Health-related quality of life and determinant factors in celiac disease. A population-based analysis of adult patients in Spain

Background: Celiac disease (CD) has a negative impact on the health-related quality of life (HRQL) of affected patients. Although HRQL and its determinants have been examined in Spanish CD patients specifically recruited in hospital settings, these aspects of CD have not been assessed among the general Spanish population. Methods: An observational, transversal study of a non-randomized, representative sample of adult celiac patients throughout all of Spain's Autonomous Regions. Subjects were recruited through celiac patient associations. A Spanish version of the self-administered Celiac Disease-Quality of Life (CD-QOL) questionnaire was used. Determinant factors of HRQL were assessed with the aid of multivariate analysis to control for confounding factors. Results: We analyzed the responses provided by 1,230 patients, 1,092 (89.2%) of whom were women. The overall mean value for the CD-QOL index was 56.3 ± 18.27 points. The dimension that obtained the most points was dysphoria, with 81.3 ± 19.56 points, followed by limitations with 52.3 ± 23.43 points; health problems, with 51.6 ± 26.08 points, and inadequate treatment, with 36.1 ± 21.18 points. Patient age and sex, along with time to diagnosis, and length of time on a gluten-free diet were all independent determinant factors of certain dimensions of HRQL: women aged 31 to 40 expressed poorer HRQL while time to diagnosis and length of time on a gluten-free diet were determinant factors for better HRQL scores. Conclusions: The HRQL of adult Spanish celiac subjects is moderate, improving with the length of time patients remain on a gluten-free diet.

FPGA implementation of a multi-population PBIL algorithm

Evolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.

The Opportunity Costs of STEM Degrees and the Unmet Needs of the Low-Skilled: Two labour market problems explained. CEPS Policy Brief No. 295, 26 June 2013

There is general consensus that to achieve employment growth, especially for vulnerable groups, it is not sufficient to simply kick-start economic growth: skills among both the high- and low-skilled population need to be improved. In particular, we argue that if the lack of graduates in science, technology, engineering and mathematics (STEM) is a true problem, it needs to be tackled via incentives and not simply via public campaigns: students are not enrolling in ‘hard-science’ subjects because the opportunity cost is very high. As far as the low-skilled population is concerned, we encourage EU and national policy-makers to invest in a more comprehensive view of this phenomenon. The ‘low-skilled’ label can hide a number of different scenarios: labour market detachment, migration, and obsolete skills that are the result of macroeconomic structural changes. For this reason lifelong learning is necessary to keep up with new technology and to shield workers from the risk of skills obsolescence and detachment from the labour market.

Japan; suggested outlines for a discussion of Japan, her history, culture, problems, and relations with the United States.

"Professor Latourette, who originally prepared the Syllabus for the Japan Society ... has, in this eighth edition, concerned himself only with the historical and political evolution of Japan and Japan's foreign relations. Mr. Harold Gould Henderson ... has revised and expanded the sections on Japanese art and literature. Professor Douglas G. Haring ... has done the same for the sections on population, family and social life, and manners and customs."--p. 3.

Prevalence of drug use in the DC Metropolitan Area institutionalized population, 1991.

Shipping list no.: 94-0324-P.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Why are there so few genetic markers available for coral population analyses?

Coral reefs are in serious decline, and research in support of reef management objectives is urgently needed. Reef connectivity analyses have been highlighted as one of the major future research avenues necessary for implementing effective management initiatives for coral reefs. Despite the number of new molecular genetic tools and the wealth of information that is now available for population-level processes in many marine disciplines, scleractinian coral population genetic information remains surprisingly limited. Here we examine the technical problems and approaches used, address the reasons contributing to this delay in understanding, and discuss the future of coral population marker development. Considerable resources are needed to target the immediate development of an array of relevant genetic markers coupled with the rapid production of management focused data in order to help conserve our globally threatened coral reef resources.

Interaction of psychosocial risk factors explain increased neck problems among female office workers

This study investigated the relationship between psychosocial risk factors and (1) neck symptoms and (2) neck pain and disability as measured by the neck disability index (NDI). Female office workers employed in local private and public organizations were invited to participate, with 333 completing a questionnaire. Data were collected on various risk factors including age, negative affectivity, history of previous neck trauma, physical work environment, and task demands. Sixty-one percent of the sample reported neck symptoms lasting greater than 8 days in the last 12 months. The mean NDI of the sample was 15.5 out of 100, indicating mild neck pain and disability. In a hierarchical multivariate logistic regression, low supervisor support was the only psychosocial risk factor identified with the presence of neck symptoms. Similarly, low supervisor support was the only factor associated with the score on the NDI. These associations remained after adjustment for potential confounders of age, negative affectivity, and physical risk factors. The interaction of job demands, decision authority, and supervisor support was significantly associated with the NDI in the final model and this association increased when those with previous trauma were excluded. Interestingly, and somewhat contrary to initial expectations, as job demands increased, high decision authority had an increasing effect on the NDI when supervisor support was low. Crown copyright (c) 2006 Published by Elsevier B.V. All rights reserved.

The problems of corruption in Post-Soviet Ukraine's Higher Education sector

This article provide an in-depth examination into how the existence of "informal" work practices, in a particular location, namely, the higher education system in Ukraine impacts the everyday lives of a specific population group, namely, students. The article provides a comprehensive overview of corruption in post-Soviet education systems, suggesting some historical and contemporary reasons for its current scale. In particular, the article focuses on students' experiences of corruption, first, exploring the difficulties that many individuals face when trying to gain access to the higher education system, and second, outlining students' experiences while progressing through the course. The article's concluding section examines the wider outcome of these processes on Ukrainian society as a whole as well as the impacts on individual students.

Evidence for the early clinical relevance of hallucinatory-delusional states in the general population

OBJECTIVE: To analyze, in a general population sample, clustering of delusional and hallucinatory experiences in relation to environmental exposures and clinical parameters. METHOD: General population-based household surveys of randomly selected adults between 18 and 65 years of age were carried out. SETTING: 52 countries participating in the World Health Organization's World Health Survey were included. PARTICIPANTS: 225 842 subjects (55.6% women), from nationally representative samples, with an individual response rate of 98.5% within households participated. RESULTS: Compared with isolated delusions and hallucinations, co-occurrence of the two phenomena was associated with poorer outcome including worse general health and functioning status (OR = 0.93; 95% CI: 0.92-0.93), greater severity of symptoms (OR = 2.5 95% CI: 2.0-3.0), higher probability of lifetime diagnosis of psychotic disorder (OR = 12.9; 95% CI: 11.5-14.4), lifetime treatment for psychotic disorder (OR = 19.7; 95% CI: 17.3-22.5), and depression during the last 12 months (OR = 11.6; 95% CI: 10.9-12.4). Co-occurrence was also associated with adversity and hearing problems (OR = 2.0; 95% CI: 1.8-2.3). CONCLUSION: The results suggest that the co-occurrence of hallucinations and delusions in populations is not random but instead can be seen, compared with either phenomenon in isolation, as the result of more etiologic loading leading to a more severe clinical state.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

Juniperus navicularis - a study of Portuguese population structure and fitness

Juniperus navicularis Gand. is a dioecious endemic conifer that constitutes the understory of seaside pine forests in Portugal, areas currently threatened by increasing urban expansion. The aim of this study is to assess the conservation status of previously known populations of this species located on its core area of distribution. The study was performed in south-west coast of Portugal. Three populations varying in size and pine density were analyzed. Number of individuals, population density, spatial distribution and individual characteristics of junipers were estimated. Female cone, seed characteristics and seed viability were also evaluated. Results suggest that J. navicularis populations are vulnerable because seminal recruitment is scarce, what may lead to a reduction of genetic variability due solely to vegetative propagation. This vulnerability seems to be strongly determined by climatic constraints toward increasing aridity. Ratio between male and female shrubs did not differ from 1:1 in any population. Deviations from 1:1 between mature and non-mature plants were found in all populations, denoting population ageing. Very low seed viability was observed. A major part of described Juniperus navicularis populations have disappeared through direct habitat loss to urban development, loss of fitness in drier and warmer locations and low seed viability. This study is the first to address J. navicularis conservation, and represents a valuable first step toward this species preservation. 

Alcohol-Related Problems in Eastern Europe : A Comparative Perspective

This thesis investigates the association between alcohol consumption and alcohol-related harm in Eastern Europe. The main aim was to estimate to what extent changes in per capita alcohol consumption have an impact on different forms of alcohol-related mortality, and to put the results in an international comparative perspective. The thesis includes four papers; the first two papers use aggregate time-series analysis to assess how changes in per capita consumption affect rates in suicide mortality and fatal non-intentional injuries in several Eastern European countries, respectively. The third paper applies the same methodological approach to analyse the population-level relationship between alcohol and homicide in Russia and the U.S.. The fourth paper employs survey data to assess how the risk of experiencing alcohol-related problems in relation to volume of consumption in the Baltic countries compares to Sweden and Italy. The results of the first three papers suggests: (i) that changes in per capita consumption are significantly related to changes in mortality rates of suicide, non-intentional injuries and homicide in the countries under study; (ii) that the relationship is stronger for men than for women, and (iii) that the relationship tends to be stronger in the countries with more detrimental drinking patterns, e.g. Russia. The results of the fourth paper suggest that the risk of experiencing alcohol-related problems in relation to level of drinking in the Baltic countries is similar to the corresponding risk in Sweden, but considerably stronger than in Italy. In conclusion, the findings support the significance of a public health approach to alcohol-related problems in Eastern Europe, i.e., policy measures directed towards total alcohol consumption. In addition, strategies aimed at reducing the occurrence of binge drinking seem to have great potential for reducing alcohol-related harm and mortality in Eastern European countries.

Health-related quality of life and determinant factors in celiac disease: a population-based analysis of adult patients in Spain

Background: Celiac disease (CD) has a negative impact on the health-related quality of life (HRQL) of affected patients. Although HRQL and its determinants have been examined in Spanish CD patients specifically recruited in hospital settings, these aspects of CD have not been assessed among the general Spanish population. Methods: An observational, cross-sectional study of a non-randomized, representative sample of adult celiac patients throughout all of Spain's Autonomous Regions. Subjects were recruited through celiac patient associations. A Spanish version of the self-administered Celiac Disease-Quality of Life (CD-QOL) questionnaire was used. Determinant factors of HRQL were assessed with the aid of multivariate analysis to control for confounding factors. Results: We analyzed the responses provided by 1,230 patients, 1,092 (89.2%) of whom were women. The overall mean value for the CD-QOL index was 56.3 ± 18.27 points. The dimension that obtained the most points was dysphoria, with 81.3 ± 19.56 points, followed by limitations with 52.3 ± 23.43 points; health problems, with 51.6 ± 26.08 points, and inadequate treatment, with 36.1 ± 21.18 points. Patient age and sex, along with time to diagnosis, and length of time on a gluten-free diet were all independent determinant factors of certain dimensions of HRQL: women aged 31 to 40 expressed poorer HRQL while time to diagnosis and length of time on a gluten-free diet were determinant factors for better HRQL scores. Conclusions: The HRQL level of adult Spanish celiac subjects is moderate, improving with the length of time patients remain on a gluten-free diet.

Role of nuclear redox control, intra-population heterogeneity and oxygen tension in human amniotic fluid stem cells aging

Amniotic fluid stem cells (hAFSC) are emerging as a potential therapeutic approach for various disorders. The low number of available hAFSC requires their ex vivo expansion prior to clinical use, however, during their in vitro culture, hAFSC quickly reach replicative senescence. The principal aim of this study was to investigate the aging process occurring during in vitro expansion of hAFSC, focusing on the redox control that has been reported to be affected in premature and physiological aging. My results show that a strong heterogeneity is present among samples that reflects their different behaviour in culture. I identified three proteins, namely Nox4, prelamin A and PML, which expression increases during hAFSC aging process and could be used as new biomarkers to screen the samples. Furthermore, I found that Nox4 degradation is regulated by sumoylation via proteasome and involves interactions with PML bodies and prelamin A. Since various studies revealed that donor-dependent differences could be explained by cell-to-cell variation within each patient, I studied in deep this phenomenon. I showed that the heterogeneity among samples is also accompanied by a strong intra-population heterogeneity. Separation of hAFSC subpopulations from the same donor, using Celector® technology, showed that an enrichment in the last eluted fraction could improve hAFSC application in regenerative medicine. One of the other problems is that nowadays hAFSC are expanded under atmospheric O2 concentration, which is higher than the O2 tension in their natural niches. This higher O2 concentration might cause environmental stress to the in vitro cultured hAFSCs and accelerate their aging process. Here, I showed that prolonged low oxygen tension exposure preserves different hAFSC stemness properties. In conclusion, my study pointed different approaches to improve in vitro hAFSC expansion and manipulation with the purpose to land at stem cell therapy.