971 resultados para Immunologic Tests -- methods


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Since the damage of the onion thrips (Thrips tabaci Lindemann) first occurred on white cabbage in Hungary several observations have been carried out, both in Hungary and abroad, to assess varietal resistance. The use of a new evaluation method for field screening is described and the result of the monitoring of 64 varieties is reported. The most susceptible varieties were ‘Bejo 1860’, ‘SG 3164’, ‘Quisto’, ‘Green Gem’ and ‘Ramada’. On the other hand, ‘Golden Cross’, ‘Balashi’, ‘Riana’, ‘Autumn Queen’, ‘Leopard’, Ama-Daneza’ and ‘Galaxy’ suffered the least damage under natural infestation. Methods for testing the patterns of resistance are also described and evaluated. In case of plants at the few leaf growth stage significant negative correlation was found between egg mortality and the egg laying preference of adults. The results of the other antibiotic and antixenotic tests were greatly affected by differences in the physiological age and condition of the varieties.

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Purpose. The Internet has provided an unprecedented opportunity for psychotropic medication consumers, a traditionally silenced group in clinical trial research, to have voice by contributing to the construction of drug knowledge in an immediate, direct manner. Currently, there are no systematic appraisals of the potential of online consumer drug reviews to contribute to drug knowledge. The purpose of this research was to explore the content of drug information on various websites representing themselves as consumer- and expert-constructed, and as a practical consideration, to examine how each source may help and hinder treatment decision-making.^ Methodology. A mixed-methods research strategy utilizing a grounded theory approach was used to analyze drug information on 5 exemplar websites (3 consumer- and 2 expertconstructed) for 2 popularly prescribed psychotropic drugs (escitalopram and quetiapine). A stratified simple random sample was used to select 1,080 consumer reviews from the websites (N=7,114) through February 2009. Text was coded using QDA Miner 3.2 software by Provalis Research. A combination of frequency tables, descriptive excerpts from text, and chi-square tests for association were used throughout analyses.^ Findings. The most frequently mentioned effects by consumers taking either drug were related to psychological/behavioral symptoms and sleep. Consumers reported many of the same effects as found on expert health sites, but provided more descriptive language and situational examples. Expert labels of less serious on certain effects were not congruent with the sometimes tremendous burden described by consumers. Consumers mentioned more than double the themes mentioned in expert text, and demonstrated a diversity and range of discourses around those themes.^ Conclusions. Drug effects from each source were complete relative to the information provided in the other, but each also offered distinct advantages. Expert health sites provided concise summaries of medications’ effects, while consumer reviews had the added advantage of concrete descriptions and greater context. In short, consumer reviews better prepared potential consumers for what it’s like to take psychotropic drugs. Both sources of information benefit clinicians and consumers in making informed treatment-related decisions. Social work practitioners are encouraged to thoughtfully utilize online consumer drug reviews as a legitimate additional source for assisting clients in learning about treatment options.^

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Elemental analysis can become an important piece of evidence to assist the solution of a case. The work presented in this dissertation aims to evaluate the evidential value of the elemental composition of three particular matrices: ink, paper and glass. In the first part of this study, the analytical performance of LIBS and LA-ICP-MS methods was evaluated for paper, writing inks and printing inks. A total of 350 ink specimens were examined including black and blue gel inks, ballpoint inks, inkjets and toners originating from several manufacturing sources and/or batches. The paper collection set consisted of over 200 paper specimens originating from 20 different paper sources produced by 10 different plants. Micro-homogeneity studies show smaller variation of elemental compositions within a single source (i.e., sheet, pen or cartridge) than the observed variation between different sources (i.e., brands, types, batches). Significant and detectable differences in the elemental profile of the inks and paper were observed between samples originating from different sources (discrimination of 87–100% of samples, depending on the sample set under investigation and the method applied). These results support the use of elemental analysis, using LA-ICP-MS and LIBS, for the examination of documents and provide additional discrimination to the currently used techniques in document examination. In the second part of this study, a direct comparison between four analytical methods (µ-XRF, solution-ICP-MS, LA-ICP-MS and LIBS) was conducted for glass analyses using interlaboratory studies. The data provided by 21 participants were used to assess the performance of the analytical methods in associating glass samples from the same source and differentiating different sources, as well as the use of different match criteria (confidence interval (±6s, ±5s, ±4s, ±3s, ±2s), modified confidence interval, t-test (sequential univariate, p=0.05 and p=0.01), t-test with Bonferroni correction (for multivariate comparisons), range overlap, and Hotelling's T2 tests. Error rates (Type 1 and Type 2) are reported for the use of each of these match criteria and depend on the heterogeneity of the glass sources, the repeatability between analytical measurements, and the number of elements that were measured. The study provided recommendations for analytical performance-based parameters for µ-XRF and LA-ICP-MS as well as the best performing match criteria for both analytical techniques, which can be applied now by forensic glass examiners.

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The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when sample size is less than one hundred and for such distributions, the kurtosis test is most powerful provided the distribution is leptokurtic or platykurtic. The Shapiro-Wilk test remains the most powerful test for asymmetric distributions. We conclude that different tests are suitable under different characteristics of alternative distributions.

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Microarray platforms have been around for many years and while there is a rise of new technologies in laboratories, microarrays are still prevalent. When it comes to the analysis of microarray data to identify differentially expressed (DE) genes, many methods have been proposed and modified for improvement. However, the most popular methods such as Significance Analysis of Microarrays (SAM), samroc, fold change, and rank product are far from perfect. When it comes down to choosing which method is most powerful, it comes down to the characteristics of the sample and distribution of the gene expressions. The most practiced method is usually SAM or samroc but when the data tends to be skewed, the power of these methods decrease. With the concept that the median becomes a better measure of central tendency than the mean when the data is skewed, the tests statistics of the SAM and fold change methods are modified in this thesis. This study shows that the median modified fold change method improves the power for many cases when identifying DE genes if the data follows a lognormal distribution.

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Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

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BACKGROUND: KRAS mutation testing is required to select patients with metastatic colorectal cancer (CRC) to receive anti-epidermal growth factor receptor antibodies, but the optimal KRAS mutation test method is uncertain. METHODS: We conducted a two-site comparison of two commercial KRAS mutation kits - the cobas KRAS Mutation Test and the Qiagen therascreen KRAS Kit - and Sanger sequencing. A panel of 120 CRC specimens was tested with all three methods. The agreement between the cobas test and each of the other methods was assessed. Specimens with discordant results were subjected to quantitative massively parallel pyrosequencing (MPP). DNA blends were tested to determine detection rates at 5% mutant alleles. RESULTS: Reproducibility of the cobas test between sites was 98%. Six mutations were detected by cobas that were not detected by Sanger, and five were confirmed by MPP. The cobas test detected eight mutations which were not detected by the therascreen test, and seven were confirmed by MPP. Detection rates with 5% mutant DNA blends were 100% for the cobas and therascreen tests and 19% for Sanger. CONCLUSION: The cobas test was reproducible between sites, and detected several mutations that were not detected by the therascreen test or Sanger. Sanger sequencing had poor sensitivity for low levels of mutation.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

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In Czech schools two teaching methods of reading are used: the analytic-synthetic (conventional) and genetic (created in the 1990s). They differ in theoretical foundations and in methodology. The aim of this paper is to describe the above mentioned theoretical approaches and present the results of study that followed the differences in the development of initial reading skills between these methods. A total of 452 first grade children (age 6-8) were assessed by a battery of reading tests at the beginning and at the end of the first grade and at the beginning of the second grade. 350 pupils participated all three times. Based on data analysis the developmental dynamics of reading skills in both methods and the main differences in several aspects of reading abilities (e.g. the speed of reading, reading technique, error rate in reading) are described. The main focus is on the reading comprehension development. Results show that pupils instructed using genetic approach scored significantly better on used reading comprehension tests, especially in the first grade. Statistically significant differences occurred between classes independently of each method. Therefore, other factors such as teacher´s role and class composition are discussed.

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Purpose: Stereopsis is the perception of depth based on retinal disparity. Global stereopsis depends on the process of random dot stimuli and local stereopsis depends on contour perception. The aim of this study was to correlate 3 stereopsis tests: TNO®, StereoTA B®, and Fly Stereo Acuity Test® and to study the sensitivity and correlation between them, using TNO® as the gold standard. Other variables as near convergence point, vergences, symptoms and optical correction were correlated with the 3 tests. Materials and Methods: Forty-nine students from Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL), aged 18-26 years old were included. Results: The stereopsis mean (standard-deviation-SD) values in each test were: TNO® = 87.04” ±84.09”; FlyTest® = 38.18” ±34.59”; StereoTA B® = 124.89’’ ±137.38’’. About the coefficient of determination: TNO® and StereoTA B® with R2 = 0.6 e TNO® and FlyTest® with R2 =0.2. Pearson correlation coefficient shows a positive correlation between TNO® and StereoTA B® (r = 0.784 with α = 0.01). Phi coefficient shows a strong and positive association between TNO® and StereoTA B® (Φ = 0.848 with α = 0.01). In the ROC Curve, the StereoTA B® has an area under the curve bigger than the FlyTest® with a sensivity of 92.3% for 94.4% of specificity, so it means that the test is sensitive with a good discriminative power. Conclusion: We conclude that the use of Stereopsis tests to study global Stereopsis are an asset for clinical use. This type of test is more sensitive, revealing changes in Stereopsis when it is actually changed, unlike the test Stereopsis, which often indicates normal Stereopsis, camouflaging a Stereopsis change. We noted also that the StereoTA B ® is very sensitive and despite being a digital application, possessed good correlation with the TNO®.

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Habitat fragmentation and the consequently the loss of connectivity between populations can reduce the individuals interchange and gene flow, increasing the chances of inbreeding, and the increase the risk of local extinction. Landscape genetics is providing more and better tools to identify genetic barriers.. To our knowledge, no comparison of methods in terms of consistency has been made with observed data and species with low dispersal ability. The aim of this study is to examine the consistency of the results of five methods to detect barriers to gene flow in a Mediterranean pine vole population Microtus duodecimcostatus: F-statistics estimations, Non-Bayesian clustering, Bayesian clustering, Boundary detection and Simple/Partial Mantel tests. All methods were consistent in detecting the stream as a non-genetic barrier. However, no consistency in results among the methods were found regarding the role of the highway as a genetic barrier. Fst, Bayesian clustering assignment test and Partial Mantel test identifyed the highway as a filter to individual interchange. The Mantel tests were the most sensitive method. Boundary detection method (Monmonier’s Algorithm) and Non-Bayesian approaches did not detect any genetic differentiation of the pine vole due to the highway. Based on our findings we recommend that the genetic barrier detection in low dispersal ability populations should be analyzed with multiple methods such as Mantel tests, Bayesian clustering approaches because they show more sensibility in those scenarios and with boundary detection methods by having the aim of detect drastic changes in a variable of interest between the closest individuals. Although simulation studies highlight the weaknesses and the strengths of each method and the factors that promote some results, tests with real data are needed to increase the effectiveness of genetic barrier detection.

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We present an IP-based nonparametric (revealed preference) testing procedure for rational consumption behavior in terms of general collective models, which include consumption externalities and public consumption. An empirical application to data drawn from the Russia Longitudinal Monitoring Survey (RLMS) demonstrates the practical usefulness of the procedure. Finally, we present extensions of the testing procedure to evaluate the goodness-of-…t of the collective model subject to testing, and to quantify and improve the power of the corresponding collective rationality tests.

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Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

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Background: The appearance of symptoms compatible with systemic autoimmune diseases has been described in relation to several viral infections like HIV, cytomegalovirus and especially PVB19, depending on the evolution of the immunological condition of the host and their age. We present a young immunocompetent male patient, with clinical manifestations simulating systemic lupus erythematosus (SLE) with important activation of cytokines. Methods: For quantification of the different cytokines in plasma, a commercially available multiplex bead immunoassay, based on the Luminex platform (Cat # HSCYTO-60SK-08, Milliplex® MAP High Sensitivity, Millipore), was used according to the manufacturer’s instructions. All samples were run in duplicate and the data (mean fluorescence intensity) were analyzed using a Luminex reader. The mean concentration was calculated using a standard curve. Results: The clinical evolution was favourable without the need for any specific treatment, showing complete recovery after two months. Whilst the symptoms and viral charge were disappearing, the anti-DNA continued to increase and we demonstrate important activation of IL-10, IL-6 and TNFα cytokines as a result of a hyperstimulating response by an immunocompetent hyperfunctional system, which persists after clinical improvement. We should emphasize the behaviour of two cytokines: IL-12p70 and IL-2, which showed opposite tendencies. Conclusions: Viral infections, especially PVB19, can produce or simulate several autoimmune diseases as a hyperstimulation response from an immunocompetent hyperfunctional system. Consequently, a persistent increase of autoantobodies and important activation of cytokines, even after clinical improvement and seroconversion, can be demonstrated.