Immunoregulation in human malaria: the challenge of understanding asymptomatic infection

Asymptomatic Plasmodium infection carriers represent a major threat to malaria control worldwide as they are silent natural reservoirs and do not seek medical care. There are no standard criteria for asymptomaticPlasmodium infection; therefore, its diagnosis relies on the presence of the parasite during a specific period of symptomless infection. The antiparasitic immune response can result in reducedPlasmodium sp. load with control of disease manifestations, which leads to asymptomatic infection. Both the innate and adaptive immune responses seem to play major roles in asymptomatic Plasmodiuminfection; T regulatory cell activity (through the production of interleukin-10 and transforming growth factor-β) and B-cells (with a broad antibody response) both play prominent roles. Furthermore, molecules involved in the haem detoxification pathway (such as haptoglobin and haeme oxygenase-1) and iron metabolism (ferritin and activated c-Jun N-terminal kinase) have emerged in recent years as potential biomarkers and thus are helping to unravel the immune response underlying asymptomatic Plasmodium infection. The acquisition of large data sets and the use of robust statistical tools, including network analysis, associated with well-designed malaria studies will likely help elucidate the immune mechanisms responsible for asymptomatic infection.

To Monty Kier, a friendly tribute.

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.

A dramatic lung cancer course in a patient with a rare EGFR germline mutation exon 21 V843I: Is EGFR TKI resistance predictable?

We report on the medical history of a Caucasian smoker woman diagnosed with a stage IV NSCLC adenocarcinoma, characterized by a rare epidermal growth factor receptor (EGFR) point mutation in exon 21 codon 843 (p.V843I/c.2527G>A/COSMIC ID 85894). This genetic alteration revealed to be germline, after its presence was demonstrated in chondroblasts from the bone biopsy. While it is the first description of germline V843I mutation without concomitant additional known EGFR activating mutation, we modeled the EGFR ATP catalytic domain in complex with ATP, gefitinib and erlotinib using computer-aided approaches to estimate possible changes in affinity upon the V843I mutation.

MR connectomics: Principles and challenges.

MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.

Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration.

Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally engaged regions are a suggested key mechanism. Thus, network analysis methods seem critical for investigation of changes in directed causal interactions between such candidate brain regions. To identify core compensatory regions, fifteen preclinical patients carrying the genetic mutation leading to Huntington's disease and twelve controls underwent fMRI scanning. They accomplished an auditory paced finger sequence tapping task, which challenged cognitive as well as executive aspects of motor functioning by varying speed and complexity of movements. To investigate causal interactions among brain regions a single Dynamic Causal Model (DCM) was constructed and fitted to the data from each subject. The DCM parameters were analysed using statistical methods to assess group differences in connectivity, and the relationship between connectivity patterns and predicted years to clinical onset was assessed in gene carriers. In preclinical patients, we found indications for neural reserve mechanisms predominantly driven by bilateral dorsal premotor cortex, which increasingly activated superior parietal cortices the closer individuals were to estimated clinical onset. This compensatory mechanism was restricted to complex movements characterised by high cognitive demand. Additionally, we identified task-induced connectivity changes in both groups of subjects towards pre- and caudal supplementary motor areas, which were linked to either faster or more complex task conditions. Interestingly, coupling of dorsal premotor cortex and supplementary motor area was more negative in controls compared to gene mutation carriers. Furthermore, changes in the connectivity pattern of gene carriers allowed prediction of the years to estimated disease onset in individuals. Our study characterises the connectivity pattern of core cortical regions maintaining motor function in relation to varying task demand. We identified connections of bilateral dorsal premotor cortex as critical for compensation as well as task-dependent recruitment of pre- and caudal supplementary motor area. The latter finding nicely mirrors a previously published general linear model-based analysis of the same data. Such knowledge about disease specific inter-regional effective connectivity may help identify foci for interventions based on transcranial magnetic stimulation designed to stimulate functioning and also to predict their impact on other regions in motor-associated networks.

Modification of the Perrine-Baum diagram to improve the calculation of high voltage electric lines

Through the history of Electrical Engineering education, vectorial and phasorial diagrams have been used as a fundamental learning tool. At present, computational power has replaced them by long data lists, the result of solving equation systems by means of numerical methods. In this sense, diagrams have been shifted to an academic background and although theoretically explained, they are not used in a practical way within specific examples. This fact may be against the understanding of the complex behavior of the electrical power systems by students. This article proposes a modification of the classical Perrine-Baum diagram construction to allowing both a more practical representation and a better understanding of the behavior of a high-voltage electric line under different levels of load. This modification allows, at the same time, the forecast of the obsolescence of this behavior and line’s loading capacity. Complementary, we evaluate the impact of this tool in the learning process showing comparative undergraduate results during three academic years

A method for extracting semantic information from on-line art music discussion forums

In this paper a method for extracting semantic informationfrom online music discussion forums is proposed. The semantic relations are inferred from the co-occurrence of musical concepts in forum posts, using network analysis. The method starts by defining a dictionary of common music terms in an art music tradition. Then, it creates a complex network representation of the online forum by matchingsuch dictionary against the forum posts. Once the complex network is built we can study different network measures, including node relevance, node co-occurrence andterm relations via semantically connecting words. Moreover, we can detect communities of concepts inside the forum posts. The rationale is that some music terms are more related to each other than to other terms. All in all, this methodology allows us to obtain meaningful and relevantinformation from forum discussions.

Character Networks and Centrality

A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.

Networks of Coordination : Swiss Business Associations as an Intermediary between Business, Politics and Administration during the 20th Century

Until the 1990's, Switzerland could be classified as either a corporatist, cooperative or coordinated market economy where non-market mechanisms of coordination among economic and political actors were very important. In this respect, Business Interest Associations (BIAs) played a key role. The aim of this paper is to look at the historical evolution of the five main peak Swiss BIAs through network analysis for five assorted dates during the 20th century (1910, 1937, 1957, 1980 and 2000) while relying on a database that includes more than 12,000 people. First, we examine the logic of membership in these associations, which allows us to analyze their position and function within the network of the Swiss economic elite. Until the 1980's, BIAs took part in the emergence and consolidation of a closely meshed national network, which declined during the two last decades of the 20th century. Second, we investigate the logic of influence of these associations by looking at the links they maintained with the political and administrative worlds through their links to the political parties and Parliament, and to the administration via the extra-parliamentary commissions (corporatist bodies). In both cases, the recent dynamic of globalization called into question the traditional role of BIAs.

Identification of novel elements of the Drosophila blisterome sheds light on potential pathological mechanisms of several human diseases.

Main developmental programs are highly conserved among species of the animal kingdom. Improper execution of these programs often leads to progression of various diseases and disorders. Here we focused on Drosophila wing tissue morphogenesis, a fairly complex developmental program, one of the steps of which - apposition of the dorsal and ventral wing sheets during metamorphosis - is mediated by integrins. Disruption of this apposition leads to wing blistering which serves as an easily screenable phenotype for components regulating this process. By means of RNAi-silencing technique and the blister phenotype as readout, we identify numerous novel proteins potentially involved in wing sheet adhesion. Remarkably, our results reveal not only participants of the integrin-mediated machinery, but also components of other cellular processes, e.g. cell cycle, RNA splicing, and vesicular trafficking. With the use of bioinformatics tools, these data are assembled into a large blisterome network. Analysis of human orthologues of the Drosophila blisterome components shows that many disease-related genes may contribute to cell adhesion implementation, providing hints on possible mechanisms of these human pathologies.

Biana: a software framework for compiling biological interactions and analyzing networks

Background: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties.Results: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php.Conclusions: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Structural covariance of superficial white matter in mild Alzheimer's disease compared to normal aging.

INTRODUCTION: Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimer's disease (AD) are of special interest, since they follow the AD-specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices. METHODS: Here, we present an SWM network analysis in comparison with SWM topography based on the myelin content quantified with magnetization transfer ratio (MTR) for 39 areas in each hemisphere in 15 AD patients and 15 controls. The networks are represented by graphs, in which nodes correspond to the areas, and edges denote statistical associations between them. RESULTS: In both groups, the networks were characterized by asymmetrically distributed edges (predominantly in the left hemisphere). The AD-related differences were also leftward. The edges lost due to AD tended to connect nodes in the temporal lobe to other lobes or nodes within or between the latter lobes. The newly gained edges were mostly confined to the temporal and paralimbic regions, which manifest demyelination of SWM already in mild AD. CONCLUSION: This pattern suggests that the AD pathological process coordinates SWM demyelination in the temporal and paralimbic regions, but not elsewhere. A comparison of the MTR maps with MTR-based networks shows that although, in general, the changes in network architecture in AD recapitulate the topography of (de)myelination, some aspects of structural covariance (including the interhemispheric asymmetry of networks) have no immediate reflection in the myelination pattern.

Conservation of mayflies (Insecta, Ephemeroptera) in Espírito Santo, southeastern Brazil

Conservation of mayflies (Insecta, Ephemeroptera) in Espírito Santo, southeastern Brazil. Ephemeroptera exhibits great diversity among bodies of freshwater in the Atlantic Forest, a biome that is suffering from massive human impact. Within this context, the creation of conservation units using biological information is more recommended than economic, cultural, or political criteria. The distribution pattern of 76 Ephemeroptera species was analyzed using the biogeographical methods Parsimony Analysis of Endemicity and Network Analysis Method in order to infer relevant areas for conservation of the mayfly community in Espírito Santo. The results obtained from both analyses were largely congruent, and pointed out four relevant areas for conservation: two in the south of the state, where conservation units or priority areas for conservation are well established; and two in the north, a region in the state where little conservation efforts have been historically done. Therefore, based on our analyses on mayflies, we recommend the expansion of the existing APCs or the creation of new APCs on the north of Espírito Santo.