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:

Detection and Characterization of Flat Aberrant Crypt Foci (Flat ACF) in the Novel A/J Min/+ Mouse Flat aberrant crypt foci (flat ACF) and mucin-depleted foci (MDF) have previously been described as preneoplastic colonic lesions. We used the novel A/J Min/+ mouse model, that demonstrates extensive spontaneous colon carcinogenesis to refine the method of detection of flat ACF and further characterize and define them as early lesions by histological examination and comparison with MDF. Colons were stained with methylene blue (MB) for flat ACF detection and restained with high-iron diamine-alcian blue (HID-AB) for MDF detection. Optimal flat ACF recognition required at least 24 h of storage post- MB staining and adherence to a set of characteristics. The fraction of flat ACF corresponding with MDF was 93%. Flat ACF / MDF displayed the same picture of severe dysplasia, lack of mucus and goblet cells and accumulation of cytoplasmic β-catenin. The easily detectable flat ACF are reliable surface biomarkers of Apc -driven colon carcinogenesis.
{"AnatomicalStructure": ["surface", "mucus", "Apc", "goblet cells", "Colons", "cytoplasmic"], "Bacterium": [], "BiologicFunction": ["mucin-depleted foci", "A/J Min/+ mouse model", "A/J Min/+ Mouse", "severe dysplasia", "MDF", "flat ACF", "colon carcinogenesis", "Flat aberrant crypt foci", "Flat ACF", "preneoplastic colonic lesions", "Flat Aberrant Crypt Foci (Flat ACF)"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["HID-AB", "MB", "high-iron diamine-alcian blue", "\u03b2-catenin"], "ClinicalAttribute": ["biomarkers"], "Eukaryote": [], "Finding": ["accumulation", "lesions"], "Food": [], "HealthCareActivity": ["stained with methylene blue", "Detection", "detection", "histological examination", "MB staining", "restained"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": [], "SpatialConcept": [], "Virus": []}