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Artemisinin is a natural product used as an alternative drug in the treatment of severe and multidrug-resistant malaria. In the present work we show that artemisinin shares with other sesquiterpene lactones the ability to inhibit the activation of the nuclear factor NF-kB: by this mechanism, artemisinin, as well as parthenolide, inhibits nitric oxide synthesis in cytokine-stimulated human astrocytoma T67 cells. These results suggest that artemisinin, in addition to its antiparasitic properties, could also exert a therapeutic effect on neurological complications of malaria.

International audience; Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only 3 CDR loops from the single variable domain (VHH) at the N-terminus of each heavy chain. This feature of the VHH, along with other important features, e.g. easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better VHH domains, it is important to thoroughly understand their sequence and structure characteristics and relationships. In this study sequence, characteristics of VHH have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of VHHs showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of VHH, an exciting view of various factors in structure prediction of VHH, like template framework selection, is also discussed.

Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (VHH) at the N-terminus of each heavy chain. This feature of the VHH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better VHH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of VHH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of VHH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of VHH, an exciting view of various factors in structure prediction of VHH, like template framework selection, is also discussed.

International audience; Sequencing the human genome began in 1994, and 10 years of work were necessary in order to provide a nearly complete sequence. Nowadays, NGS technologies allow sequencing of a whole human genome in a few days. This deluge of data challenges scientists in many ways, as they are faced with data management issues and analysis and visualization drawbacks due to the limitations of current bioinformatics tools. In this paper, we describe how the NGS Big Data revolution changes the way of managing and analysing data. We present how biologists are confronted with abundance of methods, tools, and data formats. To overcome these problems, focus on Big Data Information Technology innovations from web and business intelligence. We underline the interest of NoSQL databases, which are much more efficient than relational databases. Since Big Data leads to the loss of interactivity with data during analysis due to high processing time, we describe solutions from the Business Intelligence that allow one to regain interactivity whatever the volume of data is. We illustrate this point with a focus on the Amadea platform. Finally, we discuss visualization challenges posed by Big Data and present the latest innovations with JavaScript graphic libraries.

Background Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor (kNN) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs. Results In this study, we show that the MVs have important effects on the stability of the gene clusters. Moreover, the magnitude of the gene misallocations is depending on the aggregation algorithm. The most appropriate aggregation methods (e.g. complete-linkage and Ward) are highly sensitive to MVs, and surprisingly, for a very tiny proportion of MVs (e.g. 1%). In most of the case, the MVs must be replaced by expected values. The MVs replacement by the kNN approach clearly improves the identification of co-expressed gene clusters. Nevertheless, we observe that kNN approach is less suitable for the extreme values of gene expression. Conclusion The presence of MVs (even at a low rate) is a major factor of gene cluster instability. In addition, the impact depends on the hierarchical clustering algorithm used. Some methods should be used carefully. Nevertheless, the kNN approach constitutes one efficient method for restoring the missing expression gene values, with a low error level. Our study highlights the need of statistical treatments in microarray data to avoid misinterpretation.

International audience; The VHHs are antigen-binding region/domain of camelid heavy chain antibodies (HCAb). They have many interesting biotechnological and biomedical properties due to their small size, high solubility and stability, and high affinity and specificity for their antigens. HCAb and classical IgGs are evolutionary related and share a common fold. VHHs are composed of regions considered as constant, called the frameworks (FRs) connected by Complementarity Determining Regions (CDRs), a highly variable region that provide interaction with the epitope. Actually, no systematic structural analyses had been performed on VHH structures despite a significant number of structures. This work is the first study to analyse the structural diversity of FRs of VHHs. Using a structural alphabet that allows approximating the local conformation, we show that each of the four FRs do not have a unique structure but exhibit many structural variant patterns. Moreover, no direct simple link between the local conformational change and amino acid composition can be detected. These results indicate that long-range interactions affect the local conformation of FRs and impact the building of structural models.

International audience; The laboratory notebook is an essential tool in the company and in the laboratory. It allows durable follow-up of experiments; it is also an essential legal tool. Its electronic versions have become increasingly efficient over recent years, providing new functions, more rapid access to data and aid to decision-making, but they also raise new questions concerning their ease of use and their possible limitations. This article is designed to summarize the specificities and advantages of the electronic laboratory notebook as well as its current limitations.

BMC Genomics ISI Document Delivery No.: 565GZ Times Cited: 11 Cited Reference Count: 84 Celton, Magalie Malpertuy, Alain Lelandais, Gaelle de Brevern, Alexandre G. Ministere de la Recherche; French Institute for Health and Medical Research (INSERM); Universite - Paris Diderot Paris 7; Institut National de Transfusion Sanguine (INTS) and Genopole(R); Clustering Agreement Ration (CAR) We would like to thanks all the scientists who have deposited their experiments and make them freely available to the scientific community. In the same way, we would like to thanks all the scientists who have developed and distributed missing value replacement methods. This work was supported by grants from the Ministere de la Recherche, from French Institute for Health and Medical Research (INSERM), Universite - Paris Diderot Paris 7, Institut National de Transfusion Sanguine (INTS) and Genopole (R). Clustering Agreement Ration (CAR) was proposed by late Pr. Serge Hazout. Biomed central ltd London; International audience; BACKGROUND: Microarray technologies produced large amount of data. In a previous study, we have shown the interest of k-Nearest Neighbour approach for restoring the missing gene expression values, and its positive impact of the gene clustering by hierarchical algorithm. Since, numerous replacement methods have been proposed to impute missing values (MVs) for microarray data. In this study, we have evaluated twelve different usable methods, and their influence on the quality of gene clustering. Interestingly we have used several datasets, both kinetic and non kinetic experiments from yeast and human. RESULTS: We underline the excellent efficiency of approaches proposed and implemented by Bo and co-workers and especially one based on expected maximization (EM_array). These improvements have been observed also on the imputation of extreme values, the most difficult predictable values. We showed that the imputed MVs have still important effects on the stability of the gene clusters. The improvement on the clustering obtained by hierarchical clustering remains limited and, not sufficient to restore completely the correct gene associations. However, a common tendency can be found between the quality of the imputation method and the gene cluster stability. Even if the comparison between clustering algorithms is a complex task, we observed that k-means approach is more efficient to conserve gene associations. CONCLUSIONS: More than 6.000.000 independent simulations have assessed the quality of 12 imputation methods on five very different biological datasets. Important improvements have so been done since our last study. The EM_array approach constitutes one efficient method for restoring the missing expression gene values, with a lower estimation error level. Nonetheless, the presence of MVs even at a low rate is a major factor of gene cluster instability. Our study highlights the need for a systematic assessment of imputation methods and so of dedicated benchmarks. A noticeable point is the specific influence of some biological dataset.