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Engineering of Clostridium novyi to enhance efficacy in cancer therapy
No full textClostridium novyi-NT (non-toxic) is an attenuated clone derived from C. novyi, rendered non-pathogenic through the removal of a resident phage that carries the gene for the lethal alpha toxin. It is a Gram-positive spore-forming bacterium, which has gained significant attention for its potential use in cancer therapy. C. novyi-NT is a strictly anaerobic bacterium, enabling it to thrive in the hypoxic regions of tumours, a characteristic hallmark of solid malignancies. For therapy, C. novyi-NT can be delivered as dormant spores that germinate in hypoxic, necrotic tumours, inducing oncolysis through enzymatic activity and immune activation, while complementing treatments that target oxygen-rich tumour areas.
This study focused on genetically modifying C. novyi-NT to improve its safety profile for use in cancer therapeutics, and to improve its efficacy. Prior to modifying the organism for cancer therapeutics, gene transfer into C. novyi-NT and its molecular characteristics were assessed. Various strategies, including gene knockouts and altering donor methylation patterns, were used to bypass restriction-modification barriers, but showed no effect.
To enhance the safety profile of C. novyi-NT conditionally sporulating strains were created using CRISPR-Cas technology, whereby the strains were only able to sporulate when in the presence of specific ligands. This approach provided a solution for preventing the spread of spores beyond the targeted tumour region, thereby reducing the risk of toxicity and the dissemination of recombinant spores.
The promoters of C. novyi-NT were investigated, and reporter assays identified a suitable candidate for cytokine expression. C. novyi-NT was subsequently engineered to express the cytokines GM-CSF and IL-4, with the investigation of signal peptides resulting in the efficient secretion of GM-CSF.
Furthermore, a novel inducible xylose promoter was engineered for use in both E. coli and C. novyi-NT to control toxicity, which could facilitate the advancement of cytokine expression and cloning in future studies
An exploration of educational psychologists’ views and experiences of neurodiversity-affirming practice
Get PDFSince the late 1990s, neurodiversity discourse has increasingly shaped educational policy and practice. Educational Psychologists (EPs) frequently support neurodivergent children and young people, often through inclusive practices that promote meaningful participation and a sense of belonging. However, the rise of the neurodiversity-affirming (NDA) movement has prompted a closer look at conventional approaches to inclusion, highlighting how they often push neurodivergent children and young people to ‘fit in’ with neurotypical expectations rather than changing environments and practices to be genuinely affirming and inclusive.
This qualitative study explored EPs’ views and experiences of NDA practice. Semi-structured interviews were carried out with six EPs from Local Authority (LA) services in England. Interview data were analysed using Braun and Clarke’s (2006; 2022) reflexive thematic analysis. Five main themes emerged: Systemic barriers to NDA practice; Shifting from deficit to affirmation: redefining practice; Evolving understandings of neurodiversity and the complexities of practice; Prioritising neurodivergent voices; The importance of collaboration.
The findings contribute to the emerging research on the implementation of NDA approaches by revealing the struggles EPs face between their commitment to affirming principles and institutional constraints. Barriers such as standardised assessments, inflexible curricula, funding limitations and academic performance targets were identified by participants as significant obstacles. They also described how resistance stemming from cultural attitudes towards disability and difference create additional barriers to implementing NDA practices in schools. Despite the challenges, EPs emphasised the many opportunities for developing effective NDA practice through increased public awareness, advocacy and greater recognition of neurodivergent voices.
Implications of the findings are discussed with reference to professional development, policy reforms and increased collaboration between educators, families and the neurodivergent community
Educational Disadvantage and University Entrance for Pakistani and Nepalese School Students in Hong Kong: The Possibilities of Legal Redress
No full textThis thesis focuses on how Pakistani and Nepalese school students in Hong Kong are educationally disadvantaged compared to local Chinese students by a combination of experiencing difficulties learning Chinese and the entrance policies of universities. The research was undertaken from a legal perspective to explore the possibilities of legal redress, which is one important way of addressing these inequalities. The research involved interviews with stakeholders, developing a comparative case study and, finally, exploring the legal case.
Ethnic minority groups in Hong Kong account for 8 % of the total population. The Hong Kong Special Administrative Region Government is under an obligation to guarantee equal access to education to all students without discrimination. However, there is evidence from policy documents and scholarly literature that ethnic minority students are not supported to learn and qualify in Cantonese to a high enough level to afford them equal access to one of the nine prestigious JUPAS universities. The universities’ admissions procedures appear to be discriminatory by placing a high value on proficiency in Chinese, even when not necessary for university study.
The thesis explores the policy and legal background to the problem and then takes three methodological approaches to taking the investigation further. First, to explore how those affected perceive and experience the problem, 16 interviews were undertaken with 8 students from ethnic minority groups, 6 principals and 2 teachers of schools with a large number of ethnic minority students. These interviews revealed that students do experience educational disadvantage in relation to university entrance, but that they are often unaware of it. Despite efforts, it was eventually too difficult to gain any responses from universities about their admission policies and procedures. Secondly, it compares the education system and policies of Hong Kong with Singapore which is composed of three major ethnic student groups. The comparison shows that the situation in Hong Kong is not inevitable: Singaporean government maintains greater equality and fairness between the groups than in Hong Kong. Thirdly, it undertakes a thorough legal analysis using precedents and cases. Taking all the evidence together, the thesis concludes by confirming that an aggrieved member of the ethnic minority students could seek legal redress or remedies against one of the nine universities under Judicial Review on the basis of the Race Discrimination Ordinance and/or any other statutes on constitutional laws or through any statutory bodies such as the Equal Opportunities Commission or the Legal Aid Department
Cryptocurrency returns, volatility and investor attention: an empirical analysis using econometric and machine learning techniques
No full textThis thesis presents a comprehensive empirical investigation into the rapidly evolving cryptocurrency market, employing a range of advanced econometric and machine learning techniques, based on an overall sample spanning from 18 July 2010 to 5 May 2023. The research is systematically organised into three distinct yet interconnected studies, each contributing uniquely to the understanding of market dynamics.
The first study significantly expands the empirical foundation of prior research by examining a wide range of potential return determinants across 25 leading cryptocurrencies, including well-established assets such as BTC, ETH, and XRP, which are categorised under network, production, macroeconomic, cryptocurrency-specific, and global or uncertainty factors. This approach enables a multi-dimensional analysis of cryptocurrency price formation and supports the evaluation of several theoretical perspectives, including supply and demand, cost of production, and network effects, within the context of digital assets. Methodologically, the study employs individual-level analyses, a market index-based approach, and a panel setting to capture aggregate dynamics. Principal Component Analysis is used to reduce noise among correlated variables and to identify the most salient factors across the sample. Estimations are conducted using a variety of econometric techniques, such as OLS, regression with Newey–West standard errors and autocorrelation correction, Fixed Effects, FGLS, and Prais–Winsten regression with panel-corrected standard errors.
The findings demonstrate that, although the relative importance of each factor varies across different cryptocurrencies, network-related and cryptocurrency-specific variables consistently exert the strongest influence. From a theoretical perspective, while each framework based on the analysed set of factors provides valuable insights, the results indicate that no single set of variables or theoretical lens is sufficient to fully explain cryptocurrency returns. Drawing on these results, the research establishes a novel link between the subjective theory of value and cryptocurrencies, suggesting that the value of digital assets is not derived from intrinsic fundamentals but is instead shaped by factors such as user interest, transactional benefits, and the willingness to adopt, which in turn influence network size, trading volume, and transactional activity. This connection enables the integration of multiple theoretical perspectives, incorporating behavioural and network-based influences, and contributes to the development of a more comprehensive valuation framework tailored to the unique characteristics of digital assets. In addition, the study highlights the important role of macroeconomic factors and global uncertainty, particularly during crisis periods such as the COVID-19 pandemic. This finding challenges earlier research that deemed macroeconomic variables largely insignificant and offers empirical support for their time-varying influence. By demonstrating that the sensitivity of cryptocurrency valuations to macroeconomic and financial indicators can shift over time, the study enriches the debate on whether digital assets function purely as speculative instruments or as emerging macro-sensitive assets.
The second study extends the research by investigating the predictive capacity of the identified return determinants through out-of-sample forecasting, implementing both conventional econometric models (ARIMA/ARIMAX) and modern neural networks (NAR/NARX). Based on economic and statistical loss functions, this comparative analysis demonstrates that both methodologies can effectively forecast cryptocurrency returns over short horizons, with the highest accuracy observed for one-day-ahead predictions. Notably, neural networks outperform ARIMA models when relying solely on historical return data, while ARIMAX models exhibit strong performance and often exceed that of NARX when relevant external predictors are employed.
However, the ARIMAX model’s dependence on accurate future values of exogenous inputs presents a practical limitation, as such data are often difficult to obtain in real-world or ex-ante forecasting scenarios. In contrast, the NARX model, due to its internal feedback mechanisms, has the potential to maintain forecasting accuracy even when external inputs are unavailable, delayed, or difficult to predict. This comparison highlights the respective strengths and limitations of each modelling approach and offers practical guidance for investors, traders, and analysts in selecting appropriate forecasting methods based on data availability and forecasting objectives. Moreover, the study contributes to the literature by demonstrating the feasibility of predictive modelling in cryptocurrency markets, thereby challenging the weak and semi-strong forms of market efficiency. It also reinforces the predictive relevance of network-related and cryptocurrency-specific variables, emphasising their central role in return dynamics.
The third study makes a significant contribution to the cryptocurrency literature by examining how investor heterogeneity shapes volatility, highlighting the distinct roles of institutional and individual behaviour. It employs traditional GARCH-family models alongside advanced neural networks and support vector regression techniques using diverse model architectures. The study finds that institutional investor attention consistently increases volatility, driven by access to capital, superior information, and advanced analytical tools, positioning institutions as dominant yet destabilising participants. This challenges the assumption that institutional presence enhances market stability. In contrast, individual investor attention tends to amplify volatility during stable periods but reduces it during times of global uncertainty, revealing context-dependent behavioural shifts.
The study also presents a novel multi-asset investigation into the "whale" phenomenon, demonstrating the potential of whales and large institutions to exploit informational asymmetries and amplify market inefficiencies, contributing to various forms of herding behaviours. By uniquely framing these dynamics within the context of imperfect market competition, the findings challenge the commonly held notion of decentralisation in cryptocurrency markets. This perspective highlights the risks posed by concentrated market power and the potential for manipulation, reinforcing the importance of transparency and regulatory oversight.
Moreover, the observed interdependence among cryptocurrencies, particularly the influence of Bitcoin-related institutional activity and whale behaviour on the broader market index, enhances understanding of systemic risk by showing how dominant asset-specific factors can shape overall market dynamics. Finally, the study advances volatility modelling by demonstrating that machine learning methods outperform traditional GARCH models in predictive accuracy, measured by RMSE and MAE, with neural networks proving the most effective. Their ability to capture complex, non-linear, dynamic, and high-dimensional relationships highlights the limitations of conventional models and underscores the value of data-driven techniques for modelling the unique characteristics of digital assets.
Taken together, this thesis substantially enhances the current literature by integrating theoretical perspectives with empirical findings that illuminate the distinct market mechanisms inherent in digital assets. Theoretically, it advances the understanding of how subjectivist valuation, behavioural finance, and investor heterogeneity shape the cryptocurrency market. Practically, for investors and traders, the refined predictive models and the highlighted significance of network and cryptocurrency-specific factors, attention, and whale metrics offer practical insights for portfolio optimisation and algorithmic trading strategies. For policymakers and regulators, the insights into market inefficiencies, the impact of investor attention, and the destabilising potential of institutional trades and whale activity provide critical evidence to inform regulatory reforms aimed at controlling concentration levels and stabilising this volatile market. Furthermore, the results may prove valuable for central banks exploring the design and implementation of digital currencies, as they highlight the multifaceted drivers of cryptocurrency returns and volatility and the practical considerations involved in regulating emerging financial technologies
Reimagining constraints and accessibility in the rail sector: late technology adopters in increasingly digitalised travel environments
Get PDFThis thesis explores the constraints and accessibility of rail travel for late adopters of technology, focusing specifically on leisure travellers in Great Britain. As British rail undergoes structural and digital transformation, ensuring accessible services for all passengers has become increasingly vital. Late adopters of technology represent up to half of all leisure passengers, and are often stereotypically portrayed as elderly, technology-averse and resistant to change. However, this research reveals a more complex reality.
The overarching objective of identifying, analysing and understanding travel constraints for late technology adopters is addressed through four key research questions related to: the representativeness of existing literature on late adopters, the effectiveness of current constraints analysis methods, the constraints of rail travel, and potential service improvements. To comprehensively assess travel constraints for this passenger group, the research applies a multilayered approach incorporating both industry and passenger stakeholder perspectives. This qualitative investigation employs multiple methods including industry focus groups, semi-structured passenger interviews, travel-along ethnographies, and passenger focus groups. Methodologically, the research combines cognitive work analysis from human factors with constraints negotiation theory from leisure studies, developing an innovative interdisciplinary approach to investigate this diverse passenger group.
The findings demonstrate that late adopters are more diverse and technologically engaged than previously recognised in academic literature. Their technology use varies significantly between home and travel environments, challenging assumptions about universal adoption patterns. The research identifies multiple interconnected constraints affecting rail travel experiences, categorised as intrapersonal (confidence, trust), interpersonal (reliance on others), and structural (system design, accessibility). Notably, while many late adopters actively use digital technologies at home, they express hesitancy about using similar technologies in travel settings, preferring human interaction for complex or unfamiliar tasks.
This thesis makes several contributions to knowledge. First, it develops a novel constraints analysis framework that provides fresh insights into the constraints of rail travel and the nature of constraints for the late technology adopter passenger group. Second, it challenges stereotypical representations by revealing late adopters as selective and strategic technology users, rather than universally disinterested in technology and resistant to change. Third, it demonstrates how environmental context influences technology engagement and adoption, highlighting the importance of situational factors in understanding user behaviour.
For industry stakeholders, the findings highlight two key insights: the essential role of traditional support mechanisms alongside digital innovation and the influence of trusted intermediaries in technology adoption. Recommendations include leveraging staff and volunteers to build confidence in digital travel services. This research also identifies a significant gap in the Great British rail sector's accessibility policy regarding technological engagement. Integration of digital accessibility considerations, particularly for those hesitant or unable to use technology, could help industry better evaluate how service digitalisation impacts passenger experience
Host and molecular mechanisms behind the persistence of equine strangles
Get PDFBackground: Equine strangles is a widespread and highly infectious disease caused by the bacterium Streptococcus equi subspecies equi (S. equi). Despite the long history of strangles, much is still unknown about S. equi and the disease it causes. Understanding the complex interplay between host and bacterial factors that contribute to the carrier state is crucial for effective management of equine strangles. The aims of this project were to 1) evaluate the effectiveness of a strangles screening protocol at a UK welfare centre equids and 2) use nanopore sequencing alongside bioinformatic analysis to investigate structural variants in acute and persistent S. equi isolates
Methods: Phase 1: The clinical records of 626 equids admitted to a UK welfare centre between 2017 and 2021 were analysed. Admitted equids were subject to a strangles screening process consisting of paired dual target iELISA serological tests and guttural pouch endoscopy and lavage. Phase 2: The genomes of 11 acute and persistent S. equi isolates were analysed using nanopore sequencing technologies to investigate structural variants.
Results: Phase 1: Retrospective analysis of the clinical records of admitted equids found that the most effective way to diagnose strangles was through guttural pouch endoscopy and lavage. No host factors or haematological parameters were significantly associated with strangles carriage. The dual target iELISA was found to be unreliable for the purpose of carrier detection. Phase 2: Deletions and inversions were found in key genomic regions including genes encoding the hyaluronic acid capsule and key sortase-processed cell surface proteins. A prophage was also found, integrated within genes encoding for the hyaluronic acid capsule.
Discussion: These findings highlight the dynamic nature of persistence within the guttural pouch and reinforce the importance of implementing effective strangles screening protocols to prevent future outbreaks and maintain strangles-free herds. Endoscopically guided guttural pouch lavage and quantitative PCR was confirmed to be the most effective method for carrier detection. S. zooepidemicus was found to cause persistent strangles-like disease and should increasingly be considered alongside S. equi when dealing with strangles. Evidence of genomic decay was identified, and the inversions observed could lead to the development of subpopulations and represent a molecular mechanism associated with S. equi persistence. Structural variants could explain the failure of the dual-target iELISA
The role of the CBLL1/HAKAI E3 Ubiquitin Ligase component and its association with the RNA methyltransferase complex in breast cancer
Get PDFIndividuals’ experiences of their relationship with exercise and mind-body connection in recovery from disordered eating
Get PDFAn in vivo genetic screen of lung function candidate genes using tissue-specific RNAi in Drosophila melanogaster
Get PDFChronic Obstructive Pulmonary Disease (COPD) is a poorly treatable respiratory condition marked by a progressive and irreversible airflow limitation. The airway epithelium (AE), serving as the first line of defence against inhaled insults, fulfils multiple functions to ensure pulmonary homeostasis. In COPD, the AE is profoundly altered with major changes in epithelial structure and biology that impair barrier function. Given that a significant heritable component underlies disease risk, the identification of genetic factors that alter lung function is crucial to advancing our understanding of COPD pathophysiology and identifying key pathways and targets for therapeutic intervention. The aim of the work described in this thesis is to leverage the relative simplicity, genetic amenability and high-throughput screening potential of transgenic Drosophila melanogaster to elucidate the influence of lung function and COPD-associated genes on epithelial biology.
Using an integrative bioinformatics approach, 70 independent lung function GWAS signals were mapped to 187 human candidate causal genes. From these, 60 candidate orthologues of interest were identified in the fly to undergo an in vivo RNAi-mediated knockdown screen in two distinct epithelia: the dorsal thorax and tracheal system. A systematic loss-of-function analysis in the dorsal thorax epithelium revealed a total of 33 genes that disrupt epithelial morphology and behaviour, impacting cell-cell junctions, cell migration and clonal size. Protein-protein interaction analysis of these hits identified regulatory networks prominently associated with ribosome biogenesis and translational control. Notably, ten genes - Rtf1, pAbp, Sec6, Arf102F, RIOK1, Sra-1, INPP5E, CG31759, ssh and RpS26 - emerged as highly penetrant, pivotal regulators of epithelial barrier stability and structural organisation. Further characterisation of cell adhesion found a significant reduction in junctional E-Cadherin levels following Arf102F, Rtf1, RIOK1 and Sra-1 knockdown. A secondary screen of this subset of candidates in the Drosophila tracheal screen identified varied points of developmental arrest. The knockdown of Sec6 and RpS26 specifically resulted in significant airway defects and a reduction in larval body size in the third instar.
Expression profiling of human homologues in COPD patient tissues found altered expression in several genes, with pathway analysis linking candidates to previously described regulatory pathways, including MYC and AKT signalling and shared upstream regulators. Finally, preliminary investigations using primary human bronchial epithelial cell culture indicate that EXOC3 (Sec6) and RPS26 (RpS26) knockout may impair epithelial barrier function. Taken together, these findings offer new perspectives on the genetics of COPD and serve as a basis for future translational research using non-mammalian models as a starting point
Investigating the role of metapleural glands in social immunity and the role of co-founding in pathogen resistance in Messor barbarus
Get PDFThe risk of pathogen infection due to increased within-group transmission is theorised to be a major potential cost of group-living and eusociality. Many eusocial insects have evolved defence mechanisms to mitigate this risk and mount collective defences against pathogens. Social immunity describes the behaviours which are used to minimise pathogen spread within a colony, such as allo-grooming and waste management. Additionally, ants have developed chemical defences, such as the antimicrobial substance produced by the metapleural gland. This thesis investigated how the availability of metapleural glands and social immunity affect the survival probability of Messor barbarus and their response to an entomopathogenic fungus, Metarhizium brunneum. The results showed that the presence of fungal spores or Triton X on the cuticle increased self-grooming, and in the control treatment, an ant groomed for a longer period of time if they had a blocked gland. There was no difference in allo-grooming between individuals. Additionally, there was a high mortality of ants exposed to M. brunneum. More experiments are required to see whether the behaviours explored in this thesis are important or not in modulating the efficacity of the metapleural gland. There could be some other mechanism, potentially passive, involved in how the metapleural gland protects the ants from disease.
Colony-founding queens do not have access to the colony-wide defensive system, and new colonies suffer high rates of mortality. In a number of eusocial insects, queens join together and co-found a colony collectively. This thesis investigated how being exposed to M. brunneum and group type affects the founding of new colonies. The results showed that exposed single queens and unexposed previously paired queens produced the highest number of brood and adults comparatively. These findings could support a newly discovered phenomenon called “hygienic cannibalism” where a queen will reinvest nutrients back into egg production from eating infected larvae. The presence of an unrelated queen could be viewed as interacting with a foreign substance, as being exposed to either another queen or a pathogen produced a large number of brood and adults. Exposed previously paired queens had the disadvantage of both an immune response and energy lost due to fighting so produced a small number of brood and adults in comparison
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