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Background It has been shown that copper oxide nanoparticles (CuO NPs) induce pulmonary toxicity after acute or sub-acute inhalation exposures. However, little is known about the biodistribution and elimination kinetics of inhaled CuO NPs from the respiratory tract. The purposes of this study were to observe the kinetics of pulmonary inflammation during and after CuO NP sub-acute inhalation exposure and to investigate copper (Cu) biodistribution and clearance rate from the exposure site and homeostasis of selected trace elements in secondary organs of BALB/c mice. Results Sub-acute inhalation exposure to CuO NPs led to pulmonary inflammation represented by increases in lactate dehydrogenase, total cell counts, neutrophils, macrophages, inflammatory cytokines, iron levels in bronchoalveolar lavage (BAL) fluid, and lung weight changes. Dosimetry analysis in lung tissues and BAL fluid showed Cu concentration increased steadily during exposure and gradually declined after exposure. Cu elimination from the lung showed first-order kinetics with a half-life of 6.5 days. Total Cu levels were significantly increased in whole blood and heart indicating that inhaled Cu could be translocated into the bloodstream and heart tissue, and potentially have adverse effects on the kidneys and spleen as there were significant changes in the weights of these organs; increase in the kidneys and decrease in the spleen. Furthermore, concentrations of selenium in kidneys and iron in spleen were decreased, pointing to disruption of trace element homeostasis. Conclusions Sub-acute inhalation exposure of CuO NPs induced pulmonary inflammation, which was correlated to Cu concentrations in the lungs and started to resolve once exposure ended. Dosimetry analysis showed that Cu in the lungs was translocated into the bloodstream and heart tissue. Secondary organs affected by CuO NPs exposure were kidneys and spleen as they showed the disruption of trace element homeostasis and organ weight changes.

Iron oxides control the mobility of a host of contaminants in aquifer systems, and the microbial reduction of iron oxides in the subsurface is linked to high levels of arsenic in groundwater that affects greater than 150 million people globally. Paired observations of groundwater and solid-phase aquifer composition are critical to understand spatial and temporal trends in contamination and effectively manage changing water resources, yet field-representative mineralogical data are sparse across redox gradients relevant to arsenic contamination. We characterize iron mineralogy using X-ray absorption spectroscopy across a natural gradient of groundwater arsenic contamination in Vietnam. Hierarchical cluster analysis classifies sediments into meaningful groups delineating weathering and redox changes, diagnostic of depositional history, in this first direct characterization of redox transformations in the field. Notably, these groupings reveal a signature of iron minerals undergoing active reduction before the onset of arsenic contamination in groundwater. Pleistocene sediments undergoing postdepositional reduction may be more extensive than previously recognized due to previous misclassification. By upscaling to similar environments in South and Southeast Asia via multinomial logistic regression modeling, we show that active iron reduction, and therefore susceptibility to future arsenic contamination, is more widely distributed in presumably pristine aquifers than anticipated.

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Arsenic (As) groundwater contamination is common yet spatially heterogeneous within most environments. It is therefore necessary to measure As concentrations to determine whether a water source is safe to drink. Measurement of As in the field involves using a test strip that changes color in the presence of As. These tests are relatively inexpensive, but results are subjective and provide binned categorical data rather than exact determinations of As concentration. The goal of this work was to determine if photos of field kit test strips taken on mobile phone cameras could be used to extract more precise, continuous As concentrations. As concentrations for 376 wells sampled from Araihazar, Bangladesh were analyzed using ICP-MS, field kit and the new mobile phone photo method. Results from the field and lab indicate that normalized RGB color data extracted from images were able to accurately predict As concentrations as measured by ICP-MS, achieving detection limits of 9.2μg/L, and 21.9μg/L for the lab and field respectively. Data analysis is most consistent in the laboratory, but can successfully be carried out offline following image analysis, or on the mobile phone using basic image analysis software. The accuracy of the field method was limited by variability in image saturation, and variation in the illumination spectrum (lighting) and camera response. This work indicates that mobile phone cameras can be used as an analytical tool for quantitative measures of As and could change how water samples are analyzed in the field more widely, and that modest improvements in the consistency of photographic image collection and processing could yield measurements that are both accurate and precise.