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Our recent study revealed some early molecular and cellular events in which 17β-estradiol (E2) disrupted testis differentiation and resulted in feminization in Xenopus laevis (the African clawed frog), an ideal species for studying reproductive endocrine disruption by estrogenic endocrine disrupting chemicals (EDCs). On this basis, we aimed to develop multiple biomarkers for early detection of testis differentiation disruption by estrogenic EDCs in X. laevis. Tadpoles at stage 45/46 were exposed to four known estrogenic EDCs with different estrogenic activities, including E2, diethylstilbestrol (DES), mestranol (MES) and 4-n-nonyphenol (NP). At stage 53, gonadal morphological and histological changes as well as altered sex-dimorphic gene expression in gonad-mesonephros complexes (GMCs) showed that these estrogenic EDCs disrupted testis differentiation and caused feminization to different degrees. Then we measured transcriptional changes of 48 candidate genes, which are believed to be associated with E2-induced testis differentiation alterations, in GMCs at stage 50. As a result, 19 genes were found to be transcriptionally altered by all test chemicals and proposed as promising biomarkers for early detection of testis differentiation disruption by estrogenic EDCs. Finally, all biomarker responses were integrated as integrated biomarker response (IBR) index to characterize testis differentiation disruption by these estrogenic EDCs in X. laevis. https://www.selleckchem.com/products/ABT-869.html Compared with the methods used in previous studies, the multiple biomarker test using X. laevis at early developmental stages largely shortens the exposure duration, thereby achieving the goal of rapid detection. Certainly, the biomarker test needs further validations in the future study. With the effective control of point source pollution, rainfall runoff pollution has become the main source of water pollution in Xi'an. Understanding the characteristics and driving factors of rainfall runoff pollution would provide theoretical foundation for urban rainfall runoff pollution control. In this study, a total of 32 rainwater samples, 604 roof runoff samples and 608 road runoff samples obtained from literature and a total of 35 rainwater samples, 127 roof runoff samples and 70 road runoff samples collected by our group were mixed to analyze the rainfall runoff pollution from 2008 to 2019. The Mann-Kendall and Logarithmic Mean Divisia Index (LMDI) method were used to determine the trend of pollution and the driving factors of water quality changes. The results showed that the major pollutant from rainwater was nitrogen, while the main pollutants from roof and road runoff were COD and SS. The rainwater quality during the study period was "clean to slightly polluted". The roof runoff quality of most years (67%) was "clean to slightly polluted". The road runoff quality was poor 22% was "moderately polluted", and 45% was "heavily polluted". The concentration of pollutants except COD in rainwater showed a decreasing trend, while the trend of pollutants in roof and road runoff was not completely consistent with that in rainwater. NH3-N showed strong positive correlation with TN in roof runoff, which indicated common sources of these pollutants. There was a significant correlation between SS and COD in road runoff, and between SS and TP in roof runoff, suggesting SS was an important carrier of COD and TP. Technology innovation was the dominant factor affecting water quality, followed by industrial structure. Economic development and population scale contribute negatively to water quality improvement, and there was a sharp increase in the population scale effect in 2017. The presence of antibiotic residues, their bioactive metabolites and other transformation products in the environment may adversely affect the organisms that live in the environment and may also contribute to increasing the antibiotic resistance of bacteria. It is particularly difficult to determine the types of contaminants in solid samples, in particular, those that are anthropogenically changed, e.g., as a result of controlled biochemical processes. Therefore, the aim of this research was to develop of a new method for the determination of twelve antibiotics belonging to different groups, such as penicillins, sulfonamides, tetracyclines, quinolones, imidazoles and cefalosporins, in digested manure and activated sludge samples, which were used as examples of anthropogenically altered environmental solid samples. The analyses were performed using high performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). The solid-liquid extraction (SLE) method to isolate analytes from digestesolid substrates of environmental origin. This article provides insight into the environmental significance of bridge deck stormwater runoff from scupper drains on receiving water bodies through a review of over eighty sources of information including research and review articles, technical reports and government websites. This article discusses sources and impacts of stormwater pollutants and presents potential methods for predicting impacts of stormwater runoff on receiving waters from highways and bridges. Records of similarities and possible differences between highway and bridge deck stormwater runoff are provided, and the significance of scupper drains as points of runoff discharge from bridges is discussed. Factors that influence bridge deck stormwater runoff quality include the location of the bridge, dimensions of the bridge deck, composition of the road surface, age of the bridge, design and maintenance of the drainage system, traffic volume, and intensity and frequency of rainfall events. Several pollutants of concern are discussed, such as heavy metals, polycyclic aromatic hydrocarbons, solids, nutrients, oil, grease, polychlorinated biphenyls, and perfluorinated compounds. This review also discusses available methods for treatment of bridge deck runoff and the challenge of applying these methods for treatment of bridge deck runoff, as compared to treatment of highway runoff. Finally, this article considers the application of the stochastic empirical loading and dilution model (SELDM), a joint product of the U.S. Geological Survey and the Federal Highway Administration, to predict and assess the potential effects of runoff on receiving waters.
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