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Paired serum and urine samples were collected from workers in a fluorochemical plant from 2008 to 2012 (n = 302) to investigate the level, temporal trends, and half-lives of PFAAs in workers of a fluorochemical plant. High levels of perfluorohexane sulfonate (PFHxS), perfluorooctanoic acid (PFOA), and perfluorooctanesulfonate (PFOS) were detected in serum with median concentrations of 764, 427, and 1725 ng mL −1 , respectively. The half-lives of PFAAs in workers were estimated by daily clearance rates and annual decline rates of PFAAs in serum by a first-order model. The geometric mean and median value for PFHxS, PFOA, and PFOS were 14.7 and 11.7, 4.1 and 4.0, 32.6 and 21.6 years, respectively, by the daily clearance rates, and they were 3.6, 1.7, and 1.9 years estimated by annual decline rates. The half-lives estimated by the limited clearance route information could be considered as the upper limits for PFAAs, however, the huge difference between two estimated approaches indicated that there were other important elimination pathways of PFAAs other than renal clearance in human. The half-lives estimated by annual decline rates in the present study were the shortest values ever reported, and the intrinsic half-lives might even shorter due to the high levels of ongoing exposure to PFAAs.

Background: Inappropriate use of antibiotics in swine feed could cause accelerated emergence of antibiotic resistance genes, and agricultural application of swine waste could spread antibiotic resistance genes to the surrounding environment. Objectives: We investigated the distribution of plasmid-mediated quinolone resistance (PMQR) genes from swine feedlots and their surrounding environment. Methods: We used a culture-independent method to identify PMQR genes and estimate their levels in wastewater from seven swine feedlot operations and corresponding wastewater-irrigated farm fields. Concentrations of (fluoro) quinolones in wastewater and soil samples were determined by ultra-performance liquid chromatography— electrospray tandem mass spectrometry. Results: The predominant PMQR genes in both the wastewater and soil samples were qnrD, qepA, and oqxB, whereas qnrS and oqxA were present only in wastewater samples. Absolute concentrations of all PMQR genes combined ranged from 1.66 x 10⁷ to 4.06 x 10⁸ copies/mL in wastewater and 4.06 x 10⁶ to 9.52 x 10⁷ copies/g in soil. Concentrations of (fluoro) quinolones ranged from 4.57 to 321 ng/mL in wastewater and below detection limit to 23.4 ng/g in soil. Significant correlations were found between the relative abundance of PMQR genes and (fluoro) quinolone concentrations (r = 0.71, p = 0.005) and the relative abundance of PMQR genes in paired wastewater and agricultural soil samples (r = 0.91, p = 0.005). Conclusions: Swine feedlot wastewater may be a source of PMQR genes that could facilitate the spread of antibiotic resistance. To our knowledge, this is the first study to examine the occurrence of PMQR genes in animal husbandry environments using a culture-independent method.

The distribution and fate of polybrominated diphenyl ethers (PBDEs) in a riparian ecosystem nearby a wastewater treatment plant effluent were investigated. Different aqueous and terrestrial samples such as soil, sediment, plants, and invertebrates were collected and analyzed for tri- to heptabrominated PBDEs. Furthermore, the food web structure was elucidated using stable carbon and nitrogen isotopes. The highest PBDE levels were found for sediment- and soil-dwelling invertebrates, such as earthworms (Σ 13 PBDEs 144 ng/g lipid weight), Tubifex tubifex (77 ng/g lw), and scarab larvae (49 ng/g lw). Differences in congener composition profiles among the different matrices show that the environmental distribution and fate of PBDEs in ecosystems can be very complex. Among the analyzed PBDEs in this ecosystem, the tetra-brominated BDE-47 was the dominant PBDE congener and followed by the penta-brominated BDE-99. A potential trend of increasing BDE-47/99 ratio with the increase of δ 15 N was observed for species with similar energy sources (δ 13 C), indicating a higher bioaccumulation potential for BDE-47 in this ecosystem. A significant correlation was also found between PBDEs and polychlorinated biphenyls (PCBs), indicating similar sources and fate between the two compound groups in this area. The biota-soil or biota-sediment accumulation factors (BSAFs) were somewhat different among the PBDE congeners and species, but were generally highest for those with log K ow values around 6.5–7.

Background: Polyfluorinated iodine alkanes (PFIs) are important intermediates in the synthesis of organic fluoride products. Recently, PFIs have been detected in fluoropolymers as residual raw materials, as well as in the ambient environment. Objectives: High production volumes and potential environmental releases of PFIs might become a concern, but the exposure risk and toxicity of these chemicals are still unclear. In this study, we investigated the potential estrogenic effects of PFIs. Methods: We studied the estrogenic effects of fluorinated iodine alkanes (FIAs), fluorinated telomer iodides (FTIs), and fluorinated diiodine alkanes (FDIAs) using the E-screen and MVLN assays and the evaluation of estrogen-responsive genes in MCF-7 cells. Results: FIAs have an iodine atom at one end of the perfluorinated carbon chain. 1-Iodoperfluorohexane (PFHxI) and 1-iodoperfluorooctane (PFOI) promoted the proliferation of MCF-7 cells, induced luciferase activity in MVLN cells, and up-regulated the expression of TFF1 and EGR3. In these assays, other FIAs gave negative responses. FDIAs have an iodine atom at each end of the perfluorinated carbon chain, and all the FDIAs showed estrogenic effects. The estrogenic potencies of FIAs and FDIAs correlate well with the carbon chain length of the chemicals. The optimum chain length for estrogenic effects is six carbons, and then eight and four carbons. All FTIs have a single iodine atom at the end of a partially fluorinated carbon chain. None of the FTIs showed estrogenic effects in the tests. Conclusions: The estrogenic effects of PFIs are dependent on the structural features of iodine substitution and chain length. This research will be helpful in further understanding the estrogenic effects of perfluorinated compounds.

Neuronal toxic pollutants in environment possess hazards to human health. It is essential to determine the causative neuronal toxicants in environmental samples. In the present study, viability of primary cultured cerebellar granule neurons (CGNs), combined with sample extraction, chemical fractionation and identification, was applied for screening acid-resistant neuronal toxic substances in environmental samples. River sediments and agricultural soils along the river near a brominated flame retardant (BFR) manufacturing plant in South China were collected to screen the key neuronal toxicants. The results indicated that the manufacturing plant was a source of neuronal toxicity risks. In the sediment and soil near the plant, one of the causative toxicants was identified as tris-(2,3-dibromopropyl) isocyanurate (TBC) using HPLC-MS/MS. In addition, an unknown chemical possibly causing significant neuronal toxicity was isolated from all the soil samples in the region.

Microbial whole-cell sensor has been widely used to assess bioavailability and risk of toxic elements, but their environmental use is still limited due to the presence of other interfering pollutants and the nonspecific binding in cells, which leads to inaccurate results. Here, we proposed a strategy combining Escherichia coli sensor set with binary regression models for the specific detection of bioavailable cadmium (Cd), lead (Pb), and arsenic (As) in a co-polluted environment. Initial tests suggested that the sensor set respectively termed pcadCluc, pzntRluc, and parsRluc could be classified into two groups according to their specific response to Cd, Pb, and As: group 1 (pcadCluc and pzntRluc) induced by a Cd-Pb mix and group 2 (parsRluc) induced by a Cd-As mix. Based on the variance in responses of each sensor to mixtures of target elements, three binary linear equations for two sensor groups were set up to calculate the individual concentrations in the mixture solutions. This method was then used to quantify the bioavailable Cd, Pb, and As in soils from a co-polluted mining region and to compare the results with other methods. Results showed that the conventional single target sensor method overestimated the bioavailability of each element, while sensor set was credible for accurate bioavailable Cd, Pb, and As quantification and comparable with the results from inductively coupled plasma mass spectrometry (ICP-MS) analysis. Our method can potentially be extended to cover the specific detection of other bioavailable toxic elements in different environmental settings.

Spatial distribution, seasonal variation and potential inhalation risks of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) were investigated in the atmosphere of Beijing, using passive air samplers equipped with polyurethane foam disks. Concentrations of ΣPCDD/Fs, ΣPCBs and ΣPBDEs ranged from 8.4 to 179 fg WHO2005-TEQ/m3, 38.6–139 and 1.5–176 pg/m3, respectively. PCDFs showed higher air concentrations than those of PCDDs, indicating the influence of industrial activities and other combustion processes. The non-Aroclor congener, PCB-11, was detected in air (12.3–99.4 pg/m3) and dominated the PCB congener profiles (61.7–71.5% to ∑PCBs). The congener patterns of PBDEs showed signatures from both penta-BDE and octa-BDE products. Levels of PCDD/Fs, PCBs and PBDEs at the industrial and residential sites were higher than those at rural site, indicating human activities in urban area as potential sources. Higher air concentrations of PCDD/Fs, PCBs and PBDEs were observed in summer, which could be associated with atmospheric deposition process, re-volatilization from soil surface and volatilization from use of technical products, respectively. Results of inhalation exposure and cancer risk showed that atmospheric PCDD/Fs, dioxin-like PCBs and PBDEs did not cause high risks to the local residents of Beijing. This study provides further aid in evaluating emission sources, influencing factors and potential inhalation risks of the persistent organic pollutants to human health in mega-cities of China.

The exposure pathways of perfluoroalkyl acids (PFAAs) to humans are still not clear because of the complex living environment and few studies have simultaneously investigated the bioaccumulative behaviour of different PFAAs in humans. In this study, serum, dust, duplicate diet and other matrices were collected around a manufacturing plant in China and homologous series of PFAAs were analysed. PFAA levels in dust and serum of local residents in this area were considerably higher than those in non-polluted area. Although dietary intake was the major exposure pathway in the present study, dust ingestion played an important role in this case. Serum PFAAs in local residents was significantly correlated with dust PFAAs levels in their living or working microenvironment. Serum PFAAs and dust PFAAs were significantly higher in family members of occupational workers (FM) than in ordinary residents (OR) (p < 0.01). After a careful analysis of the PFAAs exposure pathway, a potential pathway in addition to direct dust ingestion was suggested: PFAAs might transferred from occupational worker's clothes to dinners via cooking processes. The bioaccumulative potential of PFHxS and PFOS were higher than other PFAAs, which suggested a substantial difference between the bioaccumulative ability of perfluorinated sulfonic acids and perfluorinated carboxylic acids.

Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.

Neural networks have been applied in various fields from signal processing, pattern recognition, associative memory to artificial intelligence. Recently, nanoscale memristor has renewed interest in experimental realization of neural network. A neural network with a memristive synaptic weight is studied in this work. Dynamical properties of the proposed neural network are investigated through phase portraits, Poincaré map, and Lyapunov exponents. Interestingly, the memristive neural network can generate hyperchaotic attractors without the presence of equilibrium points. Moreover, circuital implementation of such memristive neural network is presented to show its feasibility.