The Availability and Consistency of Dengue Surveillance Data Provided Online by the World Health Organization

Background: The use of high quality disease surveillance data has become increasingly important for public health action against new threats. In response, countries have developed a wide range of disease surveillance systems enabled by technological advancements. The heterogeneity and complexity of country data systems have caused a growing need for international organizations such as the World Health Organization (WHO) to coordinate the standardization, integration, and dissemination of country disease data at the global level for research and policy. The availability and consistency of currently available disease surveillance data at the global level are unclear. We investigated this for dengue surveillance data provided online by the WHO. Methods and Findings: We extracted all dengue surveillance data provided online by WHO Headquarters and Regional Offices (RO’s). We assessed the availability and consistency of these data by comparing indicators within and between sources. We also assessed the consistency of dengue data provided online by two example countries (Brazil and Indonesia). Data were available from WHO for 100 countries since 1955 representing a total of 23 million dengue cases and 82 thousand deaths ever reported to WHO. The availability of data on DengueNet and some RO’s declined dramatically after 2005. Consistency was lacking between sources (84% across all indicators representing a discrepancy of almost half a million cases). Within sources, data at high spatial resolution were often incomplete. Conclusions: The decline of publicly available, integrated dengue surveillance data at the global level will limit opportunities for research, policy, and advocacy. A new financial and operational framework will be necessary for innovation and for the continued availability of integrated country disease data at the global level

The International Mass Loading Service

The International Mass Loading Service computes four loadings: a) atmospheric pressure loading; b) land water storage loading; c) oceanic tidal loading; and d) non-tidal oceanic loading. The service provides to users the mass loading time series in three forms: 1) pre-computed time series for a list of 849 space geodesy stations; 2) pre-computed time series on the global 1deg x 1deg grid; and 3) on-demand Internet service for a list of stations and a time range specified by the user. The loading displacements are provided for the time period from 1979.01.01 through present, updated on an hourly basis, and have latencies 8-20 hours.Comment: 8 pages, 3 figures, to appear in the Proceedings of the Reference Frames for Applications in Geosciences Simposium, held in Luxemboug in October 201

Comparing the effectiveness of small-particle versus large-particle inhaled corticosteroid in COPD

Dirkje S Postma,1 Nicolas Roche,2 Gene Colice,3 Elliot Israel,4 Richard J Martin,5 Willem MC van Aalderen,6 Jonathan Grigg,7 Anne Burden,8 Elizabeth V Hillyer,8 Julie von Ziegenweidt,8 Gokul Gopalan,9 David Price8,10 1University of Groningen, Department of Pulmonary Medicine and Tuberculosis, University Medical Center Groningen, Groningen, the Netherlands; 2Respiratory and Intensive Care Medicine, Cochin Hospital Group, APHP, Paris-Descartes University (EA2511), Paris, France; 3Pulmonary, Critical Care and Respiratory Services, Washington Hospital Center and George Washington University School of Medicine, Washington DC, USA; 4Pulmonary and Critical Care Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; 5Department of Medicine, National Jewish Health, Denver, CO, USA; 6Dept of Pediatric Respiratory Medicine and Allergy, Emma Children's Hospital AMC, Amsterdam, the Netherlands; 7Blizard Institute, Queen Mary University London, London, UK; 8Research in Real Life, Ltd, Cambridge, UK; 9Respiratory, Global Scientific Affairs, Teva Pharmaceuticals, Frazer, PA, USA; 10Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK Purpose: Small airway changes and dysfunction contribute importantly to airway obstruction in chronic obstructive pulmonary disease (COPD), which is currently treated with inhaled corticosteroids (ICS) and long-acting bronchodilators at Global initiative for Obstructive Lung Disease (GOLD) grades 2–4. This retrospective matched cohort analysis compared effectiveness of a representative small-particle ICS (extrafine beclomethasone) and larger-particle ICS (fluticasone) in primary care patients with COPD. Patients and methods: Smokers and ex-smokers with COPD ≥40 years old initiating or stepping-up their dose of extrafine beclomethasone or fluticasone were matched 1:1 for demographic characteristics, index prescription year, concomitant therapies, and disease severity during 1 baseline year. During 2 subsequent years, we evaluated treatment change and COPD exacerbations, defined as emergency care/hospitalization for COPD, acute oral corticosteroids, or antibiotics for lower respiratory tract infection. Results: Mean patient age was 67 years, 57%–60% being male. For both initiation (n=334:334) and step-up (n=189:189) patients, exacerbation rates were comparable between extrafine beclomethasone and fluticasone cohorts during the 2 year outcome period. Odds of treatment stability (no exacerbation or treatment change) were significantly greater for patients initiating extrafine beclomethasone compared with fluticasone (adjusted odds ratio 2.50; 95% confidence interval, 1.32–4.73). Median ICS dose exposure during 2 outcome years was significantly lower (P<0.001) for extrafine beclomethasone than fluticasone cohorts (315 µg/day versus 436 µg/day for initiation, 438 µg/day versus 534 µg/day for step-up patients). Conclusion: We observed that small-particle ICS at significantly lower doses had comparable effects on exacerbation rates as larger-particle ICS at higher doses, whereas initiation of small-particle ICS was associated with better odds of treatment stability during 2-years' follow-up. Keywords: COPD exacerbation, extrafine particle, matched cohort analysis, real life, small airway

Statistical Signatures of Photon Localization

The realization that electron localization in disordered systems (Anderson localization) is ultimately a wave phenomenon has led to the suggestion that photons could be similarly localized by disorder. This conjecture attracted wide interest because the differences between photons and electrons - in their interactions, spin statistics, and methods of injection and detection - may open a new realm of optical and microwave phenomena, and allow a detailed study of the Anderson localization transition undisturbed by the Coulomb interaction. To date, claims of three-dimensional photon localization have been based on observations of the exponential decay of the electromagnetic wave as it propagates through the disordered medium. But these reports have come under close scrutiny because of the possibility that the decay observed may be due to residual absorption, and because absorption itself may suppress localization. Here we show that the extent of photon localization can be determined by a different approach - measurement of the relative size of fluctuations of certain transmission quantities. The variance of relative fluctuations accurately reflects the extent of localization, even in the presence of absorption. Using this approach, we demonstrate photon localization in both weakly and strongly scattering quasi-one-dimensional dielectric samples and in periodic metallic wire meshes containing metallic scatterers, while ruling it out in three-dimensional mixtures of aluminum spheres.Comment: 5 pages, including 4 figure

Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

Site-specific perturbations of alpha-synuclein fibril structure by the Parkinson's disease associated mutations A53T and E46K.

PMCID: PMC3591419This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Parkinson's disease (PD) is pathologically characterized by the presence of Lewy bodies (LBs) in dopaminergic neurons of the substantia nigra. These intracellular inclusions are largely composed of misfolded α-synuclein (AS), a neuronal protein that is abundant in the vertebrate brain. Point mutations in AS are associated with rare, early-onset forms of PD, although aggregation of the wild-type (WT) protein is observed in the more common sporadic forms of the disease. Here, we employed multidimensional solid-state NMR experiments to assess A53T and E46K mutant fibrils, in comparison to our recent description of WT AS fibrils. We made de novo chemical shift assignments for the mutants, and used these chemical shifts to empirically determine secondary structures. We observe significant perturbations in secondary structure throughout the fibril core for the E46K fibril, while the A53T fibril exhibits more localized perturbations near the mutation site. Overall, these results demonstrate that the secondary structure of A53T has some small differences from the WT and the secondary structure of E46K has significant differences, which may alter the overall structural arrangement of the fibrils

MetaboLab - advanced NMR data processing and analysis for metabolomics

Background\ud Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.\ud \ud Results\ud Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.\ud \ud Conclusions\ud The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.\ud \u

Distinct RNA profiles in subpopulations of extracellular vesicles: apoptotic bodies, microvesicles and exosomes

Introduction: In recent years, there has been an exponential increase in the number of studies aiming to understand the biology of exosomes, as well as other extracellular vesicles. However, classification of membrane vesicles and the appropriate protocols for their isolation are still under intense discussion and investigation. When isolating vesicles, it is crucial to use systems that are able to separate them, to avoid cross-contamination. Method: EVs released from three different kinds of cell lines: HMC-1, TF-1 and BV-2 were isolated using two centrifugation-based protocols. In protocol 1, apoptotic bodies were collected at 2,000×g, followed by filtering the supernatant through 0.8 µm pores and pelleting of microvesicles at 12,200×g. In protocol 2, apoptotic bodies and microvesicles were collected together at 16,500×g, followed by filtering of the supernatant through 0.2 µm pores and pelleting of exosomes at 120,000×g. Extracellular vesicles were analyzed by transmission electron microscopy, flow cytometry and the RNA profiles were investigated using a Bioanalyzer®. Results: RNA profiles showed that ribosomal RNA was primary detectable in apoptotic bodies and smaller RNAs without prominent ribosomal RNA peaks in exosomes. In contrast, microvesicles contained little or no RNA except for microvesicles collected from TF-1 cell cultures. The different vesicle pellets showed highly different distribution of size, shape and electron density with typical apoptotic body, microvesicle and exosome characteristics when analyzed by transmission electron microscopy. Flow cytometry revealed the presence of CD63 and CD81 in all vesicles investigated, as well as CD9 except in the TF-1-derived vesicles, as these cells do not express CD9. Conclusions: Our results demonstrate that centrifugation-based protocols are simple and fast systems to distinguish subpopulations of extracellular vesicles. Different vesicles show different RNA profiles and morphological characteristics, but they are indistinguishable using CD63-coated beads for flow cytometry analysis

A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data

With the availability of big medical image data, the selection of an adequate training set is becoming more important to address the heterogeneity of different datasets. Simply including all the data does not only incur high processing costs but can even harm the prediction. We formulate the smart and efficient selection of a training dataset from big medical image data as a multi-armed bandit problem, solved by Thompson sampling. Our method assumes that image features are not available at the time of the selection of the samples, and therefore relies only on meta information associated with the images. Our strategy simultaneously exploits data sources with high chances of yielding useful samples and explores new data regions. For our evaluation, we focus on the application of estimating the age from a brain MRI. Our results on 7,250 subjects from 10 datasets show that our approach leads to higher accuracy while only requiring a fraction of the training data.Comment: MICCAI 2017 Proceeding