3,134 publications from this institution
[This corrects the article DOI: 10.3389/fmicb.2021.646101.].
Endosulfan is a potentially harmful, degradation resistant pesticide that is found in soils where it has been used. Despite being hydrophobic and having high affinity for soil matrix components, it has also been found in groundwater. To investigate this behavior, we studied the passage of a commercial emulsified formulation through a column of aggregated vineyard soil under simulated light rain. Breakthrough data were obtained using gas chromatography with electron capture detection to determine the concentration of endosulfan in samples extracted from the column periodically at several depths. These data, and analogous data obtained previously for the passage of bromide, were analyzed using the program CXTFIT v.2. Analysis of the bromide data strongly suggested the existence of preferential flow paths in the column. The endosulfan data were adequately accounted for by a model in which the preferential flow and nonpreferential flow regions are almost isolated from each other. These regions differ also as regards both the partition of endosulfan between soil and soil solution and the rate at which reversibly adsorbed endosulfan is transformed into irreversibly adsorbed endosulfan. The "irreversibility" sink term accounts also for biological and chemical degradation of endosulfan. The findings imply that soil humidity favors the transport of commercial endosulfan by the formation and maintenance of preferential flow paths in soil, controlling both the presence of endosulfan in groundwater and its high persistence in soil.
Existing knowledge on the mechanisms behind polyphenol-protein reactions, the structures of the resulting products and their potential uses is reviewed.
Abstract We investigate the sources of bias that affect the most commonly used methods of estimation of the average degree of dominance (h) of deleterious mutations, focusing on estimates from segregating populations. The main emphasis is on the effect of the finite size of the populations, but other sources of bias are also considered. Using diffusion approximations to the distribution of gene frequencies in finite populations as well as stochastic simulations, we assess the behavior of the estimators obtained from populations at mutation-selection-drift balance under different mutational scenarios and compare averages of h for newly arisen and segregating mutations. Because of genetic drift, the inferences concerning newly arisen mutations based on the mutation-selection balance theory can have substantial upward bias depending upon the distribution of h. In addition, estimates usually refer to h weighted by the homozygous deleterious effect in different ways, so that inferences are complicated when these two variables are negatively correlated. Due to both sources of bias, the widely used regression of heterozygous on homozygous means underestimates the arithmetic mean of h for segregating mutations, in contrast to their repeatedly assumed equality in the literature. We conclude that none of the estimators from segregating populations provides, under general conditions, a useful tool to ascertain the properties of the degree of dominance, either for segregating or for newly arisen deleterious mutations. Direct estimates of the average h from mutation-accumulation experiments are shown to suffer some bias caused by purging selection but, because they do not require assumptions on the causes maintaining segregating variation, they appear to give a more reliable average dominance for newly arisen mutations.
Sleep-time BP is the most significant independent prognostic marker of cardiovascular events in diabetes. Most important, decreasing sleep-time BP, a novel therapeutic target requiring proper patient evaluation by ambulatory monitoring, was the most significant independent predictor of event-free survival in diabetes.
A simple, rapid and inexpensive method has been developed for the determination of benzo[a]pyrene (B(a)P, a known carcinogen) in foods with a high fat content. In-house validation was carried out by checking B(a)P recovery +/- precision from those samples by a simple spiking procedure. The method involves extracting the fat from a freeze-dried product and the saponification of the B(a)P-containing lipid fraction assisted by microwave energy. After partitioning in hexane, and purification by passage through a silica cartridge, the B(a)P-containing hexane eluate is analysed by second derivative synchronous spectrofluorimetry. The method was found to have a recovery of 90 +/- 5%. The detection and quantification limits in food (0.05 and 0.12 microgram/kg, respectively) indicate that the B(a)P maximum that the European Union (EU) intends to set for foods (1 microgram/kg), can be monitored by this method.
jModelTest is a bioinformatic tool for choosing among different models of nucleotide substitution. The program implements five different model selection strategies, including hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a performance-based decision theory method (DT). The output includes estimates of model selection uncertainty, parameter importance, and model-averaged parameter estimates, including model-averaged phylogenies. jModelTest is a Java program that runs under Mac OSX, Windows, and Unix systems with a Java Run Environment installed, and it can be freely downloaded from (http://darwin.uvigo.es).
The term "Nanocrystal Engineering" can be defined as the design and synthesis of nanocrystals with desired morphologies and compositions based on understanding and exploitation of the nucleation and growth process. It is a key process in advancing the applications of nanomaterials including biosensing, catalysis, photonics, electronics and photovoltaics. As compared to the accomplishments of organic synthesis, we are still far from the complete understanding and experimental control over the synthesis of nanocrystals with well-defined morphology. However, the last two decades of research have resulted in excellent control over the morphology and composition of noble metal and metal chalcogenide nanocrystals. In this Highlight article, we summarize various standard protocols and recent advances for the shape-controlled synthesis of such nanocrystals. From the discussion in this article, it is clear that significant progress has been made toward the design and synthesis of nanocrystals with desired shape, crystallinity and composition by controlling the nucleation and growth process using specific synthetic protocols. We hope that this Highlight article will help researchers to follow some general rules to engineer the morphology and composition of noble metal and metal chalcogenide nanocrystals to maximise their efficiency for various applications.
