Individual Chemicals Research Articles

Pharmacological characterization of kratom alkaloids at opiate receptors: binding affinities, in vitro and in vivo functional assessments

Kratom (Mitragyna speciosa) is consumed by 10‐15 million individuals in the US for its mood‐elevating effects, as an alternative to traditional opiates for pain relief and to attenuate opiate withdrawal symptoms. Complex natural products, such as kratom, contain a variety of chemicals whose combined effects can only be understood by the meticulous identification and characterization of the individual chemicals and their effects in preclinical model systems. Twenty‐five indole and oxindole kratom alkaloids were evaluated for mu (MOR), delta (DOR) and kappa (KOR) opiate receptors binding affinities, opiate receptor mediated G‐protein activation, inhibition of forskolin stimulated cAMP accumulation and b‐arrestin2 recruitment. Several indole and oxindole alkaloids exhibited partial agonism at the MOR (7‐hydroxymitragynine, corynoxine A > epiallo‐isopaynantheine, isospeciofoline, speciociliatine, corynoxine B > mitragynine, 3‐epicorynoxine B > paynantheine and speciogynine) – all of which also exhibited strong G protein bias. Mitraciliatine and isopaynantheine were weak MOR antagonists. Speciophylline exhibited positive allosteric modulatory activity at the MOR as evidenced by increased affinity of DAMGO binding and potentiation of [met]‐enkephalin‐induced inhibition of forskolin stimulated cAMP activity in the absence of intrinsic activity. Corynoxine A induced displayed similar affinity at the mu opiate receptor as 7 hydroxymitragynine but was less potent in the nociceptive hot plate assay and the mechanical allodynia von Frey test. Corynoxine did not significantly alter respiration or heart rate or induce a conditioned place preference. Results demonstrate the pharmacological complexity of kratom alkaloids and have important implications for determining the combined effects of less abundant indole and oxindole alkaloids with regard to the therapeutic as well as potential harmful effects of kratom.

Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells

There are thousands of chemicals that humans can be exposed to in their everyday environments, the majority of which are currently understudied and lack substantial testing for potential exposure and toxicity. This study aimed to implement in silico methods to characterize the chemicals that co-occur across chemical and product uses in our everyday household environments that also target a common molecular mediator, thus representing understudied mixtures that may exacerbate toxicity in humans. To detail, the Chemical and Products Database (CPDat) was queried to identify which chemicals co-occur across common exposure sources. Chemicals were preselected to include those that target an important mediator of cell health and toxicity, the peroxisome proliferator activated receptor gamma (PPARγ), in liver cells that were identified through query of the ToxCast/Tox21 database. These co-occurring chemicals were thus hypothesized to exert potential joint effects on PPARγ. To test this hypothesis, five commonly co-occurring chemicals (namely, benzyl cinnamate, butyl paraben, decanoic acid, eugenol, and sodium dodecyl sulfate) were tested individually and in combination for changes in the expression of PPARγ and its downstream target, insulin receptor (INSR), in human liver HepG2 cells. Results showed that these likely co-occurring chemicals in household environments increased both PPARγ and INSR expression more significantly when the exposures occurred as mixtures vs. as individual chemicals. Future studies will evaluate such chemical combinations across more doses, allowing for further quantification of the types of joint action while leveraging this method of chemical combination prioritization. This study demonstrates the utility of in silico-based methods to identify chemicals that co-occur in the environment for mixtures toxicity testing and highlights relationships between understudied chemicals and changes in PPARγ-associated signaling.

Predicting the binding of small molecules to nuclear receptors using machine learning.

Nuclear receptors (NRs) are important biological targets of endocrine-disrupting chemicals (EDCs). Identifying chemicals that can act as EDCs and modulate the function of NRs is difficult because of the time and cost of in vitro and in vivo screening to determine the potential hazards of the 100000s of chemicals that humans are exposed to. Hence, there is a need for computational approaches to prioritize chemicals for biological testing. Machine learning (ML) techniques are alternative methods that can quickly screen millions of chemicals and identify those that may be an EDC. Computational models of chemical binding to multiple NRs have begun to emerge. Recently, a Nuclear Receptor Activity (NuRA) dataset, describing experimentally derived small-molecule activity against various NRs has been created. We have used the NuRA dataset to develop an ensemble of ML-based models to predict the agonism, antagonism, binding and effector binding of small molecules to nine different human NRs. We defined the applicability domain of the ML models as a measure of Tanimoto similarity to the molecules in the training set, which enhanced the performance of the developed classifiers. We further developed a user-friendly web server named 'NR-ToxPred' to predict the binding of chemicals to the nine NRs using the best-performing models for each receptor. This web server is freely accessible at http://nr-toxpred.cchem.berkeley.edu. Users can upload individual chemicals using Simplified Molecular-Input Line-Entry System, CAS numbers or sketch the molecule in the provided space to predict the compound's activity against the different NRs and predict the binding mode for each.

ChemESI (Chemical Environmental Sustainability Index)—A KPI (Key Performance Indicator) for Standardizing Environmental Metrics for Chemical Sustainability

As part of the ESG (Environmental, Social, and Governance) dynamics, chemical environmental sustainability, i.e., the impact from chemicals and how to measure it across hundreds of products, is a daunting, but necessary task. Although methods are available to measure the effects and impacts of a single chemical, most enterprises do not focus on a single chemical, let alone produce “pure” chemicals for sale. Nearly all chemicals in commerce are chemical products, i.e., mixtures, while assessment methods for mixtures are few and far between. What is needed is a metric that tracks the potential risk of an enterprise's total product inventory while monitoring its improvements as it greens in coming years. The Chemical Environmental Sustainability Index (ChemESI) metric measures both risk (as the product of exposure and hazard) and hazard across numerous chemicals as a single metric/KPI. The ChemESI's for chemicals, products and facilities are expressed such that they can be summed across facilities to wrap up into a single corporate ChemESI KPI for either hazard or risk. But what about growth—if growth occurs using greener chemical inventory, a company can both grow and improves its ChemESI KPI. Given the lead-time for developing more, true green alternatives to existing chemicals, intermediate substitution of less hazardous “analogs” may drive initial ChemESI reduction. To achieve a representative risk estimate, a primary data need is chemical characterization data for products. SDS's (Safety Data Sheets) unfortunately make poor substitutes for true constituent analyses. A definite need exists for better, more detailed chemical characterization data for both mixtures and individual chemicals, as the latter most often are not 100 % “pure.” However, these SDS's are available universally, across the globe, and provide GHS (UN Globally Harmonized System) classifications for single endpoint chemical hazard assessment. GHS classifications are near universal and here used to derive chemical hazard scores over multiple endpoints for each chemical. A ChemESI Risk metric can be derived by multiplying the hazard score by the exposure, here using inventory as a surrogate. The ChemESI Hazard metric is then derived as an inventory weighted hazard score.

Complex chemical cocktail, containing insecticides diazinon and permethrin, drives acute toxicity to crustaceans in mountain lakes

Mountain lakes have long been perceived as pristine environments. However, atmospheric deposition of persistent organic pollutants (POPs) have been shown to expose these sensitive ecosystems to chemical pollution. Little is known on how this pollution impacts aquatic ecosystems at high altitudes. We combined passive sampling with liquid and gas chromatography high resolution mass spectrometry (LC- and GC-HRMS) to screen the water of eight lakes in three different regions of the French Pyrenees. In total, we screened for 479 organic chemicals including POPs, polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, biocides, and musk fragrances. We detected a complex cocktail of 151 individual chemicals and used their toxic unit summation (ΣTU) to assess toxicity for crustaceans and algae. While risks for algae never reached chronic risks, this was always the case for crustaceans. Acute toxic risk thresholds for crustaceans were even exceeded in several of our sites. At sites with acute toxic risk levels (> 0.1 ΣTU) crustaceans were completely absent or showed a low abundance. We conclude that crustaceans were at least partly impacted by the high toxic risks driven by the insecticides diazinon and permethrin. These drugs are widely used to protect livestock from blue tongue disease transmitted by sucking insects, suggesting free roaming livestock as local source. Our results provide important evidence on toxic chemical pollution in relatively remote mountain areas, with important consequences for aquatic mountain ecosystems.

Supporting the fight against the proliferation of chemical weapons through cheminformatics

Abstract International frameworks have been put in place to foster chemical weapons nonproliferation and disarmament. These frameworks feature lists of chemicals that can be used as chemical weapons or precursors for their synthesis (CW-control lists). In these lists, chemicals of concern are described through chemical names and CAS Registry Numbers®. Importantly, in some CW-control lists, some entries, rather than specifying individual chemicals, describe families of related chemicals. Working with CW-control lists poses challenges for frontline customs and export control officers implementing these frameworks. Entries that describe families of chemicals are not easy to interpret, especially for non-chemists. Moreover, synonyms and chemical variants complicate the issue of checking CW-control lists through names and registry numbers. To ameliorate these problems, we have developed a functioning prototype of a cheminformatics tool that automates the task of assessing whether a chemical is part of a CW-control list. The tool, dubbed the Nonproliferation Cheminformatics Compliance Tool (NCCT), is a database management system (based on ChemAxon’s Instant JChem) with an embedded database of chemical structures. The key feature of the database is that it contains not only the structures of the individually listed chemicals, but also the generic structures that describe the entries relative to families of chemicals (Markush structures).

Modification of cleaning product formulations could improve indoor air quality.

Cleaning products contain numerous individual chemicals, which can be liberated on use. These species can react in air to form new chemical species, some of which are harmful to health. This paper uses a detailed chemical model for indoor air chemistry, to understand the chemical reactions that can occur following cleaning, assuming cleaning products with different proportions of limonene, α‐pinene, and β‐pinene are used. The tests included the pure compounds, 50:50 mixtures and mixtures in proportion to the rates of reaction with ozone and the hydroxyl radical. For the 3 h following cleaning, pure α‐pinene was most efficient at producing particles, pure limonene for nitrated organic material, and a 50:50 mixture of β‐pinene and limonene for formaldehyde, leading to enhancements of 1.1 μg/m3, 400 ppt, and 1.8 ppb, respectively, compared to no cleaning. Cleaning in the afternoon enhanced concentrations of secondary pollutants for all the mixtures, owing to higher outdoor and hence indoor ozone compared to the morning. These enhancements in concentrations lasted several hours, despite the cleaning emissions only lasting for 10 min. Doubling the air exchange rate enhanced concentrations of formaldehyde and particulate matter by ~15% while reducing that of nitrated organic material by 13%. Changing product formulations has the potential to change the resulting indoor air quality and consequently, impacts on health.

Prenatal exposure to phthalates and phenols and preclinical vascular health during early adolescence.

Exposure to endocrine-disrupting chemicals may increase cardiovascular risk from early life, but studies in children have shown inconsistent results, most focused on analysis of single chemicals, and none included measures of micro-vascularization as early preclinical markers. This study aimed to evaluate the association between prenatal exposure to phthalates and phenols and macro- and microvascular health during early adolescence. Using data from a Spanish birth cohort (n=416), prenatal exposure to eight phthalate metabolites and seven phenols (bisphenol A, four parabens, benzophenone-3, triclosan) were assessed using first and/or third trimester spot-urine concentrations. Macrovascular health (systolic and diastolic blood pressure (SBP and DBP, mmHg), pulse wave velocity (PWV, m/s)) and microvascular health (central retinal artery/vein equivalent (CRAE/CRVE, μm)), were measured at 11 years old. Linear regression models assessed associations for individual chemicals and Bayesian weighted quantile sum regression (BWQS) evaluated the overall association of the phthalate and phenol mixture with cardiovascular health. In single exposure models, bisphenol-A was associated with decreased PWV (β per doubling of exposure=-0.06; 95% CI: -0.10, -0.01). Mono-iso-butyl phthalate was associated with an increase in CRAE (β=1.89; 95% CI: 0.34, 3.44). Methyl- and butyl-parabens were associated with a decrease in CRVE (β=-0.71; 95% CI: -1.41, -0.01) and (β=-0.96; 95% CI: -1.57, -0.35), respectively. No statistically significant associations were observed between any of the exposures and SBP or DBP. BWQS models showed no evidence of associations between the phthalate and phenol mixture and any of the outcomes. Our results provide little evidence to suggest that prenatal exposure to phthalates and phenols is associated with macro- or microvascular health during early adolescence, except a few associations with certain compounds. Errors in exposure measurement and reduced variability in cardiovascular measures at this early age limit our ability to draw strong conclusions.

Risk-Based Prioritization of Organic Chemicals and Locations of Ecological Concern in Sediment From Great Lakes Tributaries.

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.

Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures.

Exposures to environmental pollutants are often composed of mixtures of chemicals that can be highly correlated because of similar sources and/or chemical structures. The effect of an individual chemical on a health outcome can be weak and difficult to detect because of the relatively low level of exposures to many environmental pollutants. To tackle the challenging problem of assessing the health risk of exposure to a mixture of environmental pollutants, we propose a statistical approach to assessing the proportion of the variation of an outcome explained by a mixture of pollutants. The proposed approach avoids the difficult task of identifying specific pollutants that are responsible for the effects and may also be used to assess interactions among exposures. Extensive simulation results demonstrate that the proposed approach has very good performance. Application of the proposed approach is illustrated by investigating the main and interaction effects of the chemical pollutants on systolic and diastolic blood pressure in participants from the National Health and Nutrition Examination Survey.

Chimpanzee exposure to pollution revealed by human biomonitoring approaches

Wildlife is increasingly exposed to environmental pollution, but data illustrating to what extent this exposure can impact health and survival of endangered species is missing. In humans, hair matrix analysis is a reliable tool for assessing cumulative exposure to organic pollutants such as pesticides but has rarely been used in other primates for this purpose. LC/MS-MS and GC/MS-MS multi-residue methods were used to screen the presence of 152 organic pollutants and their metabolites belonging to 21 different chemical families in hair samples from our closest relative, the chimpanzee. Samples were collected from 20 wild chimpanzees in Sebitoli, Kibale National Park, Uganda and 9 captive chimpanzees in the Réserve Africaine de Sigean, France. In total, 90 chemicals were detected, 60 in wild chimpanzees and 79 in captive chimpanzees. The median concentrations of detected chemicals in captive individuals were significantly higher than those in wild chimpanzees. Hair from the captive individuals at RAS was sampled a second time after 6 months in an environment of reduced exposure to these pollutants (diet of organic food, decreased use of plastic food and water containers). The number of chemicals detected in captive chimpanzees reduced from 79 to 63, and their concentrations were also significantly reduced. In the present study we report for the first time the use of hair analysis to detect organic pollutants in primate hair. We conclude that both wild and captive chimpanzees are exposed to a large range of different chemicals through their diet. Our study provides surprising and alarming evidence that besides the direct threats of poaching, deforestation and diseases, wild chimpanzees might be endangered by indirect consequences of anthropic activities. As chimpanzees are our closest relatives, our results should be considered as an alert for human health as well.

The Association of Certain Seminal Phthalate Metabolites on Spermatozoa Apoptosis: An Exploratory Mediation Analysis via Sperm Protamine

Earlier studies have suggested that exposure to phthalates (PAEs) may induce spermatozoa apoptosis. Sperm protamine as a molecular biomarker during spermatozoa apoptotic processes may mediate the association between PAE exposure and spermatozoa apoptosis. This study aimed to explore whether sperm protamine mediates the association of PAE exposure with spermatozoa apoptosis. We determined sperm protamine levels, 8 PAE metabolite concentrations in seminal plasma, and 3 spermatozoa apoptosis parameters among 111 men from an infertility clinic. The associations of PAEs as individual chemicals and mixtures with sperm protamine were determined. The mediating roles of protamine in the associations between PAEs and spermatozoa apoptosis parameters were examined by mediation analysis. After adjusting for confounders, we observed positive correlations between seminal plasma concentrations of mono(2-ethylhexyl) phthalate (MEHP) and sperm protamine-1 and protamine ratio. Estimates comparing highest vs. lowest quartiles of MEHP concentration were 4.65% (95% CI: 1.47%, 7.82%) for protamine-1 and 25.86% (95% CI: 3.05%, 53.73%) for protamine ratio. The quantile g-computation models showed that the adjusted protamine-1 per quartile increase in PAE mixture was 9.42% (95% CI: 1.00, 20.92) with MEHP being the major contributor. Although the joint association between PAE mixture and protamine ratio was negligible, MEHP was still identified as the main contributor. Furthermore, we found that protamine-2 and protamine ratio levels in the highest quartiles exhibited a decrease of 43.45% (95% CI: 60.54%, −19.75%) and an increase of 122.55% (95% CI: 60.00%, 209.57%) in Annexin V+/PI− spermatozoa relative to the lowest quartiles, respectively. Mediation analysis revealed that protamine ratio significantly mediated 55.6% of the association between MEHP and Annexin V+/PI− spermatozoa elevation (5.13%; 95% CI: 0.04%, 10.52%). Our findings provided evidence that human exposure to PAEs was associated with increased protamine levels which may mediate the process of spermatozoa apoptosis.

A gene expression biomarker for predictive toxicology to identify chemical modulators of NF-κB.

The nuclear factor-kappa B (NF-κB) is a transcription factor with important roles in inflammation, immune response, and oncogenesis. Dysregulation of NF-κB signaling is associated with inflammation and certain cancers. We developed a gene expression biomarker predictive of NF-κB modulation and used the biomarker to screen a large compendia of gene expression data. The biomarker consists of 108 genes responsive to tumor necrosis factor α in the absence but not the presence of IκB, an inhibitor of NF-κB. Using a set of 450 profiles from cells treated with immunomodulatory factors with known NF-κB activity, the balanced accuracy for prediction of NF-κB activation was > 90%. The biomarker was used to screen a microarray compendium consisting of 12,061 microarray comparisons from human cells exposed to 2,672 individual chemicals to identify chemicals that could cause toxic effects through NF-κB. There were 215 and 49 chemicals that were identified as putative or known NF-κB activators or suppressors, respectively. NF-κB activators were also identified using two high-throughput screening assays; 165 out of the ~3,800 chemicals (ToxCast assay) and 55 out of ~7,500 unique compounds (Tox21 assay) were identified as potential activators. A set of 32 chemicals not previously associated with NF-κB activation and which partially overlapped between the different screens were selected for validation in wild-type and NFKB1-null HeLa cells. Using RT-qPCR and targeted RNA-Seq, 31 of the 32 chemicals were confirmed to be NF-κB activators. These results comprehensively identify a set of chemicals that could cause toxic effects through NF-κB.

Imputation of Below Detection Limit Missing Data in Chemical Mixture Analysis with Bayesian Group Index Regression.

There is growing scientific interest in identifying the multitude of chemical exposures related to human diseases through mixture analysis. In this paper, we address the issue of below detection limit (BDL) missing data in mixture analysis using Bayesian group index regression by treating both regression effects and missing BDL observations as parameters in a model estimated through a Markov chain Monte Carlo algorithm that we refer to as pseudo-Gibbs imputation. We compare this with other Bayesian imputation methods found in the literature (Multiple Imputation by Chained Equations and Sequential Full Bayes imputation) as well as with a non-Bayesian single-imputation method. To evaluate our proposed method, we conduct simulation studies with varying percentages of BDL missingness and strengths of association. We apply our method to the California Childhood Leukemia Study (CCLS) to estimate concentrations of chemicals in house dust in a mixture analysis of potential environmental risk factors for childhood leukemia. Our results indicate that pseudo-Gibbs imputation has superior power for exposure effects and sensitivity for identifying individual chemicals at high percentages of BDL missing data. In the CCLS, we found a significant positive association between concentrations of polycyclic aromatic hydrocarbons (PAHs) in homes and childhood leukemia as well as significant positive associations for polychlorinated biphenyls (PCBs) and herbicides among children from the highest quartile of household income. In conclusion, pseudo-Gibbs imputation addresses a commonly encountered problem in environmental epidemiology, providing practitioners the ability to jointly estimate the effects of multiple chemical exposures with high levels of BDL missingness.

Individual and mixtures of metal exposures in associations with biomarkers of oxidative stress and global DNA methylation among pregnant women

BackgroundPrenatal exposure to metals has been linked with adverse pregnancy outcomes. Oxidative stress and epigenetic changes are potential mechanisms of action. ObjectivesWe aimed to examine the associations of individual and mixtures of metal exposures with oxidative stress and DNA methylation among pregnant women. MethodsWe measured a panel of 16 metals and 3 oxidative stress biomarkers including 8-hydroxydeoxyguanosine (8-OHdG), 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA) and 8-isoprostaglandin F2α (8-isoPGF2α) in urine from 113 pregnant women in a Chinese cohort. Biomarkers of global DNA methylation including Alu and long interspersed nucleotide element-1 (LINE-1) in cord blood were measured. Multivariable linear regression and Bayesian kernel machine regression (BKMR) models were separately applied to estimate the associations between individual and mixtures of metal exposures and biomarkers of oxidative stress and global DNA methylation. ResultsIn single-metal analyses, we observed positive associations between 11 metals [arsenic (As), cadmium (Cd), thallium (Tl), barium (Ba), nickel (Ni), vanadium (V), cobalt (Co), zinc (Zn), copper (Cu), selenium (Se) and molybdenum (Mo)] and at least one of oxidative stress biomarkers (all FDR-adjusted P-values < 0.05). In mixture analyses, we found positive overall associations of metal mixtures with 8-OHdG and 8-isoPGF2α, and Se was the most important predictor. There was no evidence on associations of urinary metals as individual chemicals and mixtures with Alu and LINE-1 methylation. ConclusionUrinary metals as individual chemicals and mixtures were associated with increased oxidative stress, especially Se.

Levels and health risk assessment of pesticides and metals in Lycium barbarum L. from different sources in Ningxia, China

The berries of Lycium barbarum L. (Goji) are widely used as a Chinese traditional herbal medicine and functional food because of their reported beneficial pharmacological effects. However, there are reports of Goji berries being contaminated by chemical residues that could pose a hazard to humans. In this study, samples of L. barbarum L. berries were collected from plantations in a genuine production area and supermarkets in Ningxia, China. The major hazardous chemicals, including pesticides (dichlorvos, omethoate, cypermethrin, fenvalerate, malathion, and deltamethrin) and metals (lead (Pb), cadmium (Cd), copper (Cu), nickel (Ni), zinc (Zn), and arsenic (As)), were quantified by gas chromatography and inductively coupled plasma-optical emission spectrometry. In addition, associated daily exposures and health risks were determined using deterministic and probabilistic assessments. The levels of five pesticides from the plantation samples were considerably lower than the maximum residue limits; only dichlorvos was detected in the supermarket samples, and deltamethrin was not detected in any samples. Cu, Zn, As, Pb, Ni and Cd were detected in samples from both sources. The hazard quotient values of individual hazardous chemicals and the hazard index of combined hazardous chemicals were considerably less than 1, indicating the absence of a non-carcinogenic effect of hazardous chemical exposures through Goji berry consumption. The R value of As was much less than 10–6, which shows that consumption of the Goji berries had no obvious carcinogenic risks. The potentially harmful effects of the L. barbarum L. are more likely from berries obtained from plantations than those from supermarkets, and metal exposure is more dangerous than pesticide exposure. However, on the basis of our analysis, no population would be exposed hazardous chemicals exceeding existing standards, and the factors most affecting the health risk were exposure frequency and As content.

Ovine fetal testis stage-specific sensitivity to environmental chemical mixtures.

Exposure of the fetal testis to numerous individual environmental chemicals (ECs) is frequently associated with dysregulated development, leading to impaired adult reproductive competence. However, ‘real-life’ exposure involves complex mixtures of ECs. Here we test the consequences, for the male fetus, of exposing pregnant ewes to EC mixtures derived from pastures treated with biosolids fertiliser (processed human sewage). Fetal testes from continuously exposed ewes were either unaffected at day 80 or exhibited a reduced area of testis immunostained for CYP17A1 protein at day 140. Fetal testes from day 140 pregnant ewes that were exposed transiently for 80-day periods during early (0–80 days), mid (30–110 days), or late (60–140 days) pregnancy had fewer Sertoli cells and reduced testicular area stained for CYP17A1. Male fetuses from ewes exposed during late pregnancy also exhibited reduced fetal body, adrenal and testis mass, anogenital distance, and lowered testosterone; collectively indicative of an anti-androgenic effect. Exposure limited to early gestation induced more testis transcriptome changes than observed for continuously exposed day 140 fetuses. These data suggest that a short period of EC exposure does not allow sufficient time for the testis to adapt. Consequently, testicular transcriptomic changes induced during the first 80 days of gestation may equate with phenotypic effects observed at day 140. In contrast, relatively fewer changes in the testis transcriptome in fetuses exposed continuously to ECs throughout gestation are associated with less severe consequences. Unless corrected by or during puberty, these differential effects would predictably have adverse outcomes for adult testicular function and fertility.

Beyond Additivity: A mixture of glucose and NaCl can influence skin hydration more than the individual compounds

The barrier function of the skin mainly relies on its outermost layer, the stratum corneum (SC), which is a lipid-protein composite biomaterial. In addition, SC contains a mixture of small polar compounds, the natural moisturizing factor (NMF). Most of the NMF components are solid at ambient relative humidities (RHs). We herein raise the question of what the effects of adding a mixture of chemicals to the SC are as compared to adding the single components. We use mixtures of glucose and NaCl, both present in NMF and in skin formulations, and the effects on SC were studied using solid-state NMR, wide angle X-ray diffraction, and sorption microbalance. The deliquescence RHs of the glucose-NaCl mixtures are lower than the individual chemicals. The same trend is also seen when these chemicals are added to SC, as the dissolution occurs at lower RH for the mixture than for the single chemicals. Notably, the mixtures can also increase the mobility of SC lipids and proteins more than the individual compounds. These data illustrate a synergistic effect by adding a mixture rather than a single polar compound to the SC, which may also have implications for the complex mixture NMF inside SC in dry conditions.

Watershed-Scale Risk to Aquatic Organisms from Complex Chemical Mixtures in the Shenandoah River.

River waters contain complex chemical mixtures derived from natural and anthropogenic sources. Aquatic organisms are exposed to the entire chemical composition of the water, resulting in potential effects at the organismal through ecosystem level. This study applied a holistic approach to assess landscape, hydrological, chemical, and biological variables. On-site mobile laboratory experiments were conducted to evaluate biological effects of exposure to chemical mixtures in the Shenandoah River Watershed. A suite of 534 inorganic and organic constituents were analyzed, of which 273 were detected. A watershed-scale accumulated wastewater model was developed to predict environmental concentrations of chemicals derived from wastewater treatment plants (WWTPs) to assess potential aquatic organism exposure for all stream reaches in the watershed. Measured and modeled concentrations generally were within a factor of 2. Ecotoxicological effects from exposure to individual components of the chemical mixture were evaluated using risk quotients (RQs) based on measured or predicted environmental concentrations and no effect concentrations or chronic toxicity threshold values. Seventy-two percent of the compounds had RQ values <0.1, indicating limited risk from individual chemicals. However, when individual RQs were aggregated into a risk index, most stream reaches receiving WWTP effluent posed potential risk to aquatic organisms from exposure to complex chemical mixtures.

Evaluation of propargite 50% + bifenthrin 5% SE against red spider mite, Tetranychus urticae in okra

In present trial combination of propargite 50% + bifenthrin 5% SE, was evaluated against Tetranychus urticae. The results indicated that propargite 50% + bifenthrin 5% SE @ 1,150 ml/ha recorded the highest per cent reduction of mites over the control (91.31%) followed by lower doses of the same product tested. The combination of two chemicals was more effective than the individual chemicals tested. The effectiveness of this product also gave maximum fruit yield (9.53 t/ha) with C: B ratio as 1: 6.26.