The Effects of Fibroblast Growth Factor 8b on Reproductive Organs and Prostate Tumorigenesis

Fibroblast growth factors (FGFs) are involved in the development and homeostasis of the prostate and other reproductive organs. FGF signaling is altered in prostate cancer. Fibroblast growth factor 8 (FGF8) is a mitogenic growth factor and its expression is elevated in prostate cancer and in premalignant prostatic intraepithelial neoplasia (PIN) lesions. FGF8b is the most transforming isoform of FGF8. Experimental models show that FGF8b promotes several phases of prostate tumorigenesis - including cancer initiation, tumor growth, angiogenesis, invasion and development of bone metastasis. The mechanisms activated by FGF8b in the prostate are unclear. In the present study, to examine the tumorigenic effects of FGF8b on the prostate and other FGF8b expressing organs, an FGF8b transgenic (TG) mouse model was generated. The effect of estrogen receptor beta (ERβ) deficiency on FGF8binduced prostate tumorigenesis was studied by breeding FGF8b-TG mice with ERβ knockout mice (BERKOFVB). Overexpression of FGF8b caused progressive histological and morphological changes in the prostate, epididymis and testis of FGF8b-TG-mice. In the prostate, hyperplastic, preneoplastic and neoplastic changes, including mouse PIN (mPIN) lesions, adenocarcinomas, sarcomas and carcinosarcomas were present in the epithelium and stroma. In the epididymis, a highly cancer-resistant tissue, the epithelium contained dysplasias and the stroma had neoplasias and hyperplasias with atypical cells. Besides similar histological changes in the prostate and epididymis, overexpression of FGF8b induced similar changes in the expression of genes such as osteopontin (Spp1), connective tissue growth factor (Ctgf) and FGF receptors (Fgfrs) in these two tissues. In the testes of the FGF8b-TG mice, the seminiferous epithelium was frequently degenerative and the number of spermatids was decreased. A portion of the FGF8b-TG male mice was infertile. Deficiency of ERβ did not accelerate prostate tumorigenesis in the FGF8b-TG mice, but increased significantly the frequency of mucinous metaplasia and slightly the frequency of inflammation in the prostate. This suggests putative differentiation promoting and anti-inflammatory roles for ERβ. In summary, these results underscore the importance of FGF signaling in male reproductive organs and provide novel evidence for a role of FGF8b in stromal activation and prostate tumorigenesis.

Geo-enabling repositories - techniques, tools, and challenges

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Minimizing Conducted RF-Emissions in Switch Mode Power Supplies Using Spread-Spectrum Techniques

Switching power supplies are usually implemented with a control circuitry that uses constant clock frequency turning the power semiconductor switches on and off. A drawback of this customary operating principle is that the switching frequency and harmonic frequencies are present in both the conducted and radiated EMI spectrum of the power converter. Various variable-frequency techniques have been introduced during the last decade to overcome the EMC problem. The main objective of this study was to compare the EMI and steady-state performance of a switch mode power supply with different spread-spectrum/variable-frequency methods. Another goal was to find out suitable tools for the variable-frequency EMI analysis. This thesis can be divided into three main parts: Firstly, some aspects of spectral estimation and measurement are presented. Secondly, selected spread spectrum generation techniques are presented with simulations and background information. Finally, simulations and prototype measurements from the EMC and the steady-state performance are carried out in the last part of this work. Combination of the autocorrelation function, the Welch spectrum estimate and the spectrogram were used as a substitute for ordinary Fourier methods in the EMC analysis. It was also shown that the switching function can be used in preliminary EMC analysis of a SMPS and the spectrum and autocorrelation sequence of a switching function correlates with the final EMI spectrum. This work is based on numerous simulations and measurements made with the prototype. All these simulations and measurements are made with the boost DC/DC converter. Four different variable-frequency modulation techniques in six different configurations were analyzed and the EMI performance was compared to the constant frequency operation. Output voltage and input current waveforms were also analyzed in time domain to see the effect of the spread spectrum operation on these quantities. According to the results presented in this work, spread spectrum modulation can be utilized in power converter for EMI mitigation. The results from steady-state voltage measurements show, that the variable-frequency operation of the SMPS has effect on the voltage ripple, but the ripple measured from the prototype is still acceptable in some applications. Both current and voltage ripple can be controlled with proper main circuit and controller design.

Graphene from Graphite by Chemical and Physical Techniques.

Graphene is a material with extraordinary properties. Its mechanical and electrical properties are unparalleled but the difficulties in its production are hindering its breakthrough in on applications. Graphene is a two-dimensional material made entirely of carbon atoms and it is only a single atom thick. In this work, properties of graphene and graphene based materials are described, together with their common preparation techniques and related challenges. This Thesis concentrates on the topdown techniques, in which natural graphite is used as a precursor for the graphene production. Graphite consists of graphene sheets, which are stacked together tightly. In the top-down techniques various physical or chemical routes are used to overcome the forces keeping the graphene sheets together, and many of them are described in the Thesis. The most common chemical method is the oxidisation of graphite with strong oxidants, which creates a water-soluble graphene oxide. The properties of graphene oxide differ significantly from pristine graphene and, therefore, graphene oxide is often reduced to form materials collectively known as reduced graphene oxide. In the experimental part, the main focus is on the chemical and electrochemical reduction of graphene oxide. A novel chemical route using vanadium is introduced and compared to other common chemical graphene oxide reduction methods. A strong emphasis is placed on electrochemical reduction of graphene oxide in various solvents. Raman and infrared spectroscopy are both used in in situ spectroelectrochemistry to closely monitor the spectral changes during the reduction process. These in situ techniques allow the precise control over the reduction process and even small changes in the material can be detected. Graphene and few layer graphene were also prepared using a physical force to separate these materials from graphite. Special adsorbate molecules in aqueous solutions, together with sonic treatment, produce stable dispersions of graphene and few layer graphene sheets in water. This mechanical exfoliation method damages the graphene sheets considerable less than the chemical methods, although it suffers from a lower yield.

Surface studies of limestones and dolostones : characterisation using various techniques and batch dissolution experiments with hydrochloric acid solutions

In this thesis, stepwise titration with hydrochloric acid was used to obtain chemical reactivities and dissolution rates of ground limestones and dolostones of varying geological backgrounds (sedimentary, metamorphic or magmatic). Two different ways of conducting the calculations were used: 1) a first order mathematical model was used to calculate extrapolated initial reactivities (and dissolution rates) at pH 4, and 2) a second order mathematical model was used to acquire integrated mean specific chemical reaction constants (and dissolution rates) at pH 5. The calculations of the reactivities and dissolution rates were based on rate of change of pH and particle size distributions of the sample powders obtained by laser diffraction. The initial dissolution rates at pH 4 were repeatedly higher than previously reported literature values, whereas the dissolution rates at pH 5 were consistent with former observations. Reactivities and dissolution rates varied substantially for dolostones, whereas for limestones and calcareous rocks, the variation can be primarily explained by relatively large sample standard deviations. A list of the dolostone samples in a decreasing order of initial reactivity at pH 4 is: 1) metamorphic dolostones with calcite/dolomite ratio higher than about 6% 2) sedimentary dolostones without calcite 3) metamorphic dolostones with calcite/dolomite ratio lower than about 6% The reactivities and dissolution rates were accompanied by a wide range of experimental techniques to characterise the samples, to reveal how different rocks changed during the dissolution process, and to find out which factors had an influence on their chemical reactivities. An emphasis was put on chemical and morphological changes taking place at the surfaces of the particles via X-ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM). Supporting chemical information was obtained with X-Ray Fluorescence (XRF) measurements of the samples, and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) measurements of the solutions used in the reactivity experiments. Information on mineral (modal) compositions and their occurrence was provided by X-Ray Diffraction (XRD), Energy Dispersive X-ray analysis (EDX) and studying thin sections with a petrographic microscope. BET (Brunauer, Emmet, Teller) surface areas were determined from nitrogen physisorption data. Factors increasing chemical reactivity of dolostones and calcareous rocks were found to be sedimentary origin, higher calcite concentration and smaller quartz concentration. Also, it is assumed that finer grain size and larger BET surface areas increase the reactivity although no certain correlation was found in this thesis. Atomic concentrations did not correlate with the reactivities. Sedimentary dolostones, unlike metamorphic ones, were found to have porous surface structures after dissolution. In addition, conventional (XPS) and synchrotron based (HRXPS) X-ray Photoelectron Spectroscopy were used to study bonding environments on calcite and dolomite surfaces. Both samples are insulators, which is why neutralisation measures such as electron flood gun and a conductive mask were used. Surface core level shifts of 0.7 ± 0.1 eV for Ca 2p spectrum of calcite and 0.75 ± 0.05 eV for Mg 2p and Ca 3s spectra of dolomite were obtained. Some satellite features of Ca 2p, C 1s and O 1s spectra have been suggested to be bulk plasmons. The origin of carbide bonds was suggested to be beam assisted interaction with hydrocarbons found on the surface. The results presented in this thesis are of particular importance for choosing raw materials for wet Flue Gas Desulphurisation (FGD) and construction industry. Wet FGD benefits from high reactivity, whereas construction industry can take advantage of slow reactivity of carbonate rocks often used in the facades of fine buildings. Information on chemical bonding environments may help to create more accurate models for water-rock interactions of carbonates.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Novel Interaction Techniques for Mobile Augmented Reality applications. A Systematic Literature Review

This study reviews the research on interaction techniques and methods that could be applied in mobile augmented reality scenarios. The review is focused on themost recent advances and considers especially the use of head-mounted displays. Inthe review process, we have followed a systematic approach, which makes the reviewtransparent, repeatable, and less prone to human errors than if it was conducted in amore traditional manner. The main research subjects covered in the review are headorientation and gaze-tracking, gestures and body part-tracking, and multimodality– as far as the subjects are related to human-computer interaction. Besides these,also a number of other areas of interest will be discussed.

Analysis of testicular cell populations using flow cytometry

Studying testis is complex, because the tissue has a very heterogeneous cell composition and its structure changes dynamically during development. In reproductive field, the cell composition is traditionally studied by morphometric methods such as immunohistochemistry and immunofluorescence. These techniques provide accurate quantitative information about cell composition, cell-cell association and localization of the cells of interest. However, the sample preparation, processing, staining and data analysis are laborious and may take several working days. Flow cytometry protocols coupled with DNA stains have played an important role in providing quantitative information of testicular cells populations ex vivo and in vitro studies. Nevertheless, the addition of specific cells markers such as intracellular antibodies would allow the more specific identification of cells of crucial interest during spermatogenesis. For this study, adult rat Sprague-Dawley rats were used for optimization of the flow cytometry protocol. Specific steps within the protocol were optimized to obtain a singlecell suspension representative of the cell composition of the starting material. Fixation and permeabilization procedure were optimized to be compatible with DNA stains and fluorescent intracellular antibodies. Optimization was achieved by quantitative analysis of specific parameters such as recovery of meiotic cells, amount of debris and comparison of the proportions of the various cell populations with already published data. As a result, a new and fast flow cytometry method coupled with DNA stain and intracellular antigen detection was developed. This new technique is suitable for analysis of population behavior and specific cells during postnatal testis development and spermatogenesis in rodents. This rapid protocol recapitulated the known vimentin and γH2AX protein expression patterns during rodent testis ontogenesis. Moreover, the assay was applicable for phenotype characterization of SCRbKO and E2F1KO mouse models.

Accelerating food safety and quality control: The use of antibody engineering techniques in the detec-tion of low-molecular weight food contaminants

The increased awareness and evolved consumer habits have set more demanding standards for the quality and safety control of food products. The production of foodstuffs which fulfill these standards can be hampered by different low-molecular weight contaminants. Such compounds can consist of, for example residues of antibiotics in animal use or mycotoxins. The extremely small size of the compounds has hindered the development of analytical methods suitable for routine use, and the methods currently in use require expensive instrumentation and qualified personnel to operate them. There is a need for new, cost-efficient and simple assay concepts which can be used for field testing and are capable of processing large sample quantities rapidly. Immunoassays have been considered as the golden standard for such rapid on-site screening methods. The introduction of directed antibody engineering and in vitro display technologies has facilitated the development of novel antibody based methods for the detection of low-molecular weight food contaminants. The primary aim of this study was to generate and engineer antibodies against low-molecular weight compounds found in various foodstuffs. The three antigen groups selected as targets of antibody development cause food safety and quality defects in wide range of products: 1) fluoroquinolones: a family of synthetic broad-spectrum antibacterial drugs used to treat wide range of human and animal infections, 2) deoxynivalenol: type B trichothecene mycotoxin, a widely recognized problem for crops and animal feeds globally, and 3) skatole, or 3-methyindole is one of the two compounds responsible for boar taint, found in the meat of monogastric animals. This study describes the generation and engineering of antibodies with versatile binding properties against low-molecular weight food contaminants, and the consecutive development of immunoassays for the detection of the respective compounds.