Comparison of oxidative stress markers in HIV-infected patients on efavirenz or atazanavir/ritonavir-based therapy.

INTRODUCTION Chronic low-grade inflammation and immune activation may persist in HIV patients despite effective antiretroviral therapy (ART). These abnormalities are associated with increased oxidative stress (OS). Bilirubin (BR) may have a beneficial role in counteracting OS. Atazanavir (ATV) inhibits UGT1A1, thus increasing unconjugated BR levels, a distinctive feature of this drug. We compared changes in OS markers in HIV patients on ATV/r versus efavirenz (EFV)-based first-line therapies. MATERIALS AND METHODS Cohort of the Spanish Research Network (CoRIS) is a multicentre, open, prospective cohort of HIV-infected patients naïve to ART at entry and linked to a biobank. We identified hepatitis C virus/hepatitis B virus (HCV/HBV) negative patients who started first-line ART with either ATV/r or EFV, had a baseline biobank sample and a follow-up sample after at least nine months of ART while maintaining initial regimen and being virologically suppressed. Lipoprotein-associated Phospholipase A2 (Lp-PLA2), Myeloperoxidase (MPO) and Oxidized LDL (OxLDL) were measured in paired samples. Marker values at one year were interpolated from available data. Multiple imputations using chained equations were used to deal with missing values. Change in the OS markers was modelled using multiple linear regressions adjusting for baseline marker values and baseline confounders. Correlations between continuous variables were explored using Pearson's correlation tests. RESULTS 145 patients (97 EFV; 48 ATV/r) were studied. Mean (SD) baseline values for OS markers in EFV and ATV/r groups were: Lp-PLA2 [142.2 (72.8) and 150.1 (92.8) ng/mL], MPO [74.3 (48.2) and 93.9 (64.3) µg/L] and OxLDL [76.3 (52.3) and 82.2 (54.4) µg/L]. After adjustment for baseline variables patients on ATV/r had a significant decrease in Lp-PLA2 (estimated difference -16.3 [CI 95%: -31.4, -1.25; p=0.03]) and a significantly lower increase in OxLDL (estimated difference -21.8 [-38.0, -5.6; p<0.01] relative to those on EFV, whereas no differences in MPO were found. Adjusted changes in BR were significantly higher for the ATV/r group (estimated difference 1.33 [1.03, 1.52; p<0.01]). Changes in BR and changes in OS markers were significantly correlated. CONCLUSIONS In virologically suppressed patients on stable ART, OS was lower in ATV/r-based regimens compared to EFV. We hypothesize these changes could be in part attributable to increased BR plasma levels.

Relación entre la edad, el índice de masa corporal, el grado de dependencia y la calidad de vida en pacientes con desnutrición tras un alta hospitalaria.

Introduction: The quality of life assessment means investigating how patients perceive their disease. Malnutrition-specific characteristics make patients more vulnerable, so it is important to know how these factors impaction patients’ daily life. Aim: To assess the quality of life in malnourished patients who have had hospital admission, and to determine the relationship of the quality of life with age, body mass index, diagnosis of malnutrition, and dependency. Method: Multicenter transversal descriptive study in 106 malnourished patients after hospital admission. The quality of life (SF-12 questionnaire), BMI, functional independency (Barthel index), morbidity, and a dietary intake evaluation were assessed. The relationship between variables was tested by using the Spearman correlation coefficient Results: The patients of the present study showed a SF-12 mean of 38.32 points. The age was significantly correlated with the SF-12 (r= -0.320, p= 0.001). The BMI was correlated with the SF-12 (r= 0.251, p= 0.011) and its mental component (r= 0.289, p= 0.03). It was also reported a significant correlation between the Barthel index and the SF-12 (r= 0.370, p< 0.001). Conclusions: The general health perception in malnourished patients who have had a hospital admission was lower than the Spanish mean. Moreover, the quality of life in these patients is significantly correlated with age, BMI and functional independency.

Protocolo de investigación del atlas de mortalidad de las capitales de provincia de Andalucía y Cataluña (Proyecto AMCAC).

The aim of this work is to make known the multicentric project AMCAC, whose objective is to describe the geographical distribution of mortality from all causes in census groups of the provincial capitals of Andalusia and Catalonia during 1992-2002 and 1994-2000 respectively, and to study the relationship between the sociodemographic characteristics of the census groups and mortality. This is an ecological study in which the analytical unit is the census group. The data correspond to 298,731 individuals (152,913 men and 145,818 women) who died during the study periods in the towns of Almeria, Barcelona, Cadiz, Cordoba, Girona, Granada, Huelva, Jaen, Lleida, Malaga, Seville and Tarragona during the study periods. The dependent variable is the number of deaths observed per census group. The independent variables are the percentage of unemployment, illiteracy and manual workers. Estimation of the moderated relative risk and the study of the associations among the sociodemographic characteristics of the census groups and the mortality will be done for each town and each sex using the Besag-York-Mollie model. Dissemination of the results will help to improve and broaden knowledge about the population's health, and will provide an important starting point to establish the influence of contextual variables on the health of urban populations.

Predictors of return to work after a knee injury in patients hospitalized in vocational rehabilitation

Introduction.- Knee injuries are frequent in a young and active population. Most of the patients resume their professional activity but few studies were interested in factors that predict a return to work. The aim of this study is to identify these predictors from a large panel of bio-psychosocial variables. We postulated that the return to work 3 months and 2 years after discharge is mostly predicted by psychosocial variables.Patients and methods.- Prospective study, patients hospitalized for a knee injury. Variables measured: the abbreviated injury score (AIS) for the gravity of the injuries, analog visual scale for the intensity of pain, INTERMED for the bio-psychosocial complexity, SF-36 for the quality of life, HADs for the anxiety/depression symptoms and IKDC score for the knee function. Univariate logistic regressions, adjusted for age and gender, were performed in order to predict return to work.Results.- One hundred and twenty-six patients hospitalized during 8 months after the accident were included into this prospective study. A total of 73 (58%) and 75 (59%) questionnaires were available after 3 months and 2 years, respectively. The SF-36 pain was the sole predictor of return to work at 3 months (odds Ratio 1.06 [1.02-1.10], P = 0.01; for a one point increase) and 2 years (odds Ratio 1.06 [1.02-1.10], P = 0.01). At three months, other factors are SF-36 (physic sub-scale), IKDC score, the presence of a work contract and the presence of litigation. The bio-psychosocial complexity, the presence of depressive symptoms predicts the return to work at two years.Discussion.- Our working hypothesis was partially confirmed: some psychosocial factors (i.e. depressive symptoms, work contract, litigation, INTERMED) predict the return to work but the physical health and the knee function, perceived by the patient, are also correlated. Pain is the sole factor isolated at both times (i.e. 3 months and 2 years) and, consequently, appears a key element in the prediction of the return to work. Some factors are accessible to the rehabilitation program but only if an interdisciplinary approach is performed.

Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by asimplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able togenerate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow definingmonitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

Horizontal, but not vertical, biotic interactions affect fine-scale plant distribution patterns in a low-energy system

Studies of species range determinants have traditionally focused on abiotic variables (typically climatic conditions), and therefore the recent explicit consideration of biotic interactions represents an important advance in the field. While these studies clearly support the role of biotic interactions in shaping species distributions, most examine only the influence of a single species and/or a single interaction, failing to account for species being subject to multiple concurrent interactions. By fitting species distribution models (SDMs), we examine the influence of multiple vertical (i.e., grazing, trampling, and manuring by mammalian herbivores) and horizontal (i.e., competition and facilitation; estimated from the cover of dominant plant species) interspecific interactions on the occurrence and cover of 41 alpine tundra plant species. Adding plant-plant interactions to baseline SDMs (using five field-quantified abiotic variables) significantly improved models' predictive power for independent data, while herbivore-related variables had only a weak influence. Overall, abiotic variables had the strongest individual contributions to the distribution of alpine tundra plants, with the importance of horizontal interaction variables exceeding that of vertical interaction variables. These results were consistent across three modeling techniques, for both species occurrence and cover, demonstrating the pattern to be robust. Thus, the explicit consideration of multiple biotic interactions reveals that plant-plant interactions exert control over the fine-scale distribution of vascular species that is comparable to abiotic drivers and considerably stronger than herbivores in this low-energy system.

Disruption of GIP/GIPR axis in human adipose tissue is linked to obesity and insulin resistance.

CONTEXT Glucose-dependent insulinotropic peptide (GIP) has a central role in glucose homeostasis through its amplification of insulin secretion; however, its physiological role in adipose tissue is unclear. OBJECTIVE Our objective was to define the function of GIP in human adipose tissue in relation to obesity and insulin resistance. DESIGN GIP receptor (GIPR) expression was analyzed in human sc adipose tissue (SAT) and visceral adipose (VAT) from lean and obese subjects in 3 independent cohorts. GIPR expression was associated with anthropometric and biochemical variables. GIP responsiveness on insulin sensitivity was analyzed in human adipocyte cell lines in normoxic and hypoxic environments as well as in adipose-derived stem cells obtained from lean and obese patients. RESULTS GIPR expression was downregulated in SAT from obese patients and correlated negatively with body mass index, waist circumference, systolic blood pressure, and glucose and triglyceride levels. Furthermore, homeostasis model assessment of insulin resistance, glucose, and G protein-coupled receptor kinase 2 (GRK2) emerged as variables strongly associated with GIPR expression in SAT. Glucose uptake studies and insulin signaling in human adipocytes revealed GIP as an insulin-sensitizer incretin. Immunoprecipitation experiments suggested that GIP promotes the interaction of GRK2 with GIPR and decreases the association of GRK2 to insulin receptor substrate 1. These effects of GIP observed under normoxia were lost in human fat cells cultured in hypoxia. In support of this, GIP increased insulin sensitivity in human adipose-derived stem cells from lean patients. GIP also induced GIPR expression, which was concomitant with a downregulation of the incretin-degrading enzyme dipeptidyl peptidase 4. None of the physiological effects of GIP were detected in human fat cells obtained from an obese environment with reduced levels of GIPR. CONCLUSIONS GIP/GIPR signaling is disrupted in insulin-resistant states, such as obesity, and normalizing this function might represent a potential therapy in the treatment of obesity-associated metabolic disorders.

Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin.

Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population.

BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

An ex-post view of inequality of opportunity in France and its regions

This paper proposes an ex-post measure of inequality of opportunity in France and its regions by assessing the inequality between individuals exerting the same effort. To this end, we define a fair income that fulfils ex-post equality of opportunity requirements. Unfairness is measured by an unfair Gini based on the distance between the actual income and the fair income. Our findings reveal that the measures of ex-post inequality of opportunity largely vary across regions, and that this is due to di_erences in reward schemes and in the impact of the non responsibility factors of income. We find that most regions have actual incomes closer to fair incomes than to average income, excepted Ile de France where the actual income looks poorly related to effort variables. Finally, we find that income inequality and inequality of opportunity are positively correlated among regions.

Experimental plant communities develop phylogenetically overdispersed abundance distributions during assembly

The importance of competition between similar species in driving community assembly is much debated. Recently, phylogenetic patterns in species composition have been investigated to help resolve this question: phylogenetic clustering is taken to imply environmental filtering, and phylogenetic overdispersion to indicate limiting similarity between species. We used experimental plant communities with random species compositions and initially even abundance distributions to examine the development of phylogenetic pattern in species abundance distributions. Where composition was held constant by weeding, abundance distributions became overdispersed through time, but only in communities that contained distantly related clades, some with several species (i.e., a mix of closely and distantly related species). Phylogenetic pattern in composition therefore constrained the development of overdispersed abundance distributions, and this might indicate limiting similarity between close relatives and facilitation/complementarity between distant relatives. Comparing the phylogenetic patterns in these communities with those expected from the monoculture abundances of the constituent species revealed that interspecific competition caused the phylogenetic patterns. Opening experimental communities to colonization by all species in the species pool led to convergence in phylogenetic diversity. At convergence, communities were composed of several distantly related but species-rich clades and had overdispersed abundance distributions. This suggests that limiting similarity processes determine which species dominate a community but not which species occur in a community. Crucially, as our study was carried out in experimental communities, we could rule out local evolutionary or dispersal explanations for the patterns and identify ecological processes as the driving force, underlining the advantages of studying these processes in experimental communities. Our results show that phylogenetic relations between species provide a good guide to understanding community structure and add a new perspective to the evidence that niche complementarity is critical in driving community assembly.

The relevance of the Laplacian of intracule and extracule density distributions for analyzing electron-electron interactions in molecules

A topological analysis of intracule and extracule densities and their Laplacians computed within the Hartree-Fock approximation is presented. The analysis of the density distributions reveals that among all possible electron-electron interactions in atoms and between atoms in molecules only very few are located rigorously as local maxima. In contrast, they are clearly identified as local minima in the topology of Laplacian maps. The conceptually different interpretation of intracule and extracule maps is also discussed in detail. An application example to the C2H2, C2H4, and C2H6 series of molecules is presented

Electron localization function at the correlated level

The electron localization function (ELF) has been proven so far a valuable tool to determine the location of electron pairs. Because of that, the ELF has been widely used to understand the nature of the chemical bonding and to discuss the mechanism of chemical reactions. Up to now, most applications of the ELF have been performed with monodeterminantal methods and only few attempts to calculate this function for correlated wave functions have been carried out. Here, a formulation of ELF valid for mono- and multiconfigurational wave functions is given and compared with previous recently reported approaches. The method described does not require the use of the homogeneous electron gas to define the ELF, at variance with the ELF definition given by Becke. The effect of the electron correlation in the ELF, introduced by means of configuration interaction with singles and doubles calculations, is discussed in the light of the results derived from a set of atomic and molecular systems