Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes.

Aims/hypothesisWhile genome-wide association studies (GWASs) have been successful in identifying novel variants associated with various diseases, it has been much more difficult to determine the biological mechanisms underlying these associations. Expression quantitative trait loci (eQTL) provide another dimension to these data by associating single nucleotide polymorphisms (SNPs) with gene expression. We hypothesised that integrating SNPs known to be associated with type 2 diabetes with eQTLs and coexpression networks would enable the discovery of novel candidate genes for type 2 diabetes.MethodsWe selected 32 SNPs associated with type 2 diabetes in two or more independent GWASs. We used previously described eQTLs mapped from genotype and gene expression data collected from 1,008 morbidly obese patients to find genes with expression associated with these SNPs. We linked these genes to coexpression modules, and ranked the other genes in these modules using an inverse sum score.ResultsWe found 62 genes with expression associated with type 2 diabetes SNPs. We validated our method by linking highly ranked genes in the coexpression modules back to SNPs through a combined eQTL dataset. We showed that the eQTLs highlighted by this method are significantly enriched for association with type 2 diabetes in data from the Wellcome Trust Case Control Consortium (WTCCC, p = 0.026) and the Gene Environment Association Studies (GENEVA, p = 0.042), validating our approach. Many of the highly ranked genes are also involved in the regulation or metabolism of insulin, glucose or lipids.Conclusions/interpretationWe have devised a novel method, involving the integration of datasets of different modalities, to discover novel candidate genes for type 2 diabetes

Optimizing target nodes selection for the control energy of directed complex networks

The energy needed in controlling a complex network is a problem of practical importance. Recent works have focused on the reduction of control energy either via strategic placement of driver nodes, or by decreasing the cardinality of nodes to be controlled. However, optimizing control energy with respect to target nodes selection has yet been considered. In this work, we propose an iterative method based on Stiefel manifold optimization of selectable target node matrix to reduce control energy. We derive the matrix derivative gradient needed for the search algorithm in a general way, and search for target nodes which result in reduced control energy, assuming that driver nodes placement is fixed. Our findings reveal that the control energy is optimal when the path distances from driver nodes to target nodes are minimized. We corroborate our algorithm with extensive simulations on elementary network topologies, random and scale-free networks, as well as various real networks. The simulation results show that the control energy found using our algorithm outperforms heuristic selection strategies for choosing target nodes by a few orders of magnitude. Our work may be applicable to opinion networks, where one is interested in identifying the optimal group of individuals that the driver nodes can influence

A note on Makeev's conjectures

A counterexample is given for the Knaster-like conjecture of Makeev for functions on $S^2$. Some particular cases of another conjecture of Makeev, on inscribing a quadrangle into a smooth simple closed curve, are solved positively

Relationship between Brand Perceptions and Satisfaction: Empirical Study on Skin Products in Malaysia

In the highly competitive marketplace, marketers for the skin care product are facing challenges with identifying the consumer’s brand perception and brand satisfaction. Brand satisfaction is perceived as an important issue on skin care industry. Obviously, customers are the important stakeholders in organizations and their satisfaction is a priority to the company. This study aims to investigate the relationship between brand perceptions and brand satisfaction on skin care products with four independent variables (quality, promotion, image and preference). This study employed the statistic software of SPSS version 19.0 to evaluate 200 sets of questionnaires which collected from students, undergraduates, working adults and other respondents. The findings in this study shows that the brand perceptions on quality, image and preference have positive and significant relationship with brand satisfaction on skin care products. However, the relationship between brand perception on promotion and brand satisfaction is being rejected. Thus, the marketers can focus on perception on quality, image and preference to increase customers’ brand satisfaction to capture and retain them

Establishing Effective Operation and Maintenance that Enhances the Energy Performance of Green Office Buildings in Malaysia

The increasing concern of global warming occurring at an exceptional rate has led to a massive shift in the construction industry. Subsequently, the development of green buildings is on the rise. Along with the emergence of green buildings, the evaluation of the sustainability of a project is a necessity to ensure that the building operates according to the best practices. Various studies have shown that some green buildings are underperforming compared to their initial designs. Some are even found to be performing even worse than the conventional buildings. In addition, the operation and maintenance (O&M) aspect is often neglected in the initial design stages, despite its significance on the life span, performance, and operational expenses of the building. Therefore, this research aims to study the implementation of O&M in relation to the energy performance level of green office buildings in Malaysia. To achieve the objectives of this research, a qualitative method is used whereby the data are obtained through literature review and interviews. Qualitative data are analysed to explain the influence of O&M aspects on energy performance. It is found that the green office buildings with better implementation of O&M, particularly on the maintenance strategy and building occupant behaviour, are likely to achieve the smaller operational energy performance gap. Therefore, various practices are suggested to enhance the energy efficiency of green building, such as appropriate selection and implementation of maintenance strategy, adoption of building automation system, impose of incentives for energy efficient practices, and occupant involvement in O&M

Establishing Effective Operation and Maintenance that Enhances the Energy Performance of Green Office Buildings in Malaysia

The increasing concern of global warming occurring at an exceptional rate has led to a massive shift in the construction industry. Subsequently, the development of green buildings is on the rise. Along with the emergence of green buildings, the evaluation of the sustainability of a project is a necessity to ensure that the building operates according to the best practices. Various studies have shown that some green buildings are underperforming compared to their initial designs. Some are even found to be performing even worse than the conventional buildings. In addition, the operation and maintenance (O&M) aspect is often neglected in the initial design stages, despite its significance on the life span, performance, and operational expenses of the building. Therefore, this research aims to study the implementation of O&M in relation to the energy performance level of green office buildings in Malaysia. To achieve the objectives of this research, a qualitative method is used whereby the data are obtained through literature review and interviews. Qualitative data are analysed to explain the influence of O&M aspects on energy performance. It is found that the green office buildings with better implementation of O&M, particularly on the maintenance strategy and building occupant behaviour, are likely to achieve the smaller operational energy performance gap. Therefore, various practices are suggested to enhance the energy efficiency of green building, such as appropriate selection and implementation of maintenance strategy, adoption of building automation system, impose of incentives for energy efficient practices, and occupant involvement in O&M

White-matter structure in the right hemisphere predicts Mandarin Chinese learning success

AbstractSecond language learning becomes increasingly difficult with age, but some adults learn more successfully than others. We examined whether inter-subject variability in the microstructure of white matter pathways, as measured by diffusion tensor imaging (DTI), would predict native English speakers' outcomes in learning Mandarin Chinese. Twenty-one adults were scanned before participating in an intensive 4-week Mandarin course. At the end of the Mandarin course, participants completed a final exam that assessed their skills in both spoken and written Mandarin. Individual participants' white-matter tracts were reconstructed from their native DTI data and related to final-exam performance. Superior language learning was correlated with DTI measures in the right hemisphere, but not in the left hemisphere. In particular, greater initial fractional anisotropy (FA) in both the right superior longitudinal fasciculus (parietal bundle) and the right inferior longitudinal fasciculus was associated with more successful Mandarin learning. The relation between white-matter structure in the right hemisphere of native English speakers and successful initial language learning may reflect the tonal and visuo-spatial properties, respectively, of spoken and written Mandarin Chinese