总剂量辐照加固的功率VDMOS器件

采用先形成P-body区再生长栅氧化层的新工艺流程和薄栅氧化层配合Si3N4-SiO2钝化层加固工艺,研制出一种抗总剂量辐照加固功率VDMOS器件。给出了该器件的常态参数和总剂量辐照的实验数据,通过和二维数值仿真比较,表明实验数据和仿真数据能较好吻合。对研制的功率VDMOS器件在X射线模拟源辐照总剂量972×103rad(Si)下,阈值电压仅漂移?1V。结果证明,工艺改善了功率VDMOS器件的抗总剂量辐照能力。     

A Comparison of Three Methods for Calculating Confidence Intervals for the Benchmark Dose

Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.     

Quantitative Risk Assessment for Developmental Neurotoxic Effects

Developmental neurotoxicity concerns the adverse health effects of exogenous agents acting on neurodevelopment. Because human brain development is a delicate process involving many cellular events, the developing fetus is rather susceptible to compounds that can alter the structure and function of the brain. Today, there is clear evidence that early exposure to many neurotoxicants can severely damage the developing nervous system. Although in recent years, there has been much attention given to model development and risk assessment procedures for developmental toxicants, the area of developmental neurotoxicity has been largely ignored. Here, we consider the problem of risk estimation for developmental neurotoxicants from animal bioassay data. Since most responses from developmental neurotoxicity experiments are nonquantal in nature, an adverse health effect will be defined as a response that occurs with very small probability in unexposed animals. Using a two-stage hierarchical normal dose-response model, upper confidence limits on the excess risk due to a given level of added exposure are derived. Equivalently, the model is used to obtain lower confidence limits on dose for a small negligible level of risk. Our method is based on the asymptotic distribution of the likelihood ratio statistic (cf. Crump, 1995). An example is used to provide further illustration.     

Effects of Exposure Imprecision on Estimation of the Benchmark Dose

In regression analysis failure to adjust for imprecision in the exposure variable is likely to lead to underestimation of the exposure effect. However, the consequences of exposure error for determination of safe doses of toxic substances have so far not received much attention. The benchmark approach is one of the most widely used methods for development of exposure limits. An important advantage of this approach is that it can be applied to observational data. However, in this type of data, exposure markers are seldom measured without error. It is shown that, if the exposure error is ignored, then the benchmark approach produces results that are biased toward higher and less protective levels. It is therefore important to take exposure measurement error into account when calculating benchmark doses. Methods that allow this adjustment are described and illustrated in data from an epidemiological study on the health effects of prenatal mercury exposure.     

Benchmark Duration of Work Hours for Development of Fatigue Symptoms in Japanese Workers with Adjustment for Job‐Related Stress

The objective of this study was to calculate benchmark durations and lower 95% confidence limits for benchmark durations of working hours associated with subjective fatigue symptoms by applying the benchmark dose approach while adjusting for job‐related stress using multiple logistic regression analyses. A self‐administered questionnaire was completed by 3,069 male and 412 female daytime workers (age 18–67 years) in a Japanese steel company. The eight dependent variables in the Cumulative Fatigue Symptoms Index were decreased vitality, general fatigue, physical disorders, irritability, decreased willingness to work, anxiety, depressive feelings, and chronic tiredness. Independent variables were daily working hours, four subscales (job demand, job control, interpersonal relationship, and job suitability) of the Brief Job Stress Questionnaire, and other potential covariates. Using significant parameters for working hours and those for other covariates, the benchmark durations of working hours were calculated for the corresponding Index property. Benchmark response was set at 5% or 10%. Assuming a condition of worst job stress, the benchmark duration/lower 95% confidence limit for benchmark duration of working hours per day with a benchmark response of 5% or 10% were 10.0/9.4 or 11.7/10.7 (irritability) and 9.2/8.9 or 10.4/9.8 (chronic tiredness) in men and 8.9/8.4 or 9.8/8.9 (chronic tiredness) in women. The threshold amounts of working hours for fatigue symptoms under the worst job‐related stress were very close to the standard daily working hours in Japan. The results strongly suggest that special attention should be paid to employees whose working hours exceed threshold amounts based on individual levels of job‐related stress.     

Empirical Scaling of Single Oral Lethal Doses Across Mammalian Species Based on a Large Database

The scaling of administered doses to achieve equal degrees of toxic effect in different species has been relatively poorly examined for noncancer toxicity, either empirically or theoretically. We investigate empirical patterns in the correspondence of single oral dose LD, values across several mammalian species for a large number of chemicals based on data reported in the RTECSQ database maintained by the National Institute for Occupational Safety and Health. We find a good correspondence of LD, values across species when the dose levels are expressed in terms of mgadministered per kg of body mass. Our findings contrast with earlier analyses that support scaling doses by the 3/4-power of body mass to achieve equal subacute toxicity of antineoplastic agents. We suggest that, especially for severe toxicity, single- and repeated-dosing regimes may have different cross-species scaling properties, as they may depend on standing levels of defenses and rate of regeneration of defenses, respectively.     

A Simulation Study of Quantitative Risk Assessment for Bivariate Continuous Outcomes

The neurotoxic effects of chemical agents are often investigated in controlled studies on rodents, with binary and continuous multiple endpoints routinely collected. One goal is to conduct quantitative risk assessment to determine safe dose levels. Yu and Catalano (2005) describe a method for quantitative risk assessment for bivariate continuous outcomes by extending a univariate method of percentile regression. The model is likelihood based and allows for separate dose‐response models for each outcome while accounting for the bivariate correlation. The approach to benchmark dose (BMD) estimation is analogous to that for quantal data without having to specify arbitrary cutoff values. In this article, we evaluate the behavior of the BMD relative to background rates, sample size, level of bivariate correlation, dose‐response trend, and distributional assumptions. Using simulations, we explore the effects of these factors on the resulting BMD and BMDL distributions. In addition, we illustrate our method with data from a neurotoxicity study of parathion exposure in rats.     

Global Health Impacts and Costs Due to Mercury Emissions

Since much of the emission is in the form of metallic Hg whose atmospheric residence time is long enough to cause nearly uniform mixing in the hemisphere, much of the impact is global. This article presents a first estimate of global average neurotoxic impacts and costs by defining a comprehensive transfer factor for ingestion of methyl-Hg as ratio of global average dose rate and global emission rate. For the dose-response function (DRF) we use recent estimates of IQ decrement as function of Hg concentration in blood, as well as correlations between blood concentration and Hg ingestion. The cost of an IQ point is taken as $18,000 in the United States and applied in other countries in proportion to per capita GDP, adjusted for purchase power parity. The mean estimate of the global average of the marginal damage cost per emitted kg of Hg is about $1,500/kg, if one assumes a dose threshold of 6.7 μg/day of methyl-Hg per person, and $3,400/kg without threshold. The average global lifetime impact and cost per person at current emission levels are 0.02 IQ points lost and $78 with and 0.087 IQ points and $344 without threshold. These results are global averages; for any particular source and emission site the impacts can be quite different. An assessment of the overall uncertainties indicates that the damage cost could be a factor 4 smaller or larger than the median estimate (the uncertainty distribution is approximately log normal and the ratio median/mean is approximately 0.4).     

Relation Between Benchmark Dose and No-Observed-Adverse-Effect Level in Clinical Research: Effects of Daily Alcohol Intake on Blood Pressure in Japanese Salesmen

The benchmark dose (BMD) is defined as the dose that corresponds to a specific change in an adverse response compared to the response in unexposed subjects, and the lower 95% confidence limit is termed the benchmark dose level (BMDL). In this study, the threshold of daily ethanol intake affecting blood pressure was calculated by both the BMD approach and multiple logistic regression analysis to clarify the relation between the BMDL and no-observed-adverse-effect level (NOAEL). Systolic and diastolic blood pressures (SBP and DBP) and daily ethanol intake were explored in 1,100 Japanese salesmen. The SBP and DBP were positively related to daily ethanol intake (p < 0.001) when adjusting for possible confounders such as age, body mass index, and smoking status. The adjusted risk for hypertension (SBP >or= 140 mmHg or DBP >or= 90 mmHg) increased significantly when daily ethanol intake exceeded 60 g/day, and the categorical dose of interest was 60.1-90 g/day. The BMDL and BMD of ethanol intake for increased SBP and DBP were estimated to be approximately 60 and 75 g/day, respectively. These findings suggest that the BMDL and BMD correspond to the NOAEL and lowest-observed-adverse-effect level, respectively, if the sample number of clinical data is large enough to confirm the dose-response association.     

A bayesian predictive approach to sequential search for an optimal dose: Parametric and nonparametric models

Summary This paper looks at a new approach to the problem of finding the maximal tolerated dose (or optimal dose, Eichhorn and Zacks, 1973) of certain drugs which in addition to their therapeutic effects have secondary harmful effects. The problem is investigated in a sequential setting from a Bayesian predictive approach. Search procedures are proposed for parametric and nonparametric models.