The availability of large-scale datasets has led to more effort being made to understand characteristics of metabolic reaction networks. However, because the large-scale data are semi-quantitative, and may contain biological variations and/or analytical errors, it remains a challenge to construct a mathematical model with precise parameters using only these data. The present work proposes a simple method, referred to as PENDISC (arameter stimation in a on-mensionalized -system with onstraints), to assist the complex process of parameter estimation in the construction of a mathematical model for a given metabolic reaction system. The PENDISC method was evaluated using two simple mathematical models: a linear metabolic pathway model with inhibition and a branched metabolic pathway model with inhibition and activation. The results indicate that a smaller number of data points and rate constant parameters enhances the agreement between calculated values and time-series data of metabolite concentrations, and leads to faster convergence when the same initial estimates are used for the fitting. This method is also shown to be applicable to noisy time-series data and to unmeasurable metabolite concentrations in a network, and to have a potential to handle metabolome data of a relatively large-scale metabolic reaction system. Furthermore, it was applied to aspartate-derived amino acid biosynthesis in Arabidopsis thaliana plant. The result provides confirmation that the mathematical model constructed satisfactorily agrees with the time-series datasets of seven metabolite concentrations.Electronic supplementary materialThe online version of this article (doi:10.1007/s11538-014-9960-8) contains supplementary material, which is available to authorized users.
Plasmas that are generated on and in liquids are generally the subject of pure research at universities; however, they have considerable practical potential for use in material processing, water purification, and sterilization. Their chief drawback is that they require a large device to generate in-water plasmas and a bulky power supply. If the device size and the volume of the power supply could be reduced, it might be possible to realize water sterilization in home electric appliances, such as washing machines. We have developed a compact device with a unique structure and a dedicated power supply that provides high voltage at high frequencies for generating in-water plasmas. Our dedicated power supply occupies one-sixth of the volume of comparable types. The device can generate in-water plasmas in an air stream using ambient air introduced from outside using a pump. Hydroxyl (OH) radicals in in-water plasmas were detected by optical emission spectroscopy, and their spatial distribution was observed in the air steam using an intensified charge-coupled device camera and a bandpass filter of 309 nm. Hydroxyl radicals in water were detected as 5, 5-dimethyl-1-pyrroline-N-oxide (DMPO)-OH signals using electron spin resonance spin trapping, both before adding DMPO to water and after doping the plasma-treated water with DMPO. It was found that OH radicals were generated in in-water plasmas and persisted in plasma-treated water. Using the detection of DMPO-OH signals employing the postdoped method, OH radicals were measured at 0.86 nmol/cc; they remained in the water for a long time after turning OFF the power supply. Finally, we demonstrated the decomposition rate of indigo carmine using our device and power supply to be about 13-fold that of the comparable device, despite its consuming about one-seventh of the input power. Hydroxyl radicals have high oxidation potential, so in-water plasmas as a source of radicals may be applicable to water sterilization in home electric appliances.
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