Wood-derived biomaterials for biomedical applications

Driven by the global trend in the sustainable economy development and environmental concerns, the exploring of plant-derived biomaterials or biocomposites for potential biomedical and/or pharmaceutical applications has received tremendous attention. Therefore, the work of this thesis is dedicated to high-value and high-efficiency utilization of plant-derived materials, with the focus on cellulose and hemicelluloses in the field of biomedical applications in a novel biorefinery concept. The residual cellulose of wood processing waste, sawdust, was converted into cellulose nanofibrils (CNFs) with tunable surface charge density and geometric size through 2,2,6,6-tetramethylpiperidinyloxy (TEMPO)-mediated oxidation and mechanical defibrillation. The sawdust-based CNFs and its resultant free-standing films showed comparable or even better mechanical properties than those from a commercial bleached kraft pulp at the same condition, demonstrating the feasibility of producing CNFs and films thereof with outstanding mechanical properties from birch sawdust by a process incorporated into a novel biorefinery platform recovering also polymeric hemicelluloses for other applications. Thus, it is providing an efficient route to upgrade sawdust waste to valuable products. The surface charge density and geometric size of the CNFs were found to play key roles in the stability of the CNF suspension, as well as the gelling properties, swelling behavior, mechanical stiffness, morphology and microscopic structural properties, and biocompatibility of CNF-based materials (i.e. films, hydrogels, and aerogels). The CNFs with tunable surface chemistry and geometric size was found promising applications as transparent and tough barrier materials or as reinforcing additive for production of biocomposites. The CNFs was also applied as structural matrices for the preparation of biocomposites possessing electrical conductivity and antimicrobial activity by in situ polymerization and coating of polypyrrole, and incorporation of silver nanoparticles, which make the material possible for potential wound healing application. The CNF-based matrices (films, hydrogels, and aerogels) with tunable structural and mechanical properties and biocompatibility were further prepared towards an application as 3D scaffolds in tissue engineering. The structural and mechanical strength of the CNF matrices could be tuned by controlling the charge density of the nanocellulose, as well as the pH and temperature values of the hydrogel formation conditions. Biological tests revealed that the CNF scaffolds could promote the survival and proliferation of tumor cells, and enhance the transfection of exogenous DNA into the cells, suggesting the usefulness of the CNF-based 3D matrices in supporting crucial cellular processes during cell growth and proliferation. The CNFs was applied as host materials to incorporate biomolecules for further biomedical application. For example, to investigate how the biocompatibility of a scaffold is influenced by its mechanical and structural properties, these properties of CNF-based composite matrices were controlled by incorporation of different hemicelluloses (O-acetyl galactoglucomanan (GGM), xyloglucan (XG), and xylan) into CNF hydrogel networks in different ratios and using two different approaches. The charge density of the CNFs, the incorporated hemicellulose type and amount, and the swelling time of the hydrogels were found to affect the pore structure, the mechanical strength, and thus the cells growth in the composite hydrogel scaffolds. The mechanical properties of the composite hydrogels were found to have an influence on the cell viability during the wound healing relevant 3T3 fibroblast cell culture. The thusprepared CNF composite hydrogels may work as promising scaffolds in wound healing application to provide supporting networks and to promote cells adhesion, growth, and proliferation.

Surface Studies of Thiolate Adsorbates on Some Metals

The results and discussions in this thesis are based on my studies about selfassembled thiol layers on gold, platinum, silver and copper surfaces. These kinds of layers are two-dimensional, one molecule thick and covalently organized at the surface. They are an easy way to modify surface properties. Self-assembly is today an intensive research field because of the promise it holds for producing new technology at nanoscale, the scale of atoms and molecules. These kinds of films have applications for example, in the fields of physics, biology, engineering, chemistry and computer science. Compared to the extensive literature concerning self-assembled monolayers (SAMs) on gold, little is known about the structure and properties of thiolbased SAMs on other metals. In this thesis I have focused on thiol layers on gold, platinum, silver and copper substrates. These studies can be regarded as a basic study of SAMs. Nevertheless, an understanding of the physical and chemical nature of SAMs allows the correlation between atomic structure and macroscopic properties. The results can be used as a starting point for many practical applications. X-ray photoelectron spectroscopy (XPS) and synchrotron radiation excited high resolution photoelectron spectroscopy (HR-XPS) together with time-offlight secondary ion mass spectrometry (ToF-SIMS) were applied to investigate thin organic films formed by the spontaneous adsorption of molecules on metal surfaces. Photoelectron spectroscopy was the main method used in these studies. In photoelectron spectroscopy, the sample is irradiated with photons and emitted photoelectrons are energy-analyzed. The obtained spectra give information about the atomic composition of the surface and about the chemical state of the detected elements. It is widely used in the study of thin layers and is a very powerful tool for this purpose. Some XPS results were complemented with ToF-SIMS measurements. It provides information on the chemical composition and molecular structure of the samples. Thiol (1-Dodecanethiol, CH3(CH2)11SH) solution was used to create SAMs on metal substrates. Uniform layers were formed on most of the studied metal surfaces. On platinum, surface aligned molecules were also detected in investigations by XPS and ToF-SIMS. The influence of radiation on the layer structure was studied, leading to the conclusion that parts of the hydrocarbon chains break off due to radiation and the rest of the layer is deformed. The results obtained showed differences depending on the substrate material. The influence of oxygen on layer formation was also studied. Thiol molecules were found to replace some of the oxygen from the metal surfaces.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

Structural studies on enzymes of biotechnological and biomedical interest

Structural studies of proteins aim at elucidating the atomic details of molecular interactions in biological processes of living organisms. These studies are particularly important in understanding structure, function and evolution of proteins and in defining their roles in complex biological settings. Furthermore, structural studies can be used for the development of novel properties in biomolecules of environmental, industrial and medical importance. X-ray crystallography is an invaluable tool to obtain accurate and precise information about the structure of proteins at the atomic level. Glutathione transferases (GSTs) are amongst the most versatile enzymes in nature. They are able to catalyze a wide variety of conjugation reactions between glutathione (GSH) and non-polar components containing an electrophilic carbon, nitrogen or sulphur atom. Plant GSTs from the Tau class (a poorly characterized class) play an important role in the detoxification of xenobiotics and stress tolerance. Structural studies were performed on a Tau class fluorodifen-inducible glutathione transferase from Glycine max (GmGSTU4-4) complexed with GSH (2.7 Å) and a product analogue Nb-GSH (1.7 Å). The three-dimensional structure of the GmGSTU4-4-GSH complex revealed that GSH binds in different conformations in the two subunits of the dimer: in an ionized form in one subunit and a non-ionized form in the second subunit. Only the ionized form of the substrate may lead to the formation of a catalytically competent complex. Structural comparison between the GSH and Nb-GSH bound complexes revealed significant differences with respect to the hydrogen-bonding, electrostatic interaction pattern, the upper part of -helix H4 and the C-terminus of the enzyme. These differences indicate an intrasubunit modulation between the G-and Hsites suggesting an induced-fit mechanism of xenobiotic substrate binding. A novel binding site on the surface of the enzyme was also revealed. Bacterial type-II L-asparaginases are used in the treatment of haematopoietic diseases such as acute lymphoblastic leukaemia (ALL) and lymphomas due to their ability to catalyze the conversion of L-asparagine to L-aspartate and ammonia. Escherichia coli and Erwinia chrysanthemi asparaginases are employed for the treatment of ALL for over 30 years. However, serious side-effects affecting the liver and pancreas have been observed due to the intrinsic glutaminase activity of the administered enzymes. Structural studies on Helicobacter pylori L-asparaginase (HpA) were carried out in an effort to discover novel L-asparaginases with potential chemotherapeutic utility in ALL treatment. Detailed analysis of the active site geometry revealed structurally significant differences between HpA and other Lasparaginases that may be important for the biological activities of the enzyme and could be further exploited in protein engineering efforts.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Development and characterization of thin printed films for gas sensing applications

The monitoring and control of hydrogen sulfide (H2S) level is of great interest for a wide range of application areas including food quality control, defense and antiterrorist applications and air quality monitoring e.g. in mines. H2S is a very poisonous and flammable gas. Exposure to low concentrations of H2S can result in eye irritation, a sore throat and cough, shortness of breath, and fluid retention in the lungs. These symptoms usually disappear in a few weeks. Long-term, low-level exposure may result in fatigue, loss of appetite, headache, irritability, poor memory, and dizziness. Higher concentrations of 700 - 800 ppm tend to be fatal. H2S has a characteristic smell of rotten egg. However, because of temporary paralysis of olfactory nerves, the smelling capability at concentrations higher than 100 ppm is severely compromised. In addition, volatile H2S is one of the main products during the spoilage of poultry meat in anaerobic conditions. Currently, no commercial H2S sensor is available which can operate under anaerobic conditions and can be easily integrated in the food packaging. This thesis presents a step-wise progress in the development of printed H2S gas sensors. Efforts were made in the formulation, characterization and optimization of functional printable inks and coating pastes based on composites of a polymer and a metal salt as well as a composite of a metal salt and an organic acid. Different processing techniques including inkjet printing, flexographic printing, screen printing and spray coating were utilized in the fabrication of H2S sensors. The dispersions were characterized by measuring turbidity, surface tension, viscosity and particle size. The sensing films were characterized using X-ray photoelectron spectroscopy, X-ray diffraction, atomic force microscopy and an electrical multimeter. Thin and thick printed or coated films were developed for gas sensing applications with the aim of monitoring the H2S concentrations in real life applications. Initially, a H2S gas sensor based on a composite of polyaniline and metal salt was developed. Both aqueous and solvent-based dispersions were developed and characterized. These dispersions were then utilized in the fabrication of roll-to-roll printed H2S gas sensors. However, the humidity background, long term instability and comparatively lower detection limit made these sensors less favourable for real practical applications. To overcome these problems, copper acetate based sensors were developed for H2S gas sensing. Stable inks with excellent printability were developed by tuning the surface tension, viscosity and particle size. This enabled the formation of inkjet-printed high quality copper acetate films with excellent sensitivity towards H2S. Furthermore, these sensors showed negligible humidity effects and improved selectivity, response time, lower limit of detection and coefficient of variation. The lower limit of detection of copper acetate based sensors was further improved to sub-ppm level by incorporation of catalytic gold nano-particles and subsequent plasma treatment of the sensing film. These sensors were further integrated in an inexpensive wirelessly readable RLC-circuit (where R is resistor, L is inductor and C is capacitor). The performance of these sensors towards biogenic H2S produced during the spoilage of poultry meat in the modified atmosphere package was also demonstrated in this thesis. This serves as a proof of concept that these sensors can be utilized in real life applications.

Usability and Security in Medication. Administration Applications

The traditional process of filling the medicine trays and dispensing the medicines to the patients in the hospitals is manually done by reading the printed paper medicinechart. This process can be very strenuous and error-prone, given the number of sub-tasksinvolved in the entire workflow and the dynamic nature of the work environment.Therefore, efforts are being made to digitalise the medication dispensation process byintroducing a mobile application called Smart Dosing application. The introduction ofthe Smart Dosing application into hospital workflow raises security concerns and callsfor security requirement analysis. This thesis is written as a part of the smart medication management project at EmbeddedSystems Laboratory, A˚bo Akademi University. The project aims at digitising the medicine dispensation process by integrating information from various health systems, and making them available through the Smart Dosing application. This application is intended to be used on a tablet computer which will be incorporated on the medicine tray. The smart medication management system include the medicine tray, the tablet device, and the medicine cups with the cup holders. Introducing the Smart Dosing application should not interfere with the existing process carried out by the nurses, and it should result in minimum modifications to the tray design and the workflow. The re-designing of the tray would include integrating the device running the application into the tray in a manner that the users find it convenient and make less errors while using it. The main objective of this thesis is to enhance the security of the hospital medicine dispensation process by ensuring the security of the Smart Dosing application at various levels. The methods used for writing this thesis was to analyse how the tray design, and the application user interface design can help prevent errors and what secure technology choices have to be made before starting the development of the next prototype of the Smart Dosing application. The thesis first understands the context of the use of the application, the end-users and their needs, and the errors made in everyday medication dispensation workflow by continuous discussions with the nursing researchers. The thesis then gains insight to the vulnerabilities, threats and risks of using mobile application in hospital medication dispensation process. The resulting list of security requirements was made by analysing the previously built prototype of the Smart Dosing application, continuous interactive discussions with the nursing researchers, and an exhaustive state-of-the-art study on security risks of using mobile applications in hospital context. The thesis also uses Octave Allegro method to make the readers understand the likelihood and impact of threats, and what steps should be taken to prevent or fix them. The security requirements obtained, as a result, are a starting point for the developers of the next iteration of the prototype for the Smart Dosing application.