Sensitivity and specificity based multiobjective approach for feature selection: Application to cancer diagnosis

The study of the sensitivity and the specificity of a classification test constitute a powerful kind of analysis since it provides specialists with very detailed information useful for cancer diagnosis. In this work, we propose the use of a multiobjective genetic algorithm for gene selection of Microarray datasets. This algorithm performs gene selection from the point of view of the sensitivity and the specificity, both used as quality indicators of the classification test applied to the previously selected genes. In this algorithm, the classification task is accomplished by Support Vector Machines; in addition a 10-Fold Cross-Validation is applied to the resulting subsets. The emerging behavior of all these techniques used together is noticeable, since this approach is able to offer, in an original and easy way, a wide range of accurate solutions to professionals in this area. The effectiveness of this approach is proved on public cancer datasets by working out new and promising results. A comparative analysis of our approach using two and three objectives, and with other existing algorithms, suggest that our proposal is highly appropriate for solving this problem.     

Parallelism and evolutionary algorithms

This paper contains a modern vision of the parallelization techniques used for evolutionary algorithms (EAs). The work is motivated by two fundamental facts: 1) the different families of EAs have naturally converged in the last decade while parallel EAs (PEAs) are still lack of unified studies; and 2) there is a large number of improvements in these algorithms and in their parallelization that raise the need for a comprehensive survey. We stress the differences between the EA model and its parallel implementation throughout the paper. We discuss the advantages and drawbacks of PEAs. Also, successful applications are mentioned and open problems are identified. We propose potential solutions to these problems and classify the different ways in which recent results in theory and practice are helping to solve them. Finally, we provide a highly structured background relating to PEAs in order to make researchers aware of the benefits of decentralizing and parallelizing an EA     

Materials science and metallurgy of the Caribbean steel drum Part I Fabrication, deformation phenomena and acoustic fundamentals

Steel-drum fabrication, especially the sinking of the drum head (also referred to as the pan) by hand with a hammer, has been examined in detail utilizing light metallography (LM) and transmission electron microscopy (TEM) to characterize residual microstructures corresponding to reductions in thickness of up to 50 % at the bottom of the drum head. Dislocation densities in the low-carbon (0.01–0.05 wt % C), ferritic steels can exceed 10¹⁰ cm^-2. Simulations of simple, ideal, free circular notes utilizing 316 stainless-steel plates (0.05 wt % C), cold rolled to reductions up to 40%, revealed that deformation (per cent cold reduction) has an important effect on the acoustic spectrum, especially harmonic spectra. Harmonic-node splitting was observed for thin circular plates (0.076 cm thick); the frequency difference was 60 Hz at 20% cold reduction and 160 Hz at 40% cold reduction. These dispersion effects, due to deformation-induced microstructures, as well as irregularities in the note geometries and thicknesses, point to the complex and non-linear acoustic features that contribute to the unique sounds of the Caribbean steel drum.     

Analysis of octyl- and nonylphenol and their ethoxylates in water and sediments by liquid chromatography/tandem mass spectrometry

The ubiquitous presence of alkylphenol ethoxylates in the environment as well as concern for endocrine disruption effects in biota caused by their degradation products (such as octyl- and nonylphenol) has raised interest in the environmental fate of these compounds. As part of an effort to model their behavior in a subestuary of the Chesapeake Bay, a quantitative method for the analysis of octyl- and nonylphenol, and their ethoxylates (1-5) in water and sediment was developed. Extraction procedures are based on solid-phase extraction techniques. Identification and quantitation of the analytes is done by liquid chromatography coupled to tandem mass spectrometry. Instrument detection limits for the compounds ranged from 0.1 to 9 pg injected on column, which allowed method detection limits of 0.04-3 ng/L in water and 0.2-13 ng/g of dry weight in sediment. The method was used to analyze water and sediment from the Back River, MD, where concentrations for the individual compounds ranged from <8 to 200 ng/L in water and <9 to 6700 ng/g of dry weight in sediment. Additionally, structural information obtained in the mass spectrometer is presented that supports previous observations that nonylphenol and its ethoxylates are composed mainly of isomers with a tertiary alpha-carbon.     

Multiple biological sequence alignment in heterogeneous multicore clusters with user-selectable task allocation policies

Multiple Sequence Alignment (MSA) is an important problem in Bioinformatics that aims to align more than two sequences in order to emphasize similarity regions. This problem is known to be NP-Hard, so heuristic methods are used to solve it. DIALIGN-TX is an iterative heuristic method for MSA that generates alignments by concatenating ungapped regions with high similarity. Usually, the first phase of MSA algorithms is parallelized by distributing several independent tasks among the nodes. Even though heterogeneous multicore clusters are becoming very common nowadays, very few task allocation policies were proposed for this type of architecture. This paper proposes an MPI/OpenMP master/slave parallel strategy to run DIALIGN-TX in heterogeneous multicore clusters, with several allocation policies. We show that an appropriate choice of the master node has great impact on the overall system performance. Also, the results obtained in a heterogeneous multicore cluster composed of 4 nodes (30 cores), with real sequence sets show that the execution time can be drastically reduced when the appropriate allocation policy is used.     

Multi-Objective Optimization using Grid Computing

This paper analyzes some technical and practical issues concerning the use of parallel systems to solve multi-objective optimization problems using enumerative search. This technique constitutes a conceptually simple search strategy, and it is based on evaluating each possible solution from a given finite search space. The results obtained by enumeration are impractical for most computer platforms and researchers, but they exhibit a great interest because they can be used to be compared against the values obtained by stochastic techniques. We analyze here the use of a grid computing system to cope with the limits of enumerative search. After evaluating the performance of the sequential algorithm, we present, first, a parallel algorithm targeted to multiprocessor systems. Then, we design a distributed version prepared to be executed on a federation of geographically distributed computers known as a computational grid. Our conclusion is that this kind of systems can provide to the community with a large and precise set of Pareto fronts that would be otherwise unknown.     

The Metabolic Role of Gut Microbiota in the Development of Nonalcoholic Fatty Liver Disease and Cardiovascular Disease

The prevalence of metabolic disorders, such as type 2 diabetes (T2D), obesity, and non-alcoholic fatty liver disease (NAFLD), which are common risk factors for cardiovascular disease (CVD), has dramatically increased worldwide over the last decades. Although dietary habit is the main etiologic factor, there is an imperfect correlation between dietary habits and the development of metabolic disease. Recently, research has focused on the role of the microbiome in the development of these disorders. Indeed, gut microbiota is implicated in many metabolic functions and an altered gut microbiota is reported in metabolic disorders. Here we provide evidence linking gut microbiota and metabolic diseases, focusing on the pathogenetic mechanisms underlying this association.     

Clinical presentation of HIV infection in patients aged 50 years or older

A case of metachronous malignancy in an elderly postmenopausal lady is presented. She had previously been successfully treated for squamous cell carcinoma of the cervix and now four years later, presented with a right lower lobe lung abscess. On evaluation she was found to have a small cell carcinoma of the lung involving the right intermediate and right lower lobe bronchus. She improved clinically and radiologically with parenteral antibiotics, combination chemotherapy and local external radiotherapy.