Syndromic Surveillance Using Veterinary Laboratory Data: Algorithm Combination and Customization of Alerts

Background

Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals.

Methods

This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed.

Results

The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described.

Conclusion

The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes.     

Laboratory Test of an Automated Cell Analysis System For Cervical Screening

An automated cell analysis system (Autoplan-MIAC) for the early detection of precancerous lesions of the cervix was tested under semi-routine conditions in a clinical cytology laboratory. A set of 1500 specimens, highly enriched with abnormal cases, was analysed. Cervical scrapings were collected in suspension and processed by cytocentrifugation for microscopy. Two slides were prepared from each sample: one for staining according to Papanicolaou for the visual reference diagnosis and one for Feulgen staining for automated analysis. the specimens were evaluated in two ways: the first one, which is referred to as the automated machine classification system (AMC), classifies the specimens according to the number and ratio of selected objects (alarms) and is a fully automated system. the second system classifies the specimens after visual evaluation of the stored alarms as they are displayed on a TV monitor, and is designated the interactive machine classification system (IMC). the AMC results showed a false positive rate of 16.5% when the cut-off threshold was selected so that all 117 positively diagnosed specimens were classified ‘positive’ by the system. In that case 87.4% of the CINI and 96.9% of the CINII cases were AMC-positive. the IMC results showed a false positive rate of 2.5%, when 86.3% of the CIN I cases, 96.9% of the CIN II cases and all CIN III and invasive carcinoma cases were positively classified.     

热分析方法及裂解气相色谱在树木分类上的试探性研究

热分析是在程序控制温度下自动连续跟踪物质的物理性质与温度关系的一类技术。尤其是差热分析和热重法与其他手段联合,可用于化合物稳定性、分解机理和相转变等方面的研究。由于种子是一个复杂化合物的有机体,我们期望发现各不同种子化合物之间在成份上和组成方式上的共性和差异性,从热化学的角度对木本植物进行热化学分类。我们选用针叶类两个科(松科、杉木科)的种子进行了DTA、TG、550℃裂解气相色谱分析;300℃逸出成份分析,发现松科种子DTA图上在240±5℃有一个共同的吸热峰,而杉木则出现在320±5 ℃。TG曲线同科的不同种之间非常相似,逸出成份分析和裂解气相色谱分析同科的不同种之间也具共同特征,且又显示出一定的差异性。这种分类方法是可靠的,且可为树木(或植物)分类学提供更有价值的信息。     

Classification of Streptomyces Spore Surfaces into Five Groups

Streptomyces spores surfaces have been classified into five groups, smooth, warty, spiny, hairy, and rugose, by examination of carbon replicas of spores with the transmission electron microscope and by direct examination of spores with the scanning electron microscope.     

用于变应原疫苗分析和质控的实验技术

建立和应用一种可靠的质量分析方法是所有生物制品质量和工艺一致性的保障。一种准确反应药物中特异组成成分的活性和结构,并且优化和验证了的方法,是所有生物医药领域研发和新药上市的一个核心目标。变应原疫苗是天然物质的混合物,每一种变应原疫苗含有多种活性成分和与变应原无关未知的非活性成分,其中,具有变应原活性的物质只占一小部分,而且主要变应原成分作用在患者与患者之间差异性很大。本文介绍了一种变应原疫苗分析和质控的方法,包括变应原疫苗总蛋白含量、总蛋白组分、主要致敏蛋白组成、主要致敏蛋白含量、总生物活性几方面。     

Overview of Coronaviruses in Veterinary Medicine

Coronaviruses infect humans and a wide range of animals, causing predominantly respiratory and intestinal infections. This review provides background on the taxonomy of coronaviruses, the functions of viral proteins, and the life cycle of coronaviruses. In addition, the review focuses on coronaviral diseases in several agriculturally important, companion, and laboratory animal species (cats, cattle, chickens, dogs, mice, rats and swine) and briefly reviews human coronaviruses and their origins.

Coronaviruses get their name from their morphology, as the spike proteins present in the envelope of the virus give the virions a crown-like (‘corona’) appearance when viewed by electron microscopy. Coronaviruses are enveloped, spherical or pleomorphic viruses ranging from 120 to 160 nm in diameter. Coronaviruses have the largest nonsegmented positive-sense single-stranded RNA viral genome (25 to 32,000 nucleotides).^22,69 The genome is polyadenylated and capped. Coronavirus genomes can serve as mRNAs, and purified genomic RNA is infectious. The arrangement of genes is similar for all coronaviruses, with the nonstructural replicase gene encoded in the 5′ two thirds of the genome, and the genes for the structural proteins and several small accessory proteins encoded in the 3′ third of the genome.     

Some Exploratory Methods for Studying Curvature in Robust Regression

The paper suggests an exploratory method for studying curvature, within the context of robust regression, using an analog of the approached developed by Doksum and Samarov (1995). The strategy begins by approximating the regression surface using a proposed generalization of the so‐called running interval smoother. The generalization consists of estimating the span via arobust measure of scale associated with the residuals. This approximation can then be used to measure linearity using a robust analog of a measure considered by Doksum and Samarov. The results are illustrated with data from a study on predicting reading ability.     

Biocide-Containing Varnish for the Protection of Sandstone: Comparison of Formulations and Laboratory Test Methods

Two formulations of acrylic varnish, with and without either of two dry film biocides—one a mixture of isothiazolinones and benzimidazole derivatives, and the other a carbamate—were tested in vitro for their activity against mixtures of filamentous fungi and cyanobacteria found on sandstone buildings. Growth on filter-paper squares coated with the varnishes was assessed semi-quantitatively by naked eye, quantitatively by image analysis and chemically by measurement of ergosterol and chlorophyll a. The lower solvent content (higher resin) varnish was more inhibitory to cyanobacteria than the higher varnish content, whilst the opposite was true for the fungal inoculum. The carbamate biocide was effective against cyanobacteria, unlike the isothiazolinone mixture, but the latter produced more inhibition of fungal growth. The three assay methods produced generally similar results, although visual observation was obviously the most imprecise. There was an anomaly in the ergosterol measurements, which was considered to be caused by the varying ergosterol content and unequal inhibition of the three fungal genera used in the inoculum. Fusarium sp. was shown to contain higher levels of this membrane component than Cladosporium sp. and Penicillium sp. For this reason, the most appropriate method overall, giving reliable quantitative results, was deemed to be the image analysis.     

An Analysis of Methods for Tuning a Support-Vector Machine for Binary Classification

Biophysics - Using methods based on support-vector machines (SVMs), it is possible to handle voluminous, high-dimensional, and poorly structured datasets, which is especially important in finding...     

The Use of Global Rating Scales for OSCEs in Veterinary Medicine

OSCEs (Objective Structured Clinical Examinations) are widely used in health professions to assess clinical skills competence. Raters use standardized binary checklists (CL) or multi-dimensional global rating scales (GRS) to score candidates performing specific tasks. This study assessed the reliability of CL and GRS scores in the assessment of veterinary students, and is the first study to demonstrate the reliability of GRS within veterinary medical education. Twelve raters from two different schools (6 from University of Calgary [UCVM] and 6 from Royal (Dick) School of Veterinary Studies [R(D)SVS] were asked to score 12 students (6 from each school). All raters assessed all students (video recordings) during 4 OSCE stations (bovine haltering, gowning and gloving, equine bandaging and skin suturing). Raters scored students using a CL, followed by the GRS. Novice raters (6 R(D)SVS) were assessed independently of expert raters (6 UCVM). Generalizability theory (G theory), analysis of variance (ANOVA) and t-tests were used to determine the reliability of rater scores, assess any between school differences (by student, by rater), and determine if there were differences between CL and GRS scores. There was no significant difference in rater performance with use of the CL or the GRS. Scores from the CL were significantly higher than scores from the GRS. The reliability of checklist scores were .42 and .76 for novice and expert raters respectively. The reliability of the global rating scale scores were .7 and .86 for novice and expert raters respectively. A decision study (D-study) showed that once trained using CL, GRS could be utilized to reliably score clinical skills in veterinary medicine with both novice and experienced raters.     

Using Generalized Distances in Classification of Groups

The Mahalanobis generalized distance can advantageously be used to achieve the hierarchical clustering of groups of individuals. With a set of nearly 12,000 biometrical data, comprising populations of 14 different species of clover, we tried four methods to cluster those populations, in order to compare their results and to see whether the numerical classification obtained agrees with the botanical taxonomy. One of those methods is a conventional hierarchical clustering technique, based upon the Euclidean distances between the means of the populations, while the three other methods make use, with an increasing degree of complexity, of the generalized distances. These methods gave obviously better results.     

QRS波群自动分类技术研究进展

本文综述了QRS波群自动分类技术的关键技术及其研究方向,内容涉及QRS波群的描述方法、分类方法和训练数据集这三个重要影响因素。     

兽医中药在宠物临床上的应用

本文系统综述了我国兽医中药在宠物临床上的应用历史及概况。从兽医中药起源,到中药在宠物临床上的古今应用。重点针对宠物临床中常见病、多发病如犬猫皮肤寄生虫病、皮肤真菌病、胃肠道疾病、传染病、肝胆疾病、心肺疾病、腰病以及虚弱性疾病等等进行了归纳总结。同时指出,随着宠物饲养社会功能的变化,宠物中药将会伴随着宠物市场的扩大迎来更大的发展空间。     

Effective Automated Feature Construction and Selection for Classification of Biological Sequences

Background

Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.

Methodology

We present an algorithmic framework (EFFECT) for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.

Results

To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification of a specific signal. Code, documentation, and all data for the applications presented here are provided for the community at http://www.cs.gmu.edu/~ashehu/?q=OurTools.     

Specific Laboratory Test for Diagnosis of Multiple Sclerosis

Lymphocytes from patients with multiple sclerosis are much more susceptible to the inhibitory activity of linoleic acid (0·08 mg/ml) when tested for sensitization to thyroid by the macrophage electrophoretic mobility test (91% inhibition) than are those from normal subjects (57% inhibition). Cells from patients with a variety of other neurological diseases give 47% inhibition with linoleic acid. These differences are specific for multiple sclerosis and can be used as an in-vitro diagnostic test for the disease. Nearly 43% of clinically normal near relatives of patients with multiple sclerosis show an “anomalous” figure of about 77%; in the remainder the figure is the same as in the general population (57%). An anomalous result is compatible with lifelong freedom from M.S. Possibly a congenital anomalous handling of unsaturated fatty acids is a constant feature of the disease.     

基因芯片数据分析方法研究进展

基因芯片技术的出现改变了生物医学研究的前景,其产生的海量数据是限制其发展的瓶颈问题。为提取其中所隐含的有价值的信息,在基因芯片数据分析的复杂计算工具和方法方面近年来有很多尝试。本文对近5年来基因芯片表达数据的分类分析方法进行综述,既分类比较了以聚类分析为基础的分类方法,也吸收了当前应用数据挖掘、信息融合等系统生物学思路的研究技术,并对数据的分析结果进行评价。     

银杏品种类群的模糊聚类划分

对４２个银杏核用品种的１３个性状特征进行系统聚类分析和主成份分析．根据系统聚类分析树状图和主成份坐标点图,将银杏品种划分为５个主要类群,并对其进行了简要分析。