document.getElementById("tab1").innerHTML = '<h2>1 Introduction</h2><p>To facilitate the understanding of our multi-part system, a simulation for cell-cell interaction was developed in Java. Realistic data on movement and reproduction were applied so that our new introduced functions could be evaluated in this environment. This resulted in a two dimensional program where bacteria can interact with each other in real time, as if looked at in a microscope. In our scenario we consider the probiotic moving around on the small intestinal wall and reaching the outer surface of a Yersinia enterocolitica colony. By reading its surrounding the bacteria can invoke changes in the movement pattern or kill other species in their vicinity. This provides us with a tool to measure of how effective our introduced systems will be and add insight to how the systems can be improved. The program can easily be changed and applied to similar systems, hopefully making it a useful for understanding and evaluating future projects as well.</p><h2>2 Java Design</h2><p>In order to keep track of many different bacteria with individual properties we thought it convenient to use an object-oriented language. Since java also have the advantage of being easily distributed and made executable through a web browser environment, we found it was a perfect candidate. Most of the data that had to be visualized are dependent on the programs ability to measure distance. This was made possible by deciding upon a convenient scale and assigning the pixels a suitable size. In our simulation every pixel corresponds to 0.1µm, which makes it easy to visualize the 2x1 µm large bacteria and its movement.</p><h2>3 Introduced Data</h2><h3>3.1 Generation time & Flux</h3><p>Since the generation time of our simulated bacteria range between 20-40 min and we can only visualize a limited window, we decided to add a flux of bacteria to the visible area. In our case this will only affect the probiotic since Y. enterocolitica will be immobile at gut temperature(De Berardis et al., 2004). In other word, we assume that there are bacteria moving around outside our screen and that they “walk in” at a constant rate. They will still reproduce based on their real value but to depend solely on this force to drive the simulation would make it very time consuming.<br><br>The generation time for the probiotic is taken from E. coli, once every 20 min, and the pathogens will reproduce about every 40 min. The value for Y. enterocolitica has been measured 34 min at 30°C, which is assumed to be their optimal growth temperature (Aswathy Sreedharan, 2012). Since our simulation will take place at 37°C we had to account for this and therefor tweaked this value a bit. The reproduction will also be limited by available space so that bacteria are not able to stack on top of each other.</p><ul class="reference"><li>[1]Aswathy Sreedharan, C.J., 2012. Preventing Foodborne Illness: Yersiniosis [WWW Document]. URL http://edis.ifas.ufl.edu/fs193 (accessed 8.24.14).</li><li>[2]De Berardis, B., Torresini, G., Brucchi, M., Marinelli, S., Mattucci, S., Schietroma, M., Vecchio, L., Carlei, F., 2004. Yersinia enterocolitica intestinal infection with ileum perforation: report of a clinical observation. Acta Biomed 75, 77–81.</li><li>[3]77–81. H. C. Berg, 2004. E. coli in motion. Biological and medical physics series. (Springer, NewYork)</li><li>[4]Schwartz, S.A., Helinski, D.R., 1971. Purification and characterization of colicin E1. J. Biol. Chem. 246, 6318–6327.</li><li>[5]Spangler, R., Zhang, S.P., Krueger, J., Zubay, G., 1985. Colicin synthesis and cell death. J Bacteriol 163, 167–173.</li></ul>';

document.getElementById("tab1").innerHTML = '<h2>1 Introduction</h2><p>To facilitate the understanding of our multi-part system, a simulation for cell-cell interaction was developed in Java. Realistic data on movement and reproduction were applied so that our new introduced functions could be evaluated in this environment. This resulted in a two dimensional program where bacteria can interact with each other in real time, as if looked at in a microscope. In our scenario we consider the probiotic moving around on the small intestinal wall and reaching the outer surface of a Yersinia enterocolitica colony. By reading its surrounding the bacteria can invoke changes in the movement pattern or kill other species in their vicinity. This provides us with a tool to measure of how effective our introduced systems will be and add insight to how the systems can be improved. The program can easily be changed and applied to similar systems, hopefully making it a useful for understanding and evaluating future projects as well.</p><h2>2 Java Design</h2><p>In order to keep track of many different bacteria with individual properties we thought it convenient to use an object-oriented language. Since java also have the advantage of being easily distributed and made executable through a web browser environment, we found it was a perfect candidate. Most of the data that had to be visualized are dependent on the programs ability to measure distance. This was made possible by deciding upon a convenient scale and assigning the pixels a suitable size. In our simulation every pixel corresponds to 0.1µm, which makes it easy to visualize the 2x1 µm large bacteria and its movement.</p><h2>3 Introduced Data</h2><h3>3.1 Generation time & Flux</h3><p>Since the generation time of our simulated bacteria range between 20-40 min and we can only visualize a limited window, we decided to add a flux of bacteria to the visible area. In our case this will only affect the probiotic since Y. enterocolitica will be immobile at gut temperature(De Berardis et al., 2004). In other word, we assume that there are bacteria moving around outside our screen and that they “walk in” at a constant rate. They will still reproduce based on their real value but to depend solely on this force to drive the simulation would make it very time consuming.<br><br>The generation time for the probiotic is taken from E. coli, once every 20 min, and the pathogens will reproduce about every 40 min. The value for Y. enterocolitica has been measured 34 min at 30°C, which is assumed to be their optimal growth temperature (Aswathy Sreedharan, 2012). Since our simulation will take place at 37°C we had to account for this and therefor tweaked this value a bit. The reproduction will also be limited by available space so that bacteria are not able to stack on top of each other.</p><ul class="reference"><li>[1]Aswathy Sreedharan, C.J., 2012. Preventing Foodborne Illness: Yersiniosis [WWW Document]. URL http://edis.ifas.ufl.edu/fs193 (accessed 8.24.14).</li><li>[2]De Berardis, B., Torresini, G., Brucchi, M., Marinelli, S., Mattucci, S., Schietroma, M., Vecchio, L., Carlei, F., 2004. Yersinia enterocolitica intestinal infection with ileum perforation: report of a clinical observation. Acta Biomed 75, 77–81.</li><li>[3]77–81. H. C. Berg, 2004. E. coli in motion. Biological and medical physics series. (Springer, NewYork)</li><li>[4]Schwartz, S.A., Helinski, D.R., 1971. Purification and characterization of colicin E1. J. Biol. Chem. 246, 6318–6327.</li><li>[5]Spangler, R., Zhang, S.P., Krueger, J., Zubay, G., 1985. Colicin synthesis and cell death. J Bacteriol 163, 167–173.</li></ul>';

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