Mutation screening of the urocortin gene: identification of new single nucleotide polymorphisms and association studies with obesity in French Caucasians.

A linkage between obesity-related phenotypes and the 2p21-23 locus has been reported previously. The urocortin (UCN) gene resides at this interval, and its protein decreases appetite behavior, suggesting that UCN may be a candidate gene for susceptibility to obesity. We localized the UCN gene by radiation hybrid mapping, and the surrounding markers were genotyped in a collection of French families. Evidence for linkage was shown between the marker D2S165 and leptin levels (LOD score, 1.34; P = 0.006) and between D2S2247 and the z-score of body mass index (LOD score, 1.829; P = 0.0019). The gene was screened for SNPs in 96 obese patients. Four new variants were established. Two single nucleotide polymorphisms were located in the promoter (-535 A-->G, -286 G-->A), one in intron 1 (+31 C-->G), and one in the 3'-untranslated region (+34 C-->T). Association studies in cohorts of 722 unrelated obese and 381 control subjects and transmission disequilibrium tests, performed for the two frequent promoter polymorphisms, in 120 families (894 individuals) showed that no association was present between these variants and obesity, obesity-related phenotypes, and diabetes. Thus, our analyses of the genetic variations of the UCN gene suggest that, at least in French Caucasians, they do not represent a major cause of obesity.

Preliminary Studies of Remedial Measures for the Prevention of Bridge Deck Deterioration, HR-146, 1970

Four series of five specimens each were investigated for static and fatigue strength. These four series differed in that there were two variables, the first being the subsidence of concrete around reinforcing bars and the second being shrinkage due to two different curing conditions. The combinations of these variables were then compared to each other by use of, load-deflection curves and S-H fatigue curves.

Body mass index and risk of head and neck cancer in a pooled analysis of case-control studies in the International Head and Neck Cancer Epidemiology (INHANCE) Consortium.

BACKGROUND: Head and neck cancer (HNC) risk is elevated among lean people and reduced among overweight or obese people in some studies; however, it is unknown whether these associations differ for certain subgroups or are influenced by residual confounding from the effects of alcohol and tobacco use or by other sources of biases. METHODS: We pooled data from 17 case-control studies including 12 716 cases and the 17 438 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for associations between body mass index (BMI) at different ages and HNC risk, adjusted for age, sex, centre, race, education, tobacco smoking and alcohol consumption. RESULTS: Adjusted ORs (95% CIs) were elevated for people with BMI at reference (date of diagnosis for cases and date of selection for controls) 25.0-30.0 kg/m(2) (0.52, 0.44-0.60) and BMI >/=30 kg/m(2) (0.43, 0.33-0.57), compared with BMI >18.5-25.0 kg/m(2). These associations did not differ by age, sex, tumour site or control source. Although the increased risk among people with BMI 25 kg/m(2) was present only in smokers and drinkers. CONCLUSIONS: In our large pooled analysis, leanness was associated with increased HNC risk regardless of smoking and drinking status, although reverse causality cannot be excluded. The reduced risk among overweight or obese people may indicate body size is a modifier of the risk associated with smoking and drinking. Further clarification may be provided by analyses of prospective cohort and mechanistic studies.

Novel method to estimate the phenotypic variation explained by genome-wide association studies reveals large fraction of the missing heritability.

Genome-wide association studies (GWAS) are conducted with the promise to discover novel genetic variants associated with diverse traits. For most traits, associated markers individually explain just a modest fraction of the phenotypic variation, but their number can well be in the hundreds. We developed a maximum likelihood method that allows us to infer the distribution of associated variants even when many of them were missed by chance. Compared to previous approaches, the novelty of our method is that it (a) does not require having an independent (unbiased) estimate of the effect sizes; (b) makes use of the complete distribution of P-values while allowing for the false discovery rate; (c) takes into account allelic heterogeneity and the SNP pruning strategy. We applied our method to the latest GWAS meta-analysis results of the GIANT consortium. It revealed that while the explained variance of genome-wide (GW) significant SNPs is around 1% for waist-hip ratio (WHR), the observed P-values provide evidence for the existence of variants explaining 10% (CI=[8.5-11.5%]) of the phenotypic variance in total. Similarly, the total explained variance likely to exist for height is estimated to be 29% (CI=[28-30%]), three times higher than what the observed GW significant SNPs give rise to. This methodology also enables us to predict the benefit of future GWA studies that aim to reveal more associated genetic markers via increased sample size.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Experimental thermal hydraulic studies on the enhancement of safety of LWRs

The safe use of nuclear power plants (NPPs) requires a deep understanding of the functioning of physical processes and systems involved. Studies on thermal hydraulics have been carried out in various separate effects and integral test facilities at Lappeenranta University of Technology (LUT) either to ensure the functioning of safety systems of light water reactors (LWR) or to produce validation data for the computer codes used in safety analyses of NPPs. Several examples of safety studies on thermal hydraulics of the nuclear power plants are discussed. Studies are related to the physical phenomena existing in different processes in NPPs, such as rewetting of the fuel rods, emergency core cooling (ECC), natural circulation, small break loss-of-coolant accidents (SBLOCA), non-condensable gas release and transport, and passive safety systems. Studies on both VVER and advanced light water reactor (ALWR) systems are included. The set of cases include separate effects tests for understanding and modeling a single physical phenomenon, separate effects tests to study the behavior of a NPP component or a single system, and integral tests to study the behavior of the whole system. In the studies following steps can be found, not necessarily in the same study. Experimental studies as such have provided solutions to existing design problems. Experimental data have been created to validate a single model in a computer code. Validated models are used in various transient analyses of scaled facilities or NPPs. Integral test data are used to validate the computer codes as whole, to see how the implemented models work together in a code. In the final stage test results from the facilities are transferred to the NPP scale using computer codes. Some of the experiments have confirmed the expected behavior of the system or procedure to be studied; in some experiments there have been certain unexpected phenomena that have caused changes to the original design to avoid the recognized problems. This is the main motivation for experimental studies on thermal hydraulics of the NPP safety systems. Naturally the behavior of the new system designs have to be checked with experiments, but also the existing designs, if they are applied in the conditions that differ from what they were originally designed for. New procedures for existing reactors and new safety related systems have been developed for new nuclear power plant concepts. New experiments have been continuously needed.

Quasi real-time Raman studies on the growth of Cu-In-S thin films

In this work annealing and growth of CuInS2 thin films is investigated with quasireal-time in situ Raman spectroscopy. During the annealing a shift of the Raman A1 mode towards lower wave numbers with increasing temperature is observed. A linear temperature dependence of the phonon branch of ¿2 cm¿1/100 K is evaluated. The investigation of the growth process (sulfurization of metallic precursors) with high surface sensitivity reveals the occurrence of phases which are not detected with bulk sensitive methods. This allows a detailed insight in the formation of the CuInS2 phases. Independent from stoichiometry and doping of the starting precursors the CuAu ordering of CuInS2 initially forms as the dominating ordering. The transformation of the CuAu ordering into the chalcopyrite one is, in contrast, strongly dependent on the precursor composition and requires high temperatures.

Exploring the strategic impact of technological change - Studies on the role of Internet in magazine publishing

Over the past few decades, turbulent change has characterized the situation in the media industry. It has been noted that digitalization and new media are strongly influencing the industry: it is changing the existing market dynamics and requires new strategies. Prior research on the impact of digitalization and the Internet has emphasized news-focused media such as newspaper publishing and broadcasting, yet magazine publishing is very seldom the focus of the research. This study examines how the Internetimpacts magazine publishing. The work presents a multi-level analysis on the role and impact of the Internet on magazine products, companies and industry. The study is founded on strategic management, technology management and media economics literature. This study consists of two parts. The first part introduces the research topic and discusses the overall results of the study. The second part comprises five research publications. Qualitative research methods are used throughout. The results of the study indicate that the Internet has not had a disruptive effect on magazine publishing, and that its strategic implications could rather be considered complementary to the print magazine and the business as a whole. It seems that the co-specialized assets, together with market-related competencies and unchanged core competence have protected established firms from the disruptive effect of the new technology in magazine publishing. In addition, it seems that the Internet offers a valuable possibility to build and nourish customer relationships. The study contributes tomedia management and economics research by moving from product- or industry-level investigations towards a strategic-management perspective.

R&D Performance Analysis: Case Studies on the Challenges and Promotion of the Evaluation and Measurement of R&D

Due to the intense international competition, demanding, and sophisticated customers, and diverse transforming technological change, organizations need to renew their products and services by allocating resources on research and development (R&D). Managing R&D is complex, but vital for many organizations to survive in the dynamic, turbulent environment. Thus, the increased interest among decision-makers towards finding the right performance measures for R&D is understandable. The measures or evaluation methods of R&D performance can be utilized for multiple purposes; for strategic control, for justifying the existence of R&D, for providing information and improving activities, as well as for the purposes of motivating and benchmarking. The earlier research in the field of R&D performance analysis has generally focused on either the activities and considerable factors and dimensions - e.g. strategic perspectives, purposes of measurement, levels of analysis, types of R&D or phases of R&D process - prior to the selection of R&Dperformance measures, or on proposed principles or actual implementation of theselection or design processes of R&D performance measures or measurement systems. This study aims at integrating the consideration of essential factors anddimensions of R&D performance analysis to developed selection processes of R&D measures, which have been applied in real-world organizations. The earlier models for corporate performance measurement that can be found in the literature, are to some extent adaptable also to the development of measurement systemsand selecting the measures in R&D activities. However, it is necessary to emphasize the special aspects related to the measurement of R&D performance in a way that make the development of new approaches for especially R&D performance measure selection necessary: First, the special characteristics of R&D - such as the long time lag between the inputs and outcomes, as well as the overall complexity and difficult coordination of activities - influence the R&D performance analysis problems, such as the need for more systematic, objective, balanced and multi-dimensional approaches for R&D measure selection, as well as the incompatibility of R&D measurement systems to other corporate measurement systems and vice versa. Secondly, the above-mentioned characteristics and challenges bring forth the significance of the influencing factors and dimensions that need to be recognized in order to derive the selection criteria for measures and choose the right R&D metrics, which is the most crucial step in the measurement system development process. The main purpose of this study is to support the management and control of the research and development activities of organizations by increasing the understanding of R&D performance analysis, clarifying the main factors related to the selection of R&D measures and by providing novel types of approaches and methods for systematizing the whole strategy- and business-based selection and development process of R&D indicators.The final aim of the research is to support the management in their decision making of R&D with suitable, systematically chosen measures or evaluation methods of R&D performance. Thus, the emphasis in most sub-areas of the present research has been on the promotion of the selection and development process of R&D indicators with the help of the different tools and decision support systems, i.e. the research has normative features through providing guidelines by novel types of approaches. The gathering of data and conducting case studies in metal and electronic industry companies, in the information and communications technology (ICT) sector, and in non-profit organizations helped us to formulate a comprehensive picture of the main challenges of R&D performance analysis in different organizations, which is essential, as recognition of the most importantproblem areas is a very crucial element in the constructive research approach utilized in this study. Multiple practical benefits regarding the defined problemareas could be found in the various constructed approaches presented in this dissertation: 1) the selection of R&D measures became more systematic when compared to the empirical analysis, as it was common that there were no systematic approaches utilized in the studied organizations earlier; 2) the evaluation methods or measures of R&D chosen with the help of the developed approaches can be more directly utilized in the decision-making, because of the thorough consideration of the purpose of measurement, as well as other dimensions of measurement; 3) more balance to the set of R&D measures was desired and gained throughthe holistic approaches to the selection processes; and 4) more objectivity wasgained through organizing the selection processes, as the earlier systems were considered subjective in many organizations. Scientifically, this dissertation aims to make a contribution to the present body of knowledge of R&D performance analysis by facilitating dealing with the versatility and challenges of R&D performance analysis, as well as the factors and dimensions influencing the selection of R&D performance measures, and by integrating these aspects to the developed novel types of approaches, methods and tools in the selection processes of R&D measures, applied in real-world organizations. In the whole research, facilitation of dealing with the versatility and challenges in R&D performance analysis, as well as the factors and dimensions influencing the R&D performance measure selection are strongly integrated with the constructed approaches. Thus, the research meets the above-mentioned purposes and objectives of the dissertation from the scientific as well as from the practical point of view.

Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.