Identification of metabolic kinetic patterns in different brain regions using metabolomics methods coupled with various discriminant approaches

MultiClassMetabo: A Superior Classification Model Constructed Using Metabolic Markers in Multiclass Metabolomics

Multiclass metabolomics has become a popular technique for revealing the mechanisms underlying certain physiological processes, different tumor types, or different therapeutic responses. In multiclass metabolomics, it is highly important to uncover the underlying biological information on biosamples by identifying the metabolic markers with the most associations and classifying the different sample classes. The classification problem of multiclass metabolomics is more difficult than that of the binary problem. To date, various methods exist for constructing classification models and identifying metabolic markers consisting of well-established techniques and newly emerging machine learning algorithms. However, how to construct a superior classification model using these methods remains unclear for a given multiclass metabolomic data set. Herein, MultiClassMetabo has been developed for constructing a superior classification model using metabolic markers identified in multiclass metabolomics. MultiClassMetabo can enable online services, including (a) identifying metabolic markers by marker identification methods, (b) constructing classification models by classification methods, and (c) performing a comprehensive assessment from multiple perspectives to construct a superior classification model for multiclass metabolomics. In summary, MultiClassMetabo is distinguished for its capability to construct a superior classification model using the most appropriate method through a comprehensive assessment, which makes it an important complement to other available tools in multiclass metabolomics. MultiClassMetabo can be accessed at http://idrblab.cn/multiclassmetabo/.

Preoperative Acute Sleep Deprivation Causes Postoperative Pain Hypersensitivity and Abnormal Cerebral Function

Preoperative sleep loss can amplify post-operative mechanical hyperalgesia. However, the underlying mechanisms are still largely unknown. In the current study, rats were randomly allocated to a control group and an acute sleep deprivation (ASD) group which experienced 6 h ASD before surgery. Then the variations in cerebral function and activity were investigated with multi-modal techniques, such as nuclear magnetic resonance, functional magnetic resonance imaging, c-Fos immunofluorescence, and electrophysiology. The results indicated that ASD induced hyperalgesia, and the metabolic kinetics were remarkably decreased in the striatum and midbrain. The functional connectivity (FC) between the nucleus accumbens (NAc, a subregion of the ventral striatum) and the ventrolateral periaqueductal gray (vLPAG) was significantly reduced, and the c-Fos expression in the NAc and the vLPAG was suppressed. Furthermore, the electrophysiological recordings demonstrated that both the neuronal activity in the NAc and the vLPAG, and the coherence of the NAc-vLPAG were suppressed in both resting and task states. This study showed that neuronal activity in the NAc and the vLPAG were weakened and the FC between the NAc and the vLPAG was also suppressed in rats with ASD-induced hyperalgesia. This study highlights the importance of preoperative sleep management for surgical patients.