Blau Syndrome-Associated Uveitis:Preliminary Results From an International Prospective Interventional Case Series

Purpose Provide baseline and preliminary follow-up results in a 5-year longitudinal study of Blau syndrome. Design Multicenter, prospective interventional case series. Methods Baseline data from 50 patients from 25 centers worldwide, and follow-up data for patients followed 1, 2, or 3 years at the end of study enrollment. Ophthalmic data were collected at baseline and yearly visits by means of a standardized collection form. Results Median age at onset of eye disease was 60 months and duration of eye disease at baseline 145 months. At baseline 38 patients (78%) had uveitis, which was bilateral in 37 (97%). Eight patients (21%) had moderate to severe visual impairment. Panuveitis was found in 38 eyes (51%), with characteristic multifocal choroidal infiltrates in 29 eyes (39%). Optic disc pallor in 9 eyes (12%) and peripapillary nodules in 9 eyes (12%) were the commonest signs of optic nerve involvement. Active anterior chamber inflammation was noted in 30 eyes (40%) at baseline and in 16 (34%), 17 (57%), and 11 (61%) eyes at 1, 2, and 3 years, respectively. Panuveitis was associated with longer disease duration. At baseline, 56 eyes (75%) were on topical corticosteroids. Twenty-six patients (68%) received a combination of systemic corticosteroids and immunomodulatory therapy. Conclusions Blau uveitis is characterized by progressive panuveitis with multifocal choroiditis, resulting in severe ocular morbidity despite continuous systemic and local immunomodulatory therapy. The frequency and severity of Blau uveitis highlight the need for close ophthalmologic surveillance as well as a search for more effective therapies

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website

Le casse-tête de la terminologie administrative et territoriale russe-français : analyse d'un ensemble de termes à travers un corpus de textes spécialisés, de textes de la presse française et de textes de l'ONU

Présentation de la Fédération de Russie et de ses niveaux de pouvoirs, des principales modifications territoriales effectuées depuis la chute de l'URSS, et des lois clé qui sont à la base de la nouvelle organisation administrative et territoriale du pays. Un ensemble de termes du registre administratif et territorial a été sélectionné, notamment dans la loi relative à l'autonomie locale datant de 2003, qui traite de l'organisation actuelle des pouvoirs locaux en Russie. Chaque terme choisi est présenté avec sa définition, puis analysé et comparé à travers différents textes. Une traduction est proposée pour chaque terme. Un glossaire réunissant tous les termes observés se trouve à la fin du mémoire

Assessing the validity domains of graphical gaussian models in order to infer relationships among components of complex biological systems

International audienceThe study of the interactions of cellular components is an essential base step to understand the structure and dynamics of biological networks. Various methods were recently developed for this purpose. While most of them combine different types of data and a priori knowledge, methods based on graphical Gaussian models are capable of learning the network directly from raw data. They consider the full-order partial correlations which are partial correlations between two variables given the remaining ones, for modeling direct links between variables. Statistical methods were developed for estimating these links when the number of observations is larger than the number of variables. However, the rapid advance of new technologies that allow the simultaneous measure of genome expression, led to large-scale datasets where the number of variables is far larger than the number of observations. To get around this dimensionality problem, different strategies and new statistical methods were proposed. In this study we focused on statistical methods recently published. All are based on the fact that the number of direct relationships between two variables is very small in regards to the number of possible relationships, p(p-1)/2. In the biological context, this assumption is not always satisfied over the whole graph. It is essential to precisely know the behavior of the methods in regards to the characteristics of the studied object before applying them. For this purpose, we evaluated the validity domain of each method from wide-ranging simulated datasets. We then illustrated our results using recently published biological dat

Assessing the validity domains of graphical gaussian models in order to infer relationships among components of complex biological systems

International audienceThe study of the interactions of cellular components is an essential base step to understand the structure and dynamics of biological networks. Various methods were recently developed for this purpose. While most of them combine different types of data and a priori knowledge, methods based on graphical Gaussian models are capable of learning the network directly from raw data. They consider the full-order partial correlations which are partial correlations between two variables given the remaining ones, for modeling direct links between variables. Statistical methods were developed for estimating these links when the number of observations is larger than the number of variables. However, the rapid advance of new technologies that allow the simultaneous measure of genome expression, led to large-scale datasets where the number of variables is far larger than the number of observations. To get around this dimensionality problem, different strategies and new statistical methods were proposed. In this study we focused on statistical methods recently published. All are based on the fact that the number of direct relationships between two variables is very small in regards to the number of possible relationships, p(p-1)/2. In the biological context, this assumption is not always satisfied over the whole graph. It is essential to precisely know the behavior of the methods in regards to the characteristics of the studied object before applying them. For this purpose, we evaluated the validity domain of each method from wide-ranging simulated datasets. We then illustrated our results using recently published biological dat

Assessing the Validity Domains of Graphical Gaussian Models in Order to Infer Relationships among Components of Complex Biological Systems

The study of the interactions of cellular components is an essential base step to understand the structure and dynamics of biological networks. Various methods were recently developed for this purpose. While most of them combine different types of data and a priori knowledge, methods based on graphical Gaussian models are capable of learning the network directly from raw data. They consider the full-order partial correlations which are partial correlations between two variables given the remaining ones, for modeling direct links between variables. Statistical methods were developed for estimating these links when the number of observations is larger than the number of variables. However, the rapid advance of new technologies that allow the simultaneous measure of genome expression, led to large-scale datasets where the number of variables is far larger than the number of observations. To get around this dimensionality problem, different strategies and new statistical methods were proposed. In this study we focused on statistical methods recently published. All are based on the fact that the number of direct relationships between two variables is very small in regards to the number of possible relationships, p(p-1)/2. In the biological context, this assumption is not always satisfied over the whole graph. It is essential to precisely know the behavior of the methods in regards to the characteristics of the studied object before applying them. For this purpose, we evaluated the validity domain of each method from wide-ranging simulated datasets. We then illustrated our results using recently published biological data.

European maize landraces : genetic diversity, core collection definition and methodology of use

International audienceSince its introduction in Europe five centuries ago, maize spread in Europe and numerous landraces have been cultivated. During the second half of the XXth century, large collections have been established to preserve this genetic diversity. The objectives of this paper are (i) to review recent results on the genetic structuration and the origin of European maize, (ii) to present the constitution of the representative core-collection of European maize landraces built in RESGEN CT96-088 project, and (iii) to study the methodology of use of these landraces in present breeding programs. Based on molecular markers, five studies found a high allelic richness in landraces from Mediterranean regions such as Spain, and (for two of them) a strong similarity between several populations from Southern Spain and a group of Caribbean populations. These studies also attest the originality of Northern Eastern Europe landraces, for which a similarity is observed with American Northern Flint landraces. Historical investigations confirm the hypothesis of introductions of maize from this origin in the North of Europe, only a few decades after introduction of tropical maize in Southern Spain by Colombus. Starting from a total of 2899 European landraces, we established with the Mstrat software a representative core collection of 96 maize accessions that maximizes allelic richness at molecular markers and best represents variation at phenotypic traits. This collection is characterized for traits of agronomical interest such as silage quality and insect tolerance. Regarding the transfer of relevant traits to elite material, comparison of F[2] versus backcross foundation populations showed that this last strategy leads to a higher population mean while not leading to a decrease in variance, therefore backcross method appears superior. Preliminary selection of superior material within a landrace did not increase average expected genetic gain but increased stability in variable environments. Molecular markers should prove helpful to extend this back-cross approach to the targeted transfer of donor interesting genomic regions

Should we look for anti-RNA polymerase III antibodies in systemic sclerosis patients with anti-centromere or anti-topoisomerase I antibodies?

International audienc