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:

Novel biomarkers for patients with idiopathic acute anterior uveitis: neutrophil to lymphocyte ratio and platelet to lymphocyte ratio To assess the levels of the neutrophil to lymphocyte ratio (N / L) and the platelet to lymphocyte ratio (P / L) in patients with idiopathic acute anterior uveitis (AAU) and to compare with healthy controls. Thirty-six male patients with idiopathic AAU and 36 male healthy subjects were enrolled in this retrospective study. Complete ophthalmological examination and complete blood count measurements results of all subjects were evaluated. There was a significant difference in N / L and P / L between idiopathic AAU and control groups (P=0.006, P=0.022). Also, correlation analysis revealed a significant correlation between C-reactive protein (CRP) and N / L (P=0.002; r=0.461). Our study for the first time provides evidence of N / L and P / L may be useful biomarkers in patients with idiopathic AAU. N / L is correlated with CRP, so it can be a useful biomarker to predict the prognosis in idiopathic AAU.
{"AnatomicalStructure": ["P", "platelet", "N", "L", "neutrophil", "lymphocyte"], "Bacterium": [], "BiologicFunction": ["acute anterior uveitis", "AAU"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["C-reactive protein", "CRP"], "ClinicalAttribute": ["biomarkers", "biomarker"], "Eukaryote": [], "Finding": [], "Food": [], "HealthCareActivity": ["blood count measurements", "ophthalmological examination", "evaluated", "prognosis"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["subjects", "male"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["correlation analysis", "study", "retrospective study"], "SpatialConcept": [], "Virus": []}