99 research outputs found

    Idiopathic Pulmonary Fibrosis (IPF) incidence and prevalence in Italy

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    Background: Studies of Idiopathic Pulmonary Fibrosis (IPF) epidemiology show regional variations of incidence and prevalence; no epidemiological studies have been carried out in Italy. Objective: To determine incidence and prevalence rates of IPF in the population of a large Italian region.Methods: in this cross-sectional study study data were collected on all patients of 18 years of age and older admitted as primary or secondary idiopathic fibrosing alveolitis (ICD9-CM 516.3) to Lazio hospitals, from 1/1/2005 to 31/12/2009, using regional hospital discharge, population and cause of death databases. Reporting accuracy was assessed on a random sample of hospital charts carrying the ICD9-CM 516.3, 516.8, 516.9 and 515 codes, by reviewing radiology and pathology findings to define cases as IPF “confident”, “possible” or “inconsistent”. Results: Annual prevalence and incidence of IPF were estimated at 25.6 per 100,000 and 7.5 per 100,000 using the ICD9-CM code 516.3 without chart audit while they were estimated at 31.6 per 100,000 and at 9,3 per 100,000 for the IPF “confident” definition after hospital chart audit. Conclusion: The data provide a first estimate of IPF incidence in Italy and indicate that incidence and prevalence in southern European regions may be similar to those observed in northern Europe and North America. (Sarcoidosis Vasc Diffuse Lung Dis 2014; 31: 191-197

    An integrated multi-omics approach identifies the landscape of interferon-α-mediated responses of human pancreatic beta cells

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    Interferon-α (IFNα), a type I interferon, is expressed in the islets of type 1 diabetic individuals, and its expression and signaling are regulated by T1D genetic risk variants and viral infections associated with T1D. We presently characterize human beta cell responses to IFNα by combining ATAC-seq, RNA-seq and proteomics assays. The initial response to IFNα is characterized by chromatin remodeling, followed by changes in transcriptional and translational regulation. IFNα induces changes in alternative splicing (AS) and first exon usage, increasing the diversity of transcripts expressed by the beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may expand antigens presented by beta cells to the immune system. Beta cells also up-regulate the checkpoint proteins PDL1 and HLA-E that may exert a protective role against the autoimmune assault. Data mining of the present multi-omics analysis identifies two compound classes that antagonize IFNα effects on human beta cells.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.P30 DK097512/DK/NIDDK NIH HHS/United States UC4 DK104166/DK/NIDDK NIH HHS/United States MR/P010695/1/MRC_/Medical Research Council/United Kingdompublished version, accepted version, submitted versio

    Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

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    Measurements of electrons from Îœe\nu_e interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50~MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.Comment: 19 pages, 10 figure

    Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

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    A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the O(10)\mathcal{O}(10) MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the Îœe\nu_e component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section σ(EÎœ)\sigma(E_\nu) for charged-current Îœe\nu_e absorption on argon. In the context of a simulated extraction of supernova Îœe\nu_e spectral parameters from a toy analysis, we investigate the impact of σ(EÎœ)\sigma(E_\nu) modeling uncertainties on DUNE's supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on σ(EÎœ)\sigma(E_\nu) must be substantially reduced before the Îœe\nu_e flux parameters can be extracted reliably: in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10\% bias with DUNE requires σ(EÎœ)\sigma(E_\nu) to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of σ(EÎœ)\sigma(E_\nu). A direct measurement of low-energy Îœe\nu_e-argon scattering would be invaluable for improving the theoretical precision to the needed level.Comment: 25 pages, 21 figure

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

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    The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

    Involving the new generations in particle physics endeavours

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    Since 1984 INFN and University of Pisa scientists performing experiments at Fermilab have been running a two-month summer training program for Italian students at the lab. In 1984 the program involved only a few physics students from the University of Pisa, but it was later extended to other INFN groups and to engineering students. Since 2004 the program has been supported in part by the US Department of Energy (DOE) in the frame of an exchange agreement with INFN and has been run by the Cultural Association of Italians at Fermilab (CAIF). In 2007 the Sant’Anna School of Advanced Studies (Pisa) established an agreement with Fermilab to share the cost of four engineering students each year. In the almost 40 years of its history, the program has hosted at Fermilab approximately 550 Italian students from more than 20 Italian universities and from some non-Italian universities. In addition, in the years 2010-2019, with the support of the Italian National Institute of Astrophyics (INAF), the Italian Space Agency (ASI), and CAIF, 30 students were hosted in other US laboratories and universities. The Fermilab training programs spanned from data analysis to design and construction of particle detectors and accelerator components, R/D on superconductive elements, theory of accelerators, and analysis of astrophysical data. At the other US laboratories the offered training was on Space Science. In 2015 the University of Pisa endorsed the program as one of its own Summer Schools. The interns are enrolled as Pisa students for the duration of the internship. They are required to write summary reports published in the Fermilab and University of Pisa web pages. Upon positive evaluation by a University board, students are acknowledged 6 ECTS credits. The entire program is expected to expand further under CAIF management. An agreement has been signed between ASI and CAIF, for ASI to support yearly three two-months fellowships in US space science. In the following we inform on student recruiting, training programs, and final evaluation

    The Combimatrix platform for microarray analysis: gene expression in tomato plants infected by different combinations of cucumber mosaic virus and its satellite RNA.

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    A microarray analysis of tomato plants infected by different combinations of cucumber mosaic virus and its satellite RNAs
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