Rekonstruktion von Gen-Interaktionsnetzen durch in vitro RNA Interferenz und globale Expressionsanalyse

In dieser Arbeit wurde durch die Kombination von gezielten posttranskriptionellen Genstilllegungen mit Hilfe von sequenzspezifischen siRNAs und anschließender genomweiter Expressionsanalyse mit cDNA Microarrays die Rekonstruktion von Gen-Interaktionsnetzwerken in der ER-positiven Mammakarzinom Zelllinie MCF-7 etabliert. Zunächst wurden die verfügbaren Techniken der RNA Interferenz und der genomweiten Expressionsanalyse grundlegend an die Fragestellung und die Bedingungen der MCF-7 Zelllinie angepasst. Durch die Experimente wurden hochwertige Messdaten für die statistische Auswertung der Messungen zur Erstellung bzw. Rekonstruktion von Netzwerken erstellt. Der "Nested Effects Model" (NEM) Netzwerk Algorithmus konnte durch unterschiedliche Vergleiche (Literaturdaten, Epistaseanalyse und Connectivity Map Datenbank) mehrfach biologisch validiert werden. Durch die Interpretation des transitiv reduzierten, gerichteten Graphen der statistischen Analyse mit dem NEM Algorithmus konnte der bisher nicht beschriebene aktivierende Effekt der CCNG2 Expression auf die Expression von ESR1 dargestellt werden. Die Vergleiche der Expressionsprofile nach Silencing von AKT2 bzw. XBP1 mit den Experimenten der Connectivity Map Datenbank zeigten starke Korrelationen zu Behandlungen von MCF-7 Zellen mit antiestrogenen Substanzen (Fulvestrant und Raloxifen) bzw. PI3K Inhibitoren (Wortmannin und LY294002). Aufgrund dieser Ergebnisse, sowie der Positionierung der beiden Gene oberhalb des Estrogenrezeptors im postulierten NEM-Interaktionsnetzwerk, wurden AKT2 und XBP1 als potentielle neue therapeutische Ziele in der Behandlung von estrogenabhängigen Mammakarzinomen postuliert. Durch einen Vergleich der Expressionsänderung nach Stimulation des Estrogenrezeptors mit 17-Estradiol bzw. Inhibition mit Tamoxifen und der gezielten Stilllegung durch sequenzspezifische siRNAs in Form von hierarchischen Clusteranalysen konnte der transkriptionelle Kofaktor FHL2 als weiteres potentielles therapeutisches Ziel postuliert werden

Predicting pathway membership via domain signatures

Motivation: Functional characterization of genes is of great importance for the understanding of complex cellular processes. Valuable information for this purpose can be obtained from pathway databases, like KEGG. However, only a small fraction of genes is annotated with pathway information up to now. In contrast, information on contained protein domains can be obtained for a significantly higher number of genes, e.g. from the InterPro database

Large scale statistical inference of signaling pathways from RNAi and microarray data

<p>Abstract</p> <p>Background</p> <p>The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray technology this enables researchers to gain insights into signaling pathways by observing downstream effects of individual knock-downs on gene expression. These secondary effects can be used to computationally reverse engineer features of the upstream signaling pathway.</p> <p>Results</p> <p>In this paper we address this challenging problem by extending previous work by Markowetz <it>et al</it>., who proposed a statistical framework to score networks hypotheses in a Bayesian manner. Our extensions go in three directions: First, we introduce a way to omit the data discretization step needed in the original framework via a calculation based on <it>p</it>-values instead. Second, we show how prior assumptions on the network structure can be incorporated into the scoring scheme using regularization techniques. Third and most important, we propose methods to scale up the original approach, which is limited to around 5 genes, to large scale networks.</p> <p>Conclusion</p> <p>Comparisons of these methods on artificial data are conducted. Our proposed module network is employed to infer the signaling network between 13 genes in the ER-<it>α </it>pathway in human MCF-7 breast cancer cells. Using a bootstrapping approach this reconstruction can be found with good statistical stability.</p> <p>The code for the module network inference method is available in the latest version of the <it>R</it>-package <it>nem</it>, which can be obtained from the Bioconductor homepage.</p

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management

Neuromuscular Consequences of an Extreme Mountain Ultra-Marathon

We investigated the physiological consequences of one of the most extreme exercises realized by humans in race conditions: a 166-km mountain ultra-marathon (MUM) with 9500 m of positive and negative elevation change. For this purpose, (i) the fatigue induced by the MUM and (ii) the recovery processes over two weeks were assessed. Evaluation of neuromuscular function (NMF) and blood markers of muscle damage and inflammation were performed before and immediately following (n = 22), and 2, 5, 9 and 16 days after the MUM (n = 11) in experienced ultra-marathon runners. Large maximal voluntary contraction decreases occurred after MUM (−35% [95% CI: −28 to −42%] and −39% [95% CI: −32 to −46%] for KE and PF, respectively), with alteration of maximal voluntary activation, mainly for KE (−19% [95% CI: −7 to −32%]). Significant modifications in markers of muscle damage and inflammation were observed after the MUM as suggested by the large changes in creatine kinase (from 144±94 to 13,633±12,626 UI L−1), myoglobin (from 32±22 to 1,432±1,209 µg L−1), and C-Reactive Protein (from <2.0 to 37.7±26.5 mg L−1). Moderate to large reductions in maximal compound muscle action potential amplitude, high-frequency doublet force, and low frequency fatigue (index of excitation-contraction coupling alteration) were also observed for both muscle groups. Sixteen days after MUM, NMF had returned to initial values, with most of the recovery process occurring within 9 days of the race. These findings suggest that the large alterations in NMF after an ultra-marathon race are multi-factorial, including failure of excitation-contraction coupling, which has never been described after prolonged running. It is also concluded that as early as two weeks after such an extreme running exercise, maximal force capacities have returned to baseline

Introduction to geography

xx, 453 p. : ill. ; 27 c

Human Geography: Landscapes of Human Activities (Twelfth Edition)

This twelfth edition of Human Geography retains the organization and structure of its earlier versions. Like them, it seeks to introduce its users to the scope and excitement of geography and its relevance to their daily lives and roles as informed citizens. We recognize that for any students, human geography may be their first or only work in geography and this, their first or only textbook in the discipline. For these students particularly, we seek to convey the richness and breadth of human geography and to give insight into the nature and intellectual challenges of the field of geography itself