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This Excel file includes the data and tracked calculations of the manuscript entitled "Sponge contribution to the silicon cycle of a diatom-rich shallow bay". It includes 7 spreadsheets with the following contents: - READ ME - Standing STOCK living sponges - Sponge Si consumption FLUX - Si RESERVOIR in sediments - Sponge Si FLUXES in sediments - DIATOM Si fluxes&stocks (Fig.5) - Calculations for discussion, This research was supported by: - the Spanish Ministry grants CTM2015-67221-R and MICIU: #PID2019-108627RB-I00 to Manuel Maldonado - the grant 12735 – AO2020 of the French National research program EC2CO to Jacques Grall - the ISblue project, Interdisciplinary graduate school for the blue planet (ANR-17-EURE-0015), co-funded by a grant from the French government under the program "Investissements d'Avenir", and the “Xunta de Galicia” postdoctoral grant IN606B-2019/002 to María López-Acosta., Peer reviewed

This Excel file includes the metadata of the survey of the predation activity of the nudibranch Doris verrucosa on the sponge Hymeniacidon perlevis, This research was supported by: - the grant 12735 – AO2020 of the French National research program EC2CO - the ISblue project, Interdisciplinary graduate school for the blue planet (ANR-17-EURE-0015), co-funded by a grant from the French government under the program "Investissements d'Avenir", and the “Xunta de Galicia” postdoctoral grant IN606B-2019/002, No

[Description of methods used for collection/generation of data] In both stations a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇T), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Periodically water samplings for dissolved oxygen (DO), pH in total scale at 25 ∘C (pH𝑇25) and total alkalinity (TA) were obtained during the sensor maintenance campaigns. DO and (pH𝑇25) samples were collected in order to validate the data obtained by the sensors. DO concentrations were evaluated with the Winkler method modified by Benson and Krause by potentiometric titration with a Metrohm 808 Titrando with a accuracy of the method of ± 2.9 μmol kg−1μmol kg−1 and with an obtained standard deviation from the sensors data and the water samples collected of ± 5.9 μmol kg−1μmol kg−1. pH𝑇25T25 data was obtained by the spectrophotometric method with a Shimadzu UV-2501 spectrophotometer containing a 25 ∘C-thermostated cells with unpurified m-cresol purple as indicator following the methodology established by Clayton and Byrne by using Certified Reference Material (CRM Batch #176 supplied by Prof. Andrew Dickson, Scripps Institution of Oceanography, La Jolla, CA, USA). The accuracy obtained from the CRM Batch was of ± 0.0051 pH units and the precision of the method of ± 0.0034 pH units. The mean difference between the SAMI-pH and discrete samples was of 0.0017 pH units., Funding for this work was provided by the projects RTI2018-095441-B-C21 (SuMaEco) and, the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government. FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033.This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI WATER:iOS., Peer reviewed

[Description of methods used for collection/generation of data] Data was acquired in both stations using a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Once data (available at https://doi.org/XXX/DigitalCSIC/XXX) was validated, several processing steps were performed to ensure an optimal training process for the neural network models. First, all the data of the time series were re-sampled by averaging the data points obtaining a daily frequency. Afterwards, a standard feature-scaling procedure (min-max normalization) was applied to every feature (temperature, salinity and oxygen) and to pHT. Finally, we built our training and validations sets as tensors with dimensions (batchsize, windowsize, 𝑁features), where batchsize is the number of examples to train per iteration, windowsize is the number of past and future points considered and 𝑁features is the number of features used to predict the target series. Temperature values below 𝑇=12.5T=12.5 °C were discarded as they are considered outliers in sensor data outside the normal range in the study area. A BiDireccional Long Short-Term Memory (BD-LSTM) neural network was selected as the best architecture to reconstruct the pHT time series, with no signs of overfitting and achieving less than 1% error in both training and validation sets. Data corresponding to the Bay of Palma were used in the selection of the best neural network architecture. The code and data used to determine the best neural network architecture can be found in a GitHub repository mentioned in the context information., Funding for this work was provided by the projects RTI2018-095441-B-C21, RTI2018-095441-B-C22 (SuMaEco) and Grant MDM-2017-0711 (María de Maeztu Excellence Unit) funded by MCIN/AEI/10.13039/501100011033 and by the “ERDF A way of making Europe", the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government. FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033.This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI WATER:iOS (https://pti-waterios.csic.es/)., Peer reviewed

[Description of methods used for collection/generation of data] Periodically water sampling for dissolved oxygen (DO) and total alkalinity (TA) was done during the sensor maintenance campaigns of BOATS. In two sites, monthly samples were collected from the same depth as the sensors of the BOATS stations, at 1m at the oceanographic buoy, and 4m in PN Cabrera. Samples were taken for dissolved methane (CH4), dissolved oxygen (DO), total alkalinity (TA), dissolved organic carbon (DOC), Chlorophyll a (Chl a), In both stations monthly discrete samples were collected, at 1 m in the Bay of Palma, Surface for Cap ses Salines and at 4 m depth in Cabrera. Samples were collected by submerging a hose connected to a pump at the sensor height of the BOATS stations in Cabrera and the Bay of Palma. At the third site, the lighthouse of Cap ses Salines, a bucket was used to obtain surface water samples., readme provides background information for xlsx datafiles., Methane (CH4) gas is the most important greenhouse gas (GHG) after carbon dioxide, with open ocean areas acting as discreet CH4 sources and coastal regions as intense but variable CH4 sources to the atmosphere. In this database we report measured CH4 concentrations and calculated air-sea fluxes in three sites of the coastal area of the Balearic Islands Archipelago (Western Mediterranean Basin). CH4 levels and related biogeochemical variables were measured in three coastal sampling sites between 2019 and 2021. CH4 concentrations in seawater ranged from 2.7 to 10.9 nM, without significant differences between the sampling sites. Averaged estimated CH4 fluxes during the sampling period for the three stations oscillated between 0.2 and 9.7 μmol m−2 d−1 following a seasonal pattern and in general all sites behaved as weak CH4 sources throughout the sampling period., Funding for this work was provided by the projects RTI2018-095441-B-C21 (SuMaEco) and, the BBVA Foundation project Posi-COIN and the Balearic Islands Government project SEPPO (PRD2018/18). This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI OCEANS+., Peer reviewed

The GEOVIDE cruise was carried out coast to coast between Portugal and Newfoundland via the south tip of Greenland, following the OVIDE line in the eastern part and crossing the Labrador Sea in the western part. The classical hydrographic rosette was cast 163 times at 78 different geographical positions called stations. While the CTD-O2 probe acquired continuous profiles of the “physical” variables (pressure, temperature, salinity and dissolved oxygen), 22 Niskin bottles were closed at different levels during the upcast to provide samples for biogeochemical analysis. After calibration, we find precisions for pressure, temperature, salinity and dissolved oxygen that fit the GO-SHIP international quality requirements. In parallel, but not simultaneously, a trace-metal rosette (TMR) was cast 53 times, also acquiring profiles of physical variables, and equipped with 24 Go-Flo bottles adapted for the sampling of trace metals. Depending on the number of operations, stations were identified as “Short” (one single CTD cast), “Large” (3 CTD casts), “XLarge” (up to 6) and “Super” (up to 11). All along the track of the ship, current magnitude and direction was measured by Ship Acoustic Doppler Current Profilers, down to 1000m depth. This dataset reports for the water mass proportions (from 0 to 1, i.e., from 0 to 100%) for the classical rosette for the following water masses: East North Atlantic Central Water of 16ºC (ENACW16) and of 12 ºC (ENACW12); Subpolar Mode Water of 8ºC (SPMW8), of 7ºC (SPMW7) and of the Irminger Sea (IrSPMW); Labrador Sea Water (LSW); Subarctic Intermediate Water of 6ºC (SAIW6) and of 4ºC (SAIW4); Mediterranean Water (MW); Iceland–Scotland Overflow Water (ISOW); Denmark Strait Overflow Water (DSOW); Polar Intermediate Water (PIW); and North-East Atlantic Deep Water lower (NEADWL). The dataset also contains the changes in oxygen due to the remineralisation of organic matter (DO2bio; in µmol kg-1)., No

6 files, This dataset consists of the estimated decadal changes in the oceanic content of anthropogenic CO2 (∆Cant) between 1994, 2004 and 2014 as described in detail in Müller et al. (2023, in press, AGU Advances). These estimates have been derived from the GLODAPv2.2021 product (Lauvset et al., 2021) using the eMLR(C*) method developed by Clement & Gruber (2018). The datasets contain in addition to the standard estimate also 10 sensitivity cases, which are intended to assess the robustness of the standard estimates to different changes in the estimation procedure. All estimates are provided on a horizontal grid with 1° x 1° resolution. Two primary files are provided: one containing the full three-dimensional distribution of ∆Cant and one containing the vertically integrated values, i.e., the column inventories, 821003 - Climate-Carbon Interactions in the Coming Century (EC) 821001 - Southern Ocean Carbon and Heat Impact on Climate (EC), Peer reviewed

The trial was conducted in the Pamplona metropolitan area (Navarra, Spain). Patients were enrolled between July 31, 2020 and September 11, 2020 and randomized in a 1:1 ratio to ivermectin (400 mcg/kg) single oral dose or placebo. Assessments on enrollment and at days 4, 7, 14, 21 and 28 post treatment included: general symptoms report, physical examination and adverse events. All patients were asked to complete a daily online diary of symptoms from day 1 to 28 post treatment. On enrollment, as well as on days 7 and 14 blood samples were obtained to assess full blood count, C reactive protein, procalcitonin, ferritin, creatinine phosphokinase, lactic dehydrogenase, troponin T, D dimer, IL-6, and renal function. Viral loads were calculated at enrollment and on days 4, 7, 14 and 21 post treatment based on a nasopharyngeal swab for SARS-CoV-2 PCR (for genes N and E). A semi-quantitative serology for IgG against SARS-CoV-2 was done on samples from all patients on day 21 post-treatment.

The emergence of new SARS-CoV-2 variants and the waning of immunity raise concerns about vaccine effectiveness and protection against COVID-19. While antibody response has been shown to correlate with the risk of infection with the original variant and earlier variants of concern, the effectiveness of antibody-mediated protection against Omicron and the factors associated with protection remain uncertain. We evaluated antibody responseAQ2s to SARS-CoV-2 spike (S) and nucleocapsid (N) antigens from Wuhan and variants of concern by Luminex and their role in preventing breakthrough infections 1 year after a third dose of mRNA vaccination, in a cohort of health care workers followed since the pandemic onset in Spain (N = 393). Data were analyzed in relation to COVID-19 history, demographic factors, comorbidities, vaccine doses, brand, and adverse events. Higher levels of anti-S IgG and IgA to Wuhan, Delta, and Omicron were associated with protection against vaccine breakthroughs (IgG against Omicron S antigen HR, 0.06, 95%CI, 0.26–0.01). Previous SARS-CoV-2 infection was positively associated with antibody levels and protection against breakthroughs, and a longer time since last infection was associated with lower protection. In addition, priming with BNT162b2 followed by mRNA-1273 booster was associated with higher antibody responses than homologous mRNA-1273 vaccination. Data show that IgG and IgA induced by vaccines against the original strain or by hybrid immunization are valid correlates of protection against Omicron BA.1 despite immune escape and support the benefits of heterologous vaccination regimens to enhance antibodies and the prioritization of booster vaccination in individuals without recent infections.

Databases containing raw analytical data obtained in the SEROCOV-1 and SEROCOVAC studies and personal covariates used in the publication Moncunill G, Aguilar R, et al EBioMedicine. 2022 Jan 11;75:103805. doi: 10.1016/j.ebiom.2021.103805. Data correspond to antibody levels to SARS-CoV-2 and four seasonal coronaviruses, and the neutralization capacity of samples from 578 participants recruited from 28 March- 9 April 2020, and the follow-up visits after one, three, six, nine and twelve months. In months 9 and 12, data on vaccination status was collected and some participants had already received the 1st (N=64) or the 2nd doses (N=4). Month 12 follow-up mostly included participants who had a blood sample taken two weeks post 2nd dose. The analytical data is completed with participants' information on occupation, comorbidities, previous COVID19 diagnoses and other sociodemographic characteristics. The code was developed using R version 4.0.3.