A microRNA Cluster Controls Fat Cell Differentiation and Adipose Tissue Expansion By Regulating SNCG

The H19X-encoded miR-424(322)/503 cluster regulates multiple cellular functions. Here, it is reported for the first time that it is also a critical linchpin of fat mass expansion. Deletion of this miRNA cluster in mice results in obesity, while increasing the pool of early adipocyte progenitors and hypertrophied adipocytes. Complementary loss and gain of function experiments and RNA sequencing demonstrate that miR-424(322)/503 regulates a conserved genetic program involved in the differentiation and commitment of white adipocytes. Mechanistically, it is demonstrated that miR-424(322)/503 targets gamma-Synuclein (SNCG), a factor that mediates this program rearrangement by controlling metabolic functions in fat cells, allowing adipocyte differentiation and adipose tissue enlargement. Accordingly, diminished miR-424(322) in mice and obese humans co-segregate with increased SNCG in fat and peripheral blood as mutually exclusive features of obesity, being normalized upon weight loss. The data unveil a previously unknown regulatory mechanism offat mass expansion tightly controlled by the miR-424(322)/503 through SNCG.Peer reviewe

Genetic transformation of sweet orange with the coat protein gene of Citrus psorosis virus and evaluation of resistance against the virus

Citrus psorosis is a serious viral disease affecting citrus trees in many countries. Its causal agent is Citrus psorosis virus (CPsV), the type member of genus Ophiovirus. CPsV infects most important citrus varieties, including oranges, mandarins and grapefruits, as well as hybrids and citrus relatives used as rootstocks. Certification programs have not been sufficient to control the disease and no sources of natural resistance have been found. Pathogen-derived resistance (PDR) can provide an efficient alternative to control viral diseases in their hosts. For this purpose, we have produced 21 independent lines of sweet orange expressing the coat protein gene of CPsV and five of them were challenged with the homologous CPV 4 isolate. Two different viral loads were evaluated to challenge the transgenic plants, but so far, no resistance or tolerance has been found in any line after 1 year of observations. In contrast, after inoculation all lines showed characteristic symptoms of psorosis in the greenhouse. The transgenic lines expressed low and variable amounts of the cp gene and no correlation was found between copy number and transgene expression. One line contained three copies of the cp gene, expressed low amounts of the mRNA and no coat protein. The ORF was cytosine methylated suggesting a PTGS mechanism, although the transformant failed to protect against the viral load used. Possible causes for the failed protection against the CPsV are discussed

A microRNA Cluster Controls Fat Cell Differentiation and Adipose Tissue Expansion By Regulating SNCG

The H19X-encoded miR-424(322)/503 cluster regulates multiple cellular functions. Here, it is reported for the first time that it is also a critical linchpin of fat mass expansion. Deletion of this miRNA cluster in mice results in obesity, while increasing the pool of early adipocyte progenitors and hypertrophied adipocytes. Complementary loss and gain of function experiments and RNA sequencing demonstrate that miR-424(322)/503 regulates a conserved genetic program involved in the differentiation and commitment of white adipocytes. Mechanistically, it is demonstrated that miR-424(322)/503 targets gamma-Synuclein (SNCG), a factor that mediates this program rearrangement by controlling metabolic functions in fat cells, allowing adipocyte differentiation and adipose tissue enlargement. Accordingly, diminished miR-424(322) in mice and obese humans co-segregate with increased SNCG in fat and peripheral blood as mutually exclusive features of obesity, being normalized upon weight loss. The data unveil a previously unknown regulatory mechanism offat mass expansion tightly controlled by the miR-424(322)/503 through SNCG.Peer reviewe

Innovar en la enseñanza universitaria

Se recogen experiencias docentes innovadoras desarrolladas en la Universidad de Alcalá con el objetivo de indagar en las posibilidades y obstáculos surgidos en los procesos de cambio e innovación. En dichas experiencias docentes se han implementado nuevas metodologías, experiencias piloto y Proyectos de Innovación, que han contribuido a clarificar el proceso y a indagar en propuestas de acción contextualizadas. Las experiencias de dividen en cuatro bloques: estrategias de aprendizaje activo; estrategias de integración curricular; innovación en la educación; y uso de las nuevas tecnologías.MadridBiblioteca de Educación del Ministerio de Educación, Cultura y Deporte; Calle San Agustín 5 -3 Planta; 28014 Madrid; Tel. +34917748000; [email protected]

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

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

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

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

Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

International audienceA primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the O(10)  MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the νe component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section σ(Eν) for charged-current νe absorption on argon. In the context of a simulated extraction of supernova νe spectral parameters from a toy analysis, we investigate the impact of σ(Eν) modeling uncertainties on DUNE’s supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on σ(Eν) must be substantially reduced before the νe flux parameters can be extracted reliably; in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10% bias with DUNE requires σ(Eν) to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of σ(Eν). A direct measurement of low-energy νe-argon scattering would be invaluable for improving the theoretical precision to the needed level

The DUNE Far Detector Vertical Drift Technology, Technical Design Report

International audienceDUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals