Measuring chemical concentration is vital for understanding normal and disease physiology involving metabolism and signalling, but monitoring chemical concentrations in living systems poses a unique challenge because of biological heterogeneity. The purpose of this work is to develop a system able to monitor chemical concentrations in primary cultured cells, and apply it to the detection of oxygen, a nutritional status marker, and nitric oxide which is a signalling molecule. Both of these electroactive species are involved in angiogenesis which is the growth of new blood vessels, and a hallmark of cancer. The approach used in this study is to grow porcine endothelial cells onto bronectin-coated gold microelectrode arrays with diameter 25 μm and perform electrochemical measurement on them. An experimental protocol is developed for measurements of dissolved oxygen and nitric oxide around cells in their normal cell-culture environment. It includes developing instrumentation like a heating platform and silver reference microelectrode; data processing for automation and normalisation; and optimising voltammetry techniques. Culture medium is found to a ect electrochemical measurements by changing double layer capacitance, reaction rate constant and di usion. The measurement system is used to detect oxygen reduction around cells, and this is used to estimate their oxygen consumption rate. Nitric oxide produced by cells is also measured, and this is used to identify an angiogenic pathway leading to nitric oxide production by endothelial cells. Variability in cell measurements is shown to originate from the biological system rather than from sensor design. A novel electroanalytical technique for determining parameters of reversible redox systems is developed by experimentally testing an analytical solution for the current response to a large-amplitude sinusoidal voltage input. The technique is used to nd estimates for double layer capacitance, half wave potential and di usion coe cients for both potassium ferrocyanide and ruthenium hexaamine.

Hepatocellular carcinoma (HCC), or the cancer of the liver, is of great concern due to its poor patient outcome despite the various treatments available. It is imperative, therefore, that a novel, viable treatment method is developed such that patient survival rates may be improved from current statistics of less than 50%. The role of miRNAs in the regulation of gene expression and cellular development makes it an important player in cancer development process, as it is found that the aberrant expression of miRNAs is a typical feature of cancer cells or even pre-disposed cancer cells. MiR-181a has been shown to be an important miRNA involved in HCC. In this study, we investigated the potential effects of miR-181a in HepG2 cells and the mechanisms in which it works in controlling cell fate. As chemotherapy is widely used in liver cancer treatment, we also study the use of miR-181a along with chemotherapy (i.e. Cisplatin). Using iTRAQ-coupled 2D LC-MS/MS analysis, we report here the study of protein profile of HepG2 cells transfected with miR-181a and its inhibitor respectively. Three main types of cellular proteins including metabolic enzymes, protein binding and stress proteins displayed changes. The changes in the level of proteins (14-3-3σ, Hsp-90β and NPM1) involved in important cancer processes like cell growth were further supported by a Western blot analysis. MiR-181a was subsequently found to significantly increase HepG2 cell viability while inhibiting it displayed the opposite effect. Inhibiting miR-181a also sensitized HepG2 cells to cisplatin treatment and retards cell cycle progression by decreasing the proportion of cells in S and G2/M phases. We next investigated the reasons behind these observations at a molecular level. As miRNAs are known to regulate genes by binding to and targeting mRNAs, we first used bioinformatics to screen out potential cellular targets. Two important genes identified, cyclin-dependent kinase inhibitor 1B (CDKN1β) and transcriptional factor E2F7 (E2F7), which are involved in cell cycle and cell proliferation, were chosen to be further experimentally studied. In vitro validation via surface plasmon resonance (SPR) technique showed a positive binding between miR-181a and the seed regions of the 3'UTRs of the two putative mRNA targets, with dissociation constants being 272.5 ± 0.008 nM and 1.186 ± 0.009 uM for CDKN1β and E2F7 respectively. In vivo luciferase assay studies further validated the miR-181a:mRNA bindings, in both cases displaying significant decrease in luciferase activity when HepG2 cells were co-transfected with the 3'UTR-containing reporter plasmids and miR-181a. A positive binding, however, may not necessarily lead to a lowered expression of protein levels. A Western blot study on the expression levels of the two proteins, however, showed a decrease in the levels of CDKN1β and E2F7. Lastly, to gain an insight into the overall effects miR-181a has in HepG2 cells, a microarray analysis was performed. Cellular pathways important in cancer were studied and results show that miR-181a significantly activated the MAPK/JNK pathway by increasing the expression levels or activity of transcription factor activator protein 1 (AP-1). Inhibiting miR-181a, on the other hand, abolished this observation and significantly decreased expression levels or activity of hypoxia-inducible factors (HIF) and also significantly upregulated the expression levels or activity of SMAD2/3/4 proteins, possibly inducing a cancer-suppressing effect. Overall, miR-181a appears to activate mainly cancer-promoting pathways, and may act as an oncogene in HepG2 cells. Inhibiting it, on the other hand, activates mainly the tumour-suppressing pathways, making it a possible option for therapy. A separate microarray analysis on gene expression showed that one way in which miR-181a could have activated the SMAD, NFκB and MAPK pathways is via the significant increase in gene expression of bone morphogenetic protein receptor type II (BMPR2), a cellular receptor that mediates the signal transduction of these pathways. Our findings provide a new platform of identifying miRNA targets, in the process offering molecular evidence on the mechanism of action of miR-181a, including the beneficial effects of inhibiting miR-181a in HCC therapy.

Fiber optic chemical sensors (FOCS) have made tremendous progress since developments began in the 1960s with continuous reports of new configurations, materials and applications even today. Techniques like interferometry and plasmonic resonance are set to form the next generation of FOCS, representing a deviation from conventional luminescence based techniques. The thesis presents an optic fiber sensor platform for localized surface plasmon resonance (LSPR) by using a speciality photonic crystal fiber (PCF) to excite LSPR via cladding modes. The sensor offers facile fabrication and achieves high refractive index sensitivity of -731 % transmittance/RIU with limit of detection (LOD) 1.76 x 10-5 refractive index unit (RIU). Responsive polymers, exhibiting physio-chemical changes when exposed to specific stimuli are investigated for feasibility in FOCS based on LSPR and interferometry. A pH sensor is proposed by formation of a gold nanoparticles (AuNPs) embedded polyelectrolyte multilayer (PEM) consisting of Chitosan and poly(styrene sulfonate) (PSS) onto the forementioned sensor. The sensor exhibits pH responsiveness between physiological range of pH 6.5 to 8 and its behavior can be modeled by the Henderson-Hasselbach equation. The biocompatibility of the materials enables in-vivo application of the sensor. Interferometry FOCS using hydrogel as sensing material are investigated. Mach Zehnder interferometers (MZI) can be constructed from PCF. A proposed double- pass MZI shows higher Q factor and higher resolution than a single-pass MZI. By coating a thin poly(HEMA-co-DMAEM) hydrogel film, the MZI pH sensor shows a linear pH response with pH 6.75 to 8.25 (R2 = 0.986) with LOD pH 0.004. The sensor is successfully applied to the monitoring of cell culture media. A generalized approach in fabricating hydrogel based interferometric sensors is demonstrated through use of poly(vinyl alcohol) (PVA)-co- poly(acrylic acid) (PAA) hydrogel. The PVA/PAA offers tremendous ease in obtaining thin films on optical fiber via simple dip coating without need for additional cross linkers and polymerisation initiators. The carboxyl groups on PAA offer efficient coupling to a variety of aminated receptors using carbodiimide coupling to realise a myriad of sensing possibilities. The biocompatibility of both PVA and PAA also makes the proposed sensing film suitable for in-vivo applications. The sensor is demonstrated for sensing of small chemical species like Ni2+. It was found that sensitivity of the PVA/PAA is affected by the PVA/PAA ratio and duration of heat induced esterification which controls the degree of cross linking and the maximum amount of receptors that can be immobilised. The optimal PVA/PAA hydrogel is fabrication from a 12:6 wt % ratio and cross linked at 130 oC for 30 min. By modifying the PVA/PAA hydrogel with hydroxyquinoline, the sensor is able to detect Ni2+ with good sensitivity 0.214 nm/μM and LOD 1nM adequate for continuous monitoring of drinking water.

This PhD thesis explores, through the use of a mechanobiological simulation of prenatal joint morphogenesis, the hypotheses on how fetal movements, shapes and position impact on the shape of the developing joint. A novel mechanoregulation algorithm specific for cartilage growth was developed and, for the first time, a 3D mechanobiological simulation of joint morphogenesis in which the effects of a range of movements and different initial joint shapes was proposed. Both pre- and post-cavitational phases of joint development were simulated and the effect of rigid paralysis on joint shape was also explored. This study concluded that the starting joint configuration and applied movement are fundamental for the development of specific and anatomically recognisable joint shapes. Moreover, for the first time, a mechanobiological simulation of prenatal hip joint morphogenesis was used to investigated the effects of reduced, or asymmetric, movement at various stages of fetal hip joint development. This study concluded that normal fetal movements are important for the emergence of a physiological hip joint shape and that movements during development tend to minimise the natural trend of decreasing stability. Results showed that reduced movements at an early stage of development lead to decreased sphericity and acetabular coverage of the femoral head, increasing the risk of subluxation or dislocation of the hip. It also shows that, in the case of mal-positioning or joint laxity in utero, movements may actually lead to an abnormal hip joint shape with characteristics of developmental dysplasia of the hip (DDH). This PhD thesis has advanced the basic understanding of prenatal joint shape development and the implication that different mechanical environments within the joint region, might have on developmental skeletal diseases such as DDH.

Under the increasing pressure of issues like reducing the time to market, managing lower production costs, and improving the flexibility of operation, batch process industries thrive towards the production of high value added commodity, i.e. specialty chemicals, pharmaceuticals, agricultural, and biotechnology enabled products. For better design, consistent operation and improved control of batch chemical processes one cannot ignore the sensing and computational blessings provided by modern sensors, computers, algorithms, and software. In addition, there is a growing demand for modelling and control tools based on process operating data. This study is focused on developing process operation data-based iterative learning control (ILC) strategies for batch processes, more specifically for batch crystallisation systems. In order to proceed, the research took a step backward to explore the existing control strategies, fundamentals, mechanisms, and various process analytical technology (PAT) tools used in batch crystallisation control. From the basics of the background study, an operating data-driven ILC approach was developed to improve the product quality from batch-to-batch. The concept of ILC is to exploit the repetitive nature of batch processes to automate recipe updating using process knowledge obtained from previous runs. The methodology stated here was based on the linear time varying (LTV) perturbation model in an ILC framework to provide a convergent batch-to-batch improvement of the process performance indicator. In an attempt to create uniqueness in the research, a novel hierarchical ILC (HILC) scheme was proposed for the systematic design of the supersaturation control (SSC) of a seeded batch cooling crystalliser. This model free control approach is implemented in a hierarchical structure by assigning data-driven supersaturation controller on the upper level and a simple temperature controller in the lower level. In order to familiarise with other data based control of crystallisation processes, the study rehearsed the existing direct nucleation control (DNC) approach. However, this part was more committed to perform a detailed strategic investigation of different possible structures of DNC and to compare the results with that of a first principle model based optimisation for the very first time. The DNC results in fact outperformed the model based optimisation approach and established an ultimate guideline to select the preferable DNC structure. Batch chemical processes are distributed as well as nonlinear in nature which need to be operated over a wide range of operating conditions and often near the boundary of the admissible region. As the linear lumped model predictive controllers (MPCs) often subject to severe performance limitations, there is a growing demand of simple data driven nonlinear control strategy to control batch crystallisers that will consider the spatio-temporal aspects. In this study, an operating data-driven polynomial chaos expansion (PCE) based nonlinear surrogate modelling and optimisation strategy was presented for batch crystallisation processes. Model validation and optimisation results confirmed this approach as a promise to nonlinear control. The evaluations of the proposed data based methodologies were carried out by simulation case studies, laboratory experiments and industrial pilot plant experiments. For all the simulation case studies a detailed mathematical models covering reaction kinetics and heat mass balances were developed for a batch cooling crystallisation system of Paracetamol in water. Based on these models, rigorous simulation programs were developed in MATLAB??, which was then treated as the real batch cooling crystallisation system. The laboratory experimental works were carried out using a lab scale system of Paracetamol and iso-Propyl alcohol (IPA). All the experimental works including the qualitative and quantitative monitoring of the crystallisation experiments and products demonstrated an inclusive application of various in situ process analytical technology (PAT) tools, such as focused beam reflectance measurement (FBRM), UV/Vis spectroscopy and particle vision measurement (PVM) as well. The industrial pilot scale study was carried out in GlaxoSmithKline Bangladesh Limited, Bangladesh, and the system of experiments was Paracetamol and other powdered excipients used to make paracetamol tablets. The methodologies presented in this thesis provide a comprehensive framework for data-based dynamic optimisation and control of crystallisation processes. All the simulation and experimental evaluations of the proposed approaches emphasised the potential of the data-driven techniques to provide considerable advances in the current state-of-the-art in crystallisation control.

Public controversy over genetically modified (GM) foods illustrates the increasing complexity of the governance of technological innovation. In the light of public displays of ambivalence towards biotechnology, corporations are paying greater attention to societal concerns over the innovation of new technologies. This thesis asks how those corporations involved in the development and commercialisation of GM foods have understood and responded to recent public controversy over biotechnology in Europe and North America. Using approaches drawn from geography and science and technology studies, this thesis is concerned with concepts of citizenship and also with corporate identities in the context of technological controversy. This thesis focuses particularly on the ways that corporations have understood the emergence of citizen-like demands to participate in the governance of corporate innovation. The research for this thesis adopts an ethnographic approach to studying corporate engagements in public controversy. It uses the analysis of corporate texts, interviews and participation in meetings at which corporate presentations were made about GM foods. The empirical material for this thesis refers to three corporations: DuPont, Monsanto, Unilever and two agricultural biotechnology public relations groups: the Council for Biotechnology Information in the USA, and the Agricultural Biotechnology Council in the UK. This thesis argues that corporations have innovated new institutional forms of engagement with the public over biotechnology. These engagements have configured the 'socially responsible corporation* and the 'consumer-citizen' as actors in more democratic forms of corporate innovation. This thesis concludes that these new forms of governance are partial, fragile and contested, but that they offer potential avenues for further public debate about the governance of corporate innovation.

Transketolase catalyses asymmetric carbon-carbon bond formation and produces 1,3-dihydroxyketones, a functionality that is found in a vast number of natural and synthetic compounds. The wild-type transketolase enzymes from several species can accept a wide range of aldehydes, but industrially exploitable levels of activity tend to be limited to natural substrates and small aliphatic aldehydes. Several single mutants of the transketolase from E. coli were found to have enhanced activity towards non-phosphorylated substrates, non-hydroxylated aldehydes, and cyclic aldehydes. However, aromatic aldehydes still suffer from poor activities and yields while the key bottlenecks have not been identified. The strategy for creating new libraries from combining single mutations can have significant impact not only on the activity but also the stability of the enzyme due to the synergy between residues. On the other hand, the combination of two sites identified within a co-evolved network has created mutants with high towards propionaldehyde and decent stability. Kinetic studies of a small transkeloase library with 3-formylbenzoic acid (3-FBA) and 4-formylbenzoic acid (4-FBA) suggested that the affinity between the enzyme and the aromatic aldehyde, as well as their proximal orientations, was the key factor governing the reaction rate. This was also supported by computational modelling of substrate binding. Site-saturation mutagenesis at S385 and R358 was performed to further improve the activity of transketolase for 3-FBA, 4-FBA and also 3-hydroxybenzaldehyde (3-HBA). The new mutants were then assessed alongside transaminase for the ability to synthesise novel aromatic amino alcohols, which would provide building blocks for chloramphenicol and its derivatives. However, none of the available transaminases appeared to accept either of the compounds. The competitive reaction between 4-FBA and 4-DOPBA, the dihydroxy ketone product of 4-FBA, in an amination reaction suggested that 4-DOPBA was unable to access into the active site of CV2025 transaminase.

Human embryonic stem cells (hESCs) have the potential to provide a limitless supply of somatic cells that can find application in regenerative medicine and drug discovery. Having a scalable and cost-effective manufacturing process for the expansion and maintenance of hESCs is essential to achieving this potential. As hESC culture is currently a largely manual process, major challenges in the methods used concern variability and scalability. In this case bioprocess automation can be of benefit to reduce operator-dependent variation, therefore improving cell yield and quality, and enabling scaled-out manufacture. Use of automation will also help define a robust current Good Manufacturing Practice (cGMP) process suitable for production of cells for clinical application. To date, only certain aspects of embryonic stem cell culture have been successfully automated. This thesis describes the first use of an automated microwell platform for the completely ‘hands-free’ expansion and differentiation of hESCs. Two established hESC lines (Shef-3 and Shef-6) were taken and adapted to enzymatic passaging with TrypLE Express while maintaining their pluripotency. Culture conditions of the two cell lines were optimised using a statistical Design of Experiments (DoE) approach. This ensured that the correct feeder and hESC inoculation cell densities (ICDs) were used in microwell cultures to yield confluent, high quality hESCs. The initial automated expansion process was shown to result in a low yield of cells. The automated process was subsequently optimised primarily by making changes to the cell dissociation steps. Using the optimised automated expansion protocol, culture-adapted Shef-3 and Shef-6 hESCs were successfully expanded on the automated microwell platform over multiple passages. hESC yield was stable at ~ 2×105 cellscm-2 and was shown to be more consistent compared to the manual process. A minimum cell viability of 98.3% 0.7% was maintained throughout automated expansion. Cells were shown to be pluripotent after automated processing and maintained their ability to form EBs and differentiate into cells of all three germ layers. The automated microwell platform was also used to screen small molecules Dorsomorphin and SB431542 for their effect on neuronal differentiation, which is applicable in regenerative medicine. Overall this work has shown that automated microwell platforms provide a feasible route for the scaledout manufacture of hESCs for therapy or as high-throughput screening systems.

Multiproduct manufacturing facilities running on a campaign basis are increasingly becoming the norm for biopharmaceuticals, owing to high risks of clinical failure, regulatory pressures and the increasing number of therapeutics in clinical evaluation. The need for such flexible plants and cost-effective manufacture pose significant challenges for planning and scheduling, which are compounded by long production lead times, intermediate product stability issues and the high cost - low volume nature of biopharmaceutical manufacture. Scheduling and planning decisions are often made in the presence of variable product titres, campaign durations, contamination rates and product demands. Hence this thesis applies mathematical programming techniques to the planning of biopharmaceutical manufacture in order to identify more optimal production plans under different manufacturing scenarios. A deterministic mixed integer linear programming (MILP) medium term planning model which explicitly accounts for upstream and downstream processing is presented. A multiscenario MILP model for the medium term planning of biopharmaceutical manufacture under uncertainty is presented and solved using an iterative solution procedure. An alternative stochastic formulation for the medium term planning of biomanufacture under uncertainty based on the principles of chance constrained programming is also presented. To help manage the risks of long term capacity planning in the biopharmaceutical industry, a goal programming extension is presented which accounts for multiple objectives including cost, risk and customer service level satisfaction. The model is applied to long term capacity analysis of a mix of contractors and owned biopharmaceutical manufacturing facilities. In the final sections of this thesis an example of a commercial application of this work is presented, followed by a discussion on related validation issues in the biopharmaceutical industry. The work in this thesis highlighted the benefits of applying mathematical programming techniques for production planning of biopharmaceutical manufacturing facilities, so as to enhance the biopharmaceutical industry's strategic and operational decision-making towards achieving more cost-effective manufacture.

The benefits of llama antibodies compared to conventional IgG (most particularly low manufacturing cost and stability) have been well published in literature and this lends them to potential applications in the home and personal care industry. Llama antibody fragments have been fused to a cellulose binding domain moiety and used as a bifunctional protein to aid deposition of particles to cellulosic surfaces. The initial anticipated applications for this technology is in the delivery of actives to fabrics in laundry, however due to the ubiquitous nature of cellulose a number of other possible applications are envisaged. Efficacy of the protein was first demonstrated in a model particle system using coacervate particles coated with a dye-based antigen using ELISA, Biacore and particle deposition studies. Determined antibody affinities correlated with those in literature. A number of different fusion formats were investigated, and it was found that although addition of a fusion partner adversely affected antibody affinity, a single antibody/double cellulose binding domain format gave enhanced particle deposition, over a particle only control. The success of the hypothesis in the model system prompted study of a potential commercial equivalent. A particle consisting a melamine urea formaldehyde polymer was chosen. A protein from a range of possible candidates produced by a commercial manufacturer was selected and a purification process was developed that allowed production of protein on the gram scale, with potential for scale-up. The binding, bifunctionality and stability of the protein was then studied using gel densitometry and UV based assays. A substantial increase in particle depositions was demonstrated with a UV microscopy based assay. Use of the protein to enhance particle delivery to cellulosic surfaces showed promise in both systems studied when compared to particles alone, and has potential applications in product fields such as home and personal care, the agrochemical industry and paper processing.