3,134 publications from this institution
A simple and rapid ultrasound-assisted extraction method with hydrochloric acid for mercury speciation in fish tissues was developed. Centrifuged extracts were directly injected into a flow injection-cold vapor atomic absorption spectrometry system. First, methylmercury was separately determined using sodium tetrahydroborate as reducing agent after selective extraction with 2 mol dm –3 hydrochloric acid. Second, inorganic mercury was determined by selective reduction with stannous chloride in 5 mol dm –3 hydrochloric acid extracts containing both mercury species. Total mercury could not be determined in the sonicated acid extracts using sodium tetrahydroborate as reducing agent because the methylmercury and inorganic mercury sensitivities were different. The detection limit was 11 and 5 ng g –1 for methylmercury and inorganic mercury, respectively. The recovery was >92% and the precision (RSD) ranged from 5 to 10% for three replicates of each sample analyzed by the standard additions method. Total mercury, calculated as the sum of methylmercury and inorganic mercury, was in agreement with the total mercury content determined after microwave digestion. The method was validated by means of three fish certified reference materials. The concentrations found were in good agreement with the certified values.
A comprehensive review of the sequential extraction schemes for metal fractionation in environmental samples (ie., sediment, soil, sewage sludge, fly ash, etc.) is presented. The review contains more than 400 references and covers principally the literature published over the last decade. The use of each reagent involved in these schemes is looked at critically, and guidelines for their selectivity and extraction capacity are given. The operational character of these schemes is emphasised. Topics such as comparability between sequential extraction schemes of widespread use, harmonisation, acceleration, validation, etc. are addressed and future developments outlined.
Abstract We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (∼0.03–0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.
The similar circadian phases of plasminogen activator inhibitor antigen in controls and cirrhotic patients in the present investigation indicates that the output rhythm of the internal timekeeping system is not shifted in this pathological condition.
