Copeptin Levels Remain Unchanged during the Menstrual Cycle.

BACKGROUND: Copeptin, a surrogate marker for arginin vasopressin production, is evaluated as an osmo-dependent stress and inflammatory biomarker in different diseases. We investigated copeptin during the menstrual cycle and its relationship to sex hormones, markers of subclinical inflammation and estimates of body fluid. METHODS: In 15 healthy women with regular menstrual cycles, blood was drawn on fifteen defined days of their menstrual cycle and was assayed for copeptin, progesterone, estradiol, luteinizing hormone, high-sensitive C-reactive protein, tumor necrosis factor-alpha and procalcitonin. Symptoms of fluid retention were assessed on each visit, and bio impedance analysis was measured thrice to estimate body fluid changes. Mixed linear model analysis was performed to assess the changes of copeptin across the menstrual cycle and the relationship of sex hormones, markers of subclinical inflammation and estimates of body fluid with copeptin. RESULTS: Copeptin levels did not significantly change during the menstrual cycle (p = 0.16). Throughout the menstrual cycle, changes in estradiol (p = 0.002) and in the physical premenstrual symptom score (p = 0.01) were positively related to copeptin, but changes in other sex hormones, in markers of subclinical inflammation or in bio impedance analysis-estimated body fluid were not (all p = ns). CONCLUSION: Although changes in estradiol and the physical premenstrual symptom score appear to be related to copeptin changes, copeptin does not significantly change during the menstrual cycle.

Orthogonal organic and aqueous-based washes of tissue sections to enhance protein sensitivity by MALDI imaging mass spectrometry.

Imaging mass spectrometry (IMS) is an emergent and innovative approach for measuring the composition, abundance and regioselectivity of molecules within an investigated area of fixed dimension. Although providing unprecedented molecular information compared with conventional MS techniques, enhancement of protein signature by IMS is still necessary and challenging. This paper demonstrates the combination of conventional organic washes with an optimized aqueous-based buffer for tissue section preparation before matrix-assisted laser desorption/ionization (MALDI) IMS of proteins. Based on a 500 mM ammonium formate in water-acetonitrile (9:1; v/v, 0.1% trifluororacetic acid, 0.1% Triton) solution, this buffer wash has shown to significantly enhance protein signature by profiling and IMS (~fourfold) when used after organic washes (70% EtOH followed by 90% EtOH), improving the quality and number of ion images obtained from mouse kidney and a 14-day mouse fetus whole-body tissue sections, while maintaining a similar reproducibility with conventional tissue rinsing. Even if some protein losses were observed, the data mining has demonstrated that it was primarily low abundant signals and that the number of new peaks found is greater with the described procedure. The proposed buffer has thus demonstrated to be of high efficiency for tissue section preparation providing novel and complementary information for direct on-tissue MALDI analysis compared with solely conventional organic rinsing.

Preclinical evaluation of implantable cardioverter-defibrillator developed for magnetic resonance imaging use.

BACKGROUND: Many patients with an implantable cardioverter-defibrillator (ICD) have indications for magnetic resonance imaging (MRI). However, MRI is generally contraindicated in ICD patients because of potential risks from hazardous interactions between the MRI and ICD system. OBJECTIVE: The purpose of this study was to use preclinical computer modeling, animal studies, and bench and scanner testing to demonstrate the safety of an ICD system developed for 1.5-T whole-body MRI. METHODS: MRI hazards were assessed and mitigated using multiple approaches: design decisions to increase safety and reliability, modeling and simulation to quantify clinical MRI exposure levels, animal studies to quantify the physiologic effects of MRI exposure, and bench testing to evaluate safety margin. RESULTS: Modeling estimated the incidence of a chronic change in pacing capture threshold >0.5V and 1.0V to be less than 1 in 160,000 and less than 1 in 1,000,000 cases, respectively. Modeling also estimated the incidence of unintended cardiac stimulation to occur in less than 1 in 1,000,000 cases. Animal studies demonstrated no delay in ventricular fibrillation detection and no reduction in ventricular fibrillation amplitude at clinical MRI exposure levels, even with multiple exposures. Bench and scanner testing demonstrated performance and safety against all other MRI-induced hazards. CONCLUSION: A preclinical strategy that includes comprehensive computer modeling, animal studies, and bench and scanner testing predicts that an ICD system developed for the magnetic resonance environment is safe and poses very low risks when exposed to 1.5-T normal operating mode whole-body MRI.

Prevalence of normal weight obesity in Switzerland: effect of various definitions

BACKGROUND: Normal weight obesity (NWO) is defined as an excessive body fat associated with a normal body mass index (BMI < 25 kg/m(2)), but its prevalence in the general population is unknown. AIM OF THE STUDY: To assess the prevalence of NWO in Switzerland according to different cut points used to define excess body fat. METHODS: Cross-sectional study including 3,213 women and 2,912 men aged 35-75 years. Body fat was assessed by bioelectrical impedance analysis and prevalence of NWO was assessed using four previously published definitions for excess body fat. RESULTS: Percent body fat increased with age: in men, the values (mean +/- SD) were 20.2 +/- 5.4, 23.0 +/- 5.4, 26.3 +/- 5.2 and 28.2 +/- 4.6 for age groups 35-44, 45-54, 55-64 and 65-75 years, respectively; the corresponding values for women were 29.9 +/- 7.8, 33.1 +/- 7.4, 36.7 +/- 7.5 and 39.6 +/- 6.9. In men, prevalence of NWO was <1% irrespective of the definition used. Conversely, in women, a 1- to 20-fold difference (from 1.4 to 27.8%) in NWO prevalence was found. The prevalence of NWO increased with age when age-independent cut points were used in women, but not in men. CONCLUSIONS: Prevalence of NWO is low in the general population and higher in women than in men. The prevalence is highly dependent on the criteria used to define excess body fat, namely in women. The use of gender- and age-specific cut points to define excess body fat is better than fixed or gender-specific only cut points.

Avian haemosporidian persistence and co-infection in great tits at the individual level.

BACKGROUND: Many studies have tracked the distribution and persistence of avian haemosporidian communities across space and time at the population level, but few studies have investigated these aspects of infection at the individual level over time. Important aspects of parasite infection at the individual level can be missed if only trends at the population level are studied. This study aimed to determine how persistent Haemosporida are in great tit individuals recaptured over several years, whether parasitaemia differed by parasite lineage (mitochondrial cytochrome b haplotype) and how co-infection (i.e. concurrent infection with multiple genera of parasites) affects parasitaemia and body mass. METHODS: Parasite prevalence was determined by polymerase chain reaction (PCR), quantitative PCR were used to assess parasitaemia and sequencing was employed to determine the identity of the lineages using the MalAvi database. RESULTS: Haemosporidian prevalence was high over sampled years with 98% of 55 recaptured individuals showing infection in at least one year of capture. Eighty-two percent of all positive individuals suffered co-infection, with an overall haemosporidian lineage diversity of seventeen. Plasmodium and Haemoproteus parasites were found to be highly persistent, with lineages from these genera consistently found in individuals across years and with no differences in individual parasitaemia being recorded at subsequent captures. Conversely, Leucocytozoon parasites showed higher turnover with regard to lineage changes or transitions in infection status (infected vs non-infected) across years. Parasitaemia was found to be lineage specific and there was no relationship between Plasmodium parasitaemia or host body condition and the presence of Leucocytozoon parasites. CONCLUSIONS: The findings of this study suggest that different genera of haemosporidian parasites interact differently with their host and other co-infecting parasites, influencing parasite persistence most likely through inter-parasite competition or host-parasite immune interactions. Even-though co-infections do not seem to result in increased virulence (higher parasitaemia or poorer host body condition), further investigation into infection potential of these parasites, both individually and as co-infections, is necessary.

Entendendo estrutura molecular com a molécula de hidrogênio ionizada

In this paper a general view about the modern molecular structure theory is developed discussing the ionized hydrogen molecule. We introduce some necessary approximation methods for the electronic and nuclear spectra study adopting a systematic approach. In addition though, we have performed calculations in order to illustrate these methods.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Impact of training at ventilatory threshold on cardiopulmonary and functional capacity in overweight patients with chronic kidney disease

INTRODUCTION: Chronic kidney disease (CKD) and obesity are both associated with reduced physical capacity. The potential benefit of aerobic training on physical capacity has been recognized. The exercise intensity can be established using different methods mostly subjective or indirect. Ventilatory threshold (VT) is a direct and objective method that allows prescribing exercise intensity according to individual capacity. OBJECTIVES: To evaluate the impact of aerobic training at VT intensity on cardiopulmonary and functional capacities in CKD patients with excess of body weight. METHODS: Ten CKD patients (eight men, 49.7 ± 10.1 years; BMI 30.4 ± 3.5 kg/m², creatinine clearance 39.4 ± 9.8 mL/min/1.73 m²) underwent training on a treadmill three times per week during 12 weeks. Cardiopulmonary capacity (ergoespirometry), functional capacity and clinical parameters were evaluated. RESULTS: At the end of 12 weeks, VO2PEAK increased by 20%, and the speed at VO2PEAK increased by 16%. The training resulted in improvement in functional capacity tests, such as six-minute walk test (9.2%), two-minute step test (20.3%), arm curl test (16.3%), sit and stand test (35.7%), and time up and go test (15.3%). In addition, a decrease in systolic and diastolic blood pressures was observed despite no change in body weight, sodium intake and antihypertensive medication. CONCLUSION: Aerobic exercise performed at VT intensity improved cardipulmonary and functional capacities of overweight CKD patients. Additional benefit on blood pressure was observed. These results suggest that VT can be effectively applied for prescribing exercise intensity in this particular group of patients.

La nutrition des personnes âgées en stades précoces de la démence du type Alzheimer (DTA) : exploration du rôle du proche aidant et des répercussions sur sa santé

Contexte : La détérioration de l’état nutritionnel liée à la perte d’autonomie qui accompagne l’évolution de la démence du type Alzheimer (DTA) peut être limitée par un proche aidant efficace. À long terme, le rôle soignant du proche aidant peut affecter sa propre santé physique et psychologique. Objectifs : (1) décrire les caractéristiques sociodémographiques des patients et de leurs proches aidants; (2) examiner l’évolution de la maladie et des variables à l’étude au cours de la période de suivi; (3) explorer la relation possible entre le fardeau perçu du proche aidant, l’état nutritionnel des patients et la stabilité du poids corporel du proche aidant. Hypothèses : L’absence du fardeau chez l’aidant est associée à un meilleur état nutritionnel chez le patient; la détérioration de la fonction cognitive chez le patient s’accompagne d’une augmentation du fardeau perçu par l’aidant; la dégradation du fardeau chez l’aidant conduit à sa perte de poids. Méthode : Les données analysées proviennent de l’étude « Nutrition-mémoire » menée entre 2003 et 2006 dans les trois cliniques de cognition situées dans des hôpitaux universitaires à Montréal. Quarante-deux patients avec une DTA probable vivant dans la communauté et leurs aidants ont été suivis en dyades pendant une période de dix-huit mois. Les analyses ont porté sur les données colligées du recrutement à douze mois plus tard en raison du nombre restreint des patients interviewés à la dernière mesure. La relation entre le fardeau de l’aidant et les variables caractérisant l’état nutritionnel chez les patients a été évaluée à l’aide des analyses de corrélations, du test khi-carré ou du test de Fisher. L’état cognitif des patients était évalué à l’aide du score au Mini-Mental State Examination, le fardeau de l’aidant était estimé par le score au « Zarit Burden Interview », l’état nutritionnel des patients était défini par la suffisance en énergie et en protéines, le score à l’outil de dépistage nutritionnel des aînés, le poids et l’indice de masse corporelle des patients. Résultats : Le fardeau perçu des aidants était associé à la suffisance en énergie chez les patients. Le nombre de patients ayant des apports insuffisants en énergie était plus important chez les dyades où les aidants percevaient un fardeau plus élevé. Toutefois, aucune association n’a été observée entre le fardeau des aidants et le risque nutritionnel ou la suffisance en protéines chez les patients. La détérioration de la fonction cognitive des patients ne semble pas avoir provoqué une augmentation du fardeau chez leurs aidants. De plus, l’augmentation du fardeau de l’aidant n’était pas accompagnée d’une perte de son poids corporel. Par ailleurs, un fardeau plus important a été observé chez les aidants des patients obèses ou présentant un embonpoint. Conclusion : La réduction du fardeau perçu des aidants permettrait d’améliorer les apports alimentaires des patients et ainsi de limiter ou minimiser le risque de détérioration de leur état nutritionnel et de perte de poids.

Studies in molecular spectroscopy

This thesis is divided into two parts. The first part deals with some studies in molecular mechanics Using spectroscopic data and has four chapters in it. Certain approximation methods for the evaluation of molecular force fields are herein developed The second part, which consists of the last two chaptcrs, deals with infrared spectral studies of ternary liquid systems and a polymer film prepared by glow discharge method.

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

First order k-th moment finite element analysis of nonlinear operator equations with stochastic data

We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

The effect of the negative coupling parameter on the spectrum of a trapped Bose gas

The interest in attractive Bose-Einstein Condensates arises due to the chemical instabilities generate when the number of trapped atoms is above a critical number. In this case, recombination process promotes the collapse of the cloud. This behavior is normally geometry dependent. Within the context of the mean field approximation, the system is described by the Gross-Pitaevskii equation. We have considered the attractive Bose-Einstein condensate, confined in a nonspherical trap, investigating numerically and analytically the solutions, using controlled perturbation and self-similar approximation methods. This approximation is valid in all interval of the negative coupling parameter allowing interpolation between weak-coupling and strong-coupling limits. When using the self-similar approximation methods, accurate analytical formulas were derived. These obtained expressions are discussed for several different traps and may contribute to the understanding of experimental observations.

Imaging studies of the hindlimbs of pacas (Cuniculus paca) bred in captivity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)