Resultados totales (Incluyendo duplicados): 44426
Encontrada(s) 4443 página(s)
Encontrada(s) 4443 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286294
Dataset. 2023
DATASET RELATED TO A STUDY TO IDENTIFY GENOMIC REGIONS IN SUSCEPTIBILITY TO SCHISTOSOMA MANSONI INFECTION IN A MURINE BACKCROSS
IDENTIFICATION OF GENOMIC REGIONS IMPLICATED IN SUSCEPTIBILITY TO "SCHISTOSOMA MANSONI" INFECTION IN A MURINE GENETIC MODEL (BACKCROSS)
- Hernández-Goenaga, Juan
- López-Abán, Julio
- Blanco-Gómez, Adrián
- Vicente, Belén
- Burguillo, Francisco J.
- Pérez-Losada, J.
- Muro, Antonio
This dataset was intended to describe schistosomiasis severity in a backcross cohort and to study the genetic linkage analysis with parasitological, pathological and immunological variables., [Description of methods used for collection/generation of data] F1BX mice were infected with 150 ± 5 S. mansoni cercariae each mouse and nine weeks post-infection were euthanized. We considered 20 variables: granulomas; affected liver surface (mm2/cm2); the number of adult male and female worms; eggs per gram of liver and small intestine; eggs in liver and small intestine per female; CD4, CD8, CD45, CD220 in blood or spleen; IgG, IgG1, IgG2a, IgM antibodies. Multivariate models (cluster and principal component analyses and K-means) identified four levels of infection intensity in the cohort. The genetic regions associated with severity were assessed by massive genotyping and genetic linkage analysis using 961 informative SNPs., [Methods for processing the data] Mean and standard error in each variable, Kolmogorov-Smirnov test. ANOVA and Tukey’ test or Student t-test. The Pearson correlation coefficient (r) and Student t-test for the statistical significance. Multivariant models considering sex influence in worm recovery, eggs in the liver and intestine, fecundity, granulomas and the affected liver surface. All the variables were standardized to 0 mean and standard deviation to 1. Cluster analysis, dendrogram, Principal components analysis and conglomerates by k-means were used to generate clusters. Median proportions were performed. SIMFIT statistical package for Windows version 7.3.7 were used
Massive genotyping and geneticlinkage analysis using 961 informative SNPs: The genetic distance based on the recombination frequencies between markers in the F1BX cohort was compared with http://cgd.jax.org/mousemapconverter using maximum-likelihood mapping with HM algorithm. The Haldane function was used with a step size of 2.5 cM and a genotyping error of 0.001. We used the LOD-score to calculate the statistical significance of the linkage of the QTLs found. LOD-score higher than 1.4 suggested linkage. The Ensembl bioinformatics tool (https://www.ensembl.org/index.html) was used to identify syntenic regions between mouse and human., Here we present the dataset used in our study entitled "Identification of genomic regions implicated in susceptibility to Schistosoma mansoni infection in a murine genetic model (backcross)". Thus, we crossed the C57BL/6 mouse strain with the CBA one and then the F1B6CBA females (C57 x CBA) were backcrossed with CBA males generating the F1BX cohort of the study. The study consists of the identification of genetic markers of schistosomiasis. High infection levels and severe liver fibrosis in schistosomiasis appear only in a few highly susceptible infected people. Schistosomiasis could be a complex trait disease and it could be possible to identify genetic markers associated with severity. This study uses a genetically heterogeneous back-cross cohort with genetically unique mice. A backcross (F1BX) mouse cohort was generated after two stages; firstly, we crossed a mouse strain (CBA/2J) susceptible to schistosomiasis with a resistant one (C57BL/6J) to generate the F1B6CBA mice; secondly, the F1BX mice were generated by backcrossing. F1B6CBA female mice with CBA/2J males. F1BX mice were infected with 150 ± 5 S. mansoni cercariae each mouse and nine weeks post-infection were euthanized. We considered 20 variables: granulomas; affected liver surface (mm2/cm2); the number of adult male and female worms; eggs per gram of liver and small intestine; eggs in liver and small intestine per female; CD4, CD8, CD45, CD220 in blood or spleen; IgG, IgG1, IgG2a, IgM antibodies. Multivariate models (cluster and principal component analyses and K-means) identified four levels of infection intensity in the cohort. The genetic regions associated with severity were assessed by massive genotyping and genetic linkage analysis using 961 informative SNPs., The main research project is: Red de Investigación Colaborativa en Enfermedades Tropicales (RICET) Ref.: RD16/0027/0018., Peer reviewed
Proyecto: MINECO//RD16-0027-0018
DOI: http://hdl.handle.net/10261/286294, https://doi.org/10.20350/digitalCSIC/15081
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286294
HANDLE: http://hdl.handle.net/10261/286294, https://doi.org/10.20350/digitalCSIC/15081
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286294
PMID: http://hdl.handle.net/10261/286294, https://doi.org/10.20350/digitalCSIC/15081
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286294
Ver en: http://hdl.handle.net/10261/286294, https://doi.org/10.20350/digitalCSIC/15081
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286294
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286541
Dataset. 2023
M2EX PROJECT. TRACE METAL FATE IN SOIL AFTER APPLICATION OF DIGESTATE ORIGINATING FROM THE ANAEROBIC DIGESTION OF NON-SOURCE-SEPARATED ORGANIC FRACTION OF MUNICIPAL SOLID WASTE [DATASET]
- Baldasso, Veronica
- Bonet-Garcia, Neus
- Sayen, Stéphanie
- Guillon, Emmanuel
- Frunzo, Luigi
- Gomes, Carlos A. R.
- Alves, Maria João
- Castro, Ricardo
- Mucha, Ana Paula
- Almeida, C. Marisa R.
Exploiting metal-microbe applications to expand the circular economy (M2ex) GA no 861088, 1 Excel file, Digestate originating from anaerobic digestion of non-source-separated organic fraction of municipal solid waste (OFMSW) is produced abundantly worldwide and generally discarded in landfills. However, it can be a valuable resource for many bioeconomy strategies as land restoration, only if a consolidated understanding of the contaminants’ presence and behaviour in digestate-amended soil is achieved. This study aimed to investigate the fate of trace metals, namely Zn, Cu, Pb, and Cr found in the digestate, along the soil profile after digestate application on soil, and the influence that other contaminants as pharmaceutical compounds can have on their behaviour in the soil system. For that, a 90-day soil column experiment was conducted using a fine loamy sand soil topped with a layer of digestate-amended soil. Digestate-amended soil had a soil to digestate proportion of 14 to 1 (dry weight). Two experimental conditions were tested: soil amended with digestate, and soil amended with digestate spiked with the antidiabetic drug metformin. Soil samples were taken at 4 depths on days 1, 7, 21, 35 and 90, and total trace metals concentrations and fractionation was determined via atomic absorption spectroscopy. Results showed that Zn, Cu, Pb ad Cr initially present in the digestate were transferred from the digestate-amended soil layer to the underlying soil layer over time, although in low amounts. Nevertheless, no transfer was detected to the deeper soil layers. Trace metals in soil were predominantly in immobile and less bioavailable forms associated with clay and silicate mineral groups, whereas in the digestate-amended soil they were in more bioavailable forms, which could be related also to metals’ migration in the soil layers below. Results also show that the presence of metformin had no influence on trace metal behaviour, giving insight also on possible interactions with other potentially present contaminants as microplastics. The current study showed that OFMSW digestate can be a promising organic nutrient-rich matrix for land restoration even if it may contain high metals’ concentrations because low metal mobility along the soil profile can be expected., This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 861088., Peer reviewed
Proyecto: EC/H2020/861088
DOI: http://hdl.handle.net/10261/286541, https://doi.org/10.20350/digitalCSIC/15082
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286541
HANDLE: http://hdl.handle.net/10261/286541, https://doi.org/10.20350/digitalCSIC/15082
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286541
PMID: http://hdl.handle.net/10261/286541, https://doi.org/10.20350/digitalCSIC/15082
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286541
Ver en: http://hdl.handle.net/10261/286541, https://doi.org/10.20350/digitalCSIC/15082
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286541
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286591
Dataset. 2021
ARTIFICIAL INTELLIGENCE FOR QUALITY CONTROL OF MANUFACTURING OPERATIONS: MACRO-MECHANICAL MILLING IN THE PILOT LINE GAMHE 5.0
- Haber Guerra, Rodolfo E.
- Castaño, Fernando
- Armada, Manuel
- Villalonga, Alberto
Quality is defined as the extent to which a product conforms to the design specifications and how it complies with the requirements of component functionality. For some industries, such as automotive and aeronautical, the quality of their parts is very important given the high requirements to which they are subject. However, difficulties arise from the fact that a measure of quality can only be evaluated ‘‘out-of-process”, resulting in losses because there is no alternative to removing defective parts from the production line. Therefore, it is necessary to apply Artificial Intelligence-based kits/solutions that provide in-process estimation to predict quality from some measured variables.
The main goal of these datasets is to monitor the final quality of the manufactured components or parts by estimating surface roughness from vibration signals and cutting parameters information using Artificial Intelligence-based solutions. Surface roughness is an essential feature in quality control defined by the deviation in the direction of the normal vector of a real surface from its ideal form. Because the roughness measurement is an offline and post process procedure, being able to estimate this value online brings a series of benefits in terms of time and cost reduction in manufacturing lines, energy efficiency, unnecessary wear of tools and machines, etc. Once a part has been detected with a surface quality below what is desired, a series of corrective measures can be applied for the following operations, such as: reducing the feed rate percentage, increasing the percentage of spindle speed or reducing the axial depth per pass, etc., European Commission: KITT4SME - platform-enabled KITs of arTificial intelligence FOR an easy uptake by SMEs (952119)., Peer reviewed
Proyecto: EC/H2020/952119
DOI: http://hdl.handle.net/10261/286591, https://doi.org/10.20350/digitalCSIC/15084
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286591
HANDLE: http://hdl.handle.net/10261/286591, https://doi.org/10.20350/digitalCSIC/15084
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286591
PMID: http://hdl.handle.net/10261/286591, https://doi.org/10.20350/digitalCSIC/15084
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286591
Ver en: http://hdl.handle.net/10261/286591, https://doi.org/10.20350/digitalCSIC/15084
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286591
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286598
Dataset. 2021
_A_SPV10T2ANALYSIS-GCMS.OUTPUT.RAW
ANALYSIS OF SPV1.0 T2 PLANTS
- Moreno Giménez, Elena
- Petek, Marko
Analysis of pheromone content in T2 generation of SPv1.0 plants., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/722361
DOI: http://hdl.handle.net/10261/286598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286598
HANDLE: http://hdl.handle.net/10261/286598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286598
PMID: http://hdl.handle.net/10261/286598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286598
Ver en: http://hdl.handle.net/10261/286598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286598
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286602
Dataset. 2023
LONG-TERM MONITORING IN THE BIOMETRICS OF THE RED-SWAMP CRAYFISH (PROCAMBARUS CLARKII, GIRARD 1852) IN DOÑANA WETLANDS 2004-2022
- Bravo, Miguel A.
- Andreu, Ana C.
- Román, Isidro
- Arribas, Rosa
- Márquez-Ferrando, Rocío
- Díaz-Delgado, Ricardo
- Bustamante, Javier
Dataset are structured following well-established data formats. Three files are provided., The first file (Don_biom_red-swamp-crayfish_ev_20230111) contains the information of each event (eventID, event date, geographical coordinates, sample effort, etc…); the second file (Don_ biom_red-swamp-crayfish _occ_20230111) contains the information of the occurrences of individuals recorded in each station and its taxonomic classification; and the third file (Don_ biom_red-swamp-crayfish _mof_20230111) provide information of biometric variables of individual crayfish recorded (total body length, cephalothorax length, cephalothorax width and weight)., The monitoring of biometric parameters (total body length, cephalothorax length, cephalothorax width and weight) of red-swamp crayfish (Procambarus clarkii) in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the biometry of the species to analyze the evolution in these variables. Data were recorded annually between 2004-2022 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded.
The individuals were sampled at the 64 stations classified according to their location (on either aeolian sands or marshland). Modified commercial traps, similar to funnel traps, with 4 mm mesh size were used as sampling method, following the method by Bravo et. al., 1994. Between 5-9 traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease.
Each individual captured was weigthed using an electronic balance within 0.2 g accuracy. Cephalothorax length (from the tip of the rostrum to the tip of the cephalatorax) and cephalothorax width (maximum width of the cephalothorax) were measured using a slide caliper within 0.1 mm accuracy. Total body length (from the tip of the rostrum to the tip of the telson) were recorded using a ruler within 0.5 mm accuracy. Data recorded during the surveys also included sex and maturation stage (inmature, mature) of the organisms when possible, as well as the time and georreferenced data of the capture. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence.
The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling.
Bravo, M. A.; Duarte, C. M. & Montes, C. (1994) Environmental factors controlling the life history of Procambarus clarkii (Decapoda, Cambaridae) in a temporary marsh of the Doñana National Park (SW Spain). January 1994. Limnology 25(4):2450-2453.
Romaire, R. P. & Lutz, C. G., 1989 Population dynamics of Procambarus clarkii (Girard) and Procambarus acutus acutus (Girard) (Decapoda: Cambaridae) in commercial ponds. Aquaculture 81(3-4):253-274., National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2004)., 1. Don_biom_red-swamp-crayfish_ev_20230111: eventID, intitutionCode, institutionID, datasetName, eventDate, eventTime, continent, country, stateProvince, location, localityID, locality, decimalLatitude, decimalLongitude, habitat, sampleSizeValue, sampleSizeUnit, sampleSizeEffort.
2. Don_ biom_red-swamp-crayfish _occ_20230111: eventID, occurrenceID, occurenceTime, individualCount, basisOfRecord, sex lifestage, kingdom, phylum, class, family, genus, specificEpithet, scientificName, scientificNameAuthorship.
3. Don_ biom_red-swamp-crayfish _mof_20230111: ocurrenceID, measurementID, measurementValue, measurementUnit, measurementType, measurementAccuracy, measurementMethod., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/286602, https://doi.org/10.20350/digitalCSIC/15085
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286602
HANDLE: http://hdl.handle.net/10261/286602, https://doi.org/10.20350/digitalCSIC/15085
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286602
PMID: http://hdl.handle.net/10261/286602, https://doi.org/10.20350/digitalCSIC/15085
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286602
Ver en: http://hdl.handle.net/10261/286602, https://doi.org/10.20350/digitalCSIC/15085
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286602
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286606
Dataset. 2021
_A_ROOTSSXPV10VSV12-GCMS.OUTPUT.RAW
ROOTS VOLATILOME OF SXPV1.0, SXPV1.2 T1 AND WT
- Mateos-Fernández, Rubén
- Petek, Marko
The purpose of this assay is to define the volatilome of SxPv1.0, v1.2 and WT Nicotiana benthamiana plant roots, focusing on the differences between them, by GC-MS., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/72236
DOI: http://hdl.handle.net/10261/286606, https://doi.org/10.20350/digitalCSIC/15086
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286606
HANDLE: http://hdl.handle.net/10261/286606, https://doi.org/10.20350/digitalCSIC/15086
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286606
PMID: http://hdl.handle.net/10261/286606, https://doi.org/10.20350/digitalCSIC/15086
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286606
Ver en: http://hdl.handle.net/10261/286606, https://doi.org/10.20350/digitalCSIC/15086
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286606
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286607
Dataset. 2021
_A_LEAVESSXPV10VSV12-GCMS.OUTPUT.RAW
LEAF VOLATILOME OF SXPV1.0, SXPV1.2 T1 AND WT
- Mateos-Fernández, Rubén
- Petek, Marko
The purpose of this assay is to define the volatilome of SxPv1.0, v1.2 and WT Nicotiana benthamiana plant leaves, focusing on the differences between them, by GC-MS., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/722361
DOI: http://hdl.handle.net/10261/286607
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286607
HANDLE: http://hdl.handle.net/10261/286607
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286607
PMID: http://hdl.handle.net/10261/286607
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286607
Ver en: http://hdl.handle.net/10261/286607
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286607
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286608
Dataset. 2021
_A_SP10T1ANALYSIS-GCMS.OUTPUT.RAW
ANALYSIS OF SPV1.0 T1 PLANTS
- Moreno Giménez, Elena
- Petek, Marko
Analysis of pheromone content in T1 generation of SPv1.0 plants., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/722361
DOI: http://hdl.handle.net/10261/286608
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286608
HANDLE: http://hdl.handle.net/10261/286608
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286608
PMID: http://hdl.handle.net/10261/286608
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286608
Ver en: http://hdl.handle.net/10261/286608
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286608
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286652
Dataset. 2021
_A_SXPV12SCREENINGT2-GCMS.OUTPUT.RAW
SCREENING OF SEX PHEROMONE PRODUCTION IN SEXYPLANT V1.2 T2 TRANSGENIC GENERATION FOR FURTHER RNASEQ ANALYSIS
- Mateos-Fernández, Rubén
- Petek, Marko
The purpose of this study is to screen the population of T2 transgenic generation of SxPv1.2, to analyze the production of moth sex pheromones in these plants and be able to choose from them the most interesting ones in terms of production for further RNASeq analysis., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/722361
DOI: http://hdl.handle.net/10261/286652
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286652
HANDLE: http://hdl.handle.net/10261/286652
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286652
PMID: http://hdl.handle.net/10261/286652
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286652
Ver en: http://hdl.handle.net/10261/286652
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286652
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286653
Dataset. 2021
_A_SPV10EADACTANALYSIS-GCMS.OUTPUT.RAW
TRANSIENT EXPRESSION IN NICOTIANA BENTHAMIANA LEAVES OF THE MOTH PHEROMONE PATHWAY WITH AND WITHOUT EADACT
- Moreno Giménez, Elena
- Petek, Marko
The effect of EaDAct in pheromone production was studied by agroinfiltrating in Nicotiana benthamiana leaves the first two enzymes (AtrD11 and HarFAR) with or without the last enzyme EaDAct. P19 was also agroinfiltrated as negative control., European Commission: ERA CoBioTech - Cofund on Biotechnologies (722361)., Peer reviewed
Proyecto: EC/H2020/722361
DOI: http://hdl.handle.net/10261/286653
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286653
HANDLE: http://hdl.handle.net/10261/286653
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286653
PMID: http://hdl.handle.net/10261/286653
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286653
Ver en: http://hdl.handle.net/10261/286653
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/286653
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