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:

HERG1 potassium channel expression in potentially malignant disorders of the oral mucosa and prognostic relevance in oral squamous cell carcinoma HERG1 potassium channel plays a critical role in the cell proliferation. HERG1 protein expression was analyzed by immunohistochemistry (IHC) in 62 patients with oral leukoplakias and 100 patients with oral squamous cell carcinomas (OSCC). HERG1 mRNA levels were assessed by real-time reverse transcriptase-polymerase chain reaction (RT-PCR) in 22 patients with primary head and neck squamous cell carcinoma (HNSCC). Statistically significant associations were found between HERG1 expression and tobacco consumption, disease stage, tumor differentiation, tumor recurrence, and reduced survival. There was no association between HERG1 expression and the risk of progression from oral leukoplakia to OSCC. In addition, a high proportion of tumors (80%) showed increased HERG1 mRNA levels compared to normal mucosa from nononcologic patients. Aberrant HERG1 expression increases as oral tumorigenesis progresses from oral hyperplasia to OSCC. Increased HERG1 mRNA levels were also frequently detected in OSCC and other HNSCC subsites. HERG1 expression emerges as a clinically relevant feature during tumor progression and a potential poor prognostic biomarker for OSCC. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1708-1716, 2016.
{"AnatomicalStructure": ["HERG1", "oral mucosa", "normal mucosa"], "Bacterium": [], "BiologicFunction": ["cell proliferation", "OSCC", "oral leukoplakias", "tumors", "malignant disorders", "oral squamous cell carcinoma", "tumor", "tumor progression", "expression", "differentiation", "progression", "oral squamous cell carcinomas", "tumor recurrence", "oral leukoplakia", "HNSCC", "head and neck squamous cell carcinoma", "tumorigenesis progresses"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["HERG1", "potassium channel", "mRNA", "HERG1 protein"], "ClinicalAttribute": ["biomarker"], "Eukaryote": [], "Finding": ["detected"], "Food": [], "HealthCareActivity": ["immunohistochemistry", "IHC"], "InjuryOrPoisoning": [], "IntellectualProduct": ["prognostic"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["analyzed", "RT-PCR", "real-time reverse transcriptase-polymerase chain reaction"], "SpatialConcept": ["subsites"], "Virus": []}