Association of early repolarization with risk of cardiac mortality in the general population

Early repolarization, which is characterized by an elevation of the J-point on 12-lead electrocardiography, is a common finding that has been considered as benign for decades. However, in the last years, it has been related with vulnerability to idiopathic ventricular fibrillation and with cardiac mortality in the general population. Recently, 4 potential ECG predictors that could differentiate the benign from the malignant form of early repolarization have been suggested. Any previous study about early repolarization has been done in Spain. Aim. To ascertain whether the presence of early repolarization pattern in a resting electrocardiogram is associated with a major risk of cardiac death in a Spanish general population and to determine whether the presence of potential predictors of malignancy in a resting electrocardiogram increases the risk of cardiac mortality in patients with early repolarization pattern. Methods. We will analyse the presence of early repolarization and the occurrence of cardiac mortality in a retrospective cohort study of 4,279 participants aged 25 to 74 years in the province of Girona. This cohort has been followed during a mean of 9.8 years. Early repolarization will be stratified according to the degree of J-point elevation (≥0.1 mV or ≥0.2 mV), the morphology of the J-wave (slurring, notching or any of these two), the ST-segment pattern (ascending or descending) and the localization (inferior leads, lateral leads, or both). Association of early repolarization with cardiac death will be assessed by adjusted Cox-proportional hazards models

Scientific journals in Brazil and Spain: Alternative publishing models

This paper describes high-quality journals in Brazil and Spain, with an emphasis on the distribution models used. It presents the general characteristics (age, type of publisher, and theme) and analyzes the distribution model by studying the type of format (print or digital), the type of access (open access or subscription), and the technology platform used. The 549 journals analyzed (249 in Brazil and 300 in Spain) are included in the 2011 Web of Science (WoS) and Scopus databases. Data on each journal were collected directly from their websites between March and October 2012. Brazil has a fully open access distribution model (97%) in which few journals require payment by authors thanks to cultural, financial, operational, and technological support provided by public agencies. In Spain, open access journals account for 55% of the total and have also received support from public agencies, although to a lesser extent. These results show that there are systems support of open access in scientific journals other than the"author pays" model advocated by the Finch report for the United Kingdom.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Mechanistic population Models in Biology: Model Derivation and Application

In general, models of ecological systems can be broadly categorized as ’top-down’ or ’bottom-up’ models, based on the hierarchical level that the model processes are formulated on. The structure of a top-down, also known as phenomenological, population model can be interpreted in terms of population characteristics, but it typically lacks an interpretation on a more basic level. In contrast, bottom-up, also known as mechanistic, population models are derived from assumptions and processes on a more basic level, which allows interpretation of the model parameters in terms of individual behavior. Both approaches, phenomenological and mechanistic modelling, can have their advantages and disadvantages in different situations. However, mechanistically derived models might be better at capturing the properties of the system at hand, and thus give more accurate predictions. In particular, when models are used for evolutionary studies, mechanistic models are more appropriate, since natural selection takes place on the individual level, and in mechanistic models the direct connection between model parameters and individual properties has already been established. The purpose of this thesis is twofold. Firstly, a systematical way to derive mechanistic discrete-time population models is presented. The derivation is based on combining explicitly modelled, continuous processes on the individual level within a reproductive period with a discrete-time maturation process between reproductive periods. Secondly, as an example of how evolutionary studies can be carried out in mechanistic models, the evolution of the timing of reproduction is investigated. Thus, these two lines of research, derivation of mechanistic population models and evolutionary studies, are complementary to each other.

Factors associated with active aging in Finland, Poland, and Spain

BACKGROUND: Continuous population aging has raised international policy interest in promoting active aging (AA). AA theoretical models have been defined from a biomedical or a psychosocial perspective. These models may be expanded including components suggested by lay individuals. This paper aims to study the correlates of AA in three European countries, namely, Spain, Poland, and Finland using four different definitions of AA. METHODS: The EU COURAGE in Europe project was a cross-sectional general adult population survey conducted in a representative sample of the noninstitutionalized population of Finland, Poland, and Spain. Participants (10,800) lived in the community. This analysis focuses on individuals aged 50 years old and over (7,987). Four definitions (two biomedical, one psychosocial, and a complete definition including biomedical, psychosocial, and external variables) of AA were analyzed. RESULTS: Differences in AA were found for country, age, education, and occupation. Finland scored consistently the highest in AA followed by Spain and Poland. Younger age was associated with higher AA. Higher education and occupation was associated with AA. Being married or cohabiting was associated with better AA compared to being widowed or separated in most definitions. Gender and urbanicity were not associated with AA, with few exceptions. Men scored higher in AA only in Spain, whereas there was no gender association in the other two countries. Being widowed was only associated with lower AA in Poland and not being married was associated with lower AA in Poland and Finland but not Spain. CONCLUSIONS: Associations with education, marital status, and occupation suggest that these factors are the most important components of AA. These association patterns, however, seem to vary across the three countries. Actions to promote AA in these countries may be addressed at reducing inequalities in occupation and education or directly tackling the components of AA lacking in each country.

Intestinal microbiota in the adenoma progression to colorectal cancer: a cross-sectional study

Background: Colorectal cancer is a major health problem worldwide and many efforts have been done to delineate risk factors and develop screening strategies to reduce its incidence and mortality. Colorectal adenomas have been clearly considered preneoplastic lesions due to their potential malignant transformation via the adenoma-carcinoma sequence. Over the last years, intestinal microbiota has been studied in several diseases and it has been hypothesized that colonic microbiota could influence colorectal cancer pathogenesisObjective: The goal of this study is to analyse whether there is an association between the fecal microbiota profiling and the presence and progression of colorectal adenomas, detected in population undergoing colonoscopy, to better understand the role of intestinal microbiota in colorectal carcinogenesisDesign: A cross-sectional study in the Gastroenterology Department at Hospital Universitari Doctor Josep Trueta in Girona, in a period of time of two yearsParticipants: General population undergoing screening or diagnostic colonoscopy in the Digestive Endoscopy UnitOutcomes: Identification and characterization of intestinal microbiota in stool samples from healthy patients and patients with low and high risk colorectal adenomas

Impact of multimorbidity on disability and quality of life in the spanish older population

BACKGROUND: Population aging is closely related to high prevalence of chronic conditions in developed countries. In this context, health care policies aim to increase life span cost-effectively while maintaining quality of life and functional ability. There is still, however, a need for further understanding of how chronic conditions affect these health aspects. The aim of this paper is to assess the individual and combined impact of chronic physical and mental conditions on quality of life and disability in Spain, and secondly to show gender trends. METHODS: Cross-sectional data were collected from the COURAGE study. A total of 3,625 participants over 50 years old from Spain were included. Crude and adjusted multiple linear regressions were conducted to detect associations between individual chronic conditions and disability, and between chronic conditions and quality of life. Separate models were used to assess the influence of the number of diseases on the same variables. Additional analogous regressions were performed for males and females. RESULTS: All chronic conditions except hypertension were statistically associated with poor results in quality of life and disability. Depression, anxiety and stroke were found to have the greatest impact on outcomes. The number of chronic conditions was associated with substantially lower quality of life [β for 4+ diseases: -18.10 (-20.95,-15.25)] and greater disability [β for 4+ diseases: 27.64 (24.99,30.29]. In general, women suffered from higher rates of multimorbidity and poorer results in quality of life and disability. CONCLUSIONS: Chronic conditions impact greatly on quality of life and disability in the older Spanish population, especially when co-occurring diseases are added. Multimorbidity considerations should be a priority in the development of future health policies focused on quality of life and disability. Further studies would benefit from an expanded selection of diseases. Policies should also deal with gender idiosyncrasy in certain cases.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Computational modeling for irrigated agriculture planning. Part I: general description and linear programming

Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.

Evaluation of roof slope and exposure with different roofing materials in reduced models of animal production facilities in spring and summer

The present study was conducted at the Department of Rural Engineering and the Department of Animal Morphology and Physiology of FCAV/Unesp, Jaboticabal, SP, Brazil. The objective was to verify the influence of roof slope, exposure and roofing material on the internal temperature of reduced models of animal production facilities. For the development of the research, 48 reduced and dissemble models with dimensions 1.00 × 1.00 × 0.50 m were used. The roof was shed-type, and the models faced to the North or South directions, with 24 models for each side of exposure. Ceramic, galvanized-steel and fibro tiles were used to build the roofs. Slopes varied between 20, 30, 40 and 50% for the ceramic tile and 10, 30, 40 and 50% for the other two. Inside the models, temperature readings were performed at every hour, for 12 months. The results were evaluated in a general linear model in a nested 3 × 4 × 2 factorial arrangement, in which the effects of roofing material and exposure were nested on the factor Slope. Means were compared by the Tukey test at 5% of probability. After analyzing the data, we observed that with the increase in the slope and exposure to the South, there was a drop in the internal temperature within the model at the geographic coordinates of Jaboticabal city (SP/Brazil).

Low-fidelity bench models for basic surgical skills training during undergraduate medical education

It is remarkable the reduction in the number of medical students choosing general surgery as a career. In this context, new possibilities in the field of surgical education should be developed to combat this lack of interest. In this study, a program of surgical training based on learning with models of low-fidelity bench is designed as a complementary alternative to the various methodologies in the teaching of basic surgical skills during medical education, and to develop personal interests in career choice.

Cardiovascular risk in middle-aged breast cancer survivors: a comparison between two risk models

PURPOSE: It was to assess the risk of cardiovascular disease (CVD) in breast cancer survivors (BCS).METHODS: This cross-sectional study analyzed 67 BCS, aged 45 -65 years, who underwent complete oncological treatment, but had not received hormone therapy, tamoxifen or aromatase inhibitors during the previous 6 months. Lipid profile and CVD risk were evaluated, the latter using the Framingham and Systematic COronary Risk Evaluation (SCORE) models. The agreement between cardiovascular risk models was analyzed by calculating a kappa coefficient and its 95% confidence interval (CI).RESULTS: Mean subject age was 53.2±6.0 years, with rates of obesity, hypertension, and dyslipidemia of 25, 34 and 90%, respectively. The most frequent lipid abnormalities were high total cholesterol (70%), high LDL-C (51%) and high non-HDL-C (48%) concentrations. Based on the Framingham score, 22% of the participants had a high risk for coronary artery disease. According to the SCORE model, 100 and 93% of the participants were at low risk for fatal CVD in populations at low and high risk, respectively, for CVD. The agreement between the Framingham and SCORE risk models was poor (kappa: 0.1; 95%CI 0.01 -0.2) for populations at high risk for CVD.CONCLUSIONS: These findings indicate the need to include lipid profile and CVD risk assessment in the follow-up of BCS, focusing on adequate control of serum lipid concentrations.

Mapping financial stability

The ongoing global financial crisis has demonstrated the importance of a systemwide, or macroprudential, approach to safeguarding financial stability. An essential part of macroprudential oversight concerns the tasks of early identification and assessment of risks and vulnerabilities that eventually may lead to a systemic financial crisis. Thriving tools are crucial as they allow early policy actions to decrease or prevent further build-up of risks or to otherwise enhance the shock absorption capacity of the financial system. In the literature, three types of systemic risk can be identified: i ) build-up of widespread imbalances, ii ) exogenous aggregate shocks, and iii ) contagion. Accordingly, the systemic risks are matched by three categories of analytical methods for decision support: i ) early-warning, ii ) macro stress-testing, and iii ) contagion models. Stimulated by the prolonged global financial crisis, today's toolbox of analytical methods includes a wide range of innovative solutions to the two tasks of risk identification and risk assessment. Yet, the literature lacks a focus on the task of risk communication. This thesis discusses macroprudential oversight from the viewpoint of all three tasks: Within analytical tools for risk identification and risk assessment, the focus concerns a tight integration of means for risk communication. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats. The overall task of this thesis is to represent high-dimensional data concerning financial entities on lowdimensional displays. The low-dimensional representations have two subtasks: i ) to function as a display for individual data concerning entities and their time series, and ii ) to use the display as a basis to which additional information can be linked. The final nuance of the task is, however, set by the needs of the domain, data and methods. The following ve questions comprise subsequent steps addressed in the process of this thesis: 1. What are the needs for macroprudential oversight? 2. What form do macroprudential data take? 3. Which data and dimension reduction methods hold most promise for the task? 4. How should the methods be extended and enhanced for the task? 5. How should the methods and their extensions be applied to the task? Based upon the Self-Organizing Map (SOM), this thesis not only creates the Self-Organizing Financial Stability Map (SOFSM), but also lays out a general framework for mapping the state of financial stability. This thesis also introduces three extensions to the standard SOM for enhancing the visualization and extraction of information: i ) fuzzifications, ii ) transition probabilities, and iii ) network analysis. Thus, the SOFSM functions as a display for risk identification, on top of which risk assessments can be illustrated. In addition, this thesis puts forward the Self-Organizing Time Map (SOTM) to provide means for visual dynamic clustering, which in the context of macroprudential oversight concerns the identification of cross-sectional changes in risks and vulnerabilities over time. Rather than automated analysis, the aim of visual means for identifying and assessing risks is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence, as well as external risk communication.