Project description:Atmospheric particulate matter (PM) is a recognized risk factor for the global burden of disease in human populations. We are presenting here the application of toxicogenomics in the evaluation of the toxic effects of organic content of atmospheric particle matter (PM), from urban and rural environments (city of Barcelona and village of La Pobla, NE Spain), using the developing zebrafish embryo. The main goal is to identify the metabolic pathways involved in the adverse effects observed in zebrafish embryos exposed to PM organic content from urban and rural environments, also allowing the selection of genes of interest that are differentially expressed. The relevance of particle size to the PM toxicity is also addressed. Indeed, the zebrafish embryos were exposed to PM of aerodynamic diameter larger than 7.2 μm and smaller than 0.5 μm (PM10 and PM0.5, respectively). PM0.5 concentrated biological and toxic activities linked to organic substances. Transcriptomic analyses showed strong induction of the AhR signalling pathway (a.k.a. dioxin-like activity) for embryos exposed to both rural and urban extracts, correlating with the concentrations of PAHs. Urban extracts, with strong contribution of traffic emissions, specifically de-regulated oxidative stress-related genes, as well as pancreatic and eye-lens specific genes, two organs known to be affected by air pollution in humans. Exposure to rural extracts, with high contribution of wood burning emissions, affected genes implicated in basic cellular functions, in agreement with their strong embryotoxicity. Extracts from rural and urban samples elicited both common and specific transcriptome responses, suggesting different potentially adverse outcomes depending on PM source and composition. The authors thank the financial support of the Spanish Ministry (project TEA-PARTICLE, grant number CGL2011-29621) and the Portuguese Foundation for Science and Technology for the doctoral grant of Sofia R. Mesquita (SFRH/BD/80710/2011) funded by the Program POPH-QREN through the Portuguese Ministry of Education and Science and the European Social Fund, and support through project PEst-C/MAR/LA0015/2013.

Project description:Atmospheric particulate matter (PM) is a recognized risk factor for the global burden of disease in human populations. We are presenting here the application of toxicogenomics in the evaluation of the toxic effects of organic content of atmospheric particle matter (PM), from urban and rural environments (city of Barcelona and village of La Pobla, NE Spain), using the developing zebrafish embryo. The main goal is to identify the metabolic pathways involved in the adverse effects observed in zebrafish embryos exposed to PM organic content from urban and rural environments, also allowing the selection of genes of interest that are differentially expressed. The relevance of particle size to the PM toxicity is also addressed. Indeed, the zebrafish embryos were exposed to PM of aerodynamic diameter larger than 7.2 Î¼m and smaller than 0.5 Î¼m (PM10 and PM0.5, respectively). PM0.5 concentrated biological and toxic activities linked to organic substances. Transcriptomic analyses showed strong induction of the AhR signalling pathway (a.k.a. dioxin-like activity) for embryos exposed to both rural and urban extracts, correlating with the concentrations of PAHs. Urban extracts, with strong contribution of traffic emissions, specifically de-regulated oxidative stress-related genes, as well as pancreatic and eye-lens specific genes, two organs known to be affected by air pollution in humans. Exposure to rural extracts, with high contribution of wood burning emissions, affected genes implicated in basic cellular functions, in agreement with their strong embryotoxicity. Extracts from rural and urban samples elicited both common and specific transcriptome responses, suggesting different potentially adverse outcomes depending on PM source and composition. The authors thank the financial support of the Spanish Ministry (project TEA-PARTICLE, grant number CGL2011-29621) and the Portuguese Foundation for Science and Technology for the doctoral grant of Sofia R. Mesquita (SFRH/BD/80710/2011) funded by the Program POPH-QREN through the Portuguese Ministry of Education and Science and the European Social Fund, and support through project PEst-C/MAR/LA0015/2013. The PM filter samples used in the present study were PM10 and PM0.5 from the urban site - total of 4 samples from 2 sampling months; and PM0.5 from the rural site - total of 2 samples from 2 sampling months (PM10 samples from the rural site were not tested due to their very low concentration in organic compounds, and insignificant biological activity, previously measured). Sampling occurred during the cold periods of the year 2012/2013. The organic fraction of PM samples was extracted by sonication using a mixture of dichloromethane:methanol. Then, the extracts were filtered, evaporated and re-dissolved in Dimethyl sulfoxide (DMSO). Zebrafish fertilized eggs were exposed to PM organic extracts (0.2% DMSO) from the urban and rural sites from 24 to 120h post-fertilization. Total RNA was isolated from whole embryos (pools of 20 individuals), using Trizol reagent protocol (Invitrogen Life Technologies, Carlsberg, CA). The microarray study was performed using the Agilent Two-colour D. rerio Oligo Microarray v3 platform, following the Agilent Microarray â?? Based Gene Expression Analysis protocol. Three biological replicates were performed for each PM sample and controls. Biological replicates, a technical replicate and a self-to-self, were simultaneously amplified and labelled using Cyanine 3 (Cy3) and Cyanine 5 (Cy5) dye. After cRNA purification (RNeasy Kit, Quiagen GmbH, Hilden, Germany), the cRNA concentration and labelling were quantified in the NanoDrop spectrophotometer, obtaining incorporation rates in the range of 15-20pmol of cyanide dye/Âµl cRNA and yield values > 0.825ug, as recommended. cRNA was fragmented and hybridized in 4x44K arrays, for 17h at 65oC. After the hybridization the array slides were washed, and immediately scanned using Microarray Scanner Agilent G2505C system. Data was extracted using Agilent Feature Extraction Software v10.5.1.1, and the quality of microarray data was evaluated using the Quality Control report provided by Agilent Software. Based on the microarray data analysis, 22 primers were selected and designed using Primer Express 2.0 software (Applied Biosystems, Foster City, CA). Genes were quantified by real-time PCR to validate the microarray data, and a subset of 13 genes were further selected by their robust behaviour in the validation assays, allowing to differentiate the toxic potential of PM from urban and rural sources.

Project description:Coal mining has led to increasingly serious land subsidence, and the reclamation of the subsided land has become a hot topic of concern for governments and scholars. Soil quality of reclaimed land is the key indicator to the evaluation of the reclamation effect; hence, rapid monitoring and evaluation of reclaimed land is of great significance. Visible-near infrared (Vis-NIR) spectroscopy has been shown to be a rapid, timely and efficient tool for the prediction of soil organic carbon (SOC). In this study, 104 soil samples were collected from the Baodian mining area of Shandong province. Vis-NIR reflectance spectra and soil organic carbon content were then measured under laboratory conditions. The spectral data were first denoised using the Savitzky-Golay (SG) convolution smoothing method or the multiple scattering correction (MSC) method, after which the spectral reflectance (R) was subjected to reciprocal, reciprocal logarithm and differential transformations to improve spectral sensitivity. Finally, regression models for estimating the SOC content by the spectral data were constructed using partial least squares regression (PLSR). The results showed that: (1) The SOC content in the mining area was generally low (at the below-average level) and exhibited great variability. (2) The spectral reflectance increased with the decrease of soil organic carbon content. In addition, the sensitivity of the spectrum to the change in SOC content, especially that in the near-infrared band of the original reflectance, decreased when the SOC content was low. (3) The modeling results performed best when the spectral reflectance was preprocessed by Savitzky-Golay (SG) smoothing coupled with multiple scattering correction (MSC) and first-order differential transformation (modeling R2 = 0.86, RMSE = 2.00 g/kg, verification R2 = 0.78, RMSE = 1.81 g/kg, and RPD = 2.69). In addition, the first-order differential of R combined with SG, MSC with R, SG together with MSC and R also produced better modeling results than other pretreatment combinations. Vis-NIR modeling with specific spectral preprocessing methods could predict SOC content effectively.

Dataset Information

Changes of NOx in urban air detected with monitoring VIS-NIR field spectrometer during the coronavirus pandemic: A case study in Germany.

Publications

Changes of NOx in urban air detected with monitoring VIS-NIR field spectrometer during the coronavirus pandemic: A case study in Germany.

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