MicroRNA-222 regulates muscle alternative splicing through Rbm24 during differentiation of skeletal muscle cells

A number of microRNAs have been shown to regulate skeletal muscle development and differentiation. MicroRNA-222 is downregulated during myogenic differentiation and its overexpression leads to alteration of muscle differentiation process and specialized structures. By using RNA-induced silencing complex (RISC) pulldown followed by RNA sequencing, combined with in silico microRNA target prediction, we have identified two new targets of microRNA-222 involved in the regulation of myogenic differentiation, Ahnak and Rbm24. Specifically, the RNA-binding protein Rbm24 is a major regulator of muscle-specific alternative splicing and its downregulation by microRNA-222 results in defective exon inclusion impairing the production of muscle-specific isoforms of Coro6, Fxr1 and NACA transcripts. Reconstitution of normal levels of Rbm24 in cells overexpressing microRNA-222 rescues muscle-specific splicing. In conclusion, we have identified a new function of microRNA-222 leading to alteration of myogenic differentiation at the level of alternative splicing, and we provide evidence that this effect is mediated by Rbm24 protei

GUASOM: An Adaptive Visualization Tool for Unsupervised Clustering in Spectrophotometric Astronomical Surveys

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] We present an adaptive visualization tool for unsupervised classification of astronomical objects in a Big Data context such as the one found in the increasingly popular large spectrophotometric sky surveys. This tool is based on an artificial intelligence technique, Kohonen’s self-organizing maps, and our goal is to facilitate the analysis work of the experts by means of oriented domain visualizations, which is impossible to achieve by using a generic tool. We designed a client-server that handles the data treatment and computational tasks to give responses as quickly as possible, and we used JavaScript Object Notation to pack the data between server and client. We optimized, parallelized, and evenly distributed the necessary calculations in a cluster of machines. By applying our clustering tool to several databases, we demonstrated the main advantages of an unsupervised approach: the classification is not based on pre-established models, thus allowing the “natural classes” present in the sample to be discovered, and it is suited to isolate atypical cases, with the important potential for discovery that this entails. Gaia Utility for the Analysis of self-organizing maps is an analysis tool that has been developed in the context of the Data Processing and Analysis Consortium, which processes and analyzes the observations made by ESA’s Gaia satellite (European Space Agency) and prepares the mission archive that is presented to the international community in sequential periodic publications. Our tool is useful not only in the context of the Gaia mission, but also allows segmenting the information present in any other massive spectroscopic or spectrophotometric database.This work made use of the infrastructures acquired with grants provided by the State Research Agency (AEI) of the Spanish Government and the European Regional Development Fund (FEDER), RTI2018-095076-B-C22. We acknowledge support from CIGUS-CITIC, funded by Xunta de Galicia and the European Union (FEDER Galicia 2014-2020 Program) through grant ED431G 2019/01 and research consolidation grant ED431B 2021/36. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC), https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah. The SDSS website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration. We also want to acknowledge Alhambra survey funded by the Spanish Goverment under Grant AYA2006-14056. Open Access funding provided thanks to the Universidade da Coruña/CISUG agreement with Springer NatureXunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431B 2021/3

Detection of a multi-shell planetary nebula around the hot subdwarf O-type star 2MASS J19310888+4324577

(Abridged) The origin of hot subdwarf O-type stars (sdOs) remains unclear since their discovery in 1947. Among others, a post-Asymptotic Giant Branch (post-AGB) origin is possible for a fraction of sdOs. We are involved in a comprehensive ongoing study to search for and to analyze planetary nebulae (PNe) around sdOs with the aim of establishing the fraction and properties of sdOs with a post-AGB origin. We use deep Halpha and [OIII] images of sdOs to detect nebular emission and intermediate resolution, long-slit optical spectroscopy of the detected nebulae and their sdO central stars. These data are complemented with other observations for further analysis of the detected nebulae. We report the detection of an extremely faint, complex PN around 2MASS J19310888+4324577 (2M1931+4324), a star classified as sdO in a binary system. The PN shows a bipolar and an elliptical shell, whose major axes are oriented perpendicular to each other, and high-excitation structures outside the two shells. WISE archive images show faint, extended emission at 12 and 22 microns in the inner nebular regions. The internal nebular kinematics is consistent with a bipolar and a cylindrical/ellipsoidal shell, in both cases with the main axis mainly perpendicular to the line of sight. The nebular spectrum only exhibits Halpha, Hbeta and [OIII]4959,5007 emission lines, but suggests a very low-excitation ([OIII]/Hbeta = 1.5), in strong contrast with the absence of low-excitation emission lines. The spectrum of 2M1931+4324 presents narrow, ionized helium absorptions that confirm the previous sdO classification and suggest an effective temperature >= 60000 K. The binary nature of 2M1931+4324, its association with a complex PN, and several properties of the system provide strong support for the idea that binary central stars are a crucial ingredient in the formation of complex PNe.Comment: 8 pages, 7 figures, accepted in Astronomy and Astrophysic

Bandwidth selection for kernel density estimation with length-biased data

Length-biased data are a particular case of weighted data, which arise in many situations: biomedicine, quality control or epidemiology among others. In this paper we study the theoretical properties of kernel density estimation in the context of length-biased data, proposing two consistent bootstrap methods that we use for bandwidth selection. Apart from the bootstrap bandwidth selectors we suggest a rule-of-thumb. These bandwidth selection proposals are compared with a least-squares cross-validation method. A simulation study is accomplished to understand the behaviour of the procedures in finite samples