A hybrid approach to selecting susceptible single nucleotide polymorphisms for complex disease analysis

An increasingly popular and promising way for complex disease diagnosis is to employ artificial neural networks (ANN). Single nucleotide polymorphisms (SNP) data from individuals is used as the inputs of ANN to find out specific SNP patterns related to certain disease. Due to the large number of SNPs, it is crucial to select optimal SNP subset and their combinations so that the inputs of ANN can be reduced. With this observation in mind, a hybrid approach - a combination of genetic algorithms (GA) and ANN (called GANN) is used to automatically determine optimal SNP set and optimize the structure of ANN. The proposed GANN algorithm is evaluated by using both a synthetic dataset and a real SNP dataset of a complex disease.

Assessment of the effectiveness of light-emitting diode and diode laser hybrid light sources to intensify dental bleaching treatment

Objective. To evaluate the effectiveness of the color change of hybrid light-emitting diode (LED) and low-intensity infrared diode laser devices for activating dental bleaching and to verify the occurrence of a color regression with time. Material and methods. A total of 180 specimens obtained from human premolars were immersed in a coffee solution for 15 days for darkening and then divided into eight experimental groups (n = 20 in each) as follows: G1, bleaching without light; G2, bleaching with halogen light; G3, bleaching with a blue LED (1000 mW/470 nm) and a laser device (120 mW/795 nm) simultaneously; G4, bleaching with an LED emitting blue light (1000 mW/470 nm); G5, bleaching with a blue LED (800 mW/470 nm) and a laser device (500 mW/830 nm) simultaneously; G6, bleaching with a blue LED device (800 mW); G7, bleaching with a green LED (600 mW/530 nm) and a laser device (120 mW/795 nm) simultaneously; and G8, bleaching with a green LED (600 mW). Three measurements were performed (at baseline and 14 days and 12 months after bleaching) using a Vita Easyshade spectrophotometer. The data were submitted to two-way ANOVA and a Tukey test. Results. All groups showed significantly higher Delta E values than Group G1, with the exception of Group G8. Variations in the Delta E values at 14 days were significant when compared with those obtained at baseline and after 12 months. Conclusions. Light activation of the bleaching gel provided faster and more intense bleaching than use of the bleaching gel without light activation. Combinations of low-intensity diode lasers are ineffective as a bleaching gel activator. Color regression was observed after 12 months of storage.

Forage mass production and grazing loss of sorghum hybrid in response to the density of the sowing and the spacing between planting lines

The objective of this experiment was to evaluate dry matter yield and loss of grazing due to animal trampling in response to sowing density and spacing between lines in the planting. Sorghum hybrid 1P400 was submitted to six treatments, composed of three sowing density combinations (12; 16 and 20 kg/ha of seeds) and two spacing between lines (0.40 and 0.80 m). Sorghum hybrid 1P400 was sowed in two seasons, at the end of spring (December 3rd, 2005) and the other at the end of summer (March 20th, 2006). Cultivation strategies influenced plant population in the two experimental seasons. Diameter of the stem in season 1 decreased with density increase, whereas in the second season, interaction between sowing density and spacing was significant. In the first season, 0.40-m spacing promoted greater losses due to grazing stepping, that is, 891 kg/ha of DM, whereas in the second season there was no statistical difference. There was no significant difference in forage dry matter yield in sowing densities among the two studied seasons. Dry mater production of sorghum hybrids 1P400 did not increase with the increase of the sowing density in the two sowing seasons, therefore it is recommended 12 kg/ha of seeds for the sowing. Sorghum IP400 cultivated in 0.80-m spacing resulted in lower forage loss caused by grazing bovine trampling. © 2011 Sociedade Brasileira de Zootecnia.

Behavioural isolation may facilitate homoploid hybrid speciation in cichlid fish

Hybrid speciation is constrained by the homogenizing effects of gene flow from the parental species. In the absence of post-mating isolation due to structural changes in the genome, or temporal or spatial premating isolation, another form of reproductive isolation would be needed for homoploid hybrid speciation to occur. Here, we investigate the potential of behavioural mate choice to generate assortative mating among hybrids and parental species. We made three-first-generation hybrid crosses between different species of African cichlid fish. In three-way mate-choice experiments, we allowed hybrid and nonhybrid females to mate with either hybrid or nonhybrid males. We found that hybrids generally mated nonrandomly and that hybridization can lead to the expression of new combinations of traits and preferences that behaviourally isolate hybrids from both parental species. Specifically, we find that the phenotypic distinctiveness of hybrids predicts the symmetry and extent of their reproductive isolation. Our data suggest that behavioural mate choice among hybrids may facilitate the establishment of isolated hybrid populations, even in proximity to one or both parental species.

Surface-patterned micromechanical elements by polymer injection molding with hybrid molds

Hybrid molds enable the fabrication of polymeric parts with features of different length scales by injection molding. The resulting polymer microelements combine optical or biological functionalities with designed mechanical properties. Two applications are chosen for illustration of this concept: As a first example, microelements for optical communication via fiber-to-fiber coupling are manufactured by combining two molds to a small mold insert. Both molds are fabricated using lithography and electroplating. As a second example, microcantilevers (μCs) for chemical sensing are surface patterned using a modular mold composed of a laser-machined cavity defining the geometry of the μCs, and an opposite flat tool side which is covered by a patterned polymer foil. Injection molding results in an array of 35 μm-thick μCs with microscale surface topographies. In both cases, when the mold is assembled and closed, reliefs are transferred onto one surface of the molded element whose outlines are defined by the micromold cavity. The main advantage of these hybrid methods lies in the simple integration of optical surface structures and gratings onto the surface of microcomponents with different sizes and orientations. This allows for independent development of functional properties and combinations thereof.

MIRACLE’s Hybrid Approach to Bilingual and Monolingual Information Retrieval

The main goal of the bilingual and monolingual participation of the MIRACLE team in CLEF 2004 was to test the effect of combination approaches on information retrieval. The starting point was a set of basic components: stemming, transformation, filtering, generation of n-grams, weighting and relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. A second order combination was also tested, mainly by averaging or selective combination of the documents retrieved by different approaches for a particular query.

A comprehensive two-hybrid analysis to explore the yeast protein interactome

Protein–protein interactions play crucial roles in the execution of various biological functions. Accordingly, their comprehensive description would contribute considerably to the functional interpretation of fully sequenced genomes, which are flooded with novel genes of unpredictable functions. We previously developed a system to examine two-hybrid interactions in all possible combinations between the ≈6,000 proteins of the budding yeast Saccharomyces cerevisiae. Here we have completed the comprehensive analysis using this system to identify 4,549 two-hybrid interactions among 3,278 proteins. Unexpectedly, these data do not largely overlap with those obtained by the other project [Uetz, P., et al. (2000) Nature (London) 403, 623–627] and hence have substantially expanded our knowledge on the protein interaction space or interactome of the yeast. Cumulative connection of these binary interactions generates a single huge network linking the vast majority of the proteins. Bioinformatics-aided selection of biologically relevant interactions highlights various intriguing subnetworks. They include, for instance, the one that had successfully foreseen the involvement of a novel protein in spindle pole body function as well as the one that may uncover a hitherto unidentified multiprotein complex potentially participating in the process of vesicular transport. Our data would thus significantly expand and improve the protein interaction map for the exploration of genome functions that eventually leads to thorough understanding of the cell as a molecular system.

Hybrid multi-objective optimization and hybridized self-organizing response surface method

Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.

Rheology of bituminous mastics and mortars containing crumb rubber from tyres: a novel dry-hybrid technology

This report studied the effect of crumb rubber in the asphalt mixture. The mixtures were also having limestone filler as a modifier. Mastic and mortar (mastic-fine aggregate system) mixture having different quantities of crumb rubber and limestone filler modifiers have been tested in order to find the best rutting resistance combination with an acceptable stiffness. The rheological tests on bituminous mastics and mortars have done in the laboratories in Nottingham Transport Engineering Centre (NTEC) and University of Bologna (DICAM). In the second chapter, an extensive literature review about the binders, additives, asphalt mixtures, various modelling and testing methods have been reviewed. In the third chapter, the physical and rheological properties of the binders have been investigated using both traditional devices and DSRs. The forth chapter is dedicated to finding the behaviour of the modified mastics (Binder-modifier system) with different combinations. Five different combinations of crumb rubber and limestone filler mastic tested with various methods using Dynamic Shear Rheometers. In the fifth chapter, in order to find the effect of the modifiers in the rheological properties of the complete asphalt mixture, the fine aggregates added to the same mastic combinations. In this phase, the behaviour of the system so-called mortar; binder, rubber, filler and fine aggregates) has been studied using the DSR device and the traditional tests. The results show that using fine crumb rubber reduces the thermo sensibility of the mastic (Binder Bitumen System) and improves its elasticity. Limestone filler in the other hand increases the mixture stiffness at high Frequencies. Another important outcome of this research was that the rheological properties of the mortars were following the same trend of the mastics, therefore study the rheological properties of the mastic gives an upright estimation of the mortar.

Identification of superior reference genes for data normalisation of expression studies via quantitative PCR in hybrid roses (Rosa hybrida)

Background: Gene expression studies are a prerequisite for understanding the biological function of genes. Because of its high sensitivity and easy use, quantitative PCR (qPCR) has become the gold standard for gene expression quantification. To normalise qPCR measurements between samples, the most prominent technique is the use of stably expressed endogenous control genes, the so called reference genes. However, recent studies show there is no universal reference gene for all biological questions. Roses are important ornamental plants for which there has been no evaluation of useful reference genes for gene expression studies. Results: We used three different algorithms (BestKeeper, geNorm and NormFinder) to validate the expression stability of nine candidate reference genes in different rose tissues from three different genotypes of Rosa hybrida and in leaves treated with various stress factors. The candidate genes comprised the classical "housekeeping genes" (Actin, EF-1α, GAPDH, Tubulin and Ubiquitin), and genes showing stable expression in studies in Arabidopsis (PP2A, SAND, TIP and UBC). The programs identified no single gene that showed stable expression under all of the conditions tested, and the individual rankings of the genes differed between the algorithms. Nevertheless the new candidate genes, specifically, PP2A and UBC, were ranked higher as compared to the other traditional reference genes. In general, Tubulin showed the most variable expression and should be avoided as a reference gene. Conclusions: Reference genes evaluated as suitable in experiments with Arabidopsis thaliana were stably expressed in roses under various experimental conditions. In most cases, these genes outperformed conventional reference genes, such as EF1-α and Tubulin. We identified PP2A, SAND and UBC as suitable reference genes, which in different combinations may be used for normalisation in expression analyses via qPCR for different rose tissues and stress treatments. However, the vast genetic variation found within the genus Rosa, including differences in ploidy levels, might also influence expression stability of reference genes, so that future research should also consider different genotypes and ploidy levels.

Determination of preventive maintenance lead time using hybrid analysis

The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.