Evaluation of the Accuracy of Diagnostic Tests From Repeated Measurements Without a Gold Standard

A model is presented to evaluate the accuracy of diagnostic tests from data from individuals that are repeatedly tested in time. Repeated measurements from three diagnostic tests for foot-and-mouth disease, applied to vaccinated and experimentally infected cattle, were analyzed. At any time the true disease status of the individuals was unknown, i.e., no gold standard was available. The model allows for correlation between repeated test results, in consequence of the underlying structure for the unknown true disease status, but also by the distribution of the test results conditional upon true disease status. The model also allows for dependence between the different diagnostic tests conditional upon true disease status. Prior information about the structure of the prevalence and the specificity of the tests was incorporated in a Bayesian analysis. Posterior inference was carried out with Markov chain Monte Carlo. Simulated data were analyzed to gain insight into the performance of the posterior Bayesian inference. The simulated data are typical for the expensive and, therefore, modestly sized infection experiments that are conducted under controlled conditions.     

Testing the cascade model for food webs

The cascade model is a standard model for food web data. This article describes a method for testing the cascade model that complements existing tests. Like existing tests, the new test is conditional on the number of links observed in the predation matrix. One important feature of the cascade model is that an ordering of species is required, but in practice the true order is unknown. This feature has important implications for tests of the model, both for the new test and for existing tests. The analysis here does not require a single assumed order. Some real food webs are used for illustration.     

Bayes Factor Based on a Maximum Statistic for Case-Control Genetic Association Studies

We study a Bayes factor based on a robust test statistic, MAX3, for case-control genetic association studies. MAX3 is the maximum of three trend tests derived under the recessive, additive and dominant genetic models, respectively. The proposed Bayes factor, denoted as BFM, models the asymptotic distributions of MAX3 under the null and alternative hypotheses. It is compared to an existing Bayes factor based on Bayesian model averaging (BMA). Through simulation studies, we show that both BFM and BMA are robust under genetic model uncertainty. They both depend on specifying the prior distribution for the genetic model, and have similar performance when common objective priors are used. When the prior places a large probability on the true (wrong) genetic model, BMA (BFM) is more powerful. Applications to real data from a genome-wide association study are presented to illustrate their use and show their sensitivity under genetic model uncertainty.     

Do the soft tissues of Helix aspersa serve as a quantitative sentinel of predicted free lead concentrations in soils?

Previous research suggests that free metal concentrations in soils are the best correlate of the proportion available for uptake, especially by plants. The same may be true for animals which ingest soil, such as earthworms and gastropod molluscs. Using predictions from a simple model proposed by Sauvé et al. [Environ. Pollut. (1997) 149] and based on soil pH and total soil concentrations, the relationship between free soil Pb and soft tissue Pb concentrations is evaluated in the garden snail Helix aspersa. Five replicate adults collected from 23 sites in England and Wales were partitioned into two tissue fractions and the relationship between their Pb concentrations and those of their native soil was examined using simple regression analysis. Levels in both fractions rose with free Pb concentrations, but the terms of each relationship and its level of significance were greatly influenced by the most contaminated soils. Neither tissue fraction served as an effective sentinel of free soil Pb and the regression coefficient was a poor summary statistic across sites with a large range of contamination. The same was true of Pb concentrations in the whole soft tissues. It may be that free ion concentrations are not indicative of metal availability to animals with a range of mechanisms to assimilate nutrients, perhaps because of undescribed environmental and physiological factors governing assimilation or limiting soft tissue concentrations.     

Mastitis in dairy production: Estimation of sensitivity, specificity and disease prevalence in the absence of a gold standard

Mastitis, a worldwide endemic disease of dairy cows, is an important cause of decreased efficiency in milk production. Early medical treatment can reduce the nonreversible losses in milk production caused by this infection. Various diagnostic tests for mastitis are available, including a test measuring the electrical conductivity of milk (MEC test), the industry standard of somatic cell counting (SCC test), a bacteriological test, and a recently developed test measuring mammary associated amyloid A (MAA test). None of these tests is considered a gold standard, however. The aim of the present study was to determine which of these tests provides the best results, and at what cost, to improve the efficiency of milk production. For this study, 25 cows were tested at all four quarters of the udder with each of the aforementioned mastitis diagnostic tests. Based on the data, the disease prevalence as well as the sensitivity and the specificity of the four tests were estimated with a Bayesian approach by extending the Hui and Walter model with two independent tests and two populations to a model with four partially dependent tests and one population. This model was further combined with a receiver operating characteristics analysis to estimate the overall test accuracy.     

Qualitative and quantitative polymerase chain reaction analysis for genetically modified maize MON863

Qualitative and quantitative analytical methods were developed for the new event of genetically modified (GM) maize, MON863. One specific primer pair was designed for the qualitative polymerase chain reaction (PCR) method. The specificity and sensitivity of the designed primers were confirmed. PCR was performed on genomic DNAs extracted from MON863, other GM events, and cereal crops. Single PCR product was obtained from MON863 by the designed primer pair. Eight test samples including GM maize MON863 were prepared at 0.01 approximately 10% levels and analyzed by PCR. Limit of detection of the method was 0.01% for GM maize MON863. On the other hand, another specific primer pair and probe were also designed for quantitative method using a real-time polymerase chain reaction. As a reference molecule, a plasmid was constructed from a taxon-specific DNA sequence for maize, a universal sequence for a cauliflower mosaic virus (CaMV) 35S promoter used in most genetically modified organisms, and a construct-specific DNA sequence for the MON863 event. Six test samples of 0.1, 0.5, 1.0, 3.0, 5.0 and 10.0% of GM maize MON863 were quantitated for the validation of this method. At the 3.0% level, the bias (mean vs true value) for MON863 was 3.0%, and its relative standard deviation was 5.5%. Limit of quantitation of the method was 0.5%. These results show that the developed PCR methods can be used to qualitatively and quantitatively detect GM maize MON863.     

辽宁省黄土状母质发育土壤有机质含量高光谱预测模型的构建

  目的  建立辽宁省黄土状母质发育土壤有机质含量的高光谱预测模型,以便快速获取土壤样品的有机质含量。  方法  对省域内黄土状母质发育土壤进行了样品采集,获取样品有机质含量和高光谱数据;选择原始光谱及其一阶微分、二阶微分、倒数对数、倒数对数一阶微分、倒数对数二阶微分6种光谱变换数据作为自变量,与土壤有机质含量进行相关分析,选取特征波段,分别建立多元逐步线性回归（SMLR）、偏最小二乘回归（PLSR）和主成分回归（PCR）3种土壤有机质高光谱线性预测模型,并进行了支持向量机（SVM）方法的非线性模型拟合。  结果  土壤有机质含量与其光谱反射率呈负相关关系,对光谱进行不同的数学变换,可以提高土壤有机质含量与光谱反射率的相关性,其中一阶微分和二阶微分的提升效果最佳;相同光谱数据在不同模型中建模精度存在显著差异,以原始光谱反射率一阶微分为自变量的PLSR模型精度最高,建模集和验证集的决定系数（R2）分别为0.958和0.976;3种线性方法建立的最佳预测模型的检验精度为:PLSR > SMLR > PCR。  结论  PLSR模型是辽宁省黄土状母质发育土壤有机质含量的最佳高光谱预测模型,且基于特征波段的建模效果优于全波段;SVM非线性模型的预测精度较低。     

Bayesian capture-recapture analysis and model selection allowing for heterogeneity and behavioral effects

In this article, we present Bayesian analysis of capture-recapture models for a closed population which allows for heterogeneity of capture probabilities between animals and bait/trap effects. We use a flexible discrete mixture model to account for the heterogeneity and behavioral effects. In addition we present a solid model selection criterion. Through illustrations with a motivating dataset, we demonstrate how Bayesian analysis can be applied in this setting and discuss some major benefits which result, including consideration of informative priors based on historical data.     

牛肉大理石花纹图像特征信息提取及自动分级方法

为了解决牛肉大理石花纹在人工分级中准确率和效率低的问题,该文基于计算机视觉和图像处理技术提出一种实用的牛肉大理石花纹自动评估和分级方法。通过图像解析,利用所提出的分级算法实现牛肉大理石花纹的快速提取,并计算反映大理石花纹丰富程度的10个特征参数。使用特征参数建立主成分回归模型,对牛肉大理石花纹等级进行预测,预测相关系数Rv=0.88,预测标准差SEP=0.56。校正时模型总体的回判正确率为97.0%,验证时总体的判别正确率为91.2%。在此基础上,开发了大理石花纹自动分级软件系统和硬件装置,并且在该试验室前期研制的样机上进行了试验,验证了算法的运算速度和准确率。结果表明,所提出的分级方法的检测速度和精度均能够满足企业中对牛肉大理石花纹分级的要求。     

Dating chicks: Calibration and discrimination in a nonlinear multivariate hierarchical growth model

The motivation for this work was to investigate the possibility of accurately determining the age of a tern chick using easily obtained body measurements. We describe the construction of a nonlinear multivariate hierarchical model for chick growth and show how it can be estimated using Markov chain Monte Carlo techniques. A simple extension of the analysis allows for estimation of the ages of unknown chicks. Posterior distributions of the unknown ages are derived, so that the accuracy of age determination can be examined. We further extend our model and analysis to include the possibility that chicks fall into distinct groups with different growth characteristics. The technique is illustrated using data on the weight and wing length of black-fronted terns from the Ohau River, New Zealand. It is found that dating to within one day is possible, but only in some areas of the data space. The concept of “braiding” of multivariate growth curves is introduced to explain the varying accuracy of age determination.     

基于U-Net网络和无人机影像的松材线虫病变色木识别

松材线虫病是由松墨天牛等媒介昆虫快速传播的一种针对松树的毁灭性流行病。及时对染病变色木进行识别、定位,并砍伐清除是当前控制该病扩散蔓延的主要手段。该研究使用无人机航拍获取大区域染病松林可见光影像,结合深度学习分割网络U-Net开展染病松材变色木图像分割研究。使用制作的样本数据训练U-Net网络,得到训练精度和验证精度分别为98.74%和97.76%。使用混淆矩阵评估U-Net网络分割精度,表明变色木图像分割的用户精度和生产者精度分别达到93.51%和97.30%,误报率6.49%,漏报率2.70%。总体上,U-Net网络变色木识别精度95.17%,Kappa系数0.90,达到较高精度。U-Net分割网络运用于松材线虫病变色木图像识别较随机森林方法能更有效地降低误报,减少分割噪音。     

Detection of beef and poultry by serological field screening tests (ORBIT and PROFIT): collaborative study

Ten laboratories each analyzed 30 raw meat and raw meat product samples in a collaborative study of the ORBIT (overnight rapid bovine identification test) and PROFIT (poultry rapid overnight field identification test) serological field screening tests for the detection of beef and poultry. Versatility of the tests was shown in the analysis of whole tissue, ground, or emulsified raw meat products. Both tests were demonstrated to be reliable and were capable of detecting adulterants present at the 10% level. The method has been adopted official first action.     

Bayesian inferences for receiver operating characteristic curves in the absence of a gold standard

Sensitivity and specificity are used to characterize the accuracy of a diagnostic test. Receiver operating characteristic (ROC) analysis can be used more generally to plot the sensitivity versus (1-specificity) over all possible cutoff points. We develop an ROC analysis that can be applied to diagnostic tests with and without a gold standard. Moreover, the method can be applied to multiple correlated diagnostic tests that are used on the same individual. Simulation studies were performed to assess the discrimination ability of the no-gold-standard method compared with the situation where a gold standard exists. We used the area under the ROC curve (AUC) to quantify the diagnostic accuracy of tests and the difference between AUCs to compare their accuracies. In particular, we can estimate the prevalence of disease/infection under the no-gold-standard method. The method we proposed works well in the absence of a gold standard for correlated test data. Correlation affected the width of posterior probability intervals for these differences. The proposed method was used to analyze ELISA test scores for Johne’s disease in dairy cattle.     

Quantification of genetically modified soybean by quenching probe polymerase chain reaction

Quenching probe (QProbe) polymerase chain reaction (PCR) is a simple and cost-effective real-time PCR assay in comparison with other real-time PCR assays such as the TaqMan assay. We used QProbe-PCR to quantify genetically modified (GM) soybean (Roundup Ready soybean). We designed event-specific QProbes for Le1 (soy endogenous gene) and RRS (recombinant gene), and we quantified certified reference materials containing 0.1, 0.5, 1, 2, and 5% GM soybean. The TaqMan assay was also applied to the same samples, and the results were compared. The accuracy of QProbe-PCR was similar to that of TaqMan assay. When GM soybean content was 0.5% or more, the relative standard deviations of QProbe-PCR were less than 20%. QProbe-PCR is sensitive enough to monitor labeling systems and has acceptable levels of accuracy and precision.     

基于TRMM 3B43数据的川西高原月降水量空间降尺度模拟

利用2001-2013年TRMM 3B43、MODIS-NDVI、DEM、气象观测等数据,在分析植被对降水响应滞后性的基础上,构建了TRMM 3B43数据中月降水量与经纬度、海拔、坡向和NDVI因子间的多元线性回归方程式,作为川西高原月降水量资料的降尺度计算模型,采用“回归方程+残差”的插值方法获取研究区2001-2013年1km空间分辨率的月降水量空间数据,并利用区内16个气象站点的观测数据与模拟结果进行了相关分析和误差检验。结果表明：（1）各气象观测站点基于TRMM 3B43资料的降尺度模拟降水量的数据均具有很高的精度,其中,精度最高的稻城站模拟结果与站点观测值的相关系数高达0.9839,精度最低的小金站相关系数亦高达0.8781;（2）在月、年尺度上,降尺度模拟降水量的数据亦具有很高的精度,其中,5-10月的精度明显高于其它月份,湿润年份精度总体高于干旱年份;（3）降尺度模拟降水量与站点实测降水量整体上相关系数为0.9499,偏差为0.0866,两者吻合度较高,但降尺度模拟降水量值略偏高;（4）降尺度在月尺度上能基本保证TRMM 3B43原始数据的精度,而在年尺度上能有效提高原始数据的精度,加之对空间分辨率的提高,可为获得更加全面、精细的降水分布数据提供有效方法。     

Using power priors to improve the binomial test of water quality

To assess violations of water quality standards, measurements of water quality are collected on a regular basis over a period of time, and are then analyzed to evaluate the percentage of samples exceeding the standard. The challenge to the assessor is that often only a limited amount of data are used to determine if the stream is violating standards. Current assessment uses just the data for a period of two years. To address this issue, we present a Bayesian approach using power priors to incorporate historical information in decision-making. We demonstrate a modified power prior approach and discuss its properties under a binomial model. Exact error probabilities are compared using three approaches: a power prior approach to the binomial test, a Bayesian binomial test with noninformative prior, and a frequentist binomial test. Two examples are presented to illustrate the implementation of the power prior and its differences with alternative binary methods in water quality assessment.     

利用近红外漫反射光谱技术进行苹果糖度无损检测的研究

利用近红外漫反射光谱技术,研究了1300～2100 nm波长范围内无损检测苹果糖度的可行性。采集了每个苹果去皮前、后最大横径上四个点的近红外平均光谱和整个苹果的糖度值。采用主成分回归(PCR)和偏最小二乘法(PLS)对试验数据进行了多元统计分析。结果表明：在1300～2100 nm波长范围内无损检测(即带皮检测)苹果的糖度是可靠的,并且PLS模型的性能更优于PCR模型。本文还对用单测点光谱和多测点平均光谱建立的糖度模型进行了研究,结果表明用单测点光谱预测整个苹果的糖度,其精度明显低于多测点平均光谱。这说明用苹果上一个点的光谱来预测整个苹果的糖度,其精度是不够的。因此,在利用近红外漫反射光谱在线检测苹果糖度时,作者建议采用多个光纤探头来采集多点光谱,然后取其平均值预测。     

Interlaboratory evaluation of a real-time multiplex polymerase chain reaction method for identification of salmon and trout species in commercial products

This interlaboratory study evaluated a real-time multiplex polymerase chain reaction (PCR) method for identification of salmon and trout species in a range of commercial products in North America. Eighty salmon and trout products were tested with this method by three independent laboratories. Samples were collected in the United States and Canada, and only the collecting institution was aware of the species declaration. Following analysis with real-time PCR, all three laboratories were able to identify species in 79 of the 80 products, with 100% agreement on species assignment. A low level of fraud was detected, with only four products (5%) found to be substituted or mixtures of two species. The results for two of the fraudulent products were confirmed with alternate methods, but the other two products were heavily processed and could not be verified with methods other than real-time PCR. Overall, the results of this study show the usefulness and versatility of this real-time PCR method for the identification of commercial salmon and trout species.     

Considerations regarding the use of hyperspectral imaging data in classifications of food products, exemplified by analysis of maize kernels

Development of robust analytical procedures is critical when using hyperspectral imaging technology in food technology and agriculture. This study used near-isogenic inbred corn lines to address two basic questions: (1) To what extent is classification accuracy increased by grinding maize kernels? (2) Can the classification accuracy of two near-isogenic inbred lines be increased by using a spectral filter to classify only certain hyperspectral profiles from each image cube? Whole kernels and ground kernels in two particle intervals, 0.250-0.354 mm (size 1) and 0.354-0.841 mm (size 2), were examined. Spectral profiles acquired from ground kernels had higher spectral repeatability than data collected from whole kernels. The classification error of discriminant functions from whole kernels was >3 times lower than that of size 1 ground particles. Applying a spectral filter to input data had negligible effect on classifications of hyperspectral profiles from whole kernels and size 2 ground particles, but for size 1 ground particles a considerable increase in accuracy was observed. Independent validation confirmed that distinction between wild type and mutant inbred maize lines could be conducted with >80% accuracy after the proposed spectral filter had been applied to hyperspectral profiles of size 1 ground particles. A combination of discriminant analysis and regression analysis could be used to accurately predict mixture ratios of the two inbred lines. The use of spectral filtering to increase the level of spectral repeatability and the use of hyperspectral imaging technology in large-scale commercial operations are discussed.