Sucrose overconsumption impairs AgRP neuron dynamics and promotes palatable food intake

Summary: Rapid gut-brain communication is critical to maintain energy balance and is disrupted in diet-induced obesity. In particular, the role of carbohydrate overconsumption in the regulation of interoceptive circuits in vivo requires further investigation. Here, we report that an obesogenic high-sucrose diet (HSD) selectively blunts silencing of hunger-promoting agouti-related protein (AgRP) neurons following intragastric delivery of glucose, whereas we previously showed that overconsumption of a high-fat diet (HFD) selectively attenuates lipid-induced neural silencing. By contrast, both HSD and HFD reversibly dampen rapid AgRP neuron inhibition following chow presentation and promote intake of more palatable foods. Our findings reveal that excess sugar and fat pathologically modulate feeding circuit activity in both macronutrient-dependent and -independent ways and thus may additively exacerbate obesity

Science goals and mission architecture of the Europa Lander mission concept

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hand, K., Phillips, C., Murray, A., Garvin, J., Maize, E., Gibbs, R., Reeves, G., San Martin, A., Tan-Wang, G., Krajewski, J., Hurst, K., Crum, R., Kennedy, B., McElrath, T., Gallon, J., Sabahi, D., Thurman, S., Goldstein, B., Estabrook, P., Lee, S. W., Dooley, J. A., Brinckerhoff, W. B., Edgett, K. S., German, C. R., Hoehler, T. M., Hörst, S. M., Lunine, J. I., Paranicas, C., Nealson, K., Smith, D. E., Templeton, A. S., Russell, M. J., Schmidt, B., Christner, B., Ehlmann, B., Hayes, A., Rhoden, A., Willis, P., Yingst, R. A., Craft, K., Cameron, M. E., Nordheim, T., Pitesky, J., Scully, J., Hofgartner, J., Sell, S. W., Barltrop, K. J., Izraelevitz, J., Brandon, E. J., Seong, J., Jones, J.-P., Pasalic, J., Billings, K. J., Ruiz, J. P., Bugga, R. V., Graham, D., Arenas, L. A., Takeyama, D., Drummond, M., Aghazarian, H., Andersen, A. J., Andersen, K. B., Anderson, E. W., Babuscia, A., Backes, P. G., Bailey, E. S., Balentine, D., Ballard, C. G., Berisford, D. F., Bhandari, P., Blackwood, K., Bolotin, G. S., Bovre, E. A., Bowkett, J., Boykins, K. T., Bramble, M. S., Brice, T. M., Briggs, P., Brinkman, A. P., Brooks, S. M., Buffington, B. B., Burns, B., Cable, M. L., Campagnola, S., Cangahuala, L. A., Carr, G. A., Casani, J. R., Chahat, N. E., Chamberlain-Simon, B. K., Cheng, Y., Chien, S. A., Cook, B. T., Cooper, M., DiNicola, M., Clement, B., Dean, Z., Cullimore, E. A., Curtis, A. G., Croix, J-P. de la, Pasquale, P. Di, Dodd, E. M., Dubord, L. A., Edlund, J. A., Ellyin, R., Emanuel, B., Foster, J. T., Ganino, A. J., Garner, G. J., Gibson, M. T., Gildner, M., Glazebrook, K. J., Greco, M. E., Green, W. M., Hatch, S. J., Hetzel, M. M., Hoey, W. A., Hofmann, A. E., Ionasescu, R., Jain, A., Jasper, J. D., Johannesen, J. R., Johnson, G. K., Jun, I., Katake, A. B., Kim-Castet, S. Y., Kim, D. I., Kim, W., Klonicki, E. F., Kobeissi, B., Kobie, B. D., Kochocki, J., Kokorowski, M., Kosberg, J. A., Kriechbaum, K., Kulkarni, T. P., Lam, R. L., Landau, D. F., Lattimore, M. A., Laubach, S. L., Lawler, C. R., Lim, G., Lin, J. Y., Litwin, T. E., Lo, M. W., Logan, C. A., Maghasoudi, E., Mandrake, L., Marchetti, Y., Marteau, E., Maxwell, K. A., Namee, J. B. Mc, Mcintyre, O., Meacham, M., Melko, J. P., Mueller, J., Muliere, D. A., Mysore, A., Nash, J., Ono, H., Parker, J. M., Perkins, R. C., Petropoulos, A. E., Gaut, A., Gomez, M. Y. Piette, Casillas, R. P., Preudhomme, M., Pyrzak, G., Rapinchuk, J., Ratliff, J. M., Ray, T. L., Roberts, E. T., Roffo, K., Roth, D. C., Russino, J. A., Schmidt, T. M., Schoppers, M. J., Senent, J. S., Serricchio, F., Sheldon, D. J., Shiraishi, L. R., Shirvanian, J., Siegel, K. J., Singh, G., Sirota, A. R., Skulsky, E. D., Stehly, J. S., Strange, N. J., Stevens, S. U., Sunada, E. T., Tepsuporn, S. P., Tosi, L. P. C., Trawny, N., Uchenik, I., Verma, V., Volpe, R. A., Wagner, C. T., Wang, D., Willson, R. G., Wolff, J. L., Wong, A. T., Zimmer, A. K., Sukhatme, K. G., Bago, K. A., Chen, Y., Deardorff, A. M., Kuch, R. S., Lim, C., Syvertson, M. L., Arakaki, G. A., Avila, A., DeBruin, K. J., Frick, A., Harris, J. R., Heverly, M. C., Kawata, J. M., Kim, S.-K., Kipp, D. M., Murphy, J., Smith, M. W., Spaulding, M. D., Thakker, R., Warner, N. Z., Yahnker, C. R., Young, M. E., Magner, T., Adams, D., Bedini, P., Mehr, L., Sheldon, C., Vernon, S., Bailey, V., Briere, M., Butler, M., Davis, A., Ensor, S., Gannon, M., Haapala-Chalk, A., Hartka, T., Holdridge, M., Hong, A., Hunt, J., Iskow, J., Kahler, F., Murray, K., Napolillo, D., Norkus, M., Pfisterer, R., Porter, J., Roth, D., Schwartz, P., Wolfarth, L., Cardiff, E. H., Davis, A., Grob, E. W., Adam, J. R., Betts, E., Norwood, J., Heller, M. M., Voskuilen, T., Sakievich, P., Gray, L., Hansen, D. J., Irick, K. W., Hewson, J. C., Lamb, J., Stacy, S. C., Brotherton, C. M., Tappan, A. S., Benally, D., Thigpen, H., Ortiz, E., Sandoval, D., Ison, A. M., Warren, M., Stromberg, P. G., Thelen, P. M., Blasy, B., Nandy, P., Haddad, A. W., Trujillo, L. B., Wiseley, T. H., Bell, S. A., Teske, N. P., Post, C., Torres-Castro, L., Grosso, C. Wasiolek, M. Science goals and mission architecture of the Europa Lander mission concept. The Planetary Science Journal, 3(1), (2022): 22, https://doi.org/10.3847/psj/ac4493.Europa is a premier target for advancing both planetary science and astrobiology, as well as for opening a new window into the burgeoning field of comparative oceanography. The potentially habitable subsurface ocean of Europa may harbor life, and the globally young and comparatively thin ice shell of Europa may contain biosignatures that are readily accessible to a surface lander. Europa's icy shell also offers the opportunity to study tectonics and geologic cycles across a range of mechanisms and compositions. Here we detail the goals and mission architecture of the Europa Lander mission concept, as developed from 2015 through 2020. The science was developed by the 2016 Europa Lander Science Definition Team (SDT), and the mission architecture was developed by the preproject engineering team, in close collaboration with the SDT. In 2017 and 2018, the mission concept passed its mission concept review and delta-mission concept review, respectively. Since that time, the preproject has been advancing the technologies, and developing the hardware and software, needed to retire risks associated with technology, science, cost, and schedule.K.P.H., C.B.P., E.M., and all authors affiliated with the Jet Propulsion Laboratory carried out this research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (grant No. 80NM0018D0004). J.I.L. was the David Baltimore Distinguished Visiting Scientist during the preparation of the SDT report. JPL/Caltech2021

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

International audienceThe Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents

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

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

International audienceLiquid 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

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