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Methods of characterising the process of early biomineralisation
Get PDFMature bone is a highly ordered structure composed of hydroxyapatite crystals uniformly arranged within regularly spaced fibrils of collagen, populated with several cell types. This arrangement produces a material with a unique combination of strength and resistance to fracture, as well as the ability to remodel, repair and regenerate in response to injury or changing load. Intrafibrillar mineralisation present in mature bone is a thermodynamically unfavourable process, suggesting highly controlled processes during early mineralisation, current knowledge of which is poorly understood. Evidence suggests extracellular vesicles (EVs) are involved in this early mineralisation process, potentially acting as a nucleating and stabilising agent in mineralisation, but the heterogeneity and poor characterisation of these nanoparticles limits the understanding of their role.
Whilst the heterogeneity of EVs as a population is unquestioned, identification of the presence or absence of subgroups within these populations has not been adequately investigated. Interrogation of individual EVs would allow the construction of a highly resolved map of EV characteristics. Collecting this data is the first step in identifying distinct populations within the EV secretome. From there, identification of the impact of these distinct populations and their attendant molecular characteristics, upon mineralisation would be a significant boost to therapeutic treatments for mineralisation abnormalities, such as osteoporosis, non-union fractures, and heterotopic ossification.
This thesis investigates new techniques for investigating the biochemical and physical characterisation of EVs, as well as the early mineralisation stages of osteoblast like cells, and the role of EVs therein. Here we apply the methods of x ray fluorescence (XRF), Raman spectroscopy and transmission electron microscopy (TEM) to mineralising cell cultures and EVs to elucidate the processes and characteristics of the early mineralisation process.
We utilise XRF to detect the presence of elemental ions in control compounds, with signal strength reliably corresponding to the proportion of elements present. When applied to mineralising cell cultures, a changing elemental composition across time points is observed. We have documented the presence of a calcium deficient, phosphorous dense material in early mineralisation, maturing towards an increased calcium presence in later time points. This suggests intermediate mineral phases are present in mineralising bone prior to the hydroxyapatite present in mature tissue. XRF was also used to quantify characteristics of mineralising cell culture, using automated image analysis to identify mineral nodule number and size, and observe the rapid mineralisation induced by coculture of osteoblasts with EVs.
In addition to these results, we have shown the correlation of Raman signal with the mineral content of bone, making it another potentially useful tool in the investigation of mineralisation. Attempts to incorporate molecular tweezers with Raman spectroscopy for the characterisation of individual osteoblast EVs were ultimately unsuccessful, however, lessons were identified for future application of both techniques.
Finally, improvements to current TEM techniques of EV imaging were demonstrated in this thesis, using gold nanoparticles to label exosome associated surface proteins, and a methylcellulose supporting film to maintain a spherical morphology.
The findings presented here offer insight into the early mineralisation process, as well as developing techniques to explore these findings further. Clarification of potential intermediate mineral stages can be further explored using the XRF and Raman spectroscopy techniques developed in this manuscript. The TEM protocols developed here may provide a more physiological insight into EVs, whilst the labelling process can be used to identify the presence of specific proteins. Automated imaging analysis techniques may be useful for high throughput imaging systems, identifying the impact of drugs or changes in conditions (e.g. hypoxia) upon mineralisation progression. Together, these techniques and results contribute to the current and future understanding of early mineralisation and may one day be exploited to improve medical outcomes for implants, cements, and diseases such as osteogenesis imperfecta
Artificial intelligence technology using smart phones for train passenger ride comfort
Get PDFThis thesis presents a novel approach to evaluating Ride Comfort (RC) in railway systems by integrating Machine Learning (ML) algorithms with data collected from smartphone sensors. Traditional methods for assessing RC, such as questionnaires and vibration-based measurements, have significant limitations, including reliance on subjective feedback, and complex logistics. These challenges are addressed by developing a scalable, cost-effective, and accurate framework that leverages modern smartphones' widespread availability and advanced capabilities.
The research begins by exploring the potential of ML algorithms in processing large datasets generated from both synthesised data using D-track simulations and real-world data collected via smartphones. The study adheres to the International Organisation for Standardisation (ISO) 2631 standard and the International Union of Railways (UIC) 513 for vibration measurement, ensuring the reliability and accuracy of the data. The ML models developed, including Convolutional Neural Network (CNN), K-means clustering, and ensemble techniques, are employed to quantify dynamic track stiffness, classify various train motions (such as roll, yaw, pitch, and bounce), and evaluate RC at individual points within the train.
A key innovation of this work is using crowd-sourced data from multiple smartphones with Graph Attention Network (GAT) to perform a comprehensive assessment of RC at the train level rather than merely at the individual passenger level. This approach facilitates the transmission of real-time data to a processing centre for subsequent analysis, generating valuable insights to improve passenger experience and operational efficiency, all while ensuring driver focus and maintaining safety standards. The study also demonstrates that this methodology significantly reduces the financial and logistical burdens typically associated with traditional methods while offering a more holistic and nuanced RC evaluation.
The findings of this research have broad implications for the railway industry, particularly in improving infrastructure maintenance, optimising train operations, and enhancing overall RC. By providing a robust framework for RC assessment, this thesis contributes to advancing intelligent transportation systems and supports the future development of more comfortable and efficient railway services. The use of advanced ML models, such as CNN and GAT, in conjunction with crowd-sourced data from multiple smartphones, enables a comprehensive and dynamic assessment of RC at both individual and train-wide levels. This approach allows for more accurate quantification of crucial factors such as track stiffness and train motion, which are critical to understanding and enhancing RC. The cost-effectiveness of the methodology, driven by the use of widely available smartphones, significantly reduces the financial and logistical burdens associated with traditional methods, making it accessible to a wide range of railway services. The research also aligns with international standards, ensuring its applicability across diverse operational contexts. Beyond the railway industry, the findings have broader implications for other modes of transport, such as buses and trams, where similar methodologies could be applied to enhance comfort and operational performance. The adoption of this ML-driven framework not only promises to improve passenger satisfaction and safety but also supports the development of sustainable, passenger-centred transportation systems
Frequency domain functional near infrared spectroscopic imaging for the assessment of human brain health
Get PDFThis thesis explores the use and development of frequency domain (FD) functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) for use in the assessment of human brain health, with a focus on traumatic brain injury (TBI). The focus on TBI was chosen because TBI has the highest incident of all neurological disorders. TBI is caused when an external force impacts the head, causing an acceleration on the brain and depending on the magnitude and duration of this force, can have several minor and serious consequences on the brain. Currently TBI is graded, mild (mTBI), moderate (M-TBI) or severe (S-TBI) using a subjective assessment, the Glasgow coma scale, with supplementary imaging performed on S-TBI in the form of x-ray CT or MRI scans. These forms of imaging can not be done at the bedside, or outside of clinical environments, and in the case of MRI scans, can be resource expensive. In addition, the subjective assessments may be influenced by factors outside of the TBI itself, which means there exists an opportunity for portable, more resource efficient, objective assessment for TBI. The use of diffuse optics may present as a tool to supplement the aforementioned tools for the assessment of TBI and this thesis investigates the use of frequency domain diffuse optics of brain imaging, for the application of traumatic brain injury assessment. This thesis develops the use of FD fNIRS and DOT for functional brain imaging, which plays a role in assessing brain health. In the FD, light is emitted sinusoidally on the surface of the scalp, this light is then absorbed and scattered throughout tissue and some of that light is then detected. The measurements made are changes in the intensity (amplitude) and phase of the modulated light and it is these changes in intensity and more significantly phase that are crucial to unlocking the advantages of FD versus the much used continuous wave (CW) paradigm in diffuse optics. In CW measurements, only changes in intensity are measured, and it has been demonstrated that phase measurements actually sample deeper than intensity measurements. As well as sampling deeper and thus sampling the cortical tissue more than intensity, phase data is also less sensitive to superficial tissue changes. This thesis investigates and explores the use of phase and intensity data with FD measurements, showing that the inclusion of phase data when applied to functional brain imaging increases the contrast of measured brain activation for both fNIRS and DOT. This is performed with a specially designed workflow, to combine recent advancements of data analysis in fNIRS literature, such as short signal regression to minimise superficial tissue influence, optical subject specific registration for accurate placement of source-detector probes on the 3D subject model and a bespoke 3D printed probe holder for the subject neoprene helmet to perform standard and dual slope measurements. Through these design considerations, this workflow enables and enhances the demonstration of FD fNIRS and DOT for functional brain imaging. The final working chapter in this thesis demonstrates an experimental protocol for imaging S-TBI patients in the intensive care unit, using a lab based FD device and an injected contrast dye. It also provides insight into the challenges of imaging in this type of clinical environment. In addition, this thesis explores another unique aspect of phase data, that the distribution of sensitivity changes as a function of modulation frequency. Through simulations and then measurements on a phantom mimicking functional activation, it is shown that combining measurements of phase at different modulation frequencies increases the accuracy and resolution of DOT, unlocking the best performance of FD diffuse optics. These findings give the platform to FD fNIRS and DOT, in that when assessing human brain health, they provide a more accurate imaging of functional brain activation than the equivalent CW measurements, which could be vital for when assessing human brain health
Dynamic fault modelling and prediction in cyber-physical systems
No full textCyber-Physical Systems (CPS) are distinguished by their intricate interplay between physical components and computational processes. Each constituent entity plays an integral role in advancing the system towards its overarching objectives, resulting in a tightly coupled and complex relationship within the CPS framework. As CPS becomes increasingly pervasive in critical domains such as healthcare, transportation, robotics, smart grids, and manufacturing, ensuring their reliability and resilience against faults and failures is paramount. This thesis explores the challenges and methodologies associated with fault detection in CPS environments. There is a rise in the number of studies on CPS fault detection, with a notable emphasis on security aspects. There remains a relative dearth of research dedicated to non-intrusive faults, which may arise from natural system variability or unintended malfunction. The limited attention to nonintrusive faults underscores the need for a more comprehensive understanding and exploration of these types of faults to ensure a well-rounded and robust fault detection framework for CPS. One of the biggest challenges of fault detection is establishing what is considered the normal behaviour and the abnormal behaviour of the system with limited intervention of humans. The proposed method’s usefulness is proved through extensive simulation and experiments. The existing fault detection methods are studied, categorised, and analysed. We present the concept of surrogate modelling in CPS; wherein surrogate models are utilised to emulate the behaviour of complex physical systems. The integration of surrogate modelling techniques enhances fault detection capabilities by providing insights into system dynamics and facilitating rapid prototyping of detection algorithms. We leverage the capability of fault injection to generate different system dynamics to understand the behaviours of the system under different fault scenarios. Expert models are trained to help in fault detection with each model trained to detect and/or predict specific faults. The approach is further enhanced by adaptively training additional expert models in case the existing models are unable to detect the unknown faults. Through empirical evaluations and case studies, this thesis validates the effectiveness of the proposed fault detection methodologies against CPS application. The results demonstrate the feasibility and benefits of proactive fault management strategies in enhancing the resilience of CPS against various faults. This thesis contributes to the advancement of fault detection in CPS by providing proactive fault detection strategies, which can help CPS designers and engineers to fortify system resilience and mitigate the impact of unforeseen faults on critical infrastructure and operations
Who is responsible for the balance between art and commerce? the case of branded entertainment
Get PDFThis thesis examines a relatively novel kind of marketing communications, namely branded entertainment, and its growing importance for global branding strategies. Specifically, this work uses a socio-cultural approach to analyse industry practitioners’ perspectives on how product placement has evolved into branded entertainment, the new forms of collaboration required to develop branded entertainment projects, how branded entertainment projects are governed by industry stakeholders, and where responsibility might lie for the ethical issues that emerge as consumers engage with diverse branded entertainment formats. Using a mediated discourse analysis methodology including interviews with global industry leaders, practitioner event observations and multimodal analyses of a selected branded entertainment films and series, this research explores the interrelationships among practitioners’ actions within discourses and text. Findings reveal three core discussive themes on the complex tapestries of branded entertainment: the complexities that practitioners face in conceptualising, creating, producing, and distributing this communication format; the new ways of working that emerge, including new collaboration approaches, novel intellectual property management and ownership issues, and the power issues that emerge as practitioners navigate the world of entertainment for the purposes of communicating about brands; and, finally, the ethical and responsibilisation issues that manifest with new branded entertainment formats, given the level of brand integration in these entertainment formats and the portrayal of such projects as entertainment films or television shows. This work’s theoretical contributions are threefold. First, this research establishes clearer boundaries for the conceptualisation of branded entertainment, capturing its inherent complexities, and contributing to a more comprehensive understanding of its underlying dynamics and the roles, responsibilities and expectations involved in this mode of branded communication. Second, this research highlights the continual importance of storytelling and emotions for building strong iconic brands, where the storytelling message becomes the medium for communicating about brands, thus, inverting McLuhan’s classic proposition that the medium is the message. Finally, this research contributes to the development of the film marketing brandscape by illuminating how the various components of branded entertainment can collectively constitute a brandscape where brands can strive for meaning. It does so by focusing on how collaborations and control over creative outputs are impacted by the development of branded entertainment projects and the ethical and responsibility issues that emerge through such projects. Implications for practice, policy and consumers are also addresses in this work
Genetic improvement of growth traits in Jebel Akhdar goats, Batinah goats, and Omani sheep in Oman
Get PDFThe objective of the present thesis was to estimate the genetic parameters associated with growth traits, specifically birth weight (BW), weaning weight (WW), six-month weight (W6), and yearling weight (W12), among Jebel Akhdar (JA) goats, Batinah (BA) goats, and Omani sheep (OS) in Oman. In addition, the level of inbreeding and its trend over 13 years were investigated for the three breeds. Finally, a simulation study was carried out to examine the feasibility of implementing genomic selection (GS) in OS sheep with the aim of enhancing the genetic improvement of these traits. The analysis utilised data obtained from the Wadi Qurayyat Livestock Research Station (WQLRS) in Oman over the years 2008 to 2020. The dataset comprises 2,826 records of JA goats, 2,609 records of BA goats, and 3,530 records of OS sheep.
The heritability estimates for BW, WW, W6, and W12 in JA goats were 0.13 ± 0.04, 0.11 ± 0.04, 0.19 ± 0.05, and 0.21 ± 0.06, respectively. In comparison, the values for BW, WW, W6, and W2 were found to be 0.17 ± 0.04, 0.16 ± 0.04, 0.16 ± 0.04, and 0.24 ± 0.04, respectively, in BA goats. In Omani sheep, the observed values for BW, WW, W6, and W12 were 0.16 ± 0.03, 0.15 ± 0.03, 0.28 ± 0.05, and 0.48 ± 0.05, respectively. The three breeds showed a positive genetic trend for all growth traits, although the phenotypic trend was only significant for the W12 phenotype. The annual genetic gain for BW, WW, W6, and W12 in JA goats was measured as 0.01 kg, 0.09 kg, 0.13 kg, and 0.20 kg, respectively. The BA goats exhibited an annual increase in genetic gain of 0.01 kg, 0.08 kg, 0.10 kg, and 0.18 kg for BW, WW, W6, and W12, respectively. The genetic gain for BW, WW, W6, and W12 in OS sheep exhibited annual increments of 0.01 kg, 0.13 kg, 0.22 kg, and 0.39 kg, respectively. The genetic correlations between the different traits in the three breeds were found to be positive and strong, except for the correlations with the BW trait, which had low correlations. The results of this study highlight the potential for significant genetic improvement in the growth traits associated with the investigated Omani breeds, considering their sufficient genetic variability and the favourable genetic correlations seen between them, particularly with respect to post-weaning traits.
The inbreeding levels within the three breeds were found to be very low, with estimations of 0.67% in JA goats, 0.65% in BA goats, and 1.52% in OS sheep on average. The observed levels of inbreeding among the inbred animals were 3.88%, 3.39%, and 6.49% for the respective breeds. However, there has been a notable increase in inbreeding rates, especially in recent years, necessitating the need for continuous monitoring and the implementation of measures to control it.
The simulation study has indicated that the ssGBLUP method demonstrated superior performance on prediction accuracy of breeding values averaging (0.64) across the traits of BW, W6, and W12 in OS sheep compared to the methods of BLUP (0.56) and GBLUP (0.47). The precision of the three methods was enhanced with an increase in heritability. The genomic prediction accuracy of GBLUP and ssGBLUP was enhanced by increasing the reference size. The average improvements were 0.43, 0.48, and 0.50 for GBLUP, and 0.61, 0.64, and 0.67 for ssGBLUP. These improvements were observed at reference sizes of 500, 1000, and 2000 animals, respectively. For traits with low heritability in particular, ssGBLUP may be a useful method for increasing prediction accuracy when compared to BLUP and GBLUP. The outcomes provide a theoretical framework for implementing GS in OS sheep
Delivery of regulatory t-cell therapy via ex-situ machine perfusion
Get PDFPharmacological immunosuppression following liver transplantation has improved considerably over the last half century. Despite an improved understanding, both acute and chronic rejection are frequently encountered by liver transplant clinicians and the latter is a significant cause of graft loss. In addition, the modern-day immunosuppressive medications such as calcineurin inhibitors, antimetabolites, anti-IL2 receptor antibodies and corticosteroids remain to be associated with sequalae such as diabetes, renal failure and post-transplant lymphoproliferative disorder. Regulatory T-cells (Tregs) represent a possible alternate therapy that may induce tolerance of the liver graft, rather than systemically supress the entire immune system. This research aimed to investigate the potential for Treg cell therapy to be administer directly to the liver graft through ex-situ normothermic machine perfusion (NMP). In order to do this, we firstly investigated the effect NMP has on the immune profile of the graft and immunological outcomes. Subsequently, we developed a liver wedge perfusion model to assess therapeutic Treg cell localisation after infusion, and the effect ex-situ administration has on the Treg phenotype. This was also then applied using a whole liver perfusion model consistent with that used in clinical practice (Liver Assist®). All experiments were done using human Tregs and liver. Post infusion Treg phenotype was assessed by re-isolating the infused cells from the liver tissue and perfusate, then performing flow cytometry to assess the expression of functional markers CD39, TIGIT and CTLA4. Clinical investigation comparing NMP preservation with cold storage demonstrated that early acute rejection occurred at a similar incidence in those undergoing primary transplant but was more frequent in those undergoing retransplant with an NMP preserved graft. The time of onset and severity were similar. After optimisation of our wedge perfusion model, expansion of human Tregs, and labelling with a fluorescent dye (Cell tracker red), these cells were infused via a portal vein branch. These cells were visible within the liver parenchyma and appeared to have migrated out of the hepatic sinusoids. This process appears to occur within 4 hours, as evidenced by the findings of the whole liver experiments using the Liver Assist®. The Treg suppressive phenotype, remained stable for the infused cells that were re-isolated from the liver, but was reduced in the cells within the perfusate. A proportion of Tregs administer via ex-situ machine perfusion engraft within the liver parenchyma, and therefore could exert a long lasting local immunosuppressive effect
Change over time in people with rare Neurogenetic Syndromes
Get PDFThis thesis comprises four chapters. The first chapter contains a meta-analytic review of 154 studies reporting on the prevalence of epilepsy in genetic syndromes associated with intellectual disability. The meta-analysis used a random-effects model to estimate pooled prevalence of epilepsy across 12 genetic syndromes identified in the systematic search. Pooled prevalence estimates ranged from 4% in people with Rubinstein-Taybi syndrome to 96% in people with Wolf-Hirschhorn syndrome. The prevalence estimates varied across syndrome groups, with all estimates exceeding rates reported for the general population. The methodology varied across studies and so prevalence estimates of epilepsy may be impacted by the measurement of epilepsy and the identification of samples.
The second chapter contains an empirical research study evaluating the persistence of behaviours that challenge, specifically self-injury, aggression and destruction of property, in people with genetic syndromes associated with intellectual disability over a period of 16 years. Parents/carers of 81 people with genetic syndromes completed online questionnaires. Overall, the results suggested behaviours that challenge continue to persist over 16 years. The study also evaluated demographic and behavioural characteristics associated with the developmental trajectory of these behaviours. The results revealed that impulsivity and mood predict persistent aggressive behaviours over 16 years, with impulsivity also predicting persistent destructive behaviours. The findings highlight individual characteristics of impulsivity and mood that may support the identification of children at an increased likelihood of developing persistent behaviours that challenge.
The third and fourth chapters comprise of press releases for the meta-analytic review and empirical study, respectively
Modular fuel cell battery hybrid system for automotive application: optimal control and system optimisation
No full textThis thesis presents a comprehensive study on the optimisation of energy management systems for specialised vehicles, focusing on fire trucks, ambulances, and auxiliary power units (APUs) for military vehicles. The work begins with the development of unique drive cycles tailored to fire trucks and ambulances, subsequently analysing their driving characteristics. A vehicle model is then developed to accurately determine the motor power requirements for fire trucks and ambulances.
This research has focused on developing an optimal sizing approach for the above-mentioned vehicle powertrains, intending to optimally meet the energy requirements of these specialised vehicles. The proposed offline optimal sizing has been implemented in a simulation environment to provide valuable insights into optimal fuel cell systems and battery configurations that can improve vehicle performance while lowering fuel consumption.
Furthermore, the thesis has explored modular APU systems within military applications, focusing on imp
Targeting diabetic vascular complications using a novel rat model for diabetic retinopathy
Get PDFABSTRACT
Aims
Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes, emerging as a primary cause of vision impairment and blindness in the working-age population. Many mechanisms of DR remain incompletely understood, and existing treatments are limited. Animal models serve as an invaluable tool for advancing our knowledge of DR and identifying novel interventions for this sight-threatening disease. However, current animal models fall short of reflecting the entire spectrum of DR. The aim of this PhD research project is to develop a novel rat animal model that replicates the pathophysiology of both proliferative and non-proliferative DR. The current gold standard streptozotocin (STZ)-induced DR animal model was also assessed.
Methods
A systematic literature review was performed to outline both structural and functional readouts in the rodent STZ-induced DR animal model. A follow-up experimental study was undertaken in the STZ-induced Brown Norway (BN) rats to characterize changes in the ocular structure and functional activity following injection. In the pursuit of developing a novel preclinical model relevant to DR, the feasibility of cumate-inducible lentiviral (LV) vectors mediating vascular endothelial grow factor (VEGF-A) expression was evaluated in retinal pigment epithelial cells (ARPE-19), and the tolerability of cumate was tested in Wistar rat eyes after intravitreal delivery. Finally, intravitreally injected adeno-associated virus (AAV) vectors encoding Vegf-a were investigated in BN rats, and the efficacy of aflibercept (Eylea®) as a therapeutic intervention was assessed within this model.
Results
Systematic literature review highlighted electroretinography (ERG) as the most consistent functional redout in rodent STZ-induced DR, revealing high risk of bias in selected studies. A detailed examination of STZ-induced BN rats revealed consistent morphological changes and visual deficits post-injection, though it primarily mirrored only the early stages of DR. Cumate-inducible LV expression of VEGF-A in ARPE-19 cells led to enhanced cell proliferation, viability, permeability, and migration in tube-like structures. However, the observed retinal toxicity following intravitreal injection of cumate in Wistar rat eyes made the use of cumate-inducible LV impractical for further in vivo DR studies. Intravitreal injection of AAV vectors mediating human VEGF-A expression resulted in DR-like vascular pathology in Brown Norway rat retinas, along with reduced retinal activity, and heightened immune cell reactivity. The administration of aflibercept effectively ameliorated these effects, thereby confirming the translational applicability of this newly established model.
Conclusion
The findings described in this thesis explore the prevalent STZ-induced DR animal model and successfully culminate in the development of a novel rat model replicating the main pathophysiological features of DR. The newly established easy-to-use AAV-induced rat model recapitulates several DR-related phenotypes and serves as an attractive tool to gain valuable insights into the underlying molecular mechanisms of DR pathologies and for testing novel therapeutic strategies
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