Risk Assessment for Aflatoxin: II. Implications of Human Epidemiology Data

A review of epidemiology literature revealed that only studies conducted in Africa and Asia included data adequate to permit quantitative assessment of the dose-response relationship between aflatoxin exposure levels and liver cancer rates. Although these studies were judged adequate, their direct use to predict risks in U.S. populations may be questioned since hepatitis B virus (HBV) infections are far more common in the studied areas than in the U.S. Recent research indicates that, if aflatoxin contributes to the development of liver cancer, it almost always does so in the presence of HBV infection. The African/Asian data do not permit us to estimate the potency of aflatoxin in the absence of HBV. Recognizing this, these data can only be used to establish upper limits for the predicted excess lifetime risk for liver cancer in the U.S. When used in conjunction with aflatoxin exposure estimates for the Southeast U.S., these data predict a liver cancer rate, due to aflatoxin alone, far above that actually observed due to all causes; this provides an indication of the conservatism of this approach. Data from the Southeast U.S. may be used to estimate an excess lifetime risk for liver cancer of 2.17 x 10(-6) x (aflatoxin intake, ng/kg/day).     

Risk Assessment for Aflatoxin: An Evaluation Based on the Multistage Model

Lifetime cancer potency of alfatoxin was assessed based on the Yeh et al. study from China in which both aflatoxin exposure and hepatitis B prevalence were measured. This study provides the best available information for estimating the carcinogenic risk posed by aflatoxin to the U.S. population. Cancer potency of aflatoxin was estimated using a biologically motivated risk assessment model. The best estimate of aflatoxin potency was 9 (mg/kg/day)⁻¹ for individuals negative for hepatitis B and 230 (mg/kg/day)⁻¹ for individuals positive for hepatitis B.     

Risk Assessment for Aflatoxin: I. Metabolism of Aflatoxin B1 by Different Species

A comparison of the generation and detoxification of reactive aflatoxin B1 metabolites in different species may elucidate why animal species vary widely in sensitivity to aflatoxin B1 carcinogenicity, in addition to offering some perspective on how sensitive man may be to the carcinogenic effects of this mycotoxin. Scientific literature comparing the ability of cellular fractions from different species to metabolize aflatoxin B1 is reviewed. However, in vitro studies exclude components for multiple metabolic pathways, eliminating the possibility of competition between metabolic activation and detoxification. Quantification of metabolic activation by different species from these studies is therefore limited. The species-specific carcinogenic potency of aflatoxin B1 may be reflected in levels of aflatoxin B1-DNA adducts generated in vivo. The current paucity of quantitative information on human DNA adduct levels does not permit comparisons between different species on this basis.     

Expert Informants and Relative Risk: A Methodology for Modeling Waterways

This project describes a methodology for assessing relative risk along a transportation corridor utilizing waterborne transportation on the busiest port area in the world, the lower Mississippi River (from the mouth of Southwest Pass up through Baton Rouge, Louisiana). The paper calculates a relative risk scale, using data obtained from maritime experts, previous research, and existing databases. The research aggregates the vessel traffic data and geographic risk location data to produce relative risk scores for each mile along the River from the mouth of Southwest Pass to the termination of shipping at the U.S. 190 bridge across the River at Baton Rouge. This is done in a very simple and practical way for this initial model: (1) each vessel traveling the Mississippi is classified according to its risk potential for those miles that it passes in route to where it docks, and (2) points along the river are assigned a relative risk score based upon risk variables identified by expérts identified through a standard sampling procedure. The relative risk scores for river miles are combinations of these two factors.     

Physiologically Based Liver Modeling and Risk Assessment

Because of the inherent complexity of biological systems, there is often a choice between a number of apparently equally applicable physiologically based models to describe uptake and metabolism processes in toxicology or risk assessment. These models may fit the particular data sets of interest equally well, but may give quite different parameter estimates or predictions under different (extrapolated) conditions. Such competing models can be discriminated by a number of methods, including potential refutation by means of strategic experiments, and their ability to suitably incorporate all relevant physiological processes. For illustration, three currently used models for steady-state hepatic elimination--the venous equilibration model, the parallel tube model, and the distributed sinusoidal perfusion model--are reviewed and compared with particular reference to their application in the area of risk assessment. The ability of each of the models to describe and incorporate such physiological processes as protein binding, precursor-metabolite relations and hepatic zones of elimination, capillary recruitment, capillary heterogeneity, and intrahepatic shunting is discussed. Differences between the models in hepatic parameter estimation, extrapolation to different conditions, and interspecies scaling are discussed, and criteria for choosing one model over the others are presented. In this case, the distributed model provides the most general framework for describing physiological processes taking place in the liver, and has so far not been experimentally refuted, as have the other two models. These simpler models may, however, provide useful bounds on parameter estimates and on extrapolations and risk assessments.     

Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels

Urban road tunnels provide an increasingly cost‐effective engineering solution, especially in compact cities like Singapore. For some urban road tunnels, tunnel characteristics such as tunnel configurations, geometries, provisions of tunnel electrical and mechanical systems, traffic volumes, etc. may vary from one section to another. These urban road tunnels that have characterized nonuniform parameters are referred to as nonhomogeneous urban road tunnels. In this study, a novel quantitative risk assessment (QRA) model is proposed for nonhomogeneous urban road tunnels because the existing QRA models for road tunnels are inapplicable to assess the risks in these road tunnels. This model uses a tunnel segmentation principle whereby a nonhomogeneous urban road tunnel is divided into various homogenous sections. Individual risk for road tunnel sections as well as the integrated risk indices for the entire road tunnel is defined. The article then proceeds to develop a new QRA model for each of the homogeneous sections. Compared to the existing QRA models for road tunnels, this section‐based model incorporates one additional top event—toxic gases due to traffic congestion—and employs the Poisson regression method to estimate the vehicle accident frequencies of tunnel sections. This article further illustrates an aggregated QRA model for nonhomogeneous urban tunnels by integrating the section‐based QRA models. Finally, a case study in Singapore is carried out.     

Modeling Receptor-Mediated Processes with Dioxin: Implications for Pharmacokinetics and Risk Assessment

Dioxin (2,3,7,8-tetrachlorodibenzo- p -dioxin; TCDD), a widespread polychlorinated aromatic hydrocarbon, caused tumors in the liver and other sites when administered chronically to rats at doses as low as 0.01 μg/kg/day. It functions in combination with a cellular protein, the Ah receptor, to alter gene regulation, and this resulting modulation of gene expression is believed to be obligatory for both dioxin toxicity and carcinogenicity. The U.S. EPA is reevaluating its dioxin risk assessment and, as part of this process, will be developing risk assessment approaches for chemicals, such as dioxin, whose toxicity is receptor-mediated. This paper describes a receptor-mediated physiologically based pharmacokinetic (PB-PK) model for the tissue distribution and enzyme-inducing properties of dioxin and discusses the potential role of these models in a biologically motivated risk assessment. In this model, ternary interactions among the Ah receptor, dioxin, and DNA binding sites lead to enhanced production of specific hepatic proteins. The model was used to examine the tissue disposition of dioxin and the induction of both a dioxin-binding protein (presumably, cytochrome P4501A2), and cytochrome P4501A1. Tumor promotion correlated more closely with predicted induction of P4501A1 than with induction of hepatic binding proteins. Although increased induction of these proteins is not expected to be causally related to tumor formation, these physiological dosimetry and gene-induction response models will be important for biologically motivated dioxin risk assessments in determining both target tissue dose of dioxin and gene products and in examining the relationship between these gene products and the cellular events more directly involved in tumor promotion.     

Relative Risk Perception for Terrorism: Implications for Preparedness and Risk Communication

Terrorism presents a significant risk that is often approached at public policy, infrastructure, or emergency management level. Public perceptions of the likelihood of terrorist events, and how this may relate to individual preparedness, are not always extensively examined. The tendency to think that negative events are less likely to happen to oneself than to the average person is known as optimism bias. Optimism bias is relevant to perceptions of terrorism, because it is thought to be related to a reduction in precaution use. Using an online survey of 164 participants, this study aimed to determine whether Sydney residents thought they had a lower likelihood of experiencing terrorist events than other Australians. Significant optimism bias was observed for witnessing terrorist events, but not for personally experiencing terrorist events. In addition, Sydney residents tended to think that terrorist attacks were more likely to occur in Sydney than another major Australian city in the next five years. At the same time, household and workplace preparedness for terrorism was quite low, as was awareness of emergency strategies in the central business district. Perceptions of high likelihood of terrorism happening in one's own city, yet low preparedness present a challenge for risk communication and emergency management strategies. The diversity of possible terrorist targets, and the simple plans that can moderate the effects of a disaster may need to be emphasized in future anti‐terrorism initiatives.     

Mathematical Modeling of Reproductive and Developmental Toxic Effects for Quantitative Risk Assessment

A new mathematical dose-response model for reproductive and developmental risk assessment is proposed. The model includes the possibility of an exposure threshold as well as a litter-size effect. Correlation of responses of offspring from the same litter is taken into account through the use of the beta-binomial distribution. Confidence limits for low-dose extrapolation are based on the asymptotic distribution of the likelihood ratio. An empirical comparison of the proposed procedure to that of Rai and Van Ryzin demonstrates the improvement that can be achieved with the new procedure.     

基于风险视角的董事会相对权力与产品市场竞争力关系研究

利用2004~2012年928家深沪上市公司9年8 352个年度样本的大样本面板数据,从董事会治理风险的角度,验证了董事会相对管理层权力对公司产品市场竞争力的影响,检验了股权集中度和控股股东性质对两者关系的调节作用。研究发现,在不考虑股权集中度和控股股东性质的调节作用时,董事会相对权力同产品市场竞争力存在显著正相关关系;在考虑股权集中度和控股股东性质的情况下,股权集中度对董事会相对权力与公司产品市场竞争力之间关系有显著负向调节作用,控股股东性质对董事会相对权力与公司产品市场竞争力之间关系有显著负向调节作用。     

Probabilistic Modeling of Flood Hazard and its Risk Assessment for Eastern Region of India

This article models flood occurrence probabilistically and its risk assessment. It incorporates atmospheric parameters to forecast rainfall in an area. This measure of precipitation, together with river and ground parameters, serve as parameters in the model to predict runoff and subsequently inundation depth of an area. The inundation depth acts as a guide for predicting flood proneness and associated hazard. The vulnerability owing to flood has been analyzed as social vulnerability $(V_S)$, vulnerability to property $(V_P)$, and vulnerability to the location in terms of awareness $(V_A)$. The associated risk has been estimated for each area. The distribution of risk values can be used to classify every area into one of the six risk zones—namely, very low risk, low risk, moderately low risk, medium risk, high risk, and very high risk. The prioritization regarding preparedness, evacuation planning, or distribution of relief items should be guided by the range on the risk scale within which the area under study falls. The flood risk assessment model framework has been tested on a real‐life case study. The flood risk indices for each of the municipalities in the area under study have been calculated. The risk indices and hence the flood risk zone under which a municipality is expected to lie would alter every day. The appropriate authorities can then plan ahead in terms of preparedness to combat the impending flood situation in the most critical and vulnerable areas.     

An Interagency Comparison of Screening-Level Risk Assessment Approaches

Approaches to risk assessment have been shown to vary among regulatory agencies and across jurisdictional boundaries according to the different assumptions and justifications used. Approaches to screening-level risk assessment from six international agencies were applied to an urban case study focusing on benzo[a]pyrene (B[a]P) exposure and compared in order to provide insight into the differences between agency methods, assumptions, and justifications. Exposure estimates ranged four-fold, with most of the dose stemming from exposure to animal products (8-73%) and plant products (24-88%). Total cancer risk across agencies varied by two orders of magnitude, with exposure to air and plant and animal products contributing most to total cancer risk, while the air contribution showed the greatest variability (1-99%). Variability in cancer risk of 100-fold was attributed to choices of toxicological reference values (TRVs), either based on a combination of epidemiological and animal data, or on animal data. The contribution and importance of the urban exposure pathway for cancer risk varied according to the TRV and, ultimately, according to differences in risk assessment assumptions and guidance. While all agency risk assessment methods are predicated on science, the study results suggest that the largest impact on the differential assessment of risk by international agencies comes from policy and judgment, rather than science.     

Biological Models of Carcinogenesis and Quantitative Cancer Risk Assessment

Biologically-based models of carcinogenesis were originally developed to explain certain quanti-tative phenomena associated with carcinogenesis, and to provide a framework within which questions regarding the process could be addressed. Some limitations in the use of these models for quantitative cancer risk assessment are discussed.     

A Quantitative Microbial Risk Assessment Model for Legionnaires'' Disease: Animal Model Selection and Dose-Response Modeling

Legionnaires' disease (LD), first reported in 1976, is an atypical pneumonia caused by bacteria of the genus Legionella, and most frequently by L. pneumophila (Lp). Subsequent research on exposure to the organism employed various animal models, and with quantitative microbial risk assessment (QMRA) techniques, the animal model data may provide insights on human dose-response for LD. This article focuses on the rationale for selection of the guinea pig model, comparison of the dose-response model results, comparison of projected low-dose responses for guinea pigs, and risk estimates for humans. Based on both in vivo and in vitro comparisons, the guinea pig (Cavia porcellus) dose-response data were selected for modeling human risk. We completed dose-response modeling for the beta-Poisson (approximate and exact), exponential, probit, logistic, and Weibull models for Lp inhalation, mortality, and infection (end point elevated body temperature) in guinea pigs. For mechanistic reasons, including low-dose exposure probability, further work on human risk estimates for LD employed the exponential and beta-Poisson models. With an exposure of 10 colony-forming units (CFU) (retained dose), the QMRA model predicted a mild infection risk of 0.4 (as evaluated by seroprevalence) and a clinical severity LD case (e.g., hospitalization and supportive care) risk of 0.0009. The calculated rates based on estimated human exposures for outbreaks used for the QMRA model validation are within an order of magnitude of the reported LD rates. These validation results suggest the LD QMRA animal model selection, dose-response modeling, and extension to human risk projections were appropriate.     

Ecological Risk Assessment Framework for Low-Altitude Aircraft Overflights: I. Planning the Analysis and Estimating Exposure

An ecological risk assessment framework for low-altitude aircraft overflights was developed, with special emphasis on military applications. The problem formulation and exposure analysis phases are presented in this article; an analysis of effects and risk characterization is presented in a companion article. The intent of this article is threefold: (1) to illustrate the development of a generic framework for the ecological risk assessment of an activity, (2) to show how the U.S. Environmental Protection Agency's ecological risk assessment paradigm can be applied to an activity other than the release of a chemical, and (3) to provide guidance for the assessment of ecological risks from low-altitude aircraft overflights. The key stressor for low-altitude aircraft overflights is usually sound, although visual and physical (collision) stressors may also be significant. Susceptible and regulated wildlife populations are the major assessment endpoint entities, although plant communities may be impacted by takeoffs and landings. The exposure analysis utilizes measurements of wildlife locations, measurements of sound levels at the wildlife locations, measurements of slant distances from aircraft to wildlife, models that extrapolate sound from the source aircraft to the ground, and bird-strike probability models. Some of the challenges to conducting a risk assessment for aircraft overflights include prioritizing potential stressors and endpoints, choosing exposure metrics that relate to wildlife responses, obtaining good estimates of sound or distance, and estimating wildlife locations.     

Ecological Risk Assessment Framework for Low-Altitude Aircraft Overflights: II. Estimating Effects on Wildlife

An ecological risk assessment framework for aircraft overflights has been developed, with special emphasis on military applications. This article presents the analysis of effects and risk characterization phases; the problem formulation and exposure analysis phases are presented in a companion article. The framework addresses the effects of sound, visual stressors, and collision on the abundance and production of wildlife populations. Profiles of effects, including thresholds, are highlighted for two groups of endpoint species: ungulates (hoofed mammals) and pinnipeds (seals, sea lions, walruses). Several factors complicate the analysis of effects for aircraft overflights. Studies of the effects of aircraft overflights previously have not been associated with a quantitative assessment framework; therefore no consistent relations between exposure and population-level response have been developed. Information on behavioral effects of overflights by military aircraft (or component stressors) on most wildlife species is sparse. Moreover, models that relate behavioral changes to abundance or reproduction, and those that relate behavioral or hearing effects thresholds from one population to another are generally not available. The aggregation of sound frequencies, durations, and the view of the aircraft into the single exposure metric of slant distance is not always the best predictor of effects, but effects associated with more specific exposure metrics (e.g., narrow sound spectra) may not be easily determined or added. The weight of evidence and uncertainty analyses of the risk characterization for overflights are also discussed in this article.