266 resultados para DCA Vantage
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BACKGROUND Measurement of HbA1c is the most important parameter to assess glycemic control in diabetic patients. Different point-of-care devices for HbA1c are available. The aim of this study was to evaluate two point-of-care testing (POCT) analyzers (DCA Vantage from Siemens and Afinion from Axis-Shield). We studied the bias and precision as well as interference from carbamylated hemoglobin. METHODS Bias of the POCT analyzers was obtained by measuring 53 blood samples from diabetic patients with a wide range of HbA1c, 4%-14% (20-130 mmol/mol), and comparing the results with those obtained by the laboratory method: HPLC HA 8160 Menarini. Precision was performed by 20 successive determinations of two samples with low 4.2% (22 mmol/mol) and high 9.5% (80 mmol/mol) HbA1c values. The possible interference from carbamylated hemoglobin was studied using 25 samples from patients with chronic renal failure. RESULTS The means of the differences between measurements performed by each POCT analyzer and the laboratory method (95% confidence interval) were: 0.28% (p<0.005) (0.10-0.44) for DCA and 0.27% (p<0.001) (0.19-0.35) for Afinion. Correlation coefficients were: r=0.973 for DCA, and r=0.991 for Afinion. The mean bias observed by using samples from chronic renal failure patients were 0.2 (range -0.4, 0.4) for DCA and 0.2 (-0.2, 0.5) for Afinion. Imprecision results were: CV=3.1% (high HbA1c) and 2.97% (low HbA1c) for DCA, CV=1.95% (high HbA1c) and 2.66% (low HbA1c) for Afinion. CONCLUSIONS Both POCT analyzers for HbA1c show good correlation with the laboratory method and acceptable precision.
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Aims: Measurement of glycated hemoglobin (HbA1c) is an important indicator of glucose control over time. Point-of-care (POC) devices allow for rapid and convenient measurement of HbA1c, greatly facilitating diabetes care. We assessed two POC analyzers in the Peruvian Amazon where laboratory-based HbA1c testing is not available.
Methods: Venous blood samples were collected from 203 individuals from six different Amazonian communities with a wide range of HbA1c, 4.4-9.0% (25-75 mmol/mol). The results of the Afinion AS100 and the DCA Vantage POC analyzers were compared to a central laboratory using the Premier Hb9210 high-performance liquid chromatography (HPLC) method. Imprecision was assessed by performing 14 successive tests of a single blood sample.
Results: The correlation coefficient r for POC and HPLC results was 0.92 for the Afinion and 0.93 for the DCA Vantage. The Afinion generated higher HbA1c results than the HPLC (mean difference = +0.56% [+6 mmol/mol]; p < 0.001), as did the DCA Vantage (mean difference = +0.32% [4 mmol/mol]). The bias observed between POC and HPLC did not vary by HbA1c level for the DCA Vantage (p = 0.190), but it did for the Afinion (p < 0.001). Imprecision results were: CV = 1.75% for the Afinion, CV = 4.01% for the DCA Vantage. Sensitivity was 100% for both devices, specificity was 48.3% for the Afinion and 85.1% for the DCA Vantage, positive predictive value (PPV) was 14.4% for the Afinion and 34.9% for the DCA Vantage, and negative predictive value (NPV) for both devices was 100%. The area under the receiver operating characteristic (ROC) curve was 0.966 for the Afinion and 0.982 for the DCA Vantage. Agreement between HPLC and POC in classifying diabetes and prediabetes status was slight for the Afinion (Kappa = 0.12) and significantly different (McNemar’s statistic = 89; p < 0.001), and moderate for the DCA Vantage (Kappa = 0.45) and significantly different (McNemar’s statistic = 28; p < 0.001).
Conclusions: Despite significant variation of HbA1c results between the Afinion and DCA Vantage analyzers compared to HPLC, we conclude that both analyzers should be considered in health clinics in the Peruvian Amazon for therapeutic adjustments if healthcare workers are aware of the differences relative to testing in a clinical laboratory. However, imprecision and bias were not low enough to recommend either device for screening purposes, and the local prevalence of anemia and malaria may interfere with diagnostic determinations for a substantial portion of the population.
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Three mu(1.5)-dicyanamide bridged Mn(II) and Co(II) complexes having molecular formula [Mn(dca)(2)(H2O)(2)](n)center dot(hmt)(n) (1), [Co(dca)(2) (H2O)(2)](n)center dot(hmt)(n) (2) and [Co(dca)(2)(bpds)](n) (3) [dca = dicyanamide; hmt = hexamethylenetetramine; bpds = 4,4'-bipyridyl disulfide] have been synthesized and characterized by single crystal X-ray diffraction study, low temperature (300-2 K) magnetic measurement and thermal behavior. The X-ray diffraction analysis of 1 and 2 reveals that they are isostructural, comprising of 1D coordination polymers [M(dca)(2)(H2O)(2)](n) [M = Mn(II), Co(II) for 1 and 2. respectively] with uncoordinated hmt molecules located among the chains. The [M(dca)(2)(H2O)(2)](n) chains and the lattice hint molecules are connected through H-bonds resulting in a 3D supramolecular architecture. The octahedral N4O2 chromophore surrounding the metal ion forms via two trans located water oxygens and four nitrogens from four nitrile dca. Complex 3 is a 1D chain formed by two mu(1.5)-dca and one bridging bpds. The octahedral N-6 coordination sphere surrounding the cobalt ions comprises four nitrogens from dca and two from bpds. Low temperature magnetic study indicates small antiferromagnetic coupling for all the complexes. Best fit parameters for 1: J = -0.17 cm(-1), g = -2.03 with R = 6.1 x 10(-4), for 2, J = -0.50 cm(-1), and for 3, J = -0.95 cm(-1). (c) 2005 Elsevier B.V. All rights reserved.
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Includes bibliography
Agreement between HbA1c measured by DCA 2000 and by HPLC: effects of fetal hemoglobin concentrations
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In subjects with type 1 diabetes, persisting elevations of fetal hemoglobin (HbF) have been demonstrated. This study evaluated whether HbF levels typically seen in type 1 diabetes (up to 3%) interfere with glycohemoglobin determinations using a common immunologic method (DCA 2000).
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We compare eight pollen records reflecting climatic and environmental change from the tropical Andes. Our analysis focuses on the last 50 ka, with particular emphasis on the Pleistocene to Holocene transition. We explore ecological grouping and downcore ordination results as two approaches for extracting environmental variability from pollen records. We also use the records of aquatic and shoreline vegetation as markers for lake level fluctuations, and precipitation change. Our analysis focuses on the signature of millennial-scale variability in the tropical Andes, in particular, Heinrich stadials and Greenland interstadials. We identify rapid responses of the tropical vegetation to this climate variability, and relate differences between sites to moisture sources and site sensitivity.
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Ensuring the security of computers is a non-trivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emerged in the form of networks of hijacked zombie machines used to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These zombie machines are said to be infected with a dasiahotpsila - a malicious piece of software which is installed on a host machine and is controlled by a remote attacker, termed the dasiabotmaster of a botnetpsila. In this work, we use the biologically inspired dendritic cell algorithm (DCA) to detect the existence of a single hot on a compromised host machine. The DCA is an immune-inspired algorithm based on an abstract model of the behaviour of the dendritic cells of the human body. The basis of anomaly detection performed by the DCA is facilitated using the correlation of behavioural attributes such as keylogging and packet flooding behaviour. The results of the application of the DCA to the detection of a single hot show that the algorithm is a successful technique for the detection of such malicious software without responding to normally running programs.
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The dendritic cell algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a ‘context aware’ detection system. Previous applications of the DCA have included the detection of potentially malicious port scanning activity, where it has produced high rates of true positives and low rates of false positives. In this work we aim to compare the performance of the DCA and of a self-organizing map (SOM) when applied to the detection of SYN port scans, through experimental analysis. A SOM is an ideal candidate for comparison as it shares similarities with the DCA in terms of the data fusion method employed. It is shown that the results of the two systems are comparable, and both produce false positives for the same processes. This shows that the DCA can produce anomaly detection results to the same standard as an established technique.
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As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.
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Malicious users try to compromise systems using new techniques. One of the recent techniques used by the attacker is to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These compromised machines are said to be infected with malicious software termed a “bot”. In this paper, we investigate the correlation of behavioural attributes such as keylogging and packet flooding behaviour to detect the existence of a single bot on a compromised machine by applying (1) Spearman’s rank correlation (SRC) algorithm and (2) the Dendritic Cell Algorithm (DCA). We also compare the output results generated from these two methods to the detection of a single bot. The results show that the DCA has a better performance in detecting malicious activities.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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A análise das relações de similaridade florística entre comunidades geralmente conduz ao estabelecimento de padrões, condicionados por fatores diversos que determinam a ocorrência ou não das espécies em diferentes locais. Em busca de tais padrões, foram analisadas as relações de similaridade florística entre comunidades florestais localizadas na região do Planalto de Ibiúna, estado de São Paulo, Brasil. Incluíram-se na análise 21 fragmentos florestais e seis sítios em uma Reserva Florestal contínua, sendo que a composição florística e a estrutura da comunidade arbórea (DAP mínimo 5 cm) em cada local foram amostradas pelo método de quadrantes. Aplicaram-se dois métodos de análises multivariadas: 1) Análise de Correspondência Destendenciada (DCA), com base no índice de similaridade de Sørensen; e 2) Divisão Hierárquica Dicotômica (TWINSPAN). A similaridade florística foi mais elevada entre comunidades em estádios sucessionais semelhantes, especialmente se estivessem geograficamente próximas. Há um gradiente florístico associado à latitude, indicando tratar-se de uma região de transição entre biomas. Nos sítios situados na face norte da região de estudo estão presentes espécies que também ocorrem no cerradão e em floresta estacional semidecidual, enquanto nos sítios situados na face sul prevalecem espécies características da floresta ombrófila densa.
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Abelhas das orquídeas (Apini, Euglossina) apresentam distribuição principalmente Neotropical, com cerca de 200 espécies e cinco gêneros descritos. Muitos levantamentos locais de fauna estão disponíveis na literatura, mas estudos comparativos sobre a composição e distribuição dos Euglossina são ainda escassos. O objetivo deste estudo é analisar os dados disponíveis de 29 assembleias a fim de entender os padrões gerais de distribuição espacial nas áreas amostradas ao longo do Neotrópico. Métodos de ordenação (DCA e NMDS) foram utilizados para descrever os agrupamentos de assembleias de acordo com as ocorrências de abelhas das orquídeas. As localidades de florestas da América Central e da Amazônia formaram grupos coesos em ambas as análises, enquanto as localidades de Mata Atlântica ficaram mais dispersas nos gráficos. Localidades na margem leste da Amazônia aparecem como áreas de transição características entre esta sub-região e a Mata Atlântica. As análises de variância entre o primeiro eixo da DCA e variáveis selecionadas apresentaram valores significantes quanto à influência dos gradientes de latitude, longitude e precipitação, bem como das sub-regiões biogeográficas nos agrupamentos das assembleias. O padrão geral encontrado é congruente com os padrões biogeográficos previamente propostos para a região Neotropical. Os resultados do DCA auxiliam ainda a identificar, de forma independente, os elementos das faunas de cada uma das formações vegetais estudadas.
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When and how did the Brazilian Black movement appear in the social sciences? What are the theoretical approaches and explanations for the 20th century emergence and development? This article will address these principal issues by analyzing studies that have taken on the topic of collective black mobilization from various disciplinary vantage points, particularly, Sociology, History and Anthropology.