5,002 research outputs found

    Developing automated meta-research approaches in the preclinical Alzheimer's disease literature

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    Alzheimer’s disease is a devastating neurodegenerative disorder for which there is no cure. A crucial part of the drug development pipeline involves testing therapeutic interventions in animal disease models. However, promising findings in preclinical experiments have not translated into clinical trial success. Reproducibility has often been cited as a major issue affecting biomedical research, where experimental results in one laboratory cannot be replicated in another. By using meta-research (research on research) approaches such as systematic reviews, researchers aim to identify and summarise all available evidence relating to a specific research question. By conducting a meta-analysis, researchers can also combine the results from different experiments statistically to understand the overall effect of an intervention and to explore reasons for variations seen across different publications. Systematic reviews of the preclinical Alzheimer’s disease literature could inform decision making, encourage research improvement, and identify gaps in the literature to guide future research. However, due to the vast amount of potentially useful evidence from animal models of Alzheimer’s disease, it remains difficult to make sense of and utilise this data effectively. Systematic reviews are common practice within evidence based medicine, yet their application to preclinical research is often limited by the time and resources required. In this thesis, I develop, build-upon, and implement automated meta-research approaches to collect, curate, and evaluate the preclinical Alzheimer’s literature. I searched several biomedical databases to obtain all research relevant to Alzheimer’s disease. I developed a novel deduplication tool to automatically identify and remove duplicate publications identified across different databases with minimal human effort. I trained a crowd of reviewers to annotate a subset of the publications identified and used this data to train a machine learning algorithm to screen through the remaining publications for relevance. I developed text-mining tools to extract model, intervention, and treatment information from publications and I improved existing automated tools to extract reported measures to reduce the risk of bias. Using these tools, I created a categorised database of research in transgenic Alzheimer’s disease animal models and created a visual summary of this dataset on an interactive, openly accessible online platform. Using the techniques described, I also identified relevant publications within the categorised dataset to perform systematic reviews of two key outcomes of interest in transgenic Alzheimer’s disease models: (1) synaptic plasticity and transmission in hippocampal slices and (2) motor activity in the open field test. Over 400,000 publications were identified across biomedical research databases, with 230,203 unique publications. In a performance evaluation across different preclinical datasets, the automated deduplication tool I developed could identify over 97% of duplicate citations and a had an error rate similar to that of human performance. When evaluated on a test set of publications, the machine learning classifier trained to identify relevant research in transgenic models performed was highly sensitive (captured 96.5% of relevant publications) and excluded 87.8% of irrelevant publications. Tools to identify the model(s) and outcome measure(s) within the full-text of publications may reduce the burden on reviewers and were found to be more sensitive than searching only the title and abstract of citations. Automated tools to assess risk of bias reporting were highly sensitive and could have the potential to monitor research improvement over time. The final dataset of categorised Alzheimer’s disease research contained 22,375 publications which were then visualised in the interactive web application. Within the application, users can see how many publications report measures to reduce the risk of bias and how many have been classified as using each transgenic model, testing each intervention, and measuring each outcome. Users can also filter to obtain curated lists of relevant research, allowing them to perform systematic reviews at an accelerated pace with reduced effort required to search across databases, and a reduced number of publications to screen for relevance. Both systematic reviews and meta-analyses highlighted failures to report key methodological information within publications. Poor transparency of reporting limited the statistical power I had to understand the sources of between-study variation. However, some variables were found to explain a significant proportion of the heterogeneity. Transgenic animal model had a significant impact on results in both reviews. For certain open field test outcomes, wall colour of the open field arena and the reporting of measures to reduce the risk of bias were found to impact results. For in vitro electrophysiology experiments measuring synaptic plasticity, several electrophysiology parameters, including magnesium concentration of the recording solution, were found to explain a significant proportion of the heterogeneity. Automated meta-research approaches and curated web platforms summarising preclinical research could have the potential to accelerate the conduct of systematic reviews and maximise the potential of existing evidence to inform translation

    The Journal of Early Hearing Detection and Intervention: Volume 7 Issue 1, Pages 1-120

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    A decade of action for a change of era

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    For the fifth time, the countries of the region are convening in the framework of the Forum of the Countries of Latin America and the Caribbean on Sustainable Development. On each occasion, the Economic Commission for Latin America and the Caribbean (ECLAC) has presented a report on regional progress and challenges in relation to the 2030 Agenda for Sustainable Development. Since 2020, efforts to assess progress towards meeting the 2030 Agenda have had to be undertaken amid the constraints imposed by measures to address the coronavirus disease (COVID-19) pandemic. In this difficult context, ECLAC continued to step up its efforts to assess the progress towards the achievement of the Sustainable Development Goals (SDGs). Whereas in 2019 we only had 19 statistical series of SDG indicators for the region to analyse progress towards 2030, in this fifth report we are presenting the results for 359 series, corresponding to 111 targets, 73 of which are targets covered by the prioritized indicators for the region. Given the contradiction between, on the one hand, the growing institutional efforts to bring to fruition the Decade of Action of the Sustainable Development Goals called for by the United Nations Secretary-General and his proposal of Our Common Agenda and, on the other, the insufficient progress towards the achievement of the Goals, ECLAC stresses once again its proposal to launch a decade of action for a change of era. The Sustainable Development Goals will not be achieved by doing more of the same; we must move towards a new, inclusive and sustainable economic and social system. This document presents specific proposals in four areas in which we must continue to work: strengthening multilateralism, particularly in the area of financing for development; improving implementation of productive, social and environmental policies of national and regional scope; building up the resilience of institutions; and overcoming conflicts through agreements and compacts

    Living with dying children: the suffering of parents

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    Although the relief of suffering and emotional support are fundamental to children's palliative care, their empirical study has been limited. The research questions for this study address three areas: the lived experience of parents of dying children; how other people's responses shape the parents' lived experience; and the place of emotion and suffering in the parents' lived experience. Implementing a qualitative strategy, a collective case study was undertaken in a children's hospice in England, with fieldwork completed between March 2008 and September 2009. Data was collected with nine parents using a range of tools including a focus group, participant observation, documentary observation and individual interviews. Within-case and cross-case modified grounded theory analysis facilitated clarification of emerging themes whilst preserving individual parent voices. The findings show that parents of dying children had existential issues put at stake through the emotional experience of parenting a dying child; these included their identity, place in society, time, and relationships. Such losses could constitute suffering, but in addition they limited the parents' interaction with society so that over time both the 'quantity' and 'quality' of intersubjectivity reduced. The parents perceived that other people tended not to legitimate their lived experience. Emotion was an important influence in this process. The parents of dying children managed their emotions, particularly those of a negative nature, in everyday life and when using hospice services. As a result they expressed somewhat inauthentic accounts of their felt experience, reframed according to perceived feeling rules. This also reduced intersubjectivity and supported the delegitimation of the parental experience. In conclusion, delegitimation of the parental experience stems from feeling rules which are derived from day to day interactions and contemporary social policy. Suffering may be prevented if individual experience is legitimated through improved intersubjectivity. A key factor for this is effective communication through which observers engage with the felt emotion of the suffering individual

    The Application of Computer Techniques to ECG Interpretation

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    This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field

    Enhancing memory-related sleep spindles through learning and electrical brain stimulation

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    Sleep has been strongly implicated in mediating memory consolidation through hippocampal-neocortical communication. Evidence suggests offline processing of encoded information in the brain during slow wave sleep (SWS), specifically during slow oscillations and spindles. In this work, we used active exploration and learning tasks to study post-experience sleep spindle density changes in rats. Experiences lead to subsequent changes in sleep spindles, but the strength and timing of the effect was task-dependent. Brain stimulation in humans and rats have been shown to enhance memory consolidation. However, the exact stimulation parameters which lead to the strongest memory enhancement have not been fully explored. We tested the efficacy of both cortical sinusoidal direct current stimulation and intracortical pulse stimulation to enhance slow oscillations and spindle density. Pulse stimulation reliably evoked state-dependent slow oscillations and spindles during SWS with increased hippocampal ripple-spindle coupling, demonstrating potential in memory enhancement

    Usability of Health-related Websites by Filipino-American Adults and Nursing Informatics Experts

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    Filipino-Americans are an understudied minority group with high prevalence and mortality from chronic conditions, such as cardiovascular disease and diabetes. Facing barriers to care and lack of culturally appropriate health resources, they frequently use the internet to obtain health information. It is unknown whether they perceive health-related websites to be useful or easy to use because there are no published usability studies involving this population. Using the Technology Acceptance Model as a theoretical framework, this study investigated the difference between website design ratings by experts and the perceptions of Filipino-American users to determine if usability guidelines influenced the perceived ease of use and perceived usefulness of health-related websites. A comprehensive usability assessment was obtained by usability experts through heuristic evaluation and a sample of the Filipino-American population through an online survey. By conducting research on a Filipino-American sample, this study adds to the scarce body of Filipino-American research and is a key step towards improving their online health resources. The study aligned with the Office of Disease Prevention and Health Promotion’s Healthy People 2020 Health Communication/Health Information Technology (HC/HIT) 8.2 objective to increase the proportion of quality, health-related websites that follow established usability principles. This study highlighted the discrepancy between the experts’ and participants’ views of website usability. The findings should serve as an impetus for examining and refreshing usability guidelines with the involvement of communities of interest

    Physicians services provider manual

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    The purpose of this manual is to provide pertinent information on physicians services and includes information on South Carolina Medicaid policies for general medical care, such as, office exams. This manual provides a comprehensive overview of the program, eligible providers, covered services and definitions, utilization management, reporting/documentation, and billing guidance

    Clinical Utility of Applying PGx and Deprescribing-Based Decision Support in Polypharmacy

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    Polypharmacy is a necessary and important aspect of drug treatment; however, it becomes a challenge when the medication risks outweigh the benefits for an individual patient. Drug–drug interactions and the introduction of prescribing cascades are common features of polypharmacy, which can lead to ineffectiveness and increased risk of adverse drug reactions (ADR). Genes encoding CYP450 isozymes and other drug-related biomarkers have attracted considerable attention as targets for pharmacogenetic (PGx) testing due to their impact on drug metabolism and response. This Special Issue is devoted to explore the status and initiatives taken to circumvent ineffectiveness and to improve medication safety for polypharmacy patients. Specific areas include drug–drug interactions and consequences thereof in therapeutic management, including PK- and PD-profiling; the application of PGx-based guidance and/or decision tools for drug–gene and drug–drug gene interactions; medication reviews; development and application of deprescribing tools; and drivers and barriers to overcome for successful implementation in the healthcare system
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