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Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin-sensitizing potency. The GARDskin Dose–Response assay has previously been described; it was shown that its main readout, cDV0 concentration, is associated with skin-sensitizing potency. The ability to predict potency from cDV0 in the form of NESILs derived from LLNAs or human NOELs was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV0 values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645–0.787 [p < 1 × 10−3]). A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESILs. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNAs and humans, respectively. In conclusion, the results suggest that the GARDskin Dose–Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers. [ABSTRACT FROM AUTHOR]

Regulations of cosmetic ingredients and products have been the most advanced in embracing new approach methodologies (NAMs). Consequently, the cosmetic industry has assumed a forerunner role in the development and implementation of animal-free next-generation risk assessment (NGRA) that incorporates defined approaches (DAs) to assess the skin sensitization potency of ingredients. A Bayesian network DA predicting four potency categories (SkinSens-BN) was constructed against reference Local Lymph Node Assay data for a total of 297 substances, achieving a predictive performance similar to that of other DAs. With the aim of optimally informing risk assessment with a continuous point of departure (PoD), a weighted sum of the SkinSens-BN probabilities for four potency classes (non-, weak, moderate, and strong/extreme sensitizer) was calculated, using fixed weights based on associated LLNA EC3-values. The approach was promising, e.g., the derived PoDs for substances classified as non-sensitizers did not overlap with any others and 77% of PoDs were similar or more conservative than LLNA EC3. In addition, the predictions were assigned a level of confidence based on the probabilities to inform the evaluation of uncertainty in an NGRA context. In conclusion, the PoD derivation approach can substantially contribute to reliable skin sensitization NGRAs. [ABSTRACT FROM AUTHOR]

A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene setbased method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3-1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets. [ABSTRACT FROM AUTHOR]

The N-nitrosamine, N-nitrosodimethylamine (NDMA), is an environmental mutagen and rodent carcinogen. Small levels of NDMA have been identified as an impurity in some commonly used drugs, resulting in several product recalls. In this study, NDMA was evaluated in an OECD TG-488 compliant Muta™Mouse gene mutation assay (28-day oral dosing across seven daily doses of 0.02-4 mg/kg/day) using an integrated design that assessed mutation at the transgenic lac Z locus in various tissues and at the endogenous Pig-a gene-locus, along with micronucleus frequencies in peripheral blood. Liver pathology was determined together with NDMA exposure in blood and liver. The additivity of mutation induction was assessed by including two acute single-dose treatment groups (i.e. 5 and 10 mg/kg dose on Day 1), which represented the same total dose as two of the repeat dose treatment groups. NDMA did not induce statistically significant increases in mean lac Z mutant frequency (MF) in bone marrow, spleen, bladder, or stomach, nor in peripheral blood (Pig-a mutation or micronucleus induction) when tested up to 4 mg/kg/day. There were dose-dependent increases in mean lac Z MF in the liver, lung, and kidney following 28-day repeat dosing or in the liver and kidney after a single dose (10 mg/kg). No observed genotoxic effect levels (NOGEL) were determined for the positive repeat dose–response relationships. Mutagenicity did not exhibit simple additivity in the liver since there was a reduction in MF following NDMA repeat dosing compared with acute dosing for the same total dose. Benchmark dose modelling was used to estimate point of departure doses for NDMA mutagenicity in Muta™Mouse and rank order target organ tissue sensitivity (liver > kidney or lung). The BMD50 value for liver was 0.32 mg/kg/day following repeat dosing (confidence interval 0.21–0.46 mg/kg/day). In addition, liver toxicity was observed at doses of ≥ 1.1 mg/kg/day NDMA and correlated with systemic and target organ exposure. The integration of these results and their implications for risk assessment are discussed. [ABSTRACT FROM AUTHOR]

Fluoride is a naturally occurring substance that is also added to drinking water, dental hygiene products, and food supplements for preventing dental caries. Concerns have been raised about several other potential health risks of fluoride. To conduct a robust synthesis of evidence regarding human health risks due to exposure to fluoride in drinking water, and to develop a point of departure (POD) for setting a health-based value (HBV) for fluoride in drinking water. A systematic review of evidence published since recent reviews of human, animal, and in vitro data was carried out. Bradford Hill considerations were used to weigh the evidence for causality. Several key studies were considered for deriving PODs. The current review identified 89 human studies, 199 animal studies, and 10 major in vitro reviews. The weight of evidence on 39 health endpoints was presented. In addition to dental fluorosis, evidence was considered strong for reduction in IQ scores in children, moderate for thyroid dysfunction, weak for kidney dysfunction, and limited for sex hormone disruptions. The current review identified moderate dental fluorosis and reduction in IQ scores in children as the most relevant endpoints for establishing an HBV for fluoride in drinking water. PODs were derived for these two endpoints, although there is still some uncertainty in the causal weight of evidence for causality for reducing IQ scores in children and considerable uncertainty in the derivation of its POD. Given our evaluation of the overall weight of evidence, moderate dental fluorosis is suggested as the key endpoint until more evidence is accumulated on possible reduction of IQ scores effects. A POD of 1.56 mg fluoride/L for moderate dental fluorosis may be preferred as a starting point for setting an HBV for fluoride in drinking water to protect against moderate and severe dental fluorosis. Although outside the scope of the current review, precautionary concerns for potential neurodevelopmental cognitive effects may warrant special consideration in the derivation of the HBV for fluoride in drinking water. [ABSTRACT FROM AUTHOR]

A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3–1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.

Toxicological assessments of skin sensitizers have progressed towards a higher reliance on non-animal methods. Current technological trends aim to extend the utility of non-animal methods to accurately characterize skin-sensitizing potency. The GARDskin Dose–Response assay has previously been described; it was shown that its main readout, cDV0 concentration, is associated with skin-sensitizing potency. The ability to predict potency from cDV0 in the form of NESILs derived from LLNAs or human NOELs was evaluated. The assessment of a dataset of 30 chemicals showed that the cDV0 values still correlated strongly and significantly with both LLNA EC3 and human NOEL values (ρ = 0.645–0.787 [p < 1 × 10−3]). A composite potency value that combined LLNA and human potency data was defined, which aided the performance of the proposed model for the prediction of NESILs. The potency model accurately predicted sensitizing potency, with cross-validation errors of 2.75 and 3.22 fold changes compared with NESILs from LLNAs and humans, respectively. In conclusion, the results suggest that the GARDskin Dose–Response assay may be used to derive an accurate quantitative continuous potency estimate of skin sensitizers.

Regulations of cosmetic ingredients and products have been the most advanced in embracing new approach methodologies (NAMs). Consequently, the cosmetic industry has assumed a forerunner role in the development and implementation of animal-free next-generation risk assessment (NGRA) that incorporates defined approaches (DAs) to assess the skin sensitization potency of ingredients. A Bayesian network DA predicting four potency categories (SkinSens-BN) was constructed against reference Local Lymph Node Assay data for a total of 297 substances, achieving a predictive performance similar to that of other DAs. With the aim of optimally informing risk assessment with a continuous point of departure (PoD), a weighted sum of the SkinSens-BN probabilities for four potency classes (non-, weak, moderate, and strong/extreme sensitizer) was calculated, using fixed weights based on associated LLNA EC3-values. The approach was promising, e.g., the derived PoDs for substances classified as non-sensitizers did not overlap with any others and 77% of PoDs were similar or more conservative than LLNA EC3. In addition, the predictions were assigned a level of confidence based on the probabilities to inform the evaluation of uncertainty in an NGRA context. In conclusion, the PoD derivation approach can substantially contribute to reliable skin sensitization NGRAs.

Studies on the comparison of developmental (neuro) toxicity of parabens are currently limited, and unharmonized concentrations between phenotypic observations and transcriptome analysis hamper the understanding of their differential molecular mechanisms. Thus, developmental toxicity testing was conducted herein using the commonly used methyl- (MtP), ethyl- (EtP), and propyl-parabens (PrP) in zebrafish embryos. With a benchmark dose of 5%, embryonic-mortality-based point-of-departure (M-POD) values of the three parabens were determined, and changes in locomotor behavior were evaluated at concentrations of 0, M-POD/50, M-POD/10, and M-POD, where transcriptome analysis was conducted to explore the underlying neurotoxicity mechanism. Higher long-chained parabens were more toxic than short-chained parabens, as determined by the M-POD values of 154.1, 72.6, and 24.2 µM for MtP, EtP, and PrP, respectively. Meanwhile, exposure to EtP resulted in hyperactivity, whereas no behavioral effect was observed with MtP and PrP. Transcriptome analysis revealed that abnormal behaviors in the EtP-exposed group were associated with distinctly enriched pathways in signaling, transport, calcium ion binding, and metal binding. In contrast, exposure to MtP and PrP mainly disrupted membranes and transmembranes, which are closely linked to abnormal embryonic development rather than neurobehavioral changes. According to the changes in the expressions of signature mRNAs, tentative transcriptome-based POD values for each paraben were determined as MtP (2.68 µM), EtP (3.85 µM), and PrP (1.4 µM). This suggests that different molecular perturbations initiated at similar concentrations determined the extent and toxicity outcome differently. Our findings provide insight into better understanding the differential developmental neurotoxicity mechanisms of parabens.

Omics techniques have been increasingly recognized as promising tools for Next Generation Risk Assessment. Targeted metabolomics offer the advantage of providing readily interpretable mechanistic information about perturbed biological pathways. In this study, a high-throughput LC–MS/MS-based broad targeted metabolomics system was applied to study nitrofurantoin metabolic dynamics over time and concentration and to provide a mechanistic-anchored approach for point of departure (PoD) derivation. Upon nitrofurantoin exposure at five concentrations (7.5 µM, 15 µM, 20 µM, 30 µM and 120 µM) and four time points (3, 6, 24 and 48 h), the intracellular metabolome of HepG2 cells was evaluated. In total, 256 uniquely identified metabolites were measured, annotated, and allocated in 13 different metabolite classes. Principal component analysis (PCA) and univariate statistical analysis showed clear metabolome-based time and concentration effects. Mechanistic information evidenced the differential activation of cellular pathways indicative of early adaptive and hepatotoxic response. At low concentrations, effects were seen mainly in the energy and lipid metabolism, in the mid concentration range, the activation of the antioxidant cellular response was evidenced by increased levels of glutathione (GSH) and metabolites from the de novo GSH synthesis pathway. At the highest concentrations, the depletion of GSH, together with alternations reflective of mitochondrial impairments, were indicative of a hepatotoxic response. Finally, a metabolomics-based PoD was derived by multivariate PCA using the whole set of measured metabolites. This approach allows using the entire dataset and derive PoD that can be mechanistically anchored to established key events. Our results show the suitability of high throughput targeted metabolomics to investigate mechanisms of hepatoxicity and derive point of departures that can be linked to existing adverse outcome pathways and contribute to the development of new ones. [ABSTRACT FROM AUTHOR]

Genotoxicity data are mainly interpreted in a qualitative way, which typically results in a binary classification of chemical entities. For more than a decade, there has been a discussion about the need for a paradigm shift in this regard. Here, we review current opportunities, challenges and perspectives for a more quantitative approach to genotoxicity assessment. Currently discussed opportunities mainly include the determination of a reference point (e.g., a benchmark dose) from genetic toxicity dose–response data, followed by calculation of a margin of exposure (MOE) or derivation of a health-based guidance value (HBGV). In addition to new opportunities, major challenges emerge with the quantitative interpretation of genotoxicity data. These are mainly rooted in the limited capability of standard in vivo genotoxicity testing methods to detect different types of genetic damage in multiple target tissues and the unknown quantitative relationships between measurable genotoxic effects and the probability of experiencing an adverse health outcome. In addition, with respect to DNA-reactive mutagens, the question arises whether the widely accepted assumption of a non-threshold dose–response relationship is at all compatible with the derivation of a HBGV. Therefore, at present, any quantitative genotoxicity assessment approach remains to be evaluated case-by-case. The quantitative interpretation of in vivo genotoxicity data for prioritization purposes, e.g., in connection with the MOE approach, could be seen as a promising opportunity for routine application. However, additional research is needed to assess whether it is possible to define a genotoxicity-derived MOE that can be considered indicative of a low level of concern. To further advance quantitative genotoxicity assessment, priority should be given to the development of new experimental methods to provide a deeper mechanistic understanding and a more comprehensive basis for the analysis of dose–response relationships. [ABSTRACT FROM AUTHOR]

Use of molecular data in human and ecological health risk assessments of industrial chemicals and agrochemicals has been anticipated by the scientific community for many years; however, these data are rarely used for risk assessment. Here, a logic framework is proposed to explore the feasibility and future development of transcriptomic methods to refine and replace the current apical endpoint-based regulatory toxicity testing paradigm. Four foundational principles are outlined and discussed that would need to be accepted by stakeholders prior to this transformative vision being realized. Well-supported by current knowledge, the first principle is that transcriptomics is a reliable tool for detecting alterations in gene expression that result from endogenous or exogenous influences on the test organism. The second principle states that alterations in gene expression are indicators of adverse or adaptive biological responses to stressors in an organism. Principle 3 is that transcriptomics can be employed to establish a benchmark dose-based point of departure (POD) from short-term, in vivo studies at a dose level below which a concerted molecular change (CMC) is not expected. Finally, Principle 4 states that the use of a transcriptomic POD (set at the CMC dose level) will support a human health-protective risk assessment. If all four principles are substantiated, this vision is expected to transform aspects of the industrial chemical and agrochemical risk assessment process that are focused on establishing safe exposure levels for mammals across numerous toxicological contexts resulting in a significant reduction in animal use while providing equal or greater protection of human health. Importantly, these principles and approaches are also generally applicable for ecological safety assessment. [ABSTRACT FROM AUTHOR]

Continuous potency assessment is crucial for conducting quantitative risk assessment (QRA) of sensitizers. Quantitative regression models, based on in vitro methods, have been developed to calculate points of departure for use in skin sensitization QRA. These models calculate a point of departure as a predicted value for Local Lymph Node Assay (LLNA) EC3 or potency value (PV), integrating data from the kinetic Direct Peptide Reactivity Assay (kDPRA), KeratinoSens (KS) assay, and human Cell Line Activation Test (h-CLAT). The goal of this study was to determine how in vitro predicted EC3s and PVs compare to published reference data. In vitro data were combined in point of departure regression models to predict EC3s and PVs. These points of departure were then grouped into sensitization potency categories, such as extreme, strong, moderate, weak, very weak, or non-sensitizer, as previously described. Trends in potency distribution and high concordance between predicted EC3 and PV categories and published potency categories were observed. Furthermore, the median absolute fold-misprediction ranged between 1.8 and 2.5 for models predicting EC3 and between 1.7 and 3.4 for those predicting PVs. These regression models are a promising animal alternative for determining sensitization quantitative potency for fragrance ingredients, thereby facilitating QRA. • Quantitative potency was predicted in regression models based on OECD in vitro assays. • Fragrance ingredient points of departure were predicted as EC3 and potency values. • Predicted EC3s and potency values were compared to published reference data. • There was a high concordance between predicted and published data. • These models are promising animal-free alternatives in quantitative risk assessment. [ABSTRACT FROM AUTHOR]

An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic C max levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the C max estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios. [ABSTRACT FROM AUTHOR]

Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280–286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration–response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment. [ABSTRACT FROM AUTHOR]

This paper uses a trinocular approach – i.e. from below, from above and from roundabout – to describe Theme as point of departure (POD) in English and Spanish casual conversation (thus avoiding the more controversial 'what-the-clause-is-about' aspect of Theme). This research is part of a long-term contrastive study which includes the description of POD in academic writing and a crosslinguistic comparison of POD in academic writing and casual conversation. Among the main findings in this paper, the following stand out: (a) the identification of a conversational texture characterised by the interplay of textual and interpersonal strands of meaning; and (b) different POD arrangements of English and Spanish clauses in casual conversation, motivated by different ways of enacting communicative exchange. [ABSTRACT FROM AUTHOR]

Traditional developmental toxicity testing practice examines fetal apical endpoints to identify a point of departure (POD) for risk assessment. A potential new testing paradigm involves deriving a POD from a comprehensive analysis of molecular‐level change. Here, the rat ketoconazole endocrine‐mediated developmental toxicity model was used to test the hypothesis that maternal epigenomic (miRNA) and transcriptomic (mRNA) PODs are similar to fetal apical endpoint PODs. Sprague–Dawley rats were exposed from gestation day (GD) 6–21 to 0, 0.063, 0.2, 0.63, 2, 6.3, 20, or 40 mg/kg/day ketoconazole. Dam systemic, liver, and placenta PODs, along with GD 21 fetal resorption, body weight, and skeletal apical PODs were derived using BMDS software. GD 21 dam liver and placenta miRNA and mRNA PODs were obtained using three methods: a novel individual molecule POD accumulation method, a first mode method, and a gene set method. Dam apical POD values ranged from 2.0 to 38.6 mg/kg/day; the lowest value was for placenta histopathology. Fetal apical POD values were 10.9–20.3 mg/kg/day; the lowest value was for fetal resorption. Dam liver miRNA and mRNA POD values were 0.34–0.69 mg/kg/day, and placenta miRNA and mRNA POD values were 2.53–6.83 mg/kg/day. Epigenomic and transcriptomic POD values were similar across liver and placenta. Deriving a molecular POD from dam liver or placenta was protective of a fetal apical POD. These data support the conclusion that a molecular POD can be used to estimate, or be protective of, a developmental toxicity apical POD. [ABSTRACT FROM AUTHOR]

Two prototypical genotoxicants, benzo[ a ]pyrene (B[ a ]P) and colchicine (COL), were selected as model compounds to deduce their quantitative genotoxic dose–response relationship at low doses in a multi-endpoint genotoxicity assessment platform. Male Sprague-Dawley rats were treated with B[ a ]P (2.5–80 mg/kg bw/day) and COL (0.125–2 mg/kg bw/day) daily for 28 days. The parameters included were as follows: comet assay in the peripheral blood and liver, Pig-a gene mutation assay in the peripheral blood, and micronucleus test in the peripheral blood and bone marrow. A significant increase was observed in Pig-a mutant frequency in peripheral blood for B[ a ]P (started at 40 mg/kg bw/day on Day 14, started at 20 mg/kg bw/day on Day 28), whereas no statistical difference for COL was observed. Micronucleus frequency in reticulocytes of the peripheral blood and bone marrow increased significantly for B[ a ]P (80 mg/kg bw/day on Day 4, started at 20 mg/kg bw/day on Days 14 and 28 in the blood; started at 20 mg/kg bw/day on Day 28 in the bone marrow) and COL (started at 2 mg/kg bw/day on Day 14, 1 mg/kg bw/day on Day 28 in the blood; started at 1 mg/kg bw/day on Day 28 in the bone marrow). No statistical variation was found in indexes of comet assay at all time points for B[ a ]P and COL in the peripheral blood and liver. The dose–response relationships of Pig-a and micronucleus test data were analyzed for possible point of departures using three quantitative approaches, i.e. the benchmark dose, breakpoint dose, and no observed genotoxic effect level. The practical thresholds of the genotoxicity of B[ a ]P and COL estimated in this study were 0.122 and 0.0431 mg/kg bw/day, respectively, and our results also provided distinct genotoxic mode of action of the two chemicals. [ABSTRACT FROM AUTHOR]

This paper offers a detailed study of Theme as point of departure in English and Spanish academic texts. A corpus of around 45,000 words is examined from different perspectives to compare the realizations, functions and interplays of the point of departure in these two languages. Examples reveal crosslinguistic contrasts in terms of (a) the preferred realizations of thematic elements, (b) the strategies to maintain participant identity and present new participants and (c) the resources used to construe texture. We will see that whereas English favours thematic non-pronominal noun groups, Spanish combines these with other realizations. Additionally, the different syntactic characteristics of each language have a reflection on different ways of signalling semantic continuity and on textual development in general. The findings presented in this paper should make a significant contribution to the existing literature on Theme, as well as on academic writing and contrastive typological research. [ABSTRACT FROM AUTHOR]

Using in vitro data to estimate point of departure (POD) values is an essential component of new approach methodologies (NAMs)-based chemical risk assessments. In this case study, we evaluated a NAM for hepatotoxicity based on rat primary hepatocytes, high-content imaging (HCI), and toxicokinetic modeling. First, we treated rat primary hepatocytes with 10 concentrations (0.2–100 µM) of 51 chemicals that produced hepatotoxicity in repeat-dose subchronic and chronic exposures. Second, we used HCI to measure endoplasmic reticulum stress, mitochondrial function, lysosomal mass, steatosis, apoptosis, DNA texture, nuclear size, and cell number at 24, 48, and 72 h and calculated concentrations at 50% maximal activity (AC50). Third, we estimated administered equivalent doses (AEDs) from AC50 values using toxicokinetic modeling. AEDs using physiologically based toxicokinetic models were 4.1-fold (SD 6.3) and 8.1-fold (SD 15.5) lower than subchronic and chronic lowest observed adverse effect levels (LOAELs), respectively. In contrast, AEDs from ToxCast and Tox21 assays were 89.8-fold (SD 149.5) and 168-fold (SD 323.7) lower than subchronic and chronic LOAELs. Individual HCI endpoints also estimated AEDs for specific hepatic lesions that were lower than in vivo PODs. Lastly, AEDs were similar for different in vitro exposure durations, but steady-state toxicokinetic models produced 7.6-fold lower estimates than dynamic physiologically based ones. Our findings suggest that NAMs from diverse cell types provide conservative estimates of PODs. In contrast, NAMs based on the same species and cell type as the adverse outcome may produce estimates closer to the traditional in vivo PODs. [ABSTRACT FROM AUTHOR]

Benchmark dose (BMD) modeling is used to determine the dose of a stressor at which a predefined increase in any biological effect above background occurs (e.g. 10% increase from control values). BMD analytical tools have the capacity to model transcriptional dose-response data to derive BMDs for genes, pathways and gene ontologies. We recently demonstrated the value of this approach to support various areas of radiation research using predominately 'in-house' generated datasets. As a continuation of this work, transcriptomic studies of relevance to ionizing radiation were retrieved through the Gene Expression Omnibus (GEO). The datasets were compiled and filtered, then analyzed using BMDExpress. The objective was to determine the reproducibility of BMD values in relation to pathways and genes across different exposure scenarios and compare to those derived using cytogenetic endpoints. A number of graphic visualization approaches were used to determine if BMD outputs could be correlated to parameters such as dose-rate, radiation quality and cell type. Curated studies were diverse and derived from experiments with varied design and intent. Despite this, common genes and pathways were identified with low and high dose thresholds. The higher BMD values were associated with immune response and cell death, while transcripts with lower BMD values were generally related to the classic DNA damage response/repair processes, centered on TP53 signaling. Analysis of datasets with relatively similar dose-ranges under comparable experimental conditions showed a bi-modal distribution with a high degree of consistency in BMD values across shared genes and pathways, particularly for those below the 25th percentile of total distribution by dose. The median BMD values were noted to be approximately 0.5 Gy for genes/pathways that comprised mode 1. Furthermore, transcriptional BMD values derived from a subset of genes using in vivo and in vitro datasets were in accord to those using cytogenetic endpoints. Overall, the results from this work highlight the value of the BMD methodology to derive meaningful outputs that are consistent across different models, provided the studies are conducted using a similar dose-range. [ABSTRACT FROM AUTHOR]

Since the proliferation of scholarly works examining Ephesians 5 through the lens of modern gender debates, the preferred segmentation of the text in many articles, commentaries, Bible translations, and Greek editions of the New Testament has shifted. Verse 21, "submitting to one another out of reverence for Christ," is now commonly grouped with verses 22-24 instead of with verses 18-20. Scholars argue that verse 21, which focuses on human-to-human relationships, marks a sharp topical break from verses 18-20, which deal with humanto- divine relationships, but verse 21 fits thematically with verses 22-24. By contrast, we argue that linguistic considerations make it more natural to keep verse 21 with verses 18-20 and start a new subsection in verse 22. Our approach focuses on discourse markers that indicate coherence and discontinuity in the Greek text, most notably Levinsohn's (2000) concept of a point of departure as the primary marker of discontinuity and Baugh's (2015) notion of the distinction between a grammatical and a periodic sentence in Greek discourse. Whereas modern readers tend to dichotomize vertical and horizontal relationships, the author of Ephesians structured the text to position both giving thanks to God and submitting to one another as parallel results of being filled with the Spirit. We do violence to his train of thought when we impose modern categorizations of the world and contemporary gender concerns upon a first-century text. [ABSTRACT FROM AUTHOR]

Identifying a toxicity point of departure (POD) is a required step in human health risk characterization of crop protection molecules, and this POD has historically been derived from apical endpoints across a battery of animal-based toxicology studies. Using rat transcriptome and apical data for 79 molecules obtained from Open TG-GATES (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) (632 datasets), the hypothesis was tested that a short-term exposure, transcriptome-based liver biological effect POD (BEPOD) could estimate a longer-term exposure "systemic" apical endpoint POD. Apical endpoints considered were body weight, clinical observation, kidney weight and histopathology and liver weight and histopathology. A BMDExpress algorithm using Gene Ontology Biological Process gene sets was optimized to derive a liver BEPOD most predictive of a systemic apical POD. Liver BEPODs were stable from 3 h to 29 days of exposure; the median fold difference of the 29-day BEPOD to BEPODs from earlier time points was approximately 1 (range: 0.7–1.1). Strong positive correlation (Pearson R  = 0.86) and predictive accuracy (root mean square difference = 0.41) were observed between a concurrent (29 days) liver BEPOD and the systemic apical POD. Similar Pearson R and root mean square difference values were observed for comparisons between a 29-day systemic apical POD and liver BEPODs derived from 3 h to 15 days of exposure. These data across 79 molecules suggest that a longer-term exposure study apical POD from liver and non-liver compartments can be estimated using a liver BEPOD derived from an acute or subacute exposure study. [ABSTRACT FROM AUTHOR]

Mutations induced in somatic cells and germ cells are responsible for a variety of human diseases, and mutation per se has been considered an adverse health concern since the early part of the 20th Century. Although in vitro and in vivo somatic cell mutation data are most commonly used by regulatory agencies for hazard identification, that is, determining whether or not a substance is a potential mutagen and carcinogen, quantitative mutagenicity dose–response data are being used increasingly for risk assessments. Efforts are currently underway to both improve the measurement of mutations and to refine the computational methods used for evaluating mutation data. We recommend continuing the development of these approaches with the objective of establishing consensus regarding the value of including the quantitative analysis of mutation per se as a required endpoint for comprehensive assessments of toxicological risk. Environ. Mol. Mutagen. 61:34–41, 2020. © 2019 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening. [ABSTRACT FROM AUTHOR]

The purpose of this study was to update the existing Cancer Potency Database (CPDB) in order to support the development of a dataset of compounds, with associated points of departure (PoDs), to enable a review and update of currently applied values for the Threshold of Toxicological Concern (TTC) for cancer endpoints. This update of the current CPDB, last reviewed in 2012, includes the addition of new data (44 compounds and 158 studies leading to additional 359 dose-response curves). Strict inclusion criteria were established and applied to select compounds and studies with relevant cancer potency data. PoDs were calculated from dose-response modeling, including the benchmark dose (BMD) and the lower 90% confidence limits (BMDL) at a specified benchmark response (BMR) of 10%. The updated full CPDB database resulted in a total of 421 chemicals which had dose-response data that could be used to calculate PoDs. This candidate dataset for cancer TTC is provided in a transparent and adaptable format for further analysis of TTC to derive cancer potency thresholds. • The Cancer Potency Database (CPDB) has been curated and updated. • A dataset to support cancer threshold of toxicological concern is proposed. • Points of departure are calculated i.e., BMDL10. • Transparency, robustness and adaptability of the TTC dataset is ensured. [ABSTRACT FROM AUTHOR]

Studies on the comparison of developmental (neuro) toxicity of parabens are currently limited, and unharmonized concentrations between phenotypic observations and transcriptome analysis hamper the understanding of their differential molecular mechanisms. Thus, developmental toxicity testing was conducted herein using the commonly used methyl- (MtP), ethyl- (EtP), and propyl-parabens (PrP) in zebrafish embryos. With a benchmark dose of 5%, embryonic-mortality-based point-of-departure (M-POD) values of the three parabens were determined, and changes in locomotor behavior were evaluated at concentrations of 0, M-POD/50, M-POD/10, and M-POD, where transcriptome analysis was conducted to explore the underlying neurotoxicity mechanism. Higher long-chained parabens were more toxic than short-chained parabens, as determined by the M-POD values of 154.1, 72.6, and 24.2 µM for MtP, EtP, and PrP, respectively. Meanwhile, exposure to EtP resulted in hyperactivity, whereas no behavioral effect was observed with MtP and PrP. Transcriptome analysis revealed that abnormal behaviors in the EtP-exposed group were associated with distinctly enriched pathways in signaling, transport, calcium ion binding, and metal binding. In contrast, exposure to MtP and PrP mainly disrupted membranes and transmembranes, which are closely linked to abnormal embryonic development rather than neurobehavioral changes. According to the changes in the expressions of signature mRNAs, tentative transcriptome-based POD values for each paraben were determined as MtP (2.68 µM), EtP (3.85 µM), and PrP (1.4 µM). This suggests that different molecular perturbations initiated at similar concentrations determined the extent and toxicity outcome differently. Our findings provide insight into better understanding the differential developmental neurotoxicity mechanisms of parabens. [Display omitted] • Longer-chained propylparaben had greater acutely embryonic toxicity than methyl- and ethyl-parabens. • Hyperactivity was induced only by ethyl-paraben. • Hyperactivity was associated with disrupted pathways in signaling, transport, calcium ion binding, and metal binding. • RNA-seq analysis revealed that the three parabens had different molecular mechanisms. • Transcriptome-based-POD values were similar among the three parabens [ABSTRACT FROM AUTHOR]

It is still a major challenge to protect humans at workplaces and in the environment. To cope with this task, it is a prerequisite to obtain detailed information on the extent of chemical perturbations of biological pathways, in particular, adaptive vs. adverse effects and the dose-response relationships. This knowledge serves as the basis for the classification of non-carcinogens and carcinogens and for further distinguishing carcinogens in genotoxic (DNA damaging) or non-genotoxic compounds. Basing on quantitative dose-response relationships, points of departures can be derived for chemical risk assessment. In recent years, new methods have shown their capability to support the established rodent models of carcinogenicity testing. In vitro high throughput screening assays assess more comprehensively cell response. In addition, omics technologies were applied to study the mode of action of chemicals whereby the term "toxicogenomics" comprises various technologies such as transcriptomics, epigenomics, or metabolomics. This review aims to summarize the current state of toxicogenomic approaches in risk science and to compare them with established ones. For example, measurement of global transcriptional changes generates meaningful information for toxicological risk assessment such as accurate classification of genotoxic/non-genotoxic carcinogens. Alteration in mRNA expression offers previously unknown insights in the mode of action and enables the definition of key events. Based on these, benchmark doses can be calculated for the transition from an adaptive to an adverse state. In short, this review assesses the potential and challenges of transcriptomics and addresses the impact of other omics technologies on risk assessment in terms of hazard identification and dose-response assessment. [ABSTRACT FROM AUTHOR]

The study presents an integrated, rigorous statistical approach to define the likelihood of a threshold and point of departure (POD) based on dose–response data using nested family of bent‐hyperbola models. The family includes four models: the full bent‐hyperbola model, which allows for transition between two linear regiments with various levels of smoothness; a bent‐hyperbola model reduced to a spline model, where the transition is fixed to a knot; a bent‐hyperbola model with a restricted negative asymptote slope of zero, named hockey‐stick with arc (HS‐Arc); and spline model reduced further to a hockey‐stick type model (HS), where the first linear segment has a slope of zero. A likelihood‐ratio test is used to discriminate between the models and determine if the more flexible versions of the model provide better or significantly better fit than a hockey‐stick type model. The full bent‐hyperbola model can accommodate both threshold and nonthreshold behavior, can take on concave up and concave down shapes with various levels of curvature, can approximate the biochemically relevant Michaelis–Menten model, and even be reduced to a straight line. Therefore, with the use of this model, the presence or absence of a threshold may even become irrelevant and the best fit of the full bent‐hyperbola model be used to characterize the dose–response behavior and risk levels, with no need for mode of action (MOA) information. Point of departure (POD), characterized by exposure level at which some predetermined response is reached, can be defined using the full model or one of the better fitting reduced models. [ABSTRACT FROM AUTHOR]

Soman, a warfare nerve agent, poses a significant threat by inducing severe brain damage that often results in death. Nonetheless, our understanding of the biological changes underlying persistent neurocognitive dysfunction caused by low dosage of soman remains limited. This study used mice to examine the effects of different doses of soman over time. Phosphoproteomic analysis of the mouse brain is the first time to be used to detect toxic effects of soman at such low or ultra-low doses, which were undetectable based on measuring the activity of acetylcholinesterase at the whole-animal level. We also found that phosphoproteome alterations could accurately track the soman dose, irrespective of the sampling time. Moreover, phosphoproteome revealed a rapid and adaptive cellular response to soman exposure, with the points of departure 8–38 times lower than that of acetylcholinesterase activity. Impaired long-term potentiation was identified in phosphoproteomic studies, which was further validated by targeted quantitative proteomics, immunohistochemistry, and immunofluorescence analyses, with significantly increased levels of phosphorylation of protein phosphatase 1 in the hippocampus following soman exposure. This increase in phosphorylation inhibits long-term potentiation, ultimately leading to long-term memory dysfunction in mice. [Display omitted] • The biological effects of the exposure of low-dose soman sensitively revealed by phosphoproteomics. • Phosphoproteomic alterations accurately track the soman dose, irrespective of the sampling time. • Impaired long-term potentiation was found in the hippocampus after the low dose exposure of soman. [ABSTRACT FROM AUTHOR]

The molecular mechanism of perfluorobutanesulfonic acid (PFBS), an alternative to legacy perfluorooctanesulfonic acid (PFOS), is not fully understood yet. Therefore, we conducted a developmental toxicity evaluation on zebrafish embryos exposed to PFBS and PFOS and assessed neurobehavioral changes at concentrations below each point of departure (POD) determined by embryonic mortality. Using transcriptomics, proteomics, and metabolomics, biomolecular perturbations in response to PFBS were profiled and then integrated for comparison with those for PFOS. Although PFBS (7525.47 μM POD) was approximately 700 times less toxic than PFOS (11.42 μM POD), altered neurobehavior patterns and affected kinds of endogenous neurochemicals were similar between PFBS and PFOS at the corresponding POD-based concentrations. Multi-omics analysis revealed that the PFBS neurotoxicity mechanism was associated with oxidative stress, lipid metabolism, and glycolysis/glucogenesis. The commonalities in developmental neurotoxicity-related mechanisms between PFBS and PFOS interconnected by knowledge-based integration of multi-omics included the calcium signaling pathway, lipid homeostasis, and primary bile acid biosynthesis. Despite being less toxic than PFOS, PFBS exhibited similar dysregulated molecular mechanisms, suggesting that chain length differences do not affect the intrinsic toxicity mechanism. Overall, carefully managing potential toxicity of PFBS can secure its status as an alternative to PFOS. [Display omitted] • PFBS showed 700 times less developmental toxicity than PFOS in zebrafish embryos. • PFBS- and PFOS-induced behavioral profiles were extremely similar. • PFBS perturbed the calcium signaling pathway and lipid homeostasis. • Integrative omics revealed similar neurotoxicity mechanisms between PFBS and PFOS. [ABSTRACT FROM AUTHOR]

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

1,4-Dioxane is a widely used synthetic industrial chemical and its contamination of drinking water and food is a potential health concern. It induces liver tumors when administered in the drinking water to rats and mice. However, the mode of action (MOA) of the hepatocarcinogenicity of 1,4-dioxane remains unclear. Importantly, it is unknown if 1,4-dioxane is genotoxic, a key consideration for risk assessment. To determine the in vivo mutagenicity of 1,4-dioxane, gpt delta transgenic F344 rats were administered 1,4-dioxane at various doses in the drinking water for 16 weeks. The overall mutation frequency (MF) and A:T- to -G:C transitions and A:T- to -T:A transversions in the gpt transgene were significantly increased by administration of 5000 ppm 1,4-dioxane. A:T- to -T:A transversions were also significantly increased by administration of 1000 ppm 1,4-dioxane. Furthermore, the DNA repair enzyme MGMT was significantly induced at 5000 ppm 1,4-dioxane, implying that extensive genetic damage exceeded the repair capacity of the cells in the liver and consequently led to liver carcinogenesis. No evidence supporting other MOAs, including induction of oxidative stress, cytotoxicity, or nuclear receptor activation, that could contribute to the carcinogenic effects of 1,4-dioxane were found. These findings demonstrate that 1,4-dioxane is a genotoxic hepatocarcinogen and induces hepatocarcinogenesis through a mutagenic MOA in rats. Because our data indicate that 1,4-dioxane is a genotoxic carcinogen, we estimated the point of departure of the mutagenicity and carcinogenicity of 1,4-dioxane using the no-observed effect-level approach and the Benchmark dose approach to characterize its dose-response relationship at low doses. [ABSTRACT FROM AUTHOR]

Cosmetic regulations prohibit animal testing for the purpose of safety assessment and recent registration, evaluation and authorization of chemicals guidance states that the local lymph node assay (LLNA) in mice shall only be conducted if in vitro data cannot give sufficient information for classification and labeling. However, Quantitative Risk Assessment for fragrance ingredients requires an NESIL (no expected sensitization induction level), a dose not expected to cause induction of skin sensitization in humans. In absence of human data, this is derived from the LLNA and it remains a key challenge for risk assessors to derive this value from nonanimal data. Here we present a workflow using structural information, reactivity data and KeratinoSens results to predict an LLNA result as a point of departure. Specific additional tests (metabolic activation, complementary reactivity tests) are applied in selected cases depending on the chemical domain of a molecule. Finally, in vitro and in vivo data on close analogues are used to estimate uncertainty of the prediction in the specific chemical domain. This approach was applied to three molecules which were subsequently tested in the LLNA and 22 molecules with available and sometimes discordant human and LLNA data. Four additional case studies illustrate how this approach is being applied to recently developed molecules in the absence of animal data. Estimation of uncertainty and how this can be applied to determine a final NESIL for risk assessment is discussed. We conclude that, in the data-rich domain of fragrance ingredients, sensitization risk assessment without animal testing is possible in most cases by this integrated approach. [ABSTRACT FROM AUTHOR]

The development and application of high throughput in vitro assays is an important development for risk assessment in the twenty-first century. However, there are still significant challenges to incorporate in vitro assays into routine toxicity testing practices. In this paper, a robust learning approach was developed to infer the in vivo point of departure (POD) with in vitro assay data from ToxCast and Tox21 projects. Assay data from ToxCast and Tox21 projects were utilized to derive the in vitro PODs for several hundred chemicals. These were combined with in vivo PODs from ToxRefDB regarding the rat and mouse liver to build a high-dimensional robust regression model. This approach separates the chemicals into a majority, well-predicted set; and a minority, outlier set. Salient relationships can then be learned from the data. For both mouse and rat liver PODs, over 93% of chemicals have inferred values from in vitro PODs that are within ± 1 of the in vivo PODs on the log10 scale (the target learning region, or TLR) and R2 of 0.80 (rats) and 0.78 (mice) for these chemicals. This is comparable with extrapolation between related species (mouse and rat), which has 93% chemicals within the TLR and the R2 being 0.78. Chemicals in the outlier set tend to also have more biologically variable characteristics. With the continued accumulation of high throughput data for a wide range of chemicals, predictive modeling can provide a valuable complement for adverse outcome pathway based approach in risk assessment. [ABSTRACT FROM AUTHOR]

Abstract Benchmark dose (BMD) analysis is generally recognized superior to generate a point of departure (PoD) to conduct risk assessment on environmental toxicants, comparing with the traditionally employed no observed adverse effect level (NOAEL) or lowest observed adverse effect level (LOAEL) methods. However, only a few studies compared the two on producing PoD of thyroid toxicity caused by environmental chemicals. Here, we presented BMD analyses on several thyroid toxicity endpoints caused by a model chemical – propylthiouracil (PTU). Adult female rats underwent ovariectomy were randomly assigned into groups receiving different doses of PTU (0, 0.1, 0.5, 1.0, and 5.0 mg/kg bw) through gavage for 8 days. Results show that PTU induces significant dose-dependent changes of serum total thyroxine (tT 4 ), total triiodothyronine (tT 3 ), thyroid stimulating hormones, liver type I 5′-deiodinonase (5′-DI) and malic enzyme (ME) activity with profound histopathological exacerbation. BMD and BMDL results (0.03 and 0.01 mg/kg bw respectively) from Hill model of liver 5′-DI activity were accepted based on selection criteria in the benchmark dose analysis. In summary, BMD analysis results in much lower PoD (0.01 mg/kg bw) than LOAEL (0.1 mg/kg bw) in PTU induced thyroid toxicity. Highlights • Propylthiouracil (PTU) is a strong inhibitory agent to thyroid function. • Liver 5′-DI activity is the most sensitive endpoint of PTU thyroid toxicity based on the BMDL results. • BMD analysis generates much lower point of departure (PoD) (0.01 mg/kg bw) than LOAEL/NOAEL methods (0.1 mg/kg bw). [ABSTRACT FROM AUTHOR]

The influence of exposure duration on chemical toxicity has important implications for risk assessment. Although a default 10-fold extrapolation factor is commonly applied when the toxicological dataset includes a subchronic (90-day) study but lacks studies of chronic duration, little consensus has been reached on an appropriate extrapolation factor to apply when the dataset includes a 28-day study but lacks studies of longer durations. The goal of the present assessment was to identify a 28-day to 90-day extrapolation factor by analyzing distributions of ratios of No-Observed-Adverse-Effect Levels (NOAELs) and Benchmark Doses (BMDs) derived from 28-day and 90-day studies. The results of this analysis suggest that a default 10-fold extrapolation factor in chemical risk assessment applications is sufficient to account for the uncertainty associated with evaluating human health risk based on results from a 28-day study in the absence of results from a 90-day study. This analysis adds significantly to the growing body of literature interpreting the influence of exposure duration on chemical toxicity that will likewise facilitate discussions on the future state of testing requirements in the international regulatory community. [ABSTRACT FROM AUTHOR]

An approach is presented for ethylene oxide (EO) to derive endogenous equivalent (EE) values, which are endogenous levels normally found within the body expressed in terms of exogenous exposures. EE values can be used to support risk assessment and risk management decisions for chemicals such as EO that have both endogenous and exogenous exposure pathways. EE values were derived using a meta-analysis of data from the published literature characterizing the distribution for an EO biomarker of exposure, hemoglobin N-(2-hydroxyethyl)-valine (HEV), in unexposed populations. These levels are compared to the those reported in exposed populations (smokers, workers). Correlation between the biomarker of exposure and external exposures of EO were applied to this distribution to determine corresponding EE values, which range from 0.13 to 6.9 ppb for EO in air. These values are orders of magnitude higher than risk-based concentration values derived for EO using default methods, and are provided as a pragmatic, data-driven alternative approach to managing the potential risks from exogenous exposures to EO. [ABSTRACT FROM AUTHOR]