408 research outputs found
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A two-step simulation methodology for modelling stagnation flame synthesised aggregate nanoparticles
A two-step simulation methodology is presented that allows a detailed particle model to be used to resolve the complex morphology of aggregate nanoparticles synthesised in a stagnation flame. In the first step, a detailed chemical mechanism is coupled to a one-dimensional stagnation flow model and spherical particle model solved using method of moments with interpolative closure. The resulting gas-phase profile is post-processed with a detailed stochastic population balance model to simulate the evolution of the population of particles, including the evolution of each individual primary particle and their connectivity with other primaries in an aggregate. A thermophoretic correction is introduced to the post-processing step through a simulation volume scaling term to account for thermophoretic transport effects arising due to the steep temperature gradient near the stagnation surface. The methodology is evaluated by applying it to a test case: the synthesis of titanium dioxide from titanium tetraisopropoxide (TTIP) precursor. The thermophoretic correction is shown to improve the fidelity of the post-process to the first fully-coupled simulation, and the methodology is demonstrated to be feasible for simulating the morphology of aggregate nanoparticles formed in a stagnation flame, permitting the simulation of quantities that are directly comparable to experimental observations
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Numerical simulation and parametric sensitivity study of titanium dioxide particles synthesised in a stagnation flame
A detailed population balance model is used to simulate titanium dioxide
nanoparticles synthesised in a stagnation flame from titanium tetraisopropoxide (TTIP) precursor. A two-step simulation methodology is employed to apply the detailed particle model as a post-process to flame profiles obtained from a fully coupled simulation with detailed gas-phase chemistry, flow dynamics and a simple particle model. The detailed particle model tracks the size and coordinates of each primary in an aggregate, and is able to resolve the particle morphology, permitting direct comparison with experimental measurements through simulated TEM-style images. New sintering parameters, informed by molecular dynamics simulations in the literature, are introduced into the model to account for the sintering behaviour of sub-10 nm particles. Simulated primary and aggregate particle size distributions were in excellent
agreement with experimental measurements. A parametric sensitivity study found particle morphology to be sensitive to the sintering parameters, demonstrating the need to apply careful consideration to the sintering behaviour of nano-sized particles in modelling studies. The final particle morphology was not found to be sensitive to other model parameters
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Modelling soot formation in a benchmark ethylene stagnation flame with a new detailed population balance model
Numerical simulation of soot formation in a laminar premixed burner-stabilised benchmark ethylene stagnation flame was performed with a new detailed population balance model employing a two-step simulation methodology. In this model, soot particles are represented as aggregates composed of overlapping primary particles, where each primary particle is composed of a number of polycyclic aromatic hydrocarbons (PAHs). Coordinates of primary particles are tracked, which enables simulation on particle morphology and provides more quantities that are directly comparable to experimental observations. Parametric sensitivity study on the computed particle size distributions (PSDs) shows that the rate of production of pyrene and the collision efficiency have the most significant effect on the computed PSDs. Sensitivity of aggregate morphology to the sintering rate is studied by analysing the simulated primary particle size distributions (PPSDs) and transmission electron microscopy (TEM) images. The capability of the new model to predict PSDs in a premixed stagnation flame is investigated. Excellent agreement between the computed and measured PSDs is obtained for large burner-stagnation plate separation (≥ 0.7 cm) and for particles with mobility diameter larger than 6 nm, demonstrating the ability of this new model to describe the coagulation process of aggregate particles
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A detailed particle model for polydisperse aggregate particles
The mathematical description of a new detailed particle model for polydisperse aggregate particles is presented. An aggregate particle is represented as a collection of overlapping spherical primary particles and the model resolves the composition, radius and position coordinates of each individual primary to form a detailed geometrical description of aggregate morphology. Particles transform under inception, coagulation, surface growth, sintering and coalescence processes. The new particle description is used to model the aerosol synthesis of titanium dioxide (TiO2) aggregates from titanium tetraisopropoxide (TTIP) precursor. TiO2 particles are formed through collision-limited inception and growth reactions of Ti(OH)4 from the gas-phase, produced from the thermal decomposition of TTIP. Coupling between the particle population balance and detailed gas-phase chemistry is achieved by operator splitting. A numerical study is performed by simulating a simple batch reactor test case to investigate the convergence behaviour of key functionals with respect to the maximum number of computational particles and splitting time step. Finally, a lab-scale hot wall reactor is simulated to demonstrate the advantages of a detailed geometrical description. Simulated
particle size distributions were in reasonable agreement with experimental data. Further evaluation of the model and a parametric sensitivity study are recommended
Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs) which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF), which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF).</p> <p>Results</p> <p>SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm.</p> <p>Conclusion</p> <p>Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be used instead of ReliefF to filter a dataset before an exhaustive MDR analysis. This change increases the ability of a study to detect gene-gene interactions. The SURF algorithm is implemented in the open source Multifactor Dimensionality Reduction (MDR) software package available from <url>http://www.epistasis.org</url>.</p
Essentials of Filoviral Load Quantification
Quantitative measurement of viral load is an important parameter in the management of filovirus disease outbreaks because viral load correlates with severity of disease, survival, and infectivity. During the ongoing Ebola virus disease outbreak in parts of Western Africa, most assays used in the detection of Ebola virus disease by more than 44 diagnostic laboratories yielded qualitative results. Regulatory hurdles involved in validating quantitative assays and the urgent need for a rapid Ebola virus disease diagnosis precluded development of validated quantitative assays during the outbreak. Because of sparse quantitative data obtained from these outbreaks, opportunities for study of correlations between patient outcome, changes in viral load during the course of an outbreak, disease course in asymptomatic individuals, and the potential for virus transmission between infected patients and contacts have been limited. We strongly urge the continued development of quantitative viral load assays to carefully evaluate these parameters in future outbreaks of filovirus disease
Stroke genetics: prospects for personalized medicine.
Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice
Presence and Persistence of Ebola or Marburg Virus in Patients and Survivors: A Rapid Systematic Review
Background: The 2013-15 Ebola outbreak was unprecedented due to sustainedtransmission within urban environments and thousands of survivors. In 2014 the World Health Organization stated that there was insufficient evidence to give definitive guidance about which body fluids are infectious and when they pose a risk to humans. We report a rapid systematic review of published evidence on the presence of filoviruses in body fluids of infected people and survivors. Methods: Scientific articles were screened for information about filovirus in human body fluids. The aim was to find primary data that suggested high likelihood of actively infectious filovirus in human body fluids (viral RNA). Eligible infections were from Marburg virus (MARV or RAVV) and Zaire, Sudan, Taï Forest and Bundibugyo species of Ebola. [1] Cause of infection had to be laboratory confirmed (in practice either tissue culture or RT-PCR tests), or evidenced by compatible clinical history with subsequent positivity for filovirus antibodies or inflammatory factors. Data were extracted and summarized narratively. Results: 6831 unique articles were found, and after screening, 33 studies were eligible. For most body fluid types there were insufficient patients to draw strong conclusions, and prevalence of positivity was highly variable. Body fluids taken >16 days after onset were usually negative. In the six studies that used both assay methods RT-PCR tests for filovirus RNA gave positive results about 4 times more often than tissue culture. Conclusions: Filovirus was reported in most types of body fluid, but not in every sample from every otherwise confirmed patient. Apart from semen, most non-blood, RT-PCR positive samples are likely to be culture negative and so possibly of low infectious risk. Nevertheless, it is not apparent how relatively infectious many body fluids are during or after illness, even when culture-positive, not least because most test results come from more severe cases. Contact with blood and blood-stained body fluids remains the major risk for disease transmission because of the known high viral loads in blood
Variation in LPA Is Associated with Lp(a) Levels in Three Populations from the Third National Health and Nutrition Examination Survey
The distribution of lipoprotein(a) [Lp(a)] levels can differ dramatically across diverse racial/ethnic populations. The extent to which genetic variation in LPA can explain these differences is not fully understood. To explore this, 19 LPA tagSNPs were genotyped in 7,159 participants from the Third National Health and Nutrition Examination Survey (NHANES III). NHANES III is a diverse population-based survey with DNA samples linked to hundreds of quantitative traits, including serum Lp(a). Tests of association between LPA variants and transformed Lp(a) levels were performed across the three different NHANES subpopulations (non-Hispanic whites, non-Hispanic blacks, and Mexican Americans). At a significance threshold of p<0.0001, 15 of the 19 SNPs tested were strongly associated with Lp(a) levels in at least one subpopulation, six in at least two subpopulations, and none in all three subpopulations. In non-Hispanic whites, three variants were associated with Lp(a) levels, including previously known rs6919246 (p = 1.18×10−30). Additionally, 12 and 6 variants had significant associations in non-Hispanic blacks and Mexican Americans, respectively. The additive effects of these associated alleles explained up to 11% of the variance observed for Lp(a) levels in the different racial/ethnic populations. The findings reported here replicate previous candidate gene and genome-wide association studies for Lp(a) levels in European-descent populations and extend these findings to other populations. While we demonstrate that LPA is an important contributor to Lp(a) levels regardless of race/ethnicity, the lack of generalization of associations across all subpopulations suggests that specific LPA variants may be contributing to the observed Lp(a) between-population variance
APC/CCdh1-Mediated Degradation of the F-Box Protein NIPA Is Regulated by Its Association with Skp1
NIPA (Nuclear Interaction Partner of Alk kinase) is an F-box like protein
that targets nuclear Cyclin B1 for degradation. Integrity and therefore activity
of the SCFNIPA E3 ligase is regulated by cell-cycle-dependent phosphorylation
of NIPA, restricting substrate ubiquitination to interphase. Here we show
that phosphorylated NIPA is degraded in late mitosis in an APC/CCdh1-dependent
manner. Binding of the unphosphorylated form of NIPA to Skp1 interferes with
binding to the APC/C-adaptor protein Cdh1 and therefore protects unphosphorylated
NIPA from degradation in interphase. Our data thus define a novel mode of
regulating APC/C-mediated ubiquitination
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