Analysis of correlation between cerebrospinal fluid and plasma HIV-1 RNA levels in patients with neurological opportunistic diseases

The question of whether HIV-1 RNA in cerebrospinal fluid (CSF) is derived from viral replication in the central nervous system or simply reflects the transit of infected lymphocytes from the blood compartment has long been a matter of debate. Some studies found no correlation between CSF and plasma viral load, whereas others did. The lack of a correlation between the two compartments suggests that the presence of HIV-1 RNA is not simply due to the passive passage of the virus from blood to CSF but rather due to intrathecal replication. To evaluate the correlation between plasma and CSF HIV-1 RNA levels and to identify situations in which there is no correlation between the two compartments, seventy patients were prospectively studied. The association between CSF and plasma viral load was evaluated in the total population and in subgroups of patients with similar characteristics. A correlation between the CSF and plasma compartments was observed for patients undergoing highly active antiretroviral therapy (HAART), those with a CD4 T lymphocyte count lower than 200 cells/mm³, and those with increased CSF protein content. On the other hand, no correlation was observed for patients without adequate virological control, who had a CD4 count higher than 200 cells/mm³ and who did not use HAART. The correlation between the two compartments observed in some patients suggests that CSF HIV-1 RNA levels may reflect plasma levels in these subjects. In contrast, the lack of a correlation between the two compartments in patients who were not on HAART and who had normal CSF proteins and a poor virological control possibly indicates compartmentalization of the virus in CSF and, consequently, plasma-independent intrathecal viral replication.

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Flow cytofluorometric analysis of the binding of Vicia villosa lectin to T lymphoblasts: lack of correlation with cytolytic function.

The relationship between the binding of Vicia villosa (VV) lectin and the expression of cytolytic function in T lymphoblasts has been investigated using flow cytofluorometric techniques. Spleen cells activated in vitro in 5-day mixed leukocyte cultures (MLC) were incubated sequentially with VV, rabbit anti-V antiserum, and fluoresceinated sheep anti-rabbit IgG. When these stained MLC cells were passed on a flow cytometer gated to exclude nonviable cells and small lymphocytes, a single heterogeneous peak of fluorescence was seen, as compared to control MLC cells that had not been incubated with VV. Fluorescence of lymphoblasts was dependent upon lectin dose and was eliminated when staining was performed in the presence of N-acetyl-D-galactosamine, the appropriate competitive sugar for VV. T cell blast populations activated against H-2, Mls, or parasite antigens all had comparable levels of fluorescence after staining with VV, although the cytolytic activity of these cells varied widely. Furthermore, when MLC lymphoblasts binding large or small amounts of VV were sorted on the basis of their relative fluorescence intensity and tested for cytolytic function, no appreciable difference in activity between the 2 populations was observed. These results are inconsistent with the hypothesis that VV binds selectively to cytolytic T lymphocytes.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Colloid cysts of the third ventricle: correlation of MR and CT findings with histology and chemical analysis.

Eight patients with colloid cysts of the third ventricle were examined with CT and MR. In six, surgical resection was performed and the material was subjected to histologic evaluation; the concentrations of trace elements were determined by particle-induced X-ray emission. Stereotaxic aspiration was performed in two. The investigation showed that colloid cysts are often iso- or hypodense relative to brain on CT (5/8), but sometimes have a center of increased density. Increased density did not correlate with increased concentration of calcium or other metals but did not correlate with high cholesterol content. Colloid cysts appear more heterogeneous on MR (6/8) than on CT (3/8), despite a homogeneous appearance at histology. High signal on short TR/TE sequences is correlated with a high cholesterol content. A marked shortening of the T2 relaxation time is often noticed in the central part of the cyst. Analysis of trace elements showed that this phenomenon is not related to the presence of metals with paramagnetic effects. Our analysis of the contents of colloid cysts does not support the theory that differing metallic concentrations are responsible for differences in MR signal intensity or CT density. We did find that increased CT density and high MR signal correlated with high cholesterol content.

Bond strength tests of dental adhesive systems and their correlation with clinical results : a meta-analysis

OBJECTIVE: To evaluate the variability of bond strength test results of adhesive systems (AS) and to correlate the results with clinical parameters of clinical studies investigating cervical restorations. MATERIALS AND METHODS: Regarding the clinical studies, the internal database which had previously been used for a meta-analysis on cervical restorations was updated with clinical studies published between 2008 and 2012 by searching the PubMed and SCOPUS databases. PubMed and the International Association for Dental Research abstracts online were searched for laboratory studies on microtensile, macrotensile and macroshear bond strength tests. The inclusion criteria were (1) dentin, (2) testing of at least four adhesive systems, (3) same diameter of composite and (4) 24h of water storage prior to testing. The clinical outcome variables were retention loss, marginal discoloration, detectable margins, and a clinical index comprising the three parameters by weighing them. Linear mixed models which included a random study effect were calculated for both, the laboratory and the clinical studies. The variability was assessed by calculating a ratio of variances, dividing the variance among the estimated bonding effects obtained in the linear mixed models by the sum of all variance components estimated in these models. RESULTS: Thirty-two laboratory studies fulfilled the inclusion criteria comprising 183 experiments. Of those, 86 used the microtensile test evaluating 22 adhesive systems (AS). Twenty-seven used the macrotensile test with 17 AS, and 70 used the macroshear test with 24 AS. For 28 AS the results from clinical studies were available. Microtensile and macrotensile (Spearman rho=0.66, p=0.007) were moderately correlated and also microtensile and macroshear (Spearman rho=0.51, p=0.03) but not macroshear and macrotensile (Spearman rho=0.34, p=0.22). The effect of the adhesive system was significant for microtensile and macroshear (p<0.001) but not for macrotensile. The effect of the adhesive system could explain 36% of the variability of the microtensile test, 27% of the macrotensile and 33% of the macroshear test. For the clinical trials, about 49% of the variability of retained restorations could be explained by the adhesive system. With respect to the correlation between bond strength tests and clinical parameters, only a moderate correlation between micro- and macrotensile test results and marginal discoloration was demonstrated. However, no correlation between these tests and a retention loss or marginal integrity was shown. The correlation improved when more studies were included compared to assessing only one study. SIGNIFICANCE: The high variability of bond strength test results highlights the need to establish individual acceptance levels for a given test institute. The weak correlation of bond-strength test results with clinical parameters leads to the conclusion that one should not rely solely on bond strength tests to predict the clinical performance of an adhesive system but one should conduct other laboratory tests like tests on the marginal adaptation of fillings in extracted teeth and the retention loss of restorations in non-retentive cavities after artificial aging.

Repeatability, correlation and path analysis of physical and chemical characteristics of peach fruits

This study aimed to determine the number of measurements necessary to evaluate physical and chemical characteristics of peach fruits, study the relationships between them and their direct and indirect effects on the content of ascorbic acid and total carotenoids. The characteristics skin and pulp color, fruit weight, suture, equatorial and polar diameters, firmness, soluble solids (SS), titratable acidity (TA), SS/TA ratio, ascorbic acid and total carotenoids were evaluated in 39 cultivars of peach and 3 cultivars of nectarine from the orchard of the Universidade Federal de Viçosa. The repeatability coefficient was estimated by ANOVA and CPCOR. Phenotypic correlation coefficients (rf) were estimated and, after the multicollinearity diagnostics, they were unfolded to direct and indirect effects of the explanatory variables on the response variable using path analysis. There was agreement on the magnitude of repeatability coefficients obtained by the two methods; however, they varied among the 14 characteristics. The highest correlations were found between FW, SD, ED and PD. Seven fruits are sufficient to evaluate the physical and chemical characteristics of peach with a correlation coefficient of 90%. The characteristics considered in the path diagrams (b* skin, hº skin, b* pulp, hº pulp, ED, PD, FIR, SS, SS/AT and TC) are not the main determinants of the ascorbic acid. The yellow hue of the pulp (hº pulp) has the potential to be used in indirect selection for total carotenoids.

O6-Methylguanine-DNA methyltransferase protein expression by immunohistochemistry in brain and non-brain systemic tumours: systematic review and meta-analysis of correlation with methylation-specific polymerase chain reaction

Background: The DNA repair protein O6-Methylguanine-DNA methyltransferase (MGMT) confers resistance to alkylating agents. Several methods have been applied to its analysis, with methylation-specific polymerase chain reaction (MSP) the most commonly used for promoter methylation study, while immunohistochemistry (IHC) has become the most frequently used for the detection of MGMT protein expression. Agreement on the best and most reliable technique for evaluating MGMT status remains unsettled. The aim of this study was to perform a systematic review and meta-analysis of the correlation between IHC and MSP. Methods A computer-aided search of MEDLINE (1950-October 2009), EBSCO (1966-October 2009) and EMBASE (1974-October 2009) was performed for relevant publications. Studies meeting inclusion criteria were those comparing MGMT protein expression by IHC with MGMT promoter methylation by MSP in the same cohort of patients. Methodological quality was assessed by using the QUADAS and STARD instruments. Previously published guidelines were followed for meta-analysis performance. Results Of 254 studies identified as eligible for full-text review, 52 (20.5%) met the inclusion criteria. The review showed that results of MGMT protein expression by IHC are not in close agreement with those obtained with MSP. Moreover, type of tumour (primary brain tumour vs others) was an independent covariate of accuracy estimates in the meta-regression analysis beyond the cut-off value. Conclusions Protein expression assessed by IHC alone fails to reflect the promoter methylation status of MGMT. Thus, in attempts at clinical diagnosis the two methods seem to select different groups of patients and should not be used interchangeably.

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement -SCR-, under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Correlation, by multivariate statistical analysis, between the scavenging capacity against reactive oxygen species and the bioactive compounds from frozen fruit pulps

The contents of total phenolic compounds (TPC), total flavonoids (TF), and ascorbic acid (AA) of 18 frozen fruit pulps and their scavenging capacities against peroxyl radical (ROO•), hydrogen peroxide (H2O2), and hydroxyl radical (•OH) were determined. Principal Component Analysis (PCA) showed that TPC (total phenolic compounds) and AA (ascorbic acid) presented positive correlation with the scavenging capacity against ROO•, and TF (total flavonoids) showed positive correlation with the scavenging capacity against •OH and ROO• However, the scavenging capacity against H2O2 presented low correlation with TF (total flavonoids), TPC (total phenolic compounds), and AA (ascorbic acid). The Hierarchical Cluster Analysis (HCA) allowed the classification of the fruit pulps into three groups: one group was formed by the açai pulp with high TF, total flavonoids, content (134.02 mg CE/100 g pulp) and the highest scavenging capacity against ROO•, •OH and H2O2; the second group was formed by the acerola pulp with high TPC, total phenolic compounds, (658.40 mg GAE/100 g pulp) and AA , ascorbic acid, (506.27 mg/100 g pulp) contents; and the third group was formed by pineapple, cacao, caja, cashew-apple, coconut, cupuaçu, guava, orange, lemon, mango, passion fruit, watermelon, pitanga, tamarind, tangerine, and umbu pulps, which could not be separated considering only the contents of bioactive compounds and the scavenging properties.

Sparse Correlation Kernel Analysis and Reconstruction

This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing. To choose the appropriate features from this large dictionary, we use Support Vector Machine (SVM) regression and compare this to traditional Principal Component Analysis (PCA) for the tasks of signal reconstruction, superresolution, and compression. The testbed we use in this paper is a set of images of pedestrians. This paper also presents results of experiments in which we use a dictionary of multiscale basis functions and then use Basis Pursuit De-Noising to obtain a sparse, multiscale approximation of a signal. The results are analyzed and we conclude that 1) when used with a sparse representation technique, the correlation function is an effective kernel for image reconstruction and superresolution, 2) for image compression, PCA and SVM have different tradeoffs, depending on the particular metric that is used to evaluate the results, 3) in sparse representation techniques, L_1 is not a good proxy for the true measure of sparsity, L_0, and 4) the L_epsilon norm may be a better error metric for image reconstruction and compression than the L_2 norm, though the exact psychophysical metric should take into account high order structure in images.

Correlation between process cheese meltability determined by sensory analysis, computer vision method and Olson and Price test

The meltabilities of 14 process cheese samples were determined at 2 and 4 weeks after manufacture using sensory analysis, a computer vision method, and the Olson and Price test. Sensory analysis meltability correlated with both computer vision meltability (R-2 = 0.71, P < 0.001) and Olson and Price meltability (R-2 = 0.69, P < 0.001). There was a marked lack of correlation between the computer vision method and the Olson and Price test. This study showed that the Olson and Price test gave greater repeatability than the computer vision method. Results showed process cheese meltability decreased with increasing inorganic salt content and with lower moisture/fat ratios. There was very little evidence in this study to show that process cheese meltability changed between 2 and 4 weeks after manufacture..