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(2022) Yunana, DanladiThesisExperimental and probabilistic methods were used to assess the risk of exposure to Legionella sp from aerators used in groundwater treatment plants. Factors considered include an assessment of conditions conducive to Legionella growth, detachment and inhalation by operators; the use of coupon studies to understand temporal changes and biofilm formation; and modelling the risk of Legionella using iterative Bayesian networks (BNs). A survey of 13 groundwater treatment plants (GWTPs) aerators, including tray, open and semi-enclosed systems were identified to feature design and operational risk factors favouring elevated levels of nutrients, water stagnation, challenging water quality, aerosolisation, and inconsistent operation and maintenance. Based on these observations, design considerations for the next generation of safer aerators that can overcome identified Legionella risks factors were outlined. Analysis of 300 sampling events from the aerators over five years indicated an average of 7% increase in colony counts between the inlet and outlet, indicating growth of Legionella within the aerators. In total, 28% of all samples collected from aerator surfaces testing positive for Legionella. However, there was no correlation between the type of aerator and Legionella positivity. Coupons were placed in aerators to assess temporal changes in fouling developed after 6 weeks of operation. The biological activity per unit area (ATP/cm2) was higher for samples collected on the sprayed (vertically placed) coupons (277 ng ATP/cm2) compared with the submerged (horizontally laid) (73 ng ATP/cm2) coupons. Concentrations of dissolved organic carbon (DOC) in the biofilm formed on the coupons were statistically similar for the two tested conditions. Comparing fouling characteristics from the lab and full-scale coupons confirmed the impact of surface orientation and influent characteristics on biofilm formation. In terms of cleaning of the fouled surface, NaOCl at (concentration greater than 6%) was found to achieve 99.9% efficiency in biofilm inactivation. Oxalic acid (concentration greater than 1%) significantly removed inorganic materials like iron and manganese. Combining biocides and antiscalants was therefore recommended to efficiently address fouling challenges in aerators. A BN which considered risk of exposure due to growth and transmission was developed using a fishbone diagram and bowtie analysis. The initial iterative output BN model was elicited deterministically through expert weighted scoring process and discretisation approach and defined relative contributions of risk variables. The BN model also efficiently categorised and differentiated Legionella risk thresholds. A revised BN model conceptually mapped and estimated the causes and consequences of Legionella aerosolisation separately. The Legionella growth sub-model showed weak prediction accuracy with a negative kappa coefficient, signifying inconsistency in predicted and observed Legionella occurrence. The effect of water quality was further explored with a data-driven learning approach using diverse historical water quality records. The optimised BN model utilised the greedy thick thinning approach, complemented with domain knowledge, and achieved superior performance accuracy exceeding 90%. The results indicated that water temperature, free chlorine, season, and heterotrophic plate count can be utilised to track Legionella occurrence in water systems.
(2022) Kokkinos, JohnThesisLess than 10% of patients with pancreatic ductal adenocarcinoma (PDAC) survive more than 5 years. One of the characteristic features that drive the aggressive nature of PDAC is its multicellular, heterogeneous, and fibrotic microenvironment. We previously identified a cytoskeletal protein, βIII-tubulin, as a novel therapeutic target in PDAC. However, the PDAC cell survival mechanisms controlled by βIII-tubulin were previously unknown. We also identified a major gap in the ability of human PDAC preclinical models to accurately mimic the 3D multicellular architecture and stroma of the disease. Thus, the aims of this work were (1) to evaluate the pro-survival role of βIII-tubulin in PDAC; (2) to establish a new patient derived tumour explant model that maintains all features of the PDAC microenvironment; and (3) to use the tumour explant model to test the clinical potential of silencing βIII-tubulin expression as well as two stromal targets that had been previously explored by our lab: solute carrier 7A11 (SLC7A11) and heat shock protein 47 (HSP47) Here, we identified that silencing βIII-tubulin in pancreatic cancer cells activated extrinsic apoptosis and increased their sensitivity to extrinsic apoptosis inducers including tumour necrosis factor-α (TNFα), Fas-ligand (FasL), and TNF-related apoptosis inducing factor (TRAIL). We next established the patient derived PDAC tumour explant model. We cultured whole-tissue tumour explants from PDAC patients for 12 days and demonstrated that explants maintained their 3D multicellular architecture, proliferative state, and collagen fibrosis. We also demonstrated the ability to deliver chemotherapeutics and siRNA-nanoparticles to the tumour explants. Finally, we tested the utility of this model to investigate the clinical potential of silencing three different therapeutic targets. We showed that therapeutic silencing of βIII-tubulin combined with TRAIL increased extrinsic apoptosis, decreased cell proliferation, and decreased tumour cell number. Inhibition of the stromal target SLC7A11 reduced tumour cell number and inhibited activity of stromal cancer-associated fibroblasts. Silencing of another target, HSP47, also led to a reduction in tumour cells and decreased cell proliferation. Overall, this work has discovered a previously unexplored role of βIII-tubulin as a brake on extrinsic cell death and has developed a new human PDAC preclinical model with utility in the drug development and precision medicine pipeline.