Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Exploring the emission intensities of ICP OES aided by chemometrics in the geographical discrimination of mineral waters

A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.

Estimation of hexenuronic acids and kappa number in kraft pulps of Eucalyptus globulus by Fourier transform near infrared spectroscopy and multivariate analysis

Fourier transform near infrared (FT-NIR) spectroscopy was evaluated as an analytical too[ for monitoring residual Lignin, kappa number and hexenuronic acids (HexA) content in kraft pulps of Eucalyptus globulus. Sets of pulp samples were prepared under different cooking conditions to obtain a wide range of compound concentrations that were characterised by conventional wet chemistry analytical methods. The sample group was also analysed using FT-NIR spectroscopy in order to establish prediction models for the pulp characteristics. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of PCR or PLS algorithms. Calibration curves were built by using all the spectral data or selected regions. Best calibration models for the quantification of lignin, kappa and HexA were proposed presenting R-2 values of 0.99. Calibration models were used to predict pulp titers of 20 external samples in a validation set. The lignin concentration and kappa number in the range of 1.4-18% and 8-62, respectively, were predicted fairly accurately (standard error of prediction, SEP 1.1% for lignin and 2.9 for kappa). The HexA concentration (range of 5-71 mmol kg(-1) pulp) was more difficult to predict and the SEP was 7.0 mmol kg(-1) pulp in a model of HexA quantified by an ultraviolet (UV) technique and 6.1 mmol kg(-1) pulp in a model of HexA quantified by anion-exchange chromatography (AEC). Even in wet chemical procedures used for HexA determination, there is no good agreement between methods as demonstrated by the UV and AEC methods described in the present work. NIR spectroscopy did provide a rapid estimate of HexA content in kraft pulps prepared in routine cooking experiments.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Recognition of noisy images by PLL networks

We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Development and validation of sensitive methods for determination of sibutramine hydrochloride monohydrate and direct enantiomeric separation on a protein-based chiral stationary phase

Sibutramine hydrochloride monohydrate, chemically 1-(4-chlorophenyl)-N,N-dimethyl-alpha-(2-methylpropyl) hydrochloride monohydrate (SB center dot HCl center dot H2O), was approved by the U.S. Food and Drug Administration for the treatment of obesity. The objective of this study was to develop, validate, and compare methods using UV-derivative spectrophotometry (UVDS) and reversed-phase high-performance liquid chromatography (HPLC) for the determination of SB center dot HCl center dot H2O in pharmaceutical drug products. The UVDS and HPLC methods were found to be rapid, precise, and accurate. Statistically, there was no significant difference between the proposed UVDS and HPLC methods. The enantiomeric separation of SB was obtained on an alpha-1 acid glycoprotein column. The R- and S-sibutramine were eluted in < 5 min with baseline separation of the chromatographic peaks (alpha = 1.9 and resolution = 1.9).

Development and validation of high performance liquid chromatographic and UV-derivative spectrophotometric methods for the determination of sotalol hydrochloride in tablets

High performance liquid chromatographic (HPLC) and UV derivative spectrophotometric (UVDS) methods were developed and validated for the quantitative determination of sotalol hydrochloride in tablets. The HPLC method was performed on a C18 column with fluorescence detection. The excitation and emission wavelengths were 235 and 310nm, respectively. The mobile phase was composed of acetonitrile-water containing 0.1% trietylamine (7:93v/v) and pH adjusted to 4.6 with formic acid. The UVDS method was performed taking a signal at 239.1nm in the first derivative. The correlation coefficients (r) obtained were 0.9998 and 0.9997 for HPLC and UVDS methods, respectively. The proposed methods are simple and adaptable to routine analysis.

HPLC-FLD methods to quantify chloroaluminum phthalocyanine in nanoparticles, plasma and tissue: application in pharmacokinetic and biodistribution studies

Analytical and bioanalytical methods of high-performance liquid chromatography with fluorescence detection (HPLC-FLD) were developed and validated for the determination of chloroaluminum phthalocyanine in different formulations of polymeric nanocapsules, plasma and livers of mice. Plasma and homogenized liver samples were extracted with ethyl acetate, and zinc phthalocyanine was used as internal standard. The results indicated that the methods were linear and selective for all matrices studied. Analysis of accuracy and precision showed adequate values, with variations lower than 10% in biological samples and lower than 2% in analytical samples. The recoveries were as high as 96% and 99% in the plasma and livers, respectively. The quantification limit of the analytical method was 1.12 ng/ml, and the limits of quantification of the bioanalytical method were 15 ng/ml and 75 ng/g for plasma and liver samples, respectively. The bioanalytical method developed was sensitive in the ranges of 15-100 ng/ml in plasma and 75-500 ng/g in liver samples and was applied to studies of biodistribution and pharmacokinetics of AlClPc. (C) 2011 Elsevier B.V. All rights reserved.

Gingival capillary changes and oral motor weakness in juvenile dermatomyositis

Objective. We assessed the orofacial involvement in JDM, and evaluated the possible association of gingival and mandibular mobility alterations with demographic data, periodontal indices, clinical features, muscle enzyme levels, JDM scores and treatment. Methods. Twenty-six JDM patients were studied and compared with 22 healthy controls. Orofacial evaluation included clinical features, dental and periodontal assessment, mandibular function and salivary flow. Results. The mean current age was similar in patients with JDM and controls (P > 0.05). A unique gingival alteration characterized by erythema, capillary dilation and bush-loop formation was observed only in JDM patients (61 vs 0%, P = 0.0001). The frequencies of altered mandibular mobility and reduced mouth opening were significantly higher in patients with JDM vs controls (50 vs 14%, P = 0.013; 31 vs 0%, P = 0.005). Comparison of the patients with and without gingival alteration showed that the former had lower values of median of cementoenamel junction (-0.26 vs -0.06 mm, P = 0.013) and higher gingival bleeding index (27.7 vs 14%, P = 0.046). This pattern of gingival alteration was not associated with periodontal disease [plaque index (P = 0.332) and dental attachment loss (P = 0.482)]. The medians for skin DAS and current dose of MTX were higher in JDM with gingival alteration (2.5 vs 0.5, P = 0.029; 28.7 vs 15, P = 0.012). A significant association of lower median manual muscle testing with a reduced ability to open the mouth was observed in patients with JDM than those without this alteration (79 vs 80, P = 0.002). Conclusions. The unique gingival pattern associated with cutaneous disease activity, distinct from periodontal disease, suggests that gingiva is a possible target tissue for JDM. In addition, muscle weakness may be a relevant factor for mandibular mobility.

Distribution of HDL-cholesterol and non-HDL-cholesterol in Brazilian children and adolescents - The Floripa study

Background and aims: HDL-cholesterol (HDL-C) and non-HDL-cholesterol (nHDL-C) are involved in atherosclerosis. The aim of this study was to determine the distribution of HDL-C and nHDL-C and its association with cardiovascular and socio-cultural variables in a pediatric Brazilian sample. Methods and results: Children and adolescents from Florianopolis were randomly selected and a structured questionnaire was administered, a physical examination was performed and a blood sample was collected. Enzymatic and Direct methods in vitro were used to determine the total cholesterol and HDL-cholesterol levels. The associations among HDL-C and nHDL-C and the described variables were tested by odds ratio and logistic regression. A total of 1009 individuals were examined. Based on the Brazilian criteria, 23% were classified with low levels of HDL-C and 25% with high levels of non-HDL-C. After multivariate analysis there were significant associations among low HDL-C and high C-reactive protein (OR, 3.3; 95% CI, 2.1-5.2), paternal tobacco use (OR, 1.5; 95% CI, 1.1-2.1), and high triceps-to-subscapular index (OR, 1.5; 95% CI, 1.1-2.2). There were also significant associations among high nHDL-C and high waist circumference (OR, 1.95; 95% CI, 1.16-3.29), black skin color (OR, 1.78; 95% CI, 1.06-3.06), and high income (OR, 1.48; 95% CI, 1.09-2.02). Conclusions: In this sample, low levels of HDL-C were associated with other clinical variables such as a centripetal fat pattern and C-reactive protein, and n-HDL-C was associated with abdominal obesity, skin color and economic class. (C) 2009 Elsevier B. V. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Microangiopathy of the inner ear, deafness, and cochlear implantation in a patient with Susac syndrome

Conclusion: The cochlear implant was beneficial as an attempt to restore hearing and improve communication abilities in this patient with profound sensorineural hearing loss secondary to Susac syndrome. Objective: To report the audiological outcomes of cochlear implantation (CI) in a young woman with Susac syndrome after a 6-month follow-up period. Susac syndrome is a rare disorder. It is clinically characterized by a typical triad of sensorineural deafness, encephalopathy, and visual defect, due to microangiopathy involving the brain, inner ear, and retina. Methods: This was a retrospective review of a case at a tertiary referral center. After diagnosis, the patient was evaluated by a multidisciplinary team and received a cochlear implant in her right ear. Results: The patient achieved 100% open-set sentence recognition in noise conditions and 92% monosyllable and 68% medial consonant recognition in quiet conditions after 6 months of implant use. She reported the use of the telephone 3 months after activation.

Phenotypic and functional characterization of pulmonary macrophages subpopulations after intratracheal injection of Paracoccidioides brasiliensis cell wall components

A shift in the activation of pulmonary macrophages characterized by an increase of IL-1, INF-alpha and IL-6 production has been induced in mice infected with Paracoccidioides brasiliensis. It is still unclear whether a functional shift in the resident alveolar macrophage population would be responsible for these observations due to the expression of cell surface molecules. We investigated pulmonary macrophages by flow cytometry from mice treated with P. brasiliensis derivatives by intratracheal route. In vivo labeling with the dye PKH26GL was applied to characterize newly recruited pulmonary macrophages from the bloodstream. Pulmonary macrophages from mice inflamed with P. brasiliensis derivatives showed a high expression of the surface antigens CD11b/CD18 and CD23 among several cellular markers. The expression of these markers indicated a pattern of activation of a subpopulation characterized as CD11b(+) or CD23(+), which was modulated in vitro by IFN-gamma and IL-4. Analysis of monocytes labelled with PKH26GL demonstrated that CD11b(+) cells did infiltrate the lung exhibiting a proinflammatoni pattern of activation, whereas CD23(+) cells were considered to be resident in the lung. These findings may contribute to better understand the pathology of lung inflammation caused by P. brasiliensis infection. (C) 2010 Elsevier GmbH. All rights reserved.

Affected and non-affected skin fibroblasts from systemic sclerosis patients share a gene expression profile deviated from the one observed in healthy individuals

Objectives To evaluate the gene expression profile of fibroblasts from affected and non-affected skin of systemic sclerosis (SSc) patients and from controls. Materials and methods Labeled cDNA from fibroblast cultures from forearm (affected) and axillary (non-affected) skin from six diffuse SSc patients, from three normal controls, and from MOLT-4/HEp-2/normal fibroblasts (reference pool) was probed in microarrays generated with 4193 human cDNAs from the IMAGE Consortium. Microarray images were converted into numerical data and gene expression was calculated as the ratio between fibroblast cDNA (Cy5) and reference pool cDNA (Cy3) data and analyzed by R environment/Aroma, Cluster, Tree View, and SAM softwares. Differential expression was confirmed by real time PCR for a set of selected genes. Results Eighty-eight genes were up- and 241 genes down-regulated in SSc fibroblasts. Gene expression correlation was strong between affected and non-affected fibroblast samples from the same patient (r>0.8), moderate among fibroblasts from all patients (r=0.72) and among fibroblasts from all controls (r=0.70), and modest among fibroblasts from patients and controls (r=0.55). The differential expression was confirmed by real time PCR for all selected genes. Conclusions Fibroblasts from affected and non-affected skin of SSc patients shared a similar abnormal gene expression profile, suggesting that the widespread molecular disturbance in SSc fibroblasts is more sensitive than histological and clinical alterations. Novel molecular elements potentially involved in SSc pathogenesis were identified.