Development and assessment of new sensor systems in food packaging applications

The use of optical sensor technology for non-invasive determination of key quality pack parameters improved package/product quality. This technology can be used for optimization of packaging processes, improvement of product shelf-life and maintenance of quality. In recent years, there has been a major focus on O2 and CO2 sensor development as these are key gases used in modified atmosphere packaging (MAP) of food. The first and second experimental chapters (chapter 2 and 3) describe the development of O2, pH and CO2 solid state sensors and its (potential) use for food packaging applications. A dual-analyte sensor for dissolved O2 and pH with one bi-functional reporter dye (meso-substituted Pd- or Ptporphyrin) embedded in plasticized PVC membrane was developed in chapter 2. The developed CO2 sensor in chapter 3 was comprised of a phosphorescent reporter dye Pt(II)- tetrakis(pentafluorophenyl) porphyrin (PtTFPP) and a colourimetric pH indicator α-naphtholphthalein (NP) incorporated in a plastic matrix together with a phase transfer agent tetraoctyl- or cetyltrimethylammonium hydroxide (TOA-OH or CTA-OH). The third experimental chapter, chapter 4, described the development of liquid O2 sensors for rapid microbiological determination which are important for improvement and assurance of food safety systems. This automated screening assay produced characteristic profiles with a sharp increase in fluorescence above the baseline level at a certain threshold time (TT) which can be correlated with their initial microbial load and was applied to various raw fish and horticultural samples. Chapter 5, the fourth experimental chapter, reported upon the successful application of developed O2 and CO2 sensors for quality assessment of MAP mushrooms during storage for 7 days at 4°C.

Evanescent field sensing: optical nanofibres, whispering-gallery-mode microspherical and microbubble resonators

In this thesis, the evanescent field sensing techniques of tapered optical nanofibres and microspherical resonators are investigated. This includes evanescent field spectroscopy of a silica nanofibre in a rubidium vapour; thermo-optical tuning of Er:Yb co-doped phosphate glass microspheres; optomechanical properties of microspherical pendulums; and the fabrication and characterisation of borosilicate microbubble resonators. Doppler-broadened and sub-Doppler absorption spectroscopic techniques are performed around the D2 transition (780.24 nm) of rubidium using the evanescent field produced at the waist of a tapered nanofibre with input probe powers as low as 55 nW. Doppler-broadened Zeeman shifts and a preliminary dichroic atomic vapour laser lock (DAVLL) line shape are also observed via the nanofibre waist with an applied magnetic field of 60 G. This device has the potential for laser frequency stabilisation while also studying the effects of atom-surface interactions. A non-invasive thermo-optical tuning technique of Er:Yb co-doped microspheres to specific arbitrary wavelengths is demonstrated particularly to 1294 nm and the 5S1/2F=3 to 5P3/2Fʹ=4 laser cooling transition of 85Rb. Reversible tuning ranges of up to 474 GHz and on resonance cavity timescales on the order of 100 s are reported. This procedure has prospective applications for sensing a variety of atomic or molecular species in a cavity quantum electrodynamics (QED) experiments. The mechanical characteristics of a silica microsphere pendulum with a relatively low spring constant of 10-4 Nm-1 are explored. A novel method of frequency sweeping the motion of the pendulum to determine its natural resonance frequencies while overriding its sensitivity to environmental noise is proposed. An estimated force of 0.25 N is required to actuate the pendulum by a displacement of (1-2) μm. It is suggested that this is of sufficient magnitude to be experienced between two evanescently coupled microspheres (photonic molecule) and enable spatial trapping of the micropendulum. Finally, single-input borosilicate microbubble resonators with diameters <100 μm are fabricated using a CO2 laser. Optical whispering gallery mode spectra are observed via evanescent coupling with a tapered fibre. A red-shift of (4-22) GHz of the resonance modes is detected when the hollow cavity was filled with nano-filtered water. A polarisation conversion effect, with an efficiency of 10%, is observed when the diameter of the coupling tapered fibre waist is varied. This effect is also achieved by simply varying the polarisation of the input light in the tapered fibre where the efficiency is optimised to 92%. Thus, the microbubble device acts as a reversible band-pass to band-stop optical filter for cavity-QED, integrated solid-state and semiconductor circuit applications.

Optimisation of immune effector function within the tumour microenvironment

Cancer represents a leading of cause of death in the developed world, inflicting tremendous suffering and plundering billions from health budgets. The traditional treatment approaches of surgery, radiotherapy and chemotherapy have achieved little in terms of cure for this deadly disease. Instead, life is prolonged for many, with dubious quality of life, only for disease to reappear with the inevitable fatal outcome. “Blue sky” thinking is required to tackle this disease and improve outcomes. The realisation and acceptance of the intrinsic role of the immune system in cancer pathogenesis, pathophysiology and treatment represented such a “blue sky” thought. Moreover, the embracement of immunotherapy, the concept of targeting immune cells rather than the tumour cells themselves, represents a paradigm shift in the approach to cancer therapy. The harnessing of immunotherapy demands radical and innovative therapeutic endeavours – endeavours such as gene and cell therapies and RNA interference, which two decades ago existed as mere concepts. This thesis straddles the frontiers of fundamental tumour immunobiology and novel therapeutic discovery, design and delivery. The work undertaken focused on two distinct immune cell populations known to undermine the immune response to cancer – suppressive T cells and macrophages. Novel RNAi mediators were designed, validated and incorporated into clinically relevant gene therapy vectors – involving a traditional lentiviral vector approach, and a novel bacterial vector strategy. Chapter 2 deals with the design of novel RNAi mediators against FOXP3 – a crucial regulator of the immunosuppressive regulatory T cell population. Two mediators were tested and validated. The superior mediator was taken forward as part of work in chapter 3. Chapter 3 deals with transposing the RNA sequence from chapter 2 into a DNA-based construct and subsequent incorporation into a lentiviral-based vector system. The lentiviral vector was shown to mediate gene delivery in vitro and functional RNAi was achieved against FOXP3. Proof of gene delivery was further confirmed in vivo in tumour-bearing animals. Chapter 4 focuses on a different immune cell population – tumour-associated macrophages. Non-invasive bacteria were explored as a specific means of delivering gene therapy to this phagocytic cell type. Proof of delivery was shown in vitro and in vivo. Moreover, in vivo delivery of a gene by this method achieved the desired immune response in terms of cytokine profile. Overall, the data presented here advance exploration within the field of cancer immunotherapy, introduce novel delivery and therapeutic strategies, and demonstrate pre-clinically the potential for such novel anti-cancer therapies.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.