An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.

Discriminant analysis of trace elements in normal, benign and malignant breast tissues measured by total reflection X-ray fluorescence

In this work total reflection X-ray fluorescence spectrometry has been employed to determine trace element concentrations in different human breast tissues (normal, normal adjacent, benign and malignant). A multivariate discriminant analysis of observed levels was performed in order to build a predictive model and perform tissue-type classifications. A total of 83 breast tissue samples were studied. Results showed the presence of Ca, Ti, Fe, Cu and Zn in all analyzed samples. All trace elements, except Ti, were found in higher concentrations in both malignant and benign tissues, when compared to normal tissues and normal adjacent tissues. In addition, the concentration of Fe was higher in malignant tissues than in benign neoplastic tissues. An opposite behavior was observed for Ca, Cu and Zn. Results have shown that discriminant analysis was able to successfully identify differences between trace element distributions from normal and malignant tissues with an overall accuracy of 80% and 65% for independent and paired breast samples respectively, and of 87% for benign and malignant tissues. (C) 2009 Elsevier B.V. All rights reserved.

Familial partial epilepsy with variable foci: Clinical features and linkage to chromosome 22q12

Background: Familial partial epilepsy with variable foci (FPEVF) is an autosomal dominant syndrome characterized by partial seizures originating from different brain regions in different family members in the absence of detectable structural abnormalities. A gene for FPEVF was mapped to chromosome 22q12 in two distantly related French-Canadian families. Methods: We describe the clinical features and performed a linkage analysis in a Spanish kindred and in a third French-Canadian family distantly related to the original pedigrees. Results: Onset of seizures was typically in middle childhood, and attacks were usually easy to control. Seizure semiology varied among family members but was constant for each individual. In some, a pattern of nocturnal frontal lobe seizures led to consideration of the diagnosis of autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE). The Spanish family was mapped to chromosome 22q (multipoint lod score, 3.4), and the new French-Canadian family had a multipoint lod score of 2.97 and shared the haplotype of the original French-Canadian families. Conclusions: Identification of the various forms of familial partial epilepsy is challenging, particularly in small families, in which insufficient individuals exist to identify a specific pattern. We provide clinical guidelines for this task, which will eventually be supplanted by specific molecular diagnosis. We confirmed linkage of FPEVF to chromosome 22q 12 and redefined the region to a 5.2-Mb segment of DNA.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Genetic Analysis of Age-at-Onset for Cardiovascular Risk Factors in a Brazilian Family Study

Background/Aims: Statistical analysis of age-at-onset involving family data is particularly complicated because there is a correlation pattern that needs to be modeled and also because there are measurements that are censored. In this paper, our main purpose was to evaluate the effect of genetic and shared family environmental factors on age-at-onset of three cardiovascular risk factors: hypertension, diabetes and high cholesterol. Methods: The mixed-effects Cox model proposed by Pankratz et al. [2005] was used to analyze the data from 81 families, involving 1,675 individuals from the village of Baependi, in the state of Minas Gerais, Brazil. Results: The analyses performed showed that the polygenic effect plays a greater role than the shared family environmental effect in explaining the variability of the age-at-onset of hypertension, diabetes and high cholesterol. The model which simultaneously evaluated both effects indicated that there are individuals which may have risk of hypertension due to polygenic effects 130% higher than the overall average risk for the entire sample. For diabetes and high cholesterol the risks of some individuals were 115 and 45%, respectively, higher than the overall average risk for the entire population. Conclusions: Results showed evidence of significant polygenic effects indicating that age-at-onset is a useful trait for gene mapping of the common complex diseases analyzed. In addition, we found that the polygenic random component might absorb the effects of some covariates usually considered in the risk evaluation, such as gender, age and BMI. Copyright (C) 2008 S. Karger AG, Basel

Linkage to chromosome 2q36.1 in autosomal dominant Dandy-Walker malformation with occipital cephalocele and evidence for genetic heterogeneity

We previously reported a Vietnamese-American family with isolated autosomal dominant occipital cephalocele. Upon further neuroimaging studies, we have recharacterized this condition as autosomal dominant Dandy-Walker with occipital cephalocele (ADDWOC). A similar ADDWOC family from Brazil was also recently described. To determine the genetic etiology of ADDWOC, we performed genome-wide linkage analysis on members of the Vietnamese-American and Brazilian pedigrees. Linkage analysis of the Vietnamese-American family identified the ADDWOC causative locus on chromosome 2q36.1 with a multipoint parametric LOD score of 3.3, while haplotype analysis refined the locus to 1.1 Mb. Sequencing of the five known genes in this locus did not identify any protein-altering mutations. However, a terminal deletion of chromosome 2 in a patient with an isolated case of Dandy-Walker malformation also encompassed the 2q36.1 chromosomal region. The Brazilian pedigree did not show linkage to this 2q36.1 region. Taken together, these results demonstrate a locus for ADDWOC on 2q36.1 and also suggest locus heterogeneity for ADDWOC.

Oral mucositis in acute lymphoblastic leukaemia: analysis of 169 paediatric patients

Chemotherapy-induced oral mucositis is a frequent therapeutic challenge in cancer patients. The purpose of this retrospective study was to estimate the prevalence and risk factors of oral mucositis in 169 acute lymphoblastic leukaemia (ALL) patients treated according to different chemotherapeutic trials at the Darcy Vargas Children`s Hospital from 1994 to 2005. Demographic data, clinical history, chemotherapeutic treatment and patients` follow-up were recorded. The association of oral mucositis with age, gender, leucocyte counts at diagnosis and treatment was assessed by the chi-squared test and multivariate regression analysis. Seventy-seven ALL patients (46%) developed oral mucositis during the treatment. Patient age (P = 0.33), gender (P = 0.08) and leucocyte counts at diagnosis (P = 0.34) showed no correlation with the occurrence of oral mucositis. Multivariate regression analysis showed a significant risk for oral mucositis (P = 0.009) for ALL patients treated according to the ALL-BFM-95 protocol. These results strongly suggest the greater stomatotoxic effect of the ALL-BFM-95 trial when compared with Brazilian trials. We concluded that chemotherapy-induced oral mucositis should be systematically analysed prospectively in specialized centres for ALL treatment to establish the degree of toxicity of chemotherapeutic drugs and to improve the quality of life of patients based on more effective therapeutic and prophylactic approaches for prevention of its occurrence. Oral Diseases (2008) 14, 761-766

Linkage of Paget disease of bone to a novel region on human chromosome 18q23

Paget disease of bone (PDB) is characterized by increased osteoclast activity and localized abnormal bone remodeling. PDB has a significant genetic component, with evidence of linkage to chromosomes 6p21.3 (PDB1) and 18q21-22 (PDB2) in some pedigrees. There is evidence of genetic heterogeneity, with other pedigrees showing negative linkage to these regions. TNFRSF11A, a gene that is essential for osteoclast formation and that encodes receptor activator of nuclear factor-kappa B (RANK), has been mapped to the PDB2 region. TNFRSF11A mutations that segregate in pedigrees with either familial expansile osteolysis or familial PDB have been identified; however, linkage studies and mutation screening have excluded the involvement of RANK in the majority of patients with PDB. We have excluded linkage, both to PDB1 and to PDB2, in a large multigenerational pedigree with multiple family members affected by PDB. We have conducted a genomewide scan of this pedigree, followed by fine mapping and multipoint analysis in regions of interest. The peak two-point LOD scores from the genomewide scan were 2.75, at D7S507, and 1.76, at D18S70. Multipoint and haplotype analysis of markers flanking D7S507 did not support linkage to this region. Haplotype analysis of markers flanking D18S70 demonstrated a haplotype segregating with PDB in a large subpedigree. This subpedigree had a significantly lower age at diagnosis than the rest of the pedigree (51.2 +/- 8.5 vs. 64.2 +/- 9.7 years; P = .0012). Linkage analysis of this subpedigree demonstrated a peak two-point LOD score of 4.23, at marker D18S1390 (theta = 0), and a peak multipoint LOD score of 4.71, at marker D18S70. Our data are consistent with genetic heterogeneity within the pedigree and indicate that 18q23 harbors a novel susceptibility gene for PDB.

Prospects for whole genome linkage disequilibrium mapping in domestic dog breeds

Linkage disequilibrium (LD) mapping is commonly used as a fine mapping tool in human genome mapping and has been used with some success for initial disease gene isolation in certain isolated inbred human populations. An understanding of the population history of domestic dog breeds suggests that LID mapping could be routinely utilized in this species for initial genome-wide scans. Such an approach offers significant advantages over traditional linkage analysis. Here, we demonstrate, using canine copper toxicosis in the Bedlington terrier as the model, that LID mapping could be reasonably expected to be a useful strategy in low-resolution, genome-wide scans in pure-bred dogs. Significant LID was demonstrated over distances up to 33.3 cM. It is very unlikely, for a number of reasons discussed, that this result could be extrapolated to the rest of the genome. It is, however, consistent with the expectation given the population structure of canine breeds and, in this breed at least, with the hypothesis that it may be possible to utilize LID in a genome-wide scan. In this study, LD mapping confirmed the location of the copper toxicosis in Bedlington terrier gene (CT-BT) and was able to do so in a population that was refractory to traditional linkage analysis.

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Forest soil short term response to prescribed fire: an approach by Principal Components Analysis

In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.

Energy-dispersive x-ray fluorescence analysis of modern coloured glasses from Marinha Grande (Portugal)

X-Ray Spectrom. 2003; 32: 396–401

Carbon prices. Dynamic analysis of European and Californian markets

Dissertação para obtenção do Grau de Doutor em Alterações Climáticas e Políticas de Desenvolvimento Sustentável

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.