Portrait of Dr  Gianluca (Luca) Marcelli

Dr Gianluca (Luca) Marcelli

Senior Lecturer in Biomedical Engineering
Modelling of biological/medical systems

About

My main research interest is the mechanics of the red blood cell, for which I have developed a coarse-grained molecular model of the entire cell membrane. The structural elements of cells are soft which implies that their mechanical properties may be quite different from conventional hard materials due to the relevance of entropy and thermal fluctuations. The model I implemented consists in coarse-graining the whole cell membrane and in simulating it via a finite-temperature molecular-dynamics method. The model allows quantitative comparison with experimental data and it facilitates the interpretation of elastic-property measurements obtained with experimental techniques like micropipette-aspiration and optical-tweezers. This model clarified a long-standing problem of the red blood cell mechanical properties, showing that it possible to have nano-meter-size thermal fluctuation with a finite value of the shear modulus.

 

In collaboration with the Institute of Reproduction and Developmental Biology (Imperial College London) I undertook  research to understand the regulation of initiation of follicle growth in the mammalian ovary. Little is known about this mechanism, which is thought to be regulated by a network of signals. My work consisted in applying mathematical modeling to the spatial arrangement within the ovary in order to find relationships between follicles, surface epithelium and any other ovarian component, which can be involved in the mechanism of cell signaling. In particular I implemented a reaction diffusion model (Brownian dynamics) which helped understanding how growth factors production and receptor expression influence cell-signaling activity within the ovary.

More recently I have being working on medical instrumentation for rehabilitation (e.g. swallowing disorders) and in AI for medical application.

Research interests

Computational models for cell mechanics and cell signalling; AI for medical applications. Medical Instrumentation for rehabilitation.

Last updated 5 October 2022