Finding Links between Obesity and Diabetes: Using Diacylglycerol Kinase to Regulate Insulin Signaling

In the U.S., two-thirds of adults are overweight or obese, with 35.7% of them - nearly 78 million people – obese. What used to be a disease that only afflicted adults is now also increasingly being diagnosed in children, contributing to ever-growing obesity rates. In particular, obesity and diabetes are closely linked, with obese people at higher risk for developing type 2 diabetes. All this only further intensifies the urgent need to address obesity and type 2 diabetes. In particular, we need to understand how the two conditions are linked and what metabolic processes are involved, in order to develop treatment and prevention strategies that will ultimately reduce the burden of type 2 diabetes on healthcare. My project looks at how the triacylglycerol synthesis and insulin signaling pathways are linked. In particular, we are studying how lipid intermediates cause insulin resistance in hepatocytes. We are interested in whether phosphatidic acid (PA) and diacylglycerol (DAG) affect Akt phosphorylation, and the mechanism by which PA and DAG might inhibit insulin signaling. Diacylglycerol kinase (DGK) is the enzyme that catalyzes conversion of DAG to PA, and was used as a tool to manipulate the cellular content of PA and DAG. The content and activity of DGK was adjusted by DGK overexpression in mouse hepatocytes, thus altering the balance of PA and DAG. The physiological consequences were then used to determine how insulin signaling is affected. Our hypothesis is that DGK regulates insulin signaling by changing intracellular PA and DAG levels. The isoform used was the DGKθ isoform. Our results showed that PA is associated with impaired insulin action in mouse hepatocytes, but DAG is not.Bachelor of Science in Public Healt

A new perspective on the competitiveness of nations

The capability of firms to survive and to have a competitive advantage in global markets depends on, amongst other things, the efficiency of public institutions, the excellence of educational, health and communications infrastructures, as well as on the political and economic stability of their home country. The measurement of competitiveness and strategy development is thus an important issue for policy-makers. Despite many attempts to provide objectivity in the development of measures of national competitiveness, there are inherently subjective judgments that involve, for example, how data sets are aggregated and importance weights are applied. Generally, either equal weighting is assumed in calculating a final index, or subjective weights are specified. The same problem also occurs in the subjective assignment of countries to different clusters. Developed as such, the value of these type indices may be questioned by users. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices. For this purpose, a methodology composed of three steps is proposed. To start, a hierarchical clustering analysis is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient for purposes of country clustering. In the proposed methodology, 178 criteria are used for this purpose. Next, relationships between the criteria and classification of the countries are determined using artificial neural networks (ANNs). ANN provides an objective method for determining the attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in our third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one

The competitiveness of nations and implications for human development

This is the post-print version of the final paper published in Socio-Economic Planning Sciences. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.Human development should be the ultimate objective of human activity, its aim being healthier, longer, and fuller lives. Thus, if the competitiveness of a nation is properly managed, enhanced human welfare should be the key expected consequence. The research described here explores the relationship between the competitiveness of a nation and its implications for human development. For this purpose, 45 countries were evaluated initially using data envelopment analysis. In this stage, global competitiveness indicators were taken as input variables with human development index indicators as output variables. Subsequently, an artificial neural network analysis was conducted to identify those factors having the greatest impact on efficiency scores

Inhibited Insulin Signaling in Mouse Hepatocytes Is Associated with Increased Phosphatidic Acid but Not Diacylglycerol

Although an elevated triacylglycerol content in non-adipose tissues is often associated with insulin resistance, the mechanistic relationship remains unclear. The data support roles for intermediates in the glycerol-3-phosphate pathway of triacylglycerol synthesis: diacylglycerol (DAG), which may cause insulin resistance in liver by activating PKCϵ, and phosphatidic acid (PA), which inhibits insulin action in hepatocytes by disrupting the assembly of mTOR and rictor. To determine whether increases in DAG and PA impair insulin signaling when produced by pathways other than that of de novo synthesis, we examined primary mouse hepatocytes after enzymatically manipulating the cellular content of DAG or PA. Overexpressing phospholipase D1 or phospholipase D2 inhibited insulin signaling and was accompanied by an elevated cellular content of total PA, without a change in total DAG. Overexpression of diacylglycerol kinase-θ inhibited insulin signaling and was accompanied by an elevated cellular content of total PA and a decreased cellular content of total DAG. Overexpressing glycerol-3-phosphate acyltransferase-1 or -4 inhibited insulin signaling and increased the cellular content of both PA and DAG. Insulin signaling impairment caused by overexpression of phospholipase D1/D2 or diacylglycerol kinase-θ was always accompanied by disassociation of mTOR/rictor and reduction of mTORC2 kinase activity. However, although the protein ratio of membrane to cytosolic PKCϵ increased, PKC activity itself was unaltered. These data suggest that PA, but not DAG, is associated with impaired insulin action in mouse hepatocytes

Meeting the cultural and service needs of Arabic international students by using QFD

Quality has become an important factor in global competition for many reasons. Intensive global competition and the demand for better quality by customers has led organizations to realize the benefits of providing quality products and services in order to successfully compete and survive. Higher education institutions are one example of these organisations. Higher education institutions work in an intensive competitive environment worldwide driven by increasing demands for learning by local and international students. As a result, the managers of these sectors have realized that improving the quality of services is important for achieving customer satisfaction which can help survival in an internationally competitive market. To do this, it is necessary for organizations to know their customers and identify their requirements. To this end, many higher education institutions have adopted principles of total quality management (TQM) to improve their education quality which leads to better performance through involvement of every department to achieve excellence in business. This chapter considers the importance of measuring quality in order to assist universities to proactively manage the design and improvement of the social and academic experiences of postgraduate international students, and plan management decision-making processes to deliver high-quality services in a globalized business of provision of higher education. Higher education institutions must operate effectively and efficiently and be able to deliver quality programs, by seeking to better understand the needs of their customers to be competitive in this market space

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation

Proper and effective training of a pattern recognizer for cyclic data

IIE Transactions (Institute of Industrial Engineers)276746-756IIET

Detecting process mean shift in the presence of autocorrelation: A neural-network based monitoring scheme

10.1080/0020754032000123614International Journal of Production Research423573-595IJPR

Special-purpose ART-based identification system for statistical process control

Intelligent Engineering Systems Through Artificial Neural Networks5949-954IEAN