Inheritance of growth habit detected by genetic linkage analysis using microsatellites in the common bean (Phaseolus vulgaris L.)

The genetic linkage map for the common bean (Phaseolus vulgaris L.) is a valuable tool for breeding programs. Breeders provide new cultivars that meet the requirements of farmers and consumers, such as seed color, seed size, maturity, and growth habit. A genetic study was conducted to examine the genetics behind certain qualitative traits. Growth habit is usually described as a recessive trait inherited by a single gene, and there is no consensus about the position of the locus. The aim of this study was to develop a new genetic linkage map using genic and genomic microsatellite markers and three morphological traits: growth habit, flower color, and pod tip shape. A mapping population consisting of 380 recombinant F10 lines was generated from IAC-UNA x CAL143. A total of 871 microsatellites were screened for polymorphisms among the parents, and a linkage map was obtained with 198 mapped microsatellites. The total map length was 1865.9 cM, and the average distance between markers was 9.4 cM. Flower color and pod tip shape were mapped and segregated at Mendelian ratios, as expected. The segregation ratio and linkage data analyses indicated that the determinacy growth habit was inherited as two independent and dominant genes, and a genetic model is proposed for this trait.

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.

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

Drizzle and Fog Analysis in the Sao Paulo Metropolitan Area: Changes 1933-2005 and Correlations with other Climate Factors

In order to improve our understanding of climate change, the aim of this research project was to study the climatology and the time trends of drizzle and fog events in the Sao Paulo Metropolitan Area, and the possible connections of this variability with the sea surface temperature (SST) of the Atlantic and Pacific Oceans. The climatology of both phenomena presents differences and similarities. Fog shows a marked maximum frequency in winter and a minimum frequency in summer, while the seasonal differences of drizzle occurrence are less pronounced, there is a maximum in spring, whereas the other seasons present smaller and similar numbers of events. Both phenomena present a negative trend from 1933 to 2005 which is stronger for fog events. A multivariate statistical analysis indicates that the South Atlantic SST could increase warm temperature advection to the continent. This could be one of the responsible factors for the negative tendency in the number of both fog and drizzle events.

Fluorescence spectroscopy for the detection of tongue carcinoma - validation in an animal model

The efficacy of fluorescence spectroscopy to detect squamous cell carcinoma is evaluated in an animal model following laser excitation at 442 and 532 nm. Lesions are chemically induced with a topical DMBA application at the left lateral tongue of Golden Syrian hamsters. The animals are investigated every 2 weeks after the 4th week of induction until a total of 26 weeks. The right lateral tongue of each animal is considered as a control site (normal contralateral tissue) and the induced lesions are analyzed as a set of points covering the entire clinically detectable area. Based on fluorescence spectral differences, four indices are determined to discriminate normal and carcinoma tissues, based on intraspectral analysis. The spectral data are also analyzed using a multivariate data analysis and the results are compared with histology as the diagnostic gold standard. The best result achieved is for blue excitation using the KNN (K-nearest neighbor, a interspectral analysis) algorithm with a sensitivity of 95.7% and a specificity of 91.6%. These high indices indicate that fluorescence spectroscopy may constitute a fast noninvasive auxiliary tool for diagnostic of cancer within the oral cavity. (C) 2008 Society of Photo-Optical Instrumentation Engineers.

Heritability of cardiovascular risk factors in a Brazilian population: Baependi Heart Study

Background: The heritability of cardiovascular risk factors is expected to differ between populations because of the different distribution of environmental risk factors, as well as the genetic make-up of different human populations. Methods: The purpose of this analysis was to evaluate genetic and environmental influences on cardiovascular risk factor traits, using a variance component approach, by estimating the heritability of these traits in a sample of 1,666 individuals in 81 families ascertained randomly from a highly admixed population of a city in a rural area in Brazil. Results: Before adjustment for sex, age, age(2), and age x sex interaction, polygenic heritability of systolic (SBP) and diastolic (DBP) blood pressure were 15.0% and 16.4%, waist circumference 26.1%, triglycerides 25.7%, fasting glucose 32.8%, HDL-c 31.2%, total cholesterol 28.6%, LDL-c 26.3%, BMI 39.1%. Adjustment for covariates increased polygenic heritability estimates for all traits mainly systolic and diastolic blood pressure (25.9 and 26.2%, respectively), waist circumference (40.1%), and BMI (51.0%). Conclusion: Heritability estimates for cardiovascular traits in the Brazilian population are high and not significantly different from other studied worldwide populations. Mapping efforts to identify genetic loci associated with variability of these traits are warranted.

Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

Transcriptional responses of host peripheral blood cells to tuberculosis infection

Host responses following exposure to Mycobacterium tuberculosis (TB) are complex and can significantly affect clinical outcome. These responses, which are largely mediated by complex immune mechanisms involving peripheral blood cells (PBCs) such as T-lymphocytes, NK cells and monocyte-derived macrophages, have not been fully characterized. We hypothesize that different clinical outcome following TB exposure will be uniquely reflected in host gene expression profiles, and expression profiling of PBCs can be used to discriminate between different TB infectious outcomes. In this study, microarray analysis was performed on PBCs from three TB groups (BCG-vaccinated, latent TB infection, and active TB infection) and a control healthy group. Supervised learning algorithms were used to identify signature genomic responses that differentiate among group samples. Gene Set Enrichment Analysis was used to determine sets of genes that were co-regulated. Multivariate permutation analysis (p < 0.01) gave 645 genes differentially expressed among the four groups, with both distinct and common patterns of gene expression observed for each group. A 127-probeset, representing 77 known genes, capable of accurately classifying samples into their respective groups was identified. In addition, 13 insulin-sensitive genes were found to be differentially regulated in all three TB infected groups, underscoring the functional association between insulin signaling pathway and TB infection. Published by Elsevier Ltd.

New body fat prediction equations for severely obese patients

Background & aims: Severe obesity imposes physical limitations to body composition assessment. Our aim was to compare body fat (BF) estimations of severely obese patients obtained by bioelectrical impedance (BIA) and air displacement plethysmography (ADP) for development of new equations for BF prediction. Methods: Severely obese subjects (83 female/36 mate, mean age = 41.6 +/- 11.6 years) had BF estimated by BIA and ADP. The agreement of the data was evaluated using Bland-Altman`s graphic and concordance correlation coefficient (CCC). A multivariate regression analysis was performed to develop and validate new predictive equations. Results: BF estimations from BIA (64.8 +/- 15 kg) and ADP (65.6 +/- 16.4 kg) did not differ (p > 0.05, with good accuracy, precision, and CCC), but the Bland- Altman graphic showed a wide Limit of agreement (- 10.4; 8.8). The standard BIA equation overestimated BF in women (-1.3 kg) and underestimated BF in men (5.6 kg; p < 0.05). Two BF new predictive equations were generated after BIA measurement, which predicted BF with higher accuracy, precision, CCC, and limits of agreement than the standard BIA equation. Conclusions: Standard BIA equations were inadequate for estimating BF in severely obese patients. Equations developed especially for this population provide more accurate BF assessment. (C) 2008 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Prevalence and correlates of alcoholism in community-dwelling elderly living in Sao Paulo, Brazil

Objectives To assess the prevalence of alcoholism in elderly living in the city of Sao Paulo (Brazil) and investigate associated risk factors. Methods A total of 1,563 individuals aged 60 years or older, of both genders of three districts of different socioeconomic classes (high, medium and low) in the city of Sao Paulo (Brazil) were interviewed. The CAGE screening test for alcoholism was applied and a structured interview was used to assess associated sociodemographic and clinical factors. The tests Mini Mental State Examination, Fuld Object Memory Evaluation, The Informant Questionnaire on Cognitive Decline in the Elderly and Bayer-Activities of Daily Living Scale were used for cognitive and functional assessment. Results Prevalence of alcoholism was 9.1%. Multivariate regression analysis showed that alcoholism was associated with male gender, `mulatto` ethnicity, smoking, and cognitive and functional impairment. In addition, the younger the individual and the lower the schooling level, the higher the risk for alcoholism. Conclusions The results obtained in this study show that alcoholism is highly frequent in the community-dwelling elderly living in Sao Paulo, and that it is associated with socio-demographic and clinical risk factors similar to those reported in the literature. This suggests that alcoholism in the elderly of a developing country shares the same basic characteristics seen in developed countries. These findings suggest that it is essential for health services and professional to be prepared to meet this demand that will significantly grow in the next years, especially in developing countries, where the rates of population aging are higher than those of developed countries. Copyright (C) 2009 John Wiley & Sons, Ltd.