Difference between revisions of "Team:Tianjin/Model"

Line 220: Line 220:
 
<h3 class="collapse-card__title">
 
<h3 class="collapse-card__title">
 
<i class="fa fa-random"></i>
 
<i class="fa fa-random"></i>
Construction of Bistable Model
+
Construction of Adsorption Model
 
</h3>
 
</h3>
 
</div>
 
</div>
 
<div class="collapse-card__body">
 
<div class="collapse-card__body">
<h4>1232321</h4>
+
<h4>Overview</h4>
 +
<p> In our experiment we use engineered yeast cells to absorb and enrich heavy metals such as cooper and cadmium. At first heavy metal ions diffuse into the cell surface from the liquid phase body, and then heavy metal ions are combined with those heavy metal-treated proteins inside the yeast cells.</p>
 +
<img= src"">
 +
<h4>Summary</h4>
 +
<p>Treating heavy metal pollution by means of biosorption is a complicated process. First, it is very meaningful to study the growth of yeast in heavy metal ions solution. Considering that the toxic effects of heavy metal ions on yeast can’t be ignored, we use the matrix inhibition growth model to simulate the growth kinetics of yeast in heavy metal ions solution. Next, we decide to study the process of biological adsorption from the thermodynamic and kinetic point of view. In terms of thermodynamics, we use the basic thermodynamic function to explain the adsorption process, and the conclusions can guide the further optimization of the biosorption. In addition, different static adsorption models are used to simulate the adsorption process, and the conclusions are able to explain the mechanism of the part of the biosorption process. Then we discuss the change of heavy metal ions with time in the process of biosorption from the point of view of dynamics, and compare with the actual measured data.</p>
 +
<h4>Yeast growth model</h4>
 +
<p>Heavy metal ions inhibits the growth of yeast. In order to describe the kinetics of cell growth accurately,these crucial factors should be taken into account。Unlike the traditional Monod equation, Andrew equation takes the presence of matrix anticompetitive inhibition into consideration.</p>
 +
    <p>
 +
\[ 
 +
\[\frac{{d[mACE1]}}{{dt}} = cp{n_{\rm{1}}} \times (tr{c_1} - {\deg _1} \times [mACE1])\]
 +
\]
 +
</p>
 
   <p>Bistability is a common phenomenon in single-cell microbes, that two types of cell phenotype coexist. Bistability is very important for many single-cell microbes adapting to environmental changes. Single-cell microbes can choose the appropriate form according to changes of the environment, and bistability is the basis for achieving this change.</p>
 
   <p>Bistability is a common phenomenon in single-cell microbes, that two types of cell phenotype coexist. Bistability is very important for many single-cell microbes adapting to environmental changes. Single-cell microbes can choose the appropriate form according to changes of the environment, and bistability is the basis for achieving this change.</p>
 
         <p>the reason for the existence of bistability in single-cell microbes is complex, and is generally thought to be related to the positive feedback of the gene network. We simulate the bistability in single-celled microbes by establishing a simplified gene regulation model.</p>
 
         <p>the reason for the existence of bistability in single-cell microbes is complex, and is generally thought to be related to the positive feedback of the gene network. We simulate the bistability in single-celled microbes by establishing a simplified gene regulation model.</p>

Revision as of 01:52, 27 October 2017

/* OVERRIDE IGEM SETTINGS */

Model