324139 research outputs found
Sort by
Cardiometabolic biomarkers in blood and the risk of cerebrovascular disease
No full textBackground: Studies have reported inconsistent associations, with little causal evidence, between metabolites and ischaemic stroke. The aim of this DPhil project is to understand the molecular mechanisms underlying ischaemic stroke and to identify predictive and causal biomarkers based on the sociodemographic, lifestyle, clinical, molecular, and genetic data in UK Biobank (UKB).Methods: I studied 249 plasma metabolites using the nuclear magnetic resonance platform from UKB (N = 274,355, median 13.8 follow-up years). First, I studied the association of each of these metabolites individually with ischaemic stroke using Cox proportional hazards regression adjusting for age, sex, ethnicity, lipid modifying medication, fasting time, spectrometers, assessment centres, smoking status, alcohol intake, dietary supplement use, 13 dietary variables, physical activity, body mass index, prevalent diabetes, and systolic blood pressure. Second, I applied extreme gradient boosting model (XGBoost) and random survival forests (RSF) to assess the additional predictive values of metabolites over traditional risk factors. The Boruta algorithm was used to procure the relevant metabolites related to ischaemic stroke. Finally, bidirectional two-sample Mendelian randomisation (MR) was used to evaluate the causal relationship of identified metabolites with ischaemic stroke. Genome-wide association studies were conducted to determine genetic instruments for selected metabolites in white British ancestry of UKB (N = 230,197, more than twice the participants of any previous study), and the largest summary-level data for ischaemic stroke were from the GIGASTROKE Consortium in populations of European descent (62,100 cases and 1,234,808 controls). The false discovery rate correction was used to adjust for multiple testing.Results: After adjusting for multiple testing and potential confounders, 40 metabolites were associated with incident ischaemic stroke in Cox regression, including albumin, phenylalanine, very low-density lipoproteins (VLDLs), low-density lipoproteins, and high-density lipoproteins (e.g. albumin: hazard ratios 0.87 per 1 standard deviation increment, 95% CI 0.84-0.91; phenylalanine: 1.05, 1.02-1.10). The metabolites did not materially add predictive information over conventional risk factors for incident ischaemic stroke by XGBoost and RSF in the whole population, older adults, men, and women separately. Eight relevant metabolites with ischaemic stroke were selected using the Boruta algorithm, and albumin overlapped with the 40 metabolites from the previous analysis. Across the 47 metabolites, a total of 6,137 independent genome-wide significant associations were detected, including 3,025 novel variants (49.3%). The genetically predicted level of three VLDL ratios exhibited consistent direction of effect across univariable MR methods and cholesteryl esters to total lipids ratio in chylomicrons and extremely large VLDL further demonstrated a statistically significant direct effect on ischaemic stroke in the multivariable MR. Additionally, genetic liability to ischaemic stroke had little effect on the metabolites.Conclusion: These findings substantiate the importance of metabolites as potential modifiable risk factors for ischaemic stroke. Compared with the conventional risk factors, the metabolites did not improve the risk prediction of ischaemic stroke. The causal relationships between three VLDL ratios and ischaemic stroke indicated that indirect measurement of lipoprotein concentrations may be of greater importance than their direct measurement. This thesis makes several original contributions. First, it is the first to combine large-scale prospective analyses, high-dimensional metabolomic profiling, machine learning, and advanced causal inference methods (including the recently developed multivariable MR framework) in a single, unified investigation of ischaemic stroke. Second, it introduces an expanded GWAS with more than double the previous sample size to generate stronger genetic instruments, thereby enabling more robust Mendelian randomisation analyses of causal effects. Third, it establishes novel genetic associations for key metabolites and provides new insights into their biological architecture and potential pathways underlying ischaemic stroke risk. Future studies should focus on causality and prediction using a wider range of metabolites on ischaemic stroke subtypes in more diverse populations
A large interlaboratory electron diffraction study of monolayer graphene
Get PDFStandardisation of data collection and analysis is essential to enable commercialisation of 2D materials in a wide range of technologies. Selected area electron diffraction (SAED) in the transmission electron microscope (TEM) is one of the key methods for distinguishing monolayer from bilayer and few-layer graphene by comparing the 1st and 2nd order diffraction spot intensities. Yet there are many factors that can affect the reliability of data collection and interpretation, causing the measurement of monolayer samples to deviate from the literature boundary condition of I{2¯110}/I{11¯00}< 1 for monolayer graphene (1LG). Here we present the results of a large interlaboratory SAED comparison study, where 15 international laboratories measured and analysed nominally identical samples of chemical vapour deposited graphene. Large variations were observed in the measured ratios of diffraction spot intensities, with the largest variance associated with poor quality SAED data resulting from inadequate specimen handling and storage. To inform the reliable determination of monolayer thickness from SAED patterns we provide a description of best practice for specimen handling, TEM operation, data collection and analysis. This work was undertaken within VAMAS Technical Working Area 41: Graphene and related 2D materials—Project 9, the results of which have been directly incorporated into ISO/TS 21356–2 for the characterisation of graphene sheets. We find that when this methodology is followed, 1LG can be distinguished from bilayer or thicker material with high confidence where analysis of a single SAED pattern gives I{2¯110}/I{11¯00}< 1.2, even in the absence of precise specimen tilting
An actionable framework for AI‐ready data
Get PDFData is the foundation of AI. Poor‐quality data drive up costs and can lead to hidden problems for AI models, especially in complex fields such as healthcare and manufacturing. Meanwhile, biased data negatively affect the performance of AI models, and untested evaluation datasets can result in false positives or overestimates of model accuracy. For data publishers to realize their true potential in supporting the AI ecosystem and its impacts, they should take measures to ensure that their datasets support AI practitioners' needs; in other words, their data should be made AI‐ready. In this article, we present a framework for data publishers to follow to make their datasets AI‐ready. The framework provides specific, actionable guidance based on previous work and experience at the Open Data Institute and augmented with insights from literature and discussions with a range of experts. We first define AI‐ready data before briefly discussing a selection of frameworks in the literature and where they are insufficient. We then provide a visual snapshot of our framework for AI‐ready data, and a subsequent in‐depth discussion of its criteria. Finally, we demonstrate the usage of our framework with a number of example datasets. We conclude by discussing the further steps that should be taken for the entire open data ecosystem to be made AI‐ready in order to realize its true potential in supporting an innovative future
From Dungannon to Drumcree: street politics and the troubles
No full textThis thesis examines protests and riots during the Northern Ireland Troubles. This is a study of the wide range of popular activity (everything from peaceful demonstrations to running battles) which took place during the high points of political mobilisation in the North during the conflict. Essentially, it questions who (the groups organising and individual participants), what (parliamentary and extra-parliamentary methods), why (structural and contingent factors and individual agency), where (spatial patterns of protest and the conflict geography) and how (calculations, consequences and control). Who protested? Why did they protest? What did they protest? What did they do? What happened? Where were the flashpoints? How were demonstrations and civil disorder managed? How effective was street protest? It studies protest events and episodes in forensic detail; the processes of political and paramilitary mobilisation; the makeup of protest movements; the lives and trajectories of activists, demonstrators and rioters; internal dynamics and intra-movement competition; women’s activism; peaceful and violent protest action, including symbolic and ritualistic practices, and its objective and function; policing of protest and control mechanisms; the risks and costs of activism to social movements; and the effects and efficacy of the protest tool. It sees street politics as part of a wider political and territorial struggle. It demonstrates how politics in the streets was bound up with micro- and macro-territorial aspirations (and a territorial practice) and competing visions for a democratic political settlement. It challenges common understandings about community consent and control, levels of support and power dynamics. It further demonstrates that gendered and generational, conservative and radical and constitutional and violent divisions are poorly conceived. It provides insight on action repertoires. Ultimately, this thesis provides an episodic history of street politics during the Troubles by examining the composition, characteristics, objectives, methods and outcomes of individual events and political campaigns
Detailed theoretical modelling of the kinetic Sunyaev-Zel'dovich stacking power spectrum
Get PDFWe examine, from first principles, the angular power spectrum between the kinematic Sunyaev-Zel'dovich effect (kSZ) and the reconstructed galaxy momentum — the basis of existing and future “kSZ stacking” analyses. We present a comprehensive evaluation of all terms contributing to this cross-correlation, including both the transverse and longitudinal modes of the density-weighted velocity field, as well as all irreducible correlators that contribute to the momentum power spectrum. This includes the dominant component, involving the convolution of the electron-galaxy and velocity-velocity power spectra, an additional disconnected cross-term, and a connected non-Gaussian trispectrum term. Using this framework, we examine the impact of other commonly neglected contributions, such as the two-halo component of the dominant term, and the impact of satellite galaxies. Finally, we assess the sensitivity of upcoming CMB experiments to these effects and determine that they will be sensitive to the cross-term, the connected non-Gaussian trispectrum term, the two-halo contribution and impact of satellite galaxies, at a significance level of ∼ 4-6σ. On the other hand, the contribution from longitudinal modes is negligible in all cases. These results identify the astrophysical observables that must be accurately modelled to obtain unbiased constraints on cosmology and astrophysics from near-future kSZ measurements
The application of a fluctuating charge model for boron nitride networks
Get PDFA fluctuating charge model (FCM) is developed to consider two-dimensional networks of boron nitride. In the FCM the charge on each atom site is controlled by parameters linked to the atom electronegativity and the interactions with other atoms (the coordination environment). The charge held on each atom site is a strong function of the local (first shell) coordination environment. The site charges are shown to be in excellent agreement with those extracted from independent densityfunctional theory-based calculations. The behaviour of the site charges is investigated as a function of the network topology and site disorder. In the first case, specific defects (both site and topological) are introduced and the spatial “decay” of the local charge to bulk values is assessed. In the second, highly disordered (amorphous) networks are generated and the distribution of site charges is studied as a function of the degree of topological and site disorder (characterised by the fraction of sixmembered rings and mean boron-nitrogen coordination numbers respectively). Domains of high and low charge are observed to form across a wide range of topological disorder
Case study using mental imagery with an asylum seeker suffering with post-traumatic stress disorder to female genital mutilation and multiple instances of sexual violence
Get PDFThis paper describes a single case study of a female asylum seeker presenting at a specialist clinic for women with female genital mutilation (FGM). The patient presented with post-traumatic stress disorder (PTSD) to multiple events due to her 45-year history of sexual and physical abuse. She also had intense feelings of being contaminated due to the sexual abuse. Within the cognitive model, a cognitive restructuring and imagery modification protocol was used to treat the patient’s feelings of being contaminated. After that, imagery rescripting was used to address the patient’s many PTSD re-experiencing symptoms. Clinicians can often feel overwhelmed when working with patients who present with multiple, traumatic events spanning many years; it is hoped that this case study helps clinicians to feel more confident about working with this client group and with women with FGM. Key learning aims: (1) To be able to assess and treat survivors of multiple sexual assaults over many years using imagery rescripting. (2) To learn how to use cognitive restructuring and imagery modification to treat feelings of being contaminated. (3) For therapists to gain confidence with working with women who have experienced female genital mutilation
Evaluating land–sea linkages using land cover change and coral reef monitoring data: A case study from northeastern Puerto Rico
Get PDFLand cover change that leads to increased nutrient and sediment runoff is an important driver of change in coral reef ecosystems. Linking landscape change to seascape change is necessary for integrated land–sea management of coral reefs. This study explored the use of freely available satellite products to examine long‐term patterns of change across the land–sea continuum. We focused on northeastern Puerto Rico, where a widespread decline in live coral cover has occurred despite concomitant watershed reforestation that was expected to reduce land‐based threats. The aims of this study were (1) to examine whether these land–sea trends continued in 2000–2015 and (2) to assess the opportunities and limitations associated with using satellite data to inform land–sea management. We applied a Random Forest classifier on Landsat‐7 satellite imagery to assess changes in land cover and landscape development intensity, a spatial index to estimate land‐based pressure on nearshore marine ecosystems. We used field monitoring data to quantify benthic community change. We found that reforestation continued in 2000–2015 (+11%), suggesting reduced land‐based pressure on adjacent reefs in both northern (Luquillo) and eastern (Ceiba‐Fajardo) watersheds. Concomitantly, coral cover continued to decline, and a new aggressive expansion of peyssonnelid algal crust was recorded. Clustering analysis indicated that benthic monitoring sites in the same geographic regions (nearshore/offshore, north/east) followed similar community composition trajectories over time. Our results suggest that continued reforestation and the expected reduction in land‐based pressure have not been sufficient to halt coral cover decline in northeastern Puerto Rico. To improve the characterization and monitoring of the full causal chain from changes in land cover to water quality to benthic communities, advances in satellite‐based water quality mapping in optically shallow waters are needed. A strategic combination of remote sensing and targeted field surveys is required to monitor and mitigate land‐based stressors on coral reefs
A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models
No full textAdvances in experimental techniques allow the collection of high-resolution spatio-temporal data that track individual motile entities. These tracking data can be used to calibrate mathematical models describing the motility of individual entities. The challenges in calibrating models for singleagent motion derive from the intrinsic characteristics of experimental data, collected at discrete time steps and with measurement noise. We consider motion of individual agents that can be described by velocity-jump models in one spatial dimension. These agents transition between a network of n states, in which each state is associated with a fixed velocity and fixed rates of switching to every other state. Exploiting approximate solutions to the resultant stochastic process, we develop a Bayesian inference framework to calibrate these models to discrete-time noisy data. We first demonstrate that the framework can be used to effectively recover the model parameters of data simulated from two-state and three-state models. Finally, we explore the question of model selection first using simulated data and then using experimental data tracking mRNA transport inside Drosophila neurons. Overall, our results demonstrate that the framework is effective and efficient in calibrating and selecting between velocity-jump models and it can be applied to a range of motion processes
Developing and evaluating e-Learning to develop psychological practitioner digital competencies
Get PDFThis symposium presentation reports on the development and pilot evaluation of an e-learning programme designed to build digital mental health competencies among psychological practitioners and trainee clinical psychologists. It presents qualitative and quantitative findings demonstrating increased knowledge, confidence, and positive attitudes toward digital practice, while also highlighting areas for refinement and ongoing concerns about ethical, clinical, and risk issues in digital therapy delive