Proteomics fingerprinting of phagosome maturation and evidence for the role of a Galpha during uptake.

Phagocytosis, whether of food particles in protozoa or bacteria and cell remnants in the metazoan immune system, is a conserved process. The particles are taken up into phagosomes, which then undergo complex remodeling of their components, called maturation. By using two-dimensional gel electrophoresis and mass spectrometry combined with genomic data, we identified 179 phagosomal proteins in the amoeba Dictyostelium, including components of signal transduction, membrane traffic, and the cytoskeleton. By carrying out this proteomics analysis over the course of maturation, we obtained time profiles for 1,388 spots and thus generated a dynamic record of phagosomal protein composition. Clustering of the time profiles revealed five clusters and 24 functional groups that were mapped onto a flow chart of maturation. Two heterotrimeric G protein subunits, Galpha4 and Gbeta, appeared at the earliest times. We showed that mutations in the genes encoding these two proteins produce a phagocytic uptake defect in Dictyostelium. This analysis of phagosome protein dynamics provides a reference point for future genetic and functional investigations.

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.

The effects of sevoflurane and halothane anesthesia on cerebral blood flow velocity in children.

We compared cerebral blood flow velocity during anesthesia with sevoflurane and halothane in 23 children admitted for elective surgery (age, 0.4-9.7 yr; median age, 1.9 yr; ASA physical status I-II). Inhaled induction was performed in a randomized sequence with sevoflurane or halothane. Under steady-state conditions, cerebral blood flow velocity (systolic [V(s)], mean [V(mn)], and diastolic [VD]) were measured by a blinded investigator using transcranial pulsed Doppler ultrasonography. The anesthetic was then changed. CBFV measurements were repeated after washout of the first anesthetic and after steady-state of the second (equivalent minimal alveolar concentration to first anesthetic). The resistance index was calculated. VD and V(mn) were significantly lower during sevoflurane (V(mn) 1.35 m/s) than during halothane (V(mn) 1.50 m/s; P = 0.001), whereas V(s) was unchanged. The resistance index was lower during halothane (P < 0.001). Our results indicate lower vessel resistance and higher mean velocity during halothane than during sevoflurane. IMPLICATIONS: The mean cerebral blood flow velocity is significantly decreased in children during inhaled anesthesia with sevoflurane than during halothane. This might be relevant for the choice of anesthetic in children with risk of increased intracranial pressure, neurosurgery, or craniofacial osteotomies.

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).

Oligo-Miocene extensional tectonics and fluid flow across the Northern Snake Range detachment system, Nevada

The Northern Snake Range (Nevada) represents a spectacular example of a metamorphic core complex and exposes a complete section from the mylonitic footwall into the hanging wall of a fossil detachment system. Paired geochronological and stable isotopic data of mylonitic quartzite within the detachment footwall reveal that ductile deformation and infiltration of meteoric fluids occurred between 27 and 23 Ma. Ar-40/Ar-39 ages display complex recrystallization-cooling relationships but decrease systematically from 26.9 +/- 0.2 Ma at the top to 21.3 +/- 0.2 Ma at the bottom of footwall mylonite. Hydrogen isotope (delta D) values in white mica are very low (-150 to -145 %) within the top 80-90 m of detachment footwall, in contrast to values obtained from the deeper part of the section where values range from -77 to -64 %, suggesting that time-integrated interaction between rock and meteoric fluid was restricted to the uppermost part of the mylonitic footwall. Pervasive mica-water hydrogen isotope exchange is difficult to reconcile with models of Ar-40 loss during mylonitization solely by volume diffusion. Rather, we interpret the Ar-40/Ar-39 ages of white mica with low-delta D values to date syn-mylonitic hydrogen and argon isotope exchange, and we conclude that the hydrothermal system of the Northern Snake Range was active during late Oligocene (27-23 Ma) and has been exhumed by the combined effects of ductile strain, extensional detachment faulting, and erosion.

Dependence of brain intravoxel incoherent motion perfusion parameters on the cardiac cycle.

Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D* = D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.

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.

Heterogeneity of human monocytes: an optimized four-color flow cytometry protocol for analysis of monocyte subsets.

Monocytes are central mediators in the development of atherosclerotic plaques. They circulate in blood and eventually migrate into tissue including the vessel wall where they give rise to macrophages and dendritic cells. The existence of monocyte subsets with distinct roles in homeostasis and inflammation suggests specialization of function. These subsets are identified based on expression of the CD14 and CD16 markers. Routinely applicable protocols remain elusive, however. Here, we present an optimized four-color flow cytometry protocol for analysis of human blood monocyte subsets using a specific PE-Cy5-conjugated monoclonal antibody (mAb) to HLA-DR, a PE-Cy7-conjugated mAb to CD14, a FITC-conjugated mAb to CD16, and PE-conjugated mAbs to additional markers relevant to monocyte function. Classical CD14(+)CD16(-) monocytes (here termed "Mo1" subset) expressed high CCR2, CD36, CD64, and CD62L, but low CX(3)CR1, whereas "nonclassical" CD14(lo)CD16(+) monocytes (Mo3) essentially showed the inverse expression pattern. CD14(+)CD16(+) monocytes (Mo2) expressed high HLA-DR, CD36, and CD64. In patients with stable coronary artery disease (n = 13), classical monocytes were decreased, whereas "nonclassical" monocytes were increased 90% compared with healthy subjects with angiographically normal coronary arteries (n = 14). Classical monocytes from CAD patients expressed higher CX(3)CR1 and CCR2 than controls. Thus, stable CAD is associated with expansion of the nonclassical monocyte subset and increased expression of inflammatory markers on monocytes. Flow cytometric analysis of monocyte subsets and marker expression may provide valuable information on vascular inflammation. This may translate into the identification of monocyte subsets as selective therapeutic targets, thus avoiding adverse events associated with indiscriminate monocyte inhibition.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Error estimate and control in the MSFV method for multiphase flow in porous media

n this paper the iterative MSFV method is extended to include the sequential implicit simulation of time dependent problems involving the solution of a system of pressure-saturation equations. To control numerical errors in simulation results, an error estimate, based on the residual of the MSFV approximate pressure field, is introduced. In the initial time steps in simulation iterations are employed until a specified accuracy in pressure is achieved. This initial solution is then used to improve the localization assumption at later time steps. Additional iterations in pressure solution are employed only when the pressure residual becomes larger than a specified threshold value. Efficiency of the strategy and the error control criteria are numerically investigated. This paper also shows that it is possible to derive an a-priori estimate and control based on the allowed pressure-equation residual to guarantee the desired accuracy in saturation calculation.

Increased flow of fatty acids toward beta-oxidation in developing seeds of Arabidopsis deficient in diacylglycerol acyltransferase activity or synthesizing medium-chain-length fatty acids.

Synthesis of polyhydroxyalkanoates (PHAs) from intermediates of fatty acid beta-oxidation was used as a tool to study fatty acid degradation in developing seeds of Arabidopsis. Transgenic plants expressing a peroxisomal PHA synthase under the control of a napin promoter accumulated PHA in developing seeds to a final level of 0. 06 mg g(-1) dry weight. In plants co-expressing a plastidial acyl-acyl carrier protein thioesterase from Cuphea lanceolata and a peroxisomal PHA synthase, approximately 18-fold more PHA accumulated in developing seeds. The proportion of 3-hydroxydecanoic acid monomer in the PHA was strongly increased, indicating a large flow of capric acid toward beta-oxidation. Furthermore, expression of the peroxisomal PHA synthase in an Arabidopsis mutant deficient in the enzyme diacylglycerol acyltransferase resulted in a 10-fold increase in PHA accumulation in developing seeds. These data indicate that plants can respond to the inadequate incorporation of fatty acids into triacylglycerides by recycling the fatty acids via beta-oxidation and that a considerable flow toward beta-oxidation can occur even in a plant tissue primarily devoted to the accumulation of storage lipids.

Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

Oligoclonal expansions in the CD8(+)CD28(-) T cells largely explain the shorter telomeres detected in this subset: analysis by flow FISH.

We have previously reported that CD8(+)CD28(-) T cells have relatively shorter telomeres compared with CD8(+)CD28(+) T cells. Oligoclonal expansion is a common feature of CD8(+) T cells in human peripheral blood, and these expansions predominantly occur in the CD57(+)/CD28(-) population. We studied the telomere length in subsets of CD8(+) T cells using quantitative fluorescence in situ hybridization and flow cytometry (flow FISH). Our results confirm that CD8(+)CD28(-) T cells have shorter telomeres as compared with their CD28(+) counterpart cells. In addition, the oligoclonally expanded cells within the CD8(+)CD28(-) T cell subset generally have even shorter telomeres than the CD28(-) subset as a whole. We conclude that the presence of clonal expansions in the CD8(+)CD28(-) T cell population largely explain the shorter telomeres in this subset. These clonally expanded CD8(+)CD28(-) T cells generally have characteristics of terminally differentiated effector cells. Nevertheless, there is considerable individual variation in the degree of telomere shortening in these cells, which may reflect host genetic factors as well as the type and timing of the antigenic exposure.