Cynomolgus monkeys (Macaca fascicularis) experimentally infected with B19V and hepatitis A virus: no evidence of the co-infection as a cause of acute liver failure

This study was conducted to analyse the course and the outcome of the liver disease in the co-infected animals in order to evaluate a possible synergic effect of human parvovirus B19 (B19V) and hepatitis A virus (HAV) co-infection. Nine adult cynomolgus monkeys were inoculated with serum obtained from a fatal case of B19V infection and/or a faecal suspension of acute HAV. The presence of specific antibodies to HAV and B19V, liver enzyme levels, viraemia, haematological changes, and necroinflammatory liver lesions were used for monitoring the infections. Seroconversion was confirmed in all infected groups. A similar pattern of B19V infection to human disease was observed, which was characterised by high and persistent viraemia in association with reticulocytopenia and mild to moderate anaemia during the period of investigation (59 days). Additionally, the intranuclear inclusion bodies were observed in pro-erythroblast cell from an infected cynomolgus and B19V Ag in hepatocytes. The erythroid hypoplasia and decrease in lymphocyte counts were more evident in the co-infected group. The present results demonstrated, for the first time, the susceptibility of cynomolgus to B19V infection, but it did not show a worsening of liver histopathology in the co-infected group

DUNE Offline Computing Conceptual Design Report

International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation