BUSCADOR RECOLECTA

Data supporting the findings of the study "Constrained trait variation by water availability modulates radial growth in two coexisting Mediterranean oaks", Peer reviewed

29 figures, 7 tables., 1. Stability of the G−N4−TM structures.-- 2. O2 Interaction with the Fe–N4 Center.-- 3. Calculation methods of evaluating ORR, OER and HER activity.-- 4. Density of states calculations.-- Supplementary Figures and Tables, Peer reviewed

Additional structural (XRD and STEM) and chemical x-ray microanalysis, a detailed description of the STEM image analysis and calculation of polarization images, including the LSAT substrate, and further details on the experimental conditions are provided in the supplementary material., Peer reviewed

pdf file contains: Table S1. Parameter values of the model fitted to empirical glucocorticoid data from the Jimeno et al. (2018; Zebra finch), Zimmer et al. (2021; House sparrow), and Zimmer et al. (2023; Tree swallow)., Glucocorticoid hormones (GCs) modulate acute ‘stress’ responses in vertebrates, exerting their actions across many physiological systems to help the organism face and overcome challenges. These actions take place via binding to the glucocorticoid receptor (GR), which determines not only the magnitude of the GC-mediated physiological response but also the negative feedback that downregulates GCs to restore homeostasis. Although GR function is assumed to determine GC regulation capacity, the associations between GR abundance and individuals' coping abilities remain cryptic. We developed a dynamic model fitted to empirical data to predict the effects of GR abundance on both plasma GC response patterns and the magnitude of GC-mediated physiological response. Individuals with higher GRs showed lower GC exposure, stronger physiological responses and greater capacity to adjust this response to stressor intensity, which may be translated into more resilient and flexible GC phenotypes. Our results also show that among-individual variability in GR abundance challenges the detectability of the association between plasma GC measurements and physiological responses. Our approach provides mechanistic insights into the role of GR on plasma GC measurements and function, which point at GR abundance fundamentally driving complex features of the GC regulation system in the face of environmental change.This article is part of the theme issue ‘Endocrine responses to environmental variation: conceptual approaches and recent developments’., Peer reviewed

Geochemical data of the Variscan gneisses derived from pre-Variscan intrusives and late-Variscan granitoids in the Pyrenees and the Catalan Coastal Ranges were obtained from two main sources: (1) individually mined from published articles and unpublished PhD theses (Autran et al., 1970; Guitard, 1970; Enrique, 1989; Soler and Enrique, 1989; Enrique, 1990; Soler, 1990; Gleizes, 1992; Debon et al., 1996; Arranz, 1997; Guitard et al., 1998b, 1998b; Roberts et al., 2000; Vilà et al., 2005; Casas et al., 2010; Navidad et al., 2010; Druguet et al., 2014; Laumonier et al., 2015; Navidad et al., 2018; Lemirre et al., 2019; Álvaro et al., 2021; Liesa et al., 2021; Casas et al., 2024), and (2) the GEOROC Database (Geochemistry of Rocks of the Oceans and Continents, Göttingen University, https://georoc.eu/; last access: 03/2024; Lehnert et al., 2000). Other Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al., 2016) databases were searched using geographic and lithogeochemical constrains, yielding no results. The mined data were curated and classified based on the analysed rock types, ages, regional tectonic setting, and mode of occurrence in outcrop, resulting in more than 600 entries that are associated with up to 66 data fields. Associated with each entry are generic, descriptive and informative fields (Sample ID, Unit/Massif, Rock category, Rock details, Outcrop description, and References), major element oxide abundances (SiO2, Al2O3, FeOT, Fe2O3T, MnO, MgO, CaO, Na2O, K2O, TiO2, P2O5, and LOI), and trace element concentrations (Ag, As, Ba, Be, Bi, Co, Cr, Cs, Cu, Ga, Ge, Hf, In, Mo, Nb, Ni, Pb, Rb, Sb, Sc, Sn, Sr, Ta, Th, Tl, U, V, W, Y, Zn, Zr, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu). The resulting database, named NEIGRA (North-East Iberian GRAnitoids), represents the first Open-Access compilation of granite and orthogneiss geochemical data in the Pyrenees and the Catalan Coastal Ranges., This work was funded by DGICYT Projects PID2021-122467NB-C22 and PID2021-125585NB-I00 (MCIN/AEI/FEDER-UE/10.13039/501100011033) and PID2020-118999GB-I00 (MCIN/AEI/10.13039/501100011033), and by the Sedimentary Geology Research Group (2021 SGR 00349). EGE acknowledges the funding provided by the Geological Society of London (GSL) Student Research Grants and the PhD grants funded by Generalitat de Catalunya and the European Social Fund (2021 FI_B 00165 and 2022 FI_B1 00043). CPT acknowledges the PhD grant 2021 FISDU 00347 funded by Generalitat de Catalunya. EGR acknowledges funding provided by the Spanish Ministry of Science, Innovation and Universities (“Ramón y Cajal” fellowship RYC2018-026335-I). CA is grateful to the GEOXis Reseach Group (2021 SGR 00262) and the projects PID2020-117332GB-C21 (USAL) and PID2020-117332GB-C22 (UCM) funded by MCIN/AEI/10.13039/501100011033., 00_NEIGRA_Readme; NEIGRA_North-East Iberian GRAnitoids Database, Peer reviewed

File 1 (.doc): 1Table - Mean (±SD) δ13C and δ15N values (‰) of the prey species used to analyze the diet of the common bottlenose dolphin in Madeiran waters, per season; 1 figure - Simulated mixing region calculated for each season (‘summer/autumn’- top; ‘winter/spring’- bottom) with the most likely prey (white crosses) based on bi-plot interpretation.-- File 2 (.xls), Supplementary material of the article Trophic ecology of common bottlenose dolphins in a pelagic insular environment inferred by stable isotopes, https://doi.org/10.1007/s10750-023-05294-4, Peer reviewed

This repository may be useful for further studies, for the development of new therapeutic treatments for food intoxication and for tracking microbial sources in foodstuffs, Biogenic amine-producing bacteria are responsible for the production of basic nitrogenous compounds, such as histamine, cadaverine, tyramine and putrescine, after foods spoil due to microorganisms. In the present work, we applied a shotgun proteomics approach to quickly and easily characterize 15 different foodborne strains of biogenic amine-producing bacteria. A total of 10673 peptide spectrum matches (PSMs) belonging to 4081 nonredundant peptides and corresponding to 1811 annotated proteins were identified. With the results, relevant functional pathways were determined and the strains were differentiated into different Euclidean hierarchical clusters. Moreover, a predicted protein‒protein interaction network of biogenic amine foodborne strains was created. The whole confidence network contains 260 nodes and 1973 interactions. Most of the identified proteins were related to pathways and networks of energy, putrescine metabolism and host‒virus interaction. In addition, a total of 556 nonredundant peptides were identified as virulence factors, and most of these peptides corresponded to functions such as toxins, antimicrobial compound production, antimicrobial resistance, additional resistances and tolerances, host colonization and immune evasion, ABC transporters, phage proteins, and alternative virulence factors and proteins involved in horizontal transfer. Potential species-specific peptide biomarkers were screened. Thus, 77 species-specific peptide biomarkers belonging to 64 different proteins were proposed to identify 10 species (Enterobacter aerogenes, Enterobacter cloacae, Hafnia alvei, Klebsiella oxytoca, Morganella morganii, Proteus mirabilis, Proteus penneri, Proteus vulgaris, Raoutella planticola, Stenotrophomonas maltophilia). All of these results constitute the first major dataset of peptides and proteins of seafood biogenic amine-producing strains, Peer reviewed

This dataset contains all data used in the analysis for the associated manuscript, as well as an R script which can be used to replicate the analysis.-- There are six files, including multispecies stable isotope data, cod sampling data, cod specific stable isotope data, cod meta data, cod positions and an R script for analysis, Foraging is a behavioural process and, therefore, individual behaviour and diet are theorized to covary. However, few comparisons of individual behaviour type and diet exist in the wild. We tested whether behaviour type and diet covary in a protected population of Atlantic cod, Gadus morhua. Working in a no-take marine reserve, we could collect data on natural behavioural variation and diet choice with minimal anthropogenic disturbance. We inferred behaviour using acoustic telemetry and diet from stable isotope compositions (expressed as δ13C and δ15N values). We further investigated whether behaviour and diet could have survival costs. We found cod with shorter diel vertical migration distances fed at higher trophic levels. Cod δ13C and δ15N values scaled positively with body size. Neither behaviour nor diet predicted survival, indicating phenotypic diversity is maintained without survival costs for cod in a protected ecosystem. The links between diet and diel vertical migration highlight that future work is needed to understand whether the shifts in this behaviour during environmental change (e.g. fishing or climate), could lead to trophic cascades, The Research Council of Norway, Award: CODSIZE 294926; Natural Sciences and Engineering Research Council; European Commission, Award: 793627; Spanish National Research Council, IF_ERC; Academy of Finland, Award: 317495; European Research Council, Award: 770884, file: cod_stable_isotopes.rdata; description: Cod specific stable isotopes data in the .rdata format.-- file: TVE2011Effort.csv; description: Sampling effort and locations in the Tvedestrand fjord.-- file: SI.rdata; description: stable isotope samples collected throughout the Tvedestrand foodweb.-- file: telem.rdata; description: Data collected during each cod sampling event, including recaptures.-- file: Allcodpositions.rdata; description: dataset "pos" contains a list of all cod positions used in the stable isotope anaylsis, Peer reviewed

26 pages, 11 figures, 8 tables.-- This work is distributed under the Creative Commons Attribution 4.0 License, The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments, Nico Lange has been funded by EU Horizon 2020 through the EuroSea action (grant no. 862626). Siv K. Lauvset has received internal strategic funding from NORCE Climate. Are Olsen, Nico Lange, and Siv K. Lauvset have received funding from the EU Horizon Europe project OceanICU (grant no. 101083922). Leticia Cotrim da Cunha has been supported by the Prociencia 2022–2024 grant from Universidade do Estado do Rio de Janeiro (UERJ, Brazil) and the PQ2 309708/2021-4 grant from the National Council for Scientific and Technological Development (CNPq, Brazil). Marta Álvarez has been supported by an Instituto Español de Oceanografía (IEO) RADPROF project. Peter J. Brown has received partial funding from the UK Climate Linked Atlantic Sector Science (CLASS) NERC National Capability Long-term Single Centre Science Programme (grant no. NE/R015953/1). Anton Velo and Fiz F. Perez have been supported by the BOCATS2 (grant no. PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and the Horizon Europe project EuroGO-SHIP (grant no. 101094690). Brendan R. Carter has received funding from the Global Ocean Monitoring and Observing (GOMO) program of the National Oceanic and Atmospheric Administration (NOAA) through contributions (project no. 100007298) via the Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CIOCES) under a NOAA Cooperative Agreement (grant no. NA20OAR4320271; contribution no. 2022–2012). Mario Hoppema has received funding from the EU Horizon 2020 Action SO-CHIC (grant no. 821001). Adam Ulfsbo has been supported by the Swedish Research Council Formas (grant no. 2018-01398). Jens Daniel Müller has received support from the European Union's Horizion 2020 research and innovation program for project 4C (grant no. 821003). Alex Kozyr has been supported by NOAA (grant no. NA19NES4320002; Cooperative Institute for Satellite Earth System Studies – CISESS) at the University of Maryland/ESSIC. Ryan J. Woosley has been supported by NSF grants (grant nos. OCE-1923312 and OCE-2148468). Masao Ishii has been supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan (grant no. JPMEERF21S20810). GLODAP also acknowledges funding from the Initiative and Networking Fund of the Helmholtz Association through the project “Digital Earth” (grant no. ZT-0025), Peer reviewed

Soft tissue defects or pathologies frequently necessitate the use of biomaterials that provide the volume required for subsequent vascularization and tissue formation as autrografts are not always a feasible alternative. Supramolecular hydrogels represent promising candidates because of their 3D structure, which resembles the native extracellular matrix, and their capacity to entrap and sustain living cells. Guanosine-based hydrogels have emerged as prime candidates in recent years since the nucleoside self-assembles into well-ordered structures like G-quadruplexes by coordinating K+ ions and π–π stacking, ultimately forming an extensive nanofibrillar network. However, such compositions were frequently inappropriate for 3D printing due to material spreading and low shape stability over time. Thus, the present work aimed to develop a binary cell-laden hydrogel capable of ensuring cell survival while providing enough stability to ensure scaffold biointegration during soft tissue reconstruction. For that purpose, a binary hydrogel made of guanosine and guanosine 5'-monophosphate was optimized, rat mesenchymal stem cells were entrapped, and the composition was bioprinted. To further increase stability, the printed structure was coated with hyperbranched polyethylenimine. Scanning electron microscopic studies demonstrated an extensive nanofibrillar network, indicating excellent G-quadruplex formation, and rheological analysis confirmed good printing and thixotropic qualities. Additionally, diffusion tests using fluorescein isothiocyanate labeled-dextran (70, 500, and 2000 kDa) showed that nutrients of various molecular weights may diffuse through the hydrogel scaffold. Finally, cells were evenly distributed throughout the printed scaffold, cell survival was 85% after 21 days, and lipid droplet formation was observed after 7 days under adipogenic conditions, indicating successful differentiation and proper cell functioning. To conclude, such hydrogels may enable the 3D bioprinting of customized scaffolds perfectly matching the respective soft tissue defect, thereby potentially improving the outcome of the tissue reconstruction intervention., Peer reviewed