184 resultados para Immunoassay, Assay validation, Accuracy, recision, Hyperinsulinemia


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Background: Mutations in TP53 are common events during carcinogenesis. In addition to gene mutations, several reports have focused on TP53 polymorphisms as risk factors for malignant disease. Many studies have highlighted that the status of the TP53 codon 72 polymorphism could influence cancer susceptibility. However, the results have been inconsistent and various methodological features can contribute to departures from Hardy-Weinberg equilibrium, a condition that may influence the disease risk estimates. The most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or via a separate method. Results: We developed two new genotyping methods for TP53 codon 72 polymorphism detection: Denaturing High Performance Liquid Chromatography (DHPLC) and Dot Blot hybridization. These methods were compared with Restriction Fragment Length Polymorphism (RFLP) using two different restriction enzymes. We observed high agreement among all methodologies assayed. Dot-blot hybridization and DHPLC results were more highly concordant with each other than when either of these methods was compared with RFLP. Conclusions: Although variations may occur, our results indicate that DHPLC and Dot Blot hybridization can be used as reliable screening methods for TP53 codon 72 polymorphism detection, especially in molecular epidemiologic studies, where high throughput methodologies are required.

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P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

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The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

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Single interface flow systems (SIFA) present some noteworthy advantages when compared to other flow systems, such as a simpler configuration, a more straightforward operation and control and an undemanding optimisation routine. Moreover, the plain reaction zone establishment, which relies strictly on the mutual inter-dispersion of the adjoining solutions, could be exploited to set up multiple sequential reaction schemes providing supplementary information regarding the species under determination. In this context, strategies for accuracy assessment could be favourably implemented. To this end, the sample could be processed by two quasi-independent analytical methods and the final result would be calculated after considering the two different methods. Intrinsically more precise and accurate results would be then gathered. In order to demonstrate the feasibility of the approach, a SIFA system with spectrophotometric detection was designed for the determination of lansoprazole in pharmaceutical formulations. Two reaction interfaces with two distinct pi-acceptors, chloranilic acid (CIA) and 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ) were implemented. Linear working concentration ranges between 2.71 x 10(-4) to 8.12 x 10(-4) mol L(-1) and 2.17 x 10(-4) to 8.12 x 10(-4) mol L(-1) were obtained for DDQ and CIA methods, respectively. When compared with the results furnished by the reference procedure, the results showed relative deviations lower than 2.7%. Furthermore. the repeatability was good, with r.s.d. lower than 3.8% and 4.7% for DDQ and CIA methods, respectively. Determination rate was about 30 h(-1). (C) 2009 Elsevier B.V. All rights reserved.

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Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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Background: Although the Clock Drawing Test (CDT) is the second most used test in the world for the screening of dementia, there is still debate over its sensitivity specificity, application and interpretation in dementia diagnosis. This study has three main aims: to evaluate the sensitivity and specificity of the CDT in a sample composed of older adults with Alzheimer`s disease (AD) and normal controls; to compare CDT accuracy to the that of the Mini-mental State Examination (MMSE) and the Cambridge Cognitive Examination (CAMCOG), and to test whether the association of the MMSE with the CDT leads to higher or comparable accuracy as that reported for the CAMCOG. Methods: Cross-sectional assessment was carried out for 121 AD and 99 elderly controls with heterogeneous educational levels from a geriatric outpatient clinic who completed the Cambridge Examination for Mental Disorder of the Elderly (CAMDEX). The CDT was evaluated according to the Shulman, Mendez and Sunderland scales. Results: The CDT showed high sensitivity and specificity. There were significant correlations between the CDT and the MMSE (0.700-0.730; p < 0.001) and between the CDT and the CAMCOG (0.753-0.779; p < 0.001). The combination of the CDT with the MMSE improved sensitivity and specificity (SE = 89.2-90%; SP = 71.7-79.8%). Subgroup analysis indicated that for elderly people with lower education, sensitivity and specificity were both adequate and high. Conclusions: The CDT is a robust screening test when compared with the MMSE or the CAMCOG, independent of the scale used for its interpretation. The combination with the MMSE improves its performance significantly, becoming equivalent to the CAMCOG.

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The ""Short Cognitive Performance Test"" (Syndrom Kurztest, SKT) is a cognitive screening battery designed to detect memory and attention deficits. The aim of this study was to evaluate the diagnostic accuracy of the SKT as a screening tool for mild cognitive impairment (MCI) and dementia. A total of 46 patients with Alzheimer`s disease (AD), 82 with MCI, and 56 healthy controls were included in the study. Patients and controls were allocated into two groups according to educational level (< 8 years or > 8 years). ROC analyses suggested that the SKT adequately discriminates AD from non-demented subjects (MCI and controls), irrespective of the education group. The test had good sensitivity to discriminate MCI from unimpaired controls in the sub-sample of individuals with more than 8 years of schooling. Our findings suggest that the SKT is a good screening test for cognitive impairment and dementia. However, test results must be interpreted with caution when administered to less-educated individuals.

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The objective of this study was to validate the Piper Fatigue Scale-Revised (PFS-R) for use in Brazilian culture. Translation of the PFS-R into Portuguese and validity and reliability tests were performed. Convenience samples in Brazil we as follows: 584 cancer patients (mean age 57 +/- 13 years; 51.3% female); 184 caregivers (mean age 50 +/- 12.7 years; 65.8% female); and 189 undergraduate nursing students (mean age 21.6 +/- 2.8 years; 96.2% female); Instruments used were as follows: Brazilian PFS, Beck Depression Inventory (BDI), and Karnofsky Performance Scale (KPS). The 22 items of the Brazilian PFS loaded well (factor loading > 0.35) on three dimensions identified by factor analysis (behavioral, affective, and sensorial-psychological). These dimensions explained 65% of the variance. Internal consistency reliability was very good (Cronbach`s alpha ranged from 0.841 to 0.943 for the total scale and its dimensions). Cancer patients and their caregivers completed the Brazilian PFS twice for test-retest reliability and results showed good stability (Pearson`s r a parts per thousand yenaEuro parts per thousand 0,60, p < 0,001). Correlations among the Brazilian PFS and other scales were significant, in hypothesized directions, and mostly moderate contributing to divergent (Brazilian PFS x KPS) and convergent validity (Brazilian PFS x BDI). Mild, moderate, and severe fatigue in patients were reported by 73 (12.5%), 167 (28.6%), and 83 (14.2%), respectively. Surprisingly, students had the highest mean total fatigue scores; no significant differences were observed between patients and caregivers showing poor discriminant validity. While the Brazilian PFS is a reliable and valid instrument to measure fatigue in Brazilian cancer patients, further work is needed to evaluate the discriminant validity of the scale in Brazil.

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Background: There is growing demand for the adoption of qualification systems for health care practices. This study is aimed at describing the development and validation of indicators for evaluation of biologic occupational risk control programs. Methods: The study involved 3 stages: (1) setting up a research team, (2) development of indicators, and (3) validation of the indicators by a team of specialists recruited to validate each attribute of the developed indicators. The content validation method was used for the validation, and a psychometric scale was developed for the specialists` assessment. A consensus technique was used, and every attribute that obtained a Content Validity Index of at least 0.75 was approved. Results: Eight indicators were developed for the evaluation of the biologic occupational risk prevention program, with emphasis on accidents caused by sharp instruments and occupational tuberculosis prevention. The indicators included evaluation of the structure, process, and results at the prevention and biologic risk control levels. The majority of indicators achieved a favorable consensus regarding all validated attributes. Conclusion: The developed indicators were considered validated, and the method used for construction and validation proved to be effective.

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This study tested the concurrent and construct validity of a newly developed OMNI-Kayak Scale, testing 8 male kayakers who performed a flatwater load-incremented ""shuttle"" test over a 500-m course and 3 estimation-production trials over a 1,000-m course. Velocity, blood lactate concentration, heart rate, and rating of perceived exertion (RPE), using the OMNI-Kayak RPE Scale and the Borg 6-20 Scale were recorded. OMNI-Kayak Scale RPE was highly correlated with velocity, the Borg 6-20 Scale RPE, blood lactate, and heart rate for both load-incremented test (rs=.87-.96), and estimation trials (rs=.75-.90). There were no significant differences among velocities, heart rate and blood lactate concentration between estimation and production trials. The OMNI-Kayak RPE Scale showed concurrent and construct validity in assessing perception of effort in flatwater kayaking and is a valid tool for self-regulation of exercise intensity.

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Background: The Burns Specific Health Scale-Revised (BSHS-R) is of easy application, can be self-administered, and it is considered a good scale to evaluate various important life aspects of burn victims. Objectives: To translate and culturally adapt the BSHS-R into the Brazilian-Portuguese language and to evaluate the internal consistency and convergent validity of the translated BSHS-R. Methods: The cultural adaptation of the BSHS-R included translation and back-translation, discussions with professionals and patients to ensure conceptual equivalence, semantic evaluation, and pre-test of the instrument. The Final Brazilian-Portuguese Version (FBPV) of the BSHS-R was tested on a group of 115 burn patients for internal consistency and validity of construct (using the Rosenberg Self-Esteem Scale (RSES) and the Beck Depression Inventory (BDI)). Results: All values of Cronbach`s alpha were greater than. 8, demonstrating that the internal consistency of the FBPV was very high. Self-esteem was highly correlated with affect and body image (r = .59, p < .001), and with interpersonal relationships (T = .51, p < .001). Correlations between the domains of the FBPV and the BDI were all negative but larger in magnitude than the correlations with RSES. Depression was highly correlated with affect and body image (r = -77, p < .001), and with interpersonal relationships (r = -67, p < .001). Conclusions: The results showed that the adapted version of the BSHS-R into Brazilian-Portuguese fulfills the validity and reliability criteria required from an instrument of health status assessment for burn patients. (C) 2008 Elsevier Ltd and ISBI. All rights reserved.

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Appropriate pain assessment is very important for managing chronic pain. Given the cultural differences in verbally expressing pain and in psychosocial problems, specific tools are needed. The goal of this study was to identify and validate Brazilian pain descriptors. A purposive sample of health professionals and chronic pain patients was recruited. Four studies were conducted using direct and indirect psychophysical methods: category estimation, magnitude estimation, and magnitude estimation and tine-length. Results showed the descriptors which best describe chronic pain in Brazilian culture and demonstrated that there is not a significant correlation between patients and health professionals and that the psychophysical scale of judgment of pain descriptors is valid, stable, and consistent. Results reinforced that the translations of word descriptors and research tools into another language may be inappropriate, owing to differences in perception and communication and the inadequacy of exact translations to reflect the intended meaning. Given the complexity of the chronic pain, personal suffering involved, and the need for accurate assessment of chronic pain using descriptors stemming from Brazilian culture and language, it is essential to investigate the most adequate words to describe chronic pain. Although it requires more refinement, the Brazilian chronic pain descriptors can be used further to develop a multidimensional pain assessment tool that is culturally sensitive. (C) 2009 by the American Society for Pain Management Nursing

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A technique for improving the performance of an OSNR monitor based on a polarisation nulling method with the downhill simplex algorithm is demonstrated. Establishing a compromise between accuracy and acquisition time, the monitor has been calibrated to 0.72 dB/390 ms and 0.98 dB/320 ms, over a range of nearly 21 dB. As far as is known, these are the best values achieved with such an OSNR monitoring method.

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The activity of validating identified requirements for an information system helps to improve the quality of a requirements specification document and, consequently, the success of a project. Although various different support tools to requirements engineering exist in the market, there is still a lack of automated support for validation activity. In this context, the purpose of this paper is to make up for that deficiency, with the use of an automated tool, to provide the resources for the execution of an adequate validation activity. The contribution of this study is to enable an agile and effective follow-up of the scope established for the requirements, so as to lead the development to a solution which would satisfy the real necessities of the users, as well as to supply project managers with relevant information about the maturity of the analysts involved in requirements specification.