Polycyclic aromatic hydrocarbon (PAH) exposure and genetic susceptibility were conductive to genotoxic effects including gene damage, which can increase mutational probability. We aimed to explore the dose-effect associations of PAH exposure with damage of exons of epidermal growth factor receptor (EGFR) and breast cancer susceptibility gene 1 (BRCA1), as well as their associations whether modified by Flap endonuclease 1 (FEN1) genotype. Two hundred eighty-eight coke oven male workers were recruited, and we detected the concentration of 1-hydroxypyrene (1-OH-pyr) as PAH exposure biomarker in urine and examined base modification in exons of EGFR and BRCA1 respectively, and genotyped FEN1 rs174538 polymorphism in plasma. We found that the damage indexes of exon 19 and 21 of EGFR (EGFR-19 and EGFR-21) were both significantly associated with increased urinary 1-OH-pyr (both Ptrend < 0.001). The levels of urinary 1-OH-pyr were both significantly associated with increased EGFR-19 and EGFR-21 in both smokers and nonsmokers (both P < 0.001). Additionally, we observed that the urinary 1-OH-pyr concentrations were linearly associated with both EGFR-19 and EGFR-21 only in rs174538 GA+AA genotype carriers (both P < 0.001). Moreover, FEN1rs rs174538 showed modifying effects on the associations of urinary 1-OH-pyr with EGFR-19 and EGFR-21 (both Pinteraction < 0.05). Our findings revealed the linear dose-effect association between exon damage of EGFR and PAH exposure and highlight differences in genetic contributions to exon damage and have the potential to identify at-risk subpopulations who are susceptible to adverse health effects induced by PAH exposure.
The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance. 相似文献
A probabilistic analysis was performed on soil arsenic concentration data from 4 brownfield sites at Beijing (Chaoyang and Haidian Districts), involved in environmental assessment studies. The available data sets were processed to provide a statistical characterization of the background populations and differentiate “anomalous data” from the natural range of variation of arsenic concentrations in soil. The site-specific background distributions and the existing wide-scale background values defined for the Beijing area were compared, discussing related implications for the definition of metal contamination soil screening levels (SSLs) in site assessment studies. The statistical analysis of As data sets discriminated site-specific background populations, encompassing 88% to 94% of the sample data, from outliers values, associated with either subsoil natural enrichments or possible anthropogenic releases. Upper Baseline Concentration (UBC) limits (+ 2σ level), including most of the site-specific metal background variability, were derived based on the statistical characterization of the background populations. Sites in the Chaoyang South District area had UBC values in the range 10.4–12.6 mg·kg-1. These ranges provide meaningful SSL values to be adopted for As in local site assessment studies. Using the wide-scale background value for the Beijing area would have erroneously classified most of the areas in the subject sites as potentially contaminated. 相似文献