Gene Expression Responses Linked to Reproduction Effect Concentrations (EC10,20,50,90) of Dimethoate, Atrazine and Carbendazim, in Enchytraeus albidus

BACKGROUND: Molecular mechanisms of response to pesticides are scarce and information on such responses from soil invertebrates is almost inexistent. Enchytraeus albidus (Oligochaeta) is a standard soil ecotoxicology model species for which effects of many pesticides are known on survival, reproduction and avoidance behaviour. With the recent microarray development additional information can be retrieved on the molecular effects. METHODOLOGY/PRINCIPAL FINDINGS: Experiments were performed to investigate the transcription responses of E. albidus when exposed to three pesticides - dimethoate (insecticide), atrazine (herbicide) and carbendazim (fungicide) - in a range of concentrations that inhibited reproduction by 10%, 20%, 50% and 90% (EC(10), EC(20), EC(50) and EC(90), respectively). The goal of this study was to further identify key biological processes affected by each compound and if dose-related. All three pesticides significantly affected biological processes like translation, regulation of the cell cycle or general response to stress. Intracellular signalling and microtubule-based movement were affected by dimethoate and carbendazim whereas atrazine affected lipid and steroid metabolism (also by dimethoate) or carbohydrate metabolism (also by carbendazim). Response to DNA damage/DNA repair was exclusively affected by carbendazim. CONCLUSIONS: Changes in gene expression were significantly altered after 2 days of exposure in a dose-related manner. The mechanisms of response were comparable with the ones for mammals, suggesting across species conserved modes of action. The present results indicate the potential of using gene expression in risk assessment and the advantage as early markers

Elevation in Body Temperature to Fever Range Enhances and Prolongs Subsequent Responsiveness of Macrophages to Endotoxin Challenge

Macrophages are often considered the sentries in innate immunity, sounding early immunological alarms, a function which speeds the response to infection. Compared to the large volume of studies on regulation of macrophage function by pathogens or cytokines, relatively little attention has been devoted to the role of physical parameters such as temperature. Given that temperature is elevated during fever, a long-recognized cardinal feature of inflammation, it is possible that macrophage function is responsive to thermal signals. To explore this idea, we used LPS to model an aseptic endotoxin-induced inflammatory response in BALB/c mice and found that raising mouse body temperature by mild external heat treatment significantly enhances subsequent LPS-induced release of TNF-α into the peritoneal fluid. It also reprograms macrophages, resulting in sustained subsequent responsiveness to LPS, i.e., this treatment reduces “endotoxin tolerance” in vitro and in vivo. At the molecular level, elevating body temperature of mice results in a increase in LPS-induced downstream signaling including enhanced phosphorylation of IKK and IκB, NF-κB nuclear translocation and binding to the TNF-α promoter in macrophages upon secondary stimulation. Mild heat treatment also induces expression of HSP70 and use of HSP70 inhibitors (KNK437 or Pifithrin-µ) largely abrogates the ability of the thermal treatment to enhance TNF-α, suggesting that the induction of HSP70 is important for mediation of thermal effects on macrophage function. Collectively, these results support the idea that there has been integration between the evolution of body temperature regulation and macrophage function that could help to explain the known survival benefits of fever in organisms following infection

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

Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP's successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) will produce world-leading neutrino oscillation measurements over the lifetime of the experiment. In this work, we explore DUNE's sensitivity to observe charge-parity violation (CPV) in the neutrino sector, and to resolve the mass ordering, for exposures of up to 100 kiloton-megawatt-years (kt-MW-yr). The analysis includes detailed uncertainties on the flux prediction, the neutrino interaction model, and detector effects. We demonstrate that DUNE will be able to unambiguously resolve the neutrino mass ordering at a 3σ (5σ) level, with a 66 (100) kt-MW-yr far detector exposure, and has the ability to make strong statements at significantly shorter exposures depending on the true value of other oscillation parameters. We also show that DUNE has the potential to make a robust measurement of CPV at a 3σ level with a 100 kt-MW-yr exposure for the maximally CP-violating values \delta_{\rm CP}} = \pm\pi/2. Additionally, the dependence of DUNE's sensitivity on the exposure taken in neutrino-enhanced and antineutrino-enhanced running is discussed. An equal fraction of exposure taken in each beam mode is found to be close to optimal when considered over the entire space of interest