Network-based scoring system for genome-scale metabolic reconstructions

Background: Network reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood. Results: Here, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results. Conclusions: We foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

Nanometer-scale oxidation of Si(100) surfaces by tapping mode atomic force microscopy

The nanometer¿scale oxidation of Si(100) surfaces in air is performed with an atomic force microscope working in tapping mode. Applying a positive voltage to the sample with respect to the tip, two kinds of modifications are induced on the sample: grown silicon oxide mounds less than 5 nm high and mounds higher than 10 nm (which are assumed to be gold depositions). The threshold voltage necessary to produce the modification is studied as a function of the average tip¿to¿sample distance.

Assessment of debris-flow susceptibility at medium-scale in the Barcelonnette Basin, France

Debris flows are among the most dangerous processes in mountainous areas due to their rapid rate of movement and long runout zone. Sudden and rather unexpected impacts produce not only damages to buildings and infrastructure but also threaten human lives. Medium- to regional-scale susceptibility analyses allow the identification of the most endangered areas and suggest where further detailed studies have to be carried out. Since data availability for larger regions is mostly the key limiting factor, empirical models with low data requirements are suitable for first overviews. In this study a susceptibility analysis was carried out for the Barcelonnette Basin, situated in the southern French Alps. By means of a methodology based on empirical rules for source identification and the empirical angle of reach concept for the 2-D runout computation, a worst-case scenario was first modelled. In a second step, scenarios for high, medium and low frequency events were developed. A comparison with the footprints of a few mapped events indicates reasonable results but suggests a high dependency on the quality of the digital elevation model. This fact emphasises the need for a careful interpretation of the results while remaining conscious of the inherent assumptions of the model used and quality of the input data.

Debris flow modeling for susceptibility mapping at regional to national scale in Norway

Debris flows and related landslide processes occur in many regions all over Norway and pose a significant hazard to inhabited areas. Within the framework of the development of a national debris flows susceptibility map, we are working on a modeling approach suitable for Norway with a nationwide coverage. The discrimination of source areas is based on an index approach, which includes topographic parameters and hydrological settings. For the runout modeling, we use the Flow-R model (IGAR, University of Lausanne), which is based on combined probabilistic and energetic algorithms for the assessment of the spreading of the flow and maximum runout distances. First results for different test areas have shown that runout distances can be modeled reliably. For the selection of source areas, however, additional factors have to be considered, such as the lithological and quaternary geological setting, in order to accommodate the strong variation in debris flow activity in the different geological, geomorphological and climate regions of Norway.

Comparing the horizontal and vertical individualism and collectivism scale and the Auckland individualism and collectivism scale in two cultures: Switzerland and South Africa

This study investigated the psychometric properties of the Horizontal and Vertical Individualism and Collectivism Scale (HVIC) and the Auckland Individualism and Collectivism Scale (AICS). The sample consisted of 1,403 working individuals from Switzerland (N = 585) and from South Africa (N = 818). Principal component factor analyses indicated that a two-factor structure replicated well across the two countries for both scales. In addition, the HVIC four-factor structure replicated well across countries, whereas the responsibility dimension of individualism of the AICS replicated poorly. Confirmatory factor analyses provided satisfactory support to the original theoretical models for both the HVIC and the AICS. Equivalence measurement indices indicated that the cross-cultural replicability properties of both instruments are generally acceptable. However, canonical correlations and correlations between the HVIC and AICS dimensions confirm that these two instruments differ in their underlying meaning of the individualism and collectivism constructs, suggesting that these two instruments assess individualism and collectivism differently.

The Beck Cognitive Insight Scale in outpatients with psychotic disorders: further evidence from a French-speaking sample.

OBJECTIVE: The Beck Cognitive Insight Scale (BCIS) evaluates patients' self-report of their ability to detect and correct misinterpretation. Our study aims to confirm the factor structure and the convergent validity of the original scale in a French-speaking environment. METHOD: Outpatients (n = 158) suffering from schizophrenia or schizoaffective disorders fulfilled the BCIS. The 51 patients in Montpellier were equally assessed with the Positive and Negative Syndrome Scale (PANSS) by a psychiatrist who was blind of the BCIS scores. RESULTS: The fit indices of the confirmatory factor analysis validated the 2-factor solution reported by the developers of the scale with inpatients, and in another study with middle-aged and older outpatients. The BCIS composite index was significantly negatively correlated with the clinical insight item of the PANSS. CONCLUSIONS: The French translation of the BCIS appears to have acceptable psychometric properties and gives additional support to the scale, as well as cross-cultural validity for its use with outpatients suffering from schizophrenia or schizoaffective disorders. The correlation between clinical and composite index of cognitive insight underlines the multidimensional nature of clinical insight. Cognitive insight does not recover clinical insight but is a potential target for developing psychological treatments that will improve clinical insight.

Can we disentangle predator-prey interactions from species distributions at a macro-scale? A case study with a raptor species.

There is a debate on whether an influence of biotic interactions on species distributions can be reflected at macro-scale levels. Whereas the influence of biotic interactions on spatial arrangements is beginning to be studied at local scales, similar studies at macro-scale levels are scarce. There is no example disentangling, from other similarities with related species, the influence of predator-prey interactions on species distributions at macro-scale levels. In this study we aimed to disentangle predator-prey interactions from species distribution data following an experimental approach including a factorial design. As a case of study we selected the short-toed eagle because of its known specialization on certain prey reptiles. We used presence-absence data at a 100 Km2 spatial resolution to extract the explanatory capacity of different environmental predictors (five abiotic and two biotic predictors) on the short-toed eagle species distribution in Peninsular Spain. Abiotic predictors were relevant climatic and topographic variables, and relevant biotic predictors were prey richness and forest density. In addition to the short-toed eagle, we also obtained the predictor's explanatory capacities for i) species of the same family Accipitridae (as a reference), ii) for other birds of different families (as controls) and iii) species with randomly selected presences (as null models). We run 650 models to test for similarities of the short-toed eagle, controls and null models with reference species, assessed by regressions of explanatory capacities. We found higher similarities between the short-toed eagle and other species of the family Accipitridae than for the other two groups. Once corrected by the family effect, our analyses revealed a signal of predator-prey interaction embedded in species distribution data. This result was corroborated with additional analyses testing for differences in the concordance between the distributions of different bird categories and the distributions of either prey or non-prey species of the short-toed eagle. Our analyses were useful to disentangle a signal of predator-prey interactions from species distribution data at a macro-scale. This study highlights the importance of disentangling specific features from the variation shared with a given taxonomic level.

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides.

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Scale-specific sex-biased dispersal in the Valais shrew unveiled by genetic variation on the Y chromosome, autosomes, and mitochondrial DNA.

We investigated sex specificities in the evolutionary processes shaping Y chromosome, autosomes, and mitochondrial DNA patterns of genetic structure in the Valais shrew (Sorex antinorii), a mountain dwelling species with a hierarchical distribution. Both hierarchical analyses of variance and isolation-by-distance analyses revealed patterns of population structure that were not consistent across maternal, paternal, and biparentally inherited markers. Differentiation on a Y microsatellite was lower than expected from the comparison with autosomal microsatellites and mtDNA, and it was mostly due to genetic variance among populations within valleys, whereas the opposite was observed on other markers. In addition, there was no pattern of isolation by distance for the Y, whereas there was strong isolation by distance on mtDNA and autosomes. We use a hierarchical island model of coancestry dynamics to discuss the relative roles of the microevolutionary forces that may induce such patterns. We conclude that sex-biased dispersal is the most important driver of the observed genetic structure, but with an intriguing twist: it seems that dispersal is strongly male biased at large spatial scale, whereas it is mildly biased in favor of females at local scale. These results add to recent reports of scale-specific sex-biased dispersal patterns, and emphasize the usefulness of the Y chromosome in conjunction with mtDNA and autosomes to infer sex specificities.