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.

Numerical analysis of different methods to calculate residual stresses in thin films based on instrumented indentation data

In this work, different methods to estimate the value of thin film residual stresses using instrumented indentation data were analyzed. This study considered procedures proposed in the literature, as well as a modification on one of these methods and a new approach based on the effect of residual stress on the value of hardness calculated via the Oliver and Pharr method. The analysis of these methods was centered on an axisymmetric two-dimensional finite element model, which was developed to simulate instrumented indentation testing of thin ceramic films deposited onto hard steel substrates. Simulations were conducted varying the level of film residual stress, film strain hardening exponent, film yield strength, and film Poisson's ratio. Different ratios of maximum penetration depth h(max) over film thickness t were also considered, including h/t = 0.04, for which the contribution of the substrate in the mechanical response of the system is not significant. Residual stresses were then calculated following the procedures mentioned above and compared with the values used as input in the numerical simulations. In general, results indicate the difference that each method provides with respect to the input values depends on the conditions studied. The method by Suresh and Giannakopoulos consistently overestimated the values when stresses were compressive. The method provided by Wang et al. has shown less dependence on h/t than the others.

Bayesian analysis of weak gravitational lensing and Sunyaev-Zel'dovich data for six galaxy clusters

We present an analysis of observations made with the Arcminute Microkelvin Imager (AMI) and the CanadaFranceHawaii Telescope (CFHT) of six galaxy clusters in a redshift range of 0.160.41. The cluster gas is modelled using the SunyaevZeldovich (SZ) data provided by AMI, while the total mass is modelled using the lensing data from the CFHT. In this paper, we (i) find very good agreement between SZ measurements (assuming large-scale virialization and a gas-fraction prior) and lensing measurements of the total cluster masses out to r200; (ii) perform the first multiple-component weak-lensing analysis of A115; (iii) confirm the unusual separation between the gas and mass components in A1914 and (iv) jointly analyse the SZ and lensing data for the relaxed cluster A611, confirming our use of a simulation-derived masstemperature relation for parametrizing measurements of the SZ effect.

Hyperinsulinemic hypoglycemia of the infancy. Analysis of clinical data from a Brazilian sample

Objective: To review the presentation of hyperinsulinemic hypoglycemia of the infancy (HHI), its treatment and histology in Brazilian pediatric endocrinology sections. Materials and method: The protocol analyzed data of birth, laboratory results, treatment, surgery, and pancreas histology. Results: Twenty-five cases of HHI from six centers were analyzed: 15 male, 3/25 born by vaginal delivery. The average age at diagnosis was 10.3 days. Glucose and insulin levels in the critical sample showed an average of 24.7 mg/dL and 26.3 UI/dL. Intravenous infusion of the glucose was greater than 10 mg/kg/min in all cases (M:19,1). Diazoxide was used in 15/25 of the cases, octreotide in 10, glucocorticoid in 8, growth hormone in 3, nifedipine in 2 and glucagon in 1. Ten of the cases underwent pancreatectomy and histology results showed the diffuse form of disease. Conclusion: This is the first critic review of a Brazilian sample with congenital HHI. Arq Bras Endocrinol Metab. 2012; 56(9): 666-71

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.

Morphological, molecular and cross-breeding analysis of geographic populations of coconut-mite associated predatory mites identified as Neoseiulus baraki: evidence for cryptic species?

Surveys were conducted in Brazil, Benin and Tanzania to collect predatory mites as candidates for control of the coconut mite Aceria guerreronis Keifer, a serious pest of coconut fruits. At all locations surveyed, one of the most dominant predators on infested coconut fruits was identified as Neoseiulus baraki Athias-Henriot, based on morphological similarity with regard to taxonomically relevant characters. However, scrutiny of our own and published descriptions suggests that consistent morphological differences may exist between the Benin population and those from the other geographic origins. In this study, we combined three methods to assess whether these populations belong to one species or a few distinct, yet closely related species. First, multivariate analysis of 32 morphological characters showed that the Benin population differed from the other three populations. Second, DNA sequence analysis based on the mitochondrial cytochrome oxidase subunit I (COI) showed the same difference between these populations. Third, cross-breeding between populations was unsuccessful in all combinations. These data provide evidence for the existence of cryptic species. Subsequent morphological research showed that the Benin population can be distinguished from the others by a new character (not included in the multivariate analysis), viz. the number of teeth on the fixed digit of the female chelicera.

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

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures. (C) 2011 Elsevier B.V. All rights reserved.

BayGO: Bayesian analysis of ontology term enrichment in microarray data

Abstract Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract Background Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. Results Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. Conclusion GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

Quantitative chemical profile and multivariate statistical analysis of alembic distilled sugarcane spirit fractions

As concentrações de 39 compostos orgânicos foram determinadas em três frações (cabeça, coração e cauda) obtidas da destilação em alambique do caldo de cana fermentado. Os resultados foram avaliados utilizando-se análise de variância (ANOVA), teste de Tukey, análise de componentes principais (PCA), agrupamento hierárquico (HCA) e análise discriminante linear (LDA). De acordo com PCA e HCA, os dados experimentais conduzem à formação de três agrupamentos. As frações de cabeça deram origem a um grupo mais definido. As frações coração e cauda apresentaram alguma sobreposição coerente com sua composição em ácidos. As habilidades preditivas de calibração e validação dos modelos gerados pela LDA para a classificação das três frações foram de 90,5 e 100%, respectivamente. Este modelo reconheceu como coração doze de treze cachaças comerciais (92,3%) com boas características sensoriais, apresentando potencial para a orientação do processo de cortes.

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Comparing Different Approaches for Clustering Categorical Data

There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking

The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.