Resultados totales (Incluyendo duplicados): 33743
Encontrada(s) 3375 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331383
Dataset. 2022

TABLE_2_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX [DATASET]

  • Pedrosa, Leire
  • Foguet, Carles
  • Oliveres, Helena
  • Archilla, Iván
  • García de Herreros, Marta
  • Rodríguez, Adela
  • Postigo, Antonio
  • Benítez-Ribas, Daniel
  • Camps, Jordi
  • Cuatrecasas, Miriam
  • Castells, Antoni
  • Prat, Aleix
  • Thomson, Timothy M.
  • Maurel, Joan
  • Cascante, Marta
Supplementary Table S2: Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of different signatures between IMMETCOLS Clusters., Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331383
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331383
HANDLE: http://hdl.handle.net/10261/331383
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331383
PMID: http://hdl.handle.net/10261/331383
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331383
Ver en: http://hdl.handle.net/10261/331383
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331383

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331384
Dataset. 2023

SPANISH DROUGHT CATALOGUE V1.0.0

  • Trullenque Blanco, Víctor
  • Beguería, Santiago
  • Vicente Serrano, Sergio M.
  • Peña-Angulo, Dhais
  • González Hidalgo, José Carlos
[EN] SPI01 grid: plain text. 5219 rows (excluding the header) and 1261 columns (excluding the X and Y coordinates). SPI12 grid: plain text. 5219 rows (excluding the header) and 1250 columns (excluding the X and Y coordinates). Episode descriptive files: duration and intensity integral maps, SPI01 and SPI12 averages, and spatial propagation maps., [ES] Malla SPI01: texto plano. 5219 filas -descontando el encabezado- y 1261 columnas -descontando las coordenadas X e Y-. Malla SPI12: texto plano. 5219 filas -descontando el encabezado- y 1250 columnas -descontando las coordenadas X e Y-. Archivos descriptivos de los episodios: mapas integrales de duración e intensidad, promedios de SPI’1 y SPI12 y mapas de la propagación espacial., Open Data Commons Attribution (ODC-By 1.0)., [EN] The database consists of two files in .txt format with the precipitation anomaly grids (Standardized Precipitation Index) calculated at 1 and 12 months over the Spanish peninsular domain, covering the period 2015/12_2020/12. These have been calculated from the monthly data of the MOPREDAScentury precipitation grid (https://doi.org/10.20350/digitalCSIC/15136). In addition, a descriptive analysis of the 40 drought episodes identified according to the criteria of drought intensity (SPI12 =< -0.84) and affected area (>20 % of the grid area) is included. For each episode we include the time series of the SPI01 and SPI12 average of the whole grid (expressed in anomalies); the area of the grid under drought conditions (SPI12 =< -0.84) (expressed in percent per one); the integral maps of the episode according to its duration (expressed in number of months) and intensity (average of the cells under drought conditions); and the maps representing the spatial propagation of the episode. This record corresponds to version 1.0.0 of the dataset. The database is distributed under an open license (Open Data Commons Attribution, ODC-By)., [ES] La base de datos consta de dos archivos en formato .txt con las mallas de anomalías de precipitación (Standardized Precipitation Index) calculadas a 1 y 12 meses sobre el dominio peninsular español, cubriendo el periodo 12/2015_12/2020. Estas han sido calculadas a partir de los datos mensuales de la malla de precipitación MOPREDAScentury (https://doi.org/10.20350/digitalCSIC/15136). Además, se incluye un análisis descriptivo de los 40 episodios de sequía identificados según los criterios de intensidad de la sequía (SPI12 =< -0.84) y superficie afectada (>20 % de la superficie de la malla). Para cada episodio se incluyen las series temporales del SPI01 y SPI12 promedio de toda la malla (expresadas en anomalías); el área de la malla en condiciones de sequía (SPI12 =< -0.84) (expresada en tanto por uno); los mapas integrales del episodio atendiendo a su duración (expresada en número de meses) e intensidad (promedio de las celdas en condiciones de sequía); y los mapas que representan la propagación espacial del episodio. Este registro se corresponde con la versión 1.0.0 del conjunto de datos. La base de datos se distribuye bajo una licencia abierta (Open Data Commons Attribution, ODC-By)., Project PID2020-116860RB-C22: Extremos térmicos y pluviométricos en la España peninsular 1916-2020), funded by the Spanish Ministry of Science., Peer reviewed

DOI: http://hdl.handle.net/10261/331384
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331384
HANDLE: http://hdl.handle.net/10261/331384
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331384
PMID: http://hdl.handle.net/10261/331384
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331384
Ver en: http://hdl.handle.net/10261/331384
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331384

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331386
Dataset. 2022

SUPPLEMENTARY MATERIAL: ECOTOXICOLOGICAL TOOLS IN SUPPORT OF THE AIMS OF THE EUROPEAN WATER FRAMEWORK DIRECTIVE: A STEP TOWARDS A MORE HOLISTIC ECOSYSTEM-BASED APPROACH

  • Martínez-Haro, Mónica
  • Acevedo, Pelayo
  • Pais-Costa, Antónia Juliana
  • Neto, João M.
  • Vieira, Luis R.
  • Ospina-Álvarez, Natalia
  • Taggart, Mark A.
  • Guilhermino, Lúcia
  • Ribeiro, Rui
  • Marques, João Carlos
Supplementary data 1: -Sheets: 20 -Tables: 10 -Figures: 1, Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331386
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331386
HANDLE: http://hdl.handle.net/10261/331386
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331386
PMID: http://hdl.handle.net/10261/331386
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331386
Ver en: http://hdl.handle.net/10261/331386
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331386

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331387
Dataset. 2022

TABLE_3_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX [DATASET]

  • Pedrosa, Leire
  • Foguet, Carles
  • Oliveres, Helena
  • Archilla, Iván
  • García de Herreros, Marta
  • Rodríguez, Adela
  • Postigo, Antonio
  • Benítez-Ribas, Daniel
  • Camps, Jordi
  • Cuatrecasas, Miriam
  • Castells, Antoni
  • Prat, Aleix
  • Thomson, Timothy M.
  • Maurel, Joan
  • Cascante, Marta
Supplementary Table S3: Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of metabolic genes in the IMMETCOLS Clusters. (Part 1). Supplementary Table S3: Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of metabolic genes in the IMMETCOLS Clusters. (Part 2), Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331387
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331387
HANDLE: http://hdl.handle.net/10261/331387
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331387
PMID: http://hdl.handle.net/10261/331387
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331387
Ver en: http://hdl.handle.net/10261/331387
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331387

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331388
Dataset. 2022

SUPPLEMENTARY MATERIALS OF THE ARTICLE USE OF THE SENTINEL-2 AND LANDSAT-8 SATELLITES FOR WATER QUALITY MONITORING: AN EARLY-WARNING TOOL IN THE MAR MENOR COASTAL LAGOON

  • Caballero, Isabel
  • Roca Mora, Mar
  • Santos-Echeandía, Juan
  • Bernárdez, Patricia
  • Navarro, Gabriel
9 pages. -- Figure S1: RGB (Red–Green–Blue) composite image on (a) 8, (b) 13, and (c) 18 August 2021 of the Sentinel-2 satellite (10 m spatial resolution). -- Figure S2: Turbidity (FNU) on (a) 3, (b) 8, (c) 13, and (d) 18, August 2021 of the Sentinel-2 satellite (10 m spatial resolution); (e–h) the same for chlorophyll-a concentration (Chl-a, mg/m3). -- Figure S3: Sentinel-2 and Landsat-8 RGB (Red–Green–Blue) composite image acquired on (a) 4 September 2021, (b) 7 September 2021, (c) 11 September 2021, (d) 12 September 2021, (e) 17 September 2021, and (f) 22 September 2021. -- Figure S4: Turbidity (FNU) from Sentinel-2 and Landsat-8 acquired on (a) 4 September 2021, (b) 7 September 2021, (c) 11 September 2021, (d) 12 September 2021, (e) 17 September 2021, and (f) 22 September 2021. -- Figure S5: Chlorophyll-a concentration (Chl-a, mg/m3) from Sentinel-2 and Landsat-8 acquired on (a) 4 September 2021, (b) 7 September 2021, (c) 11 September 2021, (d) 12 September 2021, (e) 17 September 2021, and (f) 22 September 2021. -- Figure S6: RGB (Red–Green–Blue) composite image from Sentinel-2 and Landsat-8 acquired on (a) 11, (b) 12, (c) 21, and (d) 28 March 2021. -- Figure S7: Turbidity (FNU) from Sentinel-2 and Landsat-8 acquired on (a) 11, (b) 12, (c) 21, and (d) 28 March 2021. -- Figure S8: (a) RGB (Red–Green–Blue) composite image, and (b) Turbidity (FNU) from Sentinel-2 on 21 March 2021 corresponding to the southeastern shore of Mar Menor., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331388
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331388
HANDLE: http://hdl.handle.net/10261/331388
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331388
PMID: http://hdl.handle.net/10261/331388
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331388
Ver en: http://hdl.handle.net/10261/331388
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331388

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331393
Dataset. 2022

SUPPLEMENTARY MATERIAL: MAKING THE COMPETITIVE EXCLUSION PRINCIPLE OPERATIONAL AT THE BIOGEOGRAPHICAL SCALE USING FUZZY LOGIC

  • Real, Raimundo
  • Báez, José Carlos
  • Fa, Julia E.
  • Olivero, Jesús
  • Acevedo, Pelayo
Supplementary material 1: Relationship between favorability and probability. Supplementary material 2: Testing the theory with empirical data., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331393
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331393
HANDLE: http://hdl.handle.net/10261/331393
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331393
PMID: http://hdl.handle.net/10261/331393
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331393
Ver en: http://hdl.handle.net/10261/331393
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331393

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331395
Dataset. 2022

APPENDIX A. SUPPLEMENTARY DATA FOR PROTECTING PREY BY DECEIVING PREDATORS: A FIELD EXPERIMENT TESTING CHEMICAL CAMOUFLAGE AND CONDITIONED FOOD AVERSION

  • Selonen, V.
  • Banks, Peter B.
  • Tobajas, Jorge
  • Laaksonen, T.
Supplement Table: All the observed species in wildlife-camera data during spring 2021 in Southern Finland in 18 study sites and 163 cameras., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331395
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331395
HANDLE: http://hdl.handle.net/10261/331395
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331395
PMID: http://hdl.handle.net/10261/331395
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331395
Ver en: http://hdl.handle.net/10261/331395
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331395

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331398
Dataset. 2022

TABLE_4_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX [DATASET]

  • Pedrosa, Leire
  • Foguet, Carles
  • Oliveres, Helena
  • Archilla, Iván
  • García de Herreros, Marta
  • Rodríguez, Adela
  • Postigo, Antonio
  • Benítez-Ribas, Daniel
  • Camps, Jordi
  • Cuatrecasas, Miriam
  • Castells, Antoni
  • Prat, Aleix
  • Thomson, Timothy M.
  • Maurel, Joan
  • Cascante, Marta
Supplementary Table S4: Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of immune signatures in the IMMETCOLS Clusters., Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331398
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331398
HANDLE: http://hdl.handle.net/10261/331398
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331398
PMID: http://hdl.handle.net/10261/331398
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331398
Ver en: http://hdl.handle.net/10261/331398
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331398

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331399
Dataset. 2022

SUPPLEMENTARY DATA OF THE ARTICLE VARIABILITY OF EARLY AUTUMN PLANKTONIC ASSEMBLAGES IN THE STRAIT OF GIBRALTAR: A REGIONALIZATION ANALYSIS

  • Valcárcel, Nerea
  • Ramírez-Romero, Eduardo
  • García, Carlos M.
  • González-Gordillo, J. Ignacio
  • Echevarría, F.
9 pages. -- Table S1: Average values of physical and biogeochemical parameters defining each cluster during spring and neap tides. Mean, N, standard deviation (SD) and range. -- Fig. S1: Average values of physical and biogeochemical variables defining each cluster during spring and neap tides. Purple bars represent CL1, green bars for CL2. -- Fig. S2: Picoplankton groups biomass distribution. Synechococcus (A-B), Prochlorococcus (C-D) and Cryptophytes (E-F) bio-mass (mgC m-3) during spring (A, C, E) and neap tides (B, D, F). -- Fig. S3: Main microplankton groups biomass (mgC m-3) distribution during spring (A, C, E, G) and neap (B, D, F, H) tides. -- Table S2. Main pico and nanoplankton groups cell densities (cell mL-1) and biomass. -- Table S3. Microplankton abundance (cell mL-1) and biomass (mgC m-3)by major groups during neap and spring tides. -- Table S4. Mesoplankton abundance (ind m-3) and biomass (mgC m-3) by major groups during neap and spring tides. -- Table S5. Summary scheme signing main features defining each cluster. -- Table S6. Total abundance of copepods orders (ind m-3). -- Fig. S4: Mean temperature, (A) and N2 (B) profiles averaged for all the stations. The dashed lines represent the 20th and 80th percentiles in both plots., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331399
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331399
HANDLE: http://hdl.handle.net/10261/331399
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331399
PMID: http://hdl.handle.net/10261/331399
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331399
Ver en: http://hdl.handle.net/10261/331399
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331399

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331401
Dataset. 2022

SUPPORTING INFORMATION: RANDOM ENCOUNTER MODEL IS A RELIABLE METHOD FOR ESTIMATING POPULATION DENSITY OF MULTIPLE SPECIES USING CAMERA TRAPS

  • Palencia, Pablo
  • Barroso, Patricia
  • Vicente, Joaquín
  • Hofmeester, Tim R.
  • Ferreres, Javier
  • Acevedo, Pelayo
Appendix S1. Summary of random encounter model published studies. Appendix S2. Study areas and reference methods details. Appendix S3. Assessing improvements in precision., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331401
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331401
HANDLE: http://hdl.handle.net/10261/331401
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331401
PMID: http://hdl.handle.net/10261/331401
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331401
Ver en: http://hdl.handle.net/10261/331401
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331401

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