Empirical analysis of human capital development and economic growth in Europe

Recent discussion of the knowledge-based economy draws increasingly attention to the role that the creation and management of knowledge plays in economic development. Development of human capital, the principal mechanism for knowledge creation and management, becomes a central issue for policy-makers and practitioners at the regional, as well as national, level. Facing competition both within and across nations, regional policy-makers view human capital development as a key to strengthening the positions of their economies in the global market. Against this background, the aim of this study is to go some way towards answering the question of whether, and how, investment in education and vocational training at regional level provides these territorial units with comparative advantages. The study reviews literature in economics and economic geography on economic growth (Chapter 2). In growth model literature, human capital has gained increased recognition as a key production factor along with physical capital and labour. Although leaving technical progress as an exogenous factor, neoclassical Solow-Swan models have improved their estimates through the inclusion of human capital. In contrast, endogenous growth models place investment in research at centre stage in accounting for technical progress. As a result, they often focus upon research workers, who embody high-order human capital, as a key variable in their framework. An issue of discussion is how human capital facilitates economic growth: is it the level of its stock or its accumulation that influences the rate of growth? In addition, these economic models are criticised in economic geography literature for their failure to consider spatial aspects of economic development, and particularly for their lack of attention to tacit knowledge and urban environments that facilitate the exchange of such knowledge. Our empirical analysis of European regions (Chapter 3) shows that investment by individuals in human capital formation has distinct patterns. Those regions with a higher level of investment in tertiary education tend to have a larger concentration of information and communication technology (ICT) sectors (including provision of ICT services and manufacture of ICT devices and equipment) and research functions. Not surprisingly, regions with major metropolitan areas where higher education institutions are located show a high enrolment rate for tertiary education, suggesting a possible link to the demand from high-order corporate functions located there. Furthermore, the rate of human capital development (at the level of vocational type of upper secondary education) appears to have significant association with the level of entrepreneurship in emerging industries such as ICT-related services and ICT manufacturing, whereas such association is not found with traditional manufacturing industries. In general, a high level of investment by individuals in tertiary education is found in those regions that accommodate high-tech industries and high-order corporate functions such as research and development (R&D). These functions are supported through the urban infrastructure and public science base, facilitating exchange of tacit knowledge. They also enjoy a low unemployment rate. However, the existing stock of human and physical capital in those regions with a high level of urban infrastructure does not lead to a high rate of economic growth. Our empirical analysis demonstrates that the rate of economic growth is determined by the accumulation of human and physical capital, not by level of their existing stocks. We found no significant effects of scale that would favour those regions with a larger stock of human capital. The primary policy implication of our study is that, in order to facilitate economic growth, education and training need to supply human capital at a faster pace than simply replenishing it as it disappears from the labour market. Given the significant impact of high-order human capital (such as business R&D staff in our case study) as well as the increasingly fast pace of technological change that makes human capital obsolete, a concerted effort needs to be made to facilitate its continuous development.

Proteomic analysis of a noninvasive human model of acute inflammation and its resolution:the twenty-one day gingivitis model

The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

A proteo-liposome system for the analysis of the intracellular interactome of membrane proteins using amyloid precursor protein as a model

Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.