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Quantification of chemical toxicity continues to be generally based on measured external concentrations. Yet, internal chemical concentrations have been suggested to be a more suitable parameter. To better understand the relationship between the external and internal concentrations of chemicals in fish, and to quantify internal concentrations, we compared three toxicokinetic (TK) models with each other and with literature data of measured concentrations of 39 chemicals. Two one-compartment models, together with the physiologically based toxicokinetic (PBTK) model, in which we improved the treatment of lipids, were used to predict concentrations of organic chemicals in two fish species: rainbow trout (Oncorhynchus mykiss) and fathead minnow (Pimephales promelas). All models predicted the measured internal concentrations in fish within 1 order of magnitude for at least 68% of the chemicals. Furthermore, the PBTK model outperformed the one-compartment models with respect to simulating chemical concentrations in the whole body (at least 88% of internal concentrations were predicted within 1 order of magnitude using the PBTK model). All the models can be used to predict concentrations in different fish species without additional experiments. However, further development of TK models is required for polar, ionizable, and easily biotransformed compounds.
Quantitative structure-activity relationships (QSARs) were developed to predict the in vitro clearance (CLINT) of xenobiotics metabolised in human hepatocytes (118 compounds) and microsomes (115 compounds). Clearance values were gathered from the scientific literature and multiple linear models were built and validated selecting at most 6 predictors from a pool of over 2000 potential molecular descriptors. For the hepatocytes QSAR, the explained variance (Radj(2)) was 67% and the predictive ability (Rext(2)) was 62%. For the microsomes QSAR, Radj(2) was 50% and Rext(2) 30%. For both liver assays, the most important descriptor relates to electronic properties of the compound. Functional groups of fragments were useful to identify specific compounds that have a deviating reaction rate compared to the others, such as polychlorobiphenyls (PCBs) and organic amides which were poorly metabolised by hepatocytes and microsomes, respectively. For hepatocytes, clearance was predominantly determined by electronic characteristics, while size and shape characteristics were less important and partitioning properties were absent. This may suggest that uptake across the membrane and enzyme binding are not rate-limiting steps. Particularly for hepatocytes the QSAR statistics are encouraging, allowing application of the outcomes in in vitro to in vivo extrapolation.
Currently it is difficult to prospectively estimate human toxicokinetics (particularly for novel chemicals) in a high-throughput manner. The R software package httk has been developed, in part, to address this deficiency, and the aim of this investigation was to develop a generalized inhalation model for httk. The structure of the inhalation model was developed from two previously published physiologically based models from Jongeneelen and Berge (Ann Occup Hyg 55:841-864, 2011) and Clewell et al. (Toxicol Sci 63:160-172, 2001), while calculated physicochemical data was obtained from EPA's CompTox Chemicals Dashboard. In total, 142 exposure scenarios across 41 volatile organic chemicals were modeled and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed blood and exhaled breath concentrations was 0.46 with an r2 = 0.45 and a root mean square error (RMSE) of direct comparison between the log-transformed simulated and observed values of 1.11. Approximately 5.1% (n = 108) of the data points analyzed were >2 orders of magnitude different than expected. The volatile organic chemicals examined in this investigation represent small, generally lipophilic molecules. Ultimately this paper details a generalized inhalation component that integrates with the httk physiologically based toxicokinetic model to provide high-throughput estimates of inhalation chemical exposures.
Currently, there are >11,000 synthetic turf athletic fields in the United States and >13,000 in Europe. Concerns have been raised about exposure to carcinogenic chemicals resulting from contact with synthetic turf fields, particularly the infill material ("crumb rubber"), which is commonly fabricated from recycled tires. However, exposure data are scant, and the limited existing exposure studies have focused on a small subset of crumb rubber components. Our objective was to evaluate the carcinogenic potential of a broad range of chemical components of crumb rubber infill using computational toxicology and regulatory agency classifications from the United States Environmental Protection Agency (US EPA) and European Chemicals Agency (ECHA) to inform future exposure studies and risk analyses. Through a literature review, we identified 306 chemical constituents of crumb rubber infill from 20 publications. Utilizing ADMET Predictor™, a computational program to predict carcinogenicity and genotoxicity, 197 of the identified 306 chemicals met our a priori carcinogenicity criteria. Of these, 52 chemicals were also classified as known, presumed or suspected carcinogens by the US EPA and ECHA. Of the remaining 109 chemicals which were not predicted to be carcinogenic by our computational toxicology analysis, only 6 chemicals were classified as presumed or suspected human carcinogens by US EPA or ECHA. Importantly, the majority of crumb rubber constituents were not listed in the US EPA (n = 207) and ECHA (n = 262) databases, likely due to an absence of evaluation or insufficient information for a reliable carcinogenicity classification. By employing a cancer hazard scoring system to the chemicals which were predicted and classified by the computational analysis and government databases, several high priority carcinogens were identified, including benzene, benzidine, benzo(a)pyrene, trichloroethylene and vinyl chloride. Our findings demonstrate that computational toxicology assessment in conjunction with government classifications can be used to prioritize hazardous chemicals for future exposure monitoring studies for users of synthetic turf fields. This approach could be extended to other compounds or toxicity endpoints.
In vitro toxicological studies together with atomistic molecular dynamics simulations show that occupational co-exposure with C60 fullerene may strengthen the health effects of organic industrial chemicals. The chemicals studied are acetophenone, benzaldehyde, benzyl alcohol, m-cresol, and toluene which can be used with fullerene as reagents or solvents in industrial processes. Potential co-exposure scenarios include a fullerene dust and organic chemical vapor, or a fullerene solution aerosolized in workplace air. Unfiltered and filtered mixtures of C60 and organic chemicals represent different co-exposure scenarios in in vitro studies where acute cytotoxicity and immunotoxicity of C60 and organic chemicals are tested together and alone by using human THP-1-derived macrophages. Statistically significant co-effects are observed for an unfiltered mixture of benzaldehyde and C60 that is more cytotoxic than benzaldehyde alone, and for a filtered mixture of m-cresol and C60 that is slightly less cytotoxic than m-cresol. Hydrophobicity of chemicals correlates with co-effects when secretion of pro-inflammatory cytokines IL-1β and TNF-α is considered. Complementary atomistic molecular dynamics simulations reveal that C60 co-aggregates with all chemicals in aqueous environment. Stable aggregates have a fullerene-rich core and a chemical-rich surface layer, and while essentially all C60 molecules aggregate together, a portion of organic molecules remains in water.
Increased demand for recycling plastic has prompted concerns regarding potential introduction of hazardous chemicals into recycled goods. We present a broad screening of chemicals in 21 plastic flake and pellet samples from Canadian recycling companies. From target analysis, the organophosphorus ester flame retardants and plasticizers exhibited the highest detection frequencies (DFs) (5-100%) and concentrations (
In order to understand the physicochemical properties as well as the mechanisms behind adsorption of hazardous synthetic organic chemicals (SOCs) onto single walled carbon nanotubes (SWCNTs), we have developed partial least squares (PLS)-regression based QSPR models using a diverse set of 40 hazardous SOCs having defined adsorption coefficient (logK). The models were extensively validated using different validation parameters in order to assure the robustness and predictivity of the models. We have also checked the consensus predictivity of all the individual models using "Intelligent consensus predictor" tool for possible enhancement of the quality of predictions for test set compounds. The consensus predictivity of the test set compounds were found to be better than the individual models based on not only the MAE based criteria (MAE(95%) = Good) but also some other validation parameters (Q2F1 = 0.938, Q2F2 = 0.937). The contributing descriptors obtained from the QSPR models suggested that the hazardous SOCs may get adsorbed onto the SWCNTs through hydrophobic interaction as well as hydrogen bonding interactions and electrostatic interaction to the functionally modified SWCNTs. Thus, the developed models may provide knowledge to scientists to increase the efficient application of SWCNTs as a special adsorbent, which may be useful for the management of environmental pollution.
Bioaccumulation and biotransformation are key toxicokinetic processes that modify toxicity of chemicals and sensitivity of organisms. Bioaccumulation kinetics vary greatly among organisms and chemicals; thus, we investigated the influence of biotransformation kinetics on bioaccumulation in a model aquatic invertebrate using fifteen (14)C-labeled organic xenobiotics from diverse chemical classes and physicochemical properties (1,2,3-trichlorobenzene, imidacloprid, 4,6-dinitro-o-cresol, ethylacrylate, malathion, chlorpyrifos, aldicarb, carbofuran, carbaryl, 2,4-dichlorophenol, 2,4,5-trichlorophenol, pentachlorophenol, 4-nitrobenzyl-chloride, 2,4-dichloroaniline, and sea-nine (4,5-dichloro-2-octyl-3-isothiazolone)). We detected and identified metabolites using HPLC with UV and radio-detection as well as high resolution mass spectrometry (LTQ-Orbitrap). Kinetics of uptake, biotransformation, and elimination of parent compounds and metabolites were modeled with a first-order one-compartment model. Bioaccumulation factors were calculated for parent compounds and metabolite enrichment factors for metabolites. Out of 19 detected metabolites, we identified seven by standards or accurate mass measurements and two via pathway analysis and analogies to other compounds. 1,2,3-Trichlorobenzene, imidacloprid, and 4,6-dinitro-o-cresol were not biotransformed. Dietary uptake contributed little to overall uptake. Differentiation between parent and metabolites increased accuracy of bioaccumulation parameters compared to total (14)C measurements. Biotransformation dominated toxicokinetics and strongly affected internal concentrations of parent compounds and metabolites. Many metabolites reached higher internal concentrations than their parents, characterized by large metabolite enrichment factors.
Emerging organic contaminants (e.g., active pharmaceutical ingredients and personal care products ingredients) are ubiquitous in the environment and potentially harmful to ecosystems, have gained increasing public attention worldwide. Nevertheless, there is a scarcity of data on these contaminants in Africa. In this study, various types of water samples (wastewater, surface water and tap water) collected from Lagos, Nigeria were analyzed for these chemicals by both target and non-target analysis on an UHPLC-Orbitrap-MS/MS. In total, 109 compounds were identified by non-target screening using the online database mzCloud. Level 1 identification confidence was achieved for 13 compounds for which reference standards were available and level 2 was achieved for the rest. In the quantitative analysis, 18 of 38 target compounds were detected, including the parent compounds and their metabolites. Acetaminophen, sulfamethoxazole, acesulfame, and caffeine were detected in all samples with their highest concentrations at 8000, 5300, 16, and 7700 μg/L in wastewater, 140000, 3300, 7.7, and 12000 μg/L in surface water, and 66, 62, 0.17 and 1000 μg/L in tap water, respectively. The occurrence of psychoactive substances, anticancer treatments, antiretrovirals, antihypertensives, antidiabetics and their metabolites were reported in Nigeria for the first time. These results indicate poor wastewater treatment and management in Nigeria, and provide a preliminary profile of organic contaminants occurring in Nigerian waters. The findings from this study urge more future research on chemical pollution in the aquatic environments in Nigeria.
Elimination half-life is an important pharmacokinetic parameter that determines exposure duration to approach steady state of drugs and regulates drug administration. The experimental evaluation of half-life is time-consuming and costly. Thus, it is attractive to build an accurate prediction model for half-life.
Wide use of various chemicals has resulted in water pollution, which has become a global environmental concern. So far limited information is available on what chemicals in our water. Here we investigated the occurrence and profiles of organic chemicals in the North River, South China by applying non-target screening analysis with high resolution mass spectrometry. A total of 402 organic chemicals belonging to eleven categories were identified in the North River, with notable presence of industrial chemicals, pharmaceuticals and pesticides. Among these detected chemicals, over half of the tentatively identified compounds were rarely reported in the surface water, with a few compounds, e.g., sisomicin, simeton, 2-methyl-4,6-dinitrophenol, xanthurenic acid and indole-3-carboxylic acid that have never been documented in the North River before, while the metabolites like 4-acetamidoantipyrine were also observed. The maximum concentration of the identified chemicals in the North River was above 300 ng/L (Sulfamonomethoxine). Principle component analysis results of the obtained dataset showed significant seasonal distribution, which could be linked to variations in wastewater discharge, river dilution and anthropogenic activities such as pesticide spray. Agricultural activities in the upper reaches led to detection of various pesticides in the river basin, especially in the wet season. The findings from this study demonstrated the widespread presence of chemicals in our waterway, and further retrospective analysis would reveal more information about chemicals of emerging concern.
It is essential to develop effective analytical techniques for accurate and continuous monitoring of various biomanufacturing processes, such as the production of monoclonal antibodies and vaccines, through sensitive and quantitative detection of characteristic aqueous or gaseous metabolites and other analytes in the cell culture media. A comprehensive summary toward the use of mainstream techniques for bioprocess monitoring is critically reviewed here, which illustrates the instrumental and procedural advances and limitations of several major analytical tools in biomanufacturing applications. Despite those drawbacks present in modern detection systems such as mass spectrometry, gas chromatography or chemical/biological sensors, a considerable number of useful solutions and inspirations such as electronic or optoelectronic noses can be offered to greatly overcome the restrictions and facilitate the development of advanced analytical techniques that can target a more diverse range of key nutritious components, products or potential contaminants in different biomanufacturing processes.
Oil sands process-affected water (OSPW) is generated during extraction of bitumen in the surface-mining oil sands industry in Alberta, Canada, and is acutely and chronically toxic to aquatic organisms. It is known that dissolved organic compounds in OSPW are responsible for most toxic effects, but knowledge of the specific mechanism(s) of toxicity, is limited. Using bioassay-based effects-directed analysis, the dissolved organic fraction of OSPW has previously been fractionated, ultimately producing refined samples of dissolved organic chemicals in OSPW, each with distinct chemical profiles. Using the Escherichia coli K-12 strain MG1655 gene reporter live cell array, the present study investigated relationships between toxic potencies of each fraction, expression of genes and characterization of chemicals in each of five acutely toxic and one non-toxic extract of OSPW derived by use of effects-directed analysis. Effects on expressions of genes related to response to oxidative stress, protein stress and DNA damage were indicative of exposure to acutely toxic extracts of OSPW. Additionally, six genes were uniquely responsive to acutely toxic extracts of OSPW. Evidence presented supports a role for sulphur- and nitrogen-containing chemical classes in the toxicity of extracts of OSPW.
Production and utilization of nanoparticles (NPs) are increasing due to their positive and stimulating effects on biological systems. Silver (Ag) NPs improve seed germination, photosynthetic efficiency, plant growth, and antimicrobial activities. In this study, the effects of chemo-blended Ag NPs on wheat were investigated using the gel-free/label-free proteomic technique. Morphological analysis revealed that chemo-blended Ag NPs resulted in the increase of shoot length, shoot fresh weight, root length, and root fresh weight. Proteomic analysis indicated that proteins related to photosynthesis and protein synthesis were increased, while glycolysis, signaling, and cell wall related proteins were decreased. Proteins related to redox and mitochondrial electron transport chain were also decreased. Glycolysis associated proteins such as glyceraldehyde-3-phosphate dehydrogenase increased as well as decreased, while phosphoenol pyruvate carboxylase was decreased. Antioxidant enzyme activities such as superoxide dismutase, catalase, and peroxidase were promoted in response to the chemo-blended Ag NPs. These results suggested that chemo-blended Ag NPs promoted plant growth and development through regulation of energy metabolism by suppression of glycolysis. Number of grains/spike, 100-grains weight, and yield of wheat were stimulated with chemo-blended Ag NPs. Morphological study of next generational wheat plants depicted normal growth, and no toxic effects were observed. Therefore, morphological, proteomic, yield, and next generation results revealed that chemo-blended Ag NPs may promote plant growth and development through alteration in plant metabolism.
With improved analytical techniques, environmental monitoring studies are increasingly able to report the occurrence of tens or hundreds of chemicals per site, making it difficult to identify the most relevant chemicals from a biological standpoint. For the present study, organic chemical occurrence was examined, individually and as mixtures, in the context of potential biological effects. Sediment was collected at 71 Great Lakes (USA/Canada) tributary sites and analyzed for 87 chemicals. Multiple risk-based lines of evidence were used to prioritize chemicals and locations, including comparing sediment concentrations and estimated porewater concentrations with established whole-organism benchmarks (i.e., sediment and water quality criteria and screening values) and with high-throughput toxicity screening data from the US Environmental Protection Agency's ToxCast database, estimating additive effects of chemical mixtures on common ToxCast endpoints, and estimating toxic equivalencies for mixtures of alkylphenols and polycyclic aromatic hydrocarbons (PAHs). This multiple-lines-of-evidence approach enabled the screening of more chemicals, mitigated the uncertainties of individual approaches, and strengthened common conclusions. Collectively, at least one benchmark/screening value was exceeded for 54 of the 87 chemicals, with exceedances observed at all 71 of the monitoring sites. Chemicals with the greatest potential for biological effects, both individually and as mixture components, were bisphenol A, 4-nonylphenol, indole, carbazole, and several PAHs. Potential adverse outcomes based on ToxCast gene targets and putative adverse outcome pathways relevant to individual chemicals and chemical mixtures included tumors, skewed sex ratios, reproductive dysfunction, hepatic steatosis, and early mortality, among others. The results provide a screening-level prioritization of chemicals with the greatest potential for adverse biological effects and an indication of sites where they are most likely to occur. Environ Toxicol Chem 2022;41:1016-1041. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Organic chemicals in the aquatic ecosystem may inhibit algae growth and subsequently lead to the decline of primary productivity. Growth inhibition tests are required for ecotoxicological assessments for regulatory purposes. In silico study is playing an important role in replacing or reducing animal tests and decreasing experimental expense due to its efficiency. In this work, a series of theoretical models was developed for predicting algal growth inhibition (log EC50) after 72 h exposure to diverse chemicals. In total 348 organic compounds were classified into five modes of toxic action using the Verhaar Scheme. Each model was established by using molecular descriptors that characterize electronic and structural properties. The external validation and leave-one-out cross validation proved the statistical robustness of the derived models. Thus they can be used to predict log EC50 values of chemicals that lack authorized algal growth inhibition values (72 h). This work systematically studied algal growth inhibition according to toxic modes and the developed model suite covers all five toxic modes. The outcome of this research will promote toxic mechanism analysis and be made applicable to structural diversity.
Exposure to fine particulate matter (PM2.5 ) from incomplete fossil fuel combustion (coal, oil, gas and diesel) has been linked to increased morbidity and mortality due to metabolic diseases. PM2.5 exaggerate adipose inflammation and insulin resistance in mice with diet-induced obesity. Here, we elucidate the hypothesis that such systemic effects may be triggered by adhered particle components affecting adipose tissue directly. Studying adipocytes differentiated from primary human mesenchymal stem cells, we found that lipophilic organic chemicals (OC) from diesel exhaust particles induced inflammation-associated genes and increased secretion of the chemokine CXLC8/interleukin-8 as well as matrix metalloprotease 1. The oxidative stress response gene haem oxygenase-1 and tumour necrosis factor alpha were seemingly not affected, while aryl hydrocarbon receptor-regulated genes, cytochrome P450 1A1 (CYP1A1) and CYP1B1 and plasminogen activator inhibitor-2, were clearly up-regulated. Finally, expression of β-adrenergic receptor, known to regulate adipocyte homoeostasis, was down-regulated by exposure to these lipophilic OC. Our results indicate that low concentrations of OC from combustion particles have the potential to modify expression of genes in adipocytes that may be linked to metabolic disease. Further studies on mechanisms linking PM exposure and metabolic diseases are warranted.
The Control of Substances Hazardous to Health (COSHH) Essentials model was evaluated using full-shift exposure measurements of five chemical components in a mixture [acetone, ethylbenzene, methyl ethyl ketone, toluene, and xylenes] at a medium-sized plant producing paint materials. Two tasks, batch-making and bucket-washing, were examined. Varying levels of control were already established in both tasks and the average exposures of individual chemicals were considerably lower than the regulatory and advisory 8-h standards. The average exposure fractions using the additive mixture formula were also less than unity (batch-making: 0.25, bucket-washing: 0.56) indicating the mixture of chemicals did not exceed the combined occupational exposure limit (OEL). The paper version of the COSHH Essentials model was used to calculate a predicted exposure range (PER) for each chemical according to different levels of control. The estimated PERs of the tested chemicals for both tasks did not show consistent agreement with exposure measurements when the comparison was made for each control method and this is believed to be because of the considerably different volatilities of the chemicals. Given the combination of health hazard and exposure potential components, the COSHH Essentials model recommended a control approach 'special advice' for both tasks, based on the potential reproductive hazard ascribed to toluene. This would not have been the same conclusion if some other chemical had been substituted (for example styrene, which has the same threshold limit value as toluene). Nevertheless, it was special advice, which had led to the combination of hygienic procedures in place at this plant. The probability of the combined exposure fractions exceeding unity was 0.0002 for the batch-making task indicating that the employees performing this task were most likely well protected below the OELs. Although the employees involved in the bucket-washing task had greater potential to exceed the threshold limit value of the mixture (P > 1 = 0.2375), the expected personal exposure after adjusting for the assigned protection factor for the respirators in use would be considerably lower (P > 1 = 0.0161). Thus, our findings suggested that the COSHH essentials model worked reasonably well for the volatile organic chemicals at the plant. However, it was difficult to override the reproductive hazard even though it was meant to be possible in principle. Further, it became apparent that an input of existing controls, which is not possible in the web-based model, may have allowed the model be more widely applicable. The experience of using the web-based COSHH Essentials model generated some suggestions to provide a more user-friendly tool to the model users who do not have expertise in occupational hygiene.
Effluent discharged from the pulp and paper industry contains various refractory and androgenic compounds, even after secondary treatment by activated processes. Detailed knowledge is not yet available regarding the properties of organic pollutants and methods for their bioremediation. This study focused on detecting residual organic pollutants of pulp and paper mill effluent after biological treatment and assessing their degradability by biostimulation. The major compounds identified in the effluent were 2,3,6-trimethylphenol, 2-methoxyphenol (guaiacol), 2,6-dimethoxyphenol (syringol), methoxycinnamic acid, pentadecane, octadecanoic acid, trimethylsilyl ester, cyclotetracosane, 5,8-dimethoxy-6-methyl-2,4-bis(phenylmethyl)napthalen-1-ol, and 1,2-benzendicarboxylic acid diisononyl ester. Most of these compounds are classified as endocrine-disrupting chemicals and environmental toxicants. Some compounds are lignin monomers that are metabolic products from secondary treatment of the discharged effluent. This indicated that the existing industrial process could not further degrade the effluent. Supplementation by carbon (glucose 1.0%) and nitrogen (peptone 0.5%) bio-stimulated the degradation process. The degraded sample after biostimulation showed either disappearance or generation of metabolic products under optimized conditions, i.e., a stirring rate of 150 rpm and temperature of 37 ± 1°C after 3 and 6 days of bacterial incubation. Isolated potential autochthonous bacteria were identified as Klebsiella pneumoniae IITRCP04 (KU715839), Enterobacter cloacae strain IITRCP11 (KU715840), Enterobacter cloacae IITRCP14 (KU715841), and Acinetobacter pittii strain IITRCP19 (KU715842). Lactic acid, benzoic acid, and vanillin, resulting from residual chlorolignin compounds, were generated as potential value-added products during the detoxification of effluent in the biostimulation process, supporting the commercial importance of this process.
Extensive utilization of silver nanoparticles (NPs) in agricultural products results in their interaction with other chemicals in the environment. To study the combined effects of silver NPs with nicotinic acid and potassium nitrate (KNO3), a gel-free/label-free proteomic technique was used. Root length/weight and hypocotyl length/weight of soybean were enhanced by silver NPs mixed with nicotinic acid and KNO3. Out of a total 6340 identified proteins, 351 proteins were significantly changed, out of which 247 and 104 proteins increased and decreased, respectively. Differentially changed proteins were predominantly associated with protein degradation and synthesis according to the functional categorization. Protein-degradation-related proteins mainly consisted of the proteasome degradation pathway. The cell death was significantly higher in the root tips of soybean under the combined treatment compared to flooding stress. Accumulation of calnexin/calreticulin and glycoproteins was significantly increased under flooding with silver NPs, nicotinic acid, and KNO3. Growth of soybean seedlings with silver NPs, nicotinic acid, and KNO3 was improved under flooding stress. These results suggest that the combined mixture of silver NPs, nicotinic acid, and KNO3 causes positive effects on soybean seedling by regulating the protein quality control for the mis-folded proteins in the endoplasmic reticulum. Therefore, it might improve the growth of soybean under flooding stress.
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