TY - JOUR A1 - Palige, Katja A1 - Linde, Jörg A1 - Martin, Ronny A1 - Böttcher, Bettina A1 - Citiulo, Francesco A1 - Sullivan, Derek J. A1 - Weber, Johann A1 - Staib, Claudia A1 - Rupp, Steffen A1 - Hube, Bernhard A1 - Morschhäuser, Joachim A1 - Staib, Peter T1 - Global Transcriptome Sequencing Identifies Chlamydospore Specific Markers in Candida albicans and Candida dubliniensis JF - PLoS ONE N2 - Candida albicans and Candida dubliniensis are pathogenic fungi that are highly related but differ in virulence and in some phenotypic traits. During in vitro growth on certain nutrient-poor media, C. albicans and C. dubliniensis are the only yeast species which are able to produce chlamydospores, large thick-walled cells of unknown function. Interestingly, only C. dubliniensis forms pseudohyphae with abundant chlamydospores when grown on Staib medium, while C. albicans grows exclusively as a budding yeast. In order to further our understanding of chlamydospore development and assembly, we compared the global transcriptional profile of both species during growth in liquid Staib medium by RNA sequencing. We also included a C. albicans mutant in our study which lacks the morphogenetic transcriptional repressor Nrg1. This strain, which is characterized by its constitutive pseudohyphal growth, specifically produces masses of chlamydospores in Staib medium, similar to C. dubliniensis. This comparative approach identified a set of putatively chlamydospore-related genes. Two of the homologous C. albicans and C. dubliniensis genes (CSP1 and CSP2) which were most strongly upregulated during chlamydospore development were analysed in more detail. By use of the green fluorescent protein as a reporter, the encoded putative cell wall related proteins were found to exclusively localize to C. albicans and C. dubliniensis chlamydospores. Our findings uncover the first chlamydospore specific markers in Candida species and provide novel insights in the complex morphogenetic development of these important fungal pathogens. KW - NRG1 KW - staib agar KW - gene KW - morphogenesis KW - expression KW - regulator KW - virulence KW - growth KW - UME6 KW - epidemiology Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-131007 VL - 8 IS - 4 ER - TY - JOUR A1 - Dörhöfer, Lena A1 - Lammert, Alexander A1 - Krane, Vera A1 - Gorski, Mathias A1 - Banas, Bernhard A1 - Wanner, Christoph A1 - Krämer, Bernhard K. A1 - Heid, Iris M. A1 - Böger, Carsten A. T1 - Study design of DIACORE (DIAbetes COhoRtE) - a cohort study of patients with diabetes mellitus type 2 JF - BMC Medical Genetics N2 - Background: Diabetes mellitus type 2 (DM2) is highly associated with increased risk for chronic kidney disease (CKD), end stage renal disease (ESRD) and cardiovascular morbidity. Epidemiological and genetic studies generate hypotheses for innovative strategies in DM2 management by unravelling novel mechanisms of diabetes complications, which is essential for future intervention trials. We have thus initiated the DIAbetes COhoRtE study (DIACORE). Methods: DIACORE is a prospective cohort study aiming to recruit 6000 patients of self-reported Caucasian ethnicity with prevalent DM2 for at least 10 years of follow-up. Study visits are performed in University-based recruiting clinics in Germany using standard operating procedures. All prevalent DM2 patients in outpatient clinics surrounding the recruiting centers are invited to participate. At baseline and at each 2-year follow-up examination, patients are subjected to a core phenotyping protocol. This includes a standardized online questionnaire and physical examination to determine incident micro-and macrovascular DM2 complications, malignancy and hospitalization, with a primary focus on renal events. Confirmatory outcome information is requested from patient records. Blood samples are obtained for a centrally analyzed standard laboratory panel and for biobanking of aliquots of serum, plasma, urine, mRNA and DNA for future scientific use. A subset of the cohort is subjected to extended phenotyping, e. g. sleep apnea screening, skin autofluorescence measurement, non-mydriatic retinal photography and non-invasive determination of arterial stiffness. Discussion: DIACORE will enable the prospective evaluation of factors involved in DM2 complication pathogenesis using high-throughput technologies in biosamples and genetic epidemiological studies. KW - chronic kidney-disease KW - stage renal-disease KW - glomerular-filtration-rate KW - genome-wide association KW - blood-glucose control KW - genetics KW - serum creatinine KW - cardiovascular disease KW - replacement therapy KW - United States KW - risk factors KW - diabetes mellitus type 2 KW - diabetic nephropathy KW - end stage renal disease KW - cardiovascular morbidity KW - diabetes complications KW - epidemiology Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-122040 SN - 1471-2350 VL - 14 IS - 25 ER - TY - THES A1 - Pröll, Sebastian T1 - Stability of Switched Epidemiological Models T1 - Stabilität geschalteter epidemiologischer Modelle N2 - In this thesis it is shown how the spread of infectious diseases can be described via mathematical models that show the dynamic behavior of epidemics. Ordinary differential equations are used for the modeling process. SIR and SIRS models are distinguished, depending on whether a disease confers immunity to individuals after recovery or not. There are characteristic parameters for each disease like the infection rate or the recovery rate. These parameters indicate how aggressive a disease acts and how long it takes for an individual to recover, respectively. In general the parameters are time-varying and depend on population groups. For this reason, models with multiple subgroups are introduced, and switched systems are used to carry out time-variant parameters. When investigating such models, the so called disease-free equilibrium is of interest, where no infectives appear within the population. The question is whether there are conditions, under which this equilibrium is stable. Necessary mathematical tools for the stability analysis are presented. The theory of ordinary differential equations, including Lyapunov stability theory, is fundamental. Moreover, convex and nonsmooth analysis, positive systems and differential inclusions are introduced. With these tools, sufficient conditions are given for the disease-free equilibrium of SIS, SIR and SIRS systems to be asymptotically stable. N2 - In der vorliegenden Arbeit werden Möglichkeiten aufgezeigt, wie man die Ausbreitung von Infektionskrankheiten mit Hilfe von mathematischen Modellen beschreiben kann. Anhand solcher Modelle möchte man mehr über die Dynamik von Epidemien lernen und vorhersagen, wie sich eine gegebene Infektionskrankheit innerhalb einer Population ausbreitet. Zunächst werden gewöhnliche Differentialgleichungen verwendet, um grundlegende epidemiologische Modelle aufzustellen. Hierbei unterscheidet man sogenannte SIR und SIS Modelle, je nachdem ob die betrachtete Krankheit einem Individuum nach seiner Heilung Immunität verleiht oder nicht. Charakteristisch für Infektionskrankheiten sind Parameter wie die Infektionsrate oder die Heilungsrate. Sie geben an, wie ansteckend eine Krankheit ist bzw. wie schnell eine Person nach einer Erkrankung wieder gesund wird. Im Allgemeinen sind diese Parameter abhängig von bestimmten Bevölkerungsgruppen und verändern sich mit der Zeit. Daher werden am Ende des zweiten Kapitels Modelle entwickelt, die die Betrachtung mehrerer Bevölkerungsgruppen zulassen. Zeitvariante Parameter werden durch die Verwendung geschalteter Systeme berücksichtigt. Bei der Untersuchung solcher Systeme ist derjenige Zustand von besonderem Interesse, bei dem innerhalb der Bevölkerung keine Infizierten auftreten, die gesamte Bevölkerung also von der betrachteten Krankheit frei bleibt. Es stellt sich die Frage, unter welchen Bedingungen sich dieser Zustand nach einer Infizierung der Bevölkerung im Laufe der Zeit von selbst einstellt. Mathematisch gesehen untersucht man die triviale Ruhelage des Systems, bei der keine Infizierten existieren, auf Stabilität. Für die Stabilitätsanalyse sind einige mathematische Begriffe und Aussagen notwendig, die im zweiten Kapitel bereitgestellt werden. Grundlegend ist die Theorie gewöhnlicher Differentialgleichungen, einschließlich der Stabilitätstheorie von Lyapunov. Darüberhinaus kommen wichtige Erkenntnisse aus den Gebieten Konvexe und Nichtglatte Analysis, Positive Systeme und Differentialinklusionen. Ausgestattet mit diesen Hilfsmitteln werden im vierten Kapitel Sätze bewiesen, die hinreichende Bedingungen dafür angegeben, dass die triviale Ruhelage in geschalteten SIS, SIR und SIRS Systemen asymptotisch stabil ist. KW - epidemiology KW - switched systems KW - ordinary differential equations KW - stability analysis KW - Epidemiologie KW - Geschaltete Systeme KW - Gewöhnliche Differentialgleichungen KW - Stabilitätsanalyse KW - Gewöhnliche Differentialgleichung KW - Stabilität KW - Epidemiologie Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-108573 ER -