Novel ingredients from brewers' spent grain - bioactivity in cell culture model systems and bioactivity retention in fortified food products

Functional food ingredients, with scientifically proven and validated bioactive effects, present an effective means of inferring physiological health benefits to consumers to reduce the risk of certain diseases. The search for novel bioactive compounds for incorporation into functional foods is particularly active, with brewers’ spent grain (BSG, a brewing industry co-product) representing a unique source of potentially bioactive compounds. The DNA protective, antioxidant and immunomodulatory effects of phenolic extracts from both pale (P1 - P4) and black (B1 – B4) BSG were examined. Black BSG extracts significantly (P < 0.05) protected against DNA damage induced by hydrogen peroxide (H2O2) and extracts with the highest total phenolic content (TPC) protected against 3-morpholinosydnonimine hydrochloride (SIN-1)-induced oxidative DNA damage, measured by the comet assay. Cellular antioxidant activity assays were used to measured antioxidant potential in the U937 cell line. Extracts P1 – P3 and B2 - B4 demonstrated significant (P < 0.05) antioxidant activity, measured by the superoxide dismutase (SOD) activity, catalase (CAT) activity and gluatathione (GSH) content assays. Phenolic extracts P2 and P3 from pale BSG possess anti-inflammatory activity measured in concanavalin-A (conA) stimulated Jurkat T cells by an enzyme-linked immunosorbent assay (ELISA); significantly (P < 0.05) reducing production of interleukin-2 (IL-2), interleukin-4 (IL-4, P2 only), interleukin-10 (IL-10) and interferon-γ (IFN-γ). Black BSG phenolic extracts did not exhibit anti-inflammatory effects in vitro. Hydroxycinnamic acids (HA) have previously been shown to be the phenolic acids present at highest concentration in BSG; therefore the HA profile of the phenolic extracts used in this research, the original barley (before brewing) and whole BSG was characterised and quantified using high performance liquid chromatography (HPLC). The concentration of HA present in the samples was in the order of ferulic acid (FA) > p-coumaric acid (p-CA) derivatives > FA derivatives > p-CA > caffeic acid (CA) > CA derivatives. Results suggested that brewing and roasting decreased the HA content. Protein hydrolysates from BSG were also screened for their antioxidant and anti-inflammatory potential. A total of 34 BSG protein samples were tested. Initial analyses of samples A – J found the protein samples did not exert DNA protective effects (except hydrolysate H) or antioxidant effects by the comet and SOD assays, respectively. Samples D, E, F and J selectively reduced IFN-γ production (P < 0.05) in Jurkat T cells, measured using enzyme linked immunosorbent assay (ELISA). Further testing of hydrolysates K – W, including fractionated hydrolysates with molecular weight < 3, < 5 and > 5 kDa, found that higher molecular weight (> 5 kDa) and unfractionated hydrolysates demonstrate greatest anti-inflammatory effects, while fractionated hydrolysates were also shown to have antioxidant activity, by the SOD activity assay. A commercially available yogurt drink (Actimel) and snack-bar and chocolate-drink formulations were fortified with the most bioactive phenolic and protein samples – P2, B2, W, W < 3 kDa, W < 5 kDa, W > 5 kDa. All fortified foods were subjected to a simulated gastrointestinal in vitro digestion procedure and bioactivity retention in the digestates was determined using the comet and ELISA assays. Yogurt fortified with B2 digestate significantly (P < 0.05) protected against H2O2-induced DNA damage in Caco-2 cells. Greatest immunomodulatory activity was demonstrated by the snack-bar formulation, significantly (P < 0.05) reducing IFN-γ production in con-A stimulated Jurkat T cells. Hydrolysate W significantly (P < 0.05) increased the IFN-γ reducing capacity of the snack-bar. Addition of fractionated hydrolysate W < 3 kDa and W < 5 kDa to yogurt also reduced IL-2 production to a greater extent than the unfortified yogurt (P < 0.05).

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Functional application of lactic acid bacteria exopolysaccharide in complex food systems

Lactic acid bacteria expolysaccharides (LAB-EPS), in particular those formed from sucrose have the potential to improve food and beverage rheology and enhance their sensory properties potentially replacing or reducing expensive hydrocolloids currently used as improvers in food and beverage industries. Addition of sucrose not only enables EPS formation but also affects organic acid formation, thus influencing the sensory properties of the resulting food/beverage products. The first part of the study the organoleptic modulation of barley malt derived wort fermented using in situ produced bacterial polysaccharides has been investigated. Weisella cibaria MG1 was capable to produce exopolysaccharides during sucrosesupplemented barley malt derived wort fermentation. Even though the strain dominated the (sucrose-supplemented) wort fermentation, it was found to produce EPS (14.4 g l-1) with lower efficiency than in SucMRS (34.6 g l-1). Higher maltose concentration in wort led to the increased formation of oligosaccharide (OS) at the expense of EPS. Additionally, small amounts of organic acids were formed and ethanol remained below 0.5% (v/v). W. cibaria MG1 fermented worts supplemented with 5 or 10% sucrose displayed a shear-thinning behaviour indicating the formation of polymers. This report showed how novel and nutritious LAB fermented wort-base beverage with prospects for further advancements can be formulated using tailored microbial cultures. In the next step, the impact of exopolysaccharide-producing Weissella cibaria MG1 on the ability to improve rheological properties of fermented plant-based milk substitute plant based soy and quinoa grain was evaluated. W. cibaria MG1 grew well in soy milk, exceeding a cell count of log 8 cfu/g within 6 h of fermentation. The presence of W. cibaria MG1 led to a decrease in gelation and fermentation time. EPS isolated from soy yoghurts supplemented with sucrose were higher in molecular weight (1.1 x 108 g/mol vs 6.6 x 107 g/mol), and resulted in reduced gel stiffness (190 ± 2.89 Pa vs 244 ± 15.9 Pa). Soy yoghurts showed typical biopolymer gels structure and the network structure changed to larger pores and less cross-linking in the presence of sucrose and increasing molecular weight of the EPS. In situ investigation of Weissella cibaria MG1 producing EPS on quinoa-based milk was performed. The production of quinoa milk, starting from wholemeal quinoa flour, was optimised to maximise EPS production. On doing that, enzymatic destructuration of protein and carbohydrate components of quinoa milk was successfully achieved applying alpha-amylase and proteases treatments. Fermented wholemeal quinoa milk using Weissella cibaria MG1 showed high viable cell counts (>109 cfu/mL), a pH of 5.16, and significantly higher water holding capacity (WHC, 100 %), viscosity (> 0. 5 Pa s) and exopolysaccharide (EPS) amount (40 mg/L) than the chemically acidified control. High EPS (dextran) concentration in quinoa milk caused earlier aggregation because more EPS occupy more space, and the chenopodin were forced to interact with each other. Direct observation of microstructure in fermented quinoa milk indicated that the network structures of EPS-protein could improve the texture of fermented quinoa milk. Overall, Weissella cibaria MG1 showed favorable technology properties and great potential for further possible application in the development of high viscosity fermented quinoa milk. The last part of the study investigate the ex-situ LAB-EPS (dextran) application compared to other hydrocolloids as a novel food ingredient to compensate for low protein in biscuit and wholemeal wheat flour. Three hydrocolloids, xanthan gum, dextran and hydroxypropyl methylcellulose, were incorporated into bread recipes based on high-protein flours, low-protein flours and coarse wholemeal flour. Hydrocolloid levels of 0–5 % (flour basis) were used in bread recipes to test the water absorption. The quality parameters of dough (farinograph, extensograph, rheofermentometre) and bread (specific volume, crumb structure and staling profile) were determined. Results showed that xanthan had negative impact on the dough and bread quality characteristics. HPMC and dextran generally improved dough and bread quality and showed dosage dependence. Volume of low-protein flour breads were significantly improved by incorporation of 0.5 % of the latter two hydrocolloids. However, dextran outperformed HPMC regarding initial bread hardness and staling shelf life regardless the flour applied in the formulation.