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:

Natural competence for transformation While most molecular biologists are familiar with the artificial transformation of bacteria in the context of laboratory cloning experiments, natural competence for transformation refers to a specific physiological state in which prokaryotes are able to take up genetic material from their surroundings. Occasionally, such absorbed DNA is recombined into the organism's own genome, resulting in natural transformation (Figure 1). As a consequence, natural competence for transformation is considered a primary mode of horizontal gene transfer (HGT) in prokaryotes, together with conjugation (direct cell to cell transfer of DNA via a specialized conjugal pilus) and phage transduction (DNA transfer mediated by viruses). HGT plays a major role in bacterial evolution, and past research has demonstrated that HGT, including natural competence for transformation, contributes to the emergence of pathogens and the spread of virulence factors. Indeed, Frederick Griffith discovered natural competence for transformation in 1928 while he was investigating the exchange of pathogenic traits in pneumococci. Due to the increase in the abundance and spread of multidrug-resistant microbes, research on HGT is even more important today than ever before.
{"AnatomicalStructure": ["cell", "genome", "genetic material", "conjugal pilus"], "Bacterium": ["pneumococci", "multidrug-resistant microbes"], "BiologicFunction": ["evolution", "transformation of bacteria", "HGT", "transformation", "horizontal gene transfer", "conjugation", "transduction", "exchange"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["DNA", "virulence factors"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["pathogenic"], "Food": [], "HealthCareActivity": [], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": ["laboratory"], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["research", "experiments", "cloning"], "SpatialConcept": ["surroundings"], "Virus": ["phage", "viruses"]}