161 research outputs found

    24th Nordic Conference on Computational Linguistics (NoDaLiDa)

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    Modelling the genomic structure, and antiviral susceptibility of Human Cytomegalovirus

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    Human Cytomegalovirus (HCMV) is found ubiquitously in humans worldwide, and once acquired, the infection persists within the host throughout their life. Although Immunocompetent people rarely are affected by HCMV infections, their related diseases pose a major health problem worldwide for those with compromised or suppressed immune systems such as transplant recipients. Additionally, congenital transmission of HCMV is the most common infectious cause of birth defects globally and is associated with a substantial economic burden. This thesis explores the application of statistical modelling and genomics to unpick three key areas of interest in HCMV research. First, a comparative genomics analysis of global HCMV strains was undertaken to delineate the molecular population structure of this highly variable virus. By including in-house sequenced viruses of African origin and by developing a statistical framework to deconvolute highly variable regions of the genome, novel and important insights into the co-evolution of HCMV with its host were uncovered. Second, a rich database relating mutations to drug sensitivity was curated for all the antiviral treated herpesviruses. This structured information along with the development of a mutation annotation pipeline, allowed the further development of statistical models that predict the phenotype of a virus from its sequence. The predictive power of these models was validated for HSV1 by using external unseen mutation data provided in collaboration with the UK Health Security Agency. Finally, a nonlinear mixed effects model, expanded to account for Ganciclovir pharmacokinetics and pharmacodynamics, was developed by making use of rich temporal HCMV viral load data. This model allowed the estimation of the impact of immune-clearance versus antiviral inhibition in controlling HCMV lytic replication in already established infections post-haematopoietic stem cell transplant

    Exploring The Interactions Between SARS-CoV-2 and Host Proteins.

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    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current pandemic, Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 is considered to be of zoonotic origin; it originated in non-human animals and was transmitted to humans. Since the early stage of the pandemic, however, the evidence of transmissions from humans to animals (reverse zoonoses) has been found in multiple animal species including mink, white-tailed deer, and pet and zoo animals. Furthermore, secondary zoonotic events of SARS-CoV-2, transmissions from animals to humans, have been also reported. It is suggested that non-human hosts can act as SARS-CoV-2 reservoirs where accumulated mutations in viral proteins could change the transmissibility and/or pathogenicity of the virus when it is spilled over again to human populations. Our goal, therefore, is to examine the SARS-CoV-2 genomic changes in non-human hosts and to identify the changes responsible for the adaptation of the virus in non-human hosts. Changes in the physicochemical properties of viral proteins potentially affect and influence their functions. Therefore, in this study, we compared SARS-CoV-2 proteins among human and non-human hosts and analyzed the differences in their physicochemical properties using the principal component analysis. In addition to the viral proteins from bat and pangolin, those from white-tailed deer and mink showed larger differences in the properties. Van der Waals volume, isoelectric point, charge, and thermostability index were found to be the main contributing factors. We next performed the comparisons of protein-protein interaction (PPI) prediction methods that use different features including physicochemical properties and those based on natural language processing. It showed that the Cross-attention PHV had slightly better performance scores than InterSPPI-HVPPI and LGCA-VHPPI. Finally, to examine the effect of changes in physicochemical properties in viral proteins against host proteins, PPI prediction was performed using the Cross-attention PHV between viral proteins from different SARS-CoV-2 variants and host proteins. The prediction scores between the different variants and host proteins from human and white-tailed deer were highly similar. The results showed that the analysis of physicochemical properties of viral proteins helps to understand how physicochemical properties of viral proteins affect viral-host PPIs and how viral proteins evolve to adapt different host cell environments

    Motor Control of Rapid Eye Movements in Larval Zebrafish

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    Animals move the same body parts in diverse ways. How the central nervous system executes one action over related ones is poorly understood. To investigate this, I assessed the behavioural manifestation and neural control of saccadic eye rotations made by larval zebrafish, since these movements are simple and easy to investigate at a circuit level. I first classified the larva’s saccadic repertoire into 5 types, of which hunting specific convergent saccades and exploratory conjugate saccades were the main types used to orient vision. Convergent and conjugate saccades shared a nasal eye rotation, which had kinematic differences and similarities that suggested the rotation was made by overlapping but distinct populations of neurons between saccade types. I investigated this further, using two-photon Ca2+ imaging and selective circuit interventions to identify a circuit from rhombomere 5/6 to abducens internuclear neurons to motoneurons that was crucial to nasal eye rotations. Motoneurons had distinct activity patterns for convergent and conjugate saccades that were consistent with my behavioural observations and were explained largely by motoneuron kinematic tuning preferences. Surprisingly, some motoneurons also modulated activity according to saccade type independent of movement kinematics. In contrast, pre-synaptic internuclear neuron activity profiles were almost entirely explained by movement kinematics, but not neurons in rhombomere 5/6, which had mixed saccade type and kinematic encoding, like motoneurons. Regions exerting descending control on this circuit from the optic tectum and anterior pretectal nucleus had few neurons tuned to saccade kinematics compared to neurons selective for convergent saccades. My results suggest a transformation from encoding action type to encoding movement kinematics at successive circuit levels. This transformation was not monotonic or complete, and suggests that control of even simple, highly comparable, movements cannot be entirely described by a shared kinematic encoding scheme at a motor or premotor level

    Physics and Literature

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    Physics and Literature is a unique collaboration between physicists and literary scholars, the first book to explore together the relations between both fields in depth. Contributors analyze central aspects of literary and scientific thought and representation, and the forms of exchange between them. They clarify how narrative, fiction, metaphor and language interact with models, experiment, measurement and mathematics, across eras and genres

    The free energy principle induces neuromorphic development

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    We show how any finite physical system with morphological, i.e. three-dimensional embedding or shape, degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve over time towards a neuromorphic morphology that supports hierarchical computations in which each ‘level’ of the hierarchy enacts a coarse-graining of its inputs, and dually, a fine-graining of its outputs. Such hierarchies occur throughout biology, from the architectures of intracellular signal transduction pathways to the large-scale organization of perception and action cycles in the mammalian brain. The close formal connections between cone-cocone diagrams (CCCD) as models of quantum reference frames on the one hand, and between CCCDs and topological quantum field theories on the other, allow the representation of such computations in the fully-general quantum-computational framework of topological quantum neural networks

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum

    Play Among Books

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    How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

    UAVs for the Environmental Sciences

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    This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

    Methods and tools to improve performance of plant genome analysis

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    Multi -omics data analysis and integration facilitates hypothesis building toward an understanding of genes and pathway responses driven by environments. Methods designed to estimate and analyze gene expression, with regard to treatments or conditions, can be leveraged to understand gene-level responses in the cell. However, genes often interact and signal within larger structures such as pathways and networks. Complex studies guided toward describing dynamic genetic pathways and networks require algorithms or methods designed for inference based on gene interactions and related topologies. Classes of algorithms and methods may be integrated into generalized workflows for comparative genomics studies, as multi -omics data can be standardized between contact points in various software applications. Further, network inference or network comparison algorithmic designs may involve interchangeable operations given the structure of their implementations. Network comparison and inference methods can also guide transfer-of-knowledge between model organisms and those with less knowledge base
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