Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

The value of selected in vitro and in silico methods to predict acute oral toxicity in a regulatory context: results from the European Project ACuteTox.

ACuteTox is a project within the 6th European Framework Programme which had as one of its goals to develop, optimise and prevalidate a non-animal testing strategy for predicting human acute oral toxicity. In its last 6 months, a challenging exercise was conducted to assess the predictive capacity of the developed testing strategies and final identification of the most promising ones. Thirty-two chemicals were tested blind in the battery of in vitro and in silico methods selected during the first phase of the project. This paper describes the classification approaches studied: single step procedures and two step tiered testing strategies. In summary, four in vitro testing strategies were proposed as best performing in terms of predictive capacity with respect to the European acute oral toxicity classification. In addition, a heuristic testing strategy is suggested that combines the prediction results gained from the neutral red uptake assay performed in 3T3 cells, with information on neurotoxicity alerts identified by the primary rat brain aggregates test method. Octanol-water partition coefficients and in silico prediction of intestinal absorption and blood-brain barrier passage are also considered. This approach allows to reduce the number of chemicals wrongly predicted as not classified (LD50>2000 mg/kg b.w.).

Direct Determination of mechanical properties in shallow formations by (ultra) sonic methods

For several decades mechanical properties of shallow formations (soil) obtained by sonic to ultrasonic wave testing were reported to be greater than those based on mechanical tests. The present article relying on a statistical analysis of more than 300 tests shows that elastic moduli of the soil can indeed be obtained from (ultra)sonic tests and that they are identical to those resulting from mechanical tests.

Prognostic ability of practitioners of traditional arabic medicine: comparison with Western methods through a relative patient progress scale.

The ancient Greek medical theory based on balance or imbalance of humors disappeared in the western world, but does survive elsewhere. Is this survival related to a certain degree of health care efficiency? We explored this hypothesis through a study of classical Greco-Arab medicine in Mauritania. Modern general practitioners evaluated the safety and effectiveness of classical Arabic medicine in a Mauritanian traditional clinic, with a prognosis/follow-up method allowing the following comparisons: (i) actual patient progress (clinical outcome) compared with what the traditional 'tabib' had anticipated (= prognostic ability) and (ii) patient progress compared with what could be hoped for if the patient were treated by a modern physician in the same neighborhood. The practice appeared fairly safe and, on average, clinical outcome was similar to what could be expected with modern medicine. In some cases, patient progress was better than expected. The ability to correctly predict an individual's clinical outcome did not seem to be better along modern or Greco-Arab theories. Weekly joint meetings (modern and traditional practitioners) were spontaneously organized with a modern health centre in the neighborhood. Practitioners of a different medical system can predict patient progress. For the patient, avoiding false expectations with health care and ensuring appropriate referral may be the most important. Prognosis and outcome studies such as the one presented here may help to develop institutions where patients find support in making their choices, not only among several treatment options, but also among several medical systems.

Study of gene flow through a hybrid zone in the common shrew (Sorex araneus) using microsatellites

The common shrew (Sorer araneus) is subdivided into several chromosomal races. As hybrid zones between them have been characterized, this organism is of particular interest in studying the role of chromosomes in speciation. Six microsatellite loci were used to evaluate the level of gene how in the S. araneus hybrid zone between the Cordon and Valais races. Most of these loci were very polymorphic, the total number of alleles detected per locus ranging from 3 to 20. Using Mantel tests, we showed that the effect of rivers as barriers to gene flow is less important at this sampling scale. The effect of the chromosomal race is of particular importantance in diminishing gene flow.

Mechanisms of reproductive isolation between an ant species of hybrid origin and one of its parents.

The establishment of new species by hybridization is difficult because it requires the development of reproductive isolation (RI) in sympatry to escape the homogenizing effects of gene flow from the parental species. Here we investigated the role of two pre- and two postzygotic mechanisms of RI in a system comprising two interdependent Pogonomyrmex harvester ant lineages (the H1 and H2 lineages) of hybrid origin and one of their parental species (P. rugosus). Similar to most other ants, P. rugosus is characterized by an environmental system of caste determination with female brood developing either into queens or workers depending on nongenetic factors. By contrast, there is a strong genetic component to caste determination in the H1 and H2 lineages because the developmental fate of female brood depends on the genetic origin of the parents, with interlineage eggs developing into workers and intralineage eggs developing into queens. The study of a mixed mating aggregation revealed strong differences in mating flight timing between P. rugosus and the two lineages as a first mechanism of RI. A second important prezygotic mechanism was assortative mating. Laboratory experiments also provided support for one of the two investigated mechanisms of postzygotic isolation. The majority of offspring produced from the few matings between P. rugosus and the lineages aborted at the egg stage. This hybrid inviability was under maternal influence, with hybrids produced by P. rugosus queens being always inviable whereas a small proportion of H2 lineage queens produced large numbers of adult hybrid offspring. Finally, we found no evidence that genetic caste determination acted as a second postzygotic mechanism reducing gene flow between P. rugosus and the H lineages. The few viable P. rugosus-H hybrids were not preferentially shunted into functionally sterile workers but developed into both workers and queens. Overall, these results reveal that the nearly complete (99.5%) RI between P. rugosus and the two hybrid lineages stems from the combination of two typical prezygotic mechanisms (mating time divergence and assortative mating) and one postzygotic mechanism (hybrid inviability).

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Imaging molasse and quaternary sediments in Lake Geneva, Switzerland, with 3-D high-resolution seismic reflection methods: A case study

A high-resolution three-dimensional (3-D) seismic reflection survey was conducted in Lake Geneva, near the city of Lausanne, Switzerland, as part of a project for developing such seismic techniques. Using a single 48-channel streamer, the 3-D site with an area of 1200 m x 600 m was surveyed in 10 days. A variety of complex geologic structures (e.g. thrusts, folds, channel-fill) up to similar to150 m below the water bottom were obtained with a 15 in.(3) water gun. The 3-D data allowed the construction of an accurate velocity model and the distinction of five major seismic facies within the Lower Freshwater Molasse (Aquitanian) and the Quaternary sedimentary units. Additionally, the Plateau Molasse (PM) and Subalpine Molasse (SM) erosional surface, "La Paudeze" thrust fault (PM-SM boundary) and the thickness of Quaternary sediments were accurately delineated in 3-D.

Hybrid Multiscale Finite Volume method for two-phase flow in porous media

We present a novel hybrid (or multiphysics) algorithm, which couples pore-scale and Darcy descriptions of two-phase flow in porous media. The flow at the pore-scale is described by the Navier?Stokes equations, and the Volume of Fluid (VOF) method is used to model the evolution of the fluid?fluid interface. An extension of the Multiscale Finite Volume (MsFV) method is employed to construct the Darcy-scale problem. First, a set of local interpolators for pressure and velocity is constructed by solving the Navier?Stokes equations; then, a coarse mass-conservation problem is constructed by averaging the pore-scale velocity over the cells of a coarse grid, which act as control volumes; finally, a conservative pore-scale velocity field is reconstructed and used to advect the fluid?fluid interface. The method relies on the localization assumptions used to compute the interpolators (which are quite straightforward extensions of the standard MsFV) and on the postulate that the coarse-scale fluxes are proportional to the coarse-pressure differences. By numerical simulations of two-phase problems, we demonstrate that these assumptions provide hybrid solutions that are in good agreement with reference pore-scale solutions and are able to model the transition from stable to unstable flow regimes. Our hybrid method can naturally take advantage of several adaptive strategies and allows considering pore-scale fluxes only in some regions, while Darcy fluxes are used in the rest of the domain. Moreover, since the method relies on the assumption that the relationship between coarse-scale fluxes and pressure differences is local, it can be used as a numerical tool to investigate the limits of validity of Darcy's law and to understand the link between pore-scale quantities and their corresponding Darcy-scale variables.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.