Genome-Wide Analysis of the Emerging Infection with Mycobacterium avium Subspecies paratuberculosis in the Arabian Camels (Camelus dromedarius)

Mycobacterium avium subspecies paratuberculosis (M. ap) is the causative agent of paratuberculosis or Johne's disease (JD) in herbivores with potential involvement in cases of Crohn's disease in humans. JD is spread worldwide and is economically important for both beef and dairy industries. Generally, pathogenic ovine strains (M. ap-S) are mainly found in sheep while bovine strains (M. ap-C) infect other ruminants (e.g. cattle, goat, deer), as well as sheep. In an effort to characterize this emerging infection in dromedary/Arabian camels, we successfully cultured M. ap from several samples collected from infected camels suffering from chronic, intermittent diarrhea suggestive of JD. Gene-based typing of isolates indicated that all isolates belong to sheep lineage of strains of M. ap (M. ap-S), suggesting a putative transmission from infected sheep herds. Screening sheep and goat herds associated with camels identified the circulation of this type in sheep but not goats. The current genome-wide analysis recognizes these camel isolates as a sub-lineage of the sheep strain with a significant number of single nucleotide polymorphisms (SNPs) between sheep and camel isolates (∼1000 SNPs). Such polymorphism could represent geographical differences among isolates or host adaptation of M. ap during camel infection. To our knowledge, this is the first attempt to examine the genomic basis of this emerging infection in camels with implications on the evolution of this important pathogen. The sequenced genomes of M. ap isolates from camels will further assist our efforts to understand JD pathogenesis and the dynamic of disease transmission across animal species

Anesthesia advanced circulatory life support

The constellation of advanced cardiac life support (ACLS) events, such as gas embolism, local anesthetic overdose, and spinal bradycardia, in the perioperative setting differs from events in the pre-hospital arena. As a result, modification of traditional ACLS protocols allows for more specific etiology-based resuscitation. Perioperative arrests are both uncommon and heterogeneous and have not been described or studied to the same extent as cardiac arrest in the community. These crises are usually witnessed, frequently anticipated, and involve a rescuer physician with knowledge of the patient's comorbidities and coexisting anesthetic or surgically related pathophysiology. When the health care provider identifies the probable cause of arrest, the practitioner has the ability to initiate medical management rapidly. Recommendations for management must be predicated on expert opinion and physiological understanding rather than on the standards currently being used in the generation of ACLS protocols in the community. Adapting ACLS algorithms and considering the differential diagnoses of these perioperative events may prevent cardiac arrest

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Supernova neutrino burst detection with the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the νe spectral parameters of the neutrino burst will be considered

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 1: The LBNF and DUNE Projects

This document presents the Conceptual Design Report (CDR) put forward by an international neutrino community to pursue the Deep Underground Neutrino Experiment at the Long-Baseline Neutrino Facility (LBNF/DUNE), a groundbreaking science experiment for long-baseline neutrino oscillation studies and for neutrino astrophysics and nucleon decay searches. The DUNE far detector will be a very large modular liquid argon time-projection chamber (LArTPC) located deep underground, coupled to the LBNF multi-megawatt wide-band neutrino beam. DUNE will also have a high-resolution and high-precision near detector

The Single-Phase ProtoDUNE Technical Design Report

ProtoDUNE-SP is the single-phase DUNE Far Detector prototype that is under construction and will be operated at the CERN Neutrino Platform (NP) starting in 2018. ProtoDUNE-SP, a crucial part of the DUNE effort towards the construction of the first DUNE 10-kt fiducial mass far detector module (17 kt total LAr mass), is a significant experiment in its own right. With a total liquid argon (LAr) mass of 0.77 kt, it represents the largest monolithic single-phase LArTPC detector to be built to date. It's technical design is given in this report

Experiment Simulation Configurations Approximating DUNE TDR

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community

Neutrino interaction classification with a convolutional neural network in the DUNE far detector

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects