Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

Objective Sleep Structure and Cardiovascular Risk Factors in the General Population: The HypnoLaus Study.

STUDY OBJECTIVES: To evaluate the association between objective sleep measures and metabolic syndrome (MS), hypertension, diabetes, and obesity. DESIGN: Cross-sectional study. SETTING: General population sample. PARTICIPANTS: There were 2,162 patients (51.2% women, mean age 58.4 ± 11.1). INTERVENTIONS: Patients were evaluated for hypertension, diabetes, overweight/obesity, and MS, and underwent a full polysomnography (PSG). MEASUREMENTS AND RESULTS: PSG measured variables included: total sleep time (TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index (ArI). In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, and sleep efficiency, and increased ArI. After adjustment for age, sex, smoking, alcohol, physical activity, drugs that affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in patients without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes, and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. CONCLUSIONS: In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes, and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders.

Rational design of 4-aryl-1,2,3-triazoles for indoleamine 2,3-dioxygenase 1 inhibition.

Indoleamine 2,3-dioxygenase 1 (IDO1) is an important therapeutic target for the treatment of diseases such as cancer that involve pathological immune escape. Starting from the scaffold of our previously discovered IDO1 inhibitor 4-phenyl-1,2,3-triazole, we used computational structure-based methods to design more potent ligands. This approach yielded highly efficient low molecular weight inhibitors, the most active being of nanomolar potency both in an enzymatic and in a cellular assay, while showing no cellular toxicity and a high selectivity for IDO1 over tryptophan 2,3-dioxygenase (TDO). A quantitative structure-activity relationship based on the electrostatic ligand-protein interactions in the docked binding modes and on the quantum chemically derived charges of the triazole ring demonstrated a good explanatory power for the observed activities.

The four- vs. alternative six-factor structure of the French WISC-IV: Comparison using confirmatory factor analyses

Exploratory and confirmatory factor analyses reported in the French technical manual of the WISC-IV provides evidence supporting a structure with four indices: Verbal Comprehension (VCI), Perceptual Reasoning (PRI), Working Memory (WMI), and Processing Speed (PSI). Although the WISC-IV is more attuned to contemporary theory, it is still not in total accordance with the dominant theory: the Cattell-Horn-Carroll (CHC) theory of cognitive ability. This study was designed to determine whether the French WISC-IV is better described with the four-factor solution or whether an alternative model based on the CHC theory is more appropriate. The intercorrelations matrix reported in the French technical manual was submitted to confirmatory factor analysis. A comparison of competing models suggests that a model based on the CHC theory fits the data better than the current WISC-IV structure. It appears that the French WISC-IV in fact measures six factors: crystallized intelligence (Gc), fluid intelligence (Gf), short-term memory (Gsm), processing speed (Gs), quantitative knowledge (Gq), and visual processing (Gv). We recommend that clinicians interpret the subtests of the French WISC-IV in relation to this CHC model in addition to the four indices.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Social structure emerges via the interaction between local ecology and individual behaviour.

1. The formation of groups is a fundamental aspect of social organization, but there are still many questions regarding how social structure emerges from individuals making non-random associations. 2. Although food distribution and individual phenotypic traits are known to separately influence social organization, this is the first study, to our knowledge, experimentally linking them to demonstrate the importance of their interaction in the emergence of social structure. 3. Using an experimental design in which food distribution was either clumped or dispersed, in combination with individuals that varied in exploratory behaviour, our results show that social structure can be induced in the otherwise non-social European shore crab (Carcinus maenas). 4. Regardless of food distribution, individuals with relatively high exploratory behaviour played an important role in connecting otherwise poorly connected individuals. In comparison, low exploratory individuals aggregated into cohesive, stable subgroups (moving together even when not foraging), but only in tanks where resources were clumped. No such non-foraging subgroups formed in environments where food was evenly dispersed. 5. Body size did not accurately explain an individual's role within the network for either type of food distribution. 6. Because of their synchronized movements and potential to gain social information, groups of low exploratory crabs were more effective than singletons at finding food. 7. Because social structure affects selection, and social structure is shown to be sensitive to the interaction between ecological and behavioural differences among individuals, local selective pressures are likely to reflect this interaction.

Independent relations of left ventricular structure with the 24-h urinary excretion of sodium and aldosterone

Objective: Previous studies reported on the association of left ventricular mass index (LVMI) with urinary sodium or with circulating or urinary aldosterone.We investigated the independent associations of LVMI with the urinary excretion of both sodium and aldosterone. Design and method: We randomly recruited 317 untreated subjects from a White population (45.1%women; mean age 48.2 years).Measurements included echocardiographic left ventricular (LV) properties, the 24 h urinary excretion of sodium and aldosterone, plasma renin activity (PRA), and proximal (RNaprox) and distal (RNadist) renal sodium reabsorption, assessed fromthe endogenous lithium clearance. Inmultivariable-adjusted models,we expressed changes in LVMI per 1 SD increase in the explanatory variables, while accounting for sex, age, systolic blood pressure and the waist-to-hip ratio. Results: LVMI increased independentlywith the urinary excretion of both sodium (+2.48 g/m2; P=0.005) and aldosterone (+2.63 g/m2; P=0.004). Higher sodium excretion was associated with increased mean wall thickness (MWT: +0.126 mm, P=0.054), but with no change in LV end-diastolic diameter (LVID: +0.12mm, P=0.64). In contrast, higher aldosterone excretion was associated with higher LVID (+0.54 mm; P=0.017), but with no change in MWT (+0.070mm; P=0.28).Higher RNadistwas associatedwith lower relativewall thickness (−0.81×10−2, P=0.017), because of opposite trends in LVID(+0.33 mm; P=0.13) and MWT (−0.130mm; P=0.040). LVMI was not associated with PRA or RNaprox. Conclusions: LVMI independently increased with both urinary sodium and aldosterone excretion. IncreasedMWT explained the association of LVMI with urinary sodium and increased LVID the association of LVMI with urinary aldosterone.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

The design and characterization of receptor-selective APRIL variants.

A proliferation-inducing ligand (APRIL), a member of the TNF ligand superfamily with an important role in humoral immunity, is also implicated in several cancers as a prosurvival factor. APRIL binds two different TNF receptors, B cell maturation antigen (BCMA) and transmembrane activator and cylclophilin ligand interactor (TACI), and also interacts independently with heparan sulfate proteoglycans. Because APRIL shares binding of the TNF receptors with B cell activation factor, separating the precise signaling pathways activated by either ligand in a given context has proven quite difficult. In this study, we have used the protein design algorithm FoldX to successfully generate a BCMA-specific variant of APRIL, APRIL-R206E, and two TACI-selective variants, D132F and D132Y. These APRIL variants show selective activity toward their receptors in several in vitro assays. Moreover, we have used these ligands to show that BCMA and TACI have a distinct role in APRIL-induced B cell stimulation. We conclude that these ligands are useful tools for studying APRIL biology in the context of individual receptor activation.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Different transcriptional control of metabolism and extracellular matrix in visceral and subcutaneous fat of obese and rimonabant treated mice.

BACKGROUND: The visceral (VAT) and subcutaneous (SCAT) adipose tissues play different roles in physiology and obesity. The molecular mechanisms underlying their expansion in obesity and following body weight reduction are poorly defined. METHODOLOGY: C57Bl/6 mice fed a high fat diet (HFD) for 6 months developed low, medium, or high body weight as compared to normal chow fed mice. Mice from each groups were then treated with the cannabinoid receptor 1 antagonist rimonabant or vehicle for 24 days to normalize their body weight. Transcriptomic data for visceral and subcutaneous adipose tissues from each group of mice were obtained and analyzed to identify: i) genes regulated by HFD irrespective of body weight, ii) genes whose expression correlated with body weight, iii) the biological processes activated in each tissue using gene set enrichment analysis (GSEA), iv) the transcriptional programs affected by rimonabant. PRINCIPAL FINDINGS: In VAT, "metabolic" genes encoding enzymes for lipid and steroid biosynthesis and glucose catabolism were down-regulated irrespective of body weight whereas "structure" genes controlling cell architecture and tissue remodeling had expression levels correlated with body weight. In SCAT, the identified "metabolic" and "structure" genes were mostly different from those identified in VAT and were regulated irrespective of body weight. GSEA indicated active adipogenesis in both tissues but a more prominent involvement of tissue stroma in VAT than in SCAT. Rimonabant treatment normalized most gene expression but further reduced oxidative phosphorylation gene expression in SCAT but not in VAT. CONCLUSION: VAT and SCAT show strikingly different gene expression programs in response to high fat diet and rimonabant treatment. Our results may lead to identification of therapeutic targets acting on specific fat depots to control obesity.

Qualitative structure-metabolism relationships in the hydrolysis of carbamates.

The aims of this review were 1) to compile a large number of reliable literature data on the metabolic hydrolysis of medicinal carbamates and 2) to extract from such data a qualitative relation between molecular structure and lability to metabolic hydrolysis. The compounds were classified according to the nature of their substituents (R³OCONR&supl;R²), and a metabolic lability score was calculated for each class. A trend emerged, such that the metabolic lability of carbamates decreased (i.e., their metabolic stability increased), in the following series: Aryl-OCO-NHAlkyl >> Alkyl-OCO-NHAlkyl ~ Alkyl-OCO-N(Alkyl)? ? Alkyl-OCO-N(endocyclic) ? Aryl-OCO-N(Alkyl)? ~ Aryl-OCO-N(endocyclic) ? Alkyl-OCO-NHAryl ~ Alkyl-OCO-NHAcyl?>> Alkyl-OCO-NH? > Cyclic carbamates. This trend should prove useful in the design of carbamates as drugs or prodrugs.

The use of external mesh reinforcement to reduce intimal hyperplasia and preserve the structure of human saphenous veins.

The saphenous vein is the conduit of choice in bypass graft procedures. Haemodynamic factors play a major role in the development of intimal hyperplasia (IH), and subsequent bypass failure. To evaluate the potential protective effect of external reinforcement on such a failure, we developed an ex vivo model for the perfusion of segments of human saphenous veins under arterial shear stress. In veins submitted to pulsatile high pressure (mean pressure at 100 mmHg) for 3 or 7 days, the use of an external macroporous polyester mesh 1) prevented the dilatation of the vessel, 2) decreased the development of IH, 3) reduced the apoptosis of smooth muscle cells, and the subsequent fibrosis of the media layer, 4) prevented the remodelling of extracellular matrix through the up-regulation of matrix metalloproteinases (MMP-2, MMP-9) and plasminogen activator type I. The data show that, in an experimental ex vivo setting, an external scaffold decreases IH and maintains the integrity of veins exposed to arterial pressure, via increase in shear stress and decrease wall tension, that likely contribute to trigger selective molecular and cellular changes.

Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells.

Gene transfer in eukaryotic cells and organisms suffers from epigenetic effects that result in low or unstable transgene expression and high clonal variability. Use of epigenetic regulators such as matrix attachment regions (MARs) is a promising approach to alleviate such unwanted effects. Dissection of a known MAR allowed the identification of sequence motifs that mediate elevated transgene expression. Bioinformatics analysis implied that these motifs adopt a curved DNA structure that positions nucleosomes and binds specific transcription factors. From these observations, we computed putative MARs from the human genome. Cloning of several predicted MARs indicated that they are much more potent than the previously known element, boosting the expression of recombinant proteins from cultured cells as well as mediating high and sustained expression in mice. Thus we computationally identified potent epigenetic regulators, opening new strategies toward high and stable transgene expression for research, therapeutic production or gene-based therapies.