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:

Association of abdominal fat with serum amylase in an older cohort: The Baltimore Longitudinal Study of Aging Abdominal fat is a major determinant of metabolic diseases in older individuals. Obesity and diabetes are associated with low serum amylase (SA) levels, but the association between SA and metabolic disease is poorly understood. We investigated the association of low SA with diabetes and sex - specific associations of serum amylase with abdominal fat in older adults. In community-dwelling volunteers from the Baltimore Longitudinal Study of Aging (778 participants, age 66.8±13.6 years), we assessed abdominal fat by computed tomography and diabetes status using the American Diabetes Association criteria. Linear regression analyses assessed the cross-sectional associations between abdominal fat and SA, and logistic regression assessed the odds of diabetes, given low SA. In unadjusted analyses, individuals in the lowest SA quartile (<48μ/L) had 1.97 greater odds of diabetes, (95% CI, 1.01-3.83) than those in the highest quartile (⩾80μ/L). This association was no longer significant after adjusting for visceral adipose tissue area (VAT, dm(2)), abdominal subcutaneous adipose tissue (SAT, dm(2)) or BMI. In adjusted analyses, VAT and SAT were significantly associated with SA in both sexes. Among women, SA was more strongly associated with VAT than with SAT or BMI; VAT (β=-0.117±0.048, P<0.001), SAT (β=-0.023±0.025, P=0.346) and BMI (β=-0.0052±0.075, P=0.49). The association between SA and diabetes was explained mainly by abdominal visceral fat. In women, SA was more strongly associated with VAT than with BMI or SAT. These findings provide motivation for future mechanistic studies on SA's role in metabolic diseases.
{"AnatomicalStructure": ["abdominal visceral fat", "VAT", "visceral adipose tissue area", "abdominal fat", "Abdominal fat", "SAT", "abdominal subcutaneous adipose tissue"], "Bacterium": [], "BiologicFunction": ["Obesity", "metabolic diseases", "metabolic disease", "Aging", "diabetes"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": ["serum"], "BodySystem": [], "Chemical": ["SA", "amylase", "SA\u0027s"], "ClinicalAttribute": ["BMI"], "Eukaryote": [], "Finding": ["SA", "serum amylase (SA) levels"], "Food": [], "HealthCareActivity": ["computed tomography"], "InjuryOrPoisoning": [], "IntellectualProduct": ["mechanistic studies"], "MedicalDevice": [], "Organization": ["American Diabetes Association"], "PopulationGroup": ["women", "participants", "cohort", "individuals", "volunteers", "older"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["adjusted analyses", "unadjusted analyses", "logistic regression", "Longitudinal Study"], "SpatialConcept": ["Baltimore"], "Virus": []}