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:

DT MRI microstructural cortical lesion damage does not explain cognitive impairment in MS We combined double inversion recovery (DIR) and diffusion tensor (DT) magnetic resonance imaging (MRI) to quantify the severity of cortical lesion (CL) microstructural tissue abnormalities in a large cohort of relapse - onset multiple sclerosis (MS) patients and its contribution to cognitive dysfunction. DIR, DT, dual-echo, and three-dimensional (3D) T1-weighted scans were acquired from 149 MS patients and 40 controls. Cognitively impaired (CI) patients had ⩾2 abnormal neuropsychological tests. Diffusivity values in CLs, cortex, white matter (WM) lesions, and normal-appearing (NA) WM were assessed. Predictors of cognitive impairment were identified using a random forest analysis. Compared to controls, MS patients had lower normalized brain volume (NBV), gray matter volume (GMV), WM volume, lower fractional anisotropy (FA), and higher mean diffusivity in cortex and normal-appearing white matter (NAWM). A total of 44 (29.5%) patients were CI. Compared to cognitively preserved (CP), CI patients had higher T2 WM lesion volume (LV), lower NBV and GMV, and more severe diffusivity abnormalities in WM lesions, cortex, and NAWM. CL measures did not differ between CI and CP patients. Cortex FA, age, disease duration, T2 WM LV, and GMV best predicted MS -related cognitive impairment (C-statistic = 0.88). " Diffuse " GM and NAWM damage and WM lesions, rather than intrinsic CL damage, contribute to cognitive impairment in MS.
{"AnatomicalStructure": ["GM", "normal-appearing (NA) WM", "NAWM", "tissue", "cortex", "Cortex", "cortical", "abnormalities", "normal-appearing white matter"], "Bacterium": [], "BiologicFunction": ["multiple sclerosis", "lesion", "cognitive impairment", "CL", "cognitive dysfunction", "MS", "CI", "Cognitively impaired", "CLs"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["WM volume", "not differ", "abnormal", "WM lesions", "white matter (WM) lesions"], "Food": [], "HealthCareActivity": ["dual-echo", "DT", "T1-weighted scans", "neuropsychological tests", "DIR", "DT MRI", "double inversion recovery", "diffusion tensor (DT) magnetic resonance imaging (MRI)"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["cohort"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["random forest analysis"], "SpatialConcept": ["intrinsic", "three-dimensional", "Diffuse", "3D"], "Virus": []}