5,032 research outputs found

    Investigating the Innate Immune Systems of Bats and Their Roles as Zoonotic Viral Reservoirs

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    The zoonotic spillover of viral pathogens from wild animal reservoirs into human populations remains the leading cause of emerging and re-emerging infectious diseases globally. Bats represent important viral reservoirs, notorious for the diversity and richness of the viruses they host, several of which are highly pathogenic when transmitted to humans. Remarkably, bats appear to host an abundance of these viruses without exhibiting any clinical signs of disease. A dominant hypothesis for this ability suggests that bats can control viral replication early in the innate immune response, which acts as the first line of defence against infection. However, bat immunology remains fundamentally understudied, largely due to their high species diversity and the lack of accessible reagents required for bat research. Therefore, in this work we explored and characterised key components of bat innate immunity to gain a better understanding of bats as viral reservoirs and contribute to the currently limited literature. Here, we demonstrated the in vitro transcriptomic response of the bat model species, Pteropus alecto (P.alecto) upon stimulation with the bat henipavirus Cedar virus and also with a type III bat interferon (paIFNλ). These investigations highlighted key transcripts, some of which were immune-related, in the response of bats to the separate stimuli and presents a foundation for further research into significant genes concerned in bat viral infection. Building from genome-wide transcriptomics, three distinctive bat innate immune genes representative of different stages of interferon signalling were selected for comparative genomics and functional characterisation. Our work demonstrated the conservation of genes between bats and humans, including IRF7, IFIT5 and IFI35. Specific findings for IRF7 included its successful translocation to the cell nucleus upon stimulation. IFIT5 and IFI35 were specifically selected for exploration due to previous research demonstrating the respective antiviral and conflicting anti- or pro-viral roles of these genes in humans. Significantly, our research demonstrated the direct antiviral action of P.alecto IFIT5 against negative-sense RNA viruses. Collectively, our findings offer valuable contributions to the field of bat antiviral immunity and provide the framework for future investigative studies into the role and function of the bat innate immune system and bat viral tolerance mechanisms

    The Influence of Neuroendocrine and Genetic Markers of Stress on Cognitive Processing and Intrusive Symptoms

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    This body of research investigated the influence of neuroendocrine and genetic elements of arousal on cognitive processes in the development of intrusive memories and flash-forward intrusions as related to Post-Traumatic Stress Disorder. Specifically, this thesis investigated various mechanisms that may underlie intrusive symptoms as postulated by prevalent theories of PTSD. Study 1 examined the distinctive relationship between peritraumatic dissociation and subsequent re-experiencing symptoms. Network analyses revealed strong positive edges between peritraumatic dissociation and subsequent amnesia, as well as the re-experiencing symptoms of physical reactivity to reminders, flashbacks, intrusions, and dreams, and to a lesser extent emotional numbness and hypervigilance. The finding that peritraumatic dissociation is related to subsequent re-experiencing symptoms is consistent with cognitive models that emphasize the role of dissociative experiences during a traumatic event in the etiology of PTSD re-experiencing symptoms. Study 2 aimed to determine whether peri-traumatic stress, as measured via salivary cortisol and salivary alpha-amylase, as well as pre-existing genetic polymorphisms on the FKBP5 gene increased dissociation and data-driven processing, and subsequently impacted intrusive memories related to a trauma film. The findings revealed that greater noradrenergic arousal predicted less intrusive memory distress in individuals who scored higher on data-driven processing and trait dissociation, and in FKBP5 low-risk carriers. For individuals who reported less data-driven processing and trait dissociation, and in FKBP5 high-risk carriers, as noradrenergic arousal increased, intrusive memory distress increased. This study also showed no association between data-driven processing with memory fragmentation, and fragmentation with intrusive memories. Whilst these findings support some aspect of cognitive models of PTSD as they indicate a role for data-driven processing and dissociation in intrusive symptoms, they highlight a threshold at which these variables stop moderating the relationship between arousal and intrusive memories and suggest that memory fragmentation is not related to intrusive memories. Study 3 examined the role of cognitive control in flash-forward intrusions in the context of an enduring stressor, the COVID-19 pandemic. In line with expectations, results showed that as cognitive control worsened, FKBP5 high-risk carriers reported more flash-forward distress, and low-risk carriers reported less distress. These findings are considered in the context of hippocampal changes and are consistent with emerging theories of PTSD. Lastly, study 4 sought to investigate the role of two neurological processes, pattern separation and pattern completion in intrusive memories in individuals with PTSD compared to trauma exposed controls. Consistent with existing literature, the data indicate that individuals with PTSD reported more data-driven processing, more intrusive symptoms, and demonstrated better behavioural pattern completion than trauma-exposed controls. These findings are in line with current cognitive models of PTSD, as they again indicate a role for data-driven processing in PTSD. However, study 4 found no support for the postulate that deficient pattern separation is a feature of PTSD and found an opposite effect for the role of pattern completion. Whilst these findings are inconsistent with theory, they are in line with existing experimental studies. Overall, the findings from this thesis provide insight into cognitive and biological models of PTSD and shed light on the mechanisms underlying the nature and development of intrusive symptoms

    Software Product Line Engineering via Software Transplantation

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    For companies producing related products, a Software Product Line (SPL) is a software reuse method that improves time-to-market and software quality, achieving substantial cost reductions.These benefits do not come for free. It often takes years to re-architect and re-engineer a codebase to support SPL and, once adopted, it must be maintained. Current SPL practice relies on a collection of tools, tailored for different reengineering phases, whose output developers must coordinate and integrate. We present Foundry, a general automated approach for leveraging software transplantation to speed conversion to and maintenance of SPL. Foundry facilitates feature extraction and migration. It can efficiently, repeatedly, transplant a sequence of features, implemented in multiple files. We used Foundry to create two valid product lines that integrate features from three real-world systems in an automated way. Moreover, we conducted an experiment comparing Foundry's feature migration with manual effort. We show that Foundry automatically migrated features across codebases 4.8 times faster, on average, than the average time a group of SPL experts took to accomplish the task

    Multiplexed High-Resolution Imaging Approach to Decipher the Cellular Heterogeneity of the Kidney and its Alteration in Kidney Disease and Nephrolithiasis

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    Indiana University-Purdue University Indianapolis (IUPUI)Kidney disease and nephrolithiasis both present a major burden on the health care system in the US and worldwide. The cellular and molecular events governing the pathogenesis of these diseases are not fully understood. We propose that defining the cellular heterogeneity and niches in human and mouse kidney tissue specimens from controls and various models of renal disease could provide unique insights into the molecular pathogenesis. For that purpose, a multiplexed fluorescence imaging approach using co-detection by Indexing (CODEX) was used, using a panel of 33 and 38 markers for mouse and human kidney tissues, respectively. A customized computational analytical pipeline was developed and applied to the imaging data using unsupervised and/or semi-supervised machine learning and statistical approaches. The goal was to identify various cell populations present within the tissues, as well as identify unique cellular niches that may be altered with disease and/or injury. In mice, we examined disease models of acute kidney injury (AKI) and in human tissues we analyzed specimens from patients with AKI, IgA nephropathy, chronic kidney disease, systemic lupus erythematosus, and nephrolithiasis. In both mice and humans, the disease and reference samples show similar broad cell populations for the main segments of the nephron, endothelium, as well as similar groups of immune cells, such as resident macrophages and neutrophils. When comparing between health and disease, however, a change in the distribution of few sub-populations occurred. For example, in human kidney tissues, the abundance and distribution of a subpopulation of proximal tubules positive for THY1 (a marker of differentiation and repair), was markedly reduced with disease. Changes observed in mouse tissues included shifts in the immune cell population types and niches with disease. We propose that our analytical workflow and the observed changes in situ will play an important role in deciphering the pathogenesis of kidney disease

    Systemic Circular Economy Solutions for Fiber Reinforced Composites

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    This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

    Developing methods to assess evolutionary and functional equivalence of single nucleotide variants for improved clinical interpretation of human genetic variation

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    With advancements in sequencing technology there has been an unprecedented rise in human single nucleotide variant data in recent years. One of the key challenges within clinical genetics is distinguishing truly pathogenic from rare but benign variants. Many in silico tools have been developed with this aim but they often over predict pathogenicity particularly on novel variants. Here, I demonstrate how a framework designed to identify variants with functional equivalence by using information from variants in known related genes can help pathogenic variant interpretation. Using sequence alignments of human paralogues, known pathogenic variants within aligned positions can be used to transfer their annotations across to aligned variants. This Paralogue Annotation method is shown to be widely applicable exome-wide, with 71% of disease genes having at least one paralogue. As a classifier it performs more precisely than other contemporary variant predictors, having a precision of 94% or higher depending on the data. This however comes at the cost of limited sensitivity (17% and lower). But this is rescued when the framework was improved by altering the alignments to protein domains instead of whole gene sequences. The sensitivity was increased by 74% with a marginal 6% precision decrease. By expanding the framework to explore the usage of structural protein alignments instead of sequence alignments there is potential to further improve sensitivity, but current limited structural data means that predicted protein models must be relied on leading to further assumptions to be taken. In structural space, pathogenic variants across aligned models are statistically more likely to be closer together than benign and pathogenic variants. This framework can be used as a precise pathogenic variant classifier in sequence space, but overall, it can be used to search for functionally equivalent variants to variants of interest, which is a line of information not used by many.Open Acces

    QoS-aware architectures, technologies, and middleware for the cloud continuum

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    The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions

    Caracterización molecular con técnicas de secuenciación masiva para el estudio de transmisión y evolución de mycobacterium tuberculosis complex en Aragón

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    En la presente tesis doctoral se ha estudiado la epidemiología molecular de la tuberculosis en Aragón utilizando técnicas de secuenciación masiva. Se presenta como compendio de publicaciones.<br /

    Role of DNA Damage and Cellular Senescence in Osteoarthritis Pathophysiology

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    Osteoarthritis (OA) is a common degenerative joint disease characterized by progressive degradation of the articular cartilage that protects the ends of bones. Aging has been identified as the most dominant risk factor for the development of OA, and a better understanding of age-related dysfunction in joint tissues may contribute to more effective therapeutic interventions. Chapter 1 introduces two components of aging – cellular senescence and DNA damage – as well as their interaction and potential role in OA. Senescence is a state of stable cell-cycle arrest that cells enter in response to stress. Senescent chondrocytes have been found to accumulate within the joint throughout aging and contribute to cartilage dysfunction by secreting inflammatory and matrix-degrading molecules. In Chapter 2, we demonstrate that treatment of cadaveric cartilage tissue with the combination of damage (through 10 Gy irradiation) and cell-expansion stimuli (through growth factor treatment) induces a substantial percentage of chondrocytes to become senescent (~10%). In Chapter 3, we use the single-cell gel electrophoresis “comet” assay to show that older and OA chondrocytes have significantly higher levels of DNA damage compared to chondrocytes derived from young donors. In Chapter 4, we demonstrate that chondrocyte’s capacity to repair DNA damage declines with age, but can be improved by activating SIRT6, an enzyme involved in DNA repair. In Chapter 5, we show a moderate decrease in senescence induction when reducing DNA damage in cartilage explants from cadaveric and murine sources by SIRT6 activation. In a pilot in vivo study, we show that repeated intra-articular injections of MDL-800 (a SIRT6 activator) reduces DNA damage but may not be sufficient to mitigate senescence as measured by a p16tdTom senescence reporter allele. Chapter 6 summarizes how this dissertation contributes to the fields of aging biology and OA and identifies further areas of research. Collectively, this work provides novel insights connecting senescence, DNA damage, and OA. By uncovering the underlying mechanisms behind senescence and DNA damage within the joint, this research establishes a foundation for the development of next generation OA therapeutics.Doctor of Philosoph

    Chatbots for Modelling, Modelling of Chatbots

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    Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 28-03-202
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