The relative importance of individual, job-related and organisational characteristics in explaining differences in earnings.

Abstract: This paper focuses on a number of key research questions: (1) What is the relative importance of individual, job-related and organizational characteristics in explaining differences in earnings? (2) Do job characteristics such as hierarchical level and functional domain exercise a significant influence on pay differentials if we control for the traditional human capital factors? (3) Do organizational characteristics such as size and the sector in which the company is active exercise a significant influence on pay differentials if we control for the traditional human capital factors and job-related pay determinants? In order to assess the relative importance of these pay determinants, use is made of linear regression and analysis of variance. The analysis draws on data from the Salary Survey, which generated pay details for a total of more than 15,000 Belgian white-collar workers. Based on the analysis, we come to the conclusion that the five main determinants, in order of importance, are number of years' work experience; level of education; hierarchical level; sector of employment; and the nationality of the parent company. A further striking feature is that more than 50% of the total explained variance can be attributed to the three features which receive a great deal of attention in traditional human capital approaches to pay differentials: level of education, work experience and gender.Implications; Characteristics;

Relating the metatranscriptome and metagenome of the human gut

Although the composition of the human microbiome is now wellstudied, the microbiota’s \u3e8 million genes and their regulation remain largely uncharacterized. This knowledge gap is in part because of the difficulty of acquiring large numbers of samples amenable to functional studies of the microbiota. We conducted what is, to our knowledge, one of the first human microbiome studies in a well-phenotyped prospective cohort incorporating taxonomic, metagenomic, and metatranscriptomic profiling at multiple body sites using self-collected samples. Stool and saliva were provided by eight healthy subjects, with the former preserved by three different methods (freezing, ethanol, and RNAlater) to validate self-collection. Within-subject microbial species, gene, and transcript abundances were highly concordant across sampling methods, with only a small fraction of transcripts (\u3c5%) displaying between-method variation. Next, we investigated relationships between the oral and gut microbial communities, identifying a subset of abundant oral microbes that routinely survive transit to the gut, but with minimal transcriptional activity there. Finally, systematic comparison of the gut metagenome and metatranscriptome revealed that a substantial fraction (41%) of microbial transcripts were not differentially regulated relative to their genomic abundances. Of the remainder, consistently underexpressed pathways included sporulation and amino acid biosynthesis, whereas up-regulated pathways included ribosome biogenesis and methanogenesis. Across subjects, metatranscriptional profiles were significantly more individualized than DNA-level functional profiles, but less variable than microbial composition, indicative of subject-specific whole-community regulation. The results thus detail relationships between community genomic potential and gene expression in the gut, and establish the feasibility of metatranscriptomic investigations in subject-collected and shipped samples

The Human Microbiome Project: A Community Resource for the Healthy Human Microbiome

The Human Microbiome Project (HMP) [1],[2] is a concept that was long in the making. After the Human Genome Project, interest grew in sequencing the “other genome" of microbes carried in and on the human body [3],[4]. Microbial ecologists, realizing that >99% of environmental microbes could not be easily cultured, developed approaches to study microorganisms in situ [5], primarily by sequencing the 16S ribosomal RNA gene (16S) as a phylogenetic and taxonomic marker to identify members of microbial communities [6]. The need to develop corresponding new methods for culture-independent studies [7],[8] in turn precipitated a sea change in the study of microbes and human health, inspiring the new term “metagenomics" [9] both to describe a technological approach—sequencing and analysis of the genes from whole communities rather than from individual genomes—and to emphasize that microbes function within communities rather than as individual species. This shift from a focus on individual organisms to microbial interactions [10] culminated in a National Academy of Science report [11], which outlined challenges and promises for metagenomics as a way of understanding the foundational role of microbial communities both in the environment and in human health.National Institutes of Health (U.S.) (grant U54HG004969)National Institutes of Health (U.S.) (grant U54HG004973)National Institutes of Health (U.S.) (grant U54AI084844)National Institutes of Health (U.S.) (grant U01HG004866)National Institutes of Health (U.S.) (grant R01HG005969)National Institutes of Health (U.S.) (grant R01HG004872)United States. Army Research Office (grant W911NF-11-1-0473)National Science Foundation (U.S.) (NSF DBI-1053486)Howard Hughes Medical Institute (Early Career Scientist

Tracking of structural and functional cardiac measures from infancy into school-age

Objective Cardiac structure and function are important predictors for cardiovascular disease in adults. Not much is known about tracking of cardiac measures, other than left ventricular mass, from early life onwards. We examined whether and to what extent cardiac measures track from infancy into school-age. Methods We performed a population-based prospective cohort study among 1072 children. Aortic root diameter, left atrial diameter, left ventricular mass, relative wall thickness and fractional shortening were measured repeatedly by echocardiography. We explored tracking between infancy (1.5, six and 24 months) and school-age (six and 10 years). Results Of all cardiac measures, aortic root diameter, left atrial diameter and left ventricular mass were significantly correlated between infancy and school-age (r = 0.10-0.42, all p-values < 0.01), with the strongest correlations between 24 months and 10 years. Of the different structures, aortic root diameter showed the strongest correlations. Approximately 30% of children who were in the lowest or highest quartile of a measure at the age of 1.5 months remained in that quartile at the age of 10 years. When analysing the effects of the infant cardiac measures on the same outcomes at 10 years in conditional regression models, we observed ef

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

Editorial: Violence can be prevented

No Abstrac

Sub-clinical detection of gut microbial biomarkers of obesity and type 2 diabetes

Background: Obesity and type 2 diabetes (T2D) are linked both with host genetics and with environmental factors, including dysbioses of the gut microbiota. However, it is unclear whether these microbial changes precede disease onset. Twin cohorts present a unique genetically-controlled opportunity to study the relationships between lifestyle factors and the microbiome. In particular, we hypothesized that family-independent changes in microbial composition and metabolic function during the sub-clinical state of T2D could be either causal or early biomarkers of progression. Methods: We collected fecal samples and clinical metadata from 20 monozygotic Korean twins at up to two time points, resulting in 36 stool shotgun metagenomes. While the participants were neither obese nor diabetic, they spanned the entire range of healthy to near-clinical values and thus enabled the study of microbial associations during sub-clinical disease while accounting for genetic background. Results: We found changes both in composition and in function of the sub-clinical gut microbiome, including a decrease in Akkermansia muciniphila suggesting a role prior to the onset of disease, and functional changes reflecting a response to oxidative stress comparable to that previously observed in chronic T2D and inflammatory bowel diseases. Finally, our unique study design allowed us to examine the strain similarity between twins, and we found that twins demonstrate strain-level differences in composition despite species-level similarities. Conclusions: These changes in the microbiome might be used for the early diagnosis of an inflamed gut and T2D prior to clinical onset of the disease and will help to advance toward microbial interventions. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0271-6) contains supplementary material, which is available to authorized users

Prosemantic features for content-based image retrieval

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-18449-9_8Revised Selected Papers of 7th International Workshop, AMR 2009, Madrid, Spain, September 24-25, 2009We present here, an image description approach based on prosemantic features. The images are represented by a set of low-level features related to their structure and color distribution. Those descriptions are fed to a battery of image classifiers trained to evaluate the membership of the images with respect to a set of 14 overlapping classes. Prosemantic features are obtained by packing together the scores. To verify the effectiveness of the approach, we designed a target search experiment in which both low-level and prosemantic features are embedded into a content-based image retrieval system exploiting relevance feedback. The experiments show that the use of prosemantic features allows for a more successful and quick retrieval of the query images