This project aims to build on two previously successful PhD studentships supervised by Prof’s Bogle and Davies that have developed representative models of liver function addressing the metabolism of lipids (short and medium chain fatty acids) and simple sugars (fructose and glucose).
These projects have used a systems biology approach to build upon prior UCL computational liver studies and expand the scope of prior models to incorporate cellular zonation, blood flow and the initiation of pathological processes. Within the next project we aim to further develop these themes and incorporate the effects of inflammatory processes to effectively represent the pathology of liver disease. Inflammation is thekey driver in the development of cellular damage, cell death and the subsequent restructuring of the tissue architecture. Effective modelling of these processes will aid substantially in our understanding of the pathophysiology that results as a consequence liver injury.
Liver disease is a complex, multifactorial spectrum of conditions that can vary in scope and progression depending on the aetiology. For our studies we will initially utilise the work conducted on the effects of lipid accumulation within hepatocytes and the dysregulation of metabolism induced by excessivefructose availability. These represent real-world issues that relate to the continuing obesity epidemic which is intrinsically associated with over consumption of free sugars. In our studies to date we have identified potential intervention points for novel therapeutic approaches, which were subsequently supported as viable targets in cell culture studies, though more work is required to develop these concepts further.
There are numerous potential benefits to the successful development of a robust, representative model of liver metabolism and function. In addition to the ability to identify intervention points and model scenarios to chart the development of pathophysiological processes, it would also be possible to assess the impact of novel therapies prior to conducting in vivo studies, thus addressing a key area of ‘replacement’ as part of our institutional 3R’s strategy. This truly represents a cross disciplinary study in which the student will be required to develop strong computer based skills in addition to biochemical in vitro techniques and potentially also learn in vivo experimental methodologies.
Selected publications from recent PhD studentships
Liao, Y., Davies, N. A., & Bogle, I. D. L. (2020). Computational Modeling of Fructose Metabolism and Development in NAFLD. Frontiers in Bioengineering and Biotechnology, 8
Ashworth, W. B., Davies, N. A., & Bogle, I. D. (2016). A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD. PLoS Comput Biol,12 (9)
Ashworth, W., Perez-Galvan, C., Davies, N., & Bogle, I. D. L. (2016). Liver Function as an Engineering System AICHE JOURNAL,62 (9), 3285-3297
Studentships are expected to start on 26th September 2022 unless exceptional circumstances require an alternate start date.
Eligibility
Successful applicants must fulfil the academic entry requirements for the programme they are applying for. Further eligibility criteria are based on nationality and residence, see EPSRC regulations on Student eligibility.
These studentships are open to those with Home and International fee status (including EU); however, the number of students with International fee status which can be recruited is capped according to the EPSRC terms and conditions.
We particularly encourage applications from Black, Asian, and Minority Ethnic candidates, who are currently under-represented within UCL at this level.
How to Apply
Please submit applications in the following format:
- A CV, including full details of all University course grades to date.
- Contact details for two academic or professional referees.
- A personal statement (750 words maximum) outlining (i) your suitability for the project with reference to the criteria above, (ii) what you hope to achieve from the PhD and (iii) your research experience to-date.
Only shortlisted candidates will be contacted.
Please send your applications to [Email Address Removed]
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