Assignment of Putative Functions to Membrane "Hypothetical Proteins" from the Trypanosoma cruzi Genome

Protozoan parasites cause thousands of deaths each year in developing countries. The genome projects of these parasites opened a new era in the identification of therapeutic targets. However, the putative function could be predicted for fewer than half of the protein-coding genes. In this work, all Trypanosoma cruzi proteins containing predicted transmembrane spans were processed through an automated computational routine and further analyzed in order to assign the most probable function. The analysis consisted of dissecting the whole predicted protein in different regions. More than 5,000 sequences were processed, and the predicted biological functions were grouped into 19 categories according to the hits obtained after analysis. One focus of interest, due to the scarce information available on trypanosomatids, is the proteins involved in signal-transduction processes. In the present work, we identified 54 proteins belonging to this group, which were individually analyzed. The results show that by means of a simple pipeline it was possible to attribute probable functions to sequences annotated as coding for "hypothetical proteins.'' Also, we successfully identified the majority of candidates participating in the signal-transduction pathways in T. cruzi.

An Insight into the Sialotranscriptome of Triatoma matogrossensis, a Kissing Bug Associated with Fogo Selvagem in South America

Triatoma matogrossensis is a Hemiptera that belongs to the oliveirai complex, a vector of Chagas' disease that feeds on vertebrate blood in all life stages. Hematophagous insects' salivary glands (SGs) produce potent pharmacologic compounds that counteract host hemostasis, including anticlotting, antiplatelet, and vasodilatory molecules. Exposure to T. matogrossensis was also found to be a risk factor associated with the endemic form of the autoimmune skin disease pemphigus foliaceus, which is described in the same regions where Chagas' disease is observed in Brazil. To obtain a further insight into the salivary biochemical and pharmacologic diversity of this kissing bug and to identify possible allergens that might be associated with this autoimmune disease, a cDNA library from its SGs was randomly sequenced. We present the analysis of a set of 2,230 (SG) cDNA sequences, 1,182 of which coded for proteins of a putative secretory nature.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

First observation of alternative food usage (extrafloral nectar) by the assassin bug Atopozelus opsimus (Hemiptera, Reduviidae)

First observation of alternative food usage (extrafloral nectar) by the assassin bug Atopozelus opsimus (Hemiptera, Reduviidae). Assassin bugs (Reduviidae) are voracious insects that prey on other arthropods. Recent evidences have pointed out that these predators also feed on plant derived substances in rare opportunities. The present study describes the feeding behavior of the reduviid Atopozelus opsimus on extrafloral nectaries of Inga vera (Fabaceae) in a Neotropical savanna area. It was investigated if the insects feed more frequently of extrafloral nectar or prey, and if individuals of different stages of development vary according to feeding behavior. Notably, the results suggest that the diet of all instars and adults consist mainly of extrafloral nectar (N = 1013), in detriment of captured prey ingestion (N = 18). Also, there was no variation on feeding behavior and life stage.

Prey digestion in the midgut of the predatory bug Podisus nigrispinus (Hemiptera: Pentatomidae)

Pre-oral digestion is described as the liquefaction of the solid tissues of the prey by secretions of the predator. It is uncertain if pre-oral digestion means pre-oral dispersion of food or true digestion in the sense of the stepwise bond breaking of food polymers to release monomers to be absorbed. Collagenase is the only salivary proteinase, which activity is significant (10%) in relation to Podisus nigrispinus midgut activities. This suggests that pre-oral digestion in P. nigrispinus consists in prey tissue dispersion. This was confirmed by the finding of prey muscles fibers inside P. nigrispinus midguts. Soluble midgut hydrolases from P. nigrispinus were partially purified by ion-exchange chromatography, followed by gel filtration. Two cathepsin L-like proteinases (CAL1 and CAL2) were isolated with the properties: CAL1 (14.7 kDa, pH optimum (pHo) 5.5, km with carbobenzoxy-Phe-Arg-methylcoumarin, Z-FR-MCA, 32 mu M); CAL2 (17 kDa, pHo 5.5, km 11 mu M Z-FR-MCA). Only a single molecular species was found for the other enzymes with the following properties are: amylase (43 kDa, pHo 5.5, km 0.1% starch), aminopeptidase (125 kDa, pHo 5.5, km 0.11 mM L-Leucine-p-nitroanilide), alpha-glucosidase (90 kDa, pHo 5.0, km 5 mM with p-nitrophenyl alpha-D-glucoside). CAL molecular masses are probably underestimated due to interaction with the column. Taking into account the distribution of hydrolases along P. nigrispinus midguts, carbohydrate digestion takes place mainly at the anterior midgut, whereas protein digestion occurs mostly in middle and posterior midgut, as previously described in seed- sucker and blood-feeder hemipterans. (C) 2012 Elsevier Ltd. All rights reserved.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the well-known simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.

Development of a high sensitive automatic setup for screening of microcystins in surface waters by employing a LED-based photometric detector

In this manuscript, an automatic setup for screening of microcystins in surface waters by employing photometric detection is described. Microcystins are toxins delivered by cyanobacteria within an aquatic environment, which have been considered strongly poisonous for humans. For that reason, the World Health Organization (WHO) has proposed a provisional guideline value for drinking water of 1 mu g L-1. In this work, we developed an automated equipment setup, which allows the screening of water for concentration of microcystins below 0.1 mu g V. The photometric method was based on the enzyme-linked immunosorbent assay (ELISA) and the analytical signal was monitored at 458 nm using a homemade LED-based photometer. The proposed system was employed for the detection of microcystins in rivers and lakes waters. Accuracy was assessed by processing samples using a reference method and applying the paired t-test between results. No significant difference at the 95% confidence level was observed. Other useful features including a linear response ranging from 0.05 up to 2.00 mu g L-1 (R-2 =0.999) and a detection limit of 0.03 mu g L-1 microcystins were achieved. (C) 2011 Elsevier B.V. All rights reserved.

Nosocomial outbreak of Pantoea agglomerans bacteraemia associated with contaminated anticoagulant citrate dextrose solution: new name, old bug?

We describe an outbreak investigation of Pantoea agglomerans bacteraemia associated with anticoagulant citrate-dextrose 46% (ACD) solution prepared in-house. A healthy man presented with septic shock during plasmapheresis for granulocyte donation. The solution used for priming and blood samples were sent for culture. Identification of the isolate to species level was performed by gyrB sequencing. Typing was performed by pulsed-field gel electrophoresis (PFGE). In total, eight cases were identified during a three-week period. P. agglomerans was also cultured from six ACD solution bags. Isolates from patients and ACD bags were identical by PFGE. All isolates were susceptible to ampicillin, cephazolin, gentamicin, ciprofloxacin, cefepime and imipenem. (C) 2011 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Detailed H-1 and C-13 NMR structural assignment and relative stereochemistry determination for three new and one known semi-synthetic sesquiterpene lactones

In this work is described a complete H-1 and C-13 NMR analysis for a group of four sesquiterpene lactones, three previously unknown. The unequivocal assignments were achieved by H-1 NMR, C-13{H-1} NMR, gCOSY. gHMQC, gHMBC and NOESY experiments and no ambiguities were left behind. All hydrogen coupling constants were measured, clarifying all hydrogen signals multiplicities. (C) 2011 Elsevier B.V. All rights reserved.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.

Morphological analysis of Mecosarthron Buquet and Xixuthrus Thomson and Reevaluation of Generic Assignment of Xixuthrus domingoensis Fisher (Coleoptera, Cerambycidae, Prioninae)

The characters defining Mecosarthron Buquet, 1840 and Xixuthrus Thomson 1864 are discussed, along with a historical review of the literature that described and classified these taxa. Through morphological examination of these genera and most of the included species, we addressed the systematic placement of Xixuthrus domingoensis Fisher, 1932 that was placed in Mecosarthron by Ivie (1985). We restore its placement in the genus Xixuthrus. The first description of the female of X. domingoensis is provided, along with comparative redescriptions of Mecosarthron gounellei (Lameere, 1903), and M. buphagus Buquet, 1840. We include a key to the species currently in Mecosarthron.