Einfluss der zervikalen Schlingenkonisation auf Schwangerschaft und Geburt

Fragestellung: Die Studie untersucht die Auswirkungen der zur CIN-Behandlung eingesetzten LEEP auf die nachfolgende Schwangerschaft und Geburt. Methodik: Retrospektiv wurden 938 Frauen analysiert, die zwischen 2002 und 2013 eine Schlingenkonisation an der Universitätsfrauenklinik Jena erhielten. 66 nach der LEEP eingetretene Einlingsschwangerschaften wurden 122 Graviditäten gegenübergestellt, welche vor der LEEP lagen. Die Informationen wurden mittels eines selbsterstellten Fragebogens bzw. der Krankenakte erhoben. Ergebnisse: Das Frühgeburtsrisiko nach der LEEP war im Vergleich zur Kontrollgruppe nicht signifikant erhöht (p=0,127; OR=2,242; 95 %-CI [0,862-5,831]). Infolge der Adjustierung nach mütterlichem Alter und Zervixinsuffizienz relativierte sich der Einfluss der LEEP weiter (OR=1,199; 95 %-CI [0,400-3,594]). In der Studiengruppe lag die Frühgeburtenrate bei 15,2 % und im Kontrollkollektiv bei 7,4 %. Beide Gruppen unterschieden sich weder bei der Schwangerschaftswoche der Geburt (39,3 vs. 39,8 SSW; p=0.103) noch bezüglich des Geburtsgewichtes (3281±575 g vs. 3266±501 g; p=0,857) signifikant. Eine Steigerung der Schwangerschafts- (51,5 vs. 52,5 %; p=1,000) und Geburtskomplikationen nach der LEEP konnte nicht beobachtet werden (42,4 vs. 47,5 %; p=0.542). Lediglich eine Zervixinsuffizienz (16,7 vs. 5,7 %; p=0,020) und eine operative Entbindung (35,4 vs. 14,8 %; p=0,002; OR=3,164) kamen nach der LEEP häufiger vor. Schlussfolgerung: Die Schwierigkeit der Analyse liegt im komplexen Netz aus Einflussfaktoren auf die Frühgeburtenrate. Im Gegensatz zu anderen Studien wurde nicht die geburtshilfliche Allgemeinbevölkerung als Kontrollgruppe eingesetzt, sondern Frauen, die sich nach der Indexschwangerschaft einer LEEP unterzogen. Hintergrund ist die Minimierung gruppencharak-teristischer Merkmale, welche möglicherweise die Frühgeburtlichkeit unabhängig vom operativen Eingriff beeinflussen

Kohärente Softwareentwicklung: Grundlagen, Arbeitsumgebungen, Vorgehensweisen

Bei der Entwicklung von Softwaresystemen werden die unterschiedlichen Aspekte und Facetten des zu entwickelnden Systems getrennt betrachtet und entsprechend getrennt voneinander modelliert. Eine wiederkehrende Herausforderung in der Softwareentwicklung ist die Zusammenführung der so entstandenen Teilmodelle zu einem konsistenten Gesamtmodell des Softwaresystems. Wir stellen hierzu mit den Modell-Suiten einen Ansatz vor, mit dessen Hilfe sich solche Modelle integrieren, auf Konsistenz prüfen und konsistent weiterentwickeln lassen. Die Beiträge bestehender Entwicklungswerkzeuge und Arbeitsumgebungen zur Unterstützung dieses Ansatzes werden dazu untersucht. Die sich daraus ergebenden Ergänzungen bestehender Arbeitsumgebungen werden diskutiert und an Beispielen demonstriert. Die Arbeit zeigt, wie Risiken, Mehrdeutigkeiten und Widersprüche, die bei Verwendung unterschiedlicher Modellierungssprachen und Modellierungswerkzeuge entstehen, durch den Einsatz von Modell-Suiten reduziert und vermieden werden

Quality control for terms and definitions in ontologies and taxonomies

BACKGROUND: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO), the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. RESULTS: We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. CONCLUSION: Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation

Graph-based analysis and visualization of experimental results with ONDEX

Motivation: Assembling the relevant information needed to interpret the output from high-throughput, genome scale, experiments such as gene expression microarrays is challenging. Analysis reveals genes that show statistically significant changes in expression levels, but more information is needed to determine their biological relevance. The challenge is to bring these genes together with biological information distributed across hundreds of databases or buried in the scientific literature (millions of articles). Software tools are needed to automate this task which at present is labor-intensive and requires considerable informatics and biological expertise. Results: This article describes ONDEX and how it can be applied to the task of interpreting gene expression results. ONDEX is a database system that combines the features of semantic database integration and text mining with methods for graph-based analysis. An overview of the ONDEX system is presented, concentrating on recently developed features for graph-based analysis and visualization. A case study is used to show how ONDEX can help to identify causal relationships between stress response genes and metabolic pathways from gene expression data. ONDEX also discovered functional annotations for most of the genes that emerged as significant in the microarray experiment, but were previously of unknown function

Neurological Disorders and Publication Abstracts Follow Elements of Social Network Patterns when Indexed Using Ontology Tree-Based Key Term Search

Disorders of the Central Nervous System (CNS) are worldwide causes of morbidity and mortality. In order to further investigate the nature of the CNS research, we generate from an initial reference a controlled vocabulary of CNS disorder-related terms and ontological tree structure for this vocabulary, and then apply the vocabulary in an analysis of the past ten years of abstracts (N = 10,488) from a major neuroscience journal. Using literal search methodology with our terminology tree, we find over 5,200 relationships between abstracts and clinical diagnostic topics. After generating a network graph of these document-topic relationships, we find that this network graph contains characteristics of document-author and other human social networks, including evidence of scale-free and power law-like node distributions. However, we also found qualitative evidence for Z-normal-type (albeit logarithmically skewed) distributions within disorder popularity. Lastly, we discuss potential consumer-centered as well as clinic-centered uses for our ontology and search methodology

Rekonstruktion und Analyse interzellulärer Signalnetzwerke

Skusa A. Reconstruction and analysis of intercellular signaling networks. Bielefeld (Germany): Bielefeld University; 2006.Cells in the human body communicate over long distances via two systems, the humoral system and the neuronal system. The humoral system works via first messenger substances, such as hormones, cytokines and neurotransmitters, which are released into the blood. Biomedical knowledge on this kind of intercellular signaling is well established, but in contrast to signaling processes inside cells, not much of this knowledge exists in a form that is easily accessible for automated approaches, such as databases or ontologies. Most of what is known about extracellular signaling is stored in terms of natural language text in the scientific literature. The present study aims at the reconstruction and analysis of cell-cell signaling pathways by applying automated approaches. Therefore, relevant data is extracted from molecular databases as well as from biomedical literature by applying concept based text mining. For this purpose, models and corresponding graph representations are developed to assemble intercellular signals from partial information since available data sources are scattered and incomplete. The resulting information is finally applied to generate hypotheses on cell-cell signaling in the context of neurodegenerative diseases. More specifically, from the few molecular databases containing appropriate data, one database is tested in a preliminary study and reconstruction approaches accessing the specific structure of this database are developed. To reconstruct information from natural language text, ONDEX, a framework for ONtological text inDEXing and data integration has been developed in a collaborative work. ONDEX supports concept based approaches, i.e. databases and ontologies are integrated into a standardized graph-based framework, where biological entities as concepts are linked by relations (i.e., "is-a", "part-of" or "synonym"). A major part of this thesis is the development and the integration of concept based text indexing and concept based co-occurrence searches into ONDEX. On this basis, MEDLINE abstracts are mapped to concepts of a number of ontologies (e.g., Gene Ontology, MeSH terms and Cell Ontology) and mined for relevant parts of intercellular signaling. From these relations finally, cell-cell signaling hypotheses are assembled. Whereas the networks resulting from the database reconstruction are not sufficient for reasonable analysis and further use, evaluations of the text mining results show that a significant number of known facts can be found by applying concept based co-occurrences searches. Finally, the text extraction results are reduced to a manageable amount of concept based co-occurrence hits and hypotheses for cell types involved in neurodegenerative diseases. In this case a number of known facts are reconstructed and suggestions for further improvements are made. The text extraction results demonstrate the possibility to reconstruct relations between biological entities from text by applying a concept based framework and thus, how a large text set can be reduced to a number of hypotheses allowing manual examination

Suchmaschinen: Status Quo und Entwicklungstendenzen

This article deals with search engines and their prospective developement. Apart from Google, Yahoo! and Microsoft, there are new alternative services that need to be analysed

Der Markt für Internet-Suchmaschinen

This article deals with the current situation on the search engine market and alternative search approaches. The opportunities for new competitors are analysed, as well