Plos One
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HIV-infected African adults are at a considerably increased risk of life-threatening invasive pneumococcal disease (IPD) which persists despite antiretroviral therapy (ART). Defects in naturally acquired pneumococcal-specific T-cell immunity have been identified in HIV-infected adults. We have therefore determined the extent and nature of pneumococcal antigen-specific immune recovery following ART. ⋯ However, recovery of the pneumococcal-specific CD154 expression was incomplete (p = 0.0015) as were IFN-γ ELISpot responses (p = 0.0040) and polyfunctional CD4+ T-cell responses (TNF-α, IL-2 and IFN-γ expression) (p = 0.0040) to a pneumolysin-deficient mutant strain. Impaired control of pneumococcal colonisation and incomplete restoration of pneumococcal-specific immunity may explain the persistently higher risk of IPD amongst HIV-infected adults on ART. Whether vaccination and prolonged ART can overcome this immunological defect and reduce the high levels of pneumococcal colonisation requires further evaluation.
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To evaluate the prices and availability of paediatric essential medicines in Shaanxi Province, China. ⋯ The government should approve a list of national paediatric essential medicines. The availability, price and affordability of these should be improved in both public hospitals and private pharmacies to enable children to obtain effective treatment. Measures should be taken to improve the efficiency of the centralised medicine purchasing system.
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The Helping Babies Breathe" (HBB) program is an evidence-based curriculum in basic neonatal care and resuscitation, utilizing simulation-based training to educate large numbers of birth attendants in low-resource countries. We analyzed its cost-effectiveness at a faith-based Haydom Lutheran Hospital (HLH) in rural Tanzania. ⋯ The HBB program is a low-cost intervention. Implementation in a very rural faith-based hospital like HLH has been highly cost-effective. To facilitate further global implementation of HBB a cost-effectiveness analysis including government owned institutions, urban hospitals and district facilities is desirable for a more diverse analysis to explore cost-driving factors and predictors of enhanced cost-effectiveness.
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Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models' interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. ⋯ The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm.
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Bipolar disorder is characterized by a functional imbalance between hyperactive ventral/limbic areas and hypoactive dorsal/cognitive brain regions potentially contributing to affective and cognitive symptoms. Resting-state studies in bipolar disorder have identified abnormal functional connectivity between these brain regions. However, most of these studies used a seed-based approach, thus restricting the number of regions that were analyzed. ⋯ This abnormal connectivity pattern did not correlate with variables related to the clinical course of the disease. The present finding may reflect abnormal integration of affective and cognitive information in ventral-emotional and dorsal-cognitive networks in euthymic bipolar patients. Furthermore, the results provide novel insights into the role of the meso/paralimbic network in bipolar disorder.