Over the years electronic structure theory has proven to be a powerful method with which one can probe the behaviour of materials, making it possible to predict properties that are difficult to measure experimentally. The numerical tools needed for these methods are always in need of development, since the desire to calculate more complex materials pushes this field forward. This thesis contains work on both this implementational and developmental aspects. In the first part we investigate the structural properties of the 6d transition metals using the exact muffin-tin orbitals method. It is found that these elements behave similarly to their lighter counterparts, except for a few deviations. In these cases we argue that it is relativistic effects that cause this anomalous behaviour. In the second part we assess the Padé approximant, which is used in several methods where one wants to include many-body effects into the electronic structure. We point out difficulties that can occur when using this approximant, and propose and evaluate methods for their solution. / <p>QC 20130219</p>

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It is sometimes said that money speaks louder than words, and in a world where financial decisions are a major driving force, it is interesting to explore how monetary incentives influence our decision making. Some argue that intrinsic motivation is sufficient to be able to measure prosocial decision-making, but what happens when we add monetary incentives to experiments that might otherwise be conducted with hypothetical scenarios? In this study, we conduct an online experiment with 1002 participants to explore if decision making changes when monetary incentives are introduced. The experiment includes five different social dilemmas involving distributions of money between participants. There are two conditions where one group makes hypothetical decisions and the other group receives money based on their decisions (i.e., is incentivized). Furthermore, we investigate if income, age and gender affect prosocial behavior. Our results suggest that both conditions show similar effects on prosocial behavior which implies that usage of either one of the two conditions will generate an equivalent outcome. The effects from household income, age and gender were significant in some social dilemmas, but the effect was not practically relevant for this study. We believe our results may be useful to include in the discussion of whether or not monetary incentives and hypothetical decisions generate similar results when studying prosocial behavior in decision making in experiments.

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NKT cells are an important part of human immune system and recognize a specific set of antigens called glycolipids. Only a handful of "natural" NKT cell antigens are known till date. Although NKT cells play a protective role against pathogenic organisms, imbalances in NKT cell functions are implicated in many diseases including asthma. Allergic asthma, a Th2 driven inflammation of airways, is primarily caused by inhalation of environmental allergens. In the last decade, inhaled allergen Aspergillus fumigatus has been under scrutiny for the presence of NKT cell antigens that might trigger asthma. We successfully isolated, characterized and synthesized a "natural" antigenic glycolipid which activates NKT cells in CD1d dependent manner. When this glycolipid is administered intranasally to mice, WT but not CD1d-/- mice developed airway hyperreactivity (AHR), which is a cardinal feature of asthma. Our results indicate that this glycolipid also triggers the production of key cytokines responsible for development of airway hyperreactivity, namely IL-4 and IL-13. Widespread use of antibiotics has convoluted the problem of antimicrobial resistance. Our research group has developed a novel class of antimicrobial peptide mimics called Ceragennins. These cholic acid based antimicrobial compounds have many desirable properties including low MICs, effectiveness against biofilms, and relatively low manufacturing cost. In order to advance the clinical development of Ceragennins, we developed analytical methods for qualitative and quantitative determination of these compounds in complex biological matrices. These methods were also used for carrying out the stability studies of Ceragenins under varying pH and temperatures

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Embargoed until July 2016. / Active Pharmaceutical Ingredients (APIs) are frequently prepared for delivery to the lung for local topical treatment of diseases such as Chronic Obstructive Pulmonary Disease (COPD) and asthma, or for systemic delivery. One of the most commonly used devices for this purpose is the pressurised metered dose inhaler (pMDI) whereby drugs are formulated in a volatile propellant held under pressure. The compound is aerosolised to a respirably sized dose on actuation, subsequently breathed in by the user. The use of hydrofluoroalkanes (HFAs) in pMDIs since the Montreal Protocol initiated a move away from chlorofluorocarbon (CFC) based devices has resulted in better performing products, with increased lung deposition and a concomitant reduction in oropharyngeal deposition. The physical properties of HFA propellants are however poorly understood and their capacity for solubilising inhaled pharmaceutical products (IPPs) and excipients used historically in CFCs differ significantly. There is therefore a drive to establish methodologies to study these systems in-situ and post actuation to adequately direct formulation strategies for the production of stable and efficacious suspension and solution based products. Characterisation methods have been applied to pMDI dosage systems to gain insight into solubility in HFAs and to determine forms of solid deposits after actuation. A novel quantitative nuclear magnetic resonance method to investigate the physical chemistry of IPPs in these preparations has formed the centrepiece to these studies, accessing solubility data in-situ and at pressure for the first time in HFA propellants. Variable temperature NMR has provided thermodynamic data through van’t Hoff approaches. The methods have been developed and validated using budesonide to provide limits of determination as low as 1 μg/mL and extended to 11 IPPs chosen to represent currently prescribed inhaled corticosteroids (ICS), β2-adrenoagonists and antimuscarinic bronchodilators, and have highlighted solubility variations between the classes of compounds with lipophilic ICSs showing the highest, and hydrophilic β2- agonist / antimuscarinics showing the lowest solubilities from the compounds under study. To determine solid forms on deposition, a series of methods are also described using modified impaction methods in combination with analytical approaches including spectroscopy (μ-Raman), X-ray diffraction, SEM, chromatography and thermal analysis. Their application has ascertained (i) physical form / morphology data on commercial pMDI formulations of the ICS beclomethasone dipropionate (QVAR® / Sanasthmax®, Chiesi) and (ii) distribution assessment in-vitro of ICS / β2-agonist compounds from combination pMDIs confirming co-deposition (Seretide® / Symbicort®, GlaxoSmithKline / AstraZeneca). In combination, these methods provide a platform for development of new formulations based on HFA propellants. The methods have been applied to a number of ‘real’ systems incorporating derivatised cyclodextrins and the co-solvent ethanol, and provide a basis for a comprehensive study of solubilisation of the ICS budesonide in HFA134a using two approaches: mixed solvents and complexation. These new systems provide a novel approach to deliver to the lung, with reduced aerodynamic particle size distribution (APSD) potentially accessing areas suitable for delivery to peripheral areas of the lung (ICS) or to promote systemic delivery.

No description available.

Successful methods for the separation of biomolecules like amino acids, proteins, peptides, and DNA have been developed previously using HPLC, GC, GC-MS, and CE. Recently CE has become a routine laboratory technique in the analysis of biological molecules. Even though high-resolution separations with small sample volumes is the main advantage, CE is limited by lower sensitivity detection of analytes when universal detectors like UV absorption or refractive index detectors are used. Therefore, sensitivity enhancement can be obtained by either using different detection schemes or electrophoretically based pre- or on-line concentration methods. These can be grouped into two categories. The first category includes IEF, CGF or TGF where sensitivity is achieved through equilibrium electrofocusing. In these methods, electrophoresis and bulk solution is combined in the capillary or separation column to form a null velocity point, a point at which the net velocity of the analyte is zero. Using these methods 10-10,000 fold sensitivity enhancement is achieved. The second category uses velocity gradients but not the nul velocity for the enrichment of samples. These methods include FASS, LVSS, NSM, etc., which are applied for the analysis of small molecules, and 10-10,000 fold sensitivity enhancement is reported by using these methods. In this work, first GEITP an on-line preconcentration technique is applied for the detection of amino acids (using Trp and Tyr as model analytes). This work also established the effects of different parameters on enrichment. The parameters studied include effect of current flow acceleration across capillary inner diameter, the effect of leading electrolyte (LE) concentration on current density, and the effect of applied electric fields on the current density. To explore the application of GEITP in biological fluids, optimized parameters were developed for the detection and separation of Trp and Tyr in artificial cerebrospinal fluid (aCSF). Next, GEITP was applied for enrichment and separation of physiologically relevant concentrations of chromophore-derivatized Asp and Glu in high conductivity samples like artificial cerebrospinal fluid (aCSF). It was concluded from this work that the major factors which influence the enrichment is the ratio of current density to sample conductivity. Finally, GEITP is applied as a prior step before CZE to increase the resolution between analytes without using ampholyte mixtures. In this method GEITP was combined to CZE to achieve resolution adjustment between amino acids mixture using low pressure hydrodynamic flow during CZE without changing the separation column, field strength, or electrolyte system. In this work, a rapid CE method for extraction and analysis of amino acids in planarians, labeled with 4-Fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F), was developed. This method was applied to detect the changes in the levels of amino acids when planarians were fed and starved. This method can be applied to study pharmacological effects in planaria, as it can monitor different amino acid levels with respect to feeding. Finally, ssDNA photoproducts of different lengths (11-mer and 63-mer) were separated using two different matrices, a traditional C18 and a PV/DBS (PLRP-S) matrix. A faster separation (within ~ 10 mins) was achieved for a 11-mer by the PLRP-S column. A separation was achieved in the PLRP-S column for the 63-mer while there was no separation in C18 column. Baseline resolution was not achieved. Therefore, C18 can best be used for small length DNA while PLRP-S can be applied for longer length DNA, as it is more hydrophobic than C18 column. Parameters can still be optimized for a baseline separation. / Chemistry

Electronic structure methods aim to accurately describe the behaviour of the electrons in molecules and materials. To be applicable to arbitrary systems, these methods cannot depend on observations of specific chemical phenomena and must be derived solely from the fundamental physical constants and laws that govern all electrons. Such methods are called ab initio methods. Ab initio methods directly solve the electronic Schrödinger equation to obtain the electronic energy and wavefunction. For more than one electron, solving the electronic Schrödinger equation is impossible, so it is imperative to develop approximate methods that cater to the needs of their users, which can vary depending on the chemical systems under study, the available computational resources and time, and the desired level of accuracy. The most accessible ab initio approaches, including Hartree-Fock methods and Kohn-Sham density functional theory methods, assume that only one electronic configuration is needed to describe the system. While these single-reference methods are successful when describing systems where a single electron configuration dominates, like most closed-shell ground-state organic molecules in their equilibrium geometries, single-reference methods are unreliable for molecules in nonequilibrium geometries (e.g., transition states) and molecules containing unpaired electrons (e.g., transition metal complexes and radicals). For these types of multireference systems, accurate results can only be obtained if multiple electronic configurations are accounted for. Wavefunctions that incorporate many electronic configurations are called multideterminant wavefunctions. This thesis presents a systematic approach to developing multideterminant wavefunctions. First, we establish a framework that outlines the structural components of a multideterminant wavefunction and propose several novel wavefunction ansätze. Then, we present a software package that is designed to aid the development of new wavefunctions and algorithms. Using this approach, we develop an algorithm for evaluating the geminal wavefunctions, a class of multideterminant wavefunctions that are expressed with respect to electron pairs. Finally, we explore using machine learning to solve the Schrödinger equation by presenting a neural network wavefunction ansatz and optimizing its parameters using stochastic gradient descent. / Thesis / Doctor of Science (PhD)