Extrapolation Of Toxicity Research Articles

Tris(1,3-dichloro-2-propyl) Phosphate Inhibits Early Embryonic Development by Binding to Gsk-3β Protein in Zebrafish

Recently, several studies have reported that exposure to tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) results in abnormal development of zebrafish embryos in blastocyst and gastrula stages, but molecular mechanisms are still not clear. This lacking strongly affects the interspecific extrapolation of embryonic toxicity induced by TDCIPP and hazard evaluation. In this study, zebrafish embryos were exposed to 100, 500 or 1000 μg/L TDCIPP, and 6-bromoindirubin-3′-oxime (BIO, 35.62 μg/L) was used as a positive control. Results demonstrated that treatment with TDCIPP or BIO caused an abnormal stacking of blastomere cells in mid blastula transition (MBT) stage, and subsequently resulted in epiboly delay of zebrafish embryos. TDCIPP and BIO up-regulated the expression of β-catenin protein and increased its accumulation in nuclei of embryonic cells. This accumulation was considered as a driver for early embryonic developmental toxicity of TDCIPP. Furthermore, TDCIPP and BIO partly shared the same modes of action, and both of them could bind to Gsk-3β protein, and then decreased the phosphorylation level of Gsk-3β in TYR·216 site and lastly inhibited the activity of Gsk-3β kinase, which was responsible for the increased concentrations of β-catenin protein in embryonic cells and accumulation in nuclei. Our findings provide new mechanisms for clarifying the early embryonic developmental toxicity of TDCIPP in zebrafish.

Pesticides bioassays using neotropical aquatic species: Trends during the last twenty years and future challenges in Argentina

The presence of pesticides in aquatic ecosystems is one of the most relevant stressors which biota usually face. Laboratory tests using model organisms for pesticides toxicity assessment are employed worldwide. The use of these species has been encouraged in the scientific community due to their advantageous features and their acceptation by regulatory and standardization organizations. However, non-model species as well as those belonging particular ecosystems could contribute in the laboratory-field toxicity extrapolation. In this context, this work aims on exploring the state of the ecotoxicological studies of pesticides in neotropical aquatic species, focusing on bioassays performed in Argentina over the last 20 years as a case of study. Furthermore, we analyzed the possible advantages and disadvantages of these studies, possible differential sensitivities among native and model species, and future challenges to be faced. The analysis of more than 150 publications allowed identify the chemical identity of tested compounds, organisms used for the bioassays, characteristics of the experimental designs, and the toxicity endpoints. Particularly, the studied cases showed that the tested chemicals are related to those most used in the agricultural activity in Argentina, the predilection for particular species in some taxonomic groups (e.g. amphibians), and the wide election of biochemical biomarkers in the studies. Regarding the sensitivity comparison between native and non-native species, the amount of data available indicates that there is not a clear difference beyond some particular cases. However, deeper understanding of toxic effects of pesticides on non-model species could help in a more comprehensive ecological risk assessment in different ecosystems.

Low-dose and repeated exposure to nickel leads to bioaccumulation and cellular and metabolic alterations in quails

Nickel (Ni) is a widespread environmental pollutant commonly released into effluent due to industrial activities, the use of fuels, or wastewater disposal. Many studies confirm the toxic effects of this heavy metal. However, there is a lack of knowledge and data on bioaccumulation patterns in tissues as well as cellular and molecular responses following the exposure of living organisms to Ni. In this study, Japanese quails were exposed to low (10 μg/L) and high (2000 μg/L) Ni concentrations in the form of nickel(II) chloride via drinking water. Sub-chronic exposure lasted 30 days while nominal concentrations represented average Ni content in drinking water (low dose) and average Ni levels in highly polluted aquatic environments (high dose). It was revealed that a high dose of Ni was correlated with increased water intake and decreased body weight. Overall, Ni exposure induced the development of microcytic anemia and alterations in measured blood indices. Moreover, Ni exposure impaired immunological activation as seen through the increased number of the white blood cells, increased heterophile/lymphocyte (H/L) ratio, and pronounced thrombocytosis. Ni elicited changes in the albumin, glucose, cholesterol, and triglyceride serum levels in a concentration-dependent manner. Alterations of plasma protein fractions suggested liver functional impairment while high levels of urea and creatinine indicated potential kidney injury. Granulation of heterophiles and an increase in erythroblasts in the bone marrow showed that the hematopoietic tissue was also impacted by Ni toxicity. On average each quail bioaccumulated 5.87 μg of Ni per gram of tissue. Moreover, the distribution and bioaccumulation of Ni in terms of relative concentration were as follows: feathers > kidneys > heart > liver > pectoral muscles. Assessed bioaccumulation levels and associated cellular and metabolic alterations have revealed new multilayer toxicological data that will help in the extrapolation of Ni toxicity in other vertebrates, including humans.

Acute oral toxicity and risks of four classes of systemic insecticide to the Common Eastern Bumblebee (Bombus impatiens)

The Common Eastern Bumblebee (Bombus impatiens) is native to North America with an expanding range across Eastern Canada and the USA. This species is commercially produced primarily for greenhouse crop pollination and is a common and abundant component of the wild bumblebee fauna in agricultural, suburban and urban landscapes. However, there is a dearth of pesticide toxicity information about North American bumblebees. The present study determined the acute oral lethal toxicity (48-h LD50) of: the butenolide, flupyradifurone (>1.7 μg/bee); the diamide, cyantraniliprole (>0.54 μg/bee); the neonicotinoid, thiamethoxam (0.0012 μg/bee); and the sulfoximine, sulfoxaflor (0.0177 μg/bee). Compared with published honey bee (Apis mellifera) LD50 values, the present study shows that sulfoxaflor and thiamethoxam are 8.3× and 3.3× more acutely toxic to B. impatiens, whereas flupyradifurone is more acutely toxic to A. mellifera. The current rule of thumb for toxicity extrapolation beyond the honey bee as a model species, termed 10× safety factor, may be sufficient for bumblebee acute oral toxicity. A comparison of five risk assessment equations suggested that the Standard Risk Approach (SRA) and Fixed Dose Risk Approach (FDRA) provide more nuanced levels of risk evaluation compared to the Exposure Toxicity Ratio (ETR), Hazard Quotient (HQ), and Risk Quotient (RQ), primarily because the SRA and FDRA take into account real world variability in pollen and nectar pesticide residues and the chances that bees may be exposed to them.

Differences in P-glycoprotein activity in human and rodent blood\u2013brain barrier assessed by mechanistic modelling

Variation in the efficacy and safety of central nervous system drugs between humans and rodents can be explained by physiological differences between species. An important factor could be P-glycoprotein (Pgp) activity in the blood–brain barrier (BBB), as BBB expression of this drug efflux transporter is reportedly lower in humans compared to mouse and rat and subject to an age-dependent increase. This might complicate animal to human extrapolation of brain drug disposition and toxicity, especially in children. In this study, the potential species-specific effect of BBB Pgp activity on brain drug exposure was investigated. An age-dependent brain PBPK model was used to predict cerebrospinal fluid and brain mass concentrations of Pgp substrate drugs. For digoxin, verapamil and quinidine, in vitro kinetic data on their transport by Pgp were derived from literature and used to scale to in vivo parameters. In addition, age-specific digoxin transport was simulated for children with a postnatal age between 25 and 81 days. BBB Pgp activity in the model was optimized using measured CSF data for the Pgp substrates ivermectin, indinavir, vincristine, docetaxel, paclitaxel, olanzapine and citalopram, as no useful in vitro data were available. Inclusion of Pgp activity in the model resulted in optimized predictions of their brain concentration. Total brain-to-plasma AUC values (Kp,brain) in the simulations without Pgp were divided by the Kp,brain values with Pgp. Kp ratios ranged from 1 to 45 for the substrates investigated. Comparison of human with rodent Kp,brain ratios indicated ≥ twofold lower values in human for digoxin, verapamil, indinavir, paclitaxel and citalopram and ≥ twofold higher values for vincristine. In conclusion, BBB Pgp activity appears species-specific. An age-dependent PBPK model-based approach could be useful to extrapolate animal data to human adult and paediatric predictions by taking into account species-specific and developmental BBB Pgp expression.

Comparison of Joint Effect of Acute and Chronic Toxicity for Combined Assessment of Heavy Metals on Photobacterium sp.NAA-MIE.

Predicting the crucial effect of single metal pollutants against the aquatic ecosystem has been highly debatable for decades. However, dealing with complex metal mixtures management in toxicological studies creates a challenge, as heavy metals may evoke greater toxicity on interactions with other constituents rather than individually low acting concentrations. Moreover, the toxicity mechanisms are different between short term and long term exposure of the metal toxicant. In this study, acute and chronic toxicity based on luminescence inhibition assay using newly isolated Photobacterium sp.NAA-MIE as the indicator are presented. Photobacterium sp.NAA-MIE was exposed to the mixture at a predetermined ratio of 1:1. TU (Toxicity Unit) and MTI (Mixture Toxic Index) approach presented the mixture toxicity of Hg2+ + Ag+, Hg2+ + Cu2+, Ag+ + Cu2+, Hg2+ + Ag+ + Cu2+, and Cd2+ + Cu2+ showed antagonistic effect over acute and chronic test. Binary mixture of Cu2+ + Zn2+ was observed to show additive effect at acute test and antagonistic effect at chronic test while mixture of Ni2+ + Zn2+ showing antagonistic effect during acute test and synergistic effect during chronic test. Thus, the strain is suitable and their use as bioassay to predict the risk assessment of heavy metal under acute toxicity without abandoning the advantage of chronic toxicity extrapolation.

The kernel-weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models

The ability of accurate predictions of biological response (biological activity/property/toxicity) of a given chemical makes the quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) models unique among the in silico tools. In addition, experimental data of selected species can also be used as an independent variable along with other structural as well as physicochemical variables to predict the response for different species formulating quantitative activity–activity relationship (QAAR)/quantitative structure–activity–activity relationship (QSAAR) approach. Irrespective of the models' type, the developed model's quality, and reliability need to be checked through multiple classical stringent validation metrics. Among the validation metrics, error-based metrics are more significant as the basic idea of a good predictive model is to improve the predictions' quality by lowering the predicted residuals for new query compounds. Following the concept, we have checked the predictive quality of the QSAR and QSAAR models employing kernel-weighted local polynomial regression (KwLPR) approach over the traditional linear and non-linear regression-based approaches tools such as multiple linear regression (MLR) and k nearest neighbors (kNN). Five datasets which were previously modeled using linear and non-linear regression method were considered to implement the KwPLR approach, followed by comparison of their validation metrics outcomes. For all five cases, the KwLPR based models reported better results over the traditional approaches. The present study's focus is not to develop a better or improved QSAR/QSAAR model over the previous ones, but to demonstrate the advantage, prediction power, and reliability of the KwLPR algorithm and establishing it as a novel, powerful cheminformatic tool. To facilitate the use of the KwLPR algorithm for QSAR/QSPR/QSTR/QSAAR modeling, the authors provide an in-house developed KwLPR.RMD script under the open-source R programming language.

Derivation of algal acute to chronic ratios for use in chemical toxicity extrapolations

Algal toxicity studies are required by regulatory agencies for a variety of purposes including classification and labeling and environmental risk assessment of chemicals. Algae are also frequently the most sensitive taxonomic group tested. Acute to chronic ratios (ACRs) have been challenging to derive for algal species because of the complexities of the underlying experimental data including: a lack of universally agreed upon algal inhibition endpoints; evolution of experimental designs over time and by different standardization authorities; and differing statistical approaches (e.g., regression versus hypothesis-based effect concentrations). Experimental data for developing globally accepted algal ACRs have been limited because of data availability, and in most regulatory frameworks an ACR of 10 is used regardless of species, chemical type or mode of action. Acute and chronic toxicity (inhibition) data on 17 algal species and 442 chemicals were compiled from the EnviroTox database (https://envirotoxdatabase.org/) and a proprietary database of algal toxicity records. Information was probed for growth rate, yield, and final cell density endpoints focusing primarily on studies of 72 and 96 h duration. Comparisons of acute and chronic data based on either single (e.g., growth rate) and multiple (e.g., growth rate, final cell density) endpoints were used to assess acute and chronic relationships. Linear regressions of various model permutations were used to compute ACRs for multiple combinations of taxa, chemicals, and endpoints, and showed that ACRs for algae were consistently around 4 (ranging from 2.43 to 5.62). An ACR of 4 for algal toxicity is proposed as an alternative to a default value of 10, and recommendations for consideration and additional research and development are provided.

A biological characteristic extrapolation of compound toxicity for different developmental stage species with toxicokinetic-toxicodynamic model

Intraspecific difference in toxicity brings uncertainty to ecological risk assessment (ERA) and water quality criteria (WQC) of chemicals. Here, we compared intraspecies sensitivity to toxicants for Mesocyclops leuckarti of which toxicity data was obtained from published literatures, and zebrafish Danio rerio of which toxicity data was done in this study). Due to the internal concentration of chemicals not measured, simplified toxicokinetic-toxicodynamic (TK-TD) models were used, and we investigated whether TK-TD parameters estimated by Bayesian method might represent the differences in sensitivity between life-stages of 2 species. The results demonstrated that the difference in TK-TD parameters (background mortality m0, no effect concentration NEC, the killing rate ks, and the dominant rate kd) could represent the toxicity difference between life-stages of individual species. The TK-TD model could predict toxicity in individual species (Cyprinus carpio L., Enchytraeus crypticus, Folsomia candida, Hyalella Azteca) exposed to different chemical concentrations and successfully extrapolate toxicity between different life stages of Mesocyclops leuckarti and Danio rerio by scaling several TK-TD parameters. The modified TK-TD model on the extrapolation toxicity of chemicals between life stages for species could be useful for the ERA and for deriving and revising WQC for chemicals.

Cytochrome P450: Enzyme regulation and toxicological significance

The pharmacological and toxicological responses of drugs and environmental chemicals are dependent upon metabolism of the compounds. Cytochrome P450 (P450)-dependent monooxygenases are the primary enzyme system responsible for the oxidative metabolism of drugs, carcinogens, food additives, and environmental chemicals. The underlying basis for the broad substrate specificity of P450 is that there are multiple forms of P450. A nomenclature system based on amino acid sequence homology is adopted for the increasing number of P450 hemoproteins. P450 genes are subject to regulation by many physiological and environmental factors. Regulation of P450 enzymes shows marked species and tissue specificity which plays an important role in species and tissue extrapolation of chemical risk assessment and target organ toxicity. P450 isoforms are readily inducible following exposure to foreign compounds of which phenobarbital, 3-methylcholanthrene, and ethanol are the prototypic inducing agents. Many drugs and natural compounds are potent inhibitors of P450 and dependent catalytic activity. Mechanism of P450 regulation also shows multiplicity at the transcriptional, translational, and post-translational stages. Polymorphism and racial difference are important determinants of drug metabolism and susceptibility to diseases in humans. Traditional Chinese medicines have the ability to induce and inhibit multiple forms of P450 monooxygenases. Expression of human P450 in mammalian cell lines provides an alternative system to study the functions of P450s in xenobiotic metabolism and toxicity in humans. P450 may be assoicated with regulation of cellular entry of calcium. Finally, the perspective of future P450 research is discussed.

Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation

Honey bees (Apis mellifera) provide key ecosystem services as pollinators bridging agriculture, the food chain and ecological communities, thereby ensuring food production and security. Ecological risk assessment of single Plant Protection Products (PPPs) requires an understanding of the exposure and toxicity. In silico tools such as QSAR models can play a major role for the prediction of structural, physico-chemical and pharmacokinetic properties of chemicals as well as toxicity of single and multiple chemicals. Here, the first integrative honey bee QSAR model has been developed for PPPs using EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase i) to predict acute contact toxicity (LD50) and ii) to profile the Mode of Action (MoA) of pesticides active substances. Three different classification-based and four regression-based models were developed and tested for their performance, thus identifying two models providing the most reliable predictions based on k-NN algorithm. The two-category QSAR model (toxic/non-toxic; n = 411) was validated using sensitivity (=0.93), specificity (=0.85), balanced accuracy (=0.90), and Matthews correlation coefficient (MCC = 0.78) as statistical parameters. The regression-based model (n = 113) was validated for its reliability and robustness (R2 = 0.74; MAE = 0.52). Current study proposes the MoA profiling for 113 pesticides active substances and the first harmonised MoA classification scheme for acute contact toxicity in honey bees, including LD50s data points from three different databases. The classification allows to further define MoAs and the target site of PPPs active substances, thus enabling regulators and scientists to refine chemical grouping and toxicity extrapolations for single chemicals and component-based mixture risk assessment of multiple chemicals. Relevant future perspectives are briefly addressed to integrate MoA, adverse outcome pathways (AOPs) and toxicokinetic information for the refinement of single-chemical/combined toxicity predictions and risk estimates at different levels of biological organization in the bee health context.

Effective extrapolation models for ecotoxicity of benzene, toluene, ethylbenzene, and xylene (BTEX)

Benzene homologues have significant toxic effects to aquatic organisms. In this study, the acute toxicity data of benzene, toluene, ethylbenzene and xylene (BTEX) were collected and screened, and the toxicity extrapolation model of paired BTEX was established. The results showed that except the correlation between benzene and xylene was not strong due to insufficient data, the linear correlation of the other five paired BTEX was good (p < 0.01), and R2 fitted by the four out of five paired BTEX was greater than 0.85. The cross validation showed that ethylbenzene-xylene model was optimal, and for most species (81.8%), the established five BTEX models had a prediction error of less than 10%. Also, these extrapolation models were validated by experimental results of Pseudorasbora parva. The difference between the predicted and measured values of the acute toxicity of BTEX was less than 1 fold, which indicated that the extrapolation model had high accuracy.

Bayesian evaluation of a physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) to characterize the interspecies uncertainty between mice, rats, monkeys, and humans: Development and performance verification

A challenge in the risk assessment of perfluorooctane sulfonate (PFOS) is the large interspecies differences in its toxicokinetics that results in substantial uncertainty in the dosimetry and toxicity extrapolation from animals to humans. To address this challenge, the objective of this study was to develop an open-source physiologically based pharmacokinetic (PBPK) model accounting for species-specific toxicokinetic parameters of PFOS. Considering available knowledge about the toxicokinetic properties of PFOS, a PBPK model for PFOS in mice, rats, monkeys, and humans after intravenous and oral administrations was created. Available species-specific toxicokinetic data were used for model calibration and optimization, and independent datasets were used for model evaluation. Bayesian statistical analysis using Markov chain Monte Carlo (MCMC) simulation was performed to optimize the model and to characterize the uncertainty and interspecies variability of chemical-specific parameters. The model predictions well correlated with the majority of datasets for all four species, and the model was validated with independent data in rats, monkeys, and humans. The model was applied to predict human equivalent doses (HEDs) based on reported points of departure in selected critical toxicity studies in rats and monkeys following U.S. EPA's guidelines. The lower bounds of the model-derived HEDs were overall lower than the HEDs estimated by U.S. EPA (e.g., 0.2 vs. 1.3 μg/kg/day based on the rat plasma data). This integrated and comparative analysis provides an important step towards improving interspecies extrapolation and quantitative risk assessment of PFOS, and this open-source model provides a foundation for developing models for other perfluoroalkyl substances.

Ecotoxicoproteomics: A decade of progress in our understanding of anthropogenic impact on the environment

Anthropogenic pollutants are found worldwide. Their fate and effects on human and ecosystem health must be appropriately monitored. Today, ecotoxicology is focused on the development of new methods to assess the impact of pollutant toxicity on living organisms and ecosystems. In situ biomonitoring often uses sentinel animals for which, ideally, molecular biomarkers have been defined thanks to which environmental quality can be assessed. In this context, high-throughput proteomics methods offer an attractive approach to study the early molecular responses of organisms to environmental stressors. This approach can be used to identify toxicity pathways, to quantify more precisely novel biomarkers, and to draw the possible adverse outcome pathways. In this review, we discuss the major advances in ecotoxicoproteomics made over the last decade and present the current state of knowledge, emphasizing the technological and conceptual advancements that allowed major breakthroughs in this field, which aims to “make our planet great again”. SignificanceEcotoxicoproteomics is a protein-centric methodology that is useful for ecotoxicology and could have future applications as part of chemical risk assessment and environmental monitoring. Ecotoxicology employing non-model sentinel organisms with highly divergent phylogenetic backgrounds aims to preserve the functioning of ecosystems and the overall range of biological species supporting them. The classical proteomics workflow involves protein identification, functional annotation, and extrapolation of toxicity across species. Thus, it is essential to develop multi-omics approaches in order to unravel molecular information and construct the most suitable databases for protein identification and pathway analysis in non-model species. Current instrumentation and available software allow relevant combined transcriptomic/proteomic studies to be performed for almost any species. This review summarizes these approaches and illustrates how they can be implemented in ecotoxicology for routine biomonitoring.

Morphology and physiology of rat placenta for toxicological evaluation.

The placenta plays a pivotal role in fetal growth, and placental dysfunction and injury are associated with embryo/fetal toxicity. Histological examination of the rat placenta for safety evaluation provides valuable clues to the mechanisms of this toxicity. However, the placenta has specific and complex biological features unlike those of other organs, and placental structure dramatically changes depending on the time during the gestation period. Thus, time-dependent histopathological examination of the rat placenta should be performed based on the understanding of normal developmental changes in morphology and function. The placentas of rats and humans are both anatomically classified as discoid and hemochorial types. However, there are differences between rats and humans in terms of placental histological structure, the fetal-maternal interface, and the function of the yolk sac. Therefore, extrapolation of placental toxicity from rats to humans should be done cautiously in the evaluation of risk factors. This review describes the development, morphology, physiology, and toxicological features of the rat placenta and the differences between the rat and human placenta to enable accurate evaluation of reproductive and developmental toxicity in studies.

Extrapolation of imidacloprid toxicity between soils by exposing Folsomia candida in soil pore water

Soil properties like organic matter (OM) content show great variation, making it hard to predict the fate and effects of a chemical in different soils. We therefore addressed the question: can we remove the complexity of the soil matrix and yet accurately predict soil toxicity from porewater exposures? Folsomia candida was exposed to imidacloprid in natural (LUFA 2.2 [4.02% OM], Grassland [12.6% OM]) and artificial soils (OECD 5 [6.61% OM], OECD 10 [10.8% OM]), in pore water extracted from spiked LUFA 2.2 soil and in water. Toxicity decreased with increasing OM content except for Grassland soil, which had the highest OM content but the lowest clay content, suggesting a role of clay minerals in the binding of imidacloprid. Distribution coefficients for imidacloprid based on toxicity (Toxicity-Kd) were derived by comparing effect concentrations in LUFA 2.2 soil and in water. Using these Toxicity-Kds to recalculate soil LC50s/EC50s to porewater concentrations, the differences in LC50/EC50s almost disappeared. The recalculated porewater LC50s did not differ by more than a factor of 0.55–1.43 from the LC50 obtained upon water exposure. This similarity suggests that the toxicity in the soil is dependent on porewater concentrations and can be obtained from water exposure. The porewater test and the corresponding “pore-water extrapolation concept” developed in this study may be used to predict the toxicity of chemicals in the soil and extrapolate among different soils.

English

An allometric target organ dose model (TOD-Wb) with variable scaling exponent, b = br + bo(bm) - bi, is proposed for the extrapolation of animal toxicity to human. The exponent b comprises four constituent parameters representing the intake mode to entry organ (bi), route of transportation to target organ (br), mass of target organ (bo), and rate of metabolism at target organ (bm). This expression enables the a priori determination of b from known values of bi, br, bo, and bm. From nipradilol that target the respiratory system, the br values determined for intragastric (ig), intraperitoneal (ip), intravenous (iv), and subcutaneous (sc) injections were 0.15, 0.26, 0.03, and 0.61, respectively; from HF mouth breathing data, the br value is 0.07 for pulmonary absorption through inhalation (ih); and from actinomycin D data that target bone marrow through the ip-route, the bo value is 0.53. The model is tested with the parameter values obtained from literature; validating the a priori values determined in this paper with the empirical values measured. For ip-administration of OMPA and parathion, the a priori [3/4(bo) - 1] value and empirical value are -0.475 and -0.48; for nine alkylating agents, the values are -0.60 and -0.61; for ig-administration of NaCN, the [br + 3/4(bo) - 1] and empirical values are -0.1 and -0.092, respectively. The analysis of toxic gas inhalation data in student projects are also summarized herein. Consequently, values of these parameters can also be estimated by fitting known toxicity data to the TOD-Wb model. Key words: Target organ dose model, allometric scaling, extrapolating human toxicity.

English

An allometric target organ dose model (TOD-Wb) with variable scaling exponent, b = br + bo(bm) - bi, is proposed for the extrapolation of animal toxicity to human. The exponent b comprises four constituent parameters representing the intake mode to entry organ (bi), route of transportation to target organ (br), mass of target organ (bo), and rate of metabolism at target organ (bm). This expression enables the a priori determination of b from known values of bi, br, bo, and bm. From nipradilol that target the respiratory system, the br values determined for intragastric (ig), intraperitoneal (ip), intravenous (iv), and subcutaneous (sc) injections were 0.15, 0.26, 0.03, and 0.61, respectively; from HF mouth breathing data, the br value is 0.07 for pulmonary absorption through inhalation (ih); and from actinomycin D data that target bone marrow through the ip-route, the bo value is 0.53. The model is tested with the parameter values obtained from literature; validating the a priori values determined in this paper with the empirical values measured. For ip-administration of OMPA and parathion, the a priori [3/4(bo) - 1] value and empirical value are -0.475 and -0.48; for nine alkylating agents, the values are -0.60 and -0.61; for ig-administration of NaCN, the [br + 3/4(bo) - 1] and empirical values are -0.1 and -0.092, respectively. The analysis of toxic gas inhalation data in student projects are also summarized herein. Consequently, values of these parameters can also be estimated by fitting known toxicity data to the TOD-Wb model. Key words: Target organ dose model, allometric scaling, extrapolating human toxicity.

A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria

The determination of the chronic toxicity is time-consumed and costly, so it’s of great interest to predict the chronic toxicity based on acute data. Current methods include the acute to chronic ratios (ACRs) and the QSTR models, both of which have some usage limitations. In this paper, the acute and chronic mixture toxicity of three types of antibiotics, namely sulfonamides, sulfonamide potentiators and tetracyclines, were determined by a bioluminescence inhibition test. A novel QSTR model was developed for predicting the chronic mixture toxicity using the acute data and docking-based descriptors. This model revealed a complex relationship between the acute and chronic toxicity, i.e. a linear correlation between the acute and chronic lg(−lgEC50)s, rather than the simple EC50s or −lgEC50s. In particular, the interaction energies (Ebind) of the chemicals with luciferase and LitR in the bacterial quorum sensing systems were introduced to represent their acute and chronic actions, respectively, regardless of their defined toxic mechanisms. Therefore, the present QSTR model can apply to the chemicals with distinct toxic mechanisms, as well as those with undefined mechanism. This study provides a novel idea for the acute to chronic toxicity extrapolation, which may benefit the environmental risk assessment on the pollutants.

Editor's Highlight: Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A Web-Based Tool for Addressing the Challenges of Cross-Species Extrapolation of Chemical Toxicity.

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) application was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target while remaining amenable to variable degrees of protein characterization, in the context of available information about the chemical/protein interaction and the molecular target itself. To accommodate this flexibility in the analysis, 3 levels of evaluation were developed. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of orthologs); the second level evaluates sequence similarity within selected functional domains (eg, ligand-binding domain); and the third level of analysis compares individual amino acid residue positions of importance for protein conformation and/or interaction with the chemical upon binding. Each level of the SeqAPASS analysis provides additional evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further evaluation, selection of appropriate species for testing, extrapolation of empirical toxicity data, and/or assessment of the cross-species relevance of adverse outcome pathways. Three case studies are described herein to demonstrate application of the SeqAPASS tool: the first 2 focused on predictions of pollinator susceptibility to molt-accelerating compounds and neonicotinoid insecticides, and the third on evaluation of cross-species susceptibility to strobilurin fungicides. These analyses illustrate challenges in species extrapolation and demonstrate the broad utility of SeqAPASS for risk-based decision making and research.