Uncovering hidden duplicated content in public transcriptomics data.

As part of the development of the database Bgee (a dataBase for Gene Expression Evolution), we annotate and analyse expression data from different types and different sources, notably Affymetrix data from GEO and ArrayExpress, and RNA-Seq data from SRA. During our quality control procedure, we have identified duplicated content in GEO and ArrayExpress, affecting ∼14% of our data: fully or partially duplicated experiments from independent data submissions, Affymetrix chips reused in several experiments, or reused within an experiment. We present here the procedure that we have established to filter such duplicates from Affymetrix data, and our procedure to identify future potential duplicates in RNA-Seq data. Database URL: http://bgee.unil.ch/

Cryo-negative staining reveals conformational flexibility within yeast RNA polymerase I.

The structure of the yeast DNA-dependent RNA polymerase I (RNA Pol I), prepared by cryo-negative staining, was studied by electron microscopy. A structural model of the enzyme at a resolution of 1.8 nm was determined from the analysis of isolated molecules and showed an excellent fit with the atomic structure of the RNA Pol II Delta4/7. The high signal-to-noise ratio (SNR) of the stained molecular images revealed a conformational flexibility within the image data set that could be recovered in three-dimensions after implementation of a novel strategy to sort the "open" and "closed" conformations in our heterogeneous data set. This conformational change mapped in the "wall/flap" domain of the second largest subunit (beta-like) and allows a better accessibility of the DNA-binding groove. This displacement of the wall/flap domain could play an important role in the transition between initiation and elongation state of the enzyme. Moreover, a protrusion was apparent in the cryo-negatively stained model, which was absent in the atomic structure and was not detected in previous 3D models of RNA Pol I. This structure could, however, be detected in unstained views of the enzyme obtained from frozen hydrated 2D crystals, indicating that this novel feature is not induced by the staining process. Unexpectedly, negatively charged molybdenum compounds were found to accumulate within the DNA-binding groove, which is best explained by the highly positive electrostatic potential of this region of the molecule, thus, suggesting that the stain distribution reflects the overall surface charge of the molecule.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

X-ray microtomography of Larger Foraminifera

X-ray microtomography has become a new tool in earth sciences to obtain non-destructive 3D-image data from geological objects in which variations in mineralogy, chemical composition and/or porosity create sufficient x-ray density contrasts.We present here first, preliminary results of an application to the external and internal morphology of Permian to Recent Larger Foraminifera. We use a SkyScan-1072 high-resolution desk-top micro-CT system. The system has a conical x-ray source with a spot size of about 5µm that runs at 20-100kV, 0-250µA, resulting in a maximal resolution of 5µm. X-ray transmission images are captured by a scintillator coupled via fibre optics to a 1024x1024 pixel 12-bit CCD. The object is placed between the x-ray source and the scintillator on a stub that rotates 360°around its vertical axis in steps as small as 0.24 degrees. Sample size is limited to 2 cm due to the absorption of geologic material for x-rays. The transmission images are back projected using a Feldkamp algorithm into a vertical stack of up to 1000 1Kx1K images that represent horizontal cuts of the object. This calculation takes 2 to several hours on a Double-Processor 2.4GHz PC. The stack of images (.bmp) can be visualized with any 3D-imaging software, used to produce cuts of Larger Foraminifera. Among other applications, the 3D-imaging software furnished by SkyScan can produce 3D-models by defining a threshold density value to distinguish "solid" from "void. Several models with variable threshold values and colors can be imbricated, rotated and cut together. The best results were obtained with microfossils devoid of chamber-filling cements (Permian, Eocene, Recent). However, even slight differences in cement mineralogy/composition can result in surprisingly good x-ray density contrasts.X-ray microtomography may develop into a powerful tool for larger microfossils with a complex internal structure, because it is non-destructive, requires no preparation of the specimens, and produces a true 3D-image data set. We will use these data sets in the future to produce cuts in any direction to compare them with arbitrary cuts of complex microfossils in thin sections. Many groups of benthic and planktonic foraminifera may become more easily determinable in thin section by this way.

Precursor-product relationship between vitellogenin and the yolk proteins as derived from the complete sequence of a Xenopus vitellogenin gene.

In Xenopus laevis four estrogen-responsive genes are expressed simultaneously to produce vitellogenin, the precursor of the yolk proteins. One of these four genes, the gene A2, was sequenced completely, as well as cDNAs representing 75% of the coding region of the gene. From this data the exon-intron structure of the gene was established, revealing 35 exons that give a transcript of 5,619 bp without the poly A-tail. This A2 transcript encodes a vitellogenin of 1,807 amino acids, whose structure is discussed with respect to its function. At the nucleic acid as well as at the protein level no extensive homologies with any sequences other than vitellogenin were observed. Comparison of the amino acid sequence of the vitellogenin A2 molecule with biochemical data obtained from the different yolk proteins allowed us to localize the cleavage products on the vitellogenin precursor as follows: NH2 - lipovitellin I - phosvitin (or phosvette II - phosvette I) - lipovitellin II - COOH.

Entorno Colaborativo de Trabajo: La Intranet 2.0 de la Consejería de Salud de la Junta de Andalucía

The Department of Health of the Government of Andalusia provides professionals of the Andalusian Public Health Care System a collaborative working environment (Entorno colaborativo de trabajo [ECT]) based on the principles of web 2.0. The ECT is organized into communities, understood as sets of people with a common interest who share a space with its own information and collaboration tools. This space is managed and powered autonomously by the communities themselves. This paper analyzes the use and degree of implementation of the ECT, considering the user communities and activity statistics in 2009 and 2010. From the data obtained we deduce that instrumental services have easier acceptance than collaboration and knowledge management services; content generation is focused on a small number of users; and communities associated with organizational units have less development than those associated with work areas or projects.

Spatio-temporal trends of mortality in small areas of Southern Spain

Background: Most mortality atlases show static maps from count data aggregated over time. This procedure has several methodological problems and serious limitations for decision making in Public Health. The evaluation of health outcomes, including mortality, should be approached from a dynamic time perspective that is specific for each gender and age group. At the moment, researches in Spain do not provide a dynamic image of the population’s mortality status from a spatio-temporal point of view. The aim of this paper is to describe the spatial distribution of mortality from all causes in small areas of Andalusia (Southern Spain) and evolution over time from 1981 to 2006. Methods: A small-area ecological study was devised using the municipality as the unit for analysis. Two spatiotemporal hierarchical Bayesian models were estimated for each age group and gender. One of these was used to estimate the specific mortality rate, together with its time trends, and the other to estimate the specific rate ratio for each municipality compared with Spain as a whole. Results: More than 97% of the municipalities showed a diminishing or flat mortality trend in all gender and age groups. In 2006, over 95% of municipalities showed male and female mortality specific rates similar or significantly lower than Spanish rates for all age groups below 65. Systematically, municipalities in Western Andalusia showed significant male and female mortality excess from 1981 to 2006 only in age groups over 65. Conclusions: The study shows a dynamic geographical distribution of mortality, with a different pattern for each year, gender and age group. This information will contribute towards a reflection on the past, present and future of mortality in Andalusia.

Consumption and portion sizes of tree nuts, peanuts and seeds in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts from 10 European countries

Tree nuts, peanuts and seeds are nutrient dense foods whose intake has been shown to be associated with reduced risk of some chronic diseases. They are regularly consumed in European diets either as whole, in spreads or from hidden sources (e.g. commercial products). However, little is known about their intake profiles or differences in consumption between European countries or geographic regions. The objective of this study was to analyse the population mean intake and average portion sizes in subjects reporting intake of nuts and seeds consumed as whole, derived from hidden sources or from spreads. Data was obtained from standardised 24-hour dietary recalls collected from 36 994 subjects in 10 different countries that are part of the European Prospective Investigation into Cancer and Nutrition (EPIC). Overall, for nuts and seeds consumed as whole, the percentage of subjects reporting intake on the day of the recall was: tree nuts = 4. 4%, peanuts = 2.3 % and seeds = 1.3 %. The data show a clear northern (Sweden: mean intake = 0.15 g/d, average portion size = 15.1 g/d) to southern (Spain: mean intake = 2.99 g/d, average portion size = 34.7 g/d) European gradient of whole tree nut intake. The three most popular tree nuts were walnuts, almonds and hazelnuts, respectively. In general, tree nuts were more widely consumed than peanuts or seeds. In subjects reporting intake, men consumed a significantly higher average portion size of tree nuts (28.5 v. 23.1 g/d, P<0.01) and peanuts (46.1 v. 35.1 g/d, P<0.01) per day than women. These data may be useful in devising research initiatives and health policy strategies based on the intake of this food group.

Natural evidence for rapid abiogenic hydrothermal generation of CH4

Although recent hydrothermal experiments imply that abiogenic methane (CH4) generation from hydrothermal reduction of CO2 can occur, evidence from natural systems was still lacking. Based on the chemical and isotopic equilibrium signatures of low-temperature fumarolic gas discharges, we are able to provide hard evidence for its natural occurrence, namely in three subduction-related bi-phase hydrothermal systems of the Mediterranean, whose temperatures range from 260 to 470 degrees C. The attainment of equilibrium and the time spans of recent volcanic dormancy allowed us to calculate minimum rates for chemical and isotopic equilibration. These are significantly higher than those previously reported and might be due to the presence of a saturated water vapor phase in the investigated systems. The fact that nature provides conditions enabling relatively fast production of hydrocarbons from CO2 strongly supports the concerns that were recently raised from laboratory experiments. These address the use of the carbon isotope composition of reduced carbon in Archean sediments as a tracer of early life and the occurrence of CH4 on extraterrestrial planets as a bioindicator. In view of the potential role of abiogenic CH4 as a precursor of life, we also present an estimate of abiogenic hydrothermal CH4 fluxes throughout the Archean. It is not expected that these fluxes exceeded 80 Mt/yr during the past 4.0 Ga. This, however, would have been enough to facilitate HCN production on the prebiotic Earth. (C) 2007 Elsevier Ltd. All rights reserved.

Genome-wide association study of multiple sclerosis confirms a novel locus at 5p13.1.

Multiple Sclerosis (MS) is the most common progressive and disabling neurological condition affecting young adults in the world today. From a genetic point of view, MS is a complex disorder resulting from the combination of genetic and non-genetic factors. We aimed to identify previously unidentified loci conducting a new GWAS of Multiple Sclerosis (MS) in a sample of 296 MS cases and 801 controls from the Spanish population. Meta-analysis of our data in combination with previous GWAS was done. A total of 17 GWAS-significant SNPs, corresponding to three different loci were identified:HLA, IL2RA, and 5p13.1. All three have been previously reported as GWAS-significant. We confirmed our observation in 5p13.1 for rs9292777 using two additional independent Spanish samples to make a total of 4912 MS cases and 7498 controls (ORpooled = 0.84; 95%CI: 0.80-0.89; p = 1.36 × 10-9). This SNP differs from the one reported within this locus in a recent GWAS. Although it is unclear whether both signals are tapping the same genetic association, it seems clear that this locus plays an important role in the pathogenesis of MS.

Genetic diversity of Leishmania infantum field populations from Brazil

Leishmania infantum (syn. Leishmania chagasi) is the etiological agent of visceral leishmaniasis (VL) in Brazil. The epidemiology of VL is poorly understood. Therefore, a more detailed molecular characterization at an intraspecific level is certainly needed. Herein, three independent molecular methods, multilocus microsatellite typing (MLMT), random amplification of polymorphic DNA (RAPD) and simple sequence repeats-polymerase chain reaction (SSR-PCR), were used to evaluate the genetic diversity of 53 L. infantum isolates from five different endemic areas in Brazil. Population structures were inferred by distance-based and Bayesian-based approaches. Eighteen very similar genotypes were detected by MLMT, most of them differed in only one locus and no correlation was found between MLMT profiles, geographical origin or the estimated population structure. However, complex profiles composed of 182 bands obtained by both RAPD and SSR-PCR assays gave different results. Unweighted pair group method with arithmetic mean trees built from these data revealed a high degree of homogeneity within isolates of L. infantum. Interestingly, despite this genetic homogeneity, most of the isolates clustered according to their geographical origin.

Use of variability in national and regional data to estimate the prevalence of lymphangioleiomyomatosis.

Background: Understanding the true prevalence of lymphangioleiomyomatosis (LAM) is important in estimating disease burden and targeting specific interventions. As with all rare diseases, obtaining reliable epidemiological data is difficult and requires innovative approaches.Aim: To determine the prevalence and incidence of LAM using data from patient organizations in seven countries, and to use the extent to which the prevalence of LAM varies regionally and nationally to determine whether prevalence estimates are related to health-care provision.Methods: Numbers of women with LAM were obtained from patient groups and national databases from seven countries (n = 1001). Prevalence was calculated for regions within countries using female population figures from census data. Incidence estimates were calculated for the USA, UK and Switzerland. Regional variation in prevalence and changes in incidence over time were analysed using Poisson regression and linear regression.Results: Prevalence of LAM in the seven countries ranged from 3.4 to 7.8/million women with significant variation, both between countries and between states in the USA. This variation did not relate to the number of pulmonary specialists in the region nor the percentage of population with health insurance, but suggests a large number of patients remain undiagnosed. The incidence of LAM from 2004 to 2008 ranged from 0.23 to 0.31/million women/per year in the USA, UK and Switzerland.Conclusions: Using this method, we have found that the prevalence of LAM is higher than that previously recorded and that many patients with LAM are undiagnosed.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Practical signal-to-noise ratio quantification for sensitivity encoding: Application to coronary MR angiography.

Purpose: To develop and evaluate a practical method for the quantification of signal-to-noise ratio (SNR) on coronary MR angiograms (MRA) acquired with parallel imaging.Materials and Methods: To quantify the spatially varying noise due to parallel imaging reconstruction, a new method has been implemented incorporating image data acquisition followed by a fast noise scan during which radio-frequency pulses, cardiac triggering and navigator gating are disabled. The performance of this method was evaluated in a phantom study where SNR measurements were compared with those of a reference standard (multiple repetitions). Subsequently, SNR of myocardium and posterior skeletal muscle was determined on in vivo human coronary MRA.Results: In a phantom, the SNR measured using the proposed method deviated less than 10.1% from the reference method for small geometry factors (<= 2). In vivo, the noise scan for a 10 min coronary MRA acquisition was acquired in 30 s. Higher signal and lower SNR, due to spatially varying noise, were found in myocardium compared with posterior skeletal muscle.Conclusion: SNR quantification based on a fast noise scan is a validated and easy-to-use method when applied to three-dimensional coronary MRA obtained with parallel imaging as long as the geometry factor remains low.