The effect of the proton pump inhibitor pantoprazole on the biology of Campylobacter jejuni

Campylobacter is a major cause of acute bacterial gastroenteritis worldwide, with the highest number of infections being attributed to Campylobacter jejuni. C. jejuni is a Gram negative, spiral, motile bacterium that belongs to the campylobacterales order and is related to both Helicobacter spp. and Wolinella sp.. It has long been established that proton pump inhibitors (PPIs) and other benzimidazole derivatives display anti-Helicobacter activity in vitro. PPIs have in the past been shown to affect Helicobacter pylori growth, survival, motility, morphology, adhesion/invasion potential and susceptibility to conventional antibiotics. PPIs are highly effective drugs that are well tolerated, safe for prolonged daily use and are therefore in high demand. Both the PPIs omeprazole and lansoprazole featured in the top ten drugs prescribed in England in 2014. In 2014 Campylobacter was also the most commonly diagnosed gastrointestinal infection in Scotland, in England and Wales and also in Europe. It has previously been generally accepted that patients who are being treated with PPIs are more susceptible to enteric infections such as Campylobacter than people not taking PPIs. The effect of PPI exposure on H. pylori has been investigated rigorously in the past. A single previous study has hinted that PPIs may also be capable of affecting the related organism C. jejuni,but investigations have been extremely limited in comparison to those investigating the effect of PPIs on H. pylori. This study has investigated the in vitro effects of direct contact with PPIs on the biology ofC. jejuni. Exposure to the PPI pantoprazole was found to affect C. jejuni growth/survival, motility, morphology, biofilm formation, invasion potential and susceptibility to some conventional antibiotics. Microarray studies showed that the cmeA and Cj0561c genes were significantly up-regulated in response to pantoprazole exposure and a CmeABC deficient mutant was found to be significantly more susceptible to killing by pantoprazole than was the parent strain. Proteomic analysis indicated that the oxidative stress response of C. jejuni was induced following exposure to sub-lethal concentrations of pantoprazole. C. jejuni gene expression was assessed using qRT-PCR and the genes encoding for thiol peroxidase and GroEL co-chaperonin (both involved in the C. jejuni oxidative stress response) were found to be around four times higher in response to exposure to sub-lethal concentrations of pantoprazole. Experiments using the oxidative stress inhibitors thiourea (a hydroxyl radical quencher) and bipyridyl (a ferrous iron chelator) showed that killing by pantoprazole was not mediated by hydroxyl radical production.

Diketopyrrolopyrrole derivatives for bulk heterojunction and dye sensitised solar cells

This thesis describes the synthesis and characterisation of a series of molecules for use in bulk heterojunction and dye sensitised solar cells. The target molecules were based on a central diketopyrrolopyrrole subunit. Molecules based on diketopyrrolopyrrole have a conjugated structure, allowing for π-π interaction. Diketopyrrolopyrrole molecules also have relatively low lying HOMO and LUMO levels and high absorption coefficients and exhibit efficient charge transport properties. Furthermore, their electron withdrawing properties have warranted their use as promising organic photovoltaic materials. A number of molecules were successfully synthesised and sent to collaborators for testing in organic photovoltaic devices and development of this series of molecules continues to be of interest within the research group.

Pricing derivatives with stochastic volatility

This Ph.D. thesis contains 4 essays in mathematical finance with a focus on pricing Asian option (Chapter 4), pricing futures and futures option (Chapter 5 and Chapter 6) and time dependent volatility in futures option (Chapter 7). In Chapter 4, the applicability of the Albrecher et al.(2005)'s comonotonicity approach was investigated in the context of various benchmark models for equities and com- modities. Instead of classical Levy models as in Albrecher et al.(2005), the focus is the Heston stochastic volatility model, the constant elasticity of variance (CEV) model and the Schwartz (1997) two-factor model. It is shown that the method delivers rather tight upper bounds for the prices of Asian Options in these models and as a by-product delivers super-hedging strategies which can be easily implemented. In Chapter 5, two types of three-factor models were studied to give the value of com- modities futures contracts, which allow volatility to be stochastic. Both these two models have closed-form solutions for futures contracts price. However, it is shown that Model 2 is better than Model 1 theoretically and also performs very well empiri- cally. Moreover, Model 2 can easily be implemented in practice. In comparison to the Schwartz (1997) two-factor model, it is shown that Model 2 has its unique advantages; hence, it is also a good choice to price the value of commodity futures contracts. Fur- thermore, if these two models are used at the same time, a more accurate price for commodity futures contracts can be obtained in most situations. In Chapter 6, the applicability of the asymptotic approach developed in Fouque et al.(2000b) was investigated for pricing commodity futures options in a Schwartz (1997) multi-factor model, featuring both stochastic convenience yield and stochastic volatility. It is shown that the zero-order term in the expansion coincides with the Schwartz (1997) two-factor term, with averaged volatility, and an explicit expression for the first-order correction term is provided. With empirical data from the natural gas futures market, it is also demonstrated that a significantly better calibration can be achieved by using the correction term as compared to the standard Schwartz (1997) two-factor expression, at virtually no extra effort. In Chapter 7, a new pricing formula is derived for futures options in the Schwartz (1997) two-factor model with time dependent spot volatility. The pricing formula can also be used to find the result of the time dependent spot volatility with futures options prices in the market. Furthermore, the limitations of the method that is used to find the time dependent spot volatility will be explained, and it is also shown how to make sure of its accuracy.