RESUMO
Environmental risk assessment is an essential step in the development of solutions for pollution problems and new environmental regulations. An assessment system for environmental risks has been developed in China in recent decades. However, many of the Chinese technical guidelines, standards, and regulations were directly adapted from those of developed countries, and were not based on the Chinese environmental and socioeconomic context. Although existing environmental regulations for pollutants are usually obtained by extrapolations from high-dose toxicological data to low-dose scenarios using linear-non-threshold (LNT) models, toxicologists have argued that J-shaped or inverse J-shaped curves may dominate the dose-response relationships for environmental pollutants at low doses because low exposures stimulate biological protective mechanisms that are ineffective at higher doses. The costs of regulations based on LNT and J-shaped models could therefore be dramatically different. Since economic factors strongly affect the decision-making process, particularly for developing countries, it is time to strengthen basic research to provide more scientific support for Chinese environmental regulations. In this paper, we summarize current Chinese environmental policies and standards and the application of environmental risk assessment in China, and recommend a more scientific approach to the development of Chinese regulations.
RESUMO
The shape of dose response of ionizing radiation (IR) induced cancer at low dose region, either linear non-threshold or J-shaped, has been a debate for a long time. This dose response relationship can be influenced by built-in capabilities of cells that minimize the fixation of IR-mediated DNA damage as pro-carcinogenic mutations. Key capabilities include sensing of damage, activation of cell cycle checkpoint arrests that provide time needed for repair of the damage as well as apoptosis. Here we describe computational modeling of the signaling pathways that link sensing of DNA damage and checkpoint arrest activation/apoptosis to investigate how these molecular-level interactions influence the dose response relationship for IR induced cancer. The model provides qualitatively accurate descriptions of the IR-mediated activation of cell cycle checkpoints and the apoptotic pathway, and of time-course activities and dose response of relevant regulatory proteins (e.g. p53 and p21). Linking to a two-stage clonal growth cancer model, the model described here successfully captured a monotonically increasing to a J-shaped dose response curve and identified one potential mechanism leading to the J-shape: the cell cycle checkpoint arrest time saturates with the increase of the dose.
RESUMO
The hormesis phenomena or J-shaped dose response have been accepted as a common phenomenon regardless of the involved biological model, endpoint measured and chemical class/physical stressor. This paper first introduced a mathematical dose response model based on systems biology approach. It links molecular-level cell cycle checkpoint control information to clonal growth cancer model to predict the possible shapes of the dose response curves of Ionizing Radiation (IR) induced tumor transformation frequency. J-shaped dose response curves have been captured with consideration of cell cycle checkpoint control mechanisms. The simulation results indicate the shape of the dose response curve relates to the behavior of the saddle-node points of the model in the bifurcation diagram. A simplified version of the model in previous work of the authors was used mathematically to analyze behaviors relating to the saddle-node points for the J-shaped dose response curve. It indicates that low-linear energy transfer (LET) is more likely to have a J-shaped dose response curve. This result emphasizes the significance of systems biology approach, which encourages collaboration of multidiscipline of biologists, toxicologists and mathematicians, to illustrate complex cancer-related events, and confirm the biphasic dose-response at low doses.
RESUMO
We hypothesized that the growth rates of filaments and floc formers in activated sludge are affected by the combination of kinetic selection (Lou and de los Reyes, Biotechnol Bioeng 92(6): 729-739, 2005b) and substrate diffusion limitation (Martins et al., Water Res 37:2555-2570, 2003). To clarify the influence of these factors in explaining filamentous bulking, a conceptual framework was developed in this study. The framework suggests the existence of three different regions corresponding to bulking, non-bulking, and intermediate regions, based on substrate concentration. In the bulking and non-bulking regions, kinetic growth differences control the competition process, and filaments or floc formers dominate, respectively. In the intermediate region, substrate diffusion limitation, determined by the floc size, plays the major role in causing bulking. To test this framework, sequencing batch reactors (SBRs) were operated with influent COD of 100, 300, 600, and 1,000 mg/L, and the sludge settleability was measured at various floc size distributions that were developed using different mixing strengths. The experimental data in the bulking and intermediate regions supported the proposed framework. A model integrating the two factors was developed to simulate the substrate concentrations at different depths and floc sizes under intermittently feeding conditions. The modeling results confirmed that substrate diffusion limitation occurs inside the flocs at a certain range of activated sludge floc sizes over the operation cycle, and provided additional support for the proposed framework.
Assuntos
Modelos Biológicos , Esgotos/química , Esgotos/microbiologia , Biomassa , Reatores Biológicos , Difusão , Floculação , Cinética , Eliminação de Resíduos Líquidos/métodos , Microbiologia da ÁguaRESUMO
Filamentous bulking in activated sludge systems occurs when filamentous organisms outgrow floc-forming bacteria and interfere with sludge settling. The competition between filaments and floc formers has been described previously using the kinetic selection and filamentous backbone theories. We hypothesized that differences in decay rates and storage abilities also affect this competition. We tested this hypothesis by integrating these four factors into a substrate-utilization model to predict and explain coexistence in a completely mixed reactor. In addition, filamentous and nonfilamentous sludges were developed in laboratory-scale reactors and analyzed to determine decay rates. The modeling results showed coexistence of the two organism types, and sensitivity analysis showed that the kinetic parameters, storage rate constants, and backbone coefficient had the greatest effect on the simulation results. Monte Carlo simulation showed the effect of storage, and the ranges of dilution rates wherein one group outcompeted the other were delineated.