Treatment results and prognostic factors in primary thyroid lymphoma patients: a rare cancer network study.

Background: This study analyzed prognostic factors and treatment outcomes of primary thyroid lymphoma. Patients and Methods: Data were retrospectively collected for 87 patients (53 stage I and 34 stage II) with median age 65 years. Fifty-two patients were treated with single modality (31 with chemotherapy alone and 21 with radiotherapy alone) and 35 with combined modality treatment. Median follow-up was 51 months. Results: Sixty patients had aggressive lymphoma and 27 had indolent lymphoma. The 5- and 10-year overall survival (OS) rates were 74% and 71%, respectively, and the disease-free survival (DFS) rates were 68% and 64%. Univariate analysis revealed that age, tumor size, stage, lymph node involvement, B symptoms, and treatment modality were prognostic factors for OS, DFS, and local control (LC). Patients with thyroiditis had significantly better LC rates. In multivariate analysis, OS was influenced by age, B symptoms, lymph node involvement, and tumor size, whereas DFS and LC were influenced by B symptoms and tumor size. Compared with single modality treatment, patients treated with combined modality had better 5-year OS, DFS, and LC. Conclusions: Combined modality leads to an excellent prognosis for patients with aggressive lymphoma but does not improve OS and LC in patients with indolent lymphoma.

Management of adenoid cystic carcinoma of the breast: a Rare Cancer Network study.

BACKGROUND: Mammary adenoid cystic carcinoma (ACC) is a rare breast cancer. The aim of this retrospective study was to assess prognostic factors and patterns of failure, as well as the role of radiation therapy (RT), in ACC.¦METHODS: Between January 1980 and December 2007, 61 women with breast ACC were treated at participating centers of the Rare Cancer Network. Surgery consisted of lumpectomy in 41 patients and mastectomy in 20 patients. There were 51(84%) stage pN0 and 10 stage cN0 (16%) patients. Postoperative RT was administered to 40 patients (35 after lumpectomy, 5 after mastectomy).¦RESULTS: With a median follow-up of 79 months (range, 6-285), 5-year overall and disease-free survival rates were 94% (95% confidence interval [CI], 88%-100%) and 82% (95% CI, 71%-93%), respectively. The 5-year locoregional control (LRC) rate was 95% (95% CI, 89%-100%). Axillary lymph node dissection or sentinel node biopsy was performed in 84% of cases. All patients had stage pN0 disease. In univariate analysis, survival was not influenced by the type of surgery or the use of postoperative RT. The 5-year LRC rate was 100% in the mastectomy group versus 93% (95% CI, 83%-100%) in the breast-conserving surgery group, respectively (p = 0.16). For the breast-conserving surgery group, the use of RT significantly correlated with LRC (p = 0.03); the 5-year LRC rates were 95% (95% CI, 86%-100%) for the RT group versus 83% (95% CI, 54%-100%) for the group receiving no RT. No local failures occurred in patients with positive margins, all of whom received postoperative RT.¦CONCLUSION: Breast-conserving surgery is the treatment of choice for patients with ACC breast cancer. Axillary lymph node dissection or sentinel node biopsy might not be recommended. Postoperative RT should be proposed in the case of breast-conserving surgery.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Role of lymph node fibroblasts in T cell priming

SummarySecondary lymphoid organs, such as lymph nodes or spleen, are the only places in our body where primary adaptive immune responses are efficiently elicited. These organs have distinct Β and Τ cell rich zones and Τ lymphocytes constantly migrate from the bloodstream into Τ zones to scan dendritic cells (DCs) for antigens they present. Specialized fibroblasts, the Τ zone reticular cells (HR.Cs), span the Τ zone in the form a three-dimensional network. lK.Cs guide incoming Τ cells in their migration, both chemically, by the secretion of the chemokines CCL19 and CCL21, and physically, by construction of a road system to which also DCs adhere. In this way TRCs are thought to facilitate encounters of Τ cells with antigen-bearing DCs and thereby accelerate the selection of rare antigen-specific Τ cells. The resulting Τ cell activation, proliferation and differentiation all take place within the TRC network. However, the influence of TRCs on Τ cell activation has so fer not been elucidated with the possible reasons being that TRCs represent a relative rare cell population and that mice devoid of TRCs have not been described.To circumvent these technical limitations, we established TRC clones and lines to have an abundant source to functionally characterize TRCs. Both the clones and lines show a fibroblastic phenotype, express a surface marker profile comparable to ex vivo TRCs and produce extracellular matrix molecules. However, expression of Ccl19, Ccl21 and ZL-7 is lost and could not be restored by cytokine stimulation. When these TRC clones or lines were cultured in a three-dimensional cell culture system, their morphology changed and resembled that of in vivo TRCs as they formed networks. By adding Τ cells and antigen-loaded DCs to these cultures we successfully reconstructed lymphoid Τ zones that allowed antigen-specific Τ cell activation.To characterize the role of TRCs in Τ cell priming, TRCs were co-cultured with antigen-specific Τ cells in the presence antigen-loaded DCs. Surprisingly, the presence of TRC lines and ex vivo TRCs inhibited rather than enhanced CD8+ Τ cell activation, proliferation and effector cell differentiation. TRCs shared this feature with fibroblasts from non-lymphoid tissues as well as mesenchymal stromal cells. TRCs were identified as a strong source of nitric oxide (NO) thereby directly dampening Τ cell expansion as well as reducing the Τ cell priming capacity of DCs. The expression of inducible NO synthase (iNOS) was up- regulated in a subset of TRCs by both DC-signals as well as interferon-γ produced by primed CD8+ Τ cells. Importantly, iNOS expression was induced during viral infection in vivo in both lymph node TRCs and DCs. Consistent with a role for NO as a negative regulator, the primary Τ cell response was exaggerated in iNOS-/- mice. Our findings highlight that in addition to their established positive roles in Τ cell responses TRCs and DCs cooperate in a negative feedback loop to attenuate Τ cell expansion during acute inflammation.RésuméLes organes lymphoïdes secondaires, comme les ganglions lymphoïdes ou la rate, sont les seuls sites dans notre corps où la réponse primaire des lymphocytes Β et Τ est initiée efficacement. Ces organes ont des zones différentes, riches en cellules Β ou T. Des lymphocytes Τ circulent constamment du sang vers les zones T, où ils échantillonent la surface des cellules dendritiques (DCs) pour identifier les antigènes qu'ils présentent. Des fibroblastes spécialisés - nommés Τ zone reticular cells (TRCs)' forment un réseau tridimensionnel dans la zone T. Les TRCs guident la migration des cellules Τ par deux moyens: chimiquement, par la sécrétion des chimiokines CCL19 et CCL21 et physiquement, par la construction d'un réseau routier en trois dimensions, auquel adhèrent aussi des DCs. Dans ce? cas, on pense que la présence des TRCs facilite les rencontres entre les cellules Τ et les DCs chargées de l'antigène et accélère la sélection des rares cellules Τ spécifiques. Ensuite, l'activation de cellules T, ainsi que la prolifération et la différenciation se produisent toutes à l'intérieur du réseau des TRCs. L'influence des TRCs sur l'activation des cellules T n'est que très peu caractérisée, en partie parce que les TRCs représentent une population rare et que les souris déficientes dans les TRCs n'ont pas encore été découvertes.Pour contourner ces limitations techniques, nous avons établi des clones et des lignées cellulaires de TRC pour obtenir une source indéfinie de ces cellules permettant leur caractérisation fonctionnelle. Les clones et lignées établis ont un phénotype de fibroblaste, ils expriment des molécules de surface similaires aux TRCs ex vivo et produisent de la matrice extracellulaire. Mais l'expression de Ccl19, Ccl21 et 11-7 est perdue et ne peut pas être rétablie par stimulation avec différentes cytokines. Les clones TRC ou les lignées cultivées en un système tridimensionnel de culture cellulaire, montrent une morphologie changée, qui ressemble à celle de TRC ex vivo inclus la construction de réseaux tridimensionnels.Pour caractériser le rôle des TRC dans l'activation des cellules T, nous avons cultivé des TRCs avec des cellules T spécifiques et des DCs chargées avec l'antigène. Etonnamment, la présence des TRC (lignées et ex vivo) inhibait plutôt qu'elle améliorait l'activation, la prolifération et la différenciation des lymphocytes T CDS+. Les TRCs partageaient cette fonction avec des fibr-oblastes des organes non lymphoïdes et des cellules souches du type mésenchymateux. Dans ces conditions, les TRCs sont une source importante d'oxyde nitrique (NO) et par ce fait limitent directement l'expansion des cellules T et réduisent aussi la capacité des DCs à activer les cellules T. L'expression de l'enzyme NO synthase inductible (ïNOS) est régulée à la hausse par des signaux dérivés des DCs et par l'interféron-γ produit par des cellules T de type CD8+ activées. Plus important, l'expression d'iNOS est induite pendant une infection virale in vivo, dans les TRCs et dans les DCs. Par conséquent, la réponse primaire de cellules T est exagérée dans des souris iNOS-/-. Nos résultats mettent en évidence qu'en plus de leur rôle positif bien établi dans la réponse immunitaire, les TRCs et les DCs coopèrent dans une boucle de rétroaction négative pour atténuer l'expansion des cellules T pendant l'inflammation aigiie pour protéger l'intégrité et la fonctionnalité des organes lymphoïdes secondaires.

Synchronous Digital Hierarchy implementation to a Radio Transmission Node

Kiristyville markkinoille on aina tuotava jotain uutta tarjottavaa ja SDH-kortti on yksi sellainen tuote jonka Nokia Networks julkistaa osaksi uutta Nokia Flexihub Nodea. Tavoitteena on suunnitella VC-12kanavoitu STM-1 kortti yhdistämään ylemmän tason tietoliikenneverkko suuren kapasiteetin radioon. Ennen kuin markkinoilla on valmis tuote, on sen takana valtaisa määrä työtä. Erilaisia dokumentteja on pitänyt tuottaa ja sopimuksia tehdä. Esimerkiksi vaatimusmäärittelyt on oltava selvät, jotta tiedetään mitä tuotteelta halutaan. Tätä ennen on kuitenkin pitänyt ymmärtää miten SDHtoimii ja miten otsikkotavuja käsitellään. Myös erilaiset piirivalinnat aiheuttavat miettimistä, sillä markkinoilla on runsaasti valmiita piirejä SDH signaalinkäsittelyyn. Varma tiedonsiirto on tärkeää puhelinoperaattorille ja siksi joudutaan miettimään varmennuksia ja niiden toteuttamista. Myös synkronointi on tärkeä osa SDH järjestelmää ja sen toteuttaminen hyvin on tärkeää. Hälytykset on otettava huomioon ja mietittävä, miten niiden käsittely saadaan hoidettua järkevästi, ilman että mikään järjestelmän osa ruuhkautuu kohtuuttomasti. Tässä Diplomityössä on tutustuttu SDH-järjestelmään, otsikkotavujen käsittelyyn ja vaatimusmäärittelyihin.

Transport Resource Management within UMTS Radio Network Subsystem

Tällä hetkellä haastavin telekommunikaatioteollisuuden tutkimus – ja kehitystoiminta on keskittynyt kolmannen sukupolven matkapuhelinjärjestelmien ympärille. Järjestelmien standardointityössä on saatu aikaiseksi ensimmäiset vakaat spesifikaatioversiot ja kaupallista toimintaa ollaan parhaillaan aloittelemassa Japanissa ja Euroopassa. Eräs kolmannen sukupolven järjestelmistä on UMTS (Universal Mobile Telecommunications System). Tämä diplomityö antaa yleiskuvan UMTS järjestelmästä ja sen eri verkkoelementtien toiminnallisuuksista. Päähuomio on kiinnitetty radioverkkojärjestelmään (UMTS Terrestrial Radio Access Network) ja erityisesti sen radioaliverkkojärjestelmään (Radio Network Subsystem), joka koostuu radioverkonohjaimesta (Radio Network Controller) ja joukosta siihen kuuluvia tukiasemia (Node B). Radioverkonohjain ja tukiasemat on yhdistetty avoimen rajapinnan kautta jota kutsutaan Iub -rajapinnaksi. Rajapinta tarjoaa radioverkonohjaimelle mahdollisuuden kontrolloida tukiasemia signalointiviestien avulla ja mahdollistaa tehokkaan ja luotettavan käyttäjätiedon siirron radioaliverkkojärjestelmän sisällä. Tämän diplomityön pääasiallinen sisältö on siirtoresurssien hallinta Iub -rajapinnan ylitse. Työssä esitellään ja selitetään siirtoverkon arkkitehtuuri. Myös kaikki Iub:ssä sijaitsevat protokollat ja toiminnalliset yksiköt jotka vaikuttavat siirtoresurssien hallintaan esitellään ja kuvataan yksityiskohtaisesti. Päähuomio on kiinnitetty sovellusprotokolliin sekä rajapinnan siirtoverkko- että radioverkkokerroksella sekä näiden protokollien väliseen vuorovaikutukseen. Kyseiset protokollat ovat Node B Application Part (NBAP) ja Access Link Control Application Part (ALCAP). Työn toteutusosassa käydään lävitse NBAP –protokollan prototyypin ja Node B Manager –toiminnallisen yksikön prototyypin implementaatio.

Ingest into the Digital Preservation Network: Standard Pipelines

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

DataONE Member Node Implementation Workshop

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Performance improvement of multiple Connections in AODV with the concern of Node bandwidth

Mobile Ad-hoc Networks (MANETS) consists of a collection of mobile nodes without having a central coordination. In MANET, node mobility and dynamic topology play an important role in the performance. MANET provide a solution for network connection at anywhere and at any time. The major features of MANET are quick set up, self organization and self maintenance. Routing is a major challenge in MANET due to it’s dynamic topology and high mobility. Several routing algorithms have been developed for routing. This paper studies the AODV protocol and how AODV is performed under multiple connections in the network. Several issues have been identified. The bandwidth is recognized as the prominent factor reducing the performance of the network. This paper gives an improvement of normal AODV for simultaneous multiple connections under the consideration of bandwidth of node.

Impact of Node Mobility on Routing Protocols for Wireless Sensor Networks

Wireless sensor networks monitor their surrounding environment for the occurrence of some anticipated phenomenon. Most of the research related to sensor networks considers the static deployment of sensor nodes. Mobility of sensor node can be considered as an extra dimension of complexity, which poses interesting and challenging problems. Node mobility is a very important aspect in the design of effective routing algorithm for mobile wireless networks. In this work we intent to present the impact of different mobility models on the performance of the wireless sensor networks. Routing characteristics of various routing protocols for ad-hoc network were studied considering different mobility models. Performance metrics such as end-to-end delay, throughput and routing load were considered and their variations in the case of mobility models like Freeway, RPGM were studied. This work will be useful to figure out the characteristics of routing protocols depending on the mobility patterns of sensors

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of the systems. We consider their underlying data structures – socalled folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag co-occurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures – so-called folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag cooccurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

An ATM distributed simulator for network management research

Due to the high cost of a large ATM network working up to full strength to apply our ideas about network management, i.e., dynamic virtual path (VP) management and fault restoration, we developed a distributed simulation platform for performing our experiments. This platform also had to be capable of other sorts of tests, such as connection admission control (CAC) algorithms, routing algorithms, and accounting and charging methods. The platform was posed as a very simple, event-oriented and scalable simulation. The main goal was the simulation of a working ATM backbone network with a potentially large number of nodes (hundreds). As research into control algorithms and low-level, or rather cell-level methods, was beyond the scope of this study, the simulation took place at a connection level, i.e., there was no real traffic of cells. The simulated network behaved like a real network accepting and rejecting SNMP ones, or experimental tools using the API node

Availability analysis of GMPLS connections based on physical network topology

This paper presents a study of connection availability in GMPLS over optical transport networks (OTN) taking into account different network topologies. Two basic path protection schemes are considered and compared with the no protection case. The selected topologies are heterogeneous in geographic coverage, network diameter, link lengths, and average node degree. Connection availability is also computed considering the reliability data of physical components and a well-known network availability model. Results show several correspondences between suitable path protection algorithms and several network topology characteristics