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ReDIB-2020

Opening date : 2020/01/08 - Closing date :2020/12/31

Resolution of the Distributed Biomedical Image Network approving the following applications of the ReDIB-2020 call for proposals on January 4, 2021:

Code Institution Project Title
ReDIB-2020-a-01 Instituto Cajal, CSIC, Madrid Anatomical and biochemical basis of anxiety and depression in Parkinson's disease
ReDIB-2020-a-02 BIOQUÍMICA, FACULTAD DE MEDICINA-UAM CENTRO MIXTO IIBm Targeting Gasdermin-B overexpression as a new therapeutic  approa
APPROA
ReDIB-2020-a-03 Complejo Hospitalario Ruber Juan Bravo Madrid PRECOGNITIVE
ReDIB-2020-a-04 CNIC Understanding cardiotoxicity and myocardial damage
ReDIB-2020-a-05 UFV Non-invasive molecular imaging of cardiac inflammatory regression in response to acute myocardial infarction, by using nanoparticles targeting macrophage polarization in a porcine model of coronary ischemia/reperfusion”
ReDIB-2020-a-06 UCM MRI and TD-NMR as automation and control tools in fresh ham samples
ReDIB-2020-a-07 LABORATORIO DE PROCESADO DE IMÁGENES (LPI). Universidad de Valencia  'Deep Networks' en el Cerebro Visual: de las Medidas a los Algoritmos
ReDIB-2020-a-08 La Fe Health Research Institute Modulating the activity of genes controlling fat metabolism as a therapeutic strategy in Huntington Disease
ReDIB-2020-a-09 Grupo Acreditado de Investigación en Hematología (IIS La Fe) Multimethodological approach to the analysis of prognostic factors at diagnosis of Hodgkin lymphoma
ReDIB-2020-a-10 UCM METABOCARE
ReDIB-2020-a-11 CIB Margarita Salas (CSIC) Targeting RGD cadherins, a2b1 integrin and interleukin 13 receptor alpha2 (IL13Ra2) for cancer metastasis therapy (Therabodies)
ReDIB-2020-a-12 Imaging La Fe Estudio del rendimiento diagnóstico de la PET/RM [68Ga]Ga-DOTA-TOC en la detección de enfermedad local y a distancia por feocromocitomas y paragangliomas, y su implicación en cambios en la estrategia terapéutica
ReDIB-2020-a-13 Oceanográfic Active sensing in echolocating marine mammals
ReDIB-2020-a-14 IIS La Fe Multicentre prospective study of diagnostic accuracy for quantification by Magnetic Resonance multiparametric imaging of liver fibrosis, inflammation, steatosis, iron and vascular resistance