Advanced polymer membrane development in pervaporation dehydration and lateral flow diagnostics

The work in this thesis concerns the advanced development of polymeric membranes of two types; pervaporation and lateral-flow. The former produced from a solution casting method and the latter from a phase separation. All membranes were produced from casting lacquers. Early research centred on the development of viable membranes. This led to a supported polymer blend pervaporation membrane. Selective layer: plasticized 4:1 mass ratio sodium-alginate: poly(vinyl-alcohol) polymer blend. Using this membrane, pervaporation separation of ethanol/water mixtures was carefully monitored as a function of film thickness and time. Contrary to literature expectations, these films showed increased selectivity and decreased flux as film thickness was reduced. It is argued that morphology and structure of the polymer blend changes with thickness and that these changes define membrane efficiency. Mixed matrix membrane development was done using spherical, discreet, size-monodisperse mesoporous silica particles of 1.8 - 2μm diameter, with pore diameters of ~1.8 nm were incorporated into a poly(vinyl alcohol) [PVA] matrix. Inclusion of silica benefitted pervaporation performance for the dehydration of ethanol, improving flux and selectivity throughout in all but the highest silica content samples. Early lateral-flow membrane research produced a membrane from a basic lacquer composition required for phase inversion; polymer, solvent and non-solvent. Results showed that bringing lacquers to cloud point benefits both the pore structure and skin layers of the membranes. Advancement of this work showed that incorporation of ethanol as a mesosolvent into the lacquer effectively enhances membrane pore structure resulting in an improvement in lateral flow rates of the final membranes. This project details the formation mechanics of pervaporation and lateral-flow membranes and how these can be controlled. The principle methods of control can be applied to the formation of any other flat sheet polymer membranes, opening many avenues of future membrane research and industrial application.

Digital signal processing and artificial intelligence for the automated classification of food allergy

As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis

A study of diet and health in the elderly; the gut microbiota as a source of bioactive agents

The global proportion of older persons is increasing rapidly. Diet and the intestinal microbiota independently and jointly contribute to health in the elderly. The habitual dietary patterns and functional microbiota components of elderly subjects were investigated in order to identify specific effector mechanisms. A study of the dietary intake of Irish community-dwelling elderly subjects showed that the consumption of foods high in fat and/or sugar was excessive, while consumption of dairy foods was inadequate. Elderly females typically had a more nutrient- dense diet than males and a considerable proportion of subjects, particularly males, had inadequate intakes of calcium, magnesium, vitamin D, folate, zinc and vitamin C. The association between dietary patterns, glycaemic index and cognitive function was also investigated. Elderly subjects consuming ‘prudent’ dietary patterns had better cognitive function compared to those consuming ‘Western’ dietary patterns. Furthermore, fully-adjusted regression models revealed that a high glycaemic diet was associated with poor cognitive function, demonstrating a new link between nutrition and cognition. An extensive screening study of the elderly faecal-derived microbiota was also undertaken to examine the prevalence of antimicrobial production by intestinal bacteria. A number of previously characterised bacteriocins were isolated (gassericin T, ABP-118, mutacin II, enterocin L-50 and enterocin P) in this study. Interestingly, a Lactobacillus crispatus strain was found to produce a potentially novel antimicrobial compound. Full genome sequencing of this strain revealed the presence of three loci which exhibited varying degrees of homology with the genes responsible for helveticin J production in Lb. helveticus. An additional study comparing the immunomodulatory capacity of ‘viable’ and ‘non-viable’ Bifidobacterium strains found that Bifidobacterium-fermented milks (BFMs) containing ‘non-viable’ cells could stimulate levels of IL-10 and TNF-α in a manner similar to those stimulated by BFMs containing ‘viable’ cells in vitro.