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Gridded monthly climate projection dataset underpinning the IPCC AR6 Interactive Atlas for the impact-relevant variables and indices., The IPCC WG1 Interactive Atlas is an online tool that provides interactive visualizations and geospatial data related to the physical scientific basis of climate change. This platform allows users to explore and visualize geographical information interactively and dynamically. It presents data using maps, charts, and other visualizations, enabling users to understand complex information spatially and temporally. The interactive Atlas includes climate data for relevant variables, key climate indicators, and trends, all derived from climate model simulations., The IPCC-WGI AR6 Interactive Atlas dataset comprises monthly gridded data from global (CMIP5, CMIP6) and regional (CORDEX) model projections for the impact-relevant variables and indices featured in the IPCC Interactive Atlas (https://interactive-atlas.ipcc.ch)., Peer reviewed, 2

Samples were collected in the tropical and subtropical Atlantic during the MAFIA cruise (April 2015) on board the BIO Hespérides. Seawater samples were collected at 13 stations (from the Brazilian coast to the Canary Islands), from the surface down to 3500 m, using a General Oceanics oceanographic rosette equipped with 24 l PVC Niskin bottles. Abundance and cell characteristics (high nucleic acid content fraction, cell volume, viability) were based on measurements performed with a FACSCalibur (Becton-Dickinson) flow cytometer. Leucine incorporation rates were estimated with tritiated leucine (Kirchman et al. 1985) using centrifugation and filtration methods (Smith and Azam 1992). The aim of this dataset was to estimate the influence of surface productivity on the standing stock, characteristics and activity (as leucine incorporation) of prokaryotes across the water column, This dataset contains the results of the characterisation of the prokaryotic community by flow cytometry and tritiated leucine incorporation from the MAFIA cruise (Migrants and Active Flux In the Atlantic ocean), Horizon 2020 (H2020), grant/award no. 817806: Sustainable management of mesopelagic resources; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2012-39587-C04: Migrants and Active Flux In the Atlantic Ocean; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2015-69392-C3: Constraining organic carbon fluxes in an eastern boundary upwelling ecosystem (NW Africa): the role of non-sinking carbon in the context of the biological pump; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2017-83362-R: INTERES: Papel de las interacciones fitoplancton-bacterias en la respuesta del plancton microbiano a la entrada de nutrientes alóctonos; Ministerio de Ciencia e Innovación (MICINN), grant/award no. PID2019-109084RB-C21: Biogeochemical impact of mesoscale and sub-mesoscale processes along the life history of cyclonic and anticyclonic eddies: plankton variability and productivity, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), No

Data acquisition: Satellite: ESA SMOS mission (Soil Moisture and Ocean Salinity). Filenames: BEC_SSS___SMOS__SO__L3__B_YYYYMMDDT120000_25km__9d_REP_v100.nc YYYYMMDD: central date BEC ftp service: We serve netCDF data by means of a secure ftp server. NetCDF files from which the maps were made (and other additional data) can be downloaded from sftp address becftp.icm.csic.es at port 27500. If your browser is sftp compatible you can browse directly from sftp://becftp.icm.csic.es:27500 address. In order to download data you should be registered in our BEC ftp service. Registration is free, you can register just by filling the following form: http://bec.icm.csic.es/bec-ftp-service-registration/ If you need a dedicated ftp client (for instance FileZilla https://filezilla-project.org/) you should use the following configuration: Host: sftp://becftp.icm.csic.es Username: your username. Password: your password. Port: 27500, Dedicated regional Sea Surface Salinity (SSS) product in the Southern Ocean. Level 3 9-day maps. Data acquisition: Satellite ESA SMOS mission (Soil Moisture and Ocean Salinity). Time coverage 01 February 2011 - 31 December 2022. Time resolution: 9-day. Maps frequency generation: Daily. Spatial coverage: Latitude range: 30ºS-90ºS Longitude range: 180ºW-180ºE. Spatial resolution: 25 km (EASE-SL grid). Sensor Satellite SMOS / MIRAS. Format NetCDF. Climate and Forecast (CF) conventions version: 1.6, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

The study of a species' thermal tolerance and vital rate responses provides useful metrics to characterize its vulnerability to ocean warming. Under prolonged thermal stress, plastic and adaptive processes can adjust the physiology of organisms. Yet it is uncertain whether the species can expand their upper thermal limits to cope with rapid and extreme changes in environmental temperature. In this study, we reared the marine copepod Paracartia grani at control (19°C) and warmer conditions (25°C) for >18 generations and assessed their survival and fecundity under short-term exposure to a range of temperatures (11-34°C). After multigenerational warming, the upper tolerance to acute exposure (24 hours) increased by 1-1.3°C, although this enhancement decreased to 0.3-0.8°C after longer thermal stress (7 days). Warm-reared copepods were smaller and produced significantly fewer offspring at the optimum temperature. No shift in the thermal breadth of the reproductive response was observed. Yet the fecundity rates of the warm-reared copepods in the upper thermal range were up to 21-fold higher than the control. Our results show that chronic warming improved tolerance to stress temperatures and fecundity of P. grani, therefore enhancing its chances to persist under extreme heat events, This research was funded by Grants CTM2017-84288-R and PID2020-118645RB-I00 by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. “ERDF A way of making Europe” C. J. was supported by Grant [PRE2018-084738] funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Rearing temperature, generation, exposure temperature, survival 24h, survival 7d, egg production rate, fitness index, egg diameter, female prosome length, Peer reviewed

This form consists of five parts: METADATA (L10-L20), COMMON DATA (L24-L40), LOCATION CODES (L42-L52), TREATMENT LEGEND (L54-L58) AND SAMPLE DATA (L61-). The formulae used in this sheet are based on Keuskamp et al. 2013 (http://onlinelibrary.wiley.com/enhanced/doi/10.1111/2041-210X.12097/). For more information please refer to the manual included with this file. Please fill out the data in the purple cells, and optionally in the blue cells and send form to tbiteam@decolab.org or upload it on www.teatime4science.org, Coordinador del proyecto: Johann G. Zaller de BOKU., [EN] This data set was collected in 16 vineyards belonging to the DO Montilla-Moriles to determine the decomposition rate of plant material through the tea bag index (TBI) with different soil cover management (bare soil and cover crop)., [ES] Este conjunto de datos se recogió en 16 viñedos pertenecientes a la DO Montilla-Moriles para determinar la tasa de descomposición del material vegetal a través del índice de la bolsa de té (TBI) con diferentes manejos de la cobertura del suelo (suelo desnudo y cubierta vegetal)., Convocatoria del vinedivers fue la BiodivERsA/ FACCE-JPI 2013-2014., Peer reviewed

S1. Experimental Section: S1.1. Synthesis and Characterization Data. S1.2. Fluorescence Measurements. S1.3. Zeta Potential Measurements. S1.4. Dynamic Light Scattering Measurements. S1.5. Circular Dichroism Spectra. S1.6. Agarose Gel Electrophoresis. S1.7. Atomic Force Microscopy (AFM). S1.8. In Vitro Assays S1.9. Transfection Assays. S1.10. Chlamydomonas reinhardtii Nuclear Transformation. S2. Results and Discussion: S2.1. Characterization of Monomers and Polyurethanes. S2.2. Formation of the polyplexes PUMan/ctDNA. Figures: Fig. S1. FTIR spectra of PUMan and (MBocCis)DTDI. Fig. S2. SEC chromatogram of (MAL)DTDI. Fig. S3. SEC chromatogram of (MBocCis)DTDI. Fig. S4. SEC chromatogram of PUMan. Fig. S5. 1H NMR of (MAL)DTDI. Fig. S6. 1H NMR of (MBocCis)DTDI. Fig. S7. 1H NMR of PUMan. Fig. S8. TGA curve of PUMan. Fig. S9. Plot of EB emission intensities at different N/P values, circular dichroism spectra, zeta potential and hydrodynamic diameters of the PUMan-based polyplexes. Fig.S10. Electrophoresis of polyplexes PUMan/digested pEGFP-C1 and PUMan/digested Phyco69 at different N/P ratios. Fig.S11. Percentage of GFP positive cells after transfection with 3 μg of the plasmid pEGFP-C1 with the indicated reagents. The molar ratio PUMan:FuGENE and PUMan:DOPE was 1:1. Tables: Table S1. Thermal properties of PUMan and its precursors., Peer reviewed

[Description of methods used for collection/generation of data] Los talasónimos fueron recopilados de diversas fuentes. Hemos utilizado visores en línea como los catálogos de la OHI y el IGME (https://www.ngdc.noaa.gov/iho/; http://info.igme.es/visor/), así como publicaciones científicas de recopilaciones de nombres de lugares marinos. Los datos batimétricos se descargaron del geoportal EMODnet y los límites de demarcación marina se obtuvieron del sitio web del Ministerio de Transición Ecológica y Reto Demográfico de España., [ES] Esta base de datos es una recopilación de los talasónimos en las subdivisiones marinas españolas (Atlántico Norte, Atlántico Sur, Estrecho y Alborán, Levantino-Balear y Canarias). Mediante la identificación sistemática de estas características en las subdivisiones, se llevó a cabo una extensa investigación bibliográfica y de bases de datos para asignar nombres de lugar adecuados a cada elemento. Se han reconocido diez tipos principales de talasónimos geográficos, personales, descripciones de forma, conmemorativos, culturales, nombres de pescadores, nombres de embarcaciones y expediciones, otros y desconocidos. Los nombres más comunes son ubicaciones geográficas, seguidos de nombres de personalidades históricas. Esta nueva base de datos está abierta a modificaciones y nuevos nombres que podrían agregarse en el futuro. Igualmente, si se detecta algún error se puede enviar a los autores para su corrección., [EN] This database is a compilation of thalassonyms or submarine toponyms within the Spanish marine subdivisions (North Atlantic, South Atlantic, Strait of Gibraltar and Alboran, Levantine-Balearic, and Canary Islands). Through the systematic identification of these features within the subdivisions, extensive bibliographic and database research was conducted to assign appropriate place names to each element. Ten main types of thalassonyms have been identified: geographical, personal, shape descriptions, commemorative, cultural, fishermen’s names, vessel and expedition names, others, and unknown. The most common names are geographical locations, followed by historical figures’ names. This new database is open to modifications, and new names may be added in the future. Likewise, if any errors are detected, they can be submitted to the authors for correction., Proyecto Estrategías Marinas Españolas (EsMarEs). https://www.miteco.gob.es/es/costas/temas/proteccion-medio-marino/estrategias-marinas/default.aspx). Más específicamente este trabajo corresponde a la acción C12A2 del proyecto ESMARES, Caracterización de la naturaleza y composición del fondo marino de las demarcaciones marinas españolas y la generación de capas de información para su mejor gestión., Peer reviewed

Herein a versatile and scalable method to prepare periodically corrugated nanophosphor surface patterns displaying strongly polarized and directional visible light emission is demonstrated. A combination of inkjet printing and soft lithography techniques is employed to obtain arbitrarily shaped light emitting motifs. Such predesigned luminescent drawings, in which the polarization and angular properties of the emitted light are determined and finely tuned through the surface relief, can be used as anti-counterfeiting labels, as these two specific optical features provide additional means to identify any unauthorized or forged copy of the protected item. The potential of this approach is exemplified by processing a self-standing photoluminescent quick response (QR) code whose emission is both polarized and directionally beamed. Physical insight of the mechanism behind the directional out-coupled photoluminescence observed is provided by finitedifference time-domain calculations., This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (NANOPHOM, grant agreement no. 715832) and from the Spanish Ministry of Science and Innovation under grant PID2020-116593RB-I00, funded by MCIN/AEI/10.13039/501100011033, and of the Junta de Andalucía under grant P18-RT-2291 (FEDER/UE). E. C. O. acknowledges the grant FPU19/00346 funded by MCIN/AEI/10.13039/501100011033 and ESF Investing in your Future. M. R. thanks CSIC for funding through a JAE Intro ICU scholarship (JAEICU-21-ICMS-21). This work has been partially supported by the European Union and the State of Upper Austria within the strategic program Innovative Upper Austria 2020 and #upperVision2030, project: WI2020-578813/4 “DigiManu (Extended 2021), Peer reviewed

Sample processing: Peripheral blood was collected into sodium heparin tubes and centrifuged for 10 min at 8 2500 rpm at room temperature (RT) to separate the cellular fraction from the plasma. The plasma was removed from the cell pellet and stored at -80 ºC for posterior use. The cell pellet was diluted 1:1 in RPMI 1640 medium and carefully added to Histopaque-1077 (Sigma) for peripheral blood mononuclear cell (PBMC) isolation by centrifugation at 2500 rpm at RT for 10 min. PBMC layer was collected, washed with RPMI 1640, counted and aliquoted for staining and flow cytometry analysis. All flow cytometry analyses were performed using fresh PBMCs. Flow cytometry: For the surface staining, PMBCs were resuspended in 50 μl PBS with 5 % FCS and stained with the different antibody cocktails for 20 min at 4 ºC in dark, washed twice with PBS + 5 % FCS and then fixed for 30 min at 4 ºC in the dark using 2% PFA. Following surface staining, cells that required intracellular staining were fixed/permeabilized for 30 min at 4 ºC in the dark using the FoxP3 transcription factor buffer kit (Miltenyi). Following fixation/permeabilization, cells were washed twice with permeabilization buffer, resuspended in 50 μl permeabilization buffer and stained with intracellular antibodies for 30 min at 4 ºC in the dark. Samples were washed twice with permeabilization buffer following staining and fixed. All samples were acquired on a Gallios (Beckman Coulter) Flow Cytometer. The list of the antibodies used for immune cell phenotyping was: Miltenyi Biotec, CD14-VioBlue (130-110-524), CD16-FITC (130-25 113-392), CD25-APC (130-113-280), CD3-VioGreen (130-113-134), CD38-FITC (130-113-426), Treg detection kit CD4/CD25/CD127 (130-096-082), CD56-PerCP Vio700 (130-100-681), CD57-27 APC-Vio770 (130-111-813), CD8-PerCP Vio700 (130-110-682), FoxP3 Staining Buffer Set(130-28 093-142), GzmB-PE (130-116-486), HLADR-APC-VIO770 (130-111-792), LAG3-APC (130-105-29 453), NKG2A-PE-VIO615 (130-120-035), NKG2C-PE (130-103-635), NKP46-APC (130-092-609), TIM3-PE vio770 (130-121-334); Biolegend, NKp30-PE/Cy7 (325214), PD1-Alexa Fluor700 31 (329952), CD45-Brilliant Violet 421 (304032); BD, NKG2D-BV421 (743558). High dimensional flow cytometry data analysis: viSNE and FlowSOM (Self-organizing map) analyses were performed using Cytobank (https://cytobank.org). We used t-distributed stochastic neighbouring embedding (t-SNE) to reduce the dimensionality of the cell marker datasets generated using the antibody panels indicated above. FlowSOM clustering analysis compared expression of cell markers was used to identify each cluster and perform an unbiased analysis of the PBMC immunophenotyping data. CD56+ cells, CD56+ or CD14+ cells and CD3+CD8+ cells from FACS panels 2, 3 and 4 respectively, were analysed separately. SOM was generated using equal sampling of at least 1000 cells from each FCS file and hierarchical consensus clustering by the following markers: CD3, CD16, CD57, NKp30, NKp46, NKG2C, NKG2D and NKG2A for panel 2 analysis; CD14, CD3, HLA-DR, CD16, GZMB, TIM3, LAG3, PD1 or CD56,CD3, HLA-DR, CD16, GZMB, TIM3, LAG3, PD1 for panel 3 analysis and GzmB, CD38, HLA-DR, TIM3, LAG3, PD1 for panel 3 analysis. For each SOM, 100 clusters and 5, 8 or 10 metaclusters (MTs) were identified for panel 2, panel 3 and 4, which were represented in Minimum Spanning Trees (MTS). Multiplex plasma protein analyses: Luminex assay was run according to manufacturer’s instructions in 100 μl of plasma, using a custom human cytokine panel (RD Systems, catalogue no. LXSAHM). The next proteins were included: IFNα, IFNβ, IFN, IL28A/IFNλ2, IL28B/IFNλ3, IL2, IL1β,IL18/IL1F4,IL1RA,IL33, IL36b/IL1F8, IL7, IL10, IL31, IL6, IL12/IL23 p40, IL15, IL17E/IL25, IL8/CXCL8, CXCL10/IP10, CCL2/MCP1, CCL8/MCP2, CXCL9/MIG, CXCL2/MIP2α, MICA, MICB, ULBP-1, ULBP-2/5/6, ULBP-52 3, TNFα, GzmA and GzmB. Supernatants were mixed with beads coated with capture antibodies and incubated on a 96 well filter plate for 2 hours. Beads were washed and incubated with biotin-labelled detection antibodies for 1 hour, followed by a final incubation with streptavidin-PE. Assay plates were measured using a Luminex 200 instrument (ThermoFisher, catalogue no. APX10031). Data acquisition and analysis were performed using xPONENT software. The standard curve for each analyte had a five-parameter R2 value > 0.95 with or without minor fitting using xPONENT software. Granzyme activity assay in serum: Serum samples were used to evaluate the activity of both GzmA and GzmB using specific quenching FRET fluorescent substrates (FAM-VANRSAS-DABCYL and FAM-IEPDNLV-DABCYL peptides, respectively). In a nutshell, 40 μl of 100 mM Tris-HCl pH 8.5 or 100 mM Tris-HCl 50 mM NaCl pH 7.8 (buffers for GzmA or GzmB respectively) were added to flat bottom, black plates, with 10 μl of the serum samples. 50 μl of GzmA or GzmB substrates were added and the fluorescence of the plate was read at time zero and 1 h for GzmA and 24 h for GzmB using 475 nm excitation and 520 nm emission wavelenghts. Gzm activity was calculated based on a calibration curve with known concentrations of carboxyfluorescein. Statistics: To minimize inter-experimental variability and batch effects between patients, all PBMC samples were acquired, processed, and freshly analysed during four consecutive weeks from April to June 2020. Serum and plasma samples were frozen at -80ºC and later on all of them were thawed and analysed at the same time. Univariate and multivariate logistic regression models were developed using two different groups of variables, representing soluble and immunomodulatory factors (Group 1) or cell populations (Group 2) shown in Table S5. Age, sex and lymphocyte counts were included in all groups except for the comparison between HD and COVID19, since these variables were not known in HDs. First, a univariate logistic regression analysis was performed in the corresponding groups. Variables included in the multivariate discriminant analysis were those with a value of p < 0.1 in the univariate logistic regression analysis and / or with a value of p < 0.1 in the medians comparison tests. The univariate statistic test used has been chi-square or Fisher exact test for qualitative variant comparison and Mann-Whitney (comparison of two groups of variables) or Kruskal-Wallis (comparison of more than two groups of variables) for quantitative variant comparison. The post-test used was Benjamini, Krieger and Yekutieli test. Variable normality has been analysed with Kolmogorov-Smirnov test and Rho’s Spearman has been calculated as correlation coefficients. Statistical models were developed to predict COVID19 of diagnostic and severity. A multivariate logistic regression and discriminant analyses were performed to develop predictive models. Area Under the Curve (AUC), OR and CI95% values were reported for significant variables. Nagelkerke R2 was calculated to analyse sample variability and Hosmer-Lemeshow test was performed to analyse goodness of fit for the logistic regression model. Hosmer-Lemeshow p values higher than 0.05 indicate an adequate calibration of the predictive model. The statistics software used was GraphPad Software 7.0, (Inc. San Diego, CA) and SPSS 26.0 (IBM Corp., Armonk, NY).-- This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions., Supplementary materials and methods: sample processing, flow cytometry, high dimensional flow cytometry data analysis, multiplex plasma protein analyses, granzyme activity assay in serum, statistics. Supplementary figure legends (1-5). Supplementary table legends (1-7)., The authors would like to thank the Biobank of the Aragon Health System integrated in the Spanish National Biobanks Network and the Servicios Científico Técnicos de Citometria de Flujo del CIBA for their collaboration. Work in the JP laboratory is funded by the FEDER (Fondo Europeo de Desarrollo Regional, Gobierno de Aragón, Group B29_17R), Health National Institute Carlos III (COV20-00308), Aragón Government (Fondo COVID-19), Fundación Santander-Universidad de Zaragoza (Programa COVID-19), Agencia Estatal de Investigación (SAF2017-83120-C2-1-R; PID2020-113963RBI00), Fundación Inocente, ASPANOA and Carrera de la Mujer de Monzón. EMG is funded by Agencia Estatal de Investigación (SAF2017-83120-C2-1-R and PID2020-113963RB-I00). IUM and SH are supported by a PhD fellowship from Aragon Government, CP by a PhD fellowship from AECC, LS by a PhD fellowship (FPI) from the Ministry of Science, Innovation and Universities. DDM is supported by a postdoctoral fellowship 'Sara Borrell', and MA is supported by a postdoctoral fellowship 'Juan de la Cierva-incorporacion' from the Ministry of Science, Innovation and Universities. EM and BGT are supported by Rio Hortega contract. JP is supported by the ARAID Foundation., Peer reviewed

3 pages. -- Figure S1: Cyclic Voltammetry results of PW12 in water. -- Figure S2: UV-vis spectroscopy signal of reduced and oxidized states of the POM. -- Figure S3: Photography of the reaction mixtures resultant from the synthesis of POM-Ag0 NPs. -- Figure S4: STEM image and size distribution of POM-Ag0 NPs synthesized using PW125−. -- Figure S5: Variation of specific capacitance of bare AC and AC/POM-Ag0 NPs symmetric cells with scan rate; Equation (S1): Calculation of the capacitance. References [55,67] are cited in the Supplementary Materials., Peer reviewed