The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria

BACKGROUND: We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria. METHODS: Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms. RESULTS: After univariate analysis, 9 biomarkers were differentially expressed (t test; P

Comorbidities and current smoking status amongst patients starting renal replacement therapy in England, Wales and Northern Ireland from 2003 to 2008: national and centre-specific analyses

Introduction: The prevalence of comorbidities in incident renal replacement therapy (RRT) patients changes with age and varies between ethnic groups. This study describes these associations and the independent effect of comorbidities on outcomes. Methods: Adult patients starting RRT between 2003 and 2008 in centres reporting to the UK Renal Registry (UKRR) with data on comorbidity (n ¼ 14,909) were included. The UKRR studied the association of comorbidity with patient demographics, treatment modality, haemoglobin, renal function at start of RRT and subsequent listing for kidney transplantation. The relationship between comorbidities and mortality at 90 days and one year after 90 days from start of RRT was explored using Cox regression. Results: Completeness of comorbidity data was 40.0% compared with 54.3% in 2003. Of patients with data, 53.8% had one or more comorbidities. Diabetes mellitus and ischaemic heart disease were the most common conditions seen in 30.1% and 22.7% of patients respectively. Current smoking was recorded for 14.5% of incident RRT patients in the 6-year period. Comorbidities became more common with increasing age in all ethnic groups although the difference between the 65–74 and 75+ age groups was not significant. Within each age group, South Asians and Blacks had lower rates of comorbidity, despite higher rates of diabetes mellitus. In multivariate survival analysis, malignancy and ischaemic/neuropathic ulcers were the strongest independent predictors of poor survival at 1 year after 90 days from the start of RRT. Conclusion: Differences in prevalence of comorbid illnesses in incident RRT patients may reflect variation in access to health care or competing risk prior to commencing treatment. At the same time, smoking rates remained high in this ‘at risk’ population. Further work on this and ways to improve comorbidity reporting should be priorities for 2010–11.

Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets

Motivation: To date, Gene Set Analysis (GSA) approaches primarily focus on identifying differentially expressed gene sets (pathways). Methods for identifying differentially coexpressed pathways also exist but are mostly based on aggregated pairwise correlations, or other pairwise measures of coexpression. Instead, we propose Gene Sets Net Correlations Analysis (GSNCA), a multivariate differential coexpression test that accounts for the complete correlation structure between genes.

Results: In GSNCA, weight factors are assigned to genes in proportion to the genes' cross-correlations (intergene correlations). The problem of finding the weight vectors is formulated as an eigenvector problem with a unique solution. GSNCA tests the null hypothesis that for a gene set there is no difference in the weight vectors of the genes between two conditions. In simulation studies and the analyses of experimental data, we demonstrate that GSNCA, indeed, captures changes in the structure of genes' cross-correlations rather than differences in the averaged pairwise correlations. Thus, GSNCA infers differences in coexpression networks, however, bypassing method-dependent steps of network inference. As an additional result from GSNCA, we define hub genes as genes with the largest weights and show that these genes correspond frequently to major and specific pathway regulators, as well as to genes that are most affected by the biological difference between two conditions. In summary, GSNCA is a new approach for the analysis of differentially coexpressed pathways that also evaluates the importance of the genes in the pathways, thus providing unique information that may result in the generation of novel biological hypotheses.

Electronic Journal of Applied Multivariate Statistics

The ecological sciences have experienced immense growth over the course of this century, and chances are that they will continue to grow well on into the next millennium. There are some good reasons for this – ecology encompasses some of the most pressing concerns facing humanity. With recent advances in data collection technology and ambitious field research, ecologists are increasingly calling upon multivariate statistics to explore and test for patterns in their data. The goal of FISH 560 (Applied Multivariate Statistics for Ecologists) at the University of Washington is to introduce graduate students to the multivariate statistical techniques necessary to carry out sophisticated analyses and to critically evaluate scientific papers using these approaches. It is a practical, hands-on course emphasizing the analysis and interpretation of multivariate analysis, and covers the majority of approaches in common use by ecologists. To celebrate the hard work of past students, I am pleased to announce the creation of the Electronic Journal of Applied Multivariate Statistics (EJAMS). Each year, students in FISH 560 are required to write a final paper consisting of a statistical analysis of their own multivariate data set. These papers are submitted to EJAMS at the end of quarter and are peer reviewed by two other class members. A decision on publication is based on the reviewers’ recommendations and my own reading the paper. In closing, there is a need for the rapid dissemination of ecological research using multivariate statistics at the University of Washington. EJAMS is committed to this challenge.

Reconsidérer les interactions entre l’écoulement, le transport de sédiments en charge de fond et la morphologie en rivière à lit de graviers : approches, échelles et analyses

L'objectif ultime en géomorphologie fluviale est d'expliquer les formes des cours d'eau et leur évolution temporelle et spatiale. La multiplication des études nous a mené à la réalisation que les systèmes géomorphologiques sont complexes. Les formes observées sont plus que la somme des processus individuels qui les régissent en raison d’interactions et de rétroactions non-linéaires à de multiples échelles spatiales et temporelles. Dans ce contexte, le but général de la thèse est de proposer et de tester de nouvelles avenues de recherche afin de mieux appréhender la complexité des dynamiques fluviales en utilisant des approches méthodologiques et analytiques mettant l’accent sur les interactions entre l’écoulement, le transport de sédiments en charge fond et la morphologie du lit en rivière graveleuse. Cette orientation découle du constat que les paradigmes actuels en géomorphologie fluviale n’arrivent pas à expliquer adéquatement la variabilité naturelle du transport en charge de fond ainsi que des formes du lit qui en résultent. Cinq pistes de réflexion sont développées sous forme d’articles basés sur des études de cas : 1. L'intégration des échelles de variation de l'écoulement permet d’insérer la notion de structures turbulentes dans des pulsations de plus grande échelle et d'améliorer la compréhension de la variabilité du transport de sédiments. 2. La quantification des taux de changement de l’écoulement (accélération /décélération) au cours d’une crue permet d’expliquer la variabilité des flux de transport en charge fond autant que la magnitude de l’écoulement. 3. L’utilisation de techniques de mesures complémentaires révèle une nouvelle dynamique du lit des rivières graveleuses, la dilatation et la contraction du lit suite à une crue. 4. La remise en cause du fait généralement accepté que le transport en charge de fond est corrélé positivement à l'intensité des modifications morphologiques en raison d’un problème associé aux échelles différentes des processus en cause. 5. L’approche systémique des dynamiques fluviales par l’utilisation d’analyses multivariées permet d’appréhender la complexité des dynamiques de rétroactions linéaires et non-linéaires dans l’évolution d’un chenal et d’illustrer l’importance de l’historique récent des changements géomorphologiques en réponse aux crues. Cette thèse se veut une avancée conceptuelle issue d'une profonde réflexion sur les approches classiques que l'on utilise en géomorphologie fluviale depuis plusieurs décennies. Elle est basée sur un jeu de données unique récolté lors du suivi intensif de 21 évènements de crue dans un petit cours d’eau à lit de graviers, le ruisseau Béard (Québec). Le protocole expérimental axé sur la simultanéité des mesures de l’écoulement, de la morphologie du lit et du transport de sédiments en charge de fond a permis de centrer la recherche directement sur les interactions entre les processus plutôt que sur les processus individuels, une approche rarement utilisée en géomorphologie fluviale. Chacun des chapitres illustre un nouveau concept ou une nouvelle approche permettant de résoudre certaines des impasses rencontrées actuellement en géomorphologie fluviale. Ces travaux ont des implications importantes pour la compréhension de la dynamique des lits de rivières et des habitats fluviaux et servent de point de départ pour de nouveaux développements.

Analysis of Pleistocene paleodrainage evolution in the Po Basin (Italy) by multivariate statistical techniques

In order to obtain a high-resolution Pleistocene stratigraphy, eleven continuously cored boreholes, 100 to 220m deep were drilled in the northern part of the Po Plain by Regione Lombardia in the last five years. Quantitative provenance analysis (QPA, Weltje and von Eynatten, 2004) of Pleistocene sands was carried out by using multivariate statistical analysis (principal component analysis, PCA, and similarity analysis) on an integrated data set, including high-resolution bulk petrography and heavy-mineral analyses on Pleistocene sands and of 250 major and minor modern rivers draining the southern flank of the Alps from West to East (Garzanti et al, 2004; 2006). Prior to the onset of major Alpine glaciations, metamorphic and quartzofeldspathic detritus from the Western and Central Alps was carried from the axial belt to the Po basin longitudinally parallel to the SouthAlpine belt by a trunk river (Vezzoli and Garzanti, 2008). This scenario rapidly changed during the marine isotope stage 22 (0.87 Ma), with the onset of the first major Pleistocene glaciation in the Alps (Muttoni et al, 2003). PCA and similarity analysis from core samples show that the longitudinal trunk river at this time was shifted southward by the rapid southward and westward progradation of transverse alluvial river systems fed from the Central and Southern Alps. Sediments were transported southward by braided river systems as well as glacial sediments transported by Alpine valley glaciers invaded the alluvial plain. Kew words: Detrital modes; Modern sands; Provenance; Principal Components Analysis; Similarity, Canberra Distance; palaeodrainage

Rapid quality assessment of wheat cultivars registered in Poland using the 2-g mixograph and multivariate statistical analysis

Baking and 2-g mixograph analyses were performed for 55 cultivars (19 spring and 36 winter wheat) from various quality classes from the 2002 harvest in Poland. An instrumented 2-g direct-drive mixograph was used to study the mixing characteristics of the wheat cultivars. A number of parameters were extracted automatically from each mixograph trace and correlated with baking volume and flour quality parameters (protein content and high molecular weight glutenin subunit [HMW-GS] composition by SDS-PAGE) using multiple linear regression statistical analysis. Principal component analysis of the mixograph data discriminated between four flour quality classes, and predictions of baking volume were obtained using several selected mixograph parameters, chosen using a best subsets regression routine, giving R-2 values of 0.862-0.866. In particular, three new spring wheat strains (CHD 502a-c) recently registered in Poland were highly discriminated and predicted to give high baking volume on the basis of two mixograph parameters: peak bandwidth and 10-min bandwidth.

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The traceability of animal meals in layer diets as detected by stable carbon and nitrogen isotope analyses of eggs

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: Pattern-recognition analyses for screening quality control purposes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate analysis of stable isotope data in the traceability process for birds

A análise isotópica tem se mostrado uma ferramenta de suma importância ao processo de rastreabilidade, no entanto, existem divergências nas análises estatísticas dos resultados, uma vez que os dados são dependentes e advindos de vários elementos químicos tais como Carbono, Hidrogênio, Oxigênio, Nitrogênio e Enxofre (CHON'S). Com o intuito de estabelecer a análise propícia para os dados de rastreabilidade em aves pela técnica de isótopos estáveis e avaliar a necessidade da análise conjunta das variáveis, foram usados dados de carbono-13 e de nitrogênio-15 de ovos (albúmen + gema) de poedeiras e músculo peitoral de frangos de corte, os quais foram submetidos à análise estatística univariada (Anova e complementada pelo teste de Tukey) e multivariada (Manova e Discriminante). Os dados foram analisados no software Minitab 16, e os resultados, consolidados na teoria, confirmam a necessidade de análise multivariada, mostrando também que a análise discriminante esclarece as dúvidas apresentadas nos resultados de outros métodos de análise comparados nesta pesquisa.

Multivariate quality control studies applied to Ca(II) and Mg(II) determination by a portable method

A portable or field test method for simultaneous spectrophotometric determination of calcium and magnesium in water using multivariate partial least squares (PLS) calibration methods is proposed. The method is based on the reaction between the analytes and methylthymol blue at pH 11. The spectral information was used as the X-block, and the Ca(II) and Mg(II) concentrations obtained by a reference technique (ICP-AES) were used as the Y-block. Two series of analyses were performed, with a month's difference between them. The first series was used as the calibration set and the second one as the validation set. Multivariate statistical process control (MSPC) techniques, based on statistics from principal component models, were used to study the features and evolution with time of the spectral signals. Signal standardization was used to correct the deviations between series. Method validation was performed by comparing the predictions of the PLS model with the reference Ca(II) and Mg(II) concentrations determined by ICP-AES using the joint interval test for the slope and intercept of the regression line with errors in both axes. (C) 1998 John Wiley & Sons, Ltd.

Geographic variation of Africanized honey bees (Apis mellifera L.) in Brazil: Multivariate morphometrics and racial admixture

The correspondence between morphometric and isozymic geographic variation patterns of Africanized honey bees in Brazil was analyzed. Morphometric data consisted of mean vectors of 19 wing traits measured in 42 local populations distributed throughout the country. Isozymic data refer to allelic frequencies of malate dehydrogenase (MDH), and were obtained from Lobo and Krieger. The two data sets were analyzed through canonical trend surface, principal components and spatial autocorrelation analyses, and showed north-south dines, demonstrating that Africanized honey bees in southern and southeastern Brazil are more similar to European honey bees than those found in northern and northeastern regions. Also, the morphometric variation is within the limits established by the racial admixture model, considering the expected values of Africanized honey bee fore wing length (WL) in southern and northeastern regions of Brazil, estimated by combining average values of WL in the three main subspecies involved in the Africanization process (Apis mellifera scutellata, A. m. ligustica and A. m. mellifera) with racial admixture coefficients.

Cluster and meta-analyses of genetic parameters for feed intake traits in growing beef cattle

A data set based on 50 studies including feed intake and utilization traits was used to perform a meta-analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta-analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta-analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 +/- 0.04, 0.39 +/- 0.03, 0.31 +/- 0.02, 0.31 +/- 0.03 and 0.26 +/- 0.03, respectively. Pooled genetic correlation estimates ranged from -0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.

Multivariate analysis of the temporal variability of sugarcane ripening in south-eastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)