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:

High-Throughput Analysis of the IgG N-Glycome by UPLC - FLR As biological and clinical relevance of glycosylation is becoming more apparent, interest in large scale studies of the glycome is growing. Glycans attached to immunoglobulin G (IgG) were shown to be essential for its function and IgG glycosylation was shown to change with various processes, making IgG one of the most studied glycoproteins. Many approaches including liquid chromatography, capillary gel electrophoresis, and mass spectrometry were developed to study IgG glycosylation. Generation of high-quality glycomics data in a high-throughput fashion requires reproducible and robust sample preparation and accurate and reliable quantitative analysis. This chapter presents a protocol for an optimized and high-throughput IgG N-glycan release, fluorescent labeling and cleanup, and analysis of fluorescently labeled IgG N-glycans by hydrophilic interaction liquid chromatography (HILIC) on an ultra performance liquid chromatography (UPLC) system with fluorescence (FLR) detection.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["function"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["IgG", "IgG N-Glycome", "glycome", "immunoglobulin G", "Glycans", "IgG N-glycan", "glycoproteins", "IgG N-glycans"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": [], "Food": [], "HealthCareActivity": ["capillary gel electrophoresis", "mass spectrometry", "fluorescent labeling", "liquid chromatography", "ultra performance liquid chromatography", "detection", "hydrophilic interaction liquid chromatography", "UPLC", "HILIC"], "InjuryOrPoisoning": [], "IntellectualProduct": ["protocol"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study", "analysis", "large scale studies"], "SpatialConcept": ["approaches"], "Virus": []}