BUSCADOR RECOLECTA

One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2005 to January 2006 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components., Peer reviewed

One meter integrated depth surface velocity fields for the Mediterranean Sea calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components., Peer reviewed

One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2007 to June 2018 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components., Peer reviewed

The FastQ files generated for each of the samples have been submitted to the NCBI repository (https://www.ncbi.nlm.nih.gov/bioproject, accessed on 18 April 2022) under accession ID PRJNA824049., Long-read sequencing (Oxford Nanopore Technologies) analysis of the transcriptomics responses of chestnut microshoots to a root induction treatment comprising auxin and wounding. Two types of microshoots were used: BS shoots present a juvenile-character and root after the treatment, while CR shoots behave as mature and do not root. The analysis allows for the comparison of the different responses to the same treatment of plants at different maturation stages., Peer reviewed

Supplementary research data from the poster titled “Unraveling the digestive behavior of flatbreads: impact of formulations and baking process” presented at the 17th ICC International Cereal and Bread Congress in Nantes, France, 2024., PRIMA program under grant agreement No. 2031, project Flat Bread of Mediterranean area: INnovation & Emerging process & technology (Flat Bread Mine)., Peer reviewed

[Description of methods used for collection/generation of data] The database provides discrete measurements of carbon system parameters in water samples collected at 13 stations during 5 campaigns conducted over 2020–2021. Geographic coordinates of sampling stations are provided. Some physical data (i.e. pressure, temperature and salinity) are also included. During the campaigns, temperature, salinity, conductivity, dissolved oxygen and pH were obtained with an EXO TM 2 multiparametric probe sonde. Surface seawater was subsequently collected for biogeochemical analysis. The biogeochemical variables shown in the database are pH in SWS and NBS scale (pH_SWS and pH_NBS), total alkalinity (AT), and inorganic nutrients (nitrite, nitrate, ammonium, silicate and phosphate), Dissolved Organic Carbon (DOC), Suspended Solid Matter (SSM), and chlorophyll a (Chla). · pH_NBS data were obtained by the EXO TM 2 multiparametric probe sonde and pH_SWS was measured with a Metrohm pH meter (model 780) at SWS scale that was calibrated according to DelValls & Dickson, (1998). · Samples for AT analysis were collected in 500-ml borosilicate bottles, and poisoned with 200 μl of HgCl2-saturated aqueous solution and stored until measurement in the laboratory. AT was measured by potential titration according to Mintrop et al. (2000) with a Titroprocessor (model Metrohm 794 for 2020 and model Metrothm 888 for 2021). · Water samples (5 mL, two replicates) for inorganic nutrients determination were taken, filtered immediately (Whatman GF/F, 0.7 μm) and stored frozen for later analyses in the shore-based laboratory. Nutrients concentrations were measured with a continuous flow auto-analyzer using standard colorimetric techniques (Hansen & Koroleff 1999). · Water samples for DOC and total dissolved nitrogen (TDN) determination were taken, filtered immediately (Whatman GF/F, 0.7 μm) and 100 μl of orthophosphoric acid (3:1) was added. Stored in fridge for later analyses in the laboratory. DOC and TDN concentrations were obtained by catalytic oxidation at high temperature (720°C) and chemiluminescence, respectively, applying the protocol described by Alvarez-Salgado & Miller, (1998). · SSM and the organic (particulate organic matter (POM) and inorganic (particulate inorganic matter (PIM)) fractions were determined by the loss on ignition method, filtering the water through pre-weighed Whatman 0.7 μm GF/F glass fibre filters pre-combusted at 450°C, with subsequent filter desiccation for 48 h and finally combustion. · Chla concentration was obtained by filtering water through Whatman 0.7 μm GF/F glass fibre filters that were maintained frozen and in the dark until analysis. The extract was measured by fluorometry following the method of Welschmeyer (1994)., This work was supported by the European Commission, [Fondo Europeo de Desarrollo Regional (FEDER)] through the project Apoio à gestão das zonas húmidas do litoral do Sudoeste Ibérico: interações entre Aquacultura e meio Ambiente na região transfronteiriça Alentejo-Algarve-Andaluzia 2 (AQUA&AMBI2) [ref: 0750_AQUA_AMBI_2_5_P]. SAV and AR were supported by a pre-doctoral grant from the Spanish Ministry of Science, Innovation and Universities [FPU19/04338 and FPU19/04557]. This work is a contribution to the CSIC Interdisciplinary Thematic Platform OCEANS+., Peer reviewed

Peer reviewed

General information, experimental details (no uncommon hazards are noted), and NMR, IR, and UV–vis spectra and structural analysis of complexes 2–5., Peer reviewed

Supplementary Tables: Table S1. Data imported from BPS for each patient: code and definition of the variable.-- Table S2: Log Hazard ratios obtained for the drugs tested, along with standard deviations (SDs), upper and lower coefficient intervals (CI), nominal and FDR-adjusted p-values. Also, Lymphocyte proliferation values (see Methods) along with standard deviations (SDs), upper and lower coefficient intervals (CI), nominal and FDR-adjusted p-values. The two last columns indicate the drugs used in the machine learning drug repurposing prediction study and the proteins targeted by the drug. Targets marked with an * were those analyzed in the machine learning drug repurposing., [Purpose] Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19., [Methods] Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020., [Results] Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality., [Conclusions] In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively., This research was funded by Spanish Ministry of Science and Innovation (grant PID2020-117979RB-I00), the Instituto de Salud Carlos III (ISCIII), co-funded with European Regional Development Funds (ERDF) (grant IMP/00019), and has also been funded by Consejería de Salud y Consumo, Junta de Andalucía (grants COVID-0012-2020, PS-2020-342 and IE19_259 FPS) and the postdoctoral contract of Carlos Loucera (PAIDI2020- DOC_00350) co-funded by the European Social Fund (FSE) 2014–2020., Peer reviewed

Raw data for the above-mentioned article that can be found in https://onlinelibrary.wiley.com/doi/abs/10.1002/adsc.202301040, Peer reviewed