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Protactinium (Pa) is an actinide with chemical properties that are unique among the actinide elements. While the properties of other actinides are to a large extent understood, much of the chemistry of Pa remains a mystery. This thesis aims to illuminate new understanding of Pa chemistry through behavioral analysis using analytical techniques including liquid-liquid extraction (LL); extraction chromatography (ExC); and spectroscopic studies. Applications of radioanalytical chemistry and Pa: Through the research presented in this dissertation, we have developed a new way to separate uranium (U), thorium (Th), and Pa from complex environmental samples. The approach has been demonstrated for U-series dating of materials by alpha spectrometry. The method can be applied to geochronology, as well as to nuclear-forensic analysis of uranium-containing materials. In studies presented here, samples from a Paleolithic lake (Lake Bonneville, Utah USA) were analyzed for the radioactivity concentration of 230Th, 231Pa, 234U, 235U, and 238U by isotope dilution alpha spectrometry. Radioactivities were used to estimate of the time period of formation of the deposit from which the samples were collected. Ages were determined from the isotopics ratios; i.e., 231Pa/235U (40 ka); and 230Th/238U (39.5 ka) we found to be concordant with radiocarbon-14 dates (37 ka) obtained by collaborators at Brigham Young University. These studies inspired the development of a novel ExC resin to facilitate preparation of highly pure tracer isotope (233Pa) from a neptunium-237 (237Np) source. The material used for this development comprised 1-octanol adsorbed to a semi-porous resin material. The new approach greatly improved the yield and purity of 233Pa used for these chronometric analyses Developing an understanding of the chemistry of Pa at trace concentrations: The new-improved analytical described above led to the hypothesis that analytical separations approaches could be used to develop a more detailed understanding of Pa chemistry. Toward this goal, experiments were conducted to understand how the extraction of Pa is impacted by solution acidity [H+], anion concentration [A-; Cl-, NO3-], and extractant concentration ([2,6-dimethyl-4-heptanol, DIBC]). A full-factorial experimental design was employed to create a model that would allow for predictions in Pa behavior, as well as describe the nature of the observations. This model generated a multivariate equation that relates the distribution coefficient ([Pa] organic phase/ [Pa] aqueous phase) to each of the parameters ([H+], [A-], and [DIBC]). Further studies expanded to other alcohols (ROH) used as extractants (1-octanol, (2,6)-dimthyl-4-heptanol, and 2-ethyl-hexanol); and the results were analyzed using the slope analysis and comparative extraction studies using the model and compared to other actinide elements (Th, U, Np, americium (Am)) by both LL and ExC systems. These experiments revealed unique chemical behavior of Pa with respect to the other actinides. For example, it was found that Pa was the only actinide element to be extracted into the organic phase under acidic conditions (HCl and HNO3). Slope analysis experiments elucidated the stoichiometric identity of Pa species, with respect to the anion and extractant. Future studies will aim to identify the oxygen stoichiometry and species by X-ray absorption techniques. Investigations of the organic phase: In the final sections of this thesis, experiments are presented that are intended to determine if aggregation plays a key role in the extraction of Pa in systems containing 1-octanol and 2-ethyl-hexanol. This work is done in the absence of metal ions to control the dynamics of the organic phase, and are analyzed by tensiometry and Karl Fisher titrations with small angle X-ray scattering and molecular dynamic simulations. A key novel finding of these studies in that ROH molecules arrange in nanoscale aggregates that decrease the interfacial tension between the phases and extract a significant amount of water into the aggregates stabilized by a network of H-bonding. These studies lead to the hypothesis for future studies that Pa extraction is likely facilitated by solvation into the organic phase via ROH aggregates. The sum of the findings and observations of this dissertation provide insight into the chemical nature of Pa: (1) Novel extraction methods to obtain radiochemically pure fractions show that Pa can be efficiently extracted and separated from complex matrices to aid in chronometric analysis for geochronology or nuclear forensics; (2) Statistical modeling to develop a better understanding of the main effects of solvent extraction parameters; (3) Equilibrium analysis to improve our understanding of chemistry of Pa and how it is unique to the actinides; (4) Aggregation analysis to demonstrate a solvent centric understanding of extraction studies, these results lead to future experiments to investigate how organic phase aggregation can influence solvent extraction selectivity.

Phospholipids (PLs) are a component of cell membranes, biological fluids and tissues. These compounds are problematic for the bioanalytical chemist, especially when PLs are not the analytes of interest. PL interference with bioanalysis highly impacts reverse-phase chromatographic methods coupled with mass spectrometric detection. Phospholipids are strongly retained on hydrophobic columns, and can cause significant ionization suppression in the mass spectrometer, as they out-compete analyte molecules for ionization. Strategies for improving analyte detection in the presence of PLs are reviewed, including in-analysis modifications and sample preparation strategies. Removal of interfering PLs prior to analysis seems to be most effective at moderating the matrix effects from these endogenous cellular components, and has the potential to simplify chromatography and improve column lifetime. Products targeted at PL removal for sample pre-treatment, as well as products that combine multiple modes of sample preparation (i.e. Hybrid SPE), show significant promise in mediating the effect on PL interference in bioanalysis.

Purpose: Three different generic vancomycin products were compared using liquid chromatography–mass spectrometry (LC-MS) and open-access metabolomic tools. Methods: Single-lot samples of vancomycin hydrochloride from three different manufacturers (Hospira, APP Pharmaceuticals, and Pfizer) were reconstituted and injected into a high-resolution LC-MS system. The mass spectral fingerprints were compared for similarity of nonvancomycin B components using the XCMS Online system through Scripps University. Significance was defined as a p of ≤0.01 and a fold change of ≥1.5. The concentration of vancomycin B in each product was also measured using LC-MS on days 0, 1, 2, 4, 7, 10, and 14. Results: Qualitative comparisons of the products using the XCMS Online interface indicated the presence of significant differences among the products at the time of reconstitution; however, these variations seemed to converge after 14 days of storage. The concentration profiles of vancomycin B during refrigerated storage did not differ significantly among the three products. XCMS Online analyses revealed that the Pfizer and Hospira products were the most similar to each other. Conclusion:While there were no significant differences found in the concentration of vancomycin B among Pfizer, APP, and Hospira products, there were differences in their initial mass spectral analysis after reconstitution. Liquid chromatography–tandem mass spectrometry profiles of the ions or isotopes present in the three products showed significant differences in impurities such as crystalline degradation product (CDP)-1 and CDP intermediate. After 14 days of refrigerated storage, the differences among the products converged, and fewer distinct features could be detected.

In this work our driving motivation is to develop mathematically robust and computationally efficient algorithms that will help chemists towards their goal of pattern matching. Environmental chemistry today broadly faces difficult computational and interpretational challenges for vast and ever-increasing data repositories. A driving factor behind these challenges are little known intricate relationships between constituent analytes that constitute complex mixtures spanning a range of target and non-target compounds. While the end of goal of different environment applications are diverse, computationally speaking, many data interpretation bottlenecks arise from lack of efficient algorithms and robust mathematical frameworks to identify, cluster and interpret compound peaks. There is a compelling need for compound-cognizant quantitative interpretation that accounts for the full informational range of gas chromatographic (and mass spectrometric) datasets. Traditional target-oriented analysis focus only on the dominant compounds of the chemical mixture, and thus are agnostic of the contribution of unknown non-target analytes. On the other extreme, statistical methods prevalent in chemometric interpretation ignore compound identity altogether and consider only the multivariate data statistics, and thus are agnostic of intrinsic relationships between the well-known target and unknown target analytes. Thus, both schools of thought (target-based or statistical) in current-day chemical data analysis and interpretation fall short of quantifying the complex interaction between major and minor compound peaks in molecular mixtures commonly encountered in environmental toxin studies. Such interesting insights would not be revealed via these standard techniques unless a deeper analysis of these patterns be taken into account in a quantitative mathematical framework that is at once compound-cognizant and comprehensive in its coverage of all peaks, major and minor. This thesis aims to meet this grand challenge using a combination of signal processing, pattern recognition and data engineering techniques. We focus on petroleum biomarker analysis and polychlorinated biphenyl (PCB) congener studies in human breastmilk as our target applications. We propose a novel approach to chemical data analytics and interpretation that bridges the gap between target-cognizant traditional analysis from environmental chemistry with compound-agnostic computational methods in chemometric data engineering. Specically, we propose computational methods for target-cognizant data analytics that also account for local unknown analytes allied to the established target peaks. The key intuition behind our methods are based on the underlying topography of the gas chromatigraphic landscape, and we extend recent peak mapping methods as well as propose novel peak clustering and peak neighborhood allocation methods to achieve our data analytic aims. Data-driven results based on a multitude of environmental applications are presented.

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The large scale nitric acid oxidation of common sugars into their corresponding aldaric acids is being investigated as an important source of potentially useful components for industrial applications such as polymers. This thesis details the development of an Ion Chromatography (IC) method for the analysis of these oxidation mixtures and related samples from the work-up and purification processes. The method was developed for use with a Dionex ICS2000 IC system equipped with an AS11-HC column and utilising suppressed conductivity detection. IC proved to be a useful, versatile and straightforward method of studying the reactions and their products. The detected ions include but are not restricted to the anionic salt forms of: D-Glucaric acid, Xylaric acid, Mannaric acid, D-gluconic acid and both keto forms of the same, D-xylonic acid, D-mannonic acid, glycolic acid, oxalic acid, tartaric acid and tartronic acid. Nitrate from the nitric acid used in the oxidation is often observed. The results compare favorably to GC-MS and HPLC analysis of similar samples. An overview of the theory and operation of the instrument along with the method development and results from application to the oxidation mixtures and related samples are presented. As part of the investigation into the range of utility of IC for studying these reactions, a study was made of the retention behaviour of a large number of simple and low molecular weight (LMW) carboxylic acids eluted by the ion chromatography system in use. The results of this study are included with an explanation of the major factors affecting anion retention on the column

Until present, many researchers relied on the conventional plug flow dispersion models to analyse the concentration profiles obtained from the tracer injection experiments to evaluate the dispersion coefficients in packed beds. The Fickian concept in the limit of long time duration is assumed to be applicable and it implies that the mean-square displacement of the tracer profile is constant with time and the concentration profile is Gaussian. There were very few studies on identifying the conditions under which this assumption is valid and delineate the range of applicability of the existing plug flow dispersion models. If the time scales of a tracer injection experiment are not sufficient for a tracer to traverse the bed radius and sample the velocity variations, this could give rise to persisting non-Fickian transients where the mean-square displacement of the tracer profile is not constant with time and the concentration profile deviates from the normal Gaussian distribution. These transients cannot be predicted by the conventional plug dispersion models. An extended axial non-Fickian macroscopic dispersion model is derived to describe the transient development of a solute tracer when injected into a fluid flowing through a cylindrical packed bed or empty tube and some non-Fickian effects in the dispersion process. The flow profile in beds packed with uniform particles exhibits radial non-uniformity due to the oscillatory variation in porosity because of the wall confinement (wall effect). Compared with the axial plug flow dispersion model, the extended model contains time-dependent coefficients such as the transient axial dispersion coefficient and higher order derivatives (higher than second order) of the cross-sectionally averaged concentration. Including them provides some insight on non-Fickian transport in the dispersion process. The model provides time criteria on the basis that the effelongitudinal dispersion coefficient in the packed bed reaches its asymptotic value and the non-Fickian transients will die out. Some experimental conditions in the literature were checked by these criteria and found to be either marginally satisfied, or not satisfied at all, which indicates that the Fickian concept is not valid. The model results for tracer dispersion in cylindrical packed beds show that the longitudinal dispersion coefficient converges to its asymptotic value on a time scale proportional to R2/(DT) where R is the column radius and (DT) is the area averaged lateral dispersion coefficient. The extended model encouraged study of the consequences of the additional dispersion terms in other applications such as the pulse spread in the field of capillary column inverse gas chromatography (CCIGC). CCIGC is used to evaluate the solute-polymer diffusion coefficient Dp and the partition coefficient K at infinite dilute conditions. The tube geometry in CCIGC is more complex than the conventional Taylor dispersion problem due to the polymer coating on the inside of the capillary wall. The extended CCIGC model presented in this study has advantages over the previous models by including the effects of Taylor dispersion and higher order derivatives of the pulse area-averaged concentration. Taylor dispersion effect causes more pulse spread in the longitudinal direction and by not including it in the CCIGC regression models may cause a significant error in the measured Dp values. The extended CCIGC model provides for the first time criteria on capillary dimensions for the transient coefficients (multiplying the second and higher order derivatives) to become constant and for the non-Fickian effects associated with the higher order derivatives to be neglected. Model results show that Taylor dispersion effect has a significant effect on the elution profiles at high values of Dp and/or low values of gas diffusion coefficients Dg and it can be used to increase the sensitivity range of the previous CCIGC models at extremely low and high Dp values.

Vitamin C occurs in relatively high concentrations in fresh and processed fruits and vegetables but is found to a lesser extent in animal tissues and animal-derived products. Nearly 90 % of vitamin C in the human diet is obtained from fruits and vegetables but this can be indirect by way of commercially prepared fruit juices. These juices are often enriched with vitamin C which has been synthetically prepared. There is a wide range of such juices on the New Zealand market, and they are a significant source of dietary vitamin C for many in the population. The focus of this research is on the Keri range of juice products.The present study monitors the fate of vitamin C during storage of Keri juices up to the best-before date, and under a range of other storage and consumption situations. Two methods were adopted for determining ascorbic acid (AA, the chemical identity of vitamin C). These were the titrimetric method, which is based upon the reduction of the dye 2,6-dichlorophenolindophenol by AA in acidic solution, and liquid chromatography, which is used to separate AA from its immediate oxidation product dehydroascorbic acid. In the latter method these two analytes can be measured independently. The liquid chromatography was less successful than the simpler titrimetric method, so most of the work was done by titration. However, the concentration of dehydroascorbic acid, which has vitamin C activity in vivo, remained uncertain. Moreover, the titrimetric method could not be applied to juices with high purple anthocyanin concentrations, like blackcurrant, because the colour change at the titration end point could not be detected. pH adjustment to change colour was ineffective, and decolourisation with charcoal led to the rapid and complete destruction of AA. The concentration of AA in Keri juices at the time of manufacture were always much higher than claimed on the labels. Storage for up to nine months at room temperature resulted in a loss in AA of between 37 and 68 %, depending on the juice and exposure to fluorescent light. However, the time of storage was a much more dominant factor than light exposure. The kinetics of loss, straight lines, were most easily explained by an aerobic model of AA degradation from oxygen diffusing across the polyethylene tetraphthalate bottle wall. Overall, the label claims made were defensible in terms of the best-before date, because it took at least 100 days of storage before the AA concentration in the most susceptible juices fell below the claimed value. This is because these drinks are fast moving consumer goods and storage beyond 100 days is unlikely. (Nonetheless, the supplier (Keri Juice Company) has since adopted its new unitised method of formulating juice. This has resulted in an initially higher concentration of vitamin C as compared to the juices under investigation.) In the nine months storage experiment there was some evidence for the presence of dehydroascorbic acid in blackcurrant drinks, but not in another three juices. Pasteurisation during preparation of these drinks resulted in up to 7 % loss of AA, probably due to oxygen dissolved in water, and accelerated by heat of pasteurisation. Higher temperatures in later storage also accelerated losses. Progressive exposure of juice to air during simulated consumption of 3 L bottles over a week also accelerated losses. Finally, exposure to sunlight in a diurnal temperature environment accelerated losses five-fold higher than in total darkness. Filtration of ultraviolet light approximately halved the loss due to sunlight. Overall however, it can be concluded that AA in the Keri range of juices is very resistant to degradation of AA.

Neuropathic pain is defined as "pain initiated or caused by a primary lesion or dysfunction in the nervous system". In contrast to physiological pain that warns of noxious stimuli likely to result in tissue damage, neuropathic pain serves no protective function. Examples of neuropathic pain states include postherpetic neuralgia (shingles) and phantom limb / stump pain. This pain state also exists in the orofacial region, with the possibility of several variants including atypical odontalgia and burning mouth syndrome. There is a paucity of information on the prevalence of neuropathic pain in the orofacial region. One study assessed patients following endodontic treatment and found that approximately 3 to 6percent of patients reported persistent pain. Patients predisposed to the condition atypical odontalgia (phantom tooth pain) include those suffering from recurrent cluster or migraine headaches. Biochemical and neurobiological processes leading to a neuropathic pain state are complex and involve peripheral sensitisation, and neuronal plasticity of the central and peripheral nervous systems. Subsequent associated pathophysiology includes regional muscle spasm, sympathetic hyperfunction, and centralisation of pain. The relevant clinical features of neuropathic pain are: (i) precipitating factors such as trauma or disease (infection), (ii) pain that is frequently described as having burning, paroxysmal, and lancinating or sharp qualities, and (iii) physical examination may indicate hyperalgesia, allodynia and sympathetic hyperfunction. The typical patient complains of persistent, severe pain, yet there are no clearly identifiable clinical or radiographic abnormalities. Often, due to the chronicity of the problem, afflicted patients exhibit significant distress and are poor pain historians, thus complicating the clinician's task of obtaining a detailed and relevant clinical and psychosocial history. An appropriate analgetic blockade test for intraoral sites of neuropathic pain is mucosal application of topical anaesthetics. Other, more specific, tests include placebo controlled lignocaine infusions for assessing neuropathic pain, and placebo controlled phentolamine infusions for sympathetically maintained pain. The treatment and management of neuropathic pain is multidisciplinary. Medication rationalisation utilises first-line antineuropathic drugs including tricyclic antidepressants, and possibly an anticonvulsant. Topical applications of capsaicin to the gingivae and oral mucosa are a simple and effective treatment. Neuropathic pain responds poorly to opioid medication. Psychological assessment is often crucial in developing strategies for pain management. Psychological variables include distress, depression, expectations of treatment, motivation to improve, and background environmental factors. To enable a greater understanding of neuropathic pain, thereby leading to improved treatments, high-performance liquid chromatography-mass spectrometry is one analytical technique that has the potential to contribute to our knowledge base. This technique allows drugs and endogenous substances to be assayed from one sample in a relatively short time. The technique can identify, confirm, and measure the concentrations of multiple analytes from a single sample.