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Modelling the deformation of cells

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Cells are the elementary building blocks of living organisms. The correct functioning of living organisms is therefore conditioned to the ability of living cells to withstand forces and deformations and to promptly adapt to their mechanical environment. Alteration of the cell mechanical properties can contribute to disease such as cancer. It is, therefore, crucial to identify the conditions that compromise the mechanical resilience of cells.

We recently observed that cells pocked by a microscopic cantilever respond with sudden avalanche-like events [1]. Avalanche dynamics have been observed in solids (e.g. during fracture or deformation of shape memory alloys) but are more surprising for living cells which are regarded as a soft material. The behaviour is, however, not completely unexpected
since cells exhibit solid and liquid-like properties.

Another intriguing manifestation of solid-like behaviour of cells is the recently observed degradation of the cytoskeleton integrity under cyclic loading [2]. This behaviour is reminiscent of the degradation in solids which has been explained in terms of deformation-induced dislocations [3]. The mechanism behind degradation for cells, however, is unknown.

This project will study avalanches and degradation of cells under mechanical load. The study will be based on network models inspired from models of avalanches in solids [3,4]. Predictions of the model will be validated through comparison with experimental data. After validation, models will be used to make new predictions that can motivate new experiments.

The World Health Organisation reports that infectious diseases cause 63% of childhood deaths and 48% of premature deaths. There is the ongoing risk of epidemics and pandemics that can cause widespread morbidity and mortality (Spanish flu, ebola, SARS, E. coli, Listeria etc).

Infectious diseases can reach humans in many different ways: they can be transmitted between healthy and infected people, through consumption of infected food or water, through contact with animals, etc. The world is massively interconnected enabling people, animals and food to move rapidly between continents along with infectious disease agents.

Tracing the origin and spread of infectious diseases has never been more challenging and more important. The spectacular developments in detection and whole genome sequencing of disease agents as well as the computational power which enables timely processing of big data offers the opportunity to tackle this problem.

For example, the geographical spread of infectious disease is generally insufficient to trace back the labyrinth of possible pathways through which humans become infected. However, combining geographical information on disease spread with information on the genetic evolution of the infectious disease agents has promise [1-3]. Methodologies to achieve this are still in their infancy and this project is an opportunity to make a significant contribution in tackling this critical problem. The project will:

1. Use computer workstations to simulate the spread and evolution of infectious disease agents. Simulations will be based on geographical and whole genome sequence datasets of real pathogens. The simulations will generate virtual histories of their spread and evolution.
2. Use these results to develop methods that explain how epidemics occurred.
3. Use this knowledge to predict future epidemics and to develop and simulate strategies to reduce infectious disease risk.

Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in Applied maths or physics.

The applicants should have an interest in mathematical modelling of biological systems. Experience in mathematical modelling, computer programming and computational models is not essential but would be beneficial.

APPLICATION PROCEDURE:

• Apply for Degree of Doctor of Philosophy in Physics
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form

When applying please ensure all required documents are attached:

• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV
• Details of 2 academic referees

Informal inquiries can be made to Dr F Perez-Reche () with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ()

Funding Notes

This project is advertised in relation to the research areas of the discipline of physics/applied mathematics. The successful applicant will be expected to provide the funding for Tuition fees, living expenses and maintenance. Details of the cost of study can be found by visiting View Website. THERE IS NO FUNDING ATTACHED TO THESE PROJECTS. Applicants should also be aware that Additional Research Costs of £1,000 per annum are required (above Tuition Fees and Living Expenses) for numerical simulation software.

References

[1] S. Polizzi, B. Laperrousaz, F.J. Perez-Reche et al. A minimal rupture cascade model for living cell plasticity. New J. Phys. 20, 053057 (2018).

[2] N. Bonakdar et al. Mechanical plasticity of cells. Nat. Mater. 15, 1090–1094 (2016).

[3] F.J. Perez-Reche, Modelling Avalanches in Martensites. in Avalanches in Functional Materials and Geophysics (eds. Salje, E. K. H., Saxena, A. & Planes, A.) 99–136 (Springer International Publishing, 2017). doi:10.1007/978-3-319-45612-6_6

[4] F.J. Perez-Reche, C. Triguero, G. Zanzotto, L. Truskinovsky, Origin of scale-free intermittency in structural first-order phase transitions. Phys. Rev. B 94, 144102 (2016).

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