Sampling Issues Affecting Accuracy of Likelihood-based Classification Using Genetical Data

We demonstrate the effectiveness of a genetic algorithm for discovering multi-locus combinations that provide accurate individual assignment decisions and estimates of mixture composition based on likelihood classification. Using simulated data representing different levels of inter-population differentiation (F_st～ 0.01 and 0.10), genetic diversities (four or eight alleles per locus), and population sizes (20, 40, 100 individuals in baseline populations), we show that subsets of loci can be identified that provide comparable levels of accuracy in classification decisions relative to entire multi-locus data sets, where 5, 10, or 20 loci were considered. Microsatellite data sets from hatchery strains of lake trout, Salvelinus namaycush, representing a comparable range of inter-population levels of differentiation in allele frequencies confirmed simulation results. For both simulated and empirical data sets, assignment accuracy was achieved using fewer loci (e.g., three or four loci out of eight for empirical lake trout studies). Simulation results were used to investigate properties of the ‘leave-one-out’ (L1O) method for estimating assignment error rates. Accuracy of population assignments based on L1O methods should be viewed with caution under certain conditions, particularly when baseline population sample sizes are low (<50).     

影响动物模型MBLUP评定准确性的主要因素

标记辅助最佳线性无偏预测（marker-assisted best linear unbiased prediction,MBLUP）是对动物实施标记辅助选择（marker-assisted selection,MAS）的一种重要方法。通过计算机随机模拟研究了所选性状的遗传力、QTL方差和相邻两个标记间图距3个因素对动物模型MBLUP评定准确性的影响。结果表明,性状的遗传力越高、QTL方差和相邻两个标记间图距越小时,动物模型MBLUP评定的准确性越高;相反,当性状的遗传力较低、QTL方差和相邻两个标记间图距较大时,动物模型MBLUP评定的准确性则较低。     

Combining Information from Cancer Registry and Medical Records Data to Improve Analyses of Adjuvant Cancer Therapies

Summary .  Cancer registry records contain valuable data on provision of adjuvant therapies for cancer patients. Previous studies, however, have shown that these therapies are underreported in registry systems. Hence direct use of the registry data may lead to invalid analysis results. We propose first to impute correct treatment status, borrowing information from an additional source such as medical records data collected in a validation sample, and then to analyze the multiply imputed data, as in Yucel and Zaslavsky (2005,  Journal of the American Statistical Association   100, 1123–1132). We extend their models to multiple therapies using multivariate probit models with random effects. Our model takes into account the associations among different therapies in both administration and probability of reporting, as well as the multilevel structure (patients clustered within hospitals) of registry data. We use Gibbs sampling to estimate model parameters and impute treatment status. The proposed methodology is applied to the data from the Quality of Cancer Care project, in which stage II or III colorectal cancer patients were eligible to receive adjuvant chemotherapy and radiation therapy.     

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.     

Factors Affecting Somatic Embryogenesis from Cotyledonary Explants of Safflower

Frequency of safflower (Carthamus tinctorius L.) somatic embryogenesis, number of somatic embryos per responding explant and somatic embryo maturation and germination were affected by genotype, explant age, carbon source, and ethylene. Among 8 cultivars tested, 7 were embryogenic with varying frequencies. The best response was obtained with cv. Girna. Whole cotyledonary explant from 10-d-old plants was best responding compared to 5- or 15-d-old ones. Among different carbon sources, sucrose at 87.6 mM concentration was most suitable for embryo induction, maturation and germination. Of the different ethylene inhibitors, silver nitrate at 50 [micro ]M concentration significantly increased the embryogenic frequency and also the number of embryos per responding explant. Silver nitrate has pronounced effect on embryo maturation but had no effect on germination.     

上海市浦东新区继续医学教育满意度影响因素分析

目的:探讨浦东新区医务人员对继续医学教育的满意度现况。方法:采用自制调查问卷对浦东新区卫生技术培训中心正在接受继续医学教育的155名学员进行调查。结果:浦东新区继续教育总体满意度为61.2%;教育内容满意度为66.4%,教学形式满意度为57.9%,培训教材满意度为53.9%,授课教师满意度为69.7%,教育时间安排满意度为45.4%。结论:浦东新区继续医学教育总体符合区域医学发展与医学人才培养需求,但教学满意度等方面的问题有待改进与提高。     

Estimation from Censored Medical Cost Data

This paper applies the inverse probability weighted least‐squares method to predict total medical cost in the presence of censored data. Since survival time and medical costs may be subject to right censoring and therefore are not always observable, the ordinary least‐squares approach cannot be used to assess the effects of explanatory variables. We demonstrate how inverse probability weighted least‐squares estimation provides consistent asymptotic normal coefficients with easily computable standard errors. In addition, to assess the effect of censoring on coefficients, we develop a test comparing ordinary least‐squares and inverse probability weighted least‐squares estimators. We demonstrate the methods developed by applying them to the estimation of cancer costs using Medicare claims data. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Biologics Formulation Factors Affecting Metal Leachables from Stainless Steel

An area of increasing concern and scientific scrutiny is the potential contamination of drug products by leachables entering the product during manufacturing and storage. These contaminants may either have a direct safety impact on the patients or act indirectly through the alteration of the physicochemical properties of the product. In the case of biotherapeutics, trace amounts of metal contaminants can arise from various sources, but mainly from contact with stainless steel (ss). The effect of the various factors, buffer species, solution fill volume per unit contact surface area, metal chelators, and pH, on metal leachables from contact with ss over time were investigated individually. Three major metal leachables, iron, chromium, and nickel, were monitored by inductively coupled plasma–mass spectrometry because they are the major components of 316L ss. Iron was primarily used to evaluate the effect of each factor since it is the most abundant. It was observed that each studied factor exhibited its own effect on metal leachables from contact with ss. The effect of buffer species and pH exhibited temperature dependence over the studied temperature range. The metal leachables decreased with the increased fill volume (mL) per unit contact ss surface area (cm²) but a plateau was achieved at approximately 3 mL/cm². Metal chelators produced the strongest effect in facilitating metal leaching. In order to minimize the metal leachables and optimize biological product stability, each formulation factor must be evaluated for its impact, to balance its risk and benefit in achieving the target drug product shelf life.