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Untersuchung der Kinematik und Kinetik des Hundekniegelenks in verschiedenen Standwinkeln sowie nach TPLO und TTA
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Thematizer
Get PDFThematic theory, comprised of the concepts of theme, rheme, and thematic progression, concerns itself with the interplay between word order, information status, propositional content and discourse function. In contemporary research on thematic theory, researchers have begun to leverage computational means for text analysis with respect to thematic structure. However, deficiencies in both the theoretical treatment and computational operationalization of thematic theory have limited writers’ accessibility to thematic structure.
The present work set out to address these deficiencies by identifying remaining gaps in thematic theory and by developing the software Thematizer, which automatically analyzes texts in terms of themes, rhemes and thematic progression. To develop and train Thematizer, 30 Wikipedia articles, L1 and L2 university texts, blog articles and lyrics were used. The accuracy of Thematizer, measured with the F1 score, was then validated with ten novel test texts. All 160 texts were first manually analyzed for comparison against the results that the software yielded. The resulting F1 scores for Thematizer’s parsing functionality were then used as a metric for its operationalization of thematic theory via computational means. In turn, Thematizer’s degree of operationalization informed writers’ degree of accessibility to thematic theory.
In the identification of themes and rhemes, Thematizer achieved an F1 score of 85.8% for training texts and 92.0% for test texts (cf. 89.1% gold standard). The identification and classification of marked themes exceeded the gold standard of 89.1% through the training texts’ F1 score of 94.9% and the test texts’ F1 score of 93.4%. Finally, only training texts (F1 = 80.2%) exceeded the gold standard of 79.2% for the classification of thematic progression patterns, with test texts yielding an accuracy of F1 = 75.9%.
These findings indicate that Thematizer successfully operationalized marked theme identification and classification but was only able to partially operationalize the identification of themes and rhemes in text. Thematic progression, however, was inconsistently operationalized due to the wide range of F1 scores that Thematizer achieved and that were often below the gold standard. Operationalization and thereby accessibility to thematic theory were both facilitated by automated means, which represents a marked advancement in the computational treatment of theme, rheme and thematic progression.
Ultimately, the present work was able to forward thematic theory both conceptually and computationally. The inclusion of unmarked themes in conjunction with marked themes enriches thematic analyses by readily tracing GIVEN discourse topics through a text. Further delineation of marked themes into separate types and semantic subclasses reveals their functional, logical and contextualizing contribution to the discourse messages that follow. Visualization of the analytical results from the thematic analyses embedded within the user’s text in Thematizer’s web interface additionally affords greater interactability with thematic structure. Thematizer’s ability to analyze multiple documents and simultaneously present their results facilitates intertextual analyses that previous tools lacked. Including the option to export the results from the thematic analyses also provides users with agency over their own texts for subsequent use in their own research. Finally, the analytical results that Thematizer delivers can enable users to further reflect on the structural and logical development of their text
Pathology enters the proteomic era
Get PDFEach cell has a place in the order of the human body. Acting in synergy with each other, different cells assemble in conserved and self-organized structures, thereby generating tissues of diverse functionalities. The integrity of these functional units is crucial for human physiology and their imbalance may cause dysfunctionality or disease. The importance of tissue architecture was already acknowledged early on leading to the foundation of the field of pathology with fundamental discoveries form the entire organ down to the roles of single cells. In modern pathology, tissue-centered studies and omics technologies converge based on a broad portfolio of technologies, recently enhanced by artificial intelligence. Proteins provide the closest proxy to the actual phenotype of a cell; therefore, the field of proteomics is set to play a major role in modern pathology, informing on molecular protagonists in complex diseases. In particular, technological advances in mass spectrometry (MS)-based proteomics now allow sensitivity down to the single-level and enable high-throughput workflows, creating the pre-requisites for its application in the clinic.
This PhD thesis integrates pathology and MS-based proteomics to help develop a new era of molecular tissue analyses. It follows the transition from bulk to single-cell and single-cell type resolved proteomics while demonstrating the importance of spatial information on the proteome. To this end, I first contributed to the workflow optimization for formalin-fixed paraffin-embedded (FFPE) tissue, thereby enabling the processing of FFPE tissue in a high-throughput format while ensuring the robustness of the downstream data acquisition. Thereafter, I showcased this workflow on the interdisciplinary investigation of thrombosis in brown bears using laser-capture microdissection (LCM). Facing the global COVID-19 pandemic, I further streamlined the preparation of FFPE tissue and explored the impact of COVID-19 across organs and in particular, the heart during myocardial inflammation. My proteomics study demonstrates the importance of true tissue-specific effects beyond the systemic inflammatory response.
Thereafter, the thesis transitions toward the characterization of single cell types in the context of the architecture of tissue. I co-developed and optimized the novel technology of Deep Visual Proteomics (DVP) that integrates high-content imaging, artificial intelligence, LCM and ultra-sensitive mass spectrometry to uncover functional cellular heterogeneity in the native tissue environment. With this technology in hands, I set out to investigate serous borderline ovarian tumors in women of reproductive age and their transition to invasive low-grade serous cancer and subsequent metastasis. Here, we uncover mechanisms and key players in the malignant transition, such as the alternative splicing regulator NOVA2, and identify borderline tumors with micropapillary features as the intermediate transition stage. Next to the functional confirmation of these results, this study is also the very first to integrate DVP with spatial transcriptomics. Finally, I contributed to developing multiplexed MS data acquisition and its application to uncover the spatial human liver zonation at a single-cell level. In summary, proteomics-driven pathology has clearly become a powerful approach to study disease mechanisms and to enable precision medicine
Air temperature and the risk for cardiometabolic diseases – what are the underlying physiological mechanisms?
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Möglichkeiten des Anderen
Get PDFChange Management ist eine Managementmethode, die die Durchführung von Veränderungen in Organisationen unterstützt. Sie besteht aus einem Zusammenspiel von Führenden, Mitarbeitenden sowie einem strukturierten Veränderungsprozess. Selbst wenn neuere Ansätze seit den 2010er-Jahren ein dynamischeres Vorgehen behaupten, wird Change Management seit seiner Begründung nahezu unverändert angewandt.
Change Management wird in seinen Ausprägungen, Wirkungen und Logiken kritisch hinterfragt. Umfragen in betroffenen Unternehmen zeigen, dass Change Projekte kritisch gesehen werden und zu einem organisationalen Burn-out führen können. In einem dekonstruktiven Vorgehen werden die Change Management bestimmenden Merkmale einer analytisch-genealogischen Analyse unterzogen und seine konstitutiven Ausschlüsse offengelegt. Ein Beispiel dafür sind die Change Ziele eines jeden Veränderungsprozesses, die als neu und besser (als das Bestehende) verkündet werden, jedoch aus bekannten Versatzstücken der Gegenwart kalkuliert sind. Die Unberechenbarkeit einer Zukunft wird ausgeschlossen.
Der Begriff der organisationalen Veränderung wird entlang der aufgedeckten Ausschlüsse qualitativ neu ausgerichtet, sodass er nicht mehr dem Verständnis von Change Management entspricht. Diesen Arbeitsprozess unterstützen ausgesuchte Werke von Jacques Derrida und von Judith Butler. Nach Derridas Sprachphilosophie ereignen sich in jeder textlichen Wiederholung Veränderungen, für Butler bieten Wiederholungen sozialer Konventionen Gelegenheiten für deren Subversion. Beide Ansätze werden als Bewegungen von Veränderungen interpretiert und für organisationale Veränderungen neu gelesen. In den verschiedenen Ausprägungen des Zwischenraums finden sich Derridas Denkfiguren des Unentscheidbaren, Aporetischen und des Ereignisses, die für ein anderes Verständnis von Veränderung fruchtbar gemacht werden. Bei Butler werden Veränderungspotentiale in Zwischenräumen mit Blick auf Solidarität und Körperlichkeit thematisiert, die sich beispielsweise in Demonstrationen zeigen.
Im Fazit werden die Ergebnisse zusammengefasst und die Erkenntnisse für einen neuen Veränderungsbegriff formuliert. Es werden der Mehrwert einer poststrukturalistischen Philosophie für die Managementwissenschaften akzentuiert und in einem Ausblick weiterführende Forschungsfragen aufgezeigt
Genetic determination of symbiotic compatibility between Lotus species and rhizobia strains
Get PDFLegume crops greatly reduce the need for synthetic nitrogen fertilizers and thus have been indicated as central for sustainable agricultural practices. This results from a symbiosis with nitrogen-fixing rhizobia that provide legumes with nitrogen in exchange for carbohydrates in root organs known as nodules. In nature, legumes encounter the dilemma of whether to be selective on rhizobia symbiont but risk starvation or broaden the selectivity but increase the chance to be infected by ineffective rhizobia, which fix little to no nitrogen. Symbiosis between legumes and rhizobia is initiated after flavonoids in the root exudates induce the production of rhizobial Nod factors, which are perceived by the legume receptor complex. This molecular interaction determines the symbiotic compatibility between host and rhizobia species and triggers downstream rhizobia infection and root nodule organogenesis.
Variation in the symbiotic compatibility between legumes and rhizobia is observed between and within species. Here we investigate a Rhizobium leguminosarum strain Norway (Rl Norway) that nodulates different Lotus accessions without nitrogen fixation. Thus, it is considered a sub-compatible symbiont of Lotus. The most striking phenotype difference is between L. burttii and L. japonicus Gifu, as Rl Norway induces white nodules on L. burttii but fails to nodulate L. japonicus Gifu. A region associated with this variation in nodulation phenotype between L. burttii and L. japonicus Gifu was identified by quantitative trait locus (QTL) mapping, but the gene(s) responsible for the various symbiotic compatibility remained unknown. This study aimed to characterize candidate genes in the QTL region and reveal the putative regulatory mechanism mediating the symbiotic compatibility. To achieve this, phenotypic observation, transcriptomic sequencing, and genetic analysis were integrated.
We observed variation in symbiotic compatibility between Lotus accessions and Ensifer and Allorhizobium strains in addition to Rl Norway. Moreover, the substrate moisture affected the symbiotic compatibility between L. japonicus Gifu and Rl Norway, resulting in the nodulation of L. japonicus Gifu in high substrate moisture. Transcriptome analyses revealed that several genes involved in the flavonoid biosynthesis were downregulated in L. japonicus Gifu grown in high moisture. We hypothesized that the accumulation of intermediates in the flavonoid biosynthesis pathway alters the symbiotic compatibility in high moisture. Naringenin, a flavonoid compound that is predicted to accumulate in high moisture was applied to roots and its effect on nodule formation and rhizobia colonization was evaluated. Transcriptomic analyses also showed that Rl Norway activated the symbiosis response in L. burttii but not in L. japonicus Gifu. Phenotyping the F1 progeny of a cross between L. burttii and L. japonicus Gifu indicated that the nodulation phenotype of L. burttii is dominant. Four genes encoding receptor-like proteins (RLPs) in the QTL region were identified as candidates that contribute to the symbiotic compatibility, named RLP1 to RLP4. An additive effect between RLP2 and RLP4 on nodule formation was observed by trans-complementing RLP2 and RLP4 from L. burttii into L. japonicus Gifu. Furthermore, mutant lines of the RLPs were generated by the CRISPR-Cas12a gene-editing method for future studies. Altogether, we identified candidate genes that contribute to the different symbiotic compatibility between L. burttii and L. japonicus Gifu and showed the variation in symbiotic compatibility between L. japonicus Gifu and Rl Norway is altered by substrate moisture
