Mathematical Modeling of Aquaporin 4 Intracellular Transport and Design of Complex Distillation Process

Mathematical modeling is a fundamental approach for many engineering problems, which enables to solve many complex transport phenomena in chemical engineering and bioengineering problems thus far classical approach could not solve. In the background of mathematical modeling, we have chosen two basic problems, optimization of distillation process and understanding of AQP4 transportation. In the approach of distillation simulation using complex columns, the applicability and stringency of the minimum bubble point distance algorithm combined with temperature collocation for the successful design of heat-integrated complex separation networks with various feeds and volatility differences were studied. The factor to determine the criteria of feasible design, the minimum BPD criterion was robust and efficient to characterize feasible network specifications guaranteeing continuous liquid composition profiles connecting all products and feed stages in each column section of complex flow sheets. As a case study, the design and syntheses for the simulated 18 different heat-integrated networks including simple column network were rigorously evaluated and the results suggest that only complex column configurations could save enegy. enhances the energy. In the problem solving of AQP4 translocation we, at first, vesicle transport model tracking individual (agent based) vesicle through the complete cell In our present work, we improved the cell model with true model from cultured astrocyte even though its intracellular environment is simplified with a couple of compartment units which are necessary for AQP4 transport mechanism by lumping all other kinetics. Moreover, we are the first to result in both quantitative and qualitative identification of AQP4 transport in the cellular level with computational approach. In the model proposed by us, stochastic method uses propensity function which is identical to the reaction rate equation of the ordinary differential equations (ODEs) in the deterministic approach. The present simulation is thought pioneering steps to understand biological system with computational solution and 3D visualization.