TY - JOUR A1 - Boelch, Sebastian Philipp A1 - Rüeckl, Kilian A1 - Streck, Laura Elisa A1 - Szewczykowski, Viktoria A1 - Weißenberger, Manuel A1 - Jakuscheit, Axel A1 - Rudert, Maximilian T1 - Diagnosis of chronic infection at total hip arthroplasty revision is a question of definition JF - Biomed Research International N2 - Purpose. Contradicting definitions of periprosthetic joint infection (PJI) are in use. Joint aspiration is performed before total hip arthroplasty (THA) revision. This study investigated the influence of PJI definition on PJI prevalence at THA revision. Test quality of prerevision aspiration was evaluated for the different PJI definitions. Methods. 256 THA revisions were retrospectively classified to be infected or not infected. Classification was performed according to the 4 different definitions proposed by the Musculoskeletal Infection Society (MSIS), the Infectious Diseases Society of America (IDSA), the International Consensus Meeting (ICM), and the European Bone and Joint Infection Society (EBJIS). Only chronic PJIs were included. Results. PJI prevalence at revision significantly correlated with the applied PJI definition (p=0.01, Cramer's V=0.093). PJI prevalence was 20.7% for the MSIS, 25.4% for the ICM, 28.1% for the IDSA, and 32.0% for the EBJIS definition. For synovial fluid white blood cell count, the best ROC-AUC for predicting PJI was 0.953 in combination with the MSIS definition. Conclusion. PJI definition significantly influences the rate of diagnosed PJIs at THA revision. Synovial fluid white blood cell count is a reliable means to rule out PJI. In cases with a borderline high synovial white blood cell count before THA revision as the only sign of chronic PJI, an extended diagnostic work-up should be considered. KW - periprosthetic joint infection KW - algorithm KW - consensus Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-265762 VL - 2021 ER - TY - JOUR A1 - Dietz, Andreas J. A1 - Conrad, Christopher A1 - Kuenzer, Claudia A1 - Gesell, Gerhard A1 - Dech, Stefan T1 - Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data JF - Remote Sensing N2 - Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation. KW - AVHRR data KW - satellite KW - Northern Xinjiang KW - cloud KW - products KW - Central Asia KW - climate change KW - Amu Darya KW - Syr Darya KW - Tian Shan KW - snow KW - snow cover KW - snow cover duration KW - Pamir KW - AVHRR KW - MODIS KW - algorithm KW - validation Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114470 SN - 2072-4292 VL - 6 IS - 12 ER - TY - JOUR A1 - Egenolf, Nadine A1 - Altenschildesche, Caren Meyer zu A1 - Kreß, Luisa A1 - Eggermann, Katja A1 - Namer, Barbara A1 - Gross, Franziska A1 - Klitsch, Alexander A1 - Malzacher, Tobias A1 - Kampik, Daniel A1 - Malik, Rayaz A. A1 - Kurth, Ingo A1 - Sommer, Claudia A1 - Üçeyler, Nurcan T1 - Diagnosing small fiber neuropathy in clinical practice: a deep phenotyping study JF - Therapeutic Advances in Neurological Disorders N2 - Background and aims: Small fiber neuropathy (SFN) is increasingly suspected in patients with pain of uncertain origin, and making the diagnosis remains a challenge lacking a diagnostic gold standard. Methods: In this case–control study, we prospectively recruited 86 patients with a medical history and clinical phenotype suggestive of SFN. Patients underwent neurological examination, quantitative sensory testing (QST), and distal and proximal skin punch biopsy, and were tested for pain-associated gene loci. Fifty-five of these patients additionally underwent pain-related evoked potentials (PREP), corneal confocal microscopy (CCM), and a quantitative sudomotor axon reflex test (QSART). Results: Abnormal distal intraepidermal nerve fiber density (IENFD) (60/86, 70%) and neurological examination (53/86, 62%) most frequently reflected small fiber disease. Adding CCM and/or PREP further increased the number of patients with small fiber impairment to 47/55 (85%). Genetic testing revealed potentially pathogenic gene variants in 14/86 (16%) index patients. QST, QSART, and proximal IENFD were of lower impact. Conclusion: We propose to diagnose SFN primarily based on the results of neurological examination and distal IENFD, with more detailed phenotyping in specialized centers. KW - algorithm KW - diagnosis KW - neurological examination KW - skin punch biopsy KW - small fiber neuropathy Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232019 SN - 1756-2864 VL - 14 ER - TY - JOUR A1 - Kunz, Meik A1 - Wolf, Beat A1 - Schulze, Harald A1 - Atlan, David A1 - Walles, Thorsten A1 - Walles, Heike A1 - Dandekar, Thomas T1 - Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools JF - Genes N2 - Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs. KW - lung cancer KW - non-invasive biomarkers KW - miRNAs KW - lncRNAs KW - bioinformatics KW - early diagnosis KW - algorithm Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147990 VL - 8 IS - 1 ER - TY - THES A1 - Liang, Chunguang T1 - Tools for functional genomics applied to Staphylococci, Listeriae, Vaccinia virus and other organisms N2 - Genome sequence analysis A combination of genome analysis application has been established here during this project. This offers an efficient platform to interactively compare similar genome regions and reveal loci differences. The genes and operons can be rapidly analyzed and local collinear blocks (LCBs) categorized according to their function. The features of interests are parsed, recognized, and clustered into reports. Phylogenetic relationships can be readily examined such as the evolution of critical factors or a certain highly-conserved region. The resulting platform-independent software packages (GENOVA and inGeno), have been proven to be efficient and easy to handle in a number of projects. The capabilities of the software allowed the investigation of virulence factors, e.g., rsbU, strains’ biological design, and in particular pathogenicity feature storage and management. We have successfully investigated the genomes of Staphylococcus aureus strains (COL, N315, 8325, RN1HG, Newman), Listeria spp. (welshimeri, innocua and monocytogenes), E.coli strains (O157:H7 and MG1655) and Vaccinia strains (WR, Copenhagen, Lister, LIVP, GLV-1h68 and parental strains). Metabolic network analysis Our YANAsquare package offers a workbench to rapidly establish the metabolic network of such as Staphylococcous aureus bacteria in genome-scale size as well as metabolic networks of interest such as the murine phagosome lipid signalling network. YANAsquare recruits reactions from online databases using an integrated KEGG browser. This reduces the efforts in building large metabolic networks. The involved calculation routines (METATOOL-derived wrapper or native Java implementation) readily obtain all possible flux modes (EM/EP) for metabolite fluxes within the network. Advanced layout algorithms visualize the topological structure of the network. In addition, the generated structure can be dynamically modified in the graphic interface. The generated network as well as the manipulated layout can be validated and stored (XML file: scheme of SBML level-2). This format can be further parsed and analyzed by other systems biology software, such as CellDesigner. Moreover, the integrated robustness-evaluation routine is able to examine the synthesis rates affected by each single mutation throughout the whole network. We have successfully applied the method to simulate single and multiple gene knockouts, and the affected fluxes are comprehensively revealed. Recently we applied the method to proteomic data and extra-cellular metabolite data of Staphylococci, the physiological changes regarding the flux distribution are studied. Calculations at different time points, including different conditions such as hypoxia or stress, show a good fit to experimental data. Moreover, using the proteomic data (enzyme amounts) calculated from 2D-Gel-EP experiments our study provides a way to compare the fluxome and the enzyme expression. Oncolytic vaccinia virus (VACV) We investigated the genetic differences between the de novo sequence of the recombinant oncolytic GLV-1h68 and other related VACVs, including function predictions for all found genome differences. Our phylogenetic analysis indicates that GLV-1h68 is closest to Lister strains but has lost several ORFs present in its parental LIVP strain, including genes encoding CrmE and a viral Golgi anti-apoptotic protein, v-GAAP. Functions of viral genes were either strain-specific, tissue-specific or host-specific comparing viral genes in the Lister, WR and COP strains. This helps to rationally design more optimized oncolytic virus strains to benefit cancer therapy in human patients. Identified differences from the comparison in open reading frames (ORFs) include genes for host-range selection, virulence and immune modulation proteins, e.g. ankyrin-like proteins, serine proteinase inhibitor SPI-2/CrmA, tumor necrosis factor (TNF) receptor homolog CrmC, semaphorin-like and interleukin-1 receptor homolog proteins. The contribution of foreign gene expression cassettes in the therapeutic and oncolytic virus GLV-1h68 was studied, including the F14.5L, J2R and A56R loci. The contribution of F14.5L inactivation to the reduced virulence is demonstrated by comparing the virulence data of GLV-1h68 with its F14.5L-null and revertant viruses. The comparison suggests that insertion of a foreign gene expression cassette in a nonessential locus in the viral genome is a practical way to attenuate VACVs, especially if the nonessential locus itself contains a virulence gene. This reduces the virulence of the virus without compromising too much the replication competency of the virus, the key to its oncolytic activity. The reduced pathogenicity of GLV-1h68 was confirmed by our experimental collaboration partners in male mice bearing C6 rat glioma and in immunocompetent mice bearing B16-F10 murine melanoma. In conclusion, bioinformatics and experimental data show that GLV-1h68 is a promising engineered VACV variant for anticancer therapy with tumor-specific replication, reduced pathogenicity and benign tissue tropism. N2 - Genom Sequenz Analyse Im Zuge der vorliegenden Doktorarbeit wurden verschiedene Programme zur Genomanalyse kombiniert, um eine effiziente Plattform zum interaktiven Vergleich lokaler Ähnlichkeiten bzw. Unterschiede in Genomen bereitzustellen. Damit können Gene und Operons schnell untersucht und “local collinear blocks” entsprechend ihrer Funktion kategorisiert werden. Phylogenetische Beziehungen, wie beispielsweise die Evolution spezifischer Elemente oder stark konservierter Regionen können leicht überprüft werden. Die hierfür entwickelte plattformunabhängige Software (GENOVA und inGeno) hat sich in mehreren Projekten als effizient und leicht handhabbar bewährt. Die Programme erlauben die Untersuchung von Virulenzfaktoren auf Sequenz- oder Annotationsebene. Während der vorliegenden Doktorarbeit konnten so die Genome von verschiedenen Staphylococcus aureus, Listeria spp., Escherichia coli und Vaccinia Stämmen untersucht werden. Metabolische Netzwerk Analyse Unser “YANAsquare” Programmpaket bietet eine Oberfläche um schnell metabolische Netzwerke vom genomweiten Anzatz bis hinunter zum Einzelnetzwerk zu analysieren. Dafür greift YANA mit Hilfe des integrierten KEGG-Browsers auf Onlinedatenbanken zu, um die notwendigen Informationen zum metabolischen Reaktionsweg bereitzustellen und reduziert so maßgeblich den Arbeitsaufwand beim Beschreiben von Netzwerke. Die implementierten Methoden zur Berechnung (METATOOL, eigene Implementation in Java) des Netzwerkes liefern exakt alle die möglichen Elementarmoden (EM/EP) für die Metabolite zurück. Durch den Einsatz von fortgeschrittenen Layout Algorithmen wird anschliessend die Darstellung der Netzwerktopologie möglich. Außerdem kann in der grafischen Darstellung das generierte Netzwerklayout dynamisch verändert werden. Das Speichern der Daten erfolgt im XML (SBML level-2) Format und erlaubt so die Weiterverwendung in anderen systembiologischen Programmen, wie dem “CellDesigner”. Mit Hilfe einer gen-Knockout Simulations Methode kann der Einfluss von einzelnen Mutationen im gesamten Netzwerk auf die Syntheseraten untersucht werden. Wir konnten mit dieser Methode Einzel- sowie Mehrfachgenknockouts und deren Effekte auf die Elementarmoden analysieren. Die Methode wurde ebenfalls auf Proteomdaten und extrazelluläre Metabolite von Staphylokokken angewandt, um Änderungen bezüglich der Flussverteilung zu untersuchen. Die Simulationen zu verschieden Zeitpunkten und unter verschiedenen Stessbedingungen zeigen große Übereinstimmung mit experimentell erhobenen Daten. Onkolytischer Vaccinia Virus (VACV) Wir haben die genetischen Unterschiede zwischen der de novo Sequenz des rekombinanten onkolytischen Virus GLV-1h68 und anderen VACVs untersucht und gefundene Unterschiede funktionell charakterisiert. Die phylogenetische Analyse zeigt das GLV-1h68 mit dem Lister Stamm am nächsten verwandt ist. Auffällig ist dabei der Verlust von einigen open reading frames (ORFs), die noch im Eltern LIVP Stamm vorhanden sind (CrmE, v-GAAP). Beim Vergleich der Funktion viraler Gene aus Lister, WR und COP Stämmen treten stamm-, gewebe- und wirtsspezifische Gene auf. Diese Tatsache ermöglicht die Optimierung der onkolytischen Virusstämme für den Einsatz bei humanen Krebstherapien. Die beim Vergleich identifizierten Unterschiede zwischen den ORFs enthalten Gene für die Wirtsselektion, Virulenz und immunmodulierende Proteine (Ankyrin ähnliche Proteine, Serine-Proteinasen Inhibitor SPI-2/CrmA, Tumor Nekrose Faktor (TNF) Rezeptorhomolog CrmC, semaphorinähnliche und Interleukin-1 rezeptorhomologe Proteine). An den Loki F14.5L, J2R und A56R des GLV-1h68 Virus wurden die Vorteile der eingesetzten fremden Genexpressionskassetten untersucht. So zeigt GLV-1h68 mit F14.5L-Inaktivierung gegenüber der F14.5L-Revertanten Viren eine reduzierte Virulenz. Das erlaubt die Schlussfolgerung, dass die Insertion von fremden Genexpressionskassetten in nicht-essentielle Loki zur Verminderung der Virulenz von VACVs führt, besonders, wenn der nicht-essentielle Lokus selbst ein Virulenzgen enthält. Das Replikationsvermögen, welches ausschlaggebend für die onkolytische Aktivität des Virus ist, wird trotz der verminderten Virulenz nicht eingeschränkt. Die reduzierte Pathogenität des GLV-1h68 Virus wurde durch experimentelle Daten unserer Kollaborationspartner in männlichen Mäusen mit Ratten C6 Gliom und in immunokompetenten Mäusen mit B16-F10 Mausmelanom nachgewiesen. Zusammenfassend zeigen experimentelle und bioinformatisch gewonnene Daten, dass GLV-1h68 eine vielversprechende VACV Variante für die Krebstherapie mit tumorspezifischer Replikation, verringerter Pathogenität und hoher Gewebsspezifität ist. KW - Genanalyse KW - Bioinformatik KW - Systembiologie KW - bacterial KW - virulence KW - systems biologie KW - genomic KW - algorithm KW - metabolic KW - network KW - pathway KW - flux KW - Bacterial KW - genomics KW - algorithm KW - tool KW - metabolic Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-48051 ER - TY - JOUR A1 - Reichel, Alexandra A1 - Röding, Kristina A1 - Stoevesandt, Johanna A1 - Trautmann, Axel T1 - De‐labelling antibiotic allergy through five key questions JF - Clinical & Experimental Allergy KW - allergy KW - antibiotic KW - algorithm Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-215508 VL - 50 IS - 4 SP - 532 EP - 535 ER - TY - JOUR A1 - Wolf, Beat A1 - Kuonen, Pierre A1 - Dandekar, Thomas A1 - Atlan, David T1 - DNAseq workflow in a diagnostic context and an example of a user friendly implementation JF - BioMed Research International N2 - Over recent years next generation sequencing (NGS) technologies evolved from costly tools used by very few, to a much more accessible and economically viable technology. Through this recently gained popularity, its use-cases expanded from research environments into clinical settings. But the technical know-how and infrastructure required to analyze the data remain an obstacle for a wider adoption of this technology, especially in smaller laboratories. We present GensearchNGS, a commercial DNAseq software suite distributed by Phenosystems SA. The focus of GensearchNGS is the optimal usage of already existing infrastructure, while keeping its use simple. This is achieved through the integration of existing tools in a comprehensive software environment, as well as custom algorithms developed with the restrictions of limited infrastructures in mind. This includes the possibility to connect multiple computers to speed up computing intensive parts of the analysis such as sequence alignments. We present a typical DNAseq workflow for NGS data analysis and the approach GensearchNGS takes to implement it. The presented workflow goes from raw data quality control to the final variant report. This includes features such as gene panels and the integration of online databases, like Ensembl for annotations or Cafe Variome for variant sharing. KW - next generation sequencing KW - genome browser KW - mutation KW - algorithm KW - database KW - format KW - discovery KW - exome KW - variants KW - alignment Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-144527 IS - 403497 ER -