965 resultados para Spearman Rank correlation


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Purpose: 1. To review Ct features suggestive of saprophytic aspergillosis (aspergilloma) and to correlate them with the final pathological results. 2. To illustrate the wide range of differential diagnosis. Methods and materials: The electronic database of our department from 1995 to 2007 revealed CT reports of 48 patients that had been considered very suggestive of aspergilloma. Two radiologists with 6 and 12 years experience in thoracic radiology jointly reviewed the corresponding CT features including ancillary findings and the underlying lung diseases and correlated them with the final pathological diagnosis. Results: Forty patients could be included in the study (12 women, mean age 52), while in 8 patients there was no adequate clinical follow-up. In 17 patients the diagnosis "mycetoma" due to aspergillus fumigatus infection was confirmed, either by surgery, biopsy or bronchoscopy. In 23 patients, differential diagnoses were found, such as cavitating bronchial carcinoma (n = 7), bacterial abscess (n = 3), typical (n = 2) and atypical (n = 2) tuberculosis, as well as inflammatory changes due to mucoviscidosis (n = 1), Wegener's disease (n = 1) or chronic obstructive pulmonary disease (n = 3). Fibromyxoide hamartoma, lung infarction and bronchomucocele were responsible for the typical CT feature in one patient each. Conclusion: 1. The typical CT feature suggesting mycetoma is softtissue proliferation within a pre-existing wall-thickened lung cavity, oten even considered "pathognomonic". However, this diagnosis was finally confirmed by surgery or laboratory findings in less than 50% of patients only. 2. Since differential diagnoses are very large, not only including cavitating lung cancer and tuberculosis, the individual underlying lung disease needs strongly being taken into account often giving the best clue for the correct diagnosis.

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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.

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Purpose: To assess the visibility and the features of ECUATS on 3.0-T MRI studies, and evaluate their correlation with tendinosis. Methods and materials: Our retrospective study was approved by IRB, with waiver of informed consent. Fifty wrist MRI and 48 MR arthrographies from 98 patients (55 males, 43 females, mean age 42.3 years) performed between January and November 2009 on 3.0-T units were reviewed. Images (transverse T1, T2, FS Gd T1 and VIBE) were independently analyzed by two radiologists, and a consensus reached with a third reader in case of disagreement. The visibility of ECUATS was assessed on each available transverse sequence. When present, ECUATS' origins, diameters and insertions were noted. ECU tendinosis was also evaluated. Inter-rater agreement was assessed using Cohen's Kappa coefficient. Results: ECUATS observed prevalence was 23.5% (23/98). ECUATS were more frequently noted on the VIBE sequence, with a good inter-rater agreement (Kappa = 0.72). Origins were noted in 95.7% of cases: 3 were at the level of, and 20 distal to ECU subsheath. Insertions were seen in 43.5%: 2 were on 5th metacarpal bone, 8 on extensor apparatus of 5th finger. ECUATS mean shortest and longest diameters were 0.54 and 0.85 mm respectively. ECU tendinosis was statistically more frequently noted in patients with ECUATS (p <0.05). Conclusion: ECUATS are readily visible on 3.0-T MRI studies, especially on transverse GRE VIBE images. ECU tendinosis is more frequently noted in patients bearing ECUATS.

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Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

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Staphylococcus aureus infections involve numerous adhesins and toxins, which expression depends on complex regulatory networks. Adhesins include a family of surface proteins covalently attached to the peptidoglycan via a conserved LPXTG motif. Here we determined the protein and mRNA expression of LPXTG-proteins of S. aureus Newman in time-course experiments, and their relation to fibrinogen adherence in vitro. Experiments were performed with mutants in the global accessory-gene regulator (agr), surface protein A (Spa), and fibrinogen-binding protein A (ClfA), as well as during growth in iron-rich or iron-poor media. Surface proteins were recovered by trypsin-shaving of live bacteria. Released peptides were analyzed by liquid chromatography coupled to tandem mass-spectrometry. To unambiguously identify peptides unique to LPXTG-proteins, the analytical conditions were refined using a reference library of S. aureus LPXTG-proteins heterogeneously expressed in surrogate Lactococcus lactis. Transcriptomes were determined by microarrays. Sixteen of the 18 LPXTG-proteins present in S. aureus Newman were detected by proteomics. Nine LPXTG-proteins showed a bell-shape agr-like expression that was abrogated in agr-negative mutants including Spa, fibronectin-binding protein A (FnBPA), ClfA, iron-binding IsdA, and IsdB, immunomodulator SasH, functionally uncharacterized SasD, biofilm-related SasG and methicillin resistance-related FmtB. However, only Spa and SasH modified their proteomic and mRNA profiles in parallel in the parent and its agr- mutant, whereas all other LPXTG-proteins modified their proteomic profiles independently of their mRNA. Moreover, ClfA became highly transcribed and active in fibrinogen-adherence tests during late growth (24 h), whereas it remained poorly detected by proteomics. On the other hand, iron-regulated IsdA-B-C increased their protein expression by >10-times in iron-poor conditions. Thus, proteomic, transcriptomic, and adherence-phenotype demonstrated differential profiles in S. aureus. Moreover, trypsin peptide signatures suggested differential protein domain exposures in various environments, which might be relevant for anti-adhesin vaccines. A comprehensive understanding of the S. aureus physiology should integrate all three approaches.

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This project was undertaken to study the relationships between the performance of locally available asphalts and their physicochemical properties under Iowa conditions with the ultimate objective of development of a locally and performance-based asphalt specification for durable pavements. Physical and physicochemical tests were performed on three sets of asphalt samples including: (a) twelve samples from local asphalt suppliers and their TFOT residues, (b) six core samples of known service records, and (c) a total of 79 asphalts from 10 pavement projects including original, lab aged and recovered asphalts from field mixes, as well as from lab aged mixes. Tests included standard rheological tests, HP-GPC and TMA. Some specific viscoelastic tests (at 5 deg C) were run on b samples and on some a samples. DSC and X-ray diffraction studies were performed on a and b samples. Furthermore, NMR techniques were applied to some a, b and c samples. Efforts were made to identify physicochemical properties which are correlated to physical properties known to affect field performance. The significant physicochemical parameters were used as a basis for an improved performance-based trial specification for Iowa to ensure more durable pavements.

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The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.

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The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

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rejection can lead to loss of function. Histological reading of endomyocardial biopsy remains the "gold standard" for guiding immunosuppression, despite its methodological limitations (sampling error and interobserver variability). The measurement of the T2 relaxation time has been suggested for detection of allograft rejection, on the pathophysiological basis that the T2 relaxation time prolongs with local edema resulting from acute allograft rejection. Using breath-held cardiac magnetic resonance T2 mapping at 1.5 T, Usman et al. (CircCardiovascImaging2012) detected moderate allograft rejection (grade 2R, ISHLT 2004). With modern immunosuppression grade 2R rejection has become a rare event, but the need remains for a technique that permits the discrimination of absent (grade 0R) and mild rejection (grade 1R). We therefore investigated whether an increase of magnetic field strength to 3T and the use of real-time navigator-gated respiration compensation allow for an increase in the sensitivity of T2 relaxation time detection that is necessary to achieve this discrimination. Methods: Eighteen patients received EMB (Tan et al., ArchPatholLabMed2007) and cardiac T2 mapping on the same day. Reading of T2 maps was blinded to the histological results. For final analysis, 3 cases with known 2R rejection at the time of T2 mapping were added, yielding 21 T2 mapping sessions. A respiration-navigator-gated radial gradient-recalled-echo pulse sequence (resolution 1.17 mm2, matrix 2562, trigger time 3 heartbeats, T2 preparation duration TET2 Prep = 60/30/0 ms) was applied to obtain 3 short-axis T2 maps (van Heeswijk et al., JACCCardiovascImaging2012), which were segmented according to AHA guidelines (Cerqueira et al, Circulation2001). The highest segmental T2 values were grouped according to histological rejection grade and differences were analyzed by Student's t-test, except for the non-blinded cases with 2R rejection. The degree of discrimination was determined using the Spearman's ranked correlation test. Results: The high-quality T2 maps allowed for visual differentiation of the rejection degrees (Figure 1), and the correlation of T2 mapping with the histological grade of acute cellular rejection was significant (Spearman's r = 0.56, p = 0.007). The 0R (n = 15) and 1R (n = 3) degrees demonstrated significantly different T2 values (46.9 ± 5.0 and 54.3 ± 3.0 ms, p = 0.02, Figure 2). Cases with 2R rejection showed clear T2 elevation (T2 = 60.3 ± 16.2 ms). Conclusions: This pilot study demonstrates that non-invasive free-breathing cardiac T2 mapping at 3T discriminates between no and mild cardiac allograft rejection. Confirmation of these encouraging results in a larger cohort should consider a study able to show equivalency or superiority of T2 mapping.

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Objectives: Our aim in this study was to determine the concentration of salivary glucose in healthy individuals and to compare it with the capillary glycemia. Study design: Samples of unstimulated whole saliva were collected from 63 non-diabetic patients. The concentration of salivary glucose and capillary blood was measured in all of the patients. The salivary glucose was determined by enzymatic method and spectrophotometry. The data was then analyzed using the Spearman correlation test, considering values of p<0.05 to be significant. Results: The whole sample consisted of 47.6% males and 52.4% women, with an average age of 37.5±15.7 years old. The average rates of unstimulated salivary flow were 0.41±0.21 ml/min among males and 0.31±0.15 ml/min among females. No significant difference was found based on these results (p=0.078). The average blood glucose among the males studied was 100.05±13.51 mg/dL, and among females, it was 99.5±13.9 mg/dL. The average salivary glucose for the whole sample was 5.97±1.87 mg/dL, with 5.91±2.19 mg/dL among males and 5.97±1.56 mg/dL among females, respectively, without presenting any significant differences (p=0.908). The concentration of salivary glucose did not present any statistically significant correlation with the capillary glycemia (p=0.732). Conclusions: The results suggest that the concentration of salivary glucose is not dependent on capillary glycemia and that the concentration of salivary glucose does not present significant differences between the measurements for males and females.

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Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.