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.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

Recognition of cyclic, acyclic, exocyclic, and spiro Acetals via structurally diagnostic ion/molecule reactions with the (CH3)(2)N-C+=O acylium ion

Reactions of the model acylium ion (CH3)(2)N-C+=O with acyclic, exocyclic, and Spiro acetals of the general formula (RO)-O-1-(CRR4)-R-3-OR2-upole mass spectrometry. Characteristic intrinsic reactivities were observed for each of these classes of acetals. The two most Characteristic intrinsic reactivities were observed for each of these classes of acetals. The two most common reactions observed were hydride and alkoxy anion [(RO-)-O-1 and (RO-)-O-2] abstraction. Other specific reactions were also observed: (a) a secondary polar [4(+) + 2] cycloaddition for acetals bearing alpha,beta-unsaturated R-3 or R-4 substituents and (b) OH- abstraction for exocyclic and spiro acetals. These structurally diagnostic reactions, in conjunction with others observed previously for cyclic acetals, are shown to reveal the class of the acetal molecule and its ring type and substituents and to permit their recognition and distinction from other classes of isomeric molecules.

Patterns of brain asymmetry in the perception of positive and negative facial expressions

The divided visual field technique was used to investigate the pattern of brain asymmetry in the perception of positive/approach and negative/withdrawal facial expressions. A total of 80 undergraduate students (65 female, 15 male) were distributed in five experimental groups in order to investigate separately the perception of expressions of happiness, surprise, fear, sadness, and the neutral face. In each trial a target and a distractor expression were presented simultaneously in a computer screen for 150 ms and participants had to determine the side (left or right) on which the target expression was presented. Results indicated that expressions of happiness and fear were identified faster when presented in the left visual field, suggesting an advantage of the right hemisphere in the perception of these expressions. Fewer judgement errors and faster reaction times were also observed for the matching condition in which emotional faces were presented in the left visual field and neutral faces in the right visual field. Other results indicated that positive expressions (happiness and surprise) were perceived faster and more accurately than negative ones (sadness and fear). Main results tend to support the right hemisphere hypothesis, which predicts a better performance of the right hemisphere to perceive emotions, as opposed to the approach-withdrawal hypothesis.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

Quantification of Regional Left and Right Ventricular Deformation Indices in Healthy Neonates by Using Strain Rate and Strain Imaging

Background: Color Doppler myocardial imaging (CDMI) allows the calculation of local longitudinal or radial strain rate (SR) and strain (epsilon). The aims of this study were to determine the feasibility and reproducibility of longitudinal and radial SR and epsilon in neonates during the first hours of life and to establish reference values. Methods: Data were obtained from 55 healthy neonates (29 male; mean age, 20 +/- 14 hours; mean birth weight, 3,174 +/- 374 g). Apical and parasternal views quantified regional longitudinal and radial SR and epsilon in differing ventricular wall segments. Values at peak systole, early diastole, and late diastole were calculated from the extracted curves. CDMI data acquired at 300 +/- 50 frames/s were analyzed offline. Three consecutive cardiac cycles were measured during normal respiration. The timing of specific systolic or diastolic regional events was determined. Multiple comparisons between walls and segments were made. Results: Left ventricular (LV) longitudinal deformation showed basal differences compared with apical segments within one specific wall. Right ventricular (RV) longitudinal deformation was not homogeneous, with significant differences between basal and apical segments. Longitudinal 3 values were higher in the RV free basal and middle wall segments compared with the left ventricle. In the RV free wall apical segment, longitudinal SR and 3 were maximal. LV systolic SR and epsilon values were higher radially compared with longitudinally (radial peak systolic SR midportion, 2.9 +/- 0.6 s(-1); radial peak systolic epsilon 53.8 +/- 19%; longitudinal peak systolic SR midportion, -1.8 +/- 0.5 s(-1); longitudinal peak systolic epsilon, -24.8 +/- 3%; P < .01). Longitudinal systolic epsilon and SR interobserver variability values were 1.2% and 0.7%, respectively. Conclusion: Ultrasound-based SR and 3 imaging is a practical and reproducible clinical technique in neonates, allowing the calculation of regional longitudinal and radial deformation in RV and LV segments. These regional SR and epsilon indices represent new, noninvasive parameters that can quantify normal neonate regional cardiac function. Independent from visual interpretation, they can be used as reference values for diagnosis in ill neonates. (J Am Soc Echocardiogr 2009;22:369-375.)

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.

Comparative epidemiology of chronic fatigue syndrome in Brazilian and British primary care: prevalence and recognition

Background Although fatigue is a ubiquitous symptom across countries, clinical descriptions of chronic fatigue syndrome have arisen from a limited number of high-income countries. This might reflect differences in true prevalence or clinical recognition influenced by sociocultural factors. Aims To compare the prevalence, physician recognition and diagnosis of chronic fatigue syndrome in London and Sao Paulo. Method Primary care patients in London (n=2459) and Sao Paulo n=3914) were surveyed for the prevalence of chronic fatigue syndrome. Medical records were reviewed for the physician recognition and diagnosis. Results The prevalence of chronic fatigue syndrome according to Centers for Disease Control 1994 criteria was comparable in Britain and Brazil, 2.1% v. 1.6% (P=0.20). Medical records review identified 11 diagnosed cases of chronic fatigue syndrome in Britain, but none in Brazil (P<0.001). Conclusions The primary care prevalence of chronic fatigue syndrome was similar in two Culturally and economically distinct nations. However, doctors are unlikely to recognise and label chronic fatigue syndrome as a discrete disorder in Brazil. The recognition of this illness rather than the illness itself may be culturally induced.

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.

A Survey on Graphical Methods for Classification Predictive Performance Evaluation

Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.

Generalized external indexes for comparing data partitions with overlapping categories

There is a family of well-known external clustering validity indexes to measure the degree of compatibility or similarity between two hard partitions of a given data set, including partitions with different numbers of categories. A unified, fully equivalent set-theoretic formulation for an important class of such indexes was derived and extended to the fuzzy domain in a previous work by the author [Campello, R.J.G.B., 2007. A fuzzy extension of the Rand index and other related indexes for clustering and classification assessment. Pattern Recognition Lett., 28, 833-841]. However, the proposed fuzzy set-theoretic formulation is not valid as a general approach for comparing two fuzzy partitions of data. Instead, it is an approach for comparing a fuzzy partition against a hard referential partition of the data into mutually disjoint categories. In this paper, generalized external indexes for comparing two data partitions with overlapping categories are introduced. These indexes can be used as general measures for comparing two partitions of the same data set into overlapping categories. An important issue that is seldom touched in the literature is also addressed in the paper, namely, how to compare two partitions of different subsamples of data. A number of pedagogical examples and three simulation experiments are presented and analyzed in details. A review of recent related work compiled from the literature is also provided. (c) 2010 Elsevier B.V. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

Novel Zn(2+)-binding Sites in Human Transthyretin IMPLICATIONS FOR AMYLOIDOGENESIS AND RETINOL-BINDING PROTEIN RECOGNITION

Human transthyretin (TTR) is a homotetrameric protein involved in several amyloidoses. Zn(2+) enhances TTR aggregation in vitro, and is a component of ex vivo TTR amyloid fibrils. We report the first crystal structure of human TTR in complex with Zn(2+) at pH 4.6-7.5. All four structures reveal three tetra-coordinated Zn(2+)-binding sites (ZBS 1-3) per monomer, plus a fourth site (ZBS 4) involving amino acid residues from a symmetry-related tetramer that is not visible in solution by NMR.Zn(2+) binding perturbs loop E-alpha-helix-loop F, the region involved in holo-retinol-binding protein (holo-RBP) recognition, mainly at acidic pH; TTR affinity for holo-RBP decreases similar to 5-fold in the presence of Zn(2+). Interestingly, this same region is disrupted in the crystal structure of the amyloidogenic intermediate of TTR formed at acidic pH in the absence of Zn(2+). HNCO and HNCA experiments performed in solution at pH 7.5 revealed that upon Zn(2+) binding, although the alpha-helix persists, there are perturbations in the resonances of the residues that flank this region, suggesting an increase in structural flexibility. While stability of the monomer of TTR decreases in the presence of Zn(2+), which is consistent with the tertiary structural perturbation provoked by Zn(2+) binding, tetramer stability is only marginally affected by Zn(2+). These data highlight structural and functional roles of Zn(2+) in TTR-related amyloidoses, as well as in holo-RBP recognition and vitamin A homeostasis.