Molecular analysis of virulence mechanisms associated with adherent-invasive Escherichia coli (AIEC)

Crohn's Disease (CD) is a chronic inflammatory bowel disease of unknown etiology. Recent work has shown that a new pathotype of Escherichia coli, Adherent Invasive E. coli (AIEC) may be associated with CD. AIEC has been shown to adhere to and invade epithelial cells and to replicate within macrophages (together this is called the AIEC phenotype). In this thesis, the AIEC phenotype of 84 E. coli strains were determined in order to identify the prevalence of this phenotype within the E. coli genus. This study showed that a significant proportion of E. coli strains (approx. 5%) are capable of adhering to and invading epithelial cells and undergoing intramacrophage replication. Moreover, the results presented in this study indicate a correlation between survival in macrophage and resistance to grazing by amoeba supporting the coincidental evolution hypothesis that resistance to amoebae could be a driving force in the evolution of pathogenicity in some bacteria, such as AIEC. In addition, this study has identified an important regulatory role for the CpxA/R two component system (TCS) in the invasive abilities of AIEC HM605, a colonic mucosa-associated CD isolate. A mutation in cpxR was shown to be defective in the invasion of epithelial cells and this defect was shown to be independent of motility or the expression of Type 1 fimbriae, factors that have been shown to be involved in the invasion of another strain of AIEC, isolated from a patient with ileal CD, called LF82. The CpxA/R TCS responds to disturbances in the cell envelope and has been implicated in the virulence of a number of Gram negative pathogens. In this study it is shown that the CpxA/R TCS regulates the expression of a potentially novel invasin called SinH. SinH is found in a number of invasive strains of E. coli and Salmonella. Moreover work presented here shows that a critical mechanism underpinning AIEC persistence in macrophages is the repair of DNA bases damaged by macrophage oxidants. Together these findings provide evidence to suggest that AIEC are a diverse group of E. coli and possess diverse molecular mechanisms and virulence factors that contribute to the AIEC phenotype. In addition, AIEC may have gone through different evolutionary histories acquiring various molecular mechanisms ultimately culminating in the AIEC phenotype. The gastrointestinal (GI) tract harbors a diverse microbiota; most are symbiotic or commensal however some bacteria have the potential to cause disease (pathobiont). The work presented here provides evidence to support the model that AIEC are pathobionts. AIEC strains can be carried as commensals in healthy guts however, when the intestinal homeostasis is disrupted, such as in the compromised gut of CD patients, AIEC may behave as opportunistic pathogens and cause and/or contribute to disease by driving intestinal inflammation.

Application of signal detection methods to fisheries management

The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

Quantifying the value of improved wind energy forecasts in a pool-based electricity market

This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.

Caregiver burden and resilience among Malaysian caregivers of individuals with severe mental illness

Little research has focused on caregiver burden experienced by Malaysian caregivers of individuals with mental illness, despite the fact that data in the Asian region shows almost threequarter of patients with mental illness live with family members. The aim of this research was to examine the levels of caregiver burden and resilience of caregivers of individuals with severe mental illness and to determine the influencing factors on caregiver burden. A quantitative, cross sectional, correlational design was used to measure burden and resilience and to explore the relationship between demographic variables, caregiver stressors, resilience and caregiver burden. This study was guided by the model of Carer Stress and Burden. Data collection was conducted over two months in summer 2014. A self-administered questionnaire that consisted of four sections measuring demographic data, primary stressors, caregiver burden and resilience was used to collect data. Two hundred and one caregivers of individuals with mental illness attending Psychiatric Outpatient Clinics in Malaysia were recruited. Samples were selected using non-probability, consecutive sampling. Factors that were found to be significantly associated with caregiver burden were caregivers’ age, gender, ethnic group, employment status, having a medical condition and current health status. The primary stressors found to be significantly associated with caregiver burden include the time spent for caregiving tasks, unavailability of support with caregiving tasks, lack of emotional support and patients’ behavioural disturbances. In addition, it was found that caregivers who were less resilient reported a higher level of caregiver burden. Findings from hierarchical multiple regression indicated that caregivers’ marital status, current health status, time spent for caregiving and resilience predicted caregiver burden. This research provides insight into caregiver burden among caregivers of individuals with mental illness in Malaysia. It highlights the important factors associated with caregiver burden and the significant role of resilience in reducing caregiver burden.