Kulturelle Wissensnetzwerke

Das volle Potenzial des Computers wird in der Theoriefindung der Geistes-, Sozial- und Kulturwissenschaften zu selten ausgeschöpft. Um dies zu ermöglichen, versuchte diese Arbeit die Grundlagen des Wissens aus der Perspektive der Kommunikationswissenschaft zu analysieren. Die gewonnenen Erkenntnisse wurden als Framework für eine möglichst konkrete, informatische Konzept verarbeitet. Eine der grundlegenden Annahmen für die Entwicklung des kommunikationswissenschaftlichen Frameworks, war die fraktale Organisation unseres Universums. D.h. auch unser Wissen besteht aus immer gleichen Bausteinen in unterschiedlichen Kombinationen. Der Anfang der Suche nach den Fraktalen des Wissens war die uns allen gemeine Erfahrung der Raumzeit und führte zur modernen, komplexen Gesellschaft. Die Betrachtung der kommunikativen Phänomenologie in der Gesellschaft im Zusammenhang mit den Begriffen Netzwerk und Wissen schließt die Suche ab. Bei allen Analysen wurde immer die prinzipiellen Möglichkeiten des Computers mit bedacht.The potential of computers in the theoretical work in the field of humanities, social and cultural sciences is not fully tapped. To allow this to happen, this research tried to analyze the fundamentals of knowledge from the perspective of communication science. The findings were used as a framework for a concrete as possible, informatic concept. One of the basic assumptions for the development of this communication scientific Framework was the fractal organization of our universe. This means that our knowledge is built from combining the same basic components. The ultimate starting point for searching the basic fractals of our knowledge was the basic spatiotemporal human expierience and lead to the complex, modern society. The examination of the phenomenology of communication with regards to the terms network and knowledge was the end-point of this analysis. Through all this research the possibilities of computers served as a guideline

Characterization of three new imatinib-responsive fusion genes in chronic myeloproliferative disorders generated by disruption of the platelet-derived growth factor receptor beta gene

Background and Objectives: We sought to identify new fusion genes with involvement of the platelet-derived growth factor receptor ß gene (PDGFRB) in three patients presenting with various subtypes of chronic myeloproliferative disorders associated with chromosomal aberrations involving chromosome bands 5q31–33.Design and Methods: We performed 5' rapid amplification of cDNA ends (5'-RACE)-polymerase chain reaction (PCR) with RNA/cDNA derived from a patient (case #1) with a t(5;12)(q31–33;q24) and a second patient (case #2) with a complex rearrangement involving chromosomes 1, 5 and 11. A newly developed DNA-based ‘longdistance inverse PCR’ (LDI-PCR) was performed on a third patient (case #3) with a t(4;5;5)(q23;q31;q33).Results: In cases #1 and #2, we identified mRNA fusions between GIT2 exon 12 and GPIAP1 exon 7, respectively, and PDGFRB exon 11. In case #3, LDI-PCR revealed a fusion between PRKG2 exon 5 and a truncated PDGFRB exon 12. The region encoding the catalytic domain of PDGFRß is retained in all three cases, with the partner contributing a coiled-coil domain (GPIAP1, PRKG2) or an ankyrin protein interaction motif (GIT2) that may potentially lead to dimerization and constitutive activation of the fusion proteins. Treatment with imatinib (400 mg/day) has led to sustained complete hematologic remission in all three patients.Interpretation and Conclusions: These data provide further evidence that numerous partner genes fuse to PDGFRB in BCR-ABL negative chronic myeloproliferative disorders. Although these fusion genes occur rarely, their identification is essential in order to detect patients in whom targeted treatment with tyrosine kinase inhibitors is likely to be successful

Machine learning-powered antibiotics phenotypic drug discovery

Identification of novel antibiotics remains a major challenge for drug discovery. The present study explores use of phenotypic readouts beyond classical antibacterial growth inhibition adopting a combined multiparametric high content screening and genomic approach. Deployment of the semi-automated bacterial phenotypic fingerprint (BPF) profiling platform in conjunction with a machine learning-powered dataset analysis, effectively allowed us to narrow down, compare and predict compound mode of action (MoA). The method identifies weak antibacterial hits allowing full exploitation of low potency hits frequently discovered by routine antibacterial screening. We demonstrate that BPF classification tool can be successfully used to guide chemical structure activity relationship optimization, enabling antibiotic development and that this approach can be fruitfully applied across species. The BPF classification tool could be potentially applied in primary screening, effectively enabling identification of novel antibacterial compound hits and differentiating their MoA, hence widening the known antibacterial chemical space of existing pharmaceutical compound libraries. More generally, beyond the specific objective of the present work, the proposed approach could be profitably applied to a broader range of diseases amenable to phenotypic drug discovery.ISSN:2045-232

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support

The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease