Artifical intelligence in medical application: An exploration

The advancement in computer technology has encouraged the researchers to develop software for assisting doctors in making decision without consulting the specialists directly. The software development exploits the potential of human intelligence such as reasoning, making decision, learning (by experiencing) and many others. Artificial intelligence is not a new concept, yet it has been accepted as a new technology in computer science. It has been applied in many areas such as education, business, medical and manufacturing. This paper explores the potential of artificial intelligence techniques particularly for web-based medical applications. In addition, a model for web-based medical diagnosis and prediction is proposed

Mecanismos para controlo e gestão de redes 5G: redes de operador

In 5G networks, time-series data will be omnipresent for the monitoring of network metrics. With the increase in the number of Internet of Things (IoT) devices in the next years, it is expected that the number of real-time time-series data streams increases at a fast pace. To be able to monitor those streams, test and correlate different algorithms and metrics simultaneously and in a seamless way, time-series forecasting is becoming essential for the pro-active successful management of the network. The objective of this dissertation is to design, implement and test a prediction system in a communication network, that allows integrating various networks, such as a vehicular network and a 4G operator network, to improve the network reliability and Quality-of-Service (QoS). To do that, the dissertation has three main goals: (1) the analysis of different network datasets and implementation of different approaches to forecast network metrics, to test different techniques; (2) the design and implementation of a real-time distributed time-series forecasting architecture, to enable the network operator to make predictions about the network metrics; and lastly, (3) to use the forecasting models made previously and apply them to improve the network performance using resource management policies. The tests done with two different datasets, addressing the use cases of congestion management and resource splitting in a network with a limited number of resources, show that the network performance can be improved with proactive management made by a real-time system able to predict the network metrics and act on the network accordingly. It is also done a study about what network metrics can cause reduced accessibility in 4G networks, for the network operator to act more efficiently and pro-actively to avoid such eventsEm redes 5G, séries temporais serão omnipresentes para a monitorização de métricas de rede. Com o aumento do número de dispositivos da Internet das Coisas (IoT) nos próximos anos, é esperado que o número de fluxos de séries temporais em tempo real cresça a um ritmo elevado. Para monitorizar esses fluxos, testar e correlacionar diferentes algoritmos e métricas simultaneamente e de maneira integrada, a previsão de séries temporais está a tornar-se essencial para a gestão preventiva bem sucedida da rede. O objetivo desta dissertação é desenhar, implementar e testar um sistema de previsão numa rede de comunicações, que permite integrar várias redes diferentes, como por exemplo uma rede veicular e uma rede 4G de operador, para melhorar a fiabilidade e a qualidade de serviço (QoS). Para isso, a dissertação tem três objetivos principais: (1) a análise de diferentes datasets de rede e subsequente implementação de diferentes abordagens para previsão de métricas de rede, para testar diferentes técnicas; (2) o desenho e implementação de uma arquitetura distribuída de previsão de séries temporais em tempo real, para permitir ao operador de rede efetuar previsões sobre as métricas de rede; e finalmente, (3) o uso de modelos de previsão criados anteriormente e sua aplicação para melhorar o desempenho da rede utilizando políticas de gestão de recursos. Os testes efetuados com dois datasets diferentes, endereçando os casos de uso de gestão de congestionamento e divisão de recursos numa rede com recursos limitados, mostram que o desempenho da rede pode ser melhorado com gestão preventiva da rede efetuada por um sistema em tempo real capaz de prever métricas de rede e atuar em conformidade na rede. Também é efetuado um estudo sobre que métricas de rede podem causar reduzida acessibilidade em redes 4G, para o operador de rede atuar mais eficazmente e proativamente para evitar tais acontecimentos.Mestrado em Engenharia de Computadores e Telemátic

THE ROLE OF DNA METHYLATION IN WHITE MATTER HYPERINTENSITY BURDEN: AN INTEGRATIVE APPROACH

Cerebral white matter hyperintensities (WMH) on MRI are an indicator of cerebral small vessel disease, a major risk factor for vascular dementia and stroke. DNA methylation may contribute to the molecular underpinnings of WMH, which are highly heritable. We performed a meta-analysis of 11 epigenome-wide association studies in 6,019 middle-aged to elderly subjects, who were free of dementia and stroke and were of African (AA) or European (EA) descent. In each study, association between WMH volume and each CpG was tested within ancestry using a linear mixed model, adjusted for age, sex, total intracranial volume, white blood cell count, technical covariates, BMI, smoking and blood pressure (BP). To detect differentially methylated regions (DMRs), we also calculated region-based p values accounting for spatial correlations among CpGs. No individual CpG reached epigenome-wide significance, but suggestive novel associations were identified with cg17577122 (CLDN5, P=2.39E-7), cg24202936 (LOC441601, P=3.78E-7), cg03116124 (TRIM67, P=6.55E-7), cg04245766 (BMP4, P=3.78E-7) and cg06809326 (CCDC144NL, P=6.14E-7). Gene enrichment analyses implicated pathways involved in regulation of cell development and differentiation, especially of endothelial cells. We identified 11 DMRs (PSidak\u3c0.05) and two were mapped to BP-related genes (HIVEP3, TCEA2). The most significant DMRs were mapped to PRMT1, a protein arginine methyltransferase involved in glioblastomagenesis (P=7.9E-12), and mapped to CCDC144NL-AS1, an antisense transcript of CCDC144NL (P=1.6E-11). Genes mapping to DMRs were enriched in biological processes related to lipoprotein metabolism and transport. Bi-directional Mendelian randomization analysis showed that DNA methylation level at cg06809326 influenced WMH burden (OR [95% CI] = 1.7[1.2-2.5], P=0.001) but not the reverse (P=0.89). Additionally, increased methylation at cg06809326 was associated with lower expression of CCDC144NL (P=3.3E-2), and two-step Mendelian randomization analysis supported its mediating role in the association of cg06809326 and WMH burden. CCDC144NL is known to be associated with diabetic retinopathy and the coiled coil proteins in general promotes integrin-dependent cell adhesion. Integrin-related pathway was further supported by integrative genetic analyses. In conclusion, we identified novel epigenetic loci associated with WMH burden, and further supported the role of cg06809326 in the WMH etiology implicating integrin-mediated pathology

Environmental Disasters and Individuals’ Emergency Preparedness:

Environmental disasters are becoming more frequent. These disasters not only include the most common natural disasters, but also include man-made disasters, such as public health, accident disasters, etc., which have caused greater damage to human society and cities. Because of the limitations of a single government-led model in emergency response, the emergency preparedness of communities, families and individuals are more important. In particular, the emergency preparedness psychology and behavior of individuals directly determine whether or not they can effectively protect themselves and their families in the first time of disaster. This Special Issue focuses on environmental disasters and individuals’ emergency preparedness in the perspective of psychology and behavior

The Genetics of Primary Immunodeficiency in Children

Studies of children with recurrent infection demonstrate that primary immunodeficiency (PID) has a significant genetic component. In PID, over 300 genes of high penetrance inherited mostly in autosomal recessive manner have already been identified. However, many children, including those with early onset immunodeficiency have not received a genetic diagnosis, despite use of targeted sequencing methods. I performed bioinformatic analysis in whole genome sequencing data in patients with immunodeficiency. These analyses were initially in a small cohort of affected children at Great Ormond Street in whom a genetic diagnosis was not known. I devised and utilised bioinformatic programs to identify novel genetic variants in this cohort. I evaluated the performance of whole genome sequence analyses with targeted gene panel analyses, which is the most utilised method of genetic diagnosis. To expand my analysis, I looked at a larger cohort of young people and adults with immunodeficiency as part of the large national collaborative project NIHR Bioresource Rare Diseases BRIDGE-PID project. I quantified the burden of rare coding variation in a case cohort compared to controls and used rare variant association analysis to identify potential novel candidate genes in primary immunodeficiency. The final chapter focuses on 2 novel genetic variants found in the cohort and our initial functional testing to verify genetic diagnosis. The work presented in this thesis demonstrates novel genetic causes of immunodeficiency and their functional implications. The results of my work have improved understanding of the genetic architecture of primary immunodeficiencies and has clinical utility in the diagnosis and subsequent treatment of immunodeficiency

Exploring the Epigenome of Neurons and Glia in Vitro to Determine their Utility as a Model for Alzheimer's Disease

Alzheimer’s disease is a progressive neurodegenerative condition that is characterised by distinct neuropathological changes. Within the last decade post mortem human brain samples have been used to show that there are robust epigenetic changes occurring in the brain during disease. However, as these samples are collected shortly after death they are a reflection of only the very end stages of disease. Through the exposure of differentiated adult cells to exogenous reprogramming factors it is now possible to generate induced pluripotent stem cells which have the potential to differentiate into any cell type in the body. Over recent years reseach has moved towards using these stem cells to generate neurons or microglia in order to study diseases of ageing such as Alzheimer’s disease. However, there are relatively few epigenetic studies that have been undertaken using induced pluripotent stem cells. As there are global cellular epigenetic changes occurring during the induction of pluripotency and re-differentiation it is critical to ensure we understand the DNA methylation changes occurring during normal neuronal differentiation before using these as a model of Alzheimer’s disease or other diseases of ageing. The aim of this thesis is to first characterise the DNA methylation changes that are occurring in neuronal and microglial models that are exposed to AD-relevant exposures such as differentiation and maturation, drug treatment and immune challenge. This will largely be achieved through measuring DNA methylation using the Illumina Infinium HumanMethylationEPIC BeadChip array which provides information on the DNA methylation levels at over 850,000 loci across the genome.Alzheimers Research UKAlzheimer's Societ

Methylation of NOTCH genes in normal and at-risk colorectal epithelium

PhD ThesisIntroduction Colorectal cancer (CRC) arises from genetic defects in stem cells. NOTCH signalling plays a key role in stem cell replication control. NOTCH-related genes are overexpressed in CRC. The mechanism for this is not known but could include epigenetic activation of NOTCH oncogenes via promoter hypomethylation. Methylation can be modulated by environmental stimuli including dietary factors such as butyrate, produced by bacterial fermentation of non-digestible carbohydrates in the colon. Butyrate exerts potent anti-oncogenic effects in the colorectal mucosa. Methods Participants were recruited at endoscopy and included those at normal risk of CRC (n=75), or higher risk of CRC because of previous adenomatous polyps (n=28) or ulcerative colitis (n=12). Participants provided 9 rectal biopsies. Normal risk participants were randomised to resistant starch (Hi-maize 260) or polydextrose supplementation in a 2x2 factorial placebo controlled trial for 50 days. Methylation of several CpG sites in the promoters of JAG1 (NOTCH pathway ligand) and RBP-J (NOTCH intracellular activator) was quantified using pyrosequencing. Results For JAG1 there was trend towards lower methylation at all CpG sites in those at higher CRC risk. Methylation at RBP-J CpG 11 was lower in polyp patients than in controls (18.0(1.5) vs. 23.6% (0.8), p=0.011). At JAG1 CpG 4, methylation increased following polydextrose supplementation compared to placebo (3.1(0.4) vs. 1.7%(0.4), p=0.009). A similar, but non-significant, trend was observed at other CpG sites for JAG1. Conclusions DNA methylation of NOTCH signalling genes is altered in macroscopically normal colorectal mucosa of patients at higher CRC risk. The observed changes in JAG1 methylation after polydextrose supplementation are consistent with a protective effect against carcinogenesis.Northumbria Healthcare NHS Foundation Trust: The BBSRC (grant reference BH090948)