Complete genome sequence of Granulicella mallensis type strain MP5ACTX8T, an acidobacterium from tundra soil

Granulicella mallensis MP5ACTX8(T) is a novel species of the genus Granulicella in subdivision 1of Acidobacteria. G. mallensis is of ecological interest being a member of the dominant soil bacterial community active at low temperatures and nutrient limiting conditions in Arctic alpine tundra. G. mallensis is a cold-adapted acidophile and a versatile heterotroph that hydrolyzes a suite of sugars and complex polysaccharides. Genome analysis revealed metabolic versatility with genes involved in metabolism and transport of carbohydrates. These include gene modules encoding the carbohydrate-active enzyme (CAZyme) family involved in breakdown, utilization and biosynthesis of diverse structural and storage polysaccharides including plant based carbon polymers. The genome of Granulicella mallensis MP5ACTX8(T) consists of a single replicon of 6,237,577 base pairs (bp) with 4,907 protein-coding genes and 53 RNA genes

Bianchi Type V Viscous Fluid Cosmological Models in Presence of Decaying Vacuum Energy

Bianchi type V viscous fluid cosmological model for barotropic fluid distribution with varying cosmological term $\Lambda$ is investigated. We have examined a cosmological scenario proposing a variation law for Hubble parameter $H$ in the background of homogeneous, anisotropic Bianchi type V space-time. The model isotropizes asymptotically and the presence of shear viscosity accelerates the isotropization. The model describes a unified expansion history of the universe indicating initial decelerating expansion and late time accelerating phase. Cosmological consequences of the model are also discussed.Comment: 10 pages, 3 figure

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

International audienceMeasurements of electrons from νe 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 missing 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

Highly-parallelized simulation of a pixelated LArTPC on a GPU

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

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos

PD-1 is a regulator of NY-ESO-1-specific CD8+ T cell expansion in melanoma patients.

The programmed death 1 (PD-1) receptor is a negative regulator of activated T cells and is up-regulated on exhausted virus-specific CD8(+) T cells in chronically infected mice and humans. Programmed death ligand 1 (PD-L1) is expressed by multiple tumors, and its interaction with PD-1 resulted in tumor escape in experimental models. To investigate the role of PD-1 in impairing spontaneous tumor Ag-specific CD8(+) T cells in melanoma patients, we have examined the effect of PD-1 expression on ex vivo detectable CD8(+) T cells specific to the tumor Ag NY-ESO-1. In contrast to EBV, influenza, or Melan-A/MART-1-specific CD8(+) T cells, NY-ESO-1-specific CD8(+) T cells up-regulated PD-1 expression. PD-1 up-regulation on spontaneous NY-ESO-1-specific CD8(+) T cells occurs along with T cell activation and is not directly associated with an inability to produce cytokines. Importantly, blockade of the PD-1/PD-L1 pathway in combination with prolonged Ag stimulation with PD-L1(+) APCs or melanoma cells augmented the number of cytokine-producing, proliferating, and total NY-ESO-1-specific CD8(+) T cells. Collectively, our findings support the role of PD-1 as a regulator of NY-ESO-1-specific CD8(+) T cell expansion in the context of chronic Ag stimulation. They further support the use of PD-1/PD-L1 pathway blockade in cancer patients to partially restore NY-ESO-1-specific CD8(+) T cell numbers and functions, increasing the likelihood of tumor regression