Dynamic responses of O2 uptake at the onset and end of exercise in trained subjects.

Inconsistencies about dynamic asymmetry between the on- and off-transient responses in .VO2 are found in the literature. Therefore the purpose of this study was to examine .VO2on- and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (<VT) and heavy (>VT) intensities. .VO2 kinetics in exercise and recovery were better described by a single exponential model (<VT) or by a double exponential with two time delays (>VT). For moderate exercise, we found a symmetry of .VO2 kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (<VT and >VT). Our results do not support a dynamically linear system model of .VO2 during cycling exercise in the heavy-intensity domain.

Combined simulation and mutagenesis analyses reveal the involvement of key residues for peroxisome proliferator-activated receptor alpha helix 12 dynamic behavior.

The dynamic properties of helix 12 in the ligand binding domain of nuclear receptors are a major determinant of AF-2 domain activity. We investigated the molecular and structural basis of helix 12 mobility, as well as the involvement of individual residues with regard to peroxisome proliferator-activated receptor alpha (PPARalpha) constitutive and ligand-dependent transcriptional activity. Functional assays of the activity of PPARalpha helix 12 mutants were combined with free energy molecular dynamics simulations. The agreement between the results from these approaches allows us to make robust claims concerning the mechanisms that govern helix 12 functions. Our data support a model in which PPARalpha helix 12 transiently adopts a relatively stable active conformation even in the absence of a ligand. This conformation provides the interface for the recruitment of a coactivator and results in constitutive activity. The receptor agonists stabilize this conformation and increase PPARalpha transcription activation potential. Finally, we disclose important functions of residues in PPARalpha AF-2, which determine the positioning of helix 12 in the active conformation in the absence of a ligand. Substitution of these residues suppresses PPARalpha constitutive activity, without changing PPARalpha ligand-dependent activation potential.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Structural determinants for membrane association and dynamic organization of the hepatitis C virus NS3-4A complex.

Hepatitis C virus (HCV) NS3-4A is a membrane-associated multifunctional protein harboring serine protease and RNA helicase activities. It is an essential component of the HCV replication complex and a prime target for antiviral intervention. Here, we show that membrane association and structural organization of HCV NS3-4A are ensured in a cooperative manner by two membrane-binding determinants. We demonstrate that the N-terminal 21 amino acids of NS4A form a transmembrane alpha-helix that may be involved in intramembrane protein-protein interactions important for the assembly of a functional replication complex. In addition, we demonstrate that amphipathic helix alpha(0), formed by NS3 residues 12-23, serves as a second essential determinant for membrane association of NS3-4A, allowing proper positioning of the serine protease active site on the membrane. These results allowed us to propose a dynamic model for the membrane association, processing, and structural organization of NS3-4A on the membrane. This model has implications for the functional architecture of the HCV replication complex, proteolytic targeting of host factors, and drug design.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Change in defense mechanisms and coping over the course of short-term dynamic psychotherapy for adjustment disorder.

Short-term dynamic psychotherapy (STDP) has rarely been investigated with regard to its underlying mechanisms of change, even if psychoanalytic theory informs us about several potential putative mechanisms of change in patients. Change in overall defensive functioning is one. In this study, we explored the role of overall defensive functioning, by comparing it on the process level with the neighbouring concept of overall coping functioning. A total of N=32 patients, mainly presenting adjustment disorder, were included in the study. The patients underwent STDP up to 40 sessions; three sessions per psychotherapy were transcribed and analyzed by using two observer-rating scales: Defense Mechanism Rating Scales (Perry, 1990) and Coping Action Patterns (Perry, Drapeau, Dunkley, & Blake, 2005). Hierarchical linear modeling was applied to model the change over the course of therapy and relate it to outcome. Results suggest that STDP has an effect on the target variable of overall defensive functioning, which was absent for overall coping functioning. Links with outcome confirm the importance of the effect. These results are discussed from methodological and clinical viewpoints.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Repression and Protest Structural Models and Strategic Interactions

The recent wave of upheavals and revolts in Northern Africa and the Middle East goes back to an old question often raised by theories of collective action: does repression act as a negative or positive incentive for further mobilization? Through a review of the vast literature devoted to this question, this article aims to go beyond theoretical and methodological dead-ends. The article moves on to non-Western settings in order to better understand, via a macro-sociological and dynamic approach, the causal effects between mobilizations and repression. It pleads for a meso- and micro-level approach to this issue: an approach that puts analytical emphasis both on protest organizations and on individual activists' careers.

Alliance patterns over the course of short-term dynamic psychotherapy: The shape of productive relationships.

The shape of alliance processes over the course of psychotherapy has already been studied in several process-outcome studies on very brief psychotherapy. The present study applies the shape-of-change methodology to short-term dynamic psychotherapies and complements this method with hierarchical linear modeling. A total of 50 psychotherapies of up to 40 sessions were included. Alliance was measured at the end of each session. The results indicate that a linear progression model is most adequate. Three main patterns were found: stable, linear, and quadratic growth. The linear growth pattern, along with the slope parameter, was related to treatment outcome. This study sheds additional light on alliance process research, underscores the importance of linear alliance progression for outcome, and also fosters a better understanding of its limitations.

Three essays in dynamic corporate finance

Summary Throughout my thesis, I elaborate on how real and financing frictions affect corporate decision making under uncertainty, and I explore how firms time their investment and financing decisions given such frictions. While the macroeconomics literature has focused on the impact of real frictions on investment decisions assuming all equity financed firms, the financial economics literature has mainly focused on the study of financing frictions. My thesis therefore assesses the join interaction of real and financing frictions in firms' dynamic investment and financing decisions. My work provides a rationale for the documented poor empirical performance of neoclassical investment models based on the joint effect of real and financing frictions on investment. A major observation relies in how the infrequency of corporate decisions may affect standard empirical tests. My thesis suggests that the book to market sorts commonly used in the empirical asset pricing literature have economic content, as they control for the lumpiness in firms' optimal investment policies. My work also elaborates on the effects of asymmetric information and strategic interaction on firms' investment and financing decisions. I study how firms time their decision to raise public equity when outside investors lack information about their future investment prospects. I derive areal-options model that predicts either cold or hot markets for new stock issues conditional on adverse selection, and I provide a rational approach to study jointly the market timing of corporate decisions and announcement effects in stock returns. My doctoral dissertation therefore contributes to our understanding of how under real and financing frictions may bias standard empirical tests, elaborates on how adverse selection may induce hot and cold markets in new issues' markets, and suggests how the underlying economic behaviour of firms may induce alternative patterns in stock prices.

Testing demographic models of effective population size.

Due to practical difficulties in obtaining direct genetic estimates of effective sizes, conservation biologists have to rely on so-called 'demographic models' which combine life-history and mating-system parameters with F-statistics in order to produce indirect estimates of effective sizes. However, for the same practical reasons that prevent direct genetic estimates, the accuracy of demographic models is difficult to evaluate. Here we use individual-based, genetically explicit computer simulations in order to investigate the accuracy of two such demographic models aimed at investigating the hierarchical structure of populations. We show that, by and large, these models provide good estimates under a wide range of mating systems and dispersal patterns. However, one of the models should be avoided whenever the focal species' breeding system approaches monogamy with no sex bias in dispersal or when a substructure within social groups is suspected because effective sizes may then be strongly overestimated. The timing during the life cycle at which F-statistics are evaluated is also of crucial importance and attention should be paid to it when designing field sampling since different demographic models assume different timings. Our study shows that individual-based, genetically explicit models provide a promising way of evaluating the accuracy of demographic models of effective size and delineate their field of applicability.

Mating triggers dynamic immune regulations in wood ant queens.

Mating can affect female immunity in multiple ways. On the one hand, the immune system may be activated by pathogens transmitted during mating, sperm and seminal proteins, or wounds inflicted by males. On the other hand, immune defences may also be down-regulated to reallocate resources to reproduction. Ants are interesting models to study post-mating immune regulation because queens mate early in life, store sperm for many years, and use it until their death many years later, while males typically die after mating. This long-term commitment between queens and their mates limits the opportunity for sexual conflict but raises the new constraint of long-term sperm survival. In this study, we examine experimentally the effect of mating on immunity in wood ant queens. Specifically, we compared the phenoloxidase and antibacterial activities of mated and virgin Formica paralugubris queens. Queens had reduced levels of active phenoloxidase after mating, but elevated antibacterial activity 7 days after mating. These results indicate that the process of mating, dealation and ovary activation triggers dynamic patterns of immune regulation in ant queens that probably reflect functional responses to mating and pathogen exposure that are independent of sexual conflict.

Unfolding nature "in silico" : overcoming practical and metodological limitations of species distribution models

Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

Aqueous dynamic and histological findings after deep sclerectomy with collagen implant in an animal model.

AIM: The use of an animal model to study the aqueous dynamic and the histological findings after deep sclerectomy with (DSCI) and without collagen implant. METHODS: Deep sclerectomy was performed on rabbits' eyes. Eyes were randomly assigned to receive collagen implants. Measurements of intraocular pressure (IOP) and aqueous outflow facility using the constant pressure method through cannulation of the anterior chamber were performed. The system was filled with BSS and cationised ferritin. Histological assessment of the operative site was performed. Sections were stained with haematoxylin and eosin and with Prussian blue. Aqueous drainage vessels were identified by the reaction between ferritin and Prussian blue. All eyes were coded so that the investigator was blind to the type of surgery until the evaluation was completed. RESULTS: A significant decrease in IOP (p<0.05) was observed during the first 6 weeks after DSCI (mean IOP was 13.07 (2.95) mm Hg preoperatively and 9.08 (2.25) mm Hg at 6 weeks); DS without collagen implant revealed a significant decrease in IOP at weeks 4 and 8 after surgery (mean IOP 12.57 (3.52) mm Hg preoperatively, 9.45 (3.38) mm Hg at 4 weeks, and 9.22 (3.39) mm Hg at 8 weeks). Outflow facility was significantly increased throughout the 9 months of follow up in both DSCI and DS groups (p<0.05). The preoperative outflow facility (OF) was 0.15 (0.02) micro l/min/mm Hg. At 9 months, OF was 0.52 (0.28) microl/min/mm Hg and 0.46 (0.07) micro l/min/mm Hg for DSCI and DS respectively. Light microscopy studies showed the appearance of new aqueous drainage vessels in the sclera adjacent to the dissection site in DSCI and DS and the apparition of spindle cells lining the collagen implant in DSCI after 2 months. CONCLUSION: A significant IOP decrease was observed during the first weeks after DSCI and DS. DS with or without collagen implant provided a significant increase in outflow facility throughout the 9 months of follow up. This might be partly explained by new drainage vessels in the sclera surrounding the operated site. Microscopic studies revealed the appearance of spindle cells lining the collagen implant in DSCI after 2 months.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.