3,488 research outputs found

    Human urinary mutagenicity after wood smoke exposure during traditional temazcal use.

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    In Central America, the traditional temazcales or wood-fired steam baths, commonly used by many Native American populations, are often heated by wood fires with little ventilation, and this use results in high wood smoke exposure. Urinary mutagenicity has been previously employed as a non-invasive biomarker of human exposure to combustion emissions. This study examined the urinary mutagenicity in 19 indigenous Mayan families from the highlands of Guatemala who regularly use temazcales (N = 32), as well as control (unexposed) individuals from the same population (N = 9). Urine samples collected before and after temazcal exposure were enzymatically deconjugated and extracted using solid-phase extraction. The creatinine-adjusted mutagenic potency of urine extracts was assessed using the plate-incorporation version of the Salmonella mutagenicity assay with strain YG1041 in the presence of exogenous metabolic activation. The post-exposure mutagenic potency of urine extracts were, on average, 1.7-fold higher than pre-exposure samples (P < 0.005) and also significantly more mutagenic than the control samples (P < 0.05). Exhaled carbon monoxide (CO) was ~10 times higher following temazcal use (P < 0.0001), and both CO level and time spent in temazcal were positively associated with urinary mutagenic potency (i.e. P < 0.0001 and P = 0.01, respectively). Thus, the wood smoke exposure associated with temazcal use contributes to increased excretion of conjugated mutagenic metabolites. Moreover, urinary mutagenic potency is correlated with other metrics of exposure (i.e. exhaled CO, duration of exposure). Since urinary mutagenicity is a biomarker associated with genetic damage, temazcal use may therefore be expected to contribute to an increased risk of DNA damage and mutation, effects associated with the initiation of cancer

    Cell transformation assays for prediction of carcinogenic potential: State of the science and future research needs

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    Copyright @ 2011 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Cell transformation assays (CTAs) have long been proposed as in vitro methods for the identification of potential chemical carcinogens. Despite showing good correlation with rodent bioassay data, concerns over the subjective nature of using morphological criteria for identifying transformed cells and a lack of understanding of the mechanistic basis of the assays has limited their acceptance for regulatory purposes. However, recent drivers to find alternative carcinogenicity assessment methodologies, such as the Seventh Amendment to the EU Cosmetics Directive, have fuelled renewed interest in CTAs. Research is currently ongoing to improve the objectivity of the assays, reveal the underlying molecular changes leading to transformation and explore the use of novel cell types. The UK NC3Rs held an international workshop in November 2010 to review the current state of the art in this field and provide directions for future research. This paper outlines the key points highlighted at this meeting

    Investigation of in Silico Modelling to Predict the Human Health Effects of Cosmetics Ingredients

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    Animal experiments have been the standard method to assess the safety of chemicals used in cosmetic products for decades. However, public opinion has continued to demand that in vivo hazard identification methods conducted on animals are replaced with alternative methods. Research on alternative methods to replace in vivo toxicity testing continually increased over the past few decades with different alternatives developed, such as in vitro, in chemico and in silico approaches. Although different alternative techniques can be employed, no single technique can solely replace the complexity and an in vivo test, especially for chronic effects. Therefore, integrated testing strategies that can utilise the information from all available alternative testing approaches have been developed. Within the Adverse Outcome Pathway (AOP) paradigm, the molecular initiating event(s) MIE can be induced by several chemical key features which can be captured by structural alerts. When structural alerts for a MIE are compiled and supported by mechanistic and toxicity information confirming the induction of the same MIE, then they can be considered as an in silico profiler. The overall aim of the work presented in this thesis was to assess the current in silico profilers for carcinogenicity (both genotoxic and non-genotoxic), mutagenicity and skin sensitisation through assessment using multiple high-quality experimental databases. The research presented herein demonstrates the ability to assess the positive predictivity of two types of structural alert, mechanism- and chemistry-based that pertain to the endpoints and proposes ways to improve the overall accuracy of these profilers. In this context, this study has given an insight to those alerts that may be found equally in endpoint-positive or negative compounds, and those which may be more effectively utilised to form groups of analogues for read across predictions. A detailed analysis of positive predictivity of the available mutagenicity, carcinogenicity and skin sensitisation structural alerts and profilers Page 3 within the OECD QSAR Toolbox against experimental data is presented. This investigation showed the structural alerts that are accurate as such, and those that may need further refinement, or their use may need to be reconsidered. In addition, the relationship between scaffolds of a range of diverse compounds and carcinogenicity showed that a total of 17 carcinogenicity scaffolds could be identified from the available databases and could be used as a base for an in silico profiler. This work has also determined the need for further in-depth research in this area to study the suitability and merits of each of the alerts within the profilers currently included in the OECD QSAR Toolbox, and other in silico toxicity platforms, to identify the possibilities for improvement in their performance. This will, by implication, also improve the reliability of chemical read-across and grouping/categorisation for classification, labelling and risk assessment for regulatory use of the in silico methods

    Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity

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    This review of QSARs for genotoxicity and carcinogenicity was performed in a broad sense, considering both models available in software tools and models that are published in the literature. The review considered the potential applicability of diverse models to pesticides as well as to other types of regulated chemicals and pharmaceuticals. The availability of models and information on their applicability is summarised in tables, and a range of illustrative or informative examples are described in more detail in the text. In many cases, promising models were identified but they are still at the research stage. For routine application in a regulatory setting, further efforts will be needed to explore the applicability of such models for specific purposes, and to implement them in a practically useful form (i.e. user-friendly software). It is also noted that a range of software tools are research tools suitable for model development, and these require more specialised expertise than other tools that are aimed primarily at end-users such as risk assessors. It is concluded that the most useful models are those which are implemented in software tools and associated with transparent documentation on the model development and validation process. However, it is emphasised that the assessment of model predictions requires a reasonable amount of QSAR knowledge, even if it is not necessary to be a QSAR practitioner.JRC.DG.I.6-Systems toxicolog

    A Framework for assessing in silico Toxicity Predictions: Case Studies with selected Pesticides

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    In the regulatory assessment of chemicals, the use of in silico prediction methods such as (quantitative) structure-activity relationship models ([Q]SARs), is increasingly required or encouraged, in order to increase the efficiency and effectiveness of the risk assessment process, and to minimise the reliance on animal testing. The main question for the assessor concerns the usefulness of the prediction approach, which can be broken down into the practical applicability of the method and the adequacy of the predictions. A framework for assessing and documenting (Q)SAR models and their predictions has been established at the European and international levels. Exactly how the framework is applied in practice will depend on the provisions of the specific legislation and the context in which the non-testing data are being used. This report describes the current framework for documenting (Q)SAR models and their predictions, and discuses how it might be built upon to provide more detailed guidance on the use of (Q)SAR predictions in regulatory decision making. The proposed framework is illustrated by using selected pesticide active compounds as examples.JRC.DG.I.6-Systems toxicolog

    The Use of Computational Methods in the Toxicological Assessment of Chemicals in Food: Current Status and Future Prospects

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    A wide range of chemicals are intentionally added to, or unintentially found in, food products, often in very small amounts. Depending on the situation, the experimental data needed to complete a dietary risk assessment, which is the scientific basis for protecting human health, may not be available or obtainable, for reasons of cost, time and animal welfare. For example, toxicity data are often lacking for the metabolites and degradation products of pesticide active ingredients. There is therefore an interest in the development and application of efficient and effective non-animal methods for assessing chemical toxicity, including Quantitative Structure-Activity Relationship (QSAR) models and related computational methods. This report gives an overview of how computational methods are currently used in the field of food safety by national regulatory bodies, international advisory organisations and the food industry. On the basis of an international survey, a comprehensive literature review and a detailed QSAR analysis, a range of recommendations are made with the long-term aim of promoting the judicious use of suitable QSAR methods. The current status of QSAR methods is reviewed not only for toxicological endpoints relevant to dietary risk assessment, but also for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their reaction products. By referring to the concept of the Threshold of Toxicological Concern (TTC), the risk assessment context in which QSAR methods can be expected to be used is also discussed. This Joint Research Centre (JRC) Reference Report provides a summary and update of the findings obtained in a study carried out by the JRC under the terms of a contract awarded by the European Food Safety Authority (EFSA).JRC.DG.I.6-Systems toxicolog

    In silico prediction of skin metabolism and its implication in toxicity assessment

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    Skin, being the largest organ of the body, represents an important route of exposure, not only for the abundance of chemicals present in the environment, but also for products designed for topical application such as drugs and personal care products. Determining whether such incidental or intentional exposure poses a risk to human health requires consideration of temporal concentration, both externally and internally, in addition to assessing the chemicalā€™s intrinsic hazard. In order to elicit a toxic response in vivo the chemical must reach its site of action in sufficient concentration, as determined by its absorption, distribution, metabolism and elimination (ADME) profile. Whilst absorption and distribution into and through skin layers have been studied for decades, only more recently has skin metabolism become a subject of intense research, now recognised as playing a key role in both toxification and detoxification processes. The majority of information on metabolic processes, however, has generally been acquired via studies performed on the liver. This paper outlines strategies that may be used to leverage current knowledge, gained from liver metabolism studies, to inform predictions for skin metabolism through understanding the differences in the enzymatic landscapes between skin and liver. The strategies outlined demonstrate how an array of in silico tools may be used in concert to resolve a significant challenge in predicting toxicity following dermal exposure. The use of in vitro methods for determining skin metabolism, both to provide further experimental data for modelling and to verify predictions is also discussed. Herein, information on skin metabolism is placed within the context of toxicity prediction for risk assessment, which requires consideration of both exposure and hazard of parent chemicals and their metabolites

    Origin of the TTC values for compounds that are genotoxic and/or carcinogenic and an approach for their revaluation

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    The threshold of toxicological concern (TTC) approach is a resource-effective de minimismethod for the safety assessment of chemicals, based on distributional analysis of the results of a large number of toxicological studies. It is being increasingly used to screen and prioritise substances with low exposure for which there is little or no toxicological information. The first step in the approach is the identification of substances that may be DNA-reactive mutagens, to which the lowest TTC value is applied. This TTC value was based on analysis of the cancer potency database and involved a number of assumptions that no longer reflect the state-of-the-science and some of which were not as transparent as they could have been. Hence, review and updating of the database is proposed, using inclusion and exclusion criteria reflecting current knowledge. A strategy for the selection of appropriate substances for TTC determination, based on consideration of weight of evidence for genotoxicity and carcinogenicity is outlined. Identification of substances that are carcinogenic by a DNA-reactive mutagenicmode of action and those that clearly act by a non-genotoxic mode of action will enable the protectiveness to be determined of both the TTC for DNA-reactive mutagenicityand that applied by default to substances that may be carcinogenic but are unlikely to be DNA-reactive mutagens (i.e. for Cramer class I-III compounds). Critical to the application of the TTC approach to substances that are likely to be DNA-reactive mutagens is the reliability of the software tools used to identify such compounds. Current methods for this task are reviewed and recommendations made for their application
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