Predicting points of departure and potency categories for fragrance ingredients by integrating OECD in vitro models.

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.

In Vitro Prediction of Skin-Sensitizing Potency Using the GARDskin Dose-Response Assay: A Simple Regression Approach.

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.

Deriving a Continuous Point of Departure for Skin Sensitization Risk Assessment Using a Bayesian Network Model.

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.

A Qualitative Insight into Pre-Departure Orientation Training for Aspiring Nepalese Migrant Workers.

Pre-departure orientation training (PDOT) can help equip aspiring migrant workers with skills and knowledge to mitigate vulnerabilities throughout their migration journey, including health. In Nepal, PDOT has been mandatory since 2004 for migrant workers awaiting labour permits. The current PDOT programme includes country-specific information as well as health and well-being advice. However, the views of trainees and trainers on PDOT are largely unknown. This qualitative study aims to explore perceptions of migrant workers and relevant stakeholders on the content and delivery of PDOT. Six focus group discussions and six in-depth interviews were conducted with migrants, and eight interviews with key stakeholders were conducted. Thematic analysis resulted in five themes: (a) PDOT structure, accessibility, and implementation; (b) role of stakeholders in labour migration process; (c) coordination and governance; (d) curriculum development and relevance; and (e) capacity of trainers and effectiveness of training. Our findings emphasise the need for a more tailored curriculum with relevant information, education, and communication resources, possibly with input from former migrant workers. Regular updates of training topics and resources, as well as continued engagement with migrants after their employment, are essential for meeting the dynamic demands of the global employment market.

Far from Their Origins: A Transcriptomic Investigation on How 2,4-Di-tert-butyl-6-(5-chloro-2H-benzotriazol-2-yl) Phenol Affects Rainbow Trout Alevins.

Benzotriazole ultraviolet stabilizers (BUVSs) are a group of widely used chemicals added to a variety of consumer (e.g., plastics) and industrial (e.g., metal coating) goods. Although detected globally as an environmentally persistent pollutant, BUVSs have received relatively little toxicological attention and only recently have been acknowledged to affect development and the endocrine system in vivo. In our previous study, altered behavior, indicative of potential neurotoxicity, was observed among rainbow trout alevins (day 14 posthatching) that were microinjected as embryos with a single environmentally relevant dose of 2,4-di-tert-butyl-6-(5-chloro-2H-benzotriazol-2-yl) phenol (UV-327). In the present follow-up study, we performed whole-transcriptome profiling (RNA sequencing) of newly hatched alevins from the same batch. The primary aim was to identify biomarkers related to behavior and neurology. Dose-specifically, 1 to 176 differentially expressed genes (DEGs) were identified. In the group presenting altered behavior (273.4 ng g-1), 176 DEGs were identified, yet only a fraction was related to neurological functions, including water, calcium, and potassium homeostasis; acetylcholine transmission and signaling; as well insulin and energy metabolism. The second objective was to estimate the transcriptomic point of departure (tPOD) and assess if point estimate(s) are protective of altered behavior. A tPOD was established at 35 to 94 ng UV-327 g-1 egg, making this tPOD protective of behavioral alterations. Holistically, these transcriptomic alterations provide a foundation for future research on how BUVSs can influence rainbow trout alevin development, while providing support to the hypothesis that UV-327 can influence neurogenesis and subsequent behavioral endpoints. The exact structural and functional changes caused by embryonic exposure to UV-327 remain enigmatic and will require extensive investigation before being deciphered and understood toxicologically. Environ Toxicol Chem 2024;43:2026-2038. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Next generation risk assessment of biocides (PHMG-p and CMIT/MIT)-induced pulmonary fibrosis using adverse outcome pathway-based transcriptome analysis.

Next-generation risk assessment (NGRA) has emerged as a promising alternative to non-animal studies owing to the increasing demand for the risk assessment of inhaled toxicants. In this study, NGRA was used to assess the inhalation risks of two biocides commonly used as humidifier disinfectants: polyhexamethylene guanidine phosphate (PHMG-p) and chloromethylisothiazolinone/methylisothiazolinone (CMIT/MIT). Human bronchial epithelial cell transcriptomic data were processed based on adverse outcome pathways and used to establish transcriptome-based points of departure (tPODs) for each biocide. tPOD values were 0.00500-0.0510 µg/cm2 and 0.0342-0.0544 µg/cm2 for PHMG-p and CMIT/MIT, respectively. tPODs may provide predictive power comparable to that of traditional animal-based PODs (aPODs). The tPOD-based NGRA determined that both PHMG-p and CMIT/MIT present a high inhalation risk. Moreover, the identified PHMG-p posed a higher risk than CMIT/MIT, and children were identified as more susceptible population compared to adults. This finding is consistent with observations from actual exposure events. Our findings suggest that NGRA with transcriptomics offers a reliable approach for risk assessment of specific humidifier disinfectant biocides, while acknowledging the limitations of current models and in vitro systems, particularly regarding uncertainties in pharmacokinetics (PK) and pharmacodynamics (PD).

Deriving a point of departure for assessing the skin sensitization risk of wearable device constituents with in vitro methods.

Wearable devices are in contact with the skin for extended periods. As such, the device constituents should be evaluated for their skin sensitization potential, and a Point of Departure (PoD) should be derived to conduct a proper risk assessment. Without historical in vivo data, the PoD must be derived with New Approach Methods (NAMs). To accomplish this, regression models trained on LLNA data that use data inputs from OECD-validated in vitro tests were used to derive a predicted EC3 value, the LLNA value used to classify skin sensitization potency, for three adhesive monomers (Isobornyl acrylate (IBOA), N, N- Dimethylacrylamide (NNDMA), and Acryloylmorpholine (ACMO) and one dye (Solvent Orange 60 (SO60)). These chemicals can be used as constituents of wearable devices and have been associated with causing allergic contact dermatitis (ACD). Using kinetic DPRA and KeratinoSens™ data, the PoDs obtained with the regression model were 180, 215, 1535, and 8325 µg/cm2 for IBOA, SO60, ACMO, and NNDMA, respectively. The PoDs derived with the regression model using NAMs data will enable a proper skin sensitization risk assessment without using animals.

Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches.

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.

Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances.

Chemicals assessment and management frameworks rely on regulatory toxicity values, which are based on points of departure (POD) identified following rigorous dose-response assessments. Yet, regulatory PODs and toxicity values for inhalation exposure (i.e., reference concentrations [RfCs]) are available for only ∼200 chemicals. To address this gap, we applied a workflow to determine surrogate inhalation route PODs and corresponding toxicity values, where regulatory assessments are lacking. We curated and selected inhalation in vivo data from the U.S. EPA's ToxValDB and adjusted reported effect values to chronic human equivalent benchmark concentrations (BMCh) following the WHO/IPCS framework. Using ToxValDB chemicals with existing PODs associated with regulatory toxicity values, we found that the 25th %-ile of a chemical's BMCh distribution (PODp25BMCh) could serve as a suitable surrogate for regulatory PODs (Q2 ≥ 0.76, RSE ≤ 0.82 log10 units). We applied this approach to derive PODp25BMCh for 2,095 substances with general non-cancer toxicity effects and 638 substances with reproductive/developmental toxicity effects, yielding a total coverage of 2,160 substances. From these PODp25BMCh, we derived probabilistic RfCs and human population effect concentrations. With this work, we have expanded the number of chemicals with toxicity values available, thereby enabling a much broader coverage for inhalation risk and impact assessment.

Roles of Wettability and Wickability on Enhanced Hydrogen Evolution Reactions.

Bubble dynamics significantly impact mass transfer and energy conversion in electrochemical gas evolution reactions. Micro-/nanostructured surfaces with extreme wettability have been employed as gas-evolving electrodes to promote bubble departure and decrease the bubble-induced overpotential. However, effects of the electrodes' wickability on the electrochemical reaction performances remain elusive. In this work, hydrogen evolution reaction (HER) performances are experimentally investigated using micropillar array electrodes with varying interpillar spacings, and effects of the electrodes' wettability, wickability as well as bubble adhesion are discussed. A deep learning-based object detection model was used to obtain bubble counts and bubble departure size distributions. We show that microstructures on the electrode have little effect on the total bubble counts and bubble size distribution characteristics at low current densities. At high current densities, however, micropillar array electrodes have much higher total bubble counts and smaller bubble departure sizes compared with the flat electrode. We also demonstrate that surface wettability is a critical factor influencing HER performances under low current densities, where bubbles exist in an isolated regime. Under high current densities, where bubbles are in an interacting regime, the wickability of the micropillar array electrodes emerges as a determining factor. This work elucidates the roles of surface wettability and wickability on enhancing electrochemical performances, providing guidelines for the optimal design of micro-/nanostructured electrodes in various gas evolution reactions.

A methodology for estimating SARS-CoV-2 importation risk by air travel into Canada between July and November 2021.

BACKGROUND: Estimating rates of disease importation by travellers is a key activity to assess both the risk to a country from an infectious disease emerging elsewhere in the world and the effectiveness of border measures. We describe a model used to estimate the number of travellers infected with SARS-CoV-2 into Canadian airports in 2021, and assess the impact of pre-departure testing requirements on importation risk. METHODS: A mathematical model estimated the number of essential and non-essential air travellers infected with SARS-CoV-2, with the latter requiring a negative pre-departure test result. The number of travellers arriving infected (i.e. imported cases) depended on air travel volumes, SARS-CoV-2 exposure risk in the departure country, prior infection or vaccine acquired immunity, and, for non-essential travellers, screening from pre-departure molecular testing. Importation risk was estimated weekly from July to November 2021 as the number of imported cases and percent positivity (PP; i.e. imported cases normalised by travel volume). The impact of pre-departure testing was assessed by comparing three scenarios: baseline (pre-departure testing of all non-essential travellers; most probable importation risk given the pre-departure testing requirements), counterfactual scenario 1 (no pre-departure testing of fully vaccinated non-essential travellers), and counterfactual scenario 2 (no pre-departure testing of non-essential travellers). RESULTS: In the baseline scenario, weekly imported cases and PP varied over time, ranging from 145 to 539 cases and 0.15 to 0.28%, respectively. Most cases arrived from the USA, Mexico, the United Kingdom, and France. While modelling suggested that essential travellers had a higher weekly PP (0.37 - 0.65%) than non-essential travellers (0.12 - 0.24%), they contributed fewer weekly cases (62 - 154) than non-essential travellers (84 - 398 per week) given their lower travel volume. Pre-departure testing was estimated to reduce imported cases by one third (counterfactual scenario 1) to one half (counterfactual scenario 2). CONCLUSIONS: The model results highlighted the weekly variation in importation by traveller group (e.g., reason for travel and country of departure) and enabled a framework for measuring the impact of pre-departure testing requirements. Quantifying the contributors of importation risk through mathematical simulation can support the design of appropriate public health policy on border measures.

Toward a complete understanding of quasi-static bubble growth and departure.

The distortion by gravity of a quasi-static bubble attached on an upward facing surface in a quiescent liquid is investigated. The contact angle evolution during the growth of such a bubble is studied, and the consequences on the motion of the contact line between the solid and the interface are discussed. From the initial case of a bubble attached to the rim of a nucleation site, the contact line can move inside the cavity for a highly wetting fluid, causing premature departure. For a higher wettability, the contact can either remain attached to the rim of the cavity or spread out of the cavity, depending on the cavity size and geometry. For the latter case, the bubble growth is investigated taking into account a contact angle hysteresis. Finally, a comprehensive map detailing various geometrical characteristics of bubbles is presented, ranging over several orders of magnitude of Bond numbers and normalized volumes. The map aims at being used as a tool for investigating bubble growth in a similar situation.

Bioactivity assessment of organophosphate flame retardants via a dose-dependent yeast functional genomics approach.

Organophosphate flame retardants (OPFRs) have been widely detected in multiple environment media and have many adverse effects with complex toxicity mechanisms. However, the early molecular responses to OPFRs have not been fully elucidated, thereby making it difficult to assess their risks accurately. In this work, we systematically explored the point of departure (POD) of biological pathways at genome-wide level perturbed by 14 OPFRs with three substituents (alkyl, halogen, and aryl) using a dose-dependent functional genomics approach in Saccharomyces cerevisiae at 24 h exposure. Firstly, our results demonstrated that the overall biological potency at gene level (PODDRG20) ranged from 0.013 to 35.079 µM for 14 OPFRs, especially the tributyl phosphate (TnBP) exhibited the strongest biological potency with the least PODDRG20. Secondly, we found that structural characteristics of carbon number and logKow were significantly negatively correlated with POD, and carbon number and logKow also significantly affected lipid metabolism associated processes. Thirdly, these early biological pathways of OPFRs toxification were found to be involved in lipid metabolism, oxidative stress, DNA damage, MAPK signaling pathway, and amino acid and carbohydrate metabolism, among which the lipid metabolism was the most sensitive molecular response perturbed by most OPFRs. More importantly, we identified one resistant mutant strain with knockout of ERG2 (YMR202W) gene participated in steroid biosynthesis pathway, which can serve as a key yeast strain of OPFRs toxification. Overall, our study demonstrated an effective platform for accurately assessing OPFRs risks and provided a basis for further green OPFRs development.

Evaluating scientific confidence in the concordance of in vitro and in vivo protective points of departure.

To fulfil the promise of reducing reliance on mammalian in vivo laboratory animal studies, new approach methods (NAMs) need to provide a confident basis for regulatory decision-making. However, previous attempts to develop in vitro NAMs-based points of departure (PODs) have yielded mixed results, with PODs from U.S. EPA's ToxCast, for instance, appearing more conservative (protective) but poorly correlated with traditional in vivo studies. Here, we aimed to address this discordance by reducing the heterogeneity of in vivo PODs, accounting for species differences, and enhancing the biological relevance of in vitro PODs. However, we only found improved in vitro-to-in vivo concordance when combining the use of Bayesian model averaging-based benchmark dose modeling for in vivo PODs, allometric scaling for interspecies adjustments, and human-relevant in vitro assays with multiple induced pluripotent stem cell-derived models. Moreover, the available sample size was only 15 chemicals, and the resulting level of concordance was only fair, with correlation coefficients <0.5 and prediction intervals spanning several orders of magnitude. Overall, while this study suggests several ways to enhance concordance and thereby increase scientific confidence in vitro NAMs-based PODs, it also highlights challenges in their predictive accuracy and precision for use in regulatory decision making.

Environmental factors influencing red knot (Calidris canutus islandica) departure times of relocation flights within the non-breeding period.

Deciding when to depart on long-distance, sometimes global, movements can be especially important for flying species. Adverse weather conditions can affect energetic flight costs and navigational ability. While departure timings and conditions have been well-studied for migratory flights to and from the breeding range, few studies have focussed on flights within the non-breeding season. Yet in some cases, overwintering ranges can be large enough that ecological barriers, and a lack of resting sites en route, may resist movement, especially in unfavorable environmental conditions. Understanding the conditions that will enable or prohibit flights within an overwintering range is particularly relevant in light of climate change, whereby increases in extreme weather events may reduce the connectivity of sites. We tracked 495 (n = 251 in 2019; n = 244 in 2020) overwintering red knots (Calidris canutus islandica) in the Dutch Wadden Sea and investigated how many departed towards the UK (on westward relocation flights), which requires flying over the North Sea. For those that departed, we used a resource selection model to determine the effect of environmental conditions on the timing of relocation flights. Specifically, we investigated the effects of wind, rain, atmospheric pressure, cloud cover, and migratory timing relative to sunset and tidal cycle, which have all been shown to be crucial to migratory departure conditions. Approximately 37% (2019) and 36% (2020) of tagged red knots departed on westward relocation flights, indicating differences between individuals' space use within the overwintering range. Red knots selected for departures between 1 and 2.5 h after sunset, approximately 4 h before high tide, with tailwinds and little cloud cover. However, rainfall and changes in atmospheric pressure appear unimportant. Our study reveals environmental conditions that are important for relocation flights across an ecological barrier, indicating potential consequences of climate change on connectivity.

Systematic review of epidemiological and toxicological evidence on health effects of fluoride in drinking water.

INTRODUCTION: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment.

Next generation risk assessment of chemicals revolves around the use of mechanistic information without animal experimentation. In this regard, toxicogenomics has proven to be a useful tool to elucidate the underlying mechanisms of adverse effects of xenobiotics. In the present study, two widely used human in vitro hepatocyte culture systems, namely primary human hepatocytes (PHH) and human hepatoma HepaRG cells, were exposed to liver toxicants known to induce liver cholestasis, steatosis or necrosis. Benchmark concentration-response modelling was applied to transcriptomics gene co-expression networks (modules) to derive benchmark concentrations (BMCs) and to gain mechanistic insight into the hepatotoxic effects. BMCs derived by concentration-response modelling of gene co-expression modules recapitulated concentration-response modelling of individual genes. Although PHH and HepaRG cells showed overlap in deregulated genes and modules by the liver toxicants, PHH demonstrated a higher responsiveness, based on the lower BMCs of co-regulated gene modules. Such BMCs can be used as transcriptomics point of departure (tPOD) for assessing module-associated cellular (stress) pathways/processes. This approach identified clear tPODs of around maximum systemic concentration (Cmax) levels for the tested drugs, while for cosmetics ingredients the BMCs were 10-100-fold higher than the estimated plasma concentrations. This approach could serve next generation risk assessment practice to identify early responsive modules at low BMCs, that could be linked to key events in liver adverse outcome pathways. In turn, this can assist in delineating potential hazards of new test chemicals using in vitro systems and used in a risk assessment when BMCs are paired with chemical exposure assessment.

Risk assessment of chemicals has traditionally been focused on animal experiments. In contrast, next generation risk assessment uses biological information obtained from experiments in cell culture models without animals to identify potential hazards. Since the liver is the main target organ of toxicity, many liver cell (hepatocyte) models have been developed and applied for hazard assessment. In this study, two widely used human hepatocyte cell models, PHH and HepaRG, were exposed to liver toxic chemicals. Biological changes in gene expression were measured in a concentration range to identify the concentration at which a biological response was perturbed using concentration response modelling. Genes belonging to the same biological process were joined based on co-expression to derive an average concentration of this process. This animal-free approach could be applied for risk assessment when biological response concentrations were related to the expected human exposure to identify potential hazard of the test chemicals.

Reliability-based analysis of horizontal curve design by evaluating the impact of vehicle automation on roadway departure crashes and safety performance.

Roadway departure (RwD) crashes are significant safety concerns, especially at horizontal curves. The design of these curves plays a crucial role in mitigating RwD crashes. Thus, a thorough understanding of the interaction between driver behavior, vehicle automation, and geometric design is vital. Substantive safety, which emphasizes the inherent safety in a road's design and function, serves as the foundation of our approach. Building on this, the study employs a safe system approach to investigate the performance of horizontal curves under both non-automated and partially automated conditions, using a reliability-based analysis focusing on Stopping Sight Distance as the primary driver demand. Factors including Perception-Brake Time and Take-Over Time for automated vehicles are examined. The analysis covers horizontal curves, characterized by their geometric design and crash data. Our findings highlight a shift in the performance of horizontal curves under automation, emphasizing the need to consider automation in roadway design within the safe system approach. This study demonstrates how a reliability-based analysis can guide designers in making informed decisions regarding the geometric design of horizontal curves to reduce RwD crashes. To enhance transportation safety in the era of increasing automation, ongoing exploration of the relationships between driver behavior, automation, and road design is indispensable.

N-Nitrosodimethylamine investigations in Muta™Mouse define point-of-departure values and demonstrate less-than-additive somatic mutant frequency accumulations.

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 lacZ 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 lacZ 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 lacZ 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.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates.

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.