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:

Optical tweezers studies of transcription by eukaryotic RNA polymerases Transcription is the first step in the expression of genetic information and it is carried out by large macromolecular enzymes called RNA polymerases. Transcription has been studied for many years and with a myriad of experimental techniques, ranging from bulk studies to high-resolution transcript sequencing. In this review, we emphasise the advantages of using single-molecule techniques, particularly optical tweezers, to study transcription dynamics. We give an overview of the latest results in the single-molecule transcription field, focusing on transcription by eukaryotic RNA polymerases. Finally, we evaluate recent quantitative models that describe the biophysics of RNA polymerase translocation and backtracking dynamics.
{"AnatomicalStructure": ["eukaryotic"], "Bacterium": [], "BiologicFunction": ["expression", "transcription", "Transcription", "translocation"], "BiomedicalOccupationOrDiscipline": ["biophysics"], "BodySubstance": [], "BodySystem": [], "Chemical": ["macromolecular", "enzymes", "RNA polymerase", "RNA polymerases"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": [], "Food": [], "HealthCareActivity": ["high-resolution transcript sequencing"], "InjuryOrPoisoning": [], "IntellectualProduct": ["myriad", "review"], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["studied", "study", "studies", "Optical tweezers", "optical tweezers"], "SpatialConcept": [], "Virus": []}