Comment on recent modeling studies of astrocyte-neuron metabolic interactions.

Recent years have seen a surge in mathematical modeling of the various aspects of neuron-astrocyte interactions, and the field of brain energy metabolism is no exception in that regard. Despite the advent of biophysical models in the field, the long-lasting debate on the role of lactate in brain energy metabolism is still unresolved. Quite the contrary, it has been ported to the world of differential equations. Here, we summarize the present state of this discussion from the modeler's point of view and bring some crucial points to the attention of the non-mathematically proficient reader.

Eliciting consumers preferences using stated preference discrete choice models: Contingent ranking versus choice experiment

The aim of this paper is twofold: firstly, to carry out a theoreticalreview of the most recent stated preference techniques used foreliciting consumers preferences and, secondly, to compare the empiricalresults of two dierent stated preference discrete choice approaches.They dier in the measurement scale for the dependent variable and,therefore, in the estimation method, despite both using a multinomiallogit. One of the approaches uses a complete ranking of full-profiles(contingent ranking), that is, individuals must rank a set ofalternatives from the most to the least preferred, and the other usesa first-choice rule in which individuals must select the most preferredoption from a choice set (choice experiment). From the results werealize how important the measurement scale for the dependent variablebecomes and, to what extent, procedure invariance is satisfied.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Predicting species distribution: offering more than simple habitat models

n the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

Recent decrease in the prevalence of congenital heart defects in europe.

OBJECTIVES: To examine trends in the prevalence of congenital heart defects (CHDs) in Europe and to compare these trends with the recent decrease in the prevalence of CHDs in Canada (Quebec) that was attributed to the policy of mandatory folic acid fortification. STUDY DESIGN: We used data for the period 1990-2007 for 47 508 cases of CHD not associated with a chromosomal anomaly from 29 population-based European Surveillance of Congenital Anomalies registries in 16 countries covering 7.3 million births. We estimated trends for all CHDs combined and separately for 3 severity groups using random-effects Poisson regression models with splines. RESULTS: We found that the total prevalence of CHDs increased during the 1990s and the early 2000s until 2004 and decreased thereafter. We found essentially no trend in total prevalence of the most severe group (group I), whereas the prevalence of severity group II increased until about 2000 and decreased thereafter. Trends for severity group III (the most prevalent group) paralleled those for all CHDs combined. CONCLUSIONS: The prevalence of CHDs decreased in recent years in Europe in the absence of a policy for mandatory folic acid fortification. One possible explanation for this decrease may be an as-yet-undocumented increase in folic acid intake of women in Europe following recommendations for folic acid supplementation and/or voluntary fortification. However, alternative hypotheses, including reductions in risk factors of CHDs (eg, maternal smoking) and improved management of maternal chronic health conditions (eg, diabetes), must also be considered for explaining the observed decrease in the prevalence of CHDs in Europe or elsewhere.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Lipid metabolism in myelinating glial cells: lessons from human inherited disorders and mouse models.

The integrity of central and peripheral nervous system myelin is affected in numerous lipid metabolism disorders. This vulnerability was so far mostly attributed to the extraordinarily high level of lipid synthesis that is required for the formation of myelin, and to the relative autonomy in lipid synthesis of myelinating glial cells because of blood barriers shielding the nervous system from circulating lipids. Recent insights from analysis of inherited lipid disorders, especially those with prevailing lipid depletion and from mouse models with glia-specific disruption of lipid metabolism, shed new light on this issue. The particular lipid composition of myelin, the transport of lipid-associated myelin proteins, and the necessity for timely assembly of the myelin sheath all contribute to the observed vulnerability of myelin to perturbed lipid metabolism. Furthermore, the uptake of external lipids may also play a role in the formation of myelin membranes. In addition to an improved understanding of basic myelin biology, these data provide a foundation for future therapeutic interventions aiming at preserving glial cell integrity in metabolic disorders.

Crystal structure of yeast peroxisomal multifunctional enzyme: structural basis for substrate specificity of (3R)-hydroxyacyl-CoA dehydrogenase units.

(3R)-hydroxyacyl-CoA dehydrogenase is part of multifunctional enzyme type 2 (MFE-2) of peroxisomal fatty acid beta-oxidation. The MFE-2 protein from yeasts contains in the same polypeptide chain two dehydrogenases (A and B), which possess difference in substrate specificity. The crystal structure of Candida tropicalis (3R)-hydroxyacyl-CoA dehydrogenase AB heterodimer, consisting of dehydrogenase A and B, determined at the resolution of 2.2A, shows overall similarity with the prototypic counterpart from rat, but also important differences that explain the substrate specificity differences observed. Docking studies suggest that dehydrogenase A binds the hydrophobic fatty acyl chain of a medium-chain-length ((3R)-OH-C10) substrate as bent into the binding pocket, whereas the short-chain substrates are dislocated by two mechanisms: (i) a short-chain-length 3-hydroxyacyl group ((3R)-OH-C4) does not reach the hydrophobic contacts needed for anchoring the substrate into the active site; and (ii) Leu44 in the loop above the NAD(+) cofactor attracts short-chain-length substrates away from the active site. Dehydrogenase B, which can use a (3R)-OH-C4 substrate, has a more shallow binding pocket and the substrate is correctly placed for catalysis. Based on the current structure, and together with the structure of the 2-enoyl-CoA hydratase 2 unit of yeast MFE-2 it becomes obvious that in yeast and mammalian MFE-2s, despite basically identical functional domains, the assembly of these domains into a mature, dimeric multifunctional enzyme is very different.

Native homing endonucleases can target conserved genes in humans and in animal models.

In recent years, both homing endonucleases (HEases) and zinc-finger nucleases (ZFNs) have been engineered and selected for the targeting of desired human loci for gene therapy. However, enzyme engineering is lengthy and expensive and the off-target effect of the manufactured endonucleases is difficult to predict. Moreover, enzymes selected to cleave a human DNA locus may not cleave the homologous locus in the genome of animal models because of sequence divergence, thus hampering attempts to assess the in vivo efficacy and safety of any engineered enzyme prior to its application in human trials. Here, we show that naturally occurring HEases can be found, that cleave desirable human targets. Some of these enzymes are also shown to cleave the homologous sequence in the genome of animal models. In addition, the distribution of off-target effects may be more predictable for native HEases. Based on our experimental observations, we present the HomeBase algorithm, database and web server that allow a high-throughput computational search and assignment of HEases for the targeting of specific loci in the human and other genomes. We validate experimentally the predicted target specificity of candidate fungal, bacterial and archaeal HEases using cell free, yeast and archaeal assays.

Structural changes in latosols of the cerrado region: II - soil compressive behavior and modeling of additional compaction

Currently in Brazil, as in other parts of the world, the concern is great with the increase of degraded agricultural soil, which is mostly related to the occurrence of soil compaction. Although soil texture is recognized as a very important component in the soil compressive behaviors, there are few studies that quantify its influence on the structural changes of Latosols in the Brazilian Cerrado region. This study aimed to evaluate structural changes and the compressive behavior of Latosols in Rio Verde, Goiás, through the modeling of additional soil compaction. The study was carried out using five Latosols with very different textures, under different soil compaction levels. Water retention and soil compression curves, and bearing capacity models were determined from undisturbed samples collected on the B horizons. Results indicated that clayey and very clayey Latosols were more susceptible to compression than medium-textured soils. Soil compression curves at density values associate with edaphic functions were used to determine the beneficial pressure (σ b) , i.e., pressure with optimal water retention, and critical pressure (σcrMAC), i.e., pressure with macroporosity below critical levels. These pressure values were higher than the preconsolidation pressure (σp), and therefore characterized as additional compaction. Based on the compressive behavior of these Latosols, it can be concluded that the combined preconsolidation pressure, beneficial pressure and critical pressure allow a better understanding of compression processes of Latosols.

Three essays in financial economics: asset pricing, optimal portfolio selection and financial integration

Executive Summary The unifying theme of this thesis is the pursuit of a satisfactory ways to quantify the riskureward trade-off in financial economics. First in the context of a general asset pricing model, then across models and finally across country borders. The guiding principle in that pursuit was to seek innovative solutions by combining ideas from different fields in economics and broad scientific research. For example, in the first part of this thesis we sought a fruitful application of strong existence results in utility theory to topics in asset pricing. In the second part we implement an idea from the field of fuzzy set theory to the optimal portfolio selection problem, while the third part of this thesis is to the best of our knowledge, the first empirical application of some general results in asset pricing in incomplete markets to the important topic of measurement of financial integration. While the first two parts of this thesis effectively combine well-known ways to quantify the risk-reward trade-offs the third one can be viewed as an empirical verification of the usefulness of the so-called "good deal bounds" theory in designing risk-sensitive pricing bounds. Chapter 1 develops a discrete-time asset pricing model, based on a novel ordinally equivalent representation of recursive utility. To the best of our knowledge, we are the first to use a member of a novel class of recursive utility generators to construct a representative agent model to address some long-lasting issues in asset pricing. Applying strong representation results allows us to show that the model features countercyclical risk premia, for both consumption and financial risk, together with low and procyclical risk free rate. As the recursive utility used nests as a special case the well-known time-state separable utility, all results nest the corresponding ones from the standard model and thus shed light on its well-known shortcomings. The empirical investigation to support these theoretical results, however, showed that as long as one resorts to econometric methods based on approximating conditional moments with unconditional ones, it is not possible to distinguish the model we propose from the standard one. Chapter 2 is a join work with Sergei Sontchik. There we provide theoretical and empirical motivation for aggregation of performance measures. The main idea is that as it makes sense to apply several performance measures ex-post, it also makes sense to base optimal portfolio selection on ex-ante maximization of as many possible performance measures as desired. We thus offer a concrete algorithm for optimal portfolio selection via ex-ante optimization over different horizons of several risk-return trade-offs simultaneously. An empirical application of that algorithm, using seven popular performance measures, suggests that realized returns feature better distributional characteristics relative to those of realized returns from portfolio strategies optimal with respect to single performance measures. When comparing the distributions of realized returns we used two partial risk-reward orderings first and second order stochastic dominance. We first used the Kolmogorov Smirnov test to determine if the two distributions are indeed different, which combined with a visual inspection allowed us to demonstrate that the way we propose to aggregate performance measures leads to portfolio realized returns that first order stochastically dominate the ones that result from optimization only with respect to, for example, Treynor ratio and Jensen's alpha. We checked for second order stochastic dominance via point wise comparison of the so-called absolute Lorenz curve, or the sequence of expected shortfalls for a range of quantiles. As soon as the plot of the absolute Lorenz curve for the aggregated performance measures was above the one corresponding to each individual measure, we were tempted to conclude that the algorithm we propose leads to portfolio returns distribution that second order stochastically dominates virtually all performance measures considered. Chapter 3 proposes a measure of financial integration, based on recent advances in asset pricing in incomplete markets. Given a base market (a set of traded assets) and an index of another market, we propose to measure financial integration through time by the size of the spread between the pricing bounds of the market index, relative to the base market. The bigger the spread around country index A, viewed from market B, the less integrated markets A and B are. We investigate the presence of structural breaks in the size of the spread for EMU member country indices before and after the introduction of the Euro. We find evidence that both the level and the volatility of our financial integration measure increased after the introduction of the Euro. That counterintuitive result suggests the presence of an inherent weakness in the attempt to measure financial integration independently of economic fundamentals. Nevertheless, the results about the bounds on the risk free rate appear plausible from the view point of existing economic theory about the impact of integration on interest rates.

Structural sustainability of cambisol under different land use system

Incongruous management techniques have been associated with some significant loss of agricultural land to degradation in many parts of the world. Land degradation results in the alteration of physical, chemical and biological properties of the soil, thereby posing a serious threat to sustainable agricultural development. In this study, our objective is to evaluate the changes in a Cambisol structure under six land use systems using the load bearing capacity model. Sampling was conducted in Amazonas Region, Brazil, in the following land use: a) young secondary forest; b) old secondary forest; c) forest; d) pasture; e) cropping, and f) agroforestry. To obtain the load bearing capacity models the undisturbed soil samples were collected in those land use systems and subjected to the uniaxial compression test. These models were used to evaluate which land use system preserved or degraded the Cambisol structure. The results of the bulk density and total porosity of the soil samples were not adequate to quantify structural degradation in Cambisol. Using the forest topsoil level (0-0.03 m) as a reference, it was observed that pasture land use system was most severe in the degradation of the soil structure while the structure were most preserved under old secondary forest, cropping system and forest. At the subsoil level (0.10-0.13 m depth), the soil structure was most degraded in the cropping land use system while it was most preserved in young secondary forest and pasture. At the 0.20-0.23 m depth, soil structure degradation was most severe in the old secondary forest system and well preserved in young secondary forest, cropping and agroforestry.

Models that include supercoiling of topological domains reproduce several known features of interphase chromosomes.

Understanding the structure of interphase chromosomes is essential to elucidate regulatory mechanisms of gene expression. During recent years, high-throughput DNA sequencing expanded the power of chromosome conformation capture (3C) methods that provide information about reciprocal spatial proximity of chromosomal loci. Since 2012, it is known that entire chromatin in interphase chromosomes is organized into regions with strongly increased frequency of internal contacts. These regions, with the average size of ∼1 Mb, were named topological domains. More recent studies demonstrated presence of unconstrained supercoiling in interphase chromosomes. Using Brownian dynamics simulations, we show here that by including supercoiling into models of topological domains one can reproduce and thus provide possible explanations of several experimentally observed characteristics of interphase chromosomes, such as their complex contact maps.

Structural changes and degradation of Red Latosols under different management systems for 20 years

Soils are the foundation of terrestrial ecosystems and their role in food production is fundamental, although physical degradation has been observed in recent years, caused by different cultural practices that modify structures and consequently the functioning of soils. The objective of this study was to evaluate possible structural changes and degradation in an Oxisol under different managements for 20 years: no-tillage cultivation with and without crop rotation, perennial crop and conventional tillage, plus a forested area (reference). Initially, the crop profile was described and subsequently, 10 samples per management system and forest soil were collected to quantify soil organic matter, flocculation degree, bulk density, and macroporosity. The results indicated structural changes down to a soil depth of 50 cm, with predominance of structural units ∆μ (intermediate compaction level) under perennial crop and no-tillage crop rotation, and of structural units ∆ (compacted) under conventional tillage and no-tillage. The soil was increasingly degraded in the increasing order: forest => no-tillage crop rotation => perennial crop => no-tillage without crop rotation => conventional tillage. In all managements, the values of organic matter and macroporosity were always below and bulk density always above those of the reference area (forest) and, under no-tillage crop rotation and perennial crop, the flocculation degree was proportionally equal to that of the reference area.

DEA does not like positive discrimination : a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of data envelopment analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run themselves their own efficiency analysis. Within DEA, several alternative models allow for an environment adjustment. Five alternative models, each of them easily accessible to and achievable by practitioners and decision makers, are performed using the empirical case of the 90 primary schools of the State of Geneva, Switzerland. As the State of Geneva practices an upstream positive discrimination policy towards schools, this empirical case is particularly appropriate for an environment adjustment. The alternative of the majority of DEA models deliver divergent results. It is a matter of concern for applied researchers and a matter of confusion for practitioners and decision makers. From a political standpoint, these diverging results could lead to potentially opposite decisions. Grâce à l'existence de logiciels en libre accès et de guides pédagogiques, la méthode data envelopment analysis (DEA) s'est démocratisée ces dernières années. Aujourd'hui, il n'est pas rare que les décideurs avec peu ou pas de connaissances en recherche opérationnelle réalisent eux-mêmes leur propre analyse d'efficience. A l'intérieur de la méthode DEA, plusieurs modèles permettent de tenir compte des conditions plus ou moins favorables de l'environnement. Cinq de ces modèles, facilement accessibles et applicables par les décideurs, sont utilisés pour mesurer l'efficience des 90 écoles primaires du canton de Genève, Suisse. Le canton de Genève pratiquant une politique de discrimination positive envers les écoles défavorisées, ce cas pratique est particulièrement adapté pour un ajustement à l'environnement. La majorité des modèles DEA génèrent des résultats divergents. Ce constat est préoccupant pour les chercheurs appliqués et perturbant pour les décideurs. D'un point de vue politique, ces résultats divergents conduisent à des prises de décision différentes selon le modèle sur lequel elles sont fondées.