Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.718369
Title: Mathematical modelling of epithelium homeostasis
Author: Domínguez Hüttinger, Elisa
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Abstract:
The body and organs of all animals are covered by epithelial tissues, such as the epidermis and the airway epithelium. Epithelial tissues play a key role in protecting the body from environmental aggressors. Failure to maintain a competent epithelium can lead to the onset of many diseases, including Atopic dermatitis (AD) and infection by Streptococcus pneumoniae. Treatment of AD is currently restricted to the relief of symptoms, mainly because the underlying mechanisms remain elusive. Antibiotic resistance threatens the effectiveness of the prevalent treatments for infection. Devising new and effective therapeutic strategies that halt the progression of these diseases requires an understanding of the different disease mechanisms that can cause loss of epithelial homeostasis in different patients. Intricate regulatory networks of several biochemical and cellular interactions maintain epithelium homeostasis in healthy individuals, but can also propagate different disturbances, resulting in a wide spectrum of possible disease phenotypes. In this thesis, we propose mathematical models of these regulatory networks to analyse the mechanisms that lead to the onset and progression of AD and pneumococcal infection from a systems-level perspective. Our mathematical model of AD reproduced, for the first time, the different stages of the disease that have been observed in the clinic. Moreover, we proposed different pathogenic mechanisms, triggered by different genetic and environmental risk factors that are known to predispose to AD. By assessing the effects of common treatments for AD, we suggested effective treatment strategies that can prevent the aggravation of the disease, in a patient-specific way. Our data-driven mathematical model of pneumococcal infection identified four qualitatively different mechanisms by which co-infection can drive the pathogenic process. They can be counteracted by distinctive treatment strategies that only partially involve antibiotics. Our work provides a theoretical framework for the integration and analysis of clinical and experimental data describing epithelial homeostasis.
Supervisor: Tanaka, Reiko J. ; Barahona, Mauricio Sponsor: Mexican Council of Science and Technology (Consejo Mexicano de Ciencia y Tecnología ; CONACyT) ; Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.718369  DOI: Not available
Share: