Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Endothelial cells as key determinants of the tumor microenvironment: interaction with tumor cells, extracellular matrix and immune killer cells.

Besides tumor cells, the tumor microenvironment harbors a variety of host-derived cells, such as endothelial cells, fibroblasts, innate and adaptive immune cells. It is a complex and highly dynamic environment, providing very important cues to tumor development and progression. Tumor-associated endothelial cells play a key role in this process. On the one hand, they form tumor-associated (angiogenic) vessels through sprouting from locally preexisting vessels or recruitment of bone marrow-derived endothelial progenitor cells, to provide nutritional support to the growing tumor. On the other hand, they are the interface between circulating blood cells, tumor cells and the extracellular matrix, thereby playing a central role in controlling leukocyte recruitment, tumor cell behavior and metastasis formation. Hypoxia is a critical parameter modulating the tumor microenvironment and endothelial/tumor cell interactions. Under hypoxic stress, tumor cells produce factors that promote tumor angiogenesis, tumor cell motility and metastasis. Among these factors, VEGF, a main angiogenesis modulator, can also play a critical role in the control of immune tolerance. This review discusses some aspects of the role of endothelial cells within tumor microenvironment and emphasizes their interaction with tumor cells, the extracellular matrix and with immune killer cells. We will also address the role played by circulating endothelial progenitor cells and illustrate their features and mechanism of recruitment to the tumor microenvironment and their role in tumor angiogenesis.

HIV-1 vaccines and adaptive trial designs.

Developing a vaccine against the human immunodeficiency virus (HIV) poses an exceptional challenge. There are no documented cases of immune-mediated clearance of HIV from an infected individual, and no known correlates of immune protection. Although nonhuman primate models of lentivirus infection have provided valuable data about HIV pathogenesis, such models do not predict HIV vaccine efficacy in humans. The combined lack of a predictive animal model and undefined biomarkers of immune protection against HIV necessitate that vaccines to this pathogen be tested directly in clinical trials. Adaptive clinical trial designs can accelerate vaccine development by rapidly screening out poor vaccines while extending the evaluation of efficacious ones, improving the characterization of promising vaccine candidates and the identification of correlates of immune protection.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Evidence for adaptive radiation from a phylogenetic study of plant defenses.

One signature of adaptive radiation is a high level of trait change early during the diversification process and a plateau toward the end of the radiation. Although the study of the tempo of evolution has historically been the domain of paleontologists, recently developed phylogenetic tools allow for the rigorous examination of trait evolution in a tremendous diversity of organisms. Enemy-driven adaptive radiation was a key prediction of Ehrlich and Raven's coevolutionary hypothesis [Ehrlich PR, Raven PH (1964) Evolution 18:586-608], yet has remained largely untested. Here we examine patterns of trait evolution in 51 North American milkweed species (Asclepias), using maximum likelihood methods. We study 7 traits of the milkweeds, ranging from seed size and foliar physiological traits to defense traits (cardenolides, latex, and trichomes) previously shown to impact herbivores, including the monarch butterfly. We compare the fit of simple random-walk models of trait evolution to models that incorporate stabilizing selection (Ornstein-Ulenbeck process), as well as time-varying rates of trait evolution. Early bursts of trait evolution were implicated for 2 traits, while stabilizing selection was implicated for several others. We further modeled the relationship between trait change and species diversification while allowing rates of trait evolution to vary during the radiation. Species-rich lineages underwent a proportionately greater decline in latex and cardenolides relative to species-poor lineages, and the rate of trait change was most rapid early in the radiation. An interpretation of this result is that reduced investment in defensive traits accelerated diversification, and disproportionately so, early in the adaptive radiation of milkweeds.

C4 Photosynthesis evolved in grasses via parallel adaptive genetic changes.

Phenotypic convergence is a widespread and well-recognized evolutionary phenomenon. However, the responsible molecular mechanisms remain often unknown mainly because the genes involved are not identified. A well-known example of physiological convergence is the C4 photosynthetic pathway, which evolved independently more than 45 times [1]. Here, we address the question of the molecular bases of the C4 convergent phenotypes in grasses (Poaceae) by reconstructing the evolutionary history of genes encoding a C4 key enzyme, the phosphoenolpyruvate carboxylase (PEPC). PEPC genes belong to a multigene family encoding distinct isoforms of which only one is involved in C4 photosynthesis [2]. By using phylogenetic analyses, we showed that grass C4 PEPCs appeared at least eight times independently from the same non-C4 PEPC. Twenty-one amino acids evolved under positive selection and converged to similar or identical amino acids in most of the grass C4 PEPC lineages. This is the first record of such a high level of molecular convergent evolution, illustrating the repeatability of evolution. These amino acids were responsible for a strong phylogenetic bias grouping all C4 PEPCs together. The C4-specific amino acids detected must be essential for C4 PEPC enzymatic characteristics, and their identification opens new avenues for the engineering of the C4 pathway in crops.

Probing functional groups at the gas-aerosol interface using heterogeneous titration reactions: a tool for predicting aerosol health effects?

The complex chemical and physical nature of combustion and secondary organic aerosols (SOAs) in general precludes the complete characterization of both bulk and interfacial components. The bulk composition reveals the history of the growth process and therefore the source region, whereas the interface controls--to a large extent--the interaction with gases, biological membranes, and solid supports. We summarize the development of a soft interrogation technique, using heterogeneous chemistry, for the interfacial functional groups of selected probe gases [N(CH(3))(3), NH(2)OH, CF(3)COOH, HCl, O(3), NO(2)] of different reactivity. The technique reveals the identity and density of surface functional groups. Examples include acidic and basic sites, olefinic and polycyclic aromatic hydrocarbon (PAH) sites, and partially and completely oxidized surface sites. We report on the surface composition and oxidation states of laboratory-generated aerosols and of aerosols sampled in several bus depots. In the latter case, the biomarker 8-hydroxy-2'-deoxyguanosine, signaling oxidative stress caused by aerosol exposure, was isolated. The increase in biomarker levels over a working day is correlated with the surface density N(i)(O3) of olefinic and/or PAH sites obtained from O(3) uptakes as well as with the initial uptake coefficient, γ(0), of five probe gases used in the field. This correlation with γ(0) suggests the idea of competing pathways occurring at the interface of the aerosol particles between the generation of reactive oxygen species (ROS) responsible for oxidative stress and cellular antioxidants.

Lésions buccales du reflux gastro-oesophagien de l'enfant: des réalités et quelques mythes [An interface between pediatrics and oral medicine: oral manifestations of gastroesophageal reflux in children]

Gastro-oesophageal reflux (GOR) is a common disorder in the pediatric population. In association with esophagitis, GOR may impair children's quality of life. Extra-oesophageal manifestations are of specific interest in oral medicine because the refluxate may reach impair both oral mucosa and hard dental tissues. Some oral symptoms are so specific that they should raise the attention for other GOR symptoms. Dental erosion is a potential risk in children with gastroesophageal reflux: the pediatrician should routinely refer children with gastroesophageal reflux to a pediatric dentist to diagnose erosions and if needed restore the teeth. Conversely, in the presence of unexplained dental erosions the dentist and/or the pediatrician should discuss the possibility of an occult GOR.

Adaptive changes in a radial maze task: Efficient selection of baited arms with reduced foraging in senescent hooded rats

Qualitative differences in strategy selection during foraging in a partially baited maze were assessed in young and old rats. The baited and non-baited arms were at a fixed position in space and marked by a specific olfactory cue. The senescent rats did more re-entries during the first four-trial block but were more rapid than the young rats in selecting the reinforced arms during the first visits. Dissociation between the olfactory spatial cue reference by rotating the maze revealed that only few old subjects relied on olfactory cues to select the baited arms and the remainder relied mainly on the visuo-spatial cues.

Can we translate vitamin D immunomodulating effect on innate and adaptive immunity to vaccine response?

Vitamin D (VitD), which is well known for its classic role in the maintenance of bone mineral density, has now become increasingly studied for its extra-skeletal roles. It has an important influence on the body's immune system and modulates both innate and adaptive immunity and regulates the inflammatory cascade. In this review our aim was to describe how VitD might influence immune responsiveness and its potential modulating role in vaccine immunogenicity. In the first instance, we consider the literature that may provide molecular and genetic support to the idea that VitD status may be related to innate and/or adaptive immune response with a particular focus on vaccine immunogenicity and then discuss observational studies and controlled trials of VitD supplementation conducted in humans. Finally, we conclude with some knowledge gaps surrounding VitD and vaccine response, and that it is still premature to recommend "booster" of VitD at vaccination time to enhance vaccine response.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.