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:

Multitarget sensing of glucose and cholesterol based on Janus hydrogel microparticles A visualized sensing method for glucose and cholesterol was developed based on the hemispheres of the same Janus hydrogel microparticles. Single-phase and Janus hydrogel microparticles were both generated using a centrifugal microfluidic chip. For glucose sensing, concanavalin A and fluorescein labeled dextran used for competitive binding assay were encapsulated in alginate microparticles, and the fluorescence of the microparticles was positively correlated with glucose concentration. For cholesterol sensing, the microparticles embedded with γ-Fe2O3 nanoparticles were used as catalyst for the oxidation of 3,3',5,5'-Tetramethylbenzidine by H2O2, an enzymatic hydrolysis product of cholesterol. And the color transition was more sensitive in the microparticles than in solutions, indicating the microparticles are more applicable for visualized determination. Furthermore, Janus microparticles were employed for multitarget sensing in the two hemespheres, and glucose and cholesterol were detected within the same microparticles without obvious interference. Besides, the particles could be manipulated by an external magnetic field. The glucose and cholesterol levels were measured in human serum utilizing the microparticles, which confirmed the potential application of the microparticles in real sample detection.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["oxidation"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": ["serum"], "BodySystem": [], "Chemical": ["glucose", "alginate", "Janus microparticles", "H2O2", "enzymatic", "particles", "Janus hydrogel microparticles", "cholesterol", "microparticles", "3,3\u0027,5,5\u0027-Tetramethylbenzidine", "concanavalin A", "fluorescein labeled dextran"], "ClinicalAttribute": [], "Eukaryote": ["human"], "Finding": ["glucose", "positively", "detected", "confirmed", "cholesterol levels", "employed"], "Food": [], "HealthCareActivity": ["sensing of glucose", "cholesterol sensing", "glucose sensing", "sensing method for glucose", "competitive binding assay", "cholesterol", "determination", "detection"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": [], "SpatialConcept": ["external"], "Virus": []}