[In vitro screening of natural compounds with antitumor activity by trypsin].

In order to investigate the feasibility of in vitro screening the antitumor activity of natural compounds by trypsin, porcine trypsin was used to for screening test, which is marked by inhibition of enzyme activity. Four compounds, namely daidzin, genistin, matrine and oxymatrine, were selected as test subjects. The natural antitumor drug camptothecin was used as the control. The inhibitory effect was detected by two experimental methods: direct detection of trypsin activity inhibition and hydrolysis of bovine serum albumin by trypsin. The results showed the inhibitory effects of the four natural compounds on trypsin, and the inhibition rates of the four natural compounds were significantly different. The enzyme activity assay showed that the inhibitory effect of matrine was better than that of oxymatrine, indicating that trypsin had a good screening resolution. The inhibitory effect was significantly increased with the increased ratio of sample to trypsin, suggesting the structure-activity correlation and dose-effect correlation of the screening methods. Altogether, the experimental method of screening antitumor activity of natural compounds by trypsin has good application values. Since porcine trypsin is similar to human trypsin in terms of molecular structure and performance, it is more applicable for screening of antitumor efficacy of natural pharmacodynamic compounds.

Assessment of heavy metal pollution and human health risks in urban soils around an electronics manufacturing facility.

Heavy metal pollution has pervaded many parts of the world, especially in developing countries. The purpose of this study was to determine the concentrations and health risks of heavy metals in urban soils around an electronics manufacturing site in the Hubei Province of China. Soils samples were collected from commercial, roadside, farmland, and residential areas around the electronics manufacturing facility. A total of 136 topsoil samples were collected, and these samples were analyzed for Cr, Cu, Zn, As, Cd, Ni, and Pb. The geoaccumulation index (Igeo), pollution index (PI), and potential ecological risk index (PER) were calculated to assess the soil pollution levels. The hazard index (HI) was used to assess the human health risks posed by the presence of heavy metals. The total concentrations of the seven congeners (∑metals) ranged from 3738.86 to 5173.25mgkg-1, and the concentrations were highest in the commercial area followed (in decreasing order) by the roadside, farmland, and residential areas. The HI for children and adults descended in the order of Cr>As>Pb>Cd>Cu>Ni>Zn. The carcinogenic risks of two metals, namely, Cr and As, for children and adults were higher than 10-4, and children faced greater health risks.

Efficient simulation under a population genetics model of carcinogenesis.

MOTIVATION: Cancer is well known to be the end result of somatic mutations that disrupt normal cell division. The number of such mutations that have to be accumulated in a cell before cancer develops depends on the type of cancer. The waiting time T(m) until the appearance of m mutations in a cell is thus an important quantity in population genetics models of carcinogenesis. Such models are often difficult to analyze theoretically because of the complex interactions of mutation, drift and selection. They are also computationally expensive to simulate because of the large number of cells and the low mutation rate. RESULTS: We develop an efficient algorithm for simulating the waiting time T(m) until m mutations under a population genetics model of cancer development. We use an exact algorithm to simulate evolution of small cell populations and coarse-grained τ-leaping approximation to handle large populations. We compared our hybrid simulation algorithm with the exact algorithm in small populations and with available asymptotic results for large populations. The comparison suggested that our algorithm is accurate and computationally efficient. We used the algorithm to study the waiting time for up to 20 mutations under a Moran model with variable population sizes. Our new algorithm may be useful for studying realistic models of carcinogenesis, which incorporates variable mutation rates and fitness effects.