Evaluation of direct analysis for trace elements in tea and herbal beverages by ICP-MS

In general, inductively coupled plasma mass spectrometry (ICP-MS) food analysis requires numerous sample treatment steps that imply an increase of analysis time and the use of chemicals. In this study, the main objective was to evaluate the applicability of the direct analysis by ICP-MS to determine twelve elements (Al, As, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se and Zn) in tea and herbal beverages. Direct analysis method was compared with two other sample treatments: minimum treatment (acid dilution) and using a destructive method (microwave assisted digestion). Besides the lowest time of analysis, direct analysis provides a reliable response and agrees with the “green chemistry” principles. High sensitivity was also observed by low values of limits of detection and quantification, in general, below 2.5 µg L-1. The method accuracy was evaluated by spiked experiments and values ranged between 82 and 120%. Low values of coefficient of variation were also observed, 2 to 17%, for all analytes. The method exhibited applicability for commercial tea samples as well as for drinks made by herb infusion26612111217CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informaçãosem informação2012/19142-

A comprehensive investigation of the mineral composition of brazilian bee pollen: geographic and seasonal variations and contribution to human diet

The mineral composition of bee pollen was investigated in 154 samples from different Brazilian regions. Ca, Cu, Fe, K, Mg, Mn, Na, P, Se and Zn were determined by ICP OES after microwave mineralization. Employing optimized instrumental parameters, the method was shown to have a good precision and accuracy for the simultaneous determination of minerals. Overall, samples from the Northeastern states presented significantly higher amounts of minerals and showed constant production throughout the year. Manganese, Se, Cu, Zn and Fe were the elements that showed the greatest possible contributions to the diet, contributing with 70, 37, 27, 17 and 17%, respectively, of the Brazilian recommended daily intake. Principal component analysis (PCA) was applied to study geographic effects. The elements Ca, Cu, Fe, K, Mg, Mn, Na, P and Zn were important in explaining the classification of pollen according to their geographical origin. The mineral levels varied widely during the year.A composição de minerais foi investigada em 154 amostras de pólen apícola, provenientes de diferentes regiões do Brasil. A técnica de ICP OES foi utilizada para determinar Ca, Cu, Fe, K, Mg, Mn, Na, P, Se e Zn, após mineralização em sistema de microondas. Utilizando parâmetros instrumentais otimizados conseguiu-se boa exatidão e precisão na determinação simultânea dos minerais. Em geral, as amostras dos estados do Nordeste apresentaram teores de minerais mais elevados e produção constante durante o ano. Os minerais Mn, Se, Cu, Zn, Fe são os que poderiam ter maior contribuição na dieta, podendo atingir 70, 37, 27, 17 e 17%, respectivamente, da ingestão dietética diária recomendada no Brasil. A análise de componentes principais mostrou que Ca, Cu, Fe, K, Mg, Mn, Na, P e Zn podem ser usados na classificação do pólen nacional em função da origem geográfica. Os teores dos minerais variaram amplamente ao longo do ano.727736Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Iron-binding properties of sugar cane yeast peptides

AbstractThe extract of sugar-cane yeast (Saccharomyces cerevisiae) was enzymatically hydrolysed by Alcalase, Protex or Viscozyme. Hydrolysates were fractionated using a membrane ultrafiltration system and peptides smaller than 5kDa were evaluated for iron chelating ability through measurements of iron solubility, binding capacity and dialyzability. Iron-chelating peptides were isolated using immobilized metal affinity chromatography (IMAC). They showed higher content of His, Lys, and Arg than the original hydrolysates. In spite of poor iron solubility, hydrolysates of Viscozyme provided higher iron dialyzability than those of other enzymes. This means that more chelates of iron or complexes were formed and these kept the iron stable during simulated gastro-intestinal digestion in vitro, improving its dialyzability

A comprehensive investigation of the mineral composition of brazilian bee pollen: geographic and seasonal variations and contribution to human diet

The mineral composition of bee pollen was investigated in 154 samples from different Brazilian regions. Ca, Cu, Fe, K, Mg, Mn, Na, P, Se and Zn were determined by ICP OES after microwave mineralization. Employing optimized instrumental parameters, the method was shown to have a good precision and accuracy for the simultaneous determination of minerals. Overall, samples from the Northeastern states presented significantly higher amounts of minerals and showed constant production throughout the year. Manganese, Se, Cu, Zn and Fe were the elements that showed the greatest possible contributions to the diet, contributing with 70, 37, 27, 17 and 17%, respectively, of the Brazilian recommended daily intake. Principal component analysis (PCA) was applied to study geographic effects. The elements Ca, Cu, Fe, K, Mg, Mn, Na, P and Zn were important in explaining the classification of pollen according to their geographical origin. The mineral levels varied widely during the year

Global Conservation Priorities for Marine Turtles

Where conservation resources are limited and conservation targets are diverse, robust yet flexible priority-setting frameworks are vital. Priority-setting is especially important for geographically widespread species with distinct populations subject to multiple threats that operate on different spatial and temporal scales. Marine turtles are widely distributed and exhibit intra-specific variations in population sizes and trends, as well as reproduction and morphology. However, current global extinction risk assessment frameworks do not assess conservation status of spatially and biologically distinct marine turtle Regional Management Units (RMUs), and thus do not capture variations in population trends, impacts of threats, or necessary conservation actions across individual populations. To address this issue, we developed a new assessment framework that allowed us to evaluate, compare and organize marine turtle RMUs according to status and threats criteria. Because conservation priorities can vary widely (i.e. from avoiding imminent extinction to maintaining long-term monitoring efforts) we developed a “conservation priorities portfolio” system using categories of paired risk and threats scores for all RMUs (n = 58). We performed these assessments and rankings globally, by species, by ocean basin, and by recognized geopolitical bodies to identify patterns in risk, threats, and data gaps at different scales. This process resulted in characterization of risk and threats to all marine turtle RMUs, including identification of the world's 11 most endangered marine turtle RMUs based on highest risk and threats scores. This system also highlighted important gaps in available information that is crucial for accurate conservation assessments. Overall, this priority-setting framework can provide guidance for research and conservation priorities at multiple relevant scales, and should serve as a model for conservation status assessments and priority-setting for widespread, long-lived taxa

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

Background: Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques - including site-based monitoring, genetic analyses, mark-recapture studies and telemetry - can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings: To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine-to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance: The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework - including maps and supporting metadata - will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries