Analysen zur molekularen Charakterisierung von Proteinen des humanen Usher-Syndroms und Evaluation genbasierter Therapiestrategien

Analysen zur molekularen Charakterisierung von Proteinen des humanen Usher-Syndroms und Evaluation genbasierter Therapiestrategien rnDas humane Usher Syndrom (USH) ist die häufigste Form vererbter Taub-Blindheit. In der vorliegenden Dissertation wurde diese komplexe Erkrankung auf verschiedenen Ebenen analysiert: in Arbeiten zur Expression und Lokalisation von USH-Proteinen, der Analyse der USH-Proteinnetzwerke und deren Funktionen sowie darauf aufbauend die Entwicklung von Therapiestrategien für USH.rnIm Rahmen der Arbeit wurde die Expression und (sub)-zelluläre Lokalisation des USH1D-Genproduktes CDH23 in der Retina und Cochlea analysiert. CDH23-Isoformen werden in der Maus zeitlich und räumlich differentiell exprimiert. In den Retinae von Mäusen, nicht humanen Primaten und Menschen zeigten Analysen eine unterschiedliche Expression und Lokalisation des Zell-Zelladhäsionsmoleküls CDH23, was auf Funktions-unterschiede der einzelnen Isoformen in den analysierten Spezies hindeutet.rnAnalysen zur Aufklärung der USH-Proteinnetzwerke ergaben eine potentielle Interaktion des USH1G-Gerüstproteins SANS mit dem Golgi- und Centrosom-assoziierten Protein Myomegalin. Die direkte Interaktion der Proteine konnte durch unabhängige Experimente verifiziert werden. Beide Interaktionspartner sind in den Retinae verschiedener Spezies partiell ko-lokalisiert und partizipieren im periciliären USH-Proteinnetzwerk. Die Assoziation von SANS und Myomegalin mit dem Mikrotubuli-Cytoskelett weist auf eine Funktion des Proteinkomplexes in gerichteten Transportprozessen innerhalb der Photorezeptoren hin und bekräftigt die Hypothese einer Rolle von SANS und assoziierten Netzwerken mit Transportprozessen.rnDas hier gewonnene erweiterte Verständnis der molekularen Grundlagen sowie die Aufklärung der zellulären Funktion der Proteinnetzwerke ermöglichen die Entwicklung therapeutischer Strategien für USH. Ein Fokus der vorliegenden Arbeit lag auf der Entwicklung genbasierter Therapiestrategien und deren Evaluation, wobei der Schwerpunkt auf der Therapiestrategie der Genreparatur lag. Die mit Hilfe von Zinkfinger-Nukleasen (ZFN) induzierte Homologe Rekombination für die Genkorrektur wurde exemplarisch an der 91C>T/p.R31X-Mutation im USH1C-Gen gezeigt. Effiziente ZFN wurden identifiziert, generiert und erfolgreich im Zellkulturmodellsystem eingesetzt. Die Analysen demonstrierten eine Reparatur der Mutation durch Homologe Rekombination auf genomischer Ebene und die Expression des wiederhergestellten Proteins. Durch die Genkorrektur im endogenen Lokus sind Größe des Gens, Isoformen oder die Art der Mutation keine limitierenden Faktoren für die Therapie. Die in der vorliegenden Arbeit durchgeführten Experimente unterstreichen das enorme Potential ZFN-basierter Therapiestrategien hin zu personalisierten Therapieformen nicht nur für USH sondern auch für andere erbliche Erkrankungen, deren genetische Grundlagen bekannt sind.rn

Analysis Methodology for Flow-level Evaluation of a Hybrid Mobile-Sensor Network

Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

An Urn Model for Cascading Failures on a Lattice

A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.

Musculoskeletal spectroscopy

Magnetic resonance spectroscopy (MRS) of skeletal muscle has been successfully applied by physiologists over several decades, particularly for studies of high-energy phosphates (by (31)P-MRS) and glycogen (by (13)C-MRS). Unfortunately, the observation of these heteronuclei requires equipment that is typically not available on clinical MR scanners, such as broadband capability and a second channel for decoupling and nuclear Overhauser enhancement (NOE). On the other hand, (1)H-MR spectra of skeletal muscle can be acquired on many routine MR systems and also provide a wealth of physiological information. In particular, studies of intramyocellular lipids (IMCL) attract physiologists and endocrinologists because IMCL levels are related to insulin resistance and thus can lead to a better understanding of major health problems in industrial countries. The combination of (1)H-, (13)C-, and (31)P-MRS gives access to the major long- and short-term energy sources of skeletal muscle. This review summarizes the technical aspects and unique MR-methodological features of the different nuclei. It reviews clinical studies that employed MRS of one or more nuclei, or combinations of MRS with other MR modalities. It also illustrates that MR spectra contain additional physiological information that is not yet used in routine clinical applications.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Durch das Leben lernen

Web 2.0 und soziale Netzwerke gaben erste Impulse für neue Formen der Online-Lehre, welche die umfassende Vernetzung von Objekten und Nutzern im Internet nachhaltig einsetzen. Die Vielfältigkeit der unterschiedlichen Systeme erschwert aber deren ganzheitliche Nutzung in einem umfassenden Lernszenario, das den Anforderungen der modernen Informationsgesellschaft genügt. In diesem Beitrag wird eine auf dem Konnektivismus basierende Plattform für die Online-Lehre namens “Wiki-Learnia” präsentiert, welche alle wesentlichen Abschnitte des lebenslangen Lernens abbildet. Unter Einsatz zeitgemäßer Technologien werden nicht nur Nutzer untereinander verbunden, sondern auch Nutzer mit dedizierten Inhalten sowie ggf. zugehörigen Autoren und/oder Tutoren verknüpft. Für ersteres werden verschiedene Kommunikations-Werkzeuge des Web 2.0 (soziale Netzwerke, Chats, Foren etc.) eingesetzt. Letzteres fußt auf dem sogenannten “Learning-Hub”-Ansatz, welcher mit Hilfe von Web-3.0-Mechanismen insbesondere durch eine semantische Metasuchmaschine instrumentiert wird. Zum Aufzeigen der praktischen Relevanz des Ansatzes wird das mediengestützte Juniorstudium der Universität Rostock vorgestellt, ein Projekt, das Schüler der Abiturstufe aufs Studium vorbereitet. Anhand der speziellen Anforderungen dieses Vorhabens werden der enorme Funktionsumfang und die große Flexibilität von Wiki-Learnia demonstriert.

Learning through life

Web 2.0 und soziale Netzwerke gaben erste Impulse für neue Formen der Online-Lehre, welche die umfassende Vernetzung von Objekten und Nutzern im Internet nachhaltig einsetzen. Die Vielfältigkeit der unterschiedlichen Systeme erschwert aber deren ganzheitliche Nutzung in einem umfassenden Lernszenario, das den Anforderungen der modernen Informationsgesellschaft genügt. In diesem Beitrag wird eine auf dem Konnektivismus basierende Plattform für die Online-Lehre namens “Wiki-Learnia” präsentiert, welche alle wesentlichen Abschnitte des lebenslangen Lernens abbildet. Unter Einsatz zeitgemäßer Technologien werden nicht nur Nutzer untereinander verbunden, sondern auch Nutzer mit dedizierten Inhalten sowie ggf. zugehörigen Autoren und/oder Tutoren verknüpft. Für ersteres werden verschiedene Kommunikations-Werkzeuge des Web 2.0 (soziale Netzwerke, Chats, Foren etc.) eingesetzt. Letzteres fußt auf dem sogenannten “Learning-Hub”-Ansatz, welcher mit Hilfe von Web-3.0-Mechanismen insbesondere durch eine semantische Metasuchmaschine instrumentiert wird. Zum Aufzeigen der praktischen Relevanz des Ansatzes wird das mediengestützte Juniorstudium der Universität Rostock vorgestellt, ein Projekt, das Schüler der Abiturstufe aufs Studium vorbereitet. Anhand der speziellen Anforderungen dieses Vorhabens werden der enorme Funktionsumfang und die große Flexibilität von Wiki-Learnia demonstriert.

Measuring the mechanics of morphogenesis

The past decades have seen a rapid increase in the understanding of plant morphogenesis at the molecular-genetic level. However, the control of growth and morphogenesis by molecular and signaling networks ultimately requires the coordinated regulation of mechanical properties in individual cells. There is also increasing evidence that mechanical stresses can feedback on hormone signaling and growth, and may have a central role in developmental patterning. Thus the development of techniques to investigate the mechanical properties of plant tissue at the cellular level is key to understanding growth and morphogenesis.

Real-World Energy Measurements of a Wireless Mesh Network

Over the past several years the topics of energy consumption and energy harvesting have gained significant importance as a means for improved operation of wireless sensor and mesh networks. Energy-awareness of operation is especially relevant for application scenarios from the domain of environmental monitoring in hard to access areas. In this work we reflect upon our experiences with a real-world deployment of a wireless mesh network. In particular, a comprehensive study on energy measurements collected over several weeks during the summer and the winter period in a network deployment in the Swiss Alps is presented. Energy performance is monitored and analysed for three system components, namely, mesh node, battery and solar panel module. Our findings cover a number of aspects of energy consumption, including the amount of load consumed by a mesh node, the amount of load harvested by a solar panel module, and the dependencies between these two. With our work we aim to shed some light on energy-aware network operation and to help both users and developers in the planning and deployment of a new wireless (mesh) network for environmental research.

From Broadstone to Zackenberg

Ecological networks are typically complex constructions of species and their interactions. During the last decade, the study of networks has moved from static to dynamic analyses, and has attained a deeper insight into their internal structure, heterogeneity, and temporal and spatial resolution. Here, we review, discuss and suggest research lines in the study of the spatio-temporal heterogeneity of networks and their hierarchical nature. We use case study data from two well-characterized model systems (the food web in Broadstone Stream in England and the pollination network at Zackenberg in Greenland), which are complemented with additional information from other studies. We focus upon eight topics: temporal dynamic space-for-time substitutions linkage constraints habitat borders network modularity individual-based networks invasions of networks and super networks that integrate different network types. Few studies have explicitly examined temporal change in networks, and we present examples that span from daily to decadal change: a common pattern that we see is a stable core surrounded by a group of dynamic, peripheral species, which, in pollinator networks enter the web via preferential linkage to the most generalist species. To some extent, temporal and spatial scales are interchangeable (i.e. networks exhibit ‘ergodicity’) and we explore how space-for-time substitutions can be used in the study of networks. Network structure is commonly constrained by phenological uncoupling (a temporal phenomenon), abundance, body size and population structure. Some potential links are never observed, that is they are ‘forbidden’ (fully constrained) or ‘missing’ (a sampling effect), and their absence can be just as ecologically significant as their presence. Spatial habitat borders can add heterogeneity to network structure, but their importance has rarely been studied: we explore how habitat generalization can be related to other resource dimensions. Many networks are hierarchically structured, with modules forming the basic building blocks, which can result in self-similarity. Scaling down from networks of species reveals another, finer-grained level of individual-based organization, the ecological consequences of which have yet to be fully explored. The few studies of individual-based ecological networks that are available suggest the potential for large intraspecific variance and, in the case of food webs, strong size-structuring. However, such data are still scarce and more studies are required to link individual-level and species-level networks. Invasions by alien species can be tracked by following the topological ‘career’ of the invader as it establishes itself within a network, with potentially important implications for conservation biology. Finally, by scaling up to a higher level of organization, it is possible to combine different network types (e.g. food webs and mutualistic networks) to form super networks, and this new approach has yet to be integrated into mainstream ecological research. We conclude by listing a set of research topics that we see as emerging candidates for ecological network studies in the near future.

The New Concept of Universal Service in a Digital Networked Communications Environment

Digitization, sophisticated fiber-optic networks and the resultant convergence of the media, communications and information technology industries have completely transformed the communications ecosystem in the last couple of decades. New contingent business and social models were created that have been mirrored in the amended communications regimes. Yet, despite an overhaul of the communications regulation paradigm, the status of and the rules on universal service have remained surprisingly intact, both during and after the liberalization exercise. The present paper looks into this paradox and examines the sustainability of the existing concept of universal service. It suggests that there is a need for a novel concept of universal service in the digital networked communications environment, whose objectives go beyond the conventional internalizing and redistributional rationales and concentrate on communication and information networks as a public good, where not only access to infrastructure but also access to content may be essential.

Volunteering in sport clubs

Volunteers are the most important resource for non-profit sport clubs seeking to bolster their viability (e.g. sporting programs). Although many people do voluntary work in sport clubs, stable voluntary engagement can no longer be granted. This difficulty is confirmed by existing research across various European countries. From a club management point of view, a detailed understanding of how to attract volunteers and retain them in the long term is becoming a high priority. The purpose of this study is (1) to analyse the influence of individual characteristics and corresponding organisational conditions on volunteering in sports clubs as well as (2) to examine the decision-making processes in relation to implement effective strategies for recruiting volunteers. For the first perspective a multi-level framework for the investigation of the factors of voluntary engagement in sports clubs is developed. The individual and context factors are estimated in different multi-level models based on a sample of n = 1,434 sport club members from 36 sport clubs in Switzerland. Results indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sport club, longer club memberships, or a strong commitment to the club. It is also influenced by club-specific structural conditions; volunteering is more probable in rural sports clubs whereas growth-oriented goals in clubs have a destabilising effect. Concerning decision-making processes an in-depth analysis of recruitment practices for volunteers was conducted in nine selected sport clubs (case study design) based on the garbage can model. Results show that the decision-making processes are generally characterised by a reactive approach in which dominant actors try to handle personnel problems of recruitment in the administration and sport domains through routine formal committee work and informal networks. In addition, it proved possible to develop a typology that deliver an overview of different decision-making practices in terms of the specific interplay of the relevant components of process control (top-down vs. bottom-up) and problem processing (situational vs. systematic). Based on the findings some recommendations for volunteer management in sport clubs are worked out.

Measuring the mechanical properties of plant cells by combining micro-indentation with osmotic treatments

Growth in plants results from the interaction between genetic and signalling networks and the mechanical properties of cells and tissues. There has been a recent resurgence in research directed at understanding the mechanical aspects of growth, and their feedback on genetic regulation. This has been driven in part by the development of new micro-indentation techniques to measure the mechanical properties of plant cells in vivo. However, the interpretation of indentation experiments remains a challenge, since the force measures results from a combination of turgor pressure, cell wall stiffness, and cell and indenter geometry. In order to interpret the measurements, an accurate mechanical model of the experiment is required. Here, we used a plant cell system with a simple geometry, Nicotiana tabacum Bright Yellow-2 (BY-2) cells, to examine the sensitivity of micro-indentation to a variety of mechanical and experimental parameters. Using a finite-element mechanical model, we found that, for indentations of a few microns on turgid cells, the measurements were mostly sensitive to turgor pressure and the radius of the cell, and not to the exact indenter shape or elastic properties of the cell wall. By complementing indentation experiments with osmotic experiments to measure the elastic strain in turgid cells, we could fit the model to both turgor pressure and cell wall elasticity. This allowed us to interpret apparent stiffness values in terms of meaningful physical parameters that are relevant for morphogenesis.

Ruler Based Automatic C-Arm Image Stitching Without Overlapping Constraint

In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we “paste” each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.