Quantitative Analysis of Novel Prostate Cancer Markers in Tissue

Prostate cancer is a heterogeneous disease affecting an increasing number of men all over the world, but particularly in the countries with the Western lifestyle. The best biomarker assay currently available for the diagnosis of the disease, the measurement of prostate specific antigen (PSA) levels from blood, lacks specificity, and even when combined with invasive tests such as digital rectal exam and prostate tissue biopsies, these methods can both miss cancers, and lead to overdiagnosis and subsequent overtreatment of cancers. Moreover, they cannot provide an accurate prognosis for the disease. Due to the high prevalence of indolent prostate cancers, the majority of men affected by prostate cancer would be able to live without any medical intervention. Their latent prostate tumors would not cause any clinical symptoms during their lifetime, but few are willing to take the risk, as currently there are no methods or biomarkers to reliably differentiate the indolent cancers from the aggressive, lethal cases that really are in need of immediate medical treatment. This doctoral work concentrated on validating 12 novel candidate genes for use as biomarkers for prostate cancer by measuring their mRNA expression levels in prostate tissue and peripheral blood of men with cancer as well as unaffected individuals. The panel of genes included the most prominent markers in the current literature: PCA3 and the fusion gene TMPRSS2-ERG, in addition to BMP-6, FGF-8b, MSMB, PSCA, SPINK1, and TRPM8; and the kallikrein-related peptidase genes 2, 3, 4, and 15. Truly quantitative reverse-transcription PCR assays were developed for each of the genes for the purpose, time-resolved fluorometry was applied in the real-time detection of the amplification products, and the gene expression data were normalized by using artificial internal RNA standards. Cancer-related, statistically significant differences in gene transcript levels were found for TMPRSS2-ERG, PCA3, and in a more modest scale, for KLK15, PSCA, and SPINK1. PCA3 RNA was found in the blood of men with metastatic prostate cancer, but not in localized cases of cancer, suggesting limitations for using this method for early cancer detection in blood. TMPRSS2-ERG mRNA transcripts were found more frequently in cancerous than in benign prostate tissues, but they were present also in 51% of the histologically benign prostate tissues of men with prostate cancer, while being absent in specimens from men without any signs of prostate cancer. PCA3 was shown to be 5.8 times overexpressed in cancerous tissue, but similarly to the fusion gene mRNA, its levels were upregulated also in the histologically benign regions of the tissue if the corresponding prostate was harboring carcinoma. These results indicate a possibility to utilize these molecular assays to assist in prostate cancer risk evaluation especially in men with initially histologically negative biopsies.

Quantitative Magnetic Resonance Imaging of the Liver and Heart In Iron Overload

Systemic iron overload (IO) is considered a principal determinant in the clinical outcome of different forms of IO and in allogeneic hematopoietic stem cell transplantation (alloSCT). However, indirect markers for iron do not provide exact quantification of iron burden, and the evidence of iron-induced adverse effects in hematological diseases has not been established. Hepatic iron concentration (HIC) has been found to represent systemic IO, which can be quantified safely with magnetic resonance imaging (MRI), based on enhanced transverse relaxation. The iron measurement methods by MRI are evolving. The aims of this study were to implement and optimise the methodology of non-invasive iron measurement with MRI to assess the degree and the role of IO in the patients. An MRI-based HIC method (M-HIC) and a transverse relaxation rate (R2*) from M-HIC images were validated. Thereafter, a transverse relaxation rate (R2) from spin-echo imaging was calibrated for IO assessment. Two analysis methods, visual grading and rSI, for a rapid IO grading from in-phase and out-of-phase images were introduced. Additionally, clinical iron indicators were evaluated. The degree of hepatic and cardiac iron in our study patients and IO as a prognostic factor in patients undergoing alloSCT were explored. In vivo and in vitro validations indicated that M-HIC and R2* are both accurate in the quantification of liver iron. R2 was a reliable method for HIC quantification and covered a wider HIC range than M-HIC and R2*. The grading of IO was able to be performed rapidly with the visual grading and rSI methods. Transfusion load was more accurate than plasma ferritin in predicting transfusional IO. In patients with hematological disorders, the prevalence of hepatic IO was frequent, opposite to cardiac IO. Patients with myelodysplastic syndrome were found to be the most susceptible to IO. Pre-transplant IO predicted severe infections during the early post-transplant period, in contrast to the reduced risk of graft-versus-host disease. Iron-induced, poor transplantation results are most likely to be mediated by severe infections.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Social class as a factor for the construction of a musician’s identity : The Musician’s social background and identity questionnaire (MSBIQ) – a cross-sectional comparative quantitative online survey research study of music students at two higher education institutions in Finland

There is currently little empirical knowledge regarding the construction of a musician’s identity and social class. With a theoretical framework based on Bourdieu’s (1984) distinction theory, Bronfenbrenner’s (1979) theory of ecological systems, and the identity theories of Erikson (1950; 1968) and Marcia (1966), a survey called the Musician’s Social Background and Identity Questionnaire (MSBIQ) is developed to test three research hypotheses related to the construction of a musician’s identity, social class and ecological systems of development. The MSBIQ is administered to the music students at Sibelius Academy of the University of Arts Helsinki and Helsinki Metropolia University of Applied Sciences, representing the ’highbrow’ and the ’middlebrow’ samples in the field of music education in Finland. Acquired responses (N = 253) are analyzed and compared with quantitative methods including Pearson’s chi-square test, factor analysis and an adjusted analysis of variance (ANOVA). The study revealed that (1) the music students at Sibelius Academy and Metropolia construct their subjective musician’s identity differently, but (2) social class does not affect this identity construction process significantly. In turn, (3) the ecological systems of development, especially the individual’s residential location, do significantly affect the construction of a musician’s identity, as well as the age at which one starts to play one’s first musical instrument. Furthermore, a novel finding related to the structure of a musician’s identity was the tripartite model of musical identity consisting of the three dimensions of a musician’s identity: (I) ’the subjective dimension of a musician’s identity’, (II) ’the occupational dimension of a musician’s identity’ and, (III) ’the conservative-liberal dimension of a musician’s identity’. According to this finding, a musician’s identity is not a uniform, coherent entity, but a structure consisting of different elements continuously working in parallel within different dimensions. The results and limitations related to the study are discussed, as well as the objectives related to future studies using the MSBIQ to research the identity construction and social backgrounds of a musician or other performing artists.

Quantitative refinement of reaction-based biomodels

In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.

Implementation of Quantitative Reaction-based Model Refinement

Building a computational model for complex biological systems is an iterative process. It starts from an abstraction of the process and then incorporates more details regarding the specific biochemical reactions which results in the change of the model fit. Meanwhile, the model’s numerical properties such as its numerical fit and validation should be preserved. However, refitting the model after each refinement iteration is computationally expensive resource-wise. There is an alternative approach which ensures the model fit preservation without the need to refit the model after each refinement iteration. And this approach is known as quantitative model refinement. The aim of this thesis is to develop and implement a tool called ModelRef which does the quantitative model refinement automatically. It is both implemented as a stand-alone Java application and as one of Anduril framework components. ModelRef performs data refinement of a model and generates the results in two different well known formats (SBML and CPS formats). The development of this tool successfully reduces the time and resource needed and the errors generated as well by traditional reiteration of the whole model to perform the fitting procedure.

Cardiac Imaging in the Diagnosis of Coronary Artery Disease: The Value of Quantitative Imaging of Myocardial Perfusion and Deformation

Atherosclerosis is a chronic and progressive disease of the vasculature. Increasing coronary atherosclerosis can lead to obstructive coronary artery disease (CAD) or myocardial infarction. Computed tomography angiography (CTA) allows noninvasive assessment of coronary anatomy and quantitation of atherosclerotic burden. Myocardial blood flow (MBF) can be accurately measured in absolute terms (mL/g/min) by positron emission tomography (PET) with [15O] H O as a radiotracer. We studied the coronary microvascular dysfunction as a risk factor for future coronary calcification in healthy young men by measuring the coronary flow reserve (CFR) which is the ratio between resting and hyperemic MBF. Impaired vasodilator function was not linked with accelerated atherosclerosis 11 years later. Currently, there is a global interest in quantitative PET perfusion imaging. We established optimal thresholds of [15O] H O PET perfusion for diagnosis of CAD (hyperemic MBF of 2.3 mL/g/min and CFR of 2.5) in the first multicenter study of this type (Turku, Amsterdam and Uppsala). In myocardial bridging a segment of the coronary artery travels inside the myocardium and can be seen as intramural course (CTA) or systolic compression (invasive coronary angiography). Myocardial bridging is frequently linked with proximal atherosclerotic plaques. We used quantitative [15O] H O PET perfusion to evaluate the hemodynamic effects of myocardial bridging. Myocardial bridging was not associated with decreased absolute MBF or increased atherosclerotic burden. Speckle tracking allows quantitative echocardiographic imaging of myocardial deformation. Speckle tracking during dobutamine stress echocardiography was feasible and comparable to subjective wall motion analysis in the diagnosis of CAD. In addition, it correctly risk stratified patients with multivessel disease and extensive ischemia.