960 resultados para Parametric and semiparametric methods
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The in vitro susceptibility of dermatophytes to the azole antifungals itraconazole, fluconazole and ketoconazole was evaluated by broth macro and microdilution methods, according to recommendations of the CLSI, with some adaptations. Twenty nail and skin clinical isolates, four of Trichophyton mentagrophytes and 16 of T. rubrum were selected for the tests. Itraconazole minimal inhibitory concentrations (MIC) varied from < 0.03 to 0.25 µg/mL in the macrodilution and from < 0.03 to 0.5 µg/mL in the microdilution methods; for fluconazole, MICs were in the ranges of 0.5 to 64 µg/mL and 0.125 to 16 µg/mL by the macro and microdilution methods, respectively, and from < 0.03 to 0.5 µg/mL by both methods for ketoconazole. Levels of agreement between the two methods (± one dilution) were 70% for itraconazole, 45% for fluconazole and 85% for ketoconazole. It is concluded that the strains selected were inhibited by relatively low concentrations of the antifungals tested and that the two methodologies are in good agreement especially for itraconazole and ketoconazole.
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Adenovirus (AdV) respiratory infections are usually described as being associated with high mortality rates. Laboratory diagnosis is essential for the establishment of the appropriate therapy, and for guiding the implementation of preventive measures in order to prevent the spread of the infection. Aiming to analyze the sensitivity and specificity of the laboratorial diagnosis methods available, we compared antigen detection by indirect immunofluorescence assay (IF), and a specific nested polymerase chain reaction (PCR), to detect AdV in respiratory samples collected from patients admitted to hospital with acute respiratory disease. Positive samples were inoculated into a cell culture to confirm the results. We analyzed 381 samples from the nasopharyngeal aspirates collected during the year 2008; of these, 2.6% tested were positive for adenovirus through IF and 10% through PCR; positive isolation was obtained in 40% and 26% of these cases, respectively. Most infected patients were children under six months of age, and despite of the fact that a significant number of patients required intensive care, the mortality rate was low (5%). In conclusion, molecular methods were found to be useful for rapid diagnosis of adenovirus infections with higher sensitivity than antigen detection; their introduction permitted a significant increase in diagnoses of adenovirus infections.
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Fundação para a Ciência e a Tecnologia - SFRH/BD/27914/2006
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Introduction Trypanosoma cruzi, a flagellated protozoan, is the etiologic agent of Chagas disease, and it is estimated that approximately 5 million people in Brazil are infected with this parasite. This work aimed to compare the current diagnostic methods for Chagas disease, including conventional serological (IFAT and ELISA) and molecular techniques (PCR), to introduce PCR as an auxiliary technique. Methods A total of 106 chagasic patients were evaluated: 88 from endemic areas of Parana, 6 from São Paulo, 3 from Minas Gerais, 3 from Rio Grande do Sul, 1 from Bahia and 5 from the Santa Catarina T. cruzi outbreak. The samples were analyzed by conventional serological methods (IFAT, ELISA), hemoculture and PCR to confirm Chagas disease. Results When IFAT was used to determine antibody levels, the sensitivity was 81.7% for patients with the cardiac form of the disease and 100% for the other clinical forms. In contrast, ELISA showed 84% sensitivity and 100% specificity. The use of serological and molecular techniques and their implications for the diagnosis of Chagas disease in non-endemics area are discussed. Conclusions PCR constitutes an excellent support methodology for the laboratory diagnosis of Chagas disease due to its high sensitivity and specificity.
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The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.
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OBJECTIVE: To assess, in myocardium specimens obtained from necropsies, the correlation between the concentration of hydroxyproline, measured with the photocolorimetric method, and the intensity of fibrosis, determined with the morphometric method. METHODS: Left ventricle myocardium samples were obtained from 45 patients who had undergone necropsy, some of them with a variety of cardiopathies and others without any heart disease. The concentrations of hydroxyproline were determined with the photocolorimetric method. In the histologic sections from each heart, the myocardial fibrosis was quantified by using a light microscope with an integrating ocular lens. RESULTS: A median of, respectively, 4.5 and 4.3 mug of hydroxyproline/mg of dry weight was found in fixed and nonfixed left ventricle myocardium fragments. A positive correlation occurred between the hydroxyproline concentrations and the intensity of fibrosis, both in the fixed (Sr=+0.25; p=0.099) and in the nonfixed (Sr=+0.32; p=0.03) specimens. CONCLUSION: The biochemical methodology was proven to be adequate, and manual morphometry was shown to have limitations that may interfere with the statistical significance of correlations for the estimate of fibrosis intensity in the human myocardium.
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OBJECTIVE: To evaluate the performance of the turbidimetric method of C-reactive protein (CRP) as a measure of low-grade inflammation in patients admitted with non-ST elevation acute coronary syndromes (ACS). METHODS: Serum samples obtained at hospital arrival from 68 patients (66±11 years, 40 men), admitted with unstable angina or non-ST elevation acute myocardial infarction were used to measure CRP by the methods of nephelometry and turbidimetry. RESULTS: The medians of C-reactive protein by the turbidimetric and nephelometric methods were 0.5 mg/dL and 0.47 mg/dL, respectively. A strong linear association existed between the 2 methods, according to the regression coefficient (b=0.75; 95% C.I.=0.70-0.80) and correlation coefficient (r=0.96; P<0.001). The mean difference between the nephelometric and turbidimetric CRP was 0.02 ± 0.91 mg/dL, and 100% agreement between the methods in the detection of high CRP was observed. CONCLUSION: In patients with non-ST elevation ACS, CRP values obtained by turbidimetry show a strong linear association with the method of nephelometry and perfect agreement in the detection of high CRP.
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The technique of sentinel lymph node (SLN) dissection is a reliable predictor of metastatic disease in the lymphatic basin draining the primary melanoma. Reverse transcription-polymerase chain reaction (RT-PCR) is emerging as a highly sensitive technique to detect micrometastases in SLNs, but its specificity has been questioned. A prospective SLN study in melanoma patients was undertaken to compare in detail immunopathological versus molecular detection methods. Sentinel lymphadenectomy was performed on 57 patients, with a total of 71 SLNs analysed. SLNs were cut in slices, which were alternatively subjected to parallel multimarker analysis by microscopy (haematoxylin and eosin and immunohistochemistry for HMB-45, S100, tyrosinase and Melan-A/MART-1) and RT-PCR (for tyrosinase and Melan-A/MART-1). Metastases were detected by both methods in 23% of the SLNs (28% of the patients). The combined use of Melan-A/MART-1 and tyrosinase amplification increased the sensitivity of PCR detection of microscopically proven micrometastases. Of the 55 immunopathologically negative SLNs, 25 were found to be positive on RT-PCR. Notably, eight of these SLNs contained naevi, all of which were positive for tyrosinase and/or Melan-A/MART-1, as detected at both mRNA and protein level. The remaining 41% of the SLNs were negative on both immunohistochemistry and RT-PCR. Analysis of a series of adjacent non-SLNs by RT-PCR confirmed the concept of orderly progression of metastasis. Clinical follow-up showed disease recurrence in 12% of the RT-PCR-positive immunopathology-negative SLNs, indicating that even an extensive immunohistochemical analysis may underestimate the presence of micrometastases. However, molecular analyses, albeit more sensitive, need to be further improved in order to attain acceptable specificity before they can be applied diagnostically.
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National malaria control programmes have the responsibility to develop a policy for malaria disease management based on a set of defined criteria as efficacy, side effects, costs and compliance. These will fluctuate over time and national guidelines will require periodic re-assessment and revision. Changing a drug policy is a major undertaking that can take several years before being fully operational. The standard methods on which a decision can be taken are the in vivo and the in vitro tests. The latter allow a quantitative measurement of the drug response and the assessment of several drugs at once. However, in terms of drug policy change its results might be difficult to interpret although they may be used as an early warning system for 2nd or 3rd line drugs. The new WHO 14-days in vivo test addresses mainly the problem of treatment failure and of haematological parameters changes in sick children. It gives valuable information on whether a drug still `works'. None of these methods are well suited for large-scale studies. Molecular methods based on detection of mutations in parasite molecules targeted by antimalarial drugs could be attractive tools for surveillance. However, their relationship with in vivo test results needs to be established
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Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.
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An hemodialysis population in Central Brazil was screened by polymerase chain reaction (PCR) and serological methods to assess the prevalence of hepatitis C virus (HCV) infection and to investigate associated risk factors. All hemodialysis patients (n=428) were interviewed in eight dialysis units in Goiânia city. Blood samples were collected and serum samples screened for anti-HCV antibodies by an enzyme-linked immunosorbent assay (ELISA). Positive samples were retested for confirmation with a line immunoassay (LIA). All samples were also tested for HCV RNA by the PCR. An overall prevalence of 46.7% (CI 95%: 42-51.5) was found, ranging from 20.7% (CI 95%: 8.8-38.1) to 90.4% (CI 95%: 79.9-96.4) depending on the dialysis unit. Of the 428 patients, 185 were found to be seropositive by ELISA, and 167 were confirmed positive by LIA, resulting in an anti-HCV prevalence of 39%. A total of 131 patients were HCV RNA-positive. HCV viremia was present in 63.5% of the anti-HCV-positive patients and in 10.3% of the anti-HCV-negative patients. Univariate analysis of risk factors showed that the number of previous blood transfusions, transfusion of blood before mandatory screening for anti-HCV, length of time on hemodialysis, and treatment in multiple units were associated with HCV positivity. However, multivariate analysis revealed that blood transfusion before screening for anti-HCV and length of time on hemodialysis were significantly associated with HCV infection in this population. These data suggest that nosocomial transmission may play a role in the spread of HCV in the dialysis units studied. In addition to anti-HCV screening, HCV RNA detection is necessary for the diagnosis of HCV infection in hemodialysis patients.