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:

International validation of a urinary biomarker panel for identification of active lupus nephritis in children Conventional markers of juvenile-onset systemic lupus erythematosus (JSLE) disease activity fail to adequately identify lupus nephritis (LN). While individual novel urine biomarkers are good at detecting LN flares, biomarker panels may improve diagnostic accuracy. The aim of this study was to assess the performance of a biomarker panel to identify active LN in two international JSLE cohorts. Novel urinary biomarkers, namely vascular cell adhesion molecule-1 (VCAM-1), monocyte chemoattractant protein 1 (MCP-1), lipocalin-like prostaglandin D synthase (LPGDS), transferrin (TF), ceruloplasmin, alpha-1-acid glycoprotein (AGP) and neutrophil gelatinase-associated lipocalin (NGAL), were quantified in a cross-sectional study that included participants of the UK JSLE Cohort Study (Cohort 1) and validated within the Einstein Lupus Cohort (Cohort 2). Binary logistic regression modelling and receiver operating characteristic curve analysis [area under the curve (AUC)] were used to identify and assess combinations of biomarkers for diagnostic accuracy. A total of 91 JSLE patients were recruited across both cohorts, of whom 31 (34 %) had active LN and 60 (66 %) had no LN. Urinary AGP, ceruloplasmin, VCAM-1, MCP-1 and LPGDS levels were significantly higher in those patients with active LN than in non - LN patients [all corrected p values (p c) < 0.05] across both cohorts. Urinary TF also differed between patient groups in Cohort 2 (p c = 0.001). Within Cohort 1, the optimal biomarker panel included AGP, ceruloplasmin, LPGDS and TF (AUC 0.920 for active LN identification). These results were validated in Cohort 2, with the same markers resulting in the optimal urine biomarker panel (AUC 0.991). In two international JSLE cohorts, urinary AGP, ceruloplasmin, LPGDS and TF demonstrate an 'excellent' ability for accurately identifying active LN in children.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["lupus nephritis", "LN", "JSLE", "juvenile-onset systemic lupus erythematosus"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": ["urine", "urinary", "Urinary"], "BodySystem": [], "Chemical": ["neutrophil gelatinase-associated lipocalin", "ceruloplasmin", "monocyte chemoattractant protein 1", "LPGDS", "NGAL", "MCP-1", "lipocalin-like prostaglandin D synthase", "TF", "AGP", "vascular cell adhesion molecule-1", "VCAM-1", "alpha-1-acid glycoprotein", "transferrin"], "ClinicalAttribute": ["biomarkers", "biomarker", "markers"], "Eukaryote": [], "Finding": ["flares"], "Food": [], "HealthCareActivity": ["detecting", "panels", "panel"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": ["Einstein Lupus"], "PopulationGroup": ["Cohort 2", "participants", "Cohort", "Cohort 1", "cohorts"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["cross-sectional study", "study", "logistic regression modelling", "validation"], "SpatialConcept": ["UK"], "Virus": []}