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:

Lycopene and risk of cardiovascular diseases: A meta-analysis of observational studies The aim of current meta-analysis was to investigate the relation between lycopene and risk of cardiovascular diseases (CVD). Studies concerning about the association between lycopene and risk of CVD were searched on Pubmed, Embase, and Web of Science from inception to October 2016. A total of 14 eligible studies were identified. A significantly inverse association with a pooled risk ratio (RR) of 0.83 (95% CI: 0.76-0.90) was shown between lycopene exposure and risk of CVD. Findings were similar restricting to dietary studies (RR = 0.87, 95% CI = 0.79-0.96) and biomarker studies (RR = 0.74, 95% CI = 0. 62-0.87). Dietary lycopene intake was statistically significant for coronary heart disease (CHD) (RR: 0.87; 95% CI: 0.76-0.98) and stroke (RR: 0.83; 95% CI: 0.69-0.96).The pooled risk estimate was generally similar for lycopene biomarker concentrations, but the association was only statistically significant for stroke (RR: 0.65; 95% CI: 0.42-0.87). Subgroup analyses showed that retrospective and low quality studies were statistically significant sources of heterogeneity. Higher lycopene exposure is inversely associated with a lower risk of CVD. Further well-designed randomized clinical trials are required to assess the role of lycopene on CVD.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["CVD", "CHD", "cardiovascular diseases", "coronary heart disease", "stroke"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["lycopene", "Lycopene"], "ClinicalAttribute": ["biomarker"], "Eukaryote": [], "Finding": ["Findings"], "Food": ["Dietary", "dietary"], "HealthCareActivity": [], "InjuryOrPoisoning": [], "IntellectualProduct": ["Embase", "Pubmed", "Web of Science", "Subgroup"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["eligible studies", "retrospective", "studies", "randomized clinical trials", "analyses", "meta-analysis", "Studies"], "SpatialConcept": [], "Virus": []}