5,474 research outputs found

    The Role of the Metabolome in the Development of Gestational Diabetes Mellitus in High-Risk Minority Women: A Causal Investigation

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    Gestational Diabetes Mellitus (GDM) is the most common pregnancy complication worldwide. However, GDM prevalence is substantially lower in white Europeans (WEs) compared to other ethnicities, especially South Asians (SAs) who experience the highest risk. Globally, healthy diet promotion is the mainstay in GDM prevention, however current guidelines are predominantly based on evidence from WEs. Furthermore, metabolic factors responsible for the disparities in prevalence are unknown but may offer guidance for improved prevention and management. This project aimed to (i) assess the association between diet and GDM across ethnic groups, (ii) determine if distinct metabolic profiles characterise GDM in SAs and WEs, and (iii) evaluate the presence of ethnic-specific causal associations between metabolites and gestational dysglycemia. Aims (ii) and (iii) utilised data from the Born in Bradford cohort (mean gestational age 26.1 weeks). First, through a systematic review of observational and randomised studies, pre-pregnancy diet was found to associate with GDM in WEs, but not in Asians. Secondly, the multivariate analyses of metabolites identified 7 metabolites that were characteristic of GDM in both ethnicities, with an additional 6 characteristic in WEs only. Finally, through Mendelian Randomisation (MR) analyses, 14 metabolites associated with pregnancy dysglycemia in WEs and 11 in SAs. No metabolites were identified in both ethnicities. Cholesterols and fatty acids were the most commonly identified classes identified in WEs and SAs, respectively. This project demonstrated (i) inconsistencies in the association between diet and GDM across ethnicities (ii) distinct metabolic profiles that associate with GDM in WEs and SAs and offers and supports the need for ethnic-specific manage GDM management strategies. In high-risk SAs, fatty acids may be the most important predictors of GDM. Future work should evaluate the role of pre-pregnancy fatty acid intake in GDM development in SAs to aid in the development of culturally tailored dietary interventions

    EXPANSION OF BENEFITS TO PROMOTE FOOD SECURITY AMONG STUDENTS IN CLEVELAND COUNTY, NORTH CAROLINA

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    Healthy People 2030 targets several social determinants of health (SDOH) for improvement, including eliminating very low food security in children (VLFS-C). VLFS-C is the most extreme version of food insecurity (FI) and is associated with negative outcomes in the short- and long-term. In Cleveland County (CC), North Carolina (NC), 23.2% of children under 18 years of age experience FI. Summer Electronic Benefit Transfer-CC (SEBT-CC) and Community Eligibility Provision (CEP) utilize proven methodologies within existing federal and school-level structures to increase food access in students under 18 in CC. SEBT-CC targets families receiving free and reduced lunch (FRL) at baseline to receive $60 monthly food benefits during school breaks, while CEP extends FRL benefits to all students in CC. The goal of SEBTCC and CEP is to provoke a 30% reduction in CC childhood VLFS over a three-year implementation period.Master of Public Healt

    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

    Domain-specific language models for multi-label classification of medical text

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    Recent advancements in machine learning-based medical text multi-label classifications can be used to enhance the understanding of the human body and aid the need for patient care. This research considers predicting medical codes from electronic health records (EHRs) as multi-label problems, where the number of labels ranged from 15 to 923. It is motivated by the advancements in domain-specific language models to better understand and represent electronic health records and improve the predictive accuracy of medical codes. The thesis presents an extensive empirical study of language models for binary and multi-label medical text classifications. Domain-specific multi-sourced fastText pre-trained embeddings are introduced. Experimental results show considerable improvements to predictive accuracy when such embeddings are used to represent medical text. It is shown that using domain-specific transformer models outperforms results for multi-label problems with fixed sequence length. If processing time is not an issue for a long medical text, then TransformerXL will be the best model to use. Experimental results show significant improvements over other models, including state-of-the-art results, when TransformerXL is used for down-streaming tasks such as predicting medical codes. The thesis considers concatenated language models to handle long medical documents and text data from multiple sources of EHRs. Experimental results show improvements in overall micro and macro F1 scores, and such improvements are achieved with fewer resources. In addition, it is shown that concatenated domain-specific transformers improve F1 scores of infrequent labels across several multi-label problems, especially with long-tail labels

    Intervening on hypertension in Zambia: development of a culturally sensitized lifestyle programme to reduce disease incidence in urban areas

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    Background/purpose: Hypertension, like other non-communicable diseases, is becoming a major public health problem for Sub-Saharan Africa (SSA). Its increasing prevalence is driven by an epidemiological transition with more people leading unhealthy lifestyles, including poor diet and physical inactivity. This project aimed to explore the use of participatory methods with an urban community in Zambia in co-developing a culturally sensitized hypertension prevention intervention. Methods: The intervention development study was divided into four phases. I scoped and synthesized existing literature on risk factors (non-modifiable and modifiable) for hypertension in SSA in Phase One. The identified risk factors and their drivers informed Phase Two community members focus group discussions and stakeholder interviews to explore the local context in the study site to clarify the problem, identify which hypertension risk factors were malleable (potential factors to target), the mechanism of change, and how to deliver this. The findings informed the development of the causal pathway, the intervention theory of change and the Phase Three co-development of the intervention core components and small-scale evaluation. Five co-development workshops (four with local residents and one with local stakeholders) iteratively informed identification of priority risk factors, the delivery format and setting, and finalization of intervention core components. The pilot intervention was then tested with volunteer participants (N=34) to assess feasibility, acceptability and potential effectiveness in Phase four. Results: The scoping review identified the most common risk factors for hypertension in SSA. Residents FGDs and key stakeholder interviews, informed by the scoping review findings, identified a number of potentially malleable hypertension risk factors at individual and interpersonal levels, including high salt intake and other dietary factors, low physical activity, excess body weight, central obesity, high alcohol intake and smoking. From these, the workshops prioritised intervening on salt intake, other dietary factors, and physical inactivity. Using these suggestions, an 8-week group-based intervention (CHiPI) was codeveloped. Stakeholders proposed evaluation of the CHiPI on a small scale and delivery through churches: “nearly all residents belong to a church”. Stakeholders also identified community health workers and church leaders as delivery facilitators. The intervention core components were agreed and refined in close consultation with residents. These included linguistic and cultural adaptations of SMART goal setting and self-monitoring tools, which were iteratively tested and refined to reflect the local socio-cultural context. The small-scale evaluation of the intervention showed high acceptability, feasibility and potential effectiveness in improving health literacy, adoption of healthier diets (less salt added during cooking [p=0.014], reduction in added salt to the plate at mealtimes [p=0.001], increased fruit intake [p=0.001], reduced fried meals [p = 0.001]), increased physical activity [p=0.01] and reduced sedentary lifestyle [p = 0.001]. Reductions in body weight [p = 0.002], BMI [p = 0.001], WC [p = 0.001], SBP [-3mmHg, p=0.003] and DBP [-4mmHg, p = 0.001] were also observed. Conclusions and implications: Participatory methods succeeded in engaging local residents and stakeholders in the development of a potentially effective culturally sensitized, 8-week, group-based hypertension prevention lifestyle intervention for delivery through churches in Zambia. Having demonstrated high feasibility, acceptability and potential effectiveness, taking this intervention to a larger evaluation to obtain evidence of effectiveness can inform hypertension prevention intervention development in Zambia and other SSA countries

    The effect of neprilysin inhibition on left ventricular remodelling in patients with asymptomatic left ventricular systolic dysfunction late after myocardial infarction

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    Background The development of heart failure and reduced ejection fraction (HFrEF) in survivors of myocardial infarction occurs as a result of progressive left ventricular dilatation and a reduction in systolic function, a process commonly referred to as adverse left ventricular remodelling. One of the earliest advances in the management of myocardial infarction was the finding that the angiotensin converting enzyme (ACE) inhibitor captopril which inhibits the maladaptive activation of the renin-angiotensin system (RAS) promoting the process of adverse remodelling, reduced the risk of heart failure and mortality by attenuating progressive ventricular enlargement. Subsequently, the angiotensin receptor blocker valsartan (in a dose of 160 mg twice daily) was shown to be as effective as captopril in preventing adverse clinical outcomes after myocardial infarction. Beta-blockers are believed to have similar benefits as a result of attenuating the harmful actions of excessive activation of the sympathetic nervous system (SNS). Not all neurohumoral activation following myocardial infarction (and in heart failure) is harmful. The natriuretic peptides are released in response to increased left atrial and ventricular wall stress and counteract the harmful effects of RAS and SNS activation through natriuretic, vasodilatory, anti-fibrotic and sympatholytic effects. Endogenous levels of the natriuretic peptides (along with a range of other potentially cardioprotective peptides) can be increased by preventing their breakdown by the enzyme neprilysin. In patients with symptomatic HFrEF, the combined angiotensin receptorneprilysin inhibitor sacubitril/valsartan (dosed 97/103mg twice daily), compared with the gold-standard ACE inhibitor enalapril, has been demonstrated to reduce the risk of worsening heart failure and cardiovascular death. It may be that part of the clinical benefits of sacubitril/valsartan (i.e., the addition of neprilysin inhibitor), relate to a favourable reverse remodelling effect. Therefore, the addition of a neprilysin inhibition to a RAS inhibitor in high-risk patients following myocardial infarction may result in greater attenuation of adverse left ventricular remodelling than RAS inhibition alone, and potentially reduce the attendant risk of the development of HFrEF. Aim To examine the effect of neprilysin inhibition on left ventricular remodelling in patients with asymptomatic left ventricular systolic dysfunction late after myocardial infarction using the gold-standard method, cardiac magnetic resonance imaging (MRI). Methods I performed a prospective, randomised, double-blind, active-comparator trial comparing sacubitril/valsartan 97/103mg twice daily with valsartan 160mg twice daily in patients at least 3 months following an acute myocardial infarction with a left ventricular ejection fraction (LVEF) less than, or equal to 40% who were taking a RAS inhibitor (equivalent dose of ramipril ≥2.5mg twice daily), and a beta-blocker unless contraindicated or intolerant. Patients in New York Heart Association (NYHA) functional classification II or greater were excluded. The primary endpoint was change from baseline to 52-weeks in left ventricular endsystolic volume index (LVESVI) measured using cardiac MRI. Secondary endpoints included other MRI measurements of left ventricular remodelling, change in NTproBNP (a marker of left ventricular wall stress) and hs-TnI (a marker of myocardial injury), and a patient global assessment of change questionnaire. In exploratory analyses, I also examined the effect of neprilysin inhibition on a range of circulating biomarkers relating to substrates for neprilysin and myocardial fibrosis. Results In the 93 randomised patients, mean age was 60.7±10.4 years, median time from myocardial infarction 3.6 years (interquartile range [IQR] 1.2-72), mean LVEF 36.8%±7.1, median NT proBNP 230pg/ml (IQR 124-404) and a beta-blocker was taken by 94% of patients. Sacubitril/valsartan, compared with valsartan, did not significantly reduce LVESVI; between-group difference -1.9ml/m2 (95%CI -4.8, 1.0); p=0.19. A reduction in LVESVI was seen with sacubitril/valsartan in those with NT-proBNP levels greater than or equal to the median than those below (interaction p=0.036). There were no significant between-group differences in NT-proBNP, hs-TnI, left ventricular end-diastolic volume index, left atrial volume index, LVEF, left ventricular mass index, or patient global assessment of change. Sacubitril/valsartan, compared with valsartan, significantly increased levels of atrial natriuretic peptide (ANP) (p=0.013), a substrate for neprilysin, and its intracellular secondary messenger urinary cyclic guanosine monophosphate (cGMP) (P=0.001), indicating increased natriuretic peptide bioactivity. Midregional pro-atrial natriuretic peptide (MR-proANP), which is not a substrate for neprilysin, was significantly reduced with sacubitril/valsartan (P=0.009) and may reflect a reduction in left ventricular filling pressures. No significant increase in B-type natriuretic peptide (BNP) was observed which was consistent with the greater affinity neprilysin has for ANP relative to BNP. Midregional proadrenomedullin (MR-proADM) (P<0.001), glucagon-like peptide-1 (GLP-1) (P<0.001) and galectin-3 (P=0.045) were increased with sacubitril/valsartan, as compared with valsartan. No significant favourable changes were seen with the addition of a neprilysin inhibitor in biomarkers of profibrotic processes. Conclusion In patients with asymptomatic left ventricular systolic dysfunction late after myocardial infarction, treatment with sacubitril/valsartan compared with valsartan alone (i.e., the addition of a neprilysin inhibitor) did not have a significant reverse remodelling effect and did not reduce biomarkers of left ventricular wall stress (NT-proBNP) or myocardial injury (hs-TnI) despite augmenting natriuretic peptide activity
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