Toxicological Risk Assessment Research Articles

Identifying Food Consumption Patterns among Young Consumers by Unsupervised and Supervised Multivariate Data Analysis

Although computational multivariate data analysis (MDA) already has been employed in the dietary survey area, the results reported are based mainly on classical exploratory (descriptive) techniques. Therefore, data of a Swedish and a Danish dietary survey on young consumers (4 to 5 years of age) were subjected not only to modern exploratory MDA, but also modern predictive MDA that via supervised learning yielded predictive classification models. The exploratory part, also encompassing Swedish 8 or 11-year old Swedish consumers, included new innovative forms of hierarchical clustering and bi-clustering. This resulted in several interesting multi-dimensional dietary patterns (dietary prototypes), including striking difference between those of the age-matched Danish and Swedish children. The predictive MDA disclosed additional multi-dimensional food consumption relationships. For instance, the consumption patterns associated with each of several key foods like bread, milk, potato and sweetened beverages, were found to differ markedly between the Danish and Swedish consumers. In conclusion, the joint application of modern descriptive and predictive MDA to dietary surveys may enable new levels of diet quality evaluation and perhaps also prototype-based toxicology risk assessment.

Novel strategies for toxicological risk assessments

Novel strategies for toxicological risk assessments

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology.

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs – liver, lung, skin, brain – are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

Strengthening the foundation of next generation risk assessment

In a recent draft report, Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology, the US Environmental Protection Agency presents valuable contributions to understanding the roles that evolving toxicity testing methods and associated interpretative techniques can play in assessing the risks associated with chemical exposures. However, the evaluations presented in the NexGen report would benefit from more thorough consideration of several essential components of a critical review of toxicity data, e.g., data quality, data relevance, and the extent to which the test endpoints reflect adverse effects. Such considerations are necessary to ensure that the NexGen report evaluations – and the resulting conclusions and recommendations – are grounded in scientifically sound, representative data reviews. We illustrate these concerns with a critique of the report’s prototype ozone evaluation. Although substantial additional research is needed before new toxicity data types can be used reliably in rigorous risk assessment applications, they clearly offer exciting opportunities for advancing toxicological science and risk assessment. By explicitly identifying limitations still to be addressed and providing stronger guideposts for future research needs, the NexGen report could serve an influential role in achieving the promise of these new research approaches.

Current exposure of 200 pregnant Danish women to phthalates, parabens and phenols

Many phthalates, parabens and phenols are suspected to have endocrine-disrupting properties in humans. They are found in consumer products, including food wrapping, cosmetics and building materials. The foetus is particularly vulnerable and exposure to these chemicals therefore is of concern for pregnant women. We investigated current exposure to several commonly used phthalates, parabens and phenols in healthy, pregnant Danish women. A total of 200 spot urine samples were collected between 8 and 30 weeks of gestation and analysed for metabolites of ten phenols, seven parabens and 16 phthalate by liquid chromatography-tandem mass spectrometry representing 26 non-persistent compounds. The majority of analytes were present in the urine sample collected from most women who participated. Thus, in 174 of the 200 women, metabolites of more than 13 (>50%) of 26 compounds were detected simultaneously. The number of compounds detected per woman (either as the parent compound or its metabolite(s)) ranged from 7 to 21 with a median of 16. The majority of compounds correlated positively with each other within and between chemical groups, suggesting combined exposure sources. Estimated daily intakes (DIs) of phthalates and bisphenol A (BPA) were below their individual tolerable DI (TDI) and with hazard quotients below 1. In conclusion, we found detectable levels of phthalate metabolites, parabens and phenols in almost all pregnant women, suggesting combined multiple exposures. Although the estimated DI of phthalates and BPA for an individual was below TDI, our results still raise concern, as current toxicological risk assessments in humans do not take into account simultaneous exposure. The true cumulative risk for the foetus may therefore be underestimated.

Epigenetic memory of environmental organisms: A reflection of lifetime stressor exposures

Both genetic and epigenetic responses of organisms to environmental factors, including chemical exposures, influence adaptation, susceptibility to toxicity and biodiversity. In model organisms, it is established that epigenetic alterations, including changes to the methylome, can create a memory of the received signal. This is partly evidenced through the analysis of epigenetic differences that develop between identical twins throughout their lifetime. The epigenetic marks induce alterations to the gene expression profile, which, in addition to mediating homeostatic responses, have the potential to promote an abnormal physiology either immediately or at a later stage of development, for example leading to an adult onset of disease. Although this has been well established, epigenetic mechanisms are not considered in chemical risk assessment or utilised in the monitoring of the exposure and effects of chemicals and environmental change. In this review, epigenetic factors, specifically DNA methylation, are highlighted as mechanisms of adaptation and response to environmental factors and which, if persistent, have the potential, retrospectively, to reflect previous stress exposures. Thus, it is proposed that epigenetic “foot-printing” of organisms could identify classes of chemical contaminants to which they have been exposed throughout their lifetime. In some cases, the potential for persistent transgenerational modification of the epigenome may also inform on parental germ cell exposures. It is recommended that epigenetic mechanisms, alongside genetic mechanisms, should eventually be considered in environmental toxicity safety assessments and in biomonitoring studies. This will assist in determining the mode of action of toxicants, no observed adverse effect level and identification of biomarkers of toxicity for early detection and risk assessment in toxicology but there are critical areas that remain to be explored before this can be achieved.

In Pursuit of Safety: One-Hundred Years of Toxicological Risk Assessment

ABSTRACT The publication in 1962 of Rachel Carson's Silent Spring marks the mid-point in a century that saw, in its first half, the emergence of public health concerns related to human exposures to chemicals, and, in its second half, the emergence of public policies to deal with those concerns. Those policies made it imperative that the scientific community come to grips with the problem of identifying exposure levels not likely to cause harm. This problem was not significantly discussed within the scientific community until the 1950s, and well-described methods for practical solutions to it did not appear until the 1970s. An important report from the National Academy of Sciences, published in 1983 (Risk Assessment in the Federal Government), provided an analysis of these emerging methods, and recommended a useful framework for the assessment and management of risk. This framework remains central to public health and regulatory decision-making. A high-level perspective is offered on events leading to and following the 1983 report. The article describes early thinking about chemical toxicity and the scientific path that thinking followed through the 20th century, and to the present.

Semiparametric Bayesian joint modeling of a binary and continuous outcome with applications in toxicological risk assessment

Many dose-response studies collect data on correlated outcomes. For example, in developmental toxicity studies, uterine weight and presence of malformed pups are measured on the same dam. Joint modeling can result in more efficient inferences than independent models for each outcome. Most methods for joint modeling assume standard parametric response distributions. However, in toxicity studies, it is possible that response distributions vary in location and shape with dose, which may not be easily captured by standard models. To address this issue, we propose a semiparametric Bayesian joint model for a binary and continuous response. In our model, a kernel stick-breaking process prior is assigned to the distribution of a random effect shared across outcomes, which allows flexible changes in distribution shape with dose shared across outcomes. The model also includes outcome-specific fixed effects to allow different location effects. In simulation studies, we found that the proposed model provides accurate estimates of toxicological risk when the data do not satisfy assumptions of standard parametric models. We apply our method to data from a developmental toxicity study of ethylene glycol diethyl ether.

Application of high performance liquid chromatography with inductively coupled plasma mass spectrometry (HPLC–ICP-MS) for determination of chromium compounds in the air at the workplace

The toxicity and bioavailability of chromium species are highly dependable on the form or species, therefore determination of total chromium is insufficient for a complete toxicological evaluation and risk assessment. An analytical method for determination of soluble and insoluble Cr (III) and Cr (VI) compounds in welding fume at workplace air has been developed. The total chromium (Cr) was determined by using quadruple inductively coupled plasma mass spectrometry (ICP-MS) equipped with a dynamic reaction cell (DRC(®)). Soluble trivalent and hexavalent chromium compounds were determined by high performance liquid chromatography with inductively coupled plasma mass spectrometry (HPLC-ICP-MS). A high-speed, reversed-phase CR C8 column (PerkinElmer, Inc., Shelton, CT, USA) was used for the speciation of soluble Cr (III) and soluble Cr (VI). The separation was accomplished by interaction of the chromium species with the different components of the mobile phase. Cr (III) formed a complex with EDTA, i.e. retained on the column, while Cr (VI) existed in the solutions as dichromate. Alkaline extraction (2% KOH and 3% Na2CO3) and anion exchange column (PRP-X100, PEEK, Hamilton) were used for the separation of the total Cr (VI). The results of the determination of Cr (VI) were confirmed by the analysis of the certified reference material BCR CRM 545 (Cr (VI) in welding dust). The results obtained for the certified material (40.2±0.6 g kg(-1)) and the values recorded in the examined samples (40.7±0.6 g kg(-1)) were highly consistent. This analytical method was applied for the determination of chromium in the samples in the workplace air collected onto glass (Whatman, Ø 37 mm) and membrane filters (Sartorius, 0.8 μm, Ø 37 mm). High performance liquid chromatography with inductively coupled plasma mass spectrometry is a remarkably powerful and versatile technique for determination of chromium species in welding fume at workplace air.

Dose metric considerations in in vitro assays to improve quantitative in vitro–in vivo dose extrapolations

Challenges to improve toxicological risk assessment to meet the demands of the EU chemical's legislation, REACH, and the EU 7th Amendment of the Cosmetics Directive have accelerated the development of non-animal based methods. Unfortunately, uncertainties remain surrounding the power of alternative methods such as in vitro assays to predict in vivo dose-response relationships, which impedes their use in regulatory toxicology. One issue reviewed here, is the lack of a well-defined dose metric for use in concentration-effect relationships obtained from in vitro cell assays. Traditionally, the nominal concentration has been used to define in vitro concentration-effect relationships. However, chemicals may differentially and non-specifically bind to medium constituents, well plate plastic and cells. They may also evaporate, degrade or be metabolized over the exposure period at different rates. Studies have shown that these processes may reduce the bioavailable and biologically effective dose of test chemicals in in vitro assays to levels far below their nominal concentration. This subsequently hampers the interpretation of in vitro data to predict and compare the true toxic potency of test chemicals. Therefore, this review discusses a number of dose metrics and their dependency on in vitro assay setup. Recommendations are given on when to consider alternative dose metrics instead of nominal concentrations, in order to reduce effect concentration variability between in vitro assays and between in vitro and in vivo assays in toxicology.

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

Aristolochia species: Toxicological risk assessment using a metabolomic approach

Aristolochia species are toxic plants used as herbal medicines worldwide [1]. Their use has become a global public health concern [2] since they are known to cause aristolochic acid nephropathy, a devastating disease associated with kidney failure and kidney cancer [3]. The aims of this project are to assess the health risks associated with the use of different Aristolochia species and to elucidate the active principle behind their nephrotoxic effects.

Toxicological risk assessment in carbon capture and storage technology

Objective: Climate change and its consequences is one of the main topics of our time. According to the European Union, Carbon Capture and Storage Technology (CCS) should function as bridge technology for attenuating climate change. Despite well conducted geological risk analyses a major toxicological risk assessment including all components of the process is lacking until today. Results: An extensive literature analysis was conducted. Worstcase simulations for atmospherical emitted alcoholamines (used during the CO2 capture process) were found, which showed threshold exceedances of emerging nitrosamines and nitramines. Reduction of alcoholamine emissions is urgently recommended. During the transportation of CO2, humans are endangered of poisoning with hazardous CO2-concentrations in case of accidents, e.g. pipeline rupture or blowout of injection wells. It should be noticed that medical care cannot be guaranteed in occurrence of mass intoxications. Leakages of storage formations can result in CO2-accumulations in basements of not regularly vented buildings and have the potential to exceed thresholds in the worst-case. Natural storage analogues showed associations between underground degassing of CO2 and lung carcinogenic radon. This causes concern, if the process can be verified for actual storage sites. Concerning induced contaminations, simulations demonstrated that displaced arsenic and lead have the greatest potential for exceedance of drinking water thresholds. Conclusion: Despite the fact that many risks can be decreased by proper risk mitigation measures and careful storage site selection, there is an urgent demand to investigate in contaminations, acute emergency management and risk assessment. More data are required to establish CCS technology

Lazar: a modular predictive toxicology framework

lazar (lazy structure–activity relationships) is a modular framework for predictive toxicology. Similar to the read across procedure in toxicological risk assessment, lazar creates local QSAR (quantitative structure–activity relationship) models for each compound to be predicted. Model developers can choose between a large variety of algorithms for descriptor calculation and selection, chemical similarity indices, and model building. This paper presents a high level description of the lazar framework and discusses the performance of example classification and regression models.

Assessment of Potential Toxicological Risk for Public Health of Heavy Metals in Wheat Crop Irrigated with Wastewater: A Case Study in Sargodha, Pakistan

Assessment of Potential Toxicological Risk for Public Health of Heavy Metals in Wheat Crop Irrigated with Wastewater: A Case Study in Sargodha, Pakistan

Arsenic in Drinking Water Toxicological Risk Assessment in the North Region of Burkina Faso

Human health risks assessment were estimated by determining the nature and probability of adverse health effects in the North region’s populations who are now exposed to arsenic from drinking water or will be exposed in the future. Several questions were addressed in this study: what types of health problems may be caused by arsenic from drinking water? What is the chance that people will experience health problems when exposed to different levels of arsenic? What arsenic level are people exposed to and for how long? To answers these questions we have first identified the hazard by evaluating arsenic concentration in thirty-four (34) bore-hole water points among the region based on the assumption of clinical cases related to drinking water. Arsenic concentration ranged from 0 up to 87.8 micrograms per liter. Next we assessed the dose-response of exposure to arsenic. Dose-response relationship describes how the likelihood and severity of adverse health effects are related to the amount and condition of exposure to arsenic. This required us to choose toxicity reference values (TRVs) above which adverse effects may occur for noncarcinogenic and for carcinogenic effects. Exposure factors have been calculated in two scenarios: people from 0 to 14 years old and people from 15 to 70 years. Exposure has been estimated indirectly through consideration of measured concentrations of arsenic in drinking water. This study show that people in the Yatenga, Zondoma and Passore provinces are at very high risk for developing several pathologies such as hyper pigmentation, keratosis, cancer, etc. due by chronic exposure to arsenic in drinking water.

The impact of model uncertainty on benchmark dose estimation

We study the popular benchmark dose (BMD) approach for estimation of low exposure levels in toxicological risk assessment, focusing on dose-response experiments with quantal data. In such settings, representations of the risk are traditionally based on a specified, parametric, dose-response model. It is a well-known concern, however, that uncertainty can exist in specification and selection of the model. If the chosen parametric form is in fact misspecified, this can lead to inaccurate, and possibly unsafe, lowdose inferences. We study the effects of model selection and possible misspecification on the BMD, on its corresponding lower confidence limit (BMDL), and on the associated extra risks achieved at these values, via large-scale Monte Carlo simulation. It is seen that an uncomfortably high percentage of instances can occur where the true extra risk at the BMDL under a misspecified or incorrectly selected model can surpass the target BMR, exposing potential dangers of traditional strategies for model selection when calculating BMDs and BMDLs.

Effect of combining in vitro estrogenicity data with kinetic characteristics of estrogenic compounds on the in vivo predictive value

With the ultimate aim of increasing the utility of in vitro assays for toxicological risk assessment, a method was developed to calculate in vivo estrogenic potencies from in vitro estrogenic potencies of compounds by taking into account systemic availability. In vitro estrogenic potencies of three model compounds (bisphenol A, genistein, and 4-nonylphenol) relative to ethinylestradiol (EE2), determined with the estrogen receptor alpha (ERα) transcriptional activation assay using hER-HeLa-9903 cells, were taken from literature and used to calculate the EE2 equivalent (EE2EQ) effect doses in the predominantly ERα-dependent rat uterotrophic assay. Compound-specific differences in hepatic clearance relative to the reference compound EE2 were determined in vitro to examine whether in vivo estrogenic potencies reported in literature could be more accurately estimated. The EE2EQ doses allowed to predict in vivo uterotrophic responses within a factor of 6-25 and the inclusion of the hepatic clearance further improved the prediction with a factor 1.6-2.1 for especially genistein and bisphenol A. Yet, the model compounds still were less potent in vivo than predicted based on their EE2 equivalent estrogenic potency and hepatic clearance. For further improvement of the in vitro to in vivo predictive value of in vitro assays, the relevance of other kinetic characteristics should be studied, including binding to carrier proteins, oral bioavailability and the formation of estrogenic metabolites.

Investigation on heavy metal pollution in Uludag fir forests (Abies nordmanniana subsp. bornmulleriana Mattf) in the Bartın Region.

In this study carried out in pure Uludag fir forests of Bartin-Ardic district the change of amount of heavy metals in both soil and needles of Uludag fir depending on altitude was investigated. For this reason, experimental areas were established in three different altitude levels (1,000 m, 1,100 m and 1,200 m) and changes of heavy metals were determined in the soil and Uludag fir needles. According to the results obtained from this research, soil and plant contamination by heavy metals is increasing nowadays while the heavy metal (Pb, Zn, Ni, Cu, Cd, Mn, Cr and Fe) concentrations decreased with the increase in altitude. The highest levels of Cd, Cr and Fe were found in the composite soil and needle of Uludag fir adjacent to 1,000 m and other altitude levels. However, there are significant differences at the P<0.01 level according to the results of ANOVA in the amount of heavy metals in both soil and needle of Uludag fir depending on the altitude levels. The Duncan test was also applied and three different groups were found (exception of Cd); the changes of the amount of heavy metals in soil and needle of Uludag fir depends on the altitude level at the P<0.01 significance level. In this context, the area should be carefully monitored in order to detect changes in the long-term risk due to the presence of high concentrations of trace elements in soils. Toxicological tests and risk assessment will also be carried out with newly polluted soils and trees (Uludag fir) from this site to evaluate the actual environmental risk of trace elements and their transfer to the food chain. The grape plant had behaved as a metal indicator for Pb, Mn, Zn, Fe, Cu, Cr and Cd, indicating that it can be used for testing changes in metal availability in soils. The concentrations of metals in both plant species exceeded the limits established for humans and grazing animals impling a health risk linked with the spread of pollution from mining sites to Uludag fir forests in the Ardic district.