Non-biomedical aspects of Alzheimers Disease and related disorders : a comprehensive bibliography, 1960-1988

This bibliography includes references to over 1600 books, articles, theses and dissertations published in English from 1960 to 1988. Emphasis is given to works dealing with non-biomedical aspects of dementia, particularly to research concerned with the development and evaluation of programs, facilities and services designed to enhance the functional status and quality of life of Alzheimer\u27s victims and their caregivers. Bibliography Arrangement: Following an overview chapter concerned with review articles(Chapter 1), references are arranged topically into twelve subject groupings: Symptoms, Assessment and Diagnosis (Chapter 2); Stages of Deterioration (Chapter 3); Case Studies (Chapter 4); Epidemiology (Chapter 5); Pre-Dementia History (Chapter 6); Etiology (Chapter 7); Health Care System (Chapter 8); Treatment and Management (Chapter 9); Environmental Design (Chapter 10); Caregiver Support (Chapter 11); Education (Chapter 12); and Legal, Ethical and Research Issues (Chapter 13)

Genetics and Etiology of Down Syndrome

This book provides a concise yet comprehensive source of current information on Down syndrome. Research workers, scientists, medical graduates and paediatricians will find it an excellent source for reference and review. This book has been divided into four sections, beginning with the Genetics and Etiology and ending with Prenatal Diagnosis and Screening. Inside, you will find state-of-the-art information on: 1. Genetics and Etiology 2. Down syndrome Model 3. Neurologic, Urologic, Dental & Allergic disorders 4. Prenatal Diagnosis and Screening Whilst aimed primarily at research workers on Down syndrome, we hope that the appeal of this book will extend beyond the narrow confines of academic interest and be of interest to a wider audience, especially parents and relatives of Down syndrome patients

Down Syndrome

Down syndrome, the most cutting-edge book in the field congenital disorders. This book features up-to-date, well referenced research and review articles on Down syndrome. Research workers, scientists, medical graduates and pediatricians will find it to be an excellent source for references and review. It is hoped that such individuals will view this book as a resource that can be consulted during all stages of their research and clinical investigations. Key features of this book are: Common diseases in Down syndrome Molecular Genetics Neurological Disorders Prenatal Diagnosis and Genetic Counselling Whilst aimed primarily at research workers on Down syndrome, we hope that the appeal of this book will extend beyond the narrow confines of academic interest and be of interest to a wider audience, especially parents, relatives and health-care providers who work with infants and children with Down syndrome

The health and care of children with Down Syndrome

Down Syndrome (DS) affects ~10,500 children in the UK. Individuals with DS continue to have poorer health outcomes compared with the general population, and other forms of intellectual disability. By systematically mapping two decades of paediatric DS literature, I found a general decline in the number of publications, since 2014. The majority of publications utilised observational methodologies, with few interventional (5.6%) or qualitative/mixed-method studies (4.3%). Most publications focused on development & cognition, oncology and neurology; relatively few looked at the prevalence of morbidities and health surveillance. Using a large electronic health record dataset I determined the prevalence of morbidities among individuals with DS (N=4,648, age range 0-75 years), and compared with matched controls. The most prevalent morbidities in the DS cohort were hypothyroidism (30.4%), congenital cardiac disease (27.8%), epilepsy (21.9%) and hearing impairment (19.2%). We also found an increased risk of autism (aOR 7.7), chronic kidney disease (aOR 2.3), inflammatory bowel disease (aOR 2.4), non-accidental injury (aOR 1.9), sleep disordered breathing (SDB) (aOR 6.6) and vitamin-D deficiency (aOR 3.1). Finally, I explored current practice with regard to the routine health surveillance of children with DS, in paediatric departments across the UK. Sixty four departments returned a copy of their local health surveillance protocol. Practice was compared across departments, and with three national guidelines. For congenital cardiac disease, hypothyroidism and hearing/visual impairment, practice appeared to be consistent and compliant with national guidelines. However, in other areas (echocardiogram at transition, SBD, vitamin-D deficiency & renal/liver function), practice was patchy and inconsistent. The findings highlight a need for ongoing research in the field of paediatric DS, targeted at areas of greatest need, and those morbidities which are prevalent in the DS cohort. Furthermore, our findings highlight a need a single, evidence based guideline for the health surveillance of children with DS, to promote high quality, consistent care

Investigations at the Crossroads of Down Syndrome and Alzheimer’s Disease

People with Down syndrome (DS) have elevated neuroinflammation early in life and develop neuropathology by the age of twenty. Most individuals with DS go on to develop abnormal dementia and Alzheimer’s disease (AD). This dissertation is focused on biological pathways involved in DS-AD and includes studies in humans with DS and DS mouse models. Locus coeruleus (LC) noradrenergic (NE) neurons decline before other transmitter systems on the path to DS-AD, which leads to increased neuropathology and accelerated memory loss. To investigate the specific roles of LC-NE in DS-AD, designer receptors exclusively activated by designer drugs (DREADDs) were utilized in the Ts65Dn mouse model of DS to selectively stimulate or inhibit LC-NE activity. LC-NE activity modulated neuroinflammation, memory performance, and AD pathology in this mouse model. Altogether these findings implicate the importance of LC-NE function in the context of DS-AD. LC-NE dysfunction may also affect resolution response to neuroinflammation. Insufficient resolution activity was already known to correlate with AD neuropathology in humans and mouse models, but specialized pro-resolving factors have not been evaluated as a therapeutics in DS-AD. In the next portion of my thesis, I developed a novel therapeutic approach to enhance resolution activity in Ts65Dn mice with a pro-resolving mediator, resolvin E1 (RvE1). RvE1 treatment significantly reduced glial activation in the brain and pro-inflammatory cytokines in the periphery of Ts65Dn mice. RvE1 therapy reversed Ts65Dn deficits in memory and cognitive flexibility, which correlated with significant proteomic measures of the inflammatory resolution process. Finally, I investigated blood biomarkers that are relevant to AD including neuron-derived exosome levels of amyloid-beta peptides and phosphorylated-Tau (P-Tau) and serum BDNF levels. These AD biomarkers were already significantly elevated early in childhood with unique trajectories associated with dementia in humans with DS. Serum BDNF levels correlated with exosome P-Tau levels, suggesting an interaction between these two pathways in the development of DS-AD in humans. These data provide novel hope for meaningful therapeutics, to be implemented in early childhood in those with DS and inform both research and clinical perspectives at the crossroads of DS and AD

Clinical risk modelling with machine learning: adverse outcomes of pregnancy

As a complex biological process, there are various health issues that are related to pregnancy. Prenatal care, a type of preventative healthcare at different points in gestation is comprised of management, treatment, and mitigation of such issues. This also includes risk prediction for adverse pregnancy outcomes, where probabilistic modelling is used to calculate individual’s risk at the early stages of pregnancy. This type of modelling can have a definite clinical scope such as in prenatal screening, and an educational aim where awareness of a healthy lifestyle is promoted, such as in health education. Currently, the most used models are based on traditional statistical approaches, as they provide sufficient predictive power and are easily interpreted by clinicians. Machine learning, a subfield of data science, contains methods for building probabilistic models with multidimensional data. Compared to existing prediction models related to prenatal care, machine learning models can provide better results by fitting more intricate nonlinear decision boundary areas, improve data-driven model fitting by generating synthetic data, and by providing more automation for routine model adjustment processes. This thesis presents the evaluation of machine learning methods to prenatal screening and health education prediction problems, along with novel methods for generating synthetic rare disorder data to be used for modelling, and an adaptive system for continuously adjusting a prediction model to the changing patient population. This way the thesis addresses all the four main entities related to predicting adverse outcomes of pregnancy: the mother or patient, the clinician, the screening laboratory and the developer or manufacturer of screening materials and systems.Kliinisen riskin mallinnus koneoppimismenetelmin: raskaudelle haitalliset lopputulemat Raskaus on kompleksinen biologinen prosessi, jonka etenemiseen liittyy useita terveysongelmia. Äitiyshoito voidaan kuvata ennalta ehkäiseväksi terveydenhuolloksi, jossa pyritään käsittelemään, hoitamaan ja lievittämään kyseisiä ongelmia. Tähän hoitoon sisältyy myös raskauden haitallisten lopputulemien riskilaskenta, missä probabilistista mallinnusta hyödynnetään määrittämään yksilön riski raskauden varhaisissa vaiheissa. Tällä mallinnuksella voi olla selkeä kliininen tarkoitus kuten prenataaliseulonta, tai terveyssivistyksellinen tarkoitus missä odottavalle äidille esitellään raskauden kannalta terveellisiä elämäntapoja. Tällä hetkellä eniten käytössä olevat ennustemallit perustuvat perinteiseen tilastolliseen mallinnukseen, sille ne tarjoavat riittävän ennustetehokkuuden ja ovat helposti tulkittavissa. Koneoppiminen on datatieteen osa-alue, joka pitää sisällään menetelmiä millä voidaan mallintaa moniulotteista dataa ennustekäyttöön. Verrattuna olemassa oleviin äitiyshoidon ennustemalleihin, koneoppiminen mahdollistaa parempien ennustetulosten tuottamisen sovittamalla hienojakoisempia epälineaarisia päätösalueita, tehostamalla datakeskeisten mallien sovitusta luomalla synteettisiä havaintoja ja tarjoamalla enemmän automaatiota rutiininomaiseen mallien hienosäätöön. Tämä väitös esittelee koneoppimismenetelmien evaluaation prenataaliseulonta-ja terveyssivistysongelmiin, ja uusia menetelmiä harvinaisten sairauksien datan luomiseen mallinnustarkoituksiin ja jatkuvan ennustemallin hienosäätämisen järjestelmän muuttuvia potilaspopulaatiota varten. Näin väitös käy läpi kaikki neljä asianomaista jotka liittyvät haitallisten lopputulemien ennustamiseen: odottava äiti eli potilas, kliinikko, seulontalaboratorio ja seulonnassa käytettävien materiaalien ja järjestelmien kehittäjä tai valmistaja

Facilitating autonomous, confident and satisfying choices : a mixed-method study of women's choice-making in prenatal screening for common aneuploidies

Background: Population-based prenatal screening has become a common and widely available obstetrical practice in majority of developed countries. Under the patient autonomy principle, women should understand the screening options, be able to take their personal preferences and situations into account, and be encouraged to make autonomous and intentional decisions. The majority of the current research focuses on the prenatal screening uptake rate, women's choice on screening tests, and the influential factors. However, little attention has been paid to women's choice-making processes and experiences in prenatal screening and their influences on choice satisfaction. Understanding women's choice-making processes and experiences in pregnancy and childbirth is the prerequisite for designing women-centered choice aids and delivering women-centered maternity care. This paper presents a pilot study that aims to investigate women's experiences when they make choices for screening tests, quantify the choice making experience, and identify the experiential factors that affect women's satisfaction on choices they made. Method: We conducted a mixed-method research at Helsinki and Uusimaa Hospital District (HUS) in Finland. First, the women's choice-making experiences were explored by semi-structured interviews. We interviewed 28 women who participated in prenatal screening. The interview data was processed by thematic analysis. Then, a cross-sectional self-completion survey was designed and implemented, assessing women's experiences in choice-making and identifying the experiential factors that influence choice satisfaction. Of 940 distributed questionnaires, 185 responses were received. Multivariable linear regression analysis was used to detect the effects of the variables. Results: We developed a set of measurements for women's choice-making experiences in prenatal screening with seven variables: activeness, informedness, confidence, social pressure, difficulty, positive emotion and negative emotion. Regression revealed that activeness in choice-making (beta = 0.176; p = 0.023), confidence in choice-making (beta = 0.388; p <0.001), perceived social pressure (beta = -0.306; p <0.001) and perceived difficulty (beta = -0.274; p <0.001) significantly influenced women's choice satisfaction in prenatal screening. Conclusions: This study explores the experiential dimension of women's choice-making in prenatal screening. Our result will be useful for service providers to design women-centered choice environment. Women's willingness and capabilities of making active choices, their preferences, and social reliance should be well considered in order to facilitate autonomous, confident and satisfying choices.Peer reviewe

Differential effects of Down's syndrome and Alzheimer's neuropathology on default mode connectivity.

Down's syndrome is a chromosomal disorder that invariably results in both intellectual disability and Alzheimer's disease neuropathology. However, only a limited number of studies to date have investigated intrinsic brain network organisation in people with Down's syndrome, none of which addressed the links between functional connectivity and Alzheimer's disease. In this cross-sectional study, we employed 11 C-Pittsburgh Compound-B (PiB) positron emission tomography in order to group participants with Down's syndrome based on the presence of fibrillar beta-amyloid neuropathology. We also acquired resting state functional magnetic resonance imaging data to interrogate the connectivity of the default mode network; a large-scale system with demonstrated links to Alzheimer's disease. The results revealed widespread positive connectivity of the default mode network in people with Down's syndrome (n = 34, ages 30-55, median age = 43.5) and a stark lack of anti-correlation. However, in contrast to typically developing controls (n = 20, ages 30-55, median age = 43.5), the Down's syndrome group also showed significantly weaker connections in localised frontal and posterior brain regions. Notably, while a comparison of the PiB-negative Down's syndrome group (n = 19, ages 30-48, median age = 41.0) to controls suggested that alterations in default mode connectivity to frontal brain regions are related to atypical development, a comparison of the PiB-positive (n = 15, ages 39-55, median age = 48.0) and PiB-negative Down's syndrome groups indicated that aberrant connectivity in posterior cortices is associated with the presence of Alzheimer's disease neuropathology. Such distinct profiles of altered connectivity not only further our understanding of the brain physiology that underlies these two inherently linked conditions but may also potentially provide a biomarker for future studies of neurodegeneration in people with Down's syndrome

Amniocentesis dilemma : needs assessment, development and field-testing of a theory-based decision support intervention

Background: Amniocentesis is the most common prenatal diagnostic procedure undertaken in the United Kingdom, usually performed after 15 completed weeks of pregnancy. The procedure is reported to have a 1 % risk of miscarriage and the results of the chromosome tests may require further decision making about whether to continue with the pregnancy. Deciding about amniocentesis is a complex and emotionally charged decision, often undertaken in a short period of time and, under current practice, with little systematic decision support. Decision Support Interventions, also known as Patient Decision Aids, have been developed to help individuals leam about the features and implications of their treatment or screening options while improving communication with their health professionals. Those interventions are specifically targeted at preference-sensitive decisions with significant harms, benefits and uncertainty, where no screening or treatment option is objectively better than the other. This thesis proposed to assess information and decision support needs of pregnant women undertaking amniocentesis testing and to design and field-test, in collaboration with pregnant women and health professionals, a theory-based Decision Support Intervention for amniocentesis testing (amnioDex). Methods: A multi-method approach was adopted that included a systematic review, theoretical review, and qualitative analysis to develop and pilot a theory-based intervention intended for pregnant women facing a decision to undertake amniocentesis testing. The content areas and themes to be covered in the intervention were determined by a literature review and needs assessment conducted with pregnant women and health professionals. The prototype development of amnioDex (amniocentesis decision explorer) was guided by theory and included heuristic-based deliberation tools. Incremental prototypes of amnioDex and embedded deliberation tools were field-tested with lay users, health professionals and pregnant women facing a decision to undertake amniocentesis, using the "think-aloud" technique. Results: The amnioDex intervention was developed over a period of two years and field-tested for eight months. Conclusion: Findings from this thesis showed that it was feasible to use theory to generate a Decision Support Intervention acceptable to women facing amniocentesis testing and to health professionals counselling them. Future research needs to evaluate the effectiveness of amnioDex in a randomised controlled trial and to examine methods for effectively transferring theory into practice.EThOS - Electronic Theses Online ServiceGBUnited Kingdo