Team:XJTU-China/Drylab-Overview
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Team:XJTU-China/Drylab-Models
Models
Model A
Overview
In our design, we aim to manufacture psicose, which has a lot of advantages over other sugar or sweetener as is mentioned in the research of the psicose. The advantages of psicose include low energy, benefit to diabetes and hyperlipidemia, making psicose become more and more popular in people. People can get a psicose sweetener or food rich in psicose, in which psicose is synthesized by biological ways, because using chemical ways is not a good choice to synthesize clear and edible psicose in a food grade for the containing of unhealthy and poisonous by-product in chemical synthesis methods.
Latex demo：
$$|x_1-x_2|=\sqrt{x_1^2+x_2^2-2|x_1||x_2|\cos(x_1,x_2)}\,,\,\,x_1,x_2\in R^n$$
$$|x_1-x_2| = \sqrt{1+1-2\cos(x_1,x_2)}\,,\,\,x_1,x_2\in R^n, |x_1|=|x_2|=1$$
Nevertheless, biological methods in producing psicose are inefficient due to the low enzyme efficiency of D-psicose 3-epimerase. The efficiency of D-psicose 3-epimerase is different due to the various environment system and the different concentration of substrate( sounds amazing due to the efficiency of enzyme irrelevant in most occasions). As a result, the temperature, PH value and the concentration are considered in our model to describe the efficiency of D-pisocose 3-epimerase, which is significant in our manufacture.
Although the market size is estimated large enough from the market research we have made, modeling is needed to describe exactly how much is the efficiency of D-psicose 3-epimerase. we analysis the efficiency of D-psicose 3-epimerase is affected by the temperature, PH value and the concentration of substrate. In this way, we can predict the catalytic efficiency of D-psicose 3-epimerase by simulating the catalytic process.
The third model we would like to model is the market model for the application of psicose. From the research, the conclusion that the psicose is very much needed among public and patients is analyzed. By the statistics we get, the potential market and the value curve of psicose appear from our mind by running the market model.
- Psicose Synthesis Kinetic Model
- Production Simulink Model
- Market and Price Model
- Microfluidics Model
Psicose synthesis kinetic model
In our design, the DTE process is one of the most significant part in manufacturing psicose. The main process of psicose manufacture is catalyzed by D-psicose 3-epimerase. The models of device A, B, C and D are as follows.
In device A, extracellular concentration of psicose is higher than which is intracellular, so it can enter the cells by diffusion. As a small molecular, the psicose inside the cell can be combined with pPsiR to generate cci. pPsiR is a repressor, which can bind to promoters on DNA and block gene expression. After binding with psicose, pPsiR falls off from the promoter and the gene starts expressing, And eventually produce the produce EGFP.
For device A, the dynamic equation can be listed as follows:
Concentrations of A and B are different inside and outside the cell, so the diffusion rate of is proportional to the concentration difference between inside and outside of the cells. The $$psicose$$ is the concentration of psicose.The $psicose$ is the concentration of psicose.
$$$$Where is the diffusion coefficient.
Finally, based on the probability distribution function, the variation of production is defined and we can compare the psicose production in natural system and directed evolution system.
Results and Discussion
Strengths and Prospect
Reference
Schmidt F R. Optimization and scale up of industrial fermentation processes.[J]. Appl Microbiol Biotechnol, 2005, 68(4):425-435.Lin P Y, Whang L M, Wu Y R, et al. Biological hydrogen production of the genus Clostridium: Metabolic study and mathematical model simulation[J]. International Journal of Hydrogen Energy, 2007, 32(12):1728-1735.
Whang L M, Hsiao C J, Cheng S S. A dual-substrate steady-state model for biological hydrogen production in an anaerobic hydrogen fermentation process[J]. Biotechnology & Bioengineering, 2010, 95(3):492-500.
Rousu J, Elomaa T, Aarts R. Predicting the speed of beer fermentation in laboratory and industrial scale[J]. 1999, 1607.
Model B
Model C
Model D