The Effect of wake Turbulence Intensity on Transition in a Compressor Cascade

Direct numerical simulations of separating flow along a section at midspan of a low-pressure V103 compressor cascade with periodically incoming wakes were performed. By varying the strength of the wake, its influence on both boundary layer separation and bypass transition were examined. Due to the presence of small-scale three-dimensional fluctuations in the wakes, the flow along the pressure surface undergoes bypass transition. Only in the weak-wake case, the boundary layer reaches a nearly-separated state between impinging wakes. In all simulations, the flow along the suction surface was found to separate. In the simulation with the strong wakes, separation is intermittently suppressed as the periodically passing wakes managed to trigger turbulent spots upstream of the location of separation. As these turbulent spots convect downstream, they locally suppress separation. © 2014 Springer Science+Business Media Dordrecht

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Prenatal screening of sialic acid storage disease and confirmation in cultured fibroblasts by LC-MS/MS

Sialic acid storage disease (SASD) is an inborn error resulting from defects in the lysosomal membrane protein sialin. The SASD phenotypical spectrum ranges from a severe presentation, infantile sialic acid storage disease (ISSD) which may present as hydrops fetalis, to a relatively mild form, Salla disease. Screening for SASD is performed by determination of free sialic acid (FSA) in urine or amniotic fluid supernatant (AFS). Subsequent diagnosis of SASD is performed by quantification of FSA in cultured fibroblasts and by mutation analysis of the sialin gene, SLC17A5. We describe simple quantitative procedures to determine FSA as well as conjugated sialic acid in AFS, and FSA in cultured fibroblasts, using isotope dilution (13C3-sialic acid) and multiple reaction monitoring LC-ESI-MS/MS. The whole procedure can be performed in 2–4 h. Reference values in AFS were 0–8.2 μmol/L for 15–25 weeks of gestation and 3.2-12.0 μmol/L for 26–38 weeks of gestation. In AFS samples from five fetuses affected with ISSD FSA was 23.9-58.9 μmol/L demonstrating that this method is able to discriminate ISSD pregnancies from normal ones. The method was also validated for determination of FSA in fibroblast homogenates. FSA in SASD fibroblasts (ISSD; 20–154 nmol/mg protein, intermediate SASD; 12.9-15.1 nmol/mg, Salla disease; 5.9-7.4 nmol/mg) was clearly elevated compared to normal controls (0.3-2.2 nmol/mg). In conclusion, we report simple quantitative procedures to determine FSA in AFS and cultured fibroblasts improving both prenatal diagnostic efficacy for ISSD as well as confirmatory testing in cultured fibroblasts following initial screening in urine or AFS

Background risk of breast cancer and the association between physical activity and mammographic density

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Ecological implications of a flower size/number trade-off in tropical forest trees

Peer reviewedPublisher PD

Surface-enhanced Raman spectroscopy of the endothelial cell membrane

We applied surface-enhanced Raman spectroscopy (SERS) to cationic gold-labeled endothelial cells to derive SERS-enhanced spectra of the bimolecular makeup of the plasma membrane. A two-step protocol with cationic charged gold nanoparticles followed by silver-intensification to generate silver nanoparticles on the cell surface was employed. This protocol of post-labelling silver-intensification facilitates the collection of SERS-enhanced spectra from the cell membrane without contribution from conjugated antibodies or other molecules. This approach generated a 100-fold SERS-enhancement of the spectral signal. The SERS spectra exhibited many vibrational peaks that can be assigned to components of the cell membrane. We were able to carry out spectral mapping using some of the enhanced wavenumbers. Significantly, the spectral maps suggest the distribution of some membrane components are was not evenly distributed over the cells plasma membrane. These results provide some possible evidence for the existence of lipid rafts in the plasma membrane and show that SERS has great potential for the study and characterization of cell surfaces

'Sink or swim': an evaluation of the clinical characteristics of individuals with high bone mass.

SUMMARY: High bone mineral density on routine dual energy X-ray absorptiometry (DXA) may indicate an underlying skeletal dysplasia. Two hundred fifty-eight individuals with unexplained high bone mass (HBM), 236 relatives (41% with HBM) and 58 spouses were studied. Cases could not float, had mandible enlargement, extra bone, broad frames, larger shoe sizes and increased body mass index (BMI). HBM cases may harbour an underlying genetic disorder. INTRODUCTION: High bone mineral density is a sporadic incidental finding on routine DXA scanning of apparently asymptomatic individuals. Such individuals may have an underlying skeletal dysplasia, as seen in LRP5 mutations. We aimed to characterize unexplained HBM and determine the potential for an underlying skeletal dysplasia. METHODS: Two hundred fifty-eight individuals with unexplained HBM (defined as L1 Z-score ≥ +3.2 plus total hip Z-score ≥ +1.2, or total hip Z-score ≥ +3.2) were recruited from 15 UK centres, by screening 335,115 DXA scans. Unexplained HBM affected 0.181% of DXA scans. Next 236 relatives were recruited of whom 94 (41%) had HBM (defined as L1 Z-score + total hip Z-score ≥ +3.2). Fifty-eight spouses were also recruited together with the unaffected relatives as controls. Phenotypes of cases and controls, obtained from clinical assessment, were compared using random-effects linear and logistic regression models, clustered by family, adjusted for confounders, including age and sex. RESULTS: Individuals with unexplained HBM had an excess of sinking when swimming (7.11 [3.65, 13.84], p < 0.001; adjusted odds ratio with 95% confidence interval shown), mandible enlargement (4.16 [2.34, 7.39], p < 0.001), extra bone at tendon/ligament insertions (2.07 [1.13, 3.78], p = 0.018) and broad frame (3.55 [2.12, 5.95], p < 0.001). HBM cases also had a larger shoe size (mean difference 0.4 [0.1, 0.7] UK sizes, p = 0.009) and increased BMI (mean difference 2.2 [1.3, 3.1] kg/m(2), p < 0.001). CONCLUSION: Individuals with unexplained HBM have an excess of clinical characteristics associated with skeletal dysplasia and their relatives are commonly affected, suggesting many may harbour an underlying genetic disorder affecting bone mass

Physics of Neutron Star Crusts

The physics of neutron star crusts is vast, involving many different research fields, from nuclear and condensed matter physics to general relativity. This review summarizes the progress, which has been achieved over the last few years, in modeling neutron star crusts, both at the microscopic and macroscopic levels. The confrontation of these theoretical models with observations is also briefly discussed.Comment: 182 pages, published version available at <http://www.livingreviews.org/lrr-2008-10