Resultados totales (Incluyendo duplicados): 45302
Encontrada(s) 4531 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331334
Dataset. 2022

SUPPLEMENTARY MATERIAL FOR GRIFFON VULTURES, LIVESTOCK AND FARMERS: UNRAVELING A COMPLEX SOCIO-ECONOMIC ECOLOGICAL CONFLICT FROM A CONSERVATION PERSPECTIVE

  • Oliva-Vidal, Pilar
  • Hernández-Matías, Antonio
  • García, Diego
  • Colomer, M. Àngels
  • Real, Joan
  • Margalida, Antoni
Appendix S1: Questionnaire used in this study. Farmer's perceptions of vulture attacks on livestock. Appendix S2: Number of farmers who have responded each question and number of responses obtained. Appendix S3. Livestock type and characteristics (percentages) involved in the 616 complaints reported from 2008–2020: cattle (n = 471), horses (n = 92) and sheep/goats (n = 53). Appendix S4: Number of farms for each livestock type managed by the 133 farmers interviewed, and number of farms reporting attacks and characteristics (%) of the livestock involved. Some farmers provided multiple responses regarding the characteristics of the livestock involved in the attacks. Appendix S5: Models (GLMs) determining the number of complaints for vulture attacks on livestock. We present the variables included in the set of models (model description); the number of estimated parameters (K); the Akaike Information Criteria corrected for small sample sizes (AICc); and the Akaike weight (wi) by the models evaluated (32 models; n = 110). Abbreviations relating to variables correspond to: ‘extensive livestock density’ (Ext); ‘distance to nearest landfill site’ (Dland); ‘number of griffon vulture pairs’ (Gpair); ‘griffon vulture abundance’ (Gabun); and ‘distance to nearest supplementary feeding station’ (DSFS). Selected models are shown in bold. Appendix S6: Relative importance of the variables estimated from the Akaike weight of the 32 models evaluated in the analysis of the determinants of the number of complaints for vulture attacks on livestock. Values close to 1 indicate variables that appear in most models and that show the highest likelihood given the data, i.e., those that show the highest Akaike weight values., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331334
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331334
HANDLE: http://hdl.handle.net/10261/331334
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331334
PMID: http://hdl.handle.net/10261/331334
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331334
Ver en: http://hdl.handle.net/10261/331334
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331334

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331335
Dataset. 2022

SUPPLEMENTAL INFORMATION DIFFUSION AND INTERACTION DYNAMICS OF THE CYTOSOLIC PEROXISOMAL IMPORT RECEPTOR PEX5

  • Galiani, Silvia
  • Reglinski, Katharina
  • Carravilla, Pablo
  • Barbotin, Aurélien
  • Urbančič, Iztok
  • Ott, Julia
  • Sehr, Jessica
  • Sezgin, Erdinç
  • Schneider, Falk
  • Waithe, Dominic
  • Hublitz, Philip
  • Schliebs, Wolfgang
  • Erdmann, Ralf
  • Eggeling, Christian
6 pages. -- Supplementary Figure 1: Endogenous PEX5 in WT cell lines had no influence on the diffusion of labelled PEX5L. -- Supplementary Figure 2: Schematic representation of the protein constructs used in this work with their calculated molecular weights. -- Supplementary figure 3: Disordered regions from HsPEX5 and TbPEX5 amino acid sequences were predicted using the prDOS server (http://prdos.hgc.jp)., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331335
HANDLE: http://hdl.handle.net/10261/331335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331335
PMID: http://hdl.handle.net/10261/331335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331335
Ver en: http://hdl.handle.net/10261/331335
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331335

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
Dataset. 2022

SUPPORTING INFORMATION: PERMEABILITY OF ARTIFICIAL BARRIERS (FENCES) FOR WILD BOAR (SUS SCROFA) IN MEDITERRANEAN MIXED LANDSCAPES

  • Laguna, Eduardo
  • Barasona, José A.
  • Carpio, Antonio J.
  • Vicente, Joaquín
  • Acevedo, Pelayo
Table S1. Data for the 21 wild boar monitored by GPS-collars in this study. Table S2. Questionnaire for the characterization of fences, boundaries and perimeters of the estates in the study area. Fig. S1. Main type of fences presents in our study area. Type I (simple [A] or reinforced livestock-type fence [B]), type II (poorly-maintained big game-proof fence), type III (moderately-maintained big game-proof fence) and type IV (well-maintained big game- proof fence). Fig. S2. Fences crosses by wild boar family groups (data from photo-trapping) and some images of holes in fences obtained during the walking tour to quantify the permeability index (number of holes per km of fence). Table S3. Type of fence by main land use in the study area. Each fence (n=189) featured one or two land use. We included: length in m and percentage of type of fence for each of the possible combinations between land use. Table S4. Model selection results from the analysis of the factors influencing wild boar crossing success across fences. The corrected Akaike Information Criterion (AICc) and delta AICc (ΔAICc), i.e. the difference in AICc score relative to the model with the lowest value (most parsimonious model), are showed. As predictors were used: Type of fence (I-IV), Sex (males, females), Period (FSP, Hunting, FAP; see text for details) and their interactions (Sex*Period, Sex*Type and Type*Period). Individual (ID) was considered as a random effect factor. Fig. S3. Average daily activity of the wild boar monitored in this study. The grey band represent the inactivity period which will be excluded for the estimation of the crossing success. Fig. S4. Temporal and seasonal patterns of the interactions between animals and fences. (A) Number of crosses and bounces per month (from 1=January to 12=December). (B) Number of crosses and bounces per period (FSP= food shortage period, Hunting= hunting season, FAP= food abundance period). Appendix 1- Fence Behaviour Analysis., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
HANDLE: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
PMID: http://hdl.handle.net/10261/331340
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331340
Ver en: http://hdl.handle.net/10261/331340
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oai:digital.csic.es:10261/331340

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
Dataset. 2022

DATASHEET_3_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX

  • 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 Figure S3: Heatmap (A) and statistic results (B) studding the expression of genes related with autophagy in IMMETCOLS Clusters. (A) Heatmap representing the average expression of genes related to autophagy in IMMETCOLS Cluster. Gene expression values are range-scaled between -1 and 1. In top the Cluster classification is showed with red, green or blue, for Cluster 1, Cluster 2 and Cluster 3 respectively. The genes of canonical autophagy are in orange circle and the LAP genes are in blue circles. (B) Important features identified by One-way ANOVA and post-hoc analysis (Fisher’s LSD) comparing the expression of genes related to autophagy 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/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
HANDLE: http://hdl.handle.net/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
PMID: http://hdl.handle.net/10261/331351
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331351
Ver en: http://hdl.handle.net/10261/331351
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oai:digital.csic.es:10261/331351

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331352
Dataset. 2022

DATASHEET_4_A NOVEL GENE SIGNATURE UNVEILS THREE DISTINCT IMMUNE-METABOLIC REWIRING PATTERNS CONSERVED ACROSS DIVERSE TUMOR TYPES AND ASSOCIATED WITH OUTCOMES.DOCX

  • 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 Figure S4. Network integration metabolic pathways. Major activated pathways are highlighted in red in cluster 1, green in cluster 2 and in blue in cluster 3, 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/10261/331352
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331352
HANDLE: http://hdl.handle.net/10261/331352
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331352
PMID: http://hdl.handle.net/10261/331352
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331352
Ver en: http://hdl.handle.net/10261/331352
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331352

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331356
Dataset. 2022

SUPPLEMENTARY MATERIAL OF THE ARTICLE MESOSCALE ASSESSMENT OF SEDENTARY COASTAL FISH DENSITY USING VERTICAL UNDERWATER CAMERAS

  • Follana-Berná, Guillermo
  • Arechavala-López, Pablo
  • Ramírez-Romero, Eduardo
  • Koleva, Elka
  • Grau, Amàlia
  • Palmer, Miquel
4 pages. -- PDF file includes supplementary information about the main article. -- 1. Estimating fishing exposure at the sampled sites. -- 2. Detailed results of the statistical analysis. -- Table 1: Effects size for all the explanatory variables considered. -- Table 2: Fish density (fish/km2) at each of the 15 sampling sites, as estimated from the model above., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331356
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331356
HANDLE: http://hdl.handle.net/10261/331356
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331356
PMID: http://hdl.handle.net/10261/331356
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331356
Ver en: http://hdl.handle.net/10261/331356
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331356

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331359
Dataset. 2022

SUPPLEMENTARY MATERIALS FOR CORRELATES WITH VACCINE PROTECTIVE CAPACITY AND COVID-19 DISEASE SYMPTOMS IDENTIFIED BY SERUM PROTEOMICS IN VACCINATED INDIVIDUALS

  • Villar, Margarita
  • Urra, José Miguel
  • Artigas-Jerónimo, Sara
  • Mazuecos, Lorena
  • Contreras, Marinela
  • Vaz Rodrigues, Rita
  • Rodríguez del‐Río, Francisco J.
  • Gortázar, Christian
  • Fuente, José de la
Data File S1. Serum proteomics analysis; Data File S2. Analysis of immunoglobulin proteins underrepresented and overrepresented in infected cohorts when compared to PCR– individuals; Data File S3. Human-autoantibody general survey in PCR– and PCR+ cohorts; Data File S4. Analysis of selected non-immunoglobulin proteins underrepresented and overrepresented in infected cohorts when compared to PCR– individuals., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331359
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331359
HANDLE: http://hdl.handle.net/10261/331359
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331359
PMID: http://hdl.handle.net/10261/331359
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331359
Ver en: http://hdl.handle.net/10261/331359
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331359

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331361
Dataset. 2022

SUPPLEMENTARY MATERIALS FOR DIFFERENTIALLY REPRESENTED PROTEINS IN RESPONSE TO INFECTION WITH MYCOBACTERIUM TUBERCULOSIS IDENTIFIED BY QUANTITATIVE SERUM PROTEOMICS IN ASIAN ELEPHANTS

  • Villar, Margarita
  • Rajbhandari, Rajesh Man
  • Artigas-Jerónimo, Sara
  • Contreras, Marinela
  • Sadaula, Amir
  • Karmacharya, Dibesh
  • Alves, Paulo C.
  • Gortázar, Christian
  • Fuente, José de la
Data S1. Serum proteomics analysis; Data S2. Analysis of immunoglobulin proteins differentially represented in TB+ elephants when compared to TB− animals; Data S3. Gene Ontology (GO) annotations for non-immunoglobulin proteins; Data S4. Most significant pathways identified by Reactome analysis of non-immunoglobulin proteins; Data S5. Protein sequence alignment between M. tuberculosis P9WNK5|ESXB_MYCTU ESAT-6-like protein EsxB and identified mycobacterial proteins with predicted antigen binding regions to immunoglobulin proteins., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331361
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331361
HANDLE: http://hdl.handle.net/10261/331361
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331361
PMID: http://hdl.handle.net/10261/331361
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331361
Ver en: http://hdl.handle.net/10261/331361
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331361

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331363
Dataset. 2022

POSITIONS FOR "FIRST INSIGHTS INTO MIGRATION ROUTES AND NONBREEDING SITES USED BY RED-RUMPED SWALLOWS (CECROPIS DAURICA RUFULA) BREEDING IN THE IBERIAN PENINSULA"

  • Wong, Joanna B.
  • Turon, Francina
  • Fernández-Tizón, Mario
  • Hahn, Steffen
[EN] Using EURING data and geolocation, we describe migration routes and nonbreeding range of Red-rumped Swallows breeding in the Western Palearctic. One bird ringed in southern Spain and recovered in southern Morocco indicates southwestern migration; geolocator data from five birds from central and eastern Iberian Peninsula confirm migration to various nonbreeding sites in sub-Saharan west Africa between Senegal/Mauritania and Ghana. Two swallows showed non-breeding site itinerancy by using more than one nonbreeding site per season. Despite wide ranges in departure for autumn (August- October) and spring migration (February-March), all birds arrived at nonbreeding and breeding sites within ±1-week from each other., [DE] In dieser Studie beschreiben wir Zugrouten und Überwinterungsgebiete westpaläarktischer Rötelschwalben basierend auf EURING- und Geolokations-Daten. Eine Rötelschwalbe, die in Südspanien beringt und im südlichen Marokko wiedergefunden wurde, spricht für einen südwestlichen Zug. Geolokalisation von fünf Vögeln der zentralen und östlichen Iberischen Halbinsel zeigen Überwinterungsorte im sub-Saharischen Westafrika zwischen Senegal/Mauretanien und Ghana. Zwei der getrackten Rötelschwalben nutzten mehrere Überwinterungsplätze pro Saison. Trotz der großen Schwankungsbreite der Abzugszeiten im Herbst (August-Oktober) und im Frühjahr (Februar-März) erreichten die getrackten Vögel ihre Nichtbrut- bzw. Brutplätze innerhalb von 1–2 Wochen., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331363
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331363
HANDLE: http://hdl.handle.net/10261/331363
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331363
PMID: http://hdl.handle.net/10261/331363
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331363
Ver en: http://hdl.handle.net/10261/331363
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331363

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331365
Dataset. 2022

DATA FOR: FROM PATTERN TO PROCESS? DUAL TRAVELLING WAVES, WITH CONTRASTING PROPAGATION SPEEDS, BEST DESCRIBE A SELF-ORGANISED SPATIO-TEMPORAL PATTERN IN POPULATION GROWTH OF A CYCLIC RODENT

  • Roos, Deon
  • Caminero Saldaña, Constantino
  • Elston, David A.
  • Mougeot, François
  • García-Ariza, María Carmen
  • Arroyo, Beatriz
  • Luque-Larena, Juan José
  • Rojo Revilla, Francisco Javier
  • Lambin, Xavier
Transects, up to 99 m in length (dependent on the field's length), were surveyed in linear stable landscape features (field, track or ditch margins) to estimate vole abundance from November 2011 until September 2017. Each transect was divided into 3 m sections (33 in total) and the presence or absence of one or more signs of vole activity (i.e., latrines by burrows, fresh vegetation clippings, and recent burrow excavations) in each section was noted. The proportion of sections with signs of vole presence per transect was then used as the abundance index. The number of surveys carried out at any time varied adaptively with the perceived risk of an outbreak (according to changes in estimated abundance in previous monitoring surveys). The response variable typically used in all models is proportional growth rate (r_{t,i}, where is the abundance index for site at time (Royama 1992; Berryman 2002). A benefit of using r_{t,i}, rather than ln(N_{t,i}), is that any multiplicative effects of site quality are cancelled out, provided they are constant over time. To calculate r_{t,i}, vole abundance indices are required at the same location in successive time periods (i.e., N_{t,i} and N_{t+1,i}). Given that exact transect locations were rarely reused in successive months, and all transect measurements took place throughout the year rather than discrete seasons, the data had to be aggregated to consistent locations and times to allow growth rate to be calculated. As such, transects were temporally aggregated into a respective yearly quarter (e.g., January to March 2014). Transects were spatially aggregated by sequentially selecting an unassigned transect as a reference point for the ith centroid and assigning all unassigned transects within a 5 km radius to the ith centroid, and repeating until all transects had been allocated (see Figure 2 for a summary of the number of transects assigned to each centroid, centroid locations, and time series of growth rate of each centroid). Once complete, the mean Julian day, X and Y UTM (Universal Transverse Mercator) and the mean index was calculated for all transects assigned to each centroid for each time period. Where a centroid had successive values of N_{t,i} and N_{t+1,i} available, the corresponding proportional growth rate was calculated. A constant of 3.03 was added to N_{t,i} to avoid zero entries (3.03 was the lowest non-zero value of N observed). The final dataset consisted of 3,751 observations., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/331365
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331365
HANDLE: http://hdl.handle.net/10261/331365
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331365
PMID: http://hdl.handle.net/10261/331365
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/331365
Ver en: http://hdl.handle.net/10261/331365
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