The human fungal pathogens Cryptococcus neoformans and C. gattii cause life-threatening infections of the central nervous system. One of the major characteristics of cryptococcal disease is the ability of the pathogen to parasitise upon phagocytic effector cells. Cryptococcus can survive and proliferate within macrophages, and is also capable of escaping into the intracellular environment via a non-lytic mechanism (‘expulsion’) and can be transferred directly from one cell to another (lateral transfer). In the first part of this thesis, I demonstrate that enhanced Th2, but not Th1, cytokine levels lead to increased intracellular cryptococcal proliferation but lower levels of cryptococcal expulsion. In the second part, I describe the generation and characterisation of GFP-expressing derivates of two widely used cryptococcal strains: C. neoformans serotype A type strain H99 and C. gattii serotype B type strain R265. Furthermore, I have developed a method to effectively and rapidly investigate macrophage parasitism by flow cytometry that preserves the accuracy of current approaches but offers a four-fold improvement in speed. The final part dissects the regulation and induction of mitochondrial tubularisation in hypervirulent C. gattii strains and describes the first steps towards a comparative mitochondrial genome sequencing approach to identify the underlying molecular mechanisms.

Phosphoinositides are lipid signals that control cellular processes and are particularly closely associated with the control of membrane trafficking. PtdIns(3,5) \(\char{cmmi10}{0x50}\)\(_2\) is the most recently identified phosphoinositide and was previously recognised as controlling events in the late endocytic system between the late endosome and the vacuole/lysosome. Primarily associated with retrograde trafficking from the vacuole/lysosome to the late endosome/MVB, PtdIns(3,5) \(\char{cmmi10}{0x50}\)\(_2\) is generated by the kinase Fab1p (PIKfyve in animals). In mammalian cells, PtdIns(3,5) \(\char{cmmi10}{0x50}\)\(_2\) has also been implicated in control of ill-defined trafficking pathways close to the Golgi; for example, the recycling of mannose-6-phosphate receptor (M6R) back to the Golgi and also the trafficking of some types of ion and nutrient channels from the Golgi to the cell surface. This thesis describes attempts to study putative PtdIns(3,5) \(\char{cmmi10}{0x50}\)\(_2\) dependent trafficking in the early endocytic system of \(\char{cmmi10}{0x53}\). \(\char{cmmi10}{0x63}\)\(\char{cmmi10}{0x65}\)\(\char{cmmi10}{0x72}\)\(\char{cmmi10}{0x65}\)\(\char{cmmi10}{0x76}\)\(\char{cmmi10}{0x69}\)\(\char{cmmi10}{0x73}\)\(\char{cmmi10}{0x69}\)\(\char{cmmi10}{0x61}\)\(\char{cmmi10}{0x65}\) using two model proteins; the recycling of Vps10p from late endosome to Golgi and of Chs3p from recycling endosome to Golgi.

The introduction of electron capture dissociation mass spectrometry in 1998 has provided a unique technique for the analysis of peptides and proteins, especially for the identification and localisation of posttranslational modifications. Despite many successes debate continues on the radical-based mechanism of ECD. This thesis explores ECD behaviour in a wide range of PTMs with the intention of furthering our knowledge of the radical-based mechanism. Studies were undertaken on the effect of 3-nitrotyrosine, which is an electron withdrawing group, on ECD. The presence of nitration dramatically decreases peptide backbone sequence coverage but results in the presence of abundant small neutral losses. The key finding is the insight provided into the hierarchy of the various proposed ECD mechanisms. ECD of cysteine bound modifications is shown to result in the fragmentation of the sulfur-modification bond and backbone sequence coverage is highly diminished when analysing S-nitrosopeptides. ECD behaviour of hydrogen-deficient radical peptides is highly dependent on gas-phase peptide structure, with electron capture typically resulting in an increase in charge-reduced precursor intensity. Comparisons of the intermolecular phospho-guanidinium bond strengths between phospho-serine, -threonine and -tyrosine were undertaken. ECD of these complexes results in the retention of the noncovalent bond allowing backbone sequence coverage.

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In this thesis, the design, fabrication and characterisation of a bio-inspired microelectromechanical systems (MEMS) based tactile sensor array is presented. A vast amount of research has been carried out in the area of tactile sensing and various transduction methods have been explored. However, currently no device exists with a performance comparable to that of the biological tactile sensors of the human fingertip in terms of robustness, sensitivity, spatial resolution and dynamic performance. The sensors developed in this work employ the principles of electrical capacitance and are fabricated from commercially available siliconon- oxide wafers using simple process steps. Each sensor is formed from two plates of highly conductive silicon separated by an air-gap formed from sacrificial etching of the oxide layer. Deflection of the 2 \(\mu\)m thick upper plate of the sensor as a result of applied mechanical stimulus, causes a change in capacitance which is the output of the sensor. Within the array, the individual sensors are spaced 150 \(\mu\)m apart (centre-centre pitch of 570 \(\mu\)m) and therefore offer the potential for high spatial resolution. To protect the sensor array from mechanical shock and provide skin like compliance, the use of suitable packaging materials was explored. The use of poly dimethyl siloxane (PDMS) as a suitable skin-like material was demonstrated. Modification of the surface topography of the packaging layer to include ’fingerprint’ like features was explored and its benefits highlighted. Sensor characterisation experiments revealed that the sensing device was sufficiently sensitive to allow the discrimination of different textures (with feature spacing down to 0.2 mm) through tests conducted using gratings varying in spatial periodicity and fabrics. Based on the results, the sensors can be used as an analogue of the slowly adapting tactile receptors (Merkel disks) for robotic finger applications.

Perhexiline is an anti-anginal drug that is thought to shift myocardial metabolism from \(\beta\)-oxidation of fatty acids to glucose utilisation. An associated improvement in energy efficiency may be beneficial in ischaemia-reperfusion as an adjunct to established techniques for myocardial protection during cardiac surgery. In this thesis, I conduct a prospective double-blind randomised placebo-controlled trial of oral perhexiline in patients undergoing coronary artery surgery, obtaining samples of serum, right atrium and left ventricle. I measure the concentration of perhexiline using high performance liquid chromatography and find that although highly concentrated in the heart, it may not have reached steady-state in the ventricular myocardium. I perform enzymatic colourimetry and ultra-high resolution mass spectrometry to detect changes in carbohydrate and lipid metabolism; however, the myocardial metabolic profiles of patients on perhexiline are indistinguishable from controls. On analysing the results of the clinical trial, I find no improvement in the primary endpoint, the incidence of a low cardiac output episode, or any secondary outcomes. I conclude that preoperative oral perhexiline does not improve clinical markers of myocardial protection and despite significant accumulation in the myocardium, it has no significant effect on the measurable metabolic profile of the heart at the time of surgery.

Ears are a new biometric with major advantage in that they appear to maintain their structure with increasing age. Current approaches have exploited 2D and 3D images of the ear in human identification. Contending that the ear is mainly a planar shape we use 2D images, which are consistent with deployment in surveillance and other planar-image scenarios. So far ear biometric approaches have mostly used general properties and overall appearance of ear images in recognition, while the structure of the ear has not been discussed. In this thesis, we propose a new model-based approach to ear biometrics. Our model is a part-wise description of the ear structure. By embryological evidence of ear development, we shall show that the ear is indeed a composite structure of individual components. Our model parts are derived by a stochastic clustering method on a set of scale invariant features on a training set. We shall review different accounts of ear formation and consider some research into congenital ear anomalies which discuss apportioning various components to the ear's complex structure. We demonstrate that our model description is in accordance with these accounts. We extend our model description, by proposing a new wavelet-based analysis with a specific aim of capturing information in the ear's outer structures. We shall show that this section of the ear is not sufficiently explored by the model, while given that it exhibits large variations in shape, intuitively, it is significant to the recognition process. In this new analysis, log-Gabor filters exploit the frequency content of the ear's outer structures. In recognition, ears are automatically enrolled via our new enrolment algorithm, which is based on the elliptical shape of ears in head profile images. These samples are then recognized via the parts selected by the model. The incorporation of the wavelet-based analysis of the outer ear structures forms an extended or hybrid method. The performance is evaluated on test sets selected from the XM2VTS database. By results, bothin modelling and recognition, our new model-based approach does indeed appear to be a promising new approach to ear biometrics. In this, the recognition performance has improved notably by the incorporation of our new wavelet-based analysis. The main obstacle hindering the deployment of ear biometrics is the potential occlusion by hair. A model-based approach has a further attraction, since it has an advantage in handling noise and occlusion. Also, by localization, a wavelet can offer performance advantages when handling occluded data. A robust matching technique is also added to restrict the influence of corrupted wavelet projections. Furthermore, our automatic enrolment is tolerant of occlusion in ear samples. We shall present a thorough evaluation of performance in occlusion, using PCA and a robust PCA for comparison purposes. Our hybrid method obtains promising results recognizing occluded ears. Our results have confirmed the validity of this approach both in modelling and recognition. Our new hybrid method does indeed appear to be a promising new approach to ear biometrics, by guiding a model-based analysis via anatomical knowledge.

Using biological traits, such as fingerprints, iris patterns and voice print, in identification and authentication has gained increasing attention due to the demand for a more secure environment. The potential of human walking as a biometric has only attracted interest in the computer vision community since the last decade. Nevertheless, the potential of human running gait as a biometric remains largely unexplored. Here, we propose an approach for an automated non-invasive/markerless person identification system by not only the walking, but also the running gait to explore the potential of these two biomechanically distinct gaits. Two motion models both invariant to walking and running, have been developed based on the concept of harmonic motion. The first is a bilateral symmetric model made up of an upper and a lower pendulum, representing the thigh and the lower leg, joined at the knee. The upper pendulum is simple harmonic motion whilst the lower pendulum uses an empirical model requiring parameter selection for the different gait mode and lacks analytical attributes. The second model has a forced coupled oscillator to describe the knee rotation as legs are considered to be imperfect pendula with energy loss. The rhythm and pattern of gaits are automatically extracted by a temporal evidence gathering technique with the motion models as the underlying temporal templates. The spatio-temporal characteristics of the gait patterns are described by a Fourier representation, which are in turn used to create unique gait signatures for the purpose of identification. Performance analysis demonstrates the potential of gait as a biometric, with running being more potent. This technique not only performs well in discriminating individuals, but also appears capable of distinguishing the gender and gait mode. Moreover, analysis shows that the knee rotation contributes significantly to discrimination capability. Based on the hypothesis that human walking and running gaits are intimately related by the musculo-skeletal structure and that the walking pattern is the phase-modulated version of running (or vice versa), a unique mapping/transform between individuals’ walking and running gait is developed, making the signature invariant to gait mode. Furthermore, this mapping can be used alone as a compressed signature or to buttress the original signature to further improve the recognition capability. Then, a generic relationship between walking and running has been investigated via a neural network. Due to the current size of the experimental dataset, the structure of the two signature spaces could not be drawn, at least not by this approach. However, results do suggest its possible existence. The effect of different camera views is an important application issue. The gait pattern perceived by machine vision at different viewpoints has been investigated. The frequency description of the gait pattern is linearly dependent on the camera sagittal view angle. The changes of both the magnitude and the phase component are symmetric about the fronto-parallel view. This linearity offers a convenient way to map the angular motion obtained from various camera sagittal views to the true motion, for the convenience of gait analysis. More importantly, this linearity can be exploited to develop view invariant gait signatures. The new and interesting findings of this work not only benefit biometrics research, but may also draw attention from other communities such as biomechanics and graphics applications.

In obesity, lipids stored in muscle as lipid droplets (LDs) lead to accumulation of fatty acid (FA) metabolites and insulin resistance. This research involves development of immunofluorescence microscopy methods to generate novel information on the subcellular content and distribution of key enzymes that play a role in the underlying mechanisms. Chapters 3 and 4 describe visualisation of two lipid synthesising enzymes. Both are more abundant in type I muscle fibres. Chapter 5 reveals no differences between these enzymes in non obese and obese elderly women. Chapter 6 reveals that a key lipolytic enzyme (ATGL) has a higher content in type I fibres, but its activator does not. Chapter 7 describes visualisation of SNAP23 and reveals a high content at the plasma membrane and mitochondria and low content in LDs. Chapter 8 fails to observe a difference between obese and non obese elderly women in plasma membrane SNAP23, and therefore fails to confirm the hypothesis that LDs hijack SNAP23. However, obese women have less SNAP23 in mitochondria and this may limit FA oxidation. In conclusion this thesis describes several novel mechanisms by which obesity leads to accumulation of FA metabolites and insulin resistance. The developed methods will be a valuable novel tool for future diabetes research.