Kritische Frauenliteratur im Kaiserreich und in der Weimarer Republik : Konturen eines Forschungsfelds

Die Frauenliteratur des Kaiserreichs und der Weimarer Republik ist in ihrer Gesamtheit unerforscht: Romane, Gedichte und Dramen von Autorinnen im Zeichen von Naturalismus und Frauenbewegung, die die Alltagsrealität bürgerlicher Mädchen und Frauen in einer patriarchalischen Gesellschaft beschreiben. Dabei handelt es sich um eine sehr umfangreiche Gruppe von Autorinnen und Werken, von denen manche zu ihrer Zeit hohen Bekanntheitsgrad erreichten. Die Literatur der ersten Generation erlebte mit Beginn des Ersten Weltkriegs ihre Zäsur. Während sie zu Beginn der 1920er Jahre noch einmal Schilderungen des Übergangs in eine politisch und gesellschaftlich veränderte Zeit lieferte, zogen bereits die „Töchter“ (1927), so der Titel eines Romans von Gabriele Reuter, in die Literatur ein, der Typus der Neuen Frau, der zwar ohne die bürgerliche Frauenbewegung kaum möglich gewesen wäre, sich nun aber umso vehementer von ihr löste

Literatur und bürgerliche Frauenbewegung im Kaiserreich und in der Weimarer Republik : Forschungsberichte und Studien

Inhalt: DIRK HEMPEL Kritische Frauenliteratur im Kaiserreich und in der Weimarer Republik. Konturen eines Forschungsfelds JULIAN TIETZ Bildungsmotive in Hedwig Dohms Roman "Christa Ruland" (1902) ISABEL REHMER Das geschlechtsspezifische Rollenverständnis in der Lyrik von Frauen um 1900 SANDRA CUJIC Ratgeberliteratur als Medium der Lesesozialisation junger Frauen und Mädchen im deutschen Kaiserreich – ein Forschungsbericht SÖHNKE CALLSEN Maria Janitschek – eine vergessene Autorin der Jahrhundertwende? Versuch eines werkbiographischen Portraits JANINE GLUGLA Maria Janitscheks Frauen – Zwischen "alter Eva" und "neuer Frau" KRISTINA EVEN, CHRISTINA HOFMEISTER, MALGORZATA TRIFKOVIC Frauenfrage, Frauenbewegung und Literatur in der "Gartenlaube" XENIA BOE Die belletristische Literatur in den ersten Jahrgängen der Zeitschrift "Die Frau" PARVATI VASANTA Wirkungsbereiche von Frauen im Expressionismus – institutionelle Kunstförderung und literarische Produktion CARLA SWIDERSKI Die Erstrezeption von Irmgard Keuns Roman "Gilgi – eine von uns

Eigenvalue bounds in the gaps of Schrodinger operators and Jacobi matrices

We consider $C=A+B$ where $A$ is selfadjoint with a gap $(a,b)$ in its spectrum and $B$ is (relatively) compact. We prove a general result allowing $B$ of indefinite sign and apply it to obtain a $(\delta V)^{d/2}$ bound for perturbations of suitable periodic Schrodinger operators and a (not quite)Lieb-Thirring bound for perturbations of algebro-geometric almost periodic Jacobi matrices

Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data

IntroductionMicrobes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learning is a promising option in that context. While amplicon sequencing is typically applied to assess microbial communities, metagenomics and total RNA sequencing (herein summarized as omics-based methods) can provide a more holistic picture of microbial biodiversity at sufficient sequencing depths. Despite this advantage, amplicon sequencing and omics-based methods have not yet been compared for taxonomy-based environmental assessments with machine learning.MethodsIn this study, we applied 16S and ITS-2 sequencing, metagenomics, and total RNA sequencing to samples from a stream mesocosm experiment that investigated the impacts of two aquatic stressors, insecticide and increased fine sediment deposition, on stream biodiversity. We processed the data using similarity clustering and denoising (only applicable to amplicon sequencing) as well as multiple taxonomic levels, data types, feature selection, and machine learning algorithms and evaluated the stressor prediction performance of each generated model for a total of 1,536 evaluated combinations of taxonomic datasets and data-processing methods.ResultsSequencing and data-processing methods had a substantial impact on stressor prediction. While omics-based methods detected a higher diversity of taxa than amplicon sequencing, 16S sequencing outperformed all other sequencing methods in terms of stressor prediction based on the Matthews Correlation Coefficient. However, even the highest observed performance for 16S sequencing was still only moderate. Omics-based methods performed poorly overall, but this was likely due to insufficient sequencing depth. Data types had no impact on performance while feature selection significantly improved performance for omics-based methods but not for amplicon sequencing.DiscussionWe conclude that amplicon sequencing might be a better candidate for machine-learning-based environmental stressor prediction than omics-based methods, but the latter require further research at higher sequencing depths to confirm this conclusion. More sampling could improve stressor prediction performance, and while this was not possible in the context of our study, thousands of sampling sites are monitored for routine environmental assessments, providing an ideal framework to further refine the approach for possible implementation in environmental diagnostics

A multi-technique study of altered granitic rock from the Krunkelbach Valley uranium deposit, Southern Germany

Herein, a multi-technique study was performed to reveal the elemental speciation and microphase composition in altered granitic rock collected from the Krunkelbach Valley uranium (U) deposit area near an abandoned U mine, Black Forest, Southern Germany.Comment: RSC Advances (2020

A Proteomic View of an Important Human Pathogen – Towards the Quantification of the Entire Staphylococcus aureus Proteome

The genome sequence is the “blue-print of life,” but proteomics provides the link to the actual physiology of living cells. Because of their low complexity bacteria are excellent model systems to identify the entire protein assembly of a living organism. Here we show that the majority of proteins expressed in growing and non-growing cells of the human pathogen Staphylococcus aureus can be identified and even quantified by a metabolic labeling proteomic approach. S. aureus has been selected as model for this proteomic study, because it poses a major risk to our health care system by combining high pathogenicity with an increasing frequency of multiple antibiotic resistance, thus requiring the development of new anti-staphylococcal therapy strategies. Since such strategies will likely have to target extracellular and surface-exposed virulence factors as well as staphylococcal survival and adaptation capabilities, we decided to combine four subproteomic fractions: cytosolic proteins, membrane-bound proteins, cell surface-associated and extracellular proteins, to comprehensively cover the entire proteome of S. aureus. This quantitative proteomics approach integrating data ranging from gene expression to subcellular localization in growing and non-growing cells is a proof of principle for whole-cell physiological proteomics that can now be extended to address physiological questions in infection-relevant settings. Importantly, with more than 1700 identified proteins (and 1450 quantified proteins) corresponding to a coverage of about three-quarters of the expressed proteins, our model study represents the most comprehensive quantification of a bacterial proteome reported to date. It thus paves the way towards a new level in understanding of cell physiology and pathophysiology of S. aureus and related pathogenic bacteria, opening new avenues for infection-related research on this crucial pathogen

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Genetic diversity of the arbuscular mycorrhizal fungus Glomus intraradices as determined by mitochondrial large subunit rRNA gene sequences is considerably higher than previously expected

Summary: • Glomus intraradices is a widespread arbuscular mycorrhizal fungus (AMF), which has been found in an extremely broad range of habitats, indicating a high tolerance for environmental factors and a generalist life history strategy. Despite this ecological versatility, not much is known about the genetic diversity of this fungal species across different habitats or over large geographic scales. • A nested polymerase chain reaction (PCR) approach for the mitochondrial rRNA large subunit gene (mtLSU), distinguished different haplotypes among cultivated isolates of G. intraradices and within mycorrhizal root samples from the field. • From analysis of 16 isolates of this species originating from five continents, 12 mitochondrial haplotypes were distinguished. Five additional mtLSU haplotypes were detected in field‐collected mycorrhizal roots. Some introns in the mtLSU region appear to be stable over years of cultivation and are ancestral to the G. intraradices clade. • Genetic diversity within G. intraradices is substantially higher than previously thought, although some mtLSU haplotypes are widespread. A restriction fragment length polymorphism approach also was developed to distinguish mtLSU haplotypes without sequencing. Using this molecular tool, intraspecific genetic variation of an AMF species can be studied directly in field plants