Physical inactivity and associated factors in elderly people in Brazil

El objetivo fue analizar los factores asociados a la inactividad física en personas mayores en Brasil. Se utilizó un diseño transversal, con una muestra representativa de 909 sujetos de 60 años o más. Fueron clasificados como físicamente inactivos los individuos con menos de 150 minutos de actividad física semanal. La identificación de los factores sociodemográficos, aspectos comportamentales y de salud asociados con la inactividad física se realizó con un análisis multivariante a través de una regresión de Poisson Los resultados sugieren una prevalencia del 39,1% para la inactividad física. La inactividad física presenta una mayor prevalente con o el incremento de la edad, la falta de práctica de actividad física regular en el pasado, los síntomas de depresión y la discapacidad en las Actividades Instrumentales de la Vida Diaria. El aumento de la edad, la falta de práctica regular de actividad física en el pasado, los síntomas depresivos y la discapacidad en las Actividades Instrumentales de la Vida Diaria se evidencian como factores asociados a la inactividad física.The aim was to analyse factors associated with physical inactivity in elderly Brazilians. The study was carried out by using a cross-sectional design and it comprised a representative sample of 909 subjects. Physical inactivity was defined as fewer than 150 minutes per week. In order to identify socio-demographic factors and behavioural and health aspects, which may be associated with physical inactivity, we carried out a multivariate analysis through the Poisson regression. Results suggest that physical inactivity has a prevalence of 39.1%. Physical inactivity presents a higher prevalence with an increase in age, a lack of regular physical activity practice in the past, depressive symptoms and disability in the instrumental activities of daily living. An increase in age, a lack of regular physical activity practice in the past, depressive symptoms and disability in the instrumental activities of daily living are shown as causes of physical inactivit

RAB8, RAB10 and RILPL1 contribute to both LRRK2 kinase-mediated centrosomal cohesion and ciliogenesis deficits

Mutations in the LRRK2 kinase are the most common cause of familial Parkinson's disease, and variants increase risk for the sporadic form of the disease. LRRK2 phosphorylates multiple RAB GTPases including RAB8A and RAB10. Phosphorylated RAB10 is recruited to centrosome-localized RILPL1, which may interfere with ciliogenesis in a disease-relevant context. Our previous studies indicate that the centrosomal accumulation of phosphorylated RAB8A causes centrosomal cohesion deficits in dividing cells, including in peripheral patient-derived cells. Here, we show that both RAB8 and RAB10 contribute to the centrosomal cohesion deficits. Pathogenic LRRK2 causes the centrosomal accumulation not only of phosho-RAB8 but also of phospho-RAB10, and the effects on centrosomal cohesion are dependent on RAB8, RAB10 and RILPL1. Conversely, the pathogenic LRRK2-mediated ciliogenesis defects correlate with the centrosomal accumulation of both phospho-RAB8 and phospho-RAB10. LRRK2-mediated centrosomal cohesion and ciliogenesis alterations are observed in patient-derived peripheral cells, as well as in primary astrocytes from mutant LRRK2 mice, and are reverted upon LRRK2 kinase inhibition. These data suggest that the LRRK2-mediated centrosomal cohesion and ciliogenesis defects are distinct cellular readouts of the same underlying phospho-RAB8/RAB10/RILPL1 nexus and highlight the possibility that either centrosomal cohesion and/or ciliogenesis alterations may serve as cellular biomarkers for LRRK2-related PD

The plant traits that drive ecosystems: Evidence from three continents.

Question: A set of easily‐measured (‘soft’) plant traits has been identified as potentially useful predictors of ecosystem functioning in previous studies. Here we aimed to discover whether the screening techniques remain operational in widely contrasted circumstances, to test for the existence of axes of variation in the particular sets of traits, and to test for their links with ‘harder’ traits of proven importance to ecosystem functioning. Location: central‐western Argentina, central England, northern upland Iran, and north‐eastern Spain. Recurrent patterns of ecological specialization: Through ordination of a matrix of 640 vascular plant taxa by 12 standardized traits, we detected similar patterns of specialization in the four floras. The first PCA axis was identified as an axis of resource capture, usage and release. PCA axis 2 appeared to be a size‐related axis. Individual PCA for each country showed that the same traits remained valuable as predictors of resource capture and utilization in all of them, despite their major differences in climate, biogeography and land‐use. The results were not significantly driven by particular taxa: the main traits determining PCA axis 1 were very similar in eudicotyledons and monocotyledons and Asteraceae, Fabaceae and Poaceae. Links between recurrent suites of ‘soft’ traits and ‘hard’ traits: The validity of PCA axis 1 as a key predictor of resource capture and utilization was tested by comparisons between this axis and values of more rigorously established predictors (‘hard’ traits) for the floras of Argentina and England. PCA axis 1 was correlated with variation in relative growth rate, leaf nitrogen content, and litter decomposition rate. It also coincided with palatability to model generalist herbivores. Therefore, location on PCA axis 1 can be linked to major ecosystem processes in those habitats where the plants are dominant. Conclusion: We confirm the existence at the global scale of a major axis of evolutionary specialization, previously recognised in several local floras. This axis reflects a fundamental trade‐off between rapid acquisition of resources and conservation of resources within well‐protected tissues. These major trends of specialization were maintained across different environmental situations (including differences in the proximate causes of low productivity, i.e. drought or mineral nutrient deficiency). The trends were also consistent across floras and major phylogenetic groups, and were linked with traits directly relevant to ecosystem processes.Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Hodgson, J.G.. The University. Department of Animal and Plant Sciences. Unit of Comparative Plant Ecology; Reino UnidoFil: Thompson, K.. The University. Department of Animal and Plant Sciences. Unit of Comparative Plant Ecology; Reino UnidoFil: Cabido, Marcelo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Cornelissen, Johannes H. C.. Free University. Faculty Earth and Life Sciences. Department of Systems Ecology; Países BajosFil: Funes, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Pérez Harguindeguy, Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Vendramini, Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Falczuk, Valeria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Zak, Marcelo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Khoshnevi, M.. Research Institute of Forests and Rangelands; IránFil: Pérez Rontomé, M. C.. Instituto Pirenaico de Ecología; EspañaFil: Shirvani, F. A.. Research Institute of Forests and Rangelands; IránFil: Yazdani, S.. Research Institute of Forests and Rangelands; IránFil: Abbas Azimi, R. Research Institute of Forests and Rangelands; IránFil: Bogaard, A. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Boustani, S.. Research Institute of Forests and Rangelands; IránFil: Charles, M.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Dehghan, M.. Research Institute of Forests and Rangelands; IránFil: de Torres Espuny, L.. Instituto Pirenaico de Ecología; EspañaFil: Guerrero Campo, J.. Instituto Pirenaico de Ecología; EspañaFil: Hynd, A.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Jones, G.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Kowsary, E.. Research Institute of Forests and Rangelands; Irán. Instituto Pirenaico de Ecología; EspañaFil: Kazemi Saeed, F.. Research Institute of Forests and Rangelands; IránFil: Maestro Martínez, M.. Instituto Pirenaico de Ecología; EspañaFil: Romo Diez, A.. Instituto Botanico de Barcelona; EspañaFil: Shaw, S.. Research Institute of Forests and Rangelands; Irán. The University. Department of Animal and Plant Sciences; Reino UnidoFil: Siavash, B.. Research Institute of Forests and Rangelands; IránFil: Villar Salvador, P.. Instituto Pirenaico de Ecología; Españ

Prevalence and socio-demographic correlates of physical activity levels among South African adults in Cape Town and Mount Frere communities in 2008-2009

BACKGROUND: Physical activity has been linked to reduced risk of various cardiometabolic disease, cancer, and premature mortality. We investigated the prevalence and socio-demographic correlates of physical activity among adults in urban and rural communities in South Africa. METHODS: This was a cross-sectional survey comprising 1733 adults aged ?35 years from the Cape Town (urban) and Mount Frere (rural) sites of the Prospective Urban Rural Epidemiology study. Physical activity was assessed using the validated International Physical Activity Questionnaire. Multinomial logistic regressions were used to relate physical activity with socio-demographic characteristics. RESULTS: Overall, 74% of participants engaged in moderate-to-vigorous physical activity. In the adjusted regression models, women were 34% less likely to engage in vigorous physical activity (OR =0.66, 95%-CI = 0.47-0.93). Physical activity decreased with age, varied with marital status, education and occupation, always in differential ways between urban and rural participants (all interactions p ? 0.047). For instance, in urban settings, those with secondary education were more likely to engage in moderate physical activity (OR = 2.06, 95%-CI = 1.08-3.92) than those with tertiary education. Single people were more likely to engage in high physical activity (OR = 2.10, 95%-CI = 1.03-4.28) than divorced. Overall, skilled participants were more likely to engage in vigorous physical activity (OR = 2.07, 95%-CI = 1.41-3.05) driven by significant effect in rural area (OR = 2.70, 95%-CI = 1.51-4.83). Urban participants were more likely to engage in moderate physical activity (OR = 1.67, 95%-CI = 1.31-2.13) than rural participants. CONCLUSIONS: To prevent chronic diseases among South Africans, attention should be paid to specific policies and interventions aimed at promoting PA among young adults in rural and urban setting, and across the social-economic diversity

The NEXT White (NEW) detector

Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation

The additional value of patient-reported health status in predicting 1-year mortality after invasive coronary procedures: A report from the Euro Heart Survey on Coronary Revascularisation

Objective: Self-perceived health status may be helpful in identifying patients at high risk for adverse outcomes. The Euro Heart Survey on Coronary Revascularization (EHS-CR) provided an opportunity to explore whether impaired health status was a predictor of 1-year mortality in patients with coronary artery disease (CAD) undergoing angiographic procedures. Methods: Data from the EHS-CR that included 5619 patients from 31 member countries of the European Society of Cardiology were used. Inclusion criteria for the current study were completion of a self-report measure of health status, the EuroQol Questionnaire (EQ-5D) at discharge and information on 1-year follow-up, resulting in a study population of 3786 patients. Results: The 1-year mortality was 3.2% (n = 120). Survivors reported fewer problems on the five dimensions of the EQ-5D as compared with non-survivors. A broad range of potential confounders were adjusted for, which reached a p<0.10 in the unadjusted analyses. In the adjusted analyses, problems with self-care (OR 3.45; 95% CI 2.14 to 5.59) and a low rating (≤ 60) on health status (OR 2.41; 95% CI 1.47 to 3.94) were the most powerful independent predictors of mortality, among the 22 clinical variables included in the analysis. Furthermore, patients who reported no problems on all five dimensions had significantly lower 1-year mortality rates (OR 0.47; 95% CI 0.28 to 0.81). Conclusions: This analysis shows that impaired health status is associated with a 2-3-fold increased risk of all-cause mortality in patients with CAD, independent of other conventional risk factors. These results highlight the importance of including patients' subjective experience of their own health status in the evaluation strategy to optimise risk stratification and management in clinical practice

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Improved risk stratification of patients with atrial fibrillation: an integrated GARFIELD-AF tool for the prediction of mortality, stroke and bleed in patients with and without anticoagulation.

OBJECTIVES: To provide an accurate, web-based tool for stratifying patients with atrial fibrillation to facilitate decisions on the potential benefits/risks of anticoagulation, based on mortality, stroke and bleeding risks. DESIGN: The new tool was developed, using stepwise regression, for all and then applied to lower risk patients. C-statistics were compared with CHA2DS2-VASc using 30-fold cross-validation to control for overfitting. External validation was undertaken in an independent dataset, Outcome Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF). PARTICIPANTS: Data from 39 898 patients enrolled in the prospective GARFIELD-AF registry provided the basis for deriving and validating an integrated risk tool to predict stroke risk, mortality and bleeding risk. RESULTS: The discriminatory value of the GARFIELD-AF risk model was superior to CHA2DS2-VASc for patients with or without anticoagulation. C-statistics (95% CI) for all-cause mortality, ischaemic stroke/systemic embolism and haemorrhagic stroke/major bleeding (treated patients) were: 0.77 (0.76 to 0.78), 0.69 (0.67 to 0.71) and 0.66 (0.62 to 0.69), respectively, for the GARFIELD-AF risk models, and 0.66 (0.64-0.67), 0.64 (0.61-0.66) and 0.64 (0.61-0.68), respectively, for CHA2DS2-VASc (or HAS-BLED for bleeding). In very low to low risk patients (CHA2DS2-VASc 0 or 1 (men) and 1 or 2 (women)), the CHA2DS2-VASc and HAS-BLED (for bleeding) scores offered weak discriminatory value for mortality, stroke/systemic embolism and major bleeding. C-statistics for the GARFIELD-AF risk tool were 0.69 (0.64 to 0.75), 0.65 (0.56 to 0.73) and 0.60 (0.47 to 0.73) for each end point, respectively, versus 0.50 (0.45 to 0.55), 0.59 (0.50 to 0.67) and 0.55 (0.53 to 0.56) for CHA2DS2-VASc (or HAS-BLED for bleeding). Upon validation in the ORBIT-AF population, C-statistics showed that the GARFIELD-AF risk tool was effective for predicting 1-year all-cause mortality using the full and simplified model for all-cause mortality: C-statistics 0.75 (0.73 to 0.77) and 0.75 (0.73 to 0.77), respectively, and for predicting for any stroke or systemic embolism over 1 year, C-statistics 0.68 (0.62 to 0.74). CONCLUSIONS: Performance of the GARFIELD-AF risk tool was superior to CHA2DS2-VASc in predicting stroke and mortality and superior to HAS-BLED for bleeding, overall and in lower risk patients. The GARFIELD-AF tool has the potential for incorporation in routine electronic systems, and for the first time, permits simultaneous evaluation of ischaemic stroke, mortality and bleeding risks. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF (NCT01090362) and for ORBIT-AF (NCT01165710)