21 resultados para LINKING BIOLOGY

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Abstract

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Abstract The research problem in the thesis deals with improving the responsiveness and efficiency of logistics service processes between a supplier and its customers. The improvement can be sought by customizing the services and increasing the coordination of activities between the different parties in the supply chain. It is argued that to achieve coordination the parties have to have connections on several levels. In the framework employed in this research, three contexts are conceptualized at which the linkages can be planned: 1) the service policy context, 2) the process coordination context, and 3) the relationship management context. The service policy context consists of the planning methods by which a supplier analyzes its customers' logistics requirements and matches them with its own operational environment and efficiency requirements. The main conclusion related to the service policy context is that it is important to have a balanced selection of both customer-related and supplier-related factors in the analysis. This way, while the operational efficiency is planned a sufficient level of service for the most important customers is assured. This kind of policy planning involves taking multiple variables into the analysis, and there is a need to develop better tools for this purpose. Some new approaches to deal with this are presented in the thesis.The process coordination context and the relationship management context deal with the issues of how the implementation of the planned service policies can be facilitated in an inter-organizational environment. Process coordination includes typically such mechanisms as control rules, standard procedures and programs, but inhighly demanding circumstances more integrative coordination mechanisms may be necessary. In the thesis the coordination problems in third-party logistics relationship are used as an example of such an environment. Relationship management deals with issues of how separate companies organize their relationships to improve the coordination of their common processes. The main implication related to logistics planning is that by integrating further at the relationship level, companies can facilitate the use of the most efficient coordination mechanisms and thereby improve the implementation of the selected logistics service policies. In the thesis, a case of a logistics outsourcing relationship is used to demonstrate the need to address the relationship issues between the service provider andthe service buyer before the outsourcing can be done.The dissertation consists of eight research articles and a summarizing report. The principal emphasis in the articles is on the service policy planning context, which is the main theme of six articles. Coordination and relationship issues are specifically addressed in two of the papers.

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In general, models of ecological systems can be broadly categorized as ’top-down’ or ’bottom-up’ models, based on the hierarchical level that the model processes are formulated on. The structure of a top-down, also known as phenomenological, population model can be interpreted in terms of population characteristics, but it typically lacks an interpretation on a more basic level. In contrast, bottom-up, also known as mechanistic, population models are derived from assumptions and processes on a more basic level, which allows interpretation of the model parameters in terms of individual behavior. Both approaches, phenomenological and mechanistic modelling, can have their advantages and disadvantages in different situations. However, mechanistically derived models might be better at capturing the properties of the system at hand, and thus give more accurate predictions. In particular, when models are used for evolutionary studies, mechanistic models are more appropriate, since natural selection takes place on the individual level, and in mechanistic models the direct connection between model parameters and individual properties has already been established. The purpose of this thesis is twofold. Firstly, a systematical way to derive mechanistic discrete-time population models is presented. The derivation is based on combining explicitly modelled, continuous processes on the individual level within a reproductive period with a discrete-time maturation process between reproductive periods. Secondly, as an example of how evolutionary studies can be carried out in mechanistic models, the evolution of the timing of reproduction is investigated. Thus, these two lines of research, derivation of mechanistic population models and evolutionary studies, are complementary to each other.

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High-throughput screening of cellular effects of RNA interference (RNAi) libraries is now being increasingly applied to explore the role of genes in specific cell biological processes and disease states. However, the technology is still limited to specialty laboratories, due to the requirements for robotic infrastructure, access to expensive reagent libraries, expertise in high-throughput screening assay development, standardization, data analysis and applications. In the future, alternative screening platforms will be required to expand functional large-scale experiments to include more RNAi constructs, allow combinatorial loss-of-function analyses (e.g. genegene or gene-drug interaction), gain-of-function screens, multi-parametric phenotypic readouts or comparative analysis of many different cell types. Such comprehensive perturbation of gene networks in cells will require a major increase in the flexibility of the screening platforms, throughput and reduction of costs. As an alternative for the conventional multi-well based high-throughput screening -platforms, here the development of a novel cell spot microarray method for production of high density siRNA reverse transfection arrays is described. The cell spot microarray platform is distinguished from the majority of other transfection cell microarray techniques by the spatially confined array layout that allow highly parallel screening of large-scale RNAi reagent libraries with assays otherwise difficult or not applicable to high-throughput screening. This study depicts the development of the cell spot microarray method along with biological application examples of high-content immunofluorescence and phenotype based cancer cell biological analyses focusing on the regulation of prostate cancer cell growth, maintenance of genomic integrity in breast cancer cells, and functional analysis of integrin protein-protein interactions in situ.

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Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

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Prostate cancer initially responds to hormone-based therapeutics such as anti-androgen treatment or chemotherapeutics but eventually becomes resistant. Novel treatment options are therefore urgently needed. This thesis study applied a high-throughput screen of 4910 known drugs and drug-like small molecules to identify compounds that selectively inhibit growth of prostate cancer cells. In addition, the mechanisms underlying the cellular sensitivity to potent cancer selective compounds were addressed. Surprisingly, many of the compounds currently used in the clinics or studied in clinical trials were not cancer-selective. Only four drugs, aldehyde dehydrogenase inhibitor disulfiram (Antabus), antibiotic ionophore monensin, histone deacetylase inhibitor tricostatin A and fungicide thiram inhibited prostate cancer cell growth at nanomolar concentrations without major effects on non-malignant prostate epithelial cells. Disulfiram, monensin and a structurally similar compound to monensin, salinomycin, induced oxidative stress and inhibited aldehyde dehydrogenase activity. Moreover, monensin and salinomycin reduced androgen receptor signalling and steroidogenesis, enforced cell differentiation and reduced the overall levels of cancer stem cells. Taken together, novel and potentially prostate cancer-selective therapeutic agents were identified in this study, including the description of a multitude of intoxicating mechanisms such as those relating to oxidative stress. The results provide novel insights into prostate cancer biology and exemplify useful means of considering novel approaches to cancer treatment.

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Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

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Value-based selling is a salesperson behavioral mode which concentrates on generating superior customer value. Although service dominant logic emphasizes customer value as a central tenet for achieving strategic objectives, sales management literature has predominantly circumvented the subject matter of customer value. The purpose of this thesis is to demonstrate the distinctiveness and positive sales performance outcomes of value-based selling. Additionally, performance outcomes of value-based selling are contrasted with other key sales behaviors, selling skills and motivational orientations. As a part of this thesis, large-scale survey of 730 respondents was collected. The survey was tailored for the needs of a value-based selling research group led by Ph.D. Harri Terho. The research group used convenience sampling to select the salespeople of 25 medium- and large-scale companies in Finland which currently either practice value-based selling or consider developing these activities. This thesis contains three key findings: value-based selling is established as a distinct sales behavior, it relates directly and positively to salesperson performance and it explains the link between customer-oriented selling and salesperson performance. Value-based selling relates to salesperson performance especially in the following GICS-sectors: energy, industrials and materials. However, relationship selling relates to performance strongest in the energy sector and adaptive selling in industrials sector. In sum, it is evident that actively crafting customer value is a successful sales behavior in many business-to-business marketing environments while other sales behaviors, excluding customer-oriented selling, still uphold their significance.