Acute Toxicity of Ternary Cd-Cu-Ni and Cd-Ni-Zn Mixtures to Daphnia magna: Dominant Metal Pairs Change along a Concentration Gradient.

PubMed

Traudt, Elizabeth M; Ranville, James F; Meyer, Joseph S

2017-04-18

Multiple metals are usually present in surface waters, sometimes leading to toxicity that currently is difficult to predict due to potentially non-additive mixture toxicity. Previous toxicity tests with Daphnia magna exposed to binary mixtures of Ni combined with Cd, Cu, or Zn demonstrated that Ni and Zn strongly protect against Cd toxicity, but Cu-Ni toxicity is more than additive, and Ni-Zn toxicity is slightly less than additive. To consider multiple metal-metal interactions, we exposed D. magna neonates to Cd, Cu, Ni, or Zn alone and in ternary Cd-Cu-Ni and Cd-Ni-Zn combinations in standard 48 h lethality tests. In these ternary mixtures, two metals were held constant, while the third metal was varied through a series that ranged from nonlethal to lethal concentrations. In Cd-Cu-Ni mixtures, the toxicity was less than additive, additive, or more than additive, depending on the concentration (or ion activity) of the varied metal and the additivity model (concentration-addition or independent-action) used to predict toxicity. In Cd-Ni-Zn mixtures, the toxicity was less than additive or approximately additive, depending on the concentration (or ion activity) of the varied metal but independent of the additivity model. These results demonstrate that complex interactions of potentially competing toxicity-controlling mechanisms can occur in ternary-metal mixtures but might be predicted by mechanistic bioavailability-based toxicity models.

EPA’s ToxCast Program for Predicting Toxicity and Prioritizing Chemicals for Further Screening and Testing

EPA Science Inventory

Testing of environmental and industrial chemicals for toxicity potential is a daunting task because of the wide range of possible toxicity mechanisms. Although animal testing is one means of achieving broad toxicity coverage, evaluation of large numbers of chemicals is challengin...

Developing Predictive Toxicity Signatures Using In Vitro Data from the EPA ToxCast Program

EPA Science Inventory

A major focus in toxicology research is the development of in vitro methods to predict in vivo chemical toxicity. Numerous studies have evaluated the use of targeted biochemical, cell-based and genomic assay approaches. Each of these techniques is potentially helpful, but provide...

Prediction of human population responses to toxic compounds by a collaborative competition.

PubMed

Eduati, Federica; Mangravite, Lara M; Wang, Tao; Tang, Hao; Bare, J Christopher; Huang, Ruili; Norman, Thea; Kellen, Mike; Menden, Michael P; Yang, Jichen; Zhan, Xiaowei; Zhong, Rui; Xiao, Guanghua; Xia, Menghang; Abdo, Nour; Kosyk, Oksana; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond R; Rusyn, Ivan; Wright, Fred A; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

2015-09-01

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

Expanding metal mixture toxicity models to natural stream and lake invertebrate communities

USGS Publications Warehouse

Balistrieri, Laurie S.; Mebane, Christopher A.; Schmidt, Travis S.; Keller, William (Bill)

2015-01-01

A modeling approach that was used to predict the toxicity of dissolved single and multiple metals to trout is extended to stream benthic macroinvertebrates, freshwater zooplankton, and Daphnia magna. The approach predicts the accumulation of toxicants (H, Al, Cd, Cu, Ni, Pb, and Zn) in organisms using 3 equilibrium accumulation models that define interactions between dissolved cations and biological receptors (biotic ligands). These models differ in the structure of the receptors and include a 2-site biotic ligand model, a bidentate biotic ligand or 2-pKa model, and a humic acid model. The predicted accumulation of toxicants is weighted using toxicant-specific coefficients and incorporated into a toxicity function called Tox, which is then related to observed mortality or invertebrate community richness using a logistic equation. All accumulation models provide reasonable fits to metal concentrations in tissue samples of stream invertebrates. Despite the good fits, distinct differences in the magnitude of toxicant accumulation and biotic ligand speciation exist among the models for a given solution composition. However, predicted biological responses are similar among the models because there are interdependencies among model parameters in the accumulation–Tox models. To illustrate potential applications of the approaches, the 3 accumulation–Tox models for natural stream invertebrates are used in Monte Carlo simulations to predict the probability of adverse impacts in catchments of differing geology in central Colorado (USA); to link geology, water chemistry, and biological response; and to demonstrate how this approach can be used to screen for potential risks associated with resource development.

DEVELOPING COMPUTATIONAL TOOLS FOR PREDICTING CHEMICAL FATE, METABOLISM, AND TOXICITY PATHWAYS

EPA Science Inventory

ORD's research program in Computational Toxicology (CompTox) will enable EPA Program Offices and other regulators to prioritize and reduce toxicity-testing requirements for potentially hazardous chemicals. The CompTox program defines the "toxicity process" as follows : 1) a stre...

The Analysis of Genomic Dose-Response Data in the EPA ToxCast™ Program

EPA Science Inventory

The U.S. EPA must assess the potential adverse effects of thousands of chemicals, often with limited toxicity information. Accurate toxicity predictions will help prioritize chemicals for further testing, focusing resources on the greater potential hazards or risks. In vitro geno...

Evaluation of 1066 ToxCast Chemicals in a human stem cell assay for developmental toxicity (SOT)

EPA Science Inventory

To increase the diversity of assays used to assess potential developmental toxicity, the ToxCast chemical library was screened in the Stemina devTOX quickPREDICT assay using human embryonic stem (hES) cells. A model for predicting teratogenicity was based on a training set of 23 ...

Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates

USGS Publications Warehouse

Patino, Reynaldo; VanLandeghem, Matthew M.; Denny, Shawn

2016-01-01

Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.

Prevalidation of an Acute Inhalation Toxicity Test Using the EpiAirway In Vitro Human Airway Model

PubMed Central

Jackson, George R.; Maione, Anna G.; Klausner, Mitchell

2018-01-01

Abstract Introduction: Knowledge of acute inhalation toxicity potential is important for establishing safe use of chemicals and consumer products. Inhalation toxicity testing and classification procedures currently accepted within worldwide government regulatory systems rely primarily on tests conducted in animals. The goal of the current work was to develop and prevalidate a nonanimal (in vitro) test for determining acute inhalation toxicity using the EpiAirway™ in vitro human airway model as a potential alternative for currently accepted animal tests. Materials and Methods: The in vitro test method exposes EpiAirway tissues to test chemicals for 3 hours, followed by measurement of tissue viability as the test endpoint. Fifty-nine chemicals covering a broad range of toxicity classes, chemical structures, and physical properties were evaluated. The in vitro toxicity data were utilized to establish a prediction model to classify the chemicals into categories corresponding to the currently accepted Globally Harmonized System (GHS) and the Environmental Protection Agency (EPA) system. Results: The EpiAirway prediction model identified in vivo rat-based GHS Acute Inhalation Toxicity Category 1–2 and EPA Acute Inhalation Toxicity Category I–II chemicals with 100% sensitivity and specificity of 43.1% and 50.0%, for GHS and EPA acute inhalation toxicity systems, respectively. The sensitivity and specificity of the EpiAirway prediction model for identifying GHS specific target organ toxicity-single exposure (STOT-SE) Category 1 human toxicants were 75.0% and 56.5%, respectively. Corrosivity and electrophilic and oxidative reactivity appear to be the predominant mechanisms of toxicity for the most highly toxic chemicals. Conclusions: These results indicate that the EpiAirway test is a promising alternative to the currently accepted animal tests for acute inhalation toxicity. PMID:29904643

Prevalidation of an Acute Inhalation Toxicity Test Using the EpiAirway In Vitro Human Airway Model.

PubMed

Jackson, George R; Maione, Anna G; Klausner, Mitchell; Hayden, Patrick J

2018-06-01

Introduction: Knowledge of acute inhalation toxicity potential is important for establishing safe use of chemicals and consumer products. Inhalation toxicity testing and classification procedures currently accepted within worldwide government regulatory systems rely primarily on tests conducted in animals. The goal of the current work was to develop and prevalidate a nonanimal ( in vitro ) test for determining acute inhalation toxicity using the EpiAirway™ in vitro human airway model as a potential alternative for currently accepted animal tests. Materials and Methods: The in vitro test method exposes EpiAirway tissues to test chemicals for 3 hours, followed by measurement of tissue viability as the test endpoint. Fifty-nine chemicals covering a broad range of toxicity classes, chemical structures, and physical properties were evaluated. The in vitro toxicity data were utilized to establish a prediction model to classify the chemicals into categories corresponding to the currently accepted Globally Harmonized System (GHS) and the Environmental Protection Agency (EPA) system. Results: The EpiAirway prediction model identified in vivo rat-based GHS Acute Inhalation Toxicity Category 1-2 and EPA Acute Inhalation Toxicity Category I-II chemicals with 100% sensitivity and specificity of 43.1% and 50.0%, for GHS and EPA acute inhalation toxicity systems, respectively. The sensitivity and specificity of the EpiAirway prediction model for identifying GHS specific target organ toxicity-single exposure (STOT-SE) Category 1 human toxicants were 75.0% and 56.5%, respectively. Corrosivity and electrophilic and oxidative reactivity appear to be the predominant mechanisms of toxicity for the most highly toxic chemicals. Conclusions: These results indicate that the EpiAirway test is a promising alternative to the currently accepted animal tests for acute inhalation toxicity.

Radiation-induced lymphocyte apoptosis to predict radiation therapy late toxicity in prostate cancer patients.

PubMed

Schnarr, Kara; Boreham, Douglas; Sathya, Jinka; Julian, Jim; Dayes, Ian S

2009-08-01

To examine a potential correlation between the in vitro apoptotic response of lymphocytes to radiation and the risk of developing late gastrointestinal (GI)/genitourinary (GU) toxicity from radiotherapy for prostate cancer. Prostate cancer patients formerly enrolled in a randomized study were tested for radiosensitivity by using a radiation-induced lymphocyte apoptosis assay. Apoptosis was measured using flow cytometry-based Annexin-FITC/7AAD and DiOC(6)/7AAD assays in subpopulations of lymphocytes (total lymphocytes, CD4+, CD8+ and CD4-/CD8-) after exposure to an in vitro dose of 0, 2, 4, or 8 Gy. Patients with late toxicity after radiotherapy showed lower lymphocyte apoptotic responses to 8 Gy than patients who had not developed late toxicity (p = 0.01). All patients with late toxicity had apoptosis levels that were at or below the group mean. The negative predictive value in both apoptosis assays ranged from 95% to 100%, with sensitivity values of 83% to 100%. Apoptosis at lower dose points and in lymphocyte subpopulations had a weaker correlation with the occurrence of late toxicity. Lymphocyte apoptosis after 8 Gy of radiation has the potential to predict which patients will be spared late toxicity after radiation therapy. Further research should be performed to identify the specific subset of lymphocytes that correlates with late toxicity, followed by a corresponding prospective study.

Assessing the Potential Environmental Consequences of a New Energetic Material: A Phased Approach, September 2005

DTIC Science & Technology

2007-12-01

there are no reliable alternatives to animal testing in the determination of toxicity. QSARs are only as reliable as the corroborating toxicological ...2) QSAR approaches can also be used to estimate toxicological impact. Toxicity QSAR models can often predict many toxicity parameters without... Toxicology Study No. 87-XE-03N3-05, Assessing the Potential Environmental Consequences of a New Energetic Material: A Phased Approach, September 2005 1

NEW PUBLIC DATA AND INTERNET RESOURCES ...

EPA Pesticide Factsheets

High-throughput screening (HTS) technologies, along with efforts to improve public access to chemical toxicity information resources and to systematize older toxicity studies, have the potential to significantly improve predictive capabilities in toxicology. Internet Resource

DEVELOPMENT OF EPA'S TOXCAST PROGRAM FOR PRIORITIZING THE TOXICITY TESTING OF ENVIRONMENTAL CHEMICALS.

EPA Science Inventory

EPA is developing methods for utilizing computational chemistry, high-throughput screening (HTS)and genomic technologies to predict potential toxicity and prioritize the use of limited testing resources.

EPAs ToxCast Program for Predicting Toxcity and Prioritizing Chemicals for Further Screening and Testing

EPA Science Inventory

Testing of environmental and industrial chemicals for toxicity potential is a daunting task because of the wide range of possible toxicity mechanisms. Although animal testing is one means of achieving broad toxicity coverage, evaluation of large numbers of chemicals is challengin...

The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity.

PubMed

Amacher, David E

2010-05-15

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other "omics" technologies can provide added selectivity and sensitivity in preclinical drug safety testing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Gupta, Shikha

Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data,more » optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the constructed (c) DTB and (d) DTF regression models to predict the T. pyriformis toxicity of diverse chemicals. - Highlights: • Ensemble learning (EL) based models constructed for toxicity prediction of chemicals • Predictive models used a few simple non-quantum mechanical molecular descriptors. • EL-based DTB/DTF models successfully discriminated toxic and non-toxic chemicals. • DTB/DTF regression models precisely predicted toxicity of chemicals in multi-species. • Proposed EL based models can be used as tool to predict toxicity of new chemicals.« less

Application of backpropagation artificial neural network prediction model for the PAH bioremediation of polluted soil.

PubMed

Olawoyin, Richard

2016-10-01

The backpropagation (BP) artificial neural network (ANN) is a renowned and extensively functional mathematical tool used for time-series predictions and approximations; which also define results for non-linear functions. ANNs are vital tools in the predictions of toxicant levels, such as polycyclic aromatic hydrocarbons (PAH) potentially derived from anthropogenic activities in the microenvironment. In the present work, BP ANN was used as a prediction tool to study the potential toxicity of PAH carcinogens (PAHcarc) in soils. Soil samples (16 × 4 = 64) were collected from locations in South-southern Nigeria. The concentration of PAHcarc in laboratory cultivated white melilot, Melilotus alba roots grown on treated soils was predicted using ANN model training. Results indicated the Levenberg-Marquardt back-propagation training algorithm converged in 2.5E+04 epochs at an average RMSE value of 1.06E-06. The averagedR(2) comparison between the measured and predicted outputs was 0.9994. It may be deduced from this study that, analytical processes involving environmental risk assessment as used in this study can successfully provide prompt prediction and source identification of major soil toxicants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fish embryo toxicity test: identification of compounds with weak toxicity and analysis of behavioral effects to improve prediction of acute toxicity for neurotoxic compounds.

PubMed

Klüver, Nils; König, Maria; Ortmann, Julia; Massei, Riccardo; Paschke, Albrecht; Kühne, Ralph; Scholz, Stefan

2015-06-02

The fish embryo toxicity test has been proposed as an alternative for the acute fish toxicity test, but concerns have been raised for its predictivity given that a few compounds have been shown to exhibit a weak acute toxicity in the fish embryo. In order to better define the applicability domain and improve the predictive capacity of the fish embryo test, we performed a systematic analysis of existing fish embryo and acute fish toxicity data. A correlation analysis of a total of 153 compounds identified 28 compounds with a weaker or no toxicity in the fish embryo test. Eleven of these compounds exhibited a neurotoxic mode of action. We selected a subset of eight compounds with weaker or no embryo toxicity (cyanazine, picloram, aldicarb, azinphos-methyl, dieldrin, diquat dibromide, endosulfan, and esfenvalerate) to study toxicokinetics and a neurotoxic mode of action as potential reasons for the deviating fish embryo toxicity. Published fish embryo LC50 values were confirmed by experimental analysis of zebrafish embryo LC50 according to OECD guideline 236. Except for diquat dibromide, internal concentration analysis did not indicate a potential relation of the low sensitivity of fish embryos to a limited uptake of the compounds. Analysis of locomotor activity of diquat dibromide and the neurotoxic compounds in 98 hpf embryos (exposed for 96 h) indicated a specific effect on behavior (embryonic movement) for the neurotoxic compounds. The EC50s of behavior for neurotoxic compounds were close to the acute fish toxicity LC50. Our data provided the first evidence that the applicability domain of the fish embryo test (LC50s determination) may exclude neurotoxic compounds. However, neurotoxic compounds could be identified by changes in embryonic locomotion. Although a quantitative prediction of acute fish toxicity LC50 using behavioral assays in fish embryos may not yet be possible, the identification of neurotoxicity could trigger the conduction of a conventional fish acute toxicity test or application of assessment factors while considering the very good fish embryo-acute fish toxicity correlation for other compounds.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amacher, David E.

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intendedmore » human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other 'omics' technologies can provide added selectivity and sensitivity in preclinical drug safety testing.« less

Mapping the Human Toxome by Systems Toxicology

PubMed Central

Bouhifd, Mounir; Hogberg, Helena T.; Kleensang, Andre; Maertens, Alexandra; Zhao, Liang; Hartung, Thomas

2014-01-01

Toxicity testing typically involves studying adverse health outcomes in animals subjected to high doses of toxicants with subsequent extrapolation to expected human responses at lower doses. The low-throughput of current toxicity testing approaches (which are largely the same for industrial chemicals, pesticides and drugs) has led to a backlog of more than 80,000 chemicals to which human beings are potentially exposed whose potential toxicity remains largely unknown. Employing new testing strategies that employ the use of predictive, high-throughput cell-based assays (of human origin) to evaluate perturbations in key pathways, referred as pathways of toxicity, and to conduct targeted testing against those pathways, we can begin to greatly accelerate our ability to test the vast “storehouses” of chemical compounds using a rational, risk-based approach to chemical prioritization, and provide test results that are more predictive of human toxicity than current methods. The NIH Transformative Research Grant project Mapping the Human Toxome by Systems Toxicology aims at developing the tools for pathway mapping, annotation and validation as well as the respective knowledge base to share this information. PMID:24443875

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

THE TOXCAST PROGRAM FOR PRIORITIZING TOXICITY TESTING OF ENVIRONMENTAL CHEMICALS

EPA Science Inventory

The United States Environmental Protection Agency (EPA) is developing methods for utilizing computational chemistry, high-throughput screening (HTS) and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources towards chemicals...

In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

PubMed

Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

2015-01-01

The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids.

PubMed

Cao, Lingdi; Zhu, Peng; Zhao, Yongsheng; Zhao, Jihong

2018-06-15

Large-scale application of ionic liquids (ILs) hinges on the advancement of designable and eco-friendly nature. Research of the potential toxicity of ILs towards different organisms and trophic levels is insufficient. Quantitative structure-activity relationships (QSAR) model is applied to evaluate the toxicity of ILs towards the leukemia rat cell line (ICP-81). The structures of 57 cations and 21 anions were optimized by quantum chemistry. The electrostatic potential surface area (S EP ) and charge distribution area (S σ-profile ) descriptors are calculated and used to predict the toxicity of ILs. The performance and predictive aptitude of extreme learning machine (ELM) model are analyzed and compared with those of multiple linear regression (MLR) and support vector machine (SVM) models. The highest R 2 and the lowest AARD% and RMSE of the training set, test set and total set for the ELM are observed, which validates the superior performance of the ELM than that of obtained by the MLR and SVM. The applicability domain of the model is assessed by the Williams plot. Copyright © 2018 Elsevier B.V. All rights reserved.

Incorporation of absorption and metabolism into liver toxicity prediction for phytochemicals: A tiered in silico QSAR approach.

PubMed

Liu, Yitong

2018-05-18

An increased use of herbal dietary supplements has been associated with adverse liver effects such as elevated serum enzymes and liver failure. The safety assessment for herbal dietary supplements is challenging since they often contain complex mixtures of phytochemicals, most of which have unknown pharmacokinetic and toxicological properties. Rapid tools are needed to evaluate large numbers of phytochemicals for potential liver toxicity. The current study demonstrates a tiered approach combining identification of phytochemicals in liver toxic botanicals, followed by in silico quantitative structure-activity relationship (QSAR) evaluation of these phytochemicals for absorption (e.g. permeability), metabolism (cytochromes P450) and liver toxicity (e.g. elevated transaminases). First, 255 phytochemicals from 20 botanicals associated with clinical liver injury were identified, and the phytochemical structures were subsequently used for QSAR evaluation. Among these identified phytochemicals, 193 were predicted to be absorbed and then used to generate metabolites, which were both used to predict liver toxicity. Forty-eight phytochemicals were predicted as liver toxic, either due to parent phytochemicals or metabolites. Among them, nineteen phytochemicals have previous evidence of liver toxicity (e.g. pyrrolizidine alkaloids), while the majority were newly discovered (e.g. sesquiterpenoids). These findings help reveal new toxic phytochemicals in herbal dietary supplements and prioritize future toxicological testing. Published by Elsevier Ltd.

Computational Molecular Modeling for Evaluating the Toxicity of Environmental Chemicals: Prioritizing Bioassay Requirements

EPA Science Inventory

This commentary provides an overview of the challenges that arise from applying molecular modeling tools developed and commonly used for pharmaceutical discovery to the problem of predicting the potential toxicities of environmental chemicals.

Radiation Dose-Volume Effects in the Stomach and Small Bowel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kavanagh, Brian D., E-mail: Brian.Kavanagh@ucdenver.ed; Pan, Charlie C.; Dawson, Laura A.

2010-03-01

Published data suggest that the risk of moderately severe (>=Grade 3) radiation-induced acute small-bowel toxicity can be predicted with a threshold model whereby for a given dose level, D, if the volume receiving that dose or greater (VD) exceeds a threshold quantity, the risk of toxicity escalates. Estimates of VD depend on the means of structure segmenting (e.g., V15 = 120 cc if individual bowel loops are outlined or V45 = 195 cc if entire peritoneal potential space of bowel is outlined). A similar predictive model of acute toxicity is not available for stomach. Late small-bowel/stomach toxicity is likely relatedmore » to maximum dose and/or volume threshold parameters qualitatively similar to those related to acute toxicity risk. Concurrent chemotherapy has been associated with a higher risk of acute toxicity, and a history of abdominal surgery has been associated with a higher risk of late toxicity.« less

Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms

USGS Publications Warehouse

Nowell, Lisa H.; Norman, Julia E.; Moran, Patrick W.; Martin, Jeffrey D.; Stone, Wesley W.

2014-01-01

Pesticide mixtures are common in streams with agricultural or urban influence in the watershed. The Pesticide Toxicity Index (PTI) is a screening tool to assess potential aquatic toxicity of complex pesticide mixtures by combining measures of pesticide exposure and acute toxicity in an additive toxic-unit model. The PTI is determined separately for fish, cladocerans, and benthic invertebrates. This study expands the number of pesticides and degradates included in previous editions of the PTI from 124 to 492 pesticides and degradates, and includes two types of PTI for use in different applications, depending on study objectives. The Median-PTI was calculated from median toxicity values for individual pesticides, so is robust to outliers and is appropriate for comparing relative potential toxicity among samples, sites, or pesticides. The Sensitive-PTI uses the 5th percentile of available toxicity values, so is a more sensitive screening-level indicator of potential toxicity. PTI predictions of toxicity in environmental samples were tested using data aggregated from published field studies that measured pesticide concentrations and toxicity to Ceriodaphnia dubia in ambient stream water. C. dubia survival was reduced to ≤ 50% of controls in 44% of samples with Median-PTI values of 0.1–1, and to 0% in 96% of samples with Median-PTI values > 1. The PTI is a relative, but quantitative, indicator of potential toxicity that can be used to evaluate relationships between pesticide exposure and biological condition.

DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS ...

EPA Pesticide Factsheets

DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction ModelsAnn M. RichardUS Environmental Protection Agency, Research Triangle Park, NC, USADistributed: Decentralized set of standardized, field-delimited databases, each separatelyauthored and maintained, that are able to accommodate diverse toxicity data content;Structure-Searchable: Standard format (SDF) structure-data files that can be readily imported into available chemical relational databases and structure-searched;Tox: Toxicity data as it exists in widely disparate forms in current public databases, spanning diverse toxicity endpoints, test systems, levels of biological content, degrees of summarization, and information content.INTRODUCTIONThe economic and social pressures to reduce the need for animal testing and to better anticipate the potential for human and eco-toxicity of environmental, industrial, or pharmaceutical chemicals are as pressing today as at any time prior. However, the goal of predicting chemical toxicity in its many manifestations, the `T' in 'ADMET' (adsorption, distribution, metabolism, elimination, toxicity), remains one of the most difficult and largely unmet challenges in a chemical screening paradigm [1]. It is widely acknowledged that the single greatest hurdle to improving structure-activity relationship (SAR) toxicity prediction capabilities, in both the pharmaceutical and environmental regulation arenas, is the lack of suffici

Is the bitter rejection response always adaptive?

PubMed

Glendinning, J I

1994-12-01

The bitter rejection response consists of a suite of withdrawal reflexes and negative affective responses. It is generally assumed to have evolved as a way to facilitate avoidance of foods that are poisonous because they usually taste bitter to humans. Using previously published studies, the present paper examines the relationship between bitterness and toxicity in mammals, and then assesses the ecological costs and benefits of the bitter rejection response in carnivorous, omnivorous, and herbivorous (grazing and browsing) mammals. If the bitter rejection response accurately predicts the potential toxicity of foods, then one would expect the threshold for the response to be lower for highly toxic compounds than for nontoxic compounds. The data revealed no such relationship. Bitter taste thresholds varied independently of toxicity thresholds, indicating that the bitter rejection response is just as likely to be elicited by a harmless bitter food as it is by a harmful one. Thus, it is not necessarily in an animal's best interest to have an extremely high or low bitter threshold. Based on this observation, it was hypothesized that the adaptiveness of the bitter rejection response depends upon the relative occurrence of bitter and potentially toxic compounds in an animal's diet. Animals with a relatively high occurrence of bitter and potentially toxic compounds in their diet (e.g., browsing herbivores) were predicted to have evolved a high bitter taste threshold and tolerance to dietary poisons. Such an adaptation would be necessary because a browser cannot "afford" to reject all foods that are bitter and potentially toxic without unduly restricting its dietary options. At the other extreme, animals that rarely encounter bitter and potentially toxic compounds in their diet (e.g., carnivores) were predicted to have evolved a low bitter threshold. Carnivores could "afford" to utilize such a stringent rejection mechanism because foods containing bitter and potentially toxic compounds constitute a small portion of their diet. Since the low bitter threshold would reduce substantially the risk of ingesting anything poisonous, carnivores were also expected to have a relatively low tolerance to dietary poisons. This hypothesis was supported by a comparison involving 30 mammal species, in which a suggestive relationship was found between quinine hydrochloride sensitivity and trophic group, with carnivores > omnivores > grazers > browsers. Further support for the hypothesis was provided by a comparison across browsers and grazers in terms of the production of tannin-binding salivary proteins, which probably represent an adaptation for reducing the bitterness and astringency of tannins.(ABSTRACT TRUNCATED AT 400 WORDS)

ExpoCast: Exposure Science for Prioritization and Toxicity Testing (S)

EPA Science Inventory

The US EPA is completing the Phase I pilot for a chemical prioritization research program, called ToxCast. Here EPA is developing methods for using computational chemistry, high-throughput screening, and toxicogenomic technologies to predict potential toxicity and prioritize limi...

ExpoCast: Exposure Science for Prioritization and Toxicity Testing

EPA Science Inventory

The US EPA is completing the Phase I pilot for a chemical prioritization research program, called ToxCastTM. Here EPA is developing methods for using computational chemistry, high-throughput screening, and toxicogenomic technologies to predict potential toxicity and prioritize l...

A novel two-dimensional liquid-chromatography method for online prediction of the toxicity of transformation products of benzophenones after water chlorination.

PubMed

Li, Jian; Ma, Li-Yun; Xu, Li; Shi, Zhi-Guo

2015-08-01

Benzophenone-type UV filters (BPs) are ubiquitous in the environment. Transformation products (TPs) of BPs with suspected toxicity are likely to be produced during disinfection of water by chlorination. To quickly predict the toxicity of TPs, in this study, a novel two-dimensional liquid-chromatography (2D-LC) method was established in which the objective of the first dimension was to separate the multiple components of the BPs sample after chlorination, using a reversed-phase liquid-chromatography mode. A biochromatographic system, i.e. bio-partitioning micellar chromatography with the polyoxyethylene (23) lauryl ether aqueous solution as the mobile phase, served as the second dimension to predict the toxicity of the fraction from the first dimension on the basis of the quantitative retention-activity relationships (QRARs) model. Six BPs, namely 2,4-dihydroxybenzophenone, oxybenzone, 4-hydroxybenzophenone, 2-hydroxy-4-methoxybenzophenone-5-sulfonic acid, 2,2'-dihydroxy-4,4'-dimethoxybenzophenone and 2,2'-dihydroxy-4-methoxybenzophenone, were the target analytes subjected to chlorination. The products of these BPs after chlorination were directly injected to the 2D-LC system for analysis. The results indicated that most TPs may be less toxic than their parent chemicals, but some may be more toxic, and that intestinal toxicity of TPs may be more obvious than blood toxicity. The proposed method is time-saving, high-throughput, and reliable, and has great potential for predicting toxicity or bioactivity of unknown and/or known components in a complex sample. Graphical Abstract The scheme for the 2D-LC online prediction of toxicity of the transformation products of benzophenone-type UV filters after chlorination.

Exposure Space: Integrating Exposure Data and Modeling with Toxicity Information

EPA Science Inventory

Recent advances have been made in high-throughput (HTP) toxicity testing, e.g. from ToxCast, which will ultimately be combined with HTP predictions of exposure potential to support next-generation chemical safety assessment. Rapid exposure methods are essential in selecting chemi...

Biokinetics of zinc oxide nanoparticles: toxicokinetics, biological fates, and protein interaction

PubMed Central

Choi, Soo-Jin; Choy, Jin-Ho

2014-01-01

Biokinetic studies of zinc oxide (ZnO) nanoparticles involve systematic and quantitative analyses of absorption, distribution, metabolism, and excretion in plasma and tissues of whole animals after exposure. A full understanding of the biokinetics provides basic information about nanoparticle entry into systemic circulation, target organs of accumulation and toxicity, and elimination time, which is important for predicting the long-term toxic potential of nanoparticles. Biokinetic behaviors can be dependent on physicochemical properties, dissolution property in biological fluids, and nanoparticle–protein interaction. Moreover, the determination of biological fates of ZnO nanoparticles in the systemic circulation and tissues is critical in interpreting biokinetic behaviors and predicting toxicity potential as well as mechanism. This review focuses on physicochemical factors affecting the biokinetics of ZnO nanoparticles, in concert with understanding bioavailable fates and their interaction with proteins. PMID:25565844

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

PubMed

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

INTEGRATED CHEMICAL INFORMATION TECHNOLOGIES ...

EPA Pesticide Factsheets

A central regulatory mandate of the Environmental Protection Agency, spanning many Program Offices and issues, is to assess the potential health and environmental risks of large numbers of chemicals released into the environment, often in the absence of relevant test data. Models for predicting potential adverse effects of chemicals based primarily on chemical structure play a central role in prioritization and screening strategies yet are highly dependent and conditional upon the data used for developing such models. Hence, limits on data quantity, quality, and availability are considered by many to be the largest hurdles to improving prediction models in diverse areas of toxicology. Generation of new toxicity data for additional chemicals and endpoints, development of new high-throughput, mechanistically relevant bioassays, and increased generation of genomics and proteomics data that can clarify relevant mechanisms will all play important roles in improving future SAR prediction models. The potential for much greater immediate gains, across large domains of chemical and toxicity space, comes from maximizing the ability to mine and model useful information from existing toxicity data, data that represent huge past investment in research and testing expenditures. In addition, the ability to place newer “omics” data, data that potentially span many possible domains of toxicological effects, in the broader context of historical data is the means for opti

Metal-Polycyclic Aromatic Hydrocarbon Mixture Toxicity in Hyalella azteca. 1. Response Surfaces and Isoboles To Measure Non-additive Mixture Toxicity and Ecological Risk.

PubMed

Gauthier, Patrick T; Norwood, Warren P; Prepas, Ellie E; Pyle, Greg G

2015-10-06

Mixtures of metals and polycyclic aromatic hydrocarbons (PAHs) occur ubiquitously in aquatic environments, yet relatively little is known regarding their potential to produce non-additive toxicity (i.e., antagonism or potentiation). A review of the lethality of metal-PAH mixtures in aquatic biota revealed that more-than-additive lethality is as common as strictly additive effects. Approaches to ecological risk assessment do not consider non-additive toxicity of metal-PAH mixtures. Forty-eight-hour water-only binary mixture toxicity experiments were conducted to determine the additive toxic nature of mixtures of Cu, Cd, V, or Ni with phenanthrene (PHE) or phenanthrenequinone (PHQ) using the aquatic amphipod Hyalella azteca. In cases where more-than-additive toxicity was observed, we calculated the possible mortality rates at Canada's environmental water quality guideline concentrations. We used a three-dimensional response surface isobole model-based approach to compare the observed co-toxicity in juvenile amphipods to predicted outcomes based on concentration addition or effects addition mixtures models. More-than-additive lethality was observed for all Cu-PHE, Cu-PHQ, and several Cd-PHE, Cd-PHQ, and Ni-PHE mixtures. Our analysis predicts Cu-PHE, Cu-PHQ, Cd-PHE, and Cd-PHQ mixtures at the Canadian Water Quality Guideline concentrations would produce 7.5%, 3.7%, 4.4% and 1.4% mortality, respectively.

Sirc-cvs cytotoxicity test: an alternative for predicting rodent acute systemic toxicity.

PubMed

Kitagaki, Masato; Wakuri, Shinobu; Hirota, Morihiko; Tanaka, Noriho; Itagaki, Hiroshi

2006-10-01

An in vitro crystal violet staining method using the rabbit cornea-derived cell line (SIRC-CVS) has been developed as an alternative to predict acute systemic toxicity in rodents. Seventy-nine chemicals, the in vitro cytotoxicity of which was already reported by the Multicenter Evaluation of In vitro Toxicity (MEIC) and ICCVAM/ECVAM, were selected as test compounds. The cells were incubated with the chemicals for 72 hrs and the IC(50) and IC(35) values (microg/mL) were obtained. The results were compared to the in vivo (rat or mouse) "most toxic" oral, intraperitoneal, subcutaneous and intravenous LD(50) values (mg/kg) taken from the RTECS database for each of the chemicals by using Pearson's correlation statistics. The following parameters were calculated: accuracy, sensitivity, specificity, prevalence, positive predictability, and negative predictability. Good linear correlations (Pearson's coefficient; r>0.6) were observed between either the IC(50) or the IC(35) values and all the LD(50) values. Among them, a statistically significant high correlation (r=0.8102, p<0.001) required for acute systemic toxicity prediction was obtained between the IC(50) values and the oral LD(50) values. By using the cut-off concentrations of 2,000 mg/kg (LD(50)) and 4,225 microg/mL (IC(50)), no false negatives were observed, and the accuracy was 84.8%. From this, it is concluded that this method could be used to predict the acute systemic toxicity potential of chemicals in rodents.

Acute photo-induced toxicity and toxicokinetics of single compounds and mixtures of polycyclic aromatic hydrocarbons in zebrafish.

PubMed

Willis, Alison M; Oris, James T

2014-09-01

The present study examined photo-induced toxicity and toxicokinetics for acute exposure to selected polycyclic aromatic hydrocarbons (PAHs) in zebrafish. Photo-enhanced toxicity from co-exposure to ultraviolet (UV) radiation and PAHs enhanced the toxicity and exhibited toxic effects at PAH concentrations orders of magnitude below effects observed in the absence of UV. Because environmental exposure to PAHs is usually in the form of complex mixtures, the present study examined the photo-induced toxicity of both single compounds and mixtures of PAHs. In a sensitive larval life stage of zebrafish, acute photo-induced median lethal concentrations (LC50s) were derived for 4 PAHs (anthracene, pyrene, carbazole, and phenanthrene) to examine the hypothesis that phototoxic (anthracene and pyrene) and nonphototoxic (carbazole and phenanthrene) pathways of mixtures could be predicted from single exposures. Anthracene and pyrene were phototoxic as predicted; however, carbazole exhibited moderate photo-induced toxicity and phenanthrene exhibited weak photo-induced toxicity. The toxicity of each chemical alone was used to compare the toxicity of mixtures in binary, tertiary, and quaternary combinations of these PAHs, and a predictive model for environmental mixtures was generated. The results indicated that the acute toxicity of PAH mixtures was additive in phototoxic scenarios, regardless of the magnitude of photo-enhancement. Based on PAH concentrations found in water and circumstances of high UV dose to aquatic systems, there exists potential risk of photo-induced toxicity to aquatic organisms. © 2014 SETAC.

The potential of AOP networks for reproductive and developmental toxicity assay development

EPA Science Inventory

Historically, the prediction of reproductive and early developmental toxicity has largely relied on the use of animals. The Adverse Outcome Pathway (AOP) framework forms a basis for the development of new non-animal test methods. It also provides biological context for mechanisti...

Predicting the toxicity of metal mixtures

USGS Publications Warehouse

Balistrieri, Laurie S.; Mebane, Christopher A.

2013-01-01

The toxicity of single and multiple metal (Cd, Cu, Pb, and Zn) solutions to trout is predicted using an approach that combines calculations of: (1) solution speciation; (2) competition and accumulation of cations (H, Ca, Mg, Na, Cd, Cu, Pb, and Zn) on low abundance, high affinity and high abundance, low affinity biotic ligand sites; (3) a toxicity function that accounts for accumulation and potency of individual toxicants; and (4) biological response. The approach is evaluated by examining water composition from single metal toxicity tests of trout at 50% mortality, results of theoretical calculations of metal accumulation on fish gills and associated mortality for single, binary, ternary, and quaternary metal solutions, and predictions for a field site impacted by acid rock drainage. These evaluations indicate that toxicity of metal mixtures depends on the relative affinity and potency of toxicants for a given aquatic organism, suites of metals in the mixture, dissolved metal concentrations and ratios, and background solution composition (temperature, pH, and concentrations of major ions and dissolved organic carbon). A composite function that incorporates solution composition, affinity and competition of cations for two types of biotic ligand sites, and potencies of hydrogen and individual metals is proposed as a tool to evaluate potential toxicity of environmental solutions to trout.

Acute toxicity of anionic and non-ionic surfactants to aquatic organisms.

PubMed

Lechuga, M; Fernández-Serrano, M; Jurado, E; Núñez-Olea, J; Ríos, F

2016-03-01

The environmental risk of surfactants requires toxicity measurements. As different test organisms have different sensitivity to the toxics, it is necessary to establish the most appropriate organism to classify the surfactant as very toxic, toxic, harmful or safe, in order to establish the maximum permissible concentrations in aquatic ecosystems. We have determined the toxicity values of various anionic surfactants ether carboxylic derivatives using four test organisms: the freshwater crustacean Daphnia magna, the luminescent bacterium Vibrio fischeri, the microalgae Selenastrum capricornutum (freshwater algae) and Phaeodactylum tricornutum (seawater algae). In addition, in order to compare and classify the different families of surfactants, we have included a compilation of toxicity data of surfactants collected from literature. The results indicated that V. fischeri was more sensitive to the toxic effects of the surfactants than was D. magna or the microalgae, which was the least sensitive. This result shows that the most suitable toxicity assay for surfactants may be the one using V. fischeri. The toxicity data revealed considerable variation in toxicity responses with the structure of the surfactants regardless of the species tested. The toxicity data have been related to the structure of the surfactants, giving a mathematical relationship that helps to predict the toxic potential of a surfactant from its structure. Model-predicted toxicity agreed well with toxicity values reported in the literature for several surfactants previously studied. Predictive models of toxicity is a handy tool for providing a risk assessment that can be useful to establish the toxicity range for each surfactant and the different test organisms in order to select efficient surfactants with a lower impact on the aquatic environment. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluating the Zebrafish Embryo Toxicity Test for Pesticide Hazard Screening

EPA Science Inventory

Given the numerous chemicals used in society, it is critical to develop tools for accurate and efficient evaluation of potential risks to human and ecological receptors. Fish embryo acute toxicity tests are 1 tool that has been shown to be highly predictive of standard, more reso...

The U.S. EPA's ToxCast Chemical Screening Program and Predictive Modeling of Toxicity

EPA Science Inventory

The ToxCast program was developed by the U.S. EPA's National Center for Computational Toxicology to provide cost-effective high-throughput screening for the potential toxicity of thousands of chemicals. Phase I screened 309 compounds in over 500 assays to evaluate concentration-...

The US EPAs ToxCast Program for the Prioritization and Prediction of Environmental Chemical Toxicity

EPA Science Inventory

To meet the need for evaluating large numbers of chemicals for potential toxicity, the U.S. Environmental Protection Agency has initiated a research project call ToxCast that makes use of recent advances in molecular biology and high-throughput screening. These technologies have ...

Predictive Modeling of Apical Toxicity Endpoints Using Data From ToxCast

EPA Science Inventory

The US EPA and other regulatory agencies face a daunting challenge of evaluating potential toxicity for tens of thousands of environmental chemicals about which little is currently known. The EPA’s ToxCast program is testing a novel approach to this problem by screening compounds...

Toward toxicity testing of nanomaterials in the 21st century: a paradigm for moving forward.

PubMed

Lai, David Y

2012-01-01

A challenge-facing hazard identification and safety evaluation of engineered nanomaterials being introduced to market is the diversity and complexity of the types of materials with varying physicochemical properties, many of which can affect their toxicity by different mechanisms. In general, in vitro test systems have limited usefulness for hazard identification of nanoparticles due to various issues. Meanwhile, conducting chronic toxicity/carcinogenicity studies in rodents for every new nanomaterial introduced into the commerce is impractical if not impossible. New toxicity testing systems which rely on predictive, high-throughput technologies may be the ultimate goal of evaluating the potential hazard of nanomaterials. However, at present, this approach alone is unlikely to succeed in evaluating the toxicity of the wide array of nanomaterials and requires validation from in vivo studies. This article proposes a paradigm for toxicity testing and elucidation of the molecular mechanisms of reference materials for specific nanomaterial classes/subclasses using short-term in vivo animal studies in conjunction with high-throughput screenings and mechanism-based short-term in vitro assays. The hazard potential of a particular nanomaterial can be evaluated by conducting only in vitro high-throughput assays and mechanistic studies and comparing the data with those of the reference materials in the specific class/subclass-an approach in line with the vision for 'Toxicity Testing in the 21st Century' of chemicals. With well-designed experiments, testing nanomaterials of varying/selected physicochemical parameters may be able to identify the physicochemical parameters contributing to toxicity. The data so derived could be used for the development of computer model systems to predict the hazard potential of specific nanoparticles based on property-activity relationships. Copyright © 2011 John Wiley & Sons, Inc.

Metabolic Toxicity Screening Using Electrochemiluminescence Arrays Coupled with Enzyme-DNA Biocolloid Reactors and Liquid Chromatography-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Hvastkovs, Eli, G.; Schenkman, John B.; Rusling, James, F.

2012-07-01

New chemicals or drugs must be guaranteed safe before they can be marketed. Despite widespread use of bioassay panels for toxicity prediction, products that are toxic to a subset of the population often are not identified until clinical trials. This article reviews new array methodologies based on enzyme/DNA films that form and identify DNA-reactive metabolites that are indicators of potentially genotoxic species. This molecularly based methodology is designed in a rapid screening array that utilizes electrochemiluminescence (ECL) to detect metabolite-DNA reactions, as well as biocolloid reactors that provide the DNA adducts and metabolites for liquid chromatography-mass spectrometry (LC-MS) analysis. ECL arrays provide rapid toxicity screening, and the biocolloid reactor LC-MS approach provides a valuable follow-up on structure, identification, and formation rates of DNA adducts for toxicity hits from the ECL array screening. Specific examples using this strategy are discussed. Integration of high-throughput versions of these toxicity-screening methods with existing drug toxicity bioassays should allow for better human toxicity prediction as well as more informed decision making regarding new chemical and drug candidates.

In silico toxicity prediction by support vector machine and SMILES representation-based string kernel.

PubMed

Cao, D-S; Zhao, J-C; Yang, Y-N; Zhao, C-X; Yan, J; Liu, S; Hu, Q-N; Xu, Q-S; Liang, Y-Z

2012-01-01

There is a great need to assess the harmful effects or toxicities of chemicals to which man is exposed. In the present paper, the simplified molecular input line entry specification (SMILES) representation-based string kernel, together with the state-of-the-art support vector machine (SVM) algorithm, were used to classify the toxicity of chemicals from the US Environmental Protection Agency Distributed Structure-Searchable Toxicity (DSSTox) database network. In this method, the molecular structure can be directly encoded by a series of SMILES substrings that represent the presence of some chemical elements and different kinds of chemical bonds (double, triple and stereochemistry) in the molecules. Thus, SMILES string kernel can accurately and directly measure the similarities of molecules by a series of local information hidden in the molecules. Two model validation approaches, five-fold cross-validation and independent validation set, were used for assessing the predictive capability of our developed models. The results obtained indicate that SVM based on the SMILES string kernel can be regarded as a very promising and alternative modelling approach for potential toxicity prediction of chemicals.

Relation between different metal pollution criteria in sediments and its contribution on assessing toxicity.

PubMed

Alves, Cristina M; Ferreira, Carlos M H; Soares, Helena M V M

2018-05-14

Several tools have been developed and applied to evaluate the metal pollution status of sediments and predict their potential ecological risk assessment. To date, a comprehensive relationship between the information given by these sediment tools for predicting metal bioavailability and the effective toxicity observed is lacking. In this work, the possible inter-correlations between the data outcoming from using several qualitative evaluation tools of the sediment contamination (contamination factor, CF, the enrichment factor, EF, or the geoaccumulation index, Igeo), metal speciation on sediments (evaluated by the modified BCR sequential extraction procedure) and free metal concentrations in pore waters were studied. It was also our aim to evaluate if these assessment tools could be used for predicting the pore waters toxicity data as toxicity proxy. Principal component analysis and cluster analysis revealed that two quality indices used (CF and EF) were highly correlatable with the more labile fractions from BCR sediment speciation. However, neither of these parameters did correlate with the toxicity of pore waters measured by the chronic toxicity (72 h) in Pseudokirchneriella subcapitata. In contrast, the toxic effects of the given total metal load in sediments were better evaluated by using an additive metal approach using pore water free metal concentrations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predictive In Vitro Screening of Environmental Chemicals – The ToxCast Project

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Computer-assisted engineering of the synthetic pathway for biodegradation of a toxic persistent pollutant.

PubMed

Kurumbang, Nagendra Prasad; Dvorak, Pavel; Bendl, Jaroslav; Brezovsky, Jan; Prokop, Zbynek; Damborsky, Jiri

2014-03-21

Anthropogenic halogenated compounds were unknown to nature until the industrial revolution, and microorganisms have not had sufficient time to evolve enzymes for their degradation. The lack of efficient enzymes and natural pathways can be addressed through a combination of protein and metabolic engineering. We have assembled a synthetic route for conversion of the highly toxic and recalcitrant 1,2,3-trichloropropane to glycerol in Escherichia coli, and used it for a systematic study of pathway bottlenecks. Optimal ratios of enzymes for the maximal production of glycerol, and minimal toxicity of metabolites were predicted using a mathematical model. The strains containing the expected optimal ratios of enzymes were constructed and characterized for their viability and degradation efficiency. Excellent agreement between predicted and experimental data was observed. The validated model was used to quantitatively describe the kinetic limitations of currently available enzyme variants and predict improvements required for further pathway optimization. This highlights the potential of forward engineering of microorganisms for the degradation of toxic anthropogenic compounds.

Evaluation of the phototoxicity of unsubstituted and alkylated polycyclic aromatic hydrocarbons to mysid shrimp (Americamysis bahia): Validation of predictive models.

PubMed

Finch, Bryson E; Marzooghi, Solmaz; Di Toro, Dominic M; Stubblefield, William A

2017-08-01

Crude oils are composed of an assortment of hydrocarbons, some of which are polycyclic aromatic hydrocarbons (PAHs). Polycyclic aromatic hydrocarbons are of particular interest due to their narcotic and potential phototoxic effects. Several studies have examined the phototoxicity of individual PAHs and fresh and weathered crude oils, and several models have been developed to predict PAH toxicity. Fingerprint analyses of oils have shown that PAHs in crude oils are predominantly alkylated. However, current models for estimating PAH phototoxicity assume toxic equivalence between unsubstituted (i.e., parent) and alkyl-substituted compounds. This approach may be incorrect if substantial differences in toxic potency exist between unsubstituted and substituted PAHs. The objective of the present study was to examine the narcotic and photo-enhanced toxicity of commercially available unsubstituted and alkylated PAHs to mysid shrimp (Americamysis bahia). Data were used to validate predictive models of phototoxicity based on the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap approach and to develop relative effect potencies. Results demonstrated that photo-enhanced toxicity increased with increasing methylation and that phototoxic PAH potencies vary significantly among unsubstituted compounds. Overall, predictive models based on the HOMO-LUMO gap were relatively accurate in predicting phototoxicity for unsubstituted PAHs but are limited to qualitative assessments. Environ Toxicol Chem 2017;36:2043-2049. © 2017 SETAC. © 2017 SETAC.

Predictive acute toxicity tests with pesticides.

PubMed

Brown, V K

1983-01-01

By definition pesticides are biocidal products and this implies a probability that pesticides may be acutely toxic to species other than the designated target species. The ways in which pesticides are manufactured, formulated, packaged, distributed and used necessitates a potential for the exposure of non-target species although the technology exists to minimize adventitious exposure. The occurrence of deliberate exposure of non-target species due to the misuse of pesticides is known to happen. The array of predictive acute toxicity tests carried out on pesticides and involving the use of laboratory animals can be justified as providing data on which hazard assessment can be based. This paper addresses the justification and rationale of this statement.

In vitro and in silico antioxidant and toxicological activities of Achyrocline satureioides.

PubMed

Salgueiro, Andréia C F; Folmer, Vanderlei; da Rosa, Hemerson S; Costa, Márcio T; Boligon, Aline A; Paula, Fávero R; Roos, Daniel H; Puntel, Gustavo O

2016-12-24

Achyrocline satureioides ("macela or marcela") is a medicinal plant, traditionally collected in "Good Friday" before sunrise. In traditional medicine, dried flowers of A. satureioides are used as anti-dyspeptic, antispasmodic and anti-inflammatory. To evaluate the phytochemical profile and to present an in vitro and in silico approach about toxicity and antioxidant potential of A. satureioides flowers extract and its major phytoconstituents. Plant were collected according to the popular tradition. Extract were obtained by infusion and analyzed from high-performance liquid chromatography. Toxicity was evaluated in Artemia salina and human lymphocytes. Extract antioxidant activity was determined with total antioxidant capacity, DPPH • and ABTS +• scavenging, ferric reducing antioxidant power, deoxyribose degradation assay, and thiobarbituric acid reactive substances (TBA-RS) assay. TBA-RS inhibitions were evaluated in brain of rats for A. satureioides extract and its major phytoconstituents. Predictions of activity spectra for substances and in silico toxicity evaluation from major phytoconstituents were performed via computer simulation. Chromatographic data indicated isoquercitrin, quercetin and caffeic acid as main compounds in flowers extract. Toxicity tests demonstrated a very low toxic potential of A. satureioides. Extract exhibited antioxidant activities in low concentrations. Both extract and major phytochemicals standards showed protection against lipid peroxidation in brain of rats. Computer simulations pointed some biological activities in agreement with traditional use, as well as some experimental results found in this work. Moreover, in silico toxic predictions showed that the A. satureioides major compounds had low probability for toxic risk. Our results indicate that A. satureioides infusion possesses low toxicological potential and an effective antioxidant activity. These findings confirm the traditional use of this plant in the folk medicine. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

In vitro transcriptomic prediction of hepatotoxicity for early drug discovery

PubMed Central

Cheng, Feng; Theodorescu, Dan; Schulman, Ira G.; Lee, Jae K.

2012-01-01

Liver toxicity (hepatotoxicity) is a critical issue in drug discovery and development. Standard preclinical evaluation of drug hepatotoxicity is generally performed using in vivo animal systems. However, only a small number of preselected compounds can be examined in vivo due to high experimental costs. A more efficient yet accurate screening technique which can identify potentially hepatotoxic compounds in the early stages of drug development would thus be valuable. Here, we develop and apply a novel genomic prediction technique for screening hepatotoxic compounds based on in vitro human liver cell tests. Using a training set of in vivo rodent experiments for drug hepatotoxicity evaluation, we discovered common biomarkers of drug-induced liver toxicity among six heterogeneous compounds. This gene set was further triaged to a subset of 32 genes that can be used as a multi-gene expression signature to predict hepatotoxicity. This multi-gene predictor was independently validated and showed consistently high prediction performance on five test sets of in vitro human liver cell and in vivo animal toxicity experiments. The predictor also demonstrated utility in evaluating different degrees of toxicity in response to drug concentrations which may be useful not only for discerning a compound’s general hepatotoxicity but also for determining its toxic concentration. PMID:21884709

Prediction of in vivo developmental toxicity by combination of Hand1-Luc embryonic stem cell test and metabolic stability test with clarification of metabolically inapplicable candidates.

PubMed

Nagahori, Hirohisa; Suzuki, Noriyuki; Le Coz, Florian; Omori, Takashi; Saito, Koichi

2016-09-30

Hand1-Luc Embryonic Stem Cell Test (Hand1-Luc EST) is a promising alternative method for evaluation of developmental toxicity. However, the problems of predictivity have remained due to appropriateness of the solubility, metabolic system, and prediction model. Therefore, we assessed the usefulness of rat liver S9 metabolic stability test using LC-MS/MS to develop new prediction model. A total of 71 chemicals were analyzed by measuring cytotoxicity and differentiation toxicity, and highly reproducible (CV=20%) results were obtained. The first prediction model was developed by discriminant analysis performed on a full dataset using Hand1-Luc EST, and 66.2% of the chemicals were correctly classified by the cross-validated classification. A second model was developed with additional descriptors obtained from the metabolic stability test to calculate hepatic availability, and an accuracy of 83.3% was obtained with applicability domain of 50.7% (=36/71) after exclusion of 22 metabolically inapplicable candidates, which potentially have a metabolic activation property. A step-wise prediction scheme with combination of Hand1-Luc EST and metabolic stability test was therefore proposed. The current results provide a promising in vitro test method for accurately predicting in vivo developmental toxicity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Assessing and predicting drug-induced anticholinergic risks: an integrated computational approach.

PubMed

Xu, Dong; Anderson, Heather D; Tao, Aoxiang; Hannah, Katia L; Linnebur, Sunny A; Valuck, Robert J; Culbertson, Vaughn L

2017-11-01

Anticholinergic (AC) adverse drug events (ADEs) are caused by inhibition of muscarinic receptors as a result of designated or off-target drug-receptor interactions. In practice, AC toxicity is assessed primarily based on clinician experience. The goal of this study was to evaluate a novel concept of integrating big pharmacological and healthcare data to assess clinical AC toxicity risks. AC toxicity scores (ATSs) were computed using drug-receptor inhibitions identified through pharmacological data screening. A longitudinal retrospective cohort study using medical claims data was performed to quantify AC clinical risks. ATS was compared with two previously reported toxicity measures. A quantitative structure-activity relationship (QSAR) model was established for rapid assessment and prediction of AC clinical risks. A total of 25 common medications, and 575,228 exposed and unexposed patients were analyzed. Our data indicated that ATS is more consistent with the trend of AC outcomes than other toxicity methods. Incorporating drug pharmacokinetic parameters to ATS yielded a QSAR model with excellent correlation to AC incident rate ( R 2 = 0.83) and predictive performance (cross validation Q 2 = 0.64). Good correlation and predictive performance ( R 2 = 0.68/ Q 2 = 0.29) were also obtained for an M2 receptor-specific QSAR model and tachycardia, an M2 receptor-specific ADE. Albeit using a small medication sample size, our pilot data demonstrated the potential and feasibility of a new computational AC toxicity scoring approach driven by underlying pharmacology and big data analytics. Follow-up work is under way to further develop the ATS scoring approach and clinical toxicity predictive model using a large number of medications and clinical parameters.

Acute Lethality of Inhaled Hydrogen Cyanide in the Laboratory Rat: Impact of Concentration x Time Profile and Evaluation of the Predictivity of Toxic Load Models

DTIC Science & Technology

2013-05-03

public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...AVAILABILITY STATEMENT Approved for public release; distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Toxic load models are mathematical...equal). The Department of Defense (DOD) (2005) publication “Potential Military Chemical/Biological Agents and Compounds” currently uses the toxic load

COMBINED AND INTERACTIVE EFFECTS OF GLOBAL CLIMATE CHANGE AND TOXICANTS ON POPULATIONS AND COMMUNITIES

PubMed Central

Moe, S Jannicke; De Schamphelaere, Karel; Clements, William H; Sorensen, Mary T; Van den Brink, Paul J; Liess, Matthias

2013-01-01

Increased temperature and other environmental effects of global climate change (GCC) have documented impacts on many species (e.g., polar bears, amphibians, coral reefs) as well as on ecosystem processes and species interactions (e.g., the timing of predator–prey interactions). A challenge for ecotoxicologists is to predict how joint effects of climatic stress and toxicants measured at the individual level (e.g., reduced survival and reproduction) will be manifested at the population level (e.g., population growth rate, extinction risk) and community level (e.g., species richness, food-web structure). The authors discuss how population- and community-level responses to toxicants under GCC are likely to be influenced by various ecological mechanisms. Stress due to GCC may reduce the potential for resistance to and recovery from toxicant exposure. Long-term toxicant exposure can result in acquired tolerance to this stressor at the population or community level, but an associated cost of tolerance may be the reduced potential for tolerance to subsequent climatic stress (or vice versa). Moreover, GCC can induce large-scale shifts in community composition, which may affect the vulnerability of communities to other stressors. Ecological modeling based on species traits (representing life-history traits, population vulnerability, sensitivity to toxicants, and sensitivity to climate change) can be a promising approach for predicting combined impacts of GCC and toxicants on populations and communities. Environ. Toxicol. Chem. 2013;32:49–61. © 2012 SETAC PMID:23147390

Evaluation of an adherent mouse embryonic stem cell in vitro assay to predict developmental toxicity of ToxCast chemicals.

EPA Science Inventory

The potential for most environmental chemicals to produce developmental toxicity is unknown. Mouse embryonic stem cell (mESC) assays are an alternative in vitro model to assess chemicals. The chemical space evaluated using mESC and compared to in vivo is limited. We used an adher...

Assessing cross species conservation of ToxCast Assay targets using Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS)

EPA Science Inventory

US EPA’s ToxCast program has screened thousands of chemicals in hundreds of mammalian-based HTS assays for biological activity suggestive of potential toxic effects. These data are being used to prioritize toxicity testing to focus on chemicals likely to lead to adverse health ef...

Utilizing high throughput screening data for predictive toxicology models: protocols and application to MLSCN assays

NASA Astrophysics Data System (ADS)

Guha, Rajarshi; Schürer, Stephan C.

2008-06-01

Computational toxicology is emerging as an encouraging alternative to experimental testing. The Molecular Libraries Screening Center Network (MLSCN) as part of the NIH Molecular Libraries Roadmap has recently started generating large and diverse screening datasets, which are publicly available in PubChem. In this report, we investigate various aspects of developing computational models to predict cell toxicity based on cell proliferation screening data generated in the MLSCN. By capturing feature-based information in those datasets, such predictive models would be useful in evaluating cell-based screening results in general (for example from reporter assays) and could be used as an aid to identify and eliminate potentially undesired compounds. Specifically we present the results of random forest ensemble models developed using different cell proliferation datasets and highlight protocols to take into account their extremely imbalanced nature. Depending on the nature of the datasets and the descriptors employed we were able to achieve percentage correct classification rates between 70% and 85% on the prediction set, though the accuracy rate dropped significantly when the models were applied to in vivo data. In this context we also compare the MLSCN cell proliferation results with animal acute toxicity data to investigate to what extent animal toxicity can be correlated and potentially predicted by proliferation results. Finally, we present a visualization technique that allows one to compare a new dataset to the training set of the models to decide whether the new dataset may be reliably predicted.

Assessment of environmental risks from toxic and nontoxic stressors; a proposed concept for a risk-based management tool for offshore drilling discharges.

PubMed

Smit, Mathijs G D; Jak, Robbert G; Rye, Henrik; Frost, Tone Karin; Singsaas, Ivar; Karman, Chris C

2008-04-01

In order to improve the ecological status of aquatic systems, both toxic (e.g., chemical) and nontoxic stressors (e.g., suspended particles) should be evaluated. This paper describes an approach to environmental risk assessment of drilling discharges to the sea. These discharges might lead to concentrations of toxic compounds and suspended clay particles in the water compartment and concentrations of toxic compounds, burial of biota, change in sediment structure, and oxygen depletion in marine sediments. The main challenges were to apply existing protocols for environmental risk assessment to nontoxic stressors and to combine risks arising from exposure to these stressors with risk from chemical exposure. The defined approach is based on species sensitivity distributions (SSDs). In addition, precautionary principles from the EU-Technical Guidance Document were incorporated to assure that the method is acceptable in a regulatory context. For all stressors a protocol was defined to construct an SSD for no observed effect concentrations (or levels; NOEC(L)-SSD) to allow for the calculation of the potentially affected fraction of species from predicted exposures. Depending on the availability of data, a NOEC-SSD for toxicants can either be directly based on available NOECs or constructed from the predicted no effect concentration and the variation in sensitivity among species. For nontoxic stressors a NOEL-SSD can be extrapolated from an SSD based on effect or field data. Potentially affected fractions of species at predicted exposures are combined into an overall risk estimate. The developed approach facilitates environmental management of drilling discharges and can be applied to define risk-mitigating measures for both toxic and nontoxic stress.

Enhancing the fathead minnow fish embryo toxicity test: Optimizing embryo production and assessing the utility of additional test endpoints.

PubMed

Roush, Kyle S; Krzykwa, Julie C; Malmquist, Jacob A; Stephens, Dane A; Sellin Jeffries, Marlo K

2018-05-30

The fathead minnow fish embryo toxicity (FET) test has been identified as a potential alternative to toxicity test methods that utilize older fish. However, several challenges have been identified with the fathead minnow FET test, including: 1) difficulties in obtaining appropriately-staged embryos for FET test initiation, 2) a paucity of data comparing fathead minnow FET test performance to the fathead minnow larval growth and survival (LGS) test and 3) a lack of sublethal endpoints that could be used to estimate chronic toxicity and/or predict adverse effects. These challenges were addressed through three study objectives. The first objective was to optimize embryo production by assessing the effect of breeding group composition (number of males and females) on egg production. Results showed that groups containing one male and four females produced the largest clutches, enhancing the likelihood of procuring sufficient numbers of embryos for FET test initiation. The second study objective was to compare the performance of the FET test to that of the fathead minnow LGS test using three reference toxicants. The FET and LGS tests were similar in their ability to predict the acute toxicity of sodium chloride and ethanol, but the FET test was found to be more sensitive than the LGS test for sodium dodecyl sulfate. The last objective of the study was to evaluate the utility and practicality of several sublethal metrics (i.e., growth, developmental abnormalities and growth- and stress-related gene expression) as FET test endpoints. Developmental abnormalities, including pericardial edema and hatch success, were found to offer the most promise as additional FET test endpoints, given their responsiveness, potential for predicting adverse effects, ease of assessment and low cost of measurement. Copyright © 2018 Elsevier Inc. All rights reserved.

Metabolic Toxicity Screening Using Electrochemiluminescence Arrays Coupled with Enzyme-DNA Biocolloid Reactors and Liquid Chromatography–Mass Spectrometry

PubMed Central

Hvastkovs, Eli G.; Schenkman, John B.; Rusling, James F.

2012-01-01

New chemicals or drugs must be guaranteed safe before they can be marketed. Despite widespread use of bioassay panels for toxicity prediction, products that are toxic to a subset of the population often are not identified until clinical trials. This article reviews new array methodologies based on enzyme/DNA films that form and identify DNA-reactive metabolites that are indicators of potentially genotoxic species. This molecularly based methodology is designed in a rapid screening array that utilizes electrochemiluminescence (ECL) to detect metabolite-DNA reactions, as well as biocolloid reactors that provide the DNA adducts and metabolites for liquid chromatography–mass spectrometry (LC-MS) analysis. ECL arrays provide rapid toxicity screening, and the biocolloid reactor LC-MS approach provides a valuable follow-up on structure, identification, and formation rates of DNA adducts for toxicity hits from the ECL array screening. Specific examples using this strategy are discussed. Integration of high-throughput versions of these toxicity-screening methods with existing drug toxicity bioassays should allow for better human toxicity prediction as well as more informed decision making regarding new chemical and drug candidates. PMID:22482786

An interspecies correlation model to predict acute dermal toxicity of plant protection products to terrestrial life stages of amphibians using fish acute toxicity and bioconcentration data.

PubMed

Weltje, Lennart; Janz, Philipp; Sowig, Peter

2017-12-01

This paper presents a model to predict acute dermal toxicity of plant protection products (PPPs) to terrestrial amphibian life stages from (regulatory) fish data. By combining existing concepts, including interspecies correlation estimation (ICE), allometric relations, lethal body burden (LBB) and bioconcentration modelling, an equation was derived that predicts the amphibian median lethal dermal dose (LD 50 ) from standard acute toxicity values (96-h LC 50 ) for fish and bioconcentration factors (BCF) in fish. Where possible, fish BCF values were corrected to 5% lipid, and to parent compound. Then, BCF values were adjusted to an exposure duration of 96 h, in case steady state took longer to be achieved. The derived correlation equation is based on 32 LD 50 values from acute dermal toxicity experiments with 15 different species of anuran amphibians, comprising 15 different PPPs. The developed ICE model can be used in a screening approach to estimate the acute risk to amphibian terrestrial life stages from dermal exposures to PPPs with organic active substances. This has the potential to reduce unnecessary testing of vertebrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

Technical basis for using passive sampling as a biomimetic extraction procedure to assess bioavailability and predict toxicity of petroleum substances.

PubMed

Redman, A D; Butler, J D; Letinski, D J; Di Toro, D M; Leon Paumen, M; Parkerton, T F

2018-05-01

Solid-phase microextraction fibers coated with polydimethylsiloxane (PDMS) provide a convenient passive sampling format to characterize bioavailability of petroleum substances. Hydrocarbons absorb onto PDMS in proportion to both freely dissolved concentrations and partitioning properties of the individual constituents, which parallels the mechanistic basis used to predict aquatic toxicity in the PETROTOX model. When deployed in a non-depletive manner, combining SPME with thermal desorption and quantification using gas chromatography-flame ionization creates a biomimetic extraction (BE) procedure that has the potential to simplify aquatic hazard assessments of petroleum substances since the total moles of all hydrocarbons sorbed to the fiber can be related to toxic thresholds in target lipid of aquatic organisms. The objective of this work is to describe the technical basis for applying BE measurements to predict toxicity of petroleum substances. Critical BE-based PDMS concentrations corresponding to adverse effects were empirically derived from toxicity tests on different petroleum substances with multiple test species. The resulting species sensitivity distribution (SSD) of PDMS effect concentrations was then compared and found consistent with the previously reported target lipid-based SSD. Further, BE data collected on samples of aqueous media dosed with a wide range of petroleum substances were highly correlated to predicted toxic units derived using the PETROTOX model. These findings provide justification for applying BE in environmental hazard and risk evaluations of petroleum substances and related mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Water toxicity assessment and spatial pollution patterns identification in a Mediterranean River Basin District. Tools for water management and risk analysis.

PubMed

Carafa, Roberta; Faggiano, Leslie; Real, Montserrat; Munné, Antoni; Ginebreda, Antoni; Guasch, Helena; Flo, Monica; Tirapu, Luís; von der Ohe, Peter Carsten

2011-09-15

In compliance with the requirements of the EU Water Framework Directive, monitoring of the ecological and chemical status of Catalan river basins (NE Spain) is carried out by the Catalan Water Agency. The large amount of data collected and the complex relationships among the environmental variables monitored often mislead data interpretation in terms of toxic impact, especially considering that even pollutants at very low concentrations might contribute to the total toxicity. The total dataset of chemical monitoring carried out between 2007 and 2008 (232 sampling stations and 60 pollutants) has been analyzed using sequential advanced modeling techniques. Data on concentrations of contaminants in water were pre-treated in order to calculate the bioavailable fraction, depending on substance properties and local environmental conditions. The resulting values were used to predict the potential impact of toxic substances in complex mixtures on aquatic biota and to identify hot spots. Exposure assessment with Species Sensitivity Distribution (SSD) and mixture toxicity rules were used to compute the multi-substances Potentially Affected Fraction (msPAF). The combined toxicity of the pollutants analyzed in the Catalan surface waters might potentially impact more than 50% of the species in 10% of the sites. In order to understand and visualize the spatial distribution of the toxic risk, Self Organising Map (SOM), based on the Kohonen's Artificial Neural Network (ANN) algorithm, was applied on the output data of these models. Principal Component Analysis (PCA) was performed on top of Neural Network results in order to identify main influential variables which account for the pollution trends. Finally, predicted toxic impacts on biota have been linked and correlated to field data on biological quality indexes using macroinvertebrate and diatom communities (IBMWP and IPS). The methodology presented could represent a suitable tool for water managers in environmental risk assessment and management. Copyright © 2011 Elsevier B.V. All rights reserved.

Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

PubMed Central

Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

2012-01-01

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

The Impact on DoD of the Toxic Substances Control Act

DTIC Science & Technology

1980-06-01

reconcile a limit of 10 ppm in the gasoline area where there is a potential for 400,000 exposures while in the rubber industry the potential is only 150,000...that the Ames test and other mutagenic tests are predictive of tumor producing potential. Many of us in toxi - cology are not impressed with this...also be completely different; so much for generic toxi - cology and for the possibility that short term testing for mutagenic effects is predictive of

Therapeutic profile of single-fraction radiosurgery of vestibular schwannoma: unrelated malignancy predicts tumor control

PubMed Central

Wowra, Berndt; Muacevic, Alexander; Fürweger, Christoph; Schichor, Christian; Tonn, Jörg-Christian

2012-01-01

Radiosurgery has become an accepted treatment option for vestibular schwannomas. Nevertheless, predictors of tumor control and treatment toxicity in current radiosurgery of vestibular schwannomas are not well understood. To generate new information on predictors of tumor control and cranial nerve toxicity of single-fraction radiosurgery of vestibular schwannomas, we conducted a single-institution long-term observational study of radiosurgery for sporadic vestibular schwannomas. Minimum follow-up was 3 years. Investigated as potential predictors of tumor control and cranial nerve toxicity were treatment technology; tumor resection preceding radiosurgery; tumor size; gender; patient age; history of cancer, vascular disease, or metabolic disease; tumor volume; radiosurgical prescription dose; and isodose line. Three hundred eighty-six patients met inclusion criteria. Treatment failure was observed in 27 patients. History of unrelated cancer (strongest predictor) and prescription dose significantly predicted tumor control. The cumulative incidence of treatment failure was 30% after 6.5 years in patients with unrelated malignancy and 10% after ≥15 years in patients without such cancer (P < .02). Tumor volume was the only predictor of trigeminal neuropathy (observed in 6 patients). No predictor of facial nerve toxicity was found. On the House and Brackmann scale, 1 patient had a permanent one-level drop and 7 a transient drop of 1 to 3 levels. Serviceable hearing was preserved in 75.1%. Tumor hearing before radiosurgery, recurrence, and prescription isodose predicted ototoxicity. Unrelated malignancy is a strong predictor of tumor control. Tumor recurrence predominantly predicts ototoxicity. These findings potentially will aid future clinical decision making in ambiguous cases. PMID:22561798

Understanding the toxicological potential of aerosol organic compounds using informatics based screening

NASA Astrophysics Data System (ADS)

Topping, David; Decesari, Stefano; Bassan, Arianna; Pavan, Manuela; Ciacci, Andrea

2016-04-01

Exposure to atmospheric particulate matter is responsible for both short-term and long-term adverse health effects. So far, all efforts spent in achieving a systematic epidemiological evidence of specific aerosol compounds determining the overall aerosol toxicity were unsuccessful. The results of the epidemiological studies apparently conflict with the laboratory toxicological analyses which have highlighted very different chemical and toxicological potentials for speciated aerosol compounds. Speciation remains a problem, especially for organic compounds: it is impossible to conduct screening on all possible molecular species. At the same time, research on toxic compounds risks to be biased towards the already known compounds, such as PAHs and dioxins. In this study we present results from an initial assessment of the use of in silico methods (i.e. (Q)SAR, read-across) to predict toxicity of atmospheric organic compounds including evaluation of applicability of a variety of popular tools (e.g. OECD QSAR Toolbox) for selected endpoints (e.g. genotoxicity). Compounds are categorised based on the need of new experimental data for the development of in silico approaches for toxicity prediction covering this specific chemical space, namely the atmospheric aerosols. Whilst only an initial investigation, we present recommendations for continuation of this work.

Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy

PubMed Central

González-Martín, M. Inmaculada; Escuredo, Olga; Revilla, Isabel; Vivar-Quintana, Ana M.; Coello, M. Carmen; Palacios Riocerezo, Carlos; Wells Moncada, Guillermo

2015-01-01

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption. PMID:26540058

PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

PubMed

Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

2015-07-05

Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

Cardiotoxicity screening: a review of rapid-throughput in vitro approaches.

PubMed

Li, Xichun; Zhang, Rui; Zhao, Bin; Lossin, Christoph; Cao, Zhengyu

2016-08-01

Cardiac toxicity represents one of the leading causes of drug failure along different stages of drug development. Multiple very successful pharmaceuticals had to be pulled from the market or labeled with strict usage warnings due to adverse cardiac effects. In order to protect clinical trial participants and patients, the International Conference on Harmonization published guidelines to recommend that all new drugs to be tested preclinically for hERG (Kv11.1) channel sensitivity before submitting for regulatory reviews. However, extensive studies have demonstrated that measurement of hERG activity has limitations due to the multiple molecular targets of drug compound through which it may mitigate or abolish a potential arrhythmia, and therefore, a model measuring multiple ion channel effects is likely to be more predictive. Several phenotypic rapid-throughput methods have been developed to predict the potential cardiac toxic compounds in the early stages of drug development using embryonic stem cells- or human induced pluripotent stem cell-derived cardiomyocytes. These rapid-throughput methods include microelectrode array-based field potential assay, impedance-based or Ca(2+) dynamics-based cardiomyocytes contractility assays. This review aims to discuss advantages and limitations of these phenotypic assays for cardiac toxicity assessment.

Use of the Biotic Ligand Model to predict metal toxicity to aquatic biota in areas of differing geology

USGS Publications Warehouse

Smith, Kathleen S.

2005-01-01

This work evaluates the use of the biotic ligand model (BLM), an aquatic toxicity model, to predict toxic effects of metals on aquatic biota in areas underlain by different rock types. The chemical composition of water, soil, and sediment is largely derived from the composition of the underlying rock. Geologic source materials control key attributes of water chemistry that affect metal toxicity to aquatic biota, including: 1) potentially toxic elements, 2) alkalinity, 3) total dissolved solids, and 4) soluble major elements, such as Ca and Mg, which contribute to water hardness. Miller (2002) compiled chemical data for water samples collected in watersheds underlain by ten different rock types, and in a mineralized area in western Colorado. He found that each rock type has a unique range of water chemistry. In this study, the ten rock types were grouped into two general categories, igneous and sedimentary. Water collected in watersheds underlain by sedimentary rock has higher mean pH, alkalinity, and calcium concentrations than water collected in watersheds underlain by igneous rock. Water collected in the mineralized area had elevated concentrations of calcium and sulfate in addition to other chemical constituents. Miller's water-chemistry data were used in the BLM (computer program) to determine copper and zinc toxicity to Daphnia magna. Modeling results show that waters from watersheds underlain by different rock types have characteristic ranges of predicted LC 50 values (a measurement of aquatic toxicity) for copper and zinc, with watersheds underlain by igneous rock having lower predicted LC 50 values than watersheds underlain by sedimentary rock. Lower predicted LC 50 values suggest that aquatic biota in watersheds underlain by igneous rock may be more vulnerable to copper and zinc inputs than aquatic biota in watersheds underlain by sedimentary rock. For both copper and zinc, there is a trend of increasing predicted LC 50 values with increasing dissolved organic carbon (DOC) concentrations. Predicted copper LC 50 values are extremely sensitive to DOC concentrations, whereas alkalinity appears to have an influence on zinc toxicity at alkalinities in excess of about 100 mg/L CaCO 3 . These findings show promise for coupling the BLM (computer program) with measured water-chemistry data to predict metal toxicity to aquatic biota in different geologic settings and under different scenarios. This approach may ultimately be a useful tool for mine-site planning, mitigation and remediation strategies, and ecological risk assessment.

Concentration addition and independent action model: Which is better in predicting the toxicity for metal mixtures on zebrafish larvae.

PubMed

Gao, Yongfei; Feng, Jianfeng; Kang, Lili; Xu, Xin; Zhu, Lin

2018-01-01

The joint toxicity of chemical mixtures has emerged as a popular topic, particularly on the additive and potential synergistic actions of environmental mixtures. We investigated the 24h toxicity of Cu-Zn, Cu-Cd, and Cu-Pb and 96h toxicity of Cd-Pb binary mixtures on the survival of zebrafish larvae. Joint toxicity was predicted and compared using the concentration addition (CA) and independent action (IA) models with different assumptions in the toxic action mode in toxicodynamic processes through single and binary metal mixture tests. Results showed that the CA and IA models presented varying predictive abilities for different metal combinations. For the Cu-Cd and Cd-Pb mixtures, the CA model simulated the observed survival rates better than the IA model. By contrast, the IA model simulated the observed survival rates better than the CA model for the Cu-Zn and Cu-Pb mixtures. These findings revealed that the toxic action mode may depend on the combinations and concentrations of tested metal mixtures. Statistical analysis of the antagonistic or synergistic interactions indicated that synergistic interactions were observed for the Cu-Cd and Cu-Pb mixtures, non-interactions were observed for the Cd-Pb mixtures, and slight antagonistic interactions for the Cu-Zn mixtures. These results illustrated that the CA and IA models are consistent in specifying the interaction patterns of binary metal mixtures. Copyright © 2017 Elsevier B.V. All rights reserved.

Using biotic ligand models to predict metal toxicity in mineralized systems

USGS Publications Warehouse

Smith, Kathleen S.; Balistrieri, Laurie S.; Todd, Andrew S.

2015-01-01

The biotic ligand model (BLM) is a numerical approach that couples chemical speciation calculations with toxicological information to predict the toxicity of aquatic metals. This approach was proposed as an alternative to expensive toxicological testing, and the U.S. Environmental Protection Agency incorporated the BLM into the 2007 revised aquatic life ambient freshwater quality criteria for Cu. Research BLMs for Ag, Ni, Pb, and Zn are also available, and many other BLMs are under development. Current BLMs are limited to ‘one metal, one organism’ considerations. Although the BLM generally is an improvement over previous approaches to determining water quality criteria, there are several challenges in implementing the BLM, particularly at mined and mineralized sites. These challenges include: (1) historically incomplete datasets for BLM input parameters, especially dissolved organic carbon (DOC), (2) several concerns about DOC, such as DOC fractionation in Fe- and Al-rich systems and differences in DOC quality that result in variations in metal-binding affinities, (3) water-quality parameters and resulting metal-toxicity predictions that are temporally and spatially dependent, (4) additional influences on metal bioavailability, such as multiple metal toxicity, dietary metal toxicity, and competition among organisms or metals, (5) potential importance of metal interactions with solid or gas phases and/or kinetically controlled reactions, and (6) tolerance to metal toxicity observed for aquatic organisms living in areas with elevated metal concentrations.

Fish acute toxicity syndromes and their use in the QSAR approach to hazard assessment.

PubMed Central

McKim, J M; Bradbury, S P; Niemi, G J

1987-01-01

Implementation of the Toxic Substances Control Act of 1977 creates the need to reliably establish testing priorities because laboratory resources are limited and the number of industrial chemicals requiring evaluation is overwhelming. The use of quantitative structure activity relationship (QSAR) models as rapid and predictive screening tools to select more potentially hazardous chemicals for in-depth laboratory evaluation has been proposed. Further implementation and refinement of quantitative structure-toxicity relationships in aquatic toxicology and hazard assessment requires the development of a "mode-of-action" database. With such a database, a qualitative structure-activity relationship can be formulated to assign the proper mode of action, and respective QSAR, to a given chemical structure. In this review, the development of fish acute toxicity syndromes (FATS), which are toxic-response sets based on various behavioral and physiological-biochemical measurements, and their projected use in the mode-of-action database are outlined. Using behavioral parameters monitored in the fathead minnow during acute toxicity testing, FATS associated with acetylcholinesterase (AChE) inhibitors and narcotics could be reliably predicted. However, compounds classified as oxidative phosphorylation uncouplers or stimulants could not be resolved. Refinement of this approach by using respiratory-cardiovascular responses in the rainbow trout, enabled FATS associated with AChE inhibitors, convulsants, narcotics, respiratory blockers, respiratory membrane irritants, and uncouplers to be correctly predicted. PMID:3297660

Estimating aquatic toxicity as determined through laboratory tests of great lakes sediments containing complex mixtures of environmental contaminants

USGS Publications Warehouse

1996-01-01

We developed and evaluated a total toxic units modeling approach for predicting mean toxicity as measured in laboratory tests for Great Lakes sediments containing complex mixtures of environmental contaminants (e.g., polychlorinated biphenyls, polycyclic aromatic hydrocarbons, pesticides, chlorinated dioxins, and metals). The approach incorporates equilibrium partitioning and organic carbon control of bioavailability for organic contaminants and acid volatile sulfide (AVS) control for metals, and includes toxic equivalency for planar organic chemicals. A toxic unit is defined as the ratio of the estimated pore-water concentration of a contaminant to the chronic toxicity of that contaminant, as estimated by U.S. Environmental Protection Agency Ambient Water Quality Criteria (AWQC). The toxic unit models we developed assume complete additivity of contaminant effects, are completely mechanistic in form, and were evaluated without any a posteriori modification of either the models or the data from which the models were developed and against which they were tested. A linear relationship between total toxic units, which included toxicity attributable to both iron and un-ionized ammonia, accounted for about 88% of observed variability in mean toxicity; a quadratic relationship accounted for almost 94%. Exclusion of either bioavailability components (i.e., equilibrium partitioning control of organic contaminants and AVS control of metals) or iron from the model substantially decreased its ability to predict mean toxicity. A model based solely on un-ionized ammonia accounted for about 47% of the variability in mean toxicity. We found the toxic unit approach to be a viable method for assessing and ranking the relative potential toxicity of contaminated sediments.

Application of the Activity Framework for Assessing Aquatic Ecotoxicology Data for Organic Chemicals.

PubMed

Thomas, Paul; Dawick, James; Lampi, Mark; Lemaire, Philippe; Presow, Shaun; van Egmond, Roger; Arnot, Jon A; Mackay, Donald; Mayer, Philipp; Galay Burgos, Malyka

2015-10-20

Toxicological research in the 1930s gave the first indications of the link between narcotic toxicity and the chemical activity of organic chemicals. More recently, chemical activity has been proposed as a novel exposure parameter that describes the fraction of saturation and that quantifies the potential for partitioning and diffusive uptake. In the present study, more than 2000 acute and chronic algal, aquatic invertebrates and fish toxicity data, as well as water solubility and melting point values, were collected from a series of sources. The data were critically reviewed and grouped by mode of action (MoA). We considered 660 toxicity data to be of acceptable quality. The 328 data which applied to the 72 substances identified as MoA 1 were then evaluated within the activity-toxicity framework: EC50 and LC50 values for all three taxa correlated generally well with (subcooled) liquid solubilities. Acute toxicity was typically exerted within the chemical activity range of 0.01-0.1, whereas chronic toxicity was exerted in the range of 0.001-0.01. These results confirm that chemical activity has the potential to contribute to the determination, interpretation and prediction of toxicity to aquatic organisms. It also has the potential to enhance regulation of organic chemicals by linking results from laboratory tests, monitoring and modeling programs. The framework can provide an additional line of evidence for assessing aquatic toxicity, for improving the design of toxicity tests, reducing animal usage and addressing chemical mixtures.

Evaluation of the ToxCast Suite of Cellular and Molecular Assays for Prediction of In Vivo Toxicity

EPA Science Inventory

Measurement of perturbation of critical signaling pathways and cellular processes using in vitro assays provides a means to predict the potential for chemicals to cause injury in the intact animal. To explore the utility of such an approach, a diverse collection of human in vitro...

VirtualToxLab — A platform for estimating the toxic potential of drugs, chemicals and natural products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedani, Angelo, E-mail: angelo.vedani@unibas.ch; Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel; Dobler, Max

The VirtualToxLab is an in silico technology for estimating the toxic potential (endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity) of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of proteins, known or suspected to trigger adverse effects. The toxic potential, a non-linear function ranging from 0.0 (none) to 1.0 (extreme), is derived from the individual binding affinities of a compound towards currently 16 target proteins: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptormore » γ, progesterone, thyroid α, and thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, and 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The interface to the technology allows building and uploading molecular structures, viewing and downloading results and, most importantly, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. The VirtualToxLab has been used to predict the toxic potential for over 2500 compounds: the results are posted on (http://www.virtualtoxlab.org). The free platform — the OpenVirtualToxLab — is accessible (in client–server mode) over the Internet. It is free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. -- Highlights: ► In silico technology for estimating the toxic potential of drugs and chemicals. ► Simulation of binding towards 16 proteins suspected to trigger adverse effects. ► Mechanistic interpretation and real-time 3D visualization. ► Accessible over the Internet. ► Free of charge for universities, governmental agencies, regulatory bodies and NPOs.« less

Proteomic Signatures of the Zebrafish (Danio rerio) Embryo: Sensitivity and Specificity in Toxicity Assessment of Chemicals.

PubMed

Hanisch, Karen; Küster, Eberhard; Altenburger, Rolf; Gündel, Ulrike

2010-01-01

Studies using embryos of the zebrafish Danio rerio (DarT) instead of adult fish for characterising the (eco-) toxic potential of chemicals have been proposed as animal replacing methods. Effect analysis at the molecular level might enhance sensitivity, specificity, and predictive value of the embryonal studies. The present paper aimed to test the potential of toxicoproteomics with zebrafish eleutheroembryos for sensitive and specific toxicity assessment. 2-DE-based toxicoproteomics was performed applying low-dose (EC(10)) exposure for 48 h with three-model substances Rotenone, 4,6-dinitro-o-cresol (DNOC) and Diclofenac. By multivariate "pattern-only" PCA and univariate statistical analyses, alterations in the embryonal proteome were detectable in nonetheless visibly intact organisms and treatment with the three substances was distinguishable at the molecular level. Toxicoproteomics enabled the enhancement of sensitivity and specificity of the embryonal toxicity assay and bear the potency to identify protein markers serving as general stress markers and early diagnosis of toxic stress.

Proteomic Signatures of the Zebrafish (Danio rerio) Embryo: Sensitivity and Specificity in Toxicity Assessment of Chemicals

PubMed Central

Hanisch, Karen; Küster, Eberhard; Altenburger, Rolf; Gündel, Ulrike

2010-01-01

Studies using embryos of the zebrafish Danio rerio (DarT) instead of adult fish for characterising the (eco-) toxic potential of chemicals have been proposed as animal replacing methods. Effect analysis at the molecular level might enhance sensitivity, specificity, and predictive value of the embryonal studies. The present paper aimed to test the potential of toxicoproteomics with zebrafish eleutheroembryos for sensitive and specific toxicity assessment. 2-DE-based toxicoproteomics was performed applying low-dose (EC10) exposure for 48 h with three-model substances Rotenone, 4,6-dinitro-o-cresol (DNOC) and Diclofenac. By multivariate “pattern-only” PCA and univariate statistical analyses, alterations in the embryonal proteome were detectable in nonetheless visibly intact organisms and treatment with the three substances was distinguishable at the molecular level. Toxicoproteomics enabled the enhancement of sensitivity and specificity of the embryonal toxicity assay and bear the potency to identify protein markers serving as general stress markers and early diagnosis of toxic stress. PMID:22084678

Structure-activity relationships for skin sensitization: recent improvements to Derek for Windows.

PubMed

Langton, Kate; Patlewicz, Grace Y; Long, Anthony; Marchant, Carol A; Basketter, David A

2006-12-01

Derek for Windows (DfW) is a knowledge-based expert system that predicts the toxicity of a chemical from its structure. Its predictions are based in part on alerts that describe structural features or toxicophores associated with toxicity. Recently, improvements have been made to skin sensitization alerts within the DfW knowledge base in collaboration with Unilever. These include modifications to the alerts describing the skin sensitization potential of aldehydes, 1,2-diketones, and isothiazolinones and consist of enhancements to the toxicophore definition, the mechanistic classification, and the extent of supporting evidence provided. The outcomes from this collaboration demonstrate the importance of updating and refining computer models for the prediction of skin sensitization as new information from experimental and theoretical studies becomes available.

CADRE-SS, an in Silico Tool for Predicting Skin Sensitization Potential Based on Modeling of Molecular Interactions.

PubMed

Kostal, Jakub; Voutchkova-Kostal, Adelina

2016-01-19

Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

A Market-Basket Approach to Predict the Acute Aquatic Toxicity of Munitions and Energetic Materials.

PubMed

Burgoon, Lyle D

2016-06-01

An ongoing challenge in chemical production, including the production of insensitive munitions and energetics, is the ability to make predictions about potential environmental hazards early in the process. To address this challenge, a quantitative structure activity relationship model was developed to predict acute fathead minnow toxicity of insensitive munitions and energetic materials. Computational predictive toxicology models like this one may be used to identify and prioritize environmentally safer materials early in their development. The developed model is based on the Apriori market-basket/frequent itemset mining approach to identify probabilistic prediction rules using chemical atom-pairs and the lethality data for 57 compounds from a fathead minnow acute toxicity assay. Lethality data were discretized into four categories based on the Globally Harmonized System of Classification and Labelling of Chemicals. Apriori identified toxicophores for categories two and three. The model classified 32 of the 57 compounds correctly, with a fivefold cross-validation classification rate of 74 %. A structure-based surrogate approach classified the remaining 25 chemicals correctly at 48 %. This result is unsurprising as these 25 chemicals were fairly unique within the larger set.

Analysis of ToxCast data for food-relevant compounds by ...

EPA Pesticide Factsheets

The ToxCast program has generated a wealth of in vitro high throughput screening data, and best approaches for the interpretation and use of these data remain undetermined. We present case studies comparing the ToxCast and in vivo toxicity data for two food contact substances using the RISK21 approach. Available exposure data, toxicity data, and model predictions were analyzed for sodium pyrithione and dibutyltin dichloride. In-vitro to in-vivo extrapolation (IVIVE) was performed to determine oral equivalent doses (OEDs) for the ToxCast data bioactivity. For sodium pyrithione, calculated OEDs corresponded to doses that demonstrated toxicity in animal studies. For dibutyltin dichloride, calculated OEDs were below the doses that demonstrated toxicity in animals, but this was confounded by the conservative estimates used in the IVIVE calculations. These studies highlight the potential of the ToxCast approach while also indicating areas where additional data or predictive tools are needed. We present case studies comparing the ToxCast and in vivo toxicity data for two food contact substances using the RISK21 approach.

Guidance on health effects of toxic chemicals. Safety Analysis Report Update Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foust, C.B.; Griffin, G.D.; Munro, N.B.

1994-02-01

Martin Marietta Energy Systems, Inc. (MMES), and Martin Marietta Utility Services, Inc. (MMUS), are engaged in phased programs to update the safety documentation for the existing US Department of Energy (DOE)-owned facilities. The safety analysis of potential toxic hazards requires a methodology for evaluating human health effects of predicted toxic exposures. This report provides a consistent set of health effects and documents toxicity estimates corresponding to these health effects for some of the more important chemicals found within MMES and MMUS. The estimates are based on published toxicity information and apply to acute exposures for an ``average`` individual. The healthmore » effects (toxicological endpoints) used in this report are (1) the detection threshold; (2) the no-observed adverse effect level; (3) the onset of irritation/reversible effects; (4) the onset of irreversible effects; and (5) a lethal exposure, defined to be the 50% lethal level. An irreversible effect is defined as a significant effect on a person`s quality of life, e.g., serious injury. Predicted consequences are evaluated on the basis of concentration and exposure time.« less

The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation.

PubMed

Al Sharif, Merilin; Tsakovska, Ivanka; Pajeva, Ilza; Alov, Petko; Fioravanzo, Elena; Bassan, Arianna; Kovarich, Simona; Yang, Chihae; Mostrag-Szlichtyng, Aleksandra; Vitcheva, Vessela; Worth, Andrew P; Richarz, Andrea-N; Cronin, Mark T D

2017-12-01

The aim of this paper was to provide a proof of concept demonstrating that molecular modelling methodologies can be employed as a part of an integrated strategy to support toxicity prediction consistent with the mode of action/adverse outcome pathway (MoA/AOP) framework. To illustrate the role of molecular modelling in predictive toxicology, a case study was undertaken in which molecular modelling methodologies were employed to predict the activation of the peroxisome proliferator-activated nuclear receptor γ (PPARγ) as a potential molecular initiating event (MIE) for liver steatosis. A stepwise procedure combining different in silico approaches (virtual screening based on docking and pharmacophore filtering, and molecular field analysis) was developed to screen for PPARγ full agonists and to predict their transactivation activity (EC 50 ). The performance metrics of the classification model to predict PPARγ full agonists were balanced accuracy=81%, sensitivity=85% and specificity=76%. The 3D QSAR model developed to predict EC 50 of PPARγ full agonists had the following statistical parameters: q 2 cv =0.610, N opt =7, SEP cv =0.505, r 2 pr =0.552. To support the linkage of PPARγ agonism predictions to prosteatotic potential, molecular modelling was combined with independently performed mechanistic mining of available in vivo toxicity data followed by ToxPrint chemotypes analysis. The approaches investigated demonstrated a potential to predict the MIE, to facilitate the process of MoA/AOP elaboration, to increase the scientific confidence in AOP, and to become a basis for 3D chemotype development. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Functional Coupling of Human Microphysiology Systems: Intestine, Liver, Kidney Proximal Tubule, Blood-Brain Barrier and Skeletal Muscle

PubMed Central

Vernetti, Lawrence; Gough, Albert; Baetz, Nicholas; Blutt, Sarah; Broughman, James R.; Brown, Jacquelyn A.; Foulke-Abel, Jennifer; Hasan, Nesrin; In, Julie; Kelly, Edward; Kovbasnjuk, Olga; Repper, Jonathan; Senutovitch, Nina; Stabb, Janet; Yeung, Catherine; Zachos, Nick C.; Donowitz, Mark; Estes, Mary; Himmelfarb, Jonathan; Truskey, George; Wikswo, John P.; Taylor, D. Lansing

2017-01-01

Organ interactions resulting from drug, metabolite or xenobiotic transport between organs are key components of human metabolism that impact therapeutic action and toxic side effects. Preclinical animal testing often fails to predict adverse outcomes arising from sequential, multi-organ metabolism of drugs and xenobiotics. Human microphysiological systems (MPS) can model these interactions and are predicted to dramatically improve the efficiency of the drug development process. In this study, five human MPS models were evaluated for functional coupling, defined as the determination of organ interactions via an in vivo-like sequential, organ-to-organ transfer of media. MPS models representing the major absorption, metabolism and clearance organs (the jejunum, liver and kidney) were evaluated, along with skeletal muscle and neurovascular models. Three compounds were evaluated for organ-specific processing: terfenadine for pharmacokinetics (PK) and toxicity; trimethylamine (TMA) as a potentially toxic microbiome metabolite; and vitamin D3. We show that the organ-specific processing of these compounds was consistent with clinical data, and discovered that trimethylamine-N-oxide (TMAO) crosses the blood-brain barrier. These studies demonstrate the potential of human MPS for multi-organ toxicity and absorption, distribution, metabolism and excretion (ADME), provide guidance for physically coupling MPS, and offer an approach to coupling MPS with distinct media and perfusion requirements. PMID:28176881

Probing nanomechanical interaction at the interface between biological membrane and potentially toxic chemical.

PubMed

Lim, Chanoong; Park, Sohee; Park, Jinwoo; Ko, Jina; Lee, Dong Woog; Hwang, Dong Soo

2018-04-12

Various xenobiotics interact with biological membranes, and precise evaluations of the molecular interactions between them are essential to foresee the toxicity and bioavailability of existing or newly synthesized molecules. In this study, surface forces apparatus (SFA) measurement and Langmuir trough based tensiometry are performed to reveal nanomechanical interaction mechanisms between potential toxicants and biological membranes for ex vivo toxicity evaluation. As a toxicant, polyhexamethylene guanidine (PHMG) was selected because PHMG containing humidifier disinfectant and Vodka caused lots of victims in both S. Korea and Russia, respectively, due to the lack of holistic toxicity evaluation of PHMG. Here, we measured strong attraction (Wad ∼4.2 mJ/m 2 ) between PHMG and head group of biological membranes while no detectable adhesion force between the head group and control molecules was measured. Moreover, significant changes in π-A isotherm of 1,2-Dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) monolayers were measured upon PHMG adsorption. These results indicate PHMG strongly binds to hydrophilic group of lipid membranes and alters the structural and phase behavior of them. More importantly, complementary utilization of SFA and Langmuir trough techniques are found to be useful to predict the potential toxicity of a chemical by evaluating the molecular interaction with biological membranes, the primary protective barrier for living organisms. Copyright © 2018 Elsevier B.V. All rights reserved.

A Predictive Model for Toxicity Effects Assessment of Biotransformed Hepatic Drugs Using Iterative Sampling Method.

PubMed

Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

2016-12-09

Measuring toxicity is one of the main steps in drug development. Hence, there is a high demand for computational models to predict the toxicity effects of the potential drugs. In this study, we used a dataset, which consists of four toxicity effects:mutagenic, tumorigenic, irritant and reproductive effects. The proposed model consists of three phases. In the first phase, rough set-based methods are used to select the most discriminative features for reducing the classification time and improving the classification performance. Due to the imbalanced class distribution, in the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique are used to solve the problem of imbalanced datasets. ITerative Sampling (ITS) method is proposed to avoid the limitations of those methods. ITS method has two steps. The first step (sampling step) iteratively modifies the prior distribution of the minority and majority classes. In the second step, a data cleaning method is used to remove the overlapping that is produced from the first step. In the third phase, Bagging classifier is used to classify an unknown drug into toxic or non-toxic. The experimental results proved that the proposed model performed well in classifying the unknown samples according to all toxic effects in the imbalanced datasets.

Screening for angiogenic inhibitors in zebrafish to evaluate a predictive model for developmental vascular toxicity.

PubMed

Tal, Tamara; Kilty, Claire; Smith, Andrew; LaLone, Carlie; Kennedy, Brendán; Tennant, Alan; McCollum, Catherine W; Bondesson, Maria; Knudsen, Thomas; Padilla, Stephanie; Kleinstreuer, Nicole

2017-06-01

Chemically-induced vascular toxicity during embryonic development may cause a wide range of adverse effects. To identify putative vascular disrupting chemicals (pVDCs), a predictive pVDC signature was constructed from 124 U.S. EPA ToxCast high-throughput screening (HTS) assays and used to rank 1060 chemicals for their potential to disrupt vascular development. Thirty-seven compounds were selected for targeted testing in transgenic Tg(kdrl:EGFP) and Tg(fli1:EGFP) zebrafish embryos to identify chemicals that impair developmental angiogenesis. We hypothesized that zebrafish angiogenesis toxicity data would correlate with human cell-based and cell-free in vitro HTS ToxCast data. Univariate statistical associations used to filter HTS data based on correlations with zebrafish angiogenic inhibition in vivo revealed 132 total significant associations, 33 of which were already captured in the pVDC signature, and 689 non-significant assay associations. Correlated assays were enriched in cytokine and extracellular matrix pathways. Taken together, the findings indicate the utility of zebrafish assays to evaluate an HTS-based predictive toxicity signature and also provide an experimental basis for expansion of the pVDC signature with novel HTS assays. Published by Elsevier Inc.

Humanizing the zebrafish liver shifts drug metabolic profiles and improves pharmacokinetics of CYP3A4 substrates.

PubMed

Poon, Kar Lai; Wang, Xingang; Ng, Ashley S; Goh, Wei Huang; McGinnis, Claudia; Fowler, Stephen; Carney, Tom J; Wang, Haishan; Ingham, Phillip W

2017-03-01

Understanding and predicting whether new drug candidates will be safe in the clinic is a critical hurdle in pharmaceutical development, that relies in part on absorption, distribution, metabolism, excretion and toxicology studies in vivo. Zebrafish is a relatively new model system for drug metabolism and toxicity studies, offering whole organism screening coupled with small size and potential for high-throughput screening. Through toxicity and absorption analyses of a number of drugs, we find that zebrafish is generally predictive of drug toxicity, although assay outcomes are influenced by drug lipophilicity which alters drug uptake. In addition, liver microsome assays reveal specific differences in metabolism of compounds between human and zebrafish livers, likely resulting from the divergence of the cytochrome P450 superfamily between species. To reflect human metabolism more accurately, we generated a transgenic "humanized" zebrafish line that expresses the major human phase I detoxifying enzyme, CYP3A4, in the liver. Here, we show that this humanized line shows an elevated metabolism of CYP3A4-specific substrates compared to wild-type zebrafish. The generation of this first described humanized zebrafish liver suggests such approaches can enhance the accuracy of the zebrafish model for toxicity prediction.

Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases

PubMed Central

Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun

2016-01-01

Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery. PMID:26959013

Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases.

PubMed

Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun

2016-03-04

Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery.

Predictive Models and Computational Toxicology

EPA Science Inventory

Understanding the potential health risks posed by environmental chemicals is a significant challenge elevated by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicology research program was l...

The use of high-throughput screening techniques to evaluate mitochondrial toxicity.

PubMed

Wills, Lauren P

2017-11-01

Toxicologists and chemical regulators depend on accurate and effective methods to evaluate and predict the toxicity of thousands of current and future compounds. Robust high-throughput screening (HTS) experiments have the potential to efficiently test large numbers of chemical compounds for effects on biological pathways. HTS assays can be utilized to examine chemical toxicity across multiple mechanisms of action, experimental models, concentrations, and lengths of exposure. Many agricultural, industrial, and pharmaceutical chemicals classified as harmful to human and environmental health exert their effects through the mechanism of mitochondrial toxicity. Mitochondrial toxicants are compounds that cause a decrease in the number of mitochondria within a cell, and/or decrease the ability of mitochondria to perform normal functions including producing adenosine triphosphate (ATP) and maintaining cellular homeostasis. Mitochondrial dysfunction can lead to apoptosis, necrosis, altered metabolism, muscle weakness, neurodegeneration, decreased organ function, and eventually disease or death of the whole organism. The development of HTS techniques to identify mitochondrial toxicants will provide extensive databases with essential connections between mechanistic mitochondrial toxicity and chemical structure. Computational and bioinformatics approaches can be used to evaluate compound databases for specific chemical structures associated with toxicity, with the goal of developing quantitative structure-activity relationship (QSAR) models and mitochondrial toxicophores. Ultimately these predictive models will facilitate the identification of mitochondrial liabilities in consumer products, industrial compounds, pharmaceuticals and environmental hazards. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Toxicity prediction of ionic liquids based on Daphnia magna by using density functional theory

NASA Astrophysics Data System (ADS)

Nu’aim, M. N.; Bustam, M. A.

2018-04-01

By using a model called density functional theory, the toxicity of ionic liquids can be predicted and forecast. It is a theory that allowing the researcher to have a substantial tool for computation of the quantum state of atoms, molecules and solids, and molecular dynamics which also known as computer simulation method. It can be done by using structural feature based quantum chemical reactivity descriptor. The identification of ionic liquids and its Log[EC50] data are from literature data that available in Ismail Hossain thesis entitled “Synthesis, Characterization and Quantitative Structure Toxicity Relationship of Imidazolium, Pyridinium and Ammonium Based Ionic Liquids”. Each cation and anion of the ionic liquids were optimized and calculated. The geometry optimization and calculation from the software, produce the value of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). From the value of HOMO and LUMO, the value for other toxicity descriptors were obtained according to their formulas. The toxicity descriptor that involves are electrophilicity index, HOMO, LUMO, energy gap, chemical potential, hardness and electronegativity. The interrelation between the descriptors are being determined by using a multiple linear regression (MLR). From this MLR, all descriptors being analyzed and the descriptors that are significant were chosen. In order to develop the finest model equation for toxicity prediction of ionic liquids, the selected descriptors that are significant were used. The validation of model equation was performed with the Log[EC50] data from the literature and the final model equation was developed. A bigger range of ionic liquids which nearly 108 of ionic liquids can be predicted from this model equation.

Using a holistic approach to assess the impact of engineered nanomaterials inducing toxicity in aquatic systems.

PubMed

He, Xiaojia; Aker, Winfred G; Leszczynski, Jerzy; Hwang, Huey-Min

2014-03-01

In this report, we critically reviewed selected intrinsic physicochemical properties of engineered nanomaterials (ENMs) and their role in the interaction of the ENMs with the immediate surroundings in representative aquatic environments. The behavior of ENMs with respect to dynamic microenvironments at the nano-bio-eco interface level, and the resulting impact on their toxicity, fate, and exposure potential are elaborated. Based on this literature review, we conclude that a holistic approach is urgently needed to fulfill our knowledge gap regarding the safety of discharged ENMs. This comparative approach affords the capability to recognize and understand the potential hazards of ENMs and their toxicity mechanisms, and ultimately to establish a quantitative and reliable system to predict such outcomes. Copyright © 2014. Published by Elsevier B.V.

DSSTOX (DISTRIBUTED STRUCTURE-SEARCHABLE ...

EPA Pesticide Factsheets

Distributed Structure-Searchable Toxicity Database Network Major trends affecting public toxicity information resources have the potential to significantly alter the future of predictive toxicology. Chemical toxicity screening is undergoing shifts towards greater use of more fundamental information on gene/protein expression patterns and bioactivity and bioassay profiles, the latter generated with highthroughput screening technologies. Curated, systematically organized, and webaccessible toxicity and biological activity data in association with chemical structures, enabling the integration of diverse data information domains, will fuel the next frontier of advancement for QSAR (quantitative structure-activity relationship) and data mining technologies. The DSSTox project is supporting progress towards these goals on many fronts, promoting the use of formalized and structure-annotated toxicity data models, helping to interface these efforts with QSAR modelers, linking data from diverse sources, and creating a large, quality reviewed, central chemical structure information resource linked to various toxicity data sources

Inroads to predict in vivo toxicology-an introduction to the eTOX Project.

PubMed

Briggs, Katharine; Cases, Montserrat; Heard, David J; Pastor, Manuel; Pognan, François; Sanz, Ferran; Schwab, Christof H; Steger-Hartmann, Thomas; Sutter, Andreas; Watson, David K; Wichard, Jörg D

2012-01-01

There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison ("read-across"), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX ("electronic toxicity") consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of in silico prediction systems for organ and in vivo toxicity. The backbone of the project will be a database consisting of preclinical toxicity data for drug compounds or candidates extracted from previously unpublished, legacy reports from thirteen European and European operation-based pharmaceutical companies. The database will be enhanced by incorporation of publically available, high quality toxicology data. Seven academic institutes and five small-to-medium size enterprises (SMEs) contribute with their expertise in data gathering, database curation, data mining, chemoinformatics and predictive systems development. The outcome of the project will be a predictive system contributing to early potential hazard identification and risk assessment during the drug development process. The concept and strategy of the eTOX project is described here, together with current achievements and future deliverables.

Probability Based hERG Blocker Classifiers.

PubMed

Wang, Zhi; Mussa, Hamse Y; Lowe, Robert; Glen, Robert C; Yan, Aixia

2012-09-01

The US Food and Drug Administration (FDA) require in vitro human ether-a-go-go related (hERG) ion channel affinity tests for all drug candidates prior to clinical trials. In this study, probabilistic-based methods were employed to develop prediction models on hERG inhibition prediction, which are different from traditional QSAR models that are mainly based on supervised 'hard point' (HP) classification approaches giving 'yes/no' answers. The obtained models can 'ascertain' whether or not a given set of compounds can block hERG ion channels. The results presented indicate that the proposed probabilistic-based method can be a valuable tool for ranking compounds with respect to their potential cardio-toxicity and will be promising for other toxic property predictions. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Draft Genome Sequence of the Entomopathogenic Bacterium Bacillus pumilus 15.1, a Strain Highly Toxic to the Mediterranean Fruit Fly Ceratitis capitata

PubMed Central

García-Ramón, Diana C.; Palma, Leopoldo; Berry, Colin; Osuna, Antonio

2015-01-01

We present the draft whole-genome sequence of the entomopathogenic Bacillus pumilus 15.1 strain that consists of 3,795,691 bp and 3,776 predicted protein-coding genes. This genome sequence provides the basis for understanding the potential mechanism behind the toxicity and virulence of B. pumilus 15.1 against the Mediterranean fruit fly. PMID:26404596

Acute embryo toxicity and teratogenicity of three potential biofuels also used as flavor or solvent.

PubMed

Bluhm, Kerstin; Seiler, Thomas-Benjamin; Anders, Nico; Klankermayer, Jürgen; Schaeffer, Andreas; Hollert, Henner

2016-10-01

The demand for biofuels increases due to concerns regarding greenhouse gas emissions and depletion of fossil oil reserves. Many substances identified as potential biofuels are solvents or already used as flavors or fragrances. Although humans and the environment may be readily exposed little is known regarding their (eco)toxicological effects. In this study, the three potential biofuels ethyl levulinate (EL), 2-methyltetrahydrofuran (2-MTHF) and 2-methylfuran (2-MF) were investigated for their acute embryo toxicity and teratogenicity using the fish embryo toxicity (FET) test to identify unknown hazard potentials and to allow focusing further research on substances with low toxic potentials. In addition, two fossil fuels (diesel and gasoline) and an established biofuel (rapeseed oil methyl ester) were investigated as references. The FET test is widely accepted and used in (eco)toxicology. It was performed using the zebrafish Danio rerio, a model organism useful for the prediction of human teratogenicity. Testing revealed a higher acute toxicity for EL (LC50: 83mg/L) compared to 2-MTHF (LC50: 2980mg/L), 2-MF (LC50: 405mg/L) and water accommodated fractions of the reference fuels including gasoline (LC50: 244mg DOC/L). In addition, EL caused a statistically significant effect on head development resulting in elevated head lengths in zebrafish embryos. Results for EL reduce its likelihood of use as a biofuel since other substances with a lower toxic potential are available. The FET test applied at an early stage of development might be a useful tool to avoid further time and money requiring steps regarding research on unfavorable biofuels. Copyright © 2016 Elsevier B.V. All rights reserved.

A hypothetical model for predicting the toxicity of high aspect ratio nanoparticles (HARN)

NASA Astrophysics Data System (ADS)

Tran, C. L.; Tantra, R.; Donaldson, K.; Stone, V.; Hankin, S. M.; Ross, B.; Aitken, R. J.; Jones, A. D.

2011-12-01

The ability to predict nanoparticle (dimensional structures which are less than 100 nm in size) toxicity through the use of a suitable model is an important goal if nanoparticles are to be regulated in terms of exposures and toxicological effects. Recently, a model to predict toxicity of nanoparticles with high aspect ratio has been put forward by a consortium of scientists. The High aspect ratio nanoparticles (HARN) model is a platform that relates the physical dimensions of HARN (specifically length and diameter ratio) and biopersistence to their toxicity in biological environments. Potentially, this model is of great public health and economic importance, as it can be used as a tool to not only predict toxicological activity but can be used to classify the toxicity of various fibrous nanoparticles, without the need to carry out time-consuming and expensive toxicology studies. However, this model of toxicity is currently hypothetical in nature and is based solely on drawing similarities in its dimensional geometry with that of asbestos and synthetic vitreous fibres. The aim of this review is two-fold: (a) to present findings from past literature, on the physicochemical property and pathogenicity bioassay testing of HARN (b) to identify some of the challenges and future research steps crucial before the HARN model can be accepted as a predictive model. By presenting what has been done, we are able to identify scientific challenges and research directions that are needed for the HARN model to gain public acceptance. Our recommendations for future research includes the need to: (a) accurately link physicochemical data with corresponding pathogenicity assay data, through the use of suitable reference standards and standardised protocols, (b) develop better tools/techniques for physicochemical characterisation, (c) to develop better ways of monitoring HARN in the workplace, (d) to reliably measure dose exposure levels, in order to support future epidemiological studies.

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Developmental and Reproductive Toxicity (DART) testing is important for assessing the potential consequences of drug and chemical exposure on human health and well-being. Complexity of pregnancy and the reproductive cycle makes DART testing challenging and costly for traditional (animal-based) methods. A compendium of in vitro data from ToxCast/Tox21 high-throughput screening (HTS) programs is available for predictive toxicology. ‘Predictive DART’ will require an integrative strategy that mobilizes HTS data into in silico models that capture the relevant embryology. This lecture addresses progress on EPA's 'virtual embryo'. The question of how tissues and organs are shaped during development is crucial for understanding (and predicting) human birth defects. While ToxCast HTS data may predict developmental toxicity with reasonable accuracy, mechanistic models are still necessary to capture the relevant biology. Subtle microscopic changes induced chemically may amplify to an adverse outcome but coarse changes may override lesion propagation in any complex adaptive system. Modeling system dynamics in a developing tissue is a multiscale problem that challenges our ability to predict toxicity from in vitro profiling data (ToxCast/Tox21). (DISCLAIMER: The views expressed in this presentation are those of the presenter and do not necessarily reflect the views or policies of the US EPA). This was an invited seminar presentation to the National Institute for Public H

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Predicted phototoxicities of carbon nano-material by quantum mechanical calculations.

PubMed

Betowski, Don

2017-08-01

The purpose of this research was to develop a predictive model for the phototoxicity potential of carbon nanomaterials (fullerenols and single-walled carbon nanotubes). This model is based on the quantum mechanical (ab initio) calculations on these carbon-based materials and comparison of the triplet excited states of these materials to published work relating phototoxicity of polynuclear aromatic hydrocarbons (PAH) to their predictive triplet excited state energy. A successful outcome will add another tool to the arsenal of predictive methods for the U.S. EPA program offices as they assess the toxicity of compounds in use or coming into commerce. The basis of this research was obtaining the best quantum mechanical structure of the carbon nanomaterial and was fundamental in determining the triplet excited state energy. The triplet excited state, in turn, is associated with the phototoxicity of the material. This project relies heavily on the interaction of the predictive results (physical chemistry) and the experimental results obtained by biologists and toxicologists. The results of the experiments (toxicity testing) will help refine the predictive model, while the predictions will alert the scientists to red flag compounds. It is hoped that a guidance document for the U.S. EPA will be forthcoming to help determine the toxicity of compounds. This can be a screening tool that would rely on further testing for those compounds found by these predictions to be a phototoxic danger to health and the environment. Copyright © 2017. Published by Elsevier Inc.

Exploring the novel heterocyclic derivatives as lead molecules for design and development of potent anticancer agents.

PubMed

Azad, Iqbal; Nasibullah, Malik; Khan, Tahmeena; Hassan, Firoj; Akhter, Yusuf

2018-05-01

This paper deals with in silico evaluation of newly proposed heterocyclic derivatives in search of potential anticancer activity. Best possible drug candidates have been proposed using a rational approach employing a pipeline of computational techniques namely MetaPrint2D prediction, molinspiration, cheminformatics, Osiris Data warrior, AutoDock and iGEMDOCK. Lazar toxicity prediction, AdmetSAR predictions, and targeted docking studies were also performed. 27 heterocyclic derivatives were selected for bioactivity prediction and drug likeness score on the basis of Lipinski's rule, Viber rule, Ghose filter, leadlikeness and Pan Assay Interference Compounds (PAINS) rule. Bufuralol, Sunitinib, and Doxorubicin were selected as reference standard drug for the comparison of molecular descriptors and docking. Bufuralol is a known non-selective adreno-receptor blocking agent. Studies showed that beta blockers are also used against different types of cancers. Sunitinib is well known Food and Drug administration (FDA) approved pyrrole containing tyrosine kinase inhibitor and our proposed molecules possess similarities with both drug and doxorubicin is another moiety having anticancer activity. All heterocyclic derivatives were found to obey the drug filters except standard drug Doxorubicin. Bioactivity score of the compounds was predicted for drug targets including enzymes, nuclear receptors, kinase inhibitors, G protein-coupled receptor (GPCR) ligands and ion channel modulators. Absorption, distribution, metabolism and toxicity (ADMET) prediction of all proposed compound showed good Blood-brain barrier (BBB) penetration, Human intestinal absorption (HIA), Caco-2 cell permeability except compound-11 and was found to have no AdmetSAR toxicity as well as carcinogenic effect. Compounds 1-9 were slightly mutagenic while compound 2, 11, 20 and 21 showed carcinogenic effect according to Lazar toxicity prediction. Rests of the compounds were predicted to have no side effect. Molecular docking was performed with vascular endothelial growth factor receptor-2(VEGFR2) and glutathione S-transferase-1 (GSTP1) because both are common cancer causing proteins. Sunitinib and Doxorubicin possess great affinity to inhibit these cancers causing protein. Self-organizing map (SOM) was used to depict data in a simple 2D presentation. Our studies justify that good oral bioavailability and therapeutic efficacy of 10, 12-19 and 22-27 compounds can be considered as potential anticancer agents. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of adverse effects of proton and X-ray chemoradiotherapy for esophageal cancer using an adaptive dose–volume histogram analysis

PubMed Central

Makishima, Hirokazu; Ishikawa, Hitoshi; Terunuma, Toshiyuki; Hashimoto, Takayuki; Yamanashi, Koichi; Sekiguchi, Takao; Mizumoto, Masashi; Okumura, Toshiyuki; Sakae, Takeji; Sakurai, Hideyuki

2015-01-01

Cardiopulmonary late toxicity is of concern in concurrent chemoradiotherapy (CCRT) for esophageal cancer. The aim of this study was to examine the benefit of proton beam therapy (PBT) using clinical data and adaptive dose–volume histogram (DVH) analysis. The subjects were 44 patients with esophageal cancer who underwent definitive CCRT using X-rays (n = 19) or protons (n = 25). Experimental recalculation using protons was performed for the patient actually treated with X-rays, and vice versa. Target coverage and dose constraints of normal tissues were conserved. Lung V5–V20, mean lung dose (MLD), and heart V30–V50 were compared for risk organ doses between experimental plans and actual treatment plans. Potential toxicity was estimated using protons in patients actually treated with X-rays, and vice versa. Pulmonary events of Grade ≥2 occurred in 8/44 cases (18%), and cardiac events were seen in 11 cases (25%). Risk organ doses in patients with events of Grade ≥2 were significantly higher than for those with events of Grade ≤1. Risk organ doses were lower in proton plans compared with X-ray plans. All patients suffering toxicity who were treated with X-rays (n = 13) had reduced predicted doses in lung and heart using protons, while doses in all patients treated with protons (n = 24) with toxicity of Grade ≤1 had worsened predicted toxicity with X-rays. Analysis of normal tissue complication probability showed a potential reduction in toxicity by using proton beams. Irradiation dose, volume and adverse effects on the heart and lung can be reduced using protons. Thus, PBT is a promising treatment modality for the management of esophageal cancer. PMID:25755255

Mediating toxic emotions in the workplace--the impact of abusive supervision.

PubMed

Chu, Li-Chuan

2014-11-01

This study explores whether abusive supervision can effectively predict employees' counterproductive work behaviour (CWB) and organisational citizenship behaviour (OCB) and the role of toxic emotions at work as a potential mediator of these relationships in nursing settings. Workplace bullying is widespread in nursing. Despite the growing literature on abusive supervision and employees' counterproductive work behaviour and organisational citizenship behaviour, few studies have examined the relationships between abusive supervision and these work behaviours from the viewpoint of the victimed employee's emotion process. This study adopted a two-stage survey of 212 nurses, all of whom were employed by hospitals in Taiwan. Hypotheses were tested through the use of hierarchical multiple regression. The results showed that abusive supervision was positively associated with toxic emotions. Moreover, toxic emotions could effectively predict nurses' counterproductive work behaviour and organisational citizenship behaviour. Finally, it was found that toxic emotions partially mediated the negative effects of abusive supervision on both work behaviours. Toxic emotions at work are a critical mediating variable between abusive supervision and both counterproductive work behaviour and organisational citizenship behaviour. Hospital administrators can implement policies designed to manage events effectively that can spark toxic emotions in their employees. Work empowerment may be an effective way to reduce counterproductive work behaviour and to enhance organisational citizenship behaviour among nurses when supervisors do not promote a healthy work environment for them. © 2013 John Wiley & Sons Ltd.

Computational Approaches for Identifying Adverse Outcome Pathways

EPA Science Inventory

Adverse Outcome Pathways (AOPs) provide a framework for organizing toxicity information to improve predictions of the potential adverse impact of environment stressors on humans or wildlife populations, but these benefits are currently limited by the small number of AOPs currentl...

Derivation of freshwater quality criteria for zinc using interspecies correlation estimation models to protect aquatic life in China.

PubMed

Feng, C L; Wu, F C; Dyer, S D; Chang, H; Zhao, X L

2013-01-01

Species sensitivity distributions (SSDs) are usually used in the development of water quality criteria and require a large number of toxicity values to define a hazard level to protect the majority of species. However, some toxicity data for certain chemicals are limited, especially for endangered and threatened species. Thus, it is important to predict the unknown species toxicity data using available toxicity data. To address this need, interspecies correlation estimation (ICE) models were developed by US EPA to predict acute toxicity of chemicals to diverse species based on a more limited data set of surrogate species toxicity data. Use of SSDs generated from ICE models allows for the prediction of protective water quality criteria, such as the HC5 (hazard concentration, 5th percentile). In the present study, we tested this concept using toxicity data collected for zinc. ICE-based-SSDs were generated using three surrogate species (common carp (Cyprinus carpio), rainbow trout (Oncorhynchus mykiss), and Daphnia magna) and compared with the measured-based SSD and corresponding HC5. The results showed that no significant differences were observed between the ICE- and the measured-based SSDs and HC5s. Furthermore, the examination of species placements within the SSDs indicated that the most sensitive species to zinc were invertebrates, especially crustaceans. Given the similarity of SSD and HC5s for zinc, the use of ICE to derive potential water quality criteria for diverse chemicals in China is proposed. Further, a combination of measured and ICE-derived data will prove useful for assessing water quality and chemical risks in the near future. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predicting risk in patients with acetaminophen overdose

PubMed Central

James, Laura P.; Gill, Prit; Simpson, Pippa

2014-01-01

Acetaminophen (APAP) overdose is a very common cause of drug overdose and acute liver failure in the US and Europe. Mechanism-based biomarkers of APAP toxicity have the potential to improve the clinical management of patients with large dose ingestions of APAP. The current approach to the management of APAP toxicity is limited by imprecise and time-constrained risk assessments and late-stage markers of liver injury. A recent study of “low-risk” APAP overdose patients who all received treatment with N-acetylcysteine, found that cell-death biomarkers were more sensitive than alanine aminotransferase (ALT) and APAP concentrations in predicting the development of acute liver injury. The data suggest a potential role for new biomarkers to identify “low risk” patients following APAP overdose. However, a practical and ethical consideration that complicates predictive biomarker research in this area is the clinical need to deliver antidote treatment within 10 hours of APAP overdose. The treatment effect and time-dependent nature of N-acetylcysteine treatment must be considered in future “predictive” toxicology studies of APAP-induced liver injury. PMID:23984999

Ecotoxicity of quinoline and hydroxylated derivatives and their occurrence in groundwater of a tar-contaminated field site.

PubMed

Neuwoehner, Judith; Reineke, Anne-Kirsten; Hollender, Juliane; Eisentraeger, Adolf

2009-03-01

In the groundwater of a timber impregnation site higher concentrations of hydroxylated quinolines compared to their parent compounds quinoline and isoquinoline were found. Studying the toxicity of parent compounds and metabolites, genotoxicity was found with metabolic activation in the SOS-Chromotest and Ames fluctuation test only for quinoline. An adverse effect on algae was observed only for the parent compounds quinoline and isoquinoline, while in the Daphnia magna immobilization assay most hydroxylated quinoline derivatives showed toxicity. The highest ecotoxic potential was observed in the Vibrio fischeri luminescence-inhibition assay. Comparing experimental EC50-values with QSAR predicted ones, for all compounds apart from isoquinoline and 2(1H)-quinolinone in the V. fischeri test baseline toxicity or polar nacrosis is indicated. In conclusion, the hydroxylation of quinoline leads to a detoxification of the genotoxic potential, while taken additive mixture toxicity and a safety factor into account parent compounds and metabolites are found of ecotoxicological relevance in the groundwater.

Widespread Nanoparticle-Assay Interference: Implications for Nanotoxicity Testing

PubMed Central

Ong, Kimberly J.; MacCormack, Tyson J.; Clark, Rhett J.; Ede, James D.; Ortega, Van A.; Felix, Lindsey C.; Dang, Michael K. M.; Ma, Guibin; Fenniri, Hicham; Veinot, Jonathan G. C.; Goss, Greg G.

2014-01-01

The evaluation of engineered nanomaterial safety has been hindered by conflicting reports demonstrating differential degrees of toxicity with the same nanoparticles. The unique properties of these materials increase the likelihood that they will interfere with analytical techniques, which may contribute to this phenomenon. We tested the potential for: 1) nanoparticle intrinsic fluorescence/absorbance, 2) interactions between nanoparticles and assay components, and 3) the effects of adding both nanoparticles and analytes to an assay, to interfere with the accurate assessment of toxicity. Silicon, cadmium selenide, titanium dioxide, and helical rosette nanotubes each affected at least one of the six assays tested, resulting in either substantial over- or under-estimations of toxicity. Simulation of realistic assay conditions revealed that interference could not be predicted solely by interactions between nanoparticles and assay components. Moreover, the nature and degree of interference cannot be predicted solely based on our current understanding of nanomaterial behaviour. A literature survey indicated that ca. 95% of papers from 2010 using biochemical techniques to assess nanotoxicity did not account for potential interference of nanoparticles, and this number had not substantially improved in 2012. We provide guidance on avoiding and/or controlling for such interference to improve the accuracy of nanotoxicity assessments. PMID:24618833

Toxicity Assessment of Wild Mushrooms from the Western Ghats, India: An in Vitro and Sub-Acute in Vivo Study

PubMed Central

Sai Latha, S.; Naveen, S.; Pradeep, C. K.; Sivaraj, C.; Dinesh, M. G.; Anilakumar, K. R.

2018-01-01

Background: Poisoning by different kinds of toxic mushrooms is unfortunately becoming an increasingly important medical problem, evident from the growing number of reports worldwide since the 1950s. Mycetism being a health concern, deserves scientific attention. In this perspective, the present study aims to assess the potential effects of ingesting the selected wild mushrooms from regions of the Western Ghats, India. Methods: The preliminary cytotoxicity of the selected mushrooms was studied in vitro on the intestinal NCM460 and the Chang's liver cell lines on the basis of cell viability. Further, the hepatotoxicity was assessed by measuring biologically relevant endpoints such as membrane integrity, mitochondrial stress and oxidative status. A 28 day sub-acute toxicity study was carried out by orally administering the mushroom extracts to mice at 250 and 500 mg/kg body weight. The hematological and serum analysis as well as histological examinations were carried out to evaluate their in vivo toxicity. GC-MS analysis of the mushrooms facilitated the identification of their volatile chemical profile. Result: The in vitro intestinal cytotoxicity exhibited by these wild mushrooms in comparison to the edible mushroom indicated their potential gastrointestinal toxicity. The pathological findings in small intestine on exposure to Chlorophyllum molybdites and Agaricus endoxanthus also validates the speculations about their intestinal toxicity. The toxic insult to the hepatocytes due to Amanita angustilamellata, Entoloma crassum, and Clarkeinda trachodes was predictive of the observed in vivo hepatotoxicity which was also accompanied by renal toxicity at the higher dose of 500 mg/kg bwt. Conclusion: The potential toxicity exhibited by these representative mushrooms from the wild warrants caution about their consumption. The present work could also have broader implications for global mycetism. PMID:29487528

Using biodynamic models to reconcile differences between laboratory toxicity tests and field biomonitoring with aquatic insects

USGS Publications Warehouse

Buchwalter, D.B.; Cain, D.J.; Clements, W.H.; Luoma, S.N.

2007-01-01

Aquatic insects often dominate lotic ecosystems, yet these organisms are under-represented in trace metal toxicity databases. Furthermore, toxicity data for aquatic insects do not appear to reflect their actual sensitivities to metals in nature, because the concentrations required to elicit toxicity in the laboratory are considerably higher than those found to impact insect communities in the field. New approaches are therefore needed to better understand how and why insects are differentially susceptible to metal exposures. Biodynamic modeling is a powerful tool for understanding interspecific differences in trace metal bioaccumulation. Because bioaccumulation alone does not necessarily correlate with toxicity, we combined biokinetic parameters associated with dissolved cadmium exposures with studies of the subcellular compartmentalization of accumulated Cd. This combination of physiological traits allowed us to make predictions of susceptibility differences to dissolved Cd in three aquatic insect taxa: Ephemerella excrucians, Rhithrogena morrisoni, and Rhyacophila sp. We compared these predictions with long-term field monitoring data and toxicity tests with closely related taxa: Ephemerella infrequens, Rhithrogena hageni, and Rhyacophila brunea. Kinetic parameters allowed us to estimate steady-state concentrations, the time required to reach steady state, and the concentrations of Cd projected to be in potentially toxic compartments for different species. Species-specific physiological traits identified using biodynamic models provided a means for better understanding why toxicity assays with insects have failed to provide meaningful estimates for metal concentrations that would be expected to be protective in nature. ?? 2007 American Chemical Society.

Predictive modeling of nanomaterial exposure effects in biological systems

PubMed Central

Liu, Xiong; Tang, Kaizhi; Harper, Stacey; Harper, Bryan; Steevens, Jeffery A; Xu, Roger

2013-01-01

Background Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric) was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results We found several important attributes that contribute to the 24 hours post-fertilization (hpf) mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of nanomaterials. Sample prediction models can be found at http://neiminer.i-a-i.com/nei_models. Conclusion The EZ Metric-based data mining approach has been shown to have predictive power. The results provide valuable insights into the modeling and understanding of nanomaterial exposure effects. PMID:24098077

Control of trace element toxicity in Chesapeake Bay by dominant phytoplankton. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanders, J.G.; Riedel, G.F.; Connell, D.B.

1992-02-01

Copper (Cu) and arsenic (As), but not chromium (Cr), underwent large changes in chemical form during the development and senescence of natural phytoplankton blooms. In general, the percentage of organically-associated Cu was lowest during periods of rapid cell growth and highest during periods of cell decline or periods of dominance by red tide-forming dinoflagellates, a pattern tied to periods of release of organic compounds during either bloom senescence or during unusual algal blooms. Chromium, in contrast, was unreactive. The end result of biological mediation of both As and Cu was to increase the proportion of the element present in amore » less toxic form, at least to phytoplankton, thus affecting the potential toxicity of either element to a natural ecosystem. The results of the project provide a framework for the construction of general predictive models of likely trace element behavior in productive ecosystems and provide a conceptual theory of how such toxic contaminants may affect ecosystem structure and food webs within Chesapeake Bay. Predictive models of ecosystem impact will require further experimentation with multi-trophic level food chains.« less

Public Databases Supporting Computational Toxicology

EPA Science Inventory

A major goal of the emerging field of computational toxicology is the development of screening-level models that predict potential toxicity of chemicals from a combination of mechanistic in vitro assay data and chemical structure descriptors. In order to build these models, resea...

Computational Approaches to Predict Indices of Cyanobacteria Toxicity.

EPA Science Inventory

As nutrient inputs increase, productivity increases and lakes transition from low trophic state (e.g., oligotrophic) to higher trophic states (e.g., eutrophic). These broad trophic state classifications are good predictors of ecosystem health and the potential for ecosystem serv...

ToxCast: Using high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Applications of high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

In Vitro Pulmonary Toxicity of Metal Oxide Nanoparticles

EPA Science Inventory

Nanomaterials (NMs) encompass a diversity of materials with unique physicochemical characteristics which raise concerns about their potential risk to human health. Rapid predictive testing methods are needed to characterize NMs health effects as well as to screen and prioritize N...

Computational Approaches to Predict Indices of Cyanobacteria Toxicity

EPA Science Inventory

As nutrient inputs increase, productivity increases and lakes transition from low trophic state (e.g. oligotrophic) to higher trophic states (e.g. eutrophic). These broad trophic state classifications are good predictors of ecosystem health and the potential for ecosystem servic...

In vivo contaminant partitioning to silicone implants: Implications for use in biomonitoring and body burden.

PubMed

O'Connell, Steven G; Kerkvliet, Nancy I; Carozza, Susan; Rohlman, Diana; Pennington, Jamie; Anderson, Kim A

2015-12-01

Silicone polymers are used for a wide array of applications from passive samplers in environmental studies, to implants used in human augmentation and reconstruction. If silicone sequesters toxicants throughout implantation, it may represent a history of exposure and potentially reduce the body burden of toxicants influencing the risk of adverse health outcomes such as breast cancer. Objectives of this research included identifying a wide variety of toxicants in human silicone implants, and measuring the in vivo absorption of contaminants into silicone and surrounding tissue in an animal model. In the first study, eight human breast implants were analyzed for over 1400 organic contaminants including consumer products, chemicals in commerce, and pesticides. A total of 14 compounds including pesticides such as trans-nonachlor (1.2-5.9ng/g) and p,p'-DDE (1.2-34ng/g) were identified in human implants, 13 of which have not been previously reported in silicone prostheses. In the second project, female ICR mice were implanted with silicone and dosed with p,p'-DDE and PCB118 by intraperitoneal injection. After nine days, silicone and adipose samples were collected, and all implants in dosed mice had p,p'-DDE and PCB118 present. Distribution ratios from silicone and surrounding tissue in mice compare well with similar studies, and were used to predict adipose concentrations in human tissue. Similarities between predicted and measured chemical concentrations in mice and humans suggest that silicone may be a reliable surrogate measure of persistent toxicants. More research is needed to identify the potential of silicone implants to refine the predictive quality of chemicals found in silicone implants. Copyright © 2015 Elsevier Ltd. All rights reserved.

A mouse diversity panel approach reveals the potential for clinical kidney injury due to DB289 not predicted by classical rodent models.

PubMed

Harrill, Alison H; Desmet, Kristina D; Wolf, Kristina K; Bridges, Arlene S; Eaddy, J Scott; Kurtz, C Lisa; Hall, J Ed; Paine, Mary F; Tidwell, Richard R; Watkins, Paul B

2012-12-01

DB289 is the first oral drug shown in clinical trials to have efficacy in treating African trypanosomiasis (African sleeping sickness). Mild liver toxicity was noted but was not treatment limiting. However, development of DB289 was terminated when several treated subjects developed severe kidney injury, a liability not predicted from preclinical testing. We tested the hypothesis that the kidney safety liability of DB289 would be detected in a mouse diversity panel (MDP) comprised of 34 genetically diverse inbred mouse strains. MDP mice received 10 days of oral treatment with DB289 or vehicle and classical renal biomarkers blood urea nitrogen (BUN) and serum creatinine (sCr), as well as urine biomarkers of kidney injury were measured. While BUN and sCr remained within reference ranges, marked elevations were observed for kidney injury molecule-1 (KIM-1) in the urine of sensitive mouse strains. KIM-1 elevations were not always coincident with elevations in alanine aminotransferase (ALT), suggesting that renal injury was not linked to hepatic injury. Genome-wide association analyses of KIM-1 elevations indicated that genes participating in cholesterol and lipid biosynthesis and transport, oxidative stress, and cytokine release may play a role in DB289 renal injury. Taken together, the data resulting from this study highlight the utility of using an MDP to predict clinically relevant toxicities, to identify relevant toxicity biomarkers that may translate into the clinic, and to identify potential mechanisms underlying toxicities. In addition, the sensitive mouse strains identified in this study may be useful in screening next-in-class compounds for renal injury.

Predicting toxic effects of copper on aquatic biota in mineralized areas by using the Biotic Ligand Model

USGS Publications Warehouse

Smith, Kathleen S.; Ranville, James F.; Adams, M.; Choate, LaDonna M.; Church, Stan E.; Fey, David L.; Wanty, Richard B.; Crock, James G.

2006-01-01

The chemical speciation of metals influences their biological effects. The Biotic Ligand Model (BLM) is a computational approach to predict chemical speciation and acute toxicological effects of metals on aquatic biota. Recently, the U.S. Environmental Protection Agency incorporated the BLM into their regulatory water-quality criteria for copper. Results from three different laboratory copper toxicity tests were compared with BLM predictions for simulated test-waters. This was done to evaluate the ability of the BLM to accurately predict the effects of hardness and concentrations of dissolved organic carbon (DOC) and iron on aquatic toxicity. In addition, we evaluated whether the BLM and the three toxicity tests provide consistent results. Comparison of BLM predictions with two types of Ceriodaphnia dubia toxicity tests shows that there is fairly good agreement between predicted LC50 values computed by the BLM and LC50 values determined from the two toxicity tests. Specifically, the effect of increasing calcium concentration (and hardness) on copper toxicity appears to be minimal. Also, there is fairly good agreement between the BLM and the two toxicity tests for test solutions containing elevated DOC, for which the LC50 is 3-to-5 times greater (less toxic) than the LC50 for the lower-DOC test water. This illustrates the protective effects of DOC on copper toxicity and demonstrates the ability of the BLM to predict these protective effects. In contrast, for test solutions with added iron there is a decrease in LC50 values (increase in toxicity) in results from the two C. dubia toxicity tests, and the agreement between BLM LC50 predictions and results from these toxicity tests is poor. The inability of the BLM to account for competitive iron binding to DOC or DOC fractionation may be a significant shortcoming of the BLM for predicting site- specific water-quality criteria in streams affected by iron-rich acidic drainage in mined and mineralized areas.

Fractionation of fulvic acid by iron and aluminum oxides: influence on copper toxicity to Ceriodaphnia dubia

USGS Publications Warehouse

Smith, Kathleen S.; Ranville, James F.; Lesher, Emily K.; Diedrich, Daniel J.; McKnight, Diane M.; Sofield, Ruth M.

2014-01-01

This study examines the effect on aquatic copper toxicity of the chemical fractionation of fulvic acid (FA) that results from its association with iron and aluminum oxyhydroxide precipitates. Fractionated and unfractionated FAs obtained from streamwater and suspended sediment were utilized in acute Cu toxicity tests on ,i>Ceriodaphnia dubia. Toxicity test results with equal FA concentrations (6 mg FA/L) show that the fractionated dissolved FA was 3 times less effective at reducing Cu toxicity (EC50 13 ± 0.6 μg Cu/L) than were the unfractionated dissolved FAs (EC50 39 ± 0.4 and 41 ± 1.2 μg Cu/L). The fractionation is a consequence of preferential sorption of molecules having strong metal-binding (more aromatic) moieties to precipitating Fe- and Al-rich oxyhydroxides, causing the remaining dissolved FA to be depleted in these functional groups. As a result, there is more bioavailable dissolved Cu in the water and hence greater potential for Cu toxicity to aquatic organisms. In predicting Cu toxicity, biotic ligand models (BLMs) take into account dissolved organic carbon (DOC) concentration; however, unless DOC characteristics are accounted for, model predictions can underestimate acute Cu toxicity for water containing fractionated dissolved FA. This may have implications for water-quality criteria in systems containing Fe- and Al-rich sediment, and in mined and mineralized areas in particular. Optical measurements, such as specific ultraviolet absorbance at 254 nm (SUVA254), show promise for use as spectral indicators of DOC chemical fractionation and inferred increased Cu toxicity.

Proactive aquatic ecotoxicological assessment of room-temperature ionic liquids

USGS Publications Warehouse

Kulacki, K.J.; Chaloner, D.T.; Larson, J.H.; Costello, D.M.; Evans-White, M. A.; Docherty, K.M.; Bernot, R.J.; Brueseke, M.A.; Kulpa, C.F.; Lamberti, G.A.

2011-01-01

Aquatic environments are being contaminated with a myriad of anthropogenic chemicals, a problem likely to continue due to both unintentional and intentional releases. To protect valuable natural resources, novel chemicals should be shown to be environmentally safe prior to use and potential release into the environment. Such proactive assessment is currently being applied to room-temperature ionic liquids (ILs). Because most ILs are water-soluble, their effects are likely to manifest in aquatic ecosystems. Information on the impacts of ILs on numerous aquatic organisms, focused primarily on acute LC50 and EC50 endpoints, is now available, and trends in toxicity are emerging. Cation structure tends to influence IL toxicity more so than anion structure, and within a cation class, the length of alkyl chain substituents is positively correlated with toxicity. While the effects of ILs on several aquatic organisms have been studied, the challenge for aquatic toxicology is now to predict the effects of ILs in complex natural environments that often include diverse mixtures of organisms, abiotic conditions, and additional stressors. To make robust predictions about ILs will require coupling of ecologically realistic laboratory and field experiments with standard toxicity bioassays and models. Such assessments would likely discourage the development of especially toxic ILs while shifting focus to those that are more environmentally benign. Understanding the broader ecological effects of emerging chemicals, incorporating that information into predictive models, and conveying the conclusions to those who develop, regulate, and use those chemicals, should help avoid future environmental degradation. ?? 2011 Bentham Science Publishers Ltd.

Development and Application of Computational/In Vitro Toxicological Methods for Chemical Hazard Risk Reduction of New Materials for Advanced Weapon Systems

NASA Technical Reports Server (NTRS)

Frazier, John M.; Mattie, D. R.; Hussain, Saber; Pachter, Ruth; Boatz, Jerry; Hawkins, T. W.

2000-01-01

The development of quantitative structure-activity relationship (QSAR) is essential for reducing the chemical hazards of new weapon systems. The current collaboration between HEST (toxicology research and testing), MLPJ (computational chemistry) and PRS (computational chemistry, new propellant synthesis) is focusing R&D efforts on basic research goals that will rapidly transition to useful products for propellant development. Computational methods are being investigated that will assist in forecasting cellular toxicological end-points. Models developed from these chemical structure-toxicity relationships are useful for the prediction of the toxicological endpoints of new related compounds. Research is focusing on the evaluation tools to be used for the discovery of such relationships and the development of models of the mechanisms of action. Combinations of computational chemistry techniques, in vitro toxicity methods, and statistical correlations, will be employed to develop and explore potential predictive relationships; results for series of molecular systems that demonstrate the viability of this approach are reported. A number of hydrazine salts have been synthesized for evaluation. Computational chemistry methods are being used to elucidate the mechanism of action of these salts. Toxicity endpoints such as viability (LDH) and changes in enzyme activity (glutahoione peroxidase and catalase) are being experimentally measured as indicators of cellular damage. Extrapolation from computational/in vitro studies to human toxicity, is the ultimate goal. The product of this program will be a predictive tool to assist in the development of new, less toxic propellants.

Using Pareto points for model identification in predictive toxicology

PubMed Central

2013-01-01

Predictive toxicology is concerned with the development of models that are able to predict the toxicity of chemicals. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in cosmetics, drug design or food protection to speed up the process of chemical compound discovery while reducing the need for lab tests. There is an extensive literature associated with the best practice of model generation and data integration but management and automated identification of relevant models from available collections of models is still an open problem. Currently, the decision on which model should be used for a new chemical compound is left to users. This paper intends to initiate the discussion on automated model identification. We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound. The performance of this new approach is verified for two endpoints: IGC50 and LogP. The results show a great potential for automated model identification methods in predictive toxicology. PMID:23517649

Predicting severe hematologic toxicity from extended-field chemoradiation of para-aortic nodal metastases from cervical cancer.

PubMed

Yan, Kevin; Ramirez, Ezequiel; Xie, Xian-Jin; Gu, Xuejun; Xi, Yin; Albuquerque, Kevin

The purpose of this study was to determine factors predictive for severe hematologic toxicity (HT) in cervical cancer patients with para-aortic lymph node metastasis treated with concurrent cisplatin chemoradiation to an extended field (EFCRT). Thirty-eight patients with cervical cancer and para-aortic lymph node metastasis who underwent EFCRT were analyzed. Active bone marrow was defined as the region within irradiated total bone marrow (BM TOT ) with a standard uptake value on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography greater than the mean standard uptake value for BM TOT . Serial weekly blood counts from the beginning to the end of radiation treatment were evaluated for HT using Common Terminology Criteria for Adverse Events, version 4.0. Nineteen patients had grade 3 or higher hematologic toxicity (HT3+), not including lymphocyte toxicity. Obese patients (n = 12) were less likely to get HT3+ (P = .03) despite getting equivalent doses of chemotherapy. Volumes of BM TOT and active bone marrow receiving doses of 20, 30, and 45 Gy and body mass index significantly predicted HT3+. Patients who had HT3+ had prolonged treatment time (62 vs 53 days, P < .001). For patients receiving EFCRT, bone marrow irradiation parameters and patient body mass index were associated with HT3+. A simplified nomogram has been created to predict HT3+ in these patients, allowing the potential to explore bone marrow-sparing delivery techniques. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Assessment of in vivo organ-uptake and in silico prediction of CYP mediated metabolism of DA-Phen, a new dopaminergic agent.

PubMed

Sutera, Flavia Maria; Giannola, Libero Italo; Murgia, Denise; De Caro, Viviana

2017-12-01

The drug development process strives to predict metabolic fate of a drug candidate, together with its uptake in major organs, whether they act as target, deposit or metabolism sites, to the aim of establish a relationship between the pharmacodynamics and the pharmacokinetics and highlight the potential toxicity of the drug candidate. The present study was aimed at evaluating the in vivo uptake of 2-Amino-N-[2-(3,4-dihydroxy-phenyl)-ethyl]-3-phenyl-propionamide (DA-Phen) - a new dopaminergic neurotransmission modulator, in target and non-target organs of animal subjects and integrating these data with SMARTCyp results, an in silico method that predicts the sites of cytochrome P450-mediated metabolism of drug-like molecules. Wistar rats, subjected to two different behavioural studies in which DA-Phen was intraperitoneally administrated at a dose equal to 0.03mmol/kg, were sacrificed after the experimental protocols and their major organs were analysed to quantify the drug uptake. The data obtained were integrated with in silico prediction of potential metabolites of DA-Phen using the SmartCYP predictive tool. DA-Phen reached quantitatively the Central Nervous System and the results showed that the amide bond of the DA-Phen is scarcely hydrolysed as it was found intact in analyzed organs. As a consequence, it is possible to assume that DA-Phen acts as dopaminergic modulator per se and not as a Dopamine prodrug, thus avoiding peripheral release and toxic side effects due to the endogenous neurotransmitter. Furthermore the identification of potential metabolites related to biotransformation of the drug candidate leads to a more careful evaluation of the appropriate route of administration for future intended therapeutic aims and potential translation into clinical studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach

NASA Astrophysics Data System (ADS)

Wyrzykowska, Ewelina; Mikolajczyk, Alicja; Sikorska, Celina; Puzyn, Tomasz

2016-11-01

Once released into the aquatic environment, nanoparticles (NPs) are expected to interact (e.g. dissolve, agglomerate/aggregate, settle), with important consequences for NP fate and toxicity. A clear understanding of how internal and environmental factors influence the NP toxicity and fate in the environment is still in its infancy. In this study, a quantitative structure-property relationship (QSPR) approach was employed to systematically explore factors that affect surface charge (zeta potential) under environmentally realistic conditions. The nano-QSPR model developed with multiple linear regression (MLR) was characterized by high robustness ({{{Q}}{{2}}}{{CV}}=0.90) and external predictivity ({{{Q}}{{2}}}{{EXT}}=0.93). The results clearly showed that zeta potential values varied markedly as functions of the ionic radius of the metal atom in the metal oxides, confirming that agglomeration and the extent of release of free MexOy largely depend on their intrinsic properties. A developed nano-QSPR model was successfully applied to predict zeta potential in an ionized solution of NPs for which experimentally determined values of response have been unavailable. Hence, the application of our model is possible when the values of zeta potential in the ionized solution for metal oxide nanoparticles are undetermined, without the necessity of performing more time consuming and expensive experiments. We believe that our studies will be helpful in predicting the conditions under which MexOy is likely to become problematic for the environment and human health.

Computational toxicology using the OpenTox application programming interface and Bioclipse

PubMed Central

2011-01-01

Background Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. Findings This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. Conclusions A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers. PMID:22075173

Applications of high throughput screening to identify profiles of biological activity relevant to carcinogenesis

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Modeling Reactivity to Biological Macromolecules with a Deep Multitask Network

PubMed Central

2016-01-01

Most small-molecule drug candidates fail before entering the market, frequently because of unexpected toxicity. Often, toxicity is detected only late in drug development, because many types of toxicities, especially idiosyncratic adverse drug reactions (IADRs), are particularly hard to predict and detect. Moreover, drug-induced liver injury (DILI) is the most frequent reason drugs are withdrawn from the market and causes 50% of acute liver failure cases in the United States. A common mechanism often underlies many types of drug toxicities, including both DILI and IADRs. Drugs are bioactivated by drug-metabolizing enzymes into reactive metabolites, which then conjugate to sites in proteins or DNA to form adducts. DNA adducts are often mutagenic and may alter the reading and copying of genes and their regulatory elements, causing gene dysregulation and even triggering cancer. Similarly, protein adducts can disrupt their normal biological functions and induce harmful immune responses. Unfortunately, reactive metabolites are not reliably detected by experiments, and it is also expensive to test drug candidates for potential to form DNA or protein adducts during the early stages of drug development. In contrast, computational methods have the potential to quickly screen for covalent binding potential, thereby flagging problematic molecules and reducing the total number of necessary experiments. Here, we train a deep convolution neural network—the XenoSite reactivity model—using literature data to accurately predict both sites and probability of reactivity for molecules with glutathione, cyanide, protein, and DNA. On the site level, cross-validated predictions had area under the curve (AUC) performances of 89.8% for DNA and 94.4% for protein. Furthermore, the model separated molecules electrophilically reactive with DNA and protein from nonreactive molecules with cross-validated AUC performances of 78.7% and 79.8%, respectively. On both the site- and molecule-level, the model’s performances significantly outperformed reactivity indices derived from quantum simulations that are reported in the literature. Moreover, we developed and applied a selectivity score to assess preferential reactions with the macromolecules as opposed to the common screening traps. For the entire data set of 2803 molecules, this approach yielded totals of 257 (9.2%) and 227 (8.1%) molecules predicted to be reactive only with DNA and protein, respectively, and hence those that would be missed by standard reactivity screening experiments. Site of reactivity data is an underutilized resource that can be used to not only predict if molecules are reactive, but also show where they might be modified to reduce toxicity while retaining efficacy. The XenoSite reactivity model is available at http://swami.wustl.edu/xenosite/p/reactivity. PMID:27610414

Chronic toxicity of an environmentally relevant mixture of pharmaceuticals to three aquatic organisms (alga, daphnid, and fish).

PubMed

Watanabe, Haruna; Tamura, Ikumi; Abe, Ryoko; Takanobu, Hitomi; Nakamura, Ataru; Suzuki, Toshinari; Hirose, Akihiko; Nishimura, Tetsuji; Tatarazako, Norihisa

2016-04-01

Principles of concentration addition and independent action have been used as effective tools to predict mixture toxicity based on individual component toxicity. The authors investigated the toxicity of a pharmaceutical mixture composed of the top 10 detected active pharmaceutical ingredients (APIs) in the Tama River (Tokyo, Japan) in a relevant concentration ratio. Both individual and mixture toxicities of the 10 APIs were evaluated by 3 short-term chronic toxicity tests using the alga Pseudokirchneriella subcapitata, the daphnid Ceriodaphnia dubia, and the zebrafish Danio rerio. With the exception of clarithromycin toxicity to alga, the no-observed-effect concentration of individual APIs for each test species was dramatically higher than the highest concentration of APIs found in the environment. The mixture of 10 APIs resulted in toxicity to alga, daphnid, and fish at 6.25 times, 100 times, and 15,000 times higher concentrations, respectively, than the environmental concentrations of individual APIs. Predictions by concentration addition and independent action were nearly identical for alga, as clarithromycin was the predominant toxicant in the mixture. Both predictions described the observed mixture toxicity to alga fairly well, whereas they slightly underestimated the observed mixture toxicity in the daphnid test. In the fish embryo test, the observed toxicity fell between the predicted toxicity by concentration addition and independent action. These results suggested that the toxicity of environmentally relevant pharmaceutical mixtures could be predicted by individual toxicity using either concentration addition or independent action. © 2015 SETAC.

Contribution of new technologies to characterization and prediction of adverse effects.

PubMed

Rouquié, David; Heneweer, Marjoke; Botham, Jane; Ketelslegers, Hans; Markell, Lauren; Pfister, Thomas; Steiling, Winfried; Strauss, Volker; Hennes, Christa

2015-02-01

Identification of the potential hazards of chemicals has traditionally relied on studies in laboratory animals where changes in clinical pathology and histopathology compared to untreated controls defined an adverse effect. In the past decades, increased consistency in the definition of adversity with chemically-induced effects in laboratory animals, as well as in the assessment of human relevance has been reached. More recently, a paradigm shift in toxicity testing has been proposed, mainly driven by concerns over animal welfare but also thanks to the development of new methods. Currently, in vitro approaches, toxicogenomic technologies and computational tools, are available to provide mechanistic insight in toxicological Mode of Action (MOA) of the adverse effects observed in laboratory animals. The vision described as Tox21c (Toxicity Testing in the 21st century) aims at predicting in vivo toxicity using a bottom-up-approach, starting with understanding of MOA based on in vitro data to ultimately predict adverse effects in humans. At present, a practical application of the Tox21c vision is still far away. While moving towards toxicity prediction based on in vitro data, a stepwise reduction of in vivo testing is foreseen by combining in vitro with in vivo tests. Furthermore, newly developed methods will also be increasingly applied, in conjunction with established methods in order to gain trust in these new methods. This confidence is based on a critical scientific prerequisite: the establishment of a causal link between data obtained with new technologies and adverse effects manifested in repeated-dose in vivo toxicity studies. It is proposed to apply the principles described in the WHO/IPCS framework of MOA to obtain this link. Finally, an international database of known MOAs obtained in laboratory animals using data-rich chemicals will facilitate regulatory acceptance and could further help in the validation of the toxicity pathway and adverse outcome pathway concepts.

Seasonal Dynamics of Microcystis spp. and Their Toxigenicity as Assessed by qPCR in a Temperate Reservoir

PubMed Central

Martins, António; Moreira, Cristiana; Vale, Micaela; Freitas, Marisa; Regueiras, Ana; Antunes, Agostinho; Vasconcelos, Vitor

2011-01-01

Blooms of toxic cyanobacteria are becoming increasingly frequent, mainly due to water quality degradation. This work applied qPCR as a tool for early warning of microcystin(MC)-producer cyanobacteria and risk assessment of water supplies. Specific marker genes for cyanobacteria, Microcystis and MC-producing Microcystis, were quantified to determine the genotypic composition of the natural Microcystis population. Correlations between limnological parameters, pH, water temperature, dissolved oxygen and conductivity and MC concentrations as well as Microcystis abundance were assessed. A negative significant correlation was observed between toxic (with mcy genes) to non-toxic (without mcy genes) genotypes ratio and the overall Microcystis density. The highest proportions of toxic Microcystis genotypes were found 4–6 weeks before and 8–10 weeks after the peak of the bloom, with the lowest being observed at its peak. These results suggest positive selection of non-toxic genotypes under favorable environmental growth conditions. Significant positive correlations could be found between quantity of toxic genotypes and MC concentration, suggesting that the method applied can be useful to predict potential MC toxicity risk. No significant correlation was found between the limnological parameters measured and MC concentrations or toxic genotypes proportions indicating that other abiotic and biotic factors should be governing MC production and toxic genotypes dynamics. The qPCR method here applied is useful to rapidly estimate the potential toxicity of environmental samples and so, it may contribute to the more efficient management of water use in eutrophic systems. PMID:22072994

Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.

PubMed

Lodhi, Huma; Muggleton, Stephen; Sternberg, Mike J E

2010-09-17

Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi-class models by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi-class scheme with the standard multi-class Inductive Logic Programming algorithm and multi-class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Acute and chronic toxicity of six anticancer drugs on rotifers and crustaceans.

PubMed

Parrella, Alfredo; Lavorgna, Margherita; Criscuolo, Emma; Russo, Chiara; Fiumano, Vittorio; Isidori, Marina

2014-11-01

The growing use of cytostatic drugs is gaining relevance as an environmental concern. Environmental and distribution studies are increasing due to the development of accurate analytical methods, whereas ecotoxicological studies are still lacking. The aim of the present study was to investigate the acute and chronic toxicity of six cytostatics (5-fluorouracil, capecitabine, cisplatin, doxorubicin, etoposide, and imatinib) belonging to five classes of Anatomical Therapeutic Classification (ATC) on primary consumers of the aquatic chain (Daphnia magna, Ceriodaphnia dubia, Brachionus calyciflorus, and Thamnocephalus platyurus). Acute ecotoxicological effects occurred at concentrations in the order of mgL(-)(1), higher than those predicted in the environment, and the most acutely toxic drugs among those tested were cisplatin and doxorubicin for most aquatic organisms. For chronic toxicity, cisplatin and 5-fluorouracil showed the highest toxic potential in all test organisms, inducing 50% reproduction inhibition in crustaceans at concentrations on the order of μgL(-)(1). Rotifers were less susceptible to these pharmaceuticals. On the basis of chronic results, the low effective concentrations suggest a potential environmental risk of cytostatics. Thus, this study could be an important starting point for establishing the real environmental impact of these substances. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations

PubMed Central

Thiel, Christoph; Cordes, Henrik; Fabbri, Lorenzo; Aschmann, Hélène Eloise; Baier, Vanessa; Atkinson, Francis; Blank, Lars Mathias; Kuepfer, Lars

2017-01-01

Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application. PMID:28151932

HLA-G 3′UTR Polymorphisms Predict Drug-Induced G3-4 Toxicity Related to Folinic Acid/5-Fluorouracil/Oxaliplatin (FOLFOX4) Chemotherapy in Non-Metastatic Colorectal Cancer

PubMed Central

Garziera, Marica; Virdone, Saverio; De Mattia, Elena; Scarabel, Lucia; Cecchin, Erika; Polesel, Jerry; D’Andrea, Mario; Pella, Nicoletta; Buonadonna, Angela; Favaretto, Adolfo; Toffoli, Giuseppe

2017-01-01

Polymorphisms in drug-metabolizing enzymes might not completely explain inter-individual differences in toxicity profiles of patients with colorectal cancer (CRC) that receive folinic acid/5-fluorouracil/oxaliplatin (FOLFOX4). Recent data indicate that the immune system could contribute to FOLFOX4 outcomes. In light of the immune inhibitory nature of human leukocyte antigen-G (HLA-G), a non-classical major histocompatibility complex (MHC) class I molecule, we aimed to identify novel genomic markers of grades 3 and 4 (G3-4) toxicity related to FOLFOX4 therapy in patients with CRC. We retrospectively analyzed data for 144 patients with stages II-III CRC to identify HLA-G 3′ untranslated region (3′UTR) polymorphisms and related haplotypes and evaluate their impact on the risk of developing G3-4 toxicities (i.e., neutropenia, hematological/non-hematological toxicity, neurotoxicity) with logistic regression. The rs1610696-G/G polymorphism was associated with increased risk of G3-4 neutropenia (OR = 3.76, p = 0.015) and neurotoxicity (OR = 8.78, p = 0.016); rs371194629-Ins/Ins was associated with increased risk of neurotoxicity (OR = 5.49, p = 0.027). HLA-G 3′UTR-2, which contains rs1610696-G/G and rs371194629-Ins/Ins polymorphisms, was associated with increased risk of G3-4 neutropenia (OR = 3.92, p = 0.017) and neurotoxicity (OR = 11.29, p = 0.009). A bootstrap analysis confirmed the predictive value of rs1610696 and rs371194629, but the UTR-2 haplotype was validated only for neurotoxicity. This exploratory study identified new HLA-G 3′UTR polymorphisms/haplotypes as potential predictive markers of G3-4 toxicities in CRC. PMID:28653974

Integrating publicly-available data to generate computationally-predicted adverse outcome pathways for hepatic steatosis

EPA Science Inventory

The adverse outcome pathway (AOP) framework provides a way of organizing knowledge related to the key biological events that result in a particular health outcome. For the majority of environmental chemicals, the availability of curated pathways characterizing potential toxicity ...

High-throughput screening, predictive modeling and computational embryology

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...

Nanomaterial Toxicity Testing in the 21st Century: Use of a Predictive Toxicological Approach and High Throughput Screening

PubMed Central

NEL, ANDRE; XIA, TIAN; MENG, HUAN; WANG, XIANG; LIN, SIJIE; JI, ZHAOXIA; ZHANG, HAIYUAN

2014-01-01

Conspectus The production of engineered nanomaterials (ENMs) is a scientific breakthrough in material design and the development of new consumer products. While the successful implementation of nanotechnology is important for the growth of the global economy, we also need to consider the possible environmental health and safety (EHS) impact as a result of the novel physicochemical properties that could generate hazardous biological outcomes. In order to assess ENM hazard, reliable and reproducible screening approaches are needed to test the basic materials as well as nano-enabled products. A platform is required to investigate the potentially endless number of bio-physicochemical interactions at the nano/bio interface, in response to which we have developed a predictive toxicological approach. We define a predictive toxicological approach as the use of mechanisms-based high throughput screening in vitro to make predictions about the physicochemical properties of ENMs that may lead to the generation of pathology or disease outcomes in vivo. The in vivo results are used to validate and improve the in vitro high throughput screening (HTS) and to establish structure-activity relationships (SARs) that allow hazard ranking and modeling by an appropriate combination of in vitro and in vivo testing. This notion is in agreement with the landmark 2007 report from the US National Academy of Sciences, “Toxicity Testing in the 21st Century: A Vision and a Strategy” (http://www.nap.edu/catalog.php?record_id=11970), which advocates increased efficiency of toxicity testing by transitioning from qualitative, descriptive animal testing to quantitative, mechanistic and pathway-based toxicity testing in human cells or cell lines using high throughput approaches. Accordingly, we have implemented HTS approaches to screen compositional and combinatorial ENM libraries to develop hazard ranking and structure-activity relationships that can be used for predicting in vivo injury outcomes. This predictive approach allows the bulk of the screening analysis and high volume data generation to be carried out in vitro, following which limited, but critical, validation studies are carried out in animals or whole organisms. Risk reduction in the exposed human or environmental populations can then focus on limiting or avoiding exposures that trigger these toxicological responses as well as implementing safer design of potentially hazardous ENMs. In this communication, we review the tools required for establishing predictive toxicology paradigms to assess inhalation and environmental toxicological scenarios through the use of compositional and combinatorial ENM libraries, mechanism-based HTS assays, hazard ranking and development of nano-SARs. We will discuss the major injury paradigms that have emerged based on specific ENM properties, as well as describing the safer design of ZnO nanoparticles based on characterization of dissolution chemistry as a major predictor of toxicity. PMID:22676423

Assessing time-integrated dissolved concentrations and predicting toxicity of metals during diel cycling in streams

USGS Publications Warehouse

Balistrieri, Laurie S.; Nimick, David A.; Mebane, Christopher A.

2012-01-01

Evaluating water quality and the health of aquatic organisms is challenging in systems with systematic diel (24 hour) or less predictable runoff-induced changes in water composition. To advance our understanding of how to evaluate environmental health in these dynamic systems, field studies of diel cycling were conducted in two streams (Silver Bow Creek and High Ore Creek) affected by historical mining activities in southwestern Montana. A combination of sampling and modeling tools were used to assess the toxicity of metals in these systems. Diffusive Gradients in Thin Films (DGT) samplers were deployed at multiple time intervals during diel sampling to confirm that DGT integrates time-varying concentrations of dissolved metals. Thermodynamic speciation calculations using site specific water compositions, including time-integrated dissolved metal concentrations determined from DGT, and a competitive, multiple-metal biotic ligand model incorporated into the Windemere Humic Aqueous Model Version 6.0 (WHAM VI) were used to determine the chemical speciation of dissolved metals and biotic ligands. The model results were combined with previously collected toxicity data on cutthroat trout to derive a relationship that predicts the relative survivability of these fish at a given site. This integrative approach may prove useful for assessing water quality and toxicity of metals to aquatic organisms in dynamic systems and evaluating whether potential changes in environmental health of aquatic systems are due to anthropogenic activities or natural variability.

A novel logic-based approach for quantitative toxicology prediction.

PubMed

Amini, Ata; Muggleton, Stephen H; Lodhi, Huma; Sternberg, Michael J E

2007-01-01

There is a pressing need for accurate in silico methods to predict the toxicity of molecules that are being introduced into the environment or are being developed into new pharmaceuticals. Predictive toxicology is in the realm of structure activity relationships (SAR), and many approaches have been used to derive such SAR. Previous work has shown that inductive logic programming (ILP) is a powerful approach that circumvents several major difficulties, such as molecular superposition, faced by some other SAR methods. The ILP approach reasons with chemical substructures within a relational framework and yields chemically understandable rules. Here, we report a general new approach, support vector inductive logic programming (SVILP), which extends the essentially qualitative ILP-based SAR to quantitative modeling. First, ILP is used to learn rules, the predictions of which are then used within a novel kernel to derive a support-vector generalization model. For a highly heterogeneous dataset of 576 molecules with known fathead minnow fish toxicity, the cross-validated correlation coefficients (R2CV) from a chemical descriptor method (CHEM) and SVILP are 0.52 and 0.66, respectively. The ILP, CHEM, and SVILP approaches correctly predict 55, 58, and 73%, respectively, of toxic molecules. In a set of 165 unseen molecules, the R2 values from the commercial software TOPKAT and SVILP are 0.26 and 0.57, respectively. In all calculations, SVILP showed significant improvements in comparison with the other methods. The SVILP approach has a major advantage in that it uses ILP automatically and consistently to derive rules, mostly novel, describing fragments that are toxicity alerts. The SVILP is a general machine-learning approach and has the potential of tackling many problems relevant to chemoinformatics including in silico drug design.

Proposing Novel MAO-B Hit Inhibitors Using Multidimensional Molecular Modeling Approaches and Application of Binary QSAR Models for Prediction of Their Therapeutic Activity, Pharmacokinetic and Toxicity Properties.

PubMed

Is, Yusuf Serhat; Durdagi, Serdar; Aksoydan, Busecan; Yurtsever, Mine

2018-05-07

Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure-activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.

User’s Guide for T.E.S.T. (version 4.2) (Toxicity Estimation Software Tool) A Program to Estimate Toxicity from Molecular Structure

EPA Science Inventory

The user's guide describes the methods used by TEST to predict toxicity and physical properties (including the new mode of action based method used to predict acute aquatic toxicity). It describes all of the experimental data sets included in the tool. It gives the prediction res...

Chemical and ecotoxicological properties of three bio-oils from pyrolysis of biomasses.

PubMed

Campisi, Tiziana; Samorì, Chiara; Torri, Cristian; Barbera, Giuseppe; Foschini, Anna; Kiwan, Alisar; Galletti, Paola; Tagliavini, Emilio; Pasteris, Andrea

2016-10-01

In view of the potential use of pyrolysis-based technologies, it is crucial to understand the environmental hazards of pyrolysis-derived products, in particular bio-oils. Here, three bio-oils were produced from fast pyrolysis of pine wood and intermediate pyrolysis of corn stalk and poultry litter. They were fully characterized by chemical analysis and tested for their biodegradability and their ecotoxicity on the crustacean Daphnia magna and the green alga Raphidocelis subcapitata. These tests were chosen as required by the European REACH regulation. These three bio-oils were biodegradable, with 40-60% of biodegradation after 28 days, and had EC50 values above 100mgL(-1) for the crustacean and above 10mgL(-1) for the alga, showing low toxicity to the aquatic life. The toxic unit approach was applied to verify whether the observed toxicity could be predicted from the data available for the substances detected in the bio-oils. The predicted values largely underestimated the experimental values. Copyright © 2016 Elsevier Inc. All rights reserved.

Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions.

PubMed

Kleandrova, Valeria V; Luan, Feng; González-Díaz, Humberto; Ruso, Juan M; Melo, André; Speck-Planche, Alejandro; Cordeiro, M Natália D S

2014-12-01

Nanotechnology has brought great advances to many fields of modern science. A manifold of applications of nanoparticles have been found due to their interesting optical, electrical, and biological/chemical properties. However, the potential toxic effects of nanoparticles to different ecosystems are of special concern nowadays. Despite the efforts of the scientific community, the mechanisms of toxicity of nanoparticles are still poorly understood. Quantitative-structure activity/toxicity relationships (QSAR/QSTR) models have just started being useful computational tools for the assessment of toxic effects of nanomaterials. But most QSAR/QSTR models have been applied so far to predict ecotoxicity against only one organism/bio-indicator such as Daphnia magna. This prevents having a deeper knowledge about the real ecotoxic effects of nanoparticles, and consequently, there is no possibility to establish an efficient risk assessment of nanomaterials in the environment. In this work, a perturbation model for nano-QSAR problems is introduced with the aim of simultaneously predicting the ecotoxicity of different nanoparticles against several assay organisms (bio-indicators), by considering also multiple measures of ecotoxicity, as well as the chemical compositions, sizes, conditions under which the sizes were measured, shapes, and the time during which the diverse assay organisms were exposed to nanoparticles. The QSAR-perturbation model was derived from a database containing 5520 cases (nanoparticle-nanoparticle pairs), and it was shown to exhibit accuracies of ca. 99% in both training and prediction sets. In order to demonstrate the practical applicability of our model, three different nickel-based nanoparticles (Ni) with experimental values reported in the literature were predicted. The predictions were found to be in very good agreement with the experimental evidences, confirming that Ni-nanoparticles are not ecotoxic when compared with other nanoparticles. The results of this study thus provide a single valuable tool toward an efficient prediction of the ecotoxicity of nanoparticles under multiple experimental conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of an alternative in vitro test battery for detecting reproductive toxicants in a grouping context.

PubMed

Kroese, E Dinant; Bosgra, Sieto; Buist, Harrie E; Lewin, Geertje; van der Linden, Sander C; Man, Hai-yen; Piersma, Aldert H; Rorije, Emiel; Schulpen, Sjors H W; Schwarz, Michael; Uibel, Frederik; van Vugt-Lussenburg, Barbara M A; Wolterbeek, Andre P M; van der Burg, Bart

2015-08-01

Previously we showed a battery consisting of CALUX transcriptional activation assays, the ReProGlo assay, and the embryonic stem cell test, and zebrafish embryotoxicity assay as 'apical' tests to correctly predict developmental toxicity for 11 out of 12 compounds, and to explain the one false negative [7]. Here we report on applying this battery within the context of grouping and read across, put forward as a potential tool to fill data gaps and avoid animal testing, to distinguish in vivo non- or weak developmental toxicants from potent developmental toxicants within groups of structural analogs. The battery correctly distinguished 2-methylhexanoic acid, monomethyl phthalate, and monobutyltin trichloride as non- or weak developmental toxicants from structurally related developmental toxicants valproic acid, mono-ethylhexyl phthalate, and tributyltin chloride, respectively, and, therefore, holds promise as a biological verification model in grouping and read across approaches. The relevance of toxicokinetic information is indicated. Copyright © 2014 Elsevier Inc. All rights reserved.

Sida tuberculata (Malvaceae): a study based on development of extractive system and in silico and in vitro properties

PubMed Central

da Rosa, H.S.; Salgueiro, A.C.F.; Colpo, A.Z.C.; Paula, F.R.; Mendez, A.S.L.; Folmer, V.

2016-01-01

Sida tuberculata (Malvaceae) is a medicinal plant traditionally used in Brazil as an antimicrobial and anti-inflammatory agent. Here, we aimed to investigate the different extractive techniques on phytochemical parameters, as well as to evaluate the toxicity and antioxidant capacity of S. tuberculata extracts using in silico and in vitro models. Therefore, in order to determine the dry residue content and the main compound 20-hydroxyecdysone (20E) concentration, extracts from leaves and roots were prepared testing ethanol and water in different proportions. Extracts were then assessed by Artemia salina lethality test, and toxicity prediction of 20E was estimated. Antioxidant activity was performed by DPPH and ABTS radical scavenger assays, ferric reducing power assay, nitrogen derivative scavenger, deoxyribose degradation, and TBARS assays. HPLC evaluation detected 20E as main compound in leaves and roots. Percolation method showed the highest concentrations of 20E (0.134 and 0.096 mg/mL of extract for leaves and roots, respectively). All crude extracts presented low toxic potential on A. salina (LD50 >1000 µg/mL). The computational evaluation of 20E showed a low toxicity prediction. For in vitro antioxidant tests, hydroethanolic extracts of leaves were most effective compared to roots. In addition, hydroethanolic extracts presented a higher IC50 antioxidant than aqueous extracts. TBARS formation was prevented by leaves hydroethanolic extract from 0.015 and 0.03 mg/mL and for roots from 0.03 and 0.3 mg/mL on egg yolk and rat tissue, respectively (P<0.05). These findings suggest that S. tuberculata extracts are a considerable source of ecdysteroids and possesses a significant antioxidant property with low toxic potential. PMID:27409335

Sida tuberculata (Malvaceae): a study based on development of extractive system and in silico and in vitro properties.

PubMed

da Rosa, H S; Salgueiro, A C F; Colpo, A Z C; Paula, F R; Mendez, A S L; Folmer, V

2016-07-11

Sida tuberculata (Malvaceae) is a medicinal plant traditionally used in Brazil as an antimicrobial and anti-inflammatory agent. Here, we aimed to investigate the different extractive techniques on phytochemical parameters, as well as to evaluate the toxicity and antioxidant capacity of S. tuberculata extracts using in silico and in vitro models. Therefore, in order to determine the dry residue content and the main compound 20-hydroxyecdysone (20E) concentration, extracts from leaves and roots were prepared testing ethanol and water in different proportions. Extracts were then assessed by Artemia salina lethality test, and toxicity prediction of 20E was estimated. Antioxidant activity was performed by DPPH and ABTS radical scavenger assays, ferric reducing power assay, nitrogen derivative scavenger, deoxyribose degradation, and TBARS assays. HPLC evaluation detected 20E as main compound in leaves and roots. Percolation method showed the highest concentrations of 20E (0.134 and 0.096 mg/mL of extract for leaves and roots, respectively). All crude extracts presented low toxic potential on A. salina (LD50 >1000 µg/mL). The computational evaluation of 20E showed a low toxicity prediction. For in vitro antioxidant tests, hydroethanolic extracts of leaves were most effective compared to roots. In addition, hydroethanolic extracts presented a higher IC50 antioxidant than aqueous extracts. TBARS formation was prevented by leaves hydroethanolic extract from 0.015 and 0.03 mg/mL and for roots from 0.03 and 0.3 mg/mL on egg yolk and rat tissue, respectively (P<0.05). These findings suggest that S. tuberculata extracts are a considerable source of ecdysteroids and possesses a significant antioxidant property with low toxic potential.

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

SEURAT: Safety Evaluation Ultimately Replacing Animal Testing--recommendations for future research in the field of predictive toxicology.

PubMed

Daston, George; Knight, Derek J; Schwarz, Michael; Gocht, Tilman; Thomas, Russell S; Mahony, Catherine; Whelan, Maurice

2015-01-01

The development of non-animal methodology to evaluate the potential for a chemical to cause systemic toxicity is one of the grand challenges of modern science. The European research programme SEURAT is active in this field and will conclude its first phase, SEURAT-1, in December 2015. Drawing on the experience gained in SEURAT-1 and appreciating international advancement in both basic and regulatory science, we reflect here on how SEURAT should evolve and propose that further research and development should be directed along two complementary and interconnecting work streams. The first work stream would focus on developing new 'paradigm' approaches for regulatory science. The goal here is the identification of 'critical biological targets' relevant for toxicity and to test their suitability to be used as anchors for predicting toxicity. The second work stream would focus on integration and application of new approach methods for hazard (and risk) assessment within the current regulatory 'paradigm', aiming for acceptance of animal-free testing strategies by regulatory authorities (i.e. translating scientific achievements into regulation). Components for both work streams are discussed and may provide a structure for a future research programme in the field of predictive toxicology.

Predictive Model of Systemic Toxicity (SOT)

EPA Science Inventory

In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

ToxCast Chemical Landscape: Paving the Road to 21st Century Toxicology.

PubMed

Richard, Ann M; Judson, Richard S; Houck, Keith A; Grulke, Christopher M; Volarath, Patra; Thillainadarajah, Inthirany; Yang, Chihae; Rathman, James; Martin, Matthew T; Wambaugh, John F; Knudsen, Thomas B; Kancherla, Jayaram; Mansouri, Kamel; Patlewicz, Grace; Williams, Antony J; Little, Stephen B; Crofton, Kevin M; Thomas, Russell S

2016-08-15

The U.S. Environmental Protection Agency's (EPA) ToxCast program is testing a large library of Agency-relevant chemicals using in vitro high-throughput screening (HTS) approaches to support the development of improved toxicity prediction models. Launched in 2007, Phase I of the program screened 310 chemicals, mostly pesticides, across hundreds of ToxCast assay end points. In Phase II, the ToxCast library was expanded to 1878 chemicals, culminating in the public release of screening data at the end of 2013. Subsequent expansion in Phase III has resulted in more than 3800 chemicals actively undergoing ToxCast screening, 96% of which are also being screened in the multi-Agency Tox21 project. The chemical library unpinning these efforts plays a central role in defining the scope and potential application of ToxCast HTS results. The history of the phased construction of EPA's ToxCast library is reviewed, followed by a survey of the library contents from several different vantage points. CAS Registry Numbers are used to assess ToxCast library coverage of important toxicity, regulatory, and exposure inventories. Structure-based representations of ToxCast chemicals are then used to compute physicochemical properties, substructural features, and structural alerts for toxicity and biotransformation. Cheminformatics approaches using these varied representations are applied to defining the boundaries of HTS testability, evaluating chemical diversity, and comparing the ToxCast library to potential target application inventories, such as used in EPA's Endocrine Disruption Screening Program (EDSP). Through several examples, the ToxCast chemical library is demonstrated to provide comprehensive coverage of the knowledge domains and target inventories of potential interest to EPA. Furthermore, the varied representations and approaches presented here define local chemistry domains potentially worthy of further investigation (e.g., not currently covered in the testing library or defined by toxicity "alerts") to strategically support data mining and predictive toxicology modeling moving forward.

Androgen receptor mediated compensation of estradiol in response to aromatase inhibition: a mathematical model

EPA Science Inventory

Chemicals in the environment have the potential to cause reproductive toxicity by acting on the hypothalamus-pituitary-gonadal (HPG) axis. We have developed a mathematical model to predict chemical impacts on reproductive hormone production in the highly conserved HPG axis using...

Overview of the ToxCast Research Program: Applications to Predictive Toxicology and Chemical Prioritization (SETAC)

EPA Science Inventory

Understanding the potential health risks posed by environmental chemicals is a significant challenge driven by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms and toxicities. The U.S. EPA’s ToxCast chemical prioritization research projec...

A computational approach for predicting off-target toxicity of antiviral ribonucleoside analogues to mitochondrial RNA polymerase.

PubMed

Freedman, Holly; Winter, Philip; Tuszynski, Jack; Tyrrell, D Lorne; Houghton, Michael

2018-06-22

In the development of antiviral drugs that target viral RNA-dependent RNA polymerases, off-target toxicity caused by the inhibition of the human mitochondrial RNA polymerase (POLRMT) is a major liability. Therefore, it is essential that all new ribonucleoside analogue drugs be accurately screened for POLRMT inhibition. A computational tool that can accurately predict NTP binding to POLRMT could assist in evaluating any potential toxicity and in designing possible salvaging strategies. Using the available crystal structure of POLRMT bound to an RNA transcript, here we created a model of POLRMT with an NTP molecule bound in the active site. Furthermore, we implemented a computational screening procedure that determines the relative binding free energy of an NTP analogue to POLRMT by free energy perturbation (FEP), i.e. a simulation in which the natural NTP molecule is slowly transformed into the analogue and back. In each direction, the transformation was performed over 40 ns of simulation on our IBM Blue Gene Q supercomputer. This procedure was validated across a panel of drugs for which experimental dissociation constants were available, showing that NTP relative binding free energies could be predicted to within 0.97 kcal/mol of the experimental values on average. These results demonstrate for the first time that free-energy simulation can be a useful tool for predicting binding affinities of NTP analogues to a polymerase. We expect that our model, together with similar models of viral polymerases, will be very useful in the screening and future design of NTP inhibitors of viral polymerases that have no mitochondrial toxicity. © 2018 Freedman et al.

The clinical development of p53-reactivating drugs in sarcomas - charting future therapeutic approaches and understanding the clinical molecular toxicology of Nutlins.

PubMed

Biswas, Swethajit; Killick, Emma; Jochemsen, Aart G; Lunec, John

2014-05-01

The majority of human sarcomas, particularly soft tissue sarcomas, are relatively resistant to traditional cytotoxic therapies. The proof-of-concept study by Ray-Coquard et al., using the Nutlin human double minute (HDM)2-binding antagonist RG7112, has recently opened a new chapter in the molecular targeting of human sarcomas. In this review, the authors discuss the challenges and prospective remedies for minimizing the significant haematological toxicities of the cis-imidazole Nutlin HDM2-binding antagonists. Furthermore, they also chart the future direction of the development of p53-reactivating (p53-RA) drugs in 12q13-15 amplicon sarcomas and as potential chemopreventative therapies against sarcomagenesis in germ line mutated TP53 carriers. Drawing lessons from the therapeutic use of Imatinib in gastrointestinal tumours, the authors predict the potential pitfalls, which may lie in ahead for the future clinical development of p53-RA agents, as well as discussing potential non-invasive methods to identify the development of drug resistance. Medicinal chemistry strategies, based on structure-based drug design, are required to re-engineer cis-imidazoline Nutlin HDM2-binding antagonists into less haematologically toxic drugs. In silico modelling is also required to predict toxicities of other p53-RA drugs at a much earlier stage in drug development. Whether p53-RA drugs will be therapeutically effective as a monotherapy remains to be determined.

Ecotoxicological assessment of the potential impact on soil porewater, surface and groundwater from the use of organic wastes as soil amendments.

PubMed

Alvarenga, Paula; Mourinha, Clarisse; Farto, Márcia; Palma, Patrícia; Sengo, Joana; Morais, Marie-Christine; Cunha-Queda, Cristina

2016-04-01

This study aimed to assess the potential impact on soil porewater, surface and groundwater from the beneficial application of organic wastes to soil, using their eluates and acute bioassays with aquatic organisms and plants: luminescence inhibition of Vibrio fischeri (15 and 30 min), Daphnia magna immobilization (48 h), Thamnocephalus platyurus survival (24 h), and seed germination of Lolium perenne (7 d) and Lactuca sativa (5 d). Some organic wastes' eluates promoted high toxic responses, but that toxicity could not be predicted by their chemical characterization, which is compulsory by regulatory documents. In fact, when organisms were exposed to the water-extractable chemical compounds of the organic wastes, the toxic responses were more connected to the degree of stabilization of the organic wastes, or to the treatment used to achieve that stabilization, than to their contaminant load. That is why the environmental risk assessment of the use of organic wastes as soil amendments should integrate bioassays with eluates, in order to correctly evaluate the effects of the most bioavailable fraction of all the chemical compounds, which can be difficult to predict from the characterization required in regulatory documents. According to our results, some rapid and standardized acute bioassays can be suggested to integrate a Tier 1 ecotoxicological evaluation of organic wastes with potential to be land applied, namely luminescence inhibition of V. fischeri, D. magna immobilization, and the germination of L. perenne and L. sativa. Copyright © 2015 Elsevier Inc. All rights reserved.

A zeta potential value determines the aggregate's size of penta-substituted [60]fullerene derivatives in aqueous suspension whereas positive charge is required for toxicity against bacterial cells.

PubMed

Deryabin, Dmitry G; Efremova, Ludmila V; Vasilchenko, Alexey S; Saidakova, Evgeniya V; Sizova, Elena A; Troshin, Pavel A; Zhilenkov, Alexander V; Khakina, Ekaterina A; Khakina, Ekaterina E

2015-08-08

The cause-effect relationships between physicochemical properties of amphiphilic [60]fullerene derivatives and their toxicity against bacterial cells have not yet been clarified. In this study, we report how the differences in the chemical structure of organic addends in 10 originally synthesized penta-substituted [60]fullerene derivatives modulate their zeta potential and aggregate's size in salt-free and salt-added aqueous suspensions as well as how these physicochemical characteristics affect the bioenergetics of freshwater Escherichia coli and marine Photobacterium phosphoreum bacteria. Dynamic light scattering, laser Doppler micro-electrophoresis, agarose gel electrophoresis, atomic force microscopy, and bioluminescence inhibition assay were used to characterize the fullerene aggregation behavior in aqueous solution and their interaction with the bacterial cell surface, following zeta potential changes and toxic effects. Dynamic light scattering results indicated the formation of self-assembled [60]fullerene aggregates in aqueous suspensions. The measurement of the zeta potential of the particles revealed that they have different surface charges. The relationship between these physicochemical characteristics was presented as an exponential regression that correctly described the dependence of the aggregate's size of penta-substituted [60]fullerene derivatives in salt-free aqueous suspension from zeta potential value. The prevalence of DLVO-related effects was shown in salt-added aqueous suspension that decreased zeta potential values and affected the aggregation of [60]fullerene derivatives expressed differently for individual compounds. A bioluminescence inhibition assay demonstrated that the toxic effect of [60]fullerene derivatives against E. coli cells was strictly determined by their positive zeta potential charge value being weakened against P. phosphoreum cells in an aquatic system of high salinity. Atomic force microscopy data suggested that the activity of positively charged [60]fullerene derivatives against bacterial cells required their direct interaction. The following zeta potential inversion on the bacterial cells surface was observed as an early stage of toxicity mechanism that violates the membrane-associated energetic functions. The novel data about interrelations between physicochemical parameters and toxic properties of amphiphilic [60]fullerene derivatives make possible predicting their behavior in aquatic environment and their activity against bacterial cells.

Optimization of Hyalella azteca IQ Toxicity Test{trademark} for prediction of 28-day sediment toxicity tests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novotny, A.N.; Ezzard, C.L.; Douglas, W.S.

1995-12-31

The IQ Toxicity Test, which is a rapid screening toxicity test consisting of the observation of in-vivo inhibition of an enzymatic process using a fluorescent substrate, has proven successful for the determination of 24 and 48-hour EC50`s of D. magna, C. dubia, D. pulex and M. bahia. The application of this concept to utilize the freshwater amphipod Hyalella azteca may be an excellent way in which to reduce the standard 28-day chronic sediment toxicity test to possibly one hour`s time. This study incorporates an additive experimental design to explore the effects of and interactions between five specific variables: size ofmore » the amphipod, exposure time to the toxicant, concentration of substrate, exposure time to the substrate, and length of time starved prior to testing. The results of the IQ toxicity test were compared to those of a 28-day chronic sediment toxicity test. Preliminary data indicate that there is an optimal combination of these variables which results in a concise, reproducible toxicity test for use with Hyalella azteca, and would potentially be applicable to other freshwater amphipods in the future.« less

Oxidation of danofloxacin by free chlorine-kinetic study, structural identification of by-products by LC-MS/MS and potential toxicity of by-products using in silico test.

PubMed

Yassine, Montaha; Rifai, Ahmad; Doumyati, Samah; Trivella, Aurélien; Mazellier, Patrick; Budzinski, Hélène; Al Iskandarani, Mohamad

2017-03-01

In this study, we aimed to investigate the kinetics and the mechanism of reaction of the fluoroquinolone antibacterial danofloxacin (DANO) by free available chlorine (FAC) during water chlorination process. Kinetic study was thus performed at pH 7.2, 20 °C in the presence of an excess of total chlorine. Under these experimental conditions, a second-order reaction rate constant (first-order relative to DANO concentration and first-order relative to FAC concentration) was evaluated to k~1446 M -1  s -1 . Five degradation products were identified at different reaction times. Their structures were investigated by using fragmentations obtained at different CID collision energies in MS/MS experiments. Moreover, the toxicity of the proposed structures was predicted by using T.E.S.T. The results indicated that all by-products may have a developmental toxicity. The oral rat LD 50 concentration was predicted to be lower than that of DANO. Furthermore, two degradation compounds presented a concentration level for fathead minnow LC 50 (96 h) lower than that of DANO and presented toxicity for the marine animals.

An analysis of the use of dogs in predicting human toxicology and drug safety.

PubMed

Bailey, Jarrod; Thew, Michelle; Balls, Michael

2013-11-01

Dogs remain the main non-rodent species in preclinical drug development. Despite the current dearth of new drug approvals and meagre pipelines, this continues, with little supportive evidence of its value or necessity. To estimate the evidential weight provided by canine data to the probability that a new drug may be toxic to humans, we have calculated Likelihood Ratios (LRs) for an extensive dataset of 2,366 drugs with both animal and human data, including tissue-level effects and Medical Dictionary for Regulatory Activities (MedDRA) Level 1-4 biomedical observations. The resulting LRs show that the absence of toxicity in dogs provides virtually no evidence that adverse drug reactions (ADRs) will also be absent in humans. While the LRs suggest that the presence of toxic effects in dogs can provide considerable evidential weight for a risk of potential ADRs in humans, this is highly inconsistent, varying by over two orders of magnitude for different classes of compounds and their effects. Our results therefore have important implications for the value of the dog in predicting human toxicity, and suggest that alternative methods are urgently required. 2013 FRAME.

Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity

USGS Publications Warehouse

Fornaroli, Riccardo; Ippolito, Alessio; Tolkkinen, Mari J.; Mykrä, Heikki; Muotka, Timo; Balistrieri, Laurie S.; Schmidt, Travis S.

2018-01-01

One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters.

Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity.

PubMed

Fornaroli, Riccardo; Ippolito, Alessio; Tolkkinen, Mari J; Mykrä, Heikki; Muotka, Timo; Balistrieri, Laurie S; Schmidt, Travis S

2018-04-01

One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters. Copyright © 2018 Elsevier Ltd. All rights reserved.

LiverTox: Advanced QSAR and Toxicogeomic Software for Hepatotoxicity Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, P-Y.; Yuracko, K.

2011-02-25

YAHSGS LLC and Oak Ridge National Laboratory (ORNL) established a CRADA in an attempt to develop a predictive system using a pre-existing ORNL computational neural network and wavelets format. This was in the interest of addressing national needs for toxicity prediction system to help overcome the significant drain of resources (money and time) being directed toward developing chemical agents for commerce. The research project has been supported through an STTR mechanism and funded by the National Institute of Environmental Health Sciences beginning Phase I in 2004 (CRADA No. ORNL-04-0688) and extending Phase II through 2007 (ORNL NFE-06-00020). To attempt themore » research objectives and aims outlined under this CRADA, state-of-the-art computational neural network and wavelet methods were used in an effort to design a predictive toxicity system that used two independent areas on which to base the system’s predictions. These two areas were quantitative structure-activity relationships and gene-expression data obtained from microarrays. A third area, using the new Massively Parallel Signature Sequencing (MPSS) technology to assess gene expression, also was attempted but had to be dropped because the company holding the rights to this promising MPSS technology went out of business. A research-scale predictive toxicity database system called Multi-Intelligent System for Toxicogenomic Applications (MISTA) was developed and its feasibility for use as a predictor of toxicological activity was tested. The fundamental focus of the CRADA was an attempt and effort to operate the MISTA database using the ORNL neural network. This effort indicated the potential that such a fully developed system might be used to assist in predicting such biological endpoints as hepatotoxcity and neurotoxicity. The MISTA/LiverTox approach if eventually fully developed might also be useful for automatic processing of microarray data to predict modes of action. A technical paper describing the methods and technology used in the CRADA has been published. This paper was entitled “A Toxicity Evaluation and Predictive System Based on Neural Networks and Wavelets” and appeared in an American Chemical Society peer-reviewed publication this year (J. Chem. Inf. Model. 47: 676685, 2007). A patent application was filed but later abandoned.« less

Serum Creatinine Versus Plasma Methotrexate Levels to Predict Toxicities in Children Receiving High-dose Methotrexate.

PubMed

Tiwari, Priya; Thomas, M K; Pathania, Subha; Dhawan, Deepa; Gupta, Y K; Vishnubhatla, Sreenivas; Bakhshi, Sameer

2015-01-01

Facilities for measuring methotrexate (MTX) levels are not available everywhere, potentially limiting administration of high-dose methotrexate (HDMTX). We hypothesized that serum creatinine alteration after HDMTX administration predicts MTX clearance. Overall, 122 cycles in 50 patients of non-Hodgkin lymphoma or acute lymphoblastic leukemia aged ≤18 years receiving HDMTX were enrolled prospectively. Plasma MTX levels were measured at 12, 24, 36, 48, 60, and 72 hours; serum creatinine was measured at baseline, 24, 48, and 72 hours. Correlation of plasma MTX levels with creatinine levels and changes in creatinine from baseline (Δ creatinine) were evaluated. Plasma MTX levels at 72 hours showed positive correlation with serum creatinine at 48 hours (P = .011) and 72 hours (P = .013) as also Δ creatinine at 48 hours (P = .042) and 72 hours (P = .045). However, cut-off value of either creatinine or Δ creatinine could not be established to reliably predict delayed MTX clearance. Greater than 50% Δ creatinine at 48 and 72 hours significantly predicted grade 3/4 leucopenia (P = .036 and P = .001, respectively) and thrombocytopenia (P = .012 and P = .009, respectively) but not mucositis (P = .827 and P = .910, respectively). Delayed MTX elimination did not predict any grade 3/4 toxicity. In spite of demonstration of significant correlation between serum creatinine and Δ creatinine with plasma MTX levels at 72 hours, cut-off value of either variable to predict MTX delay could not be established. Thus, either of these cannot be used as a surrogate for plasma MTX estimation. Interestingly, Δ creatinine effectively predicted hematological toxicities, which were not predicted by delayed MTX clearance.

Comparison of adverse effects of proton and X-ray chemoradiotherapy for esophageal cancer using an adaptive dose-volume histogram analysis.

PubMed

Makishima, Hirokazu; Ishikawa, Hitoshi; Terunuma, Toshiyuki; Hashimoto, Takayuki; Yamanashi, Koichi; Sekiguchi, Takao; Mizumoto, Masashi; Okumura, Toshiyuki; Sakae, Takeji; Sakurai, Hideyuki

2015-05-01

Cardiopulmonary late toxicity is of concern in concurrent chemoradiotherapy (CCRT) for esophageal cancer. The aim of this study was to examine the benefit of proton beam therapy (PBT) using clinical data and adaptive dose-volume histogram (DVH) analysis. The subjects were 44 patients with esophageal cancer who underwent definitive CCRT using X-rays (n = 19) or protons (n = 25). Experimental recalculation using protons was performed for the patient actually treated with X-rays, and vice versa. Target coverage and dose constraints of normal tissues were conserved. Lung V5-V20, mean lung dose (MLD), and heart V30-V50 were compared for risk organ doses between experimental plans and actual treatment plans. Potential toxicity was estimated using protons in patients actually treated with X-rays, and vice versa. Pulmonary events of Grade ≥2 occurred in 8/44 cases (18%), and cardiac events were seen in 11 cases (25%). Risk organ doses in patients with events of Grade ≥2 were significantly higher than for those with events of Grade ≤1. Risk organ doses were lower in proton plans compared with X-ray plans. All patients suffering toxicity who were treated with X-rays (n = 13) had reduced predicted doses in lung and heart using protons, while doses in all patients treated with protons (n = 24) with toxicity of Grade ≤1 had worsened predicted toxicity with X-rays. Analysis of normal tissue complication probability showed a potential reduction in toxicity by using proton beams. Irradiation dose, volume and adverse effects on the heart and lung can be reduced using protons. Thus, PBT is a promising treatment modality for the management of esophageal cancer. © The Author 2015. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Classifying environmental pollutants: Part 3. External validation of the classification system.

PubMed

Verhaar, H J; Solbé, J; Speksnijder, J; van Leeuwen, C J; Hermens, J L

2000-04-01

In order to validate a classification system for the prediction of the toxic effect concentrations of organic environmental pollutants to fish, all available fish acute toxicity data were retrieved from the ECETOC database, a database of quality-evaluated aquatic toxicity measurements created and maintained by the European Centre for the Ecotoxicology and Toxicology of Chemicals. The individual chemicals for which these data were available were classified according to the rulebase under consideration and predictions of effect concentrations or ranges of possible effect concentrations were generated. These predictions were compared to the actual toxicity data retrieved from the database. The results of this comparison show that generally, the classification system provides adequate predictions of either the aquatic toxicity (class 1) or the possible range of toxicity (other classes) of organic compounds. A slight underestimation of effect concentrations occurs for some highly water soluble, reactive chemicals with low log K(ow) values. On the other end of the scale, some compounds that are classified as belonging to a relatively toxic class appear to belong to the so-called baseline toxicity compounds. For some of these, additional classification rules are proposed. Furthermore, some groups of compounds cannot be classified, although they should be amenable to predictions. For these compounds additional research as to class membership and associated prediction rules is proposed.

UV-visible degradation of boscalid--structural characterization of photoproducts and potential toxicity using in silico tests.

PubMed

Lassalle, Yannick; Kinani, Aziz; Rifai, Ahmad; Souissi, Yasmine; Clavaguera, Carine; Bourcier, Sophie; Jaber, Farouk; Bouchonnet, Stéphane

2014-05-30

Boscalid is a carboximide fungicide mainly used for vineyard protection as well as for tomato, apple, blueberry and various ornamental cultivations. The structural elucidation of by-products arising from the UV-visible photodegradation of boscalid has been investigated by gas chromatography/multi-stage mass spectrometry (GC/MS(n) ) and liquid chromatography/tandem mass spectrometry (LC/MS/MS) couplings. The potential toxicities of transformation products were estimated by in silico calculations. Aqueous solutions of boscalid were irradiated up to 150 min in a self-made reactor equipped with a mercury lamp. Analyses were carried out using a gas chromatograph coupled with an ion trap mass spectrometer operated in both electron ionization (EI) and chemical ionization (CI) modes and a liquid chromatograph coupled with a quadrupole time-of-flight (Q-TOF) mass spectrometer operated in electrospray ionization (ESI) mode. Multiple-stage collision-induced dissociation (CID) experiments were performed to establish dissociation pathways of ions. The QSAR (Quantitative Structure-Activity Relationship) T.E.S.T. program allowed the estimation of the toxicities of the by-products. Eight photoproducts were investigated. Chemical structures were proposed not only on the interpretation of multi-stage CID experiments, but also on kinetics data. These structures led us to suggest photodegradation pathways. Three photoproducts were finally detected in Lebanon in a real sample of grape leaves for which routine analysis had led to the detection of boscalid at 4 mg kg(-1). With one exception, the structures proposed for the photoproducts on the basis of mass spectra interpretation have not been reported in previous studies. In silico toxicity predictions showed that two photoproducts are potentially more toxic than the parent compound considering oral rat LD50 while five photoproducts may induce mutagenic toxicity. With the exception of one compound, all photoproducts may potentially induce developmental toxicity. Copyright © 2014 John Wiley & Sons, Ltd.

Computational embryology as an integrative platform for predictive DART (45th Conf of Europ Teratology Society)

EPA Science Inventory

Chemical regulation is challenged by the large number of chemicals requiring assessment for potential human health and environmental impacts. For example, the USEPA lists more than 85,000 chemicals on its inventory of substances that fall under the Toxic Substances Control Act (T...

Computational prediction of dermal diffusivity for large number of chemicals – challenges and applications

EPA Science Inventory

The assessment of risk from dermal exposure for thousands of chemicals, such as consumer products, due to their potential to enter the environment as contaminants is a daunting task. A strategy has been developed to integrate high-throughput technologies with toxicity, known as ...

20180312 - Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Points of Departure (SOT)

EPA Science Inventory

Due to the large quantity of new chemicals being developed and potentially introduced into aquatic ecosystems, there is a need to prioritize chemicals with the greatest likelihood of ecological hazard for further research. To this end, a useful in silico estimation of ecotoxicity...

ToxMiner: Relating ToxCast bioactivity profiles to phenotypic outcomes

EPA Science Inventory

One aim of the U.S. EPA ToxCast program is to develop predictive models that use in vitro assays to screen and prioritize environmental chemicals for further evaluation of potential toxicity. One aspect of this task is the compilation, quality control and analysis of large amount...

THE FUTURE OF COMPUTER-BASED TOXICITY PREDICTION: MECHANISM-BASED MODELS VS. INFORMATION MINING APPROACHES

EPA Science Inventory

The Future of Computer-Based Toxicity Prediction:
Mechanism-Based Models vs. Information Mining Approaches

When we speak of computer-based toxicity prediction, we are generally referring to a broad array of approaches which rely primarily upon chemical structure ...

ProTox: a web server for the in silico prediction of rodent oral toxicity

PubMed Central

Drwal, Malgorzata N.; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R.; Preissner, Robert

2014-01-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein–ligand-based pharmacophore models (‘toxicophores’) for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. PMID:24838562

Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients.

PubMed

Hisaki, Tomoka; Aiba Née Kaneko, Maki; Yamaguchi, Masahiko; Sasa, Hitoshi; Kouzuki, Hirokazu

2015-04-01

Use of laboratory animals for systemic toxicity testing is subject to strong ethical and regulatory constraints, but few alternatives are yet available. One possible approach to predict systemic toxicity of chemicals in the absence of experimental data is quantitative structure-activity relationship (QSAR) analysis. Here, we present QSAR models for prediction of maximum "no observed effect level" (NOEL) for repeated-dose, developmental and reproductive toxicities. NOEL values of 421 chemicals for repeated-dose toxicity, 315 for reproductive toxicity, and 156 for developmental toxicity were collected from Japan Existing Chemical Data Base (JECDB). Descriptors to predict toxicity were selected based on molecular orbital (MO) calculations, and QSAR models employing multiple independent descriptors as the input layer of an artificial neural network (ANN) were constructed to predict NOEL values. Robustness of the models was indicated by the root-mean-square (RMS) errors after 10-fold cross-validation (0.529 for repeated-dose, 0.508 for reproductive, and 0.558 for developmental toxicity). Evaluation of the models in terms of the percentages of predicted NOELs falling within factors of 2, 5 and 10 of the in-vivo-determined NOELs suggested that the model is applicable to both general chemicals and the subset of chemicals listed in International Nomenclature of Cosmetic Ingredients (INCI). Our results indicate that ANN models using in silico parameters have useful predictive performance, and should contribute to integrated risk assessment of systemic toxicity using a weight-of-evidence approach. Availability of predicted NOELs will allow calculation of the margin of safety, as recommended by the Scientific Committee on Consumer Safety (SCCS).

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling.

PubMed

Woodhead, Jeffrey L; Paech, Franziska; Maurer, Martina; Engelhardt, Marc; Schmitt-Hoffmann, Anne H; Spickermann, Jochen; Messner, Simon; Wind, Mathias; Witschi, Anne-Therese; Krähenbühl, Stephan; Siler, Scott Q; Watkins, Paul B; Howell, Brett A

2018-06-07

Elevations of liver enzymes have been observed in clinical trials with BAL30072, a novel antibiotic. In vitro assays have identified potential mechanisms for the observed hepatotoxicity, including electron transport chain (ETC) inhibition and reactive oxygen species (ROS) generation. DILIsym, a quantitative systems pharmacology (QSP) model of drug-induced liver injury, has been used to predict the likelihood that each mechanism explains the observed toxicity. DILIsym was also used to predict the safety margin for a novel BAL30072 dosing scheme; it was predicted to be low. DILIsym was then used to recommend potential modifications to this dosing scheme; weight-adjusted dosing and a requirement to assay plasma alanine aminotransferase (ALT) daily and stop dosing as soon as ALT increases were observed improved the predicted safety margin of BAL30072 and decreased the predicted likelihood of severe injury. This research demonstrates a potential application for QSP modeling in improving the safety profile of candidate drugs. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

PubMed

Qin, Li-Tang; Chen, Yu-Han; Zhang, Xin; Mo, Ling-Yun; Zeng, Hong-Hu; Liang, Yan-Peng

2018-05-01

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC 50 ) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Effects of Temperature and Hydrostatic Pressure on Metal Toxicity: Insights into Toxicity in the Deep Sea.

PubMed

Brown, Alastair; Thatje, Sven; Hauton, Chris

2017-09-05

Mineral prospecting in the deep sea is increasing, promoting concern regarding potential ecotoxicological impacts on deep-sea fauna. Technological difficulties in assessing toxicity in deep-sea species has promoted interest in developing shallow-water ecotoxicological proxy species. However, it is unclear how the low temperature and high hydrostatic pressure prevalent in the deep sea affect toxicity, and whether adaptation to deep-sea environmental conditions moderates any effects of these factors. To address these uncertainties we assessed the effects of temperature and hydrostatic pressure on lethal and sublethal (respiration rate, antioxidant enzyme activity) toxicity in acute (96 h) copper and cadmium exposures, using the shallow-water ecophysiological model organism Palaemon varians. Low temperature reduced toxicity in both metals, but reduced cadmium toxicity significantly more. In contrast, elevated hydrostatic pressure increased copper toxicity, but did not affect cadmium toxicity. The synergistic interaction between copper and cadmium was not affected by low temperature, but high hydrostatic pressure significantly enhanced the synergism. Differential environmental effects on toxicity suggest different mechanisms of action for copper and cadmium, and highlight that mechanistic understanding of toxicity is fundamental to predicting environmental effects on toxicity. Although results infer that sensitivity to toxicants differs across biogeographic ranges, shallow-water species may be suitable ecotoxicological proxies for deep-sea species, dependent on adaptation to habitats with similar environmental variability.

Potential Health Impact of Environmentally Released Micro- and Nanoplastics in the Human Food Production Chain: Experiences from Nanotoxicology.

PubMed

Bouwmeester, Hans; Hollman, Peter C H; Peters, Ruud J B

2015-08-04

High concentrations of plastic debris have been observed in the oceans. Much of the recent concern has focused on microplastics in the marine environment. Recent studies of the size distribution of the plastic debris suggested that continued fragmenting of microplastics into nanosized particles may occur. In this review we assess the current literature on the occurrence of environmentally released micro- and nanoplastics in the human food production chain and their potential health impact. The currently used analytical techniques introduce a great bias in the knowledge, since they are only able to detect plastic particles well above the nanorange. We discuss the potential use of the very sensitive analytical techniques that have been developed for the detection and quantification of engineered nanoparticles. We recognize three possible toxic effects of plastic particles: first due to the plastic particles themselves, second to the release of persistent organic pollutant adsorbed to the plastics, and third to the leaching of additives of the plastics. The limited data on microplastics in foods do not predict adverse effect of these pollutants or additives. Potential toxic effects of microplastic particles will be confined to the gut. The potential human toxicity of nanoplastics is poorly studied. Based on our experiences in nanotoxicology we prioritized future research questions.

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Assessing interactions of binary mixtures of Penicillium mycotoxins (PMs) by using a bovine macrophage cell line (BoMacs)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oh, Se-Young, E-mail: ohs@uoguelph.ca

Penicillium mycotoxins (PMs) are toxic contaminants commonly found as mixtures in animal feed. Therefore, it is important to investigate potential joint toxicity of PM mixtures. In the present study, we assessed the joint effect of binary combinations of the following PMs: citrinin (CIT), ochratoxin A (OTA), patulin (PAT), mycophenolic acid (MPA) and penicillic acid (PA) using independent action (IA) and concentration addition (CA) concepts. Previously published toxicity data (i.e. IC25; PM concentration that inhibited bovine macrophage (BoMacs) proliferation by 25%) were initially analyzed, and both concepts agreed that OTA + PA demonstrated synergism (p < 0.05), while PAT + PAmore » showed antagonism (p < 0.05). When a follow-up dilution study was carried out using binary combinations of PMs at three different dilution levels (i.e. IC25, 0.5 ∗ IC25, 0.25 ∗ IC25), only the mixture of CIT + OTA at 0.5 ∗ IC25 was determined to have synergism by both IA and CA concepts with Model Deviation Ratios (MDRs; the ratio of predicted versus observed effect concentrations) of 1.4 and 1.7, respectively. The joint effect of OTA + MPA, OTA + PA and CIT + PAT complied with the IA concept, while CIT + PA, PAT + MPA and PAT + PA were better predicted with the CA over the IA concept. The present study suggests to test both IA and CA concepts using multiple doses when assessing risk of mycotoxin mixtures if the mode of action is unknown. In addition, the study showed that the tested PMs could be predicted by IA or CA within an approximate two-fold certainty, raising the possibility for a joint risk assessment of mycotoxins in food and feed. - Highlights: • We investigated the potential joint toxicity of Penicillium mycotoxin (PM) mixtures. • Independent action (IA) and concentration addition (CA) concepts were used. • 7 out of 10 mixtures followed joint toxicity described by IA or CA concepts. • Both concepts agreed that CIT + OTA mixture had synergistic interaction.« less

Pesticides drive risk of micropollutants in wastewater-impacted streams during low flow conditions.

PubMed

Munz, Nicole A; Burdon, Francis J; de Zwart, Dick; Junghans, Marion; Melo, Laura; Reyes, Marta; Schönenberger, Urs; Singer, Heinz P; Spycher, Barbara; Hollender, Juliane; Stamm, Christian

2017-03-01

Micropollutants enter surface waters through various pathways, of which wastewater treatment plants (WWTPs) are a major source. The large diversity of micropollutants and their many modes of toxic action pose a challenge for assessing environmental risks. In this study, we investigated the potential impact of WWTPs on receiving ecosystems by describing concentration patterns of micropollutants, predicting acute risks for aquatic organisms and validating these results with macroinvertebrate biomonitoring data. Grab samples were taken upstream, downstream and at the effluent of 24 Swiss WWTPs during low flow conditions across independent catchments with different land uses. Using liquid chromatography high resolution tandem mass spectrometry, a comprehensive target screening of almost 400 organic substances, focusing mainly on pesticides and pharmaceuticals, was conducted at two time points, and complemented with the analysis of a priority mixture of 57 substances over eight time points. Acute toxic pressure was predicted using the risk assessment approach of the multi-substance potentially affected fraction, first applying concentration addition for substances with the same toxic mode of action and subsequently response addition for the calculation of the risk of the total mixture. This toxic pressure was compared to macroinvertebrate sensitivity to pesticides (SPEAR index) upstream and downstream of the WWTPs. The concentrations were, as expected, especially for pharmaceuticals and other household chemicals higher downstream than upstream, with the detection frequency of plant protection products upstream correlating with the fraction of arable land in the catchments. While the concentration sums downstream were clearly dominated by pharmaceuticals or other household chemicals, the acute toxic pressure was mainly driven by pesticides, often caused by the episodic occurrence of these compounds even during low flow conditions. In general, five single substances explained much of the total risk, with diclofenac, diazinon and clothianidin as the main drivers. Despite the low predicted acute risk of 0%-2.1% for affected species, a significant positive correlation with macroinvertebrate sensitivity to pesticides was observed. However, more effect data for pharmaceuticals and a better quantification of episodic pesticide pollution events are needed for a more comprehensive risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Toxico-Cheminformatics: New and Expanding Public ...

EPA Pesticide Factsheets

High-throughput screening (HTS) technologies, along with efforts to improve public access to chemical toxicity information resources and to systematize older toxicity studies, have the potential to significantly improve information gathering efforts for chemical assessments and predictive capabilities in toxicology. Important developments include: 1) large and growing public resources that link chemical structures to biological activity and toxicity data in searchable format, and that offer more nuanced and varied representations of activity; 2) standardized relational data models that capture relevant details of chemical treatment and effects of published in vivo experiments; and 3) the generation of large amounts of new data from public efforts that are employing HTS technologies to probe a wide range of bioactivity and cellular processes across large swaths of chemical space. By annotating toxicity data with associated chemical structure information, these efforts link data across diverse study domains (e.g., ‘omics’, HTS, traditional toxicity studies), toxicity domains (carcinogenicity, developmental toxicity, neurotoxicity, immunotoxicity, etc) and database sources (EPA, FDA, NCI, DSSTox, PubChem, GEO, ArrayExpress, etc.). Public initiatives are developing systematized data models of toxicity study areas and introducing standardized templates, controlled vocabularies, hierarchical organization, and powerful relational searching capability across capt

Effects of gamma radiation on cork wastewater: Antioxidant activity and toxicity.

PubMed

Madureira, Joana; Pimenta, Andreia I; Popescu, Larisa; Besleaga, Alexandra; Dias, Maria Inês; Santos, Pedro M P; Melo, Rita; Ferreira, Isabel C F R; Cabo Verde, Sandra; Margaça, Fernanda M A

2017-02-01

A comprehensive assessment of the toxicity and antioxidant activity of cork boiling wastewater and the effects of gamma radiation on these parameters was performed. Antioxidant activity was evaluated using different methodologies as DPPH radical scavenging activity, reducing power and inhibition of β-carotene bleaching. The results have shown that gamma radiation can induce an increase on the antioxidant activity of cork boiling wastewater. Toxicity tests were performed to access the potential added value of the irradiated wastewaters and/or minimization of the impact for discharge in the environment. Two different methods for toxicity evaluation were followed, bacterial growth inhibition test and cytotoxicity assay, in order to predict the behavior of different cells (prokaryotic and eukaryotic) in the presence of cork wastewater. Non-treated cork boiling wastewater seemed to be non-toxic for prokaryotic cells (Pseudomonas fluorescens and Bacillus subtilis) but toxic for eukaryotic cells (A549 human cells and RAW264.7 mouse cells). The gamma radiation treatment at doses of 100 kGy appeared to increase the toxicity of cork compounds for all tested cells, which could be related to a toxic effect of radiolytic products of cork compounds in the wastewaters. Copyright © 2016 Elsevier Ltd. All rights reserved.

Potential toxicity of pesticides measured in midwestern streams to aquatic organisms

USGS Publications Warehouse

Battaglin, W.; Fairchild, J.

2002-01-01

Society is becoming increasingly aware of the value of healthy aquatic ecosystems as well as the effects that man’s activities have on those ecosystems. In recent years, many urban and industrial sources of contamination have been reduced or eliminated. The agricultural community also has worked towards reducing off-site movement of agricultural chemicals, but their use in farming is still growing. A small fraction, estimated at <1 to 2% of the pesticides applied to crops are lost from fields and enter nearby streams during rainfall events. In many cases aquatic organisms are exposed to mixtures of chemicals, which may lead to greater non-target risk than that predicted based on traditional risk assessments for single chemicals. We evaluated the potential toxicity of environmental mixtures of 5 classes of pesticides using concentrations from water samples collected from ∼50 sites on midwestern streams during late spring or early summer runoff events in 1989 and 1998. Toxicity index values are calculated as the concentration of the compound in the sample divided by the EC50 or LC50 of an aquatic organism. These index values are summed within a pesticide class and for all classes to determine additive pesticide class and total pesticide toxicity indices. Toxicity index values greater than 1.0 indicate probable toxicity of a class of pesticides measured in a water sample to aquatic organisms. Results indicate that some samples had probable toxicity to duckweed and green algae, but few are suspected of having significant toxicity to bluegill sunfish or chorus frogs.

Lung deposition analyses of inhaled toxic aerosols in conventional and less harmful cigarette smoke: a review.

PubMed

Kleinstreuer, Clement; Feng, Yu

2013-09-23

Inhaled toxic aerosols of conventional cigarette smoke may impact not only the health of smokers, but also those exposed to second-stream smoke, especially children. Thus, less harmful cigarettes (LHCs), also called potential reduced exposure products (PREPs), or modified risk tobacco products (MRTP) have been designed by tobacco manufacturers to focus on the reduction of the concentration of carcinogenic components and toxicants in tobacco. However, some studies have pointed out that the new cigarette products may be actually more harmful than the conventional ones due to variations in puffing or post-puffing behavior, different physical and chemical characteristics of inhaled toxic aerosols, and longer exposure conditions. In order to understand the toxicological impact of tobacco smoke, it is essential for scientists, engineers and manufacturers to develop experiments, clinical investigations, and predictive numerical models for tracking the intake and deposition of toxicants of both LHCs and conventional cigarettes. Furthermore, to link inhaled toxicants to lung and other diseases, it is necessary to determine the physical mechanisms and parameters that have significant impacts on droplet/vapor transport and deposition. Complex mechanisms include droplet coagulation, hygroscopic growth, condensation and evaporation, vapor formation and changes in composition. Of interest are also different puffing behavior, smoke inlet conditions, subject geometries, and mass transfer of deposited material into systemic regions. This review article is intended to serve as an overview of contributions mainly published between 2009 and 2013, focusing on the potential health risks of toxicants in cigarette smoke, progress made in different approaches of impact analyses for inhaled toxic aerosols, as well as challenges and future directions.

Predicting pulmonary fibrosis in humans after exposure to multi-walled carbon nanotubes (MWCNTs).

PubMed

Sharma, Monita; Nikota, Jake; Halappanavar, Sabina; Castranova, Vincent; Rothen-Rutishauser, Barbara; Clippinger, Amy J

2016-07-01

The increased production and use of multi-walled carbon nanotubes (MWCNTs) in a diverse array of consumer, medical, and industrial applications have raised concerns about potential human exposure to these materials in the workplace and ambient environments. Inhalation is a primary route of exposure to MWCNTs, and the existing data indicate that they are potentially hazardous to human health. While a 90-day rodent inhalation test (e.g., OECD Test No. 413: subchronic inhalation toxicity: 90-day study or EPA Health Effects Test Guidelines OPPTS 870.3465 90-day inhalation toxicity) is recommended by the U.S. Environmental Protection Agency Office of Pollution Prevention and Toxics for MWCNTs (and other CNTs) if they are to be commercially produced (Godwin et al. in ACS Nano 9:3409-3417, 2015), this test is time and cost-intensive and subject to scientific and ethical concerns. As a result, there has been much interest in transitioning away from studies on animals and moving toward human-based in vitro and in silico models. However, given the multiple mechanisms of toxicity associated with subchronic exposure to inhaled MWCNTs, a battery of non-animal tests will likely be needed to evaluate the key endpoints assessed by the 90-day rodent study. Pulmonary fibrosis is an important adverse outcome related to inhalation exposure to MWCNTs and one that the non-animal approach should be able to assess. This review summarizes the state-of-the-science regarding in vivo and in vitro toxicological methods for predicting MWCNT-induced pulmonary fibrosis.

PREDICTING CHRONIC TOXICITY OF CHEMICALS TO FISHES FROM ACUTE TOXICITY TEST DATA: CONCEPT AND LINEAR REGRESSION

EPA Science Inventory

A comprehensive approach to predicting chronic toxicity from acute.toxicity data was developed in which simultaneous consideration is given to concentration, degree of response, and time course of effect. onsistent endpoint (lethality) and degree of response (O%) were used to com...

STATISTICAL APPROACH TO PREDICTING CHRONIC TOXICITY OF CHEMICALS TO FISHES FROM ACUTE TOXICITY TEST DATA

EPA Science Inventory

A comprehensive approach to predicting chronic toxicity from cute toxicity data was developed in which simultaneous onsideration is given to concentration, degree of response, and ime course of effect. onsistent endpoint (lethality) and degree of response (0 percent) were used to...

MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development (SETAC abstract)

EPA Science Inventory

The mode of toxic action (MOA) has been recognized as a key determinant of chemical toxicity and as an alternative to chemical class-based predictive toxicity modeling. However, the development of quantitative structure activity relationship (QSAR) and other models has been limit...

MOAtox: A Comprehensive Mode of Action and Acute Aquatic Toxicity Database for Predictive Model Development

EPA Science Inventory

tThe mode of toxic action (MOA) has been recognized as a key determinant of chemical toxicity andas an alternative to chemical class-based predictive toxicity modeling. However, the development ofquantitative structure activity relationship (QSAR) and other models has been limite...

Sediment nickel bioavailability and toxicity to estuarine crustaceans of contrasting bioturbative behaviors--an evaluation of the SEM-AVS paradigm.

PubMed

Chandler, G Thomas; Schlekat, Christian E; Garman, Emily R; He, Lijian; Washburn, Katherine M; Stewart, Emily R; Ferry, John L

2014-11-04

Robust sediment quality criteria require chemistry and toxicity data predictive of concentrations where population/community response should occur under known geochemical conditions. Understanding kinetic and geochemical effects on toxicant bioavailability is key, and these are influenced by infaunal sediment bioturbation. This study used fine-scale sediment and porewater measurement of contrasting infaunal effects on carbon-normalized SEM-AVS to evaluate safe or potentially toxic nickel concentrations in a high-binding Spartina saltmarsh sediment (4%TOC; 35-45 μmol-S2-·g(-1)). Two crustaceans producing sharply contrasting bioturbation--the copepod Amphiascus tenuiremis and amphipod Leptocheirus plumulosus--were cultured in oxic to anoxic sediments with SEM[Ni]-AVS, TOC, porewater [Ni], and porewater DOC measured weekly. From 180 to 750 μg-Ni·g(-1) sediment, amphipod bioturbation reduced [AVS] and enhanced porewater [Ni]. Significant amphipod uptake, mortality, and growth-depression occurred at the higher sediment [Ni] even when [SEM-AVS]/foc suggested acceptable risk. Less bioturbative copepods produced higher AVS and porewater DOC but exhibited net population growth despite porewater [Ni] 1.3-1.7× their aqueous [Ni] LOEC. Copepod aqueous tests with/without dissolved organic matter showed significant aqueous DOC protection, which suggests porewater DOC attenuates sediment Ni toxicity. The SEM[Ni]-AVS relationship was predictive of acceptable risk for copepods at the important population-growth level.

Toxicity Testing in the 21st Century Beyond Environmental Chemicals

PubMed Central

Rovida, Costanza; Asakura, Shoji; Daneshian, Mardas; Hofman-Huether, Hana; Leist, Marcel; Meunier, Leo; Reif, David; Rossi, Anna; Schmutz, Markus; Valentin, Jean-Pierre; Zurlo, Joanne; Hartung, Thomas

2018-01-01

Summary After the publication of the report titled Toxicity Testing in the 21st Century – A Vision and a Strategy, many initiatives started to foster a major paradigm shift for toxicity testing – from apical endpoints in animal-based tests to mechanistic endpoints through delineation of pathways of toxicity (PoT) in human cell based systems. The US EPA has funded an important project to develop new high throughput technologies based on human cell based in vitro technologies. These methods are currently being incorporated into the chemical risk assessment process. In the pharmaceutical industry, the efficacy and toxicity of new drugs are evaluated during preclinical investigations that include drug metabolism, pharmacokinetics, pharmacodynamics and safety toxicology studies. The results of these studies are analyzed and extrapolated to predict efficacy and potential adverse effects in humans. However, due to the high failure rate of drugs during the clinical phases, a new approach for a more predictive assessment of drugs both in terms of efficacy and adverse effects is getting urgent. The food industry faces the challenge of assessing novel foods and food ingredients for the general population, while using animal safety testing for extrapolation purposes is often of limited relevance. The question is whether the latest paradigm shift proposed by the Tox21c report for chemicals may provide a useful tool to improve the risk assessment approach also for drugs and food ingredients. PMID:26168280

Application of the target lipid model and passive samplers to characterize the toxicity of bioavailable organics in oil sands process-affected water.

PubMed

Redman, Aaron D; Parkerton, Thomas F; Butler, Josh David; Letinski, Daniel J; Frank, Richard A; Hewitt, L Mark; Bartlett, Adrienne J; Gillis, Patricia Leigh; Marentette, Julie R; Parrott, Joanne L; Hughes, Sarah A; Guest, Rodney; Bekele, Asfaw; Zhang, Kun; Morandi, Garrett; Wiseman, Steve B; Giesy, John P

2018-06-14

Oil sand operations in Alberta, Canada will eventually include returning treated process-affected waters to the environment. Organic constituents in oil sand process-affected water (OSPW) represent complex mixtures of nonionic and ionic (e.g. naphthenic acids) compounds, and compositions can vary spatially and temporally, which has impeded development of water quality benchmarks. To address this challenge, it was hypothesized that solid phase microextraction fibers coated with polydimethylsiloxane (PDMS) could be used as a biomimetic extraction (BE) to measure bioavailable organics in OSPW. Organic constituents of OSPW were assumed to contribute additively to toxicity, and partitioning to PDMS was assumed to be predictive of accumulation in target lipids, which were the presumed site of action. This method was tested using toxicity data for individual model compounds, defined mixtures, and organic mixtures extracted from OSPW. Toxicity was correlated with BE data, which supports the use of this method in hazard assessments of acute lethality to aquatic organisms. A species sensitivity distribution (SSD), based on target lipid model and BE values, was similar to SSDs based on residues in tissues for both nonionic and ionic organics. BE was shown to be an analytical tool that accounts for bioaccumulation of organic compound mixtures from which toxicity can be predicted, with the potential to aid in the development of water quality guidelines.

3D spheroid culture of hESC/hiPSC-derived hepatocyte-like cells for drug toxicity testing.

PubMed

Takayama, Kazuo; Kawabata, Kenji; Nagamoto, Yasuhito; Kishimoto, Keisuke; Tashiro, Katsuhisa; Sakurai, Fuminori; Tachibana, Masashi; Kanda, Katsuhiro; Hayakawa, Takao; Furue, Miho Kusuda; Mizuguchi, Hiroyuki

2013-02-01

Although it is expected that hepatocyte-like cells differentiated from human embryonic stem (ES) cells or induced pluripotent stem (iPS) cells will be utilized in drug toxicity testing, the actual applicability of hepatocyte-like cells in this context has not been well examined so far. To generate mature hepatocyte-like cells that would be applicable for drug toxicity testing, we established a hepatocyte differentiation method that employs not only stage-specific transient overexpression of hepatocyte-related transcription factors but also a three-dimensional spheroid culture system using a Nanopillar Plate. We succeeded in establishing protocol that could generate more matured hepatocyte-like cells than our previous protocol. In addition, our hepatocyte-like cells could sensitively predict drug-induced hepatotoxicity, including reactive metabolite-mediated toxicity. In conclusion, our hepatocyte-like cells differentiated from human ES cells or iPS cells have potential to be applied in drug toxicity testing. Copyright © 2012 Elsevier Ltd. All rights reserved.

A systematic review and meta-analysis of MTHFR polymorphisms in methotrexate toxicity prediction in pediatric acute lymphoblastic leukemia.

PubMed

Lopez-Lopez, E; Martin-Guerrero, I; Ballesteros, J; Garcia-Orad, A

2013-12-01

Methotrexate (MTX) is an important component of therapy used to treat childhood acute lymphoblastic leukemia (ALL). Two single-nucleotide polymorphisms (SNPs) in the methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, affect MTHFR activity. A large body of studies has investigated the potential role of MTHFR SNPs in MTX toxicity in pediatric ALL. However, the results are controversial. In this review and meta-analysis, we critically evaluate the relationship between the C677T and A1298C polymorphisms of MTHFR and MTX toxicity in pediatric ALL. The majority of published reports do not find associations between MTHFR polymorphisms and toxicity in pediatric ALL. When associations are reported, often the results are contradictory to each other. The meta-analysis confirms a lack of association. In conclusion, MTHFR, C677T and A1298C polymorphisms do not seem to be good markers of MTX-related toxicity in pediatric ALL.

(Q)SARs to predict environmental toxicities: current status and future needs.

PubMed

Cronin, Mark T D

2017-03-22

The current state of the art of (Quantitative) Structure-Activity Relationships ((Q)SARs) to predict environmental toxicity is assessed along with recommendations to develop these models further. The acute toxicity of compounds acting by the non-polar narcotic mechanism of action can be well predicted, however other approaches, including read-across, may be required for compounds acting by specific mechanisms of action. The chronic toxicity of compounds to environmental species is more difficult to predict from (Q)SARs, with robust data sets and more mechanistic information required. In addition, the toxicity of mixtures is little addressed by (Q)SAR approaches. Developments in environmental toxicology including Adverse Outcome Pathways (AOPs) and omics responses should be utilised to develop better, more mechanistically relevant, (Q)SAR models.

ProTox: a web server for the in silico prediction of rodent oral toxicity.

PubMed

Drwal, Malgorzata N; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R; Preissner, Robert

2014-07-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein-ligand-based pharmacophore models ('toxicophores') for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

PubMed

Ruiz, Patricia; Begluitti, Gino; Tincher, Terry; Wheeler, John; Mumtaz, Moiz

2012-07-27

Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance's database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (LD₅₀) for determining relative toxicity of a number of substances. In general, the smaller the LD₅₀ value, the more toxic the chemical, and the larger the LD₅₀ value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD₅₀ values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD₅₀ models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD₅₀ values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.

Toxicity of Water Accommodated Fractions of Estonian Shale Fuel Oils to Aquatic Organisms.

PubMed

Blinova, Irina; Kanarbik, Liina; Sihtmäe, Mariliis; Kahru, Anne

2016-02-01

Estonia is the worldwide leading producer of the fuel oils from the oil shale. We evaluated the ecotoxicity of water accommodated fraction (WAF) of two Estonian shale fuel oils ("VKG D" and "VKG sweet") to aquatic species belonging to different trophic levels (marine bacteria, freshwater crustaceans and aquatic plants). Artificial fresh water and natural lake water were used to prepare WAFs. "VKG sweet" (lower density) proved more toxic to aquatic species than "VKG D" (higher density). Our data indicate that though shale oils were very toxic to crustaceans, the short-term exposure of Daphnia magna to sub-lethal concentrations of shale fuel oils WAFs may increase the reproductive potential of survived organisms. The weak correlation between measured chemical parameters (C10-C40 hydrocarbons and sum of 16 PAHs) and WAF's toxicity to studied species indicates that such integrated chemical parameters are not very informative for prediction of shale fuel oils ecotoxicity.

Modeling of Toxicity-Relevant Electrophilic Reactivity for Guanine with Epoxides: Estimating the Hard and Soft Acids and Bases (HSAB) Parameter as a Predictor.

PubMed

Zhang, Jing; Wang, Chenchen; Ji, Li; Liu, Weiping

2016-05-16

According to the electrophilic theory in toxicology, many chemical carcinogens in the environment and/or their active metabolites are electrophiles that exert their effects by forming covalent bonds with nucleophilic DNA centers. The theory of hard and soft acids and bases (HSAB), which states that a toxic electrophile reacts preferentially with a biological macromolecule that has a similar hardness or softness, clarifies the underlying chemistry involved in this critical event. Epoxides are hard electrophiles that are produced endogenously by the enzymatic oxidation of parent chemicals (e.g., alkenes and PAHs). Epoxide ring opening proceeds through a SN2-type mechanism with hard nucleophile DNA sites as the major facilitators of toxic effects. Thus, the quantitative prediction of chemical reactivity would enable a predictive assessment of the molecular potential to exert electrophile-mediated toxicity. In this study, we calculated the activation energies for reactions between epoxides and the guanine N7 site for a diverse set of epoxides, including aliphatic epoxides, substituted styrene oxides, and PAH epoxides, using a state-of-the-art density functional theory (DFT) method. It is worth noting that these activation energies for diverse epoxides can be further predicted by quantum chemically calculated nucleophilic indices from HSAB theory, which is a less computationally demanding method than the exacting procedure for locating the transition state. More importantly, the good qualitative/quantitative correlations between the chemical reactivity of epoxides and their bioactivity suggest that the developed model based on HSAB theory may aid in the predictive hazard evaluation of epoxides, enabling the early identification of mutagenicity/carcinogenicity-relevant SN2 reactivity.

Prediction of toxicity and comparison of alternatives using WebTEST (Web-services Toxicity Estimation Software Tool)

EPA Science Inventory

A Java-based web service is being developed within the US EPA’s Chemistry Dashboard to provide real time estimates of toxicity values and physical properties. WebTEST can generate toxicity predictions directly from a simple URL which includes the endpoint, QSAR method, and ...

Prediction of toxicity and comparison of alternatives using WebTEST (Web-services Toxicity Estimation Software Tool)(Bled Slovenia)

EPA Science Inventory

A Java-based web service is being developed within the US EPA’s Chemistry Dashboard to provide real time estimates of toxicity values and physical properties. WebTEST can generate toxicity predictions directly from a simple URL which includes the endpoint, QSAR method, and ...

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

Deriving Points of Departure and Performance Baselines for Predictive Modeling of Systemic Toxicity using ToxRefDB (SOT)

EPA Science Inventory

A primary goal of computational toxicology is to generate predictive models of toxicity. An elusive target of alternative test methods and models has been the accurate prediction of systemic toxicity points of departure (PoD). We aim not only to provide a large and valuable resou...

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

A web accessible software tool is being developed to predict the toxicity of unknown chemicals for a wide variety of endpoints. The tool will enable a user to easily predict the toxicity of a query compound by simply entering its structure in a 2-dimensional (2-D) chemical sketc...

Predicting fecundity of fathead minnows (Pimephales promelas) exposed toeEndocrine-disrupting chemicals using a MATLAB®-based model of oocyte growth dynamics

EPA Science Inventory

Fish spawning is often used as an integrated measure of reproductive toxicity, and an indicator of aquatic ecosystem health in the context of forecasting potential population-level effects considered important for ecological risk assessment. Consequently, there is a need for fle...

High-throughput Screening of ToxCast" Phase I Chemicals in an Embryonic Stem Cell Assay Reveals Potential Disruption of a Critical Developmental Signaling Pathway

EPA Science Inventory

Little is known about the developmental toxicity of the expansive chemical landscape in existence today. Significant efforts are being made to apply novel methods to predict developmental activity of chemicals utilizing high-throughput screening (HTS) and high-content screening (...

Chemical-gene interaction networks and causal reasoning for biological effects prediction and prioritization of contaminants for environmental monitoring and surveillance (poster)

EPA Science Inventory

Product Description:Evaluation of the potential effects of complex mixtures of chemicals in the environment is challenged by the lack of extensive toxicity data for many chemicals. However, there are growing sources of online information that curate and compile literature reports...

Use of the HepaRG Cell Line to Assess Potential Human Hepatotoxicity of ToxCast™ Chemicals

EPA Science Inventory

The HepaRG cell line is a promising model system for predicting human hepatotoxicity in part because of the greater capacity to metabolize chemicals than other cell models. We hypothesized that this cell line would be a relevant model for toxicity testing of industrial chemicals....

Using In Vitro High-Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

EPA Science Inventory

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values and risk screening values. We aim to use computa...

A SYSTEMS APPROACH TO CHARACTERIZING AND PREDICTING THYROID TOXICITY USING AN AMPHIBIAN MODEL

EPA Science Inventory

The EPA was recently mandated to evaluate the potential effects of chemicals on endocrine function and has identified Xenopus as a model organism to use as the basis for a thyroid disruption screening assay. The main objective of this work is to develop a hypothalamic-pituitary-t...

Too many chemicals, too little time: Rapid in silico methods to characterize and predict ADME properties for chemical toxicity and exposure potential

EPA Science Inventory

Evaluating proposed alternative chemical structures to support the design of safer chemicals and products is an important component of EPA's Green Chemistry and Design for the Environment (DfE) Programs. As such, science-based alternatives assessment is essential to support EPA's...

Machine learning algorithms for the prediction of hERG and CYP450 binding in drug development.

PubMed

Klon, Anthony E

2010-07-01

The cost of developing new drugs is estimated at approximately $1 billion; the withdrawal of a marketed compound due to toxicity can result in serious financial loss for a pharmaceutical company. There has been a greater interest in the development of in silico tools that can identify compounds with metabolic liabilities before they are brought to market. The two largest classes of machine learning (ML) models, which will be discussed in this review, have been developed to predict binding to the human ether-a-go-go related gene (hERG) ion channel protein and the various CYP isoforms. Being able to identify potentially toxic compounds before they are made would greatly reduce the number of compound failures and the costs associated with drug development. This review summarizes the state of modeling hERG and CYP binding towards this goal since 2003 using ML algorithms. A wide variety of ML algorithms that are comparable in their overall performance are available. These ML methods may be applied regularly in discovery projects to flag compounds with potential metabolic liabilities.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

NASA Astrophysics Data System (ADS)

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-03-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

PubMed Central

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-01-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures. PMID:28287626

Predicting mixture toxicity of seven phenolic compounds with similar and dissimilar action mechanisms to Vibrio qinghaiensis sp.nov.Q67.

PubMed

Huang, Wei Ying; Liu, Fei; Liu, Shu Shen; Ge, Hui Lin; Chen, Hong Han

2011-09-01

The predictions of mixture toxicity for chemicals are commonly based on two models: concentration addition (CA) and independent action (IA). Whether the CA and IA can predict mixture toxicity of phenolic compounds with similar and dissimilar action mechanisms was studied. The mixture toxicity was predicted on the basis of the concentration-response data of individual compounds. Test mixtures at different concentration ratios and concentration levels were designed using two methods. The results showed that the Weibull function fit well with the concentration-response data of all the components and their mixtures, with all relative coefficients (Rs) greater than 0.99 and root mean squared errors (RMSEs) less than 0.04. The predicted values from CA and IA models conformed to observed values of the mixtures. Therefore, it can be concluded that both CA and IA can predict reliable results for the mixture toxicity of the phenolic compounds with similar and dissimilar action mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example.

PubMed

Li, Tong; Liu, Shu-Shen; Qu, Rui; Liu, Hai-Ling

2017-10-01

The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC 50 ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC 30 , and EC 70 ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs. Copyright © 2017. Published by Elsevier Inc.

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

Acute toxicity prediction to threatened and endangered ...

EPA Pesticide Factsheets

Evaluating contaminant sensitivity of threatened and endangered (listed) species and protectiveness of chemical regulations often depends on toxicity data for commonly tested surrogate species. The U.S. EPA’s Internet application Web-ICE is a suite of Interspecies Correlation Estimation (ICE) models that can extrapolate species sensitivity to listed taxa using least-squares regressions of the sensitivity of a surrogate species and a predicted taxon (species, genus, or family). Web-ICE was expanded with new models that can predict toxicity to over 250 listed species. A case study was used to assess protectiveness of genus and family model estimates derived from either geometric mean or minimum taxa toxicity values for listed species. Models developed from the most sensitive value for each chemical were generally protective of the most sensitive species within predicted taxa, including listed species, and were more protective than geometric means models. ICE model estimates were compared to HC5 values derived from Species Sensitivity Distributions for the case study chemicals to assess protectiveness of the two approaches. ICE models provide robust toxicity predictions and can generate protective toxicity estimates for assessing contaminant risk to listed species. Reporting on the development and optimization of ICE models for listed species toxicity estimation

An integrated in vitro and in vivo high throughput screen identifies treatment leads for ependymoma

PubMed Central

Atkinson, Jennifer M.; Shelat, Anang A.; Carcaboso, Angel Montero; Kranenburg, Tanya A.; Arnold, Alexander; Boulos, Nidal; Wright, Karen; Johnson, Robert A.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Feau, Clementine; Phoenix, Timothy; Gibson, Paul; Zhu, Liqin; Tong, Yiai; Eden, Chris; Ellison, David W.; Priebe, Waldemar; Koul, Dimpy; Yung, W. K. Alfred; Gajjar, Amar; Stewart, Clinton F.; Guy, R. Kip; Gilbertson, Richard J.

2011-01-01

Summary Using a mouse model of ependymoma—a chemoresistant brain tumor—we combined multi-cell high-throughput screening (HTS), kinome-wide binding assays, and in vivo efficacy studies, to identify potential treatments with predicted toxicity against neural stem cells (NSC). We identified kinases within the insulin signaling pathway and centrosome cycle as regulators of ependymoma cell proliferation, and their corresponding inhibitors as potential therapies. FDA approved drugs not currently used to treat ependymoma were also identified that posses selective toxicity against ependymoma cells relative to normal NSCs both in vitro and in vivo e.g., 5-fluoruracil. Our comprehensive approach advances understanding of the biology and treatment of ependymoma including the discovery of several treatment leads for immediate clinical translation. PMID:21907928

Reducing aquatic hazards of industrial chemicals: probabilistic assessment of sustainable molecular design guidelines.

PubMed

Connors, Kristin A; Voutchkova-Kostal, Adelina M; Kostal, Jakub; Anastas, Paul; Zimmerman, Julie B; Brooks, Bryan W

2014-08-01

Basic toxicological information is lacking for the majority of industrial chemicals. In addition to increasing empirical toxicity data through additional testing, prospective computational approaches to drug development aim to serve as a rational basis for the design of chemicals with reduced toxicity. Recent work has resulted in the derivation of a "rule of 2," wherein chemicals with an octanol-water partition coefficient (log P) less than 2 and a difference between the lowest unoccupied molecular orbital and the highest occupied molecular orbital (ΔE) greater than 9 (log P<2 and ΔE >9 eV) are predicted to be 4 to 5 times less likely to elicit acute or chronic toxicity to model aquatic organisms. The present study examines potential reduction of aquatic toxicity hazards from industrial chemicals if these 2 molecular design guidelines were employed. Probabilistic hazard assessment approaches were used to model the likelihood of encountering industrial chemicals exceeding toxicological categories of concern both with and without the rule of 2. Modeling predicted that utilization of these molecular design guidelines for log P and ΔE would appreciably decrease the number of chemicals that would be designated to be of "high" and "very high" concern for acute and chronic toxicity to standard model aquatic organisms and end points as defined by the US Environmental Protection Agency. For example, 14.5% of chemicals were categorized as having high and very high acute toxicity to the fathead minnow model, whereas only 3.3% of chemicals conforming to the design guidelines were predicted to be in these categories. Considerations of specific chemical classes (e.g., aldehydes), chemical attributes (e.g., ionization), and adverse outcome pathways in representative species (e.g., receptor-mediated responses) could be used to derive future property guidelines for broader classes of contaminants. © 2014 SETAC.

Personal care product preservatives: risk assessment and mixture toxicities with an industrial wastewater.

PubMed

Carbajo, Jose B; Perdigón-Melón, Jose A; Petre, Alice L; Rosal, Roberto; Letón, Pedro; García-Calvo, Eloy

2015-04-01

The aquatic toxicity of eight preservatives frequently used in personal care products (PCPs) (iodopropynyl butylcarbamate, bronopol, diazolidinyl urea, benzalkonium chloride, zinc pyrithione, propylparaben, triclosan and a mixture of methylchloroisothiazolinone and methylisothiazolinone) was assessed by means of two different approaches: a battery of bioassays composed of single species tests of bacteria (Vibrio fischeri and Pseudomonas putida) and protozoa (Tetrahymena thermophila), and a whole biological community resazurin-based assay using activated sludge. The tested preservatives showed considerable toxicity in the studied bioassays, but with a marked difference in potency. In fact, all biocides except propylparaben and diazolidinyl urea had EC50 values lower than 1 mg L(-1) in at least one assay. Risk quotients for zinc pyrithione, benzalkonium chloride, iodopropynyl butylcarbamate and triclosan as well as the mixture of the studied preservatives exceeded 1, indicating a potential risk for the process performance and efficiency of municipal sewage treatment plants (STPs). These four single biocides explained more than 95% of the preservative mixture risk in all bioassays. Each individual preservative was also tested in combination with an industrial wastewater (IWW) from a cosmetics manufacturing facility. The toxicity assessment was performed on binary mixtures (preservative + IWW) and carried out using the median-effect principle, which is a special case of the concept of Concentration Addition (CA). Almost 70% of all experiments resulted in EC50 values within a factor of 2 of the values predicted by the median-effect principle (CI values between 0.5 and 2). The rest of the mixtures whose toxicity was mispredicted by CA were assessed with the alternative concept of Independent Action (IA), which showed higher predictive power for the biological community assay. Therefore, the concept used to accurately predict the toxicity of mixtures of a preservative with a complex industrial wastewater depends on degree of biological complexity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effect-Based Tools for Monitoring and Predicting the Ecotoxicological Effects of Chemicals in the Aquatic Environment

PubMed Central

Connon, Richard E.; Geist, Juergen; Werner, Inge

2012-01-01

Ecotoxicology faces the challenge of assessing and predicting the effects of an increasing number of chemical stressors on aquatic species and ecosystems. Herein we review currently applied tools in ecological risk assessment, combining information on exposure with expected biological effects or environmental water quality standards; currently applied effect-based tools are presented based on whether exposure occurs in a controlled laboratory environment or in the field. With increasing ecological relevance the reproducibility, specificity and thus suitability for standardisation of methods tends to diminish. We discuss the use of biomarkers in ecotoxicology including ecotoxicogenomics-based endpoints, which are becoming increasingly important for the detection of sublethal effects. Carefully selected sets of biomarkers allow an assessment of exposure to and effects of toxic chemicals, as well as the health status of organisms and, when combined with chemical analysis, identification of toxicant(s). The promising concept of “adverse outcome pathways (AOP)” links mechanistic responses on the cellular level with whole organism, population, community and potentially ecosystem effects and services. For most toxic mechanisms, however, practical application of AOPs will require more information and the identification of key links between responses, as well as key indicators, at different levels of biological organization, ecosystem functioning and ecosystem services. PMID:23112741

Model-based approach for quantitative estimates of skin, heart, and lung toxicity risk for left-side photon and proton irradiation after breast-conserving surgery.

PubMed

Tommasino, Francesco; Durante, Marco; D'Avino, Vittoria; Liuzzi, Raffaele; Conson, Manuel; Farace, Paolo; Palma, Giuseppe; Schwarz, Marco; Cella, Laura; Pacelli, Roberto

2017-05-01

Proton beam therapy represents a promising modality for left-side breast cancer (BC) treatment, but concerns have been raised about skin toxicity and poor cosmesis. The aim of this study is to apply skin normal tissue complication probability (NTCP) model for intensity modulated proton therapy (IMPT) optimization in left-side BC. Ten left-side BC patients undergoing photon irradiation after breast-conserving surgery were randomly selected from our clinical database. Intensity modulated photon (IMRT) and IMPT plans were calculated with iso-tumor-coverage criteria and according to RTOG 1005 guidelines. Proton plans were computed with and without skin optimization. Published NTCP models were employed to estimate the risk of different toxicity endpoints for skin, lung, heart and its substructures. Acute skin NTCP evaluation suggests a lower toxicity level with IMPT compared to IMRT when the skin is included in proton optimization strategy (0.1% versus 1.7%, p < 0.001). Dosimetric results show that, with the same level of tumor coverage, IMPT attains significant heart and lung dose sparing compared with IMRT. By NTCP model-based analysis, an overall reduction in the cardiopulmonary toxicity risk prediction can be observed for all IMPT compared to IMRT plans: the relative risk reduction from protons varies between 0.1 and 0.7 depending on the considered toxicity endpoint. Our analysis suggests that IMPT might be safely applied without increasing the risk of severe acute radiation induced skin toxicity. The quantitative risk estimates also support the potential clinical benefits of IMPT for left-side BC irradiation due to lower risk of cardiac and pulmonary morbidity. The applied approach might be relevant on the long term for the setup of cost-effectiveness evaluation strategies based on NTCP predictions.

A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

EPA Science Inventory

The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently pu...

Evaluating the Spatial Distribution of Toxic Air Contaminants in Multiple Ecosystem Indicators in the Sierra Nevada-Southern Cascades

NASA Astrophysics Data System (ADS)

Nanus, L.; Simonich, S. L.; Rocchio, J.; Flanagan, C.

2013-12-01

Toxic air contaminants originating from agricultural areas of the Central Valley in California threaten vulnerable sensitive receptors including surface water, vegetation, snow, sediments, fish, and amphibians in the Sierra Nevada-Southern Cascades region. The spatial distribution of toxic air contaminants in different ecosystem indicators depends on variation in atmospheric concentrations and deposition, and variation in air toxics accumulation in ecosystems. The spatial distribution of organic air toxics and mercury at over 330 unique sampling locations and sample types over two decades (1990-2009) in the Sierra Nevada-Southern Cascades region were compiled and maps were developed to further understand spatial patterns and linkages between air toxics deposition and ecological effects. Potential ecosystem impacts in the Sierra Nevada-Southern Cascades region include bioaccumulation of air toxics in both aquatic and terrestrial ecosystems, reproductive disruption, and immune suppression. The most sensitive ecological end points in the region that are affected by bioaccumulation of toxic air contaminants are fish. Mercury was detected in all fish and approximately 6% exceeded human consumption thresholds. Organic air toxics were also detected in fish yielding variable spatial patterns. For amphibians, which are sensitive to pesticide exposure and potential immune suppression, increasing trends in current and historic use pesticides are observed from north to south across the region. In other indicators, such as vegetation, pesticide concentrations in lichen increase with increasing elevation. Current and historic use pesticides and mercury were also observed in snowpack at high elevations in the study area. This study shows spatial patterns in toxic air contaminants, evaluates associated risks to sensitive receptors, and identifies data gaps. Future research on atmospheric modeling and information on sources is needed in order to predict which ecosystems are the most sensitive to toxic air contaminants in the Sierra Nevada-Southern Cascades region.

Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method.

PubMed

Zhang, Hui; Yu, Peng; Ren, Ji-Xia; Li, Xi-Bo; Wang, He-Li; Ding, Lan; Kong, Wei-Bao

2017-12-01

Mitochondrial dysfunction has been considered as an important contributing factor in the etiology of drug-induced organ toxicity, and even plays an important role in the pathogenesis of some diseases. The objective of this investigation was to develop a novel prediction model of drug-induced mitochondrial toxicity by using a naïve Bayes classifier. For comparison, the recursive partitioning classifier prediction model was also constructed. Among these methods, the prediction performance of naïve Bayes classifier established here showed best, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set were 95 ± 0.6% and 81 ± 1.1%, respectively. In addition, four important molecular descriptors and some representative substructures of toxicants produced by ECFP_6 fingerprints were identified. We hope the established naïve Bayes prediction model can be employed for the mitochondrial toxicity assessment, and these obtained important information of mitochondrial toxicants can provide guidance for medicinal chemists working in drug discovery and lead optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of In Silico Anti-parkinson potential of β-asarone.

PubMed

Gupta, Meenakshi; Kant, Kamal; Sharma, Ruchika; Kumar, Anoop

2018-04-16

Parkinson's disease is affecting millions of people worldwide. The prevalence of Parkinson's disease is 0.3% globally, rising to 1% in more than 60 years of age and 4% in more than 80 years of age and the figures are thought to be doubled by 2030. Thus, there is a great need to identify novel therapeutic strategies or candidate drug molecule which can rescue neuronal degeneration. β-asarone has potential to act as a neuroprotective agent but regarding its role in Parkinson disease, very few reports are available. Thus, this study was undertaken to unlock the potential of β-asarone against Parkinson's disease. The Absorption, Distribution, Metabolism, and Excretion (ADME) analysis has been done by using Swiss ADME Predictor. The interactions of β-asarone towards dopaminergic receptors were investigated by Glide Program 5.0. The crystal structures of dopamine receptors were retrieved from Research Collaboratory for Structural Bioinformatics- Protein Data Bank (RCSB-PDB). The structure of β-asarone was drawn in Chem Draw Ultra 7.0.1. Finally, the toxicity of β-asarone has been predicted by using online web-servers like Lazar and Protox. The ADME data of current investigation has shown good oral bioavailability of β-asarone. It also showed a good binding affinity towards dopaminergic receptors. Further, it was found to be interacting through hydrogen bond with different amino acid residues of D2 and D3 receptors. However, β-asarone was predicted to be toxic in various species of rodents, as per the results of toxicity online web servers. Based on the current finding from ADME and docking studies, these preliminary results may act as effective precursor tool for development of β-asarone as a promising anti-Parkinson agent. However, furthermore experimental validation using in-vitro & in-vivo studies is needed to explore their therapeutic & toxic effects. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In vitro screening for population variability in toxicity of pesticide-containing mixtures

PubMed Central

Abdo, Nour; Wetmore, Barbara A.; Chappell, Grace A.; Shea, Damian; Wright, Fred A.; Rusyna, Ivan

2016-01-01

Population-based human in vitro models offer exceptional opportunities for evaluating the potential hazard and mode of action of chemicals, as well as variability in responses to toxic insults among individuals. This study was designed to test the hypothesis that comparative population genomics with efficient in vitro experimental design can be used for evaluation of the potential for hazard, mode of action, and the extent of population variability in responses to chemical mixtures. We selected 146 lymphoblast cell lines from 4 ancestrally and geographically diverse human populations based on the availability of genome sequence and basal RNA-seq data. Cells were exposed to two pesticide mixtures – an environmental surface water sample comprised primarily of organochlorine pesticides and a laboratory-prepared mixture of 36 currently used pesticides – in concentration response and evaluated for cytotoxicity. On average, the two mixtures exhibited a similar range of in vitro cytotoxicity and showed considerable inter-individual variability across screened cell lines. However, when in vitroto-in vivo extrapolation (IVIVE) coupled with reverse dosimetry was employed to convert the in vitro cytotoxic concentrations to oral equivalent doses and compared to the upper bound of predicted human exposure, we found that a nominally more cytotoxic chlorinated pesticide mixture is expected to have greater margin of safety (more than 5 orders of magnitude) as compared to the current use pesticide mixture (less than 2 orders of magnitude) due primarily to differences in exposure predictions. Multivariate genome-wide association mapping revealed an association between the toxicity of current use pesticide mixture and a polymorphism in rs1947825 in C17orf54. We conclude that a combination of in vitro human population-based cytotoxicity screening followed by dosimetric adjustment and comparative population genomics analyses enables quantitative evaluation of human health hazard from complex environmental mixtures. Additionally, such an approach yields testable hypotheses regarding potential toxicity mechanisms. PMID:26386728

Probing the toxicity of nanoparticles: a unified in silico machine learning model based on perturbation theory.

PubMed

Concu, Riccardo; Kleandrova, Valeria V; Speck-Planche, Alejandro; Cordeiro, M Natália D S

2017-09-01

Nanoparticles (NPs) are part of our daily life, having a wide range of applications in engineering, physics, chemistry, and biomedicine. However, there are serious concerns regarding the harmful effects that NPs can cause to the different biological systems and their ecosystems. Toxicity testing is an essential step for assessing the potential risks of the NPs, but the experimental assays are often very expensive and usually too slow to flag the number of NPs that may cause adverse effects. In silico models centered on quantitative structure-activity/toxicity relationships (QSAR/QSTR) are alternative tools that have become valuable supports to risk assessment, rationalizing the search for safer NPs. In this work, we develop a unified QSTR-perturbation model based on artificial neural networks, aimed at simultaneously predicting general toxicity profiles of NPs under diverse experimental conditions. The model is derived from 54,371 NP-NP pair cases generated by applying the perturbation theory to a set of 260 unique NPs, and showed an accuracy higher than 97% in both training and validation sets. Physicochemical interpretation of the different descriptors in the model are additionally provided. The QSTR-perturbation model is then employed to predict the toxic effects of several NPs not included in the original dataset. The theoretical results obtained for this independent set are strongly consistent with the experimental evidence found in the literature, suggesting that the present QSTR-perturbation model can be viewed as a promising and reliable computational tool for probing the toxicity of NPs.

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.

PubMed

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2016-05-01

Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Quantitative structure-activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro-in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634-641; http://dx.doi.org/10.1289/ehp.1509763.

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data

PubMed Central

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2015-01-01

Background: Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. Objective: The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Methods: Quantitative structure–activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro–in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. Results: The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Conclusion: Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Citation: Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634–641; http://dx.doi.org/10.1289/ehp.1509763 PMID:26383846

Combined approaches using adverse outcome pathways and big data to find potential diseases associated with humidifier disinfectant

PubMed Central

2017-01-01

According to previous survey, about two million of people were expected to suffer from toxic effects due to humidifier disinfectant (HD), regardless of healing or not. Extremely small group are recognized as HDs’ victims. Up to now, previous research tried to focus on interstitial fibrosis on terminal bronchiole because it is specific finding, compared with other diseases. To figure out overall effects from HDs, we recommend adverse outcome pathways (AOPs) as new approach. Reactive oxygen species (ROS) generation, decreased T-cell and pro-inflammatory cytokine release from macrophage could be key events between the exposure to HDs and diseases. ROS generation, decreased cell and pro-inflammatory cytokine release from macrophage could be cause of interstitial fibrosis, pneumonia and many other diseases such as asthma, allergic rhinitis, allergic dermatitis, fetal death, premature baby, autoimmune disease, hepatic toxicity, renal toxicity, cancer, and so on. We predict potential disease candidate by AOPs. We can validate the real risk of the adverse outcome by epidemiologic and toxicologic study using big data such as National Health Insurance data and AOPs knowledge base. Application of these kinds of new methods can find the potential disease list from the exposure to HD. PMID:28111421

Combined approaches using adverse outcome pathways and big data to find potential diseases associated with humidifier disinfectant.

PubMed

Leem, Jong-Han; Chung, Kyu Hyuck

2016-01-01

According to previous survey, about two million of people were expected to suffer from toxic effects due to humidifier disinfectant (HD), regardless of healing or not. Extremely small group are recognized as HDs' victims. Up to now, previous research tried to focus on interstitial fibrosis on terminal bronchiole because it is specific finding, compared with other diseases. To figure out overall effects from HDs, we recommend adverse outcome pathways (AOPs) as new approach. Reactive oxygen species (ROS) generation, decreased T-cell and pro-inflammatory cytokine release from macrophage could be key events between the exposure to HDs and diseases. ROS generation, decreased cell and pro-inflammatory cytokine release from macrophage could be cause of interstitial fibrosis, pneumonia and many other diseases such as asthma, allergic rhinitis, allergic dermatitis, fetal death, premature baby, autoimmune disease, hepatic toxicity, renal toxicity, cancer, and so on. We predict potential disease candidate by AOPs. We can validate the real risk of the adverse outcome by epidemiologic and toxicologic study using big data such as National Health Insurance data and AOPs knowledge base. Application of these kinds of new methods can find the potential disease list from the exposure to HD.

Effects of 31 FDA approved small-molecule kinase inhibitors on isolated rat liver mitochondria.

PubMed

Zhang, Jun; Salminen, Alec; Yang, Xi; Luo, Yong; Wu, Qiangen; White, Matthew; Greenhaw, James; Ren, Lijun; Bryant, Matthew; Salminen, William; Papoian, Thomas; Mattes, William; Shi, Qiang

2017-08-01

The FDA has approved 31 small-molecule kinase inhibitors (KIs) for human use as of November 2016, with six having black box warnings for hepatotoxicity (BBW-H) in product labeling. The precise mechanisms and risk factors for KI-induced hepatotoxicity are poorly understood. Here, the 31 KIs were tested in isolated rat liver mitochondria, an in vitro system recently proposed to be a useful tool to predict drug-induced hepatotoxicity in humans. The KIs were incubated with mitochondria or submitochondrial particles at concentrations ranging from therapeutic maximal blood concentrations (Cmax) levels to 100-fold Cmax levels. Ten endpoints were measured, including oxygen consumption rate, inner membrane potential, cytochrome c release, swelling, reactive oxygen species, and individual respiratory chain complex (I-V) activities. Of the 31 KIs examined only three including sorafenib, regorafenib and pazopanib, all of which are hepatotoxic, caused significant mitochondrial toxicity at concentrations equal to the Cmax, indicating that mitochondrial toxicity likely contributes to the pathogenesis of hepatotoxicity associated with these KIs. At concentrations equal to 100-fold Cmax, 18 KIs were found to be toxic to mitochondria, and among six KIs with BBW-H, mitochondrial injury was induced by regorafenib, lapatinib, idelalisib, and pazopanib, but not ponatinib, or sunitinib. Mitochondrial liability at 100-fold Cmax had a positive predictive power (PPV) of 72% and negative predictive power (NPV) of 33% in predicting human KI hepatotoxicity as defined by product labeling, with the sensitivity and specificity being 62% and 44%, respectively. Similar predictive power was obtained using the criterion of Cmax ≥1.1 µM or daily dose ≥100 mg. Mitochondrial liability at 1-2.5-fold Cmax showed a 100% PPV and specificity, though the NPV and sensitivity were 32% and 14%, respectively. These data provide novel mechanistic insights into KI hepatotoxicity and indicate that mitochondrial toxicity at therapeutic levels can help identify hepatotoxic KIs.

Developmental Toxicity of Nanoparticles on the Brain.

PubMed

Umezawa, Masakazu; Onoda, Atsuto; Takeda, Ken

2017-01-01

The toxicity of nanoparticles (nanotoxicology) is being investigated to understand both the health impacts of atmospheric ultrafine particles-the size of which is a fraction (<0.1 μm aerodynamic diameter) of that of PM 2.5 (<2.5 μm diameter)-and the safer use of engineered nanomaterials. Developmental toxicity of nanoparticles has been studied since their transfer from pregnant body to fetal circulation and offspring body was first reported. Here we reviewed the developmental toxicity of nanoparticles on the brain, one of the most important organs in maintenance of mental health and high quality of life. Recently the dose- and size-dependency of transplacental nanoparticle transfer to the fetus was reported. It is important to understand both the mechanism of direct effect of nanoparticles transferred to the fetus and offspring and the indirect effect mediated by induction of oxidative stress and inflammation in the pregnant body. Locomotor activity, learning and memory, motor coordination, and social behavior were reported as potential neurobehavioral targets of maternal nanoparticle exposure. Histopathologically, brain perivascular cells, including perivascular macrophages and surrounding astrocytes, have an important role in waste clearance from the brain parenchyma. They are potentially the most sensitive target of maternal exposure to low-dose nanoparticles. Further investigations will show the detailed mechanism of developmental toxicity of nanoparticles and preventive strategies against intended and unintended nanoparticle exposure. This knowledge will contribute to the safer design of nanoparticles through the development of sensitive and quantitative endpoints for prediction of their developmental toxicity.

The Impact of Detoxification Costs and Predation Risk on Foraging: Implications for Mimicry Dynamics

PubMed Central

Skelhorn, John; Rowe, Candy; Ruxton, Graeme D.; Higginson, Andrew D.

2017-01-01

Prey often evolve defences to deter predators, such as noxious chemicals including toxins. Toxic species often advertise their defence to potential predators by distinctive sensory signals. Predators learn to associate toxicity with the signals of these so-called aposematic prey, and may avoid them in future. In turn, this selects for mildly toxic prey to mimic the appearance of more toxic prey. Empirical evidence shows that mimicry could be either beneficial (‘Mullerian’) or detrimental (‘quasi-Batesian’) to the highly toxic prey, but the factors determining which are unknown. Here, we use state-dependent models to explore how tri-trophic interactions could influence the evolution of prey defences. We consider how predation risk affects predators’ optimal foraging strategies on aposematic prey, and explore the resultant impact this has on mimicry dynamics between unequally defended species. In addition, we also investigate how the potential energetic cost of metabolising a toxin can alter the benefits to eating toxic prey and thus impact on predators’ foraging decisions. Our model predicts that both how predators perceive their own predation risk, and the cost of detoxification, can have significant, sometimes counterintuitive, effects on the foraging decisions of predators. For example, in some conditions predators should: (i) avoid prey they know to be undefended, (ii) eat more mildly toxic prey as detoxification costs increase, (iii) increase their intake of highly toxic prey as the abundance of undefended prey increases. These effects mean that the relationship between a mimic and its model can qualitatively depend on the density of alternative prey and the cost of metabolising toxins. In addition, these effects are mediated by the predators’ own predation risk, which demonstrates that, higher trophic levels than previously considered can have fundamental impacts on interactions among aposematic prey species. PMID:28045959

Lung Deposition Analyses of Inhaled Toxic Aerosols in Conventional and Less Harmful Cigarette Smoke: A Review

PubMed Central

Kleinstreuer, Clement; Feng, Yu

2013-01-01

Inhaled toxic aerosols of conventional cigarette smoke may impact not only the health of smokers, but also those exposed to second-stream smoke, especially children. Thus, less harmful cigarettes (LHCs), also called potential reduced exposure products (PREPs), or modified risk tobacco products (MRTP) have been designed by tobacco manufacturers to focus on the reduction of the concentration of carcinogenic components and toxicants in tobacco. However, some studies have pointed out that the new cigarette products may be actually more harmful than the conventional ones due to variations in puffing or post-puffing behavior, different physical and chemical characteristics of inhaled toxic aerosols, and longer exposure conditions. In order to understand the toxicological impact of tobacco smoke, it is essential for scientists, engineers and manufacturers to develop experiments, clinical investigations, and predictive numerical models for tracking the intake and deposition of toxicants of both LHCs and conventional cigarettes. Furthermore, to link inhaled toxicants to lung and other diseases, it is necessary to determine the physical mechanisms and parameters that have significant impacts on droplet/vapor transport and deposition. Complex mechanisms include droplet coagulation, hygroscopic growth, condensation and evaporation, vapor formation and changes in composition. Of interest are also different puffing behavior, smoke inlet conditions, subject geometries, and mass transfer of deposited material into systemic regions. This review article is intended to serve as an overview of contributions mainly published between 2009 and 2013, focusing on the potential health risks of toxicants in cigarette smoke, progress made in different approaches of impact analyses for inhaled toxic aerosols, as well as challenges and future directions. PMID:24065038

Dosimetric and clinical predictors for radiation-induced esophageal injury.

PubMed

Ahn, Sung-Ja; Kahn, Daniel; Zhou, Sumin; Yu, Xiaoli; Hollis, Donna; Shafman, Timothy D; Marks, Lawrence B

2005-02-01

To evaluate the clinical and three-dimensional dosimetric parameters associated with esophageal injury after radiotherapy (RT) for non-small-cell lung cancer. The records of 254 patients treated for non-small-cell lung cancer between 1992 and 2001 were reviewed. A variety of metrics describing the esophageal dose were extracted. The Radiation Therapy Oncology Group toxicity criteria for grading of esophageal injury were used. The median follow-up time for all patients was 43 months (range, 0.5-120 months). Logistic regression analysis, contingency table analyses, and Fisher's exact tests were used for statistical analysis. Acute toxicity occurred in 199 (78%) of 254 patients. For acute toxicity of Grade 2 or worse, twice-daily RT, age, nodal stage of N2 or worse, and most dosimetric parameters were predictive. Late toxicity occurred in 17 (7%) of 238 patients. The median and maximal time to the onset of late toxicity was 5 and 40 months after RT, respectively. Late toxicity occurred in 2%, 3%, 17%, 26%, and 100% of patients with acute Grade 0, 1, 2, 3, and 4 toxicity, respectively. For late toxicity, the severity of acute toxicity was most predictive. A variety of dosimetric parameters are predictive of acute and late esophageal injury. A strong correlation between the dosimetric parameters prevented a comparison between the predictive abilities of these metrics. The presence of acute injury was the most predictive factor for the development of late injury. Additional studies to define better the predictors of RT-induced esophageal injury are needed.

A mixture toxicity approach to predict the toxicity of Ag decorated ZnO nanomaterials.

PubMed

Azevedo, S L; Holz, T; Rodrigues, J; Monteiro, T; Costa, F M; Soares, A M V M; Loureiro, S

2017-02-01

Nanotechnology is a rising field and nanomaterials can now be found in a vast variety of products with different chemical compositions, sizes and shapes. New nanostructures combining different nanomaterials are being developed due to their enhancing characteristics when compared to nanomaterials alone. In the present study, the toxicity of a nanostructure composed by a ZnO nanomaterial with Ag nanomaterials on its surface (designated as ZnO/Ag nanostructure) was assessed using the model-organism Daphnia magna and its toxicity predicted based on the toxicity of the single components (Zn and Ag). For that ZnO and Ag nanomaterials as single components, along with its mixture prepared in the laboratory, were compared in terms of toxicity to ZnO/Ag nanostructures. Toxicity was assessed by immobilization and reproduction tests. A mixture toxicity approach was carried out using as starting point the conceptual model of Concentration Addition. The laboratory mixture of both nanomaterials showed that toxicity was dependent on the doses of ZnO and Ag used (immobilization) or presented a synergistic pattern (reproduction). The ZnO/Ag nanostructure toxicity prediction, based on the percentage of individual components, showed an increase in toxicity when compared to the expected (immobilization) and dependent on the concentration used (reproduction). This study demonstrates that the toxicity of the prepared mixture of ZnO and Ag and of the ZnO/Ag nanostructure cannot be predicted based on the toxicity of their components, highlighting the importance of taking into account the interaction between nanomaterials when assessing hazard and risk. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

EPA Science Inventory

Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

Exploring the Q-marker of "sweat soaking method" processed radix Wikstroemia indica: Based on the "effect-toxicity-chemicals" study.

PubMed

Feng, Guo; Chen, Yun-Long; Li, Wei; Li, Lai-Lai; Wu, Zeng-Guang; Wu, Zi-Jun; Hai, Yue; Zhang, Si-Chao; Zheng, Chuan-Qi; Liu, Chang-Xiao; He, Xin

2018-06-01

Radix Wikstroemia indica (RWI), named "Liao Ge Wang" in Chinese, is a kind of toxic Chinese herbal medicine (CHM) commonly used in Miao nationality of South China. "Sweat soaking method" processed RWI could effectively decrease its toxicity and preserve therapeutic effect. However, the underlying mechanism of processing is still not clear, and the Q-markers database for processed RWI has not been established. Our study is to investigate and establish the quality evaluation system and potential Q-markers based on "effect-toxicity-chemicals" relationship of RWI for quality/safety assessment of "sweat soaking method" processing. The variation of RWI in efficacy and toxicity before and after processing was investigated by pharmacological and toxicological studies. Cytotoxicity test was used to screen the cytotoxicity of components in RWI. The material basis in ethanol extract of raw and processed RWI was studied by UPLC-Q-TOF/MS. And the potential Q-markers were analyzed and predicted according to "effect-toxicity-chemical" relationship. RWI was processed by "sweat soaking method", which could preserve efficacy and reduce toxicity. Raw RWI and processed RWI did not show significant difference on the antinociceptive and anti-inflammatory effect, however, the injury of liver and kidney by processed RWI was much weaker than that by raw RWI. The 20 compounds were identified from the ethanol extract of raw product and processed product of RWI using UPLC-Q-TOF/MS, including daphnoretin, emodin, triumbelletin, dibutyl phthalate, Methyl Paraben, YH-10 + OH and matairesinol, arctigenin, kaempferol and physcion. Furthermore, 3 diterpenoids (YH-10, YH-12 and YH-15) were proved to possess the high toxicity and decreased by 48%, 44% and 65%, respectively, which could be regarded as the potential Q-markers for quality/safety assessment of "sweat soaking method" processed RWI. A Q-marker database of processed RWI by "sweat soaking method" was established according to the results and relationship of "effect-toxicity-chemicals", which provided a scientific evidence for processing methods, mechanism and the clinical application of RWI, also provided experimental results to explore the application of Q-marker in CHM. Copyright © 2018 Elsevier GmbH. All rights reserved.

EPA'S TOXCAST PROGRAM FOR PREDICTING TOXICITY AND PRIORITIZING ENVIRONMENTAL CHEMICALS

EPA Science Inventory

ToxCast is a research program to predict or forecast toxicity by evaluating a broad spectrum of chemicals and effects; physical-chemical properties, predicted bioactivities, HTS and cell-based assays, and genomics. Data will be interpretively linked to known or predicted toxicol...

Use of fish embryo toxicity tests for the prediction of acute fish toxicity to chemicals.

PubMed

Belanger, Scott E; Rawlings, Jane M; Carr, Gregory J

2013-08-01

The fish embryo test (FET) is a potential animal alternative for the acute fish toxicity (AFT) test. A comprehensive validation program assessed 20 different chemicals to understand intra- and interlaboratory variability for the FET. The FET had sufficient reproducibility across a range of potencies and modes of action. In the present study, the suitability of the FET as an alternative model is reviewed by relating FET and AFT. In total, 985 FET studies and 1531 AFT studies were summarized. The authors performed FET-AFT regressions to understand potential relationships based on physical-chemical properties, species choices, duration of exposure, chemical classes, chemical functional uses, and modes of action. The FET-AFT relationships are very robust (slopes near 1.0, intercepts near 0) across 9 orders of magnitude in potency. A recommendation for the predictive regression relationship is based on 96-h FET and AFT data: log FET median lethal concentration (LC50) = (0.989 × log fish LC50) - 0.195; n = 72 chemicals, r = 0.95, p < 0.001, LC50 in mg/L. A similar, not statistically different regression was developed for the entire data set (n = 144 chemicals, unreliable studies deleted). The FET-AFT regressions were robust for major chemical classes with suitably large data sets. Furthermore, regressions were similar to those for large groups of functional chemical categories such as pesticides, surfactants, and industrial organics. Pharmaceutical regressions (n = 8 studies only) were directionally correct. The FET-AFT relationships were not quantitatively different from acute fish-acute fish toxicity relationships with the following species: fathead minnow, rainbow trout, bluegill sunfish, Japanese medaka, and zebrafish. The FET is scientifically supportable as a rational animal alternative model for ecotoxicological testing of acute toxicity of chemicals to fish. Copyright © 2013 SETAC.

Clinical trials with velnacrine: (PROPP) the physician reference of predicted probabilities--a statistical model for the estimation of hepatotoxicity risk with velnacrine maleate.

PubMed

Hardiman, S; Miller, K; Murphy, M

1993-01-01

Safety observations during the clinical development of Mentane (velnacrine maleate) have included the occurrence of generally asymptomatic liver enzyme elevations confined to patients with Alzheimer's disease (AD). The clinical presentation of this reversible hepatocellular injury is analogous to that reported for tetrahydroaminoacridine (THA). Direct liver injury, possibly associated with the production of a toxic metabolite, would be consistent with reports of aberrant xenobiotic metabolism in Alzheimer's disease patients. Since a patient related aberration in drug metabolism was suspected, a biostatistical strategy was developed with the objective of predicting hepatotoxicity in individual patients prior to exposure to velnacrine maleate. The method used logistic regression techniques with variable selection restricted to those items which could be routinely and inexpensively accessed at screen evaluation for potential candidates for treatment. The model was to be predictive (a marker for eventual hepatotoxicity) rather than a causative model, and techniques employed "goodness of fit", percentage correct, and positive and negative predictive values. On the basis of demographic and baseline laboratory data from 942 patients, the PROPP statistic was developed (the Physician Reference Of Predicted Probabilities). Main effect variables included age, gender, and nine hematological and serum chemistry variables. The sensitivity of the current model is approximately 49%, specificity approximately 88%. Using prior probability estimates, however, in which the patient's likelihood of liver toxicity is presumed to be at least 30%, the positive predictive value ranged between 64-77%. Although the clinical utility of this statistic will require refinements and additional prospective confirmation, its potential existence speaks to the possibility of markers for idiosyncratic drug metabolism in patients with Alzheimer's disease.

SEURAT: Safety Evaluation Ultimately Replacing Animal Testing – Recommendations for future research in the field of predictive toxicology

EPA Science Inventory

The development of non-animal methodology to evaluate the potential for a chemical to cause systemic toxicity is one of the grand challenges of modern science. The European research programme SEURAT is active in this field and will conclude its first phase, SEURAT-1, in December ...

Methylene Blue as a Diagnostic Aid in the Early Detection of Potentially Malignant and Malignant Lesions of Oral Mucosa.

PubMed

Lejoy, Abraham; Arpita, Rai; Krishna, Burde; Venkatesh, Naikmasur

2016-05-01

In vivo stains are the prompt resources, which have emerged in recent years to aid as clinical diagnostic tools in detecting early potentially malignant and malignant lesions. Toluidine blue, by its property of retaining in the increased DNA and RNA cellular activity areas, aids in delineating the suspicious areas. However, it is hazardous if swallowed, and has been shown to have toxicity to fibroblasts. Methylene blue has a similar chemical structure and exhibits similar physicochemical properties as toluidine blue. It is less toxic to the human body and has recently been proposed for screening some gastrointestinal or prostate tumors. The application of this material in detecting oral lesions has so far not been addressed. The objective of this study was to evaluate the sensitivity and reliability of in vivo staining with methylene blue as a diagnostic adjunct in screening for oral malignant or potentially malignant lesions. The present study involved the examination of 75 patients suspected of having oral malignant or potentially malignant lesions by methylene blue staining. The results of methylene blue uptake were compared with a simultaneous biopsy of these lesions. The overall sensitivity was 95% (100% for malignancy and 92% for potentially malignant lesions) and specificity was 70%. The positive predictive value was 91% and negative predictive value of 80% was observed in the study. We consider that methylene blue staining is a useful diagnostic adjunct in a large, community-based oral cancer screening program for high-risk individuals.

SAR/QSAR MODELS FOR TOXICITY PREDICTION: APPROACHES AND NEW DIRECTIONS

EPA Science Inventory

Abstract

SAR/QSAR MODELS FOR TOXICITY PREDICTION: APPROACHES AND NEW DIRECTIONS

Risk assessment typically incorporates some relevant toxicity information upon which to base a sound estimation for a chemical of concern. However, there are many circumstances in whic...

Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method.

PubMed

Zhang, Hui; Ren, Ji-Xia; Kang, Yan-Li; Bo, Peng; Liang, Jun-Yu; Ding, Lan; Kong, Wei-Bao; Zhang, Ji

2017-08-01

Toxicological testing associated with developmental toxicity endpoints are very expensive, time consuming and labor intensive. Thus, developing alternative approaches for developmental toxicity testing is an important and urgent task in the drug development filed. In this investigation, the naïve Bayes classifier was applied to develop a novel prediction model for developmental toxicity. The established prediction model was evaluated by the internal 5-fold cross validation and external test set. The overall prediction results for the internal 5-fold cross validation of the training set and external test set were 96.6% and 82.8%, respectively. In addition, four simple descriptors and some representative substructures of developmental toxicants were identified. Thus, we hope the established in silico prediction model could be used as alternative method for toxicological assessment. And these obtained molecular information could afford a deeper understanding on the developmental toxicants, and provide guidance for medicinal chemists working in drug discovery and lead optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction of mutagenic toxicity by combination of Recursive Partitioning and Support Vector Machines.

PubMed

Liao, Quan; Yao, Jianhua; Yuan, Shengang

2007-05-01

The study of prediction of toxicity is very important and necessary because measurement of toxicity is typically time-consuming and expensive. In this paper, Recursive Partitioning (RP) method was used to select descriptors. RP and Support Vector Machines (SVM) were used to construct structure-toxicity relationship models, RP model and SVM model, respectively. The performances of the two models are different. The prediction accuracies of the RP model are 80.2% for mutagenic compounds in MDL's toxicity database, 83.4% for compounds in CMC and 84.9% for agrochemicals in in-house database respectively. Those of SVM model are 81.4%, 87.0% and 87.3% respectively.

Mixture toxicity of wood preservative products in the fish embryo toxicity test.

PubMed

Coors, Anja; Dobrick, Jan; Möder, Monika; Kehrer, Anja

2012-06-01

Wood preservative products are used globally to protect wood from fungal decay and insects. We investigated the aquatic toxicity of five commercial wood preservative products, the biocidal active substances and some formulation additives contained therein, as well as six generic binary mixtures of the active substances in the fish embryo toxicity test (FET). Median lethal concentrations (LC50) of the single substances, the mixtures, and the products were estimated from concentration-response curves and corrected for concentrations measured in the test medium. The comparison of the experimentally observed mixture toxicity with the toxicity predicted by the concept of concentration addition (CA) showed less than twofold deviation for all binary mixtures of the active substances and for three of the biocidal products. A more than 60-fold underestimation of the toxicity of the fourth product by the CA prediction was detected and could be explained fully by the toxicity of one formulation additive, which had been labeled as a hazardous substance. The reason for the 4.6-fold underestimation of toxicity of the fifth product could not be explained unambiguously. Overall, the FET was found to be a suitable screening tool to verify whether the toxicity of formulated wood preservatives can reliably be predicted by CA. Applied as a quick and simple nonanimal screening test, the FET may support approaches of applying component-based mixture toxicity predictions within the environmental risk assessment of biocidal products, which is required according to European regulations. Copyright © 2012 SETAC.

Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

PubMed Central

Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

2017-01-01

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

Predicting acute contact toxicity of pesticides in honeybees (Apis mellifera) through a k-nearest neighbor model.

PubMed

Como, F; Carnesecchi, E; Volani, S; Dorne, J L; Richardson, J; Bassan, A; Pavan, M; Benfenati, E

2017-01-01

Ecological risk assessment of plant protection products (PPPs) requires an understanding of both the toxicity and the extent of exposure to assess risks for a range of taxa of ecological importance including target and non-target species. Non-target species such as honey bees (Apis mellifera), solitary bees and bumble bees are of utmost importance because of their vital ecological services as pollinators of wild plants and crops. To improve risk assessment of PPPs in bee species, computational models predicting the acute and chronic toxicity of a range of PPPs and contaminants can play a major role in providing structural and physico-chemical properties for the prioritisation of compounds of concern and future risk assessments. Over the last three decades, scientific advisory bodies and the research community have developed toxicological databases and quantitative structure-activity relationship (QSAR) models that are proving invaluable to predict toxicity using historical data and reduce animal testing. This paper describes the development and validation of a k-Nearest Neighbor (k-NN) model using in-house software for the prediction of acute contact toxicity of pesticides on honey bees. Acute contact toxicity data were collected from different sources for 256 pesticides, which were divided into training and test sets. The k-NN models were validated with good prediction, with an accuracy of 70% for all compounds and of 65% for highly toxic compounds, suggesting that they might reliably predict the toxicity of structurally diverse pesticides and could be used to screen and prioritise new pesticides. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Pharmacogenomics in neuro-oncology].

PubMed

Riese-Jorda, H H; Baez, J M

Chemotherapy protocols for treatment of brain tumors use toxic molecules for killing cancer cells in a similar way that protocols for treating other cancers. Therefore, secondary effects and poor response are the major handicaps. Technological developments based on pharmacogenomics and pharmacoproteomics will predict response and toxicity giving rise to a personalized medicine. However, there are only few studies that correlate chemotherapeutical molecules for brain tumor treatment and prediction of response and toxicity. The development of new technologies based on high-density microarrays allows the progressive identification of genes whose presence will predict the efficacy of therapeutic protocols. Once identified, specific equipments based on low-density arrays will detect exclusively in an easy and fast way the presence of genes in order to predict patient's response and avoid toxicity. Other more sophisticated techniques at present still at an experimental step based on proteomics as MALDI (Matrix-Assisted Laser Desorption Ionization) and SELDI (Surface-Enhanced Laser Desorption Ionization) will allow the identification of proteins that could predict response and toxicity.

Validation of a biotic ligand model on site-specific copper toxicity to Daphnia magna in the Yeongsan River, Korea.

PubMed

Park, Jinhee; Ra, Jin-Sung; Rho, Hojung; Cho, Jaeweon; Kim, Sang Don

2018-03-01

The objective of this study was to determine whether the water effect ratio (WER) or biotic ligand model (BLM) could be applied to efficiently develop water quality criteria (WQC) in Korea. Samples were collected from 12 specific sites along the Yeongsan River (YSR), Korea, including two sewage treatment plants and one estuary lake. A copper toxicity test using Daphnia magna was performed to determine the WER and to compare to the BLM prediction. The results of the WER from YSR samples also indicated significantly different copper toxicities in all sites. The model-based predictions showed that effluent and estuary waters had significantly different properties in regard to their ability to be used to investigate water characteristics and copper toxicity. It was supposed that the slight water characteristics changes, such as pH, DOC, hardness, conductivity, among others, influence copper toxicity, and these variable effects on copper toxicity interacted with the water composition. The 38% prediction was outside of the validation range by a factor of two in all sites, showing a poor predictive ability, especially in STPs and streams adjacent to the estuary, while the measured toxicity was more stable. The samples that ranged from pH 7.3-7.7 generated stable predictions, while other samples, including those with lower and the higher pH values, led to more unstable predictions. The results also showed that the toxicity of Cu in sample waters to D. magna was closely proportional to the amounts of acidity, including the carboxylic and phenolic groups, as well as the DOC concentrations. Consequently, the acceptable prediction of metal toxicity in various water samples needs the site-specific results considering the water characteristics such as pH and DOC properties particularly in STPs and estuary regions. Copyright © 2017 Elsevier Inc. All rights reserved.

CON4EI: CONsortium for in vitro Eye Irritation testing strategy - EpiOcular™ time-to-toxicity (EpiOcular ET-50) protocols for hazard identification and labelling of eye irritating chemicals.

PubMed

Kandarova, Helena; Letasiova, Silvia; Adriaens, Els; Guest, Robert; Willoughby, Jamin A; Drzewiecka, Agnieszka; Gruszka, Katarzyna; Alépée, Nathalie; Verstraelen, Sandra; Van Rompay, An R

2018-06-01

Assessment of acute eye irritation potential is part of the international regulatory requirements for testing of chemicals. The objective of the CON4EI (CONsortium for in vitro Eye Irritation testing strategy) project was to develop tiered testing strategies for eye irritation assessment for all drivers of classification. A set of 80 reference chemicals (38 liquids and 42 solids) was tested with eight different alternative methods. Here, the results obtained with reconstructed human cornea-like epithelium (RhCE) EpiOcular™ in the EpiOcular time-to-toxicity Tests (Neat and Dilution ET-50 protocols) are presented. The primary aim of this study was to evaluate whether test methods can discriminate chemicals not requiring classification for serious eye damage/eye irritancy (No Category) from chemicals requiring classification and labelling for Category 1 and Category 2. In addition, the predictive capacity in terms of in vivo drivers of classification was investigated. The chemicals were tested in two independent runs by MatTek In Vitro Life Science Laboratories. Results of this study demonstrate very high specificity of both test protocols. With the existing prediction models described in the SOPs, the specificity of the Neat and Dilution method was 87% and 100%, respectively. The Dilution method was able to correctly predicting 66% of GHS Cat 2 chemicals, however, prediction of GHS Cat 1 chemicals was only 47%-55% using the current protocols. In order to achieve optimal prediction for all three classes, a testing strategy was developed which combines the most predictive time-points of both protocols and for tests liquids and solids separately. Using this new testing strategy, the sensitivity for predicting GHS Cat 1 and GHS Cat 2 chemicals was 73% and 64%, respectively and the very high specificity of 97% was maintained. None of the Cat 1 chemicals was underpredicted as GHS No Category. Further combination of the EpiOcular time-to-toxicity protocols with other validated in vitro systems evaluated in this project, should enable significant reduction and even possible replacement of the animal tests for the final assessment of the irritation potential in all of the GHS classes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of Caenorhabditis elegans (nematode) and Danio rerio embryo (zebrafish) as model systems to screen for developmental and reproductive toxicity of Piperazine compounds.

PubMed

Racz, Peter I; Wildwater, Marjolein; Rooseboom, Martijn; Kerkhof, Engelien; Pieters, Raymond; Yebra-Pimentel, Elena Santidrian; Dirks, Ron P; Spaink, Herman P; Smulders, Chantal; Whale, Graham F

2017-10-01

To enable selection of novel chemicals for new processes, there is a recognized need for alternative toxicity screening assays to assess potential risks to man and the environment. For human health hazard assessment these screening assays need to be translational to humans, have high throughput capability, and from an animal welfare perspective be harmonized with the principles of the 3Rs (Reduction, Refinement, Replacement). In the area of toxicology a number of cell culture systems are available but while these have some predictive value, they are not ideally suited for the prediction of developmental and reproductive toxicology (DART). This is because they often lack biotransformation capacity, multicellular or multi- organ complexity, for example, the hypothalamus pituitary gonad (HPG) axis and the complete life cycle of whole organisms. To try to overcome some of these limitations in this study, we have used Caenorhabditis elegans (nematode) and Danio rerio embryos (zebrafish) as alternative assays for DART hazard assessment of some candidate chemicals being considered for a new commercial application. Nematodes exposed to Piperazine and one of the analogs tested showed a slight delay in development compared to untreated animals but only at high concentrations and with Piperazine as the most sensitive compound. Total brood size of the nematodes was also reduced primarily by Piperazine and one of the analogs. In zebrafish Piperazine and analogs showed developmental delays. Malformations and mortality in individual fish were also scored. Significant malformations were most sensitively identified with Piperazine, significant mortality was only observed in Piperazine and only at the higest dose. Thus, Piperazine seemed the most toxic compound for both nematodes and zebrafish. The results of the nematode and zebrafish studies were in alignment with data obtained from conventional mammalian toxicity studies indicating that these have potential as developmental toxicity screening systems. The results of these studies also provided reassurance that none of the Piperazines tested are likely to have any significant developmental and/or reproductive toxicity issues to humans when used in their commercial applications. Copyright © 2017. Published by Elsevier Ltd.

Observed and predicted reproduction of Ceriodaphnia dubia exposed to chloride, sulfate, and bicarbonate

USGS Publications Warehouse

Lasier, Peter J.; Hardin, Ian R.

2010-01-01

Chronic toxicities of Cl-, SO42-, and HCO3- to Ceriodaphnia dubia were evaluated in low- and moderate-hardness waters using a three-brood reproduction test method. Toxicity tests of anion mixtures were used to determine interaction effects and to produce models predicting C. dubia reproduction. Effluents diluted with low- and moderate-hardness waters were tested with animals acclimated to low- and moderate-hardness conditions to evaluate the models and to assess the effects of hardness and acclimation. Sulfate was significantly less toxic than Cl- and HCO3- in both types of water. Chloride and HCO3- toxicities were similar in low-hardness water, but HCO3- was the most toxic in moderate-hardness water. Low acute-to-chronic ratios indicate that toxicities of these anions will decrease quickly with dilution. Hardness significantly reduced Cl- and SO42- toxicity but had little effect on HCO3-. Chloride toxicity decreased with an increase in Na+ concentration, and CO3- toxicity may have been reduced by the dissolved organic carbon in effluent. Multivariate models using measured anion concentrations in effluents with low to moderate hardness levels provided fairly accurate predictions of reproduction. Determinations of toxicity for several effluents differed significantly depending on the hardness of the dilution water and the hardness of the water used to culture test animals. These results can be used to predict the contribution of elevated anion concentrations to the chronic toxicity of effluents; to identify effluents that are toxic due to contaminants other than Cl-, SO42-, and HCO3-; and to provide a basis for chemical substitutions in manufacturing processes.

Predicting human developmental toxicity of pharmaceuticals using human embryonic stem cells and metabolomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

West, Paul R., E-mail: pwest@stemina.co; Weir, April M.; Smith, Alan M.

2010-08-15

Teratogens, substances that may cause fetal abnormalities during development, are responsible for a significant number of birth defects. Animal models used to predict teratogenicity often do not faithfully correlate to human response. Here, we seek to develop a more predictive developmental toxicity model based on an in vitro method that utilizes both human embryonic stem (hES) cells and metabolomics to discover biomarkers of developmental toxicity. We developed a method where hES cells were dosed with several drugs of known teratogenicity then LC-MS analysis was performed to measure changes in abundance levels of small molecules in response to drug dosing. Statisticalmore » analysis was employed to select for specific mass features that can provide a prediction of the developmental toxicity of a substance. These molecules can serve as biomarkers of developmental toxicity, leading to better prediction of teratogenicity. In particular, our work shows a correlation between teratogenicity and changes of greater than 10% in the ratio of arginine to asymmetric dimethylarginine levels. In addition, this study resulted in the establishment of a predictive model based on the most informative mass features. This model was subsequently tested for its predictive accuracy in two blinded studies using eight drugs of known teratogenicity, where it correctly predicted the teratogenicity for seven of the eight drugs. Thus, our initial data shows that this platform is a robust alternative to animal and other in vitro models for the prediction of the developmental toxicity of chemicals that may also provide invaluable information about the underlying biochemical pathways.« less

A Review of Pharmacological Treatment Options for Lung Cancer: Emphasis on Novel Nanotherapeutics and Associated Toxicity.

PubMed

England, Christopher G; Ng, Chin F; van Berkel, Victor; Frieboes, Hermann B

2015-01-01

Lung cancer remains a leading cause of death. Current treatment options are generally ineffective, highlighting the dire need for novel approaches. While numerous biologically-active chemotherapeutics have been discovered in the last two decades, biological barriers including minimal water solubility, stability, and cellular resistance hinder in vivo effectiveness. To overcome these limitations, nanoparticles have been designed to deliver chemotherapeutics selectively to cancerous tissue while minimizing pharmacokinetics hindrance. Numerous studies are underway analyzing the efficacy of nanoparticles in drug delivery, theranostic applications, and photothermal therapy. However, while nanoparticles have shown efficacy in treating some cancers, their potential toxicity and lack of targeting may hinder clinical potential. With the aim to help sort through these issues, we conduct a review to describe recent applications of nanotherapeutics for the treatment and diagnosis of lung cancer. We first provide a detailed background of statistics, etiology, histological classification, staging, diagnosis, and current treatment options. This is followed by a description of current applications of nanotherapeutics, focusing primarily on results published during the past five years. The potential toxicity associated with nanoparticles is evaluated, revealing inconclusive information which highlights the need for further studies. Lastly, recent advances in mathematical modeling and computational simulation have shown potential in predicting tumor response to nanotherapeutics. Thus, although nanoparticles have shown promise in treating lung cancer, further multi-disciplinary studies to quantify optimal dosages and assess possible toxicity are still needed. To this end, nanotherapeutic options currently in clinical trials offer hope to help address some of these critical issues.

Acute Toxicity Prediction to Threatened and Endangered Species Using Interspecies Correlation Estimation (ICE) Models.

PubMed

Willming, Morgan M; Lilavois, Crystal R; Barron, Mace G; Raimondo, Sandy

2016-10-04

Evaluating contaminant sensitivity of threatened and endangered (listed) species and protectiveness of chemical regulations often depends on toxicity data for commonly tested surrogate species. The U.S. EPA's Internet application Web-ICE is a suite of Interspecies Correlation Estimation (ICE) models that can extrapolate species sensitivity to listed taxa using least-squares regressions of the sensitivity of a surrogate species and a predicted taxon (species, genus, or family). Web-ICE was expanded with new models that can predict toxicity to over 250 listed species. A case study was used to assess protectiveness of genus and family model estimates derived from either geometric mean or minimum taxa toxicity values for listed species. Models developed from the most sensitive value for each chemical were generally protective of the most sensitive species within predicted taxa, including listed species, and were more protective than geometric means models. ICE model estimates were compared to HC5 values derived from Species Sensitivity Distributions for the case study chemicals to assess protectiveness of the two approaches. ICE models provide robust toxicity predictions and can generate protective toxicity estimates for assessing contaminant risk to listed species.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Identification of Chemical Vascular Disruptors During Development Using An Integrative Predictive Toxicity Model and Zebrafish and in Vitro Functional Angiogenesis Assays.

EPA Science Inventory

Identification of chemical vascular disruptors during development using an integrative predictive toxicity model and zebrafish and in vitro functional angiogenesis assays Chemically-induced vascular toxicity during embryonic development can result in a wide range of adverse pre...

Behaviour of five pharmaceuticals with high baseline toxicity in wastewater treatment

NASA Astrophysics Data System (ADS)

van Driezum, Inge; McArdell, Christa; Fenner, Kathrin; Helbling, Damian; van Breukelen, Boris

2013-04-01

Many pharmaceuticals enter the aquatic environment through sewer systems and are partially removed in wastewater treatment plants (WWTP) by sorption to sludge biomass or biodegradation. Biodegradation often does not lead to complete mineralization but to the formation of stable transformation products (TPs), which might still be harmful to the environment. Recently, a study was undertaken to assess the risk of the top 100 pharmaceuticals from wastewater of a hospital in Switzerland. The predicted toxicity was linked to the predicted environmental concentration in order to assess overall risk potential. In this study, biodegradation and sorption studies were carried out on the top five selected pharmaceuticals (amiodarone, atorvastatin, clotrimazole, meclozine and ritonavir). Potential TPs that are formed during activated sludge treatment were identified and concentrations of both the parent compounds and TPs were measured in the WWTP. With this data, the fate of these compounds was modeled in a WWTP system using a multi-reactor steady-state WWTP model. This study showed that sorption was the most important loss process for amiodarone and meclozine. They had an elimination of more than 99%. Sorption was also the main loss process for clotrimazole, but it was combined with some biodegradation. For ritonavir, both biodegradation and sorption played a role in the loss of this compound. The most important removal process for atorvastatin was biodegradation. Four TPs, formed through β-oxidation and monohydroxilation, were identified in both the activated sludge batch reactors and the WWTP effluent. In the WWTP effluent, only atorvastatin, clotrimazole and ritonavir were found. All identified TPs of atorvastatin were detected in the effluent. Risk quotients (RQ) of all five pharmaceuticals were estimated based on effluent concentration and baseline toxicity and ranged from zero to 2.14. Only ritonavir potentially poses an ecotoxicological risk for the aquatic environment.

Computational protein design and protein-ligand interaction studies for the improvement of organophosphorus degrading potential of Deinococcus radiodurans.

PubMed

Manoharan, Prabu; Sridhar, J

2018-05-01

The organophosphorus hydrolase enzyme is involved in the catalyzing reaction that involve hydrolysis of organophosphate toxic compounds. An enzyme from Deinococcus radiodurans reported as homologous to phosphotriesterase and show activity against organophosphate. In the past activity of this enzyme is low and efforts made to improve the activity by experimental mutation study. However only very few organophosphates tested against very few catalytic site mutations. In order to improve the catalytic power of the organophosphorus hydrolase enzyme, we carried out systematic functional hotspot based protein engineering strategy. The mutants tested against 46 know organophosphate compounds using molecular docking study. Finally, we carried out an extensive molecular docking study to predict the binding of 46 organophosphate compounds to wild-type protein and mutant organophosphorus hydrolase enzyme. At the end we are able to improve the degrading potential of organophosphorus hydrolase enzyme against organophosphate toxic compounds. This preliminary study and the outcome would be useful guide for the experimental scientist involved in the bioremediation of toxic organophosphate compounds. Copyright © 2018 Elsevier Inc. All rights reserved.

Humanized mouse model of glucose 6-phosphate dehydrogenase deficiency for in vivo assessment of hemolytic toxicity.

PubMed

Rochford, Rosemary; Ohrt, Colin; Baresel, Paul C; Campo, Brice; Sampath, Aruna; Magill, Alan J; Tekwani, Babu L; Walker, Larry A

2013-10-22

Individuals with glucose 6-phosphate dehydrogenase (G6PD) deficiency are at risk for the development of hemolytic anemia when given 8-aminoquinolines (8-AQs), an important class of antimalarial/antiinfective therapeutics. However, there is no suitable animal model that can predict the clinical hemolytic potential of drugs. We developed and validated a human (hu)RBC-SCID mouse model by giving nonobese diabetic/SCID mice daily transfusions of huRBCs from G6PD-deficient donors. Treatment of SCID mice engrafted with G6PD-deficient huRBCs with primaquine, an 8-AQ, resulted in a dose-dependent selective loss of huRBCs. To validate the specificity of this model, we tested known nonhemolytic antimalarial drugs: mefloquine, chloroquine, doxycycline, and pyrimethamine. No significant loss of G6PD-deficient huRBCs was observed. Treatment with drugs known to cause hemolytic toxicity (pamaquine, sitamaquine, tafenoquine, and dapsone) resulted in loss of G6PD-deficient huRBCs comparable to primaquine. This mouse model provides an important tool to test drugs for their potential to cause hemolytic toxicity in G6PD-deficient populations.

Developmental Effects of the ToxCast™ Phase I and Phase II Chemicals in Caenorhabditis elegans and Corresponding Responses in Zebrafish, Rats, and Rabbits

PubMed Central

Boyd, Windy A.; Smith, Marjolein V.; Co, Caroll A.; Pirone, Jason R.; Rice, Julie R.; Shockley, Keith R.; Freedman, Jonathan H.

2015-01-01

Background: Modern toxicology is shifting from an observational to a mechanistic science. As part of this shift, high-throughput toxicity assays are being developed using alternative, nonmammalian species to prioritize chemicals and develop prediction models of human toxicity. Methods: The nematode Caenorhabditis elegans (C. elegans) was used to screen the U.S. Environmental Protection Agency’s (EPA’s) ToxCast™ Phase I and Phase II libraries, which contain 292 and 676 chemicals, respectively, for chemicals leading to decreased larval development and growth. Chemical toxicity was evaluated using three parameters: a biologically defined effect size threshold, half-maximal activity concentration (AC50), and lowest effective concentration (LEC). Results: Across both the Phase I and Phase II libraries, 62% of the chemicals were classified as active ≤ 200 μM in the C. elegans assay. Chemical activities and potencies in C. elegans were compared with those from two zebrafish embryonic development toxicity studies and developmental toxicity data for rats and rabbits. Concordance of chemical activity was higher between C. elegans and one zebrafish assay across Phase I chemicals (79%) than with a second zebrafish assay (59%). Using C. elegans or zebrafish to predict rat or rabbit developmental toxicity resulted in balanced accuracies (the average value of the sensitivity and specificity for an assay) ranging from 45% to 53%, slightly lower than the concordance between rat and rabbit (58%). Conclusions: Here, we present an assay that quantitatively and reliably describes the effects of chemical toxicants on C. elegans growth and development. We found significant overlap in the activity of chemicals in the ToxCast™ libraries between C. elegans and zebrafish developmental screens. Incorporating C. elegans toxicological assays as part of a battery of in vitro and in vivo assays provides additional information for the development of models to predict a chemical’s potential toxicity to humans. Citation: Boyd WA, Smith MV, Co CA, Pirone JR, Rice JR, Shockley KR, Freedman JH. 2016. Developmental effects of the ToxCast™ Phase I and II chemicals in Caenorhabditis elegans and corresponding responses in zebrafish, rats, and rabbits. Environ Health Perspect 124:586–593; http://dx.doi.org/10.1289/ehp.1409645 PMID:26496690

A systems-level approach for investigating organophosphorus pesticide toxicity.

PubMed

Zhu, Jingbo; Wang, Jing; Ding, Yan; Liu, Baoyue; Xiao, Wei

2018-03-01

The full understanding of the single and joint toxicity of a variety of organophosphorus (OP) pesticides is still unavailable, because of the extreme complex mechanism of action. This study established a systems-level approach based on systems toxicology to investigate OP pesticide toxicity by incorporating ADME/T properties, protein prediction, and network and pathway analysis. The results showed that most OP pesticides are highly toxic according to the ADME/T parameters, and can interact with significant receptor proteins to cooperatively lead to various diseases by the established OP pesticide -protein and protein-disease networks. Furthermore, the studies that multiple OP pesticides potentially act on the same receptor proteins and/or the functionally diverse proteins explained that multiple OP pesticides could mutually enhance toxicological synergy or additive on a molecular/systematic level. To the end, the integrated pathways revealed the mechanism of toxicity of the interaction of OP pesticides and elucidated the pathogenesis induced by OP pesticides. This study demonstrates a systems-level approach for investigating OP pesticide toxicity that can be further applied to risk assessments of various toxins, which is of significant interest to food security and environmental protection. Copyright © 2017 Elsevier Inc. All rights reserved.

Characteristics of suspended solids affect bifenthrin toxicity to the calanoid copepods Eurytemora affinis and Pseudodiaptomus forbesi.

PubMed

Parry, Emily; Lesmeister, Sarah; Teh, Swee; Young, Thomas M

2015-10-01

Bifenthrin is a pyrethroid pesticide that is highly toxic to aquatic invertebrates. The dissolved concentration is generally thought to be the best predictor of acute toxicity. However, for the filter-feeding calanoid copepods Eurytemora affinis and Pseudodiaptomus forbesi, ingestion of pesticide-bound particles could prove to be another route of exposure. The present study investigated bifenthrin toxicity to E. affinis and P. forbesi in the presence of suspended solids from municipal wastewater effluent and surface water of the San Francisco (CA, USA) Estuary. Suspended solids mitigated the toxicity of total bifenthrin to E. affinis and P. forbesi, but mortality was higher than what would be predicted from dissolved concentrations alone. The results indicate that the toxicity and bioavailability of particle-associated bifenthrin was significantly correlated with counts of 0.5-µm to 2-µm particle sizes. Potential explanations could include direct ingestion of bifenthrin-bound particles, changes in food consumption and feeding behavior, and physical contact with small particles. The complex interactions between pesticides and particles of different types and sizes demonstrate a need for future ecotoxicological studies to investigate the role of particle sizes on aquatic organisms. © 2015 SETAC.

Poison frog colors are honest signals of toxicity, particularly for bird predators.

PubMed

Maan, Martine E; Cummings, Molly E

2012-01-01

Antipredator defenses and warning signals typically evolve in concert. However, the extensive variation across taxa in both these components of predator deterrence and the relationship between them are poorly understood. Here we test whether there is a predictive relationship between visual conspicuousness and toxicity levels across 10 populations of the color-polymorphic strawberry poison frog, Dendrobates pumilio. Using a mouse-based toxicity assay, we find extreme variation in toxicity between frog populations. This variation is significantly positively correlated with frog coloration brightness, a viewer-independent measure of visual conspicuousness (i.e., total reflectance flux). We also examine conspicuousness from the view of three potential predator taxa, as well as conspecific frogs, using taxon-specific visual detection models and three natural background substrates. We find very strong positive relationships between frog toxicity and conspicuousness for bird-specific perceptual models. Weaker but still positive correlations are found for crab and D. pumilio conspecific visual perception, while frog coloration as viewed by snakes is not related to toxicity. These results suggest that poison frog colors can be honest signals of prey unpalatability to predators and that birds in particular may exert selection on aposematic signal design. © 2011 by The University of Chicago.

Modelling interactions of toxicants and density dependence in wildlife populations

USGS Publications Warehouse

Schipper, Aafke M.; Hendriks, Harrie W.M.; Kauffman, Matthew J.; Hendriks, A. Jan; Huijbregts, Mark A.J.

2013-01-01

1. A major challenge in the conservation of threatened and endangered species is to predict population decline and design appropriate recovery measures. However, anthropogenic impacts on wildlife populations are notoriously difficult to predict due to potentially nonlinear responses and interactions with natural ecological processes like density dependence. 2. Here, we incorporated both density dependence and anthropogenic stressors in a stage-based matrix population model and parameterized it for a density-dependent population of peregrine falcons Falco peregrinus exposed to two anthropogenic toxicants [dichlorodiphenyldichloroethylene (DDE) and polybrominated diphenyl ethers (PBDEs)]. Log-logistic exposure–response relationships were used to translate toxicant concentrations in peregrine falcon eggs to effects on fecundity. Density dependence was modelled as the probability of a nonbreeding bird acquiring a breeding territory as a function of the current number of breeders. 3. The equilibrium size of the population, as represented by the number of breeders, responded nonlinearly to increasing toxicant concentrations, showing a gradual decrease followed by a relatively steep decline. Initially, toxicant-induced reductions in population size were mitigated by an alleviation of the density limitation, that is, an increasing probability of territory acquisition. Once population density was no longer limiting, the toxicant impacts were no longer buffered by an increasing proportion of nonbreeders shifting to the breeding stage, resulting in a strong decrease in the equilibrium number of breeders. 4. Median critical exposure concentrations, that is, median toxicant concentrations in eggs corresponding with an equilibrium population size of zero, were 33 and 46 μg g−1 fresh weight for DDE and PBDEs, respectively. 5. Synthesis and applications. Our modelling results showed that particular life stages of a density-limited population may be relatively insensitive to toxicant impacts until a critical threshold is crossed. In our study population, toxicant-induced changes were observed in the equilibrium number of nonbreeding rather than breeding birds, suggesting that monitoring efforts including both life stages are needed to timely detect population declines. Further, by combining quantitative exposure–response relationships with a wildlife demographic model, we provided a method to quantify critical toxicant thresholds for wildlife population persistence.

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Cross, Kevin P.

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describemore » the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.« less

Urinary metabonomics study on toxicity biomarker discovery in rats treated with Xanthii Fructus.

PubMed

Lu, Fang; Cao, Min; Wu, Bin; Li, Xu-zhao; Liu, Hong-yu; Chen, Da-zhong; Liu, Shu-min

2013-08-26

Xanthii Fructus (XF) is commonly called "Cang-Erzi" in traditional Chinese medicine (TCM) and widely used for the treatment of sinusitis, headache, rheumatism, and skin itching. However, the clinical utilization of XF is relatively restricted owing to its toxicity. To discover the characteristic potential biomarkers in rats treated with XF by urinary metabonomics. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was applied in the study. The total ion chromatograms obtained from control and different dosage groups were distinguishable by a multivariate statistical analysis method. The greatest difference in metabolic profile was observed between high dosage group and control group, and the metabolic characters in rats treated with XF were perturbed in a dose-dependent manner. The metabolic changes in response for XF treatment were observed in urinary samples, which were revealed by orthogonal projection to latent structures discriminate analysis (OPLS-DA), and 10 metabolites could be served as the potential toxicity biomarkers. In addition, the mechanism associated with the damages of lipid per-oxidation and the metabolic disturbances of fatty acid oxidation were investigated. These results indicate that metabonomics analysis in urinary samples may be useful for predicting the toxicity induced by XF. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Pluripotent stem cell derived hepatocyte like cells and their potential in toxicity screening.

PubMed

Greenhough, Sebastian; Medine, Claire N; Hay, David C

2010-12-30

Despite considerable progress in modelling human liver toxicity, the requirement still exists for efficient, predictive and cost effective in vitro models to reduce attrition during drug development. Thousands of compounds fail in this process, with hepatotoxicity being one of the significant causes of failure. The cost of clinical studies is substantial, therefore it is essential that toxicological screening is performed early on in the drug development process. Human hepatocytes represent the gold standard model for evaluating drug toxicity, but are a limited resource. Current alternative models are based on immortalised cell lines and animal tissue, but these are limited by poor function, exhibit species variability and show instability in culture. Pluripotent stem cells are an attractive alternative as they are capable of self-renewal and differentiation to all three germ layers, and thereby represent a potentially inexhaustible source of somatic cells. The differentiation of human embryonic stem cells and induced pluripotent stem cells to functional hepatocyte like cells has recently been reported. Further development of this technology could lead to the scalable production of hepatocyte like cells for liver toxicity screening and clinical therapies. Additionally, induced pluripotent stem cell derived hepatocyte like cells may permit in vitro modelling of gene polymorphisms and genetic diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Formation of toxic 2-nonyl-p-benzoquinones from α-tertiary 4-nonylphenol isomers during microbial metabolism of technical nonylphenol.

PubMed

Gabriel, Frédéric L P; Mora, Mauricio Arrieta; Kolvenbach, Boris A; Corvini, Philippe F X; Kohler, Hans-Peter E

2012-06-05

In many environmental compartments, microbial degradation of α-quaternary nonylphenols proceeds along an ipso-substitution pathway. It has been reported that technical nonylphenol contains, besides α-quaternary nonylphenols, minor amounts of various α-H, α-methyl substituted tertiary isomers. Here, we show that potentially toxic metabolites of such minor components are formed during ipso-degradation of technical nonylphenol by Sphingobium xenophagum Bayram, a strain isolated from activated sewage sludge. Small but significant amounts of nonylphenols were converted to the corresponding nonylhydroquinones, which in the presence of air oxygen oxidized to the corresponding nonyl-p-benzoquinones-yielding a complex mixture of potentially toxic metabolites. Through reduction with ascorbic acid and subsequent analysis by gas chromatography-mass spectrometry, we were able to characterize this unique metabolic fingerprint and to show that its components originated for the most part from α-tertiary nonylphenol isomers. Furthermore, our results indicate that the metabolites mixture also contained several α, β-dehydrogenated derivatives of nonyl-p-benzoquinones that originated by hydroxylation induced rearrangement, and subsequent ring and side chain oxidation from α-tertiary nonylphenol isomers. We predict that in nonylphenol polluted natural systems, in which microbial ipso-degradation is prominent, 2-alkylquinone metabolites will be produced and will contribute to the overall toxicity of the remaining material.

An exposure system for measuring nasal and lung uptake of vapors in rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dahl, A.R.; Brookins, L.K.; Gerde, P.

1995-12-01

Inhaled gases and vapors often produce biological damage in the nasal cavity and lower respiratory tract. The specific site within the respirator tract at which a gas or vapor is absorbed strongly influences the tissues at risk to potential toxic effects; to predict or to explain tissue or cell specific toxicity of inhaled gases or vapors, the sites at which they are absorbed must be known. The purpose of the work reported here was to develop a system for determining nose and lung absorption of vapors in rats, an animal commonly used in inhalation toxicity studies. In summary, the exposuremore » system described allows us to measure in the rate: (1) nasal absorption and desorption of vapors; (2) net lung uptake of vapors; and (3) the effects of changed breathing parameters on vapor uptake.« less

Analysis and prediction of structure-reactive toxicity relationships of substituted aromatic compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Z.T.; Wang, L.S.; Chen, S.P.

1996-12-31

The fundamental differentiation of toxicity is between reactive and nonreactive toxicity. Reactive toxicity is associated with a specific mechanism for the reaction with an enzyme or inhibition of a metabolic pathway, and nonreactive toxicity is related directly to the quantity of toxicant acting upon the cell. The quantitative structure-activity relationships (QSARs) have been successfully used in the nonreactive toxicity, such as prediction of the toxicity of nonreactive compounds based on their solubility in the lipids of organisms. The elements of molecular structure that are most closely related to nonreactive toxicity are those that describe the partitioning of the toxicant intomore » the organism, while QSARs for the reactive toxicity are less common in the environmental toxicology literature. With the recent increase in the use of synthetic substituted benzenes as industrial chemicals, the accurate analysis of the effect of reactive toxic chemicals has become recognized with QSAR. For this purpose, we selected the fish (Carassias auratus) as the test organism, measured the acute toxicity of 50% lethal concentration (LC{sub 50}) of the chemicals and the adenosine triphosphate (ATP) content of the liver cells for the organism. These determined the relationships of the acute toxicity of some substituted benzenes with their physicochemical structural parameters. The effects on the ATP content was also compared to predict biological reactivities of the chemicals, so as to find some clues to explain the mode of mechanism of the toxicity. 17 refs., 1 tab.« less

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: II. A focus on growth impairment in fish.

PubMed

Groh, Ksenia J; Carvalho, Raquel N; Chipman, James K; Denslow, Nancy D; Halder, Marlies; Murphy, Cheryl A; Roelofs, Dick; Rolaki, Alexandra; Schirmer, Kristin; Watanabe, Karen H

2015-02-01

Adverse outcome pathways (AOPs) organize knowledge on the progression of toxicity through levels of biological organization. By determining the linkages between toxicity events at different levels, AOPs lay the foundation for mechanism-based alternative testing approaches to hazard assessment. Here, we focus on growth impairment in fish to illustrate the initial stages in the process of AOP development for chronic toxicity outcomes. Growth is an apical endpoint commonly assessed in chronic toxicity tests for which a replacement is desirable. Based on several criteria, we identified reduction in food intake to be a suitable key event for initiation of middle-out AOP development. To start exploring the upstream and downstream links of this key event, we developed three AOP case studies, for pyrethroids, selective serotonin reuptake inhibitors (SSRIs) and cadmium. Our analysis showed that the effect of pyrethroids and SSRIs on food intake is strongly linked to growth impairment, while cadmium causes a reduction in growth due to increased metabolic demands rather than changes in food intake. Locomotion impairment by pyrethroids is strongly linked to their effects on food intake and growth, while for SSRIs their direct influence on appetite may play a more important role. We further discuss which alternative tests could be used to inform on the predictive key events identified in the case studies. In conclusion, our work demonstrates how the AOP concept can be used in practice to assess critically the knowledge available for specific chronic toxicity cases and to identify existing knowledge gaps and potential alternative tests. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study

NASA Astrophysics Data System (ADS)

Zhen, Xin; Chen, Jiawei; Zhong, Zichun; Hrycushko, Brian; Zhou, Linghong; Jiang, Steve; Albuquerque, Kevin; Gu, Xuejun

2017-11-01

Better understanding of the dose-toxicity relationship is critical for safe dose escalation to improve local control in late-stage cervical cancer radiotherapy. In this study, we introduced a convolutional neural network (CNN) model to analyze rectum dose distribution and predict rectum toxicity. Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively collected, including twelve toxicity patients and thirty non-toxicity patients. We adopted a transfer learning strategy to overcome the limited patient data issue. A 16-layers CNN developed by the visual geometry group (VGG-16) of the University of Oxford was pre-trained on a large-scale natural image database, ImageNet, and fine-tuned with patient rectum surface dose maps (RSDMs), which were accumulated EBRT  +  BT doses on the unfolded rectum surface. We used the adaptive synthetic sampling approach and the data augmentation method to address the two challenges, data imbalance and data scarcity. The gradient-weighted class activation maps (Grad-CAM) were also generated to highlight the discriminative regions on the RSDM along with the prediction model. We compare different CNN coefficients fine-tuning strategies, and compare the predictive performance using the traditional dose volume parameters, e.g. D 0.1/1/2cc, and the texture features extracted from the RSDM. Satisfactory prediction performance was achieved with the proposed scheme, and we found that the mean Grad-CAM over the toxicity patient group has geometric consistence of distribution with the statistical analysis result, which indicates possible rectum toxicity location. The evaluation results have demonstrated the feasibility of building a CNN-based rectum dose-toxicity prediction model with transfer learning for cervical cancer radiotherapy.

Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study.

PubMed

Zhen, Xin; Chen, Jiawei; Zhong, Zichun; Hrycushko, Brian; Zhou, Linghong; Jiang, Steve; Albuquerque, Kevin; Gu, Xuejun

2017-10-12

Better understanding of the dose-toxicity relationship is critical for safe dose escalation to improve local control in late-stage cervical cancer radiotherapy. In this study, we introduced a convolutional neural network (CNN) model to analyze rectum dose distribution and predict rectum toxicity. Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively collected, including twelve toxicity patients and thirty non-toxicity patients. We adopted a transfer learning strategy to overcome the limited patient data issue. A 16-layers CNN developed by the visual geometry group (VGG-16) of the University of Oxford was pre-trained on a large-scale natural image database, ImageNet, and fine-tuned with patient rectum surface dose maps (RSDMs), which were accumulated EBRT  +  BT doses on the unfolded rectum surface. We used the adaptive synthetic sampling approach and the data augmentation method to address the two challenges, data imbalance and data scarcity. The gradient-weighted class activation maps (Grad-CAM) were also generated to highlight the discriminative regions on the RSDM along with the prediction model. We compare different CNN coefficients fine-tuning strategies, and compare the predictive performance using the traditional dose volume parameters, e.g. D 0.1/1/2cc , and the texture features extracted from the RSDM. Satisfactory prediction performance was achieved with the proposed scheme, and we found that the mean Grad-CAM over the toxicity patient group has geometric consistence of distribution with the statistical analysis result, which indicates possible rectum toxicity location. The evaluation results have demonstrated the feasibility of building a CNN-based rectum dose-toxicity prediction model with transfer learning for cervical cancer radiotherapy.

ECOSAR model performance with a large test set of industrial chemicals.

PubMed

Reuschenbach, Peter; Silvani, Maurizio; Dammann, Martina; Warnecke, Dietmar; Knacker, Thomas

2008-05-01

The widely used ECOSAR computer programme for QSAR prediction of chemical toxicity towards aquatic organisms was evaluated by using large data sets of industrial chemicals with varying molecular structures. Experimentally derived toxicity data covering acute effects on fish, Daphnia and green algae growth inhibition of in total more than 1,000 randomly selected substances were compared to the prediction results of the ECOSAR programme in order (1) to assess the capability of ECOSAR to correctly classify the chemicals into defined classes of aquatic toxicity according to rules of EU regulation and (2) to determine the number of correct predictions within tolerance factors from 2 to 1,000. Regarding ecotoxicity classification, 65% (fish), 52% (Daphnia) and 49% (algae) of the substances were correctly predicted into the classes "not harmful", "harmful", "toxic" and "very toxic". At all trophic levels about 20% of the chemicals were underestimated in their toxicity. The class of "not harmful" substances (experimental LC/EC(50)>100 mg l(-1)) represents nearly half of the whole data set. The percentages for correct predictions of toxic effects on fish, Daphnia and algae growth inhibition were 69%, 64% and 60%, respectively, when a tolerance factor of 10 was allowed. Focussing on those experimental results which were verified by analytically measured concentrations, the predictability for Daphnia and algae toxicity was improved by approximately three percentage points, whereas for fish no improvement was determined. The calculated correlation coefficients demonstrated poor correlation when the complete data set was taken, but showed good results for some of the ECOSAR chemical classes. The results are discussed in the context of literature data on the performance of ECOSAR and other QSAR models.

Genetic risk variants as therapeutic targets for Crohn's disease.

PubMed

Gabbani, Tommaso; Deiana, Simona; Marocchi, Margherita; Annese, Vito

2017-04-01

The pathogenesis of Inflammatory bowel diseases (IBD) is multifactorial, with interactions between genetic and environmental factors. Despite the existence of genetic factors being largely demonstrated by epidemiological data and several genetic studies, only a few findings have been useful in term of disease prediction, disease progression and targeting therapy. Areas covered: This review summarizes the results of genome-wide association studies in Crohn's disease, the role of epigenetics and the recent discovery by genetic studies of new pathogenetic pathways. Furthermore, it focuses on the importance of applying genetic data to clinical practice, and more specifically how to better target therapy and predict potential drug-related toxicity. Expert opinion: Some genetic markers identified in Crohn`s disease have allowed investigators to hypothesize about, and in some cases, prove the usefulness of new specific therapeutic agents. However, the heterogeneity and complexity of this disease has so far limited the daily clinical use of genetic information. Finally, the study of the implications of genetics on therapy, either to predict efficacy or avoid toxicity, is considered still to be in its infancy.

Sediment porewater toxicity assessment studies in the vicinity of offshore oil and gas production platforms in the Gulf of Mexico

USGS Publications Warehouse

Carr, R.S.; Chapman, D.C.; Presley, B.J.; Biedenbach, J.M.; Robertson, L.; Boothe, P.; Kilada, R.; Wade, T.; Montagna, P.

1996-01-01

As part of a multidisciplinary program to assess the potential long-term impacts of offshore oil and gas exploration and production activities in the Gulf of Mexico, sediment chemical analyses and porewater toxicity tests were conducted in the vicinity of five offshore platforms. Based on data from sea urchin fertilization and embryological development assays, toxicity was observed near four of the five platforms sampled; the majority of the toxic samples were collected within 150 m of a platform. There was excellent agreement among the results of porewater tests with three different species (sea urchin embryological development, polychaete reproduction, and copepod nauplii survival). The sediment concentrations of several metals were well in excess of sediment quality assessment guidelines at a number of stations, and good agreement was observed between predicted and observed toxicity. Porewater metal concentrations compared with EC50, LOEC, and NOEC values generated for water-only exposures indicated that the porewater concentrations for several metals were high enough to account for the observed toxicity. Results of these studies utilizing highly sensitive toxicity tests suggest that the contaminant-induced impacts from offshore platforms are limited to a localized area in the immediate vicinity of the platforms. 

Assessing the concentrations and risks of toxicity from the antibiotics ciprofloxacin, sulfamethoxazole, trimethoprim and erythromycin in European rivers.

PubMed

Johnson, Andrew C; Keller, Virginie; Dumont, Egon; Sumpter, John P

2015-04-01

This study evaluated the potential concentrations of four antibiotics: ciprofloxacin (CIP), sulfamethoxazole (SUF), trimethoprim (TRI) and erythromycin (ERY) throughout the rivers of Europe. This involved reviewing national consumption rates together with assessing excretion and sewage treatment removal rates. From this information, it was possible to construct best, expected and worst case scenarios for the discharge of these antibiotics into rivers. Consumption data showed surprising variations, up to 200-fold in the popularity of different antibiotics across different European nations. Using the water resources model GWAVA which has a spatial resolution of approximately 6×9 km, river water concentrations throughout Europe were predicted based on 31-year climate data. The modelled antibiotic concentrations were within the range of measurements reported previously in European effluents and rivers. With the expected scenario, the predicted annual-average antibiotic concentrations ranged between 0 and 10 ng/L for 90% by length of surface waters. In the worst case scenario concentrations could reach between 0.1 and 1 μg/L at the most exposed locations. As both predicted and observed sewage effluent concentrations were below reported effect levels for the most sensitive aquatic wildlife, no direct toxicity in rivers is expected. Predicted river concentrations for CIP and ERY were closest to effect levels in wildlife, followed by SUF which was 2-3 orders of magnitude lower. TRI appeared to be of the least concern with around 6 orders of magnitude difference between predicted and effect levels. However, mixture toxicity may elevate this risk and antibiotic levels of 0.1-1 μg/L in hotspots may contribute to local environmental antibiotic resistance in microorganisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Mechanistic-based non-animal assessment of eye toxicity: Inflammatory profile of human keratinocytes cells after exposure to eye damage/irritant agents.

PubMed

da Silva, Artur Christian Garcia; Chialchia, Adrienny Rodrigues; de Ávila, Renato Ivan; Valadares, Marize Campos

2018-06-25

Eye toxicity is a mandatory parameter in human risk and safety evaluation for products including chemicals, pesticides, medicines and cosmetics. Historically, this endpoint has been evaluated using the Draize rabbit eye test, an in vivo model that was never formally validated. Due to advances in scientific knowledge, economic and ethical issues, non-animal methods based on mechanisms of toxicity are being developed and validated for increasing the capability of these models to predict eye toxicity. In this study, the Cytometric Bead Array (CBA) and ELISA assays were used to evaluate the inflammatory cytokine profile produced by HaCaT human keratinocytes after exposure to chemicals with different UN GHS eye toxicity classifications, aiming to stablish a correlation between inflammatory endpoints and eye toxicity (damage/irritation) potential. As a first step, cytotoxic profile of the chemicals, including 3 non-irritants and 10 eye toxicants (GHS Category 1, 2A and 2B), was evaluated after 24 h exposure using MTT assay and Inhibitory Concentration of 20% of cell viability (IC 20 ) was calculated for each chemical. Then, the cells were exposed to these chemicals at IC 20 for 24 h and supernatants and cell lysates were analyzed by CBA assay for quantification of the following cytokines: IL-6, IL-8, IL-10, IL-1β, TNF and IL-12p70. Regarding cytotoxicity evaluation, chemicals showed different cytotoxicity profiles and data demonstrated no correlation with their UN GHS classification. Among the cytokines evaluated, IL-1β production has changed after exposure and such alterations were confirmed by quantification employing ELISA method. The higher intracellular levels of IL-1β were found in GHS Category 1 chemicals, followed by Category 2A and 2B, while non irritants did not induce such increase. Thus, these findings show that IL-1β measurement, using HaCaT model, can be a considerable biomarker to identify chemicals according to their potential in promote eye toxicity, differentiating damage from irritation potential. Copyright © 2018. Published by Elsevier B.V.

Predicting acute and chronic effects of wood preservative products in Daphnia magna and Pseudokirchneriella subcapitata based on the concept of concentration addition.

PubMed

Coors, Anja; Weisbrod, Barbara; Schoknecht, Ute; Sacher, Frank; Kehrer, Anja

2014-02-01

The current European legislation requires that combined effects of the active substances and any substance of concern contained in biocidal products are taken into account in environmental risk assessment. The hypothesis whether the consideration of active substances together with all formulation additives that are labeled as presenting an environmental hazard is sufficient for a reliable environmental risk assessment was tested in the present study by investigating 3 wood preservative products. Relevant single substances in the products, some of their generic mixtures, the biocidal products themselves, and aqueous eluates prepared from the products (representing potential environmental mixtures) were tested for effects on algal growth and Daphnia acute immobilization as well as reproduction. Predictions for the products and the eluates were based on the concept of concentration addition and were mostly found to provide reliable or at least protective estimates for the observed acute and chronic toxicity of the mixtures. The mixture toxicity considerations also indicated that the toxicity of each product was dominated by just 1 of the components, and that assessments based only on the dominating substance would be similarly protective as a full-mixture risk assessment. Yet, there remained uncertainty in some cases that could be related to the toxicity of transformation products, the impact of unidentified formulation additives, or synergistic interaction between active substances and formulation additives. © 2013 SETAC.

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

EPA Science Inventory

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

Development of structure-activity relationship for metal oxide nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Rong; Zhang, Hai Yuan; Ji, Zhao Xia; Rallo, Robert; Xia, Tian; Chang, Chong Hyun; Nel, Andre; Cohen, Yoram

2013-05-01

Nanomaterial structure-activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose-response analysis and consensus self-organizing map clustering. The NP cellular toxicity dataset included toxicity profiles consisting of seven different assays for human bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells, over a concentration range of 0.39-100 mg L-1 and exposure time up to 24 h, for twenty-four different metal oxide NPs. Various nano-SAR building models were evaluated, based on an initial pool of thirty NP descriptors. The conduction band energy and ionic index (often correlated with the hydration enthalpy) were identified as suitable NP descriptors that are consistent with suggested toxicity mechanisms for metal oxide NPs and metal ions. The best performing nano-SAR with the above two descriptors, built with support vector machine (SVM) model and of validated robustness, had a balanced classification accuracy of ~94%. An applicability domain for the present data was established with a reasonable confidence level of 80%. Given the potential role of nano-SARs in decision making, regarding the environmental impact of NPs, the class probabilities provided by the SVM nano-SAR enabled the construction of decision boundaries with respect to toxicity classification under different acceptance levels of false negative relative to false positive predictions.Nanomaterial structure-activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose-response analysis and consensus self-organizing map clustering. The NP cellular toxicity dataset included toxicity profiles consisting of seven different assays for human bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells, over a concentration range of 0.39-100 mg L-1 and exposure time up to 24 h, for twenty-four different metal oxide NPs. Various nano-SAR building models were evaluated, based on an initial pool of thirty NP descriptors. The conduction band energy and ionic index (often correlated with the hydration enthalpy) were identified as suitable NP descriptors that are consistent with suggested toxicity mechanisms for metal oxide NPs and metal ions. The best performing nano-SAR with the above two descriptors, built with support vector machine (SVM) model and of validated robustness, had a balanced classification accuracy of ~94%. An applicability domain for the present data was established with a reasonable confidence level of 80%. Given the potential role of nano-SARs in decision making, regarding the environmental impact of NPs, the class probabilities provided by the SVM nano-SAR enabled the construction of decision boundaries with respect to toxicity classification under different acceptance levels of false negative relative to false positive predictions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr01533e

Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

PubMed Central

Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

2015-01-01

Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used with predicted toxicity results. Furthermore, by presenting the suitability of individual predicted results, we aimed to provide a foundation that could be used in actual assessments and regulations. PMID:26206368

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

In general, the accuracy of a predicted toxicity value increases with increase in similarity between the query chemical and the chemicals used to develop a QSAR model. A toxicity estimation methodology employing this finding has been developed. A hierarchical based clustering t...

Organic Pollutants in Shale Gas Flowback and Produced Waters: Identification, Potential Ecological Impact, and Implications for Treatment Strategies.

PubMed

Butkovskyi, Andrii; Bruning, Harry; Kools, Stefan A E; Rijnaarts, Huub H M; Van Wezel, Annemarie P

2017-05-02

Organic contaminants in shale gas flowback and produced water (FPW) are traditionally expressed as total organic carbon (TOC) or chemical oxygen demand (COD), though these parameters do not provide information on the toxicity and environmental fate of individual components. This review addresses identification of individual organic contaminants in FPW, and stresses the gaps in the knowledge on FPW composition that exist so far. Furthermore, the risk quotient approach was applied to predict the toxicity of the quantified organic compounds for fresh water organisms in recipient surface waters. This resulted in an identification of a number of FPW related organic compounds that are potentially harmful namely those compounds originating from shale formations (e.g., polycyclic aromatic hydrocarbons, phthalates), fracturing fluids (e.g., quaternary ammonium biocides, 2-butoxyethanol) and downhole transformations of organic compounds (e.g., carbon disulfide, halogenated organic compounds). Removal of these compounds by FPW treatment processes is reviewed and potential and efficient abatement strategies are defined.

Organic Pollutants in Shale Gas Flowback and Produced Waters: Identification, Potential Ecological Impact, and Implications for Treatment Strategies

PubMed Central

2017-01-01

Organic contaminants in shale gas flowback and produced water (FPW) are traditionally expressed as total organic carbon (TOC) or chemical oxygen demand (COD), though these parameters do not provide information on the toxicity and environmental fate of individual components. This review addresses identification of individual organic contaminants in FPW, and stresses the gaps in the knowledge on FPW composition that exist so far. Furthermore, the risk quotient approach was applied to predict the toxicity of the quantified organic compounds for fresh water organisms in recipient surface waters. This resulted in an identification of a number of FPW related organic compounds that are potentially harmful namely those compounds originating from shale formations (e.g., polycyclic aromatic hydrocarbons, phthalates), fracturing fluids (e.g., quaternary ammonium biocides, 2-butoxyethanol) and downhole transformations of organic compounds (e.g., carbon disulfide, halogenated organic compounds). Removal of these compounds by FPW treatment processes is reviewed and potential and efficient abatement strategies are defined. PMID:28376616

Development of linear free energy relationships for aqueous phase radical-involved chemical reactions.

PubMed

Minakata, Daisuke; Mezyk, Stephen P; Jones, Jace W; Daws, Brittany R; Crittenden, John C

2014-12-02

Aqueous phase advanced oxidation processes (AOPs) produce hydroxyl radicals (HO•) which can completely oxidize electron rich organic compounds. The proper design and operation of AOPs require that we predict the formation and fate of the byproducts and their associated toxicity. Accordingly, there is a need to develop a first-principles kinetic model that can predict the dominant reaction pathways that potentially produce toxic byproducts. We have published some of our efforts on predicting the elementary reaction pathways and the HO• rate constants. Here we develop linear free energy relationships (LFERs) that predict the rate constants for aqueous phase radical reactions. The LFERs relate experimentally obtained kinetic rate constants to quantum mechanically calculated aqueous phase free energies of activation. The LFERs have been applied to 101 reactions, including (1) HO• addition to 15 aromatic compounds; (2) addition of molecular oxygen to 65 carbon-centered aliphatic and cyclohexadienyl radicals; (3) disproportionation of 10 peroxyl radicals, and (4) unimolecular decay of nine peroxyl radicals. The LFERs correlations predict the rate constants within a factor of 2 from the experimental values for HO• reactions and molecular oxygen addition, and a factor of 5 for peroxyl radical reactions. The LFERs and the elementary reaction pathways will enable us to predict the formation and initial fate of the byproducts in AOPs. Furthermore, our methodology can be applied to other environmental processes in which aqueous phase radical-involved reactions occur.

Conditional Toxicity Value (CTV) Predictor: An In Silico Approach for Generating Quantitative Risk Estimates for Chemicals.

PubMed

Wignall, Jessica A; Muratov, Eugene; Sedykh, Alexander; Guyton, Kathryn Z; Tropsha, Alexander; Rusyn, Ivan; Chiu, Weihsueh A

2018-05-01

Human health assessments synthesize human, animal, and mechanistic data to produce toxicity values that are key inputs to risk-based decision making. Traditional assessments are data-, time-, and resource-intensive, and they cannot be developed for most environmental chemicals owing to a lack of appropriate data. As recommended by the National Research Council, we propose a solution for predicting toxicity values for data-poor chemicals through development of quantitative structure-activity relationship (QSAR) models. We used a comprehensive database of chemicals with existing regulatory toxicity values from U.S. federal and state agencies to develop quantitative QSAR models. We compared QSAR-based model predictions to those based on high-throughput screening (HTS) assays. QSAR models for noncancer threshold-based values and cancer slope factors had cross-validation-based Q 2 of 0.25-0.45, mean model errors of 0.70-1.11 log 10 units, and applicability domains covering >80% of environmental chemicals. Toxicity values predicted from QSAR models developed in this study were more accurate and precise than those based on HTS assays or mean-based predictions. A publicly accessible web interface to make predictions for any chemical of interest is available at http://toxvalue.org. An in silico tool that can predict toxicity values with an uncertainty of an order of magnitude or less can be used to quickly and quantitatively assess risks of environmental chemicals when traditional toxicity data or human health assessments are unavailable. This tool can fill a critical gap in the risk assessment and management of data-poor chemicals. https://doi.org/10.1289/EHP2998.

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

Development of a category approach to predict the testicular toxicity of chemical substances structurally related to ethylene glycol methyl ether.

PubMed

Yamada, Takashi; Tanaka, Yushiro; Hasegawa, Ryuichi; Sakuratani, Yuki; Yamazoe, Yasushi; Ono, Atsushi; Hirose, Akihiko; Hayashi, Makoto

2014-12-01

We propose a category approach to assessing the testicular toxicity of chemicals with a similar structure to ethylene glycol methyl ether (EGME). Based on toxicity information for EGME and related chemicals and accompanied by adverse outcome pathway information on the testicular toxicity of EGME, this category was defined as chemicals that are metabolized to methoxy- or ethoxyacetic acid, a substance responsible for testicular toxicity. A Japanese chemical inventory was screened using the Hazard Evaluation Support System, which we have developed to support a category approach for predicting the repeated-dose toxicity of chemical substances. Quantitative metabolic information on the related chemicals was then considered, and seventeen chemicals were finally obtained from the inventory as a shortlist for the category. Available data in the literature shows that chemicals for which information is available on the metabolic formation of EGME, ethylene glycol ethyl ether, methoxy- or ethoxyacetic acid do in fact possess testicular toxicity, suggesting that testicular toxicity is a concern, due to metabolic activation, for the remaining chemicals. Our results clearly demonstrate practical utility of AOP-based category approach for predicting repeated-dose toxicity of chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessment of trace metals contamination level, bioavailability and toxicity in sediments from Dakar coast and Saint Louis estuary in Senegal, West Africa.

PubMed

Diop, Cheikh; Dewaelé, Dorothée; Cazier, Fabrice; Diouf, Amadou; Ouddane, Baghdad

2015-11-01

Trace metals have the potential to associate with sediments that have been recognised as significant source of contamination for the benthic environment. The current study aims assessing the trace metals contamination level in sediments from Dakar coast and Saint Louis estuary, and to examine their bioavailability to predict potential toxicity of sediments. Surface sediment samples were collected between June 2012 and January 2013 in three sampling periods from eight stations. Trace metals were analysed using inductively coupled plasma-optical emission spectrometer. Geoaccumulation indexes (Igeo) showed strong pollution by Cd, Cr, Cu and Pb confirmed by enrichment factor (EF) suggesting that these metals derived from anthropogenic sources. Toxicity indexes exceeded one in several sites suggesting the potential effects on sediment-dwelling organisms, which may constitute a risk to populations' health. However, seasonal variability of metal bioavailability was noted, revealing the best period to monitor metal contamination. From an ecotoxicological point of view, concentrations of Cd, Cr, Cu and Pb were above the effects range low threshold limit of the sediment quality guidelines for adverse biological effects. In addition, with Pb concentrations above the effect range medium values in some sites, biological effects may occur. Copyright © 2014 Elsevier Ltd. All rights reserved.

Extensive review of fish embryo acute toxicities for the prediction of GHS acute systemic toxicity categories.

PubMed

Scholz, Stefan; Ortmann, Julia; Klüver, Nils; Léonard, Marc

2014-08-01

Distribution and marketing of chemicals require appropriate labelling of health, physical and environmental hazards according to the United Nations global harmonisation system (GHS). Labelling for (human) acute toxicity categories is based on experimental findings usually obtained by oral, dermal or inhalative exposure of rodents. There is a strong societal demand for replacing animal experiments conducted for safety assessment of chemicals. Fish embryos are considered as alternative to animal testing and are proposed as predictive model both for environmental and human health effects. Therefore, we tested whether LC50s of the fish embryo acute toxicity test would allow effectively predicting of acute mammalian toxicity categories. A database of published fish embryo LC50 containing 641 compounds was established. For these compounds corresponding rat oral LD50 were identified resulting in 364 compounds for which both fish embryo LC50 and rat LD50 was available. Only a weak correlation of fish embryo LC50 and rat oral LD50 was obtained. Fish embryos were also not able to effectively predict GHS oral acute toxicity categories. We concluded that due to fundamental exposure protocol differences (single oral dose versus water-borne exposure) a reverse dosimetry approach is needed to explore the predictive capacity of fish embryos. Copyright © 2014 Elsevier Inc. All rights reserved.

Non-animal Replacements for Acute Toxicity Testing.

PubMed

Barker-Treasure, Carol; Coll, Kevin; Belot, Nathalie; Longmore, Chris; Bygrave, Karl; Avey, Suzanne; Clothier, Richard

2015-07-01

Current approaches to predicting adverse effects in humans from acute toxic exposure to cosmetic ingredients still heavily necessitate the use of animals under EU legislation, particularly in the context of the REACH system, when cosmetic ingredients are also destined for use in other industries. These include the LD50 test, the Up-and-Down Procedure and the Fixed Dose Procedure, which are regarded as having notable scientific deficiencies and low transferability to humans. By expanding on previous in vitro tests, such as the animal cell-based 3T3 Neutral Red Uptake (NRU) assay, this project aims to develop a truly animal-free predictive test for the acute toxicity of cosmetic ingredients in humans, by using human-derived cells and a prediction model that does not rely on animal data. The project, funded by Innovate UK, will incorporate the NRU assay with human dermal fibroblasts in animal product-free culture, to generate an in vitro protocol that can be validated as an accepted replacement for the currently available in vivo tests. To date, the project has successfully completed an assessment of the robustness and reproducibility of the method, by using sodium lauryl sulphate (SLS) as a positive control, and displaying analogous results to those of the original studies with mouse 3T3 cells. Currently, the testing of five known ingredients from key groups (a surfactant, a preservative, a fragrance, a colour and an emulsifier) is under way. The testing consists of initial range-finding runs followed by three valid runs of a main experiment with the appropriate concentration ranges, to generate IC50 values. Expanded blind trials of 20 ingredients will follow. Early results indicate that this human cell-based test holds the potential to replace aspects of in vivo animal acute toxicity testing, particularly with reference to cosmetic ingredients. 2015 FRAME.

Use of biomarkers for the assessment of chemotherapy-induced cardiac toxicity

PubMed Central

Christenson, Eric S.; James, Theodore; Agrawal, Vineet; Park, Ben H.

2015-01-01

Objectives To review the evidence for the use of various biomarkers in the detection of chemotherapy associated cardiac damage. Design and methods Pubmed.gov was queried using the search words chemotherapy and cardiac biomarkers with the filters of past 10 years, humans, and English language. An emphasis was placed on obtaining primary research articles looking at the utility of biomarkers for the detection of chemotherapy-mediated cardiac injury. Results Biomarkers may help identify patients undergoing treatment who are at high risk for cardiotoxicity and may assist in identification of a low risk cohort that does not necessitate continued intensive screening. cTn assays are the best studied biomarkers in this context and may represent a promising and potentially valuable modality for detecting cardiac toxicity in patients undergoing chemotherapy. Monitoring cTnI levels may provide information regarding the development of cardiac toxicity before left ventricular dysfunction becomes apparent on echocardiography or via clinical symptoms. A host of other biomarkers have been evaluated for their utility in the field of chemotherapy related cardiac toxicity with intermittent success; further trials are necessary to determine what role they may end up playing for prediction and prognostication in this setting. Conclusions Biomarkers represent an exciting potential complement or replacement for echocardiographic monitoring of chemotherapy related cardiac toxicity which may allow for earlier realization of the degree of cardiac damage occurring during treatment, creating the opportunity for more timely modulation of therapy. PMID:25445234

Toxicity prediction of PHDDs and phenols in the light of nucleic acid bases and DNA base pair interaction.

PubMed

Mondal Roy, Sutapa; Roy, Debesh R; Sahoo, Suban K

2015-11-01

The applicability of Density Functional Theory (DFT) based descriptors for the development of quantitative structure-toxicity relationships (QSTR) is assessed for two different series of toxic aromatic compounds, viz., polyhalogenated dibenzo-p-dioxins (PHDDs) and phenols (PHs). A series of 20 compounds each for PHDDs and PHs with their experimental toxicities (IC50 and IGC50) is chosen in the present study to develop DFT based efficient quantum chemical parameters (QCPs) for explaining the toxin potential of the considered compounds. A systematic analysis to find out the electron donation/acceptance nature of these selected compounds with the considered model biosystems, viz., nucleic acid (NA) bases and DNA base pairs, is performed to identify potential QCPs. Accordingly, PHDDs is found to be electron acceptors whereas phenols as donors, during their interaction with biosystems. Two parameter regression model is carried out comprising global charge transfer (ΔN), and local Fukui Function's for nucleophilic attack (fk(+)) for PHDDs and the same for electrophilic attack (fk(-)) in case of PHs. It is heartening to note that our chosen descriptors, viz, charge transfer (ΔN) and Fukui Function (fk(±)) plays a crucial role by explaining more than 90% of the observed toxic behavior (in terms of correlation-coefficient, R) of PHDDs and PHs. The developed QCPs, viz., ΔN and fk(±) can be added as the new descriptors in the QSTR parlance. Copyright © 2015 Elsevier Inc. All rights reserved.

Extension of a PBPK model for ethylene glycol and glycolic acid to include the competitive formation and clearance of metabolites associated with kidney toxicity in rats and humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corley, R.A., E-mail: rick.corley@pnl.gov; Saghir, S.A.; Bartels, M.J.

2011-02-01

A previously developed PBPK model for ethylene glycol and glycolic acid was extended to include glyoxylic acid, oxalic acid, and the precipitation of calcium oxalate that is associated with kidney toxicity in rats and humans. The development and evaluation of the PBPK model was based upon previously published pharmacokinetic studies coupled with measured blood and tissue partition coefficients and rates of in vitro metabolism of glyoxylic acid to oxalic acid, glycine and other metabolites using primary hepatocytes isolated from male Wistar rats and humans. Precipitation of oxalic acid with calcium in the kidneys was assumed to occur only at concentrationsmore » exceeding the thermodynamic solubility product for calcium oxalate. This solubility product can be affected by local concentrations of calcium and other ions that are expressed in the model using an ion activity product estimated from toxicity studies such that calcium oxalate precipitation would be minimal at dietary exposures below the NOAEL for kidney toxicity in the sensitive male Wistar rat. The resulting integrated PBPK predicts that bolus oral or dietary exposures to ethylene glycol would result in typically 1.4-1.6-fold higher peak oxalate levels and 1.6-2-fold higher AUC's for calcium oxalate in kidneys of humans as compared with comparably exposed male Wistar rats over a dose range of 1-1000 mg/kg. The converse (male Wistar rats predicted to have greater oxalate levels in the kidneys than humans) was found for inhalation exposures although no accumulation of calcium oxalate is predicted to occur until exposures are well in excess of the theoretical saturated vapor concentration of 200 mg/m{sup 3}. While the current model is capable of such cross-species, dose, and route-of-exposure comparisons, it also highlights several areas of potential research that will improve confidence in such predictions, especially at low doses relevant for most human exposures.« less

Monitoring late-onset toxicities in phase I trials using predicted risks

PubMed Central

Bekele, B. Nebiyou; Ji, Yuan; Shen, Yu; Thall, Peter F.

2008-01-01

Late-onset (LO) toxicities are a serious concern in many phase I trials. Since most dose-limiting toxicities occur soon after therapy begins, most dose-finding methods use a binary indicator of toxicity occurring within a short initial time period. If an agent causes LO toxicities, however, an undesirably large number of patients may be treated at toxic doses before any toxicities are observed. A method addressing this problem is the time-to-event continual reassessment method (TITE-CRM, Cheung and Chappell, 2000). We propose a Bayesian dose-finding method similar to the TITE-CRM in which doses are chosen using time-to-toxicity data. The new aspect of our method is a set of rules, based on predictive probabilities, that temporarily suspend accrual if the risk of toxicity at prospective doses for future patients is unacceptably high. If additional follow-up data reduce the predicted risk of toxicity to an acceptable level, then accrual is restarted, and this process may be repeated several times during the trial. A simulation study shows that the proposed method provides a greater degree of safety than the TITE-CRM, while still reliably choosing the preferred dose. This advantage increases with accrual rate, but the price of this additional safety is that the trial takes longer to complete on average. PMID:18084008

Predicting the toxicity of sediment-associated trace metals with simultaneously extracted trace metal: Acid-volatile sulfide concentrations and dry weight-normalized concentrations: A critical comparison

USGS Publications Warehouse

Long, E.R.; MacDonald, D.D.; Cubbage, J.C.; Ingersoll, C.G.

1998-01-01

The relative abilities of sediment concentrations of simultaneously extracted trace metal: acid-volatile sulfide (SEM: AVS) and dry weight-normalized trace metals to correctly predict both toxicity and nontoxicity were compared by analysis of 77 field-collected samples. Relative to the SEM:AVS concentrations, sediment guidelines based upon dry weight-normalized concentrations were equally or slightly more accurate in predicting both nontoxic and toxic results in laboratory tests.

SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions

DOE PAGES

Mansfeldt, Cresten B.; Logsdon, Benjamin A.; Debs, Garrett E.; ...

2015-02-25

We present a statistical model designed to identify the effect of experimental perturbations on the aggregate behavior of the transcriptome expressed by the bacterium Dehalococcoides mccartyi strain 195. Strains of Dehalococcoides are used in sub-surface bioremediation applications because they organohalorespire tetrachloroethene and trichloroethene (common chlorinated solvents that contaminate the environment) to non-toxic ethene. However, the biochemical mechanism of this process remains incompletely described. Additionally, the response of Dehalococcoides to stress-inducing conditions that may be encountered at field-sites is not well understood. The constructed statistical model captured the aggregate behavior of gene expression phenotypes by modeling the distinct eigengenes of 100more » transcript clusters, determining stable relationships among these clusters of gene transcripts with a sparse network-inference algorithm, and directly modeling the effect of changes in experimental conditions by constructing networks conditioned on the experimental state. Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. The network identified a cluster containing thirteen gene transcripts directly connected to the solvent toxicity condition. Transcripts in this cluster include an iron-dependent regulator (DET0096-97) and a methylglyoxal synthase (DET0137). To validate these predictions, additional experiments were performed. Continuously fed cultures were exposed to saturating levels of tetrachloethene, thereby causing solvent toxicity, and transcripts that were predicted to be linked to solvent toxicity were monitored by quantitative reverse-transcription polymerase chain reaction. Twelve hours after being shocked with saturating levels of tetrachloroethene, the control transcripts (encoding for a key hydrogenase and the 16S rRNA) did not significantly change. By contrast, transcripts for DET0137 and DET0097 displayed a 46.8±11.5 and 14.6±9.3 fold up-regulation, respectively, supporting the model. This is the first study to identify transcripts in Dehalococcoides that potentially respond to tetrachloroethene solvent-toxicity conditions that may be encountered near contamination source zones in sub-surface environments.« less

Trace elements in coal. Environmental and health significance

USGS Publications Warehouse

Finkelman, R.B.

1999-01-01

Trace elements can have profound adverse effects on the health of people burning coal in homes or living near coal deposits, coal mines, and coal- burning power plants. Trace elements such as arsenic emitted from coal- burning power plants in Europe and Asia have been shown to cause severe health problems. Perhaps the most widespread health problems are caused by domestic coal combustion in developing countries where millions of people suffer from fluorosis and thousands from arsenism. Better knowledge of coal quality characteristics may help to reduce some of these health problems. For example, information on concentrations and distributions of potentially toxic elements in coal may help delineate areas of a coal deposit to be avoided. Information on the modes of occurrence of these elements and the textural relations of the minerals in coal may help to predict the behavior of the potentially toxic trace metals during coal cleaning, combustion, weathering, and leaching.

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

PubMed

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Prediction of the bioavailability of potentially toxic elements in freshwaters. Comparison between speciation models and passive samplers.

PubMed

Sierra, Jordi; Roig, Neus; Giménez Papiol, Gemma; Pérez-Gallego, Elena; Schuhmacher, Marta

2017-12-15

The aim of this work is to predict the bioavailability of the Potentially Toxic Elements (PTEs) Cd, Pb, Hg, Ni, Cu, Zn, As, Cr and Se in 6 sites within the Ebro River basin. In situ Diffusive gradient in thin-films (DGTs) and classical sampling have been used and compared. The potentially bioavailable fractions of each PTE was estimated by modelling their chemical speciation using three programs (WHAM 7.0, Visual MINTEQ 3.1 and Bio-met), following the suggestions published in recent European regulations. Results of the equilibrium-based models WHAM 7.0 and Visual MINTEQ 3.1 indicate that As, Cd, Ni, Se and Zn, predominate as free metals ions or forming inorganic soluble complexes. Copper, Pb and Hg bioavailability is conditioned by their affinity to dissolved humic substances. According to Visual MINTEQ 3.1, Cr is subjected to redox reactions, being Cr (VI) present (at low concentrations) in the studied rivers. According to Bio-met model, the bioavailability of Cu and Zn is highly influenced by soluble organic matter and water hardness, respectively. For most PTEs, the bioavailability estimated by deploying DGTs in river waters tends to be slightly lower than the estimation obtained with speciation models, since in real conditions more environmental factors take place comparing to the finite number of parameters considered in models. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and validation of a metal mixture bioavailability model (MMBM) to predict chronic toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia.

PubMed

Nys, Charlotte; Janssen, Colin R; De Schamphelaere, Karel A C

2017-01-01

Recently, several bioavailability-based models have been shown to predict acute metal mixture toxicity with reasonable accuracy. However, the application of such models to chronic mixture toxicity is less well established. Therefore, we developed in the present study a chronic metal mixture bioavailability model (MMBM) by combining the existing chronic daphnid bioavailability models for Ni, Zn, and Pb with the independent action (IA) model, assuming strict non-interaction between the metals for binding at the metal-specific biotic ligand sites. To evaluate the predictive capacity of the MMBM, chronic (7d) reproductive toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia was investigated in four different natural waters (pH range: 7-8; Ca range: 1-2 mM; Dissolved Organic Carbon range: 5-12 mg/L). In each water, mixture toxicity was investigated at equitoxic metal concentration ratios as well as at environmental (i.e. realistic) metal concentration ratios. Statistical analysis of mixture effects revealed that observed interactive effects depended on the metal concentration ratio investigated when evaluated relative to the concentration addition (CA) model, but not when evaluated relative to the IA model. This indicates that interactive effects observed in an equitoxic experimental design cannot always be simply extrapolated to environmentally realistic exposure situations. Generally, the IA model predicted Ni-Zn-Pb mixture toxicity more accurately than the CA model. Overall, the MMBM predicted Ni-Zn-Pb mixture toxicity (expressed as % reproductive inhibition relative to a control) in 85% of the treatments with less than 20% error. Moreover, the MMBM predicted chronic toxicity of the ternary Ni-Zn-Pb mixture at least equally accurately as the toxicity of the individual metal treatments (RMSE Mix  = 16; RMSE Zn only  = 18; RMSE Ni only  = 17; RMSE Pb only  = 23). Based on the present study, we believe MMBMs can be a promising tool to account for the effects of water chemistry on metal mixture toxicity during chronic exposure and could be used in metal risk assessment frameworks. Copyright © 2016 Elsevier Ltd. All rights reserved.

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Pre-therapy mRNA expression of TNF is associated with regimen-related gastrointestinal toxicity in patients with esophageal cancer: a pilot study.

PubMed

Bowen, J M; White, I; Smith, L; Tsykin, A; Kristaly, K; Thompson, S K; Karapetis, C S; Tan, H; Game, P A; Irvine, T; Hussey, D J; Watson, D I; Keefe, D M K

2015-11-01

Esophageal cancer has a high mortality rate, and its multimodality treatment is often associated with significant rates of severe toxicity. Effort is needed to uncover ways to maximize effectiveness of therapy through identification of predictive markers of response and toxicity. As such, the aim of this study was to identify genes predictive of chemoradiotherapy-induced gastrointestinal toxicity using an immune pathway-targeted approach. Adults with esophageal cancer treated with chemotherapy consisting of 5-fluorouracil and cisplatin and 45-50 Gy radiation were recruited to the study. Pre-therapy-collected whole blood was analyzed for relative expression of immune genes using real-time polymerase chain reaction (RT-PCR). Gene expression was compared between patients who experienced severe regimen-related gastrointestinal toxicity vs. those experiencing mild to moderate toxicity. Blood from 31 patients were analyzed by RT-PCR. Out of 84 immune genes investigated, TNF was significantly elevated (2.05-fold, p = 0.025) in the toxic group (n = 12) compared to the non-toxic group (n = 19). Nausea and vomiting was the most commonly documented severe toxicity. No associations between toxicity and response, age, sex, histology, or treatment were evident. This study supports evidence of TNF as a predictive biomarker in regimen-related gastrointestinal toxicity. Confirming these findings in a larger cohort is warranted.

Effects of rainfall patterns on toxic cyanobacterial blooms in a changing climate: between simplistic scenarios and complex dynamics.

PubMed

Reichwaldt, Elke S; Ghadouani, Anas

2012-04-01

Toxic cyanobacterial blooms represent a serious hazard to environmental and human health, and the management and restoration of affected waterbodies can be challenging. While cyanobacterial blooms are already a frequent occurrence, in the future their incidence and severity are predicted to increase due to climate change. Climate change is predicted to lead to increased temperature and changes in rainfall patterns, which will both have a significant impact on inland water resources. While many studies indicate that a higher temperature will favour cyanobacterial bloom occurrences, the impact of changed rainfall patterns is widely under-researched and therefore less understood. This review synthesizes the predicted changes in rainfall patterns and their potential impact on inland waterbodies, and identifies mechanisms that influence the occurrence and severity of toxic cyanobacterial blooms. It is predicted that there will be a higher frequency and intensity of rainfall events with longer drought periods in between. Such changes in the rainfall patterns will lead to favourable conditions for cyanobacterial growth due to a greater nutrient input into waterbodies during heavy rainfall events, combined with potentially longer periods of high evaporation and stratification. These conditions are likely to lead to an acceleration of the eutrophication process and prolonged warm periods without mixing of the water column. However, the frequent occurrence of heavy rain events can also lead to a temporary disruption of cyanobacterial blooms due to flushing and de-stratification, and large storm events have been shown to have a long-term negative effect on cyanobacterial blooms. In contrast, a higher number of small rainfall events or wet days can lead to proliferation of cyanobacteria, as they can rapidly use nutrients that are added during rainfall events, especially if stratification remains unchanged. With rainfall patterns changing, cyanobacterial toxin concentration in waterbodies is expected to increase. Firstly, this is due to accelerated eutrophication which supports higher cyanobacterial biomass. Secondly, predicted changes in rainfall patterns produce more favourable growth conditions for cyanobacteria, which is likely to increase the toxin production rate. However, the toxin concentration in inland waterbodies will also depend on the effect of rainfall events on cyanobacterial strain succession, a process that is still little understood. Low light conditions after heavy rainfall events might favour non-toxic strains, whilst inorganic nutrient input might promote the dominance of toxic strains in blooms. This review emphasizes that the impact of changes in rainfall patterns is very complex and will strongly depend on the site-specific dynamics, cyanobacterial species composition and cyanobacterial strain succession. More effort is needed to understand the relationship between rainfall patterns and cyanobacterial bloom dynamics, and in particular toxin production, to be able to assess and mediate the significant threat cyanobacterial blooms pose to our water resources. Copyright © 2011 Elsevier Ltd. All rights reserved.

ACToR-AGGREGATED COMPUTATIONAL TOXICOLOGY ...

EPA Pesticide Factsheets

One goal of the field of computational toxicology is to predict chemical toxicity by combining computer models with biological and toxicological data. predict chemical toxicity by combining computer models with biological and toxicological data

EPA's ToxCast Program for Predicting Hazard and Prioritizing the Toxicity Testing of Environmental Chemicals

EPA Science Inventory

An alternative is to perform a set of relatively inexpensive and rapid high throughput screening (HTS) assays, derive signatures predictive of effects or modes of chemical toxicity from the HTS data, then use these predictions to prioritize chemicals for more detailed analysis. T...

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

PubMed Central

Chen, Ming; Wang, Quanxin; Zhang, Lixin; Yan, Guiying

2016-01-01

Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations. PMID:27415801

Reliable Prescreening of Candidate NerveAgent Prophylaxes via 3D QSAR

DTIC Science & Technology

2005-12-31

recognize and predict prospective toxicity among covalent -binding AChE inhibitors of potential application to nerve agent prophylaxis and...is below since many authors do not follow the 200 word limit 14. SUBJECT TERMS nerve agents , acetylcholinesterase, prophylaxis, QSAR, virtual...Report: Reliable Prescreening of Candidate NerveAgent Prophylaxes via 3D QSAR Report Title ABSTRACT Organophosphorus (OP) nerve agents are among the

Analysis of microRNA and gene expression profiling in triazole fungicide-treated HepG2 cell line.

PubMed

An, Yu Ri; Kim, Seung Jun; Oh, Moon-Ju; Kim, Hyun-Mi; Shim, Il-Seob; Kim, Pil-Je; Choi, Kyunghee; Hwang, Seung Yong

2013-01-07

MicroRNA (miRNA) plays an important role in various diseases and in cellular and molecular responses to toxicants. In the present study, we investigated differential expression of miRNAs in response to three triazole fungicides (myclobutanil, propiconazole, and triadimefon). The human hepatoma cell line (HepG2) was treated with the above triazoles for 3 h or 48 h. miRNA-based microarray experiments were carried out using the Agilent human miRNA v13 array. At early exposure (3h), six miRNAs were differentially expressed and at late exposure (48 h), three miRNAs were significantly expressed. Overall, this study provides an array of potential biomarkers for the above triazole fungicides. Furthermore, these miRNAs induced by triazoles could be the foundation for the development of a miRNA-based toxic biomarker library that can predict environmental toxicity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Prediction of toxic metals concentration using artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Gholami, R.; Kamkar-Rouhani, A.; Doulati Ardejani, F.; Maleki, Sh.

2011-12-01

Groundwater and soil pollution are noted to be the worst environmental problem related to the mining industry because of the pyrite oxidation, and hence acid mine drainage generation, release and transport of the toxic metals. The aim of this paper is to predict the concentration of Ni and Fe using a robust algorithm named support vector machine (SVM). Comparison of the obtained results of SVM with those of the back-propagation neural network (BPNN) indicates that the SVM can be regarded as a proper algorithm for the prediction of toxic metals concentration due to its relative high correlation coefficient and the associated running time. As a matter of fact, the SVM method has provided a better prediction of the toxic metals Fe and Ni and resulted the running time faster compared with that of the BPNN.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Environmental toxicology and risk assessment of pharmaceuticals from hospital wastewater.

PubMed

Escher, Beate I; Baumgartner, Rebekka; Koller, Mirjam; Treyer, Karin; Lienert, Judit; McArdell, Christa S

2011-01-01

In this paper, we evaluated the ecotoxicological potential of the 100 pharmaceuticals expected to occur in highest quantities in the wastewater of a general hospital and a psychiatric center in Switzerland. We related the toxicity data to predicted concentrations in different wastewater streams to assess the overall risk potential for different scenarios, including conventional biological pretreatment in the hospital and urine source separation. The concentrations in wastewater were estimated with pharmaceutical usage information provided by the hospitals and literature data on human excretion into feces and urine. Environmental concentrations in the effluents of the exposure scenarios were predicted by estimating dilution in sewers and with literature data on elimination during wastewater treatment. Effect assessment was performed using quantitative structure-activity relationships because experimental ecotoxicity data were only available for less than 20% of the 100 pharmaceuticals with expected highest loads. As many pharmaceuticals are acids or bases, a correction for the speciation was implemented in the toxicity prediction model. The lists of Top-100 pharmaceuticals were distinctly different between the two hospital types with only 37 pharmaceuticals overlapping in both datasets. 31 Pharmaceuticals in the general hospital and 42 pharmaceuticals in the psychiatric center had a risk quotient above 0.01 and thus contributed to the mixture risk quotient. However, together they constituted only 14% (hospital) and 30% (psychiatry) of the load of pharmaceuticals. Hence, medical consumption data alone are insufficient predictors of environmental risk. The risk quotients were dominated by amiodarone, ritonavir, clotrimazole, and diclofenac. Only diclofenac is well researched in ecotoxicology, while amiodarone, ritonavir, and clotrimazole have no or very limited experimental fate or toxicity data available. The presented computational analysis thus helps setting priorities for further testing. Separate treatment of hospital wastewater would reduce the pharmaceutical load of wastewater treatment plants, and the risk from the newly identified priority pharmaceuticals. However, because high-risk pharmaceuticals are excreted mainly with feces, urine source separation is not a viable option for reducing the risk potential from hospital wastewater, while a sorption step could be beneficial. Copyright © 2010 Elsevier Ltd. All rights reserved.

Acute toxicity of two generic drilling fluids and six additives, alone and combined, to mysids (Mysidopsis bahia)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parrish, P.R.; Macauley, J.M.; Montgomery, R.M.

1988-01-01

Toxicity tests were conducted with two laboratory-prepared generic drilling fluids (muds) and six commonly used drilling-fluid additives to determine their toxicity, alone and combined, to mysids (Mysidopsis bahia). In 25 tests, the acute toxicity of combinations of one, two, or three of the drilling-fluid additives mixed with either drilling fluid was less than the toxicity predicted from the empirical 96-h LC50s for drilling fluid additive(s) and/or drilling fluid alone; the observed 96-h LC50s of the mixtures were from 1.3 to 23.6 times the values predicted from the presumption of additive toxicity.

Prediction of acute inhalation toxicity using in vitro lung surfactant inhibition.

PubMed

Sørli, Jorid B; Huang, Yishi; Da Silva, Emilie; Hansen, Jitka S; Zuo, Yi Y; Frederiksen, Marie; Nørgaard, Asger W; Ebbehøj, Niels E; Larsen, Søren T; Hougaard, Karin S

2018-01-01

Private consumers and professionals may experience acute inhalation toxicity after inhaling aerosolized impregnation products. The distinction between toxic and non-toxic products is difficult to make for producers and product users alike, as there is no clearly described relationship between the chemical composition of the products and induction of toxicity. The currently accepted method for determination of acute inhalation toxicity is based on experiments on animals; it is time-consuming, expensive and causes stress for the animals. Impregnation products are present on the market in large numbers and amounts and exhibit great variety. Therefore, an alternative method to screen for acute inhalation toxicity is needed. The aim of our study was to determine if inhibition of lung surfactant by impregnation products in vitro could accurately predict toxicity in vivo in mice. We tested 21 impregnation products using the constant flow through set-up of the constrained drop surfactometer to determine if the products inhibited surfactant function or not. The same products were tested in a mouse inhalation bioassay to determine their toxicity in vivo. The sensitivity was 100%, i.e., the in vitro method predicted all the products that were toxic for mice to inhale. The specificity of the in vitro test was 63%, i.e., the in vitro method found three false positives in the 21 tested products. Six of the products had been involved in accidental human inhalation where they caused acute inhalation toxicity. All of these six products inhibited lung surfactant function in vitro and were toxic to mice.

Cheminformatics Analysis of EPA ToxCast Chemical Libraries to Identify Domains of Applicability for Predictive Toxicity Models and Prioritize Compounds for Toxicity Testing

EPA Science Inventory

An important goal of toxicology research is the development of robust methods that use in vitro and chemical structure information to predict in vivo toxicity endpoints. The US EPA ToxCast program is addressing this goal using ~600 in vitro assays to create bioactivity profiles o...

Age and Comorbid Illness Are Associated With Late Rectal Toxicity Following Dose-Escalated Radiation Therapy for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamstra, Daniel A.; Stenmark, Matt H.; Ritter, Tim

2013-04-01

Purpose: To assess the impacts of patient age and comorbid illness on rectal toxicity following external beam radiation therapy (EBRT) for prostate cancer and to assess the Qualitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) normal tissue complication probability (NTCP) model in this context. Methods and Materials: Rectal toxicity was analyzed in 718 men previously treated for prostate cancer with EBRT (≥75 Gy). Comorbid illness was scored using the Charlson Comorbidity Index (CCMI), and the NTCP was evaluated with the QUANTEC model. The influence of clinical and treatment-related parameters on rectal toxicity was assessed by Kaplan-Meier and Coxmore » proportional hazards models. Results: The cumulative incidence of rectal toxicity grade ≥2 was 9.5% and 11.6% at 3 and 5 years and 3.3% and 3.9% at 3 and 5 years for grade ≥3 toxicity, respectively. Each year of age predicted an increasing relative risk of grade ≥2 (P<.03; hazard ratio [HR], 1.04 [95% confidence interval (CI), 1.01-1.06]) and ≥3 rectal toxicity (P<.0001; HR, 1.14 [95% CI,1.07-1.22]). Increasing CCMI predicted rectal toxicity where a history of either myocardial infarction (MI) (P<.0001; HR, 5.1 [95% CI, 1.9-13.7]) or congestive heart failure (CHF) (P<.0006; HR, 5.4 [95% CI, 0.6-47.5]) predicted grade ≥3 rectal toxicity, with lesser correlation with grade ≥2 toxicity (P<.02 for MI, and P<.09 for CHF). An age comorbidity model to predict rectal toxicity was developed and confirmed in a validation cohort. The use of anticoagulants increased toxicity independent of age and comorbidity. NTCP was prognostic for grade ≥3 (P=.015) but not grade ≥2 (P=.49) toxicity. On multivariate analysis, age, MI, CHF, and an NTCP >20% all correlated with late rectal toxicity. Conclusions: Patient age and a history of MI or CHF significantly impact rectal toxicity following EBRT for the treatment of prostate cancer, even after controlling for NTCP.« less

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

PubMed

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

The taste of toxicity: A quantitative analysis of bitter and toxic molecules.

PubMed

Nissim, Ido; Dagan-Wiener, Ayana; Niv, Masha Y

2017-12-01

The role of bitter taste-one of the few basic taste modalities-is commonly assumed to signal toxicity and alert animals against consuming harmful compounds. However, it is known that some toxic compounds are not bitter and that many bitter compounds have negligible toxicity while having important health benefits. Here we apply a quantitative analysis of the chemical space to shed light on the bitterness-toxicity relationship. Using the BitterDB dataset of bitter molecules, The BitterPredict prediction tool, and datasets of toxic compounds, we quantify the identity and similarity between bitter and toxic compounds. About 60% of the bitter compounds have documented toxicity and only 56% of the toxic compounds are known or predicted to be bitter. The LD 50 value distributions suggest that most of the bitter compounds are not very toxic, but there is a somewhat higher chance of toxicity for known bitter compounds compared to known nonbitter ones. Flavonoids and alpha acids are more common in the bitter dataset compared with the toxic dataset. In contrast, alkaloids are more common in the toxic datasets compared to the bitter dataset. Interestingly, no trend linking LD 50 values with the number of activated bitter taste receptors (TAS2Rs) subtypes is apparent in the currently available data. This is in accord with the newly discovered expression of TAS2Rs in several extra-oral tissues, in which they might be activated by yet unknown endogenous ligands and play non-gustatory physiological roles. These results suggest that bitter taste is not a very reliable marker for toxicity, and is likely to have other physiological roles. © 2017 IUBMB Life, 69(12):938-946, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

Quantitative structure-toxicity relationship of the aquatic toxicity for various narcotic pollutants using the norm indexes.

PubMed

Wang, Qiang; Jia, Qingzhu; Yan, Lihong; Xia, Shuqian; Ma, Peisheng

2014-08-01

The aquatic toxicity value of hazardous contaminants plays an important role in the risk assessments of aquatic ecosystems. The following study presents a stable and accurate structure-toxicity relationship model based on the norm indexes for the prediction of toxicity value (log(LC50)) for 190 diverse narcotic pollutants (96 h LC50 data for Poecilia reticulata). Research indicates that this new model is very efficient and provides satisfactory results. The suggested prediction model is evidenced by R(2) (square correlation coefficient) and ARD (average relative difference) values of 0.9376 and 10.45%, respectively, for the training set, and 0.9264 and 13.90% for the testing set. Comparison results with reference models demonstrate that this new method, based on the norm indexes proposed in this work, results in significant improvements, both in accuracy and stability for predicting aquatic toxicity values of narcotic pollutants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.

PubMed

Elferink, M G L; Olinga, P; Draaisma, A L; Merema, M T; Bauerschmidt, S; Polman, J; Schoonen, W G; Groothuis, G M M

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elferink, M.G.L.; Olinga, P.; Draaisma, A.L.

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such asmore » Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.« less

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

PubMed

Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

2017-02-01

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Retained Lumbar Bullet: A Case Report of Chronic Lead Toxicity and Review of the Literature.

PubMed

Bustamante, Nirma D; Macias-Konstantopoulos, Wendy L

2016-07-01

Lead toxicity from retained bullet fragments is difficult to both predict and diagnose, but important to treat early, given the potential severity of disease. Blood lead levels > 25 μg/dL and 40 μg/dL are considered toxic in children and adults, respectively. Symptoms may range from nonspecific constitutional symptoms to seizures and coma. Chelation is the mainstay therapy for lead poisoning and levels to treat depend on patient age, blood lead levels, and the presence of symptoms. CASE  We present the case of a woman with symptoms of severe lead toxicity from 20-year-old retained bullet fragments. She had been seen by multiple providers for evaluation of each symptom, but a unifying diagnosis had not been found. After identifying this complication, she was treated appropriately and more serious complications were prevented. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: We present this case to increase awareness among emergency physicians of lead toxicity in patients with a seemingly unrelated constellation of symptoms and a history of a previous gunshot wound with retained bullet or bullet fragments. Copyright © 2016 Elsevier Inc. All rights reserved.

Toxic behavior of silver and zinc oxide nanoparticles on environmental microorganisms.

PubMed

Dhas, Sindhu Priya; Shiny, Punalur John; Khan, Sudheer; Mukherjee, Amitava; Chandrasekaran, Natrajan

2014-09-01

Silver and zinc oxide nanoparticles (Ag and ZnO NPs) are widely used as antimicrobial agents. However, their potential toxicological impact on environmental microorganisms is largely unexplored. The aim of this work was to investigate the sensitivity and adaptability of five bacterial species isolated from sewage towards Ag and ZnO NPs. The bacterial species were exposed to increasing concentration of nanoparticles and the growth inhibitory effect, exopolysaccharides (EPSs) and extracellular proteins (ECPs) productions were determined. The involvement of surface charge in nanoparticles toxicity was also determined. The bacterial species were constantly exposed to nanoparticles to determine the adaptation behavior toward nanoparticles. The nanoparticles exhibited remarkable growth inhibitory effect on tested bacterial species. The toxicity of nanoparticles was found to be strongly dependent on surface charge effects. Though, these organisms are highly sensitive to Ag and ZnO NPs, the continuous exposure to these nanoparticles leads to moderate adaptation of bacterial species and the adapted bacterial species convert the highly toxic nano form to less toxic microform. Finally we predict that the continuing applications of nanoparticles in consumer products may lead to the development of nanoparticles resistant bacterial strains in future. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes

PubMed Central

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system. PMID:28584447

Analysis of EAWAG-BBD pathway prediction system for the identification of malathion degrading microbes.

PubMed

Sivakumar, Subramaniam; Anitha, Palanivel; Ramesh, Balsubramanian; Suresh, Gopal

2017-01-01

Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system.

Transcriptomics analysis of lungs and peripheral blood of crystalline silica-exposed rats

PubMed Central

Sellamuthu, Rajendran; Umbright, Christina; Roberts, Jenny R.; Chapman, Rebecca; Young, Shih-Houng; Richardson, Diana; Cumpston, Jared; McKinney, Walter; Chen, Bean T.; Frazer, David; Li, Shengqiao; Kashon, Michael; Joseph, Pius

2015-01-01

Minimally invasive approaches to detect/predict target organ toxicity have significant practical applications in occupational toxicology. The potential application of peripheral blood transcriptomics as a practical approach to study the mechanisms of silica-induced pulmonary toxicity was investigated. Rats were exposed by inhalation to crystalline silica (15 mg/m3, 6 h/day, 5 days) and pulmonary toxicity and global gene expression profiles of lungs and peripheral blood were determined at 32 weeks following termination of exposure. A significant elevation in bronchoalveolar lavage fluid lactate dehydrogenase activity and moderate histological changes in the lungs, including type II pneumocyte hyperplasia and fibrosis, indicated pulmonary toxicity in the rats. Similarly, significant infiltration of neutrophils and elevated monocyte chemotactic protein-1 levels in the lungs showed pulmonary inflammation in the rats. Microarray analysis of global gene expression profiles identified significant differential expression [>1.5-fold change and false discovery rate (FDR) p < 0.01] of 520 and 537 genes, respectively, in the lungs and blood of the exposed rats. Bioinformatics analysis of the differentially expressed genes demonstrated significant similarity in the biological processes, molecular networks, and canonical pathways enriched by silica exposure in the lungs and blood of the rats. Several genes involved in functions relevant to silica-induced pulmonary toxicity such as inflammation, respiratory diseases, cancer, cellular movement, fibrosis, etc, were found significantly differentially expressed in the lungs and blood of the silica-exposed rats. The results of this study suggested the potential application of peripheral blood gene expression profiling as a toxicologically relevant and minimally invasive surrogate approach to study the mechanisms underlying silica-induced pulmonary toxicity. PMID:22861000

The effect of soil properties on the toxicity of silver to the soil nitrification process.

PubMed

Langdon, Kate A; McLaughlin, Mike J; Kirby, Jason K; Merrington, Graham

2014-05-01

Silver (Ag) is being increasingly used in a range of consumer products, predominantly as an antimicrobial agent, leading to a higher likelihood of its release into the environment. The present study investigated the toxicity of Ag to the nitrification process in European and Australian soils in both leached and unleached conditions. Overall, leaching of soils was found to have a minimal effect on the final toxicity data, with an average leaching factor of approximately 1. Across the soils, the toxicity was found to vary by several orders of magnitude, with concentrations of Ag causing a 50% reduction in nitrification relative to the controls (EC50) ranging from 0.43 mg Ag/kg to >640 mg Ag/kg. Interestingly, the dose-response relationships in most of the soils showed significant stimulation in nitrification at low Ag concentrations (i.e., hormesis), which in some cases produced responses up to double that observed in the controls. Soil pH and organic carbon were the properties found to have the greatest influence on the variations in toxicity thresholds across the soils, and significant relationships were developed that accounted for approximately 90% of the variability in the data. The toxicity relationships developed from the present study will assist in future assessment of potential Ag risks and enable the site-specific prediction of Ag toxicity. © 2014 SETAC.

Evaluating the Zebrafish Embryo Toxicity Test for Pesticide ...

EPA Pesticide Factsheets

Given the numerous chemicals used in society, it is critical to develop tools for accurate and efficient evaluation of potential risks to human and ecological receptors. Fish embryo acute toxicity tests are 1 tool that has been shown to be highly predictive of standard, more resource-intensive, juvenile fish acute toxicity tests. However, there is also evidence that fish embryos are less sensitive than juvenile fish for certain types of chemicals, including neurotoxicants. The utility of fish embryos for pesticide hazard assessment was investigated by comparing published zebrafish embryo toxicity data from pesticides with median lethal concentration 50% (LC50) data for juveniles of 3 commonly tested fish species: rainbow trout, bluegill sunfish, and sheepshead minnow. A poor, albeit significant, relationship (r2 = 0.28; p < 0.05) was found between zebrafish embryo and juvenile fish toxicity when pesticides were considered as a single group, but a much better relationship (r2 = 0.64; p < 0.05) when pesticide mode of action was factored into an analysis of covariance. This discrepancy is partly explained by the large number of neurotoxic pesticides in the dataset, supporting previous findings that commonly used fish embryo toxicity test endpoints are particularly insensitive to neurotoxicants. These results indicate that it is still premature to replace juvenile fish toxicity tests with embryo-based tests such as the Organisation for Economic Co-op

Predictive models attribute effects on fish assemblages to toxicity and habitat alteration.

PubMed

de Zwart, Dick; Dyer, Scott D; Posthuma, Leo; Hawkins, Charles P

2006-08-01

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and ecotoxicology, but they have not previously been used in concert to quantify impairment and its likely causes. Although data limitations constrained our ability to examine complex interactions between stressors and species, the direct relationships we detected likely represent conservative estimates of stressor contributions to local impairment. Future refinements of the general approach and specific methods described here should yield even more promising results.

Estimated sediment thickness, quality, and toxicity to benthic organisms in selected impoundments in Massachusetts

USGS Publications Warehouse

Breault, Robert F.; Sorenson, Jason R.; Weiskel, Peter K.

2013-01-01

The U.S. Geological Survey and the Massachusetts Department of Fish and Game, Division of Ecological Restoration, collaborated to collect baseline information on the quantity and quality of sediment impounded behind selected dams in Massachusetts, including sediment thickness and the occurrence of contaminants potentially toxic to benthic organisms. The thicknesses of impounded sediments were measured, and cores of sediment were collected from 32 impoundments in 2004 and 2005. Cores were chemically analyzed, and concentrations of 32 inorganic elements and 108 organic compounds were quantified. Sediment thicknesses varied considerably among the 32 impoundments, with an average thickness of 3.7 feet. Estimated volumes also varied greatly, ranging from 100,000 cubic feet to 81 million cubic feet. Concentrations of toxic contaminants as well as the number of contaminants detected above analytical quantification levels (also known as laboratory reporting levels) varied greatly among sampling locations. Based on measured contaminant concentrations and comparison to published screening thresholds, bottom sediments were predicted to be toxic to bottom-dwelling (benthic) organisms in slightly under 30 percent of the impoundments sampled. Statistically significant relations were found between several of the contaminants and individual indicators of urban land use and industrial activity in the upstream drainage areas of the impoundments. However, models developed to estimate contaminant concentrations at unsampled sites from upstream landscape characteristics had low predictive power, consistent with the long and complex land-use history that is typical of many drainage areas in Massachusetts.

Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system, March 2009 version.

PubMed

Furuhama, A; Toida, T; Nishikawa, N; Aoki, Y; Yoshioka, Y; Shiraishi, H

2010-07-01

The KAshinhou Tool for Ecotoxicity (KATE) system, including ecotoxicity quantitative structure-activity relationship (QSAR) models, was developed by the Japanese National Institute for Environmental Studies (NIES) using the database of aquatic toxicity results gathered by the Japanese Ministry of the Environment and the US EPA fathead minnow database. In this system chemicals can be entered according to their one-dimensional structures and classified by substructure. The QSAR equations for predicting the toxicity of a chemical compound assume a linear correlation between its log P value and its aquatic toxicity. KATE uses a structural domain called C-judgement, defined by the substructures of specified functional groups in the QSAR models. Internal validation by the leave-one-out method confirms that the QSAR equations, with r(2 )> 0.7, RMSE 5, give acceptable q(2) values. Such external validation indicates that a group of chemicals with an in-domain of KATE C-judgements exhibits a lower root mean square error (RMSE). These findings demonstrate that the KATE system has the potential to enable chemicals to be categorised as potential hazards.

Characterization of synergistic embryotoxicity of nickel and buprofezin in zebrafish.

PubMed

Ku, Tingting; Yan, Wei; Jia, Wuyao; Yun, Yang; Zhu, Na; Li, Guangke; Sang, Nan

2015-04-07

Multiple pollutants, usually at low levels, coexist and may interact in the environment. It is therefore important to analyze the toxicity of mixtures of coexisting chemicals to evaluate the potential ecological risk. Concern regarding the co-occurrence and combined bioeffects of heavy metals and organic insecticides in aquatic settings has existed for many years, but a clear understanding of the interactions between and potential combined toxicity of these chemicals remains elusive. In the present study, the combined effects of the heavy metal nickel (NiSO4) and insect growth regulator buprofezin on the induction of embryo toxicity in zebrafish were assessed. By applying nonlinear regression to the concentration-response data with each of the chemicals using the Hill and Langmuir functions and computing the predictions using the model of concentration addition (CA), we confirmed that NiSO4 and buprofezin acted together to produce synergistic embryotoxicity in zebrafish. Subsequently, we further found that the combination of NiSO4 and buprofezin formed a complex that facilitated the uptake of nickel (Ni) and buprofezin by the embryos. Following this, we clarified that an oxidative mechanism of the complex might underlie the synergistic embryotoxicity of NiSO4 and buprofezin.

Humanized mouse model of glucose 6-phosphate dehydrogenase deficiency for in vivo assessment of hemolytic toxicity

PubMed Central

Rochford, Rosemary; Ohrt, Colin; Baresel, Paul C.; Campo, Brice; Sampath, Aruna; Magill, Alan J.; Tekwani, Babu L.; Walker, Larry A.

2013-01-01

Individuals with glucose 6-phosphate dehydrogenase (G6PD) deficiency are at risk for the development of hemolytic anemia when given 8-aminoquinolines (8-AQs), an important class of antimalarial/antiinfective therapeutics. However, there is no suitable animal model that can predict the clinical hemolytic potential of drugs. We developed and validated a human (hu)RBC-SCID mouse model by giving nonobese diabetic/SCID mice daily transfusions of huRBCs from G6PD-deficient donors. Treatment of SCID mice engrafted with G6PD-deficient huRBCs with primaquine, an 8-AQ, resulted in a dose-dependent selective loss of huRBCs. To validate the specificity of this model, we tested known nonhemolytic antimalarial drugs: mefloquine, chloroquine, doxycycline, and pyrimethamine. No significant loss of G6PD-deficient huRBCs was observed. Treatment with drugs known to cause hemolytic toxicity (pamaquine, sitamaquine, tafenoquine, and dapsone) resulted in loss of G6PD-deficient huRBCs comparable to primaquine. This mouse model provides an important tool to test drugs for their potential to cause hemolytic toxicity in G6PD-deficient populations. PMID:24101478

Evaluation of the potential toxicity of unmodified and modified cyclodextrins on murine blood-brain barrier endothelial cells.

PubMed

Shityakov, Sergey; Salmas, Ramin Ekhteiari; Salvador, Ellaine; Roewer, Norbert; Broscheit, Jens; Förster, Carola

2016-04-01

In this study, we investigated the cytotoxic effects of unmodified α-cyclodextrin (α-CD) and modified cyclodextrins, including trimethyl-β-cyclodextrin (TRIMEB) and hydroxypropyl-β-cyclodextrin (HPβCD), on immortalized murine microvascular endothelial (cEND) cells of the blood-brain barrier (BBB). A CellTiter-Glo viability test, performed on the cEND cells showed significant differences among the different cyclodextrins. After 24 hr of incubation, TRIMEB was the most cytotoxic, and HPβCD was non-toxic. α-CD and TRIMEB exhibited greater cytotoxicity in the Dulbecco's modified Eagle's medium than in heat-inactivated human serum indicating protective properties of the human serum. The predicted dynamic toxicity profiles (Td) for α-CD and TRIMEB indicated higher cytotoxicity for these cyclodextrins compared to the reference compound (dimethylsulfoxide). Molecular dynamics simulation of cholesterol binding to the CDs suggested that not just cholesterol but phospholipids extraction might be involved in the cytotoxicity. Overall, the results demonstrate that HPβCD has the potential to be used as a candidate for drug delivery vector development and signify a correlation between the in vitro cytotoxic effect and cholesterol binding of cyclodextrins.

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

PubMed Central

Basuino, Li; Chambers, Henry F.; Lee, Deok-Sun; Wiest, Olaf G.; Babbitt, Patricia C.

2009-01-01

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism. PMID:19701464

Use of the University of Minnesota Biocatalysis/Biodegradation Database for study of microbial degradation

PubMed Central

2012-01-01

Microorganisms are ubiquitous on earth and have diverse metabolic transformative capabilities important for environmental biodegradation of chemicals that helps maintain ecosystem and human health. Microbial biodegradative metabolism is the main focus of the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD). UM-BBD data has also been used to develop a computational metabolic pathway prediction system that can be applied to chemicals for which biodegradation data is currently lacking. The UM-Pathway Prediction System (UM-PPS) relies on metabolic rules that are based on organic functional groups and predicts plausible biodegradative metabolism. The predictions are useful to environmental chemists that look for metabolic intermediates, for regulators looking for potential toxic products, for microbiologists seeking to understand microbial biodegradation, and others with a wide-range of interests. PMID:22587916

Toxicity Estimation Software Tool (TEST)

EPA Science Inventory

The Toxicity Estimation Software Tool (TEST) was developed to allow users to easily estimate the toxicity of chemicals using Quantitative Structure Activity Relationships (QSARs) methodologies. QSARs are mathematical models used to predict measures of toxicity from the physical c...

Random Forests to Predict Rectal Toxicity Following Prostate Cancer Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ospina, Juan D.; INSERM, U1099, Rennes; Escuela de Estadística, Universidad Nacional de Colombia Sede Medellín, Medellín

2014-08-01

Purpose: To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models. Methods and Materials: Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression modelmore » was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC). Results: The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69. Conclusions: The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.« less

Classification of Chemicals Based On Structured Toxicity ...

EPA Pesticide Factsheets

Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-based classifications of chemicals were performed as a model application of ToxRefDB. These endpoints will ultimately provide the anchoring toxicity information for the development of predictive models and biological signatures utilizing in vitro assay data. Utilizing query and structured data mining approaches, toxicity profiles were uniformly generated for greater than 300 chemicals. Based on observation rate, species concordance and regulatory relevance, individual and aggregated effects have been selected to classify the chemicals providing a set of predictable endpoints. ToxRefDB exhibits the utility of transforming unstructured toxicity data into structured data and, furthermore, into computable outputs, and serves as a model for applying such data to address modern toxicological problems.

From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles.

PubMed

Sizochenko, Natalia; Rasulev, Bakhtiyor; Gajewicz, Agnieszka; Kuz'min, Victor; Puzyn, Tomasz; Leszczynski, Jerzy

2014-11-21

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the "liquid drop" model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.

Behavioral toxicology in the 21st century: challenges and opportunities for behavioral scientists. Summary of a symposium presented at the annual meeting of the neurobehavioral teratology society, June, 2009.

PubMed

Bushnell, Philip J; Kavlock, Robert J; Crofton, Kevin M; Weiss, Bernard; Rice, Deborah C

2010-01-01

The National Research Council (NRC) of the National Academies of Science recently published a report of its vision of toxicity testing in the 21st century. The report proposes that the current toxicity testing paradigm that depends upon whole-animal tests be replaced with a strategy based upon in vitro tests, in silico models and evaluations of toxicity at the human population level. These goals are intended to set in motion changes that will transform risk assessment into a process in which adverse effects on public health are predicted by quantitative structure-activity relationship (QSAR) models and data from suites of high-throughput in vitro tests. The potential roles for whole-animal testing in this futuristic vision are both various and undefined. A symposium was convened at the annual meeting of the Neurobehavioral Teratology Society in Rio Grande, Puerto Rico in June, 2009 to discuss the potential challenges and opportunities for behavioral scientists in developing and/or altering this strategy toward the ultimate goal of protecting public health from hazardous chemicals. R. Kavlock described the NRC vision, introduced the concept of the 'toxicity pathway' (a central guiding principle of the NRC vision), and described the current status of an initial implementation this approach with the EPA's ToxCast(R) program. K. Crofton described a pathway based upon disruption of thyroid hormone metabolism during development, including agents, targets, and outcomes linked by this mode of action. P. Bushnell proposed a pathway linking the neural targets and cellular to behavioral effects of acute exposure to organic solvents, whose predictive power is limited by our incomplete understanding of the complex CNS circuitry that mediates the behavioral responses to solvents. B. Weiss cautioned the audience regarding a pathway approach to toxicity testing, using the example of the developmental toxicity of phthalates, whose effects on mammalian sexual differentiation would be difficult to identify based on screening tests in vitro. Finally, D. Rice raised concerns regarding the use of data derived from toxicity screening tests to human health risk assessments. Discussion centered around opportunities and challenges for behavioral toxicologists regarding this impending paradigm shift. Opportunities include: identifying and characterizing toxicity pathways; informing the conditions and limits of extrapolation; addressing issues of susceptibility and variability; providing reality-checks on selected positives and negatives from screens; and performing targeted testing and dose-response assessments of chemicals flagged during screening. Challenges include: predicting behavior using models of complex neurobiological pathways; standardizing study designs and dependent variables to facilitate creation of databases; and managing the cost and efficiency of behavioral assessments. Thus, while progress is being made in approaching the vision of 21st century toxicology, we remain a long way from replacing whole-animal tests; indeed, some animal testing will be essential for the foreseeable future at least. Initial advances will likely provide better prioritization tools so that animal resources are used more efficiently and effectively.

A DPYD variant (Y186C) specific to individuals of African descent in a patient with life-threatening 5-FU toxic effects: potential for an individualized medicine approach.

PubMed

Saif, M Wasif; Lee, Adam M; Offer, Steven M; McConnell, Kathleen; Relias, Valerie; Diasio, Robert B

2014-01-01

5-Fluorouracil (5-FU) is commonly administered as a therapeutic agent for the treatment of various aggressive cancers. Severe toxic reactions to 5-FU have been associated with decreased levels of dihydropyrimidine dehydrogenase (DPD) enzyme activity. Manifestations of 5-FU toxicity typically include cytopenia, diarrhea, stomatitis, mucositis, neurotoxicity, and, in extreme cases, death. A variety of genetic variations in DPYD, the gene encoding DPD, are known to result in decreased DPD enzyme activity and to contribute to 5-FU toxic effects. Recently, it was reported that healthy African American individuals carrying the Y186C DPYD variant (rs115232898) had significantly reduced DPD enzyme activity compared with noncarriers of Y186C. Herein, we describe for the first time, to our knowledge, an African American patient with cancer with the Y186C variant who had severe toxic effects after administration of the standard dose of 5-FU chemotherapy. The patient lacked any additional toxic effect-associated variations in the DPYD gene or the thymidylate synthase (TYMS) promoter. This case suggests that Y186C may have contributed to 5-FU toxicity in this patient and supports the use of Y186C as a predictive marker for 5-FU toxic effects in individuals of African ancestry. Copyright © 2014 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology.

PubMed

Groh, Ksenia J; Carvalho, Raquel N; Chipman, James K; Denslow, Nancy D; Halder, Marlies; Murphy, Cheryl A; Roelofs, Dick; Rolaki, Alexandra; Schirmer, Kristin; Watanabe, Karen H

2015-02-01

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mine wastes and human health

USGS Publications Warehouse

Plumlee, Geoffrey S.; Morman, Suzette A.

2011-01-01

Historical mining and mineral processing have been linked definitively to health problems resulting from occupational and environmental exposures to mine wastes. Modern mining and processing methods, when properly designed and implemented, prevent or greatly reduce potential environmental health impacts. However, particularly in developing countries, there are examples of health problems linked to recent mining. In other cases, recent mining has been blamed for health problems but no clear links have been found. The types and abundances of potential toxicants in mine wastes are predictably influenced by the geologic characteristics of the deposit being mined. Hence, Earth scientists can help understand, anticipate, and mitigate potential health issues associated with mining and mineral processing.

Merchant ships discharging unwanted marine species in close proximity of a French aquaculture area: risks involved.

PubMed

Masson, Daniel; Thomas, Gerard; Genauzeau, Sylvie; Le Moine, Olivier; Derrien, Annick

2013-12-15

The most important oyster farming area in Europe is in a close proximity of two medium size merchant ports. Cargo ships deballast in this area before loading, releasing unwanted or noxious marine species. During a sampling campaign aboard these arriving ships, we found in some ballast water samples a huge number of potentially toxic dinoflagellates and some potentially pathogenic bacteria. A model was applied to find the potential geographical spread of the discharged ballast water. This model predicts the water to reach highly vulnerable shellfish farmed areas in six to eight days. Copyright © 2013 Elsevier Ltd. All rights reserved.

The two faces of DOC.

PubMed

Wood, Chris M; Al-Reasi, H A; Smith, D Scott

2011-10-01

Dissolved organic carbon (DOC), through its ability to complex metals and thereby reduce their bioavailability, plays a major role in ameliorating metal toxicity in natural waters. Indeed DOC is a key variable in the Biotic Ligand Model (BLM) for predicting metal toxicity on a site-specific basis. However, recent evidence indicates that all DOCs are not alike, but rather heterogeneous in their ability to protect organisms against metal toxicity, at least in fresh water. The degree of protection appears to correlate with optical properties, such that dark, aromatic-rich compounds of allochthonous origin, with greater humic acid content, are more effective in this regard, particularly against Cu, Ag, and Pb toxicity. The specific absorption coefficient of the DOC in the 300-350nm range (SAC(300-350)) has proven to be a simple and effective index of this protective ability. PARAFAC, a multivariate statistical technique for analysis of excitation-emission fluorescence spectroscopy data, also holds promise for quantifying the humic-like and fulvic-like fluorophores, which tend to be positively and negatively correlated with protective ability, respectively. However, what has been largely missing in the toxicological realm is any appreciation that DOC may also affect the physiology of target organisms, such that part of the protection may occur by a mechanism other than metal complexation. Recently published evidence demonstrates that DOC has effects on Na(+) transport, diffusive permeability, and electrical properties of the gills in fish and crustaceans in a manner which will promote Na(+) homeostasis. These actions could thereby protect against metal toxicity by physiological mechanisms. Future research should investigate potential direct interactions of DOC molecules with the branchial epithelium. Incorporation of optical properties of DOC could be used to improve the predictive capabilities of the BLM. 2011 Elsevier B.V. All rights reserved.

Preventing Drug-Induced Liver Injury: How Useful Are Animal Models?

PubMed

Ballet, François

2015-01-01

Drug-induced liver injury (DILI) is the most common organ toxicity encountered in regulatory animal toxicology studies required prior to the clinical development of new drug candidates. Very few reports have evaluated the value of these studies for predicting DILI in humans. Indeed, compounds inducing liver toxicity in regulatory toxicology studies are not always correlated with a risk of DILI in humans. Conversely, compounds associated with the occurrence of DILI in phase 3 studies or after market release are often tested negative in regulatory toxicology studies. Idiosyncratic DILI is a rare event that is precipitated in an individual by the simultaneous occurrence of several critical factors. These factors may relate to the host (e.g. human leukocyte antigen polymorphism, inflammation), the drug (e.g. reactive metabolites) or the environment (e.g. diet/microbiota). This type of toxicity therefore cannot be detected in conventional animal toxicology studies. Several animal models have recently been proposed for the identification of drugs with the potential to cause idiosyncratic DILI: rats treated with lipopolysaccharide, Sod2(+/-) mice, panels of inbred mouse strains or chimeric mice with humanized livers. These models are not suitable for use in the prospective screening of new drug candidates. Humans therefore constitute the best model for predicting and assessing idiopathic DILI. © 2015 S. Karger AG, Basel.

UV-vis degradation of α-tocopherol in a model system and in a cosmetic emulsion-Structural elucidation of photoproducts and toxicological consequences.

PubMed

De Vaugelade, Ségolène; Nicol, Edith; Vujovic, Svetlana; Bourcier, Sophie; Pirnay, Stéphane; Bouchonnet, Stéphane

2017-09-29

The UV-vis photodegradation of α-tocopherol was investigated in a model system and in a cosmetic emulsion. Both gas chromatography coupled with tandem mass spectrometry (GC-MS/MS) and high performance liquid chromatography coupled with ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (LC-UHR-MS) were used for photoproducts structural identification. Nine photoproduct families were detected and identified based on their mass spectra and additional experiments with α-tocopherol-d 9 ; phototransformation mechanisms were postulated to rationalize their formation under irradiation. In silico QSAR (Quantitative Structure Activity Relationship) toxicity predictions were conducted with the Toxicity Estimation Software Tool (T.E.S.T.). Low oral rat LD50 values of 466.78mgkg -1 and 467.9mgkg -1 were predicted for some photoproducts, indicating a potential toxicity more than 10 times greater that of α-tocopherol (5742.54mgkg -1 ). In vitro assays on Vibrio fischeri bacteria showed that the global ecotoxicity of the α-tocopherol solution significantly increases with irradiation time. One identified product should contribute to this ecotoxicity enhancement since in silico estimations for D. magna provide a LC50 value 4 times lower than that of the parent molecule. Copyright © 2017. Published by Elsevier B.V.

From metabolism to ecology: cross-feeding interactions shape the balance between polymicrobial conflict and mutualism

PubMed Central

Estrela, Sylvie; Trisos, Christopher H.; Brown, Sam P.

2012-01-01

Polymicrobial interactions are widespread in nature, and play a major role in maintaining human health and ecosystems. Whenever one organism uses metabolites produced by another organism as energy or nutrient sources, this is called cross-feeding. The ecological outcomes of cross-feeding interactions are poorly understood and potentially diverse: mutualism, competition, exploitation or commensalism. A major reason for this uncertainty is the lack of theoretical approaches linking microbial metabolism to microbial ecology. To address this issue, we explore the dynamics of a one-way interspecific cross-feeding interaction, in which food can be traded for a service (detoxification). Our results show that diverse ecological interactions (competition, mutualism, exploitation) can emerge from this simple cross-feeding interaction, and can be predicted by the metabolic, demographic and environmental parameters that govern the balance of the costs and benefits of association. In particular, our model predicts stronger mutualism for intermediate by-product toxicity because the resource-service exchange is constrained to the service being neither too vital (high toxicity impairs resource provision) nor dispensable (low toxicity reduces need for service). These results support the idea that bridging microbial ecology and metabolism is a critical step towards a better understanding of the factors governing the emergence and dynamics of polymicrobial interactions. PMID:23070318

Alarms about structural alerts.

PubMed

Alves, Vinicius; Muratov, Eugene; Capuzzi, Stephen; Politi, Regina; Low, Yen; Braga, Rodolpho; Zakharov, Alexey V; Sedykh, Alexander; Mokshyna, Elena; Farag, Sherif; Andrade, Carolina; Kuz'min, Victor; Fourches, Denis; Tropsha, Alexander

2016-08-21

Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability. We demonstrate that contrary to the common perception of QSAR models as "black boxes" they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.

Pore-Water Carbonate and Phosphate As Predictors of Arsenate Toxicity in Soil.

PubMed

Lamb, Dane T; Kader, Mohammed; Wang, Liang; Choppala, Girish; Rahman, Mohammad Mahmudur; Megharaj, Mallavarapu; Naidu, Ravi

2016-12-06

Phytotoxicity of inorganic contaminants is influenced by the presence of competing ions at the site of uptake. In this study, interaction of soil pore-water constituents with arsenate toxicity was investigated in cucumber (Cucumis sativa L) using 10 contrasting soils. Arsenate phytotoxicity was shown to be related to soluble carbonate and phosphate. The data indicated that dissolved phosphate and carbonate had an antagonistic impact on arsenate toxicity to cucumber. To predict arsenate phytotoxicity in soils with a diverse range of soil solution properties, both carbonate and phosphate were required. The relationship between arsenic and pore-water toxicity parameters was established initially using multiple regression. In addition, based on the relationship with carbonate and phosphate we successively applied a terrestrial biotic ligand-like model (BLM) including carbonate and phosphate. Estimated effective concentrations from the BLM-like parametrization were strongly correlated to measured arsenate values in pore-water (R 2 = 0.76, P < 0.001). The data indicates that an ion interaction model similar to the BLM for arsenate is possible, potentially improving current risk assessments at arsenic and co-contaminated soils.

Limitations of experiments performed in artificially made OECD standard soils for predicting cadmium, lead and zinc toxicity towards organisms living in natural soils.

PubMed

Sydow, Mateusz; Chrzanowski, Łukasz; Cedergreen, Nina; Owsianiak, Mikołaj

2017-08-01

Development of comparative toxicity potentials of cationic metals in soils for applications in hazard ranking and toxic impact assessment is currently jeopardized by the availability of experimental effect data. To compensate for this deficiency, data retrieved from experiments carried out in standardized artificial soils, like OECD soils, could potentially be tapped as a source of effect data. It is, however, unknown whether such data are applicable to natural soils where the variability in pore water concentrations of dissolved base cations is large, and where mass transfer limitations of metal uptake can occur. Here, free ion activity models (FIAM) and empirical regression models (ERM, with pH as a predictor) were derived from total metal EC50 values (concentration with effects in 50% of individuals) using speciation for experiments performed in artificial OECD soils measuring ecotoxicological endpoints for terrestrial earthworms, potworms, and springtails. The models were validated by predicting total metal based EC50 values using backward speciation employing an independent set of natural soils with missing information about ionic composition of pore water, as retrieved from a literature review. ERMs performed better than FIAMs. Pearson's r for log 10 -transformed total metal based EC50s values (ERM) ranged from 0.25 to 0.74, suggesting a general correlation between predicted and measured values. Yet, root-mean-square-error (RMSE) ranged from 0.16 to 0.87 and was either smaller or comparable with the variability of measured EC50 values, suggesting modest performance. This modest performance was mainly due to the omission of pore water concentrations of base cations during model development and their validation, as verified by comparisons with predictions of published terrestrial biotic ligand models. Thus, the usefulness of data from artificial OECD soils for global-scale assessment of terrestrial ecotoxic impacts of Cd, Pb and Zn in soils is limited due to relatively small variability of pore water concentrations of dissolved base cations in OECD soils, preventing their inclusion in development of predictive models. Our findings stress the importance of considering differences in ionic composition of soil pore water when characterizing terrestrial ecotoxicity of cationic metals in natural soils. Copyright © 2017 Elsevier Ltd. All rights reserved.

A high-throughput method for assessing chemical toxicity using a Caenorhabditis elegans reproduction assay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, Windy A.; McBride, Sandra J.; Rice, Julie R.

2010-06-01

The National Research Council has outlined the need for non-mammalian toxicological models to test the potential health effects of a large number of chemicals while also reducing the use of traditional animal models. The nematode Caenorhabditis elegans is an attractive alternative model because of its well-characterized and evolutionarily conserved biology, low cost, and ability to be used in high-throughput screening. A high-throughput method is described for quantifying the reproductive capacity of C. elegans exposed to chemicals for 48 h from the last larval stage (L4) to adulthood using a COPAS Biosort. Initially, the effects of exposure conditions that could influencemore » reproduction were defined. Concentrations of DMSO vehicle {<=} 1% did not affect reproduction. Previous studies indicated that C. elegans may be influenced by exposure to low pH conditions. At pHs greater than 4.5, C. elegans reproduction was not affected; however below this pH there was a significant decrease in the number of offspring. Cadmium chloride was chosen as a model toxicant to verify that automated measurements were comparable to those of traditional observational studies. EC{sub 50} values for cadmium for automated measurements (176-192 {mu}M) were comparable to those previously reported for a 72-h exposure using manual counting (151 {mu}M). The toxicity of seven test toxicants on C. elegans reproduction was highly correlative with rodent lethality suggesting that this assay may be useful in predicting the potential toxicity of chemicals in other organisms.« less

Cancer Treatment Side Effects: A Meta-analysis of the Relationship Between Response Expectancies and Experience.

PubMed

Devlin, Elise J; Denson, Linley A; Whitford, Hayley S

2017-08-01

Although previous research has, overall, suggested a moderate relationship between response expectancies (REs) and cancer treatment-related side effects, empirical results have been mixed. We aimed to further explore these relationships, hypothesizing that REs would predict subsequent toxicities with the inclusion of more recent studies, across a broader range of side effects, while incorporating the impact of potential moderators including patients' experience with treatment and measurement methods. We further investigated the impact of REs across individual toxicities. A systematic search and analysis were conducted across four databases (PsychInfo, PubMed, CINAHL, and Embase) and reference lists, from 1985 to February 2016. This provided 27 eligible studies with 4474 participants, through which the main analysis, moderator analyses, and individual side-effect analyses were explored. REs were moderately related to side effects overall (r = 0.26), and effect sizes were significantly influenced by sample diagnostic homogeneity, whereas differences between type and timing of measurement showed trends. Of the 16 toxicities examined, 15 demonstrated significant relationships between REs and side-effect experience, with hair loss (r = 0.48) the strongest. No clear difference emerged between objective and subjective side effects; however, significant differences across individual toxicities were revealed. Findings support a relationship between REs and a wide range of subsequent side effects, yet differences between individual RE-toxicity associations emerged. These findings provide direction for the measurement of side effects and REs and support REs as potential targets for intervention during the informed consent process. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Effect of pH and ionic strength on exposure and toxicity of encapsulated lambda-cyhalothrin to Daphnia magna.

PubMed

Son, Jino; Hooven, Louisa A; Harper, Bryan; Harper, Stacey L

2015-12-15

Encapsulation of pesticide active ingredients in polymers has been widely employed to control the release of poorly water-soluble active ingredients. Given the high dispersibility of these encapsulated pesticides in water, they are expected to behave differently compared to their active ingredients; however, our current understanding of the fate and effects of encapsulated pesticides is still limited. In this study, we employed a central composite design (CCD) to investigate how pH and ionic strength (IS) affect the hydrodynamic diameter (HDD) and zeta potential of encapsulated λ-cyhalothrin and how those changes affect the exposure and toxicity to Daphnia magna. R(2) values greater than 0.82 and 0.84 for HDD and zeta potential, respectively, irrespective of incubation time suggest those changes could be predicted as a function of pH and IS. For HDD, the linear factor of pH and quadratic factor of pH×pH were found to be the most significant factors affecting the change of HDD at the beginning of incubation, whereas the effects of IS and IS×IS became significant as incubation time increased. For zeta potential, the linear factor of IS and quadratic factor of IS×IS were found to be the most dominant factors affecting the change of zeta potential of encapsulated λ-cyhalothrin, irrespective of incubation time. The toxicity tests with D. magna under exposure conditions in which HDD or zeta potential of encapsulated λ-cyhalothrin was maximized or minimized in the overlying water also clearly showed the worst-case exposure condition to D. magna was when the encapsulated λ-cyhalothrin is either stable or small in the overlying water. Our results show that water quality could modify the fate and toxicity of encapsulated λ-cyhalothrin in aquatic environments, suggesting understanding their aquatic interactions are critical in environmental risk assessment. Herein, we discuss the implications of our findings for risk assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of potential risks from ash disposal site leachate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mills, W.B.; Loh, J.Y.; Bate, M.C.

1999-04-01

A risk-based approach is used to evaluate potential human health risks associated with a discharge from an ash disposal site into a small stream. The RIVRISK model was used to estimate downstream concentrations and corresponding risks. The modeling and risk analyses focus on boron, the constituent of greatest potential concern to public health at the site investigated, in Riddle Run, Pennsylvania. Prior to performing the risk assessment, the model is validated by comparing observed and predicted results. The comparison is good and an uncertainty analysis is provided to explain the comparison. The hazard quotient (HQ) for boron is predicted tomore » be greater than 1 at presently regulated compliance points over a range of flow rates. The reference dose (RfD) currently recommended by the United States Environmental Protection Agency (US EPA) was used for the analyses. However, the toxicity of boron as expressed by the RfD is now under review by both the U.S. EPA and the World Health Organization. Alternative reference doses being examined would produce predicted boron hazard quotients of less than 1 at nearly all flow conditions.« less

Comparison of in silico models for prediction of mutagenicity.

PubMed

Bakhtyari, Nazanin G; Raitano, Giuseppa; Benfenati, Emilio; Martin, Todd; Young, Douglas

2013-01-01

Using a dataset with more than 6000 compounds, the performance of eight quantitative structure activity relationships (QSAR) models was evaluated: ACD/Tox Suite, Absorption, Distribution, Metabolism, Elimination, and Toxicity of chemical substances (ADMET) predictor, Derek, Toxicity Estimation Software Tool (T.E.S.T.), TOxicity Prediction by Komputer Assisted Technology (TOPKAT), Toxtree, CEASAR, and SARpy (SAR in python). In general, the results showed a high level of performance. To have a realistic estimate of the predictive ability, the results for chemicals inside and outside the training set for each model were considered. The effect of applicability domain tools (when available) on the prediction accuracy was also evaluated. The predictive tools included QSAR models, knowledge-based systems, and a combination of both methods. Models based on statistical QSAR methods gave better results.

Getting More Ecologically Relevant Information from Laboratory Tests: Recovery of Lemna minor After Exposure to Herbicides and Their Mixtures.

PubMed

Knežević, Varja; Tunić, Tanja; Gajić, Pero; Marjan, Patricija; Savić, Danko; Tenji, Dina; Teodorović, Ivana

2016-11-01

Recovery after exposure to herbicides-atrazine, isoproturon, and trifluralin-their binary and ternary mixtures, was studied under laboratory conditions using a slightly adapted standard protocol for Lemna minor. The objectives of the present study were (1) to compare empirical to predicted toxicity of selected herbicide mixtures; (2) to assess L. minor recovery potential after exposure to selected individual herbicides and their mixtures; and (3) to suggest an appropriate recovery potential assessment approach and endpoint in a modified laboratory growth inhibition test. The deviation of empirical from predicted toxicity was highest in binary mixtures of dissimilarly acting herbicides. The concentration addition model slightly underestimated mixture effects, indicating potential synergistic interactions between photosynthetic inhibitors (atrazine and isoproturon) and a cell mitosis inhibitor (trifluralin). Recovery after exposure to the binary mixture of atrazine and isoproturon was fast and concentration-independent: no significant differences between relative growth rates (RGRs) in any of the mixtures (IC10 Mix , 25 Mix , and 50 Mix ) versus control level were recorded in the last interval of the recovery phase. The recovery of the plants exposed to binary and ternary mixtures of dissimilarly acting herbicides was strictly concentration-dependent. Only plants exposed to IC10 Mix , regardless of the herbicides, recovered RGRs close to control level in the last interval of the recovery phase. The inhibition of the RGRs in the last interval of the recovery phase compared with the control level is a proposed endpoint that could inform on reversibility of the effects and indicate possible mixture effects on plant population recovery potential.

Grand Rounds: An Outbreak of Toxic Hepatitis among Industrial Waste Disposal Workers

PubMed Central

Cheong, Hae-Kwan; Kim, Eun A; Choi, Jung-Keun; Choi, Sung-Bong; Suh, Jeong-Ill; Choi, Dae Seob; Kim, Jung Ran

2007-01-01

Context Industrial waste (which is composed of various toxic chemicals), changes to the disposal process, and addition of chemicals should all be monitored and controlled carefully in the industrial waste industry to reduce the health hazard to workers. Case presentation Five workers in an industrial waste plant developed acute toxic hepatitis, one of whom died after 3 months due to fulminant hepatitis. In the plant, we detected several chemicals with hepatotoxic potential, including pyridine, dimethylformamide, dimethylacetamide, and methylenedianiline. The workers had been working in the high-vapor-generating area of the plant, and the findings of pathologic examination showed typical features of acute toxic hepatitis. Discussion Infectious hepatitis and drug-induced hepatitis were excluded by laboratory findings, as well as the clinical course of hepatitis. All cases of toxic hepatitis in this plant developed after the change of the disposal process to thermochemical reaction–type treatment using unslaked lime reacted with industrial wastes. During this chemical reaction, vapor containing several toxic materials was generated. Although we could not confirm the definitive causative chemical, we suspect that these cases of hepatitis were caused by one of the hepatotoxic agents or by a synergistic interaction among several of them. Relevance to clinical or professional practice In the industrial waste treatment process, the danger of developing toxic hepatitis should be kept in mind, because any subtle change of the treatment process can generate various toxic materials and threaten the workers’ health. A mixture of hepatotoxic chemicals can induce clinical manifestations that are quite different from those predicted by the toxic property of a single agent. PMID:17366828

The effect of pH on the toxicity of fatty acids and fatty acid amides to rainbow trout gill cells.

PubMed

Bertin, Matthew J; Voronca, Delia C; Chapman, Robert W; Moeller, Peter D R

2014-01-01

Harmful algal blooms (HABs) expose aquatic organisms to multiple physical and chemical stressors during an acute time period. Algal toxins themselves may be altered by water chemistry parameters affecting their bioavailability and resultant toxicity. The purpose of this study was to determine the effects of two abiotic parameters (pH, inorganic metal salts) on the toxicity of fatty acid amides and fatty acids, two classes of lipids produced by harmful algae, including the golden alga, Prymnesium parvum, that are toxic to aquatic organisms. Rainbow trout gill cells were used as a model of the fish gill and exposed to single compounds and mixtures of compounds along with variations in pH level and concentration of inorganic metal salts. We employed artificial neural networks (ANNs) and standard ANOVA statistical analysis to examine and predict the effects of these abiotic parameters on the toxicity of fatty acid amides and fatty acids. Our results demonstrate that increasing pH levels increases the toxicity of fatty acid amides and inhibits the toxicity of fatty acids. This phenomenon is reversed at lower pH levels. Exposing gill cells to complex mixtures of chemical factors resulted in dramatic increases in toxicity compared to tests of single compounds for both the fatty acid amides and fatty acids. These findings highlight the potential of physicochemical factors to affect the toxicity of chemicals released during algal blooms and demonstrate drastic differences in the effect of pH on fatty acid amides and fatty acids. Published by Elsevier B.V.

Grand rounds: an outbreak of toxic hepatitis among industrial waste disposal workers.

PubMed

Cheong, Hae-Kwan; Kim, Eun A; Choi, Jung-Keun; Choi, Sung-Bong; Suh, Jeong-Ill; Choi, Dae Seob; Kim, Jung Ran

2007-01-01

Industrial waste (which is composed of various toxic chemicals), changes to the disposal process, and addition of chemicals should all be monitored and controlled carefully in the industrial waste industry to reduce the health hazard to workers. Five workers in an industrial waste plant developed acute toxic hepatitis, one of whom died after 3 months due to fulminant hepatitis. In the plant, we detected several chemicals with hepatotoxic potential, including pyridine, dimethylformamide, dimethylacetamide, and methylenedianiline. The workers had been working in the high-vapor-generating area of the plant, and the findings of pathologic examination showed typical features of acute toxic hepatitis. Infectious hepatitis and drug-induced hepatitis were excluded by laboratory findings, as well as the clinical course of hepatitis. All cases of toxic hepatitis in this plant developed after the change of the disposal process to thermochemical reaction-type treatment using unslaked lime reacted with industrial wastes. During this chemical reaction, vapor containing several toxic materials was generated. Although we could not confirm the definitive causative chemical, we suspect that these cases of hepatitis were caused by one of the hepatotoxic agents or by a synergistic interaction among several of them. In the industrial waste treatment process, the danger of developing toxic hepatitis should be kept in mind, because any subtle change of the treatment process can generate various toxic materials and threaten the workers' health. A mixture of hepatotoxic chemicals can induce clinical manifestations that are quite different from those predicted by the toxic property of a single agent.

Effects of medicinal compounds on the differentiation of the eukaryotic microorganism dictyostelium discoideum: can this model be used as a screening test for reproductive toxicity in humans?

PubMed

Dannat, K; Tillner, J; Winckler, T; Weiss, M; Eger, K; Dingermann, T

2003-03-01

Dictyostelium discoideum is a single-cell, eukaryotic microorganism that can undergo multicellular development in order to produce dormant spores. We investigated the capacity of D. discoideum to be used as a rapid screening system for potential developmental toxicity of compounds under development as pharmaceuticals. We used a set of four transgenic D. discoideum strains that expressed a reporter gene under the control of promoters that are active at certain time periods and in distinct cell types during D. discoideum development. We found that teratogens such as valproic acid, tretinoin, or thalidomide interfered to various extents with D. discoideum development, and had different effects on prestalk and prespore cell-specific reporter gene expression. Phenytoin was inactive in this assay, which may point to limitations in metabolization of the compound in Dictyostelium required to exert developmental toxicity. D. discoideum cell culture is cheap and easy to handle compared to mammalian cell cultures or animal teratogenicity models. Although the Dictyostelium-based assay described in this report may not securely predict the teratogenic potential of these drugs in humans, this organism may be qualified for rapid large-scale screenings of synthetic compounds under development as new pharmaceuticals for their potential to interfere with developmental processes and thus help to reduce the amount of teratogenicity tests in animal models.

Application of Multispectral and Hyperspectral Remote Sensing For Detection of Freshwater Harmful Algal Blooms

NASA Astrophysics Data System (ADS)

Kudela, R. M.; Accorsi, E.; Austerberry, D.; Palacios, S. L.

2013-12-01

Freshwater Cyanobacterial Harmful algal blooms (CHABs) represent a pressing and apparently increasing threat to both human and environmental health. In California, toxin producing blooms of several species, including Aphanizomenon, Microcystis, Lyngbya, and Anabaena are common; toxins from these blooms have been linked to impaired drinking water, domestic and wild animal deaths, and increasing evidence for toxin transfer to coastal marine environments, including the death of several California sea otters, a threatened marine species. California scientists and managers are under increasing pressure to identify and mitigate these potentially toxic blooms, but point-source measurements and grab samples have been less than effective. There is increasing awareness that these toxic events are both spatially widespread and ephememeral, leading to the need for better monitoring methods applicable to large spatial and temporal scales. Based on monitoring in several California water bodies, it appears that Aphanizomenon blooms frequently precede dangerous levels of toxins from Microcystis. We are exploring new detection methods for identifying CHABs and potentially distinguishing between blooms of the harmful cyanobacteria Aphanizomenon and Microcystis using remote sensing reflectance from a variety of airborne and satellite sensors. We suggest that Aphanizomenon blooms could potentially be used as an early warning of more highly toxic subsequent blooms, and that these methods, combined with better toxin monitoring, can lead to improved understanding and prediction of CHABs by pinpointing problematic watersheds.

Mechanistic quantitative structure-activity relationship model for the photoinduced toxicity of polycyclic aromatic hydrocarbons. 2: An empirical model for the toxicity of 16 polycyclic aromatic hydrocarbons to the duckweed Lemna gibba L. G-3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, X.D.; Krylov, S.N.; Ren, L.

1997-11-01

Photoinduced toxicity of polycyclic aromatic hydrocarbons (PAHs) occurs via photosensitization reactions (e.g., generation of singlet-state oxygen) and by photomodification (photooxidation and/or photolysis) of the chemicals to more toxic species. The quantitative structure-activity relationship (QSAR) described in the companion paper predicted, in theory, that photosensitization and photomodification additively contribute to toxicity. To substantiate this QSAR modeling exercise it was necessary to show that toxicity can be described by empirically derived parameters. The toxicity of 16 PAHs to the duckweed Lemna gibba was measured as inhibition of leaf production in simulated solar radiation (a light source with a spectrum similar to thatmore » of sunlight). A predictive model for toxicity was generated based on the theoretical model developed in the companion paper. The photophysical descriptors required of each PAH for modeling were efficiency of photon absorbance, relative uptake, quantum yield for triplet-state formation, and the rate of photomodification. The photomodification rates of the PAHs showed a moderate correlation to toxicity, whereas a derived photosensitization factor (PSF; based on absorbance, triplet-state quantum yield, and uptake) for each PAH showed only a weak, complex correlation to toxicity. However, summing the rate of photomodification and the PSF resulted in a strong correlation to toxicity that had predictive value. When the PSF and a derived photomodification factor (PMF; based on the photomodification rate and toxicity of the photomodified PAHs) were summed, an excellent explanatory model of toxicity was produced, substantiating the additive contributions of the two factors.« less

Discriminating modes of toxic action in mice using toxicity in BALB/c mouse fibroblast (3T3) cells.

PubMed

Huang, Tao; Yan, Lichen; Zheng, Shanshan; Wang, Yue; Wang, Xiaohong; Fan, Lingyun; Li, Chao; Zhao, Yuanhui; Martyniuk, Christopher J

2017-12-01

The objective of this study was to determine whether toxicity in mouse fibroblast cells (3T3 cells) could predict toxicity in mice. Synthesized data on toxicity was subjected to regression analysis and it was observed that relationship of toxicities between mice and 3T3 cells was not strong (R 2  = 0.41). Inclusion of molecular descriptors (e.g. ionization, pKa) improved the regression to R 2  = 0.56, indicating that this relationship is influenced by kinetic processes of chemicals or specific toxic mechanisms associated to the compounds. However, to determine if we were able to discriminate modes of action (MOAs) in mice using the toxicities generated from 3T3 cells, compounds were first classified into "baseline" and "reactive" guided by the toxic ratio (TR) for each compound in mice. Sequence, binomial and recursive partitioning analyses provided strong predictions of MOAs in mice based upon toxicities in 3T3 cells. The correct classification of MOAs based on these methods was 86%. Nearly all the baseline compounds predicted from toxicities in 3T3 cells were identified as baseline compounds from the TR in mice. The incorrect assignment of MOAs for some compounds is hypothesized to be due to experimental uncertainty that exists in toxicity assays for both mice and 3T3 cells. Conversely, lack of assignment can also arise because some reactive compounds have MOAs that are different in mice compared to 3T3 cells. The methods developed here are novel and contribute to efforts to reduce animal numbers in toxicity tests that are used to evaluate risks associated with organic pollutants in the environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction of the effect of formulation on the toxicity of chemicals.

PubMed

Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

2017-01-01

Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

Toxicity of ionic liquids: database and prediction via quantitative structure-activity relationship method.

PubMed

Zhao, Yongsheng; Zhao, Jihong; Huang, Ying; Zhou, Qing; Zhang, Xiangping; Zhang, Suojiang

2014-08-15

A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure-Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R(2)) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R(2) and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. Copyright © 2014 Elsevier B.V. All rights reserved.

Diffusive gradients in thin films technique provide robust prediction of metal bioavailability and toxicity in estuarine sediments.

PubMed

Amato, Elvio D; Simpson, Stuart L; Jarolimek, Chad V; Jolley, Dianne F

2014-04-15

Many sediment quality assessment frameworks incorporate contaminant bioavailability as a critical factor regulating toxicity in aquatic ecosystems. However, current approaches do not always adequately predict metal bioavailability to organisms living in the oxidized sediment surface layers. The deployment of the diffusive gradients in thin films (DGT) probes in sediments allows labile metals present in pore waters and weakly bound to the particulate phase to be assessed in a time-integrated manner in situ. In this study, relationships between DGT-labile metal fluxes within 5 mm of the sediment-water interface and lethal and sublethal effects to the amphipod Melita plumulosa were assessed in a range of contaminated estuarine sediments during 10-day laboratory-based bioassays. To account for differing toxicities of metals, DGT fluxes were normalized to water (WQG) or sediment quality guidelines or toxicity thresholds specific for the amphipod. The better dose-response relationship appeared to be the one based on WQG-normalized DGT fluxes, which successfully predicted toxicity despite the wide range of metals and large variations in sediment properties. The study indicated that the labile fraction of metals measured by DGT is useful for predicting metal toxicity to benthic invertebrates, supporting the applicability of this technique as a rapid monitoring tool for sediments quality assessments.

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

DOE PAGES

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish; ...

2015-06-04

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

Modeling Exposures to the Oxidative Potential of PM10

PubMed Central

2012-01-01

Differences in the toxicity of ambient particulate matter (PM) due to varying particle composition across locations may contribute to variability in results from air pollution epidemiologic studies. Though most studies have used PM mass concentration as the exposure metric, an alternative which accounts for particle toxicity due to varying particle composition may better elucidate whether PM from specific sources is responsible for observed health effects. The oxidative potential (OP) of PM < 10 μm (PM10) was measured as the rate of depletion of the antioxidant reduced glutathione (GSH) in a model of human respiratory tract lining fluid. Using a database of GSH OP measures collected in greater London, U.K. from 2002 to 2006, we developed and validated a predictive spatiotemporal model of the weekly GSH OP of PM10 that included geographic predictors. Predicted levels of OP were then used in combination with those of weekly PM10 mass to estimate exposure to PM10 weighted by its OP. Using cross-validation (CV), brake and tire wear emissions of PM10 from traffic within 50 m and tailpipe emissions of nitrogen oxides from heavy-goods vehicles within 100 m were important predictors of GSH OP levels. Predictive accuracy of the models was high for PM10 (CV R2=0.83) but only moderate for GSH OP (CV R2 = 0.44) when comparing weekly levels; however, the GSH OP model predicted spatial trends well (spatial CV R2 = 0.73). Results suggest that PM10 emitted from traffic sources, specifically brake and tire wear, has a higher OP than that from other sources, and that this effect is very local, occurring within 50–100 m of roadways. PMID:22731499

Sediment quality in Burlington Harbor, Lake Champlain, U.S.A.

USGS Publications Warehouse

Lacey, E.M.; King, J.W.; Quinn, J.G.; Mecray, E.L.; Appleby, P.G.; Hunt, A.S.

2001-01-01

Surface samples and cores were collected in 1993 from the Burlington Harbor region of Lake Champlain. Sediment samples were analyzed for trace metals (cadmium, copper, lead, nickel, silver and zinc), simultaneously extracted metal/acid volatile sulfide (SEM-AVS), grain size, nutrients (carbon and nitrogen) and organic contaminants (polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs)). The concentrations of cadmium, copper, silver and zinc from the partial sediment digestion of the surface samples correlated well with each other (r2 > 0.60) indicating that either a common process, or group of processes determined the sediment concentrations of these metals. In an analysis of the spatial distribution of the trace metals and PAHs, high surficial concentrations were present in the southern portion of the Harbor. The trace metal trend was strengthened when the concentrations were normalized by grain size. A sewage treatment plant outfall discharge was present in the southeastern portion of the Harbor at the time of this study and is the major source of trace metal and PAH contamination. Evaluation of sediment cores provides a proxy record of historical trace metal and organic inputs. The peak accumulation rate for copper, cadmium, lead, and zinc was in the late 1960s and the peak silver accumulation rate was later. The greatest accumulation of trace metals occurred in the late 1960s after discharges from the STP began. Subsequent declines in trace metal concentrations may be attributed to increased water and air regulations. The potential toxicity of trace metals and organic contaminants was predicted by comparing contaminant concentrations to benchmark concentrations and potential trace metal bioavailability was predicted with SEM-AVS results. Surface sample results indicate lead, silver, ???PAHs and ???PCBs are potentially toxic and/or bioavailable. These predictions were supported by studies of biota in the Burlington Harbor watershed. There is a clear trend of decreasing PAH and trace metal contaminant concentrations with distance from the STP outfall.Surface samples and cores were collected in 1993 from the Burlington Harbor region of Lake Champlain. Sediment samples were analyzed for trace metals (cadmium, copper, lead, nickel, silver and zinc), simultaneously extracted metal/acid volatile sulfide (SEM-AVS), grain size, nutrients (carbon and nitrogen) and organic contaminants (polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs)). The concentrations of cadmium, copper, silver and zinc from the partial sediment digestion of the surface samples correlated well with each other (r2>0.60) indicating that either a common process, or group of processes determined the sediment concentrations of these metals. In an analysis of the spatial distribution of the trace metals and PAHs, high surficial concentrations were present in the southern portion of the Harbor. The trace metal trend was strengthened when the concentrations were normalized by grain size. A sewage treatment plant outfall discharge was present in the southeastern portion of the Harbor at the time of this study and is the major source of trace metal and PAH contamination. Evaluation of sediment cores provides a proxy record of historical trace metal and organic inputs. The peak accumulation rate for copper, cadmium, lead, and zinc was in the late 1960s and the peak silver accumulation rate was later. The greatest accumulation of trace metals occurred in the late 1960s after discharges from the STP began. Subsequent declines in trace metal concentrations may be attributed to increased water and air regulations. The potential toxicity of trace metals and organic contaminants was predicted by comparing contaminant concentrations to benchmark concentrations and potential trace metal bioavailability was predicted with SEM-AVS results. Surface sample results indicate lead, silver, ??PAHs and ??PCBs are potentially toxic and/or bi

STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

EPA Science Inventory

Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

Inhibition of growth of Zymomonas mobilis by model compounds found in lignocellulosic hydrolysates

PubMed Central

2013-01-01

Background During the pretreatment of biomass feedstocks and subsequent conditioning prior to saccharification, many toxic compounds are produced or introduced which inhibit microbial growth and in many cases, production of ethanol. An understanding of the toxic effects of compounds found in hydrolysate is critical to improving sugar utilization and ethanol yields in the fermentation process. In this study, we established a useful tool for surveying hydrolysate toxicity by measuring growth rates in the presence of toxic compounds, and examined the effects of selected model inhibitors of aldehydes, organic and inorganic acids (along with various cations), and alcohols on growth of Zymomonas mobilis 8b (a ZM4 derivative) using glucose or xylose as the carbon source. Results Toxicity strongly correlated to hydrophobicity in Z. mobilis, which has been observed in Escherichia coli and Saccharomyces cerevisiae for aldehydes and with some exceptions, organic acids. We observed Z. mobilis 8b to be more tolerant to organic acids than previously reported, although the carbon source and growth conditions play a role in tolerance. Growth in xylose was profoundly inhibited by monocarboxylic organic acids compared to growth in glucose, whereas dicarboxylic acids demonstrated little or no effects on growth rate in either substrate. Furthermore, cations can be ranked in order of their toxicity, Ca++ > > Na+ > NH4+ > K+. HMF (5-hydroxymethylfurfural), furfural and acetate, which were observed to contribute to inhibition of Z. mobilis growth in dilute acid pretreated corn stover hydrolysate, do not interact in a synergistic manner in combination. We provide further evidence that Z. mobilis 8b is capable of converting the aldehydes furfural, vanillin, 4-hydroxybenzaldehyde and to some extent syringaldehyde to their alcohol forms (furfuryl, vanillyl, 4-hydroxybenzyl and syringyl alcohol) during fermentation. Conclusions Several key findings in this report provide a mechanism for predicting toxic contributions of inhibitory components of hydrolysate and provide guidance for potential process development, along with potential future strain improvement and tolerance strategies. PMID:23837621

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

PubMed Central

Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

2016-01-01

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

ICRF-187 in clinical oncology.

PubMed

Poster, D S; Penta, J S; Bruno, S; Macdonald, J S

1981-01-01

Although the mechanism of action of ICRF-159 and 187 has not been clearly defined, it is evident from both preclinical and early clinical studies that these compounds are of interest. There are three distinct characteristics of these ICRF compounds that deserve careful clinical evaluation. First, these drugs are apparently alkylating agents with modest, predictable and noncumulative bone marrow toxicity that makes them good potential candidates for combination chemotherapy regimens. The second characteristic that should be investigated is the suggestion that combination of ICRF-187 with an anthracycline may ameliorate the cardiac toxicity of the latter. The third factor in the preclinical evaluation of the bis-diketopiperazines that may have clinical application is the evidence that suggests that these drugs have an antimetastatic effect.

Dosimetric and clinical predictors of radiation-induced lung toxicity in esophageal carcinoma.

PubMed

Zhu, Shu-Chai; Shen, Wen-Bin; Liu, Zhi-Kun; Li, Juan; Su, Jing-Wei; Wang, Yu-Xiang

2011-01-01

Radiation-induced lung toxicity occurs frequently in patients with esophageal carcinoma. This study aims to evaluate the clinical and three-dimensional dosimetric parameters associated with lung toxicity after radiotherapy for esophageal carcinoma. The records of 56 patients treated for esophageal carcinoma were reviewed. The Radiation Therapy Oncology Group criteria for grading of lung toxicity were followed. Spearman's correlation test, the chi-square test and logistic regression analyses were used for statistical analysis. Ten of the 56 patients developed acute toxicity. The toxicity grades were grade 2 in 7 patients and grade 3 in 3 patients; none of the patients developed grade 4 or worse toxicity. One case of toxicity occurred during radiotherapy and 9 occurred 2 weeks to 3 months after radiotherapy. The median time was 2.0 months after radiotherapy. Fourteen patients developed late irradiated lung injury, 3 after 3.5 months, 7 after 9 months, and 4 after 14 months. Radiographic imaging demonstrated patchy consolidation (n = 5), atelectasis with parenchymal distortion (n = 6), and solid consolidation (n = 3). For acute toxicity, the irradiated esophageal volume, number of fields, and most dosimetric parameters were predictive. For late toxicity, chemotherapy combined with radiotherapy and other dosimetric parameters were predictive. No obvious association between the occurrence of acute and late injury was observed. The percent of lung tissue receiving at least 25 Gy (V25), the number of fields, and the irradiated length of the esophagus can be used as predictors of the risk of acute toxicity. Lungs V30, as well as chemotherapy combined with radiotherapy, are predictive of late lung injury.

The influence of particles on bioavailability and toxicity of pesticides in surface water.

PubMed

Knauer, Katja; Homazava, Nadzeya; Junghans, Marion; Werner, Inge

2017-07-01

Environmental risk assessment is an essential part of the approval process for pesticides. Exposure concentrations are compared with ecotoxicological data obtained from standardized laboratory studies and, if available, from field studies to determine the risk of a substance or formulation for aquatic communities. Predicted concentrations in surface waters are derived using, for example, the European FOrum for the Co-ordination of pesticide fate models and their USe (FOCUS) or the German Exposit models, which distinguish between exposure to dissolved and particle-associated pesticide concentrations, because the dissolved concentration is thought to be the best predictor of bioavailability and toxicity. Water and particle-associated concentrations are estimated based on the organic carbon-water partitioning coefficient (K OC ). This review summarizes published information on the influence of natural suspended solids on bioavailability and toxicity of pesticides to aquatic organisms (algae, invertebrates and fish), and the value of log K OC and log K OW (octanol-water coefficient) as sole predictors of the bioavailable fraction is discussed. The information showed that: 1) the quality and origin of suspended solids played an important role in influencing pesticide bioavailability and toxicity; 2) a decrease in toxicity due to the presence of suspended solids was shown only for pyrethroid insecticides with log K OW greater than 5, but the extent of this reduction depended on particle concentration and size, and potentially also on the ecotoxicological endpoint; 3) for pesticides with a log K OW less than 3 (e.g., triazines, carbamates, and organophosphates), the impact of particles on bioavailability and toxicity is small and species dependent; and 4) pesticide bioavailability is greatly influenced by the test species and their physiology (e.g., feeding behavior or digestion). We conclude that exposure of aquatic organisms to pesticides and environmental risk of many pesticides might be underestimated in prospective risk assessment, when predicted environmental concentration is estimated based on the K OC of a compound. Integr Environ Assess Manag 2017;13:585-600. © 2016 SETAC. © 2016 SETAC.

Relationships between soil properties and toxicity of copper and nickel to bok choy and tomato in Chinese soils.

PubMed

Li, Bo; Zhang, Hongtao; Ma, Yibing; McLaughlin, Mike J

2013-10-01

The toxicity of copper (Cu) and nickel (Ni) to bok choy and tomato shoot growth was investigated in a wide range of Chinese soils with and without leaching with artificial rainwater. The results showed that the variations of Ni toxicity induced by soil properties were wider than those of Cu toxicity to both tomato and bok choy plant growth. Leaching generally decreased the toxicity of Cu and Ni added to soils, which also depended on soils, metals, and test plant species. Soil factors controlling metal phytotoxicity were found to be soil pH and soil organic carbon content for Cu, and soil pH for Ni. It was also found that soil pH had stronger effects on Ni toxicity than on Cu toxicity. Predictive toxicity models based on these soil factors were developed. These toxicity models for Cu and Ni toxicity to tomato plant growth were validated using an independent data set for European soils. These models could be applied to predict the Cu and Ni phytotoxicity in not only Chinese soils but also European soils. © 2013 SETAC.

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

PubMed Central

Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D

2007-01-01

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344

Predicting organ toxicity using in vitro bioactivity data and chemical structure

EPA Science Inventory

Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches together with high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a superv...

Predicting acute toxicity of traditional Chinese medicine wastewater using UV absorption and volatile fatty acids as surrogates.

PubMed

Lv, Longyi; Li, Weiguang; Yu, Yang; Meng, Liqiang; Qin, Wen; Wu, Chuandong

2018-03-01

In this study, the applicability of UV absorbance at 254 nm (UV 254 ) and volatile fatty acids (VFAs) to serve as reliable surrogates to predict acute toxicity of traditional Chinese medicine (TCM) wastewater was investigated. The medicine residues and VFAs were identified as main components of the TCM wastewater, and their individual and joint toxicity assays were operated with luminescent bacteria. The median effective concentration (EC 50 ) values of medicine residues and VFAs were in the range of 26.46-165.55 mg/L and 11.45-20.58 g/L, respectively. The joint toxicity action modes of medicine residues, VFAs and medicine residues-VFAs were identified as additive, additive and synergistic respectively. UV 254 and VFAs showed better correlations with acute toxicity according to the correlation analysis, compared with other conventional parameters. The regression model was a good fit for toxic unit (TU 50 ) as a function of UV 254 and VFAs according to the stepwise regression method (adjusted R 2  = 0.836). Validation of the model to the pilot-scale samples provided satisfactory prediction results in the influent and hydrolysis acidification effluent samples tests, but for EGSB effluent and final effluent samples, the model needed further optimization. Surrogates prediction using UV 254 and VFAs provided a valuable and cost-saving tool for rapid or on-line monitoring of acute toxicity of TCM wastewater. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fate and risks of nanomaterials in aquatic and terrestrial environments.

PubMed

Batley, Graeme E; Kirby, Jason K; McLaughlin, Michael J

2013-03-19

Over the last decade, nanoparticles have been used more frequently in industrial applications and in consumer and medical products, and these applications of nanoparticles will likely continue to increase. Concerns about the environmental fate and effects of these materials have stimulated studies to predict environmental concentrations in air, water, and soils and to determine threshold concentrations for their ecotoxicological effects on aquatic or terrestrial biota. Nanoparticles can be added to soils directly in fertilizers orplant protection products or indirectly through application to land or wastewater treatment products such as sludges or biosolids. Nanoparticles may enter aquatic systems directly through industrial discharges or from disposal of wastewater treatment effluents or indirectly through surface runoff from soils. Researchers have used laboratory experiments to begin to understand the effects of nanoparticles on waters and soils, and this Account reviews that research and the translation of those results to natural conditions. In the environment, nanoparticles can undergo a number of potential transformations that depend on the properties both of the nanoparticle and of the receiving medium. These transformations largely involve chemical and physical processes, but they can involve biodegradation of surface coatings used to stabilize many nanomaterial formulations. The toxicity of nanomaterials to algae involves adsorption to cell surfaces and disruption to membrane transport. Higher organisms can directly ingest nanoparticles, and within the food web, both aquatic and terrestrial organisms can accumulate nanoparticles. The dissolution of nanoparticles may release potentially toxic components into the environment. Aggregation with other nanoparticles (homoaggregation) or with natural mineral and organic colloids (heteroaggregation) will dramatically change their fate and potential toxicity in the environment. Soluble natural organic matter may interact with nanoparticles to change surface charge and mobility and affect the interactions of those nanoparticles with biota. Ultimately, aquatic nanomaterials accumulate in bottom sediments, facilitated in natural systems by heteroaggregation. Homoaggregates of nanoparticles sediment more slowly. Nanomaterials from urban, medical, and industrial sources may undergo significant transformations during wastewater treatment processes. For example, sulfidation of silver nanoparticles in wastewater treatment systems converts most of the nanoparticles to silver sulfides (Ag₂S). Aggregation of the nanomaterials with other mineral and organic components of the wastewater often results in most of the nanomaterial being associated with other solids rather than remaining as dispersed nanosized suspensions. Risk assessments for nanomaterial releases to the environment are still in their infancy, and reliable measurements of nanomaterials at environmental concentrations remain challenging. Predicted environmental concentrations based on current usage are low but are expected to increase as use increases. At this early stage, comparisons of estimated exposure data with known toxicity data indicate that the predicted environmental concentrations are orders of magnitude below those known to have environmental effects on biota. As more toxicity data are generated under environmentally-relevant conditions, risk assessments for nanomaterials will improve to produce accurate assessments that assure environmental safety.

Predicting when biliary excretion of parent drug is a major route of elimination in humans.

PubMed

Hosey, Chelsea M; Broccatelli, Fabio; Benet, Leslie Z

2014-09-01

Biliary excretion is an important route of elimination for many drugs, yet measuring the extent of biliary elimination is difficult, invasive, and variable. Biliary elimination has been quantified for few drugs with a limited number of subjects, who are often diseased patients. An accurate prediction of which drugs or new molecular entities are significantly eliminated in the bile may predict potential drug-drug interactions, pharmacokinetics, and toxicities. The Biopharmaceutics Drug Disposition Classification System (BDDCS) characterizes significant routes of drug elimination, identifies potential transporter effects, and is useful in understanding drug-drug interactions. Class 1 and 2 drugs are primarily eliminated in humans via metabolism and will not exhibit significant biliary excretion of parent compound. In contrast, class 3 and 4 drugs are primarily excreted unchanged in the urine or bile. Here, we characterize the significant elimination route of 105 orally administered class 3 and 4 drugs. We introduce and validate a novel model, predicting significant biliary elimination using a simple classification scheme. The model is accurate for 83% of 30 drugs collected after model development. The model corroborates the observation that biliarily eliminated drugs have high molecular weights, while demonstrating the necessity of considering route of administration and extent of metabolism when predicting biliary excretion. Interestingly, a predictor of potential metabolism significantly improves predictions of major elimination routes of poorly metabolized drugs. This model successfully predicts the major elimination route for poorly permeable/poorly metabolized drugs and may be applied prior to human dosing.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

PubMed

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

NASA Astrophysics Data System (ADS)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Callaghan, Michael E., E-mail: elspeth.raymond@health.sa.gov.au; Freemasons Foundation Centre for Men's Health, University of Adelaide; Urology Unit, Repatriation General Hospital, SA Health, Flinders Centre for Innovation in Cancer

Purpose: To identify, through a systematic review, all validated tools used for the prediction of patient-reported outcome measures (PROMs) in patients being treated with radiation therapy for prostate cancer, and provide a comparative summary of accuracy and generalizability. Methods and Materials: PubMed and EMBASE were searched from July 2007. Title/abstract screening, full text review, and critical appraisal were undertaken by 2 reviewers, whereas data extraction was performed by a single reviewer. Eligible articles had to provide a summary measure of accuracy and undertake internal or external validation. Tools were recommended for clinical implementation if they had been externally validated and foundmore » to have accuracy ≥70%. Results: The search strategy identified 3839 potential studies, of which 236 progressed to full text review and 22 were included. From these studies, 50 tools predicted gastrointestinal/rectal symptoms, 29 tools predicted genitourinary symptoms, 4 tools predicted erectile dysfunction, and no tools predicted quality of life. For patients treated with external beam radiation therapy, 3 tools could be recommended for the prediction of rectal toxicity, gastrointestinal toxicity, and erectile dysfunction. For patients treated with brachytherapy, 2 tools could be recommended for the prediction of urinary retention and erectile dysfunction. Conclusions: A large number of tools for the prediction of PROMs in prostate cancer patients treated with radiation therapy have been developed. Only a small minority are accurate and have been shown to be generalizable through external validation. This review provides an accessible catalogue of tools that are ready for clinical implementation as well as which should be prioritized for validation.« less

Prediction of pharmacokinetic and toxicological parameters of a 4-phenylcoumarin isolated from geopropolis: In silico and in vitro approaches.

PubMed

da Cunha, Marcos Guilherme; Franco, Gilson César Nobre; Franchin, Marcelo; Beutler, John A; de Alencar, Severino Matias; Ikegaki, Masaharu; Rosalen, Pedro Luiz

2016-11-30

In silico and in vitro methodologies have been used as important tools in the drug discovery process, including from natural sources. The aim of this study was to predict pharmacokinetic and toxicity (ADME/Tox) properties of a coumarin isolated from geopropolis using in silico and in vitro approaches. Cinnamoyloxy-mammeisin (CNM) isolated from Brazilian M. scutellaris geopropolis was evaluated for its pharmacokinetic parameters by in silico models (ACD/Percepta™ and MetaDrug™ software). Genotoxicity was assessed by in vitro DNA damage signaling PCR array. CNM did not pass all parameters of Lipinski's rule of five, with a predicted low oral bioavailability and high plasma protein binding, but with good predicted blood brain barrier penetration. CNM was predicted to show low affinity to cytochrome P450 family members. Furthermore, the predicted Ames test indicated potential mutagenicity of CNM. Also, the probability of toxicity for organs and tissues was classified as moderate and high for liver and kidney, and moderate and low for skin and eye irritation, respectively. The PCR array analysis showed that CNM significantly upregulated about 7% of all DNA damage-related genes. By exploring the biological function of these genes, it was found that the predicted CNM genotoxicity is likely to be mediated by apoptosis. The predicted ADME/Tox profile suggests that external use of CNM may be preferable to systemic exposure, while its genotoxicity was characterized by the upregulation of apoptosis-related genes after treatment. The combined use of in silico and in vitro approaches to evaluate these parameters generated useful hypotheses to guide further preclinical studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does monensin in chicken manure from poultry farms pose a threat to soil invertebrates?

PubMed

Zižek, Suzana; Hrženjak, Rok; Kalcher, Gabrijela Tavčar; Srimpf, Karin; Semrov, Neva; Zidar, Primož

2011-04-01

Monensin is a carboxylic polyether ionophore used in the poultry industry as a coccidiostat. It enters the environment via manure from broiler farms. In spite of its potential presence in the environment, information concerning monensin residues in manure and soil and its toxicity to soil organisms are insufficient. In the present study, two beneficial soil invertebrate species, earthworms (Eisenia andrei) and woodlice (Porcellio scaber), were used to assess the toxicity of monensin. Animals were exposed to a range of monensin concentrations via soil or food. Earthworm reproduction was found to be the most susceptible endpoint (NOEC=3.5 mg kg(-1) dry soil; EC(50)=12.7 mg kg(-1) dry soil), while no adverse effects were recorded in isopods (NOEC⩾849mgkg(-1) dry soil, NOEC⩾357mgkg(-1) dry food). The obtained toxicity data were compared with potential concentrations of monensin in soil. In view of this, manure from broiler chickens treated with monensin at a poultry farm was sampled. According to monensin and nitrogen concentrations in the chicken manure and the degradation time of monensin, the predicted environmental concentration (PEC) was calculated. PEC of monensin is around 0.013 mg kg(-1) soil if manure is used after 3 months of composting and 0.05 mg kg(-1) soil if used without storage. Data for earthworm reproduction was used to estimate the predicted no-effect concentration (PNEC). If fresh chicken manure is applied to terrestrial ecosystems, the risk quotient (PEC/PNEC ratio) is above 1, which indicates that monensin might pose an environmental risk under certain conditions. To prevent this, it is strongly recommended to compost chicken manure for several months before using it as fertiliser. Copyright © 2010 Elsevier Ltd. All rights reserved.

A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostadinova, Radina; Boess, Franziska; Applegate, Dawn

2013-04-01

Drug-induced liver injury (DILI) is the major cause for liver failure and post-marketing drug withdrawals. Due to species-specific differences in hepatocellular function, animal experiments to assess potential liabilities of drug candidates can predict hepatotoxicity in humans only to a certain extent. In addition to animal experimentation, primary hepatocytes from rat or human are widely used for pre-clinical safety assessment. However, as many toxic responses in vivo are mediated by a complex interplay among different cell types and often require chronic drug exposures, the predictive performance of hepatocytes is very limited. Here, we established and characterized human and rat in vitromore » three-dimensional (3D) liver co-culture systems containing primary parenchymal and non-parenchymal hepatic cells. Our data demonstrate that cells cultured on a 3D scaffold have a preserved composition of hepatocytes, stellate, Kupffer and endothelial cells and maintain liver function for up to 3 months, as measured by the production of albumin, fibrinogen, transferrin and urea. Additionally, 3D liver co-cultures maintain cytochrome P450 inducibility, form bile canaliculi-like structures and respond to inflammatory stimuli. Upon incubation with selected hepatotoxicants including drugs which have been shown to induce idiosyncratic toxicity, we demonstrated that this model better detected in vivo drug-induced toxicity, including species-specific drug effects, when compared to monolayer hepatocyte cultures. In conclusion, our results underline the importance of more complex and long lasting in vitro cell culture models that contain all liver cell types and allow repeated drug-treatments for detection of in vivo-relevant adverse drug effects. - Highlights: ► 3D liver co-cultures maintain liver specific functions for up to three months. ► Activities of Cytochrome P450s remain drug- inducible accross three months. ► 3D liver co-cultures recapitulate drug-induced liver toxicity observed in vivo. ► 3D liver co-cultures can detect species-specific drug toxicity observed in vivo. ► This in vitro model may improve assessment of human relevance of preclinical findings.« less

Applicability of the fish embryo acute toxicity (FET) test (OECD 236) in the regulatory context of Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH).

PubMed

Sobanska, Marta; Scholz, Stefan; Nyman, Anna-Maija; Cesnaitis, Romanas; Gutierrez Alonso, Simon; Klüver, Nils; Kühne, Ralph; Tyle, Henrik; de Knecht, Joop; Dang, Zhichao; Lundbergh, Ivar; Carlon, Claudio; De Coen, Wim

2018-03-01

In 2013 the Organisation for Economic Co-operation and Development (OECD) test guideline (236) for fish embryo acute toxicity (FET) was adopted. It determines the acute toxicity of chemicals to embryonic fish. Previous studies show a good correlation of FET with the standard acute fish toxicity (AFT) test; however, the potential of the FET test to predict AFT, which is required by the Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH) regulation (EC 1907/2006) and the Classification, Labelling and Packaging (CLP) Regulation (EC 1272/2008), has not yet been fully clarified. In 2015 the European Chemicals Agency (ECHA) requested that a consultant perform a scientific analysis of the applicability of FET to predict AFT. The purpose was to compare the toxicity of substances to fish embryos and to adult fish, and to investigate whether certain factors (e.g., physicochemical properties, modes of action, or chemical structures) could be used to define the applicability boundaries of the FET test. Given the limited data availability, the analysis focused on organic substances. The present critical review summarizes the main findings and discusses regulatory application of the FET test under REACH. Given some limitations (e.g., neurotoxic mode of action) and/or remaining uncertainties (e.g., deviation of some narcotic substances), it has been found that the FET test alone is currently not sufficient to meet the essential information on AFT as required by the REACH regulation. However, the test may be used within weight-of-evidence approaches together with other independent, relevant, and reliable sources of information. The present review also discusses further research needs that may overcome the remaining uncertainties and help to increase acceptance of FET as a replacement for AFT in the future. For example, an increase in the availability of data generated according to OECD test guideline 236 may provide evidence of a higher predictive power of the test. Environ Toxicol Chem 2018;37:657-670. © 2017 SETAC. © 2017 SETAC.

Cytotoxicity assays with fish cells as an alternative to the acute lethality test with fish.

PubMed

Segner, Helmut

2004-10-01

In ecotoxicology, in vitro assays with fish cells are currently applied for mechanistic studies, bioanalytical purposes and toxicity screening. This paper discusses the potential of cytotoxicity assays with fish cells to reduce, refine or replace acute lethality tests using fish. Basal cytotoxicity data obtained with fish cell lines or fish primary cell cultures show a reasonable to good correlation with lethality data from acute toxicity tests, with the exception of compounds that exert a specific mode of toxic action. Basal cytotoxicity data from fish cell lines also correlate well with cytotoxicity data from mammalian cell lines. However, both the piscine and mammalian in vitro assays are clearly less sensitive than the fish test. Therefore, in vivo LC50 values (concentrations of the test compounds that are lethal to 50% of the fish in the experiment within 96 hours) currently cannot be predicted from in vitro values. This in vitro-in vivo difference in sensitivity appears to be true for both fish cell lines and mammalian cell lines. Given the good in vitro-in vivo correlation in toxicity ranking, together with the clear-cut difference in sensitivity, the role of cytotoxicity assays in a tiered alternative testing strategy could be in priority setting in relation to toxic hazard and in the toxicity classification of chemicals and environmental samples.

Prediction of in vivo hepatotoxicity effects using in vitro transcriptomics data (SOT)

EPA Science Inventory

High-throughput in vitro transcriptomics data support molecular understanding of chemical-induced toxicity. Here, we evaluated the utility of such data to predict liver toxicity. First, in vitro gene expression data for 93 genes was generated following exposure of metabolically c...

DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS TO DATABASES FOR BUILDING STRUCTURE-TOXICITY PREDICTION MODELS

EPA Science Inventory

DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction Models
Ann M. Richard
US Environmental Protection Agency, Research Triangle Park, NC, USA

Distributed: Decentralized set of standardized, field-delimited databases,...

AOP-informed assessment of endocrine disruption in freshwater crustaceans

EPA Science Inventory

To date, most research focused on developing more efficient and cost effective methods to predict toxicity have focused on human biology. However, there is also a need for effective high throughput tools to predict toxicity to other species that perform critical ecosystem functio...

LARGE-SCALE PREDICTIONS OF MOBILE SOURCE CONTRIBUTIONS TO CONCENTRATIONS OF TOXIC AIR POLLUTANTS

EPA Science Inventory

This presentation shows concentrations and deposition of toxic air pollutants predicted by a 3-D air quality model, the Community Multi Scale Air Quality (CMAQ) modeling system. Contributions from both on-road and non-road mobile sources are analyzed.

Recent Developments in Toxico-Cheminformatics; Supporting a New Paradigm for Predictive Toxicology

EPA Science Inventory

EPA's National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-content and high-thoughput screening d...

Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology

EPA Science Inventory

EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-throughput screening (HTS) data. The D...

QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats.

PubMed

Rasulev, Bakhtiyor; Kusić, Hrvoje; Leszczynska, Danuta; Leszczynski, Jerzy; Koprivanac, Natalija

2010-05-01

The goal of the study was to predict toxicity in vivo caused by aromatic compounds structured with a single benzene ring and the presence or absence of different substituent groups such as hydroxyl-, nitro-, amino-, methyl-, methoxy-, etc., by using QSAR/QSPR tools. A Genetic Algorithm and multiple regression analysis were applied to select the descriptors and to generate the correlation models. The most predictive model is shown to be the 3-variable model which also has a good ratio of the number of descriptors and their predictive ability to avoid overfitting. The main contributions to the toxicity were shown to be the polarizability weighted MATS2p and the number of certain groups C-026 descriptors. The GA-MLRA approach showed good results in this study, which allows the building of a simple, interpretable and transparent model that can be used for future studies of predicting toxicity of organic compounds to mammals.

A comparative study of the usefulness of color vision, photostress recovery time, and visual evoked potential tests in early detection of ocular toxicity from hydroxychloroquine.

PubMed

Heravian, Javad; Saghafi, Massoud; Shoeibi, Naser; Hassanzadeh, Samira; Shakeri, Mohammad Taghi; Sharepoor, Maria

2011-08-01

Ocular toxicity from hydroxychloroquine (HCQ) is rare, but its potential permanence and severity makes it imperative to employ measures and screening protocols to minimize its occurrence. This study was performed to assess the usefulness of color vision, photo stress recovery time (PSRT), and visual evoked potentials (VEP) in early detection of ocular toxicity of HCQ, in patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). 86 patients were included in the study and divided into three groups: (1) with history of HCQ use: interventional 1 (Int.1) without fundoscopic changes and Int.2 with fundoscopic changes; and (2) without history of HCQ use, as control. Visual field, color vision, PSRT and VEP results were recorded for all patients and the effect of age, disease duration, treatment duration and cumulative dose of HCQ on each test was assessed in each group. There was a significant relationship among PSRT and age, treatment duration, cumulative dose of HCQ and disease duration (P<0.001 for all). Color vision was normal in all the cases. P100 amplitude was not different between the three groups (P=0.846), but P100 latency was significantly different (P=0.025) and for Int.2 it was greater than the others. The percentage of abnormal visual fields for Int.2 was more than Int.1 and control groups (P=0.002 and P=0.005 respectively), but Int.1 and control groups were not significantly different (P>0.50). In the early stages of maculopathy, P100 latencies of VEP and PSRT are useful predictors of HCQ ocular toxicity. In patients without ocular symptoms and fundoscopic changes, the P100 latency of VEP predicts more precisely than the others.

Performance of a biological deoxygenation process for ships' ballast water treatment under very cold water conditions.

PubMed

de Lafontaine, Yves; Despatie, Simon-Pierre

2014-02-15

Water deoxygenation is listed among the promising on-board treatment technologies to treat ships' ballast waters to reduce the risk of species transfer. We assessed the performance of a yeast-based bioreactive deoxygenation process in very cold water (<2°C) and determined the potential toxicity of the residual treated waters. Experiments using two treatment levels (0.5% and 1% v/v) were conducted in large-volume (4.5m(3)) tanks over 19 days at mean temperature of 1.5°C. Time to hypoxia varied between 10.3 and 16 days, being slightly higher than the predicted time of 9.8 days from previous empirical relationships. Water deoxygenation was achieved when yeast density exceeded 5×10(5) viable cellsmL(-1) and variation in time to hypoxia was mainly explained by difference in yeast growth. There was no oxycline and no significant difference in yeast density over the 2-m deep water column. Results from six bioassays indicated weak toxic response of treated waters at the 1.0% level, but no potential toxic response at the 0.5% treatment level. Results confirmed that the potential application of a yeast-based deoxygenation process for treating ships' ballast waters extended over the range of water temperature typically encountered during most shipping operational conditions. Time to reach full deoxygenation may however be limiting for universal application of this treatment which should be preferably used for ships making longer voyages in cold environments. There was no evidence that biological deoxygenation at low temperature did increase toxicity risk of treated waters to impede their disposal at the time of discharge. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Mechanisms of Silver Nanoparticle Release, Transformation and Toxicity: A Critical Review of Current Knowledge and Recommendations for Future Studies and Applications

PubMed Central

Reidy, Bogumiła; Haase, Andrea; Luch, Andreas; Dawson, Kenneth A.; Lynch, Iseult

2013-01-01

Nanosilver, due to its small particle size and enormous specific surface area, facilitates more rapid dissolution of ions than the equivalent bulk material; potentially leading to increased toxicity of nanosilver. This, coupled with their capacity to adsorb biomolecules and interact with biological receptors can mean that nanoparticles can reach sub-cellular locations leading to potentially higher localized concentrations of ions once those particles start to dissolve or degrade in situ. Further complicating the story is the capacity for nanoparticles to generate reactive oxygen species, and to interact with, and potentially disturb the functioning of biomolecules such as proteins, enzymes and DNA. The fact that the nanoparticle size, shape, surface coating and a host of other factors contribute to these interactions, and that the particles themselves are evolving or ageing leads to further complications in terms of elucidating mechanisms of interaction and modes of action for silver nanoparticles, in contrast to dissolved silver species. This review aims to provide a critical assessment of the current understanding of silver nanoparticle toxicity, as well as to provide a set of pointers and guidelines for experimental design of future studies to assess the environmental and biological impacts of silver nanoparticles. In particular; in future we require a detailed description of the nanoparticles; their synthesis route and stabilisation mechanisms; their coating; and evolution and ageing under the exposure conditions of the assay. This would allow for comparison of data from different particles; different environmental or biological systems; and structure-activity or structure-property relationships to emerge as the basis for predictive toxicology. On the basis of currently available data; such comparisons or predictions are difficult; as the characterisation and time-resolved data is not available; and a full understanding of silver nanoparticle dissolution and ageing under different conditions is observed. Clear concerns are emerging regarding the overuse of nanosilver and the potential for bacterial resistance to develop. A significant conclusion includes the need for a risk—benefit analysis for all applications and eventually restrictions of the uses where a clear benefit cannot be demonstrated. PMID:28809275

Aging of TiO2 Nanoparticles Transiently Increases Their Toxicity to the Pelagic Microcrustacean Daphnia magna

PubMed Central

Seitz, Frank; Lüderwald, Simon; Rosenfeldt, Ricki R.; Schulz, Ralf; Bundschuh, Mirco

2015-01-01

During their aquatic life cycle, nanoparticles are subject to environmentally driven surface modifications (e.g. agglomeration or coating) associated with aging. Although the ecotoxicological potential of nanoparticles might be affected by these processes, only limited information about the potential impact of aging is available. In this context, the present study investigated acute (96 h) and chronic (21 d) implications of systematically aged titanium dioxide nanoparticles (nTiO2; ~90 nm) on the standard test species Daphnia magna by following the respective test guidelines. The nTiO2 were aged for 0, 1, 3 and 6 d in media with varying ionic strengths (Milli-Q water: approx. 0.00 mmol/L and ASTM: 9.25 mmol/L) in the presence or absence of natural organic matter (NOM). Irrespective of the other parameters, aging in Milli-Q did not change the acute toxicity relative to an unaged control. In contrast, 6 d aged nTiO2 in ASTM without NOM caused a fourfold decreased acute toxicity. Relative to the 0 d aged particles, nTiO2 aged for 1 and 3 d in ASTM with NOM, which is the most environmentally-relevant setup used here, significantly increased acute toxicity (by approximately 30%), while a toxicity reduction (60%) was observed for 6 d aged nTiO2. Comparable patterns were observed during the chronic experiments. A likely explanation for this phenomenon is that the aging of nTiO2 increases the particle size at the start of the experiment or the time of the water exchange from <100 nm to approximately 500 nm, which is the optimal size range to be taken up by filter feeding D. magna. If subjected to further agglomeration, larger nTiO2 particles, however, cannot be retained by the daphnids’ filter apparatus ultimately reducing their ecotoxicological potential. This non-linear pattern of increasing and decreasing nTiO2 related toxicity over the aging duration, highlights the knowledge gap regarding the underlying mechanisms and processes. This understanding seems, however, fundamental to predict the risks of nanoparticles in the field. PMID:25933435

Assessment and prediction of joint algal toxicity of binary mixtures of graphene and ionic liquids.

PubMed

Wang, Zhuang; Zhang, Fan; Wang, Se; Peijnenburg, Willie J G M

2017-10-01

Graphene and ionic liquids (ILs) released into the environment will interact with each other. So far however, the risks associated with the concurrent exposure of biota to graphene and ILs in the environment have received little attention. The research reported here focused on observing and predicting the joint toxicity effects in the green alga Scenedesmus obliquus exposed to binary mixtures of intrinsic graphene (iG)/graphene oxide (GO) and five ILs of varying anionic and cationic types. The isolated ILs in the binary mixtures were the main contributors to toxicity. The binary GO-IL mixtures resulted in more severe joint toxicity than the binary iG-IL mixtures, irrespective of mixture ratios. The mechanism of the joint toxicity may be associated with the adsorption capability of the graphenes for the ILs, the dispersion stability of the graphenes in aquatic media, and modulation of the binary mixtures-induced oxidative stress. A toxic unit assessment showed that the graphene and IL toxicities were additive at low concentration of the mixtures but antagonistic at high concentration of the mixtures. Predictions made using the concentration addition and independent action models were close to the observed joint toxicities regardless of mixture types and mixture ratios. These findings provide new insights that are of use in the risk assessment of mixtures of engineered nanoparticles and other environmentally relevant contaminants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of graphene-based nanomaterials (GBNMs) on the structural and functional conformations of hepcidin peptide

NASA Astrophysics Data System (ADS)

Singh, Krishna P.; Baweja, Lokesh; Wolkenhauer, Olaf; Rahman, Qamar; Gupta, Shailendra K.

2018-03-01

Graphene-based nanomaterials (GBNMs) are widely used in various industrial and biomedical applications. GBNMs of different compositions, size and shapes are being introduced without thorough toxicity evaluation due to the unavailability of regulatory guidelines. Computational toxicity prediction methods are used by regulatory bodies to quickly assess health hazards caused by newer materials. Due to increasing demand of GBNMs in various size and functional groups in industrial and consumer based applications, rapid and reliable computational toxicity assessment methods are urgently needed. In the present work, we investigate the impact of graphene and graphene oxide nanomaterials on the structural conformations of small hepcidin peptide and compare the materials for their structural and conformational changes. Our molecular dynamics simulation studies revealed conformational changes in hepcidin due to its interaction with GBMNs, which results in a loss of its functional properties. Our results indicate that hepcidin peptide undergo severe structural deformations when superimposed on the graphene sheet in comparison to graphene oxide sheet. These observations suggest that graphene is more toxic than a graphene oxide nanosheet of similar area. Overall, this study indicates that computational methods based on structural deformation, using molecular dynamics (MD) simulations, can be used for the early evaluation of toxicity potential of novel nanomaterials.

Cellular evaluation of the toxicity of combustion derived particulate matter: influence of particle grinding and washing on cellular response.

PubMed

Katterman, Matthew E; Birchard, Stephanie; Seraphin, Supapan; Riley, Mark R

2007-01-01

There is increasing interest in continual monitoring of air for the presence of inhalation health hazards, such as particulate matter, produced through combustion of fossil fuels. Currently there are no means to rapidly evaluate the relative toxicity of materials or to reliably predict potential health impact due to the complexity of the composition, size, and physical properties of particulate matter. This research evaluates the feasibility of utilizing cell cultures as the biological recognition element of an inhalation health monitoring system. The response of rat lung type II epithelial (RLE-6TN) cells to a variety of combustion derived particulates and their components has been evaluated. The focus of the current work is an evaluation of how particles are delivered to a cellular sensing array and to what degree does washing or grinding of the particles impacts the cellular response. There were significant differences in the response of these lung cells to PM's of varying sources. Mechanical grinding or washing was found to alter the toxicity of some of these particulates; however these effects were strongly dependent on the fuel source. Washing reduced toxicity of oil PM's, but had little effect on those from diesel or coal. Mechanical grinding could significantly increase the toxicity of coal PM's, but not for oil or diesel.

Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stierum, Rob; Heijne, Wilbert; Kienhuis, Anne

2005-09-01

Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicologicalmore » assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole.« less

Cross-species extrapolation of toxicity information using the ...

EPA Pesticide Factsheets

In the United States, the Endocrine Disruptor Screening Program (EDSP) was established to identify chemicals that may lead to adverse effects via perturbation of the endocrine system (i.e., estrogen, androgen, and thyroid hormone systems). In the mid-1990s the EDSP adopted a two tiered approach for screening chemicals that applied standardized in vitro and in vivo toxicity tests. The Tier 1 screening assays were designed to identify substances that have the potential of interacting with the endocrine system and Tier 2 testing was developed to identify adverse effects caused by the chemical, with documentation of dose-response relationships. While this tiered approach was effective in identifying possible endocrine disrupting chemicals, the cost and time to screen a single chemical was significant. Therefore, in 2012 the EDSP proposed a transition to make greater use of computational approaches (in silico) and high-throughput screening (HTS; in vitro) assays to more rapidly and cost-efficiently screen chemicals for endocrine activity. This transition from resource intensive, primarily in vivo, screening methods to more pathway-based approaches aligns with the simultaneously occurring transformation in toxicity testing termed “Toxicity Testing in the 21st Century” which shifts the focus to the disturbance of the biological pathway predictive of the observable toxic effects. An example of such screening tools include the US Environmental Protection Agency’s

Geographic boundaries in breast, lung and colorectal cancers in relation to exposure to air toxics in Long Island, New York

PubMed Central

Jacquez, Geoffrey M; Greiling, Dunrie A

2003-01-01

Background This two-part study employs several statistical techniques to evaluate the geographic distribution of breast cancer in females and colorectal and lung cancers in males and females in Nassau, Queens, and Suffolk counties, New York, USA. In this second paper, we compare patterns in standardized morbidity ratios (SMR values), calculated from New York State Department of Health (NYSDOH) data, to geographic patterns in overall predicted risk (OPR) from air toxics using exposures estimated in the USEPA National Air Toxics Assessment database. Results We identified significant geographic boundaries in SMR and OPR. We found little or no association between the SMR of colorectal and breast cancers and the OPR for each cancer from exposure to the air toxics. We did find boundaries in male and female lung cancer SMR and boundaries in lung cancer OPR to be closer to one another than expected. Conclusion While consistent with a causal relationship between air toxics and lung cancer incidence, the boundary analysis does not demonstrate the existence of a causal relationship. However, now that the areas of overlap between boundaries in lung cancer incidence and potential airborne exposures have been identified, we can begin to evaluate local- as well as large-scale determinants of lung cancer. PMID:12633502

Evaluation of Short-Term Bioassays to Predict Functional Impairment. Development of Hepatic Bioassays in Laboratory Animals, Directory of Institutions/Individuals.

DTIC Science & Technology

1980-10-01

Organizations Compounds Tested Morphological Tests Toxic Substances Functional Tests rR ACT Cutlue OM v.a e sif nemooery ad Identify by block number) %MITRE has...demonstrated ability to evaluate and predict hepatic impairment rvsulting from toxicant exposures. This directory is a companion to Selected Short-Term...Hepatic Toxicity Tests, which describes the available hepatic testing protocols and assesses their suitability for a screening program. This direc

Three dimensional quantitative structure-toxicity relationship modeling and prediction of acute toxicity for organic contaminants to algae.

PubMed

Jin, Xiangqin; Jin, Minghao; Sheng, Lianxi

2014-08-01

Although numerous chemicals have been identified to have significant toxicological effect on aquatic organisms, there is still lack of a reliable, high-throughput approach to evaluate, screen and monitor the presence of organic contaminants in aquatic system. In the current study, we proposed a synthetic pipeline to automatically model and predict the acute toxicity of chemicals to algae. In the procedure, a new alignment-free three dimensional (3D) structure characterization method was described and, with this method, several 3D-quantitative structure-toxicity relationship (3D-QSTR) models were developed, from which two were found to exhibit strong internal fitting ability and high external predictive power. The best model was established by Gaussian process (GP), which was further employed to perform extrapolation on a random compound library consisting of 1014 virtually generated substituted benzenes. It was found that (i) substitution number can only exert slight influence on chemical׳s toxicity, but low-substituted benzenes seem to have higher toxicity than those of high-substituted entities, and (ii) benzenes substituted by nitro group and halogens exhibit high acute toxicity as compared to other substituents such as methyl and carboxyl groups. Subsequently, several promising candidates suggested by computational prediction were assayed by using a standard algal growth inhibition test. Consequently, four substituted benzenes, namely 2,3-dinitrophenol, 2-chloro-4-nitroaniline, 1,2,3-trinitrobenzene and 3-bromophenol, were determined to have high acute toxicity to Scenedesmus obliquus, with their EC50 values of 2.5±0.8, 10.5±2.1, 1.4±0.2 and 42.7±5.4μmol/L, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Small Bowel Dose Parameters Predicting Grade ≥3 Acute Toxicity in Rectal Cancer Patients Treated With Neoadjuvant Chemoradiation: An Independent Validation Study Comparing Peritoneal Space Versus Small Bowel Loop Contouring Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, Robyn, E-mail: robynbanerjee@gmail.com; Chakraborty, Santam; Nygren, Ian

Purpose: To determine whether volumes based on contours of the peritoneal space can be used instead of individual small bowel loops to predict for grade ≥3 acute small bowel toxicity in patients with rectal cancer treated with neoadjuvant chemoradiation therapy. Methods and Materials: A standardized contouring method was developed for the peritoneal space and retrospectively applied to the radiation treatment plans of 67 patients treated with neoadjuvant chemoradiation therapy for rectal cancer. Dose-volume histogram (DVH) data were extracted and analyzed against patient toxicity. Receiver operating characteristic analysis and logistic regression were carried out for both contouring methods. Results: Grade ≥3more » small bowel toxicity occurred in 16% (11/67) of patients in the study. A highly significant dose-volume relationship between small bowel irradiation and acute small bowel toxicity was supported by the use of both small bowel loop and peritoneal space contouring techniques. Receiver operating characteristic analysis demonstrated that, for both contouring methods, the greatest sensitivity for predicting toxicity was associated with the volume receiving between 15 and 25 Gy. Conclusion: DVH analysis of peritoneal space volumes accurately predicts grade ≥3 small bowel toxicity in patients with rectal cancer receiving neoadjuvant chemoradiation therapy, suggesting that the contours of the peritoneal space provide a reasonable surrogate for the contours of individual small bowel loops. The study finds that a small bowel V15 less than 275 cc and a peritoneal space V15 less than 830 cc are associated with a less than 10% risk of grade ≥3 acute toxicity.« less

Acute toxicity value extrapolation with fish and aquatic invertebrates

USGS Publications Warehouse

Buckler, Denny R.; Mayer, Foster L.; Ellersieck, Mark R.; Asfaw, Amha

2005-01-01

Assessment of risk posed by an environmental contaminant to an aquatic community requires estimation of both its magnitude of occurrence (exposure) and its ability to cause harm (effects). Our ability to estimate effects is often hindered by limited toxicological information. As a result, resource managers and environmental regulators are often faced with the need to extrapolate across taxonomic groups in order to protect the more sensitive members of the aquatic community. The goals of this effort were to 1) compile and organize an extensive body of acute toxicity data, 2) characterize the distribution of toxicant sensitivity across taxa and species, and 3) evaluate the utility of toxicity extrapolation methods based upon sensitivity relations among species and chemicals. Although the analysis encompassed a wide range of toxicants and species, pesticides and freshwater fish and invertebrates were emphasized as a reflection of available data. Although it is obviously desirable to have high-quality acute toxicity values for as many species as possible, the results of this effort allow for better use of available information for predicting the sensitivity of untested species to environmental contaminants. A software program entitled “Ecological Risk Analysis” (ERA) was developed that predicts toxicity values for sensitive members of the aquatic community using species sensitivity distributions. Of several methods evaluated, the ERA program used with minimum data sets comprising acute toxicity values for rainbow trout, bluegill, daphnia, and mysids provided the most satisfactory predictions with the least amount of data. However, if predictions must be made using data for a single species, the most satisfactory results were obtained with extrapolation factors developed for rainbow trout (0.412), bluegill (0.331), or scud (0.041). Although many specific exceptions occur, our results also support the conventional wisdom that invertebrates are generally more sensitive to contaminants than fish are.

An integrated approach to improved toxicity prediction for the safety assessment during preclinical drug development using Hep G2 cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noor, Fozia; Niklas, Jens; Mueller-Vieira, Ursula

2009-06-01

Efficient and accurate safety assessment of compounds is extremely important in the preclinical development of drugs especially when hepatotoxicty is in question. Multiparameter and time resolved assays are expected to greatly improve the prediction of toxicity by assessing complex mechanisms of toxicity. An integrated approach is presented in which Hep G2 cells and primary rat hepatocytes are compared in frequently used cytotoxicity assays for parent compound toxicity. The interassay variability was determined. The cytotoxicity assays were also compared with a reliable alternative time resolved respirometric assay. The set of training compounds consisted of well known hepatotoxins; amiodarone, carbamazepine, clozapine, diclofenac,more » tacrine, troglitazone and verapamil. The sensitivity of both cell systems in each tested assay was determined. Results show that careful selection of assay parameters and inclusion of a kinetic time resolved assay improves prediction for non-metabolism mediated toxicity using Hep G2 cells as indicated by a sensitivity ratio of 1. The drugs with EC{sub 50} values 100 {mu}M or lower were considered toxic. The difference in the sensitivity of the two cell systems to carbamazepine which causes toxicity via reactive metabolites emphasizes the importance of human cell based in-vitro assays. Using the described system, primary rat hepatocytes do not offer advantage over the Hep G2 cells in parent compound toxicity evaluation. Moreover, respiration method is non invasive, highly sensitive and allows following the time course of toxicity. Respiration assay could serve as early indicator of changes that subsequently lead to toxicity.« less

Assessment of herbal medicinal products: Challenges, and opportunities to increase the knowledge base for safety assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jordan, Scott A., E-mail: scott.jordan@hc-sc.gc.c; Cunningham, David G.; Marles, Robin J.

Although herbal medicinal products (HMP) have been perceived by the public as relatively low risk, there has been more recognition of the potential risks associated with this type of product as the use of HMPs increases. Potential harm can occur via inherent toxicity of herbs, as well as from contamination, adulteration, plant misidentification, and interactions with other herbal products or pharmaceutical drugs. Regulatory safety assessment for HMPs relies on both the assessment of cases of adverse reactions and the review of published toxicity information. However, the conduct of such an integrated investigation has many challenges in terms of the quantitymore » and quality of information. Adverse reactions are under-reported, product quality may be less than ideal, herbs have a complex composition and there is lack of information on the toxicity of medicinal herbs or their constituents. Nevertheless, opportunities exist to capitalise on newer information to increase the current body of scientific evidence. Novel sources of information are reviewed, such as the use of poison control data to augment adverse reaction information from national pharmacovigilance databases, and the use of more recent toxicological assessment techniques such as predictive toxicology and omics. The integration of all available information can reduce the uncertainty in decision making with respect to herbal medicinal products. The example of Aristolochia and aristolochic acids is used to highlight the challenges related to safety assessment, and the opportunities that exist to more accurately elucidate the toxicity of herbal medicines.« less

Evaluation of antimicrobial activity of glycerol monolaurate nanocapsules against American foulbrood disease agent and toxicity on bees.

PubMed

Lopes, Leonardo Q S; Santos, Cayane G; de Almeida Vaucher, Rodrigo; Gende, Liesel; Raffin, Renata P; Santos, Roberto C V

2016-08-01

The American Foulbrood Disease (AFB) is a fatal larval bee infection. The etiologic agent is the bacterium Paenibacillus larvae. The treatment involves incineration of all contaminated materials, leading to high losses. The Glycerol Monolaurate (GML) is a known antimicrobial potential compound, however its use is reduced due to its low solubility in water and high melting point. The nanoencapsulation of some drugs offers several advantages like improved stability and solubility in water. The present study aimed to evaluate the antimicrobial activity against P. larvae and the toxicity in bees of GML nanoparticles. The nanocapsules were produced and presented mean diameter of 210 nm, polydispersity index of 0.044, and zeta potential of -23.4 mV demonstrating the acceptable values to predict a stable system. The microdilution assay showed that it is necessary 142 and 285 μg/mL of GML nanocapsules to obtain a bacteriostatic and bactericidal effect respectively. The time-kill curve showed the controlled release of compound, exterminating the microorganism after 24 h. The GML nanocapsules were able to kill the spore form of Paenibacillus larvae while the GML do not cause any effect. The assay in bees showed that the GML has a high toxicity while the GML nanoparticles showed a decrease on toxic effects. Concluding, the formulation shows positive results in the action to combat AFB besides not causing damage to bees. Copyright © 2016 Elsevier Ltd. All rights reserved.

Is qPCR a Reliable Indicator of Cyanotoxin Risk in Freshwater?

PubMed Central

Pacheco, Ana Beatriz F.; Guedes, Iame A.; Azevedo, Sandra M.F.O.

2016-01-01

The wide distribution of cyanobacteria in aquatic environments leads to the risk of water contamination by cyanotoxins, which generate environmental and public health issues. Measurements of cell densities or pigment contents allow both the early detection of cellular growth and bloom monitoring, but these methods are not sufficiently accurate to predict actual cyanobacterial risk. To quantify cyanotoxins, analytical methods are considered the gold standards, but they are laborious, expensive, time-consuming and available in a limited number of laboratories. In cyanobacterial species with toxic potential, cyanotoxin production is restricted to some strains, and blooms can contain varying proportions of both toxic and non-toxic cells, which are morphologically indistinguishable. The sequencing of cyanobacterial genomes led to the description of gene clusters responsible for cyanotoxin production, which paved the way for the use of these genes as targets for PCR and then quantitative PCR (qPCR). Thus, the quantification of cyanotoxin genes appeared as a new method for estimating the potential toxicity of blooms. This raises a question concerning whether qPCR-based methods would be a reliable indicator of toxin concentration in the environment. Here, we review studies that report the parallel detection of microcystin genes and microcystin concentrations in natural populations and also a smaller number of studies dedicated to cylindrospermopsin and saxitoxin. We discuss the possible issues associated with the contradictory findings reported to date, present methodological limitations and consider the use of qPCR as an indicator of cyanotoxin risk. PMID:27338471

Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation.

PubMed

Shinde, Vaibhav; Klima, Stefanie; Sureshkumar, Perumal Srinivasan; Meganathan, Kesavan; Jagtap, Smita; Rempel, Eugen; Rahnenführer, Jörg; Hengstler, Jan Georg; Waldmann, Tanja; Hescheler, Jürgen; Leist, Marcel; Sachinidis, Agapios

2015-06-17

Efficient protocols to differentiate human pluripotent stem cells to various tissues in combination with -omics technologies opened up new horizons for in vitro toxicity testing of potential drugs. To provide a solid scientific basis for such assays, it will be important to gain quantitative information on the time course of development and on the underlying regulatory mechanisms by systems biology approaches. Two assays have therefore been tuned here for these requirements. In the UKK test system, human embryonic stem cells (hESC) (or other pluripotent cells) are left to spontaneously differentiate for 14 days in embryoid bodies, to allow generation of cells of all three germ layers. This system recapitulates key steps of early human embryonic development, and it can predict human-specific early embryonic toxicity/teratogenicity, if cells are exposed to chemicals during differentiation. The UKN1 test system is based on hESC differentiating to a population of neuroectodermal progenitor (NEP) cells for 6 days. This system recapitulates early neural development and predicts early developmental neurotoxicity and epigenetic changes triggered by chemicals. Both systems, in combination with transcriptome microarray studies, are suitable for identifying toxicity biomarkers. Moreover, they may be used in combination to generate input data for systems biology analysis. These test systems have advantages over the traditional toxicological studies requiring large amounts of animals. The test systems may contribute to a reduction of the costs for drug development and chemical safety evaluation. Their combination sheds light especially on compounds that may influence neurodevelopment specifically.

Characterization of human-induced pluripotent stem cell-derived cardiomyocytes: bioenergetics and utilization in safety screening.

PubMed

Rana, Payal; Anson, Blake; Engle, Sandra; Will, Yvonne

2012-11-01

Cardiotoxicity remains the number one reason for drug withdrawal from the market, and Food and Drug Administration issued black box warnings, thus demonstrating the need for more predictive preclinical safety screening, especially early in the drug discovery process when much chemical substrate is available. Whereas human-ether-a-go-go related gene screening has become routine to mitigate proarrhythmic risk, the development of in vitro assays predicting additional on- and off-target biochemical toxicities will benefit from cellular models exhibiting true cardiomyocyte characteristics such as native tissue-like mitochondrial activity. Human stem cell-derived tissue cells may provide such a model. This hypothesis was tested using a combination of flux analysis, gene and protein expression, and toxicity-profiling techniques to characterize mitochondrial function in induced pluripotent stem cell (iPSC) derived human cardiomyocytes in the presence of differing carbon sources over extended periods in cell culture. Functional analyses demonstrate that iPSC-derived cardiomyocytes are (1) capable of utilizing anaerobic or aerobic respiration depending upon the available carbon substrate and (2) bioenergetically closest to adult heart tissue cells when cultured in galactose or galactose supplemented with fatty acids. We utilized this model to test a variety of kinase inhibitors with known clinical cardiac liabilities for their potential toxicity toward these cells. We found that the kinase inhibitors showed a dose-dependent toxicity to iPSC cardiomyocytes grown in galactose and that oxygen consumption rates were significantly more affected than adenosine triphosphate production. Sorafenib was found to have the most effect, followed by sunitinib, dasatinib, imatinib, lapatinib, and nioltinib.

Overlooking relevant confounders in the assessment of pesticides and human health: a reply to Mostafalou and Abdollahi.

PubMed

Fluegge, Keith

2017-02-01

Mostafalou and Abdollahi (Arch Toxicol, 2016. doi: 10.1007/s00204-016-1849-x ) have recently conducted a review exploring human exposure to pesticides and systematically highlighting known toxic mechanisms from these exposures. Their review is extensive and appraises the literature on pesticide toxicity in a number of domains, including neurotoxicity and developmental toxicity. However, as important as it may be to understand the toxicological potential of these chemicals in humans and other species, the role of these chemicals as proxies for other environmental exposures should not be excluded. Recently, we published evidence suggesting use of the herbicide, glyphosate, may predict health care utilization for attention-deficit hyperactivity disorder (ADHD), a neurodevelopmental disorder that is characterized by cognitive impairments leading to attention deficits, impulsivity, and hyperactivity. Given that the finding appeared to be land-dependent, we concluded that glyphosate may be an instrumental variable that predicts severe ADHD mostly through its inseparableness from nitrogen fertilizers at a county level and increasing agricultural air emissions of the compound, nitrous oxide (N 2 O). Since the WHO designates N 2 O as an important modern health medicine, its environmental imprint is largely thought to be inconsequential in a human health context and, unfortunately, not worthy of further consideration. Our findings and subsequent review on the topic are not amenable to this complacency. We argue that future pesticide risk assessments be made more comprehensive insofar as identifying not only critical, direct routes of toxicity, as extensively reviewed by Mostafalou and Abdollahi (2016), but also indirect toxicological mechanisms such as the one presented in this correspondence.

Validation of a novel air toxic risk model with air monitoring.

PubMed

Pratt, Gregory C; Dymond, Mary; Ellickson, Kristie; Thé, Jesse

2012-01-01

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity. © 2011 Society for Risk Analysis.

NanoE-Tox: New and in-depth database concerning ecotoxicity of nanomaterials.

PubMed

Juganson, Katre; Ivask, Angela; Blinova, Irina; Mortimer, Monika; Kahru, Anne

2015-01-01

The increasing production and use of engineered nanomaterials (ENMs) inevitably results in their higher concentrations in the environment. This may lead to undesirable environmental effects and thus warrants risk assessment. The ecotoxicity testing of a wide variety of ENMs rapidly evolving in the market is costly but also ethically questionable when bioassays with vertebrates are conducted. Therefore, alternative methods, e.g., models for predicting toxicity mechanisms of ENMs based on their physico-chemical properties (e.g., quantitative (nano)structure-activity relationships, QSARs/QNARs), should be developed. While the development of such models relies on good-quality experimental toxicity data, most of the available data in the literature even for the same test species are highly variable. In order to map and analyse the state of the art of the existing nanoecotoxicological information suitable for QNARs, we created a database NanoE-Tox that is available as Supporting Information File 1. The database is based on existing literature on ecotoxicology of eight ENMs with different chemical composition: carbon nanotubes (CNTs), fullerenes, silver (Ag), titanium dioxide (TiO2), zinc oxide (ZnO), cerium dioxide (CeO2), copper oxide (CuO), and iron oxide (FeO x ; Fe2O3, Fe3O4). Altogether, NanoE-Tox database consolidates data from 224 articles and lists altogether 1,518 toxicity values (EC50/LC50/NOEC) with corresponding test conditions and physico-chemical parameters of the ENMs as well as reported toxicity mechanisms and uptake of ENMs in the organisms. 35% of the data in NanoE-Tox concerns ecotoxicity of Ag NPs, followed by TiO2 (22%), CeO2 (13%), and ZnO (10%). Most of the data originates from studies with crustaceans (26%), bacteria (17%), fish (13%), and algae (11%). Based on the median toxicity values of the most sensitive organism (data derived from three or more articles) the toxicity order was as follows: Ag > ZnO > CuO > CeO2 > CNTs > TiO2 > FeO x . We believe NanoE-Tox database contains valuable information for ENM environmental hazard estimation and development of models for predicting toxic potential of ENMs.

NEW METHODS TO SCREEN FOR DEVELOPMENTAL NEUROTOXICITY.

EPA Science Inventory

The development of alternative methods for toxicity testing is driven by the need for scientifically valid data (i.e. predictive of a toxic effect) that can be obtained in a rapid and cost-efficient manner. These predictions will enable decisions to be made as to whether further ...

Challenges for the development of a biotic ligand model predicting copper toxicity in estuaries and seas.

PubMed

de Polo, Anna; Scrimshaw, Mark D

2012-02-01

An effort is ongoing to develop a biotic ligand model (BLM) that predicts copper (Cu) toxicity in estuarine and marine environments. At present, the BLM accounts for the effects of water chemistry on Cu speciation, but it does not consider the influence of water chemistry on the physiology of the organisms. We discuss how chemistry affects Cu toxicity not only by controlling its speciation, but also by affecting the osmoregulatory physiology of the organism, which varies according to salinity. In an attempt to understand the mechanisms of Cu toxicity and predict its impacts, we explore the hypothesis that the common factor linking the main toxic effects of Cu is the enzyme carbonic anhydrase (CA), because it is a Cu target with multiple functions and salinity-dependent expression and activity. According to this hypothesis, the site of action of Cu in marine fish may be not only the gill, but also the intestine, because in this tissue CA plays an important role in ion transport and water adsorption. Therefore, the BLM of Cu toxicity to marine fish should also consider the intestine as a biotic ligand. Finally, we underline the need to incorporate the osmotic gradient into the BLM calculations to account for the influence of physiology on Cu toxicity. Copyright © 2011 SETAC.

Bioavailability of cyanide and metal-cyanide mixtures to aquatic life.

PubMed

Redman, Aaron; Santore, Robert

2012-08-01

Cyanide can be toxic to aquatic organisms, and the U.S. Environmental Protection Agency has developed ambient water-quality criteria to protect aquatic life. Recent work suggests that considering free, rather than total, cyanide provides a more accurate measure of the biological effects of cyanides and provides a basis for water-quality criteria. Aquatic organisms are sensitive to free cyanide, although certain metals can form stable complexes and reduce the amount of free cyanide. As a result, total cyanide is less toxic when complexing metals are present. Cyanide is often present in complex effluents, which requires understanding how other components within these complex effluents can affect cyanide speciation and bioavailability. The authors have developed a model to predict the aqueous speciation of cyanide and have shown that this model can predict the toxicity of metal-cyanide complexes in terms of free cyanide in solutions with varying water chemistry. Toxicity endpoints based on total cyanide ranged over several orders of magnitude for various metal-cyanide mixtures. However, predicted free cyanide concentrations among these same tests described the observed toxicity data to within a factor of 2. Aquatic toxicity can be well-described using free cyanide, and under certain conditions the toxicity was jointly described by free cyanide and elevated levels of bioavailable metals. Copyright © 2012 SETAC.

"Artificial micro organs"--a microfluidic device for dielectrophoretic assembly of liver sinusoids.

PubMed

Schütte, Julia; Hagmeyer, Britta; Holzner, Felix; Kubon, Massimo; Werner, Simon; Freudigmann, Christian; Benz, Karin; Böttger, Jan; Gebhardt, Rolf; Becker, Holger; Stelzle, Martin

2011-06-01

In order to study possible toxic side effects of potential drug compounds in vitro a reliable test system is needed. Predicting liver toxicity presents a major challenge of particular importance as liver cells grown in a cell culture suffer from a rapid loss of their liver specific functions. Therefore we are developing a new microfluidic test system for liver toxicity. This test system is based on an organ-like liver 3D co-culture of hepatocytes and endothelial cells. We devised a microfluidic chip featuring cell culture chambers with integrated electrodes for the assembly of liver sinusoids by dielectrophoresis. Fluid channels enable an organ-like perfusion with culture media and test compounds. Different chamber designs were studied and optimized with regard to dielectrophoretic force distribution, hydrodynamic flow profile, and cell trapping rate using numeric simulations. Based on simulation results a microchip was injection-moulded from COP. This chip allowed the assembly of viable hepatocytes and endothelial cells in a sinusoid-like fashion.

Defense mechanisms against toxic phytochemicals in the diet of domestic animals.

PubMed

Fink-Gremmels, Johanna

2010-02-01

Plant secondary metabolites (PSMs) are non-nutritional components that occur in numerous feed materials and are able to exert toxic effects in animals. The current article aims to summarize innate defense strategies developed by different animal species to avoid excessive exposure to PSMs. These mechanisms include pre-systemic degradation of PSMs by rumen microbiota, the intestinal barrier including efflux transporters of monogastric species, as well as pre-hepatic and intra-hepatic biotransformation processes. These physiological barriers determine systemic exposure and ultimately the dose-dependent adverse effects in the target animal species. Considering the large number of potentially toxic PSMs, which makes an evaluation of all individual PSMs virtually impossible, such a mechanism-oriented approach could improve the predictability of adverse effects and support the interpretation of clinical field observations. Moreover, mechanistic data related to tissue disposition and excretion pathways of PSMs for example into milk, could substantially support the assessment of the risks for consumers of foods derived from PSM-exposed animals.

Estimation of reliability of predictions and model applicability domain evaluation in the analysis of acute toxicity (LD50).

PubMed

Sazonovas, A; Japertas, P; Didziapetris, R

2010-01-01

This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.

Estimation of Wildlife Hazard Levels Using Interspecies Correlation Models and Standard Laboratory Rodent Toxicity Data

EPA Science Inventory

Toxicity data from laboratory rodents are widely available and frequently used in human health assessments as an animal model. We explore the possibility of using single rodent acute toxicity values to predict chemical toxicity to a diversity of wildlife species and to estimate ...

Refinement, Reduction, and Replacement of Animal Toxicity Tests by Computational Methods.

PubMed

Ford, Kevin A

2016-12-01

Widespread public and scientific interest in promoting the care and well-being of animals used for toxicity testing has given rise to improvements in animal welfare practices and views over time, as well as laws and regulations that support means to reduce, refine, and replace animal use (known as the 3Rs) in certain toxicity studies. One way these regulations continue to achieve their aim is by promoting the research, development, and application of alternative testing approaches to characterize potential toxicities either without animals or with minimal use. An important example of an alternative approach is the use of computational toxicology models. Along with the potential capacity to reduce or replace the use of animals for the assessment of particular toxicological endpoints, computational models offer several advantages compared to in vitro and in vivo approaches, including cost-effectiveness, rapid availability of results, and the ability to fully standardize procedures. Pharmaceutical research incorporating the use of computational models has increased steadily over the past 15 years, likely driven by the motivation of companies to screen out toxic compounds in the early stages of development. Models are currently available to aid in the prediction of several important toxicological endpoints, including mutagenicity, carcinogenicity, eye irritation, hepatotoxicity, and skin sensitization, albeit with varying degrees of success. This review serves to introduce the concepts of computational toxicology and evaluate their role in the safety assessment of compounds, while also highlighting the application of in silico methods in the support of the goal and vision of the 3Rs. © The Author 2016. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research.All rights reserved. For permissions, please email: journals.permissions@oup.com.

Health effects research in direct coal liquefaction. Studies of H-coal distillates: Phase I. PDU samples - the effects of hydrotreatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Epler, J.L.; Fry, R.J.M.; Larimer, F.W.

1981-11-01

A multi-divisional effort aimed at the integrated assessment of the health and environmental effects of various coal conversion and shale oil technologies is being carried out. The feasibility of using health effects bioassays to predict the potential biohazard of various H-Coal derived test materials is examined in a coupled chemical and biological approach. The primary focus of the research is the use of preliminary chemical characterizations and preparation for bioassay, followed by testing in short-term assays in order to rapidly ascertain the potential biohazard. Mammalian toxicological assays parallel the testing. Raw and hydrotreated product liquids from process development units ofmore » H-Coal and the pilot plant solvent refined coal process were examined for acute toxicity monitored as population growth impairment of Tetrahymena exposed to aqueous extracts and for mutagenic activity monitored as revertants of Salmonella exposed to metabolically activated chemical class fractions. Medium to high severity hydrotreatment appears to be an effective means of reducing biological activity, presumably by reducing the aromaticity and heteroatom content. Five basic mammalian, acute toxicity tests have been conducted with selected H-coal samples and shale oil derivatives. The data show that H-Coal samples are moderately toxic whereas the toxicity of shale oil derived products is slight and comparable to samples obtained from naturally occurring petroleums. No overt skin or eye toxicity was found. The present data reveal that coal-derived distillates generated by the H-coal process are highly carcinogenic to mouse skin. An extreme form of neurotoxicity associated with dermal exposure to one of the lighter, minimally carcinogenic, materials was noted. (DMC)« less

Benzene exposure is associated with epigenetic changes (Review).

PubMed

Fenga, Concettina; Gangemi, Silvia; Costa, Chiara

2016-04-01

Benzene is a volatile aromatic hydrocarbon solvent and is known as one of the predominant air pollutants in the environment. Chronic exposure to benzene is known to cause aplastic anemia and increased risk of acute myelogenous leukemia in humans. Although the mechanisms by which benzene causes toxicity remain to be fully elucidated, it is widely accepted that its metabolism is crucial to its toxicity, with involvement of one or more reactive metabolites. Novel approaches aimed at evaluating different mechanisms by which benzene can impact on human health by altering gene regulation have been developed. Among these novel approaches, epigenetics appears to be promising. The present review article summarizes the most important findings, reported from the literature, on epigenetic modifications correlated to benzene exposure. A computerized search in PubMed was performed in November 2014, using search terms, including 'benzene', 'epigenetic', 'histone modifications', 'DNA methylation' and 'microRNA'. Epidemiological and experimental studies have demonstrated the potential epigenetic effects of benzene exposure. Several of the epigenomic changes observed in response to environmental exposures may be mechanistically associated with susceptibility to diseases. However, further elucidation of the mechanisms by which benzene alters gene expression may improve prediction of the toxic potential of novel compounds introduced into the environment, and allow for more targeted and appropriate disease prevention strategies.

Sediment contamination of residential streams in the metropolitan kansas city area, USA: Part II. whole-sediment toxicity to the amphipod hyalella azteca

USGS Publications Warehouse

Tao, J.; Ingersoll, C.G.; Kemble, N.E.; Dias, J.R.; Murowchick, J.B.; Welker, G.; Huggins, D.

2010-01-01

This is the second part of a study that evaluates the influence of nonpoint sources on the sediment quality of five adjacent streams within the metropolitan Kansas City area, central United States. Physical, chemical, and toxicity data (Hyalella azteca 28-day whole-sediment toxicity test) for 29 samples collected in 2003 were used for this evaluation, and the potential causes for the toxic effects were explored. The sediments exhibited a low to moderate toxicity, with five samples identified as toxic to H. azteca. Metals did not likely cause the toxicity based on low concentrations of metals in the pore water and elevated concentrations of acid volatile sulfide in the sediments. Although individual polycyclic aromatic hydrocarbons (PAHs) frequently exceeded effect-based sediment quality guidelines [probable effect concentrations (PECs)], only four of the samples had a PEC quotient (PEC-Q) for total PAHs over 1.0 and only one of these four samples was identified as toxic. For the mean PEC-Q for organochlorine compounds (chlordane, dieldrin, sum DDEs), 4 of the 12 samples with a mean PEC-Q above 1.0 were toxic and 4 of the 8 samples with a mean PEC-Q above 3.0 were toxic. Additionally, four of eight samples were toxic, with a mean PEC-Q above 1.0 based on metals, PAHs, polychlorinated biphenyls (PCBs), and organochlorine pesticides. The increase in the incidence of toxicity with the increase in the mean PEC-Q based on organochlorine pesticides or based on metals, PAHs, PCBs, and organochlorine pesticides suggests that organochlorine pesticides might have contributed to the observed toxicity and that the use of a mean PEC-Q, rather than PEC-Qs for individual compounds, might be more informative in predicting toxic effects. Our study shows that stream sediments subject to predominant nonpoint sources contamination can be toxic and that many factors, including analysis of a full suite of PAHs and pesticides of both past and present urban applications and the origins of these organic compounds, are important to identify the causes of toxicity. ?? 2010 Springer Science+Business Media, LLC.

NMR-based urine analysis in rats: prediction of proximal tubule kidney toxicity and phospholipidosis.

PubMed

Lienemann, Kai; Plötz, Thomas; Pestel, Sabine

2008-01-01

The aim of safety pharmacology is early detection of compound-induced side-effects. NMR-based urine analysis followed by multivariate data analysis (metabonomics) identifies efficiently differences between toxic and non-toxic compounds; but in most cases multiple administrations of the test compound are necessary. We tested the feasibility of detecting proximal tubule kidney toxicity and phospholipidosis with metabonomics techniques after single compound administration as an early safety pharmacology approach. Rats were treated orally, intravenously, inhalatively or intraperitoneally with different test compounds. Urine was collected at 0-8 h and 8-24 h after compound administration, and (1)H NMR-patterns were recorded from the samples. Variation of post-processing and feature extraction methods led to different views on the data. Support Vector Machines were trained on these different data sets and then aggregated as experts in an Ensemble. Finally, validity was monitored with a cross-validation study using a training, validation, and test data set. Proximal tubule kidney toxicity could be predicted with reasonable total classification accuracy (85%), specificity (88%) and sensitivity (78%). In comparison to alternative histological studies, results were obtained quicker, compound need was reduced, and very importantly fewer animals were needed. In contrast, the induction of phospholipidosis by the test compounds could not be predicted using NMR-based urine analysis or the previously published biomarker PAG. NMR-based urine analysis was shown to effectively predict proximal tubule kidney toxicity after single compound administration in rats. Thus, this experimental design allows early detection of toxicity risks with relatively low amounts of compound in a reasonably short period of time.

Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches.

PubMed

de Morais E Silva, Luana; Alves, Mateus Feitosa; Scotti, Luciana; Lopes, Wilton Silva; Scotti, Marcus Tullius

2018-05-30

Persistent organic products are compounds used for various purposes, such as personal care products, surfactants, colorants, industrial additives, food, pesticides and pharmaceuticals. These substances are constantly introduced into the environment and many of these pollutants are difficult to degrade. Toxic compounds classified as MoA 1 (Mode of Action 1) are low toxicity compounds that comprise nonreactive chemicals. In silico methods such as Quantitative Structure-Activity Relationships (QSARs) have been used to develop important models for prediction in several areas of science, as well as aquatic toxicity studies. The aim of the present study was to build a QSAR model-based set of theoretical Volsurf molecular descriptors using the fish acute toxicity values of compounds defined as MoA 1 to identify the molecular properties related to this mechanism. The selected Partial Least Squares (PLS) results based on the values of cross-validation coefficients of determination (Q cv 2 ) show the following values: Q cv 2 = 0.793, coefficient of determination (R 2 ) = 0.823, explained variance in external prediction (Q ext 2 ) = 0.87. From the selected descriptors, not only the hydrophobicity is related to the toxicity as already mentioned in previously published studies but other physicochemical properties combined contribute to the activity of these compounds. The symmetric distribution of the hydrophobic moieties in the structure of the compounds as well as the shape, as branched chains, are important features that are related to the toxicity. This information from the model can be useful in predicting so as to minimize the toxicity of organic compounds. Copyright © 2018. Published by Elsevier Inc.

Using Web-based Interspecies Correlation Estimation (Web-ICE) models as a tool for acute toxicity prediction

EPA Science Inventory

In order to assess risk of contaminants to taxa with limited or no toxicity data available, Interspecies Correlation Estimation (ICE) models have been developed by the U.S. Environmental Protection Agency to extrapolate contaminant sensitivity predictions based on data from commo...

Development of Algal Interspecies Correlation Estimation Models for Chemical Hazard Assessment

EPA Science Inventory

Web-based Interspecies Correlation Estimation (ICE) is an application developed to predict the acute toxicity of a chemical from 1 species to another taxon. Web-ICE models use the acute toxicity value for a surrogate species to predict effect values for other species, thus potent...

Development and Application of In Vitro Models for Screening Drugs and Environmental Chemicals that Predict Toxicity in Animals and Humans

EPA Pesticide Factsheets

Development and Application of In Vitro Models for Screening Drugs and Environmental Chemicals that Predict Toxicity in Animals and Humans (Presented by James McKim, Ph.D., DABT, Founder and Chief Science Officer, CeeTox) (5/25/2012)

EPA Project Updates: DSSTox and ToxCast Generating New Data and Data Linkages for Use in Predictive Modeling

EPA Science Inventory

EPAs National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than tr...

Consensus Modeling of Oral Rat Acute Toxicity

EPA Science Inventory

An acute toxicity dataset (oral rat LD50) with about 7400 compounds was compiled from the ChemIDplus database. This dataset was divided into a modeling set and a prediction set. The compounds in the prediction set were selected so that they were present in the modeling set used...

Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

Developing predictions of in vivo developmental toxicity of ToxCast chemicals using mouse embryonic stem cells.

EPA Science Inventory

Developing predictions of in vivo developmental toxicity of ToxCast chemicals using mouse embryonic stem cells S. Hunter, M. Rosen, M. Hoopes, H. Nichols, S. Jeffay, K. Chandler1, Integrated Systems Toxicology Division, National Health and Environmental Effects Research Labor...

How adverse outcome pathways can aid the development and use of computational prediction models for regulatory toxicology

EPA Science Inventory

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumu...

Validation, acceptance, and extension of a predictive model of reproductive toxicity using ToxCast data

EPA Science Inventory

The EPA ToxCast research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I tested 309 well-characterized chemicals (mostly pesticides) in over 500 assays of different molecular targets, cellular responses an...

Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening

EPA Science Inventory

The EPA ToxCast research program uses high throughput screening for bioactivity profiling and predicting the toxicity of large numbers of chemicals. ToxCast Phase‐I tested 309 well‐characterized chemicals in over 500 assays for a wide range of molecular targets and cellular respo...

IN SILICO METHODOLOGIES FOR PREDICTIVE EVALUATION OF TOXICITY BASED ON INTEGRATION OF DATABASES

EPA Science Inventory

In silico methodologies for predictive evaluation of toxicity based on integration of databases

Chihae Yang1 and Ann M. Richard2, 1LeadScope, Inc. 1245 Kinnear Rd. Columbus, OH. 43212 2National Health & Environmental Effects Research Lab, U.S. EPA, Research Triangle Park, ...