Mass Spectrometry and Nuclear Magnetic Resonance in the Chemometric Analysis of Cellular Metabolism

The development and awareness of Machine Learning and “big data” has led to a growing interest in applying these methods to bioanalytical research. Methods such as Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) can now obtain tens of thousands to millions of data points from a single sample, due to fundamental instrumental advances and ever-increasing resolution. Simple pairwise comparisons on datasets of this magnitude can obfuscate more complex underlying trends, and does a disservice to the richness of information contained within. This necessitates the need for multivariate approaches that can more fully take advantage of the complexity of these datasets. Performing these multivariate analyses takes high degree of expertise, requiring knowledge of such disparate areas as chemistry, physics, mathematics, statistics, software development and signal processing. As a result, this barrier to entry prevents many investigators from fully utilizing all the tools available to them, instead relying on a mix of commercial and free software, chained together with in-house developed solutions just to perform a single analysis. While there are numerous methods in published literature for statistical analysis of these larger datasets, most are still confined to the realm of theory due to them not being implemented into publicly available software for the research community. This dissertation outlines the development of routines for handling LC-MS data with freely available tools, including the Octave programming language. This presents, in combination with our previously developed software MVAPACK, a unified platform for metabolomics data analysis that will encourage the wider adoption of multi-instrument investigations and multiblock statistical analyses. Advisor: Robert Power

Evaluation of Banks' Interest Rate Risk: An Alternative Approach

Interest rate risk is often assessed through parallel yield curve shifts of 100, 200 or 400 basis points. In order to provide a more realistic view, we did simulations based on periods of growing interest rates that actually occurred in the past. These simulations show that non-bank deposits and non-bank loans react more strongly to rising interest rates than certain interbank and security positions. Existing research usually overestimates related risks slightly as it does not take the interest-elastic reactions of non-banks into account. We found three types of effects. Firstly, the direct earnings effect stems from changed market interest rates applied to constant balance sheet positions. This effect is typically measured by straightforward models. Secondly, to increase accuracy, we identified an indirect earnings effect. Customers react to interest rate changes, and therefore balance sheet positions increase or decrease. The size of this effect depends on how strongly they react, i. e. their interest elasticity. Thirdly, the induced earnings effect results from a bank’s reactions in an attempt to compensate for the changed business volume

Mass Spectrometry and Nuclear Magnetic Resonance in the Chemometric Analysis of Cellular Metabolism

The development and awareness of Machine Learning and “big data” has led to a growing interest in applying these methods to bioanalytical research. Methods such as Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) can now obtain tens of thousands to millions of data points from a single sample, due to fundamental instrumental advances and ever-increasing resolution. Simple pairwise comparisons on datasets of this magnitude can obfuscate more complex underlying trends, and does a disservice to the richness of information contained within. This necessitates the need for multivariate approaches that can more fully take advantage of the complexity of these datasets. Performing these multivariate analyses takes high degree of expertise, requiring knowledge of such disparate areas as chemistry, physics, mathematics, statistics, software development and signal processing. As a result, this barrier to entry prevents many investigators from fully utilizing all the tools available to them, instead relying on a mix of commercial and free software, chained together with in-house developed solutions just to perform a single analysis. While there are numerous methods in published literature for statistical analysis of these larger datasets, most are still confined to the realm of theory due to them not being implemented into publicly available software for the research community. This dissertation outlines the development of routines for handling LC-MS data with freely available tools, including the Octave programming language. This presents, in combination with our previously developed software MVAPACK, a unified platform for metabolomics data analysis that will encourage the wider adoption of multi-instrument investigations and multiblock statistical analyses. Advisor: Robert Power

REVIEW: New frontiers in metabolomics: from measurement to insight

Metabolomics is the newest addition to the “omics” disciplines and has shown rapid growth in its application to human health research because of fundamental advancements in measurement and analysis techniques. Metabolomics has unique and proven advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. A review of current advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications

From White Collar to Influencer Marketing? How Banks Can Reach Young Customers

Banks distribute intangible services, so that traditional marketing instruments are often limited concerning their effectiveness to reach new clients, especially teenagers and young adults. With respect to this relevant practical problem, we used survey data for the relevant group (n = 302) in Austria to investigate whether influencer marketing could be a banking strategy to reach the young generation. Due to the particular complexity of a financial product, we assume that the credibility and trustworthiness of an influencer can lead to respondents being more willing to engage with financial products. Based on our survey results, we can provide first evidence that influencer marketing also has untapped potential for banks. Although our respondents revealed a certain skepticism towards this form of marketing, the results indicate a weak positive correlation between influencer marketing, customer engagement with the subject of financial products and ultimately the purchase of financial products. In this respect, our results are of particular interest to decision-makers in banks. However, they are also relevant for the whole of society. If influencer marketing works for financial products, then other topics that are particularly sensitive, e.g., health care, could be addressed accordingly

In the Flow

In order to enable advanced technological applications of nanocrystal composites, e.g., as functional coatings and layers in flexible optics and electronics, it is necessary to understand and control their mechanical properties. The objective of this study was to show how the elasticity of such composites depends on the nanocrystals’ dimensionality. To this end, thin films of titania nanodots (TNDs; diameter: ~3–7 nm), nanorods (TNRs; diameter: ~3.4 nm; length: ~29 nm), and nanoplates (TNPs; thickness: ~6 nm; edge length: ~34 nm) were assembled via layer-by-layer spin-coating. 1,12-dodecanedioic acid (12DAC) was added to cross-link the nanocrystals and to enable regular film deposition. The optical attenuation coefficients of the films were determined by ultraviolet/visible (UV/vis) absorbance measurements, revealing much lower values than those known for titania films prepared via chemical vapor deposition (CVD). Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images showed a homogeneous coverage of the substrates on the µm-scale but a highly disordered arrangement of nanocrystals on the nm-scale. X-ray photoelectron spectroscopy (XPS) analyses confirmed the presence of the 12DAC cross-linker after film fabrication. After transferring the films onto silicon substrates featuring circular apertures (diameter: 32–111 µm), freestanding membranes (thickness: 20–42 nm) were obtained and subjected to atomic force microscopy bulge tests (AFM-bulge tests). These measurements revealed increasing elastic moduli with increasing dimensionality of the nanocrystals, i.e., 2.57 ± 0.18 GPa for the TND films, 5.22 ± 0.39 GPa for the TNR films, and 7.21 ± 1.04 GPa for the TNP films

Visualization of Multimerization and Self-Assembly of DNA-Functionalized Gold Nanoparticles Using In-Liquid Transmission Electron Microscopy

Base-pairing stability in DNA-gold nanoparticle (DNA-AuNP) multimers along with their dynamics under different electron beam intensities was investigated with in-liquid transmission electron microscopy (in-liquid TEM). Multimer formation was triggered by hybridization of DNA oligonucleotides to another DNA strand (Hyb-DNA) related to the concept of DNA origami. We analyzed the degree of multimer formation for a number of samples and a series of control samples to determine the specificity of the multimerization during the TEM imaging. DNA-AuNPs with Hyb-DNA showed an interactive motion and assembly into 1D structures once the electron beam intensity exceeds a threshold value. This behavior was in contrast with control studies with noncomplementary DNA linkers where statistically significantly reduced multimerization was observed and for suspensions of citrate-stabilized AuNPs without DNA, where we did not observe any significant motion or aggregation. These findings indicate that DNA base-pairing interactions are the driving force for multimerization and suggest a high stability of the DNA base pairing even under electron exposure