Dietary patterns and nutritional adequacy in a Mediterranean country

Dietary patterns have been related to health outcomes and morbi-mortality. Mediterranean diet indexes are correlated With adequate nutrient intake. The objective of the present study was to analyse the adequacy of nutrient intake of a posteriori defined Mediterranean (MDP) and Western (WDP) diet patterns in the Seguimiento Universidad de Navarra (SUN) cohort. A sample of 17 197 subjects participated in the study. Participants completed I 136-item validated semi-quantitative FFQ. Principal component analysis was used to define dietary patterns. Individuals were classified according to quintiles of adherence based on dietary pattern scores. Non-dietary variables, such as smoking and physical activity habits, were also taken into account. The probability approach was used to assess nutrient intake adequacy of certain vitamins (vitamins B(12), B(6), B(3), B(2), B(1), A, C, D and E) and minerals (Na, Zn, iodine, Se, folic acid, P, Mg, K, Fe and Ca). Logistic regression analysis was used to assess the adequacy of nutrient intake according to adherence to dietary patterns. WDP and MDP were defined. A higher quintile of adherence to an MDP was associated to I lower prevalence of inadequacy for the intake of Zn, iodine, vitamin E, Mg, Fe, vitamin B I, vitamin A, Se, vitamin C and folic acid. The adjusted OR for not reaching at least six (or at leas( ten) nutrient recommendations were 0.09 (95% Cl: 0.07, 0.11) (and 0.02 (95% Cl: 0.00, 0.16)) for the upper quintile of MDP and 4.4 (95% Cl: 3.6, 5.5) and 2.5 (95 % Cl: 1.1, 5.4) for the WDP. The MDP was associated to a better profile of nutrient intake.

Treatment outcome in individuals with chronic pain: is the Pain Stages of Change Questionnaire (PSOCQ) a useful tool? Jenny StrongCorresponding Author Contact Information, E-mail The Corresponding Author, a, Kym Westburya, Glen Smithb, Ian McKenziec and William Ryan

The efficacy of psychological treatments emphasising a self-management approach to chronic pain has been demonstrated by substantial empirical research. Nevertheless, high drop-out and relapse rates and low or unsuccessful engagement in self-management pain rehabilitation programs have prompted the suggestion that people vary in their readiness to adopt a self-management approach to their pain. The Pain Stages of Change Questionnaire (PSOCQ) was developed to assess a patient's readiness to adopt a self-management approach to their chronic pain. Preliminary evidence has supported the PSOCQ's psychometric properties. The current study was designed to further examine the psychometric properties of the PSOCQ, including its reliability, factorial structure and predictive validity. A total of 107 patients with an average age of 36.2 years (SD = 10.63) attending a multi-disciplinary pain management program completed the PSOCQ, the Pain Self-Efficacy Questionnaire (PSEQ) and the West Haven-Yale Multidimensional Pain Inventory (WHYMPI) pre-admission and at discharge from the program. Initial data analysis found inadequate internal consistencies of the precontemplation and action scales of the PSOCQ and a high correlation (r = 0.66, P < 0.01) between the action and maintenance scales. Principal component analysis supported a two-factor structure: 'Contemplation' and 'Engagement'. Subsequent analyses revealed that the PSEQ was a better predictor of treatment outcome than the PSOCQ scales. Discussion centres upon the utility of the PSOCQ in a clinical pain setting in light of the above findings, and a need for further research. (C) 2002 International Association for the Study of Pain. Published by Elsevier Science B.V. All rights reserved.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

Genetic variability in cultivated common bean beyond the two major gene pools

It is generally accepted that two major gene pools exist in cultivated common bean (Phaseolus vulgaris L.), a Middle American and an Andean one. Some evidence, based on unique phaseolin morphotypes and AFLP analysis, suggests that at least one more gene pool exists in cultivated common bean. To investigate this hypothesis, 1072 accessions from a common bean core collection from the primary centres of origin, held at CIAT, were investigated. Various agronomic and morphological attributes (14 categorical and 11 quantitative) were measured. Multivariate analyses, consisting of homogeneity analysis and clustering for categorical data, clustering and ordination techniques for quantitative data and nonlinear principal component analysis for mixed data, were undertaken. The results of most analyses supported the existence of the two major gene pools. However, the analysis of categorical data of protein types showed an additional minor gene pool. The minor gene pool is designated North Andean and includes phaseolin types CH, S and T; lectin types 312, Pr, B and K; and mostly A5, A6 and A4 types alpha-amylase inhibitor. Analysis of the combined categorical data of protein types and some plant categorical data also suggested that some other germplasm with C type phaseolin are distinguished from the major gene pools.

Are wing size, wing shape and asymmetry related to field fitness of Trichogramma egg parasitoids?

The effects of wing shape, wing size, and fluctuating asymmetry in these measures oil the field fitness of T. nr. brassicae and T. pretiosum were investigated. Trichogramma wasps mass-reared on eggs of the factitious host Sitotroga cerealella were released in tomato paddocks and those females ovipositing on Helicoverpo spp. eggs were recaptured. Comparisons of the recaptured group with a sample from the release population were used to assess fitness. Wing data were obtained by positioning landmarks on mounted forewings. Size was then measured as the centroid size computed from landmark distances, while Procrustes analysis followed by principal component analysis was used to assess wing shape. Similar findings were obtained for both Trichogramma species: fitness of wasps was strongly related to wing size and some shape dimensions, but not to the asymmetries of these measures. Wasps which performed well in the field had larger wings and a different wing shape compared to wasps from the mass reared population. Both size and the shape dimensions were linearly associated with fitness although there was also some evidence for non-linear selection on shape. The results suggest that wing shape and wing size are reliable predictors of field fitness for these Trichogramma wasps.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.

Chemical, morphological, rheological and thermal properties of Solanum lycocarpum phosphorylated starches

The increasing need for starches with specific characteristics makes it important to study unconventional starches and their modifications in order to meet consumer demands. The aim of this work was to study physicochemical characteristics of native starch and phosphate starch of S. lycocarpum. Native starch was phosphated with sodium tripolyphosphate (5-11%) added with stirring. Chemical composition, morphology, density, binding ability to cold water, swelling power and solubility index, turbidity and syneresis, rheological and calorimetric properties were determined. Phosphorus was not detected in the native sample, but the phosphating process produced modified starches with phosphorus contents of 0.015, 0.092 and 0.397%, with the capacity of absorbing more water, either cold or hot. Rheological data showed the strong influence of phosphorus content on viscosity of phosphate starch, with lower pasting temperature and peak viscosity higher than those of native starch. Enthalpy was negatively correlated with the phosphorus content, requiring 9.7; 8.5; 8.1 and 6.4 kJ g-1 of energy for the transition from the amorphous to the crystalline state for the starch granules with phosphorus contents of 0; 0.015; 0.092 and 0.397%, respectively. Cluster analysis and principal component analysis showed that starches with 0.015 and 0.092% phosphorus have similar characteristics and are different from the others. Our results show that the characteristics of phosphate modified S. lycocarpum starch have optimal conditions to meet the demands of raw materials, which require greater consistency in stickiness, combined with low rates of retrogradation and syneresis.

Multiple centroid method to evaluate the adaptability of alfalfa genotypes

This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.). In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data). In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.

Burn wood influence on outdoor air quality in a small village: Foros de Arrão, Portugal

One Plus Sequential Air Sampler—Partisol was placed in a small village (Foros de Arrão) in central Portugal to collect PM10 (particles with an aerodynamic diameter below 10 μm), during the winter period for 3 months (December 2009–March 2010). Particles masses were gravimetrically determined and the filters were analyzed by instrumental neutron activation analysis to assess their chemical composition. The water-soluble ion compositions of the collected particles were determined by Ion-exchange Chromatography. Principal component analysis was applied to the data set of chemical elements and soluble ions to assess the main sources of the air pollutants. The use of both analytical techniques provided information about elemental solubility, such as for potassium, which was important to differentiate sources.

Estudo da qualidade organizacional da unidade de rastreio da retinopatia diabética do Alentejo central: projecto de intervenção comunitária em saúde

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Gestão e Administração dos Serviços de Saúde.

Impact of maritime air mass trajectories on the Western European coast urban aerosol

Lisbon is the largest urban area in the Western European coast. Due to this geographical position the Atlantic Ocean serves as an important source of particles and plays an important role in many atmospheric processes. The main objectives of this study were to (1) perform a chemical characterization of particulate matter (PM2.5) sampled in Lisbon, (2) identify the main sources of particles, (3) determine PM contribution to this urban area, and (4) assess the impact of maritime air mass trajectories on concentration and composition of respirable PM sampled in Lisbon. During 2007, PM2.5 was collected on a daily basis in the center of Lisbon with a Partisol sampler. The exposed Teflon filters were measured by gravimetry and cut into two parts: one for analysis by instrumental neutron activation analysis (INAA) and the other by ion chromatography (IC). Principal component analysis (PCA) and multilinear regression analysis (MLRA) were used to identify possible sources of PM2.5 and determine mass contribution. Five main groups of sources were identified: secondary aerosols, traffic, calcium, soil, and sea. Four-day backtracking trajectories ending in Lisbon at the starting sampling time were calculated using the HYSPLIT model. Results showed that maritime transport scenarios were frequent. These episodes were characterized by a significant decrease of anthropogenic aerosol concentrations and exerted a significant role on air quality in this urban area.

Fungos endofíticos em Eugenia brasiliensis: prospecção química, biológica, enzimática e avaliação do co-cultivo e epigenética em Xylaria cubensis, Diaporthe sp. e Colletotrichum sp.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação dos comportamentos de pastejo e suas relações com caracteres individuais dos bovinos de corte

Pós-graduação em Zootecnia - FCAV

Modelo de data mining para detecção de tumores em exames de rastreio

Dissertação para obtenção do grau de Mestre em Engenharia Informática