Recurrent paroxysmal fever revealing ocular syphilis.

An increased prevalence of ocular syphilis has been reported in recent years reflecting a trend towards liberalisation of sexual practices in the era of Highly Active Anti-retroviral Treatment for HIV infection [1][2]. In view of the protean nature of the disease, pathognomonic features that could guide differential diagnosis of ocular inflammation towards syphilis are lacking. Ocular involvement can antedate or follow systemic manifestations of syphilitic infection, ranging widely and potentially involving all ocular tissue [3][4]. We report here an unusual case of chronic fever and fatigue the cause of which remained elusive for a period of three years, despite extensive investigations, until the development of bilateral panuveitis, raising the suspicion of syphilitc infection.

Networks of people in specialty production: family firms in the iron and steel Wire industries in Spain (1870-2000)

Capital intensive industries in specialized niches of production have constituted solid ground for family firms in Spain , as evidenced by the experience of the iron and steel wire industries between 1870 and 2000. The embeddedness of these firms in their local and regional environments have allowed the creation of networks that, together with favourable institutional conditions, significantly explain the dominance of family entrepreneurship in iron and steel wire manufacturing in Spain, until the end of the 20 th century. Dominance of family firms at the regional level has not been not an obstacle for innovation in wire manufacturing in Spain, which has taken place even when institutional conditions blocked innovation and traditional networking. Therefore, economic theories about the difficulties dynastic family firms may have to perform appropriately in science-based industries must be questioned

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Dynamics of case-fatalilty rates of recurrent thromboembolism and major bleeding in patients treated for venous thromboembolism.

In patients with venous thromboembolism (VTE), assessment of the risk of fatal recurrent VTE and fatal bleeding during anticoagulation may help to guide intensity and duration of therapy. We aimed to provide estimates of the case-fatality rate (CFR) of recurrent VTE and major bleeding during anticoagulation in a 'real life' population, and to assess these outcomes according to the initial presentation of VTE and its etiology. The study included 41,826 patients with confirmed VTE from the RIETE registry who received different durations of anticoagulation (mean 7.8 ± 0.6 months). During 27,110 patient-years, the CFR was 12.1% (95% CI, 10.2-14.2) for recurrent VTE, and 19.7% (95% CI, 17.4-22.1) for major bleeding. During the first three months of anticoagulant therapy, the CFR of recurrent VTE was 16.1% (95% CI, 13.6-18.9), compared to 2.0% (95% CI, 0-4.2) beyond this period. The CFR of bleeding was 20.2% (95% CI, 17.5-23.1) during the first three months, compared to 18.2% (95% CI, 14.0-23.2) beyond this period. The CFR of recurrent VTE was higher in patients initially presenting with PE (18.5%; 95% CI, 15.3-22.1) than in those with DVT (6.3%; 95% CI, 4.5-8.6), and in patients with provoked VTE (16.3%; 95% CI, 13.6-19.4) than in those with unprovoked VTE (5.5%; 95% CI, 3.5-8.0). In conclusion, the CFR of recurrent VTE decreased over time during anticoagulation, while the CFR of major bleeding remained stable. The CFR of recurrent VTE was higher in patients initially presenting with PE and in those with provoked VTE.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

A conspectus on estimating function theory and its applicability to recurrent modeling issues in forest biometry

Summary

Modelling non-industrial private forest landowners' strategic decision making by using logistic regression and neural networks: case of predicting the choice of forest taxation basis

Summary

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

EORTC 26083 phase I/II trial of dasatinib in combination with CCNU in patients with recurrent glioblastoma.

The treatment of patients with recurrent glioblastoma remains a major oncologic problem, with median survival after progression of 7-9 months. To determine the maximum tolerated dose and dose-limiting toxicity (DLT), the combination of dasatinib and cyclonexyl-chloroethyl-nitrosourea (CCNU) was investigated in this setting. The study was designed as multicenter, randomized phase II trial, preceded by a lead-in safety phase. The safety component reported here, which also investigated pharmacokinetics and preliminary clinical activity, required expansion and is therefore considered a phase I part to establish a recommended dosing regimen of the combination of CCNU (90-110 mg/m(2)) and dasatinib (100-200 mg daily). Overall, 28 patients were screened, and 26 patients were enrolled. Five dose levels were explored. DLTs, mainly myelosuppression, occurred in 10 patients. Grade 3 or 4 neutropenia was recorded in 7 patients (26.9%) and thrombocytopenia in 11 patients (42.3%). No significant effect of CCNU coadministration on dasatinib pharmacokinetics was found. Median progression-free survival (PFS) was 1.35 months (95% confidence interval: 1.2-1.4) and 6-month PFS was 7.7%. In this phase I study of recurrent glioblastoma patients, the combination of CCNU and dasatinib showed significant hematological toxicities and led to suboptimal exposure to both agents.

Communication in networks with hierarchical branching

We present a simple model of communication in networks with hierarchical branching. We analyze the behavior of the model from the viewpoint of critical systems under different situations. For certain values of the parameters, a continuous phase transition between a sparse and a congested regime is observed and accurately described by an order parameter and the power spectra. At the critical point the behavior of the model is totally independent of the number of hierarchical levels. Also scaling properties are observed when the size of the system varies. The presence of noise in the communication is shown to break the transition. The analytical results are a useful guide to forecasting the main features of real networks.