5,574 research outputs found

    Challenges to estimating vaccine impact using hospitalization data.

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    Because the real-world impact of new vaccines cannot be known before they are implemented in national programs, post-implementation studies at the population level are critical. Studies based on analysis of hospitalization rates of vaccine-preventable outcomes are typically used for this purpose. However, estimates of vaccine impact based on hospitalization data are particularly prone to confounding, as hospitalization rates are tightly linked to changes in the quality, access and use of the healthcare system, which often occur simultaneously with introduction of new vaccines. Here we illustrate how changes in healthcare delivery coincident with vaccine introduction can influence estimates of vaccine impact, using as an example reductions in infant pneumonia hospitalizations after introduction of the 10-valent pneumococcal conjugate vaccine (PCV10) in Brazil. To this end, we explore the effect of changes in several metrics of quality and access to public healthcare on trends in hospitalization rates before (2008-09) and after (2011-12) PCV10 introduction in 2010. Changes in infant pneumonia hospitalization rates following vaccine introduction were significantly associated with concomitant changes in hospital capacity and the fraction of the population using public hospitals. Importantly, reduction of pneumonia hospitalization rates after PCV10 were also associated with the expansion of outpatient services in several Brazilian states, falling more sharply where primary care coverage and the number of health units offering basic and emergency care increased more. We show that adjustments for unrelated (non-vaccine) trends commonly employed by impact studies, such as use of single control outcomes, are not always sufficient for accurate impact assessment. We discuss several ways to identify and overcome such biases, including sensitivity analyses using different denominators to calculate hospitalizations rates and methods that track changes in the outpatient setting. Employing these practices can improve the accuracy of vaccine impact estimates, particularly in evolving healthcare settings typical of low- and middle-income countries

    Decoding the enigma of antiviral crisis: Does one target molecule regulate all?

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    Disease fatality associated with Ebola, SARS-CoV and dengue infections in humans is attributed to a cytokine storm that is triggered by excessive pro-inflammatory responses. Interleukin (IL)-6 acts as a mediator between pro- and anti-inflammatory reactivity by initiating trans- and classical-signaling, respectively. Hence, IL-6 is assumed to provide a target for a broad range of antiviral agents. Available immunosuppressive antivirals are directed to control an often exaggerated pro-inflammatory response that gives rise to complex clinical conditions such as lymphocytopenia. It is known that IL-6, via its soluble receptor (sIL-6R), initiates a pro-inflammatory response while an anti-inflammatory response is triggered by the membrane-bound IL-6 receptor (IL-6R). Future antivirals should thus aim to target the mechanism that regulates switching between IL-6 trans- and classical-signaling. In this review, we propose that the tumour necrosis factor-α converting enzyme ADAM-17 could be the master molecule involved in regulating IL-6 class switching and through this in controlling pro- and anti-inflammatory responses to viral antigenic stimuli. Therefore, ADAM-17 should be considered as a potential target molecule for novel antiviral drug discovery that would regulate host reactivity to infection and thereby limit or prevent fatal outcomes

    The impact of epilepsy surgery on the structural connectome and its relation to outcome

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    BACKGROUND: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. METHODS: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. RESULTS: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. CONCLUSIONS: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only

    Improved timed-mating, non-invasive method using fewer unproven female rats with pregnancy validation via early body mass increases

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    For studies requiring accurate conception-timing, reliable, efficient methods of detecting oestrus reduce time and costs, whilst improving welfare. Standard methods use vaginal cytology to stage cycle, and breeders are paired–up using approximately five proven females with proven males to achieve at least one conception on a specific day. We describe an alternative, fast, consistent, non-invasive method of timed-mating using detection of lordosis behaviour in Wistar and Lister-Hooded rats that used unproven females with high success rates. Rats under reverse-lighting had body masses recorded pre-mating, day (d) 3-4, d8, d10 and d18 of pregnancy. Using only the presence of the oestrus dance to time-mate females for 24-hrs, 89% Wistar and 88% Lister-Hooded rats successfully conceived. We did not observe behavioural oestrus in Sprague-Dawleys without males present. Significant body mass increases following mating distinguished pregnant from non-pregnant rats, as early as d4 of pregnancy (10% ± 1.0 increase cf 3% ± 1.2). The pattern of increases throughout gestation was similar for all pregnant rats until late pregnancy, when there were smaller increases for primi- and multiparous rats (32% ± 2.5; 25% ± 2.4), whereas nulliparous rats had highest gains (38% ± 1.5). This method demonstrated a distinct refinement of the previous timed-mating common practice used, as disturbance of females was minimised. Only the number required of nulli-, primi- or multiparous rats were mated, and body mass increases validated pregnancy status. This new breeding-management method is now established practice for two strains of rat and resulted in a reduction in animal use

    Climate change and the aquatic ecosystems of the Rwenzori Mountains, Uganda

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    The Rwenzori Mountains are home to one of the last remaining tropical icefields outside of the Andes. Over the last century, equatorial icefields of the East African highlands have been steadily shrinking but the precise climate tropical alpine glaciers remain unclear. More than a decade had passed since the last detailed measurements of glacial cover were made in the Rwenzori Mountains. Recent evidence from Kilimanjaro suggests that its icecap will disappear entirely by the year 2020(1). The Rwenzori glaciers contribute meltwater flows to aquatic ecosystems of the Rwenzori Mountains National Park, a Word Heritage Site featuring spectacular, rare Afroalpine flora and fauna, and are headwaters of the River Nile. With the overall aim of assessing the impact of recent climate change on alpine aquatic ecosystems of the Rwenzori Mountains, a collaborative, international research team led by the University College London (United Kingdom) and Makerere University (Uganda), and involving the Institut für Geographie from the University of Innsbruck (Austria) and Water Resources Management Department (Uganda) was assembled in order to pursue three primary scientific objectives: • to assess the magnitude of current glacial recession; • to assess the impact of glacial recession on alpine riverflow; and • to assess recent environmental change from observational datasets and available, environmental archives stored in lake sediment and glacial ice

    Structural brain network abnormalities and the probability of seizure recurrence after epilepsy surgery

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    OBJECTIVE: We assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences. METHODS: We examined data from 51 patients with TLE who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the preoperative structural, diffusion, and postoperative structural MRI, we generated 2 networks: presurgery network and surgically spared network. Standardizing these networks with respect to controls, we determined the number of abnormal nodes before surgery and expected to be spared by surgery. We incorporated these 2 abnormality measures and 13 commonly acquired clinical data from each patient into a robust machine learning framework to estimate patient-specific chances of seizures persisting after surgery. RESULTS: Patients with more abnormal nodes had a lower chance of complete seizure freedom at 1 year and, even if seizure-free at 1 year, were more likely to relapse within 5 years. The number of abnormal nodes was greater and their locations more widespread in the surgically spared networks of patients with poor outcome than in patients with good outcome. We achieved an area under the curve of 0.84 ± 0.06 and specificity of 0.89 ± 0.09 in predicting unsuccessful seizure outcomes (International League Against Epilepsy [ILAE] 3–5) as opposed to complete seizure freedom (ILAE 1) at 1 year. Moreover, the model-predicted likelihood of seizure relapse was significantly correlated with the grade of surgical outcome at year 1 and associated with relapses up to 5 years after surgery. CONCLUSION: Node abnormality offers a personalized, noninvasive marker that can be combined with clinical data to better estimate the chances of seizure freedom at 1 year and subsequent relapse up to 5 years after ATLR. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that node abnormality predicts postsurgical seizure recurrence
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