Influencia de la fertilización nitrogenada sobre las concentraciones de K+, Mg2+ y Ca2+ y sus bioindicadores en raíces y hojas de plantas de judía

The pyruvate kinase (PK) and ATPase activities taking part in nitrogen (N) assimilation is essential for the growth and development of plants. Studies on the kinetics of these enzymes reveal that its activities are dependent of the cofactors K+, Ca2+, and Mg2+. Therefore, the objective of the present work was to determine the effect of different doses of N on enzymatic activities of ATPase and PK as potentials biochemical indicators of the levels of K+, Mg2+, and Ca2+ in the roots and leaves of green bean plants. The N was applied to the nutrient solution as NH4NO3 at the following rates: 1.5, 3.0, 6.0, 12.0, 18.0, and 24.0 mM of N. These results indicate that deficient conditions of N (N1 and N2) were characterized by the lowest accumulation of K+, Mg2+ and Ca2+ in both total and soluble forms, and also minimum activities of PK and ATPase induced by K+, Mg2+ and Ca2+, with respect to the activity of basal PK and ATPase; this could mean near optimum conditions for these cations. On the contrary, high-N treatments (N4, N5 and N6) were characterized by presenting decreasing concentrations of total and soluble K+, Mg2+ and Ca2+ in roots and leaves of green bean plants; however, the activities of PK and ATPase induced with K+, Mg2+ and Ca2+ were increased reaching their maximum activity with respect to basal PK and ATPase, both enzymes reflecting the level of cations in roots and leaves, hence being considered as good physiological bioindicators of these cations.Las actividades piruvato kinasa (PK) y ATPasa participan en la asimilación de nitrógeno (N), la cual es esencial para el crecimiento y desarrollo de las plantas. Estudios sobre cinéticas de estas enzimas revelan que sus actividades son dependientes de los cofactores K+, Ca2+ y Mg2+. Por lo tanto, el objetivo del presente trabajo fue determinar el efecto de diferentes dosis de N sobre las actividades de la ATPasa y PK como posibles bioindicadores de los niveles de K+, Mg2+ y Ca2+ en raíces y hojas de plantas de judía (Phaseolus vulgaris L. cv. Strike). Se aplicó N a la solución nutritiva como NH4NO3 en las siguientes dosis: N1=1,5 mM, N2=3,0 mM, N3=6,0 mM, N4=12,0 mM, N5=18,0 mM y N6=24,0 mM. Los resultados indican que bajo condiciones deficientes de N (N1 y N2), las plantas presentaron menor acumulación de K+, Mg2+ y Ca2+ en su forma total y soluble, así como mínimas actividades PK y ATPasa inducidas por K+, Mg2+ y Ca2+ respecto a la actividad PK y ATPasa basal; lo cual indica condiciones cercanas a las óptimas de estos cationes. Por el contrario, en los tratamientos elevados de N (N4, N5 y N6) las plantas presentaron concentraciones decrecientes de K+, Mg2+ y Ca2+ total y soluble tanto en raíces como en hojas; sin embargo, las actividades PK y ATPasa inducidas con K+, Mg2+ y Ca2+ se incrementaron alcanzando sus máximas actividades con respecto a la PK y ATPasa basal, lo que indica una mayor necesidad fisiológica de estos cationes en los tratamientos elevados de N. Finalmente, la actividad ATPasa basal y la inducida con K+, Mg2+ y Ca2+ se comportaron de forma similar a la actividad PK, lo que refleja el nivel de cationes en raíces y en hojas, por lo que se consideran buenos bioindicadores fisiológicos de estos cationes

Arquitectura de Microservicios para Ensayos Clínicos en Pérdida de Peso con Plataformas mHealth

Las terapias contra el sobrepeso y la obesidad se basan en la modificación del estilo de vida sin embargo la adherencia es baja porque los estilos saludables son difíciles de mantener en el tiempo. Las funcionalidades adecuadas para que las aplicaciones móviles (mHealth) faciliten el cambio permanecen sin identificar. El presente trabajo presenta una arquitectura mHealth de microservicios para estudios clínicos con los que identificarlas. La metodología de diseño y desarrollo incluyo historias de usuario, Domain-Driven Design (DDD) y Scrum. Los microservicios identificados, su definición, y la organización de nuestra arquitectura son suficientes para realizar estudios clínicos en pérdida de peso con plataformas mHealth. Entre los trabajos futuros mas inmediatos destaca la conexión de la presente arquitectura con servicios de gestión de estudios clínicos de uso común como RedCap.Esta investigación fue financiada por CIBER - Consorcio Centro de Investigación Biomédica en Red- (CB06/01/0051), el proyecto AN´IMATE 2 (CIBER- BBN early stage intramural projects 2022) y el proyecto ALEVINT (CIBERESP-BBN collaboration projects 2022), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovació

Gaia Data Release 3. Catalogue validation

Babusiaux, C., et al.[Context] The third Gaia data release (DR3) provides a wealth of new data products. The early part of the release, Gaia EDR3, already provided the astrometric and photometric data for nearly two billion sources. The full release now adds improved parameters compared to Gaia DR2 for radial velocities, astrophysical parameters, variability information, light curves, and orbits for Solar System objects. The improvements are in terms of the number of sources, the variety of parameter information, precision, and accuracy. For the first time, Gaia DR3 also provides a sample of spectrophotometry and spectra obtained with the Radial Velocity Spectrometer, binary star solutions, and a characterisation of extragalactic object candidates.[Aims] Before the publication of the catalogue, these data have undergone a dedicated transversal validation process. The aim of this paper is to highlight limitations of the data that were found during this process and to provide recommendations for the usage of the catalogue.[Methods] The validation was obtained through a statistical analysis of the data, a confirmation of the internal consistency of different products, and a comparison of the values to external data or models.[Results] Gaia DR3 is a new major step forward in terms of the number, diversity, precision, and accuracy of the Gaia products. As always in such a large and complex catalogue, however, issues and limitations have also been found. Detailed examples of the scientific quality of the Gaia DR3 release can be found in the accompanying data-processing papers as well as in the performance verification papers. Here we focus only on the caveats that the user should be aware of to scientifically exploit the data.This work has been supported by the Agence Nationale de la Recherche (ANR project SEGAL ANR-19-CE31-0017). It has also received funding from the project ANR-18-CE31-0006 and from the European Research Council (ERC grant agreement No. 834148). ZKR acknowledges funding from the Netherlands Research School for Astronomy (NOVA). This work was partially funded by the Spanish MICIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” by the “European Union” through grant RTI2018-095076-B-C21, and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia ‘María de Maeztu’) through grant CEX2019-000918-M.Peer reviewe

A catalogue of Spanish archaeomagnetic data

International audienceA total of 58 new archaeomagnetic directions has been determined from archaeological structures in Spain. Together with five previous results they allow the compilation of the first archaeomagnetic catalogue for Spain, which includes 63 directions with ages ranging between the 2nd century BC and the 20th century AD. Characteristic remanence directions have been obtained from stepwise thermal and alternating field demagnetization. The hierarchical structure has been respected in the calculation of the mean site directions. Rock magnetic experiments reveal that the main magnetic carrier is magnetite or titanomagnetite with different titanium contents. The age estimate of the studied structures is generally well justified by archaeological constraints. For six structures the proposed date is also supported by physical methods. The data are in close agreement with the French secular variation (SV) curve. This catalogue represents the first step in the construction of a SV curve for the Iberian Peninsula, which will be of much use in archaeomagnetic dating and in modelling of the Earth's magnetic field in Western Europe

Gaia Focused Product Release: Radial velocity time series of long-period variables

Context. The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (FPR) provides radial-velocity time series for a selection of LPV candidates with high-quality observations. Aims. We describe the production and content of the Gaia catalog of LPV radial-velocity time series, and the methods used to compute the variability parameters published as part of the Gaia FPR. Methods. Starting from the DR3 catalog of LPV candidates, we applied several filters to construct a sample of sources with high-quality radial-velocity measurements. We modeled their radial-velocity and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the radial-velocity period and at least one of the G, GBP, or GRP photometric periods. Results. The catalog includes radial-velocity time series and variability parameters for 9614 sources in the magnitude range 6 ≲ G/mag ≲ 14, including a flagged top-quality subsample of 6093 stars whose radial-velocity periods are fully compatible with the values derived from the G, GBP, and GRP photometric time series. The radial-velocity time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great majority of the sources (88%) as genuine LPV candidates, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% of the catalog consists of candidate ellipsoidal binaries. Quality checks against radial velocities available in the literature show excellent agreement. We provide some illustrative examples and cautionary remarks. Conclusions. The publication of radial-velocity time series for almost ten thousand LPV candidates constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog

Taxonomic and Environmental Variability in the Elemental Composition and Stoichiometry of Individual Dinoflagellate and Diatom Cells from the NW Mediterranean Sea

Here we present, for the first time, the elemental concentration, including C, N and O, of single phytoplankton cells collected from the sea. Plankton elemental concentration and stoichiometry are key variables in phytoplankton ecophysiology and ocean biogeochemistry, and are used to link cells and ecosystems. However, most field studies rely on bulk techniques that overestimate carbon and nitrogen because the samples include organic matter other than plankton organisms. Here we used X-ray microanalysis (XRMA), a technique that, unlike bulk analyses, gives simultaneous quotas of C, N, O, Mg, Si, P, and S, in single-cell organisms that can be collected directly from the sea. We analysed the elemental composition of dinoflagellates and diatoms (largely Chaetoceros spp.) collected from different sites of the Catalan coast (NW Mediterranean Sea). As expected, a lower C content is found in our cells compared to historical values of cultured cells. Our results indicate that, except for Si and O in diatoms, the mass of all elements is not a constant fraction of cell volume but rather decreases with increasing cell volume. Also, diatoms are significantly less dense in all the measured elements, except Si, compared to dinoflagellates. The N:P ratio of both groups is higher than the Redfield ratio, as it is the N:P nutrient ratio in deep NW Mediterranean Sea waters (N:P = 20–23). The results suggest that the P requirement is highest for bacterioplankton, followed by dinoflagellates, and lowest for diatoms, giving them a clear ecological advantage in P-limited environments like the Mediterranean Sea. Finally, the P concentration of cells of the same genera but growing under different nutrient conditions was the same, suggesting that the P quota of these cells is at a critical level. Our results indicate that XRMA is an accurate technique to determine single cell elemental quotas and derived conversion factors used to understand and model ocean biogeochemical cycles

Gaia Focused Product Release: Radial velocity time series of long-period variables

The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity (RV) in DR4, this Focused Product Release (FPR) provides RV time series for a selection of LPVs with high-quality observations. We describe the production and content of the Gaia catalog of LPV RV time series, and the methods used to compute variability parameters published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied filters to construct a sample of sources with high-quality RV measurements. We modeled their RV and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the RV period and at least one of the $G$, $G_{\rm BP}$, or $G_{\rm RP}$ photometric periods. The catalog includes RV time series and variability parameters for 9\,614 sources in the magnitude range $6\lesssim G/{\rm mag}\lesssim 14$, including a flagged top-quality subsample of 6\,093 stars whose RV periods are fully compatible with the values derived from the $G$, $G_{\rm BP}$, and $G_{\rm RP}$ photometric time series. The RV time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great most sources (88%) as genuine LPVs, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% consists of candidate ellipsoidal binaries. Quality checks against RVs available in the literature show excellent agreement. We provide illustrative examples and cautionary remarks. The publication of RV time series for almost 10\,000 LPVs constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog (abridged)Comment: 36 pages, 38 figure

Gaia focused product release: Spatial distribution of two diffuse interstellar bands

Gaia Collaboration: et al.Diffuse interstellar bands (DIBs) are absorption features seen in optical and infrared spectra of stars and extragalactic objects that are probably caused by large and complex molecules in the galactic interstellar medium (ISM). Here we investigate the Galactic distribution and properties of two DIBs identified in almost six million stellar spectra collected by the Gaia Radial Velocity Spectrometer. These measurements constitute a part of the Gaia Focused Product Release to be made public between the Gaia DR3 and DR4 data releases. In order to isolate the DIB signal from the stellar features in each individual spectrum, we identified a set of 160 000 spectra at high Galactic latitudes (|b| ⩾ 65°) covering a range of stellar parameters which we consider to be the DIB-free reference sample. Matching each target spectrum to its closest reference spectra in stellar parameter space allowed us to remove the stellar spectrum empirically, without reference to stellar models, leaving a set of six million ISM spectra. Using the star’s parallax and sky coordinates, we then allocated each ISM spectrum to a voxel (VOlume piXEL) on a contiguous three-dimensional grid with an angular size of 1.8° (level 5 HEALPix) and 29 unequally sized distance bins. Identifying the two DIBs at 862.1 nm (λ862.1) and 864.8 nm (λ864.8) in the stacked spectra, we modelled their shapes and report the depth, central wavelength, width, and equivalent width (EW) for each, along with confidence bounds on these measurements. We then explored the properties and distributions of these quantities and compared them with similar measurements from other surveys. Our main results are as follows: (1) the strength and spatial distribution of the DIB λ862.1 are very consistent with what was found in Gaia DR3, but for this work we attained a higher signal-to-noise ratio in the stacked spectra to larger distances, which allowed us to trace DIBs in the outer spiral arm and beyond the Scutum–Centaurus spiral arm; (2) we produced an all-sky map below ±65° of Galactic latitude to ~4000 pc of both DIB features and their correlations; (3) we detected the signals of DIB λ862.1 inside the Local Bubble (≲200 pc); and (4) there is a reasonable correlation with the dust reddening found from stellar absorption and EWs of both DIBs with a correlation coefficient of 0.90 for λ862.1 and 0.77 for λ864.8.This work presents results from the European Space Agency (ESA) space mission Gaia. Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia MultiLat eral Agreement (MLA). The Gaia mission website is https: //www.cosmos.esa.int/gaia. The Gaia archive website is https://archives.esac.esa.int/gaia. The Gaia mission and data processing have financially been supported by, in alphabetical order by country: – the Algerian Centre de Recherche en Astronomie, Astro physique 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 (BEL SPO) through various PROgramme de Développement d’Expériences scientifiques (PRODEX) grants of the European Space Agency (ESA), the Research Foundation Flanders (Fonds Wetenschappelijk Onderzoek) through grant VS.091.16N, the Fonds de la Recherche Scientifique (FNRS), and the Research Council of Katholieke Univer siteit (KU) Leuven through grant C16/18/005 (Pushing AsteRoseismology to the next level with TESS, GaiA, and the Sloan DIgital Sky SurvEy – PARADISE); – the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeicoamento de Pessoal de Nível Supe rior (CAPES) - Comité Français d’Evaluation de la Coopéra tion Universitaire et Scientifique avec le Brésil (COFECUB); – the Chilean Agencia Nacional de Investigación y Desar rollo (ANID) through Fondo Nacional de Desarrollo Cientí fico y Tecnológico (FONDECYT) Regular Project 1210992 (L. Chemin); – the National Natural Science Foundation of China (NSFC) through grants 11573054, 11703065, and 12173069, the China Scholarship Council through grant 201806040200, and the Natural Science Foundation of Shanghai through grant 21ZR1474100; – the Tenure Track Pilot Programme of the Croatian Sci ence 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 Ser vices (GENIUS) and through grant 264895 for the Gaia Research for European Astronomy Training (GREAT-ITN) network; – the European Cooperation in Science and Technology (COST) through COST Action CA18104 ‘Revealing the Milky Way with Gaia (MW-Gaia)’; – the European Research Council (ERC) through grants 320360, 647208, and 834148 and through the European Union’s Horizon 2020 research and innovation and excel lent science programmes through Marie Skłodowska-Curie grants 687378 (Small Bodies: Near and Far), 682115 (Using the Magellanic Clouds to Understand the Interaction of Galaxies), 695099 (A sub-percent distance scale from bina ries and Cepheids – CepBin), 716155 (Structured ACCRE tion Disks – SACCRED), 745617 (Our Galaxy at full HD – Gal-HD), 895174 (The build-up and fate of self-gravitating systems in the Universe), 951549 (Sub-percent calibration of the extragalactic distance scale in the era of big surveys – UniverScale), 101004214 (Innovative Scientific Data Explo ration and Exploitation Applications for Space Sciences – EXPLORE), 101004719 (OPTICON-RadioNET Pilot), 101055318 (The 3D motion of the Interstellar Medium with ESO and ESA telescopes – ISM-FLOW), and 101063193 (Evolutionary Mechanisms in the Milky waY; the Gaia Data Release 3 revolution – EMMY); – 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 Cooper ating States (PECS) programme through contracts C98090 and 4000106398/12/NL/KML for Hungary, through contract 4000115263/15/NL/IB for Germany, through PROgramme de Développement d’Expériences scientifiques (PRODEX) grants 4000132054 for Hungary and through contract 4000132226/20/ES/CM; – the Academy of Finland through grants 299543, 307157, 325805, 328654, 336546, and 345115 and the Magnus Ehrn rooth Foundation; – the French Centre National d’Études 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), through grant ANR-15-CE31-0012-01 for project ‘Unlock ing the potential of Cepheids as primary distance cali brators’ (UnlockCepheids), through grant ANR-19-CE31-0017 for project ‘Secular evolution of galaxies’ (SEGAL), and through grant ANR-18-CE31-0006 for project ‘Galac tic Dark Matter’ (GaDaMa), the Centre National de la Recherche Scientifique (CNRS) and its SNO Gaia of the Institut des Sciences de l’Univers (INSU), its Programmes Nationaux: Cosmologie et Galaxies (PNCG), Gravitation Références Astronomie Métrologie (PNGRAM), Planétolo gie (PNP), Physique et Chimie du Milieu Interstellaire (PCMI), and Physique Stellaire (PNPS), supported by INSU along with the Institut National de Physique (INP) and the Institut National de Physique nucléaire et de Physique des Particules (IN2P3), and co-funded by CNES; the ‘Action Fédératrice Gaia’ of the Observatoire de Paris, and the Région de Franche-comté; – 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, 50QG1904, 50QG2101, 50QG2102, and 50QG2202, and the Centre for Information Services and High Performance Computing (ZIH) at the Technische Universität Dresden for generous allocations of computer time; – the Hungarian Academy of Sciences through the János Bolyai Research Scholarship (G. Marton and Z. Nagy), the Lendület Programme grants LP2014-17 and LP2018-7 and the Hungarian National Research, Development, and Innovation Office (NKFIH) through grant KKP-137523 (‘SeismoLab’); – the Science Foundation Ireland (SFI) through a Royal Soci ety - SFI University Research Fellowship (M. Fraser); – the Israel Ministry of Science and Technology through grant 3-18143 and the Israel Science Foundation (ISF) through grant 1404/22; – 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 and its addendum 2018-24-HH.1-2022 to the Italian Istituto Nazionale di Astrofisica (INAF), contract 2014-049-R.0/1/2, 2022-14-HH.0 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 Tech nology 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 HAR MONIA grant 2018/30/M/ST9/00311 and DAINA grant 2017/27/L/ST9/03221 and the Ministry of Sci ence and Higher Education (MNiSW) through grant DIR/WK/2018/12; – the Portuguese Fundação para a Ciência e a Tecnologia (FCT) through national funds, grants 2022.06962.PTDC and 2022.03993.PTDC, and work contract DL 57/2016/CP1364/CT0006, grants UIDB/04434/2020 and UIDP/04434/2020 for the Instituto de Astrofísica e Ciências do Espaço (IA), grants UIDB/00408/2020 and UIDP/00408/2020 for LASIGE, and grants UIDB/00099/2020 and UIDP/00099/2020 for the Centro de Astrofísica e Gravitação (CENTRA); – the Slovenian Research Agency through grant P1-0188; – the Spanish Ministry of Economy (MINECO/FEDER, UE), the Spanish Ministry of Science and Innovation (MCIN), the Spanish Ministry of Education, Culture, and Sports, and the Spanish Government through grants BES-2016-078499, BES-2017-083126, BES-C-2017-0085, ESP2016-80079-C2-1-R, FPU16/03827, RTI2018-095076-B-C22, PID2021-122842OB-C22, PDC2021-121059-C22, and TIN2015-65316-P (‘Computación de Altas Prestaciones VII’), the Juan de la Cierva Incorporación Programme (FJCI-2015-2671 and IJC2019-04862-I for F. Anders), the Severo Ochoa Centre of Excellence Programme (SEV2015-0493) and MCIN/AEI/10.13039/501100011033/EU FEDER and Next Generation EU/PRTR (PRTR C17.I1); the European Union through European Regional Development Fund ‘A way of making Europe’ through grants PID2021-122842OB-C21, PID2021-125451NA-I00, CNS2022-13523 and RTI2018-095076-B-C21, the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia ‘María de Maeztu’) through grant 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 For mació (APIF) grant, the Spanish Virtual Observatory project funded by MCIN/AEI/10.13039/501100011033/through grant PID2020-112949GB-I00; the Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC), funded by the Xunta de Galicia through the collaboration agreement to reinforce CIGUS research centers, research consolidation grant ED431B 2021/36 and scholarships from Xunta de Galicia and the EU - ESF ED481A-2019/155 and ED481A 2021/296; the Red Española de Supercomputación (RES) computer resources at MareNostrum, the Barcelona Supercomputing Centre - Centro Nacional de Supercomputación (BSC-CNS) through activities AECT-2017-2-0002, AECT-2017-3-0006, AECT 2018-1-0017, AECT-2018-2-0013, AECT-2018-3-0011, AECT-2019-1-0010, AECT-2019-2-0014, AECT-2019-3-0003, AECT-2020-1-0004, and DATA-2020-1-0010, 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 Fellowships RYC2018-025968-I, RYC2021-031683-I and RYC2021-033762-I, funded by MICIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR and the European Science Foundation (‘Investing in your future’); the Port d’Informació Científica (PIC), through a collaboration between the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) and the Institut de Física d’Altes Energies (IFAE), supported by the call for grants for Scientific and Technical Equipment 2021 of the State Program for Knowledge Generation and Scientific and Technological Strengthening of the R+D+i System, financed by MCIN/AEI/ 10.13039/501100011033 and the EU NextGeneration/PRTR (Hadoop Cluster for the comprehensive management of massive scientific data, reference EQC2021-007479-P); – the Swedish National Space Agency (SNSA/Rymdstyrelsen); – the Swiss State Secretariat for Education, Research, and Innovation through the Swiss Activités Nationales Com plémentaires and the Swiss National Science Founda tion through an Eccellenza Professorial Fellowship (award PCEFP2_194638 for R. Anderson); – 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, Brunel University London, the Open University, the University of Cambridge, the University of Edinburgh, the University of Leicester, the Mullard Space Sci ences Laboratory of University College London, and the United Kingdom Rutherford Appleton Laboratory (RAL): PP/D006503/1, PP/D006511/1, PP/D006546/1, PP/D006570/1, PP/D006791/1, ST/I000852/1, ST/J005045/1, ST/K00056X/1, ST/K000209/1, ST/K000756/1, ST/K000578/1, ST/L002388/1, ST/L006553/1, ST/L006561/1, ST/N000595/1, ST/N000641/1, ST/N000978/1, ST/N001117/1, ST/S000089/1, ST/S000976/1, ST/S000984/1, ST/S001123/1, ST/S001948/1, ST/S001980/1, ST/S002103/1, ST/V000969/1, ST/W002469/1, ST/W002493/1, ST/W002671/1, ST/W002809/1, EP/V520342/1, ST/X00158X/1, ST/X001601/1, ST/X001636/1, ST/X001687/1, ST/X002667/1, ST/X002683/1 and ST/X002969/1. The Gaia project and data processing have made use of: – the Set of Identifications, Measurements, and Bibliog raphy for Astronomical Data (SIMBAD, Wenger et al. 2000), the ‘Aladin sky atlas’ (Bonnarel et al. 2000; Boch & Fernique 2014), and the VizieR catalogue access tool (Ochsenbein et al. 2000), all operated at the Centre de Données astronomiques de Strasbourg (CDS); – the National Aeronautics and Space Administration (NASA) Astrophysics Data System (ADS); – the SPace ENVironment Information System (SPENVIS), initiated by the Space Environment and Effects Section (TEC-EES) of ESA and developed by the Belgian Insti tute for Space Aeronomy (BIRA-IASB) under ESA contract through ESA’s General Support Technologies Programme (GSTP), administered by the BELgian federal Science Pol icy Office (BELSPO); – the software products TOPCAT, STIL, and STILTS (Taylor 2005, 2006); – Matplotlib (Hunter 2007); – IPython (Pérez & Granger 2007); – Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration 2018); – R (R Core Team 2013); – the HEALPix package (Górski et al. 2005, http://healpix.sourceforge.net/); – Vaex (Breddels & Veljanoski 2018); – the HIPPARCOS-2 catalogue (van Leeuwen 2007). The HIPPARCOS and Tycho catalogues were constructed under the responsibility of large scientific teams collaborating with ESA. The Consortia Leaders were Lennart Lindegren (Lund, Sweden: NDAC) and Jean Kovalevsky (Grasse, France: FAST), together responsible for the HIPPARCOS Catalogue; Erik Høg (Copenhagen, Denmark: TDAC) responsible for the Tycho Catalogue; and Catherine Turon (Meudon, France: INCA) responsible for the HIPPARCOS Input Catalogue (HIC); – the Tycho-2 catalogue (Høg et al. 2000), the construction of which was supported by the Velux Foundation of 1981 and the Danish Space Board; – The Tycho double star catalogue (TDSC, Fabricius et al. 2002), based on observations made with the ESA HIPPAR COS astrometry satellite, as supported by the Danish Space Board and the United States Naval Observatory through their double-star programme; – data products from the Two Micron All Sky Survey (2MASS, Skrutskie et al. 2006), which is a joint project of the University of Massachusetts and the Infrared Pro cessing and Analysis Center (IPAC) / California Institute of Technology, funded by the National Aeronautics and Space Administration (NASA) and the National Science Foundation (NSF) of the USA; – the ninth data release of the AAVSO Photometric All-Sky Survey (APASS, Henden et al. 2016), funded by the Robert Martin Ayers Sciences Fund; – the first data release of the Pan-STARRS survey (Chambers et al. 2016; Magnier et al. 2020a; Waters et al. 2020; Magnier et al. 2020c,b; Flewelling et al. 2020). The Pan-STARRS1 Surveys (PS1) and the PS1 public sci ence archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration (NASA) through grant NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation through grant AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation; – the second release of the Guide Star Catalogue (GSC2.3, Lasker et al. 2008). The Guide Star Catalogue II is a joint project of the Space Telescope Science Institute (STScI) and the Osservatorio Astrofisico di Torino (OATo). STScI is operated by the Association of Universities for Research in Astronomy (AURA), for the National Aeronautics and Space Administration (NASA) under contract NAS5-26555. OATo is operated by the Italian National Institute for Astrophysics (INAF). Additional support was provided by the European Southern Observatory (ESO), the Space Telescope European Coordinating Facility (STECF), the International GEMINI project, and the European Space Agency (ESA) Astrophysics Division (nowadays SCI-S); – the eXtended, Large (XL) version of the catalogue of Posi tions and Proper Motions (PPM-XL, Roeser et al. 2010); – data products from the Wide-field Infrared Survey Explorer (WISE), which is a joint project of the University of Cal ifornia, Los Angeles, and the Jet Propulsion Laboratory/-California Institute of Technology, and NEOWISE, which is a project of the Jet Propulsion Laboratory/California Insti tute of Technology. WISE and NEOWISE are funded by the National Aeronautics and Space Administration (NASA); – the first data release of the United States Naval Obser vatory (USNO) Robotic Astrometric Telescope (URAT-1, Zacharias et al. 2015); – the fourth data release of the United States Naval Obser vatory (USNO) CCD Astrograph Catalogue (UCAC-4, Zacharias et al. 2013); – the sixth and final data release of the Radial Velocity Exper iment (RAVE DR6, Steinmetz et al. 2020a,b). Funding for RAVE has been provided by the Leibniz Institute for Astro physics Potsdam (AIP), the Australian Astronomical Obser vatory, the Australian National University, the Australian Research Council, the French National Research Agency, the German Research Foundation (SPP 1177 and SFB 881), the European Research Council (ERC-StG 240271 Galactica), the Istituto Nazionale di Astrofisica at Padova, the Johns Hopkins University, the National Science Foundation of the USA (AST-0908326), the W.M. Keck foundation, the Macquarie University, the Netherlands Research School for Astronomy, the Natural Sciences and Engineering Research Council of Canada, the Slovenian Research Agen

Gaia Early Data Release 3: The celestial reference frame (Gaia-CRF3)

Context. Gaia-CRF3 is the celestial reference frame for positions and proper motions in the third release of data from the Gaia mission, Gaia DR3 (and for the early third release, Gaia EDR3, which contains identical astrometric results). The reference frame is defined by the positions and proper motions at epoch 2016.0 for a specific set of extragalactic sources in the (E)DR3 catalogue. Aims. We describe the construction of Gaia-CRF3 and its properties in terms of the distributions in magnitude, colour, and astrometric quality. Methods. Compact extragalactic sources in Gaia DR3 were identified by positional cross-matching with 17 external catalogues of quasi-stellar objects (QSO) and active galactic nuclei (AGN), followed by astrometric filtering designed to remove stellar contaminants. Selecting a clean sample was favoured over including a higher number of extragalactic sources. For the final sample, the random and systematic errors in the proper motions are analysed, as well as the radio-optical offsets in position for sources in the third realisation of the International Celestial Reference Frame (ICRF3). Results. Gaia-CRF3 comprises about 1.6 million QSO-like sources, of which 1.2 million have five-parameter astrometric solutions in Gaia DR3 and 0.4 million have six-parameter solutions. The sources span the magnitude range G = 13-21 with a peak density at 20.6 mag, at which the typical positional uncertainty is about 1 mas. The proper motions show systematic errors on the level of 12 μas yr-1 on angular scales greater than 15 deg. For the 3142 optical counterparts of ICRF3 sources in the S/X frequency bands, the median offset from the radio positions is about 0.5 mas, but it exceeds 4 mas in either coordinate for 127 sources. We outline the future of Gaia-CRF in the next Gaia data releases. Appendices give further details on the external catalogues used, how to extract information about the Gaia-CRF3 sources, potential (Galactic) confusion sources, and the estimation of the spin and orientation of an astrometric solution

Deep-sequencing reveals broad subtype-specific HCV resistance mutations associated with treatment failure

A percentage of hepatitis C virus (HCV)-infected patients fail direct acting antiviral (DAA)-based treatment regimens, often because of drug resistance-associated substitutions (RAS). The aim of this study was to characterize the resistance profile of a large cohort of patients failing DAA-based treatments, and investigate the relationship between HCV subtype and failure, as an aid to optimizing management of these patients. A new, standardized HCV-RAS testing protocol based on deep sequencing was designed and applied to 220 previously subtyped samples from patients failing DAA treatment, collected in 39 Spanish hospitals. The majority had received DAA-based interferon (IFN) a-free regimens; 79% had failed sofosbuvir-containing therapy. Genomic regions encoding the nonstructural protein (NS) 3, NS5A, and NS5B (DAA target regions) were analyzed using subtype-specific primers. Viral subtype distribution was as follows: genotype (G) 1, 62.7%; G3a, 21.4%; G4d, 12.3%; G2, 1.8%; and mixed infections 1.8%. Overall, 88.6% of patients carried at least 1 RAS, and 19% carried RAS at frequencies below 20% in the mutant spectrum. There were no differences in RAS selection between treatments with and without ribavirin. Regardless of the treatment received, each HCV subtype showed specific types of RAS. Of note, no RAS were detected in the target proteins of 18.6% of patients failing treatment, and 30.4% of patients had RAS in proteins that were not targets of the inhibitors they received. HCV patients failing DAA therapy showed a high diversity of RAS. Ribavirin use did not influence the type or number of RAS at failure. The subtype-specific pattern of RAS emergence underscores the importance of accurate HCV subtyping. The frequency of “extra-target” RAS suggests the need for RAS screening in all three DAA target regions