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Die Dissertation ,Spuren des Religiösen´ im Werk der deutsch-jüdischen Schriftstellerin Barbara Honigmann – eine literaturwissenschaftlich-theologische Werkanalyse – analysiert und interpretiert das literarische Frühwerk der deutsch-jüdischen Schriftstellerin Barbara Honigmann (geb. 12. Februar 1949 in Ostberlin). Die Schriftstellerin verlässt Mitte der achtziger Jahre mit ihrer Familie die ehemalige DDR und findet in Straßburg (Frankreich) eine neue Heimat. In der Dissertation werden der Erzählband Roman von einem Kinde (1986) und die Romane Eine Liebe aus nichts (1991) und Soharas Reise (1996) aus der Sicht verschiedener Fachwissenschaften beleuchtet. Die meisten Texte sind nach ihrer Emigration in Frankreich entstanden. Methodisch werden die Texte nach der Erzähltextanalyse von Sönke Finnern analysiert. Das Judentum und jüdische Religiosität bilden dabei das gemeinsame Zentrum der literarischen Werke Barbara Honigmanns (Hans Otto Horch). In differenzierter Weise werden unterschiedliche jüdisch-theologische Aspekte wie Gottesfrage, Bedeutung der jüdischen Feste, Riten und Exilerfahrung anhand der Werke herausgearbeitet. Aus literaturwissenschaftlicher Sicht wird der Aspekt des exterritorialen Schreibens betont (Andreas Kilcher). Dabei wird die besondere Perspektive als Autorin der sogenannten zweiten Generation nach der Shoah hervorgehoben (Hartmut Steinecke). Georg Langenhorst macht auf die Bedeutung Honigmanns im Kontext des religionspädagogischen Diskurses unter interkultureller und interreligiöser Fragestellung aufmerksam. Die Erzählte Religion bildet das Zentrum der literarisch-theologischen Werkanalyse. Die Kategorie der Grenzerfahrung bzw. der Liminalität rückt dabei in das Zentrum der Verhältnisbestimmung (Victor Turner und Dirk Hohnsträter). Auf der theologischen Ebene werden die jüdischen Konzepte von makom (hebr. Ort), galut (hebr. Exil) und jetzirat (hebr. Schöpfung) herausgearbeitet. Die jüdische Erfahrung von Heimat und Heimatlosigkeit wird hervorgehoben (Yannif Feller). Die Arbeit schließt mit einer Einordnung der Werkinterpretation in den Bereich Literatur und Ritual (Wolfgang Braungart).
Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe−/−, n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe−/− mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.
Abstract
Amphidiploid fungal Verticillium longisporum strains Vl43 and Vl32 colonize the plant host Brassica napus but differ in their ability to cause disease symptoms. These strains represent two V. longisporum lineages derived from different hybridization events of haploid parental Verticillium strains. Vl32 and Vl43 carry same‐sex mating‐type genes derived from both parental lineages. Vl32 and Vl43 similarly colonize and penetrate plant roots, but asymptomatic Vl32 proliferation in planta is lower than virulent Vl43. The highly conserved Vl43 and Vl32 genomes include less than 1% unique genes, and the karyotypes of 15 or 16 chromosomes display changed genetic synteny due to substantial genomic reshuffling. A 20 kb Vl43 lineage‐specific (LS) region apparently originating from the Verticillium dahliae‐related ancestor is specific for symptomatic Vl43 and encodes seven genes, including two putative transcription factors. Either partial or complete deletion of this LS region in Vl43 did not reduce virulence but led to induction of even more severe disease symptoms in rapeseed. This suggests that the LS insertion in the genome of symptomatic V. longisporum Vl43 mediates virulence‐reducing functions, limits damage on the host plant, and therefore tames Vl43 from being even more virulent.
A Brief History of APIs
(2021)
Online platforms such as Facebook, YouTube and Twitter offer a wide range of data for scientific research. Since many of the social media providers have set up application programming interfaces (APIs), extensive volumes of data can be collected automatically (Jünger, 2018; Keyling & Jünger, 2016). Social media data are attractive, inter alia, because they not only include already available communication, such as that from public media, but they also make organisational and interpersonal communication visible (Ledford, 2020). In addition, these data are process-generated (Baur, 2011, p. 1234), meaning that they are generated independently of scientific research and thus promise an authentic insight into human behaviour. 1 A wide range of studies in the social sciences exploit APIs for data collection and analysis. Thus, the establishment and development of APIs has significant implications for science.
Our goal was to provide a comprehensive overview of the antibody response to Staphylococcus aureus antigens in the general population as a basis for defining disease-specific profiles and diagnostic signatures. We tested the specific IgG and IgA responses to 79 staphylococcal antigens in 996 individuals from the population-based Study of Health in Pomerania. Using a dilution-based multiplex suspension array, we extended the dynamic range of specific antibody detection to seven orders of magnitude, allowing the precise quantification of high and low abundant antibody specificities in the same sample. The observed IgG and IgA antibody responses were highly heterogeneous with differences between individuals as well as between bacterial antigens that spanned several orders of magnitude. Some antigens elicited significantly more IgG than IgA and vice versa. We confirmed a strong influence of colonization on the antibody response and quantified the influence of sex, smoking, age, body mass index, and serum glucose on anti-staphylococcal IgG and IgA. However, all host parameters tested explain only a small part of the extensive variability in individual response to the different antigens of S. aureus.
A lot of research data has become available since the outbreak of the COVID-19
pandemic in 2019. Connecting this data is essential for the understanding of the
SARS-CoV-2 virus and the fight against the pandemic.
Amongst biological and biomedical research data, computational models targeting
COVID-19 have been emerging and their number is growing constantly. They are a
central part of the field of Systems Biology, which aims to understand the mechanisms
and behaviour of biological systems. Model predictions help to understand the
mechanisms of the novel coronavirus and the life-threatening disease it is causing.
Both biomedical research data and modelling data regarding COVID-19 have
previously been stored in separated domain-specific graph databases. MaSyMoS,
short for Management System for Models and Simulations, is a graph database for
storing simulation studies of biological and biochemical systems. The CovidGraph
project integrates research data regarding COVID-19 and the coronavirus family
from various data resources in a knowledge graph.
In this thesis, we integrate simulation models from MaSyMoS, including models
targeting COVID-19, into the CovidGraph. Therefore, we present a concept for
the integration of simulation studies and the linkage through ontology terms and
reference publications in the CovidGraph. Ultimately, we connect data from the field
of systems biology and biomedical research data in a graph database.
Background: Previous studies suggest that blood donation impacts blood donors’ psychological state, with either positive or negative effects, such as feeling more energetic or more exhausted. It has not yet been described how long these effects last. Materials and Methods: This prospective cohort study consisted of a qualitative and a quantitative part: (1) Psychological characteristics which changed after blood donation were identified by structured interviews of regular whole blood donors (n = 42). Based on this, a questionnaire addressing 7 psychological dimensions was established. (2) The psychological state of 100 blood donors was assessed after blood donation by applying the questionnaire 15–30 min before and during donation, as well as 15–30 min, 6 h, 24 h, 72 h, 1 week, and 8 weeks after donation. The resulting changes were summarized to a score. Furthermore, potential correlations of the score with pre-donation blood pressure, hemoglobin, or body mass index were calculated. Results: Seven items were identified which changed in at least 25% of blood donors (mood, concentration, satisfaction, resilience, spirit of initiative, physical well-being, energy level). In the 100 blood donors, the well-being score increased (positive effects, n = 23), showed minor changes (n = 53), or decreased (negative effects, n = 24). The positive effects lasted for about 1 week and the negative effects for 3 days. Conclusion: While the frequency of psychological effects following blood donation identified by our study was comparable to others, the changes of the psychological state in our donors were traceable for a longer period than previously acknowledged.
We introduce PVSC-DTM (Parallel Vectorized Stencil Code for Dirac and Topological Materials), a library and code generator based on a domain-specific language tailored to implement the specific stencil-like algorithms that can describe Dirac and topological materials such as graphene and topological insulators in a matrix-free way. The generated hybrid-parallel (MPI+OpenMP) code is fully vectorized using Single Instruction Multiple Data (SIMD) extensions. It is significantly faster than matrix-based approaches on the node level and performs in accordance with the roofline model. We demonstrate the chip-level performance and distributed-memory scalability of basic building blocks such as sparse matrix-(multiple-) vector multiplication on modern multicore CPUs. As an application example, we use the PVSC-DTM scheme to (i) explore the scattering of a Dirac wave on an array of gate-defined quantum dots, to (ii) calculate a bunch of interior eigenvalues for strong topological insulators, and to (iii) discuss the photoemission spectra of a disordered Weyl semimetal.