Cross-scale analysis of the region effect on vascular plant species diversity in southern and northern European mountain ranges.

Background: The divergent glacial histories of southern and northern Europe affect present-day species diversity at coarse-grained scales in these two regions, but do these effects also penetrate to the more fine-grained scales of local communities?Methodology/Principal Findings: We carried out a cross-scale analysis to address this question for vascular plants in two mountain regions, the Alps in southern Europe and the Scandes in northern Europe, using environmentally paired vegetation plots in the two regions (n = 403 in each region) to quantify four diversity components: (i) total number of species occurring in a region (total gamma-diversity), (ii) number of species that could occur in a target plot after environmental filtering (habitat-specific gamma-diversity), (iii) pair-wise species compositional turnover between plots (plot-to-plot beta-diversity) and (iv) number of species present per plot (plot gamma-diversity). We found strong region effects on total gamma-diversity, habitat-specific gamma-diversity and plot-to-plot beta-diversity, with a greater diversity in the Alps even towards distances smaller than 50 m between plots. In contrast, there was a slightly greater plot alpha-diversity in the Scandes, but with a tendency towards contrasting region effects on high and low soil-acidity plots.Conclusions/Significance: We conclude that there are strong regional differences between coarse-grained (landscape- to regional-scale) diversity components of the flora in the Alps and the Scandes mountain ranges,but that these differences do not necessarily penetrate to the finest-grained (plot-scale) diversity component, at least not on acidic soils. Because different processes can lead to a similar pattern, we discuss the consistency of our results with Quaternary history and other divergent features between the two regions such as habitat connectivity, selection for vagility and environmental differences not accounted for in our analyses

A modular approach for integrative analysis of large-scale gene-expression and drug-response data

High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution.

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a "covarion-like" pattern of correlated changes in evolutionary rates, and switches in conserved residues ("conserved but different"). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than "constant but different," but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.

A positive interaction between inhibitors of protein synthesis and cefepime in the fight against methicillin-resistant Staphylococcus aureus.

Quinupristin-dalfopristin (Q-D) synergizes with cefepime for the treatment of methicillin-resistant Staphylococcus aureus (MRSA). Here, we studied whether the synergism was restricted to MRSA and if it extended to non-beta-lactam cell wall inhibitors or to other inhibitors of protein synthesis. Three MRSA and two methicillin-susceptible S. aureus (MSSA) strains were tested, including an isogenic pair of mecA (-)/mecA (+) S. aureus Newman. The drug interactions were determined by fractional inhibitory concentration (FIC) indices and population analysis profiles. The antibacterial drugs that we used included beta-lactam (cefepime) and non-beta-lactam cell wall inhibitors (D-cycloserine, fosfomycin, vancomycin, teicoplanin), inhibitors of protein synthesis (Q-D, erythromycin, chloramphenicol, tetracycline, linezolid, fusidic acid), and polynucleotide inhibitors (cotrimoxazole, ciprofloxacin). The addition of each protein inhibitor to cefepime was synergistic (FIC ≤ 0.5) or additive (FIC > 0.5 but < 1) against MRSA, but mostly indifferent against MSSA (FIC ≥ 1 but ≤ 4). This segregation was not observed after adding cotrimoxazole or ciprofloxacin to cefepime. Population analysis profiles were performed on plates in the presence of increasing concentrations of the cell wall inhibitors plus 0.25 × minimum inhibitory concentration (MIC) of Q-D. Cefepime combined with Q-D was synergistic against MRSA, but D-cycloserine and glycopeptides were not. Thus, the synergism was specific to beta-lactam antibiotics. Moreover, the synergism was not lost against fem mutants, indicating that it acted at another level. The restriction of the beneficial effect to MRSA suggests that the functionality of penicillin-binding protein 2A (PBP2A) was affected, either directly or indirectly. Further studies are necessary in order to provide a mechanism for this positive interaction.

Automobile Corporate Networks in Europe : Sectoral Specialization of Central and Eastern European Cities

The global automobile industry is made up of very large corporations and their various subsidiaries containing different functions that create complex locational structures. The networks formed by the 19 largest automobile transnational corporations constitute an automobile "oligopoly" representing more than 90% (OICA, 2012) of the world's production. Since the mid-1990s, Central and Eastern European cities have become attractive for transnational corporations and particularly for the production functions in the automobile sector. This leads to a crucial question. Are strategic functions (such as R&D) within these networks also located in Central and Eastern Europe, or is the region still manufacturing-oriented in the automobile industry? This paper focuses on the patterns and the main factors influencing the role of some of these new central and Eastern European cities that have become integrated in the global value chain of the automobile industry. By analysing the various locations of the specialized functions within the corporations, this study aims to extend the research on global value chains (Gereffi and Korzeniewicz; 1994, Sturgeon, 2000; Krätke, 2014). The spatial patterns of the various functions and the ownerships networks of the automobile industry are constructed in order to identify the cities supporting it. In particular, the way that national metropolises bring their national territories into the globalization of the automobile industry is addressed. For example, are there some specific advantages of capital cities compared to cities that have less integration in globalization terms?

Identification of tumor-associated antigens by large-scale analysis of genes expressed in human colorectal cancer.

Despite the high prevalence of colon cancer in the world and the great interest in targeted anti-cancer therapy, only few tumor-specific gene products have been identified that could serve as targets for the immunological treatment of colorectal cancers. The aim of our study was therefore to identify frequently expressed colon cancer-specific antigens. We performed a large-scale analysis of genes expressed in normal colon and colon cancer tissues isolated from colorectal cancer patients using massively parallel signal sequencing (MPSS). Candidates were additionally subjected to experimental evaluation by semi-quantitative RT-PCR on a cohort of colorectal cancer patients. From a pool of more than 6000 genes identified unambiguously in the analysis, we found 2124 genes that were selectively expressed in colon cancer tissue and 147 genes that were differentially expressed to a significant degree between normal and cancer cells. Differential expression of many genes was confirmed by RT-PCR on a cohort of patients. Despite the fact that deregulated genes were involved in many different cellular pathways, we found that genes expressed in the extracellular space were significantly over-represented in colorectal cancer. Strikingly, we identified a transcript from a chromosome X-linked member of the human endogenous retrovirus (HERV) H family that was frequently and selectively expressed in colon cancer but not in normal tissues. Our data suggest that this sequence should be considered as a target of immunological interventions against colorectal cancer.

Fine-scale genetic structure and marginal processes in an expanding population of Biscutella laevigata L. (Brassicaceae).

Evolutionary processes acting at the expanding margins of a species' range are still poorly understood. Genetic drift is considered prevalent in marginal populations, and the maintenance of genetic diversity during recolonization might seem puzzling. To investigate such processes, a fine-scale investigation of 219 individuals was performed within a population of Biscutella laevigata (Brassicaceae), located at the leading edge of its range. The survey used amplified fragment length polymorphisms (AFLPs). As commonly reported across the whole species distribution range, individual density and genetic diversity decreased along the local axis of recolonization of this expanding population, highlighting the enduring effect of the historical colonization on present-day diversity. The self-incompatibility system of the plant may have prevented local inbreeding in newly found patches and sustained genetic diversity by ensuring gene flow from established populations. Within the more continuously populated region, spatial analysis of genetic structure revealed restricted gene flow among individuals. The distribution of genotypes formed a mosaic of relatively homogenous patches within the continuous population. This pattern could be explained by a history of expansion by long-distance dispersal followed by fine-scale diffusion (that is, a stratified dispersal combination). The secondary contact among expanding patches apparently led to admixture among differentiated genotypes where they met (that is, a reshuffling effect). This type of dynamics could explain the maintenance of genetic diversity during recolonization.

Synthesis and Biological Evaluation of S-Neofucopeptides as E- and P-Selectin Inhibitors.

The synthesis of /-L-fucosylated cysteamine, 3-thiopropionic acid, and 3-thioacetic acid derivatives as building blocks for the preparation of S-neofucopeptides is shown. These compounds were used in the synthesis of new thiofucosides derivatives (8, 9, 9, 10, 22, 22, 24, 26) that show affinity towards E- and P-selectins. They constitute a new series of hydrolytically stable and low-molecular-weight mimetics of the natural SLex tetrasaccharide.

Man Made Black Holes and Big Bangs: Diffusion and Integration of Scientific Information into Everyday Thinking

Drawing on Social Representations Theory, this study investigates focalisation and anchoring during the diffusion of information concerning the Large Hadron Collider (LHC), the particle accelerator at the European Organisation for Nuclear Research (CERN). We hypothesised that people focus on striking elements of the message, abandoning others, that the nature of the initial information affects diffusion of information, and that information is anchored in prior attitudes toward CERN and science. A serial reproduction experiment with two generations and four chains of reproduction diffusing controversial versus descriptive information about the LHC shows a reduction of information through generations, the persistence of terminology regarding the controversy and a decrease of other elements for participants exposed to polemical information. Concerning anchoring, positive attitudes toward CERN and science increase the use of expert terminology unrelated to the controversy. This research highlights the relevance of a social representational approach in the public understanding of science.

Application of the 2008 definitions for invasive fungal diseases to the trial comparing voriconazole versus amphotericin B for therapy of invasive aspergillosis: a collaborative study of the Mycoses Study Group (MSG 05) and the European Organization for Research and Treatment of Cancer Infectious Diseases Group.

BACKGROUND: Strict definition of invasive aspergillosis (IA) cases is required to allow precise conclusions about the efficacy of antifungal therapy. The Global Comparative Aspergillus Study (GCAS) compared voriconazole to amphotericin B (AmB) deoxycholate for the primary therapy of IA. Because predefined definitions used for this trial were substantially different from the consensus definitions proposed by the European Organization for Research and Treatment of Cancer/Mycoses Study Group in 2008, we recategorized the 379 episodes of the GCAS according to the later definitions. METHODS: The objectives were to assess the impact of the current definitions on the classification of the episodes and to provide comparative efficacy for probable/proven and possible IA in patients treated with either voriconazole or AmB. In addition to original data, we integrated the results of baseline galactomannan serum levels obtained from 249 (65.7%) frozen samples. The original response assessment was accepted unchanged. RESULTS: Recategorization allowed 59 proven, 178 probable, and 106 possible IA cases to be identified. A higher favorable 12-week response rate was obtained with voriconazole (54.7%) than with AmB (29.9%) (P < .0001). Survival was higher for voriconazole for mycologically documented (probable/proven) IA (70.2%) than with AmB (54.9%) (P = .010). Higher response rates were obtained in possible IA treated with voriconazole vs AmB with the same magnitude of difference (26.2%; 95% confidence interval [CI], 7.2%-45.3%) as in mycologically documented episodes (24.3%; 95% CI, 11.9%-36.7%), suggesting that possible cases are true IA. CONCLUSIONS: Recategorization resulted in a better identification of the episodes and confirmed the higher efficacy of voriconazole over AmB deoxycholate in mycologically documented IA.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Regulation by aldosterone of Na+,K+-ATPase mRNAs, protein synthesis, and sodium transport in cultured kidney cells.

Transepithelial Na+ reabsorption across tight epithelia is regulated by aldosterone. Mineralocorticoids modulate the expression of a number of proteins. Na+,K+-ATPase has been identified as an aldosterone-induced protein (Geering, K., M. Girardet, C. Bron, J. P. Kraehenbuhl, and B. C. Rossier, 1982, J. Biol. Chem., 257:10338-10343). Using A6 cells (kidney of Xenopus laevis) grown on filters we demonstrated by Northern blot analysis that the induction of Na+,K+-ATPase was mainly mediated by a two- to fourfold accumulation of both alpha- and beta-subunit mRNAs. The specific competitor spironolactone decreased basal Na+ transport, Na+,K+-ATPase mRNA, and the relative rate of protein biosynthesis, and it blocked the response to aldosterone. Cycloheximide inhibited the aldosterone-dependent sodium transport but did not significantly affect the cytoplasmic accumulation of Na+,K+-ATPase mRNA induced by aldosterone.

Design, synthesis and biological evaluation of a class of bioisosteric oximes of the novel dual peroxisome proliferator-activated receptor α/γ ligand LT175.

The effects resulting from the introduction of an oxime group in place of the distal aromatic ring of the diphenyl moiety of LT175, previously reported as a PPARα/γ dual agonist, have been investigated. This modification allowed the identification of new bioisosteric ligands with fairly good activity on PPARα and fine-tuned moderate activity on PPARγ. For the most interesting compound (S)-3, docking studies in PPARα and PPARγ provided a molecular explanation for its different behavior as full and partial agonist of the two receptor isotypes, respectively. A further investigation of this compound was carried out performing gene expression studies on HepaRG cells. The results obtained allowed to hypothesize a possible mechanism through which this ligand could be useful in the treatment of metabolic disorders. The higher induction of the expression of some genes, compared to selective agonists, seems to confirm the importance of a dual PPARα/γ activity which probably involves a synergistic effect on both receptor subtypes.

Loss of insulin synthesis and beta cell survival induced by oxidized LDL require activation of reticulum endoplasmic stress: a mechanism countered by HDL

Elevated circulating concentrations in modified LDL-cholesterol particles (e.g. oxidised LDL) and low levels in HDL increase not only the risk for diabetic patients to develop cardiovascular diseases but also may contribute to development and progression of diabetes by directly having adverse effects on β-cells. Chronic exposure of β-cells to 2 mM human oxidised LDL-cholesterol (oxLDL) increases the rate of apoptosis, reduce insulin biosynthesis and the secretory capacity of the cells in response to nutrients. In line with the protective role, HDL efficiently antagonised the harmful effects of ox- LDL, suggesting that low levels of HDL would be inefficient to protect β-cells against oxLDL attack in patients. Activation of endoplasmic reticulum (ER) stress is pointed out to contribute to β-cell dysfunction elicited by environmental stressors. In this study we investigated whether activation of ER stress is required for oxLDL to mediate detrimental effects on β-cells and we tested the potential antagonist properties of HDL: The mouse MIN6 insulin-secreting cells were cultured with 2 mM of LDL-cholesterol preparation (native or in vitro oxidized) in the presence or absence of 1 mM of HDL-cholesterol or the ER stress inhibitor 4-phenylbutyrate (4-PBA): Prolonged exposure of MIN6 cells to 2 mM oxLDL-cholesterol for 48 hours led to an increase in expression of ER stress markers such as ATF4, CHOP and p58 and stimulated the splicing of XBP-1 whereas, induction of these markers was not observable in the cells cultured with native LDL. Treatment of the cells with the 4-PBA chemical chaperone molecule efficiently blocked activation of the ER stress markers induced by oxLDL. The latter mediates β-cell dysfunction and apoptosis by diminishing the expression of islet brain 1 (IB1) and Bcl2. The levels of these two proteins were preserved in the cells that were co-treated with oxLDL and the 4-PBA. Consistent with this result we found that blockade of ER stress activation alleviated the loss of insulin synthesis and abolished apoptosis evoked by oxLDL. However incubation of the cells with 4-PBA did not prevent impairment of insulin secretion elicited by oxLDL, indicating that ER stress is not responsible for the oxLDL-mediated defect of insulin secretion. Co-incubation of the cells with HDL mimicked the effects of 4-PBA on the expression of IB1 and Blc2 and thereby counteracted oxLDL attacks on insulin synthesis and cell survivals. We found that HDL efficiently inhibited activation of the ER stress mediated by oxLDL: These data highlight the contribution of the ER stress in the defects of insulin synthesis and cell survivals induced by oxLDL and emphasize the potent role of HDL to counter activation of the oxLDL-mediated ER-stress activation: