Association between single-nucleotide polymorphisms in growth factor genes and quality of life in men with prostate cancer and the general population

Purpose Improved survival for men with prostate cancer has led to increased attention to factors influencing quality of life (QOL). As protein levels of vascular endothelial growth factor (VEGF) and insulin-like growth factor 1 (IGF-1) have been reported to be associated with QOL in people with cancer, we sought to identify whether single-nucleotide polymorphisms (SNPs) of these genes were associated with QOL in men with prostate cancer. Methods Multiple linear regression of two data sets (including approximately 750 men newly diagnosed with prostate cancer and 550 men from the general population) was used to investigate SNPs of VEGF and IGF-1 (10 SNPs in total) for associations with QOL (measured by the SF-36v2 health survey). Results Men with prostate cancer who carried the minor ‘T’ allele for IGF-1 SNP rs35767 had higher mean Role-Physical scale scores (≥0.3 SD) compared to non-carriers (p < 0.05). While this association was not identified in men from the general population, one IGF-1 SNP rs7965399 was associated with higher mean Bodily Pain scale scores in men from the general population that was not found in men with prostate cancer. Men from the general population who carried the rare ‘C’ allele had higher mean Bodily Pain scale scores (≥0.3 SD) than non-carriers (p < 0.05). Conclusions Through identifying SNPs that are associated with QOL in men with prostate cancer and men from the general population, this study adds to the mapping of complex interrelationships that influence QOL and suggests a role for IGF-I in physical QOL outcomes. Future research may identify biomarkers associated with increased risk of poor QOL that could assist in the provision of pre-emptive support for those identified at risk.

Impact of particle formation on atmospheric ions and particle number concentrations in an urban environment

A measurement campaign was conducted from 3 to 19 December 2012 at an urban site of Brisbane, Australia. Size distribution of ions and particle number concentrations were measured to investigate the influence of particle formation and biomass burning on atmospheric ion and particle concentrations. Overall ion and particle number concentrations during the measurement period were found to be (-1.2 x 103 cm-3 | +1.6 x 103 cm-3) and 4.4 x 103, respectively. The results of correlation analysis between concentrations of ions and nitrogen oxides indicated that positive and negative ions originated from similar sources, and that vehicle exhaust emissions had a more significant influence on intermediate/large ions, while cluster ions rapidly attached to larger particles once emitted into the atmosphere. Diurnal variations in ion concentration suggested the enrichment of intermediate and large ions on new particle formation event days, indicating that they were involved in the particle formation processes. Elevated total ions, particularly larger ions, and particle number concentrations were found during biomass burning episodes. This could be due to the attachment of cluster ions onto accumulation mode particles or production of charged particles from biomass burning, which were in turn transported to the measurement site. The results of this work enhance scientific understanding of the sources of atmospheric ions in an urban environment, as well as their interactions with particles during particle formation processes.

Particle doses in the pulmonary lobes of electronic and conventional cigarette users

The main aim of the present study was to estimate size segregated doses from e-cigarette aerosols as a function of the airway generation number in lung lobes.. After a 2-second puff, 7.7×1010 particles (DTot) with a surface area of 3.6×103 mm2 (STot), and 3.3×1010 particles with a surface area of 4.2×103 mm2 were deposited in the respiratory system for the electronic and conventional cigarettes, respectively. Alveolar and tracheobronchial deposited doses were compared to the ones received by non-smoking individuals in Western countries, showing a similar order of magnitude. Total regional doses (DR), in head and lobar tracheobronchial and alveolar regions, ranged from 2.7×109 to 1.3×1010 particles and 1.1×109 to 5.3×1010 particles, for the electronic and conventional cigarettes, respectively. DR in the right-upper lung lobe was about twice that found in left-upper lobe and 20% greater in right-lower lobe than the left-lower lobe.

Inhaled particle surface area dose: Stationary vs personal monitoring

The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

Evaluation of a meteorological and three-dimensional chemical transport model for gaseous and particle concentrations in an urban airshed

The Air Pollution Model and Chemical Transport Model (TAPM-CTM) framework has been tested and applied originally in Sydney to quantify particle and gaseous concentration (Cope et al, 2014). However, the model performance had not been tested in the south-eastern Queensland region (SEQR), Australia.

Influence of kaolinite particle size on cross-link density, microstructure and mechanical properties of latex blending styrene butadiene rubber composites

Cross-link density, microstructure and mechanical properties of styrene butadiene rubber (SBR) composites filled with different particle sized kaolinites are investigated. With the increase of kaolinite particle size, the cross-link density of the filled SBR composites, the dispersibility and orientation degree of kaolinite particles gradually decrease. Some big cracks in filled rubber composites are distributed along the fringe of kaolinite aggregates, and the absorbance of all the absorption bands of kaolinites gradually increase with the increase of kaolinite particle size. All mechanical property indexes of kaolinite filled SBR composites decrease due to the decrease of cross-linking and reduction of interface interaction between filler and rubber matrix.

The structural basis of DNA binding by the single-stranded DNA-binding protein from Sulfolobus solfataricus

Canonical single-stranded DNA-binding proteins (SSBs) from the oligosaccharide/oligonucleotide-binding (OB) domain family are present in all known organisms and are critical for DNA replication, recombination and repair. The SSB from the hyperthermophilic crenarchaeote Sulfolobus solfataricus (SsoSSB) has a ‘simple’ domain organization consisting of a single DNA-binding OB fold coupled to a flexible C-terminal tail, in contrast with other SSBs in this family that incorporate up to four OB domains. Despite the large differences in the domain organization within the SSB family, the structure of the OB domain is remarkably similar all cellular life forms. However, there are significant differences in the molecular mechanism of ssDNA binding. We have determined the structure of the SsoSSB OB domain bound to ssDNA by NMR spectroscopy. We reveal that ssDNA recognition is modulated by base-stacking of three key aromatic residues, in contrast with the OB domains of human RPA and the recently discovered human homologue of SsoSSB, hSSB1. We also demonstrate that SsoSSB binds ssDNA with a footprint of five bases and with a defined binding polarity. These data elucidate the structural basis of DNA binding and shed light on the molecular mechanism by which these ‘simple’ SSBs interact with ssDNA.

Different approaches of applying single-objective binary genetic algorithm on the wind farm design

This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.

Prediction of shrinkage and porosity during drying: Considering both material properties and process conditions

Drying of food materials offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Shrinkage and variations in porosity are the common micro and microstructural changes that take place during the drying of mostly the food materials. Although extensive research has been carried out on the prediction of shrinkage and porosity over the time of drying, no single model exists which consider both material properties and process condition in the same model. In this study, an attempt has been made to develop and validate shrinkage and porosity models of food materials during drying considering both process parameters and sample properties. The stored energy within the sample, elastic potential energy, glass transition temperature and physical properties of the sample such as initial porosity, particle density, bulk density and moisture content have been taken into consideration. Physical properties and validation have been made by using a universal testing machine ( Instron 2kN), a profilometer (Nanovea) and a pycnometer. Apart from these, COMSOL Multiphysics 4.4 has been used to solve heat and mass transfer physics. Results obtained from models of shrinkage and porosity is quite consistent with the experimental data. Successful implementation of these models would ensure the use of optimum energy in the course of drying and better quality retention of dried foods.

Versatile single-layer sodium phosphidostannate(II): Strain-tunable electronic structure, excellent mechanical flexibility, and an ideal gap for photovoltaics

Density functional theory (DFT) calculations were performed to study the structural, mechanical, electrical, optical properties, and strain effects in single-layer sodium phosphidostannate(II) (NaSnP). We find the exfoliation of single-layer NaSnP from bulk form is highly feasible because the cleavage energy is comparable to graphite and MoS2. In addition, the breaking strain of the NaSnP monolayer is comparable to other widely studied 2D materials, indicating excellent mechanical flexibility of 2D NaSnP. Using the hybrid functional method, the calculated band gap of single-layer NaSnP is close to the ideal band gap of solar cell materials (1.5 eV), demonstrating great potential in future photovoltaic application. Furthermore, strain effect study shows that a moderate compression (2%) can trigger indirect-to-direct gap transition, which would enhance the ability of light absorption for the NaSnP monolayer. With sufficient compression (8%), the single-layer NaSnP can be tuned from semiconductor to metal, suggesting great applications in nanoelectronic devices based on strain engineering techniques.

A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

Parameterization and reliability of single-leg balance test assessed with inertial sensors in stroke survivors: a cross-sectional study

Background and purpose There are no published studies on the parameterisation and reliability of the single-leg stance (SLS) test with inertial sensors in stroke patients. Purpose: to analyse the reliability (intra-observer/inter-observer) and sensitivity of inertial sensors used for the SLS test in stroke patients. Secondary objective: to compare the records of the two inertial sensors (trunk and lumbar) to detect any significant differences in the kinematic data obtained in the SLS test. Methods Design: cross-sectional study. While performing the SLS test, two inertial sensors were placed at lumbar (L5-S1) and trunk regions (T7–T8). Setting: Laboratory of Biomechanics (Health Science Faculty - University of Málaga). Participants: Four chronic stroke survivors (over 65 yrs old). Measurement: displacement and velocity, Rotation (X-axis), Flexion/Extension (Y-axis), Inclination (Z-axis); Resultant displacement and velocity (V): RV=(Vx2+Vy2+Vz2)−−−−−−−−−−−−−−−−−√ Along with SLS kinematic variables, descriptive analyses, differences between sensors locations and intra-observer and inter-observer reliability were also calculated. Results Differences between the sensors were significant only for left inclination velocity (p = 0.036) and extension displacement in the non-affected leg with eyes open (p = 0.038). Intra-observer reliability of the trunk sensor ranged from 0.889-0.921 for the displacement and 0.849-0.892 for velocity. Intra-observer reliability of the lumbar sensor was between 0.896-0.949 for the displacement and 0.873-0.894 for velocity. Inter-observer reliability of the trunk sensor was between 0.878-0.917 for the displacement and 0.847-0.884 for velocity. Inter-observer reliability of the lumbar sensor ranged from 0.870-0.940 for the displacement and 0.863-0.884 for velocity. Conclusion There were no significant differences between the kinematic records made by an inertial sensor during the development of the SLS testing between two inertial sensors placed in the lumbar and thoracic regions. In addition, inertial sensors. Have the potential to be reliable, valid and sensitive instruments for kinematic measurements during SLS testing but further research is needed.

Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

Influence of pipe length and flow rate on nano-particle deposition in laminar circular pipe flows

The Lagrangian particle tracking provides an effective method for simulating the deposition of nano- particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. The aim of this paper is to study the deposition of nano-particles in cylindrical tubes under laminar condition using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different pipe lengths and flow rates are examined. The results show good agreement between the calculated deposition efficiency and different analytic correlations in the literature. Furthermore, for the nano-particles with higher diameters and when the effect of inertia has a higher importance, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.

Balancing exploration and exploitation in particle swarm optimization on search tasking

In this study we present a combinatorial optimization method based on particle swarm optimization and local search algorithm on the multi-robot search system. Under this method, in order to create a balance between exploration and exploitation and guarantee the global convergence, at each iteration step if the distance between target and the robot become less than specific measure then a local search algorithm is performed. The local search encourages the particle to explore the local region beyond to reach the target in lesser search time. Experimental results obtained in a simulated environment show that biological and sociological inspiration could be useful to meet the challenges of robotic applications that can be described as optimization problems.