Computational Modelling Group

How far can we stretch the MARTINI?

Syma Khalid (Investigator), Ric Gillams

To date, coarse-grained lipid models have generally been parameterised to ensure the correct prediction of structural properties of membranes, such as the area per lipid and the bilayer thickness. The work described here explores the extent to which coarse-grained models are able to predict correctly bulk properties of lipids (phase behaviour) as well as the mechanical properties, such as lateral pressure profiles and stored elastic stress in bilayers. Such an evaluation is crucial for understanding the predictive capabilities of coarse-grained models.

Modelling mechanoreceptor reaction to tissue deformation

Mark Taylor (Investigator), Gwen Palmer

This project involved the modelling of a piece of knee joint capsule, which will produce an electrical output when mechanically stimulated. The model is based on expermental work carried out by P. Grigg and A.H. Hoffman (1982).

Modelling neuronal activity at the knee joint

Mark Taylor, Tiina Roose (Investigators), Gwen Palmer

The function of the knee joint is reliant on proprioception, which involves the response of nerve endings in the tissues at the joint. This project will be concentrating on the neuronal activity, caused by mechanical stimuli, of the more common receptors found at the knee (Ruffini, Paciniform, Golgi and Nociceptor).

There are three stages to this project:
1. Modelling the behaviour of each individual receptor, with the use of the Hodgkin-Huxley model [1].
2. These models will then be applied to the soft tissues around a knee, where a global deformation of the tissue will result in local stimulation of receptors.
3. The soft tissue models will then be applied to structures in the knee.

[1] - Hodgkin, A.L. and A.F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 1952. 117: p. 500-544.

Multi-objective design optimisation of coronary stents

Neil Bressloff, Georges Limbert (Investigators), Sanjay Pant

Stents are tubular type scaffolds that are deployed (using an inflatable balloon on a catheter), most commonly to recover the shape of narrowed (diseased) arterial segments. Despite the widespread clinical use of stents in cardiovascular intervention, the presence of such devices can cause adverse responses leading to fatality or to the need for further treatment. The most common unwanted responses of inflammation are in-stent restenosis and thrombosis. Such adverse biological responses in a stented artery are influenced by many factors, including the design of the stent. This project aims at using multi-objective optimisation techniques to find an optimum family of coronary stents which are more resistant to the processes of in-stent restenosis (IR) and stent thrombosis (ST).

MXL Project

Mark Taylor, Junfen Shi (Investigators)

‘MXL’ is short for “Enhanced patient safety by computational Modelling from clinically available X-rays to minimise the risk of overload and instability for optimised function and Longevity”. This is an international EU-funded project which the Bioengineering Sciences Research Group at Southampton is involved in. For more information, visit http://www.m-x-l.eu

Statistical model of the knee

Mark Taylor (Investigator), Francis Galloway, Prasanth Nair

Development of methods for large scale computational testing of a tibial tray incorporating inter-patient variability.

µ-VIS Computed Tomography Centre

Ian Sinclair, Richard Boardman, Dmitry Grinev, Philipp Thurner, Simon Cox, Jeremy Frey, Mark Spearing, Kenji Takeda (Investigators)

A dedicated centre for computed tomography (CT) at Southampton, providing complete support for 3D imaging science, serving Engineering, Biomedical, Environmental and Archaeological Sciences. The centre encompasses five complementary scanning systems supporting resolutions down to 200nm and imaging volumes in excess of one metre: from a matchstick to a tree trunk, from an ant's wing to a gas turbine blade.