943 resultados para DIAGNOSTICS
Resumo:
This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.
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The continued global spread and evolution of HIV diversity pose significant challenges to diagnostics and vaccine strategies. NIAID partnered with the FDA, WRAIR, academia, and industry to form a Viral Panel Working Group to design and prepare a panel of well-characterized current and diverse HIV isolates. Plasma samples that had screened positive for HIV infection and had evidence of recently acquired infection were donated by blood centers in North and South America, Europe, and Africa. A total of 80 plasma samples were tested by quantitative nucleic acid tests, p24 antigen, EIA, and Western blot to assign a Fiebig stage indicative of approximate time from initial infection. Evaluation of viral load using FDA-cleared assays showed excellent concordance when subtype B virus was tested, but lower correlations for subtype C. Plasma samples were cocultivated with phytohemagglutinin (PHA)-stimulated peripheral blood mononuclear cells (PBMCs) from normal donors to generate 30 viral isolates (50-80% success rate for samples with viral load >10,000 copies/ml), which were then expanded to 10(7)-10(9) virus copies per ml. Analysis of env sequences showed that sequences derived from cultured PBMCs were not distinguishable from those obtained from the original plasma. The pilot collection includes 30 isolates representing subtypes B, C, B/F, CRF04_cpx, and CRF02_AG. These studies will serve as a basis for the development of a comprehensive panel of highly characterized viral isolates that reflects the current dynamic and complex HIV epidemic, and will be made available through the External Quality Assurance Program Oversight Laboratory (EQAPOL).
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The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.
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Dengue fever is a mosquito-borne viral disease estimated to cause about 230 million infections worldwide every year, of which 25,000 are fatal. Global incidence has risen rapidly in recent decades with some 3.6 billion people, over half of the world's population, now at risk, mainly in urban centres of the tropics and subtropics. Demographic and societal changes, in particular urbanization, globalization, and increased international travel, are major contributors to the rise in incidence and geographic expansion of dengue infections. Major research gaps continue to hamper the control of dengue. The European Commission launched a call under the 7th Framework Programme with the title of 'Comprehensive control of Dengue fever under changing climatic conditions'. Fourteen partners from several countries in Europe, Asia, and South America formed a consortium named 'DengueTools' to respond to the call to achieve better diagnosis, surveillance, prevention, and predictive models and improve our understanding of the spread of dengue to previously uninfected regions (including Europe) in the context of globalization and climate change. The consortium comprises 12 work packages to address a set of research questions in three areas: Research area 1: Develop a comprehensive early warning and surveillance system that has predictive capability for epidemic dengue and benefits from novel tools for laboratory diagnosis and vector monitoring. Research area 2: Develop novel strategies to prevent dengue in children. Research area 3: Understand and predict the risk of global spread of dengue, in particular the risk of introduction and establishment in Europe, within the context of parameters of vectorial capacity, global mobility, and climate change. In this paper, we report on the rationale and specific study objectives of 'DengueTools'. DengueTools is funded under the Health theme of the Seventh Framework Programme of the European Community, Grant Agreement Number: 282589 Dengue Tools.
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In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.
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In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.
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This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.
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Abstract Background Invasive cervical cancer is the second most common malignant tumor affecting Brazilian women. Knowledge on Human Papillomavirus (HPV) genotypes in invasive cervical cancer cases is crucial to guide the introduction and further evaluate the impact of new preventive strategies based on HPV. We aimed to provide updated comprehensive data about the HPV types’ distribution in patients with invasive cervical cancer. Methods Fresh tumor tissue samples of histologically confirmed invasive cervical cancer were collected from 175 women attending two cancer reference hospitals from São Paulo State: ICESP and Hospital de Câncer de Barretos. HPV detection and genotyping were performed by the Linear Array HPV Genotyping Test (Roche Molecular Diagnostics, Pleasanton,USA). Results 170 out of 172 valid samples (99%) were HPV DNA positive. The most frequent types were HPV16 (77.6%), HPV18 (12.3%), HPV31 (8.8%), HPV33 (7.1%) and HPV35 (5.9%). Most infections (75%) were caused by individual HPV types. Women with adenocarcinoma were not younger than those with squamous cell carcinoma, as well, as women infected with HPV33 were older than those infected by other HPV types. Some differences between results obtained in the two hospitals were observed: higher overall prevalence of HPV16, absence of single infection by HPV31 and HPV45 was verified in HC-Barretos in comparison to ICESP patients. Conclusions To our knowledge, this is one of the largest studies made with fresh tumor tissues of invasive cervical cancer cases in Brazil. This study depicted a distinct HPV genotype distribution between two centers that may reflect the local epidemiology of HPV transmission among these populations. Due to the impact of these findings on cervical cancer preventive strategies, extension of this investigation to routine screening populations is warranted.
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Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.
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The complete surgical removal of disease is a desirable outcome particularly in oncology. Unfortunately much disease is microscopic and difficult to detect causing a liability to recurrence and worsened overall prognosis with attendant costs in terms of morbidity and mortality. It is hoped that by advances in optical diagnostic technology we could better define our surgical margin and so increase the rate of truly negative margins on the one hand and on the other hand to take out only the necessary amount of tissue and leave more unaffected non-diseased areas so preserving function of vital structures. The task has not been easy but progress is being made as exemplified by the presentations at the 2nd Scientific Meeting of the Head and Neck Optical Diagnostics Society (HNODS) in San Francisco in January 2010. We review the salient advances in the field and propose further directions of investigation.
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Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is known by its aggressiveness and lack of effective therapeutic options. Thus, improvement in current knowledge of molecular changes associated with pancreatic cancer is urgently needed to explore novel venues of diagnostics and treatment of this dismal disease. While there is mounting evidence that long noncoding RNAs (lncRNAs) transcribed from intronic and intergenic regions of the human genome may play different roles in the regulation of gene expression in normal and cancer cells, their expression pattern and biological relevance in pancreatic cancer is currently unknown. In the present work we investigated the relative abundance of a collection of lncRNAs in patients' pancreatic tissue samples aiming at identifying gene expression profiles correlated to pancreatic cancer and metastasis. Methods Custom 3,355-element spotted cDNA microarray interrogating protein-coding genes and putative lncRNA were used to obtain expression profiles from 38 clinical samples of tumor and non-tumor pancreatic tissues. Bioinformatics analyses were performed to characterize structure and conservation of lncRNAs expressed in pancreatic tissues, as well as to identify expression signatures correlated to tissue histology. Strand-specific reverse transcription followed by PCR and qRT-PCR were employed to determine strandedness of lncRNAs and to validate microarray results, respectively. Results We show that subsets of intronic/intergenic lncRNAs are expressed across tumor and non-tumor pancreatic tissue samples. Enrichment of promoter-associated chromatin marks and over-representation of conserved DNA elements and stable secondary structure predictions suggest that these transcripts are generated from independent transcriptional units and that at least a fraction is under evolutionary selection, and thus potentially functional. Statistically significant expression signatures comprising protein-coding mRNAs and lncRNAs that correlate to PDAC or to pancreatic cancer metastasis were identified. Interestingly, loci harboring intronic lncRNAs differentially expressed in PDAC metastases were enriched in genes associated to the MAPK pathway. Orientation-specific RT-PCR documented that intronic transcripts are expressed in sense, antisense or both orientations relative to protein-coding mRNAs. Differential expression of a subset of intronic lncRNAs (PPP3CB, MAP3K14 and DAPK1 loci) in metastatic samples was confirmed by Real-Time PCR. Conclusion Our findings reveal sets of intronic lncRNAs expressed in pancreatic tissues whose abundance is correlated to PDAC or metastasis, thus pointing to the potential relevance of this class of transcripts in biological processes related to malignant transformation and metastasis in pancreatic cancer.
Resumo:
This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.
Resumo:
INTRODUÇÃO: O ácido ascórbico (vitamina C) é comumente ingerido como suplemento vitamínico. É uma vitamina hidrossolúvel, excretada pela urina e pode interferir nos ensaios laboratoriais, como nas reações de oxirredução para detecção da glicosúria. OBJETIVO: Este trabalho tem como objetivo avaliar a interferência do ácido ascórbico na detecção de glicosúria pelo método de química seca por meio do uso de tiras reagentes. MATERIAIS E MÉTODOS: Amostras de urina foram avaliadas no analisador da marca Clinitek Atlas (Siemens Healthcare Diagnostics Inc., EUA). Foram selecionadas quatro amostras de urina com diferentes concentrações de glicose: 100 mg/dl, 250 mg/dl, 500 mg/dl e 1.000 mg/dl. Para cada concentração de glicose foram criadas cinco alíquotas, adicionando-se uma solução de ácido ascórbico 200 mg/dl, suficiente para obter uma concentração final de ácido ascórbico de 20 mg/dl no primeiro tubo, de 50 mg/dl no segundo tubo, de 270 mg/dl no terceiro tubo, de 1.000 mg/dl no quarto tubo e de 2.000 mg/dl no quinto tubo. Após essa adição, as amostras foram novamente avaliadas no analisador Clinitek Atlas. RESULTADOS: Nas amostras com concentração de 20 mg/dl de ácido, não se evidenciou interferência. Nas concentrações iguais e acima de 50 mg/dl, a interferência do ácido ascórbico se fez presente, sendo que o fato foi caracterizado pelos resultados falso negativos para detecção da glicose urinária. CONCLUSÃO: Os resultados demonstraram a interferência do ácido ascórbico no método da química seca (tiras reagentes), subestimando o nível de glicose urinária.
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The study of organic pollution in estuaries is very relevant as they are transitional zones, which control the fluxes of water, nutrients, particles and organisms from and to the continental margins, rivers and oceans. The aims of this study are:(1) to evaluate organic pollution in coastal sediments of Montevideo, Río de la Plata Estuary by a multi-biomarker approach, (2) to identify major sources of organic pollutants through qualitative analysis using molecular indices, (3) to assess the relative contribution of different sources of hydrocarbons through quantitative source apportionment employing (PCA/MLR) as chemometric technique. Sampling surveys were carried out in July 2009, January 2010 and March 2011 in 37 stations along the middle portion of the Río de la Plata Estuary across the coast of Montevideo. In each station surface (0–2 cm depth) sediment samples were taken with a 0.05 m2 van Veen grab. The Soxhlet extracted organic compounds included aliphatic hydrocarbons (AHs) and steroids, analysed by gas chromatograph with flame ionization detector (GC-FID), linear alkylbenzenes (LABs) and polycyclic aromatic hydrocarbons (PAHs) quantified by gas chromatograph with mass spectrometer (GC/MS). All biomarkers presented the highest concentrations in the stations of Montevideo Bay indicating high levels of organic pollution. The combination of molecular indices and the chemometric technique showed that major sources of AHs and PAHs are petroleum inputs and combustion, due to oil transport and refinement, harbour activities and vehicular emissions.Major sources of LABs and steroids are urban and domestic sewage. Identification, quantification and source assignment of those organic compounds are very important to assess pollution and to give tools to help minimize the inputs into the environment
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Background Adult community-acquired pneumonia (CAP) is a relevant worldwide cause of morbidity and mortality, however the aetiology often remains uncertain and the therapy is empirical. We applied conventional and molecular diagnostics to identify viruses and atypical bacteria associated with CAP in Chile. Methods We used sputum and blood cultures, IgG/IgM serology and molecular diagnostic techniques (PCR, reverse transcriptase PCR) for detection of classical and atypical bacteria (Mycoplasma pneumoniae, Chlamydia pneumoniae, Legionella pneumoniae) and respiratory viruses (adenovirus, respiratory syncytial virus (RSV), human metapneumovirus, influenza virus, parainfluenzavirus, rhinovirus, coronavirus) in adults >18 years old presenting with CAP in Santiago from February 2005 to September 2007. Severity was qualified at admission by Fine's pneumonia severity index. Results Overall detection in 356 enrolled adults were 92 (26%) cases of a single bacterial pathogen, 80 (22%) cases of a single viral pathogen, 60 (17%) cases with mixed bacterial and viral infection and 124 (35%) cases with no identified pathogen. Streptococcus pneumoniae and RSV were the most common bacterial and viral pathogens identified. Infectious agent detection by PCR provided greater sensitivity than conventional techniques. To our surprise, no relationship was observed between clinical severity and sole or coinfections. Conclusions The use of molecular diagnostics expanded the detection of viruses and atypical bacteria in adults with CAP, as unique or coinfections. Clinical severity and outcome were independent of the aetiological agents detected.