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    A systematic review of self compassion and stress in parents, and an exploration of emotion regulation and psychopathology in adolescence

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    BACKGROUND: Self compassion is considered an adaptive coping strategy in the face of stress and is thought to be an important factor in parent functioning. Self compassion can also be understood within an emotion regulation framework. High levels of self compassion and effective emotion regulation have been shown to be associated with lower levels of psychopathology. The adolescent stage is thought to be an important period in the development of emotion regulation and how this relates to psychopathology. METHOD: Chapter 1 is a systematic review and meta analysis of the association between self compassion and parenting stress. Chapter 3 explored the relationship between emotion regulation and psychopathology in adolescence using a cross sectional design. RESULTS: Chapter 1 demonstrated a medium effect size for the association between self compassion and stress in parents, with high levels of self compassion being related to lower levels of stress. Chapter 3 demonstrated that in an adolescent population, dysfunctional emotion regulation is related to symptoms of anxiety and depression, and that age did not appear to moderate this relationship. CONCLUSIONS: This project explored ways of regulating emotions in parent and adolescent populations. Taken together, these findings demonstrate that emotion regulation and self compassion are important concepts in relation to understanding how individuals cope with stress and how this impacts their psychological wellbeing

    Using data to understand outcomes for cancer surgery in low- and middle-income countries

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    BACKGROUND: Of the 15.2 million individuals diagnosed with cancer worldwide in 2015, 80% had a need for surgery. Yet little comparative data globally exist on early outcomes, particularly within low-income and middle-income countries (LMICs). I designed and delivered an international, prospective cohort study to provide comprehensive data across income settings on early outcomes in patients undergoing surgery for three common cancers. METHODS: I determined the early outcomes following cancer surgery through standardised and prospective methodology to gather contemporaneous and comprehensive data across multiple countries. Next, I validated this data to ensure accuracy and high case ascertainment. Finally, I determined the patient- and hospital-level factors which influence early outcomes following cancer surgery, to identify potential interventions which may improve surgical cancer care worldwide. RESULTS: In an international cohort of 15 958 patients from 428 hospitals and 82 countries undergoing surgery for breast, colorectal, or gastric cancer, case ascertainment and data accuracy were high. Higher postoperative mortality was seen in patients receiving surgery in LMICs, despite equivalent complication rates. The capacity to rescue patients from death after the development of common postoperative complications explains some of the disproportionate mortality burden experienced in LMICs. I demonstrated improvements in hospital facilities, which correlate with a hospital’s ability to perform safe, high-quality operations and aid the early identification and treatment of postoperative complications, are likely to prevent up to three early surgical deaths for every 100 patients undergoing cancer surgery worldwide. CONCLUSIONS: Perioperative mortality is disproportionately greater in LMICs, which contributes to worse cancer survival in these settings. Excess early mortality following cancer surgery is avoidable, but improving access to surgical care alone is unlikely to significantly reduce cancer-associated mortality. Urgent assessment of pragmatic perioperative interventions led by investigators in LMICs is needed to avert avoidable mortality after the development of common complications after cancer surgery

    Exploring S-Nitrosoglutathione reductase function in the non-vascular plant, Marchantia polymorpha

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    A key feature of plant immunity is the rapid engagement of a burst of nitric oxide (NO) following pathogen recognition. In addition to direct antimicrobial activity NO also orchestrates a plethora of signalling functions to control the deployment of plant immune responses. The predominant route for NO signalling is S-nitrosylation, a key redox-based, post-translational modification involving the addition of a NO moiety to a protein cysteine (Cys) thiol, forming an S-nitrosothiol (SNO). To explore a potential role for S-nitrosylation in the immune system of early land plants, we identified a single-copy S-nitrosoglutathione reductase 1 (GSNOR1) gene in Marchantia polymorpha (Mp) and introduced loss-of-function mutations using the CRISPR/Cas9 gene editing method to explore the potential function of GSNOR in this early land plant. We observed distinct morphological changes in Mp resulting from the absence of GSNOR1 function, providing new insights into the structural adaptations of this plant. In addition, we found GSNOR1 plays a central role in the immune system of Mp. This research contributes to a broader understanding of plant-microbe interactions. It offers a fundamental understanding of the function of NO and GSNOR1 in Mp development and immunity and also provides insights into evolutionary plant biology

    Understanding and stratifying brain health through blood-based omics data

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    Brain health across the lifespan is dynamic and influenced by a complex interplay of genetics and the environment. Age-related neurological diseases are a growing burden on healthcare systems and society. Individuals that do not have overt diagnoses of neurological diseases will still experience declines in cognitive ability and reductions in grey matter volumes as they age. Understanding why some brains are healthier than others may provide insight into targets for the preservation of brain health. Early identification of individuals at high-risk of neurological diseases is a priority for preventative strategies. Proteins are the effector molecules of disease in the body and are often the targets of therapeutic interventions. Blood samples can be used to derive measures of many thousands of blood proteins and are routinely collected in clinical and research settings. Another measure available from blood is DNA methylation (DNAm), which is an epigenetic mechanism that can regulate gene expression and protein levels. DNAm is thought to record the body’s response to a range of biological and environmental factors. The first aim of this thesis is to perform methylome-wide association studies (MWAS) of circulating proteins, with a focus on those related to brain health. DNAm patterns can also be used to derive proxy scores for protein levels – an approach that is somewhat analogous to polygenic scores. These proxies are known as protein epigenetic scores (or EpiScores). In some cases, protein EpiScores outperform measured proteins in associations with brain imaging and lifestyle traits, possibly due to the relative lack of stability observed across some single time point protein measurements. Protein EpiScores could represent biomarkers for risk stratification. However, this has not been examined at scale. Consequently, the second aim of this thesis is to develop a comprehensive set of protein EpiScores and evaluate them as tools for risk stratification. For neurological diseases such as Alzheimer’s dementia, damage is thought to occur in the brain decades prior to symptom presentation. Dysfunction at the blood brain barrier can facilitate leakage of proteins into the bloodstream in the early stages of neurological disease. Similarly, peripherally-produced proteins may also serve as warning signatures. Therefore, the final aim of this thesis is to conduct an assessment of blood protein signatures of incident neurological diseases and associated morbidities. In Chapters 1-3, I provide an overview of brain health and disease, blood-based molecular measures and key statistical approaches. In Chapter 4, I detail the population cohorts used in this thesis, before outlining my research aims and chosen methodologies in Chapter 5. In Chapter 6, I study serum measurements of S100 calcium-binding protein β (S100β) – a well-characterised marker with links to neuroinflammation and brain disease. I map the epigenetic and genetic signatures of this protein and test for evidence of a putative causal relationship between the protein and Alzheimer’s dementia. Chapter 7 extends this approach via a proteome-wide analysis. Instead of focusing on a single candidate biomarker, I conduct MWAS of 4,235 plasma proteins, identifying 2,928 associations (n ≥ 778 individuals). I also scan the proteome against fifteen brain health traits, identifying 405 associations involving 191 proteins. I integrate these signatures to highlight potential pathways between the methylome and proteome that may have relevance to brain health. In Chapter 8, I consider 953 possible plasma proteins for protein EpiScore development (N in the training set ranged from 706 to 944 individuals). I evaluate these EpiScores in independent populations, with 109 statistically significant EpiScores taken forward and modelled as biomarkers of incident diseases in 9,537 individuals. I build on this work in Chapter 9, where I generate protein EpiScores for GDF15 and NT-proBNP, which are two leading cardiovascular disease (CVD) markers implicated in brain health. I use a much-expanded sample size (n ≥ 16,963) to train these scores and show that they replicate protein-disease associations and associate with brain health outcomes. Finally, in Chapter 10, I test individual protein associations with 23 incident morbidities and death. I map whether proteins are markers for multiple neurological diseases, or specific to singular diseases. I then create ProteinScores for 10-year onset stratification of each incident outcome. ProteinScores for Alzheimer’s dementia and Parkinson’s disease are amongst the best-performing 10-year onset scores. The work done in this thesis provides information to help us identify those at the highest risk of developing neurological diseases (and associated morbidities), up to a decade prior to onset. My findings also tell us about the individual protein and DNAm patterns that associate with brain health and disease. Taken together, these results indicate that profiling epigenetic and proteomic information from our blood may improve our understanding of brain ageing. This work sits within the ethos of early detection and prevention, which should be at the heart of healthcare as we age

    Fanconi anaemia and LINE-1 retrotransposition in the mammalian genome

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    Transposable elements (TEs) are discrete, repetitive sequences of DNA that mobilise within genomes. For decades, TEs were dismissed as “junk DNA”, however, it is now clear that these elements have the potential to trigger genome instability, cause disease and shape the course of genome evolution. L1 elements constitute the only autonomous elements which remain active in the human genome and comprises approximately 17% of human DNA. As a retrotransposon, L1 canonically mobilises through a “cut and paste” mechanism called target primed reverse transcription (TPRT). Due to the deleterious impacts of L1 activity, mammalian cells have evolved a range of mechanisms to supress the mobilisation of these elements. The interactions between L1 elements and the host factors which regulate them are therefore an area of active research. Several DNA repair genes have shown potential as regulators of L1 activity. Moreover, in cell lines deficient in non-homologous end-joining, L1 has shown the potential to retrotranspose without its ORF2p endonuclease, which is usually a requirement for canonical TPRT. This retrotransposition has been termed endonuclease independent (ENi) retrotransposition, and takes place at unrepaired double stranded breaks in the DNA. Interestingly, several DNA repair factors have also been identified as potential regulators of L1 retrotransposition (both positive and negative), including a number of proteins from the Fanconi Anaemia pathway. The relationship between these factors and L1 has yet to be fully characterised, and it remains to be seen whether L1 can exploit other DNA lesions in the way that it utilises DSBs in ENi retrotransposition. This thesis aims to further investigate the relationship between L1 retrotransposition in the mammalian genome and DNA repair factors, particularly those comprising the Fanconi Anaemia pathway. Using cultured cell retrotransposition assays, I systematically tested a battery of mutant element in cells deficient in different proteins of the FANC pathway. In this way, I establish that ENi retrotransposition can be observed in a FANC background. I also demonstrate that FANC A deficient cells support retrotransposition of several L1 mutants which are immobile in parental cell lines. This includes elements with severe ORF1p mutations, mutations in the ORF2p endonuclease domain and mutations in the ORF2p PIP box. Despite testing a range of cell lines deficient in different DNA repair factors, including cells deficient in a range of FANC proteins, the retrotransposition of ORF1p, PIP and mutants appears to be unique to FANC A. My results are potentially indicative of a unique mechanism of retrotransposition in FANC A cells, a phenomena which has precedence in the ENi pathway of retrotransposition. Mass spectrometry of immunoprecipitated T7-tagged ORF1p, both in FANC A and parental cells, demonstrated that a different selection of host factors interact with ORF1p in the two cell lines. Several of these have not been previously identified as L1 interactors, including YTHDF2, a protein which binds and destabilises m6A-containing RNA. Previous reports suggest that YTHDF2 regulates the stability of RNA:DNA hybrids in vivo, and associates with R loop containing loci. Through co-immunoprecipitation of YTHDF2 with ORF1p, I confirm that the protein interacts with L1 elements in vitro

    Injuries and illnesses in golfers and returning to play following orthopaedic surgery

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    This thesis represents a discussion and critical appraisal of a selected number of research articles published in international peer-reviewed journals in the field of sports medicine and orthopaedic surgery. This work reflects over 5 years of dedication and passion in the field of golf medicine. The research is novel in a number of domains including assessing rates of COVID-19 in elite golfers, rates of returning to golf following orthopaedic surgery, and introducing new methods to this field. This body of work was initially planned to be focussed on the injuries of elite golfers however, two unique scenarios arose early in the process. The first was the COVID-19 pandemic and the need for evidence-based protocols for conducting professional golf events. The second was the opportunity for international collaboration around returning to golf following orthopaedic surgery which developed during the 2nd International Congress for Golf and Health. Therefore, this thesis is divided into two themes; the first on injuries and illnesses in golfers and the second on returning to golf following orthopaedic surgery. The thesis contains; two retrospective studies, four prospective studies, one prospective study protocol, one systematic review, one systematic review/meta-analysis, one narrative review, one consensus statement, one letter to the editor and one infographic. It flows in chronological order from theme one into theme two which represents the strategy in place moving from one project to another and the interconnected nature of each study. There was a small amount of overlap as theme two began and theme 1 concluded and this represents the opportunity to begin collaborative work following the golf and health congress. Each study is critically appraised in turn covering the aims and objectives, methodology, results and conclusions as well the contribution of the study to the literature and my own contribution. This thesis builds on existing research, identifies knowledge gaps, and presents reviews and original research that contribute to and enhance knowledge in the area of golf injury and illness.

    Detection of developmental deficits in epileptic children using multimodal tensor decomposition techniques

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    Early childhood epilepsy can affect the child’s development and lead to developmental deficits. Early detection and intervention are key to enabling the child to develop normally. Resting state electroencephalogram (EEG) and Magnetic resonance imaging (MRI) are the main tools clinicians use to diagnose children with epilepsy. This motivates us to take advantage of these available data and jointly analyse them to explore the features related to developmental deficits and predict the developmental scores of newly-onset patients. In particular, our work considers EEG information, sMRI volumetric data, and psychometric evaluation scores. We use matrix-tensor decompositions to analyse the shared features between each modality all at once. This allows us to investigate the occurrence of shared profiles in EEG and sMRI related to developmental impairment. Hence, this thesis develops data fusion methods based on well-established tensor decomposition methods (canonical polyadic decomposition, CPD; block term decomposition, BTD; and Tucker decomposition, TD). The methods are validated in a publicly available dataset with healthy children (Child Mind Institute: CMI) and, more importantly, in a local dataset of preschool children with epilepsy (NEUROPROFILE: Neu). First, the thesis focuses on a CPD data fusion model, which decomposes the multi-way data into a sum of rank-one factor matrices with the subject factor shared across three modalities. The model is optimised via grid search. The CPD model reveals distinct features associated with developmental deficits that agree with prior clinical knowledge. Then, we expand the model through direct projection to predict the developmental scores from EEG and sMRI data. A support vector machine (SVM) is used as a benchmark to compare the predicted score performance. The result reveals CPD model is better at estimating the developmental scores than the SVM. The CPD shows the feasibility of score prediction but still lacks the ability to correctly identify the deficits, which highlights the need for a more flexible data fusion model. Next, the thesis adopts block term decomposition (BTD) to bring in additional flexibility in the modelling of the EEG tensor data. In BTD (Lᵣ,Lᵣ, 1), one mode of interest is fixed to rank one while the others vary together to rank L. Subjects with missing scores and more sMRI regions and sub-scores are included in this analysis. Bayesian optimisation is applied to reduce the hyperparameter optimisation time. The results show that BTD (Lᵣ,Lᵣ, 1) can extract additional features related to the deficits that the CPD model does not pick up. Then, we built a model to predict the developmental scores. Overall, the prediction from BTD is generally better than the CPD. However, the result shows both models may not be fully compatible with EEG tensors and suggests the need for a better-fit model. Therefore, we adopt TD as a flexible model for the EEG data. TD can decompose tensors into factor matrices with different ranks interacting through a core tensor. However, TD without constraints is not unique. Thus, we promote the sparseness in the TD core tensor in our joint decomposition. In addition, we use structural connectivity information in the form of diffusion tensor imaging (DTI) as a graph regularisation to the data fusion model to promote interpretability. The effects of each constraint are investigated, and the most stable result is extended to predict the scores. Since not all the patients have DTI data, the score prediction is executed for both patients with and without DTI. Implementing the DTI graph regularisation is found to result in predicted scores in a more plausible range. The sparse core TD with graph regularisation performs best with the Neu dataset. However, some deficit patients are estimated to score within the normal range, which does not fulfil the aim of identifying deficits accurately. In addition, and given that the BTD (Lᵣ,Lᵣ, 1) tensor decomposition is closely related to CPD, we investigate and expand the existing principle of CPD core consistency diagnosis (CORCONDIA) to BTD (Lᵣ,Lᵣ, 1). BTDCORCONDIA is built to assist in determining the number of components and the data compatibility to the model. The model is tested with simulated and real EEG tensor data. We show that data generated with a unique core compatible with BTD (Lᵣ,Lᵣ, 1) results in BTDCORCONDIA values of ∼ 100%. In contrast, incompatible data will lead to low values. The result confirms that it is possible to perform a core consistency diagnosis to check the compatibility between the model and data in BTD. In summary, multimodal data fusion of paediatric brain data through matrix-tensor decomposition offers a new approach to studying the shared underlying profiles and developmental status of children with neurological diseases such as epilepsy. This could be a stepping stone for future research seeking to integrate and adopt data fusion approaches as additional tools for clinicians to prioritise children for an exhaustive assessment of their development

    Symmetries of Riemann surfaces and magnetic monopoles

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    This thesis studies, broadly, the role of symmetry in elucidating structure. In particular, I investigate the role that automorphisms of algebraic curves play in three specific contexts; determining the orbits of theta characteristics, influencing the geometry of the highly-symmetric Bring’s curve, and in constructing magnetic monopole solutions. On theta characteristics, I show how to turn questions on the existence of invariant characteristics into questions of group cohomology, compute comprehensive tables of orbit decompositions for curves of genus 9 or less, and prove results on the existence of infinite families of curves with invariant characteristics. On Bring’s curve, I identify key points with geometric significance on the curve, completely determine the structure of the quotients by subgroups of automorphisms, finding new elliptic curves in the process, and identify the unique invariant theta characteristic on the curve. With respect to monopoles, I elucidate the role that the Hitchin conditions play in determining monopole spectral curves, the relation between these conditions and the automorphism group of the curve, and I develop the theory of computing Nahm data of symmetric monopoles. As such I classify all 3-monopoles whose Nahm data may be solved for in terms of elliptic functions

    The development and understanding of iron-catalysed C–H functionalisation reactions

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    C–H functionalisation reactions allow for an efficient and sustainable manner of increasing molecular complexity. The application of Earth-abundant metal-catalysed methods is dependent on systems that are reliable, predictable, and easily accessible. However, current methods typically show limited reaction tolerances, often have little mechanistic understanding, and rely on highly sensitive reagents and pre-catalysts. An iron-catalysed C–H borylation reaction of arenes has been developed using only commercially available, bench-stable reagents (Scheme A-1). The reaction demonstrates the largest functional group tolerance of any Earth-abundant metalcatalysed C–H borylation reaction and provides insight into observed side reactivity. Mechanistic studies of an iron halide-catalysed system for the directed C–H borylation of 2-phenylpyridine derivatives identified iron to be an initiator in a reaction driven by hidden Brønsted acid catalysis. The development of parallel non-metal-catalysed reaction conditions and methods for main group catalyst activation has also been demonstrated. Mechanistic studies on an iron-catalysed hydrogen isotope exchange (HIE) reaction of heteroarenes and alkenes identified the modes of exchange and a novel method for accessing iron-hydrides in situ. Reaction selectivity and the isolation of catalytic intermediates, including products of C–H metallation, suggested deuterium incorporation was proceeding through a selection of reaction pathways

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