Influenza in children – Diagnosis, treatment and prevention

Background: The burden of influenza on children is substantial. Although mortality rates are low, the incidence of influenza is highest in children, among whom also complications are frequent. A more accurate recognition of influenza in children could enable the rational use of antiviral drugs and help to avoid unnecessary courses of antibiotics. Limited data exists on the efficacy of oseltamivir treatment and the trivalent inactivated influenza vaccine (TIV) in children. Aims and methods: We sought for signs and symptoms that could help clinicians to diagnose influenza on clinical grounds in a case-control study in children <13 years of age. We further assessed the feasibility of different diagnostics methods during the early stage of the illness in children aged 1-3 years. The efficacy of early oseltamivir treatment (started <24h from the onset of symptoms) was evaluated in a randomized controlled trial (RCT) conducted in children 1-3 years of age, and the effectiveness of TIV to prevent laboratory-confirmed influenza was determined in a prospective, observational cohort study conducted among children aged 9 months to 3 years of age. Results: Fever was the only symptom predicting influenza in children. The sensitivity of conventionally used laboratory methods to detect influenza during the first 24h of illness was 92%. The sensitivity of the influenza rapid test in the same setting was 90% for influenza A and 25% for influenza B. Early oseltamivir treatment shortened the duration of the illness in children with influenza A by 3.5-4.0 days, but no efficacy was observed against influenza B. The effectiveness of TIV was 84% against the wellmatched influenza A, while no effectiveness against the mismatched influenza B was observed. Conclusions: Laboratory diagnostics are needed for a reliable diagnosis of influenza in children and were found sensitive already during the early stage of the illness. Early oseltamivir treatment was highly effective against influenza A, but no efficacy was seen against influenza B. TIV is effective also in young children if a good match between the vaccine and circulating strain is achieved.

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.

AMB system for high-speed motors using automatic commissioning

The general trend towards increasing e ciency and energy density drives the industry to high-speed technologies. Active Magnetic Bearings (AMBs) are one of the technologies that allow contactless support of a rotating body. Theoretically, there are no limitations on the rotational speed. The absence of friction, low maintenance cost, micrometer precision, and programmable sti ness have made AMBs a viable choice for highdemanding applications. Along with the advances in power electronics, such as signi cantly improved reliability and cost, AMB systems have gained a wide adoption in the industry. The AMB system is a complex, open-loop unstable system with multiple inputs and outputs. For normal operation, such a system requires a feedback control. To meet the high demands for performance and robustness, model-based control techniques should be applied. These techniques require an accurate plant model description and uncertainty estimations. The advanced control methods require more e ort at the commissioning stage. In this work, a methodology is developed for an automatic commissioning of a subcritical, rigid gas blower machine. The commissioning process includes open-loop tuning of separate parts such as sensors and actuators. The next step is to apply a system identi cation procedure to obtain a model for the controller synthesis. Finally, a robust model-based controller is synthesized and experimentally evaluated in the full operating range of the system. The commissioning procedure is developed by applying only the system components available and a priori knowledge without any additional hardware. Thus, the work provides an intelligent system with a self-diagnostics feature and an automatic commissioning.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Detection of Pathologic Changes Following Traumatic Brain Injury Using Magnetic Resonance Imaging

Background: Approximately two percent of Finns have sequels after traumatic brain injury (TBI), and many TBI patients are young or middle-aged. The high rate of unemployment after TBI has major economic consequences for society, and traumatic brain injury often has remarkable personal consequences, as well. Structural imaging is often needed to support the clinical TBI diagnosis. Accurate early diagnosis is essential for successful rehabilition and, thus, may also influence the patient’s outcome. Traumatic axonal injury and cortical contusions constitute the majority of traumatic brain lesions. Several studies have shown magnetic resonance imaging (MRI) to be superior to computed tomography (CT) in the detection of these lesions. However, traumatic brain injury often leads to persistent symptoms even in cases with few or no findings in conventional MRI. Aims and methods: The aim of this prospective study was to clarify the role of conventional MRI in the imaging of traumatic brain injury, and to investigate how to improve the radiologic diagnostics of TBI by using more modern diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) techniques. We estimated, in a longitudinal study, the visibility of the contusions and other intraparenchymal lesions in conventional MRI at one week and one year after TBI. We used DWI-based measurements to look for changes in the diffusivity of the normal-appearing brain in a case-control study. DTI-based tractography was used in a case-control study to evaluate changes in the volume, diffusivity, and anisotropy of the long association tracts in symptomatic TBI patients with no visible signs of intracranial or intraparenchymal abnormalities on routine MRI. We further studied the reproducibility of different tools to identify and measure white-matter tracts by using a DTI sequence suitable for clinical protocols. Results: Both the number and extent of visible traumatic lesions on conventional MRI diminished significantly with time. Slightly increased diffusion in the normal-appearing brain was a common finding at one week after TBI, but it was not significantly associated with the injury severity. Fractional anisotropy values, that represent the integrity of the white-matter tracts, were significantly diminished in several tracts in TBI patients compared to the control subjects. Compared to the cross-sectional ROI method, the tract-based analyses had better reproducibility to identify and measure white-matter tracts of interest by means of DTI tractography. Conclusions: As conventional MRI is still applied in clinical practice, it should be carried out soon after the injury, at least in symptomatic patients with negative CT scan. DWI-related brain diffusivity measurements may be used to improve the documenting of TBI. DTI tractography can be used to improve radiologic diagnostics in a symptomatic TBI sub-population with no findings on conventional MRI. Reproducibility of different tools to quantify fibre tracts vary considerably, which should be taken into consideration in the clinical DTI applications.

PET Imaging of Osteomyelitis. Feasibility of 18F-FDG, 68Ga-Chloride and 68Ga-DOTAVAP-P1 Tracers in Staphylococcal Bone Infections

Due to technical restrictions of the database system the title of the thesis does not show corretly on this page. Numbers in the title are in superscript. Please see the PDF-file for correct title. ---- Osteomyelitis is a progressive inflammatory disease of bone and bone marrow that results in bone destruction due to an infective microorganism, most frequently Staphylococcus aureus. Orthopaedic concern relates to the need for reconstructive and trauma-related surgical procedures in the fast grow¬ing population of fragile, aged patients, who have an increased susceptibility to surgical site infections. Depending on the type of osteomyelitis, infection may be acute or a slowly progressing, low-grade infection. Peri-implant infections lead to implant loosening. The emerging antibiotic resistance of com¬mon pathogens further complicates the situation. With current imaging methods, significant limitations exist in the diagnosing of osteomyelitis and implant-related infections. Positron emission tomography (PET) with a glucose analogue, 18F-fluoro¬deoxyglucose (18F-FDG), seems to facilitate a more accurate diagnosis of chronic osteomyelitis. The method is based on the increased glucose consumption of activated inflammatory cells. Unfortunately, 18F-FDG accumulates also in sterile inflammation regions and causes false-positive findings, for exam¬ple, due to post-operative healing processes. Therefore, there is a clinical need for new, more infection-specific tracers. In addition, it is still unknown why 18F-FDG PET imaging is less accurate in the detec¬tion of periprosthetic joint infections, most frequently due to Staphylococcus epidermidis. This doctoral thesis focused on testing novel PET tracers (68Ga-chloride and 68Ga-DOTAVAP-P1) for early detections of bone infections and evaluated the role of pathogen-related factors in the appli¬cations of 18F-FDG PET in the diagnostics of bone infections. For preclinical models of S. epidermidis and S. aureus bone/implant infections, the significance of the causative pathogen was studied with respect to 18F-FDG uptake. In a retrospective analysis of patients with confirmed bone infections, the significance of the presence or absence of positive bacterial cultures on 18F-FDG uptake was evalu¬ated. 18F-FDG and 68Ga-chloride resulted in a similar uptake in S. aureus osteomyelitic bones. However, 68Ga-chloride did not show uptake in healing bones, and therefore it may be a more-specific tracer in the early post-operative or post-traumatic phase. 68Ga-DOTAVAP-P1, a novel synthetic peptide bind¬ing to vascular adhesion protein 1 (VAP-1), was able to detect the phase of inflammation in healing bones, but the uptake of the tracer was elevated also in osteomyelitis. Low-grade peri-implant infec¬tions due to S. epidermidis were characterized by a low uptake of 18F-FDG, which reflects the virulence of the causative pathogen and the degree of leukocyte infiltration. In the clinical study, no relationship was found between the level of 18F-FDG uptake and the presence of positive or negative bacterial cul¬tures. Thus 18F-FDG PET may help to confirm metabolically active infection process in patients with culture-negative, histologically confirmed, low-grade osteomyelitis.

Magnetic Resocance Imaging Methods in the Follow-up of Multiple Sclerosis and in Farby Disease

Multiple sclerosis (MS) is a chronic immune-mediated inflammatory disorder of the central nervous system. MS is the most common disabling central nervous system (CNS) disease of young adults in the Western world. In Finland, the prevalence of MS ranges between 1/1000 and 2/1000 in different areas. Fabry disease (FD) is a rare hereditary metabolic disease due to mutation in a single gene coding α-galactosidase A (alpha-gal A) enzyme. It leads to multi-organ pathology, including cerebrovascular disease. Currently there are 44 patients with diagnosed FD in Finland. Magnetic resonance imaging (MRI) is commonly used in the diagnostics and follow-up of these diseases. The disease activity can be demonstrated by occurrence of new or Gadolinium (Gd)-enhancing lesions in routine studies. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced MR sequences which can reveal pathologies in brain regions which appear normal on conventional MR images in several CNS diseases. The main focus in this study was to reveal whether whole brain apparent diffusion coefficient (ADC) analysis can be used to demonstrate MS disease activity. MS patients were investigated before and after delivery and before and after initiation of diseasemodifying treatment (DMT). In FD, DTI was used to reveal possible microstructural alterations at early timepoints when excessive signs of cerebrovascular disease are not yet visible in conventional MR sequences. Our clinical and MRI findings at 1.5T indicated that post-partum activation of the disease is an early and common phenomenon amongst mothers with MS. MRI seems to be a more sensitive method for assessing MS disease activity than the recording of relapses. However, whole brain ADC histogram analysis is of limited value in the follow-up of inflammatory conditions in a pregnancy-related setting because the pregnancy-related physiological effects on ADC overwhelm the alterations in ADC associated with MS pathology in brain tissue areas which appear normal on conventional MRI sequences. DTI reveals signs of microstructural damage in brain white matter of FD patients before excessive white matter lesion load can be observed on conventional MR scans. DTI could offer a valuable tool for monitoring the possible effects of enzyme replacement therapy in FD.

Toimitusketjun diagnostiikkatyökalu

Tässä työssä luodaan diagnostiikkatyökalu toimitusketjun nykytilan määritystä varten. Sen tavoitteena on muodostaa tieteellisen kirjallisuuden pohjalta selkeästi esitettävissä oleva prosessimuotoinen työkalu, jota voidaan käyttää mahdollisimman monessa erilaisessa toimitusketjussa. Lisäksi sen tulee olla sopiva yrityksen ulkopuolisen toimijan, esimerkiksi konsultin, käytettäväksi. Työssä käydään ensin läpi toimitusketjun diagnosoinnin ja sen suorituskyvyn mittauksen teoriaa. Sen jälkeen muodostetaan näiden avulla tavoitteita vastaava nelivaiheinen työkalu, joka ulottuu aina projektin suunnittelusta mittaukseen, kehitystoimenpiteiden tunnistamiseen ja niiden esittämiseen yrityksen johdolle.

Hydrometallurgical recovery of valuable metals from secondary raw materials

Wastes and side streams in the mining industry and different anthropogenic wastes often contain valuable metals in such concentrations their recovery may be economically viable. These raw materials are collectively called secondary raw materials. The recovery of metals from these materials is also environmentally favorable, since many of the metals, for example heavy metals, are hazardous to the environment. This has been noticed in legislative bodies, and strict regulations for handling both mining and anthropogenic wastes have been developed, mainly in the last decade. In the mining and metallurgy industry, important secondary raw materials include, for example, steelmaking dusts (recoverable metals e.g. Zn and Mo), zinc plant residues (Ag, Au, Ga, Ge, In) and waste slurry from Bayer process alumina production (Ga, REE, Ti, V). From anthropogenic wastes, waste electrical and electronic equipment (WEEE), among them LCD screens and fluorescent lamps, are clearly the most important from a metals recovery point of view. Metals that are commonly recovered from WEEE include, for example, Ag, Au, Cu, Pd and Pt. In LCD screens indium, and in fluorescent lamps, REEs, are possible target metals. Hydrometallurgical processing routes are highly suitable for the treatment of complex and/or low grade raw materials, as secondary raw materials often are. These solid or liquid raw materials often contain large amounts of base metals, for example. Thus, in order to recover valuable metals, with small concentrations, highly selective separation methods, such as hydrometallurgical routes, are needed. In addition, hydrometallurgical processes are also seen as more environmental friendly, and they have lower energy consumption, when compared to pyrometallurgical processes. In this thesis, solvent extraction and ion exchange are the most important hydrometallurgical separation methods studied. Solvent extraction is a mainstream unit operation in the metallurgical industry for all kinds of metals, but for ion exchange, practical applications are not as widespread. However, ion exchange is known to be particularly suitable for dilute feed solutions and complex separation tasks, which makes it a viable option, especially for processing secondary raw materials. Recovering valuable metals was studied with five different raw materials, which included liquid and solid side streams from metallurgical industries and WEEE. Recovery of high purity (99.7%) In, from LCD screens, was achieved by leaching with H2SO4, extracting In and Sn to D2EHPA, and selectively stripping In to HCl. In was also concentrated in the solvent extraction stage from 44 mg/L to 6.5 g/L. Ge was recovered as a side product from two different base metal process liquors with Nmethylglucamine functional chelating ion exchange resin (IRA-743). Based on equilibrium and dynamic modeling, a mechanism for this moderately complex adsorption process was suggested. Eu and Y were leached with high yields (91 and 83%) by 2 M H2SO4 from a fluorescent lamp precipitate of waste treatment plant. The waste also contained significant amounts of other REEs such as Gd and Tb, but these were not leached with common mineral acids in ambient conditions. Zn was selectively leached over Fe from steelmaking dusts with a controlled acidic leaching method, in which the pH did not go below, but was held close as possible to, 3. Mo was also present in the other studied dust, and was leached with pure water more effectively than with the acidic methods. Good yield and selectivity in the solvent extraction of Zn was achieved by D2EHPA. However, Fe needs to be eliminated in advance, either by the controlled leaching method or, for example, by precipitation. 100% Pure Mo/Cr product was achieved with quaternary ammonium salt (Aliquat 336) directly from the water leachate, without pH adjustment (pH 13.7). A Mo/Cr mixture was also obtained from H2SO4 leachates with hydroxyoxime LIX 84-I and trioctylamine (TOA), but the purities were 70% at most. However with Aliquat 336, again an over 99% pure mixture was obtained. High selectivity for Mo over Cr was not achieved with any of the studied reagents. Ag-NaCl solution was purified from divalent impurity metals by aminomethylphosphonium functional Lewatit TP-260 ion exchange resin. A novel preconditioning method, named controlled partial neutralization, with conjugate bases of weak organic acids, was used to control the pH in the column to avoid capacity losses or precipitations. Counter-current SMB was shown to be a better process configuration than either batch column operation or the cross-current operation conventionally used in the metallurgical industry. The raw materials used in this thesis were also evaluated from an economic point of view, and the precipitate from a waste fluorescent lamp treatment process was clearly shown to be the most promising.

Capillary electrophoresis for monitoring of carboxylic, phenolic and amino acids in bioprocesses

Bioprocess technology is a multidisciplinary industry that combines knowledge of biology and chemistry with process engineering. It is a growing industry because its applications have an important role in the food, pharmaceutical, diagnostics and chemical industries. In addition, the current pressure to decrease our dependence on fossil fuels motivates new, innovative research in the replacement of petrochemical products. Bioprocesses are processes that utilize cells and/or their components in the production of desired products. Bioprocesses are already used to produce fuels and chemicals, especially ethanol and building-block chemicals such as carboxylic acids. In order to enable more efficient, sustainable and economically feasible bioprocesses, the raw materials must be cheap and the bioprocesses must be operated at optimal conditions. It is essential to measure different parameters that provide information about the process conditions and the main critical process parameters including cell density, substrate concentrations and products. In addition to offline analysis methods, online monitoring tools are becoming increasingly important in the optimization of bioprocesses. Capillary electrophoresis (CE) is a versatile analysis technique with no limitations concerning polar solvents, analytes or samples. Its resolution and efficiency are high in optimized methods creating a great potential for rapid detection and quantification. This work demonstrates the potential and possibilities of CE as a versatile bioprocess monitoring tool. As a part of this study a commercial CE device was modified for use as an online analysis tool for automated monitoring. The work describes three offline CE analysis methods for the determination of carboxylic, phenolic and amino acids that are present in bioprocesses, and an online CE analysis method for the monitoring of carboxylic acid production during bioprocesses. The detection methods were indirect and direct UV, and laser-induced frescence. The results of this work can be used for the optimization of bioprocess conditions, for the development of more robust and tolerant microorganisms, and to study the dynamics of bioprocesses.

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.

From Molecular Blocks To Bioanalytical Assays: Combining Lanthanide Luminescence and Bioaffinity Binders for Protein Detection

Measuring protein biomarkers from sample matrix, such as plasma, is one of the basic tasks in clinical diagnostics. Bioanalytical assays used for the measuring should be able to measure proteins with high sensitivity and specificity. Furthermore, multiplexing capability would also be advantageous. To ensure the utility of the diagnostic test in point-of-care setting, additional requirements such as short turn-around times, ease-ofuse and low costs need to be met. On the other hand, enhancement of assay sensitivity could enable exploiting novel biomarkers, which are present in very low concentrations and which the current immunoassays are unable to measure. Furthermore, highly sensitive assays could enable the use of minimally invasive sampling. In the development of high-sensitivity assays the label technology and affinity binders are in pivotal role. Additionally, innovative assay designs contribute to the obtained sensitivity and other characteristics of the assay as well as its applicability. The aim of this thesis was to study the impact of assay components on the performance of both homogeneous and heterogeneous assays. Applicability of two different lanthanide-based label technologies, upconverting nanoparticles and switchable lanthanide luminescence, to protein detection was explored. Moreover, the potential of recombinant antibodies and aptamers as alternative affinity binders were evaluated. Additionally, alternative conjugation chemistries for production of the labeled binders were studied. Different assay concepts were also evaluated with respect to their applicability to point-of-care testing, which requires simple yet sensitive methods. The applicability of upconverting nanoparticles to the simultaneous quantitative measurement of multiple analytes using imaging-based detection was demonstrated. Additionally, the required instrumentation was relatively simple and inexpensive compared to other luminescent lanthanide-based labels requiring time-resolved measurement. The developed homogeneous assays exploiting switchable lanthanide luminescence were rapid and simple to perform and thus applicable even to point-ofcare testing. The sensitivities of the homogeneous assays were in the picomolar range, which are still inadequate for some analytes, such as cardiac troponins, requiring ultralow limits of detection. For most analytes, however, the obtained limits of detection were sufficient. The use of recombinant antibody fragments and aptamers as binders allowed site-specific and controlled covalent conjugation to construct labeled binders reproducibly either by using chemical modification or recombinant technology. Luminescent lanthanide labels were shown to be widely applicable for protein detection in various assay setups and to contribute assay sensitivity.

NIR-Vis Up-Conversion Luminescence in the Yb3+,Er3+ Doped Y2O2S, ZrO2, and NaYF4 Nanomaterials

Since the discovery of the up-conversion phenomenon, there has been an ever increasing interest in up-converting phosphors in which the absorption of two or more low energy photons is followed by emission of a higher energy photon. Most up-conversion luminescence materials operate by using a combination of a trivalent rare earth (lanthanide) sensitizer (e.g. Yb or Er) and an activator (e.g. Er, Ho, Tm or Pr) ion in a crystal lattice. Up-converting phosphors have a variety of potential applications as lasers and displays as well as inks for security printing (e.g. bank notes and bonds). One of the most sophisticated applications of lanthanide up-conversion luminescence is probably in medical diagnostics. However, there are some major problems in the use of photoluminescence based on the direct UV excitation in immunoassays. Human blood absorbs strongly UV radiation as well as the emission of the phosphor in the visible. A promising way to overcome the problems arising from the blood absorption is to use a long wavelength excitation and benefit from the up-conversion luminescence. Since there is practically no absorption by the whole-blood in the near IR region, it has no capability for up-conversion in the excitation wavelength region of the conventional up-converting phosphor based on the Yb3+ (sensitizer) and Er3+ (activator) combination. The aim of this work was to prepare nanocrystalline materials with high red (and green) up-conversion luminescence efficiency for use in quantitative whole-blood immunoassays. For coupling to biological compounds, nanometer-sized (crystallite size below 50 nm) up-converting phosphor particles are required. The nanocrystalline ZrO2:Yb3+,Er3+, Y2O2S:Yb3+,Er3+, NaYF4:Yb3+,Er3+ and NaRF4-NaR’F4 (R: Y, Yb, Er) materials, prepared with the combustion, sol-gel, flux, co-precipitation and solvothermal synthesis, were studied using the thermal analysis, FT-IR spectroscopy, transmission electron microscopy, EDX spectroscopy, XANES/EXAFS measurements, absorption spectroscopy, X-ray powder diffraction, as well as up-conversion and thermoluminescence spectroscopies. The effect of the impurities of the phosphors, crystallite size, as well as the crystal structure on the up-conversion luminescence intensity was analyzed. Finally, a new phenomenon, persistent up-conversion luminescence was introduced and discussed. For efficient use in bioassays, more work is needed to yield nanomaterials with smaller and more uniform crystallite sizes. Surface modifications need to be studied to improve the dispersion in water. On the other hand, further work must be carried out to optimize the persistent up-conversion luminescence of the nanomaterials to allow for their use as efficient immunoassay nanomaterials combining the advantages of both up-conversion and persistent luminescence.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Advanced epithelial ovarian cancer – studies on preoperative [18F] FDG PET/CT and HE4 profile during primary chemotherapy

Epithelial ovarian cancer (EOC) is usually diagnosed in an advanced stage. The prognosis depends highly on the amount of the residual tumor in surgery. In patients with extensive disease, neoadjuvant chemotherapy (NACT) is used to diminish the tumor load before debulking surgery. New non-invasive methods are needed to preoperatively evaluate the disease dissemination and operability. [18F] FDG PET/CT (Positron emission tomography/computed tomography) is a promising method for cancer diagnostics and staging. The biomarker profiles during treatment can predict patient’s outcome. This prospective study included 41 EOC patients, 21 treated with primary surgery and 20 with NACT and interval surgery. The performances of preoperative contrast enhanced PET/CT (PET/ceCT) and diagnostic CT (ceCT) were compared. Perioperative visual estimation of tumor spread was studied in primary and interval surgery. The profile of the serum marker HE4 (Human epididymis 4) during primary chemotherapy was evaluated. In primary surgery, surgical findings were found to form an adequate reference standard for imaging studies. After NACT, the sensitivity for visual estimation of cancer dissemination was significantly worse. Preoperative PET/ceCT was more effective than ceCT alone in detecting extra-abdominal disease spread. The high number of supradiaphragmatic lymph node metastases detected by PET/ceCT at the time of diagnosis brings new insight in EOC spread patterns. The sensitivity of both PET/CT and ceCT remained modest in intra-abdominal areas important to operability. The HE4 profile was in concordance with the CA125 profile during primary chemotherapy. Its role in the evaluation of EOC chemotherapy response will be clarified in further studies.