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(2012)ThesisCell immunoisolation systems are fast becoming a favourable approach to cure various challenging diseases and disorders such as type I diabetes. Although the addition of biological molecules to cell immunoisolation devices can significantly enhance their performance by supporting cell viability and function, little is known about their effects on the immunoisolating membrane properties especially its permselectivity. Therefore, this research focused on examining the effect of combining biological molecules with a synthetic polymer on the permeability of hydrogels, with a specific emphasis on encapsulation of insulin producing cells for treatment of diabetes. The research aimed at achieving an optimum balance between a controlled permselectivity and cell survival support. It was hypothesised that covalent incorporation of small amounts of model extracellular matrix (ECM) molecules, heparin and gelatin, would support cell viability without compromising the controlled permselectivity and physico-mechanical properties of the base PVA network. Varying the number of functional groups per PVA backbone successfully controlled the PVA permeability and physico-mechanical properties. A suitable degree of permselectivity was achieved by the highly crosslinked hydrogels. Covalent incorporation of heparin and gelatin at low percentage was successfully achieved without interfering with either their biofunctionalities or the base PVA properties, including its permselectivity. Moreover, the incorporated ECM analogues supported the viability and metabolic activity of pancreatic β-cell lines encapsulated for two weeks. Consequently, biosynthetic hydrogels composed of permselective PVA base material and a small amount of biological molecules show promise as immunoisolating materials for cell-based therapy.
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(2019)ThesisA weave of collagen and elastin fibers supports every tissue in the body, with tissue-, age- and health status-specific spatial and temporal fibre distributions. The newly presented concept of biotextilogy refers to the creation of textiles that emulate nature's own. Microscopy Aided Design and ManufacturE (MADAME) describes an advanced manufacturing method by which spatial distributions of tissue structures such as porosity, structural protein fibers, and permeability characteristics can be engineered and manufactured using biotextilogy alone or in combination with additive manufacturing. Periosteum, a hyperelastic soft tissue sheath covering every bone in the body, exhibits stimuli-responsive or smart properties that would confer great benefit if integrated into medical textiles. These benefits include harnessing movement or displacements to deliver pressure gradients, e.g. to oedematous limbs (actuator function) or changing of its own form when strained by neighboring tissues (sensor function). This thesis also applies biotextilogy and MADAME to test textiles created to mimic the natural patterns of collagen and elastin in periosteum. First the mechanical and strain properties of compression sleeves were characterized. The mechanical testing results from this study showed a lack of gradients in textile samples taken along the length of the sleeve, providing a first step to develop more efficacious compression sleeves. MADAME was then applied, first using microscopy to study elastin and collagen in periosteum, then implementing a recursive approach to better incorporate gradients into textile design using elastic and stiffer fibers mimicking elastin and collagen. Textiles demonstrated spatially tuneable mechanical gradients and strain distributions, validating the concept. Once feasibility had been shown, a set of prototype textiles was constructed using different compositions and combinations of sutures as elastin and collagen analogues. Textiles were tested for biocompatibility by seeding with mammalian cells, and observing cell viability and proliferation over 15 days. Sterilization showed significant effects on material stiffness, though results vary across material and sterilisation procedure. Biotextilogy and MADAME provide a platform for a new class of smart materials and products that exhibit advantageous properties in bending, tension and compression, as well as the capacity to harness forces associated with physiological activity to activate the material’s smart properties.
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(2018)ThesisA patient’s own T cells can be genetically modified and amplified in the laboratory to target antigens expressed on tumour cells through the introduction of chimeric antigen receptor (CAR) genes. Despite considerable advances in the treatment of B cell leukaemia using chimeric antigen receptor T (CART) cells targeting the CD19 antigen, some patients have not responded well, particularly those with solid tumours. Understanding the biology of CART cell effector function may explain treatment failure, and lead to more effective cell therapy products. Population-based assays such as flow cytometry give a snapshot of these complex cellular systems, but do not allow one to study the fate of individual cells over time. Therefore, the aim of this thesis was to apply flow cytometry, time-lapse imaging and singlecell tracking to characterise the dynamics of CART and tumour cell interactions in vitro. The utility of time-lapse imaging and single-cell tracking was demonstrated by quantifying the cytotoxicity of CART cells targeting CD19+ leukaemia cell lines. This thesis also addresses the problem of minimal CART cell effector function against solid tumours by studying the potency of anti-GD2 re-directed Natural Killer (GD2NK) and T cells (GD2T) targeting neuroblastoma spheroids with time-lapse imaging. Flow cytometry studies show that at least 90% of CD19+ leukaemia cells were killed at high effector to target ratios (E:T=10:1), however only 10% killing was achieved at lower ratios (E:T=1:1). Cooperative killing by CART cells was observed by time-lapse imaging without serial killing. In the clinical context, localisation of effector cells through chemotaxis and proliferation at tumour sites may be required for tumour elimination. NK and GD2NK cell penetration of solid neuroblastoma spheroids was superior to T or CART cells. NK but not T cells were able to destroy tumour spheroids. However, coculture of neuroblastoma spheroids with NK and T cells resulted in loss of NK-mediated tumour killing. In conclusion, this thesis provides methodological advances to the study of anti-tumour response generated by innate and CAR-enhanced effector cells against haematological malignancy and solid tumours by application of time-lapse imaging. This thesis also provides insights into the detailed mechanism of effector cell killing by direct observation of the dynamics of effector cell migration, infiltration, conjugate formation and cytotoxicity using single-cell tracking.
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(2018)ThesisAs robotic applications move towards unstructured environments, there is a need for grippers that can manipulate objects securely (preventing slip) and efficiently (applying minimal grip forces). One approach for achieving this involves measuring the coefficient of static friction (COE) at the gripper-object interface. In the absence of torque, the minimum grip force to prevent slip can be estimated from COE and the contact forces . However, torque at the gripper-object interface is generated when the lifting force does not align with the weight vector of the object being lifted. Current robotic gripping systems ignore the need to measure COE, and there is little literature on the grip force required to prevent slip in the presence of a tangential torque (T) at the gripping interface. In this thesis, a grip force control system was developed, using the measurement of COE at the first contact between the gripper and the object, and the continuous measurement of contact forces and torque to approach the minimal grip force required to hold the object stably. The target grip force is determined in real-time during object manipulation. To demonstrate the importance of COE when no torque is present, objects were gripped with the target grip force dependent only on the measured loads and COE. Furthermore, a model was developed in which the minimum grip force preventing slip can be estimated based on COE, load force, and T. This friction model is first validated with respect to the grip force at which slip is predicted to occur, for varying COE, load force, and T. Objects were then gripped (varying load, COE, and T) with the target grip force calculated by the friction model. The results demonstrate that COE-dependent grip force control is superior to gripping without knowledge of COE, irrespective of T at the contact interface, with respect to the system’s ability to prevent slip and simultaneously minimise the grip force applied. The minimum grip force estimation model and grip force controller developed and validated in this thesis have highlighted the value of measuring COE and the necessity of countering torque to ensure a secure and efficient grip.
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(2019)ThesisRecent advancements in cardiac computational modelling allow for ready simulation of bileaflet mitral valve (MV) motion in a contracting left ventricle (LV), demonstrating the capability of computational modelling to simulate the MV diseased state and treatment strategies. Furthermore, recent advancements in image-based modelling can be used for pre-procedural planning of mitral prosthetic valve placement and analysis of intraventricular blood flow. This thesis aims to develop a set of computational models that can simulate normal MV function, MV disorders and treatments to help in the understanding of MV movement and its interaction with blood. In addition, a moving-wall LV computational framework was developed to provide pre-surgical guidance for determining optimal orientation of mitral prostheses. In this thesis, the structural boundaries of a 2D model of the left heart were represented as a spring-like elastic structure. A 3D LV model was subsequently developed, consisting of ideal geometric-shaped MV leaflets and the LV wall. An experimentally-based hyperelastic material formulation was used to model mechanical behaviour of the MV leaflets. For both 2D and 3D ideal models, the MV chordae tendineae and papillary muscle were incorporated. Finally, for the image-based models based on wide-volume full cycle cardiovascular CT images prior to transcatheter MV implantation (TMVI) were developed and analysed (n = 6 patients). Patient-specific computational fluid dynamics simulations of TMVI at various implant insertion angles were performed (n = 30). The 2D and 3D ideal models were successful in simulating the normal and prolapsed states of the MV. Additionally, both models were able to simulate blood movement after the MV prosthetic with and without left ventricular outflow tract (LVOT) flow obstruction. In the image-based models, computed pressure gradients following artificial valve placement compared well with clinical measurements and accurately predicted clinical LVOT obstruction. The simulations demonstrated that LVOT obstruction can be mitigated by adjusting the valve insertion angle, with the extent of residual obstruction contingent on the aorto-mitral-annular angle and LV anatomy.