Resultados totales (Incluyendo duplicados): 33862
Encontrada(s) 3387 página(s)
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/189950
Dataset. 2022

PROTEIN-FUNCTIONALIZED MICROGEL FOR MULTIPLE MYELOMA CELLS’ 3D CULTURE

  • Marín Pallá, Juan Carlos
  • Clara Trujillo, Sandra
  • Cordón, Lourdes
  • Gallego Ferrer, Gloria|||0000-0002-2428-0903
  • Sempere, Amparo
  • Gómez Ribelles, José Luís|||0000-0001-9099-0885
Multiple myeloma is a hematologic neoplasm caused by an uncontrolled clonal proliferation of neoplastic plasma cells (nPCs) in the bone marrow. The development and survival of this disease is tightly related to the bone marrow environment. Proliferation and viability of nPCs depend on their interaction with the stromal cells and the extracellular matrix components, which also influences the appearance of drug resistance. Recapitulating these interactions in an in vitro culture requires 3D environments that incorporate the biomolecules of interest. In this work, we studied the proliferation and viability of three multiple myeloma cell lines in a microgel consisting of biostable microspheres with fibronectin (FN) on their surfaces. We also showed that the interaction of the RPMI8226 cell line with FN induced cell arrest in the G0/G1 cell cycle phase. RPMI8226 cells developed a significant resistance to dexamethasone, which was reduced when they were treated with dexamethasone and bortezomib in combination., CIBER-BBN is an initiative funded by the VI National R&D&I Plan 2008–2011, Iniciativa Ingenio 2010, and Consolider Program. CIBER Actions were financed by the Instituto de Salud Carlos III, with assistance from the European Regional Development Fund. The kind supplying of RPMI 8226 cells by Beatriz Martin (Josep Carreras Leukaemia Research Institute) is greatly acknowledged. The Microscopy Service of the UPV (Universitat Politècnica de València) is gratefully acknowledged.

DOI: Dataset/10251/189950" target="_blank">http://hdl.handle.net/10251/189950, https://dx.doi.org/10.4995/Dataset/10251/189950
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/189950
HANDLE: Dataset/10251/189950" target="_blank">http://hdl.handle.net/10251/189950, https://dx.doi.org/10.4995/Dataset/10251/189950
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/189950
PMID: Dataset/10251/189950" target="_blank">http://hdl.handle.net/10251/189950, https://dx.doi.org/10.4995/Dataset/10251/189950
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/189950
Ver en: Dataset/10251/189950" target="_blank">http://hdl.handle.net/10251/189950, https://dx.doi.org/10.4995/Dataset/10251/189950
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/189950

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/190519
Dataset. 2022

DATOS MUSEOS MARÍTIMOS ESPAÑA

  • Márquez Escamilla, Andrea
  • Cervelló Royo, Roberto Elías|||0000-0002-8304-4177
  • Herrera Racionero, Paloma|||0000-0002-3750-622X
  • Miret Pastor, Luis Gaspar|||0000-0002-9644-0021
Base de datos de los museos marítimos españoles con datos sobre fondos recibidos, This research was funded by SPANISH ECONOMY AND COMPETITIVENESS MINISTRY, grant number PID2019-105497 GB-I00, European Fisheries Funds, opportunities for the fisheries sector through diversification, and the FLAGs management (DivPesc).

DOI: Dataset/10251/190519" target="_blank">http://hdl.handle.net/10251/190519, https://dx.doi.org/10.4995/Dataset/10251/190519
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/190519
HANDLE: Dataset/10251/190519" target="_blank">http://hdl.handle.net/10251/190519, https://dx.doi.org/10.4995/Dataset/10251/190519
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/190519
PMID: Dataset/10251/190519" target="_blank">http://hdl.handle.net/10251/190519, https://dx.doi.org/10.4995/Dataset/10251/190519
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/190519
Ver en: Dataset/10251/190519" target="_blank">http://hdl.handle.net/10251/190519, https://dx.doi.org/10.4995/Dataset/10251/190519
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/190519

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191866
Dataset. 2022

GROW-GREEN CORE KPIS

GROW-GREEN PILOTS MONITORING

  • Orozco Messana, Javier|||0000-0001-8611-8816
  • Calabuig Moreno, Raimon|||0000-0003-0810-881X
  • Vallés Planells, María Concepción|||0000-0002-5932-0485
  • Galiana Galán, Francisco|||0000-0001-7897-6538
  • Tudorie, Carla Ana-Maria|||0000-0002-3060-6199
  • Alfonso Solar, David|||0000-0003-0141-075X
  • Peñalvo López, Elisa|||0000-0002-3143-822X
  • Andrés Doménech, Ignacio|||0000-0003-4237-4863
[EN] The H2020 project “Green Cities for Climate and Water Resilience, Sustainable Economic Growth, Healthy Citizens and Environments" (GROW GREEN, Grant Agreement: 730283), developed green infrastructure pilots in: Manchester, Valencia and Wroclaw. The monitoring framework supported the pilot analysis and its impact assessment through the development of core Key Performance Indicators (KPIs) through all pilots. The historical evolution of these core KPIs are available on the Grow-Green Open Data platform sharing the software architecture for the smart city platform of Valencia City. It is an implementation of Telefónica’s Thinking Cities platform, which is based on the FIWARE standards and interfaces. All monitoring data are included on this dataset grouped on the core KPIs structure., This research was co-funded by the European Commission through the H2020 project “Green Cities for Climate and Water Resilience, Sustainable Economic Growth, Healthy Citizens and Environments (GROW GREEN)” Grant Agreement: 730283.

DOI: Dataset/10251/191866" target="_blank">http://hdl.handle.net/10251/191866, https://dx.doi.org/10.4995/Dataset/10251/191866
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191866
HANDLE: Dataset/10251/191866" target="_blank">http://hdl.handle.net/10251/191866, https://dx.doi.org/10.4995/Dataset/10251/191866
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191866
PMID: Dataset/10251/191866" target="_blank">http://hdl.handle.net/10251/191866, https://dx.doi.org/10.4995/Dataset/10251/191866
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191866
Ver en: Dataset/10251/191866" target="_blank">http://hdl.handle.net/10251/191866, https://dx.doi.org/10.4995/Dataset/10251/191866
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191866

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191820
Dataset. 2023

UNCERTAINTY ASSESSMENT OF PROARRHYTHMIA PREDICTIONS DERIVED FROM MULTI-LEVEL IN SILICO MODELS

  • Kopanska, Karolina
  • Rodríguez-Belenguer, Pablo
  • Llopis-Lorente, Jordi|||0000-0002-3958-8062
  • Trénor, Beatriz|||0000-0001-9166-6112
  • Saiz, Javier|||0000-0002-9850-0825
  • Pastor, Manuel
[EN] These datasets were generated to train ("PopulationDrugsTrainingKrNaLCaL.xlsx") and test ("PopulationDrugsTestKrCaLNaL.xlsx") the uncertainty assessment models developed in the paper "Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models" by Kopanska, Rodríguez-Belenguer, et al., The authors received funding from the eTRANSAFE project, Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777365, supported from European Union's Horizon 2020 and the EFPIA. We also received funding from the SimCardioTest supported by European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016496. J.L.L. is being funded by the Ministerio de Ciencia, Innovacion y Universidades for the “Formacion de Profesorado Universitario” (Grant Reference: FPU18/01659). The work was also partially support by the Dirección General de Política Científica de la Generalitat Valenciana (PROMETEO/ 2020/043).

DOI: Dataset/10251/191820" target="_blank">http://hdl.handle.net/10251/191820, https://dx.doi.org/10.4995/Dataset/10251/191820
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191820
HANDLE: Dataset/10251/191820" target="_blank">http://hdl.handle.net/10251/191820, https://dx.doi.org/10.4995/Dataset/10251/191820
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191820
PMID: Dataset/10251/191820" target="_blank">http://hdl.handle.net/10251/191820, https://dx.doi.org/10.4995/Dataset/10251/191820
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191820
Ver en: Dataset/10251/191820" target="_blank">http://hdl.handle.net/10251/191820, https://dx.doi.org/10.4995/Dataset/10251/191820
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/191820

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193255
Dataset. 2023

COMBINING PHARMACOKINETIC AND ELECTROPHYSIOLOGICAL MODELS FOR EARLY PREDICTION OF DRUG-INDUCED ARRHYTHMOGENICITY

  • Llopis-Lorente, Jordi|||0000-0002-3958-8062
  • Baroudi, Samuel
  • Koloskoff, Kévin
  • Romero Pérez, Lucia|||0000-0003-4605-8630
  • Mora-Fenoll, María Teresa|||0000-0002-8069-2486
  • Basset, Matthieu
  • Benito, Sylvain
  • Dayan, Frederic
  • Saiz Rodríguez, Francisco Javier|||0000-0002-9850-0825
  • Trénor Gomis, Beatriz Ana|||0000-0001-9166-6112
This repository contains the code used to generate the male and female population of models and simulate the different pharmacokinetic scenarios in Llopis-Lorente et al. (2023). Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity

DOI: Dataset/10251/193255" target="_blank">http://hdl.handle.net/10251/193255, https://dx.doi.org/10.4995/Dataset/10251/193255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193255
HANDLE: Dataset/10251/193255" target="_blank">http://hdl.handle.net/10251/193255, https://dx.doi.org/10.4995/Dataset/10251/193255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193255
PMID: Dataset/10251/193255" target="_blank">http://hdl.handle.net/10251/193255, https://dx.doi.org/10.4995/Dataset/10251/193255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193255
Ver en: Dataset/10251/193255" target="_blank">http://hdl.handle.net/10251/193255, https://dx.doi.org/10.4995/Dataset/10251/193255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193255

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193552
Dataset. 2023

WEBSITE INDICATORS ON TEXTILE COMPANIES IN THE COMUNITAT VALENCIANA REGION

  • Doménech i de Soria, Josep|||0000-0002-7302-5810
  • García-Bernabeu, Ana|||0000-0003-3181-7745
  • Díaz García, Pablo|||0000-0002-7093-6061
Sustainability website indicators after scraping the websites of textile companies in the Comunitat Valencia region.

DOI: Dataset/10251/193552" target="_blank">http://hdl.handle.net/10251/193552, https://dx.doi.org/10.4995/Dataset/10251/193552
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193552
HANDLE: Dataset/10251/193552" target="_blank">http://hdl.handle.net/10251/193552, https://dx.doi.org/10.4995/Dataset/10251/193552
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193552
PMID: Dataset/10251/193552" target="_blank">http://hdl.handle.net/10251/193552, https://dx.doi.org/10.4995/Dataset/10251/193552
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193552
Ver en: Dataset/10251/193552" target="_blank">http://hdl.handle.net/10251/193552, https://dx.doi.org/10.4995/Dataset/10251/193552
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/193552

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/194651
Dataset. 2023

MEASURING QUALITY OF LIFE IN EUROPE: A NEW MULTICRITERIA APPROACH

MEASURING QUALITY OF LIFE IN EUROPE: A NEW MULTICRITERIA APPROACH

  • García Bernabeu, Ana María|||0000-0003-3181-7745
Quality of life indicators include measures of both objective and subjective well-being to broaden the traditional income-focused view towards a multidimensional view of welfare. In this paper, we develop a single reliable composite index that considers the effect of uncertainty and imprecision related to the specific nature of the phenomenon being measured. Additionally, we suggest a procedure for incorporating this new way of assigning priorities through multicriteria techniques. To this end, we propose a new multicriteria approach that introduces the recent notion of picture fuzzy sets to deal with uncertainty and imprecision in the assessment of objective and subjective dimensions of quality-of-life performance. To verify the effectiveness of the whole approach and the credibility of the results, we show its application for monitoring the quality of life in the European Union. Our results show that fuzzy numbers can be a useful tool when combined with multicriteria techniques in the prioritization phase of the criteria and that they increase the quality and reliability of the overall aggregate indicator. Moreover, we find that in a picture environment, the results are consistent regardless of the multicriteria approach used to provide a final ranking.

Proyecto: //
DOI: Dataset/10251/194651" target="_blank">http://hdl.handle.net/10251/194651, https://dx.doi.org/10.4995/Dataset/10251/194651
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/194651
HANDLE: Dataset/10251/194651" target="_blank">http://hdl.handle.net/10251/194651, https://dx.doi.org/10.4995/Dataset/10251/194651
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/194651
PMID: Dataset/10251/194651" target="_blank">http://hdl.handle.net/10251/194651, https://dx.doi.org/10.4995/Dataset/10251/194651
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/194651
Ver en: Dataset/10251/194651" target="_blank">http://hdl.handle.net/10251/194651, https://dx.doi.org/10.4995/Dataset/10251/194651
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/194651

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/199150
Dataset. 2023

DORA DECLARATION TWEET COLLECTION

  • Orduña Malea, Enrique|||0000-0002-1989-8477
  • Bautista Puig, Núria
This dataset includes the raw data used to carry out a study related to the analysis of the DORA Declaration on Twitter. The dataset includes the tweets collected from the Twitter Academic API (comprising three collections: tweets published by DORA, tweets mentioning DORA, and tweets including a DORA-related hashtag), supplementary material (including extra tables and figures), and the script used to collect data from Twitch API.

DOI: Dataset/10251/199150" target="_blank">http://hdl.handle.net/10251/199150, https://dx.doi.org/10.4995/Dataset/10251/199150
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/199150
HANDLE: Dataset/10251/199150" target="_blank">http://hdl.handle.net/10251/199150, https://dx.doi.org/10.4995/Dataset/10251/199150
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/199150
PMID: Dataset/10251/199150" target="_blank">http://hdl.handle.net/10251/199150, https://dx.doi.org/10.4995/Dataset/10251/199150
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/199150
Ver en: Dataset/10251/199150" target="_blank">http://hdl.handle.net/10251/199150, https://dx.doi.org/10.4995/Dataset/10251/199150
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/199150

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
Dataset. 2023

CHARACTERIZATION OF WO3 NANOSTRUCTURES USED IN THE DEGRADATION OF METHYLPARABEN

  • García Antón, José|||0000-0002-0289-1324
  • Cifre Herrando, Mireia|||0000-0002-8800-3585
  • Roselló Márquez, Gemma
  • García García, Dionisio Miguel|||0000-0001-8951-4558
The data were use to study the degradation of Methylparaben using WO3 Nanostructures. WO3 nanostructures were synthesized with different complexing agents (0.05 M H2O2 and 0.1 M citric acid) and annealing conditions (400 _C, 500 _C and 600 _C) to obtain optimal WO3 nanostructures to use them as a photoanode in the photoelectrochemical (PEC) degradation of an endocrine disruptor chemical. X-ray photoelectron spectroscopy was performed to provide information of the electronic states of the nanostructures. The crystallinity of the samples was observed by a confocal Raman laser microscope and X-ray diffraction. Furthermore, photoelectrochemical measurements (photostability, photoelectrochemical impedance spectroscopy, Mott–Schottky and water-splitting test) were also performed using a solar simulator with AM 1.5 conditions at 100 mW_cm-2. Once the optimal nanostructure was obtained, the PEC degradation of methylparaben was carried out. It was followed by ultra-high-performance liquid chromatography and mass spectrometry, which allowed to obtain the concentration of the contaminant during degradation and the identification of degradation intermediates.

DOI: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
HANDLE: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
PMID: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
Ver en: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
Dataset. 2023

PREPARATION OF ELECTRODES BASED ON WO3 NANOSTRUCTURES FOR LI-ION BATTERIES

  • García Antón, José|||0000-0002-0289-1324
  • Roselló Márquez, Gemma
  • García García, Dionisio Miguel|||0000-0001-8951-4558
  • Cifre Herrando, Mireia|||0000-0002-8800-3585
  • Blasco Tamarit, María Encarnación|||0000-0001-7314-082X
The data are related with the preparation of electrodes based on WO3 nanostructures used as anode materials for Li-ion batteries. The nanostructured WO3 thin film was effectively synthesized by an electrochemical procedure. Then, an annealing treatment at 600◦C in air environment for 4 h was carried out. In the second electrode synthesized, a carbon layer was uniformly deposited on WO3 nanostructures to obtain a WO3/C electrode. Finally, WO3/WS2 electrodes were prepared by means of in situ sulfurization of WO3 one-step solid-state synthesis using tungsten trioxide (WO3) and thiourea as precursor material. By using X-ray photoelectron spectroscopy, X-ray diffraction analysis and Raman spectra, the three electrodes have been morphologically characterized. Electrochemical properties were analysed by cyclic voltammogram, galvanostatic charge/discharge cycling, and electrochemical impedance spectroscopy.

DOI: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
HANDLE: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
PMID: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
Ver en: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255

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