Influence of surface functionalization on the behavior of silica nanoparticles in biological systems

Personalized nanomedicine has been shown to provide advantages over traditional clinical imaging, diagnosis, and conventional medical treatment. Using nanoparticles can enhance and clarify the clinical targeting and imaging, and lead them exactly to the place in the body that is the goal of treatment. At the same time, one can reduce the side effects that usually occur in the parts of the body that are not targets for treatment. Nanoparticles are of a size that can penetrate into cells. Their surface functionalization offers a way to increase their sensitivity when detecting target molecules. In addition, it increases the potential for flexibility in particle design, their therapeutic function, and variation possibilities in diagnostics. Mesoporous nanoparticles of amorphous silica have attractive physical and chemical characteristics such as particle morphology, controllable pore size, and high surface area and pore volume. Additionally, the surface functionalization of silica nanoparticles is relatively straightforward, which enables optimization of the interaction between the particles and the biological system. The main goal of this study was to prepare traceable and targetable silica nanoparticles for medical applications with a special focus on particle dispersion stability, biocompatibility, and targeting capabilities. Nanoparticle properties are highly particle-size dependent and a good dispersion stability is a prerequisite for active therapeutic and diagnostic agents. In the study it was shown that traceable streptavidin-conjugated silica nanoparticles which exhibit a good dispersibility could be obtained by the suitable choice of a proper surface functionalization route. Theranostic nanoparticles should exhibit sufficient hydrolytic stability to effectively carry the medicine to the target cells after which they should disintegrate and dissolve. Furthermore, the surface groups should stay at the particle surface until the particle has been internalized by the cell in order to optimize cell specificity. Model particles with fluorescently-labeled regions were tested in vitro using light microscopy and image processing technology, which allowed a detailed study of the disintegration and dissolution process. The study showed that nanoparticles degrade more slowly outside, as compared to inside the cell. The main advantage of theranostic agents is their successful targeting in vitro and in vivo. Non-porous nanoparticles using monoclonal antibodies as guiding ligands were tested in vitro in order to follow their targeting ability and internalization. In addition to the targeting that was found successful, a specific internalization route for the particles could be detected. In the last part of the study, the objective was to clarify the feasibility of traceable mesoporous silica nanoparticles, loaded with a hydrophobic cancer drug, being applied for targeted drug delivery in vitro and in vivo. Particles were provided with a small molecular targeting ligand. In the study a significantly higher therapeutic effect could be achieved with nanoparticles compared to free drug. The nanoparticles were biocompatible and stayed in the tumor for a longer time than a free medicine did, before being eliminated by renal excretion. Overall, the results showed that mesoporous silica nanoparticles are biocompatible, biodegradable drug carriers and that cell specificity can be achieved both in vitro and in vivo.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

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.

Cell Model Systems in Characterizing Alpha2-Adrenoceptors as Drug Targets.

The three alpha2-adrenoceptor (alpha2-AR) subtypes belong to the G protein-coupled receptor superfamily and represent potential drug targets. These receptors have many vital physiological functions, but their actions are complex and often oppose each other. Current research is therefore driven towards discovering drugs that selectively interact with a specific subtype. Cell model systems can be used to evaluate a chemical compound's activity in complex biological systems. The aim of this thesis was to optimize and validate cell-based model systems and assays to investigate alpha2-ARs as drug targets. The use of immortalized cell lines as model systems is firmly established but poses several problems, since the protein of interest is expressed in a foreign environment, and thus essential components of receptor regulation or signaling cascades might be missing. Careful cell model validation is thus required; this was exemplified by three different approaches. In cells heterologously expressing alpha2A-ARs, it was noted that the transfection technique affected the test outcome; false negative adenylyl cyclase test results were produced unless a cell population expressing receptors in a homogenous fashion was used. Recombinant alpha2C-ARs in non-neuronal cells were retained inside the cells, and not expressed in the cell membrane, complicating investigation of this receptor subtype. Receptor expression enhancing proteins (REEPs) were found to be neuronalspecific adapter proteins that regulate the processing of the alpha2C-AR, resulting in an increased level of total receptor expression. Current trends call for the use of primary cells endogenously expressing the receptor of interest; therefore, primary human vascular smooth muscle cells (SMC) expressing alpha2-ARs were tested in a functional assay monitoring contractility with a myosin light chain phosphorylation assay. However, these cells were not compatible with this assay due to the loss of differentiation. A rat aortic SMC cell line transfected to express the human alpha2B-AR was adapted for the assay, and it was found that the alpha2-AR agonist, dexmedetomidine, evoked myosin light chain phosphorylation in this model.

Tautomerism and Fragmentation of Biologically Active Hetero Atom (O, N)-Containing Acyclic and Cyclic Compounds Under Electron Ionization

In this thesis a total of 86 compounds containing the hetero atoms oxygen and nitrogen were studied under electron ionization mass spectrometry (EIMS). These compounds are biologically active and were synthesized by various research groups. The main attention of this study was paid on the fragmentations related to different tautomeric forms of 2- phenacylpyridines, 2-phenacylquinolines, 8-aryl-3,4-dioxo-2H,8H-6,7-dihydroimidazo- [2,1-c][1,2,4]triazines and aryl- and benzyl-substituted 2,3-dihydroimidazo[1,2-a]pyrimidine-5,7-(1H,6H)-diones. Also regio/stereospecific effects on fragmentations of pyrrolo- and isoindoloquinazolinones and naphthoxazine, naphthpyrrolo-oxazinone and naphthoxazino-benzoxazine derivatives were screened. Results were compared with NMR data, when available. The first part of thesis consists of theory and literature review of different types of tautomerism and fragmentation mechanisms in EIMS. The effects of tautomerism in biological systems are also briefly reviewed. In the second part of the thesis the own results of the author, based on six publications,are discussed. For 2-phenacylpyridines and 2-phenacylquinolines the correlation of different Hammett substituent constants to the relative abundances (RA) or total ion currents (% TIC) of selected ions were investigated. Although it was not possible to assign most of the ions formed unambiguously to the different tautomers, the linear fits of their RAs and % TICs can be related to changing contributions of different tautomeric forms. For dioxoimidazotriazines and imidazopyrimidinediones the effects of substituents were rather weak. The fragmentations were also found useful for obtaining structural information. Some stereoisomeric pairs of pyrrolo- and isoindoloquinazolines and regiomeric pairs of naphtoxazine derivatives showed clear differences in thir mass spectra. Some mechanisms are suggested for their fragmentations.

The Significance of Hydrogen Bonding Interactions in the Cleavage of RNA

RNA is essential for all living organisms. It has important roles in protein synthesis, controlling gene expression as well as catalyzing biological reactions. Chemically RNA is a very stable molecule, although in biological systems many agents catalyze the cleavage of RNA, such as naturally occurring enzymes and ribozymes. Much effort has been put in the last decades in developing highly active artificial ribonucleases since such molecules could have potential in the therapeutic field and provide tools for molecular biology. Several potential catalysts have emerged, but usually detailed cleavage mechanism remains unresolved. This thesis is aimed at clarifying mechanistic details of the cleavage and isomerization of RNA by using simpler nucleoside models of RNA. The topics in the experimental part cover three different studies, one concerning the mechanism of catalysis by large ribozymes, one dealing with the reactivity of modified and unmodified RNA oligonucleotides and one showing an efficient catalysis of the cleavage and isomerization of an RNA phosphodiester bond by a dinuclear metal ion complex. A review of the literature concerning stabilization of the phosphorane intermediate of the hydrolysis and isomerization of RNA phosphodiester bond is first presented. The results obtained in the experimental work followed by mechanistic interpretations are introduced in the second part of the thesis. Especially the significance of hydrogen bonding interactions is discussed.

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.

Development of Craniofacial Bone Defect Reconstruction Implant Based on Fibre-Reinforced Composite with Photopolymerisable Resin Systems. Experimental studies in vitro and in vivo.

Reconstruction of defects in the craniomaxillofacial (CMF) area has mainly been based on bone grafts or metallic fixing plates and screws. Particularly in the case of large calvarial and/or craniofacial defects caused by trauma, tumours or congenital malformations, there is a need for reliable reconstruction biomaterials, because bone grafts or metallic fixing systems do not completely fulfill the criteria for the best possible reconstruction methods in these complicated cases. In this series of studies, the usability of fibre-reinforced composite (FRC) was studied as a biostable, nonmetallic alternative material for reconstructing artificially created bone defects in frontal and calvarial areas of rabbits. The experimental part of this work describes the different stages of the product development process from the first in vitro tests with resin-impregnated fibrereinforced composites to the in vivo animal studies, in which this FRC was tested as an implant material for reconstructing different size bone defects in rabbit frontal and calvarial areas. In the first in vitro study, the FRC was polymerised in contact with bone or blood in the laboratory. The polymerised FRC samples were then incubated in water, which was analysed for residual monomer content by using high performance liquid chromatography (HPLC). It was found that this in vitro polymerisation in contact with bone and blood did not markedly increase the residual monomer leaching from the FRC. In the second in vitro study, different adhesive systems were tested in fixing the implant to bone surface. This was done to find an alternative implant fixing system to screws and pins. On the basis of this study, it was found that the surface of the calvarial bone needed both mechanical and chemical treatments before the resinimpregnated FRC could be properly fixed onto it. In three animal studies performed with rabbit frontal bone defects and critical size calvarial bone defect models, biological responses to the FRC implants were evaluated. On the basis of theseevaluations, it can be concluded that the FRC, based on E-glass (electrical glass) fibres forming a porous fibre veil enables the ingrowth of connective tissues to the inner structures of the material, as well as the bone formation and mineralization inside the fibre veil. Bone formation could be enhanced by using bioactive glass granules fixed to the FRC implants. FRC-implanted bone defects healed partly; no total healing of defects was achieved. Biological responses during the follow-up time, at a maximum of 12 weeks, to resin-impregnated composite implant seemed to depend on the polymerization time of the resin matrix of the FRC. Both of the studied resin systems used in the FRC were photopolymerised and the heat-induced postpolymerisation was used additionally.

Development of Measurement Systems in Scientific Research: Case Study

In recent years, technological advancements in microelectronics and sensor technologies have revolutionized the field of electrical engineering. New manufacturing techniques have enabled a higher level of integration that has combined sensors and electronics into compact and inexpensive systems. Previously, the challenge in measurements was to understand the operation of the electronics and sensors, but this has now changed. Nowadays, the challenge in measurement instrumentation lies in mastering the whole system, not just the electronics. To address this issue, this doctoral dissertation studies whether it would be beneficial to consider a measurement system as a whole from the physical phenomena to the digital recording device, where each piece of the measurement system affects the system performance, rather than as a system consisting of small independent parts such as a sensor or an amplifier that could be designed separately. The objective of this doctoral dissertation is to describe in depth the development of the measurement system taking into account the challenges caused by the electrical and mechanical requirements and the measurement environment. The work is done as an empirical case study in two example applications that are both intended for scientific studies. The cases are a light sensitive biological sensor used in imaging and a gas electron multiplier detector for particle physics. The study showed that in these two cases there were a number of different parts of the measurement system that interacted with each other. Without considering these interactions, the reliability of the measurement may be compromised, which may lead to wrong conclusions about the measurement. For this reason it is beneficial to conceptualize the measurement system as a whole from the physical phenomena to the digital recording device where each piece of the measurement system affects the system performance. The results work as examples of how a measurement system can be successfully constructed to support a study of sensors and electronics.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.