Modeling the Dose Response Relationship of Waterborne Acanthamoeba

This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta‐Poisson model. The HN‐3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD₅₀ of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free‐living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free‐living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.     

Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Welfare for Continuous Effects

The benchmark dose (BMD) approach is increasingly used as a preferred approach for dose–effect analysis, but standard experimental designs are generally not optimized for BMD analysis. The aim of this study was to evaluate how the use of unequally sized dose groups affects the quality of BMD estimates in toxicity testing, with special consideration of the total burden of animal distress. We generated continuous dose–effect data by Monte Carlo simulation using two dose–effect curves based on endpoints with different shape parameters. Eighty‐five designs, each with four dose groups of unequal size, were examined in scenarios ranging from low‐ to high‐dose placements and with a total number of animals set to 40, 80, or 200. For each simulation, a BMD value was estimated and compared with the “true” BMD. In general, redistribution of animals from higher to lower dose groups resulted in an improved precision of the calculated BMD value as long as dose placements were high enough to detect a significant trend in the dose–effect data with sufficient power. The improved BMD precision and the associated reduction of the number of animals exposed to the highest dose, where chemically induced distress is most likely to occur, are favorable for the reduction and refinement principles. The result thereby strengthen BMD‐aligned design of experiments as a means for more accurate hazard characterization along with animal welfare improvements.     

Bayesian adaptive linearization method for phase I drug combination trials with dimension reduction

Many phase I drug combination designs have been proposed to find the maximum tolerated combination (MTC). Due to the two‐dimension nature of drug combination trials, these designs typically require complicated statistical modeling and estimation, which limit their use in practice. In this article, we propose an easy‐to‐implement Bayesian phase I combination design, called Bayesian adaptive linearization method (BALM), to simplify the dose finding for drug combination trials. BALM takes the dimension reduction approach. It selects a subset of combinations, through a procedure called linearization, to convert the two‐dimensional dose matrix into a string of combinations that are fully ordered in toxicity. As a result, existing single‐agent dose‐finding methods can be directly used to find the MTC. In case that the selected linear path does not contain the MTC, a dose‐insertion procedure is performed to add new doses whose expected toxicity rate is equal to the target toxicity rate. Our simulation studies show that the proposed BALM design performs better than competing, more complicated combination designs.     

Quantitative Risk Assessment: Developing a Bayesian Approach to Dichotomous Dose–Response Uncertainty

Model averaging for dichotomous dose–response estimation is preferred to estimate the benchmark dose (BMD) from a single model, but challenges remain regarding implementing these methods for general analyses before model averaging is feasible to use in many risk assessment applications, and there is little work on Bayesian methods that include informative prior information for both the models and the parameters of the constituent models. This article introduces a novel approach that addresses many of the challenges seen while providing a fully Bayesian framework. Furthermore, in contrast to methods that use Monte Carlo Markov Chain, we approximate the posterior density using maximum a posteriori estimation. The approximation allows for an accurate and reproducible estimate while maintaining the speed of maximum likelihood, which is crucial in many applications such as processing massive high throughput data sets. We assess this method by applying it to empirical laboratory dose–response data and measuring the coverage of confidence limits for the BMD. We compare the coverage of this method to that of other approaches using the same set of models. Through the simulation study, the method is shown to be markedly superior to the traditional approach of selecting a single preferred model (e.g., from the U.S. EPA BMD software) for the analysis of dichotomous data and is comparable or superior to the other approaches.     

Robust extrapolation designs and weights for biased regression models with heteroscedastic errors

We consider the construction of designs for the extrapolation of regression responses, allowing both for possible heteroscedasticity in the errors and for imprecision in the specification of the response function. We find minimax designs and correspondingly optimal estimation weights in the context of the following problems: (1) for ordinary least squares estimation, determine a design to minimize the maximum value of the integrated mean squared prediction error (IMSPE), with the maximum being evaluated over both types of departure; (2) for weighted least squares estimation, determine both weights and a design to minimize the maximum IMSPE; (3) choose weights and design points to minimize the maximum IMSPE, subject to a side condition of unbiasedness. Solutions to (1) and (2) are given for multiple linear regression with no interactions, a spherical design space and an annular extrapolation space. For (3) the solution is given in complete generality; as one example we consider polynomial regression. Applications to a dose-response problem for bioassays are discussed. Numerical comparisons, including a simulation study, indicate that, as well as being easily implemented, the designs and weights for (3) perform as well as those for (1) and (2) and outperform some common competitors for moderate but undetectable amounts of model bias.     

Dose Response Models For Infectious Gastroenteritis

When pathogenic microorganisms enter the human body via ingestion with food or drinking water, they encounter a system of barriers mounted by the host. In order to reach parts of the intestinal tract that are suitable for growth and attachment, each of the barriers must be overcome successfully. The present view on infection states that at least one of the ingested pathogens must survive to start colonization. This is the basis for dose response models, used for quantitative risk assessment. In this paper, the usefulness of the Beta Poisson model for multiple barriers is corroborated. Infection is associated with the presence of elevated numbers of reproducing pathogens in the intestinal tract. This does not necessarily imply illness symptoms: when intestinal microorganisms engage in damaging activities, this may lead to illness symptoms. At the same time, these activities probably elicit defensive measures from the host, promoting the removal of pathogens and terminating infection. The duration of the period of colonization reflects the balance between the colonization potential of pathogens and the strength of host defenses. Starting from the assumption that during infection the host has a certain hazard of becoming ill, a simple dose response relation for acute gastroenteritis is developed. With the use of literature data from volunteer experiments, we show that examples can be found for three possible alternatives: an increase in the probability of illness with increasing dose, a decrease with higher doses, and a probability of illness (given infection) independent of the ingested dose. These alternatives may reflect different modes of interaction between pathogens and host.     

Planning a Bayesian early-phase phase I/II study for human vaccines in HER2 carcinomas

Recent innovative statistical approaches for phase I/II clinical trials allow one to jointly model the toxicity and efficacy of a new treatment, taking into account the information gathered during the trial. Prior probabilities are then updated with interim data and thus predictive probabilities become more accurate as the trial progresses. In this study, prior distribution elicited from a physician's opinion on the available dose levels planned for a vaccination dose-finding trial, with human DNA in patients with HER2-positive tumours in terms of toxicity and therapeutic response is presented and discussed. A simulation study was conducted in order to quantify the impact of the choice of prior on study results, i.e. the recommended dose level at the end of the trial.     

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。     

对高师运用微格教学的几点阐述

微格教学是一种系统的训练方式,是高等师范教育培养学生教学技能的重要途径.它的实施可以在很大程度上提高师范生的教学能力.随着课程改革的深入,必须重新思考微格教学技能的内涵、特点.微格教学在实施过程中必须充分利用其特有的训练模式,要求学生开展试教活动.同时还要把握微格教学的实施要点.