lines was inhibited by genistein treatment in a dose-dependent manner. To obtain the gene expression profile of genistein in LNCaP cells, we performed cDNA microarray analysis. The expression of many genes, including apoptosis inhibitor (survivin), DNA topoisomerase II, cell division cycle 6 (CDC6) and mitogen-activated protein kinase 6 (MAPK 6), was downregulated. Expression levels were increased more than 2-fold in only 4 genes. The glutathione peroxidase (GPx)-1 gene expression level was the most upregulated. Quantitative real-time polymerase chain reaction revealed significant elevation of transcript levels of GPx-1 in both LNCaP and PC-3 cells. Upregulation of gene expression levels accompanied elevation of GPx enzyme activities. In contrast, no significant changes were observed in the gene expression levels and enzyme activities of the other antioxidant enzymes, superoxide dismutase and catalase. GPx activation might be one of the important characteristics of the effects of genistein on prostate cancer cells.

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Spatial statistics methods are used to determine the effect of the sampling scale and method on two measures of mixing: the coefficient of variance CoV and the maximum striation thickness. Three sampling methods: quadrats, probes and transects, were tested. Two CFD data sets were used as test cases: dispersion of floating particles in a turbulent stirred tank and laminar mixing of tracer particles in a micromixer. Over 100 probes are needed to track the evolution of the CoV, and the probe size should match the smallest mixing scale of interest. The final value of the CoV varies by up to a factor of 5 as the probe size increases. The most useful measurement is the one which changes the most in the later stages of mixing: intensity of segregation, or CoV, for the turbulent case; and scale of segregation, or maximum striation thickness on a transect, for the laminar case. © 2008 American Institute of Chemical Engineers AIChE J, 2008

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Misestimating risk could lead to disadvantaged choices such as initiation of drug use (or gambling) and transition to regular drug use (or gambling). Although the normative theory in decision-making under risks assumes that people typically take the probability-weighted expectation over possible utilities, experimental studies of choices among risks suggest that outcome probabilities are transformed nonlinearly into subjective decision weights by a nonlinear weighting function that overweights low probabilities and underweights high probabilities. Recent studies have revealed the neurocognitive mechanism of decision-making under risk. However, the role of modulatory neurotransmission in this process remains unclear. Using positron emission tomography, we directly investigated whether dopamine D 1 and D 2 receptors in the brain are associated with transformation of probabilities into decision weights in healthy volunteers. The binding of striatal D 1 receptors is negatively correlated with the degree of nonlinearity of weighting function. Individuals with lower striatal D 1 receptor density showed more pronounced overestimation of low probabilities and underestimation of high probabilities. This finding should contribute to a better understanding of the molecular mechanism of risky choice, and extreme or impaired decisionmaking observed in drug and gambling addiction.