Concentrations Of Individual Chemicals Research Articles

Optimization of Gelatin Methacryloyl Hydrogel Properties through an Artificial Neural Network Model.

Gelatin methacryloyl (GelMA) hydrogels are promising materials for tissue engineering applications due to their biocompatibility and tunable properties. However, the time-consuming process of preparing GelMA hydrogels with desirable properties for specific biomedical applications limits their clinical use. Visible-light-induced cross-linking is a well-known method for the preparation of GelMA hydrogels; however, a comprehensive investigation on the influence of critical parameters such as Eosin Y (EY), triethanolamine (TEA), and N-vinyl-2-pyrrolidone (NVP) concentrations on the stiffness and gelation time has yet to be performed. In this study, we systematically investigated the effect of these critical parameters on the stiffness and gelation time of GelMA hydrogels. We developed an artificial neural network (ANN) model with three input variables, EY, TEA, and NVP concentrations, and two output variables, Young's modulus and gelation time, derived from our experimental design. Through the alteration of individual chemical concentrations, [EY] between 0.005 and 0.5 mM and [TEA] and [NVP] between 10 and 1000 mM, we studied the impact of these alterations on the real-time values of stiffness and gelation time. Furthermore, we demonstrated the validity of the ANN model in predicting the properties of GelMA hydrogels. We also studied cell survival to establish nontoxic concentration ranges for each component, enabling safer use of GelMA hydrogels in relevant biomedical applications. Our results showed that the ANN model can accurately predict the properties of GelMA hydrogels, allowing for the synthesis of hydrogels with desirable stiffness for various biomedical applications. In conclusion, our study provides a comprehensive library that characterizes the stiffness and gelation time and demonstrates the potential of the ANN model to predict these properties of GelMA hydrogels depending on the critical parameters. The ANN models developed here can facilitate the optimization of GelMA hydrogels with the most efficient mechanical properties that resemble a native extracellular matrix and better address the need in the in vivo microenvironment. The approach of this study is to bring research about the synthesis of GelMA hydrogels to a new level where the synthesis of these hydrogels can be standardized with minimum cost and effort.

Evaluation of volatile organic compound (VOC) emissions from memory foam mattresses and potential implications for consumer health risk.

Chemical emissions from two new memory foam mattresses were evaluated in a simulated consumer use environment over the course of 32 days. Passive 12- and 24-h samples (n=62) were collected for various VOCs. Airborne concentrations of chemicals associated with the mattresses (2-propanol, acetone, chloromethane, toluene, and ΣVOC) peaked during the first day after installation and progressively decayed over the course of the following 31 days. Emission rates were derived using a two-phase, double exponential source decay model paired with a one-compartment generalized indoor air quality model; short- and long-term emission half-lives for individual chemicals were on the order of hours (approximately 4 or 12h) and days (approximately 24 days), respectively. Model-estimated average ΣVOC concentrations for the 32-day period of the study were approximately 20 and 33μg/m3 for Mattress 1 and 2, respectively, while the modeled one-year average concentrations were 2.7 and 4.2μg/m3, respectively. First-year trends for both mattresses were qualitatively similar, with the sum of 2-propanol, acetone, chloromethane, and toluene contributing to approximately 81% and 95% of the first-year ΣVOC concentration of Mattress 1 and 2, respectively. The airborne concentrations of individual chemicals and ΣVOC measured and modeled in this study were well below available health-based benchmarks for individual chemicals and within available indoor air quality recommendations for ΣVOC, suggesting that it is unlikely that the use of the models of mattresses evaluated in this study would pose a health risk to consumers.

An eight-compound mixture but not corresponding concentrations of individual chemicals induces triglyceride accumulation in human liver cells

In real life, organisms are exposed to complex mixtures of chemicals at low concentration levels, whereas research on toxicological effects is mostly focused on single compounds at comparably high doses. Mixture effects deviating from the assumption of additivity, especially synergistic effects, are of concern. In an adverse outcome pathway (AOP)-guided manner, we analyzed the accumulation of triglycerides in human HepaRG liver cells by a mixture of eight steatotic chemicals (amiodarone, benzoic acid, cyproconazole, flusilazole, imazalil, prochloraz, propiconazole and tebuconazole), each present below its individual effect concentration at 1–3 μM. Pronounced and significantly enhanced triglyceride accumulation was observed with the mixture, and similar effects were seen at the level of pregnane-X-receptor activation, a molecular initiating event leading to hepatic steatosis. Transcript pattern analysis indicated subtle pro-steatotic changes at low compound concentrations, which did not exert measurable effects on cellular triglycerides. Mathematical modeling of mixture effects indicated potentially more than additive behavior using a model for compounds with similar modes of action. The present data underline the usefulness of AOP-guided in vitro testing for the identification of mixture effects and highlight the need for further research on chemical mixtures and harmonization of data interpretation of mixture effects.

Risk Characterization and Probabilistic Concentration-Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays.

Background:Risk assessment of chemical mixtures or complex substances remains a major methodological challenge due to lack of available hazard or exposure data. Therefore, risk assessors usually infer hazard or risk from data on the subset of constituents with available toxicity values.Objectives:We evaluated the validity of the widely used traditional mixtures risk assessment paradigms, Independent Action (IA) and Concentration Addition (CA), with new approach methodologies (NAMs) data from human cell-based in vitro assays.Methods:A diverse set of 42 chemicals was tested both individually and as mixtures for functional and cytotoxic effects in vitro. A panel of induced pluripotent stem cell (iPSCs)-derived models (hepatocytes, cardiomyocytes, endothelial, and neurons) and one primary cell type (HUVEC) were used. Bayesian concentration–response modeling of individual chemicals or their mixtures was performed for a total of 47 phenotypes to derive point-of-departure (POD) values. Probabilistic IA or CA was conducted to estimate the mixture effects based on the bioactivity profiles from the individual chemicals and compared with mixture bioactivity.Results:All mixtures showed significant bioactivity, even though some were constructed using individual chemical concentrations considered “low” or “safe.” Even though CA is much more accurate as a predictor of mixture effects in comparison with IA, with CA-based POD typically within an order of magnitude of the actual mixture, in some cases, the bioactivity of the mixtures appeared to be much greater than that of their components under either additivity assumption.Discussion:These results suggest that CA is a preferred first approximation for predicting mixture toxicity when data for all constituents are available. However, because the accuracy of additivity assumptions varies greatly across phenotypes, we posit that mixtures and complex substances need to be directly tested for their hazard potential. NAMs provide a practical solution that rapidly yields highly informative data for mixtures risk assessment. https://doi.org/10.1289/EHP7600

Organophosphate and novel brominated flame retardants exposure in childbearing women via house dust

PDS 62: Chemicals and metals: exposure and biomarkers, Johan Friso Foyer, Floor 1, August 28, 2019, 10:30 AM - 12:00 PM Background: Polybrominated diphenyl ethers, suspected endocrine disruptors, have been replaced by organophosphate (OPFR) and novel brominated flame retardants (NBFR). OPFRs and NBFRs readily migrate from consumer products, including furniture and electronics, into dust where humans are exposed via accidental ingestion and inhalation. Toxicological studies have found potential carcinogenicity, endocrine disruption, and neurobehavioral alterations from these alternative flame retardants. However, no comprehensive assessments of exposure to OPFRs and NBFRs have been completed in a longitudinal cohort. Methods: We quantified concentrations of OPFRs and NBFRs in house dust samples (n=317) collected from pregnant women (~20 weeks) enrolled in the Health Outcomes and Measures of the Environment (HOME) Study in Cincinnati, Ohio (2003-2006). We used multiple regression modeling to identify personal characteristics that were associated with concentrations of individual chemicals and summary concentrations for each class. Finally, we estimated personal daily dust exposure for each participant based on dust concentration and cross-sectional weight data. Results: Tris(1-chloro-2-propyl)phosphate (TCIPP) (median: 1860 ng/g, range: 70.1-166,000 ng/g), tris(1,3-dichloro-2-propyl)phosphate (TDCIPP) (median: 1860 ng/g, range: 55.2-228,000 ng/g), triphenyl phosphate (TPHP) (median: 995 ng/g, range: 34.1-62,100 ng/g), 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) (median: 45.8 ng/g, range: 2.82-7,800 ng/g), and bis(2-ethylhexyl)tetrabromophthalate (BEH-TEBP) (median: 115 ng/g, range 2.17-13,600 ng/g) were all detected in over 90% of dust samples; tris(2-chloroethyl)phosphate (TCEP) (median: 759.4 ng/g, range: 56.8-160,000 ng/g) was detected in 80.1% of samples. Concentrations of individual chemicals, ∑OPFRs, and ∑NBFRs were associated with the number of people living in the home, race, education, floor type, and visible cleanliness of the room. Daily exposure to ∑OPFRs from dust was 2.1 ng/kg/day based on average dust ingestion and 6.3 ng/kg/day among women in the 95th percentile of dust ingestion. Conclusions: This study shows that OPFRs and NBFRs are ubiquitous in childbearing women’s house dust, and justifies more research on the consequences of exposure in these concentration ranges.

Bisphenol A, phthalate metabolites and glucose homeostasis in healthy normal-weight children.

IntroductionBisphenol A and several of the most commonly used phthalates have been associated with adverse metabolic health effects such as obesity and diabetes. Therefore, we analyzed these man-made chemicals in first morning urine samples from 107 healthy normal-weight Danish children and adolescents.MethodThis was a cross-sectional study. Participants were recruited as part of the Copenhagen Puberty Study. The subjects were evaluated by an oral glucose tolerance test (OGTT), a dual-energy X-ray absorptiometry (DXA) scan, direct oxygen uptake measurement during cycle ergometry and fasting blood samples. First morning urine was collected and phthalate metabolites and BPA were measured by liquid chromatography-tandem mass spectrometry (LC–MS/MS) with prior enzymatic deconjugation. Individual chemical concentrations were divided into tertiles and analyzed in relation to biological outcome.ResultsChildren in the lowest tertile of urinary BPA had significantly higher peak insulin levels during OGTT (P = 0.01), lower insulin sensitivity index (P < 0.01), higher leptin (P = 0.03), triglyceride (P < 0.01) and total cholesterol levels (P = 0.04), lower aerobic fitness (P = 0.02) and a tendency toward higher fat mass index (P = 0.1) compared with children in the highest tertile for uBPA. No significant differences in anthropometrics, body composition or glucose metabolism were associated with any of the phthalate metabolites measured.ConclusionThis pilot study on healthy normal-weight children suggests an inverse association between BPA and insulin resistance. Our findings contrast other cross-sectional studies showing a positive association for BPA, which may be due to confounding or reverse causation because diet is an important source of both BPA exposure and obesity.

Investigation of 10 herbicides in surface waters of a horticultural production catchment in southeastern Australia.

Herbicides are regularly applied in horticultural production systems and may migrate off-site, potentially posing an ecological risk to surface waterways. However, few studies have investigated the levels and potential ecotoxicological impact of herbicides in horticultural catchments in southern Australia. This study investigated the presence of 10 herbicides at 18 sites during a 5-month period in horticulturally important areas of the Yarra Valley in southeastern Australia. Seven of the 10 herbicides were detected in the streams, in 39% of spot water samples, in 25% of surface sediment samples, and in >70% of the passive sampler systems deployed. Few samples contained residues of ≥2 herbicides. Simazine was the herbicide most frequently detected in water, sediment, and passive sampler samples and had the highest concentrations in water (0.67μg/L) and sediment (260μg/kg dry weight). Generally the concentrations of the herbicides detected were several orders of magnitude lower than reported ecotoxicological effect values, including those for aquatic plants and algae, suggesting that concentrations of individual chemicals in the catchment were unlikely to pose an ecological risk. However, little is known about the combined effects of simultaneous, low-level exposure of multiple herbicides of the same mode of action on Australian aquatic organisms nor their contribution when found in mixtures with other pesticides. Further research is required to adequately assess the risk of pesticides in Victorian aquatic environments.

0296 The NIEHS GuLF STUDY: Correlations of Concentrations Between Various Oil Chemicals and Total Hydrocarbons

ObjectivesIn the 2010 Deepwater Horizon Oil Spill, thousands of workers may have been exposed to various potentially harmful chemicals found in crude oil including benzene, ethylbenzene, xylene, and toluene. These...

Toxicity on the luminescent bacterium Vibrio fischeri (Beijerinck). II: Response to complex mixtures of heterogeneous chemicals at low levels of individual components

The toxicity of eight complex mixtures of chemicals with different chemical structures and toxicological modes of action (narcotics, polar narcotics, herbicides, insecticides, fungicides) was tested on the luminescent bacterium Vibrio fischeri. There were maximum 84 individual chemicals in the mixtures. Suitable statistical approaches were applied for the comparison between experimental results and theoretical predictions. The results demonstrated that the two models of Concentration Addition (CA) and Independent Action (IA) are suitable to explain the effect of the mixtures.Even extremely lower concentrations of individual chemicals contributed to the effect of the mixtures. Synergistic effects were not observed in any of the tested mixtures.In particular, the CA approach well predicted the effects of six out of eight mixtures and slightly overestimated the effects of the remaining two mixtures. Therefore, the CA model can be proposed as a pragmatic and adequately protective approach for regulatory purposes.

Selective Quantification by 2D HSQC0 Spectroscopy of Thiocoraline in an Extract from a Sponge-Derived Verrucosispora sp.

We recently developed a 2D 1H-13C HSQC0 approach to quantify individual chemicals in complex mixtures. The HSQC0 approach has been implemented in phase-cycled and gradient-selective versions. As in quantitative 1D NMR, the normalized integrated signal intensities in HSQC0 are proportional to the concentrations of individual chemicals in the mixture. We applied the HSQC0 approach to selectively quantify thiocoraline present at a level of 1% w/w in an extract from a Verrucosispora sp. isolated from the sponge Chondrilla caribensis f. caribensis. We expect that this approach can be used to quantify other natural products of interest in extracts without prior purification.

The synergistic toxicity of pesticide mixtures: implications for risk assessment and the conservation of endangered Pacific salmon.

BackgroundMixtures of organophosphate and carbamate pesticides are commonly detected in freshwater habitats that support threatened and endangered species of Pacific salmon (Oncorhynchus sp.). These pesticides inhibit the activity of acetylcholinesterase (AChE) and thus have potential to interfere with behaviors that may be essential for salmon survival. Although the effects of individual anticholin-esterase insecticides on aquatic species have been studied for decades, the neurotoxicity of mixtures is still poorly understood.ObjectivesWe assessed whether chemicals in a mixture act in isolation (resulting in additive AChE inhibition) or whether components interact to produce either antagonistic or synergistic toxicity.MethodsWe measured brain AChE inhibition in juvenile coho salmon (Oncorhynchus kisutch) exposed to sublethal concentrations of the organophosphates diazinon, malathion, and chlorpyrifos, as well as the carbamates carbaryl and carbofuran. Concentrations of individual chemicals were normalized to their respective median effective concentrations (EC50) and collectively fit to a nonlinear regression. We used this curve to determine whether toxicologic responses to binary mixtures were additive, antagonistic, or synergistic.ResultsWe observed addition and synergism, with a greater degree of synergism at higher exposure concentrations. Several combinations of organophosphates were lethal at concentrations that were sublethal in single-chemical trials.ConclusionSingle-chemical risk assessments are likely to underestimate the impacts of these insecticides on salmon in river systems where mixtures occur. Moreover, mixtures of pesticides that have been commonly reported in salmon habitats may pose a more important challenge for species recovery than previously anticipated.

Autism Spectrum Disorders in Relation to Distribution of Hazardous Air Pollutants in the San Francisco Bay Area

ObjectiveTo explore possible associations between autism spectrum disorders (ASD) and environmental exposures, we linked the California autism surveillance system to estimated hazardous air pollutant (HAP) concentrations compiled by the U.S. Environmental Protection Agency.MethodsSubjects included 284 children with ASD and 657 controls, born in 1994 in the San Francisco Bay area. We assigned exposure level by census tract of birth residence for 19 chemicals we identified as potential neurotoxicants, developmental toxicants, and/or endocrine disruptors from the 1996 HAPs database. Because concentrations of many of these were highly correlated, we combined the chemicals into mechanistic and structural groups, calculating summary index scores. We calculated ASD risk in the upper quartiles of these group scores or individual chemical concentrations compared with below the median, adjusting for demographic factors.ResultsThe adjusted odds ratios (AORs) were elevated by 50% in the top quartile of chlorinated solvents and heavy metals [95% confidence intervals (CIs), 1.1–2.1], but not for aromatic solvents. Adjusting for these three groups simultaneously led to decreased risks for the solvents and increased risk for metals (AORs for metals: fourth quartile = 1.7; 95% CI, 1.0–3.0; third quartile = 1.95; 95% CI, 1.2–3.1). The individual compounds that contributed most to these associations included mercury, cadmium, nickel, trichloroethylene, and vinyl chloride.ConclusionsOur results suggest a potential association between autism and estimated metal concentrations, and possibly solvents, in ambient air around the birth residence, requiring confirmation and more refined exposure assessment in future studies.

Metallic and organic contaminants in sediments of Sydney Harbour, Australia and vicinity — A chemical dataset for evaluating sediment quality guidelines

An internally consistent dataset comprising 103 surficial estuarine sediment samples were collected from Sydney Harbour, Australia and locations south of Sydney. This paper describes the chemical characteristics of the dataset and evaluates its suitability for use in evaluating biological effects-based sediment quality guidelines (SQGs). The sediments contained mixtures of chemicals, the most prevalent chemical classes being metals and polycyclic aromatic hydrocarbons, whereas sediments from coastal lakes/estuaries south of Sydney had low concentrations of contaminants. Maximum concentrations of the prevalent contaminants zinc, lead, copper and pyrene were 11300, 1420, 1060 mg kg−1 and 23300 μg kg−1, respectively. For the majority of samples, concentrations of individual chemicals exceeded most effects-based SQGs that have been adopted for use in Australia, implying occasional or frequent adverse biological effects are expected. Comparing mixtures of contaminants to ranges in numbers of SQGs exceeded and mean SQG quotients showed that most samples (57% to 68%) had contamination characteristics associated with moderate probabilities (30% to 52%) of acute toxicity, based on North American data. A smaller proportion of samples (15% to 17%) had contamination characteristics associated with high probabilities (74% to 85%) of toxicity. The wide range of chemicals and concentrations, associated with low, medium and high probabilities of toxicity, indicated that the dataset was suitable for future use in evaluating predictive abilities of SQGs. This is relevant, given the recent introduction of North American-derived SQGs for Australia.

A modeling approach to account for toxicokinetic interactions in the calculation of biological hazard index for chemical mixtures

Biological hazard index (BHI) is defined as biological level tolerable for exposure to mixture, and is calculated by an equation similar to the conventional hazard index. The BHI calculation, at the present time, is advocated for use in situations where toxicokinetic interactions do not occur among mixture constituents. The objective of this study was to develop an approach for calculating interactions-based BHI for chemical mixtures. The approach consisted of simulating the concentration of exposure indicator in the biological matrix of choice (e.g. venous blood) for each component of the mixture to which workers are exposed and then comparing these to the established BEI values, for calculating the BHI. The simulation of biomarker concentrations was performed using a physiologically-based toxicokinetic (PBTK) model which accounted for the mechanism of interactions among all mixture components (e.g. competitive inhibition). The usefulness of the present approach is illustrated by calculating BHI for varying ambient concentrations of a mixture of three chemicals (toluene (5–40 ppm), m-xylene (10–50 ppm), and ethylbenzene (10–50 ppm)). The results show that the interactions-based BHI can be greater or smaller than that calculated on the basis of additivity principle, particularly at high exposure concentrations. At lower exposure concentrations (e.g. 20 ppm each of toluene, m-xylene and ethylbenzene), the BHI values obtained using the conventional methodology are similar to the interactions-based methodology, confirming that the consequences of competitive inhibition are negligible at lower concentrations. The advantage of the PBTK model-based methodology developed in this study relates to the fact that, the concentrations of individual chemicals in mixtures that will not result in a significant increase in the BHI (i.e. >1) can be determined by iterative simulation.

Spatial-temporal variations in snowfall chemistry in the montreal region

Snowfall was collected on an event basis for 6 winter storms in 1980 at 10 locations around the greater Montreal region. Six sites were urban, 2 suburban and 2 rural (small town). For all storms, 4 of the urban stations had the highest pH of the 10 locations, with the 6 Montreal Island sites having the highest chemical concentrations. Employing principal component analysis, two chemical species associations are apparent: (1) an alkaline/fly ash factor and (2) an ‘acid snow’ factor. The former indicates the possible effects of local emissions. Generally, the storms produced individual chemical concentrations patterns enabling five of the storms to be separated into distinct events. Three storms were designated as ‘type’ storms in which pH, sulphates, and nitrates varied according to individual storm characteristics and air trajectories. If the air trajectory passed over SOx and NOx sources to the west and south-west (Ontario-Great Lakes region) pH values were lower and sulphate and nitrate concentrations in the snowfall higher.