Occam's razor in minimally invasive pituitary surgery: tailoring the endoscopic endonasal uninostril trans-sphenoidal approach to sella turcica.

BACKGROUND: Since the introduction of the endoscopic endonasal approaches in the field of skull base surgery during the last two decades, several variants of the sella turcica endoscopic surgery have been described. The aim of this study is to provide a stepwise description of one of these variants in a minimally invasive/maximally efficient perspective. METHOD: For the majority of our sella turcica pathologies, we have progressively adopted a uninostril endoscopic approach that is very conservative towards the nasal mucosa with a very limited mucosal incision, resection of the vomer and allowing an almost ad integrum sellar floor reconstruction, without compromising the efficacy and completeness of both surgical oncologic and endocrine targets. CONCLUSION: The uninostril trans-sphenoidal endoscopic endonasal approach to sella turcica is tailored to ally maximal efficiency and minimal invasiveness.

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.

Early Stage Primary Bone Lymphoma: A Retrospective, Multicenter Rare Cancer Network Study

PURPOSE/OBJECTIVE(S): Primary bone lymphoma (PBL) represents less than 1% of all malignant lymphomas, and 4-5% of all extranodal lymphomas. In this study, we assessed the disease profile, outcome, and prognostic factors in patients with stage I and II PBL. MATERIALS/METHODS: Between 1987 and 2008, 116 consecutive patients with PBL treated in 13 RCNinstitutions were included in this study. Inclusion criteriawere: age.17 yrs, PBLin stage I and II, andminimum6months follow-up. The median agewas 51 yrs (range: 17-93).Diagnosticwork-up included plain boneXray (74%of patients), scintigraphy (62%), CT-scan (65%),MRI (58%), PET (18%), and bone-marrow biopsy (84%).All patients had biopsy-proven confirmation of non-Hodgkin's lymphoma (NHL). The histopathological type was predominantly diffuse large B-cell lymphoma (78%) and follicular lymphoma (6%), according to theWHOclassification. One hundred patients had a high-grade, 7 intermediate and 9 low-gradeNHL. Ninety-three patients had anAnn-Arbor stage I, and 23 had a stage II. Seventy-seven patients underwent chemoradiotherapy (CXRT), 12 radiotherapy (RT) alone, 10 chemotherapy alone (CXT), 9 surgery followed by CXRT, 5 surgery followed by CXT, and 2 surgery followed by RT. One patient died before treatment.Median RT dosewas 40Gy (range: 4-60).Themedian number ofCXTcycleswas 6 (range, : 2-8).Median follow-upwas 41months (range: 6-242). RESULTS: Following treatment, the overall response rate was 91% (CR 74%, PR 17%). Local recurrence was observed in 12 (10%) patients, and systemic recurrence in 17 (15%) patients. Causes of death included disease progression in 16, unrelated disease in 6, CXT-related toxicity in 1, and secondary cancer in 2 patients. The 5-yr overall survival (OS), disease-free survival (DFS), lymphoma- specific survival (LSS), and local control (LC) were 76%, 69%, 78%, and 92%, respectively. In univariate analyses (log-rank test), favorable prognostic factors for survival were: age\50 years (p = 0.008), IPI score #1 (p = 0.009), complete response (p\0.001), CXT (p = 0.008), number of CXT cycles $6 (p = 0.007), and RT dose . 40 Gy (p = 0.005). In multivariate analysis age, RT dose, complete response, and absence of B symptoms were independent factors influencing the outcome. There were 3 patients developing grade 3 or more (CTCAE.V3.0) toxicities. CONCLUSIONS: This large multicenter study, confirms the relatively good prognosis of early stage PBL, treated with combined CXRT. Local control was excellent, and systemic failure occurred infrequently. A sufficient dose of RT (. 40 Gy) and complete CXT regime (. 6 cycles) were associated with a better outcome. Combined modality appears to be the treatment of choice.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

The role of the Fanconi anemia network in the response to DNA replication stress.

Fanconi anemia is a genetically heterogeneous disorder associated with chromosome instability and a highly elevated risk for developing cancer. The mutated genes encode proteins involved in the cellular response to DNA replication stress. Fanconi anemia proteins are extensively connected with DNA caretaker proteins, and appear to function as a hub for the coordination of DNA repair with DNA replication and cell cycle progression. At a molecular level, however, the raison d'être of Fanconi anemia proteins still remains largely elusive. The thirteen Fanconi anemia proteins identified to date have not been embraced into a single and defined biological process. To help put the Fanconi anemia puzzle into perspective, we begin this review with a summary of the strategies employed by prokaryotes and eukaryotes to tolerate obstacles to the progression of replication forks. We then summarize what we know about Fanconi anemia with an emphasis on biochemical aspects, and discuss how the Fanconi anemia network, a late acquisition in evolution, may function to permit the faithful and complete duplication of our very large vertebrate chromosomes.

An interaction network of the mammalian COP9 signalosome identifies Dda1 as a core subunit of multiple Cul4-based E3 ligases.

The COP9 signalosome (CSN) is an evolutionarily conserved macromolecular complex that interacts with cullin-RING E3 ligases (CRLs) and regulates their activity by hydrolyzing cullin-Nedd8 conjugates. The CSN sequesters inactive CRL4(Ddb2), which rapidly dissociates from the CSN upon DNA damage. Here we systematically define the protein interaction network of the mammalian CSN through mass spectrometric interrogation of the CSN subunits Csn1, Csn3, Csn4, Csn5, Csn6 and Csn7a. Notably, we identified a subset of CRL complexes that stably interact with the CSN and thus might similarly be activated by dissociation from the CSN in response to specific cues. In addition, we detected several new proteins in the CRL-CSN interactome, including Dda1, which we characterized as a chromatin-associated core subunit of multiple CRL4 proteins. Cells depleted of Dda1 spontaneously accumulated double-stranded DNA breaks in a similar way to Cul4A-, Cul4B- or Wdr23-depleted cells, indicating that Dda1 interacts physically and functionally with CRL4 complexes. This analysis identifies new components of the CRL family of E3 ligases and elaborates new connections between the CRL and CSN complexes.

La cohorte sepsis lausannoise: une opportunité de développer la recherche dans le Réseau latin de médecine intensive [Lausanne Cohort of septic patients as an opportunity to develop multidisciplinary research within the Swiss Latin Network of Intensive Care Medicine]

Despite recent medical progresses in patient support, the mortality of sepsis remains high. Recently, new supporting strategies were proposed to improve outcome. Whereas such strategies are currently considered as standard of care, their real impact on mortality, morbidity, length of stay, and hence, health care resources utilization has been only weakly evaluated so far. Obviously, there is a critical need for epidemiologic surveys of sepsis to better address these major issues. The Lausanne Cohort of septic patients aims at building a large clinical, biological and microbiological database that will be used as a multidisciplinary research platform to study the various pathogenic mechanisms of sepsis in collaboration with the various specialists. This could be an opportunity to strengthen the collaboration within the Swiss Latin network of Intensive Care Medicine.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

Social network architecture and the maintenance of deleterious cultural traits.

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

Light intensity modulates the regulatory network of the shade avoidance response in Arabidopsis.

Plants such as Arabidopsis thaliana respond to foliar shade and neighbors who may become competitors for light resources by elongation growth to secure access to unfiltered sunlight. Challenges faced during this shade avoidance response (SAR) are different under a light-absorbing canopy and during neighbor detection where light remains abundant. In both situations, elongation growth depends on auxin and transcription factors of the phytochrome interacting factor (PIF) class. Using a computational modeling approach to study the SAR regulatory network, we identify and experimentally validate a previously unidentified role for long hypocotyl in far red 1, a negative regulator of the PIFs. Moreover, we find that during neighbor detection, growth is promoted primarily by the production of auxin. In contrast, in true shade, the system operates with less auxin but with an increased sensitivity to the hormonal signal. Our data suggest that this latter signal is less robust, which may reflect a cost-to-robustness tradeoff, a system trait long recognized by engineers and forming the basis of information theory.

Analysis of the contribution of the β-oxidation auxiliary enzymes in the degradation of the dietary conjugated linoleic acid 9-cis-11-trans-octadecadienoic acid in the peroxisomes of Saccharomyces cerevisiae

Beta-oxidation of the conjugated linoleic acid 9-cis,11-trans-octadecadienoic acid (rumenic acid) was analyzed in vivo in Saccharomyces cerevisiae by monitoring polyhydroxyalkanoate production in the peroxisome. Polyhydroxyalkanoate is synthesized by the polymerization of the beta-oxidation intermediates 3-hydroxyacyl-CoAs via a bacterial polyhydroxyalkanoate synthase targeted to the peroxisome. The amount of polyhydroxyalkanaote synthesized from the degradation of rumenic acid was found to be similar to the amount synthesized from the degradation of 10-trans,12-cis-octadecadienoic acid, oleic acid or 10-cis-heptadecenoic acid. Furthermore, the degradation of 10-cis-heptadecenoic acid was found to be unaffected by the presence of rumenic acid in the media. Efficient degradation of rumenic acid was found to be independent of the Delta(3,5),Delta(2,4)-dienoyl-CoA isomerase but instead relied on the presence of Delta(3),Delta(2)-enoyl-CoA isomerase activity. The presence of the unsaturated monomer 3-hydroxydodecenoic acid in polyhydroxyalkanoate derived from rumenic acid degradation was found to be dependent on the presence of a Delta(3),Delta(2)-enoyl-CoA isomerase activity. Together, these data indicate that rumenic acid is mainly degraded in vivo in S. cerevisiae through a pathway requiring only the participation of the auxiliary enzymes Delta(3),Delta(2)-enoyl-CoA isomerase, along with the enzyme of the core beta-oxidation cycle.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

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.