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The impact of host community composition on pathogen hazard in a tick-borne disease hotspot
No full textAbstract not currently available
Harnessing brain imaging data to personalise management of fatigue in inflammatory arthritis
Get PDFRheumatoid arthritis and psoriatic arthritis are chronic inflammatory conditions in which chronic fatigue persists in the majority of patients despite successful management of disease activity. This multidimensional, disabling fatigue correlates with various brain characteristics. Current treatments inadequately address fatigue, emphasising the importance of exploring its neural underpinnings and what potential imaging the brain has to inform the management of fatigue in these inflammatory arthritis conditions. To do so, I applied brain measures to stratify inflammatory arthritis patients into fatigue-related subgroups with potentially amendable biological differences, identify correlates of different subdimensions of fatigue, and predict fatigue follow-up after fatigue-specific or pharmacological treatments in different inflammatory arthritis cohorts of rheumatoid and psoriatic arthritis. I hypothesised that there are (1) subtypes of fatigue in patients with rheumatoid arthritis, illustrated by distinct subgroups stratified by a relationship between neuroimaging brain characteristics and fatigue; (2) statistically significant correlates of subcomponents of fatigue; (3) statistically significant predictors of fatigue scores after non-pharmacological treatments in rheumatoid arthritis; (4) statistically significant predictors of fatigue scores after pharmacological treatments in rheumatoid and psoriatic arthritis; (5) models that can predict individual fatigue outcomes above chance in a trial of non-pharmacological treatments in rheumatoid arthritis using machine learning to combine multiple neuroimaging and clinical variables.
I found a link between neuroimaging brain connectivity and distinct subgroups in rheumatoid arthritis related to fatigue subdimensions, albeit only within a specific cohort. Associations emerged between brain imaging metrics and baseline fatigue subcomponents, showing varied correlations with different metrics. In rheumatoid arthritis patients undergoing exercise or cognitive-behavioural interventions, baseline brain imaging predictors of fatigue centred on structural connectivity from the precuneus to the anterior cingulate cortex. In contrast, I did not find significant neuroimaging predictors of fatigue in rheumatoid arthritis patients who started a new disease-modifying antirheumatic drug. However, I did find such predictors in psoriatic arthritis patients, encompassing cortical thickness of the visual pericalcarine cortex and functional connectivity within the default mode and salience networks, involving the inferior parietal lobule and anterior cingulate cortex. Finally, models using diverse neuroimaging and clinical modalities along with different machine learning algorithms outperformed models using solely the baseline median fatigue. Significantly, these models did not surpass chance level or replicate their utility in usual care patients in an independent rheumatoid arthritis cohort. Overall, despite not finding a model that can predict individual fatigue outcomes, this research advanced our understanding by pinpointing different fatigue-related brain circuits, delineating associations with subcomponents, and identifying group-level predictors of fatigue. If such findings are utilised by future studies using molecular and brain stimulation techniques, neuroimaging can offer innovative solutions to patients to significantly improve their quality of life
Characterisation of the neurobiological phenotype of pain in psoriatic arthritis
Get PDFPsoriatic arthritis (PsA) is a prevalent immune-mediated inflammatory arthritis marked by chronic inflammation in both articular and periarticular regions. Advances in understanding the immunopathogenesis have paved the way for the development of advanced immunotherapies, effectively controlling inflammation and the associated tissue damage linked with PsA. Nevertheless, the chronic pain remains a significant issue for individuals with PsA. Chronic pain, frequently linked with musculoskeletal conditions, represents a substantial burden on those affected, leading to diminished quality of life and increased mortality.
The classical pain mechanisms involve damage to peripheral tissues (nociceptive) or peripheral nerves (neuropathic), causing pain. In PsA, nociceptive pain mechanisms are classically considered to prevail, primarily due to peripheral inflammation. Recently, however, a novel pain mechanism, described as nociplastic pain, characterised by dysfunctional nociception processes within the central nervous system (CNS) has been identified. This type of pain lacks evidence of peripheral damage. Fibromyalgia serves as a prototype for nociplastic pain. Specific neurobiological features are identified in fibromyalgia through functional neuroimaging and quantitative sensory testing (QST). Clinically, fibromyalgia (nociplastic pain) appears to co-exist in PsA, however there is no objective evidence to support this observation yet.
This thesis's primary hypothesis is that chronic pain in PsA manifests as a mixed pain state in individuals with a substantial pain burden, potentially explaining the high rates of chronic pain in PsA. To test this hypothesis, this study examines nociplastic pain features and their neurobiological correlations within a wellcharacterised cohort of 50 individuals with PsA with active disease and employing QST and functional MRI to objectively assess nociplastic pain.
The study's evidenced a heightened pressure pain sensitivity at articular and entheseal sites among participants experiencing pronounced nociplastic pain, indicating peripheral sensitisation where inflammation prevails. Observations also unveil altered functional connectivity in subjects with PsA with substantial nociplastic pain, particularly within the insula and DMN regions. Intriguingly, distinct features in the parahippocampal and visual areas predominate within this subgroup, reflecting the complexities of pain perception. This individual and condition-specific diversity defines a distinctive “pain signature”. These findings present an opportunity to pinpoint specific neurobiological markers in PsA.
Despite available evidence suggesting the role of inflammation, the mechanisms sustaining the interaction between the nervous and immune systems remain elusive. Chronic inflammation in rheumatoid arthritis relates to altered connectivity in the inferior parietal lobule (IPL), a similar phenomenon is identified within this study participants with PsA. However, peripheral circulating pro-inflammatory cytokines did not exhibit significant associations with the nociplastic pain neurobiological features investigated in this study.
To date, this study represents the first exploration into the neurobiological features of nociplastic pain in PsA, employing advanced neuroimaging techniques alongside an extensive QST protocol. The findings suggest a distinct pain signature of PsA, sharing characteristics with fibromyalgia and rheumatoid arthritis. To confirm these findings and gain further insights into the role of inflammation in nervous system sensitisation, additional studies are needed. Ultimately, a better understanding of pain mechanisms in PsA will translate into improved patient management and a better quality of life for those affected by this challenging disease
Thermal aging of three-way catalysts: in situ characterisation studies
No full textAbstract not currently available
Gut microbial regulation of organismal health through Tachykinin in Drosophila
Get PDFThe complex relationship between the gut microbiota and host physiology is a multifaceted area of investigation with profound implications for systemic health and ageing. Despite residing predominantly in the gut, the microbiota holds the potential to systemically impact overall host health, including complex processes like ageing. This prompts the question, by what mechanisms does the gut microbiota systematically influence the host? Host-derived hormones, particularly gut peptides secreted by enteroendocrine cells, emerge as potential mediators for conveying the microbiota's influence on lifespan and metabolism. However, the exact molecular mechanisms through which microbiota regulate host enteroendocrine signalling, and the relevance of this in systemic host health, is unknown.
Drosophila melanogaster was used as an in vivo model to study the impact of microbiota on host via enteroendocrine signalling. To address this, I used a unique approach, integrating germ-free and gnotobiotic conditions with targeted genetic manipulations. This strategy provided a platform to unravel the specific roles of enteroendocrine peptides in the context of microbial influence. RNAseq analysis and fluorescence staining showed that the microbiota shapes the expression levels of gut peptides, and the number EE cells present in the gut. In particular, the differentially expressed host derived gut peptide, tachykinin (TK), proved to be a strong candidate to mediate the influence of microbiota on host health. Germ-free and conventional flies were used to determine if TK responds to microbial cues to regulate complex host phenotypes such lipid metabolism, lifespan, starvation resistance, feeding behaviour and fecundity. The focus was specifically on two phenotypes: lifespan and lipid metabolism. In the presence of microbiota, ubiquitous RNAi against TK extended lifespan, but eliminating the microbiota had no additive effect. TK knockdown also increased lipid levels in conventional flies, but this effect was reversed in germ-free flies, demonstrating that the microbiota regulates complex host traits through a TK mediary. To refine which members of the microbiota interact through TK, gnotobiotic flies mono-colonised by either the gut symbiont Acetobacter pomorum, or Lactobacillus brevis were used. A. pomorum was found to strongly modulate lifespan and lipid levels via TK, while L. brevis had a marginal impact. It was further determined that in order to achieve lifespan modulation, A. pomorum regulated TK expression in the gut, which then targets its receptor TKR99D in the brain. In terms of potential mechanisms mediating the impact of the interaction between A. pomorum and TK - feeding and egg laying assays suggest that nutrient restriction and reduced reproduction can be excluded but impacts on 4E-BP and Akt expression suggest roles for the IIS/TOR signalling network. In support of this, ablation of insulin producing cells phenocopies the TK knockdown lifespan phenotype. However, knockdown of TK in null-dFOXO mutants showed that, while dFOXO is required for TK to modulate lifespan, it is not required for microbial lifespan regulation, suggesting that other interacting mechanisms are likely to be involved.
In conclusion, this thesis implicates TK as a pivotal mediator of the effect of microbiota on host lifespan, setting the stage for innovative approaches to delay ageing and improve healthspan
Gender-STEM stereotypes: a cross-cultural, mixed-methods exploration of women’s STEM pathways between the UK and China
Get PDFWomen’s underrepresentation in higher education and careers in science, technology, engineering, and mathematics (STEM) fields remains a persistent global problem. Grounded in social psychological theories related to gender stereotypes, this cross-cultural thesis aims to understand the reasons for British and Chinese women’s underrepresentation. A review of existing empirical research highlights gaps in understanding British and Chinese women’s underrepresentation in STEM disciplines and careers identified gaps into why and how women maintain careers in these fields. Therefore, this study aimed to 1) identify British and Chinese women’s explicit and implicit gender-STEM stereotypes and the factors impacting these stereotypes; 2) explore what factors positively influenced women studying to PhD level in STEM fields; 3) investigate and interpret patterns of how Chinese Eearly career researchers (ECRs) achieve in their STEM fields. A sequential explanatory mixed-methods design was conducted. The first phase used a quantitative survey and lab-based Implicit Association Test to compare the explicit and implicit gender-STEM stereotypes and attitudes toward STEM fields of British and Chinese women (n = 113). Using a 2 x 2 ANOVA design, Chinese women in the cohort had higher explicit gender-STEM stereotypes than British women, and women studying in STEM fields had lower explicit attitudes on STEM subjects than women not studying in STEM fields. There were no significant main effects or interactions of nationality and STEM study on the implicit measure. However, a planned independent contrast found that Chinese women studying STEM subjects had lower implicit gender-STEM stereotypes than women not studying STEM. The second phase included qualitative focus groups with women from the UK (n= 5) and China (n= 6) studying STEM in the UK, and interviews with Chinese women working successfully in their STEM fields (n = 4) to more deeply understand why women’s persistence in higher level education and careers in STEM. Analyses uncovered factors influencing women’s attrition in STEM fields and possibilities for how women could maintain and achieve at higher level of education and careers in STEM fields. This mixed-method, cross-cultural, and interdisciplinary thesis makes a significant contribution through uncovering common barriers to STEM fields, women’s cognitive dissonance regarding gender-STEM stereotypes, and cultural differences suggesting “glass ceilings” effects in the UK and the pressures from the “ground floor” from Chinese family and society. Policy and educational recommendations are provided, including the importance of embedding STEM career knowledges early, policies such as flexible working, successful female role models in STEM, and the role of social media in raising women’s career profiles and widening their networks
Combining T2K with other experiments to better constrain oscillation parameters
Get PDFThis thesis presents an analysis of T2K data using a new external reactor constraint from Daya Bay instead of the regular one-dimensional Gaussian provided by the Particle Data Group (PDG). Both the PDG and Daya Bay data sets can be used to update the prior of given parameters in the T2K analyses. Applying Daya Bay’s two-dimensional constraint on the mixing angle θ₁₃ and mass splitting Δm² ₃₂ improves the constraint on the mass splitting parameter by 25% in normal hierarchy and 18% in inverted hierarchy compared to using the PDG external prior. Furthermore, denoted with a Bayes factor value which compares two hypotheses using the posterior results, it was found that there was a small increase in the preference for normal hierarchy over inverted hierarchy, B(NH/IH): PDG = 2.77 and Daya Bay = 2.79. There was a slightly larger increase for the upper octant in the octant degeneracy, B(UO/LO): PDG = 2.27 and Daya Bay = 2.38. The thesis also describes development work towards the first full joint-fit between two long baseline experiments, T2K and NOvA, showcasing the increase in statistical sensitivity for the oscillation parameters and the potential to solve some of the current degeneracies limiting the sensitivity of both experiments. Finally, there is an introductory insight into an alternate parameterisation of neutrino oscillations that could be used to better understand the constraint from the T2K data
The impact of economic stimulus package on the Chinese economy
Get PDFChina’s stimulus package after the global financial crisis in 2008 rapidly boosted its GDP. However, it also raised concerns about its long-lasting and unintended consequences that have reduced China’s growth potential. This thesis aims to explore the effect of China’s stimulus package from macro-, industry-, and firm-level perspectives. The first topic investigates the growth effects of the stimulus package. Based on province-level high-frequency data and a “heterogeneous panel” econometric method - Pooled Mean Group (PMG), the results reveal a significant long-term negative association between the stimulus package and GDP growth in China, despite positive short-term effects. The second topic examines how the stimulus package, when interacting with government intervention, influences industry investment and its subsequent outcomes. Using province-industry observations from 2003 to 2016 and employing the Difference-in-Differences (DID) strategy, I find that government backup encourages industries to invest more, at the expense of worsening aggregate efficiency. The third topic studies how the stimulus-driven credit boom affects the bank loan financing of firms. Through Chinese listed firm data from 2003 to 2018, the finding indicates that political connections serve as an implicit guarantee, enabling firms with these connections to obtain and maintain favourable treatment from bank lending after the stimulus package. Overall, this thesis supports the view that the stimulus package led more resources to being allocated to industries and firms with government backup, which, in turn, contributed to the slowdown in Chinese growth in the recent decade
Using FLIM-FRET to visualise self-generated gradients in cancer cells
No full textAbstract not currently available
