Every year approximately 2800 Swedes are diagnosed with malignant melanoma, the form of cancer that is most rapidly increasing in incidence in the Western world. The earlier we can identify and diagnose a malignant melanoma, the better is the prognosis. In Sweden, 155 000 benign naevi, harmless skin tumours or moles, are surgically excised each year, many of them because melanoma cannot be dismissed by non-invasive methods. The excisions result in substantial medical costs and cause unrest and suffering of the individual patient. For untrained physicians, it is often difficult to make an accurate diagnosis of melanoma, thus a tool that could help to strengthen the diagnosis of suspected melanomas would be highly valuable. This thesis describes the development and assessment of a non-invasive method for early skin cancer detection. Using near infrared (NIR) and skin impedance spectroscopy, healthy and diseased skin of various subjects was examined to develop a new instrument for detecting malignant melanoma. Due to the complex nature of skin and the numerous variables involved, the spectroscopic data were analysed multivariately using Principal Component Analysis (PCA) and partial leas square discriminant analysis (PLS-DA). The reproducibility of the measurements was determined by calculating Scatter Values (SVs), and the significance of separations between overlapping groups in score plots was determined by calculating intra-model distances. The studies indicate that combining skin impedance and NIR spectroscopy measurements adds value, therefore a new probe-head for simultaneous NIR and skin impedance measurements was introduced. Using both spectroscopic techniques it was possible to separate healthy skin at one body location from healthy skin at another location due to the differences in skin characteristics at various body locations. In addition, statistically significant differences between overlapping groups of both age and gender in score plots were detected. However, the differences in skin characteristics at different body locations had stronger effects on the measurements than both age and gender. Intake of coffee and alcohol prior to measurement did not significantly influence the outcome data. Measurements on dysplastic naevi were significantly separated in a score plot and the influence of diseased skin was stronger than that of body location. This was confirmed in a study where measurements were performed on 12 malignant melanomas, 19 dysplastic naevi and 19 benign naevi. The malignant melanomas were significantly separated from both dysplastic naevi and benign naevi. Overall, the presented findings show that the instrument we have developed provides fast, reproducible measurements, capable of distinguishing malignant melanoma from dysplastic naevi and benign naevi non-invasively with 83% sensitivity and 95% specificity. Thus, the results are highly promising and the instrument appears to have high potential diagnostic utility.

Flax is often considered a total utilization crop because of the potential to extract value from two distinct products - seeds and stem fibres. However, very little genetic information is available on flax fibre genetics in comparison to oil improvement studies. In order to gain a detailed understanding of genetic control of the fibre concentration and search for the possibilities of developing dual purpose flax lines using both seed oil and stem fibre, the following studies were initiated: The first study evaluated the fibre and oil-related traits in a recombinant inbred population derived from a cross between a fibre flax variety Viking and an oilseed flax genotype E1747 over multiple locations under western Canadian field conditions. The study confirmed the presence of a significant genotype by environment interaction (p < 0.01) for fibre concentration indicating selection for this trait will be challenging. However, a lack of significant correlation between fibre and oilseed characteristics in field trials was encouraging and strengthened the hypothesis that breeding dual purpose flax types for western Canada is possible. The study also identified potential recombinant inbred lines (RILs) with enhanced fibre concentration as well as oil characteristics for use in future breeding endeavors. The second study established an anatomical basis for further research into flax fibre improvement by studying differences between the stem anatomy of 14 diverse flax genotypes in the field and under controlled environments such as a growth chamber. The results from the study supported the use of controlled environments for the purpose of quick screening of high fibre containing genotypes, especially at the green capsule stage of plant growth. The results also indicated that it was possible to select high fibre oilseed flax lines based on anatomical markers such as average area of single fibre cells, total fibre area and fibre to stem area ratio. In the third study, 17 simple sequence repeat (SSR) and 2 cleaved amplified polymorphic sequences (CAPS) molecular markers were used to assess the extent of genetic variability in the Viking × E1747 RIL population. CAPS markers LuFAD3A and LuFAD3B had the highest marker trait association (p < 0.0001) with linoleic and linolenic acid concentration. SSR markers such as CV8824, 5B6 and LU32 were found to be associated with plant height, oil concentration and protein concentration respectively using single marker analysis and step wise regression analysis. The molecular study confirmed the importance of Viking × E1747 mapping population in identifying genes/ markers related to both fibre and oilseed related traits in flax. In the fourth study, global transcript profiling using cDNA - based microarrays was performed to identify differentially expressed fibre related transcripts between Viking and E1747. The largest group of transcripts (7 %) found more abundant in Viking relative to E1747 fell under the functional group of cell wall development using gene ontology (GO) analysis. Transcripts such as callose synthases, expansins, cytochrome P450, fasciclin-like arabino galactan proteins and β-galactosidases were highly abundant in Viking relative to E1747. The transcripts more abundant in E1747 relative to Viking were UDP – glucose glucosyltransferase, auxin repressed protein, ubiquitin conjugating enzyme, peroxidases and lipid transfer proteins. Quantitative real time PCR results confirmed the suitability of the microarray platform to accurately discriminate transcript profiles between the two diverse flax types. In conclusion, this research has provided a number of new insights into flax fibre genetics. This information lays the foundation for further genetic studies on flax bast fibres and will complement research on developing dual purpose flax varieties.

A few computational models currently exist to predict heat production and dissipation in tissue when a tumor containing optically-tunable gold nanoparticles such as nanoshells or nanorods is illuminated with near infrared (NIR) laser. The validity of any computational model still needs to be established by experiments before its wide use for various future clinical applications. One of the possible ways to validate the model is through the heat measurements within a phantom made with tissue-equivalent heat-sensitive gel. Currently, there are a few recipes available for this type of gel and the majority of them use severely toxic ingredients. However, none of them seems to perfectly serve the current purposes. Therefore, the primary goal of this thesis work was to develop and characterize two new types of heat-sensitive gels, using relatively non-toxic substances for the in-phantom validation of computational models. Specifically, two novel agar based phantoms, TG1 and TG2, were developed and characterized. The basic optical response of these phantoms at 808 nm NIR light was determined to test their equivalency to human tissue. Thermal damage to the phantoms was quantified by heating them to specific temperatures and obtaining calibration curves to relate temperature and R2 relaxation rates. The phantoms were scanned with magnetic resonance imaging (MRI) to obtain T2 values. TG1 gel, agar and bovine serum albumin (BSA) mixture, was found not to be optically tissue-equivalent. However, TG1 gel demonstrated unambiguous digital response capable of distinguishing temperature of at least 70 °C compared to the sample receiving no heat. Additionally, TG1 gel produced high degree of linearity in the thermal therapy temperature regime (60 - 80 °C). TG2 gel containing agar mixed with BSA and Intralipid has exhibited tissue equivalency based on laser transmission measurements. TG2 gel exhibited heat damage based on T2 values, only when the temperature reaches 80 °C. This digital response is considered less sensitive in view of the fact that BSA starts to undergo denaturing and cause optical density change at approximately 70 °C. Both gels, however, have shown to be thermally stable at temperatures up to 80 °C with no evidence of gel melting being observed.

Zugl.: Dresden, Techn. Univ., Diss., 2009

The evaluation of the soil spatial variability using a fast, robust and cheap tool is one of the key steps towards the implementation of Precision Agriculture (PA) successfully. Soil organic carbon (OC), soil total nitrogen (TN) and soil moisture content (MC) are needed to be monitored for both agriculture and environmental applications. The literature has proven that visible and near infrared (vis-NIR) spectroscopy to be a quick, cheap and robust tool to acquire information about key soil properties simultaneously with relatively high accuracy. The on-line vis-NIR measurement accuracy depends largely on the quality of calibration models. In order to establish robust calibration models for OC, TN and MC valid for few selected European farms, several factors affecting model accuracy have been studied. Nonlinear calibration techniques, e.g. artificial neural network (ANN) combined with partial least squares regression (PLSR) has provided better calibration accuracy than the linear PLSR or principal component regression analysis (PCR) alone. It was also found that effects of sample concentration statistics, including the range or standard derivation and the number of samples used for model calibration are substantial, which should be taking into account carefully. Soil MC, texture and their interaction effects are other principle factors affecting the in situ and on-line vis-NIR measurement accuracy. This study confirmed that MC is the main negative effect, whereas soil clay content plays a positive role. The general calibration models developed for soil OC, TN and MC for farms in European were validated using a previously developed vis-NIR on-line measurement system equipped with a wider vis-NIR spectrophotometer (305 – 2200 nm) than the previous version. The validation results showed this wider range on-line vis-NIR system can acquire larger than 1500 data point per ha with a very good measurement accuracy for TN and OC and excellent accuracy for MC. The validation also showed that spiking few target field samples into the general calibration models is an effective and efficient approach for upgrading the implementation of the on-line vis-NIR sensor for measurement in new fields in the selected European farms.

A novel approach of using near infrared region (NIR) dyes is applied to elucidate the binding interaction between human serum albumin (HSA) and mangiferin (MGF). HSA is a blood carrier protein used for drug delivery, while mangiferin is a natural polyphenol found in mangoes that possesses numerous beneficial health properties. The NIR dyes are used as a probe to investigate MGF binding interaction with HSA via monitoring fluorescence of Trp-214 residue. Molecular modeling is used for docking and semi-empirical analysis. The investigation of the binding interaction between Trp-214 and MGF is significant, for it may offer broader pharmacological insight and applications for the polyphenol. Mangiferin in proposed to bind with a 2:1 stoichiometric ratio with HSA to the Trp-214 residue in subdomain IIA and another possible binding site to be determined in future studies. Spectral changes suggest a stabilized protein conformation upon mangiferin binding with the addition of NIR dye E-06 and MHI-06.

Blue compact galaxies (BCGs) are gas-rich star-forming low redshift galaxies with low metallicities. In some cases the relative strength of the starburst can be so high that it completely dominates the light output of the galaxy, an obstacle which has been countered by deeper optical imaging data and observations in the near infra-red (NIR) regime. This has revealed an older population referred to as the "host". In an effort to study the hosts of BCGs we have analyzed new and extremely deep UBVRIHKs imaging data for 46 high and low luminosity BCGs. For several BCGs the data reveal previously undetected extended low surface brightness components beyond the μB~26 mag arcsec-2 isophote. These are predominantly the luminous BCGs in the sample, and they show tails, plumes, optical bridges between companion galaxies, and other signs of merging or strong tidal interactions. The low luminosity BCGs, on the other hand, are well represented by an exponential disk profile down to the reliability limit of the data at a surface brightness level of μB~28 mag arcsec-2. The burst and host populations are examined separately. The integrated colors of both are compared to predictions from spectral evolutionary models, giving an indication of their respective ages and metallicities. Our analysis suggests that for the luminous BCGs a strong contribution by nebular emission is present almost down to the Holmberg radius, invalidating the host structural parameters obtained from brighter isophotes. Possible evolutionary links to quiescent galaxies like dEs, dIs, and LSBGs are explored by examining the structural parameters derived from two radial ranges typically assumed to be dominated by the underlying host galaxy. In this parameter space the luminous BCGs in our sample deviate from their low luminosity counterparts and from BCG data in the literature. They are instead consistent with the structural properties of giant low surface brightness galaxies with central surface brightnesses μB≥23 mag arcsec-2. We further examine the asymmetry and concentration parameters for the sample and study the correlation between the minimum asymmetry distribution in the optical and NIR vs morphological class, concentration and integrated colors to identify mergers/tidally interacting galaxies. A shift in the asymmetry distribution occurs for low luminosity BCGs from the optical to the NIR. In contrast, we find that the flocculent asymmetry component (due to star formation) completely dominates the composite asymmetry of high luminosity BCGs. We introduce an alternative asymmetry measure which successfully traces the dynamical asymmetry component (due to merging/tidal interaction) of the host. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Manuscript. Paper 5: Manuscript.</p>

Many areas of science now generate huge volumes of data that present visualization, modeling, and interpretation challenges. Methods for effectively representing the original data in a reduced coordinate space are therefore receiving much attention. The purpose of this research is to test the hypothesis that molecular computing of vectors for transformation matrices enables spectra to be represented in any arbitrary coordinate system. New coordinate systems are selected to reduce the dimensionality of the spectral hyperspace and simplify the mechanical/electrical/computational construction of a spectrometer. A novel integrated sensing and processing system, termed Molecular Factor Computing (MFC) based near infrared (NIR) spectrometer, is proposed in this dissertation. In an MFC -based NIR spectrometer, spectral features are encoded by the transmission spectrum of MFC filters which effectively compute the calibration function or the discriminant functions by weighing the signals received from a broad wavelength band. Compared with the conventional spectrometers, the novel NIR analyzer proposed in this work is orders of magnitude faster and more rugged than traditional spectroscopy instruments without sacrificing the accuracy that makes it an ideal analytical tool for process analysis. Two different MFC filter-generating algorithms are developed and tested for searching a near-infrared spectral library to select molecular filters for MFC-based spectroscopy. One using genetic algorithms coupled with predictive modeling methods to select MFC filters from a spectral library for quantitative prediction is firstly described. The second filter-generating algorithm designed to select MFC filters for qualitative classification purpose is then presented. The concept of molecular factor computing (MFC)-based predictive spectroscopy is demonstrated with quantitative analysis of ethanol-in-water mixtures in a MFC-based prototype instrument.

The desire to use the tools and concepts of chemometrics when studying problems in the life sciences, especially biology and medicine, has prompted chemometricians to shift their focus away from their field‘s traditional emphasis on model predictivity and towards the more contemporary objective of optimizing information exchange via model interpretation. The complex data structures that are captured by modern advanced analytical instruments open up new possibilities for extracting information from complex data sets. This in turn imposes higher demands on the quality of data and the modeling techniques used. The introduction of the concept of orthogonal variation in the late 1990‘s led to a shift of focus within chemometrics; the information gained from analysis of orthogonal structures complements that obtained from the predictive structures that were the discipline‘s previous focus. OPLS, which was introduced in the beginning of 2000‘s, refined this view by formalizing the model structure and the separation of orthogonal variations. Orthogonal variation stems from experimental/analytical issues such as time trends, process drift, storage, sample handling, and instrumental differences, or from inherent properties of the sample such as age, gender, genetics, and environmental influence. The usefulness and versatility of OPLS has been demonstrated in over 500 citations, mainly in the fields of metabolomics and transcriptomics but also in NIR, UV and FTIR spectroscopy. In all cases, the predictive precision of OPLS is identical to that of PLS, but OPLS is superior when it comes to the interpretation of both predictive and orthogonal variation. Thus, OPLS models the same data structures but provides increased scope for interpretation, making it more suitable for contemporary applications in the life sciences. This thesis discusses four different research projects, including analyses of NIR, FTIR and NMR spectroscopic data. The discussion includes comparisons of OPLS and PLS models of complex datasets in which experimental variation conceals and confounds relevant information. The PLS and OPLS methods are discussed in detail. In addition, the thesis describes new OPLS-based methods developed to accommodate hyperspectral images for supervised modeling. Proper handling of orthogonal structures revealed the weaknesses in the analytical chains examined. In all of the studies described, the orthogonal structures were used to validate the quality of the generated models as well as gaining new knowledge. These aspects are crucial in order to enhance the information exchange from both past and future studies.

Techn. Hochsch., Diss.--Aachen, 2007.