The HL-60 human promyelocytic cell line constitutes an effective in vitro model for evaluating toxicity, oxidative stress and necrosis/apoptosis after exposure to black carbon particles and 2.45 GHz radio frequency

The cellular and molecular mechanisms by which atmospheric pollution from particulate matter and/or electromagnetic fields (EMFs) may prove harmful to human health have not been extensively researched. We analyzed whether the combined action of EMFs and black carbon (BC) particles induced cell damage and a pro-apoptotic response in the HL-60 promyelocytic cell line when exposed to 2.45 GHz radio frequency (RF) radiation in a gigahertz transverse electromagnetic (GTEM) chamber at sub-thermal specific absorption rate (SAR) levels. RF and BC induced moderately significant levels of cell damage in the first 8 or 24 h for all exposure times/doses and much greater damage after 48 h irradiation and the higher dose of BC. We observed a clear antiproliferative effect that increased with RF exposure time and BC dose. Oxidative stress or ROS production increased with time (24 or 48 h of radiation), BC dose and the combination of both. Significant differences between the proportion of damaged and healthy cells were observed in all groups. Both radiation and BC participated separately and jointly in triggering necrosis and apoptosis in a programmed way. Oxidative-antioxidant action activated mitochondrial anti-apoptotic BCL2a gene expression after 24 h irradiation and exposure to BC. After irradiation of the cells for 48 h, expression of FASR cell death receptors was activated, precipitating the onset of pro-apoptotic phenomena and expression and intracellular activity of caspase-3 in the mitochondrial pathways, all of which can lead to cell death. Our results indicate that the interaction between BC and RF modifies the immune response in the human promyelocytic cell line and that these cells had two fates mediated by different pathways: necrosis and mitochondria-caspase dependent apoptosis. The findings may be important in regard to antimicrobial, inflammatory and autoimmune responses in humansS

Pharmacological Opportunities for Prevention of Preeclampsia

Preeclampsia (PE) is a disorder that occurs during pregnancy, it has an estimated worldwide prevalence of 5–8%, being one of the leading causes of maternal and perinatal morbidity and mortality. Currently, different diagnostic criteria exist, however, due to its complexity; the clinical presentation that makes up this syndrome could make its presence unclear. The pathophysiology of PE has been recently postulated and divided into three processes: inadequate uterine remodeling, placental dysfunction and maternal endothelial dysfunction. Despite the advances in the treatment of PE, the outcome of the medical interventions has failed to decrease the morbidity and mortality of this disease. The main reason might be the multifactorial origin of pathogenic processes that lead to the development of PE. That is why treatment is focused on the prevention of PE in patients that might present the risk before developing it late in pregnancy. The knowledge of the pathophysiological factors that trigger the processes that culminate in the presentation of PE, is key for prevention of this disease. However, the origin of these processes is poorly understood. It may be attributed to the ethical considerations that come with the study of these population of patients compared with the study of non-pregnant women

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Sickness presenteeism in Spanish-born and immigrant workers in Spain

<p>Abstract</p> <p><b>Background</b></p> <p>Previous studies have shown that immigrant workers face relatively worse working and employment conditions, as well as lower rates of sickness absence than native-born workers. This study aims to assess rates of sickness presenteeism in a sample of Spanish-born and foreign-born workers according to different characteristics.</p> <p>Methods</p> <p>A cross-sectional survey was conducted amongst a convenience sample of workers (Spanish-born and foreign-born), living in four Spanish cities: Barcelona, Huelva, Madrid and Valencia (2008-2009). Sickness presenteeism information was collected through two items in the questionnaire ("Have you had health problems in the last year?" and "Have you ever had to miss work for any health problem?") and was defined as worker who had a health problem (answered yes, first item) and had not missed work (answered no, second item). For the analysis, the sample of 2,059 workers (1,617 foreign-born) who answered yes to health problems was included. After descriptives, logistic regressions were used to establish the association between origin country and sickness presenteeism (adjusted odds ratios aOR; 95% confidence interval 95%CI). Analyses were stratified per time spent in Spain among foreign-born workers.</p> <p>Results</p> <p>All of the results refer to the comparison between foreign-born and Spanish-born workers as a whole, and in some categories relating to personal and occupational conditions. Foreign-born workers were more likely to report sickness presenteeism compared with their Spanish-born counterparts, especially those living in Spain for under 2 years [Prevalence: 42% in Spanish-born and 56.3% in Foreign-born; aOR 1.77 95%CI 1.24-2.53]. In case of foreign-born workers (with time in Spain < 2 years), men [aOR 2.31 95%CI 1.40-3.80], those with university studies [aOR 3.01 95%CI 1.04-8.69], temporary contracts [aOR 2.26 95%CI 1.29-3.98] and salaries between 751-1,200€ per month [aOR 1.74 95% CI 1.04-2.92] were more likely to report sickness presenteeism. Also, recent immigrants with good self-perceived health and good mental health were more likely to report presenteeism than Spanish-born workers with the same good health indicators.</p> <p>Conclusions</p> <p>Immigrant workers report more sickness presenteeism than their Spanish-born counterparts. These results could be related to precarious work and employment conditions of immigrants. Immigrant workers should benefit from the same standards of social security, and of health and safety in the workplace that are enjoyed by Spanish workers.</p

State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event

The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P &gt; 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother–child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field

The effect of perceived discrimination on the health of immigrant workers in Spain

Background: Discrimination is an important determinant of health inequalities, and immigrants may be more vulnerable to certain types of discrimination than the native-born. This study analyses the relationship between immigrants' perceived discrimination and various self-reported health indicators. Methods: A cross-sectional survey was conducted (2008) amongst a non-random sample of 2434 immigrants from Ecuador, Morocco, Romania and Colombia in four Spanish cities: Barcelona, Huelva, Madrid and Valencia. A factorial analysis of variables revealed three dimensions of perceived discrimination (due to immigrant status, due to physical appearance, and workplace-related). The association of these dimensions with self-rated health, mental health (GHQ-12), change in self-rated health between origin and host country, and other self-reported health outcomes was analysed. Logistic regression was used adjusting for potential confounders (aOR-95%CI). Subjects with worsening self-reported health status potentially attributable to perceived discrimination was estimated (population attributable proportion, PAP %). Results: 73.3% of men and 69.3% of women immigrants reported discrimination due to immigrant status. Moroccans showed the highest prevalence of perceived discrimination. Immigrants reporting discrimination were at significantly higher risk of reporting health problems than those not reporting discrimination. Workplace-related discrimination was associated with poor mental health (aOR 2.97 95%CI 2.45-3.60), and the worsening of self-rated health (aOR 2.20 95%CI 1.73- 2.80). 40% (95% CI 24-53) PAP of those reporting worse self-rated health could be attributable to discrimination due to immigrant status. Conclusions: Discrimination may constitute a risk factor for health in immigrant workers in Spain and could explain some health inequalities among immigrant populations in Spanish society.This work was supported by the following sources: Carolina Foundation (Spain), Healthcare Research Fund of the Spanish Ministry of Health and Consumption (references PI050497, PI052202, PI052334, PI061701, and PI0790470

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

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)