Analytic and bootstrap approximations of prediction errors under a multivariate fay-herriot model

A Multivariate Fay-Herriot model is used to aid the prediction of small area parameters of dependent variables with sample data aggregated to area level. The empirical best linear unbiased predictor of the parameter vector is used, and an approximation of the elements of the mean cross product error matrix is obtained by an extension of the results of Prasad and Rao (1990) to the multiparameter case. Three different bootstrap approximations of those elements are introduced, and a simulation study is developed in order to compare the efficiency of all presented approximations, including a comparison under lack of normality. Further, the number of replications needed for the bootstrap procedures to get stabilized are studied

Insights into the inter-ring plasticity of caseinolytic proteases from the X-ray structure of Mycobacterium tuberculosis ClpP1.

International audienceMycobacterium tuberculosis caseinolytic protease ClpP1 (Mt ClpP1) is a self-compartmentalized protease consisting of two heptameric rings stacked on top of each other, thus enclosing a catalytic chamber. Within the chamber, which can be reached through two axial pores, each of the 14 identical monomers possesses a serine protease active site. The unfolding and translocation of substrates into the chamber are mediated by associated hexameric ATPases covering the axial pores. Three crystal structures of Mt ClpP1, determined by molecular replacement, are presented in this study. Two of the models were refined to a resolution of 2.6 A and the third to 3.0 A. It was found that disorder in the handle domain affects the formation and configuration of the tetradecamer and results in condensed structures with larger equatorial pores when compared with ClpPs from other species. Additionally, this disorder accompanies conformational changes of the residues in the catalytic triad. The models also reveal structural differences within the N-terminal hairpin-loop domain, which possibly reflect the significant differences in amino-acid sequence between Mt ClpP1 and other ClpP homologues in this region

Child Poverty, Youth (Un)Employment, and Social Inclusion

Worldwide child and youth poverty remain the biggest barrier to achieving a better life in adulthood. Progress in lifting children out of poverty in the last decades has been slow and limited in the developing world, while the recent global economic crisis has exacerbated child poverty, youth unemployment, and social exclusion in many developed countries. This book critically examines the long-term consequences of growing up poor, the close linkages between deprivation and human rights violations in childhood and adolescence, and their effects on labor market entry and future career in a number of developing and developed countries. Drawing on multiple disciplinary perspectives, it makes a forceful case for the eradication of child poverty to take center stage in the Sustainable Development Goals

Surfing transcriptomic landscapes. A step beyond the annotation of chromosome 16 proteome.

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC-MS/MS and gel/LC-MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study