Ansiedad competitiva y clima motivacional en jóvenes futbolistas de competición, en relación con las habilidades y el rendimiento percibido por sus entrenadores

En este estudio se analizan las relaciones existentes entre la ansiedad competitiva (en sus facetas cognitiva y somática) y el clima motivacional percibido (de ego y de maestría) en una población de 54 jóvenes futbolistas decompetición de edad media de 9,45 años, respecto de la percepción de sus habilidades y rendimiento deportivos por parte de sus 4 entrenadores, que también participaron en el estudio. Para ello se les administró las versiones españolas del SAS-2 (Sport Anxiety Scale-2, Smith, Smoll, Cumming y Grossbard, 2006) y el MCSYS (Motivational Climate Scale for Youth Sports,Smith, Cumming y Smoll, 2008), así como dos escalas ad hoc para evaluar la percepción de su habilidad y rendimiento. Los resultados muestran, por una parte, que los jóvenes futbolistas perciben y discriminan claramente los climas motivacionales, que se distribuyen casi al 50% entre ego y maestría; por otra, que aparece ansiedad competitiva, aunque más cognitiva que somática, y que no existe relación significativa con las percepciones de habilidad y rendimiento por parte de los entrenadores. Finalmente, estos resultados se discuten y se comparan con otros similares en poblaciones preadolescentesThis study analysed the relationships between competitive anxiety (both cognitive and somatic) and perceived motivational climate (ego and mastery) in 54 young competitive soccer players (mean age: 9.45 years), related to their four coaches' perceptions of the soccer players' skills and performance. We administered the Spanish versions of the SAS-2 (Sport Anxiety Scale-2, Smith, Smoll, Cumming and Grossbard, 2006) and the MCSYS (Motivational Climate Scale for Youth Sports, Smith, Cumming and Smoll, 2008), along with two ad hoc scales to evaluate perceived skills and performance.The results show that 1) young players perceived and discriminated clearly between motivational climates (which were more or less equally distributed between ego and mastery orientations), 2) some performance-related anxiety (mostly cognitive rather than somatic) appeared and 3) no significant relationships were found between their coaches' perceptions of their skills and their performance. Lastly, the results are discussed and compared with similar results from preadolescent player

Novel CYP4F22 mutations associated with autosomal recessive congenital ichthyosis (ARCI). Study of the CYP4F22 c.1303C>T founder mutation

Mutations in CYP4F22 cause autosomal recessive congenital ichthyosis (ARCI). However, less than 10% of all ARCI patients carry a mutation in CYP4F22. In order to identify the molecular basis of ARCI among our patients (a cohort of ninety-two Spanish individuals) we performed a mutational analysis using direct Sanger sequencing in combination with a multigene targeted NGS panel. From these, eight ARCI families (three of them with Moroccan origin) were found to carry five different CYP4F22 mutations, of which two were novel. Computational analysis showed that the mutations found were present in highly conserved residues of the protein and may affect its structure and function. Seven of the eight families were carriers of a highly recurrent CYP4F22 variant, c.1303C>T; p.(His435Tyr). A 12Mb haplotype was reconstructed in all c.1303C>T carriers by genotyping ten microsatellite markers flanking the CYP4F22 gene. A prevalent 2.52Mb haplotype was observed among Spanish carrier patients suggesting a recent common ancestor. A smaller core haplotype of 1.2Mb was shared by Spanish and Moroccan families. Different approaches were applied to estimate the time to the most recent common ancestor (TMRCA) of carrier patients with Spanish origin. The age of the mutation was calculated by using DMLE and BDMC2. The algorithms estimated that the c.1303C>T variant arose approximately 2925 to 4925 years ago, while Spanish carrier families derived from a common ancestor who lived in the XIII century. The present study reports five CYP4F22 mutations, two of them novel, increasing the number of CYP4F22 mutations currently listed. Additionally, our results suggest that the recurrent c.1303C>T change has a founder effect in Spanish population and c.1303C>T carrier families originated from a single ancestor with probable African ancestry

Impact of obstructive sleep apnea on the occurrence of restenosis after elective percutaneous coronary intervention in ischemic heart disease

<p>Abstract</p> <p>Rationale</p> <p>There is growing evidence that obstructive sleep apnea is associated with coronary artery disease. However, there are no data on the course of coronary stenosis after percutaneous coronary intervention in patients with obstructive sleep apnea.</p> <p>Objectives</p> <p>To determine whether sleep apnea is associated with increased late lumen loss and restenosis after percutaneous coronary intervention.</p> <p>Methods</p> <p>78 patients with coronary artery disease who underwent elective percutaneous coronary intervention were divided in 2 groups: 43 patients with an apnea hypopnea – Index < 10/h (group I) and 35 pt. with obstructive sleep apnea and an AHI > 10/h (group II). Late lumen loss, a marker of restenosis, was determined using quantitative coronary angiography after 6.9 ± 3.1 months.</p> <p>Main results</p> <p>Angiographic restenosis (>50% luminal diameter), was present in 6 (14%) of group I and in 9 (25%) of group II (p = 0.11). Late lumen loss was significant higher in pt. with an AHI > 10/h (0.7 ± 0.69 mm vs. 0.38 ± 0.37 mm, p = 0.01). Among these 35 patients, 21(60%) used their CPAP devices regularly. There was a marginally lower late lumen loss in treated patients, nevertheless, this difference did not reach statistical significance (0.57 ± 0.47 mm vs. 0.99 ± 0.86 mm, p = 0.08). There was no difference in late lumen loss between treated patients and the group I (p = 0.206).</p> <p>Conclusion</p> <p>In summary, patients with OSA and coronary artery disease have a higher degree of late lumen loss, which is a marker of restenosis and vessel remodeling after elective percutaneous intervention.</p

Diabetes Is an Independent Risk Factor for Severe Nocturnal Hypoxemia in Obese Patients. A Case-Control Study

Type 2 diabetes mellitus (T2DM) and obesity have become two of the main threats to public health in the Western world. In addition, obesity is the most important determinant of the sleep apnea-hypopnea syndrome (SAHS), a condition that adversely affects glucose metabolism. However, it is unknown whether patients with diabetes have more severe SAHS than non-diabetic subjects. The aim of this cross-sectional case-control study was to evaluate whether obese patients with T2DM are more prone to severe SAHS than obese non-diabetic subjects.Thirty obese T2DM and 60 non-diabetic women closely matched by age, body mass index, waist circumference, and smoking status were recruited from the outpatient Obesity Unit of a university hospital. The exclusion criteria included chronic respiratory disease, smoking habit, neuromuscular and cerebrovascular disease, alcohol abuse, use of sedatives, and pregnancy. Examinations included a non-attended respiratory polygraphy, pulmonary function testing, and an awake arterial gasometry. Oxygen saturation measures included the percentage of time spent at saturations below 90% (CT90). A high prevalence of SAHS was found in both groups (T2DM:80%, nondiabetic:78.3%). No differences in the number of sleep apnea-hypopnea events between diabetic and non-diabetic patients were observed. However, in diabetic patients, a significantly increase in the CT90 was detected (20.2+/-30.2% vs. 6.8+/-13,5%; p = 0.027). In addition, residual volume (RV) was significantly higher in T2DM (percentage of predicted: 79.7+/-18.1 vs. 100.1+/-22.8; p<0.001). Multiple linear regression analyses showed that T2DM but not RV was independently associated with CT90.T2DM adversely affects breathing during sleep, becoming an independent risk factor for severe nocturnal hypoxemia in obese patients. Given that SAHS is a risk factor of cardiovascular disease, the screening for SAHS in T2DM patients seems mandatory

Gaia Early Data Release 3: Summary of the contents and survey properties

Brown, A., et al. (Gaia Collaboration). This article has an erratum: [https://doi.org/10.1051/0004-6361/202039657e][Context] We present the early installment of the third Gaia data release, Gaia EDR3, consisting of astrometry and photometry for 1.8 billion sources brighter than magnitude 21, complemented with the list of radial velocities from Gaia DR2. [Aims] A summary of the contents of Gaia EDR3 is presented, accompanied by a discussion on the differences with respect to Gaia DR2 and an overview of the main limitations which are present in the survey. Recommendations are made on the responsible use of Gaia EDR3 results. [Methods] The raw data collected with the Gaia instruments during the first 34 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium and turned into this early third data release, which represents a major advance with respect to Gaia DR2 in terms of astrometric and photometric precision, accuracy, and homogeneity. Results. Gaia EDR3 contains celestial positions and the apparent brightness in G for approximately 1.8 billion sources. For 1.5 billion of those sources, parallaxes, proper motions, and the (GBP - GRP) colour are also available. The passbands for G, GBP, and GRP are provided as part of the release. For ease of use, the 7 million radial velocities from Gaia DR2 are included in this release, after the removal of a small number of spurious values. New radial velocities will appear as part of Gaia DR3. Finally, Gaia EDR3 represents an updated materialisation of the celestial reference frame (CRF) in the optical, the Gaia-CRF3, which is based solely on extragalactic sources. The creation of the source list for Gaia EDR3 includes enhancements that make it more robust with respect to high proper motion stars, and the disturbing effects of spurious and partially resolved sources. The source list is largely the same as that for Gaia DR2, but it does feature new sources and there are some notable changes. The source list will not change for Gaia DR3. [Conclusions] Gaia EDR3 represents a significant advance over Gaia DR2, with parallax precisions increased by 30 per cent, proper motion precisions increased by a factor of 2, and the systematic errors in the astrometry suppressed by 30-40% for the parallaxes and by a factor ~2.5 for the proper motions. The photometry also features increased precision, but above all much better homogeneity across colour, magnitude, and celestial position. A single passband for G, GBP, and GRP is valid over the entire magnitude and colour range, with no systematics above the 1% levelThe Gaia mission and data processing have financially been supported by, in alphabetical order by country: the Algerian Centre de Recherche en Astronomie, Astrophysique et Géophysique of Bouzareah Observatory; the Austrian Fonds zur Förderung der wissenschaftlichen Forschung (FWF) Hertha Firnberg Programme through grants T359, P20046, and P23737; the BELgian federal Science Policy Office (BELSPO) through various PROgramme de Développement d’Expériences scientifiques (PRODEX) grants and the Polish Academy of Sciences – Fonds Wetenschappelijk Onderzoek through grant VS.091.16N, and the Fonds de la Recherche Scientifique (FNRS); the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES) – Comité Français d’Evaluation de la Coopération Universitaire et Scientifique avec le Brésil (COFECUB); the National Science Foundation of China (NSFC) through grants 11573054 and 11703065 and the China Scholarship Council through grant 201806040200; the Tenure Track Pilot Programme of the Croatian Science Foundation and the École Polytechnique Fédérale de Lausanne and the project TTP-2018-07-1171 “Mining the Variable Sky”, with the funds of the Croatian-Swiss Research Programme; the Czech-Republic Ministry of Education, Youth, and Sports through grant LG 15010 and INTER-EXCELLENCE grant LTAUSA18093, and the Czech Space Office through ESA PECS contract 98058; the Danish Ministry of Science; the Estonian Ministry of Education and Research through grant IUT40-1; the European Commission’s Sixth Framework Programme through the European Leadership in Space Astrometry (ELSA) Marie Curie Research Training Network (MRTN-CT-2006-033481), through Marie Curie project PIOF-GA-2009-255267 (Space AsteroSeismology & RR Lyrae stars, SAS-RRL), and through a Marie Curie Transfer-of-Knowledge (ToK) fellowship (MTKD-CT-2004-014188); the European Commission’s Seventh Framework Programme through grant FP7-606740 (FP7-SPACE-2013-1) for the Gaia European Network for Improved data User Services (GENIUS) and through grant 264895 for the Gaia Research for European Astronomy Training (GREAT-ITN) network; the European Research Council (ERC) through grants 320360 and 647208 and through the European Union’s Horizon 2020 research and innovation and excellent science programmes through Marie Skłodowska-Curie grant 745617 as well as grants 670519 (Mixing and Angular Momentum tranSport of massIvE stars – MAMSIE), 687378 (Small Bodies: Near and Far), 682115 (Using the Magellanic Clouds to Understand the Interaction of Galaxies), and 695099 (A sub-percent distance scale from binaries and Cepheids – CepBin); the European Science Foundation (ESF), in the framework of the Gaia Research for European Astronomy Training Research Network Programme (GREAT-ESF); the European Space Agency (ESA) in the framework of the Gaia project, through the Plan for European Cooperating States (PECS) programme through grants for Slovenia, through contracts C98090 and 4000106398/12/NL/KML for Hungary, and through contract 4000115263/15/NL/IB for Germany; the Academy of Finland and the Magnus Ehrnrooth Foundation; the French Centre National d’Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR) through grant ANR-10-IDEX-0001-02 for the “Investissements d’avenir” programme, through grant ANR-15-CE31-0007 for project “Modelling the Milky Way in the Gaia era” (MOD4Gaia), through grant ANR-14-CE33-0014-01 for project “The Milky Way disc formation in the Gaia era” (ARCHEOGAL), and through grant ANR-15-CE31-0012-01 for project “Unlocking the potential of Cepheids as primary distance calibrators” (UnlockCepheids), the Centre National de la Recherche Scientifique (CNRS) and its SNO Gaia of the Institut des Sciences de l’Univers (INSU), the “Action Fédératrice Gaia” of the Observatoire de Paris, the Région de Franche-Comté, and the Programme National de Gravitation, Références, Astronomie, et Métrologie (GRAM) of CNRS/INSU with the Institut National Polytechnique (INP) and the Institut National de Physique nucléaire et de Physique des Particules (IN2P3) co-funded by CNES; the German Aerospace Agency (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) through grants 50QG0501, 50QG0601, 50QG0602, 50QG0701, 50QG0901, 50QG1001, 50QG1101, 50QG1401, 50QG1402, 50QG1403, 50QG1404, and 50QG1904 and the Centre for Information Services and High Performance Computing (ZIH) at the Technische Universität (TU) Dresden for generous allocations of computer time; the Hungarian Academy of Sciences through the Lendület Programme grants LP2014-17 and LP2018-7 and through the Premium Postdoctoral Research Programme (L. Molnár), and the Hungarian National Research, Development, and Innovation Office (NKFIH) through grant KH_18-130405; the Science Foundation Ireland (SFI) through a Royal Society – SFI University Research Fellowship (M. Fraser); the Israel Science Foundation (ISF) through grant 848/16; the Agenzia Spaziale Italiana (ASI) through contracts I/037/08/0, I/058/10/0, 2014-025-R.0, 2014-025-R.1.2015, and 2018-24-HH.0 to the Italian Istituto Nazionale di Astrofisica (INAF), contract 2014-049-R.0/1/2 to INAF forthe Space Science Data Centre (SSDC, formerly known as the ASI Science Data Center, ASDC), contracts I/008/10/0, 2013/030/I.0, 2013-030-I.0.1-2015, and 2016-17-I.0 to the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.), INAF, and the Italian Ministry of Education, University, and Research (Ministero dell’Istruzione, dell’Università e della Ricerca) through the Premiale project “MIning The Cosmos Big Data and Innovative Italian Technology for Frontier Astrophysics and Cosmology” (MITiC); the Netherlands Organisation for Scientific Research (NWO) through grant NWO-M-614.061.414, through a VICI grant (A.H.), and through a Spinoza prize (A.H.), and the Netherlands Research School for Astronomy (NOVA); the Polish National Science Centre through HARMONIA grant 2018/06/M/ST9/00311, DAINA grant 2017/27/L/ST9/03221, and PRELUDIUM grant 2017/25/N/ST9/01253, and the Ministry of Science and Higher Education (MNiSW) through grant DIR/WK/2018/12; the Portugese Fundação para a Ciência e a Tecnologia (FCT) through grants SFRH/BPD/74697/2010 and SFRH/BD/128840/2017 and the Strategic Programme UID/FIS/00099/2019 for CENTRA; the Slovenian Research Agency through grant P1-0188; the Spanish Ministry of Economy (MINECO/FEDER, UE) through grants ESP2016-80079-C2-1-R, ESP2016-80079-C2-2-R, RTI2018-095076-B-C21, RTI2018-095076-B-C22, BES-2016-078499, and BES-2017-083126 and the Juan de la Cierva formación 2015 grant FJCI-2015-2671, the Spanish Ministry of Education, Culture, and Sports through grant FPU16/03827, the Spanish Ministry of Science and Innovation (MICINN) through grant AYA2017-89841P for project “Estudio de las propiedades de los fósiles estelares en el entorno del Grupo Local” and through grant TIN2015-65316-P for project “Computación de Altas Prestaciones VII”, the Severo Ochoa Centre of Excellence Programme of the Spanish Government through grant SEV2015-0493, the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grants MDM-2014-0369 and CEX2019-000918-M, the University of Barcelona’s official doctoral programme for the development of an R+D+i project through an Ajuts de Personal Investigador en Formació (APIF) grant, the Spanish Virtual Observatory through project AyA2017-84089, the Galician Regional Government, Xunta de Galicia, through grants ED431B-2018/42 and ED481A-2019/155, support received from the Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC) funded by the Xunta de Galicia, the Xunta de Galicia and the Centros Singulares de Investigación de Galicia for the period 2016-2019 through CITIC, the European Union through the European Regional Development Fund (ERDF) / Fondo Europeo de Desenvolvemento Rexional (FEDER) for the Galicia 2014-2020 Programme through grant ED431G-2019/01, the Red Española de Supercomputación (RES) computer resources at MareNostrum, the Barcelona Supercomputing Centre – Centro Nacional de Supercomputación (BSC-CNS) through activities AECT-2016-1-0006, AECT-2016-2-0013, AECT-2016-3-0011, and AECT-2017-1-0020, the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya through grant 2014-SGR-1051 for project “Models de Programació i Entorns d’Execució Parallels” (MPEXPAR), and Ramon y Cajal Fellowship RYC2018-025968-I; the Swedish National Space Agency (SNSA/Rymdstyrelsen); the Swiss State Secretariat for Education, Research, and Innovation through the Mesures d’Accompagnement, the Swiss Activités Nationales Complémentaires, and the Swiss National Science Foundation; the United Kingdom Particle Physics and Astronomy Research Council (PPARC), the United Kingdom Science and Technology Facilities Council (STFC), and the United Kingdom Space Agency (UKSA) through the following grants to the University of Bristol, the University of Cambridge, the University of Edinburgh, the University of Leicester, the Mullard Space Sciences Laboratory of University College London, and the United Kingdom Rutherford Appleton Laboratory (RAL): PP/D006511/1, PP/D006546/1, PP/D006570/1, ST/I000852/1, ST/J005045/1, ST/K00056X/1, ST/K000209/1, ST/K000756/1, ST/L006561/1, ST/N000595/1, ST/N000641/1, ST/N000978/1, ST/N001117/1, ST/S000089/1, ST/S000976/1, ST/S001123/1, ST/S001948/1, ST/S002103/1, and ST/V000969/1. This work made use of the following software: Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration 2013, 2018, http://www.astropy.org), IPython (Pérez & Granger 2007, https://ipython.org/), Jupyter (https://jupyter.org/), Matplotlib (Hunter 2007, https://matplotlib.org), SciPy (Virtanen et al. 2020, https://www.scipy.org), NumPy (Harris et al. 2020, https://numpy.org), and TOPCAT (Taylor 2005, http://www.starlink.ac.uk/topcat/). This work has made use of NASA’s Astrophysics Data System. We thank the referee, Andy Casey, for a careful reading of the manuscript

Predicting Survival after Allogeneic Hematopoietic Cell Transplantation in Myelofibrosis : Performance of the Myelofibrosis Transplant Scoring System (MTSS) and Development of a New Prognostic Model

Accurate prognostic tools are crucial to assess the risk/benefit ratio of allogeneic hematopoietic cell transplantation (allo-HCT) in patients with myelofibrosis (MF). We aimed to evaluate the performance of the Myelofibrosis Transplant Scoring System (MTSS) and identify risk factors for survival in a multicenter series of 197 patients with MF undergoing allo-HCT. After a median follow-up of 3.1 years, 47% of patients had died, and the estimated 5-year survival rate was 51%. Projected 5-year risk of nonrelapse mortality and relapse incidence was 30% and 20%, respectively. Factors independently associated with increased mortality were a hematopoietic cell transplantation-specific comorbidity index (HCT-CI) ≥3 and receiving a graft from an HLA-mismatched unrelated donor or cord blood, whereas post-transplant cyclophosphamide (PT-Cy) was associated with improved survival. Donor type was the only parameter included in the MTSS model with independent prognostic value for survival. According to the MTSS, 3-year survival was 62%, 66%, 37%, and 17% for low-, intermediate-, high-, and very high-risk groups, respectively. By pooling together the low- and intermediate-risk groups, as well as the high- and very high-risk groups, we pinpointed 2 categories: standard risk and high risk (25% of the series). Three-year survival was 62% in standard-risk and 25% in high-risk categories (P <.001). We derived a risk score based on the 3 independent risk factors for survival in our series (donor type, HCT-CI, and PT-Cy). The corresponding 5-year survival for the low-, intermediate-, and high-risk categories was 79%, 55%, and 32%, respectively (P <.001). In conclusion, the MTSS model failed to clearly delineate 4 prognostic groups in our series but may still be useful to identify a subset of patients with poor outcome. We provide a simple prognostic scoring system for risk/benefit considerations before transplantation in patients with MF

Secuencia de tratamiento óptima para el tratamiento del mieloma múltiple en España un modelo secuencial

PO-014 Introducción: El mieloma múltiple (MM) se sigue considerando una enfermedad incurable. Sin embargo, con la disponibilidad de nuevos fármacos, las opciones de tratamiento para pacientes de MM han incrementado drásticamente, aumentando a su vez su supervivencia. Esto hace que sea necesario evaluar la secuencia de tratamiento más apropiada, en lugar de los regímenes de manera aislada. Junto con la seguridad y la eficacia, la evaluación económica se está convirtiendo en una herramienta cada vez más útil y necesaria en la toma de decisiones. Objetivos: El estudio tiene como objetivo estimar los beneficios y costes de las secuencias de tratamiento en el MM más comunes para establecer un umbral de eficiencia y determinar la ratio coste-eficacia incremental (ICER) entre las secuencias. Métodos: Se diseñó un modelo de Markov con 5 estados de salud que representan líneas de tratamiento (1ª, 2ª, 3ª y posteriores) y muerte, con 3 subestados relacionados con la respuesta (respuesta completa [CR], respuesta parcial [PR] y no respuesta [NR]) para simular la transición de pacientes (cada 4 semanas) a lo largo del curso de la enfermedad. Un consejo de hematólogos definió veinte posibles secuencias de tratamiento, como las más utilizadas en la práctica clínica en España. Una revisión de la literatura permitió la identificación de los estudios para estimar las tasas de respuesta específica de cada terapia y los eventos adversos (EA), junto con el tiempo de progresión dependiente de la respuesta requerido para modelar la transición entre las líneas terapéuticas sucesivas y los valores de utilidad necesarios para evaluar la calidad de vida de los pacientes para poder estimar la variable principal del estudio ..

Gaia Early Data Release 3: The Gaia Catalogue of Nearby Stars

Smart, R. L., et al. (Gaia Collaboration)[Aims] We produce a clean and well-characterised catalogue of objects within 100 pc of the Sun from the Gaia Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. [Methods] Theselection of objects within 100 pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100 pc is included in the catalogue. [Results] We have produced a catalogue of 331 312 objects that we estimate contains at least 92% of stars of stellar type M9 within 100 pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100 pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of Gaia Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10 pc of the Sun. [Conclusions] We provide the community with a large, well-characterised catalogue of objects in the solar neighbourhood. This is a primary benchmark for measuring and understanding fundamental parameters and descriptive functions in astronomy.The Gaia mission and data processing have financially been supported by, in alphabetical order by country: the Algerian Centre de Recherche en Astronomie, Astrophysique et Géophysique of Bouzareah Observatory; the Austrian Fonds zur Förderung der wissenschaftlichen Forschung (FWF) Hertha Firnberg Programme through grants T359, P20046, and P23737; the BELgian federal Science Policy Office (BELSPO) through various PROgramme de Développement d’Expériences scientifiques (PRODEX) grants and the Polish Academy of Sciences – Fonds Wetenschappelijk Onderzoek through grant VS.091.16N, and the Fonds de la Recherche Scientifique (FNRS); the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES) – Comité Français d’Evaluation de la Coopération Universitaire et Scientifique avec le Brésil (COFECUB); the National Science Foundation of China (NSFC) through grants 11573054 and 11703065 and the China Scholarship Council through grant 201806040200; the Tenure Track Pilot Programme of the Croatian Science Foundation and the École Polytechnique Fédérale de Lausanne and the project TTP-2018-07-1171 “Mining the Variable Sky”, with the funds of the Croatian-Swiss Research Programme; the Czech-Republic Ministry of Education, Youth, and Sports through grant LG 15010 and INTER-EXCELLENCE grant LTAUSA18093, and the Czech Space Office through ESA PECS contract 98058; the Danish Ministry of Science; the Estonian Ministry of Education and Research through grant IUT40-1; the European Commission’s Sixth Framework Programme through the European Leadership in Space Astrometry (ELSA) Marie Curie Research Training Network (MRTN-CT-2006-033481), through Marie Curie project PIOF-GA-2009-255267 (Space AsteroSeismology & RR Lyrae stars, SAS-RRL), and through a Marie Curie Transfer-of-Knowledge (ToK) fellowship (MTKD-CT-2004-014188); the European Commission’s Seventh Framework Programme through grant FP7-606740 (FP7-SPACE-2013-1) for the Gaia European Network for Improved data User Services (GENIUS) and through grant 264895 for the Gaia Research for European Astronomy Training (GREAT-ITN) network; the European Research Council (ERC) through grants 320360 and 647208 and through the European Union’s Horizon 2020 research and innovation and excellent science programmes through Marie Skłodowska-Curie grant 745617 as well as grants 670519 (Mixing and Angular Momentum tranSport of massIvE stars – MAMSIE), 687378 (Small Bodies: Near and Far), 682115 (Using the Magellanic Clouds to Understand the Interaction of Galaxies), and 695099 (A sub-percent distance scale from binaries and Cepheids – CepBin); the European Science Foundation (ESF), in the framework of the Gaia Research for European Astronomy Training Research Network Programme (GREAT-ESF); the European Space Agency (ESA) in the framework of the Gaia project, through the Plan for European Cooperating States (PECS) programme through grants for Slovenia, through contracts C98090 and 4000106398/12/NL/KML for Hungary, and through contract 4000115263/15/NL/IB for Germany; the Academy of Finland and the Magnus Ehrnrooth Foundation; the French Centre National d’Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR) through grant ANR-10-IDEX-0001-02 for the “Investissements d’avenir” programme, through grant ANR-15-CE31-0007 for project “Modelling the Milky Way in the Gaia era” (MOD4Gaia), through grant ANR-14-CE33-0014-01 for project “The Milky Way disc formation in the Gaia era” (ARCHEOGAL), and through grant ANR-15-CE31-0012-01 for project “Unlocking the potential of Cepheids as primary distance calibrators” (UnlockCepheids), the Centre National de la Recherche Scientifique (CNRS) and its SNO Gaia of the Institut des Sciences de l’Univers (INSU), the “Action Fédératrice Gaia” of the Observatoire de Paris, the Région de Franche-Comté, and the Programme National de Gravitation, Références, Astronomie,et Métrologie (GRAM) of CNRS/INSU with the Institut National Polytechnique (INP) and the Institut National de Physique nucléaire et de Physique des Particules (IN2P3) co-funded by CNES; the German Aerospace Agency (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) through grants 50QG0501, 50QG0601, 50QG0602, 50QG0701, 50QG0901, 50QG1001, 50QG1101, 50QG1401, 50QG1402, 50QG1403, 50QG1404, and 50QG1904 and the Centre for Information Services and High Performance Computing (ZIH) at the Technische Universität (TU) Dresden for generous allocations of computer time; the Hungarian Academy of Sciences through the Lendület Programme grants LP2014-17 and LP2018-7 and through the Premium Postdoctoral Research Programme (L. Molnár), and the Hungarian National Research, Development, and Innovation Office (NKFIH) through grant KH_18-130405; the Science Foundation Ireland (SFI) through a Royal Society - SFI University Research Fellowship (M. Fraser); the Israel Science Foundation (ISF) through grant 848/16; the Agenzia Spaziale Italiana (ASI) through contracts I/037/08/0, I/058/10/0, 2014-025-R.0, 2014-025-R.1.2015, and 2018-24-HH.0 to the Italian Istituto Nazionale di Astrofisica (INAF), contract 2014-049-R.0/1/2 to INAF for the Space Science Data Centre (SSDC, formerly known as the ASI Science Data Center, ASDC), contracts I/008/10/0, 2013/030/I.0, 2013-030-I.0.1-2015, and 2016-17-I.0 to the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.), INAF, and the Italian Ministry of Education, University, and Research (Ministero dell’Istruzione, dell’Università e della Ricerca) through the Premiale project “MIning The Cosmos Big Data and Innovative Italian Technology for Frontier Astrophysics and Cosmology” (MITiC); the Netherlands Organisation for Scientific Research (NWO) through grant NWO-M-614.061.414, through a VICI grant (A. Helmi), and through a Spinoza prize (A. Helmi), and the Netherlands Research School for Astronomy (NOVA); the Polish National Science Centre through HARMONIA grant 2018/06/M/ST9/00311, DAINA grant 2017/27/L/ST9/03221, and PRELUDIUM grant 2017/25/N/ST9/01253, and the Ministry of Science and Higher Education (MNiSW) through grant DIR/WK/2018/12; the Portugese Fundação para a Ciência e a Tecnologia (FCT) through grants SFRH/BPD/74697/2010 and SFRH/BD/128840/2017 and the Strategic Programme UID/FIS/00099/2019 for CENTRA; the Slovenian Research Agency through grant P1-0188; the Spanish Ministry of Economy (MINECO/FEDER, UE) through grants ESP2016-80079-C2-1-R, ESP2016-80079-C2-2-R, RTI2018-095076-B-C21, RTI2018-095076-B-C22, BES-2016-078499, and BES-2017-083126 and the Juan de la Cierva formación 2015 grant FJCI-2015-2671, the Spanish Ministry of Education, Culture, and Sports through grant FPU16/03827, the Spanish Ministry of Science and Innovation (MICINN) through grant AYA2017-89841P for project “Estudio de las propiedades de los fósiles estelares en el entorno del Grupo Local” and through grant TIN2015-65316-P for project “Computación de Altas Prestaciones VII”, the Severo Ochoa Centre of Excellence Programme of the Spanish Government through grant SEV2015-0493, the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grants MDM-2014-0369 and CEX2019-000918-M, the University of Barcelona’s official doctoral programme for the development of an R+D+i project through an Ajuts de Personal Investigador en Formació (APIF) grant, the Spanish Virtual Observatory through project AyA2017-84089, the Galician Regional Government, Xunta de Galicia, through grants ED431B-2018/42 and ED481A-2019/155, support received from the Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC) funded by the Xunta de Galicia, the Xunta de Galicia and the Centros Singulares de Investigación de Galicia for the period 2016-2019 through CITIC, the European Union through the European Regional Development Fund (ERDF) / Fondo Europeo de Desenvolvemento Rexional (FEDER) for the Galicia 2014-2020 Programme through grant ED431G-2019/01, the Red Española de Supercomputación (RES) computer resources at MareNostrum, the Barcelona Supercomputing Centre – Centro Nacional de Supercomputación (BSC-CNS) through activities AECT-2016-1-0006, AECT-2016-2-0013, AECT-2016-3-0011, and AECT-2017-1-0020, the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya through grant 2014-SGR-1051 for project “Models de Programació i Entorns d’Execució Parallels” (MPEXPAR), and Ramon y Cajal Fellowship RYC2018-025968-I; the Swedish National Space Agency (SNSA/Rymdstyrelsen); the Swiss State Secretariat for Education, Research, and Innovation through the Mesures d’Accompagnement, the Swiss Activités Nationales Complémentaires, and the Swiss National Science Foundation; the United Kingdom Particle Physics and Astronomy Research Council (PPARC), the United Kingdom Science and Technology Facilities Council (STFC), and the United Kingdom Space Agency (UKSA) through the following grants to the University of Bristol, the University of Cambridge, the University of Edinburgh, the University of Leicester, the Mullard Space Sciences Laboratory of University College London, and the United Kingdom Rutherford Appleton Laboratory (RAL): PP/D006511/1, PP/D006546/1, PP/D006570/1, ST/I000852/1, ST/J005045/1, ST/K00056X/1, ST/K000209/1, ST/K000756/1, ST/L006561/1, ST/N000595/1, ST/N000641/1, ST/N000978/1, ST/N001117/1, ST/S000089/1, ST/S000976/1, ST/S001123/1, ST/S001948/1, ST/S002103/1, and ST/V000969/1

MKS3/TMEM67 mutations are a major cause of COACH syndrome, a joubert syndrome related disorder with liver involvement

The acronym COACH defines an autosomal recessive condition of Cerebellar vermis hypo/ aplasia, Oligophrenia, congenital Ataxia, Coloboma and Hepatic fibrosis. Patients present the “molar tooth sign”, a midbrain-hindbrain malformation pathognomonic for Joubert Syndrome (JS) and Related Disorders (JSRDs). The main feature of COACH is congenital hepatic fibrosis (CHF), resulting from malformation of the embryonic ductal plate. CHF is invariably found also in Meckel syndrome (MS), a lethal ciliopathy already found to be allelic with JSRDs at the CEP290 and RPGRIP1L genes. Recently, mutations in the MKS3 gene (approved symbol TMEM67), causative of about 7% MS cases, have been detected in few Meckel-like and pure JS patients. Analysis of MKS3 in 14 COACH families identified mutations in 8 (57%). Features such as colobomas and nephronophthisis were found only in a subset of mutated cases. These data confirm COACH as a distinct JSRD subgroup with core features of JS plus CHF, which major gene is MKS3, and further strengthen gene-phenotype correlates in JSRDs

Gaia Early Data Release 3 Acceleration of the Solar System from Gaia astrometry

Context. Gaia Early Data Release 3 (Gaia EDR3) provides accurate astrometry for about 1.6 million compact (QSO-like) extragalactic sources, 1.2 million of which have the best-quality five-parameter astrometric solutions. Aims. The proper motions of QSO-like sources are used to reveal a systematic pattern due to the acceleration of the solar systembarycentre with respect to the rest frame of the Universe. Apart from being an important scientific result by itself, the acceleration measured in this way is a good quality indicator of the Gaia astrometric solution. Methods. Theeffect of the acceleration was obtained as a part of the general expansion of the vector field of proper motions in vector spherical harmonics (VSH). Various versions of the VSH fit and various subsets of the sources were tried and compared to get the most consistent result and a realistic estimate of its uncertainty. Additional tests with the Gaia astrometric solution were used to get a better idea of the possible systematic errors in the estimate. Results. Our best estimate of the acceleration based on Gaia EDR3 is (2.32 +/- 0.16) x 10(-10) m s(-2) (or 7.33 +/- 0.51 km s(-1) Myr-1) towards alpha = 269.1 degrees +/- 5.4 degrees, delta = -31.6 degrees +/- 4.1 degrees, corresponding to a proper motion amplitude of 5.05 +/- 0.35 mu as yr(-1). This is in good agreement with the acceleration expected from current models of the Galactic gravitational potential. We expect that future Gaia data releases will provide estimates of the acceleration with uncertainties substantially below 0.1 mu as yr(-1).Peer reviewe