Study of the combined radial post-feeding dispersion of the blowflies Chrysomya megacephala (Fabricius) and C. albiceps (Wiedemann) (Diptera, Calliphoridae)

Blowflies use discrete and ephemeral substrates to feed their larvae. After they run out of food, the larvae begin to disperse in order to find adequate places for pupation or additional food sources, a process named post-feeding larval dispersion. Some important aspects of this process were studied in a circular arena allowing the combined radial post-feeding dispersion from the center of the arena of C. albiceps and C. megacephala larvae. To determine the location of each pupa, the arena was divided in 72 identical sections starting from the center. The distance from the center, the depth and weight of each pupa were evaluated. Statistical tests were done to verify the relation between weight, depth and distance for pupation. From the total an average of 976 larvae released (488 for each species) were collected considering both experiments 456 C. megacephala pupae and 488 of C. albiceps. This demonstrates that C. albiceps probably preyed on 32 C. megacephala larvae during post-feeding dispersion. The study of this dispersion process can be used to estimate the postmortem interval (PMI) of human cadavers in legal medicine.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Groundwater Availability Modeling: Lower Dakota Aquifer, 2008

This monthly report from the Iowa Department of Natural Resources is about the water quality management of Iowa's rivers, streams and lakes.

Molecular modeling study of the binding and signaling properties of the TCRpMHC complex

The activation of the specific immune response against tumor cells is based on the recognition by the CD8+ Cytotoxic Τ Lymphocytes (CTL), of antigenic peptides (p) presented at the surface of the cell by the class I major histocompatibility complex (MHC). The ability of the so-called T-Cell Receptors (TCR) to discriminate between self and non-self peptides constitutes the most important specific control mechanism against infected cells. The TCR/pMHC interaction has been the subject of much attention in cancer therapy since the design of the adoptive transfer approach, in which Τ lymphocytes presenting an interesting response against tumor cells are extracted from the patient, expanded in vitro, and reinfused after immunodepletion, possibly leading to cancer regression. In the last decade, major progress has been achieved by the introduction of engineered lypmhocytes. In the meantime, the understanding of the molecular aspects of the TCRpMHC interaction has become essential to guide in vitro and in vivo studies. In 1996, the determination of the first structure of a TCRpMHC complex by X-ray crystallography revealed the molecular basis of the interaction. Since then, molecular modeling techniques have taken advantage of crystal structures to study the conformational space of the complex, and understand the specificity of the recognition of the pMHC by the TCR. In the meantime, experimental techniques used to determine the sequences of TCR that bind to a pMHC complex have been used intensively, leading to the collection of large repertoires of TCR sequences that are specific for a given pMHC. There is a growing need for computational approaches capable of predicting the molecular interactions that occur upon TCR/pMHC binding without relying on the time consuming resolution of a crystal structure. This work presents new approaches to analyze the molecular principles that govern the recognition of the pMHC by the TCR and the subsequent activation of the T-cell. We first introduce TCRep 3D, a new method to model and study the structural properties of TCR repertoires, based on homology and ab initio modeling. We discuss the methodology in details, and demonstrate that it outperforms state of the art modeling methods in predicting relevant TCR conformations. Two successful applications of TCRep 3D that supported experimental studies on TCR repertoires are presented. Second, we present a rigid body study of TCRpMHC complexes that gives a fair insight on the TCR approach towards pMHC. We show that the binding mode of the TCR is correctly described by long-distance interactions. Finally, the last section is dedicated to a detailed analysis of an experimental hydrogen exchange study, which suggests that some regions of the constant domain of the TCR are subject to conformational changes upon binding to the pMHC. We propose a hypothesis of the structural signaling of TCR molecules leading to the activation of the T-cell. It is based on the analysis of correlated motions in the TCRpMHC structure. - L'activation de la réponse immunitaire spécifique dirigée contre les cellules tumorales est basée sur la reconnaissance par les Lymphocytes Τ Cytotoxiques (CTL), d'un peptide antigénique (p) présenté à la suface de la cellule par le complexe majeur d'histocompatibilité de classe I (MHC). La capacité des récepteurs des lymphocytes (TCR) à distinguer les peptides endogènes des peptides étrangers constitue le mécanisme de contrôle le plus important dirigé contre les cellules infectées. L'interaction entre le TCR et le pMHC est le sujet de beaucoup d'attention dans la thérapie du cancer, depuis la conception de la méthode de transfer adoptif: les lymphocytes capables d'une réponse importante contre les cellules tumorales sont extraits du patient, amplifiés in vitro, et réintroduits après immunosuppression. Il peut en résulter une régression du cancer. Ces dix dernières années, d'importants progrès ont été réalisés grâce à l'introduction de lymphocytes modifiés par génie génétique. En parallèle, la compréhension du TCRpMHC au niveau moléculaire est donc devenue essentielle pour soutenir les études in vitro et in vivo. En 1996, l'obtention de la première structure du complexe TCRpMHC à l'aide de la cristallographie par rayons X a révélé les bases moléculaires de l'interaction. Depuis lors, les techniques de modélisation moléculaire ont exploité les structures expérimentales pour comprendre la spécificité de la reconnaissance du pMHC par le TCR. Dans le même temps, de nouvelles techniques expérimentales permettant de déterminer la séquence de TCR spécifiques envers un pMHC donné, ont été largement exploitées. Ainsi, d'importants répertoires de TCR sont devenus disponibles, et il est plus que jamais nécessaire de développer des approches informatiques capables de prédire les interactions moléculaires qui ont lieu lors de la liaison du TCR au pMHC, et ce sans dépendre systématiquement de la résolution d'une structure cristalline. Ce mémoire présente une nouvelle approche pour analyser les principes moléculaires régissant la reconnaissance du pMHC par le TCR, et l'activation du lymphocyte qui en résulte. Dans un premier temps, nous présentons TCRep 3D, une nouvelle méthode basée sur les modélisations par homologie et ab initio, pour l'étude de propriétés structurales des répertoires de TCR. Le procédé est discuté en détails et comparé à des approches standard. Nous démontrons ainsi que TCRep 3D est le plus performant pour prédire des conformations pertinentes du TCR. Deux applications à des études expérimentales des répertoires TCR sont ensuite présentées. Dans la seconde partie de ce travail nous présentons une étude de complexes TCRpMHC qui donne un aperçu intéressant du mécanisme d'approche du pMHC par le TCR. Finalement, la dernière section se concentre sur l'analyse détaillée d'une étude expérimentale basée sur les échanges deuterium/hydrogène, dont les résultats révèlent que certaines régions clés du domaine constant du TCR sont sujettes à un changement conformationnel lors de la liaison au pMHC. Nous proposons une hypothèse pour la signalisation structurelle des TCR, menant à l'activation du lymphocyte. Celle-ci est basée sur l'analyse des mouvements corrélés observés dans la structure du TCRpMHC.

On the relevance of modeling volatility for pricing purposes

This paper presents a two-factor (Vasicek-CIR) model of the term structure of interest rates and develops its pricing and empirical properties. We assume that default free discount bond prices are determined by the time to maturity and two factors, the long-term interest rate and the spread. Assuming a certain process for both factors, a general bond pricing equation is derived and a closed-form expression for bond prices is obtained. Empirical evidence of the model's performance in comparisson with a double Vasicek model is presented. The main conclusion is that the modeling of the volatility in the long-term rate process can help (in a large amount) to fit the observed data can improve - in a reasonable quantity - the prediction of the future movements in the medium- and long-term interest rates. However, for shorter maturities, it is shown that the pricing errors are, basically, negligible and it is not so clear which is the best model to be used.

Pitfalls in the modeling of forward-looking price setting and investment decisions

The present paper makes progress in explaining the role of capital for inflation and output dynamics. We followWoodford (2003, Ch. 5) in assuming Calvo pricing combined with a convex capital adjustment cost at the firm level. Our main result is that capital accumulation affects inflation dynamics primarily through its impact on the marginal cost. This mechanism is much simpler than the one implied by the analysis in Woodford's text. The reason is that his analysis suffers from a conceptual mistake, as we show. The latter obscures the economic mechanism through which capital affects inflation and output dynamics in the Calvo model, as discussed in Woodford (2004).

Flexible multivariate GARCH modeling with an application to international stock markets

The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

Macroeconomic modeling for monetary policy evaluation

We describe some of the main features of the recent vintage macroeconomic models used for monetary policy evaluation. We point to some of the key differences with respect to the earlier generation ofmacro models, and highlight the insights for policy that these new frameworks have to offer. Our discussion emphasizes two key aspects of the new models: the significant role of expectations of future policy actions in the monetary transmission mechanism, and the importance for the central bank of tracking of the flexible price equilibrium values of the natural levels of output and the real interest rate. We argue that both features have important implications for the conduct of monetary policy.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Dispersion of natural arsenic in the Malcantone watershed, Southern Switzerland: field evidence for repeated sorption-desorption and oxidation-reduction processes

In recent years, elevated arsenic concentrations have been found in waters and soils of many, countries, often resulting in a health threat for the local population. Switzerland is not an exception and this paper deals with the release and subsequent fate of arsenic in a 200-km(2) mountainous watershed, characterized by crystalline silicate rocks (gneisses, schists, amphibolites) that contain abundant As-bearing sulfide ore deposits, some of which have been mined for iron and gold in the past. Using analytical methods common for mineralogical, ground water and soil studies (XRD, XRF, XAS-XANES and -EXAFS, electron microprobe, extraction, ICP, AAS with hydride generator, ion chromatography), seven different field situations and related dispersion processes of natural arsenic have been studied: (1) release by rock weathering, (2) transport and deposition by water and ice; (3) release of As to the ground and surface water due to increasing pH; (4) accumulation in humic soil horizons; (5) remobilization by reduction in water-saturated soils and stagnant ground waters; (6) remobilization by using P-rich fertilizers or dung and (7) oxidation, precipitation and dilution in surface waters. Comparison of the results with experimental adsorption studies and speciation diagrams from the literature allows us to reconstruct and identify the typical behavior of arsenic in a natural environment under temperate climatic conditions. The main parameters identified are: (a) once liberated from the primary minerals, sorption processes on Fe-oxy-hydroxides dominate over Al-phases, such as Al-hydroxides or clay minerals and limit the As concentrations in the spring and well waters between 20 and 300 mug/l. (b) Precipitation as secondary minerals is limited to the weathering domain, where the As concentrations are still high and not yet too diluted by rain and soils waters. (c) Although neutral and alkaline pH conditions clearly increase the mobility of As, the main factor to mobilize As is a low redox potential (Eh close or below 0 mV), which favors the dissolution of the Fe-oxy-hydroxides on which the As is sorbed. (d) X-ray absorption spectroscopy (XAS) of As in water-logged humic forest soils indicates that the reduction to As III only occurs at the solid-water interface and that the solid contains As as As V (e) A and Bh horizons of humic cambisols can effectively capture As when As-rich waters flow through them. Complex spatial and temporal variation of the various parameters in a watershed results in repeated mobilization and immobilization of As, which continuously transports As from the upper to the lower part of a watershed and ultimately to the ocean. (C) 2004 Elsevier B.V. All rights reserved.

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.

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.