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:

Development of a liquid chromatography-tandem mass spectrometry method for quantitative analysis of trace d-amino acids d-Amino acids have recently attracted much attention in various research fields including medical, clinical and food industry due to their important biological functions that differ from l-amino acid. Most chiral amino acid separation techniques require complicated derivatization procedures in order to achieve the desirable chromatographic behavior and detectability. Thus, the aim of this research is to develop a highly sensitive analytical method for the enantioseparation of chiral amino acids without any derivatization process using liquid chromatography-tandem mass spectrometry (LC-MS/MS). By optimizing MS/MS parameters, we established a quantification method that allowed the simultaneous analysis of 18 d-amino acids with high sensitivity and reproducibility. Additionally, we applied the method to food sample (vinegar) for the validation, and successfully quantified trace levels of d-amino acids in samples. These results demonstrated the applicability and feasibility of the LC-MS/MS method as a novel, effective tool for d-amino acid measurement in various biological samples.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["biological functions", "attention"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["d-Amino acids", "amino acids", "amino acid", "vinegar", "l-amino acid", "d-amino acids", "d-amino acid"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["detectability", "results"], "Food": [], "HealthCareActivity": ["liquid chromatography-tandem mass spectrometry", "LC-MS/MS"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["research", "research fields", "analysis", "validation"], "SpatialConcept": [], "Virus": []}