Molecular profiling of human endometrium and endometriosis

Endometriosis is a common hormone-dependent gynecological disease leading to severe menstrual and/or chronic pelvic pain with or without subfertility. The disease is defined by the presence of endometrium-like tissue outside the uterine cavity, primarily on the pelvic peritoneum, ovaries and infiltrating organs of the peritoneal cavity. The current tools for diagnosis and treatment of endometriosis need to be improved to ensure reliable diagnosis and effective treatment. In addition, endometriosis is associated with increased risk of ovarian cancer and, therefore, the differential diagnosis between the benign and malignant ovarian cysts is of importance. The long-term objective of the present study was to support the discovery of novel tools for diagnosis and treatment of endometriosis. This was approached by exploiting genome-wide expression analysis of endometriosis specimens. A novel expression profiling -based classification of endometriosis indicated specific subgroups of lesions partially consistent with the clinical appearance, but partially according to unknown factors. The peritoneum of women with endometriosis appeared to be altered in comparison to that of healthy control subjects, suggesting a novel aspect on the pathogenesis of the disease. The evaluation of action and metabolism of sex hormones in endometrium and endometriosis tissue indicated a novel role of androgens in regulation of the tissues. In addition, an enzyme involved in androgen and neurosteroid metabolism, hydroxysteroid (17beta) dehydrogenase 6, was found to be highly up-regulated in endometriosis tissue as compared to healthy endometrium. The enzyme may have a role in the pathogenesis of endometriosis or in the endometriosis associated pain generation. Finally, a new diagnostic biomarker, HE4, was discovered distinguishing patients with ovarian endometriotic cysts from those with malignant ovarian cancer. The information acquired in this study enables deeper understanding of endometriosis and facilitates the development of improved diagnostic tools and more specific treatments of the disease

Transcriptional Profiling of Organ‐Specific Autoimmunity in Human

Our understanding of the pathogenesis of organ‐specific autoinflammation has been restricted by limited access to the target organs. Peripheral blood, however, as a preferred transportation route for immune cells, provides a window to assess the entire immune system throughout the body. Transcriptional profiling with RNA stabilizing blood collection tubes reflects in vivo expression profiles at the time the blood is drawn, allowing detection of the disease activity in different samples or within the same sample over time. The main objective of this Ph.D. study was to apply gene‐expression microarrays in the characterization of peripheral blood transcriptional profiles in patients with autoimmune diseases. To achieve this goal a custom cDNA microarray targeted for gene‐expression profiling of human immune system was designed and produced. Sample collection and preparation was then optimized to allow gene‐expression profiling from whole‐blood samples. To overcome challenges resulting from minute amounts of sample material, RNA amplification was successfully applied to study pregnancy related immunosuppression in patients with multiple sclerosis (MS). Furthermore, similar sample preparation was applied to characterize longitudinal genome‐wide expression profiles in children with type 1 diabetes (T1D) associated autoantibodies and eventually clinical T1D. Blood transcriptome analyses, using both the ImmunoChip cDNA microarray with targeted probe selection and genome‐wide Affymetrix U133 Plus 2.0 oligonucleotide array, enabled monitoring of autoimmune activity. Novel disease related genes and general autoimmune signatures were identified. Notably, down‐regulation of the HLA class Ib molecules in peripheral blood was associated with disease activity in both MS and T1D. Taken together, these studies demonstrate the potential of peripheral blood transcriptional profiling in biomedical research and diagnostics. Imbalances in peripheral blood transcriptional activity may reveal dynamic changes that are relevant for the disease but might be completely missed in conventional cross‐sectional studies.

Profiling the Value of Industrial Maintenance Services

Industrial maintenance can be executed internally, acquired from the original equipment manufacturer or outsourced to a service provider, and this concludes in many different kind of business relationships. To maximize the total value in a maintenance business relationship it is important to know what the partner values. The value of maintenance services can be considered to consist of value elements and the perceived total value for the customer and the service provider is the sum of these value elements. The specific objectives of this thesis are to identify the most important value elements for the maintenance service customer and provider and also to recognize where the value elements differ. The study was executed as a statistical analysis using the survey method. The data has been collected by an online survey sent to 345 maintenance service professionals in Finland. In the survey, four different types of value elements were considered: the customer’s high critical and low critical items and the service provider’s core and support service. The most valued elements by the respondents were reliability, safety at work, environmental safety, and operator knowledge. The least valued elements were asset management factors and access to markets. Statistically significant differences in value elements between service types were also found. As a managerial implication a value gap profile is presented. This Master’s Thesis is part of the MaiSeMa (Industrial Maintenance Services in a Renewing Business Network: Identify, Model and Manage Value) research project where network decision models are created to identify, model and manage the value of maintenance services.

Perception of privacy in smartphone applications: profiling users based on personality types.

This document is focused on studying privacy perception and personality traits of users in the context of smartphone application privacy. It is divided into two parts. The first part presents an in depth systematic literature review of the existing academic writings available on the topic of relation between privacy perception and personality traits. Demographics, methodologies and other useful insight is extracted and the available literature is divided into broader group of topics bringing the five main areas of research to light and highlighting the current research trends in the field along with pinpointing the research gap of interest to the author. The second part of the thesis uses the results from the literature review to administer an empirical study to investigate the current privacy perception of users and the correlation between personality traits and privacy perception in smartphone applications. Big five personality test is used as the measure for personality traits whereas three sub-variables are used to measure privacy perception i.e. perceived privacy awareness, perceived threat to privacy and willingness to trade privacy. According to the study openness to experience is the most dominant trait having a strong correlation with two privacy sub-variables whereas emotional stability doesn’t show any correlation with privacy perception. Empirical study also explores other findings as preferred privacy sources and application installation preferences that provide further insight about users and might be useful in future.