A biological-inspired support frame for an artificial cornea

Bilateral corneal blindness represents a quarter of the total blind, world-wide. The artificial cornea in assorted forms, was developed to replace opaque non-functional corneas and to return sight in otherwise hopeless cases that were not amenable to corneal grafts; believed to be 2% of corneal blind. Despite technological advances in materials design and tissue engineering no artificial cornea has provided absolute, long-term success. Formidable problems exist, due to a combination of unpredictable wound healing and unmanageable pathology. To have a solid guarantee of reliable success an artificial cornea must possess three attributes: an optical window to replace the opaque cornea; a strong, long term union to surrounding ocular tissue; and the ability to induce desired host responses. A unique artificial cornea possesses all three functional attributes- the Osteo-odonto-keratoprosthesis (OOKP). The OOKP has a high success rate and can survive for up to twenty years, but it is complicated both in structure and in surgical procedure; it is expensive and not universally available. The aim of this project was to develop a synthetic substitute for the OOKP, based upon key features of the tooth and bone structure. In doing so, surgical complexity and biological complications would be reduced. Analysis of the biological effectiveness of the OOKP showed that the structure of bone was the most crucial component for implant retention. An experimental semi-rigid hydroxyapatite framework was fabricated with a complex bone-like architecture, which could be fused to the optical window. The first method for making such a framework, was pressing and sintering of hydroxyapatite powders; however, it was not possible to fabricate a void architecture with the correct sizes and uniformity of pores. Ceramers were synthesised using alternative pore forming methods, providing for improved mechanical properties and stronger attachment to the plastic optical window. Naturally occurring skeletal structures closely match the structural features of all forms of natural bone. Synthetic casts were fabricated using the replamineform process, of desirable natural artifacts, such as coral and sponges. The final method of construction by-passed ceramic fabrication in favour of pre-formed coral derivatives and focused on methods for polymer infiltration, adhesion and fabrication. Prototypes were constructed and evaluated; a fully penetrative synthetic OOKP analogue was fabricated according to the dimensions of the OOKP. Fabrication of the cornea shaped OOKP synthetic analogue was also attempted.

A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis

A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

The formulation of artificial reference standards for use within the ELISPOT assay

Whether to assess the functionality of equipment or as a determinate for the accuracy of assays, reference standards are essential for the purposes of standardisation and validation. The ELISPOT assay, developed over thirty years ago, has emerged as a leading immunological assay in the development of novel vaccines for the assessment of efficacy. However, with its widespread use, there is a growing demand for a greater level of standardisation across different laboratories. One of the major difficulties in achieving this goal has been the lack of definitive reference standards. This is partly due to the ex vivo nature of the assay, which relies on cells being placed directly into the wells. Thus, the aim of this thesis was to produce an artificial reference standard using liposomes, for use within the assay. Liposomes are spherical bilayer vesicles with an enclosed aqueous compartment and therefore are models for biological membranes. Initial work examined pre-design considerations in order to produce an optimal formulation that would closely mimic the action of the cells ordinarily placed on the assay. Recognition of the structural differences between liposomes and cells led to the formulation of liposomes with increased density. This was achieved by using a synthesised cholesterol analogue. By incorporating this cholesterol analogue in liposomes, increased sedimentation rates were observed within the first few hours. The optimal liposome formulation from these studies was composed of 2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), cholesterol (Chol) and brominated cholesterol (Brchol) at a 16:4:12 µMol ratio, based on a significantly higher (p<0.01) sedimentation (as determined by a percentage transmission of 59 ± 5.9 % compared to the control formulation at 29 ± 12 % after four hours). By considering a range of liposome formulations ‘proof of principle’ for using liposomes as ELISPOT reference standards was shown; recombinant IFN? cytokine was successfully entrapped within vesicles of different lipid compositions, which were able to promote spot formation within the ELISPOT assay. Using optimised liposome formulations composed of phosphatidylcholine with or without cholesterol (16 µMol total lipid) further development was undertaken to produce an optimised, scalable protocol for the production of liposomes as reference standards. A linear increase in spot number by the manipulation of cytokine concentration and/or lipid concentrations was not possible, potentially due to the saturation that occurred within the base of wells. Investigations into storage of the formulations demonstrated the feasibility of freezing and lyophilisation with disaccharide cryoprotectants, but also highlighted the need for further protocol optimisation to achieve a robust reference standard upon storage. Finally, the transfer of small-scale production to a medium lab-scale batch (40 mL) demonstrated this was feasible within the laboratory using the optimised protocol.

Characteristics of motor resonance predict the pattern of flash-lag effects for biological motion

Background - When a moving stimulus and a briefly flashed static stimulus are physically aligned in space the static stimulus is perceived as lagging behind the moving stimulus. This vastly replicated phenomenon is known as the Flash-Lag Effect (FLE). For the first time we employed biological motion as the moving stimulus, which is important for two reasons. Firstly, biological motion is processed by visual as well as somatosensory brain areas, which makes it a prime candidate for elucidating the interplay between the two systems with respect to the FLE. Secondly, discussions about the mechanisms of the FLE tend to recur to evolutionary arguments, while most studies employ highly artificial stimuli with constant velocities. Methodology/Principal Finding - Since biological motion is ecologically valid it follows complex patterns with changing velocity. We therefore compared biological to symbolic motion with the same acceleration profile. Our results with 16 observers revealed a qualitatively different pattern for biological compared to symbolic motion and this pattern was predicted by the characteristics of motor resonance: The amount of anticipatory processing of perceived actions based on the induced perspective and agency modulated the FLE. Conclusions/Significance - Our study provides first evidence for an FLE with non-linear motion in general and with biological motion in particular. Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. Our findings are compatible with visual prediction (Nijhawan, 2008) which assumes that extrapolated motion representations within the visual system generate the FLE. These representations are modulated by sudden visual input (e.g. offset signals) or by input from other systems (e.g. sensorimotor) that can boost or attenuate overshooting representations in accordance with biased neural competition (Desimone & Duncan, 1995).