From field to fermentation: characterisation and application of non-dairy cultures in dairy foods

This thesis investigates the phenotypic and genotypic diversity of non-dairy L. lactis strains and their application to dairy fermentations. A bank of non-dairy lactococci were isolated from grass, vegetables and the bovine rumen. Subsequent analysis of these L. lactis strains revealed seven strains to possess cremoris genotypes which did not correlate with their observed phenotypes. Multi-locus sequence typing (MLST) and average nucleotide identity (ANI) highlighted the genetic diversity of lactis and cremoris subspecies. The application of these non-dairy lactococci to cheese production was also assessed. In milk, non-dairy strains formed diverse volatile profiles and selected strains were used as adjuncts in a mini Gouda-type cheese system. Sensory analysis showed non-dairy strains to be strongly associated with the development of off-flavours and bitterness. However, microfluidisation appeared to reduce bitterness. A novel bacteriophage, ɸL47, was isolated using the grass isolate L. lactis ssp. cremoris DPC6860 as a host. The phage, a member of the Siphoviridae, possessed a long tail fiber, previously unseen in dairy lactococcal phages. Genome sequencing revealed ɸL47 to be the largest sequenced lactococcal phage to date and owing to the high % similarity with ɸ949, a second member of the 949 group. Finally, to identify and characterise specific genes which may be important in niche adaptation and for applications to dairy fermentations, comparative genome sequence analysis was performed on L. lactis from corn (DPC6853), the bovine rumen (DPC6853) and grass (DPC6860). This study highlights the contribution of niche specialisation to the intra-species diversity of L. lactis and the adaptation of this organism to different environments. In summary this thesis describes the genetic diversity of L. lactis strains from outside the dairy environment and their potential application in dairy fermentations.

Hybrid density functional theory description of N- and C-doping of NiO

The large intrinsic bandgap of NiO hinders its potential application as a photocatalyst under visible-light irradiation. In this study, we have performed first-principles screened exchange hybrid density functional theory with the HSE06 functional calculations of N- and C-doped NiO to investigate the effect of doping on the electronic structure of NiO. C-doping at an oxygen site induces gap states due to the dopant, the positions of which suggest that the top of the valence band is made up primarily of C 2p-derived states with some Ni 3d contributions, and the lowest-energy empty state is in the middle of the gap. This leads to an effective bandgap of 1.7 eV, which is of potential interest for photocatalytic applications. N-doping induces comparatively little dopant-Ni 3d interactions, but results in similar positions of dopant-induced states, i.e., the top of the valence band is made up of dopant 2p states and the lowest unoccupied state is the empty gap state derived from the dopant, leading to bandgap narrowing. With the hybrid density functional theory (DFT) results available, we discuss issues with the DFT corrected for on-site Coulomb description of these systems.

Immunotherapy for the treatment of poor prognosis cancers

Cancer is amongst the leading causes of death worldwide and the number one cause in the developed world. Every year there are close to 10 million cancer related deaths and this corresponds to hundreds of millions of euro in health care costs and lost productivity, placing a substantial drain on the economy. The efficacy of traditional treatment modalities for cancer therapy, such as surgery, radiotherapy and chemotherapy has plateaued, and while they are undoubtedly effective at prolonging patient lifespan, there is a high rate of adverse side effects and fatal reoccurrence. Currently, there is a huge amount of interest in the areas of cancer immunosurveillance and cancer immuno-editing, which explain some of the complex interactions between the host immune system and cancer. If left unchecked, cancerous malignancies have the ability to generate an immunosuppressive microenvironment, effectively shielding themselves from elimination and promoting tumour growth and progression. To overcome this, the potential of the immune system must be harnessed and the work undertaken in this thesis sought to contribute to this goal. Focus was placed on using novel therapies, combining tumour ablation with immune-modulating antibodies to maximise tumour elimination in an immune dependent manner, to overcome immunosuppression and promote immune activation. Chapter 2 focuses on the use of ECT as a method of tumour ablation and its effects on the immune system. ECT proved to be effective at inhibiting the tumour growth both in vitro and in vivo, and conferred significant survival advantages in both small and large animal models. More importantly, ECT proved to cause tumour death in an immune dependent manner, displaying the hallmarks of Immunogenic Cell Death, increases in immune cell infiltration and generating tumour-specific immune responses. Chapter 3 focuses on combining ECT with immune checkpoint blockade inhibitors; anti- CTLA-4 and anti-PD-1. Both combinations proved to be effective at inhibiting both primary and distal tumour growth, indicating the generation of tumour specific immune responses and prolonged animal survival. In addition, the treatments caused increases in the levels of certain intra-tumoural immune cell subsets and modulated the cytokine profile of treated animals in a way that was favourable overall. Chapter 4 focuses on the combining ECT with an anti-iCOS agonist antibody, capable of causing immune co-stimulation. This novel combinational therapy proved to be the most effective by far, with a high cure rate achieved across a number of different in vivo tumour models. Total regression was seen in both primary and distal tumours, as well as spontaneous metastases, with the tumour specific immune response generated conferring total protection to animals on tumour rechallenge. Overall the data presented here adds further insight into the area of cancer immunotherapy with some of the novel combinational therapies demonstrating substantial clinic potential.

Nanofiber control of ultracold quantum gases

While a great amount of attention is being given to the development of nanodevices, both through academic research and private industry, the field is still on the verge. Progress hinges upon the development of tools and components that can precisely control the interaction between light and matter, and that can be efficiently integrated into nano-devices. Nanofibers are one of the most promising candidates for such purposes. However, in order to fully exploit their potential, a more intimate knowledge of how nanofibers interact with single neutral atoms must be gained. As we learn more about the properties of nanofiber modes, and the way they interface with atoms, and as the technology develops that allows them to be prepared with more precisely known properties, they become more and more adaptable and effective. The work presented in this thesis touches on many topics, which is testament to the broad range of applications and high degree of promise that nanofibers hold. For immediate use, we need to fully grasp how they can be best implemented as sensors, filters, detectors, and switches in existing nano-technologies. Areas of interest also include how they might be best exploited for probing atom-surface interactions, single-atom detection and single photon generation. Nanofiber research is also motivated by their potential integration into fundamental cold atom quantum experiments, and the role they can play there. Combining nanofibers with existing optical and quantum technologies is a powerful strategy for advancing areas like quantum computation, quantum information processing, and quantum communication. In this thesis I present a variety of theoretical work, which explores a range of the applications listed above. The first work presented concerns the use of the evanescent fields around a nanofiber to manipulate an existing trapping geometry and therefore influence the centre-of-mass dynamics of the atom. The second work presented explores interesting trapping geometries that can be achieved in the vicinity of a fiber in which just four modes are allowed to propagate. In a third study I explore the use of a nanofiber as a detector of small numbers of photons by calculating the rate of emission into the fiber modes when the fiber is moved along next to a regularly separated array of atoms. Also included are some results from a work in progress, where I consider the scattered field that appears along the nanofiber axis when a small number of atoms trapped along that axis are illuminated orthogonally; some interesting preliminary results are outlined. Finally, in contrast with the rest of the thesis, I consider some interesting physics that can be done in one of the trapping geometries that can be created around the fiber, here I explore the ground states of a phase separated two-component superfluid Bose-Einstein condensate trapped in a toroidal potential.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Delivering enhanced efficiency in the synthesis of α-diazosulfoxides by exploiting the process control enabled in flow

Continuous-flow generation of α-diazosulfoxides results in a two- to three-fold increase in yields and decreased reaction times compared to standard batch synthesis methods. These high yielding reactions are enabled by flowing through a bed of polystyrene-supported base (PS-DBU or PS-NMe2) with highly controlled residence times. This engineered solution allows the α-diazosulfoxides to be rapidly synthesized while limiting exposure of the products to basic reaction conditions, which have been found to cause rapid decomposition. In addition to improved yields, this work has the added advantage of ease of processing, increased safety profile, and scale-up potential.

The impact of user charges on patient choice of healthcare services in Ireland

This research assesses the impact of user charges in the context of consumer choice to ascertain how user charges in healthcare impact on patient behaviour in Ireland. Quantitative data is collected from a subset of the population in walk-in Urgent Care Clinics and General Practitioner surgeries to assess their responses to user charges and whether user charges are a viable source of part-funding healthcare in Ireland. Examining the economic theories of Becker (1965) and Grossman (1972), the research has assessed the impact of user charges on patient choice in terms of affordability and accessibility in healthcare. The research examined a number of private, public and part-publicly funded healthcare services in Ireland for which varying levels of user charges exist depending on patients’ healthcare cover. Firstly, the study identifies the factors affecting patient choice of privately funded walk-in Urgent Care Clinics in Ireland given user charges. Secondly, the study assesses patient response to user charges for a mainly public or part-publicly provided service; prescription drugs. Finally, the study examines patients’ attitudes towards the potential application of user charges for both public and private healthcare services when patient choice is part of a time-money trade-off, convenience choice or preference choice. These services are valued in the context of user charges becoming more prevalent in healthcare systems over time. The results indicate that the impact of user charges on healthcare services vary according to socio-economic status. The study shows that user charges can disproportionately affect lower income groups and consequently lead to affordability and accessibility issues. However, when valuing the potential application of user charges for three healthcare services (MRI scans, blood tests and a branded over a generic prescription drug), this research indicates that lower income individuals are willing to pay for healthcare services, albeit at a lower user charge than higher income earners. Consequently, this study suggests that user charges may be a feasible source of part-financing Irish healthcare, once the user charge is determined from the patients’ perspective, taking into account their ability to pay.

Engineering design of an integrated sustainable process system for cassava biobased materials

Cassava contributes significantly to biobased material development. Conventional approaches for its bio-derivative-production and application cause significant wastes, tailored material development challenges, with negative environmental impact and application limitations. Transforming cassava into sustainable value-added resources requires redesigning new approaches. Harnessing unexplored material source, and downstream process innovations can mitigate challenges. The ultimate goal proposed an integrated sustainable process system for cassava biomaterial development and potential application. An improved simultaneous release recovery cyanogenesis (SRRC) methodology, incorporating intact bitter cassava, was developed and standardized. Films were formulated, characterised, their mass transport behaviour, simulating real-distribution-chain conditions quantified, and optimised for desirable properties. Integrated process design system, for sustainable waste-elimination and biomaterial development, was developed. Films and bioderivatives for desired MAP, fast-delivery nutraceutical excipients and antifungal active coating applications were demonstrated. SRRC-processed intact bitter cassava produced significantly higher yield safe bio-derivatives than peeled, guaranteeing 16% waste-elimination. Process standardization transformed entire root into higher yield and clarified colour bio-derivatives and efficient material balance at optimal global desirability. Solvent mass through temperature-humidity-stressed films induced structural changes, and influenced water vapour and oxygen permeability. Sevenunit integrated-process design led to cost-effectiveness, energy-efficient and green cassava processing and biomaterials with zero-environment footprints. Desirable optimised bio-derivatives and films demonstrated application in desirable in-package O2/CO2, mouldgrowth inhibition, faster tablet excipient nutraceutical dissolutions and releases, and thymolencapsulated smooth antifungal coatings. Novel material resources, non-root peeling, zero-waste-elimination, and desirable standardised methodology present promising process integration tools for sustainable cassava biobased system development. Emerging design outcomes have potential applications to mitigate cyanide challenges and provide bio-derivative development pathways. Process system leads to zero-waste, with potential to reshape current style one-way processes into circular designs modelled on nature's effective approaches. Indigenous cassava components as natural material reinforcements, and SRRC processing approach has initiated a process with potential wider deployment in broad product research development. This research contributes to scientific knowledge in material science and engineering process design.

The epigenome as a therapeutic target for Parkinson's disease

Parkinson’s disease (PD) is a common, progressive neurodegenerative disease characterised by degeneration of nigrostriatal dopaminergic neurons, aggregation of α-synuclein and motor symptoms. Current dopamine-replacement strategies provide symptomatic relief, however their effectiveness wear off over time and their prolonged use leads to disabling side-effects in PD patients. There is therefore a critical need to develop new drugs and drug targets to protect dopaminergic neurons and their axons from degeneration in PD. Over recent years, there has been robust evidence generated showing that epigenetic dysregulation occurs in PD patients, and that epigenetic modulation is a promising therapeutic approach for PD. This article first discusses the present evidence implicating global, and dopaminergic neuron-specific, alterations in the methylome in PD, and the therapeutic potential of pharmacologically targeting the methylome. It then focuses on another mechanism of epigenetic regulation, histone acetylation, and describes how the histone acetyltransferase (HAT) and histone deacetylase (HDAC) enzymes that mediate this process are attractive therapeutic targets for PD. It discusses the use of activators and/or inhibitors of HDACs and HATs in models of PD, and how these approaches for the selective modulation of histone acetylation elicit neuroprotective effects. Finally, it outlines the potential of employing small molecule epigenetic modulators as neuroprotective therapies for PD, and the future research that will be required to determine and realise this therapeutic potential.