Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of interest because its occurrence may affect the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to the phenomenon, generating a database of historical observations on the regional behavior of ionospheric scintillation. The analysis of such data is very challenging, since it consists of time-varying measurements of many variables which are heterogeneous in nature and with possibly many missing values, recorded over extensive time periods. There is a need to introduce alternative intuitive strategies that contribute to experts acquiring further knowledge from the ionospheric scintillation data. Such challenges motivated a study on the applicability of visualization techniques to support tasks of identification of relevant attributes in the study of the behavior of phenomena described by multiple time-varying variables, of which the ionospheric scintillation is a good example. In particular, this thesis introduces a visual analytics framework, named TV-MV Analytics, that supports exploratory tasks on time-varying multivariate data and was developed following the requirements of experts on ionospheric scintillation from the Faculty of Science and Technology of UNESP at Presidente Prudente, Brazil. TV-MV Analytics provides an interactive visual exploration loop to analysts inspecting the behavior of multiple variables at different temporal scales, through temporal representations associated with clustering and multidimensional projection techniques. Analysts can also assess how different feature sub-spaces contribute to characterizing a certain behavior, where they may direct the analysis process and include their domain knowledge in the exploratory analysis. We also illustrate the application of TV-MV Analytics on multivariate time-varying data sets from three alternative application domains. Experimental results indicate the proposed solutions show good potential on assisting time-varying multivariate data mining tasks, since it reduces the effort required from experts to gain deeper insight into the historical behavior of the variables describing a phenomenon or domain. / A cintilação ionosférica é uma variação rápida na amplitude e/ou na fase dos sinais de rádio que viajam através da ionosfera. Este fenômeno espacial e variante no tempo é de grande interesse, pois pode afetar a qualidade de recepção dos sinais de satélite. Receptores especializados em regiões estratégicas podem rastrear múltiplas variáveis relacionadas ao fenômeno, gerando um banco de dados de observações históricas sobre o comportamento regional da cintilação. O estudo do comportamento da cintilação é desafiador, uma vez que requer a análise extensiva de dados multivariados e variantes no tempo, coletados por longos períodos. Medições são registradas continuamente, e são de natureza heterogênea, compreendendo múltiplas variáveis de diferentes categorias e possivelmente com muitos valores faltantes. Portanto, existe a necessidade de introduzir estratégias alternativas, eficientes e intuitivas, que contribuam para a adquisição de conhecimento, a partir dos dados, por especialistas que estudam a cintilação ionosférica. Tais desafios motivaram o estudo da aplicabilidade de técnicas de visualização para apoiar tarefas de identificação de atributos relevantes no estudo do comportamento de fenômenos ou domínios que envolvem múltiplas variáveis, como a cintilação. Em particular, esta tese introduz um arcabouço visual, o qual foi denominado TV-MV Analytics, que apoia tarefas de análise exploratória sobre dados multivariados e variáveis no tempo, inspirado em requisitos de especialistas no estudo da cintilação, vinculados à Faculdade de Ciências e Tecnologia da UNESP de Presidente Prudente, Brasil. O TV-MV Analytics fornece aos analistas um ciclo de interativo de exploração que apoia a inspeção do comportamento temporal de múltiplas variáveis, em diferentes escalas temporais, por meio de representações visuais temporais associadas a técnicas de agrupamento e de projeção multidimensional. Também permite avaliar como diferentes sub-espaços de atributos caracterizam um determinado comportamento, podendo direcionar o processo de análise e inserir seu conhecimento do domínio no processo de análise exploratória. As funcionalidades do TV-MV Analytics também são ilustradas em dados variantes no tempo oriundos de outros três domínios de aplicação. Os resultados experimentais indicaram que as soluções propostas têm bom potencial em tarefas de mineração de dados multivariados e variantes no tempo, uma vez que reduz o esforço e contribui para os especialistas obterem informações detalhadas sobre o comportamento histórico das variáveis que descrevem um determinado fenômeno ou domínio.

<p>The present thesis proposes new methods for obtaining objective and accurate diagnoses in modern healthcare. Non-invasive techniques have been used to examine or diagnose three different medical conditions, namely neuropathy among diabetics, radiotherapy induced erythema (skin redness) among breast cancer patients and diagnoses of cutaneous malignant melanoma. The techniques used were Near-InfraRed spectroscopy (NIR), Multi Frequency Bio Impedance Analysis of whole body (MFBIA-body), Laser Doppler Imaging (LDI) and Digital Colour Photography (DCP).</p><p>The neuropathy for diabetics was studied in papers I and II. The first study was performed on diabetics and control subjects of both genders. A separation was seen between males and females and therefore the data had to be divided in order to obtain good models. NIR spectroscopy was shown to be a viable technique for measuring neuropathy once the division according to gender was made. The second study on diabetics, where MFBIA-body was added to the analysis, was performed on males exclusively. Principal component analysis showed that healthy reference subjects tend to separate from diabetics. Also, diabetics with severe neuropathy separate from persons less affected.</p><p>The preliminary study presented in paper III was performed on breast cancer patients in order to investigate if NIR, LDI and DCP were able to detect radiotherapy induced erythema. The promising results in the preliminary study motivated a new and larger study. This study, presented in papers IV and V, intended to investigate the measurement techniques further but also to examine the effect that two different skin lotions, Essex and Aloe vera have on the development of erythema. The Wilcoxon signed rank sum test showed that DCP and NIR could detect erythema, which is developed during one week of radiation treatment. LDI was able to detect erythema developed during two weeks of treatment. None of the techniques could detect any differences between the two lotions regarding the development of erythema.</p><p>The use of NIR to diagnose cutaneous malignant melanoma is presented as unpublished results in this thesis. This study gave promising but inconclusive results. NIR could be of interest for future development of instrumentation for diagnosis of skin cancer.</p>

<p>New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds.</p><p>The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled.</p><p>The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The <i>in silico</i> solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process. </p>

<p>A trend in natural science and especially in analytical chemistry is the increasing need for analysis of a large number of complex samples with low analyte concentrations. Biological samples (urine, blood, plasma, cerebral spinal fluid, tissue etc.) are often suitable for analysis with liquid separation mass spectrometry (LS-MS), resulting in two-way data tables (time vs. m/z). Such biological 'fingerprints' taken for all samples in a study correspond to a large amount of data. Detailed characterization requires a high sampling rate in combination with high mass resolution and wide mass range, which presents a challenge in data handling and exploration. This thesis describes methods for managing and exploring large data sets made up of such detailed 'fingerprints' (represented as data matrices). </p><p>The methods were implemented as scripts and functions in Matlab, a wide-spread environment for matrix manipulations. A single-file structure to hold the imported data facilitated both easy access and fast manipulation. Routines for baseline removal and noise reduction were intended to reduce the amount of data without loosing relevant information. A tool for visualizing and exploring single runs was also included. When comparing two or more 'fingerprints' they usually have to be aligned due to unintended shifts in analyte positions in time and m/z. A PCA-like multivariate method proved to be less sensitive to such shifts, and an ANOVA implementation made it easier to find systematic differences within the data sets.</p><p>The above strategies and methods were applied to complex samples such as plasma, protein digests, and urine. The field of application included urine profiling (paracetamole intake; beverage effects), peptide mapping (different digestion protocols) and search for potential biomarkers (appendicitis diagnosis) . The influence of the experimental factors was visualized by PCA score plots as well as clustering diagrams (dendrograms).</p>

<p>Transport into and across the cells of the human body is a prerequisite for the pharmacological action of drugs. Passive membrane permeability and active transport mechanisms are major determinants of the intestinal absorption of drugs, as well as of the distribution to target tissues and the subsequent metabolism and excretion from the body. In this thesis, the role of ATP-binding cassette (ABC) transporters and passive permeability on drug absorption and disposition was investigated. Particular emphasis was placed on defining the molecular properties important for these transport mechanisms. </p><p>The influence of different transport pathways on predictions of intestinal drug absorption was investigated using experimental models of different complexity. Experimental models that include the paracellular pathway gave improved predictions of intestinal drug absorption, especially for incompletely absorbed drugs. Further, the inhibition of the ABC transporters breast cancer resistance protein (BCRP/ABCG2) and multidrug-resistance associated protein 2 (MRP2/ABCC2) was experimentally investigated using structurally diverse datasets that were representative of orally administered drugs. A large number of previously unknown inhibitors were identified among registered drugs, but their clinical relevance for drug-drug interactions and drug-induced toxicity remains to be determined. The majority of the inhibitors affected all three major ABC transporters BCRP, MRP2 and P-glycoprotein (P gp/ABCB1), and these multi-specific inhibitors were found to be enriched in highly lipophilic weak bases. </p><p>To summarize, the present work has led to an increased knowledge of the molecular features of importance for ABC transporter inhibition and passive membrane permeability. Previously unknown ABC transporter inhibitors were identified and predictive computational models were developed for the different drug transport mechanisms. These could be valuable tools to assist in the prioritization of experimental efforts in early drug discovery.</p>

New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds. The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled. The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The in silico solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process.

Transport into and across the cells of the human body is a prerequisite for the pharmacological action of drugs. Passive membrane permeability and active transport mechanisms are major determinants of the intestinal absorption of drugs, as well as of the distribution to target tissues and the subsequent metabolism and excretion from the body. In this thesis, the role of ATP-binding cassette (ABC) transporters and passive permeability on drug absorption and disposition was investigated. Particular emphasis was placed on defining the molecular properties important for these transport mechanisms. The influence of different transport pathways on predictions of intestinal drug absorption was investigated using experimental models of different complexity. Experimental models that include the paracellular pathway gave improved predictions of intestinal drug absorption, especially for incompletely absorbed drugs. Further, the inhibition of the ABC transporters breast cancer resistance protein (BCRP/ABCG2) and multidrug-resistance associated protein 2 (MRP2/ABCC2) was experimentally investigated using structurally diverse datasets that were representative of orally administered drugs. A large number of previously unknown inhibitors were identified among registered drugs, but their clinical relevance for drug-drug interactions and drug-induced toxicity remains to be determined. The majority of the inhibitors affected all three major ABC transporters BCRP, MRP2 and P-glycoprotein (P gp/ABCB1), and these multi-specific inhibitors were found to be enriched in highly lipophilic weak bases. To summarize, the present work has led to an increased knowledge of the molecular features of importance for ABC transporter inhibition and passive membrane permeability. Previously unknown ABC transporter inhibitors were identified and predictive computational models were developed for the different drug transport mechanisms. These could be valuable tools to assist in the prioritization of experimental efforts in early drug discovery.

Liquid chromatography (LC) coupled to mass spectrometry (MS) offers highly selective and sensitive analysis of a wide variety of compounds. However, the use of hyphenated experimental set-ups implies that many parameters may have an effect on the studied response. Therefore, in order to determine optimized experimental conditions it is of vital importance to incorporate systematic procedures during method development. In this thesis, a generic stepwise optimization strategy is proposed that aims at high chromatographic quality, as well as high mass spectrometric response. The procedure comprises (i) screening experiments to identify the most important parameters, (ii) LC studies to ensure sufficient chromatographic separation, (iii) extended infusion experiments in order to maximize precursor signal(s), and in the case of tandem MS (iv) extended infusion experiments to determine optimal conditions for collision induced dissociation and when applicable also ion trap settings. Experimental design and response surface methodology is used throughout the procedure. Further, the general applicability of LC-MS is demonstrated in this thesis. Specifically, a novel quantitative column-switched LC-MS method for ferrichrome, ferrichrysin and ferricrocin determination is presented. Using the method it was shown how the siderophore content varies with depth in podzolic soil profiles in the north and south of Sweden. The parallel approach using LC coupled to both inductively coupled plasma (ICP) mass spectrometry, and electrospray ionization (ESI) tandem MS is also evaluated as a tool to identify unknown siderophores in a sample. Additionally, different trypsin digestion schemes used for LC-ESI-MS peptide mapping were compared. By multivariate data analysis, it was clearly shown that the procedures tested induce differences that are detectable using LC-ESI-MS. Finally, the glutathione S-transferase catalyzed bioactivation of the prodrug azathioprine was verified using LC-MS.

Drug transport across cells and cell membranes in the human body is crucial for the pharmacological effect of drugs. Active transport governed by transport proteins plays an important role in this process. A vast number of transport proteins with a wide tissue distribution have been identified during the last 15 years. Several important examples of their role in drug disposition and drug-drug interactions have been described to date. Investigation of drug-drug interactions at the transport protein level are therefore of increasing interest to the academic, industrial and regulatory research communities. The gene expression of transport proteins involved in drug transport was investigated in the jejunum, liver, kidney and colon to better understand their influence on the ADMET properties of drugs. In addition, the gene and protein expression of transport proteins in cell lines, widely used for predictions of drug transport and metabolism, was examined. The substrate and inhibitor heterogeneity of many transport proteins makes it difficult to foresee whether the transport proteins will cause drug-drug interactions. Therefore, in vitro assays for OCT1 and OATP1B1, among the highest expressed transport proteins in human liver, were developed to allow investigation of the inhibitory patterns of these proteins. These assays were used to investigate two data sets, consisting of 191 and 135 registered drugs and drug-like molecules for the inhibition of OCT1 and OATP1B1, respectively. Numerous new inhibitors of the transport proteins were identified in the data sets and the properties governing inhibition were determined. Further, antidepressant drugs and statins displayed strong inhibition of OCT1 and OATP1B1, respectively. The inhibition data was used to develop predictive in silico models for each of the two transport proteins. The highly polymorphic nature of some transport proteins has been shown to affect drug response and may lead to an increased risk of drug-drug interactions, and therefore, the OCT1 in vitro assay was used to study the effect of common genetic variants of OCT1 on drug inhibition and drug-drug interactions. The results indicated that OCT1 variants with reduced function were more susceptible to inhibition. Further, a drug-drug interaction of potential clinical significance in the genetic OCT1 variant M420del was proposed. In summary, gene expression of transport proteins was investigated in human tissues and cell lines. In vitro assays for two of the highest expressed liver transport proteins were used to identify previously unknown SLC transport protein inhibitors and to develop predictive in silico models, which may detect previously known drug-drug interactions and enable new ones to be identified at the transport protein level. In addition, the effect of genetic variation on inhibition of the OCT1 was investigated.

During the last three decades, a number of studies based on national environmental monitoring data have found increased concentrations of total organic carbon (TOC) in surface waters in much of the northern hemisphere including Sweden. There are many hypothesis of what has been the main cause of this trend, including changes in land use, decreased atmospheric deposition of acidifying compounds and climate change. Different hypothesis may have different implications for quantifying pre-industrial levels and for future predictions of TOC concentrations, which in turn will have different implications for water classification according to the European Water Framework Directive, water management and drinking water treatment. To analyse the long term effects of industrialisation and climate change on TOC in surface waters there is a need for long term time series of data. Since environmental monitoring data in Sweden only extends back to the mid-1980s, other techniques must be used in order to reconstruct data. In this study, sediment cores from 17 lakes along a climatic and deposition gradient in Sweden were collected and analysed with visible near infrared spectroscopy (VNIRS), an analytical technique that makes it possible to reconstruct historic surface water concentrations of TOC to pre-industrial conditions. A previous study with VNIRS showed that TOC concentrations declined in response to sulfate deposition until peak sulfur deposition in 1980, and thereafter increased as a result of sharp reductions of sulfate emissions. It was noted that the rate of increase of TOC after 1980 was faster than the rate of decrease due to sulfate deposition before 1980. The purpose of this study was therefore to explore the hypothesis that increasing TOC concentrations have not only been due to recovery from acidification, but also due to changes in climate. It was possible to analyse the long term effects of industrialisation and climate change on surface water TOC by analysing the reconstructed TOC data together with climate data from the beginning of the 1900s, modelled data of atmospheric sulfate deposition and environmental monitoring data, with uni- and multivariate analysis methods. It was found that the recent increase in TOC concentrations could be explained by both decreases in acidifying atmospheric deposition and increased precipitation, while temperature may have a decreasing effect on TOC. It was also found that the rate of increase of TOC-concentrations has been faster in the colder northern parts of Sweden and slower in the warmer south. The results imply that TOC concentrations will continue to rise to unpreceded levels and should be of concern for drinking water treatment plants that will need to adapt their treatment processes in the future. / Under de senaste tre årtiondena har ett flertal studier baserade på data från nationella miljöövervakningsprogram rapporterat ökande koncentrationer av organiskt kol (TOC) i ytvatten på norra halvklotet inklusive Sverige. Det finns många hypoteser om vad som ligger bakom trenden, till exempel förändringar i markanvändning, minskad atmosfärisk deposition av försurande ämnen och klimatförändringar. Olika förklaringar till vad som ligger bakom den ökande trenden ger konsekvenser vid kvantifiering av förindustriella nivåer och för förutsägelser om framtida koncentrationer, vilket i sin tur ger konsekvenser för vattenklassificering enligt Ramvattendirektivet, vattenförvaltning och dricksvattenberedning. För att kunna analysera de långsiktiga effekterna av industrialisering och klimatförändringar på TOC i ytvatten behövs långa tidsserier av data. Då den svenska miljöövervakningen endast sträcker sig tillbaka till mitten av 1980-talet måste andra tekniker användas för att rekonstruera data. I den här studien har sedimentproppar från 17 sjöar längs en klimat- och depositionsgradient analyserats med visible near infrared spektroskopi (VNIRS), en analysteknik som gör det möjligt att rekonstruera TOC-koncentrationer i ytvatten till förindustriell tid. En tidigare studie med VNIRS visade att TOC-koncentrationer sjönk till följd av försurande nedfall fram till 1980 då nedfallet kraftigt minskade, varefter koncentrationer av TOC började öka. Det noterades i studien att ökningen av TOC efter 1980 varit snabbare än vad minskningen var före 1980 på grund av försurande nedfall. Syftet med den här studien var därför att undersöka hypotesen att den senaste tidens ökning av TOC inte bara berott på minskat nedfall av försurande ämnen, utan även på grund av klimatförändringar. Det var möjligt att undersöka de långsiktiga effekterna av industrialisering och klimatförändringar på TOC i ytvatten genom att analysera rekonstruerad TOC data, klimatdata från början av 1900-talet, modellerad sulfatdepositionsdata och miljöövervakningsdata med uni- och multivariata analysmetoder. Resultaten visade att den senaste tidens ökning av TOC kunde förklaras med både en minskande deposition av försurande ämnen och en ökad nederbörd, medan ökande temperaturer kan ha haft en minskande effekt på TOC. Resultaten visade även att förändringshastigheten av TOC-koncentrationer varit snabbare i de norra, kalla delarna av Sverige och långsammare i de varmare södra. Resultaten indikerar att koncentrationer av TOC kommer att öka till nivåer som aldrig tidigare skådats, vilket är något vattenreningsverk kommer att behöva anpassa sina reningsmetoder till i framtiden.