Investigating metabolomic biomarkers of hypoxic ischaemic encephalopathy

Background An early objective biomarker to predict the severity of hypoxic-ischaemic encephalopathy (HIE) and identify infants suitable for intervention remains elusive. This thesis aims to progress metabolomic markers of HIE through a pipeline of biomarker discovery and validation by employing a novel untargeted mass spectrometry metabolomic method. Methodology Term infants with perinatal asphyxia were recruited, all having umbilical cord blood (UCB) drawn and biobanked within three hours of birth. HIE was defined by Sarnat score at 24hours and continuous multichannel-EEG. Infant neurodevelopment was assessed at 36-42 months using the Bayley Scales of Infant and Toddler Development Ed. III (BSID-III). Untargeted metabolomic analysis of UCB was performed using direct injection FT-ICR mass spectrometry (DI FT-ICR MS). Putative metabolite annotations and lipid classes were assigned and pathway analysis was performed. Results Untargeted metabolomic analysis: Thirty enrolled infants were diagnosed with HIE, including 17 mild, 8 moderate, and 5 severe cases. Pathway analysis revealed that ΔHIE was associated with a 50% and 75% perturbation of tryptophan and pyrimidine metabolism respectively, alongside alterations in amino acid pathways. Significant metabolite alterations were detected from six putatively identified lipid classes including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids and prenol lipids. Outcome prediction: Metabolite model scores significantly correlated with outcome R=0.429 (model A) and R=0.549 (model B) respectively. Model B demonstrates the potential to predict both severe outcome (AUROC of 0.915) and intact survival (AUROC of 0.800). The effect of haemolysis: On average 5% of polar and 1.5% of non-polar features were altered between paired haemolysed and clean samples. However unsupervised multivariate analysis concluded that the preanalytical variability introduced by haemolysis was negligible compared with the inherent biological inter-individual variability. Conclusion This research has employed untargeted metabolomics to identify potential early cord blood biomarkers of HIE and has performed the technical validation of previously proposed markers.

Women's help seeking behaviour and the associated influencing factors on self discovery of a breast symptom

To investigate women’s help seeking behavior (HSB) following self discovery of a breast symptom and determine the associated influencing factors. A descriptive correlation design was used to ascertain the help seeking behavior (HSB) and the associated influencing factors of a sample of women (n = 449) with self discovered breast symptoms. The study was guided by the ‘Help Seeking Behaviour and Influencing Factors” conceptual framework (Facione et al., 2002; Meechan et al., 2003, 2002; Leventhal, Brissette and Leventhal, 2003 and O’Mahony and Hegarty, 2009b). Data was collected using a researcher developed multi-scale questionnaire package to ascertain women’s help seeking behavior on self discovery of a breast symptom and determine the factors most associated with HSB. Factors examined include: socio-demographics, knowledge and beliefs (regarding breast symptom; breast changes associated with breast cancer; use of alternative help seeking behaviours and presence or absence of a family history of breast cancer),emotional responses, social factors, health seeking habits and health service system utilization and help seeking behavior. A convenience sample (n = 449 was obtained by the researcher from amongst women attending the breast clinics of two large urban hospitals within the Republic of Ireland. All participants had self-discovered breast symptoms and no previous history of breast cancer. The study identified that while the majority of women (69.9%; n=314) sought help within one month, 30.1% (n=135) delayed help seeking for more than one month following self discovery of their breast symptom. The factors most significantly associated with HSB were the presenting symptom of ‘nipple indrawn/changes’ (p = 0.005), ‘ignoring the symptom and hoping it would go away’ (p < 0.001), the emotional response of being ‘afraid@ on symptom discovery (p = 0.005) and the perception/belief in longer symptom duration (p = 0.023). It was found that women who presented with an indrawn/changed nipple were more likely to delay (OR = 4.81) as were women who ‘ignored the symptoms and hoped it would go away’ (OR = 10.717). Additionally, the longer women perceived that their symptom would last, they more likely they were to delay (OR = 1.18). Conversely, being afraid following symptom discovery was associated with less delay (OR = 0.37; p=0.005). This study provides further insight into the HSB of women who self discovered breast symptoms. It highlights the complexity of the help seeking process, indicating that is not a linear event but is influenced by multiple factors which can have a significant impact on the outcomes in terms of whether women delay or seek help promptly. The study further demonstrates that delayed HSB persists amongst women with self discovered breast symptoms. This has important implications for continued emphasis on the promotion of breast awareness, prompt help seeking for self discovered breast symptoms and early detection and treatment of breast cancer, amongst women of all ages.

Delivering mobile cloud services to the user: description, discovery, and consumption

The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.