Tailoring treatment to the individual in type 2 diabetes practical guidance from the Global Partnership for Effective Diabetes Management

Good glycaemic control continues to be the most effective therapeutic manoeuvre to reduce the risk of development and/or progression of microvascular disease, and therefore remains the cornerstone of diabetes management despite recent scepticism about tight glucose control strategies. The impact on macrovascular complications is still a matter of debate, and so glycaemic control strategies should be placed in the context of multifactorial intervention to address all cardiovascular risk factors. Approaches to achieve glycaemic targets should always ensure patient safety, and results from recent landmark outcome studies support the need for appropriate individualisation of glycaemic targets and of the means to achieve these targets, with the ultimate aim to optimise outcomes and minimise adverse events, such as hypoglycaemia and marked weight gain. The primary goal of the Global Partnership for Effective Diabetes Management is the provision of practical guidance to improve patient outcomes and, in this article, we aim to support healthcare professionals in appropriately tailoring type 2 diabetes treatment to the individual. Patient groups requiring special consideration are identified, including newly diagnosed individuals with type 2 diabetes but no complications, individuals with a history of inadequate glycaemic control, those with a history of cardiovascular disease, children and individuals at risk of hypoglycaemia. Practical guidance specific to each group is provided.

Person-oriented and process-oriented teachers : an investigation of the links between ESOL teachers' personal belief systems and approaches to teaching

This thesis looks to two traditions in research into language teaching, teacher beliefs and classroom interaction, in order to investigate the question: Do teachers of ESOL have an identifiable and coherent system of beliefs about teaching and learning that may account for different approaches to teaching? A qualitative approach to research is taken, following a case study tradition, in order to carry out an in-depth study into the beliefs of six ESOL teachers. Five teachers participated in an initial pilot study and two subsequently became the main case studies for the research. The beliefs of a sixth teacher were then investigated to verify the findings. Semi-structured interviews and classroom observations were carried out with all the teachers. The teachers in the study were found to have personal belief systems that cohere around two orientations to teaching and learning - a person orientation and a process orientation. Moreover, the findings suggest that underlying the orientations is the perception that teachers have of their teacher identity, in terms of whether this is seen as a separate identity or as part of their personality. It is suggested that the two orientations may offer a powerful tool for teacher education as it is increasingly recognised that, in order to be effective, teacher educators must take into account the beliefs that teachers bring with them to training and development programmes. An initial investigations into the teachers’ classroom behaviour suggests that while their methodologies approach may be very similar there are fundamental differences in their interactions patterns and these differences may be a result of their own orientation. However, while teachers’ personal belief systems undoubtedly underlie their approach to teaching, further research is needed to establish the extent and the nature of the relationship between orientation and classroom interaction.

The effects of varying forms and degrees of government intervention upon the effective competitiveness of UK small businesses

This doctoral thesis responds to the need for greater understanding of small businesses and their inherent unique problem-types. Integral to the investigation is the theme that for governments to effectively influence small business, a sound understanding of the factors they are seeking to influence is essential. Moreover, the study, in its recognition of the many shortcomings in management research and, in particular that the research methods and approaches adopted often fail to give adequate understanding of issues under study, attempts to develop an innovative and creative research approach. The aim thus being to produce, not only advances in small business management knowledge from the standpoints of government policy makers and `lq recipient small business, but also insights into future potential research method for the continued development of that knowledge. The origins of the methodology lay in the non-acceptance of traditional philosophical positions in epistemology and ontology, with a philosophical standpoint of internal realism underpinning the research. Internal realism presents the basis for the potential co-existence of qualitative and quantitative research strategy and underlines the crucial contributory role of research method in provision of ultimate factual status of the assertions of research findings. The concept of epistemological bootstrapping is thus used to develop a `lq partial research framework to foothold case study research, thereby avoiding limitations of objectivism and brute inductivism. The major insights and issues highlighted by the `lq bootstrap, guide the researcher around the participant case studies. A novel attempt at contextualist (linked multi-level and processual) analysis was attempted in the major in-depth case study, with two further cases playing a support role and contributing to a balanced emphasis of empirical research within the context of time constraints inherent within part-time research.

Novel formulations for antigen delivery using biodegradable polymers: new approaches for the use of new and established adjuvants

The use of immunological adjuvants has been established since 1924 and ever since many candidates have been extensively researched in vaccine development. The controlled release of vaccine is another area of biotechnology research, which is advancing rapidly with great potential and success. Encapsulation of peptide and protein drugs within biodegradable microspheres has been amongst the most successful of approaches within the past decade. The present studies have focused on combining the advantages of microsphere delivery systems composed of biodegradable polylactide (PLLA) and polylactide-co-glycolide (PLGA) polymers with that of safe and effective adjuvants. The research efforts were directed to the development of single-dose delivery vehicles which, can be manufactured easily, safely, under mild and favourable conditions to the encapsulated antigens. In pursuing this objective non ionic block copolymers (NIBCs) (Pluronics@ LI01 and L121) were incorporated within poly-dl-lactide (PDLA) micorospheres prepared with emulsification-diffusion method. LI0I and L121 served both as adjuvants and stabilising agents within these vaccine delivery vehicles. These formulations encapsulating the model antigens lysozyme, ovalbumin (OVA) and diphtheria toxoid (DT) resulted in high entrapment efficiency (99%), yield (96.7%) and elicited high and sustained immune response (IgG titres up to 9427) after one single administration over nine months. The structural integrity of the antigens was preserved within these formulations. In evaluating new approaches for the use of well-established adjuvants such as alum, these particles were incorporated within PLLA and PLGA microspheres at much lesser quantities (5-10 times lower) than those contained within conventional alum-adsorbed vaccines. These studies focused on the incorporation of the clinically relevant tetanus toxoid (TT) antigen within biodegradable microspheres. The encapsulation of both alum particles and TT antigen within these micropheres resulted in preparations with high encapsulation efficiency (95%) and yield (91.2%). The immune response to these particles was also investigated to evaluate the secretion of serum IgG, IgG1, IgG2a and IgG2b after a single administration of these vaccines. The Splenic cells proliferation was also investigated as an indication for the induction of cell mediated immunity. These particles resulted in high and sustained immune response over a period of 14 months. The stability of TT within particles was also investigated under dry storage over a period of several months. NIBC microspheres were also investigated as potential DNA vaccine delivery systems using hepatitis B plasmid. These particles resulted in micro spheres of 3-5 μm diameter and were shown to preserve the integrity of the encapsulated (27.7% entrapment efficiency) hepatitis B plasmid.

An argument for using participatory approaches for the design of online health interventions targeted at young women

The Internet is becoming an increasingly important portal to health information and means for promoting health in user populations. As the most frequent users of online health information, young women are an important target population for e-health promotion interventions. Health-related websites have traditionally been generic in design, resulting in poor user engagement and affecting limited impacts on health behaviour change. Mounting evidence suggests that the most effective health promotion communication strategies are collaborative in nature, fully engaging target users throughout the development process. Participatory design approaches to interface development enable researchers to better identify the needs and expectations of users, thus increasing user engagement in, and promoting behaviour change via, online health interventions. This article introduces participatory design methods applicable to online health intervention design and presents an argument for the use of such methods in the development of e-Health applications targeted at young women.

Reporter ion-based mass spectrometry approaches for the detection of non-enzymatic protein modifications in biological samples

Development of mass spectrometry techniques to detect protein oxidation, which contributes to signalling and inflammation, is important. Label-free approaches have the advantage of reduced sample manipulation, but are challenging in complex samples owing to undirected analysis of large data sets using statistical search engines. To identify oxidised proteins in biological samples, we previously developed a targeted approach involving precursor ion scanning for diagnostic MS3 ions from oxidised residues. Here, we tested this approach for other oxidations, and compared it with an alternative approach involving the use of extracted ion chromatograms (XICs) generated from high-resolution MSMS data using very narrow mass windows. This accurate mass XIC data methodology was effective at identifying nitrotyrosine, chlorotyrosine, and oxidative deamination of lysine, and for tyrosine oxidations highlighted more modified peptide species than precursor ion scanning or statistical database searches. Although some false positive peaks still occurred in the XICs, these could be identified by comparative assessment of the peak intensities. The method has the advantage that a number of different modifications can be analysed simultaneously in a single LC-MSMS run. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Biological significance: The use of accurate mass extracted product ion chromatograms to detect oxidised peptides could improve the identification of oxidatively damaged proteins in inflammatory conditions. © 2013 Elsevier B.V.

Automated System for Effective Internet Marketing Campaign (ASEIMC)

The purpose of the paper is to present an automated system for realization of effective internet marketing campaign (ASEIMC). The constantly growing number of websites available online brings more problems for the contemporary enterprises to reach their potential customers. Therefore the companies have to discover novel approaches to increase their online sales. The presented ASEIMC system gives such an approach and helps small and medium enterprises to compete for customers with big corporations in the Internet space.

Temperature management for heterogeneous multi-core FPGAs using adaptive evolutionary multi-objective approaches

Heterogeneous multi-core FPGAs contain different types of cores, which can improve efficiency when used with an effective online task scheduler. However, it is not easy to find the right cores for tasks when there are multiple objectives or dozens of cores. Inappropriate scheduling may cause hot spots which decrease the reliability of the chip. Given that, our research builds a simulating platform to evaluate all kinds of scheduling algorithms on a variety of architectures. On this platform, we provide an online scheduler which uses multi-objective evolutionary algorithm (EA). Comparing the EA and current algorithms such as Predictive Dynamic Thermal Management (PDTM) and Adaptive Temperature Threshold Dynamic Thermal Management (ATDTM), we find some drawbacks in previous work. First, current algorithms are overly dependent on manually set constant parameters. Second, those algorithms neglect optimization for heterogeneous architectures. Third, they use single-objective methods, or use linear weighting method to convert a multi-objective optimization into a single-objective optimization. Unlike other algorithms, the EA is adaptive and does not require resetting parameters when workloads switch from one to another. EAs also improve performance when used on heterogeneous architecture. A efficient Pareto front can be obtained with EAs for the purpose of multiple objectives.

Truly interactive approaches to browsing image databases

Image collections are ever growing and hence efficient and effective tools to manage these repositories are highly sought after. In this paper, we present effective image browsing systems that are operated on a large multi-touch environment for truly interactive exploration. Not only do image browsers pose a useful alternative to retrieval-based systems, they also provide a visualisation of the whole image collection and allow users to interactively explore particular parts of the collection. Our systems are based on the idea that visually similar images are located close to each other in the visualisation, that image thumbnails are arranged on a regular lattice (either a regular grid projected onto a sphere or a hexagonal lattice), and that large image datasets can be accessed through a hierarchical tree structure. A pilot study has shown that the presented systems do indeed work well and are preferred compared to conventional image browsers. © 2011 IEEE.

Geographic Information Systems-Based Approaches to Study Congressional Redistricting in the United States

The ability for the citizens of a nation to determine their own representation has long been regarded as one of the most critical objectives of any electoral system. Without having the assurance of equality in representation, the fundamental nature and operation of the political system is severely undermined. Given the centuries of institutional reforms and population changes in the American system, Congressional Redistricting stands as an institution whereby this promise of effective representation can either be fulfilled or denied. The broad set of processes that encapsulate Congres- sional Redistricting have been discussed, experimented, and modified to achieve clear objectives and have long been understood to be important. Questions remain about how the dynamics which link all of these processes operate and what impact the real- ities of Congressional Redistricting hold for representation in the American system. This dissertation examines three aspects of how Congressional Redistricting in the Untied States operates in accordance with the principle of “One Person, One Vote.” By utilizing data and data analysis techniques of Geographic Information Systems (GIS), this dissertation seeks to address how Congressional Redistricting impacts the principle of one person, one vote from the standpoint of legislator accountability, redistricting institutions, and the promise of effective minority representation.

National, inter-institutional, graduate modules – blended learning approaches for PhD education in Ireland

This paper is a case study that describes the design and delivery of national PhD lectures with 40 PhD candidates in Digital Arts and Humanities in Ireland simultaneously to four remote locations, in Trinity College Dublin, in University College Cork, in NUI Maynooth and NUI Galway. Blended learning approaches were utilized to augment traditional teaching practices combining: face-to-face engagement, video-conferencing to multiple sites, social media lecture delivery support – a live blog and micro blogging, shared, open student web presence online. Techniques for creating an effective, active learning environment were discerned via a range of learning options offered to students through student surveys after semester one. Students rejected the traditional lecture format, even through the novel delivery method via video link to a number of national academic institutions was employed. Students also rejected the use of a moderated forum as a means of creating engagement across the various institutions involved. Students preferred a mix of approaches for this online national engagement. The paper discusses successful methods used to promote interactive teaching and learning. These included Peer to peer learning, Workshop style delivery, Social media. The lecture became a national, synchronous workshop. The paper describes how allowing students to have a voice in the virtual classroom they become animated and engaged in an open culture of shared experience and scholarship, create networks beyond their institutions, and across disciplinary boundaries. We offer an analysis of our experiences to assist other educators in their course design, with a particular emphasis on social media engagement.

Putting Adequate Financial and Human Resources in Healthcare for Effective Universal Health Coverage in Kenya: Lessons and Experiences from China

In recent years, most low and middle-income countries, have adopted different approaches to universal health coverage (UHC), to ensure equity and financial risk protection in accessing essential healthcare services. UHC-related policies and delivery strategies are largely based on existing healthcare systems, a result of gradual development (based on local factors and priorities). Most countries have emphasized on health financing, and human resources for health (HRH) reform policies, based on good practices of several healthcare plans to deliver UHC for their population.

Health financing and labor market frameworks were used, to understand health financing, HRH dynamics, and to analyze key health policies implemented over the past decade in Kenya’s effort to achieve UHC. Through the understanding, policy options are proposed to Kenya; analyzing, and generating lessons from health financing, and HRH reforms experiences in China. Data was collected using mixed methods approach, utilizing both quantitative (documents and literature review), and qualitative (in-depth interviews) data collection techniques.

The problems in Kenya are substantial: high levels of out-of-pocket health expenditure, slow progress in expanding health insurance among informal sector workers, inefficiencies in pulling of health are revenues, inadequate deployed HRH, maldistribution of HRH, and inadequate quality measures in training health worker. The government has identified the critical role of strengthening primary health care and the National Hospital Insurance Fund (NHIF) in Kenya’s move towards UHC. Strengthening primary health care requires; re-defining the role of hospitals, and health insurance schemes, and training, deploying and retaining primary care professionals according to the health needs of the population; concepts not emphasized in Kenya’s healthcare reforms or programs design. Kenya’s top leadership commitment is urgently needed for tougher reforms implementation, and important lessons from China’s extensive health reforms in the past decade are beneficial. Key lessons from China include health insurance expansion through rigorous research, monitoring, and evaluation, substantially increasing government health expenditure, innovative primary healthcare strengthening, designing, and implementing health policy reforms that are responsive to the population, and regional approaches to strengthening HRH.

Non-Pharmacological Approaches for Pain Management in Sickle Cell Disease: Development of a Mindfulness-Based Intervention

Background: Sickle Cell Disease (SCD) is a genetic hematological disorder that affects more than 7 million people globally (NHLBI, 2009). It is estimated that 50% of adults with SCD experience pain on most days, with 1/3 experiencing chronic pain daily (Smith et al., 2008). Persons with SCD also experience higher levels of pain catastrophizing (feelings of helplessness, pain rumination and magnification) than other chronic pain conditions, which is associated with increases in pain intensity, pain behavior, analgesic consumption, frequency and duration of hospital visits, and with reduced daily activities (Sullivan, Bishop, & Pivik, 1995; Keefe et al., 2000; Gil et al., 1992 & 1993). Therefore effective interventions are needed that can successfully be used manage pain and pain-related outcomes (e.g., pain catastrophizing) in persons with SCD. A review of the literature demonstrated limited information regarding the feasibility and efficacy of non-pharmacological approaches for pain in persons with SCD, finding an average effect size of .33 on pain reduction across measurable non-pharmacological studies. Second, a prospective study on persons with SCD that received care for a vaso-occlusive crisis (VOC; N = 95) found: (1) high levels of patient reported depression (29%) and anxiety (34%), and (2) that unemployment was significantly associated with increased frequency of acute care encounters and hospital admissions per person. Research suggests that one promising category of non-pharmacological interventions for managing both physical and affective components of pain are Mindfulness-based Interventions (MBIs; Thompson et al., 2010; Cox et al., 2013). The primary goal of this dissertation was thus to develop and test the feasibility, acceptability, and efficacy of a telephonic MBI for pain catastrophizing in persons with SCD and chronic pain.

Methods: First, a telephonic MBI was developed through an informal process that involved iterative feedback from patients, clinical experts in SCD and pain management, social workers, psychologists, and mindfulness clinicians. Through this process, relevant topics and skills were selected to adapt in each MBI session. Second, a pilot randomized controlled trial was conducted to test the feasibility, acceptability, and efficacy of the telephonic MBI for pain catastrophizing in persons with SCD and chronic pain. Acceptability and feasibility were determined by assessment of recruitment, attrition, dropout, and refusal rates (including refusal reasons), along with semi-structured interviews with nine randomly selected patients at the end of study. Participants completed assessments at baseline, Week 1, 3, and 6 to assess efficacy of the intervention on decreasing pain catastrophizing and other pain-related outcomes.

Results: A telephonic MBI is feasible and acceptable for persons with SCD and chronic pain. Seventy-eight patients with SCD and chronic pain were approached, and 76% (N = 60) were enrolled and randomized. The MBI attendance rate, approximately 57% of participants completing at least four mindfulness sessions, was deemed acceptable, and participants that received the telephonic MBI described it as acceptable, easy to access, and consume in post-intervention interviews. The amount of missing data was undesirable (MBI condition, 40%; control condition, 25%), but fell within the range of expected missing outcome data for a RCT with multiple follow-up assessments. Efficacy of the MBI on pain catastrophizing could not be determined due to small sample size and degree of missing data, but trajectory analyses conducted for the MBI condition only trended in the right direction and pain catastrophizing approached statistically significance.

Conclusion: Overall results showed that at telephonic group-based MBI is acceptable and feasible for persons with SCD and chronic pain. Though the study was not able to determine treatment efficacy nor powered to detect a statistically significant difference between conditions, participants (1) described the intervention as acceptable, and (2) the observed effect sizes for the MBI condition demonstrated large effects of the MBI on pain catastrophizing, mental health, and physical health. Replication of this MBI study with a larger sample size, active control group, and additional assessments at the end of each week (e.g., Week 1 through Week 6) is needed to determine treatment efficacy. Many lessons were learned that will guide the development of future studies including which MBI strategies were most helpful, methods to encourage continued participation, and how to improve data capture.

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.