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:

Assessing nitrous oxide effect using electroencephalographically -based depth of anesthesia measures cortical state and cortical input Existing electroencephalography (EEG) based depth of anesthesia monitors cannot reliably track sedative or anesthetic states during n-methyl-D-aspartate (NMDA) receptor antagonist based anesthesia with ketamine or nitrous oxide (N2O). Here, a physiologically -motivated depth of anesthesia monitoring algorithm based on autoregressive-moving-average (ARMA) modeling and derivative measures of interest, Cortical State (CS) and Cortical Input (CI), is retrospectively applied in an exploratory manner to the NMDA receptor antagonist N2O, an adjuvant anesthetic gas used in clinical practice. Composite Cortical State (CCS) and Composite Cortical State distance (CCSd), two new modifications of CS, along with CS and CI were evaluated on electroencephalographic (EEG) data of healthy control individuals undergoing N2O inhalation up to equilibrated peak gas concentrations of 20, 40 or 60% N2O / O2. In particular, CCSd has been devised to vary consistently for increasing levels of anesthetic concentration independent of the anesthetic's microscopic mode of action for both N2O and propofol. The strongest effects were observed for the 60% peak gas concentration group. For the 50-60% peak gas levels, individuals showed statistically significant reductions in responsiveness compared to rest, and across the group CS and CCS increased by 39 and 42%, respectively, while CCSd was found to decrease by 398%. On the other hand a clear conclusion regarding the changes in CI could not be reached. These results indicate that, contrary to previous depth of anesthesia monitoring measures, the CS, CCS, and especially CCSd measures derived from frontal EEG are potentially useful for differentiating gas concentration and responsiveness levels in people under N2O. On the other hand, determining the utility of CI in this regard will require larger sample sizes and potentially higher gas concentrations. Future work will assess the sensitivity of CS -based and CI measures to other anesthetics and their utility in a clinical environment.
{"AnatomicalStructure": ["Cortical", "cortical"], "Bacterium": [], "BiologicFunction": ["inhalation"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["sedative", "adjuvant anesthetic gas", "propofol", "N2O", "ketamine", "nitrous oxide", "anesthetic", "NMDA receptor antagonist", "anesthetics", "n-methyl-D-aspartate (NMDA) receptor antagonist", "anesthetic\u0027s", "O2"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["depth of anesthesia", "modifications", "anesthetic concentration"], "Food": [], "HealthCareActivity": ["anesthesia", "EEG", "monitoring", "electroencephalographic", "electroencephalography", "evaluated", "reductions", "electroencephalographically"], "InjuryOrPoisoning": [], "IntellectualProduct": ["state", "Composite Cortical State", "CCSd", "CS", "State", "CCS", "input", "CI", "autoregressive-moving-average (ARMA) modeling", "Composite Cortical State distance", "algorithm", "Input"], "MedicalDevice": [], "Organization": ["clinical"], "PopulationGroup": ["people", "group", "individuals"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["retrospectively"], "SpatialConcept": ["frontal", "contrary", "environment"], "Virus": []}