Bioaccessibility of Fukushima‐Accident‐Derived Cs in Soils and the Contribution of Soil Ingestion to Radiation Doses in Children

Ingestion of contaminated soil is one potential internal exposure pathway in areas contaminated by the Fukushima Daiichi Nuclear Power Plant accident. Doses from this pathway can be overestimated if the availability of radioactive nuclides in soils for the gastrointestinal tract is not considered. The concept of bioaccessibility has been adopted to evaluate this availability based on in vitro tests. This study evaluated the bioaccessibility of radioactive cesium from soils via the physiologically‐based extraction test (PBET) and the extractability of those via an extraction test with 1 mol/L of hydrochloric acid (HCl). The bioaccessibility obtained in the PBET was 5.3% ± 1%, and the extractability in the tests with HCl was 16% ± 3%. The bioaccessibility was strongly correlated with the extractability. This result indicates the possibility that the extractability in HCl can be used as a good predictor of the bioaccessibility with PBET. In addition, we assessed the doses to children from the ingestion of soil via hand‐to‐mouth activity based on our PBET results using a probabilistic approach considering the spatial distribution of radioactive cesium in Date City in Fukushima Prefecture and the interindividual differences in the surveyed amounts of soil ingestion in Japan. The results of this assessment indicate that even if children were to routinely ingest a large amount of soil with relatively high contamination, the radiation doses from this pathway are negligible compared with doses from external exposure owing to deposited radionuclides in Fukushima Prefecture.     

Aldrin and Dieldrin: A Reevaluation of the Cancer and Noncancer Dose‐Response Assessments

The dose‐response analyses of cancer and noncancer health effects of aldrin and dieldrin were evaluated using current methodology, including benchmark dose analysis and the current U.S. Environmental Protection Agency (U.S. EPA) guidance on body weight scaling and uncertainty factors. A literature review was performed to determine the most appropriate adverse effect endpoints. Using current methodology and information, the estimated reference dose values were 0.0001 and 0.00008 mg/kg‐day for aldrin and dieldrin, respectively. The estimated cancer slope factors for aldrin and dieldrin were 3.4 and 7.0 (mg/kg‐day)^?1, respectively (i.e., about 5‐ and 2.3‐fold lower risk than the 1987 U.S. EPA assessments). Because aldrin and dieldrin are no longer used as pesticides in the United States, they are presumed to be a low priority for additional review by the U.S. EPA. However, because they are persistent and still detected in environmental samples, quantitative risk assessments based on the best available methods are required. Recent epidemiologic studies do not demonstrate a causal association between aldrin and dieldrin and human cancer risk. The proposed reevaluations suggest that these two compounds pose a lower human health risk than currently reported by the U.S. EPA.     

Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Distress for Quantal Responses

Increasingly, dose‐response data are being evaluated with the benchmark dose (BMD) approach rather than by the less precise no‐observed‐adverse‐effect‐level (NOAEL) approach. However, the basis for designing animal experiments, using equally sized dose groups, is still primed for the NOAEL approach. The major objective here was to assess the impact of using dose groups of unequal size on both the quality of the BMD and overall animal distress. We examined study designs with a total number of 200 animals distributed in four dose groups employing quantal data generated by Monte Carlo simulations. Placing more animals at doses close to the targeted BMD provided an estimate of BMD that was slightly better than the standard design with equally sized dose groups. In situations involving a clear dose‐response, this translates into fewer animals receiving high doses and thus less overall animal distress. Accordingly, in connection with risk and safety assessment, animal distress can potentially be reduced by distributing the animals appropriately between dose groups without decreasing the quality of the information obtained.     

Uncertainties in Biologically-Based Modeling of Formaldehyde-Induced Respiratory Cancer Risk: Identification of Key Issues

In a series of articles and a health-risk assessment report, scientists at the CIIT Hamner Institutes developed a model (CIIT model) for estimating respiratory cancer risk due to inhaled formaldehyde within a conceptual framework incorporating extensive mechanistic information and advanced computational methods at the toxicokinetic and toxicodynamic levels. Several regulatory bodies have utilized predictions from this model; on the other hand, upon detailed evaluation the California EPA has decided against doing so. In this article, we study the CIIT model to identify key biological and statistical uncertainties that need careful evaluation if such two-stage clonal expansion models are to be used for extrapolation of cancer risk from animal bioassays to human exposure. Broadly, these issues pertain to the use and interpretation of experimental labeling index and tumor data, the evaluation and biological interpretation of estimated parameters, and uncertainties in model specification, in particular that of initiated cells. We also identify key uncertainties in the scale-up of the CIIT model to humans, focusing on assumptions underlying model parameters for cell replication rates and formaldehyde-induced mutation. We discuss uncertainties in identifying parameter values in the model used to estimate and extrapolate DNA protein cross-link levels. The authors of the CIIT modeling endeavor characterized their human risk estimates as "conservative in the face of modeling uncertainties." The uncertainties discussed in this article indicate that such a claim is premature.     

Perspective: Risk Apportionment and Disease Intervention Strategies

The ultimate public health objective is the ability to predict and prevent disease, and not necessarily to identify an exhaustive list of potential disease risk factors. For any important public health outcome with multiple and potentially interrelated risk factors, an improved understanding of the contribution of individual and combinations of modifiable risk factors to the disease burden is essential for formulating an appropriate public health strategy. Partitioning techniques that divide the combined impact of multiple risk factors into exposure-specific components while taking into account the potential interrelations among those components, have been described in the epidemiological literature. In this article, we review and compare the available methods and options for such apportionment and apply them in a more general public health context as a method of selecting and prioritizing coronary heart disease (CHD) prevention strategies.     

Simultaneous confidence bands for Abbott-adjusted quantal response models in benchmark analysis

We study the use of a Scheffé-style simultaneous confidence band as applied to low-dose risk estimation with quantal response data. We consider two formulations for the dose-response risk function, an Abbott-adjusted Weibull model and an Abbott-adjusted log-logistic model. Using the simultaneous construction, we derive methods for estimating upper confidence limits on predicted extra risk and, by inverting the upper bands on risk, lower bounds on the benchmark dose, or BMD, at a specific level of ‘benchmark risk’. Monte Carlo evaluations explore the operating characteristics of the simultaneous limits.     

Statistical methods to evaluate health effects associated with major sources of air pollution: a case-study of breathing patterns during exposure to concentrated Boston air particles

Summary.  We conduct a case-study evaluating the source-specific effects of particulate matter on respiratory function. Using a structural equation approach, we assess the effect of different receptor models on the estimated source-specific effects for univariate respiratory response. Furthermore, we extend the structural equation model by placing a factor analysis model on the response to represent the measured respiratory responses in terms of underlying respiratory patterns. We estimate the particulate matter source-specific effects on respiratory rate, accentuated normal breathing and airway irritation and find a strong increase in airway irritation that is associated with exposure to motor vehicle particulate matter.     

On the multivariate predictive distribution of multi-dimensional effective dose: a Bayesian approach

We propose a Bayesian procedure to sample from the distribution of the multi-dimensional effective dose. This effective dose is the set of dose levels of multiple predictive factors that produce a binary response with a fixed probability.We apply our algorithms to parametric and semiparametric logistics regression models, respectively. The graphical display of random samples obtained through Markov chain Monte Carlo can provide some insight into the predictive distribution.     

Benzene Risk Estimation Using Radiation Equivalent Coefficients

We estimated benzene risk using a novel framework of risk assessment that employed the measurement of radiation dose equivalents to benzene metabolites and a PBPK model. The highest risks for 1 μg/m³ and 3.2 mg/m³ life time exposure of benzene estimated with a linear regression were 5.4 × 10⁻⁷ and 1.3 × 10⁻³, respectively. Even though these estimates were based on in vitro chromosome aberration test data, they were about one-sixth to one-fourteenth that from other studies and represent a fairly good estimate by using radiation equivalent coefficient as an "internal standard."     

论产品质量纠纷中供货者的责任

供货者处在产品流通过程的中间环节，不同于流通链条两端的生产者与销售者，在产品质量纠纷中具有特殊法律地位，为避免过多“内部求偿”之诉讼浪费，不必与生产者或销售者就产品缺陷损害承担连带责任，而应采取相对法定责任的模式。现行产品质量法关于供货者与销售者的规定含混不清，不利于消费者群体及各方合法权益的平衡，必须对供货者的责任分担作出具体明晰的规定。