Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.EEA Santa CruzFil: Poyatos, Rafael. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Poyatos, Rafael. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Joint Research Unit CREAF-CTFC. Bellaterra; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Adams, Mark A. Swinburne University of Technology. Faculty of Science Engineering and Technology; Australia.Fil: Adams, Mark A. University of Sydney. School of Life and Environmental Sciences; Australia.Fil: Adorján, Balázs. University of Debrecen. Faculty of Science and Technology. Department of Botany; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Aidar, Marcos P. M. Institute of Botany. Plant Physiology and Biochemistry; BrasilFil: Allen, Scott. University of Nevada. Department of Natural Resources and Environmental Science; Estados UnidosFil: Alvarado-Barrientos, M. Susana. Instituto de Ecología A.C. Red Ecología Funcional; México.Fil: Anderson-Teixeira, Kristina J. Center for Tropical Forest Science-Forest Global Earth Observatory, Smithsonian Tropical Research Institute; PanamáFil: Anderson-Teixeira, Kristina J. Conservation Ecology Center. Smithsonian Conservation Biology Institute; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Martínez-Vilalta, Jordi. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Martínez-Vilalta, Jordi. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); Españ

Malignant astrocyte swelling and impaired glutamate clearance drive the expansion of injurious spreading depolarization foci

Spreading depolarizations (SDs) indicate injury progression and predict worse clinical outcome in acute brain injury. We demonstrate in rodents that acute brain swelling upon cerebral ischemia impairs astroglial glutamate clearance and increases the tissue area invaded by SD. The cytotoxic extracellular glutamate accumulation (>15 mu M) predisposes an extensive bulk of tissue (4-5 mm(2)) for a yet undescribed simultaneous depolarization (SiD). We confirm in rat brain slices exposed to osmotic stress that SiD is the pathological expansion of prior punctual SD foci (0.5-1 mm(2)), is associated with astrocyte swelling, and triggers oncotic neuron death. The blockade of astrocytic aquaporin-4 channels and Na+/K+/Cl- co-transporters, or volume-regulated anion channels mitigated slice edema, extracellular glutamate accumulation (<10 mu M) and SiD occurrence. Reversal of slice swelling by hyperosmotic mannitol counteracted glutamate accumulation and prevented SiD. In contrast, inhibition of glial metabolism or inhibition of astrocyte glutamate transporters reproduced the SiD phenotype. Finally, we show in the rodent water intoxication model of cytotoxic edema that astrocyte swelling and altered astrocyte calcium waves are central in the evolution of SiD. We discuss our results in the light of evidence for SiD in the human cortex. Our results emphasize the need of preventive osmotherapy in acute brain injury

Development of a large-scale pathogen screening test for the biosafety evaluation of canine mesenchymal stem cells

Background The action of mesenchymal stem cells (MSCs) is the subject of intense research in the field of regenerative medicine, including their potential use in companion animals, such as dogs. To ensure the safety of canine MSC batches for their application in regenerative medicine, a quality control test must be conducted in accordance with Good Manufacturing Practices (GMP). Based on guidance provided by the European Medicines Agency, this study aimed to develop and validate a highly sensitive and robust, nucleic acid-based test panel for the detection of various canine pathogens. Analytical sensitivity, specificity, amplification efficiency, and linearity were evaluated to ensure robust assessment. Additionally, viable spike-in controls were used to control for optimal nucleic acid extraction. The conventional PCR-based and real-time PCR-based pathogen assays were evaluated in a real-life setting, by direct testing MSC batches. Results The established nucleic acid-based assays displayed remarkable sensitivity, detecting 100–1 copies/reaction of template DNA. They also exhibited high specificity and efficiency. Moreover, highly effective nucleic acid isolation was confirmed by the sensitive detection of spike-in controls. The detection capacity of our optimized and validated methods was determined by direct pathogen testing of nine MSC batches that displayed unusual phenotypes, such as reduced cell division or other deviating characteristics. Among these MCS batches of uncertain purity, only one tested negative for all pathogens. The direct testing of these samples yielded positive results for important canine pathogens, including tick-borne disease-associated species and viral members of the canine infectious respiratory disease complex (CIRDC). Notably, samples positive for the etiological agents responsible for enteritis (CPV), leptospirosis (Leptospira interrogans), and neosporosis (Neospora caninum) were also identified. Furthermore, we conducted biosafety evaluation of 12 MSC batches intended for therapeutic application. Eleven MSC batches were found to be free of extraneous agents, and only one tested positive for a specific pathogen, namely, canine parvovirus. Conclusion In this study, we established and validated reliable, highly sensitive, and accurate nucleic acid-based testing methods for a broad spectrum of canine pathogens

Description of two cultivated and two uncultivated new Salinibacter species, one named following the rules of the bacteriological code: Salinibacter grassmerensis sp. nov.; and three named following the rules of the SeqCode: Salinibacter pepae sp. nov., Salinibacter abyssi sp. nov., and Salinibacter pampae sp. nov.

Current -omics methods allow the collection of a large amount of information that helps in describing the microbial diversity in nature. Here, and as a result of a culturomic approach that rendered the collection of thousands of isolates from 5 different hypersaline sites (in Spain, USA and New Zealand), we obtained 21 strains that represent two new Salinibacter species. For these species we propose the names Salinibacter pepae sp. nov. and Salinibacter grassmerensis sp. nov. (showing average nucleotide identity (ANI) values < 95.09% and 87.08% with Sal. ruber M31T, respectively). Metabolomics revealed species-specific discriminative profiles. Sal. ruber strains were distinguished by a higher percentage of polyunsaturated fatty acids and specific N-functionalized fatty acids; and Sal. altiplanensis was distinguished by an increased number of glycosylated molecules. Based on sequence characteristics and inferred phenotype of metagenome-assembled genomes (MAGs), we describe two new members of the genus Salinibacter. These species dominated in different sites and always coexisted with Sal. ruber and Sal. pepae. Based on the MAGs from three Argentinian lakes in the Pampa region of Argentina and the MAG of the Romanian lake Fără Fund, we describe the species Salinibacter pampae sp. nov. and Salinibacter abyssi sp. nov. respectively (showing ANI values 90.94% and 91.48% with Sal. ruber M31T, respectively). Sal. grassmerensis sp. nov. name was formed according to the rules of the International Code for Nomenclature of Prokaryotes (ICNP), and Sal. pepae, Sal. pampae sp. nov. and Sal. abyssi sp. nov. are proposed following the rules of the newly published Code of Nomenclature of Prokaryotes Described from Sequence Data (SeqCode). This work constitutes an example on how classification under ICNP and SeqCode can coexist, and how the official naming a cultivated organism for which the deposit in public repositories is difficult finds an intermediate solution.This study was funded by the Spanish Ministry of Science, Innovation and Universities projects PGC2018-096956-B-C41, RTC-2017-6405-1 and PID2021-126114NB-C42, which were also supported by the European Regional Development Fund (FEDER). RRM acknowledges the financial support of the sabbatical stay at Georgia Tech and HelmholzZentrum München by the grants PRX18/00048 and PRX21/00043 respectively also from the Spanish Ministry of Science, Innovation and Universities. This research was carried out within the framework of the activities of the Spanish Government through the “Maria de Maeztu Centre of Excellence” accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198). KTK’s research was supported, in part, by the U.S. National Science Foundation (Award No. 1831582 and No. 2129823). IMG. AC and HLB were financially supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI, project number PN-III-P4-ID-PCE-2020-1559, within PNCDI III. HLB acknowledges Ocna Sibiului City Hall (Sibiu County, Romania) for granting the access to Fără Fund Lake and A. Baricz and D.F. Bogdan for technical support during sampling and sample preparation. MBS thanks Dominion Salt for their assistance in sample Lake Grassmere. MELL acknowledges the financial support of the Argentinian National Scientific and Technical Research Council (Grant CONICET-NSFC 2017 N° IF-2018-10102222-APN-GDCT-CONICET) and the National Geographic Society (Grant # NGS 357R-18). BPH was supported by NASA (award 80NSSC18M0027). TV acknowledges the “Margarita Salas” postdoctoral grant, funded by the Spanish Ministry of Universities, within the framework of Recovery, Transformation and Resilience Plan, and funded by the European Union (NextGenerationEU), with the participation of the University of Balearic Islands (UIB)

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land?atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets,while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes.Fil: Poyatos, Rafael. Universitat Autònoma de Barcelona; EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Adams, Mark A.. Swinburne University of Technology; Australia. University of Sydney; AustraliaFil: Adorján, Balázs. University of Debrecen; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona; EspañaFil: Aidar, Marcos P. M.. Institute of Botany; BrasilFil: Allen, Scott. University of Nevada; Estados UnidosFil: Alvarado Barrientos, M. Susana. Instituto de Ecología A.C.; MéxicoFil: Anderson Teixeira, Kristina J.. Smithsonian Tropical Research Institute; PanamáFil: Aparecido, Luiza Maria. Arizona State University; Estados Unidos. Texas A&M University; Estados UnidosFil: Arain, M. Altaf. McMaster University; CanadáFil: Aranda, Ismael. National Institute for Agricultural and Food Research and Technology; EspañaFil: Asbjornsen, Heidi. University of New Hampshire; Estados UnidosFil: Robert Baxter. Durham University; Reino UnidoFil: Beamesderfer, Eric. McMaster University; Canadá. Northern Arizona University; Estados UnidosFil: Carter Berry, Z.. Chapman University; Estados UnidosFil: Berveiller, Daniel. Université Paris Saclay; Francia. Centre National de la Recherche Scientifique; FranciaFil: Blakely, Bethany. University of Illinois at Urbana-Champaign; Estados UnidosFil: Boggs, Johnny. United States Forest Service; Estados UnidosFil: Gil Bohrer. Ohio State University; Estados UnidosFil: Bolstad, Paul V.. University of Minnesota; Estados UnidosFil: Bonal, Damien. Université de Lorraine; FranciaFil: Bracho, Rosvel. University of Florida; Estados UnidosFil: Brito, Patricia. Universidad de La Laguna; EspañaFil: Brodeur, Jason. McMaster University; CanadáFil: Casanoves, Fernando. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Chave, Jérôme. Université Paul Sabatier; FranciaFil: Chen, Hui. Xiamen University; ChinaFil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentin

Global transpiration data from sap flow measurements: The SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.This research was supported by the Minis-terio de Economía y Competitividad (grant no. CGL2014-55883-JIN), the Ministerio de Ciencia e Innovación (grant no. RTI2018-095297-J-I00), the Ministerio de Ciencia e Innovación (grant no. CAS16/00207), the Agència de Gestió d’Ajuts Universitaris i de Recerca (grant no. SGR1001), the Alexander von Humboldt-Stiftung (Humboldt Research Fellowship for Experienced Researchers (RP)), and the Institució Catalana de Recerca i Estudis Avançats (Academia Award (JMV)). Víctor Flo was supported by the doctoral fellowship FPU15/03939 (MECD, Spain)

Global transpiration data from sap flow measurements : the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr" R package - designed to access, visualize, and process SAPFLUXNET data - is available from CRAN.Peer reviewe