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Title
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Mathematical model of plasma therapy on bacterial growth
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Author
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Abstract
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| In this thesis we have modeled the effect of plasma on bacteria (Escherichia coli) focusing on the glycolysis pathway. Development of cold atmospheric plasmas (CAP) and its potential applications have made plasma-medicine a popular field. Plasma is a complex mixture of reactive species, including charged and excited particles, reactive neutrals and UV photons. CAP has shown promising activity against bacteria, which is attributed to the reactive species. Indeed, the oxidative stress induced by plasma causes oxidation of biomolecules, especially proteins. To model in detail the interaction between bacteria and reactive species, we have extended the model introduced by Marr, i.e., a set of coupled ordinary differential equations based on protein production, to include the effect of plasma, using the Treanor distribution function (cold atmospheric plasma distribution function). The purpose of this study is not to describe rigorously all the biochemical processes occurring in a cell, but only the main ones. We added a term to one of the equations to describe protein damage and consequently bacterial death. The effect of exposure time and multi-step treatment are also discussed. Subsequently, we have tried to explain the antibacterial effect of cold atmospheric plasma through the glycolysis pathway. We already know that plasma oxidation kills bacteria through DNA damage and lipid peroxidation, but we do not know the effect of oxidative stress on different pathways. Because of the importance of the glycolysis pathway and its abnormal behavior, we have chosen this pathway. We have computationally investigated the effect of plasma-induced oxidation on various glycolysis metabolites, by monitoring the production of the biomass. We performed this study using the constraint-based reconstruction and analysis (COBRA) method, which is widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. COBRA is a constraint-base reconstruction algorithm, and using simple rules it tries to explain the behavior of the cell. It enables us to identify what happens in the whole cell when something changes in a specific part. We have solved our model using the Gourbi solver and observed that in addition to the significant reduction in biomass production, the rate of some reactions has increased. These reactions produce anti-oxidant products, showing the bacterial defense mechanism to escape the oxidative damage. Nevertheless, the simulations show that the plasma-induced oxidation effect is much stronger than the defense mechanism, causing killing of the bacteria. |
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Language
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English
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Publication
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Antwerp
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University of Antwerp, Department of Chemistry
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2020
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Volume/pages
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95 p.
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Note
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Bogaerts, Annemie [Supervisor]
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Shahmansouri, Mehran [Supervisor]
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Attri, Pankaj [Supervisor]
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Full text (publisher's version - intranet only)
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