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Polychlorinated biphenyls (PCBs) were widely used in industrial and commercial applications, until they were banned in the late 1970s as a result of their significant environmental pollution. PCBs in the environment gained scientific interest because of their persistence and the potential threats they pose to humans. Traditionally, human exposure to PCBs was linked to dietary ingestion. Inhalational exposure to these contaminants is often overlooked. This review discusses the occurrence and distribution of PCBs in environmental matrices and their associated health impacts. Severe PCB contamination levels have been reported in e-waste recycling areas. The occurrence of high PCB levels, notably in urban and industrial areas, might result from extensive PCB use and intensive human activity. Furthermore, PCB contamination in the indoor environment is ten-fold higher than outdoors, which may present expose risk for humans through the inhalation of contaminated air or through the ingestion of dust. In such settings, the inhalation route may contribute significantly to PCB exposure. The data on human health effects due to PCB inhalation are scarce. More epidemiological studies should be performed to investigate the inhalation dose and response mechanism and to evaluate the health risks. Further studies should also evaluate the health impact of prolonged low-concentration PCB exposure.

Objectives: Exposure to high concentrations of persistent organochlorines may cause fetal toxicity, but the evidence at low exposure levels is limited. Large studies with substantial exposure contrasts and appropriate exposure assessment are warranted. Within the framework of the EU (European Union) ENRIECO (ENvironmental Health Risks in European Birth Cohorts) and EU OBELIX (OBesogenic Endocrine disrupting chemicals: Linking prenatal eXposure to the development of obesity later in life) projects, we examined the hypothesis that the combination of polychlorinated biphenyls (PCBs) and dichlorodiphenyldichloroethylene (DDE) adversely affects birth weight. Methods: We used maternal and cord blood and breast milk samples of 7,990 women enrolled in 15 study populations from 12 European birth cohorts from 1990 through 2008. Using identical variable definitions, we performed for each cohort linear regression of birth weight on estimates of cord serum concentration of PCB-153 and P,P'-DDE adjusted for gestational age and a priori selected covariates. We obtained summary estimates by meta-analysis and performed analyses of interactions. Results: The median concentration of cord serum PCB-153 was 140 ng/L (range of cohort medians 20-484 ng/L) and that of P,P'-DDE was 528 ng/L (range of cohort medians 50-1,208 ng/L). Birth weight decreased with increasing cord serum concentration of PCB-153 after adjustment for potential confounders in 12 of 15 study populations. The meta-analysis including all cohorts indicated a birth weight decline of 150 g [95% confidence interval (CI): -250, -50 g] per 1-ug/L increase in PCB-153, an exposure contrast that is close to the range of exposures across the cohorts. A 1-ug/L increase in P, P'-DDE was associated with a 7-g decrease in birth weight (95% CI: —18, 4 g). Conclusions: The findings suggest that low-level exposure to PCB (or correlated exposures) impairs fetal growth, but that exposure to P,P'-DDE does not.The study adds to mounting evidence that low-level exposure to PCBs is inversely associated with fetal growth.

We examined whether environmentally relevant concentrations of different types of microplastics, with or without PCBs, directly affect freshwater prey and indirectly affect their predators. Asian clams (Corbicula fluminea) were exposed to environmentally relevant concentrations of polyethylene terephthalate (PET), polyethylene, polyvinylchloride (PVC) or polystyrene with and without polychlorinated biphenyls (PCBs) for 28 days. Their predators, white sturgeon (Acipenser transmontanus), were exposed to clams from each treatment for 28 days. In both species, we examined bioaccumulation of PCBs and effects (i.e., immunohistochemistry, histology, behavior, condition, mortality) across several levels of biological organization. PCBs were not detected in prey or predator, and thus differences in bioaccumulation of PCBs among polymers and biomagnification in predators could not be measured. One of the main objectives of this study was to test the hypothesis that bioaccumulation of PCBs would differ among polymer types. Because we could not answer this question experimentally, a bioaccumulation model was run and predicted that concentrations of PCBs in clams exposed to polyethylene and polystyrene would be greater than PET and PVC. Observed effects, although subtle, seemed to be due to microplastics rather than PCBs alone. For example, histopathology showed tubular dilation in clams exposed to microplastics with PCBs, with only mild effects in clams exposed to PCBs alone.

Neurodevelopmental disabilities, including autism, attention-deficit hyperactivity disorder, dyslexia, and other cognitive impairments, affect millions of children worldwide, and some diagnoses seem to be increasing in frequency. Industrial chemicals that injure the developing brain are among the known causes for this rise in prevalence. In 2006, we did a systematic review and identified five industrial chemicals as developmental neurotoxicants: lead, methylmercury, polychlorinated biphenyls, arsenic, and toluene. Since 2006, epidemiological studies have documented six additional developmental neurotoxicants—manganese, fluoride, chlorpyrifos, dichlorodiphenyltrichloroethane, tetrachloroethylene, and the polybrominated diphenyl ethers. We postulate that even more neurotoxicants remain undiscovered. To control the pandemic of developmental neurotoxicity, we propose a global prevention strategy. Untested chemicals should not be presumed to be safe to brain development, and chemicals in existing use and all new chemicals must therefore be tested for developmental neurotoxicity. To coordinate these efforts and to accelerate translation of science into prevention, we propose the urgent formation of a new international clearinghouse.

Organohalide pollutants are prevalent in coastal regions due to extensive intervention by anthropogenic activities, threatening public health and ecosystems. Gradients in salinity are a natural feature of coasts, but their impacts on the environmental fate of organohalides and the underlying microbial communities remain poorly understood. Here we report the effects of salinity on microbial reductive dechlorination of tetrachloroethene (PCE) and polychlorinated biphenyls (PCBs) in consortia derived from distinct environments (freshwater and marine sediments). Marine-derived microcosms exhibited higher halotolerance during PCE and PCB dechlorination, and a halotolerant dechlorinating culture was enriched from these microcosms. The organohalide-respiring bacteria (OHRB) responsible for PCE and PCB dechlorination in marine microcosms shifted from Dehalococcoides to Dehalobium when salinity increased. Broadly, lower microbial diversity, simpler co-occurrence networks, and more deterministic microbial community assemblages were observed under higher salinity. Separately, we observed that inhibition of dechlorination by high salinity could be attributed to suppressed viability of Dehalococcoides rather than reduced provision of substrates by syntrophic microorganisms. Additionally, the high activity of PCE dechlorinating reductive dehalogenases (RDases) in in vitro tests under high salinity suggests that high salinity likely disrupted cellular components other than RDases in Dehalococcoides . Genomic analyses indicated that the capability of Dehalobium to perform dehalogenation under high salinity was likely owing to the presence of genes associated with halotolerance in its genomes. Collectively, these mechanistic and ecological insights contribute to understanding the fate and bioremediation of organohalide pollutants in environments with changing salinity.

Understanding the transfer of polychlorinated dibenzo- p -dioxins (PCDDs) and dibenzofurans (PCDFs) as well as polychlorinated biphenyls (PCBs) from oral exposure into cow’s milk is not purely an experimental endeavour, as it has produced a large corpus of theoretical work. This work consists of a variety of predictive toxicokinetic models in the realms of health and environmental risk assessment and risk management. Their purpose is to provide mathematical predictive tools to organise and integrate knowledge on the absorption, distribution, metabolism and excretion processes. Toxicokinetic models are based on more than 50 years of transfer studies summarised in part I of this review series. Here in part II, several of these models are described and systematically classified with a focus on their applicability to risk analysis as well as their limitations. This part of the review highlights the opportunities and challenges along the way towards accurate, congener-specific predictive models applicable to changing animal breeds and husbandry conditions.

A recent review by the International Agency for Research on Cancer (IARC) updated the assessments of the > 100 agents classified as Group 1, carcinogenic to humans (IARC Monographs Volume 100, parts A-F). This exercise was complicated by the absence of a broadly accepted, systematic method for evaluating mechanistic data to support conclusions regarding human hazard from exposure to carcinogens. IARC therefore convened two workshops in which an international Working Group of experts identified 10 key characteristics, one or more of which are commonly exhibited by established human carcinogens. These characteristics provide the basis for an objective approach to identifying and organizing results from pertinent mechanistic studies. The 10 characteristics are the abilities of an agent to 1) act as an electrophile either directly or after metabolic activation; 2) be genotoxic; 3) alter DNA repair or cause genomic instability; 4) induce epigenetic alterations; 5) induce oxidative stress; 6) induce chronic inflammation; 7) be immunosuppressive; 8) modulate receptor-mediated effects; 9) cause immortalization; and 10) alter cell proliferation, cell death, or nutrient supply. We describe the use of the 10 key characteristics to conduct a systematic literature search focused on relevant end points and construct a graphical representation of the identified mechanistic information. Next, we use benzene and polychlorinated biphenyls as examples to illustrate how this approach may work in practice. The approach described is similar in many respects to those currently being implemented by the U.S. EPA's Integrated Risk Information System Program and the U.S. National Toxicology Program. Smith MT, Guyton KZ, Gibbons CF, Fritz JM, Portier CJ, Rusyn I, DeMarini DM, Caldwell JC, Kavlock RJ, Lambert P, Hecht SS, Bucher JR, Stewart BW, Baan R, Cogliano VJ, Straif K. 2016. Key characteristics of carcinogens as a basis for organizing data on mechanisms of carcinogenesis. Environ Health Perspect 124:713-721; http://dx.doi.org/10.1289/ehp.1509912.

Despite international regulation, polychlorinated biphenyls (PCBs) are routinely detected at levels threatening human and environmental health. While previous research has emphasized trophic transfer as the principle pathway for PCB accumulation, our study reveals the critical role that non-trophic interactions can play in controlling PCB bioavailability and biomagnification. In a 5-month field experiment manipulating saltmarsh macro-invertebrates, we show that suspension-feeding mussels increase concentrations of total PCBs and toxic dioxin-like coplanars by 11- and 7.5-fold in sediment and 10.5- and 9-fold in cordgrass-grazing crabs relative to no-mussel controls, but do not affect PCB bioaccumulation in algae-grazing crabs. PCB homolog composition and corroborative dietary analyses demonstrate that mussels, as ecosystem engineers, amplify sediment contamination and PCB exposure for this burrowing marsh crab through non-trophic mechanisms. We conclude that these ecosystem engineering activities and other non-trophic interactions may have cascading effects on trophic biomagnification pathways, and therefore exert strong bottom-up control on PCB biomagnification up this coastal food web.

Presence of plastic debris in marine and freshwater ecosystems is increasingly reported. Previous research suggested plastic debris had a strong affiliation for many pollutants, such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and heavy metals. In this study, the sorption behavior of pharmaceuticals and personal care products (PPCPs), including carbamazepine (CBZ), 4-methylbenzylidene camphor (4MBC), triclosan (TCS), and 17α-ethinyl estradiol (EE2), to polyethylene (PE) debris (250 to 280 μm) was investigated. The estimated linear sorption coefficients ( K d ) are 191.4, 311.5, 5140, and 53,225 L/kg for CBZ, EE2, TCS, and 4MBC, and are related to their hydrophobicities. Increase of salinity from 0.05 to 3.5 % did not affect the sorption of 4MBC, CBZ, and EE2 but enhanced the sorption of TCS, likely due to the salting-out effect. Increase of dissolved organic matter (DOM) content using Aldrich humic acid (HA) as a proxy reduced the sorption of 4MBC, EE2, and TCS, all of which show a relatively strong affiliation to HA. Results from this work suggest that microplastics may play an important role in the fate and transport of PPCPs, especially for those hydrophobic ones.

Aiming at the problems of low accuracy and large computation in the task of PCB defect detection. This paper proposes a lightweight PCB defect detection algorithm based on YOLO. To address the problem of large numbers of parameters and calculations, GhostNet are used in Backbone to keep the model lightweight. Second, the ordinary convolution of the neck network is improved by depthwise separable convolution, resulting in a reduction of redundant parameters within the neck network. Afterwards, the Swin-Transformer is integrated with the C3 module in the Neck to build the C3STR module, which aims to address the issue of cluttered background in defective images and the confusion caused by simple defect types. Finally, the PANet network structure is replaced with the bidirectional feature pyramid network (BIFPN) structure to enhance the fusion of multi-scale features in the network. The results indicated that when comparing our model with the original model, there was a 47.2% reduction in the model’s parameter count, a 48.5% reduction in GFLOPs, a 42.4% reduction in Weight, a 2.0% reduction in FPS, and a 2.4% rise in mAP. The model is better suited for use on low-arithmetic platforms as a result.