393 research outputs found

    Displacement and the Humanities: Manifestos from the Ancient to the Present

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    This is the final version. Available on open access from MDPI via the DOI in this recordThis is a reprint of articles from the Special Issue published online in the open access journal Humanities (ISSN 2076-0787) (available at: https://www.mdpi.com/journal/humanities/special_issues/Manifestos Ancient Present)This volume brings together the work of practitioners, communities, artists and other researchers from multiple disciplines. Seeking to provoke a discourse around displacement within and beyond the field of Humanities, it positions historical cases and debates, some reaching into the ancient past, within diverse geo-chronological contexts and current world urgencies. In adopting an innovative dialogic structure, between practitioners on the ground - from architects and urban planners to artists - and academics working across subject areas, the volume is a proposition to: remap priorities for current research agendas; open up disciplines, critically analysing their approaches; address the socio-political responsibilities that we have as scholars and practitioners; and provide an alternative site of discourse for contemporary concerns about displacement. Ultimately, this volume aims to provoke future work and collaborations - hence, manifestos - not only in the historical and literary fields, but wider research concerned with human mobility and the challenges confronting people who are out of place of rights, protection and belonging

    Unravelling the complex reproductive tactics of male humpback whales : an integrative analysis of paternity, age, testosterone, and genetic diversity

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    How the underlying forces of sexual selection impact reproductive tactics including elaborate acoustic displays in cetaceans remains poorly understood. Here, I combined 26 years (1995-2020) of photo-identification, behavioural, (epi)genetic, and endocrine data from an endangered population of humpback whales (New Caledonia), to explore male reproductive success, age, physiology, and population dynamics over almost a third of the lifespan of a humpback whale. First, I conducted a paternity analysis on 177 known mother-offspring pairs and confirmed previous findings of low variation in reproductive success in male humpback whales. Second, epigenetic age estimates of 485 males revealed a left-skewed population age structure in the first half of the study period that became more balanced in the second half. Further, older males (> 23 years) more often engaged in certain reproductive tactics (singing and escorting) and were more successful in siring offspring once the population age structure stabilised, suggesting reproductive tactics and reproductive success in male humpback whales may be age-dependent. Third, using enzyme immunoassays on 457 blubber samples, I observed a seasonal decline in male testosterone in the population over the breeding season. Testosterone levels appeared highest during puberty, then decreased and levelled off at the onset of maturity, yet were highly variable at any point during the breeding season and across males of all ages. Lastly, I investigated the influence of genetic diversity at the major histocompatibility complex (MHC) class I and class IIa (DQB and DRB-a) on patterns of male reproductive success in humpback whales. Mating pairs shared fewer alleles than expected under random mating at MHC class I and IIa, thus, providing evidence of an MHC-mediated female mate choice in humpback whales. This thesis provides novel, critical insights into the evolutionary consequences of commercial whaling on the demography, patterns of reproduction and sexual selection of exploited populations of baleen whales."This work was supported by a University of St Andrews School of Biology Ph.D. Scholarship and the Louis M. Herman Research Scholarship 2022 to Franca Eichenberger. Sample collection and analyses from 2018-2020 were supported by grants to Ellen C. Garland (Royal Society University Research Fellowship (UF160081 & URF\R\221020), Royal Society Research Fellows Enhancement Award (RGF\EA\180213), Royal Society Research Grants for Research Fellows 2018 (RGF\R1\181014), National Geographic Grant (#NGS-50654R-18), Carnegie Trust Research Incentive Grant (RIG007772), British Ecological Society Small Research Grant (SR18/1288) and School of Biology Research Committee funding)."--Fundin

    Summer/Fall 2023

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    Topological data analysis of organoids

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    Organoids are multi-cellular structures which are cultured in vitro from stem cells to resemble specific organs (e.g., colon, liver) in their three- dimensional composition. The gene expression and the tissue composition of organoids constantly affect each other. Dynamic changes in the shape, cellular composition and transcriptomic profile of these model systems can be used to understand the effect of mutations and treatments in health and disease. In this thesis, I propose new techniques in the field of topological data analysis (TDA) to analyse the gene expression and the morphology of organoids. I use TDA methods, which are inspired by topology, to analyse and quantify the continuous structure of single-cell RNA sequencing data, which is embedded in high dimensional space, and the shape of an organoid. For single-cell RNA sequencing data, I developed the multiscale Laplacian score (MLS) and the UMAP diffusion cover, which both extend and im- prove existing topological analysis methods. I demonstrate the utility of these techniques by applying them to a published benchmark single-cell data set and a data set of mouse colon organoids. The methods validate previously identified genes and detect additional genes with known involvement cancers. To study the morphology of organoids I propose DETECT, a rotationally invariant signature of dynamically changing shapes. I demonstrate the efficacy of this method on a data set of segmented videos of mouse small intestine organoid experiments and show that it outperforms classical shape descriptors. I verify the method on a synthetic organoid data set and illustrate how it generalises to 3D to conclude that DETECT offers rigorous quantification of organoids and opens up computationally scalable methods for distinguishing different growth regimes and assessing treatment effects. Finally, I make a theoretical contribution to the statistical inference of the method underlying DETECT

    Performing Authority in Byzantium. Bodies, Gestures, and Behaviour in the Practice and in the Literary Representation of Power

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    This research analyses the role of gesture, postures and bodily movements in Byzantine society and politics, with a particular attention to the imperial figure and through the theoretical lens provided by social sciences and performative studies. Far away from being a trivial one, the topic had been successfully addressed by the Greek-Roman and Middle Ages Western historical research, and only recently and occasionally had been put forward in the Byzantine field, where it remains an underestimated area of research. The present study wishes, first of all, to define the meaning and the values of bodily display and gesture (schema and schemata) in Byzantium, together with an analysis of the implications of the way in which the relation between body and soul was perceived, as well as of the rationale behind the use of physical movements. A more complex and comprehensive picture of the imperial body has emerged, unveiling its physical and performative dimension, its role in the ‘theater’ of a court potentially aware of the play, as well as its importance to understand the emperor’s divine and human nature. A review of the gestural occurrences has been conducted in the most exemplificative sources from Late Antiquity down to the Middle Byzantine period, and concluded with an exceptional case-study, the Chronographia of Michael Psellos

    Network-based methods for biological data integration in precision medicine

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    [eng] The vast and continuously increasing volume of available biomedical data produced during the last decades opens new opportunities for large-scale modeling of disease biology, facilitating a more comprehensive and integrative understanding of its processes. Nevertheless, this type of modelling requires highly efficient computational systems capable of dealing with such levels of data volumes. Computational approximations commonly used in machine learning and data analysis, namely dimensionality reduction and network-based approaches, have been developed with the goal of effectively integrating biomedical data. Among these methods, network-based machine learning stands out due to its major advantage in terms of biomedical interpretability. These methodologies provide a highly intuitive framework for the integration and modelling of biological processes. This PhD thesis aims to explore the potential of integration of complementary available biomedical knowledge with patient-specific data to provide novel computational approaches to solve biomedical scenarios characterized by data scarcity. The primary focus is on studying how high-order graph analysis (i.e., community detection in multiplex and multilayer networks) may help elucidate the interplay of different types of data in contexts where statistical power is heavily impacted by small sample sizes, such as rare diseases and precision oncology. The central focus of this thesis is to illustrate how network biology, among the several data integration approaches with the potential to achieve this task, can play a pivotal role in addressing this challenge provided its advantages in molecular interpretability. Through its insights and methodologies, it introduces how network biology, and in particular, models based on multilayer networks, facilitates bringing the vision of precision medicine to these complex scenarios, providing a natural approach for the discovery of new biomedical relationships that overcomes the difficulties for the study of cohorts presenting limited sample sizes (data-scarce scenarios). Delving into the potential of current artificial intelligence (AI) and network biology applications to address data granularity issues in the precision medicine field, this PhD thesis presents pivotal research works, based on multilayer networks, for the analysis of two rare disease scenarios with specific data granularities, effectively overcoming the classical constraints hindering rare disease and precision oncology research. The first research article presents a personalized medicine study of the molecular determinants of severity in congenital myasthenic syndromes (CMS), a group of rare disorders of the neuromuscular junction (NMJ). The analysis of severity in rare diseases, despite its importance, is typically neglected due to data availability. In this study, modelling of biomedical knowledge via multilayer networks allowed understanding the functional implications of individual mutations in the cohort under study, as well as their relationships with the causal mutations of the disease and the different levels of severity observed. Moreover, the study presents experimental evidence of the role of a previously unsuspected gene in NMJ activity, validating the hypothetical role predicted using the newly introduced methodologies. The second research article focuses on the applicability of multilayer networks for gene priorization. Enhancing concepts for the analysis of different data granularities firstly introduced in the previous article, the presented research provides a methodology based on the persistency of network community structures in a range of modularity resolution, effectively providing a new framework for gene priorization for patient stratification. In summary, this PhD thesis presents major advances on the use of multilayer network-based approaches for the application of precision medicine to data-scarce scenarios, exploring the potential of integrating extensive available biomedical knowledge with patient-specific data

    Life and cell cycle progression analysis in Leishmania mexicana by single cell RNA-sequencing

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    Leishmaniasis is a neglected tropical disease, which is estimated to produce approximately 1.3 million new cases annually. As yet, no vaccines are available and current effective chemotherapeutic strategies are lacking, due to drug toxicity, resistance, and social and economic barriers affecting availability. Pivotal in the discovery of new interventions for infectious diseases is the understanding of the fundamental biology of the pathogen and its role in infection. Here, the application of single cell RNA sequencing (scRNA-seq) was employed to investigate the fundamental biology behind transcriptomic changes as the parasite progresses through life cycle stages, from promastigote to metacyclic forms before differentiating into amastigotes. The transcriptomic dynamics underpinning these multifarious developmental transitions through life cycle stages are yet to be fully described. To investigate these changes, we employed scRNA-seq over five time-points as Leishmania mexicana (L. mexicana) differentiated from promastigotes to axenicamastigotes in vitro. With clustering and marker analysis of over 16,500 parasites across three experiments, revealing thousands of stage specific markers. Of note during gene marker analysis was the discovery of a transitional cluster placed between promastigote and amastigote stages. This cluster, named here Trans A, displayed overlap between both promastigote and amastigote markers, and potentially representing a new intermediate life cycle stage, defined transcriptionally. Additionally in these data was the identification of over 1,500 differentially expressed markers for a metacyclic like cluster. To examine the timing and the patterns of gene expression over the life and cell cycle, pseudotime analysis was used for the first time in Leishmania, so that we may further explain the order of these transitional events and any potential stage specific patterns in gene expression, providing an unprecedented understanding of the life cycle transitions. Analysis indicated the development between promastigote and amastigote stages was possible by progression through this Trans A cluster, circumventing the infective metacyclic form. Thus, potentially revealing a new developmental strategy for life cycle progression. Furthermore, cell cycle labelling analysis was performed using phase marker orthologues, also revealing new cell cycle phase specific markers. When combined with promastigote stage marker orthologues, a striking overlap between promastigote life stages and cell cycle stages was found, potentially providing further evidence that promastigote morphologies are intrinsically linked with cell cycle stages. To validated how transient gene expression changes may be represented at the protein level, 96 fluorescently tagged cell lines were produced using a highthroughput CRISPR-Cas9 system. Of the 96 cell lines produced, 91 were hypothetical proteins identified as having transient expression patterns for developmental trajectories drawn over promastigote to metacyclic and axenic amastigote stages. Initial assessments by fluorescent microscopy revealed 80 out of the 96 tagged proteins matched overall pseudotime expression profiles, indicating that dynamics of RNA levels detected by scRNA-seq could reflect changes in protein levels. Furthermore, these 91 cell lines of tagged hypothetical proteins provide the opportunity for further research into new biology. So that this transitional gene progression may be explored in broader contexts, scRNA-seq of L. mexicana-infected human macrophages was undertaken. Allowing the comparison of the RNA populations found in differentiation to axenic amastigotes in vitro, to those of the amastigote forms infecting a host cell. This crucial life-cycle development stage of Leishmania within the macrophage revealed infection response associated genes, linked with parasite removal strategies. This project aimed to provide an example of investigating fundamental Leishmania biology by applying scRNA-seq for the study of life and cell cycle transitions, with the application of pseudotime analysis for the first time. Results of differential gene expression analysis revealed new biology not previously described in previous methods. Thereby demonstrating how the application of scRNA-seq may further disseminate parasite biology and infection dynamics

    Perspectives on adaptive dynamical systems

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    Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges, and give perspectives on future research directions, looking to inspire interdisciplinary approaches.Comment: 46 pages, 9 figure

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
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