Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations.

Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented and artificial inteligence (AI) and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. We argue that collaborative efforts in data curation and storage, scientific computing, and training are of paramount importance to empower researchers within environmental sciences and the broader public health community to apply AI approaches and fully realize their potential. Leaders in the field were asked to prioritize challenges in incorporating big data in environmental public health research: inconsistent implementation of FAIR principles in data collection and sharing, a lack of skilled data scientists and appropriate cyber-infrastructures, and limited understanding of possibilities and communication of benefits were among those identified. These issues are discussed, and actionable recommendations are provided.

Physiologically Based Pharmacokinetic Modeling in Risk Assessment: Case Study With Pyrethroids.

The assessment of potentially sensitive populations is an important application of risk assessment. To address the concern for age-related sensitivity to pyrethroid insecticides, life-stage physiologically based pharmacokinetic (PBPK) modeling supported by in vitro to in vivo extrapolation was conducted to predict age-dependent changes in target tissue exposure to 8 pyrethroids. The purpose of this age-dependent dosimetry was to calculate a Data-derived Extrapolation Factor (DDEF) to address age-related pharmacokinetic differences for pyrethroids in humans. We developed a generic human PBPK model for pyrethroids based on our previously published rat model that was developed with in vivo rat data. The results demonstrated that the age-related differences in internal exposure to pyrethroids in the brain are largely determined by the differences in metabolic capacity and in physiology for pyrethroids between children and adults. The most important conclusion from our research is that, given an identical external exposure, the internal (target tissue) concentration is equal or lower in children than in adults in response to the same level of exposure to a pyrethroid. Our results show that, based on the use of the life-stage PBPK models with 8 pyrethroids, DDEF values are essentially close to 1, resulting in a DDEF for age-related pharmacokinetic differences of 1. For risk assessment purposes, this indicates that no additional adjustment factor is necessary to account for age-related pharmacokinetic differences for these pyrethroids.

Development and Application of a Life-Stage Physiologically Based Pharmacokinetic (PBPK) Model to the Assessment of Internal Dose of Pyrethroids in Humans.

To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.

A Time-Embedding Network Models the Ontogeny of 23 Hepatic Drug Metabolizing Enzymes.

Pediatric patients are at elevated risk of adverse drug reactions, and there is insufficient information on drug safety in children. Complicating risk assessment in children, there are numerous age-dependent changes in the absorption, distribution, metabolism, and elimination of drugs. A key contributor to age-dependent drug toxicity risk is the ontogeny of drug metabolism enzymes, the changes in both abundance and type throughout development from the fetal period through adulthood. Critically, these changes affect not only the overall clearance of drugs but also exposure to individual metabolites. In this study, we introduce time-embedding neural networks in order to model population-level variation in metabolism enzyme expression as a function of age. We use a time-embedding network to model the ontogeny of 23 drug metabolism enzymes. The time-embedding network recapitulates known demographic factors impacting 3A5 expression. The time-embedding network also effectively models the nonlinear dynamics of 2D6 expression, enabling a better fit to clinical data than prior work. In contrast, a standard neural network fails to model these features of 3A5 and 2D6 expression. Finally, we combine the time-embedding model of ontogeny with additional information to estimate age-dependent changes in reactive metabolite exposure. This simple approach identifies age-dependent changes in exposure to valproic acid and dextromethorphan metabolites and suggests potential mechanisms of valproic acid toxicity. This approach may help researchers evaluate the risk of drug toxicity in pediatric populations.

Developmental Expression of the Cytosolic Sulfotransferases in Human Liver.

The liver is the predominant organ of metabolism for many endogenous and foreign chemicals. Cytosolic sulfotransferases (SULTs) catalyze the sulfonation of drugs and other xenobiotics, as well as hormones, neurotransmitters, and sterols, with consequences that include enhanced drug elimination, hormone inactivation, and procarcinogen bioactivation. SULTs are classified into six gene families, but only SULT1 and SULT2 enzymes are expressed in human liver. We characterized the developmental expression patterns of SULT1 and SULT2 mRNAs and proteins in human liver samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), RNA sequencing, and targeted quantitative proteomics. Using a set of prenatal, infant, and adult liver specimens, RT-qPCR analysis demonstrated that SULT1A1 (transcript variant 1) expression did not vary appreciably during development; SULT1C2, 1C4, and 1E1 mRNA levels were highest in prenatal and/or infant liver, and 1A2, 1B1, and 2A1 mRNA levels were highest in infant and/or adult. Hepatic SULT1A1 (transcript variant 5), 1C3, and 2B1 mRNA levels were low regardless of developmental stage. Results obtained with RNA sequencing of a different set of liver specimens (prenatal and pediatric) were generally comparable results to those of the RT-qPCR analysis, with the additional finding that SULT1A3 expression was highest during gestation. Analysis of SULT protein content in a library of human liver cytosols demonstrated that protein levels generally corresponded to the mRNAs, with the major exception that SULT1C4 protein levels were much lower than expected based on mRNA levels. These findings further support the concept that hepatic SULTs play important metabolic roles throughout the human life course, including early development.

A Chemical Category-Based Prioritization Approach for Selecting 75 Per- and Polyfluoroalkyl Substances (PFAS) for Tiered Toxicity and Toxicokinetic Testing.

Per- and polyfluoroalkyl substances (PFASs) are a group of fluorinated substances of interest to researchers, regulators, and the public due to their widespread presence in the environment. A few PFASs have comparatively extensive amounts of human epidemiological, exposure, and experimental animal toxicity data (e.g., perfluorooctanoic acid), whereas little toxicity and exposure information exists for much of the broader set of PFASs. Given that traditional approaches to generate toxicity information are resource intensive, new approach methods, including in vitro high-throughput toxicity (HTT) testing, are being employed to inform PFAS hazard characterization and further (in vivo) testing. The U.S. Environmental Protection Agency (EPA) and the National Toxicology Program (NTP) are collaborating to develop a risk-based approach for conducting PFAS toxicity testing to facilitate PFAS human health assessments. This article describes the construction of a PFAS screening library and the process by which a targeted subset of 75 PFASs were selected. Multiple factors were considered, including interest to the U.S. EPA, compounds within targeted categories, structural diversity, exposure considerations, procurability and testability, and availability of existing toxicity data. Generating targeted HTT data for PFASs represents a new frontier for informing priority setting. https://doi.org/10.1289/EHP4555.

The Impact of Scaling Factor Variability on Risk-Relevant Pharmacokinetic Outcomes in Children: A Case Study Using Bromodichloromethane (BDCM).

Biotransformation rates extrapolated from in vitro data are used increasingly in human physiologically based pharmacokinetic (PBPK) models. This practice requires use of scaling factors, including microsomal content (mg of microsomal protein/g liver, MPPGL), enzyme specific content, and liver mass as a fraction of body weight (FVL). Previous analyses indicated that scaling factor variability impacts pharmacokinetic (PK) outcomes used in adult population dose-response studies. This analysis was extended to pediatric populations because large inter-individual differences in enzyme ontogeny likely would further contribute to scaling factor variability. An adult bromodichloromethane (BDCM) model (Kenyon, E. M., Eklund, C., Leavens, T. L., and Pegram, R. A. (2016a). Development and application of a human PBPK model for bromodichloromethane (BDCM) to investigate impacts of multi-route exposure. J. Appl. Toxicol. 36, 1095-1111) was re-parameterized for neonates, infants, and toddlers. Monte Carlo analysis was used to assess the impact of pediatric scaling factor variation on model-derived PK outcomes compared with adult findings. BDCM dose metrics were estimated following a single 0.05-liter drink of water or a 20-min bath, under typical (5 µg/l) and plausible higher (20 µg/l) BDCM concentrations. MPPGL, CYP2E1, and FVL values reflected the distribution of reported pediatric population values. The impact of scaling factor variability on PK outcome variation was different for each exposure scenario, but similar for each BDCM water concentration. The higher CYP2E1 expression variability during early childhood was reflected in greater variability in predicted PK outcomes in younger age groups, particularly for the oral exposure route. Sensitivity analysis confirmed the most influential parameter for this variability was CYP2E1, particularly in neonates. These findings demonstrate the importance of age-dependent scaling factor variation used for in vitro to in vivo extrapolation of biotransformation rates.

Determination of Human Hepatic CYP2C8 and CYP1A2 Age-Dependent Expression to Support Human Health Risk Assessment for Early Ages.

Predicting age-specific metabolism is important for evaluating age-related drug and chemical sensitivity. Multiple cytochrome P450s and carboxylesterase enzymes are responsible for human pyrethroid metabolism. Complete ontogeny data for each enzyme are needed to support in vitro to in vivo extrapolation (IVIVE). This study was designed to determine age-dependent human hepatic CYP2C8 expression, for which only limited ontogeny data are available, and to further define CYP1A2 ontogeny. CYP2C8 and 1A2 protein levels were measured by quantitative Western blotting using liver microsomal samples prepared from 222 subjects with ages ranging from 8 weeks gestation to 18 years after birth. The median CYP2C8 expression was significantly greater among samples from subjects older than 35 postnatal days (n = 122) compared with fetal samples and those from very young infants (fetal to 35 days postnatal, n = 100) (0.00 vs. 13.38 pmol/mg microsomal protein; p < 0.0001). In contrast, the median CYP1A2 expression was significantly greater after 15 months postnatal age (n = 55) than in fetal and younger postnatal samples (fetal to 15 months postnatal, n = 167) (0.0167 vs. 2.354 pmol/mg microsomal protein; p < 0.0001). CYP2C8, but not CYP1A2, protein levels significantly correlated with those of CYP2C9, CYP2C19, and CYP3A4 (p < 0.001), consistent with CYP2C8 and CYP1A2 ontogeny probably being controlled by different mechanisms. This study provides key data for the physiologically based pharmacokinetic model-based prediction of age-dependent pyrethroid metabolism, which will be used for IVIVE to support pyrethroid risk assessment for early life stages.

Application of epigenetic data in human health risk assessment.

Despite the many recent advances in the field of epigenetics, application of this knowledge in environmental health risk assessment has been limited. In this paper, we identify opportunities for application of epigenetic data to support health risk assessment. We consider current applications and present a vision for the future.

FutureTox III: Bridges for Translation.

Future Tox III, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2015. Building upon Future Tox I and II, Future Tox III was focused on developing the high throughput risk assessment paradigm and taking the science of in vitro data and in silico models forward to explore the question-what progress is being made to address challenges in implementing the emerging big-data toolbox for risk assessment and regulatory decision-making. This article reports on the outcome of the workshop including 2 examples of where advancements in predictive toxicology approaches are being applied within Federal agencies, where opportunities remain within the exposome and AOP domains, and how collectively the toxicology community across multiple sectors can continue to bridge the translation from historical approaches to Tox21 implementation relative to risk assessment and regulatory decision-making.

Prediction of Warfarin Dose in Pediatric Patients: An Evaluation of the Predictive Performance of Several Models.

OBJECTIVES: The objective of this study was to evaluate the performance of pediatric pharmacogenetic-based dose prediction models by using an independent cohort of pediatric patients from a multicenter trial. METHODS: Clinical and genetic data (CYP2C9 [cytochrome P450 2C9] and VKORC1 [vitamin K epoxide reductase]) were collected from pediatric patients aged 3 months to 17 years who were receiving warfarin as part of standard care at 3 separate clinical sites. The accuracy of 8 previously published pediatric pharmacogenetic-based dose models was evaluated in the validation cohort by comparing predicted maintenance doses to actual stable warfarin doses. The predictive ability was assessed by using the proportion of variance (R(2)), mean prediction error (MPE), and the percentage of predictions that fell within 20% of the actual maintenance dose. RESULTS: Thirty-two children reached a stable international normalized ratio and were included in the validation cohort. The pharmacogenetic-based warfarin dose models showed a proportion of variance ranging from 35% to 78% and an MPE ranging from -2.67 to 0.85 mg/day in the validation cohort. Overall, the model developed by Hamberg et al showed the best performance in the validation cohort (R(2) = 78%; MPE = 0.15 mg/day) with 38% of the predictions falling within 20% of observed doses. CONCLUSIONS: Pharmacogenetic-based algorithms provide better predictions than a fixed-dose approach, although an optimal dose algorithm has not yet been developed.

Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards.

A computational framework was developed to assist in screening and prioritizing chemicals based on their dosimetry, toxicity, and potential exposures. The overall strategy started with contextualizing chemical activity observed in high-throughput toxicity screening (HTS) by mapping these assays to biological events described in Adverse Outcome Pathways (AOPs). Next, in vitro to in vivo (IVIVE) extrapolation was used to convert an in vitro dose to an external exposure level, which was compared with potential exposure levels to derive an AOP-based margins of exposure (MOE). In this study, the framework was applied to estimate MOEs for chemicals that can potentially cause developmental toxicity following a putative AOP for fetal vasculogenesis/angiogenesis. A physiologically based pharmacokinetic (PBPK) model was developed to describe chemical disposition during pregnancy, fetal, neonatal, and infant to adulthood stages. Using this life-stage PBPK model, maternal exposures were estimated that would yield fetal blood levels equivalent to the chemical concentration that altered in vitro activity of selected HTS assays related to the most sensitive vasculogenesis/angiogenesis putative AOP. The resulting maternal exposure estimates were then compared with potential exposure levels using literature data or exposure models to derive AOP-based MOEs.

Expression Patterns of Organic Anion Transporting Polypeptides 1B1 and 1B3 Protein in Human Pediatric Liver.

Determining appropriate pharmacotherapy in young children can be challenging due to uncertainties in the development of drug disposition pathways. With knowledge of the ontogeny of drug-metabolizing enzymes and an emerging focus on drug transporters, the developmental pattern of the uptake transporters organic anion transporting polypeptide (OATP) 1B1 and 1B3 was assessed by relative protein quantification using Western blotting in 80 human pediatric liver specimens covering an age range from 9 days to 12 years. OATP1B3 exhibited high expression at birth, which declined over the first months of life, and then increased again in the preadolescent period. In comparison with children 6-12 years of age, the relative protein expression of highly glycosylated (total) OATP1B3 was 235% (357%) in children <3 months of age, 33% (64%) in the age group from 3 months to 2 years, and 50% (59%) in children 2-6 years of age. The fraction of highly glycosylated to total OATP1B3 increased with age, indicating ontogenic processes not only at the transcriptional level but also at the post-translational level. Similar to OATP1B3, OATP1B1 showed high interindividual variability in relative protein expression but no statistically significant difference among the studied age groups.

Role of Chromatin Structural Changes in Regulating Human CYP3A Ontogeny.

Variability in drug-metabolizing enzyme developmental trajectories contributes to interindividual differences in susceptibility to chemical toxicity and adverse drug reactions, particularly in the first years of life. Factors linked to these interindividual differences are largely unknown, but molecular mechanisms regulating ontogeny are likely involved. To evaluate chromatin structure dynamics as a likely contributing mechanism, age-dependent changes in modified and variant histone occupancy were evaluated within known CYP3A4 and 3A7 regulatory domains. Chromatin immunoprecipitation using fetal or postnatal human hepatocyte chromatin pools followed by quantitative polymerase chain reaction DNA amplification was used to determine relative chromatin occupancy by modified and variant histones. Chromatin structure representing a poised transcriptional state (bivalent chromatin), indicated by the occupancy by modified histones associated with both active and repressed transcription, was observed for CYP3A4 and most 3A7 regulatory regions in both postnatal and fetal livers. However, the CYP3A4 regulatory regions had significantly greater occupancy by modified histones associated with repressed transcription in the fetal liver. Conversely, some modified histones associated with active transcription exhibited greater occupancy in the postnatal liver. CYP3A7 regulatory regions also had significantly greater occupancy by modified histones associated with repressed transcription in the fetus. The observed occupancy by modified histones is consistent with chromatin structural dynamics contributing to CYP3A4 ontogeny, although the data are less conclusive regarding CYP3A7. Interpretation of the latter data may be confounded by cell-type heterogeneity in the fetal liver.

Age-Dependent Human Hepatic Carboxylesterase 1 (CES1) and Carboxylesterase 2 (CES2) Postnatal Ontogeny.

Human hepatic carboxylesterase 1 and 2 (CES1 and CES2) are important for the disposition of ester- and amide-bond-containing pharmaceuticals and environmental chemicals. CES1 and CES2 ontogeny has not been well characterized, causing difficulty in addressing concerns regarding juvenile sensitivity to adverse outcomes associated with exposure to certain substrates. To characterize postnatal human hepatic CES1 and CES2 expression, microsomal and cytosolic fractions were prepared using liver samples from subjects without liver disease (N = 165, aged 1 day to 18 years). Proteins were fractionated, detected, and quantitated by Western blotting. Median microsomal CES1 was lower among samples from subjects younger than 3 weeks (n = 36) compared with the rest of the population (n = 126; 6.27 vs. 17.5 pmol/mg microsomal protein, respectively; P < 0.001; Kruskal-Wallis test). Median cytosolic CES1 expression was lowest among samples from individuals between birth and 3 weeks of age (n = 36), markedly greater among those aged 3 weeks to 6 years (n = 90), and modestly greater still among those older than 6 years (n = 36; median values = 4.7, 15.8, and 16.6 pmol/mg cytosolic protein, respectively; P values < 0.001 and 0.05, respectively; Kruskal-Wallis test). Median microsomal CES2 expression increased across the same three age groups with median values of 1.8, 2.9, and 4.2 pmol/mg microsomal protein, respectively (P < 0.001, both). For cytosolic CES2, only the youngest age group differed from the two older groups (P < 0.001; median values = 1.29, 1.93, 2.0, respectively). These data suggest that infants younger than 3 weeks of age would exhibit significantly lower CES1- and CES2-dependent metabolic clearance compared with older individuals.

Baseline Chromatin Modification Levels May Predict Interindividual Variability in Ozone-Induced Gene Expression.

Traditional toxicological paradigms have relied on factors such as age, genotype, and disease status to explain variability in responsiveness to toxicant exposure; however, these are neither sufficient to faithfully identify differentially responsive individuals nor are they modifiable factors that can be leveraged to mitigate the exposure effects. Unlike these factors, the epigenome is dynamic and shaped by an individual's environment. We sought to determine whether baseline levels of specific chromatin modifications correlated with the interindividual variability in their ozone (O3)-mediated induction in an air-liquid interface model using primary human bronchial epithelial cells from a panel of 11 donors. We characterized the relationship between the baseline abundance of 6 epigenetic markers with established roles as key regulators of gene expression-histone H3 lysine 4 trimethylation (H3K4me3), H3K27 acetylation (H3K27ac), pan-acetyl H4 (H4ac), histone H3K27 di/trimethylation (H3K27me2/3), unmodified H3, and 5-hydroxymethylcytosine (5-hmC)-and the variability in the O3-induced expression of IL-8, IL-6, COX2, and HMOX1. Baseline levels of H3K4me3, H3K27me2/3, and 5-hmC, but not H3K27ac, H4ac, and total H3, correlated with the interindividual variability in O3-mediated induction of HMOX1 and COX2. In contrast, none of the chromatin modifications that we examined correlated with the induction of IL-8 and IL-6. From these findings, we propose an "epigenetic seed and soil" model in which chromatin modification states between individuals differ in the relative abundance of specific modifications (the "soil") that govern how receptive the gene is to toxicant-mediated cellular signals (the "seed") and thus regulate the magnitude of exposure-related gene induction.

Use of the RISK21 roadmap and matrix: human health risk assessment of the use of a pyrethroid in bed netting.

The HESI-coordinated RISK21 roadmap and matrix are tools that provide a transparent method to compare exposure and toxicity information and assess whether additional refinement is required to obtain the necessary precision level for a decision regarding safety. A case study of the use of a pyrethroid, "pseudomethrin," in bed netting to control malaria is presented to demonstrate the application of the roadmap and matrix. The evaluation began with a problem formulation step. The first assessment utilized existing information pertaining to the use and the class of chemistry. At each stage of the step-wise approach, the precision of the toxicity and exposure estimates were refined as necessary by obtaining key data which enabled a decision on safety to be made efficiently and with confidence. The evaluation demonstrated the concept of using existing information within the RISK21 matrix to drive the generation of additional data using a value-of-information approach. The use of the matrix highlighted whether exposure or toxicity required further investigation and emphasized the need to address the default uncertainty factor of 100 at the highest tier of the evaluation. It also showed how new methodology such as the use of in vitro studies and assays could be used to answer the specific questions which arise through the use of the matrix. The matrix also serves as a useful means to communicate progress to stakeholders during an assessment of chemical use.

Ontogeny of plasma proteins, albumin and binding of diazepam, cyclosporine, and deltamethrin.

BACKGROUND: To characterize the ontogeny of plasma albumin and total proteins, due to the lack of a comprehensive pediatric database. Secondly, to establish the magnitude and duration of maturational changes in binding of highly-bound drugs/chemicals. METHODS: Anonymized plasma samples from 296 donors were pooled in 6 age brackets from birth to adolescence. Total protein and albumin levels were measured in each age group, as was the age-dependency of plasma binding of diazepam (DZP), cyclosporine (CYC), and deltamethrin (DLM), a pyrethroid insecticide. RESULTS: Plasma levels of albumin and total proteins steadily increased for the first 1-3 y of life. Unbound DZP and CYC fractions were elevated three- to fourfold in neonates, but decreased to adult levels after 1 and 3 y, respectively. Unbound DLM levels exceeded those in adults for just 1 mo. CONCLUSION: Neonates and infants under 1-3 y may be at risk from increased amounts of free drug, when given standard doses of some highly-bound drugs. Pyrethroid insecticides might be anticipated to pose increased risk for 1 mo.

Oxidative stress-responsive transcription factor NRF2 is not indispensable for the human hepatic Flavin-containing monooxygenase-3 (FMO3) gene expression in HepG2 cells.

The flavin-containing monooxygenases (FMOs) are important for the oxidation of a variety of endogenous compounds and xenobiotics. The hepatic expression of FMO3 is highly variable and until recently, it was thought to be uninducible. In this study, human FMO3 gene regulation by the oxidative stress transcription factor, nuclear factor (erythroid-derived 2)-like 2 (NRF2) was examined. Constitutive FMO3 gene expression is repressed in HepG2 cells, thus this cell can be a good model for FMO3 gene regulation studies. Over-expression of NRF2 in HepG2 cells increased NRF2 target gene expression, heme oxygenase-1 (HMOX1) and NAD(P)H: quinone oxidoreductase-1 (NQO1), but did not alter FMO3 gene expression. Co-transfection studies with NRF2 or its cytosolic regulatory protein, Kelch-like ECH-associated protein 1 (KEAP1), expression vectors, along with FMO3 promoter luciferase reporter constructs of various lengths (5kb or 6kb), did not change FMO3 reporter gene activity significantly. Furthermore, treatment with tert-butyl hydroperoxide (tBHP) and tert-butyl hydroquinone (tBHQ) did not alter FMO3 reporter construct activity. In summary, in vitro results suggest that the transcriptional regulation of FMO3 might not involve the NRF2-KEAP1 regulatory pathway.

Raising the bar for reproducible science at the U.S. Environmental Protection Agency Office of Research and Development.

Considerable concern has been raised regarding research reproducibility both within and outside the scientific community. Several factors possibly contribute to a lack of reproducibility, including a failure to adequately employ statistical considerations during study design, bias in sample selection or subject recruitment, errors in developing data inclusion/exclusion criteria, and flawed statistical analysis. To address some of these issues, several publishers have developed checklists that authors must complete. Others have either enhanced statistical expertise on existing editorial boards, or formed distinct statistics editorial boards. Although the U.S. Environmental Protection Agency, Office of Research and Development, already has a strong Quality Assurance Program, an initiative was undertaken to further strengthen statistics consideration and other factors in study design and also to ensure these same factors are evaluated during the review and approval of study protocols. To raise awareness of the importance of statistical issues and provide a forum for robust discussion, a Community of Practice for Statistics was formed in January 2014. In addition, three working groups were established to develop a series of questions or criteria that should be considered when designing or reviewing experimental, observational, or modeling focused research. This article describes the process used to develop these study design guidance documents, their contents, how they are being employed by the Agency's research enterprise, and expected benefits to Agency science. The process and guidance documents presented here may be of utility for any research enterprise interested in enhancing the reproducibility of its science.