The Key Events Dose-Response Framework: a cross-disciplinary mode-of-action based approach to examining dose-response and thresholds

A new approach methodology to identify tumorigenic chemicals using short-term exposures and transcript profiling

Current methods for cancer risk assessment are resource-intensive and not feasible for most of the thousands of untested chemicals. In earlier studies, we developed a new approach methodology (NAM) to identify liver tumorigens using gene expression biomarkers and associated tumorigenic activation levels (TALs) after short-term exposures in rats. The biomarkers are used to predict the six most common rodent liver cancer molecular initiating events. In the present study, we wished to confirm that our approach could be used to identify liver tumorigens at only one time point/dose and if the approach could be applied to (targeted) RNA-Seq analyses. Male rats were exposed for 4 days by daily gavage to 15 chemicals at doses with known chronic outcomes and liver transcript profiles were generated using Affymetrix arrays. Our approach had 75% or 85% predictive accuracy using TALs derived from the TG-GATES or DrugMatrix studies, respectively. In a dataset generated from the livers of male rats exposed to 16 chemicals at up to 10 doses for 5 days, we found that our NAM coupled with targeted RNA-Seq (TempO-Seq) could be used to identify tumorigenic chemicals with predictive accuracies of up to 91%. Overall, these results demonstrate that our NAM can be applied to both microarray and (targeted) RNA-Seq data generated from short-term rat exposures to identify chemicals, their doses, and mode of action that would induce liver tumors, one of the most common endpoints in rodent bioassays.

Effects of intrinsic characteristics of Salmonella enterica strains isolated from foods and humans, and their interaction with food matrices during simulated gastric conditions

The stomach's acidic pH is a crucial barrier against foodborne pathogens such as Salmonella enterica. This study investigated the survival of S. enterica under simulated oral and gastric conditions (SGC; pH 2 for 120 min) as a function of intrinsic pathogen characteristics and food matrix. Fifty-seven S. enterica strains isolated from food and human infections (previously characterized by serotype, virulotype, multi-drug resistance, isolation source, and isolation season) were subjected to SGC using water as a vehicle. Population reduction among the 57 isolates ranged from 2.7 to 4.7 log CFU, revealing that human isolates were inactivated less than food isolates (p = 0.0008). Among food strains, strains isolated during the cold season (food sampled from December to February) displayed the highest reduction (p = 0.00002). Six representatives of the 57 S. enterica strains were selected according to their virulotype and antimicrobial profile. They were further used to evaluate their survival under SGC in four food matrices (water, mango, tomato, and chicken), measuring S. enterica at 30 min intervals. The strains in chicken showed the lowest reduction and inactivation rate (1.42 ± 0.35 log CFU; 0.03 ± 0.005 min-1), followed by tomato (3.75 ± 0.57 log CFU; 0.15 ± 0.02 min-1), water (4.23 ± 0.27 log CFU; 0.17 ± 0.02 min-1), and mango (4.49 ± 0.39 log CFU; 0.17 ± 0.03 min-1). These data suggest that not all S. enterica strains have the same ability to survive under SGC, influencing the probability of arriving into the small intestine.

A mode of action-based probabilistic framework of dose-response assessment for nonmutagenic liver carcinogens: a case study of PCB-126

A main function of dose-response assessment is to estimate a "safe" dose in the target population to support chemical risk assessment. Typically, a "safe" dose is developed differently for cancer and noncancer effects based on a 2-step procedure, ie, point of departure (POD) derivation and low-dose extrapolation. However, the current dose-response assessment framework is criticized for its dichotomized strategy without integrating the mode of action (MOA) information. The objective of this study was, based on our previous work, to develop a MOA-based probabilistic dose-response framework that quantitatively synthesizes a biological pathway in a dose-response modeling process to estimate the risk of chemicals that have carcinogenic potential. 3,3',4,4',5-Pentachlorobiphenyl (PCB-126) was exemplified to demonstrate our proposed approach. There were 4 major steps in the new modeling framework, including (1) key quantifiable events (KQEs) identification and extraction, (2) essential dose calculation, (3) MOA-based POD derivation, and (4) MOA-based probabilistic reference dose (RfD) estimation. Compared with reported PODs and traditional RfDs, the MOA-based estimates derived from our approach were comparable and plausible. One key feature of our approach was the use of overall MOA information to build the dose-response relationship on the entire dose continuum including the low-dose region. On the other hand, by adjusting uncertainty and variability in a probabilistic manner, the MOA-based probabilistic RfDs can provide useful insights of health protection for the specific proportion of population. Moreover, the proposed framework had important potential to be generalized to assess different types of chemicals other than nonmutagenic carcinogens, highlighting its utility to improve current chemical risk assessment.

Research advances in identification procedures of endocrine disrupting chemicals

Endocrine disrupting chemicals (EDCs) are increasingly concerned substance endangering human health and environment. However, there is no unified standard for identifying chemicals as EDCs, which is also controversial internationally. In this review, the procedures for EDC identification in different organizations/countries were described. Importantly, three aspects to be considered in identifying chemical substances as EDCs were summarized, which were mechanistic data, animal experiments, and epidemiological information. The relationships between them were also discussed. To elaborate more clearly on these three aspects of evidence, scientific data on some chemicals including bisphenol A, 1,2-dibromo-4-(1,2 dibromoethyl) cyclohexane and perchlorate were collected and evaluated. Altogether, the above three chemicals were assessed for interfering with hormones and elaborated their health hazards from macroscopic to microscopic. This review is helpful for standardizing the identification procedure of EDCs.

An Adverse Outcome Pathway Network for Chemically Induced Oxidative Stress Leading to (Non)genotoxic Carcinogenesis

Nongenotoxic (NGTX) carcinogens induce cancer via other mechanisms than direct DNA damage. A recognized mode of action for NGTX carcinogens is induction of oxidative stress, a state in which the amount of oxidants in a cell exceeds its antioxidant capacity, leading to regenerative proliferation. Currently, carcinogenicity assessment of environmental chemicals primarily relies on genetic toxicity end points. Since NGTX carcinogens lack genotoxic potential, these chemicals may remain undetected in such evaluations. To enhance the predictivity of test strategies for carcinogenicity assessment, a shift toward mechanism-based approaches is required. Here, we present an adverse outcome pathway (AOP) network for chemically induced oxidative stress leading to (NGTX) carcinogenesis. To develop this AOP network, we first investigated the role of oxidative stress in the various cancer hallmarks. Next, possible mechanisms for chemical induction of oxidative stress and the biological effects of oxidative damage to macromolecules were considered. This resulted in an AOP network, of which associated uncertainties were explored. Ultimately, development of AOP networks relevant for carcinogenesis in humans will aid the transition to a mechanism-based, human relevant carcinogenicity assessment that involves a substantially lower number of laboratory animals.

A Collaborative Initiative to Establish Genomic Biomarkers for Assessing Tumorigenic Potential to Reduce Reliance on Conventional Rodent Carcinogenicity Studies

There is growing recognition across broad sectors of the scientific community that use of genomic biomarkers has the potential to reduce the need for conventional rodent carcinogenicity studies of industrial chemicals, agrochemicals, and pharmaceuticals through a weight-of-evidence approach. These biomarkers fall into 2 major categories: (1) sets of gene transcripts that can identify distinct tumorigenic mechanisms of action; and (2) cancer driver gene mutations indicative of rapidly expanding growth-advantaged clonal cell populations. This call-to-action article describes a collaborative approach launched to develop and qualify biomarker gene expression panels that measure widely accepted molecular pathways linked to tumorigenesis and their activation levels to predict tumorigenic doses of chemicals from short-term exposures. Growing evidence suggests that application of such biomarker panels in short-term exposure rodent studies can identify both tumorigenic hazard and tumorigenic activation levels for chemical-induced carcinogenicity. In the future, this approach will be expanded to include methodologies examining mutations in key cancer driver gene mutation hotspots as biomarkers of both genotoxic and nongenotoxic chemical tumor risk. Analytical, technical, and biological validation studies of these complementary genomic tools are being undertaken by multisector and multidisciplinary collaborative teams within the Health and Environmental Sciences Institute. Success from these efforts will facilitate the transition from current heavy reliance on conventional 2-year rodent carcinogenicity studies to more rapid animal- and resource-sparing approaches for mechanism-based carcinogenicity evaluation supporting internal and regulatory decision-making.

Adverse Outcome Pathways as Versatile Tools in Liver Toxicity Testing

Adverse outcome pathways (AOPs) are tools to capture and visualize mechanisms driving toxicological effects. They share a common structure consisting of a molecular initiating event, a series of key events connected by key event relationships and an adverse outcome. Development and evaluation of AOPs ideally comply with guidelines issued by the Organization for Economic Cooperation and Development. AOPs have been introduced for major types of hepatotoxicity, which is not a surprise, as the liver is a frequent target for systemic adversity. Various applications for AOPs have been proposed in the areas of toxicology and chemical risk assessment, in particular in relation to the establishment of quantitative structure-activity relationships, the elaboration of prioritization strategies, and the development of novel in vitro toxicity screening tests and testing strategies.

Competitive growth kinetics of Campylobacter jejuni, Escherichia coli O157:H7 and Listeria monocytogenes with enteric microflora in a small-intestine model

Aims

The biological events occurring during human digestion help to understand the mechanisms underlying the dose–response relationships of enteric bacterial pathogens. To better understand these events, we investigated the growth and reduction behaviour of bacterial pathogens in an in vitro model simulating the environment of the small intestine.

Methods and Results

The foodborne pathogens Campylobacter jejuni, Listeria monocytogenes and Escherichia coli O157:H7 were cultured with multiple competing enteric bacteria. Differences in the pathogen's growth kinetics due to the relative amount of competing enteric bacteria were investigated. These growth differences were described using a mathematical model based on Bayesian inference. When pathogenic and enteric bacteria were inoculated at 1 log CFU per ml and 9 log CFU per ml, respectively, L. monocytogenes was inactivated over time, while C. jejuni and E. coli O157:H7 survived without multiplying. However, as pathogen inocula were increased, its inhibition by enteric bacteria also decreased.

Conclusions

Although the growth of pathogenic species was inhibited by enteric bacteria, the pathogens still survived.

Significance and Impact of the Study

Competition experiments in a small‐intestine model have enhanced understanding of the infection risk in the intestine and provide insights for evaluating dose–response relationships.

Implementing a new dose-response model for estimating infection probability of Campylobacter jejuni based on the key events dose-response framework

Understanding the dose-response relationship between ingested pathogenic bacteria and infection probability is a key factor for appropriate risk assessment of foodborne pathogens. The objectives of this study were to develop and validate a novel mechanistic dose-response model for Campylobacter jejuni and simulate the underlying mechanism of foodborne illness during digestion. Bacterial behavior in the human gastrointestinal environment, including survival at low pH in the gastric environment after meals, transition to intestines, and invasion to intestinal tissues, was described using a Bayesian statistical model based on the reported experimental results of each process while considering physical food types (liquid or solid) and host age (young adult or elderly). Combining the models in each process, the relationship between pathogen intake and the infection probability of C. jejuni was estimated and compared with reported epidemiological dose-response relationships. Taking food types and host age into account, the prediction range of the infection probability of C. jejuni successfully covered the reported dose-response relationships from actual C. jejuni outbreaks. According to sensitivity analysis of predicted infection probabilities, the host age factor and the food type factor have relatively higher relevance than other factors. Thus, the developed Key Events Dose Response Framework can derive novel information for quantitative microbiological risk assessment in addition of dose-response relationship. The developed framework is potentially applicable to other pathogens to quantify the dose-response relationship from experimental data obtained from digestion. Importance Based on the mechanistic approach called Key Events Dose Response Framework alternative to previous non-mechanistic approach, the dose-response models for infection probability of C. jejuni were developed considering with age of people who take pathogen and food type. The developed predictive framework illustrated highly accurate prediction of dose (minimum difference 0.21 log CFU) for a certain infection probability compared with the previously reported dose-response relationship. In addition, the developed prediction procedure revealed that the dose-response relationship strongly depends on food type as well as host age. The implementation of Key Event Dose Response Framework will mechanistically and logically reveal the dose-response relationship and provide useful information with quantitative microbiological risk assessment of C. jejuni on foods.

Evaluation of Strain Variability in Inactivation of Campylobacter jejuni in Simulated Gastric Fluid by Using Hierarchical Bayesian Modeling

This study was conducted to quantitatively evaluate the variability of stress resistance in different strains of Campylobacter jejuni and the uncertainty of such strain variability. We developed Bayesian statistical models with multilevel analysis to quantify variability within a strain, variability between different strains, and the uncertainty associated with these estimates. Furthermore, we measured the inactivation of 11 strains of C. jejuni in simulated gastric fluid with low pH, using the Weibullian survival model. The model was first developed for separate pH conditions and then analyzed over a range of pH levels. We found that the model parameters developed under separate pH conditions exhibited a clear dependence of survival on pH. In addition, the uncertainty of the variability between different strains could be described as the joint distribution of the model parameters. The latter model, including pH dependency, accurately predicted the number of surviving cells in individual as well as multiple strains. In conclusion, variabilities and uncertainties in inactivation could be simultaneously evaluated and interpreted via a probabilistic approach based on Bayesian theory. Such hierarchical Bayesian models could be useful for understanding individual-strain variability in quantitative microbial risk assessment. IMPORTANCE Since microbial strains vary in their growth and inactivation patterns in food materials, it is important to accurately predict these patterns for quantitative microbial risk assessment. However, most previous studies in this area have used highly resistant strains, which could lead to inaccurate predictions. Moreover, variability, including measurement errors and variability within a strain and between different strains, can contribute to predicted individual-level outcomes. Therefore, a multilevel framework is required to resolve these levels of variability and estimate their uncertainties. We developed a Bayesian predictive model for the survival of Campylobacter jejuni under simulated gastric conditions taking into account the variabilities and uncertainties. We demonstrated a high correspondence between predictions from the model and empirical measurements. The modeling procedure proposed in this study recommends a novel framework for predicting pathogen behavior, which can help improve quantitative microbial risk assessment during food production and distribution.

Modeling Invasion of Campylobacter jejuni into Human Small Intestinal Epithelial-Like Cells by Bayesian Inference

Current approaches used for dose-response modeling of low-dose exposures of pathogens rely on assumptions and extrapolations. These models are important for quantitative microbial risk assessment of food. A mechanistic framework has been advocated as an alternative approach for evaluating dose-response relationships. The objectives of this study were to investigate the invasion behavior of Campylobacter jejuni, which could arise as a foodborne illness even if there are low counts of pathogens, into Caco-2 cells as a model of intestinal cells and to develop a mathematical model for invading cell counts to reveal a part of the infection dose-response mechanism. Monolayer-cultured Caco-2 cells and various concentrations of C. jejuni in culture were cocultured for up to 12 h. The numbers of C. jejuni bacteria invading Caco-2 cells were determined after coculture for different time periods. There appeared to be a maximum limit to the invading bacterial counts, which showed an asymptotic exponential increase. The invading bacterial counts were higher with higher exposure concentrations (maximum, 5.0 log CFU/cm²) than with lower exposure concentrations (minimum, 0.6 log CFU/cm²). In contrast, the ratio of invading bacteria (number of invading bacteria divided by the total number of bacteria exposed) showed a similar trend regardless of the exposure concentration. Invasion of C. jejuni into intestinal cells was successfully demonstrated and described by the developed differential equation model with Bayesian inference. The model accuracy showed that the 99% prediction band covered more than 97% of the observed values. These findings provide important information on mechanistic pathogen dose-response relationships and an alternative approach for dose-response modeling.IMPORTANCE One of the infection processes of C. jejuni, the invasion behavior of the bacteria in intestinal epithelial cells, was revealed, and a mathematical model for prediction of the cell-invading pathogen counts was developed for the purpose of providing part of a dose-response model for C. jejuni based on the infection mechanism. The developed predictive model showed a high accuracy of more than 97% and successfully described the C. jejuni invading counts. The bacterial invasion predictive model of this study will be essential for the development of a dose-response model for C. jejuni based on the infection mechanism.

A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays

Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chemicals. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in transcript profiles derived from chemically-treated rats using either a Toxicological Priority Index (ToxPi) approach or using derived biomarker thresholds for cancer. The biomarkers consisting of 7-113 genes are used to predict the most common liver cancer molecular initiating events: genotoxicity, cytotoxicity and activation of the xenobiotic receptors AhR, CAR, ER, and PPARα. In the present study, we apply and evaluate the performance of these methods for cancer prediction in an independent rat liver study of 44 chemicals (6 h-7d exposures) examined by Affymetrix arrays. In the first approach, ToxPi ranking of biomarker scores consistently gave the highest scores to tumorigenic chemical-dose pairs; balanced accuracies for identification of liver tumorigenic chemicals were up to 89 %. The second approach used tumorigenic thresholds derived in the present study or from our earlier study that were set at the maximum value for chemical-dose exposures without detectable liver tumor outcomes. Using these thresholds, balanced accuracies were up to 90 %. Both approaches identified all tumorigenic chemicals. Almost all of the tumorigenic chemicals activated more than one MIE. We also compared biomarker responses between two types of profiling platforms (Affymetrix full-genome array, TempO-Seq 1500+ array containing ∼2600 genes) and found that the lack of the full set of biomarker genes on the 1500+ array resulted in decreased ability to identify chemicals that activate the MIEs. Overall, these results demonstrate that predictive approaches based on the 6 biomarkers could be used in short-term assays to identify chemicals and their doses that induce liver tumors, the most common endpoint in rodent bioassays.

Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens

Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3-29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%-97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%-94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or "molecular tipping points" that are predictive of later-life health outcomes.

Evaluating Mode of Action of Acrolein Toxicity in an In Vitro Human Airway Tissue Model

Acrolein is a reactive unsaturated aldehyde and is found at high concentrations in both mainstream and side-stream tobacco smoke. Exposure to acrolein via cigarette smoking has been associated with acute lung injury, chronic obstructive pulmonary diseases (COPDs), and asthma. In this study, we developed an in vitro treatment strategy that resembles the inhalation exposure to acrolein experienced by smokers and systematically examined the adverse respiratory effects induced by the noncytotoxic doses of acrolein in a human airway epithelial tissue model. A single 10-min exposure to buffered saline containing acrolein significantly induced oxidative stress and inflammatory responses, with changes in protein oxidation and GSH depletion occurring immediately after the treatment whereas responses in inflammation requiring a manifestation time of at least 24 h. Repeated exposure to acrolein for 10 consecutive days resulted in structural and functional changes that recapitulate the pathological lesions of COPD, including alterations in the beating frequency and structures of ciliated cells, inhibition of mucin expression and secretion apparatus, and development of squamous differentiation. Although some of the early responses caused by acrolein exposure were reversible after a 10-day recovery, perturbations in the functions and structures of the air-liquid-interface (ALI) cultures, such as mucin production, cilia structures, and morphological changes, failed to fully recover over the observation period. Taken together, these findings are consistent with its mode of action that oxidative stress and inflammation have fundamental roles in acrolein-induced tissue remodeling. Furthermore, these data demonstrate the usefulness of analytical methods and testing strategy for recapitulating the key events in acrolein toxicity using an in vitro model.

The association between chemical-induced porphyria and hepatic cancer

The haem biosynthetic pathway is of fundamental importance for cellular metabolism both for the erythroid and nonerythroid tissues. There are several genetic variants of the pathway in the human population that cause dysfunction of one or other of the enzymes resulting in porphyrias of varying severity. Serious chronic hepatic and systemic diseases may result. Some of these can be precipitated by exposure to drugs including hormones, barbiturates and antibiotics, as well as alcohol and particular chlorinated aromatic chemicals. In experimental animals some of the steps of this pathway can also be severely disrupted by a variety of environmental chemicals, potential drugs and pesticides, especially in the liver, leading to the accumulation of uroporphyrins derived from the intermediate uroporphyrinogens or protoporphyrin IX, the immediate precursor of haem. With some of these chemicals this also leads to cholestasis and liver cell injury and eventually hepatic tumours. The review evaluates the available evidence linking hepatic porphyria with carcinogenesis in naturally occurring human genetic conditions and in chemically-induced porphyrias in laboratory animals. The existing data showing gender, strain, and species differences in sensitivity to the chemical-induced porphyrias, liver injury and liver tumours are discussed and the role that transgenically altered mouse models have played in defining the varying mechanisms. Finally, the review proposes a novel, unifying hypothesis linking the hepatotoxicity induced by the accumulation of various porphyrins, with the increased risk of developing hepatic cancer as a long term consequence.

The PPARα-dependent rodent liver tumor response is not relevant to humans: addressing misconceptions

A number of industrial chemicals and therapeutic agents cause liver tumors in rats and mice by activating the nuclear receptor peroxisome proliferator-activated receptor α (PPARα). The molecular and cellular events by which PPARα activators induce rodent hepatocarcinogenesis have been extensively studied elucidating a number of consistent mechanistic changes linked to the increased incidence of liver neoplasms. The weight of evidence relevant to the hypothesized mode of action (MOA) for PPARα activator-induced rodent hepatocarcinogenesis is summarized here. Chemical-specific and mechanistic data support concordance of temporal and dose-response relationships for the key events associated with many PPARα activators. The key events (KE) identified in the MOA are PPARα activation (KE1), alteration in cell growth pathways (KE2), perturbation of hepatocyte growth and survival (KE3), and selective clonal expansion of preneoplastic foci cells (KE4), which leads to the apical event-increases in hepatocellular adenomas and carcinomas (KE5). In addition, a number of concurrent molecular and cellular events have been classified as modulating factors, because they potentially alter the ability of PPARα activators to increase rodent liver cancer while not being key events themselves. These modulating factors include increases in oxidative stress and activation of NF-kB. PPARα activators are unlikely to induce liver tumors in humans due to biological differences in the response of KEs downstream of PPARα activation. This conclusion is based on minimal or no effects observed on cell growth pathways and hepatocellular proliferation in human primary hepatocytes and absence of alteration in growth pathways, hepatocyte proliferation, and tumors in the livers of species (hamsters, guinea pigs and cynomolgus monkeys) that are more appropriate human surrogates than mice and rats at overlapping dose levels. Despite this overwhelming body of evidence and almost universal acceptance of the PPARα MOA and lack of human relevance, several reviews have selectively focused on specific studies that, as discussed, contradict the consensus opinion and suggest uncertainty. In the present review, we systematically address these most germane suggested weaknesses of the PPARα MOA.

Next generation testing strategy for assessment of genomic damage: A conceptual framework and considerations

For several decades, regulatory testing schemes for genetic damage have been standardized where the tests being utilized examined mutations and structural and numerical chromosomal damage. This has served the genetic toxicity community well when most of the substances being tested were amenable to such assays. The outcome from this testing is usually a dichotomous (yes/no) evaluation of test results, and in many instances, the information is only used to determine whether a substance has carcinogenic potential or not. Over the same time period, mechanisms and modes of action (MOAs) that elucidate a wider range of genomic damage involved in many adverse health outcomes have been recognized. In addition, a paradigm shift in applied genetic toxicology is moving the field toward a more quantitative dose-response analysis and point-of-departure (PoD) determination with a focus on risks to exposed humans. This is directing emphasis on genomic damage that is likely to induce changes associated with a variety of adverse health outcomes. This paradigm shift is moving the testing emphasis for genetic damage from a hazard identification only evaluation to a more comprehensive risk assessment approach that provides more insightful information for decision makers regarding the potential risk of genetic damage to exposed humans. To enable this broader context for examining genetic damage, a next generation testing strategy needs to take into account a broader, more flexible approach to testing, and ultimately modeling, of genomic damage as it relates to human exposure. This is consistent with the larger risk assessment context being used in regulatory decision making. As presented here, this flexible approach for examining genomic damage focuses on testing for relevant genomic effects that can be, as best as possible, associated with an adverse health effect. The most desired linkage for risk to humans would be changes in loci associated with human diseases, whether in somatic or germ cells. The outline of a flexible approach and associated considerations are presented in a series of nine steps, some of which can occur in parallel, which was developed through a collaborative effort by leading genetic toxicologists from academia, government, and industry through the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC). The ultimate goal is to provide quantitative data to model the potential risk levels of substances, which induce genomic damage contributing to human adverse health outcomes. Any good risk assessment begins with asking the appropriate risk management questions in a planning and scoping effort. This step sets up the problem to be addressed (e.g., broadly, does genomic damage need to be addressed, and if so, how to proceed). The next two steps assemble what is known about the problem by building a knowledge base about the substance of concern and developing a rational biological argument for why testing for genomic damage is needed or not. By focusing on the risk management problem and potential genomic damage of concern, the next step of assay(s) selection takes place. The work-up of the problem during the earlier steps provides the insight to which assays would most likely produce the most meaningful data. This discussion does not detail the wide range of genomic damage tests available, but points to types of testing systems that can be very useful. Once the assays are performed and analyzed, the relevant data sets are selected for modeling potential risk. From this point on, the data are evaluated and modeled as they are for any other toxicology endpoint. Any observed genomic damage/effects (or genetic event(s)) can be modeled via a dose-response analysis and determination of an estimated PoD. When a quantitative risk analysis is needed for decision making, a parallel exposure assessment effort is performed (exposure assessment is not detailed here as this is not the focus of this discussion; guidelines for this assessment exist elsewhere). Then the PoD for genomic damage is used with the exposure information to develop risk estimations (e.g., using reference dose (RfD), margin of exposure (MOE) approaches) in a risk characterization and presented to risk managers for informing decision making. This approach is applicable now for incorporating genomic damage results into the decision-making process for assessing potential adverse outcomes in chemically exposed humans and is consistent with the ILSI HESI Risk Assessment in the 21st Century (RISK21) roadmap. This applies to any substance to which humans are exposed, including pharmaceuticals, agricultural products, food additives, and other chemicals. It is time for regulatory bodies to incorporate the broader knowledge and insights provided by genomic damage results into the assessments of risk to more fully understand the potential of adverse outcomes in chemically exposed humans, thus improving the assessment of risk due to genomic damage. The historical use of genomic damage data as a yes/no gateway for possible cancer risk has been too narrowly focused in risk assessment. The recent advances in assaying for and understanding genomic damage, including eventually epigenetic alterations, obviously add a greater wealth of information for determining potential risk to humans. Regulatory bodies need to embrace this paradigm shift from hazard identification to quantitative analysis and to incorporate the wider range of genomic damage in their assessments of risk to humans. The quantitative analyses and methodologies discussed here can be readily applied to genomic damage testing results now. Indeed, with the passage of the recent update to the Toxic Substances Control Act (TSCA) in the US, the new generation testing strategy for genomic damage described here provides a regulatory agency (here the US Environmental Protection Agency (EPA), but suitable for others) a golden opportunity to reexamine the way it addresses risk-based genomic damage testing (including hazard identification and exposure). Environ. Mol. Mutagen. 58:264-283, 2017. © 2016 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc.

Dose response models and a quantitative microbial risk assessment framework for the Mycobacterium avium complex that account for recent developments in molecular biology, taxonomy, and epidemiology

Mycobacterium avium complex (MAC) is a group of environmentally-transmitted pathogens of great public health importance. This group is known to be harbored, amplified, and selected for more human-virulent characteristics by amoeba species in aquatic biofilms. However, a quantitative microbial risk assessment (QMRA) has not been performed due to the lack of dose response models resulting from significant heterogeneity within even a single species or subspecies of MAC, as well as the range of human susceptibilities to mycobacterial disease. The primary human-relevant species and subspecies responsible for the majority of the human disease burden and present in drinking water, biofilms, and soil are M. avium subsp. hominissuis, M. intracellulare, and M. chimaera. A critical review of the published literature identified important health endpoints, exposure routes, and susceptible populations for MAC risk assessment. In addition, data sets for quantitative dose-response functions were extracted from published in vivo animal dosing experiments. As a result, seven new exponential dose response models for human-relevant species of MAC with endpoints of lung lesions, death, disseminated infection, liver infection, and lymph node lesions are proposed. Although current physical and biochemical tests used in clinical settings do not differentiate between M. avium and M. intracellulare, differentiating between environmental species and subspecies of the MAC can aid in the assessment of health risks and control of MAC sources. A framework is proposed for incorporating the proposed dose response models into susceptible population- and exposure route-specific QMRA models.

Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as 'Hepatocellular proliferation leading to cancer', were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

The role of dose rate in radiation cancer risk: evaluating the effect of dose rate at the molecular, cellular and tissue levels using key events in critical pathways following exposure to low LET radiation

PURPOSE

This review evaluates the role of dose rate on cell and molecular responses. It focuses on the influence of dose rate on key events in critical pathways in the development of cancer. This approach is similar to that used by the U.S. EPA and others to evaluate risk from chemicals. It provides a mechanistic method to account for the influence of the dose rate from low-LET radiation, especially in the low-dose region on cancer risk assessment. Molecular, cellular, and tissues changes are observed in many key events and change as a function of dose rate. The magnitude and direction of change can be used to help establish an appropriate dose rate effectiveness factor (DREF).

CONCLUSIONS

Extensive data on key events suggest that exposure to low dose-rates are less effective in producing changes than high dose rates. Most of these data at the molecular and cellular level support a large (2-30) DREF. In addition, some evidence suggests that doses delivered at a low dose rate decrease damage to levels below that observed in the controls. However, there are some data human and mechanistic data that support a dose-rate effectiveness factor of 1. In summary, a review of the available molecular, cellular and tissue data indicates that not only is dose rate an important variable in understanding radiation risk but it also supports the selection of a DREF greater than one as currently recommended by ICRP ( 2007 ) and BEIR VII (NRC/NAS 2006 ).

Key Elements for Judging the Quality of a Risk Assessment

BACKGROUND

Many reports have been published that contain recommendations for improving the quality, transparency, and usefulness of decision making for risk assessments prepared by agencies of the U.S. federal government. A substantial measure of consensus has emerged regarding the characteristics that high-quality assessments should possess.

OBJECTIVE

The goal was to summarize the key characteristics of a high-quality assessment as identified in the consensus-building process and to integrate them into a guide for use by decision makers, risk assessors, peer reviewers and other interested stakeholders to determine if an assessment meets the criteria for high quality.

DISCUSSION

Most of the features cited in the guide are applicable to any type of assessment, whether it encompasses one, two, or all four phases of the risk-assessment paradigm; whether it is qualitative or quantitative; and whether it is screening level or highly sophisticated and complex. Other features are tailored to specific elements of an assessment. Just as agencies at all levels of government are responsible for determining the effectiveness of their programs, so too should they determine the effectiveness of their assessments used in support of their regulatory decisions. Furthermore, if a nongovernmental entity wishes to have its assessments considered in the governmental regulatory decision-making process, then these assessments should be judged in the same rigorous manner and be held to similar standards.

CONCLUSIONS

The key characteristics of a high-quality assessment can be summarized and integrated into a guide for judging whether an assessment possesses the desired features of high quality, transparency, and usefulness.

CITATION

Fenner-Crisp PA, Dellarco VL. 2016. Key elements for judging the quality of a risk assessment. Environ Health Perspect 124:1127-1135; http://dx.doi.org/10.1289/ehp.1510483.

Benzo(a)pyrene Is Mutagenic in Mouse Spermatogonial Stem Cells and Dividing Spermatogonia

Although many environmental agents are established male germ cell mutagens, few are known to induce mutations in spermatogonial stem cells. Stem cell mutations are of great concern because they result in a permanent increase in the number of mutations carried in sperm. We investigated mutation induction during mouse spermatogenesis following exposure to benzo(a)pyrene (BaP). MutaMouse males were given 0, 12.5, 25, 50, or 100 mg/kg bw/day BaP for 28 days by oral gavage. Germ cells were collected from the cauda epididymis and seminiferous tubules 3 days after exposure and from cauda epididymis 42 and 70 days after exposure. This design enabled targeted investigation of effects on post-spermatogonia, dividing spermatogonia, and spermatogonial stem cells, respectively. BaP increased lacZ mutant frequency (MF) in cauda sperm after exposure of dividing spermatogonia (4.2-fold at highest dose, P < .01) and spermatogonial stem cells (2.1-fold at highest dose, P < .01). No significant increases in MF were detected in cauda sperm or seminiferous tubule cells collected 3 days post-exposure. Dose-response modelling suggested that the mutational response in male germ cells to BaP is sub-linear at low doses. Our results demonstrate that oral exposure to BaP causes spermatogonial stem cell mutations, that different phases of spermatogenesis exhibit varying sensitivities to BaP, with dividing spermatogonia representing a window of peak sensitivity, and that sampling spermatogenic cells from the seminiferous tubules at earlier time-points may underestimate germ cell mutagenicity. This information is critical to optimize the use of the international test guideline for transgenic rodent mutation assays for detecting germ cell mutagens.

Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity

Adverse outcome pathways (AOPs) are novel tools in toxicology and human risk assessment with broad potential. AOPs are designed to provide a clear-cut mechanistic representation of toxicological effects that span over different layers of biological organization. AOPs share a common structure consisting of a molecular initiating event, a series of key events connected by key event relationships, and an adverse outcome. Development and evaluation of AOPs ideally complies with guidelines issued by the Organization for Economic Cooperation and Development. AOP frameworks have yet been proposed for major types of drug-induced injury, especially in the liver, including steatosis, fibrosis, and cholestasis. These newly postulated AOPs can serve a number of purposes pertinent to safety assessment of drugs, in particular the establishment of quantitative structure-activity relationships, the development of novel in vitro toxicity screening tests, and the elaboration of prioritization strategies.

A proof-of-concept model for the identification of the key events in the infection process with specific reference to Pseudomonas aeruginosa in corneal infections

BACKGROUND

It is a common medical practice to characterise an infection based on the causative agent and to adopt therapeutic and prevention strategies targeting the agent itself. However, from an epidemiological perspective, exposure to a microbe can be harmless to a host as a result of low-level exposure or due to host immune response, with opportunistic infection only occurring as a result of changes in the host, pathogen, or surrounding environment.

METHODS

We have attempted to review systematically the key host, pathogen, and environmental factors that may significantly impact clinical outcomes of exposure to a pathogen, using Pseudomonas aeruginosa eye infection as a case study.

RESULTS AND DISCUSSION

Extended contact lens wearing and compromised hygiene may predispose users to microbial keratitis, which can be a severe and vision-threatening infection. P. aeruginosa has a wide array of virulence-associated genes and sensing systems to initiate and maintain cell populations at the corneal surface and beyond. We have adapted the well-known concept of the epidemiological triangle in combination with the classic risk assessment framework (hazard identification, characterisation, and exposure) to develop a conceptual pathway-based model that demonstrates the overlapping relationships between the host, the pathogen, and the environment; and to illustrate the key events in P. aeruginosa eye infection.

CONCLUSION

This strategy differs from traditional approaches that consider potential risk factors in isolation, and hopefully will aid the identification of data and models to inform preventive and therapeutic measures in addition to risk assessment. Furthermore, this may facilitate the identification of knowledge gaps to direct research in areas of greatest impact to avert or mitigate adverse outcomes of infection.

Modelling microbial health risk of wastewater reuse: A systems perspective

There is a widespread need for the use of quantitative microbial risk assessment (QMRA) to determine reclaimed water quality for specific uses, however neither faecal indicator levels nor pathogen concentrations alone are adequate for assessing exposure health risk. The aim of this study was to build a conceptual model representing factors contributing to the microbiological health risks of reusing water treated in maturation ponds. This paper describes the development of an unparameterised model that provides a visual representation of theoretical constructs and variables of interest. Information was collected from the peer-reviewed literature and through consultation with experts from regulatory authorities and academic disciplines. In this paper we explore how, considering microbial risk as a modular system, following the QMRA framework enables incorporation of the many factors influencing human exposure and dose response, to better characterise likely human health impacts. By using and expanding upon the QMRA framework we deliver new insights into this important field of environmental exposures. We present a conceptual model of health risk of microbial exposure which can be used for maturation ponds and, more importantly, as a generic tool to assess health risk in diverse wastewater reuse scenarios.

The adverse outcome pathway for rodent liver tumor promotion by sustained activation of the aryl hydrocarbon receptor

An Adverse Outcome Pathway (AOP) represents the existing knowledge of a biological pathway leading from initial molecular interactions of a toxicant and progressing through a series of key events (KEs), culminating with an apical adverse outcome (AO) that has to be of regulatory relevance. An AOP based on the mode of action (MOA) of rodent liver tumor promotion by dioxin-like compounds (DLCs) has been developed and the weight of evidence (WoE) of key event relationships (KERs) evaluated using evolved Bradford Hill considerations. Dioxins and DLCs are potent aryl hydrocarbon receptor (AHR) ligands that cause a range of species-specific adverse outcomes. The occurrence of KEs is necessary for inducing downstream biological responses and KEs may occur at the molecular, cellular, tissue and organ levels. The common convention is that an AOP begins with the toxicant interaction with a biological response element; for this AOP, this initial event is binding of a DLC ligand to the AHR. Data from mechanistic studies, lifetime bioassays and approximately thirty initiation-promotion studies have established dioxin and DLCs as rat liver tumor promoters. Such studies clearly show that sustained AHR activation, weeks or months in duration, is necessary to induce rodent liver tumor promotion--hence, sustained AHR activation is deemed the molecular initiating event (MIE). After this MIE, subsequent KEs are 1) changes in cellular growth homeostasis likely associated with expression changes in a number of genes and observed as development of hepatic foci and decreases in apoptosis within foci; 2) extensive liver toxicity observed as the constellation of effects called toxic hepatopathy; 3) cellular proliferation and hyperplasia in several hepatic cell types. This progression of KEs culminates in the AO, the development of hepatocellular adenomas and carcinomas and cholangiolar carcinomas. A rich data set provides both qualitative and quantitative knowledge of the progression of this AOP through KEs and the KERs. Thus, the WoE for this AOP is judged to be strong. Species-specific effects of dioxins and DLCs are well known--humans are less responsive than rodents and rodent species differ in sensitivity between strains. Consequently, application of this AOP to evaluate potential human health risks must take these differences into account.

Dose-response algorithms for water-borne Pseudomonas aeruginosa folliculitis

We developed two dose-response algorithms for P. aeruginosa pool folliculitis using bacterial and lesion density estimates, associated with undetectable, significant, and almost certain folliculitis. Literature data were fitted to Furumoto & Mickey's equations, developed for plant epidermis-invading pathogens: N l = A ln(1 + BC) (log-linear model); P inf = 1-e(-r c C) (exponential model), where A and B are 2.51644 × 107 lesions/m2 and 2.28011 × 10-11 c.f.u./ml P. aeruginosa, respectively; C = pathogen density (c.f.u./ml), N l = folliculitis lesions/m2, P inf = probability of infection, and r C = 4·3 × 10-7 c.f.u./ml P. aeruginosa. Outbreak data indicates these algorithms apply to exposure durations of 41 ± 25 min. Typical water quality benchmarks (≈10-2 c.f.u./ml) appear conservative but still useful as the literature indicated repeated detection likely implies unstable control barriers and bacterial bloom potential. In future, culture-based outbreak testing should be supplemented with quantitative polymerase chain reaction and organic carbon assays, and quantification of folliculitis aetiology to better understand P. aeruginosa risks.

Sublinear response in lacZ mutant frequency of Muta™ Mouse spermatogonial stem cells after low dose subchronic exposure to N-ethyl-N-nitrosourea

The transgenic rodent mutation assay was used to compare the dose-response relationship of lacZ mutant frequency (MF) in spermatogonial stem cells exposed acutely or subchronically to N-ethyl-N-nitrosourea (ENU). Muta(™) Mouse males were exposed orally to 0, 25, 50, or 100 mg/kg ENU for acute exposures and 0, 1, 2, or 5 mg/(kg day) for 28-day subchronic exposures. LacZ MF was measured in sperm collected 70 days post-exposure to target spermatogonial stem cells. Dose-response data were fit to linear, quadratic, exponential, or power models. Acute exposure resulted in a dose-dependent increase in MF that was significant (P < 0.05) at all doses tested and was best described by a quadratic dose-response model that was linear in the low dose range. In contrast, similar total doses fragmented over a 28-day subchronic exposure only resulted in a significant increase in lacZ MF at the highest dose tested. Therefore, the subchronic no observable genotoxic effect level (NOGEL) was 2 mg/(kg day) (or 56 mg/kg total dose). The subchronic dose-response was best described by the exponential and power models, which were sublinear in the low dose range. Benchmark dose lower confidence limits (BMDLs) for acute and subchronic exposure were 3.0 and 1.0 mg/(kg day) (or 27.4 mg/kg total dose), respectively. These findings are supportive of a saturable DNA repair mechanism as the mutagenic mode of action for ENU in spermatogonia and imply that sufficiently low exposures would not cause appreciable genotoxic effects over background. This may have important implications for the quantitative risk assessment of germ cell mutagens.

A 21st century roadmap for human health risk assessment

The Health and Environmental Sciences Institute (HESI)-coordinated Risk Assessment in the 21st Century (RISK21) project was initiated to develop a scientific, transparent, and efficient approach to the evolving world of human health risk assessment, and involved over 120 participants from 12 countries, 15 government institutions, 20 universities, 2 non-governmental organizations, and 12 corporations. This paper provides a brief overview of the tiered RISK21 framework called the roadmap and risk visualization matrix, and articulates the core principles derived by RISK21 participants that guided its development. Subsequent papers describe the roadmap and matrix in greater detail. RISK21 principles include focusing on problem formulation, utilizing existing information, starting with exposure assessment (rather than toxicity), and using a tiered process for data development. Bringing estimates of exposure and toxicity together on a two-dimensional matrix provides a clear rendition of human safety and risk. The value of the roadmap is its capacity to chronicle the stepwise acquisition of scientific information and display it in a clear and concise fashion. Furthermore, the tiered approach and transparent display of information will contribute to greater efficiencies by calling for data only as needed (enough precision to make a decision), thus conserving animals and other resources.

Proposing a scientific confidence framework to help support the application of adverse outcome pathways for regulatory purposes

An adverse outcome pathway (AOP) describes the causal linkage between initial molecular events and an adverse outcome at individual or population levels. Whilst there has been considerable momentum in AOP development, far less attention has been paid to how AOPs might be practically applied for different regulatory purposes. This paper proposes a scientific confidence framework (SCF) for evaluating and applying a given AOP for different regulatory purposes ranging from prioritizing chemicals for further evaluation, to hazard prediction, and ultimately, risk assessment. The framework is illustrated using three different AOPs for several typical regulatory applications. The AOPs chosen are ones that have been recently developed and/or published, namely those for estrogenic effects, skin sensitisation, and rodent liver tumor promotion. The examples confirm how critical the data-richness of an AOP is for driving its practical application. In terms of performing risk assessment, human dosimetry methods are necessary to inform meaningful comparisons with human exposures; dosimetry is applied to effect levels based on non-testing approaches and in vitro data. Such a comparison is presented in the form of an exposure:activity ratio (EAR) to interpret biological activity in the context of exposure and to provide a basis for product stewardship and regulatory decision making.

Microbial dose response modeling: past, present, and future

The understanding of the risk to humans from exposure to pathogens has been firmly put into a risk assessment framework. A key element of applying this approach is the understanding of the relationship between dose and response for particular pathogens. This understanding has progressed from early use of threshold concepts ("minimal infectious dose") thru multiple generations of models. Generation 1 models describe probability of response to exposed dose. Generation 2 models incorporate host factors (e.g., age) and/or pathogen factors (e.g., particle size of inhaled agents). Generation 3 models describe the rate at which effects develop, i.e. the epidemic curve. These (generation 1 through three models) have been developed and used in multiple contexts. Beyond Generation 3 lies an opportunity for the deep incorporation of in vivo physiological responses and the coupling of the individual host dynamics to the dynamics of spread of contagious diseases in the population. This would enable more direct extrapolation from controlled dosing studies to estimate population level effects. There remain also needs to understand broader categories of infectious agents, including pathogenic amoebae and fungi. More advanced models need to be validated against well-characterized human outbreak data.

Improving weight of evidence approaches to chemical evaluations

Federal and other regulatory agencies often use or claim to use a weight of evidence (WoE) approach in chemical evaluation. Their approaches to the use of WoE, however, differ significantly, rely heavily on subjective professional judgment, and merit improvement. We review uses of WoE approaches in key articles in the peer-reviewed scientific literature, and find significant variations. We find that a hypothesis-based WoE approach, developed by Lorenz Rhomberg et al., can provide a stronger scientific basis for chemical assessment while improving transparency and preserving the appropriate scope of professional judgment. Their approach, while still evolving, relies on the explicit specification of the hypothesized basis for using the information at hand to infer the ability of an agent to cause human health impacts or, more broadly, affect other endpoints of concern. We describe and endorse such a hypothesis-based WoE approach to chemical evaluation.

A survey of frameworks for best practices in weight-of-evidence analyses

The National Academy of Sciences (NAS) Review of the Environmental Protection Agency's Draft IRIS Assessment of Formaldehyde proposed a "roadmap" for reform and improvement of the Agency's risk assessment process. Specifically, it called for development of a transparent and defensible methodology for weight-of-evidence (WoE) assessments. To facilitate development of an improved process, we developed a white paper that reviewed approximately 50 existing WoE frameworks, seeking insights from their variations and nominating best practices for WoE analyses of causation of chemical risks. Four phases of WoE analysis were identified and evaluated in each framework: (1) defining the causal question and developing criteria for study selection, (2) developing and applying criteria for review of individual studies, (3) evaluating and integrating evidence and (4) drawing conclusions based on inferences. We circulated the draft white paper to stakeholders and then held a facilitated, multi-disciplinary invited stakeholder workshop to broaden and deepen the discussion on methods, rationales, utility and limitations among the surveyed WoE frameworks. The workshop developed recommendations for improving the conduct of WoE evaluations. Based on the analysis of the 50 frameworks and discussions at the workshop, best practices in conducting WoE analyses were identified for each of the four phases. Many of these best practices noted from the analysis and workshop could be implemented immediately, while others may require additional refinement as part of the ongoing discussions for improving the scientific basis of chemical risk assessments.

Modeling inoculum dose dependent patterns of acute virus infections

Inoculum dose, i.e. the number of pathogens at the beginning of an infection, often affects key aspects of pathogen and immune response dynamics. These in turn determine clinically relevant outcomes, such as morbidity and mortality. Despite the general recognition that inoculum dose is an important component of infection outcomes, we currently do not understand its impact in much detail. This study is intended to start filling this knowledge gap by analyzing inoculum dependent patterns of viral load dynamics in acute infections. Using experimental data for adenovirus and infectious bronchitis virus infections as examples, we demonstrate inoculum dose dependent patterns of virus dynamics. We analyze the data with the help of mathematical models to investigate what mechanisms can reproduce the patterns observed in experimental data. We find that models including components of both the innate and adaptive immune response are needed to reproduce the patterns found in the data. We further analyze which types of innate or adaptive immune response models agree with observed data. One interesting finding is that only models for the adaptive immune response that contain growth terms partially independent of viral load can properly reproduce observed patterns. This agrees with the idea that an antigen-independent, programmed response is part of the adaptive response. Our analysis provides useful insights into the types of model structures that are required to properly reproduce observed virus dynamics for varying inoculum doses. We suggest that such models should be taken as basis for future models of acute viral infections.

Pseudomonas aeruginosadose response and bathing water infection

Pseudomonas aeruginosais the opportunistic pathogen mostly implicated in folliculitis and acute otitis externa in pools and hot tubs. Nevertheless, infection risks remain poorly quantified. This paper reviews disease aetiologies and bacterial skin colonization science to advance dose-response theory development. Three model forms are identified for predicting disease likelihood from pathogen density. Two are based on Furumoto & Mickey's exponential ‘single-hit’ model and predict infection likelihood and severity (lesions/m2), respectively. ‘Third-generation’, mechanistic, dose-response algorithm development is additionally scoped. The proposed formulation integrates dispersion, epidermal interaction, and follicle invasion. The review also details uncertainties needing consideration which pertain to water quality, outbreaks, exposure time, infection sites, biofilms, cerumen, environmental factors (e.g. skin saturation, hydrodynamics), and whetherP. aeruginosais endogenous or exogenous. The review's findings are used to propose a conceptual infection model and identify research priorities including pool dose-response modelling, epidermis ecology and infection likelihood-based hygiene management.

Mode of action framework analysis for receptor-mediated toxicity: The peroxisome proliferator-activated receptor alpha (PPARα) as a case study

Several therapeutic agents and industrial chemicals induce liver tumors in rodents through the activation of the peroxisome proliferator-activated receptor alpha (PPARα). The cellular and molecular events by which PPARα activators induce rodent hepatocarcinogenesis has been extensively studied and elucidated. This review summarizes the weight of evidence relevant to the hypothesized mode of action (MOA) for PPARα activator-induced rodent hepatocarcinogenesis and identifies gaps in our knowledge of this MOA. Chemical-specific and mechanistic data support concordance of temporal and dose-response relationships for the key events associated with many PPARα activators including a phthalate ester plasticizer di(2-ethylhexyl) phthalate (DEHP) and the drug gemfibrozil. While biologically plausible in humans, the hypothesized key events in the rodent MOA, for PPARα activators, are unlikely to induce liver tumors in humans because of toxicodynamic and biological differences in responses. This conclusion is based on minimal or no effects observed on growth pathways, hepatocellular proliferation and liver tumors in humans and/or species (including hamsters, guinea pigs and cynomolgous monkeys) that are more appropriate human surrogates than mice and rats at overlapping dose levels. Overall, the panel concluded that significant quantitative differences in PPARα activator-induced effects related to liver cancer formation exist between rodents and humans. On the basis of these quantitative differences, most of the workgroup felt that the rodent MOA is "not relevant to humans" with the remaining members concluding that the MOA is "unlikely to be relevant to humans". The two groups differed in their level of confidence based on perceived limitations of the quantitative and mechanistic knowledge of the species differences, which for some panel members strongly supports but cannot preclude the absence of effects under unlikely exposure scenarios.

New developments in the evolution and application of the WHO/IPCS framework on mode of action/species concordance analysis

The World Health Organization/International Programme on Chemical Safety mode of action/human relevance framework has been updated to reflect the experience acquired in its application and extend its utility to emerging areas in toxicity testing and non-testing methods. The underlying principles have not changed, but the framework’s scope has been extended to enable integration of information at different levels of biological organization and reflect evolving experience in a much broader range of potential applications. Mode of action/species concordance analysis can also inform hypothesis-based data generation and research priorities in support of risk assessment.

The modified framework is incorporated within a roadmap, with feedback loops encouraging continuous refinement of fit-for-purpose testing strategies and risk assessment. Important in this construct is consideration of dose–response relationships and species concordance analysis in weight of evidence. The modified Bradford Hill considerations have been updated and additionally articulated to reflect increasing experience in application for cases where the toxicological outcome of chemical exposure is known.

The modified framework can be used as originally intended, where the toxicological effects of chemical exposure are known, or in hypothesizing effects resulting from chemical exposure, using information on putative key events in established modes of action from appropriate in vitro or in silico systems and other lines of evidence.

This modified mode of action framework and accompanying roadmap and case examples are expected to contribute to improving transparency in explicitly addressing weight of evidence considerations in mode of action/species concordance analysis based on both conventional data sources and evolving methods.