Four cypermethrin isomers induced stereoselective metabolism in H295R cells

Cypermethrin (CP) is widely used for controlling agricultural and indoor vermin. Previous studies have reported the stereoselective difference of CP in biological activities. However, little is known about their potential mechanisms between metabolic phenotypes and endocrine-disrupting effects. Herein, nuclear magnetic resonance (NMR)-based metabolomics combining metabolite identification and pathway analysis were applied to evaluate the stereoselective metabolic cdisorders induced by CP isomers in human adrenocortical carcinoma cells (H295R) culture medium. Then, gene expression levels related to disturbed metabolic pathways were assessed to verify according to metabolic phenotypes. Metabolomics profiles showed that [(S)-cyano(3-phenoxyphenyl)methyl](1R,3R)-3-(2,2-dichloroethenyl)-2,2-dimethylcyclopropane-1-carboxylate [(1R,3R,αS)-CP] induced the most significant changes in metabolic phenotypes than did the other stereoisomers. There are 10 differential metabolites (isoleucine, valine, leucine, ethanol, alanine, acetate, aspartate, arginine, lactate, and glucose) as well as two significantly disturbed pathways, including “pyruvate metabolism” and “alanine, aspartate, and glutamate metabolism,” that were confirmed in H295R cells culture medium of (1R,3R,αS)-CP compared with other stereoisomers. Polymerase chain reaction (PCR) array also confirmed the results of metabolomics. Our results can help to understand the potential mechanisms between the isomer selectivity in metabolic phenotypes and endocrine-disrupting effects. Data provided here not only lend authenticity to the cautions issued by the scientists and researchers but also offer a solution for the balance between environment and political regulations.     

Effect of woody plant expansion on decomposition of fine root mixtures in a grass-dominated temperate wetland

Wetlands Ecology and Management - Little is known about the effect of woody plant expansion on decomposition of root mixtures in grass-dominant temperate wetlands. Here, we collected fine roots...     

A comparison of diversity estimators applied to a database of host–parasite associations

Understanding the drivers of biodiversity is important for forecasting changes in the distribution of life on earth. However, most studies of biodiversity are limited by uneven sampling effort, with some regions or taxa better sampled than others. Numerous methods have been developed to account for differences in sampling effort, but most methods were developed for systematic surveys in which all study units are sampled using the same design and assemblages are sampled randomly. Databases compiled from multiple sources, such as from the literature, often violate these assumptions because they are composed of studies that vary widely in their goals and methods. Here, we compared the performance of several popular methods for estimating parasite diversity based on a large and widely used parasite database, the Global Mammal Parasite Database (GMPD). We created artificial datasets of host–parasite interactions based on the structure of the GMPD, then used these datasets to evaluate which methods best control for differential sampling effort. We evaluated the precision and bias of seven methods, including species accumulation and nonparametric diversity estimators, compared to analyzing the raw data without controlling for sampling variation. We find that nonparametric estimators, and particularly the Chao2 and second-order jackknife estimators, perform better than other methods. However, these estimators still perform poorly relative to systematic sampling, and effect sizes should be interpreted with caution because they tend to be lower than actual effect sizes. Overall, these estimators are more effective in comparative studies than for producing true estimates of diversity. We make recommendations for future sampling strategies and statistical methods that would improve estimates of global parasite diversity.