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The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

Global DEMs are fundamental for global applications and are necessary also at the local scale, in regions where local models are not available. Local DEMs are preferred when they are available and if are characterized by better accuracies and resolutions. In general, two problems arise. Firstly, an interest region could be patched by several partly overlapping DEMs that present similar accuracies and spatial resolutions: they should be merged in a unified model. Moreover, even when the interest region is covered by one unified DEM, local DEMs with better accuracy could be available and should be used to locally improve it. All these problems have been addressed within HELI-DEM project. HELI-DEM (HELvetia-Italy Digital Elevation Model) is a project that has been funded by the European Regional Development Fund (ERDF) within the Italy-Switzerland cooperation program. It started in 2010 and finished at the end of 2013. The involved institutions in the project were Fondazione Politecnico di Milano, Politecnico di Milano, Politecnico di Torino, Regione Lombardia, Regione Piemonte and Scuola Universitaria della Svizzera Italiana. One specific aim of the project was the creation and the publication of a unified Digital Elevation Model for the part of the Alps between Italy and Switzerland. The interest area is prevalently mountainous, with heights that range from about 200 m to 4'600 m. Three low Resolution DTMs (20- 25-50 m of resolution) are available that partly overlap and patch the whole project area: they are characterized by accuracies of some meters. Also High Resolution DTMs (1-5 m) are available: they have accuracies of some decimeters but cover limited areas of the project. The various models are available in different reference frames (the European ETRF89 and the Italian Roma40) and are gridded either in cartographic or geographic coordinates. Before merging them, a validation of the input data has been performed in three steps: cross validation of LR DTMs, validation of LR DTMs by HR DTMs and final check by geodetic techniques. The comparisons confirm the accuracy of HR data and the presence of few local anomalies in LR DTMs. Considering the goal of the project and the previous results, two different DTMs have been produced. Both of them cover the whole project area (boundaries: =7.80° East and =10.70° East, f=45.10° North e f=46.70° North). They are gridded in ETRF2000 geographical coordinates and their spatial resolution is 2 10-4 degrees. The former has been obtained by interpolating and merging all the input LR DTMs on a new common grid. This DTM has been called HD-1. HD-1 presents the same local anomalies of the LR DTMs used as input for the interpolation: therefore, at least in areas where better data (HR DTMs) are available, its correction was needed. In order to avoid sharp discontinuities, corrections obtained by HR DTMs have been filtered by a numerical FFT approach before applying them. The result of this correction has been called HD-2. HD-1 and HD-2 have already been published by an open access geoservice. [ABSTRACT FROM AUTHOR]

In the night of April 6, 2009, an earthquake of MW 6.3 magnitude occurred in the Abruzzo region. The hypocenter was estimated by the INGV at 42,35° N, 13,38° E, at a 9.5 km depth; moreover, at least one month of pre-seismic events preceded the main shock and aftershocks continued for at least 6 months. For the understanding of the geodetic and geodynamic implications of the earthquake, the temporal and spatial analyses of the phenomenon are fundamental; our research group has collected the GNSS data provided by about 50 permanent stations in the earthquake area and neighbouring regions; all the data have been processed in order to investigate the stations displacements and, if possible, the deformation pattern. In particular, the time series (two months of data both before and after the earthquake) of the daily coordinates were interpolated for each station in order to estimate the displacement at the main shock epoch: particular attention has been paid to carry out a proper covariance empirical estimation, in order to evaluate the displacement significance. Finally, the displacements of all the stations have been spatially analyzed to indentify the areas with similar displacements and the main discontinuities between them. Thirteen stations that significantly displace horizontally have been found: a rough clustering allows us to discriminate between a near field area that displaces mainly southwards, a south-western region that displaces in a SWdirection and a northeast region with an opposite motion. Only four station in the epicenter area significantly displace vertically, with drops between 3 and 12 cm. [ABSTRACT FROM AUTHOR]