0000000000590592
AUTHOR
Marianne Mueller
Ketamine’s Effects on the Glutamatergic and GABAergic Systems: A Proteomics and Metabolomics Study in Mice
Ketamine, a noncompetitive, voltage-dependent N-Methyl-D-aspartate receptor (NMDAR) antagonist, has been shown to have a rapid antidepressant effect and is used for patients experiencing treatment-resistant depression. We carried out a time-dependent targeted mass spectrometry-based metabolomics profiling analysis combined with a quantitative based on in vivo <sup>15</sup>N metabolic labeling proteome comparison of ketamine- and vehicle-treated mice. The metabolomics and proteomics datasets were used to further elucidate ketamine’s mode of action on the gamma-aminobutyric acid (GABA)ergic and glutamatergic systems. In addition, myelin basic protein levels were analyzed by Wester…
Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…