2008 intake

   
Thomas Blacker Optical measurements of cellular metabolic signalling
Anton Flugge Analysing spatial patterns of tropical rainforest tree species
Jack Honeysett Clinical monitoring with acousto-optic techniques and microbubbles
Tracy Moroz Shedding light on brain energy metabolism in traumatic brain injury patients using novel photonic systems and in silico methods.
Francesca Norris High resolution micro MRI for mouse phenotyping
Martin O'Reilly 3D reconstruction and analysis of neural circuits
Mae Woods

Modelling Cell Migration


Tom Blacker 

Optical measurements of cellular metabolic signalling

Supervisors: Prof. Michael Duchen (Cell & Developmental Biology) and Dr.
Angus Bain (Physics & Astronomy)

Obtaining images of live cells using fluorescence microscopy typically
involves staining a component of interest in the biological sample using a
specific fluorescent label.  However, a collection of molecules in the
cell are intrinsically fluorescent, requiring no staining to monitor their
status.  These molecules, NAD(P)H and flavoproteins, have important roles
in regulating metabolic processes.  In this research, live-cell imaging
and photophysical studies will be combined to investigate how NAD(P)H and
flavoprotein autofluorescence can be used to gain an understanding of the
metabolic state of a cell.

Tom's Website: http://www.ucl.ac.uk/~ucbptsb



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Tom Blacker

Anton Flugge

Analysing spatial patterns of tropical rainforest tree species

Supervisors: David Murrell (Genetics, Evolution, and Environment), Sofia Olhede (Statistical Science)

Spatial patterns of trees in the forest can provide information on the ecological processes that shape those patterns. The project will use computer modelling and an extensive, spatially referenced dataset that holds information on over 300,000 individual trees
over 25 years to investigate the roles of habitat heterogeneity; neighbour competition; and dispersal on growth and survival. In particular the focus is on investigating the properties of rare species, which have an
important role in tropical rainforests given their high bio-diversity.

Anton's Homepage: http://www.ucl.ac.uk/~ucbpajf




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Anton Flugge

Jack Honeysett

Clinical monitoring with acousto-optic techniques and microbubbles

Supervisors : Dr. Terence Leung (Medical Physics), Dr. Jing Deng, Dr. Eleanor Stride

Conventional optical imaging of biological tissue can achieve improved spatial resolution by incorporating focused ultrasound. This hybrid acousto-optic (AO) technique however is too weak to be used reliably in biomedical imaging. Here the introduction of microbubbles is proposed as a means to amplify the AO signal to an experimentally useful level. Microbubbles are well established as contrast agents for clinical ultrasound imaging. Their effect on AO imaging is investigated using Monte Carlo simulations of photon transport through a highly scattering medium. We hope that these will be verified by experimental results using tissue phantoms constructed in the lab.


Microbubbles could eventually be used as a clinical contrast agent in acousto-optical measurements of oxygen saturation, with the aim of non-invasively monitoring oxygen levels in the pulmonary artery of intensive care patients.


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Jack Honeysett

Tracy Moroz

Shedding light on brain energy metabolism in traumatic brain injury patients using novel photonic systems and in silico methods.

Supervisors - Dr Ilias Tachtsidis (Medical Physics and Bioengineering) and Prof. Chris Cooper (Biological Sciences, University of Essex)

Recent development in photonics instrumentation have allowed continuous, non-invasive measurements of the distribution of oxygen and blood in the human brain, and of how oxygen is used. UCL's Biomedical Optics Research Laboratory is one of the leading groups in optical instrumentation development and clinical application. A recently developed optical system is currently being used at the National Hospital for Neurology and Neurosurgery to monitor brain injury patients.

My project involves the development of algorithms to translate optical data to brain biophysical quantities, and the construction of a computational model of the underpinning biochemistry and physiology of brain tissue autoregulation. This will contribute to the evolution of a new monitoring tool that integrates the photonic systems with in silico modelling. It will allow testing of different hypotheses on brain energetics and help in interpreting experimental data towards clinical information.



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Tracy Moroz's Research

Francesca Norris

High resolution micro MRI for mouse phenotyping

Supervisors: Dr. Mark Lythgoe (Centre for Advanced Biomedical Imaging) and Prof. Peter Scambler (Institute of Child Health)

There are an increasing number of mutant mouse models, which are employed to explore mechanisms of disease and development, driving the need for effective methods of phenotyping embryos and transgenic adult mice. The aim of my PhD is to explore different ways of optimising and formalising the phenotyping process in order to identify a consistent phenotype in embryos and adult mutant mice with possible cardiac and CNS defects.

This will involve using micro magnetic resonance imaging (µMRI), which is an established method of producing non-invasive, high resolution (25µm), 3D data with high tissue contrast, to investigate different ways of enhancing MR sensitivity ex vivo, in vivo and in utero using different contrast agents and reporter genes, developing new MR sequences, and exploring image processing methods, such as (semi)automated segmentation.




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Francesca Norris's Research

Martin O'Reilly

3D reconstruction and analysis of neural circuits

Supervisors: Lewis Griffin (Department of Computer Science, UCL) and Arnd Roth (Wolfson Institute for Biological Research, UCL)

We are aiming to identify every neuron and synapse in a small volume of brain tissue in order to reconstruct its neural circuitry in 3D. We are looking at the cerebellar cortex, an area of the brain that plays a key role in the control and co-ordination of motor movements. It receives millions of connections carrying information from the motor control area of the brain and the motor centres in the spinal cord. By understanding the circuits formed in the cerebellar cortex we hope to gain a greater understanding of how it co-ordinates motion.

Although we are looking at a small volume of brain, the number of neuronal processes and synapses that exist within it would take years to trace manually. Therefore one of the primary goals of this project is to develop automated tools to dramatically reduce the time it takes to trace the paths and connections of neuronal processes from electron microscopy data. Ultimately the hope is that these tools can be applied in other brain areas to greatly increase the size of neural circuits that can be analysed throughout the brain.

Martin's Homepage: http://www.ucl.ac.uk/~ucbpmor







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Martin O'Reilly's Research

Mae Woods

Modelling Cell Migration

Supervisors: Dr. Roberto Mayor, Dr. Karen Page

I am interested in the migration of neural crest cells and the factors that govern their directional migration. A mathematical model can lead to some counterintuitive results that may not be deduced from qualitative analyses alone. Hence, the current aim of my research is to construct a mathematical model of migration based on the local interactions between cells and analyse the macroscopic (large scale or collective) dynamics of the model. By applying the theory of statistical mechanics to an infinitely large system of interacting particles it is possible to obtain laws describing the macroscopic variables of the system. Although groups of migrating cells are not infinitely large this theory has inspired and led to interaction models describing the migration and movement of a finite group of animals, such as schools of fishes or flocks of birds. We are applying the techniques of modelling collective animal behaviour to identify some key cell interactions and to determine how these interactions collectively regulate directional migration.

Mae's Webpage: http://www.ucl.ac.uk/~ucbpmlw/Site



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Mae Woods

Page last modified on 06 feb 13 16:56