Analysis of the procedures used to evaluate suicide crime scenes in Brazil: A statistical approach to interpret reports

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

Genetic analysis of feet and legs in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Multivariate analysis for animal selection in experimental research

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

Estimates of covariance functions for growth from birth to 630 days of age in Nelore cattle

Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polynomial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high.

Analysis of relevant factors in patients with oral and pharyngeal cancers

This study presented an epidemiological data of 177 medical records of patients affected by oral and pharyngeal cancers with prosthesis indication. The gender, age, sun exposure, disease diagnosis, cancer anatomic site, radiation treatment and type of prosthesis, death from oral and pharyngeal cancers were collected. Data were analyzed by summary measures and logistic regression analysis. The mean age of the patients was 62.7 years, and 46.8％ died between 52 and 62 years old. Most of the patients were male (74％), and 42％ died among them. Squamous cell carcinoma was the most prevalent cancer (75.1％) and 42.1％ of these patients died. The age, gender, diagnosis and the interaction of these factors exhibited strong association with the patients’ death (P<.05, Chi-square test). The multivariate odds ratios (OR) of the death were 0.40 for women and 0.39 for other pathologies versus male and squamous cell carcinoma, respectively. It was concluded that age, gender and diagnosis of cancer had significant effect on patients’ death.

Multivariate analysis for selecting animals for experimental research

Background Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Atmospheric conditions, lunar phases, and childbirth: a multivariate analysis

Our objective was to assess extrinsic influences upon childbirth. In a cohort of 1,826 days containing 17,417 childbirths among them 13,252 spontaneous labor admissions, we studied the influence of environment upon the high incidence of labor (defined by 75th percentile or higher), analyzed by logistic regression. The predictors of high labor admission included increases in outdoor temperature (odds ratio: 1.742, P = 0.045, 95%CI: 1.011 to 3.001), and decreases in atmospheric pressure (odds ratio: 1.269, P = 0.029, 95%CI: 1.055 to 1.483). In contrast, increases in tidal range were associated with a lower probability of high admission (odds ratio: 0.762, P = 0.030, 95%CI: 0.515 to 0.999). Lunar phase was not a predictor of high labor admission (P = 0.339). Using multivariate analysis, increases in temperature and decreases in atmospheric pressure predicted high labor admission, and increases of tidal range, as a measurement of the lunar gravitational force, predicted a lower probability of high admission.

Association analysis of clinical aspects and vitamin D receptor gene polymorphism with external apical root resorption in orthodontic patients

Introduction: Vitamin D is responsible for the regulation of certain genes at the transcription level, via interaction with the vitamin D receptor, and influences host immune responses and aspects of bone development, growth, and homeostasis. Our aim was to investigate the association of TaqI vitamin D receptor gene polymorphism with external apical root resorption during orthodontic treatment. Methods: Our subjects were 377 patients with Class II Division 1 malocclusion, divided into 3 groups: (1) 160 with external apical root resorption <= 1.43 mm, (2) 179 with external apical root resorption >1.43 mm), and (3) 38 untreated subjects. External apical root resorption of the maxillary incisors was evaluated on periapical radiographs taken before and after 6 months of treatment. After DNA collection and purification, vitamin D receptor TaqI polymorphism analysis was performed by polymerase chain reaction-restriction fragment length polymorphism. Univariate and multivariate analyses were performed to verify the association of clinical and genetic variables with external apical root resorption (P <0.05). Results: There was a higher proportion of external apical root resorption in orthodontically treated patients compared with the untreated subjects. In patients orthodontically treated, age higher than 14 years old, initial size of the maxillary incisor root superior to 30 mm, and premolar extraction were associated with increased external apical root resorption. Genotypes containing the C allele were weakly associated with protection against external apical root resorption (CC + CT x TT [odds ratio, 0.29; 95% confidence interval, 0.07-1.23; P = 0.091]) when treated orthodontic patients were compared to untreated individuals. Conclusions: Clinical factors and vitamin D receptor TaqI polymorphism were associated with external apical root resorption in orthodontic patients. (Am J Orthod Dentofacial Orthop 2012; 142: 339-47)

Multivariate analysis in the maximum strength performance

This study performed an exploratory analysis of the anthropometrical and morphological muscle variables related to the one-repetition maximum (1RM) performance. In addition, the capacity of these variables to predict the force production was analyzed. 50 active males were submitted to the experimental procedures: vastus lateralis muscle biopsy, quadriceps magnetic resonance imaging, body mass assessment and 1RM test in the leg-press exercise. K-means cluster analysis was performed after obtaining the body mass, sum of the left and right quadriceps muscle cross-sectional area (Sigma CSA), percentage of the type II fibers and the 1RM performance. The number of clusters was defined a priori and then were labeled as high strength performance (HSP1RM) group and low strength performance (LSP1RM) group. Stepwise multiple regressions were performed by means of body mass, Sigma CSA, percentage of the type II fibers and clusters as predictors' variables and 1RM performance as response variable. The clusters mean +/- SD were: 292.8 +/- 52.1 kg, 84.7 +/- 17.9 kg, 19249.7 +/- 1645.5 mm(2) and 50.8 +/- 7.2% for the HSP1RM and 254.0 +/- 51.1 kg, 69.2 +/- 8.1 kg, 15483.1 +/- 1 104.8 mm(2) and 51.7 +/- 6.2 %, for the LSP1RM in the 1RM, body mass, Sigma CSA and muscle fiber type II percentage, respectively. The most important variable in the clusters division was the Sigma CSA. In addition, the Sigma CSA and muscle fiber type II percentage explained the variance in the 1RM performance (Adj R-2 = 0.35, p = 0.0001) for all participants and for the LSP1RM (Adj R-2 = 0.25, p = 0.002). For the HSP1RM, only the Sigma CSA was entered in the model and showed the highest capacity to explain the variance in the 1RM performance (Adj R-2 = 0.38, p = 0.01). As a conclusion, the muscle CSA was the most relevant variable to predict force production in individuals with no strength training background.

Risk Factor Analysis of Late Survival After Heart Transplantation According to Donor Profile: A Multi-Institutional Retrospective Study of 512 Transplants

Introduction. Patients with terminal heart failure have increased more than the available organs leading to a high mortality rate on the waiting list. Use of Marginal and expanded criteria donors has increased due to the heart shortage. Objective. We analyzed all heart transplantations (HTx) in Sao Paulo state over 8 years for donor profile and recipient risk factors. Method. This multi-institutional review collected HTx data from all institutions in the state of Sao Paulo, Brazil. From 2002 to 2008 (6 years), only 512 (28.8%) of 1777 available heart donors were accepted for transplantation. All medical records were analyzed retrospectively; none of the used donors was excluded, even those considered to be nonstandard. Results. The hospital mortality rate was 27.9% (n = 143) and the average follow-up time was 29.4 +/- 28.4 months. The survival rate was 55.5% (n = 285) at 6 years after HTx. Univariate analysis showed the following factors to impact survival: age (P = .0004), arterial hypertension (P = .4620), norepinephrine (P = .0450), cardiac arrest (P = .8500), diabetes mellitus (P = .5120), infection (P = .1470), CKMB (creatine kinase MB) (P = .8694), creatinine (P = .7225), and Na+ (P = .3273). On multivariate analysis, only age showed significance; logistic regression showed a significant cut-off at 40 years: organs from donors older than 40 years showed a lower late survival rates (P = .0032). Conclusions. Donor age older than 40 years represents an important risk factor for survival after HTx. Neither donor gender nor norepinephrine use negatively affected early survival.

Multivariate analyses of UV-Vis absorption spectral data from cachaca wood extracts: a model to classify aged Brazilian cachacas according to the wood species used

Multivariate analyses of UV-Vis spectral data from cachaca wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. The model is based on inspection of 93 extracts of oak and different Brazilian wood species by a non-aged cachaca used as an extraction solvent. Application of PCA (Principal Components Analysis) and HCA (Hierarchical Cluster Analysis) leads to identification of 6 clusters of cachaca wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaca extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatoba, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (balsamo and jequitiba-rosa). The methodology provides a low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachacas aged in barrels that are composed of different wood species.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

DNA repair gene excision repair cross complementing-group 1 (ERCC1) in head and neck squamous cell carcinoma: analysis of methylation and polymorphism (G19007A), protein expression and association with epidemiological and clinicopathological factors

Aims: To evaluate the associations of excision repair cross complementing-group 1 (ERCC1) (DNA repair protein) (G19007A) polymorphism, methylation and immunohistochemical expression with epidemiological and clinicopathological factors and with overall survival in head and neck squamous cell carcinoma (HNSCC) patients. Methods and results: The study group comprised 84 patients with HNSCC who underwent surgery and adjuvant radiotherapy without chemotherapy. Bivariate and multivariate analyses were used. The allele A genotype variant was observed in 79.8% of the samples, GG in 20.2%, GA in 28.6% and AA in 51.2%. Individuals aged more than 45 years had a higher prevalence of the allelic A variant and a high (83.3%) immunohistochemical expression of ERCC1 protein [odds ratio (OR) = 4.86, 95% confidence interval (CI): 1.2-19.7, P = 0.027], which was also high in patients with advanced stage (OR= 5.04, 95% CI: 1.07-23.7, P = 0.041). Methylated status was found in 51.2% of the samples, and was higher in patients who did not present distant metastasis (OR = 6.67, 95% CI: 1.40-33.33, P = 0.019) and in patients with advanced stage (OR = 5.04, 95% CI: 1.07-23.7, P = 0.041). At 2 and 5 years, overall survival was 55% and 36%, respectively (median = 30 months). Conclusion: Our findings may reflect a high rate of DNA repair due to frequent tissue injury during the lifetime of these individuals, and also more advanced disease presentation in this population with worse prognosis.

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.