Molecular Mechanisms of Androgen Receptor Interactions

The androgen receptor (AR) mediates the effects of the male sex-steroid hormones (androgens), testosterone and 5?-dihydrotestosterone. Androgens are critical in the development and maintenance of male sexual characteristics. AR is a member of the steroid receptor ligand-inducible transcription factor family. The steroid receptor family is a subgroup of the nuclear receptor superfamily that also includes receptors for the active forms of vitamin A, vitamin D3, and thyroid hormones. Like all nuclear receptors, AR has a conserved modular structure consisting of a non-conserved amino-terminal domain (NTD), containing the intrinsic activation function 1, a highly conserved DNA-binding domain, and a conserved ligand-binding domain (LBD) that harbors the activation function 2. Each of these domains plays an important role in receptor function and signaling, either via intra- and inter-receptor interactions, interactions with specific DNA sequences, termed hormone response elements, or via functional interactions with domain-specific proteins, termed coregulators (coactivators and corepressors). Upon binding androgens, AR acquires a new conformational state, translocates to the nucleus, binds to androgen response elements, homodimerizes and recruits sequence-specific coregulatory factors and the basal transcription machinery. This set of events is required to activate gene transcription (expression). Gene transcription is a strictly modulated process that governs cell growth, cell homeostasis, cell function and cell death. Disruptions of AR transcriptional activity caused by receptor mutations and/or altered coregulator interactions are linked to a wide spectrum of androgen insensitivity syndromes, and to the pathogenesis of prostate cancer (CaP). The treatment of CaP usually involves androgen depletion therapy (ADT). ADT achieves significant clinical responses during the early stages of the disease. However, under the selective pressure of androgen withdrawal, androgen-dependent CaP can progress to an androgen-independent CaP. Androgen-independent CaP is invariably a more aggressive and untreatable form of the disease. Advancing our understanding of the molecular mechanisms behind the switch in androgen-dependency would improve our success of treating CaP and other AR related illnesses. This study evaluates how clinically identified AR mutations affect the receptor s transcriptional activity. We reveal that a potential molecular abnormality in androgen insensitivity syndrome and CaP patients is caused by disruptions of the important intra-receptor NTD/LBD interaction. We demonstrate that the same AR LBD mutations can also disrupt the recruitment of the p160 coactivator protein GRIP1. Our investigations reveal that 30% of patients with advanced, untreated local CaP have somatic mutations that may lead to increases in AR activity. We report that somatic mutations that activate AR may lead to early relapse in ADT. Our results demonstrate that the types of ADT a CaP patient receives may cause a clustering of mutations to a particular region of the receptor. Furthermore, the mutations that arise before and during ADT do not always result in a receptor that is more active, indicating that coregulator interactions play a pivotal role in the progression of androgen-independent CaP. To improve CaP therapy, it is necessary to identify critical coregulators of AR. We screened a HeLa cell cDNA library and identified small carboxyl-terminal domain phosphatase 2 (SCP2). SCP2 is a protein phosphatase that directly interacts with the AR NTD and represses AR activity. We demonstrated that reducing the endogenous cellular levels of SCP2 causes more AR to load on to the prostate specific antigen (PSA) gene promoter and enhancer regions. Additionally, under the same conditions, more RNA polymerase II was recruited to the PSA promoter region and overall there was an increase in androgen-dependent transcription of the PSA gene, revealing that SCP2 could play a role in the pathogenesis of CaP.

Suunnittelunäkemys metsäorganisaatioissa ja sen vaikutus tietojärjestelmälle asetettaviin vaatimuksiin

Department of Forest Resource Management in the University of Helsinki has in years 2004?2007 carried out so-called SIMO -project to develop a new generation planning system for forest management. Project parties are organisations doing most of Finnish forest planning in government, industry and private owned forests. Aim of this study was to find out the needs and requirements for new forest planning system and to clarify how parties see targets and processes in today's forest planning. Representatives responsible for forest planning in each organisation were interviewed one by one. According to study the stand-based system for managing and treating forests continues in the future. Because of variable data acquisition methods with different accuracy and sources, and development of single tree interpretation, more and more forest data is collected without field work. The benefits of using more specific forest data also calls for use of information units smaller than tree stand. In Finland the traditional way to arrange forest planning computation is divided in two elements. After updating the forest data to present situation every stand unit's growth is simulated with different alternative treatment schedule. After simulation, optimisation selects for every stand one treatment schedule so that the management program satisfies the owner's goals in the best possible way. This arrangement will be maintained in the future system. The parties' requirements to add multi-criteria problem solving, group decision support methods as well as heuristic and spatial optimisation into system make the programming work more challenging. Generally the new system is expected to be adjustable and transparent. Strict documentation and free source code helps to bring these expectations into effect. Variable growing models and treatment schedules with different source information, accuracy, methods and the speed of processing are supposed to work easily in system. Also possibilities to calibrate models regionally and to set local parameters changing in time are required. In future the forest planning system will be integrated in comprehensive data management systems together with geographic, economic and work supervision information. This requires a modular method of implementing the system and the use of a simple data transmission interface between modules and together with other systems. No major differences in parties' view of the systems requirements were noticed in this study. Rather the interviews completed the full picture from slightly different angles. In organisation the forest management is considered quite inflexible and it only draws the strategic lines. It does not yet have a role in operative activity, although the need and benefits of team level forest planning are admitted. Demands and opportunities of variable forest data, new planning goals and development of information technology are known. Party organisations want to keep on track with development. One example is the engagement in extensive SIMO-project which connects the whole field of forest planning in Finland.

NMR Spectroscopy of Multi-domain Proteins : Immunoglobulin-like Domains of Human Filamin A

Proteins are complex biomacromolecules playing fundamental roles in the physiological processes of all living organisms. They function as structural units, enzymes, transporters, process regulators, and signal transducers. Defects in protein functions often derive from genetic mutations altering the protein structure, and impairment of essential protein functions manifests itself as pathological conditions. Proteins operate through interactions, and all protein functions depend on protein structure. In order to understand biological mechanisms at the molecular level, one has to know the structures of the proteins involved. This thesis covers structural and functional characterization of human filamins. Filamins are actin-binding and -bundling proteins that have numerous interaction partners. In addition to their actin-organizing functions, filamins are also known to have roles in cell adhesion and locomotion, and to participate in the logistics of cell membrane receptors, and in the coordination of intracellular signaling pathways. Filamin mutations in humans induce severe pathological conditions affecting the brain, bones, limbs, and the cardiovascular system. Filamins are large modular proteins composed of an N-terminal actin-binding domain and 24 consecutive immunoglobulin-like domains (IgFLNs). Nuclear magnetic resonance (NMR) spectroscopy is a versatile method of gaining insight into protein structure, dynamics and interactions. NMR spectroscopy was employed in this thesis to study the atomic structure and interaction mechanisms of C-terminal IgFLNs, which are known to house the majority of the filamin interaction sites. The structures of IgFLN single-domains 17 and 23 and IgFLN domain pairs 16-17 and 18-19 were determined using NMR spectroscopy. The structures of domain pairs 16 17 and 18 19 both revealed novel domain domain interaction modes of IgFLNs. NMR titrations were employed to characterize the interactions of filamins with glycoprotein Ibα, FilGAP, integrin β7 and dopamine receptors. Domain packing of IgFLN domain sextet 16 21 was further characterized using residual dipolar couplings and NMR relaxation analysis. This thesis demonstrates the versatility and potential of NMR spectroscopy in structural and functional studies of multi-domain proteins.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Characterization of genomic diversity in extraintestinal pathogenic Escherichia coli (ExPEC) and development of a diagnostic DNA microarray for the differentiation of ExPEC isolates causing urinary tract infections

Extraintestinal pathogenic Escherichia coli (ExPEC) represent a diverse group of strains of E. coli, which infect extraintestinal sites, such as the urinary tract, the bloodstream, the meninges, the peritoneal cavity, and the lungs. Urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC), the major subgroup of ExPEC, are among the most prevalent microbial diseases world wide and a substantial burden for public health care systems. UTIs are responsible for serious morbidity and mortality in the elderly, in young children, and in immune-compromised and hospitalized patients. ExPEC strains are different, both from genetic and clinical perspectives, from commensal E. coli strains belonging to the normal intestinal flora and from intestinal pathogenic E. coli strains causing diarrhea. ExPEC strains are characterized by a broad range of alternate virulence factors, such as adhesins, toxins, and iron accumulation systems. Unlike diarrheagenic E. coli, whose distinctive virulence determinants evoke characteristic diarrheagenic symptoms and signs, ExPEC strains are exceedingly heterogeneous and are known to possess no specific virulence factors or a set of factors, which are obligatory for the infection of a certain extraintestinal site (e. g. the urinary tract). The ExPEC genomes are highly diverse mosaic structures in permanent flux. These strains have obtained a significant amount of DNA (predictably up to 25% of the genomes) through acquisition of foreign DNA from diverse related or non-related donor species by lateral transfer of mobile genetic elements, including pathogenicity islands (PAIs), plasmids, phages, transposons, and insertion elements. The ability of ExPEC strains to cause disease is mainly derived from this horizontally acquired gene pool; the extragenous DNA facilitates rapid adaptation of the pathogen to changing conditions and hence the extent of the spectrum of sites that can be infected. However, neither the amount of unique DNA in different ExPEC strains (or UPEC strains) nor the mechanisms lying behind the observed genomic mobility are known. Due to this extreme heterogeneity of the UPEC and ExPEC populations in general, the routine surveillance of ExPEC is exceedingly difficult. In this project, we presented a novel virulence gene algorithm (VGA) for the estimation of the extraintestinal virulence potential (VP, pathogenicity risk) of clinically relevant ExPECs and fecal E. coli isolates. The VGA was based on a DNA microarray specific for the ExPEC phenotype (ExPEC pathoarray). This array contained 77 DNA probes homologous with known (e.g. adhesion factors, iron accumulation systems, and toxins) and putative (e.g. genes predictably involved in adhesion, iron uptake, or in metabolic functions) ExPEC virulence determinants. In total, 25 of DNA probes homologous with known virulence factors and 36 of DNA probes representing putative extraintestinal virulence determinants were found at significantly higher frequency in virulent ExPEC isolates than in commensal E. coli strains. We showed that the ExPEC pathoarray and the VGA could be readily used for the differentiation of highly virulent ExPECs both from less virulent ExPEC clones and from commensal E. coli strains as well. Implementing the VGA in a group of unknown ExPECs (n=53) and fecal E. coli isolates (n=37), 83% of strains were correctly identified as extraintestinal virulent or commensal E. coli. Conversely, 15% of clinical ExPECs and 19% of fecal E. coli strains failed to raster into their respective pathogenic and non-pathogenic groups. Clinical data and virulence gene profiles of these strains warranted the estimated VPs; UPEC strains with atypically low risk-ratios were largely isolated from patients with certain medical history, including diabetes mellitus or catheterization, or from elderly patients. In addition, fecal E. coli strains with VPs characteristic for ExPEC were shown to represent the diagnostically important fraction of resident strains of the gut flora with a high potential of causing extraintestinal infections. Interestingly, a large fraction of DNA probes associated with the ExPEC phenotype corresponded to novel DNA sequences without any known function in UTIs and thus represented new genetic markers for the extraintestinal virulence. These DNA probes included unknown DNA sequences originating from the genomic subtractions of four clinical ExPEC isolates as well as from five novel cosmid sequences identified in the UPEC strains HE300 and JS299. The characterized cosmid sequences (pJS332, pJS448, pJS666, pJS700, and pJS706) revealed complex modular DNA structures with known and unknown DNA fragments arranged in a puzzle-like manner and integrated into the common E. coli genomic backbone. Furthermore, cosmid pJS332 of the UPEC strain HE300, which carried a chromosomal virulence gene cluster (iroBCDEN) encoding the salmochelin siderophore system, was shown to be part of a transmissible plasmid of Salmonella enterica. Taken together, the results of this project pointed towards the assumptions that first, (i) homologous recombination, even within coding genes, contributes to the observed mosaicism of ExPEC genomes and secondly, (ii) besides en block transfer of large DNA regions (e.g. chromosomal PAIs) also rearrangements of small DNA modules provide a means of genomic plasticity. The data presented in this project supplemented previous whole genome sequencing projects of E. coli and indicated that each E. coli genome displays a unique assemblage of individual mosaic structures, which enable these strains to successfully colonize and infect different anatomical sites.

Primary total hip arthroplasty for primary osteoarthritis in Finland : A national register based analysis

The first aim of the current study was to evaluate the survival of total hip arthroplasty (THA) in patients aged 55 years and older on a nation-wide level. The second aim was to evaluate, on a nation wide-basis, the geographical variation of the incidence of primary THA for primary OA and also to identify those variables that are possibly associated with this variation. The third aim was to evaluate the effects of hospital volume: on the length of stay, on the numbers of re-admissions and on the numbers of complications of THR on population-based level in Finland. The survival of implants was analysed based on data from the Finnish Arthroplasty Register. The incidence and hospital volume data were obtained from the Hospital Discharge Register. Cementless total hip replacements had a significantly reduced risk of revision for aseptic loosening compared with cemented hip replacements. When revision for any reason was the end point in the survival analyses, there were no significant differences found between the groups. Adjusted incidence ratios of THA varied from 1.9- to 3.0-fold during the study period. Neither the average income within a region nor the morbidity index was associated with the incidence of THA. For the four categories of volume of total hip replacements performed per hospital, the length of the surgical treatment period was shorter for the highest volume group than for the lowest volume group. The odds ratio for dislocations was significantly lower in the high volume group than in the low volume group. In patients who were 55 years of age or older, the survival of cementless total hip replacements was as good as that of the cemented replacements. However, multiple wear-related revisions of the cementless cups indicate that excessive polyethylene wear was a major clinical problem with modular cementless cups. The variation in the long-term rates of survival for different cemented stems was considerable. Cementless proximal porous-coated stems were found to be a good option for elderly patients. When hip surgery was performed on with a large repertoire, the indications to perform THAs due to primary OA were tight. Socio-economic status of the patient had no apparent effect on THA rate. Specialization of hip replacements in high volume hospitals should reduce costs by significantly shortening the length of stay, and may reduce the dislocation rate.

Studies on orographic effects in a numerical weather prediction model

Numerical models, used for atmospheric research, weather prediction and climate simulation, describe the state of the atmosphere over the heterogeneous surface of the Earth. Several fundamental properties of atmospheric models depend on orography, i.e. on the average elevation of land over a model area. The higher is the models' resolution, the more the details of orography directly influence the simulated atmospheric processes. This sets new requirements for the accuracy of the model formulations with respect to the spatially varying orography. Orography is always averaged, representing the surface elevation within the horizontal resolution of the model. In order to remove the smallest scales and steepest slopes, the continuous spectrum of orography is normally filtered (truncated) even more, typically beyond a few gridlengths of the model. This means, that in the numerical weather prediction (NWP) models, there will always be subgridscale orography effects, which cannot be explicitly resolved by numerical integration of the basic equations, but require parametrization. In the subgrid-scale, different physical processes contribute in different scales. The parametrized processes interact with the resolved-scale processes and with each other. This study contributes to building of a consistent, scale-dependent system of orography-related parametrizations for the High Resolution Limited Area Model (HIRLAM). The system comprises schemes for handling the effects of mesoscale (MSO) and small-scale (SSO) orographic effects on the simulated flow and a scheme of orographic effects on the surface-level radiation fluxes. Representation of orography, scale-dependencies of the simulated processes and interactions between the parametrized and resolved processes are discussed. From the high-resolution digital elevation data, orographic parameters are derived for both momentum and radiation flux parametrizations. Tools for diagnostics and validation are developed and presented. The parametrization schemes applied, developed and validated in this study, are currently being implemented into the reference version of HIRLAM.

Molecular studies on LIM-domain protein CRP1

Various intrinsic and external factors are constantly attacking the cells causing damage to DNA and to other cellular structures. Cells in turn have evolved with different kinds of mechanisms to protect against the attacks and to repair the damage. Ultraviolet radiation (UVR) is one of the major environmental genotoxic carcinogens that causes inflammation, mutations, immunosuppression, accelerated aging of the skin and skin cancers. Epidermis is the outermost layer of the skin consisting mostly of keratinocytes, whose primary function is to protect the skin against e.g. UV radiation. LIM domain proteins are a group of proteins involved in regulation of cell growth, damage signalling, cell fate determination and signal transduction. Despite their two zinc fingers, LIM domains do not bind to DNA, but rather mediate protein-protein interactions and function as modular protein binding interfaces. We initially identified CSRP1 as UVR-regulated transcript by using expression profiling. Here we have further studied the regulation and function of CRP1, a representative of cysteine rich protein- family consisting of two LIM domains. We find that CRP1 is increased by UVR in primary human keratinocytes and in normal human skin fibroblasts. Ectopic expression of CRP1 protected the cells against UVR and provided a survival advantage, whereas silencing of CRP1 rendered the cells more photosensitive. Actinic keratosis is a premalignant lesion of skin caused by excess exposure to sunlight and sunburn, which may lead to formation of squamous cell carcinoma. The expression of CRP1 was increased in basal keratinocytes of Actinic keratosis patient specimens suggesting that CRP1 may be increased by constant exposure to UVR and may provide survival advantage for the cells also in vivo. In squamous cell carcinoma, CRP1 was only expressed in the fibroblasts surrounding the tumour. Moreover, we found that ectopic expression of CRP1 suppresses cell proliferation. Transforming growth factor beta (TGFbeta) is a multifunctional cytokine that regulates several functions in cell including growth, apoptosis and differentiation, and plays important roles in pathological disorders like cancer and fibrosis. We found that TGFbeta-signalling pathway regulates CRP1 at protein, but not at transcriptional level. The increase was mediated both through Smad and non-Smad signalling pathways involving MAPK/p38. Furthermore, we found that TGFbeta-mediated increase in CRP1 was associated with myofibroblast differentiation, and that CRP1 was significantly more expressed in idiopathic pulmonary fibrosis as compared to normal lung specimens. Since cell contractility is a distinct feature of myofibroblasts, and CRP1 is associated with actin cytoskeleton, we studied the role of CRP1 in cell contractility. CRP1 was found to localize to stress fibres that mediate contractility and to mediate myofibroblast contraction. These studies identify CRP1 as a stress responsive and cytokine regulated cytoskeletal protein that participates in pathological processes involved in fibrotic diseases and cancer.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.