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:

Prevalence and correlates of antibiotic sharing in the Philippines: antibiotic misconceptions and community - level access to non-medical sources of antibiotics To identify sociodemographic, knowledge and attitudinal correlates to antibiotic sharing among a community-based sample of adults (age 18 and older) in a low-income setting of the Philippines and to explore community - level data on informal antibiotic distribution in roadside stands (i.e., sari-sari stands). Participants (n = 307) completed self-administered surveys. Correlates to antibiotic sharing were assessed using logistic regression with Firth's bias-adjusted estimate s. Study staff also visited 106 roadside stands and collected data on availability and characteristics of antibiotics in the stands. 78% had shared antibiotics in their lifetime, most often with family members. In multivariable analysis, agreement with the belief that it is safe to prematurely stop an antibiotic course (OR: 2.8, CI: 1.3-5.8) and concerns about antibiotic side effects (OR: 2.1, CI: 1.1-4.4) were significantly associated with increased odds of reported antibiotic sharing. Antibiotic sharing was not associated with sociodemographic characteristics or antibiotic knowledge. Antibiotics were widely available in 60% of sampled sari-sari stands, in which 59% of antibiotics were missing expiration dates. Amoxicillin and cephalexin were the most commonly available antibiotics for sale at the stands (60% and 21%, respectively). Antibiotic sharing was common and was associated with misconceptions about proper antibiotic use. Antibiotics were widely available in sari-sari stands, and usually without expiration information. This study suggests that multipronged and locally tailored approaches to curbing informal antibiotic access are needed in the Philippines and similar Southeast-Asian countries.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["attitudinal", "misconceptions"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["antibiotic", "cephalexin", "antibiotics", "Antibiotic", "Antibiotics", "Amoxicillin"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["informal", "collected data", "low-income setting", "sources", "missing expiration dates"], "Food": [], "HealthCareActivity": [], "InjuryOrPoisoning": [], "IntellectualProduct": ["surveys", "knowledge", "Firth\u0027s bias-adjusted estimate", "expiration information"], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["Participants"], "ProfessionalOrOccupationalGroup": ["staff"], "ResearchActivity": ["logistic regression"], "SpatialConcept": ["Philippines", "Southeast-Asian countries"], "Virus": []}