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:

Tailor-made drug carrier: Comparison of formation-dependent physicochemical properties within self-assembled aggregates for an optimal drug carrier Self-assembled surfactant aggregates, such as micelles and vesicles, have been investigated for their application as drug carriers in the treatment of various diseases. However, the characteristics that decide which aggregate is the best drug carrier for each disease have not yet been clarified. In order to design an optimal drug carrier for each disease, various kinds of self-assembled aggregates, such as spherical micelles, lens-like vesicles, and tube-like vesicles, were evaluated by " multiple techniques " including dynamic light scattering, differential scanning calorimetry, nuclear magnetic resonance spectroscopy, and fluorescence measurement using the Laurdan probe. These studies led to the compilation of a database on the formation-dependent properties of self-assembled aggregates. As the relationship between physicochemical properties of self-assembled aggregates and their functions as drug carriers have been extensively reported, this database can be utilized for designing an optimal drug carrier, i.e., a tailor-made drug carrier.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["disease", "diseases"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["surfactant", "spherical micelles", "Tailor-made drug carrier", "drug carrier", "Laurdan", "drug carriers", "micelles", "tailor-made drug carrier"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": [], "Food": [], "HealthCareActivity": ["differential scanning calorimetry", "nuclear magnetic resonance spectroscopy", "treatment", "dynamic light scattering", "fluorescence measurement"], "InjuryOrPoisoning": [], "IntellectualProduct": ["database"], "MedicalDevice": ["probe"], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["studies"], "SpatialConcept": [], "Virus": []}