2-Arc-transitive metacyclic covers of complete graphs

Regular covers of complete graphs whose fibre-preserving automorphism groups act 2-arc-transitively are investigated. Such covers have been classified when the covering transformation groups K are cyclic groups Z(d) for an integer d >= 2, metacyclic abelian groups Z(p)(2), or nonmetacyclic abelian groups Z(p)(3) for a prime p (see S.F. Du et al. (1998) [5] for the first two metacyclic group cases and see S.F. Du et al. (2005) [3] for the third nonmetacyclic group case). In this paper, a complete classification is achieved of all such covers when K is any metacyclic group. (C) 2014 Elsevier Inc. All rights reserved.116Ysciescopu

Effects of grassland management on soil organic carbon density in agro-pastoral zone of Northern China

The objective of this study was to estimate the soil organic carbon (SOC) in grasslands with different management measures including: (1) uncontrolled or free grazing grassland (FG); (2) grassland enclosured, excluding grazing and mowing (EG); (3) grassland enclosured and mowed early in October every year (MG) and (4) grassland enclosured under controlled grazing (CG) by examining soil bulk density and SOC content from 0 to 50 cm soil depth in agro-pastoral ecotone, Northern China. The results showed that, by implementing CG, EG and MG practices, the grasslands in agro-pastoral ecotone of Northern China achieved higher SOC storage on decade scales when compared to FG field. CG field had the highest SOC density in 0 to 50 cm soil layer, while the least SOC density was displayed by FG. However, SOC density was similar between MG and EG plots. CG increased SOC concentration by 56.08% and SOC density by 4.96 kg/m2 when compared to FG practice. In addition, it was likely to give positive financial returns in providing livestock products when compared to EG practice. CG therefore was the most feasible and benign short-term grassland management option which could deposit even higher carbon dioxide in agro-pastoral ecotone in Northern China.Key words: Agro-pastoral zone, soil organic carbon density, grassland management, Northern China

Inactivation of hypoxia inducible factor (HIF) 1 alpha induces obesity-associated metabolic disorders through brown adipose tissue dysfunction

published_or_final_versionThe 14th Medical Research Conference, Hong Kong, 10 January 2009. In Hong Kong Medical Journal, 2009, v. 15, suppl. 1, p. 40, article no. 6

Serum levels of IL-33 and soluble ST2 and their association with disease activity in systemic lupus erythematosus

BACKGROUND: IL-33 has recently been found to be the specific ligand of ST2, an IL-1 receptor family member that is selectively expressed on Th2 cells and mediates Th2 response. This study aimed to measure serum levels of soluble form of ST2 (sST2) and IL-33 in patients with systemic lupus erythematosus (SLE) and to examine its association with disease activity. METHODS: Seventy SLE patients were evaluated for disease activity determined by SLE disease activity index (SLEDAI), serological features (anti-dsDNA antibody, C3 and C4) and 57 patients were evaluated longitudinally on a second occasion. IL-33 and sST2 were measured by sandwich ELISA in the 127 SLE serum samples and compared to 28 age- and sex-matched healthy controls. RESULTS: Serum sST2 level was significantly higher in SLE patients with active disease (0.51+0.18 ng/mL) compared to those with inactive disease (0.42+0.08 ng/mL) [P=0.006] and to normal controls (0.36+0.13 ng/mL) [P<0.001]. sST2 level correlated significantly and positively with SLEDAI, level of anti-dsDNA antibody and prednisolone dosage and negatively with C3 and remained significantly predictive of active disease after adjustment for prednisolone use in logistic regression analysis (odds ratio=4.6, P=0.01). sST2 level was sensitive to change in disease activity in longitudinal evaluation and not influenced by age, gender, and renal function. Elevated serum IL-33 was comparable in frequency (4.3% vs 7.1%, P=0.62) and levels (P=0.53) between SLE patients and controls. CONCLUSION: Elevated serum sST2 level in SLE patients was found to correlate with disease activity and was sensitive to change, suggesting a potential role as surrogate marker of disease activity.published_or_final_versionThe 15th Medical Research Conference (15th MRC), Department of Medicine, University of Hong Kong, Hong Kong, 16 January 2010. In Hong Kong Medical Journal, 2010, v. 16 n. 1, suppl. 1, p. 46, abstract no. 7

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

Tankyrase Inhibitors Target YAP by Stabilizing Angiomotin Family Proteins

SummaryAs the key effector in the Hippo pathway, YAP was identified as an oncoprotein whose expression is elevated in various human cancers. However, the development of potentially therapeutic compounds targeting YAP has been slow and limited. Here, we find that tankyrase inhibitors suppress YAP activity. This effect is mediated by anigomotin (AMOT) family proteins. Tankyrases associate with AMOT family proteins and promote their degradation through E3 ligase RNF146. By antagonizing tankyrase activity, tankyrase inhibitors stabilize AMOT family proteins, thereby suppressing YAP oncogenic functions. Together, our studies not only demonstrate the tankyrase-RNF146-AMOT axis as an upstream pathway regulating YAP but also reveal a therapeutic opportunity in targeting YAP for cancer treatment

Evaluation of computational methodologies for accurate prediction of wall shear stress and turbulence parameters in a patient-specific aorta

Background: Recent studies suggest that blood flow in main arteries is intrinsically disturbed, even under healthy conditions. Despite this, many computational fluid dynamics (CFD) analyses of aortic haemodynamics make the assumption of laminar flow, and best practices surrounding appropriate modelling choices are lacking. This study aims to address this gap by evaluating different modelling and post-processing approaches in simulations of a patient-specific aorta. Methods: Magnetic resonance imaging (MRI) and 4D flow MRI from a patient with aortic valve stenosis were used to reconstruct the aortic geometry and derive patient-specific inlet and outlet boundary conditions. Three different computational approaches were considered based on assumed laminar or assumed disturbed flow states including low-resolution laminar (LR-laminar), high-resolution laminar (HR-Laminar) and large-eddy simulation (LES). Each simulation was ran for 30 cardiac cycles and post-processing was conducted on either the final cardiac cycle, or using a phase-averaged approach which utilised all 30 simulated cycles. Model capabilities were evaluated in terms of mean and turbulence-based parameters. Results: All simulation types, regardless of post-processing approach could correctly predict velocity values and flow patterns throughout the aorta. Lower resolution simulations could not accurately predict gradient-derived parameters including wall shear stress and viscous energy loss (largest differences up to 44.6% and 130.3%, respectively), although phase-averaging these parameters improved predictions. The HR-Laminar simulation produced more comparable results to LES with largest differences in wall shear stress and viscous energy loss parameters up to 5.1% and 11.6%, respectively. Laminar-based parameters were better estimated than turbulence-based parameters. Conclusions: Our findings suggest that well-resolved laminar simulations can accurately predict many laminar-based parameters in disturbed flows, but there is no clear benefit to running a HR-Laminar simulation over an LES simulation based on their comparable computational cost. Additionally, post-processing ‘typical’ laminar simulation results with a phase-averaged approach is a simple and cost-effective way to improve accuracy of lower-resolution simulation results

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1