Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501440
Title: Dynamics of the host and vector response to malaria
Author: Cromer, Deborah
ISNI:       0000 0004 2672 8067
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2008
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Abstract:
This thesis presents a dual pronged approach to understanding malaria through the use of mathematical models. We present models both of infection within the host and of the immune response in the vector. The within host malaria model explores effects of the parasite's preference for young cells and the replacement rate of red blood cells (RBCs). We quantify the preference of the P. berghei parasite for young RBCs at 150 fold over older cells and deduce that the production of new cells is not suppressed during this rodent malaria infection. By altering the model slightly we apply it to a human malaria infection, and predict an optimal rate of RBC replacement during a malaria infection. This optimal rate is dependent on the preference of the parasite for younger cells and is generally far lower than the "healthy" replacement rate. This observation can explain experimental findings that iron deficient and anaemic children are less susceptible to malaria whilst iron supplemented children are more susceptible. The work pertaining to the vector response involves a model of cooperative gene regulation by two transcription factors. This is of particular relevance to studying the mosquito's immune response to the malaria parasite, as the immune genes are believed to be regulated by two transcription factors, REL1 and REL2. Using data from wild-type and knockdown cells we extract the activity profiles of the two transcription factors, and predict the sensitivity of target genes to each of the factors. This model should aid in understanding the mosquito immune response. Overall the thesis presents attempts at modelling the effects of malaria in mice, men and mosquitoes. The conclusions we are able to draw from our models provide insight into the factors affecting the dynamics of infection and form as a basis on which further studies can be built.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.501440  DOI: Not available
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