Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Resultados preliminares de um algoritmo para ablação de lente de contato personalizada

OBJETIVO: Desenvolver simulação computadorizada de ablação para produzir lentes de contato personalizadas a fim de corrigir aberrações de alta ordem. MÉTODOS: Usando dados reais de um paciente com ceratocone, mensurados em um aberrômetro ("wavefront") com sensor Hartmann-Shack, foram determinados as espessuras de lentes de contato que compensam essas aberrações assim como os números de pulsos necessários para fazer ablação as lentes especificamente para este paciente. RESULTADOS: Os mapas de correção são apresentados e os números dos pulsos foram calculados, usando feixes com a largura de 0,5 mm e profundidade de ablação de 0,3 µm. CONCLUSÕES: Os resultados simulados foram promissores, mas ainda precisam ser aprimorados para que o sistema de ablação "real" possa alcançar a precisão desejada.

Spatial analysis of urban violence based on emergency room data

OBJECTIVE: To estimate the spatial intensity of urban violence events using wavelet-based methods and emergency room data. METHODS: Information on victims attended at the emergency room of a public hospital in the city of São Paulo, Southeastern Brazil, from January 1, 2002 to January 11, 2003 were obtained from hospital records. The spatial distribution of 3,540 events was recorded and a uniform random procedure was used to allocate records with incomplete addresses. Point processes and wavelet analysis technique were used to estimate the spatial intensity, defined as the expected number of events by unit area. RESULTS: Of all georeferenced points, 59% were accidents and 40% were assaults. There is a non-homogeneous spatial distribution of the events with high concentration in two districts and three large avenues in the southern area of the city of São Paulo. CONCLUSIONS: Hospital records combined with methodological tools to estimate intensity of events are useful to study urban violence. The wavelet analysis is useful in the computation of the expected number of events and their respective confidence bands for any sub-region and, consequently, in the specification of risk estimates that could be used in decision-making processes for public policies.

New data on the natural history and description of the immatures of Fulgeochlizus bruchi, a bioluminescent beetle from Central Brazil (Elateridae, Pyrophorini)

The mature larva and pupa of Fulgeochlizus bruchi (Candèze, 1896) are described and illustrated. Bioluminescent patterns are also given. Comments, new data on the first instar larva and natural history data are presented. The first instar larvae differ from the mature larvae mainly in their chaetotaxy, which is sparse and more symmetrically distributed.

Calibration of the dietary data obtained from the Brazilian center of the Natural History of HPV Infection in Men study: the HIM Study

The objective of this study was to estimate the regressions calibration for the dietary data that were measured using the quantitative food frequency questionnaire (QFFQ) in the Natural History of HPV Infection in Men: the HIM Study in Brazil. A sample of 98 individuals from the HIM study answered one QFFQ and three 24-hour recalls (24HR) at interviews. The calibration was performed using linear regression analysis in which the 24HR was the dependent variable and the QFFQ was the independent variable. Age, body mass index, physical activity, income and schooling were used as adjustment variables in the models. The geometric means between the 24HR and the calibration-corrected QFFQ were statistically equal. The dispersion graphs between the instruments demonstrate increased correlation after making the correction, although there is greater dispersion of the points with worse explanatory power of the models. Identification of the regressions calibration for the dietary data of the HIM study will make it possible to estimate the effect of the diet on HPV infection, corrected for the measurement error of the QFFQ.

Discrepancies among ecological, household, and individual data on fruits and vegetables consumption in Brazil

Information on fruits and vegetables consumption in Brazil in the three levels of dietary data was analyzed and compared. Data about national supply came from Food Balance Sheets compiled by the FAO; household availability information was obtained from the Brazilian National Household Budget Survey (HBS); and actual intake information came from a large individual dietary intake survey that was representative of the adult population of São Paulo city. All sources of information were collected between 2002 and 2003. A subset of the HBS, representative of São Paulo city, was used in our analysis in order to improve the quality of the comparison with actual intake data. The ratio of national supply to household availability of fruits and vegetables was 2.6 while the ratio of national supply to actual intake was 4.0. The discrepancy ratio in the comparison between household availability and actual intake was smaller, 1.6. While the use of supply and availability data has advantages, as lower cost, must be taken into account that these sources tend to overestimate actual intake of fruits and vegetables.

Body Mass Index, Cigarette Smoking, and Alcohol Consumption and Cancers of the Oral Cavity, Pharynx, and Larynx: Modeling Odds Ratios in Pooled Case-Control Data

study-specific results, their findings should be interpreted with caution

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Combining Legendre's Polynomials and Genetic Algorithm in the Solution of Nonlinear Initial-Value Problems

This work develops a method for solving ordinary differential equations, that is, initial-value problems, with solutions approximated by using Legendre's polynomials. An iterative procedure for the adjustment of the polynomial coefficients is developed, based on the genetic algorithm. This procedure is applied to several examples providing comparisons between its results and the best polynomial fitting when numerical solutions by the traditional Runge-Kutta or Adams methods are available. The resulting algorithm provides reliable solutions even if the numerical solutions are not available, that is, when the mass matrix is singular or the equation produces unstable running processes.

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

System-Size Independence of Directed Flow Measured at the BNL Relativistic Heavy-Ion Collider

We measure directed flow (v(1)) for charged particles in Au + Au and Cu + Cu collisions at root s(NN) = 200 and 62.4 GeV, as a function of pseudorapidity (eta), transverse momentum (p(t)), and collision centrality, based on data from the STAR experiment. We find that the directed flow depends on the incident energy but, contrary to all available model implementations, not on the size of the colliding system at a given centrality. We extend the validity of the limiting fragmentation concept to v(1) in different collision systems, and investigate possible explanations for the observed sign change in v(1)(p(t)).

Factor (NF) kappa B polymorphism is associated with heart function in patients with heart failure

Background: Cardiac remodeling is generally an adverse sign and is associated with heart failure (HF) progression. NFkB, an important transcription factor involved in many cell survival pathways, has been implicated in the remodeling process, but its role in the heart is still controversial. Recently, a promoter polymorphism associated with a lesser activation of the NFKB1 gene was also associated with Dilated Cardiomyopathy. The purpose of this study was to evaluate the association of this polymorphism with clinical and functional characteristics of heart failure patients of different etiologies. Methods: A total of 493 patients with HF and 916 individuals from a cohort of individuals from the general population were investigated. The NFKB1-94 insertion/deletion ATTG polymorphism was genotyped by High Resolution Melt discrimination. Allele and genotype frequencies were compared between groups. In addition, frequencies or mean values of different phenotypes associated with cardiovascular disease were compared between genotype groups. Finally, patients were prospectively followed-up for death incidence and genotypes for the polymorphism were compared regarding disease onset and mortality incidence in HF patients. Results: We did not find differences in genotype and allelic frequencies between cases and controls. Interestingly, we found an association between the ATTG(1)/ATTG(1) genotype with right ventricle diameter (P = 0.001), left ventricle diastolic diameter (P = 0.04), and ejection fraction (EF) (P = 0.016), being the genotype ATTG(1)/ATTG(1) more frequent in patients with EF lower than 50% (P = 0.01). Finally, we observed a significantly earlier disease onset in ATTG(1)/ATTG(1) carriers. Conclusion: There is no genotype or allelic association between the studied polymorphism and the occurrence of HF in the tested population. However, our data suggest that a diminished activation of NFKB1, previously associated with the ATTG(1)/ATTG(1) genotype, may act modulating on the onset of disease and, once the individual has HF, the genotype may modulate disease severity by increasing cardiac remodeling and function deterioration.

Remote Cerebellar Hemorrhage (Zebra Sign) in Vascular Neurosurgery: Pathophysiological Insights

Hemorrhage in regions remote from the site of initial intracranial operations is rare, but may be fatal. Postoperative cerebellar hemorrhage as a complication of supratentorial surgery, with a radiological appearance known as zebra sign, is an increasingly recognized clinical entity and is associated mainly with vascular neurosurgery or temporal lobe resection. The pathophysiology remains unclear. Three cases of remote cerebellar hematoma occurred after neck clipping of anterior communicating artery aneurysms. All patients had similar clinical findings and underwent pterional craniotomy with the head in accentuated extension. One patient died and the two were discharged without symptoms. Cerebellar hemorrhage probably has a multifactorial origin involving positioning associated with abundant cerebrospinal fluid drainage causing cerebellar sag with resultant vein stretching and bleeding, and use of aspirin or other antiplatelet agents.

Qualitative Analysis of the Interdisciplinary Interaction between Data Analysis Specialists and Novice Clinical Researchers

Background: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. Methods/Principal Findings: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of ""what if'' situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. Conclusion/Significance: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.