You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Datasets for the validation of the " in vivo " siRNA - silencing of CD40 and for the detection of new markers of atherosclerosis progression in ApoE - deficient mice Data presented in this Data in Brief article correspond to the article " in vivo " silencing of CD40 reduces progression of experimental atherogenesis through a NFκB / miR-125b axis and reveals new potential mediators in the pathogenesis of atherosclerosis " (M. Hueso, L. De Ramon, E. Navarro, E. Ripoll, J.M. Cruzado, J.M. Grinyo, J. Torras, 2016) [1]. Here, we describe the validation of the silencing of CD40 expression with a specific siRNA in ApoE(-/-) mouse aortas, and its systemic effects on splenic lymphocytic subpopulations as well as on the infiltration of aortic intima by F4/80(+), galectin-3(+) macrophages or by NF-κB(+) cells. We also show the output of a Gene Ontology and TLDA analysis which allowed the detection of potential mediators of atherosclerosis progression. We provide the scientific community with a set of genes whose expression is increased during atherosclerosis progression but downregulated upon CD40 silencing.
{"AnatomicalStructure": ["splenic", "NF-\u03baB(+) cells", "aortic intima", "genes", "galectin-3(+) macrophages", "ApoE(-/-)", "aortas", "ApoE", "F4/80(+)", "CD40"], "Bacterium": [], "BiologicFunction": ["atherogenesis", "silencing", "markers", "expression", "infiltration", "progression", "downregulated", "atherosclerosis", "pathogenesis"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["siRNA", "NF\u03baB", "mediators", "miR-125b"], "ClinicalAttribute": [], "Eukaryote": ["mouse", "mice"], "Finding": [], "Food": [], "HealthCareActivity": ["detection"], "InjuryOrPoisoning": [], "IntellectualProduct": ["M. Hueso", "E. Navarro", "Gene Ontology", "L. De Ramon", "lymphocytic subpopulations", "J.M. Cruzado", "J. Torras", "E. Ripoll", "J.M. Grinyo", "Datasets"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["TLDA analysis", "experimental", "validation"], "SpatialConcept": ["in vivo"], "Virus": []}