BackgroundWith the emergence of the metaverse, virtual reality, as a digital technology, must be getting hotter. High quality virtual reality related nursing knowledge scene learning is gradually replacing traditional education and intervention skills.ObjectiveThis systematic study aimed to gain insights into the overall application of virtual reality technology in the study of nursing.MethodsCitations downloaded from the Web of Science Core Collection database for use in VR in nursing publications published from January 1, 2012, to December 31, 2021, were considered in the research. Information retrieval was analyzed using https://bibliometric.com/app, CiteSpace.5.8. R3, and VOS viewer.ResultsA total of 408 institutions from 95 areas contributed to relevant publications, of which the United States is the most influential country in this research field. The clustering labels of cited documents were obtained from the citing documents. Virtual simulation, virtual learning, clinical skills, and dementia are the clustering labels of co-cited documents. The burst keywords represented the research frontiers in 2020–2021, which were knowledge and simulation.ConclusionVirtual nursing has had an impact on both nurses and clients. With the emergence of the concept of the metaverse, the research and application of virtual reality technology in nursing will gradually increase.

At present, lots of studies have tried to apply machine learning to different electroencephalography (EEG) measures for diagnosing schizophrenia (SZ) patients. However, most EEG measures previously used are either a univariate measure or a single type of brain connectivity, which may not fully capture the abnormal brain changes of SZ patients. In this paper, event-related potentials were collected from 45 SZ patients and 30 healthy controls (HCs) during a learning task, and then a combination of partial directed coherence (PDC) effective and phase lag index (PLI) functional connectivity were used as features to train a support vector machine classifier with leave-one-out cross-validation for classification of SZ from HCs. Our results indicated that an excellent classification performance (accuracy = 95.16%, specificity = 94.44%, and sensitivity = 96.15%) was obtained when the combination of functional and effective connectivity features was used, and the corresponding optimal feature number was 15, which included 12 PDC and three PLI connectivity features. The selected effective connectivity features were mainly located between the frontal/temporal/central and visual/parietal lobes, and the selected functional connectivity features were mainly located between the frontal/temporal and visual cortexes of the right hemisphere. In addition, most of the selected effective connectivity abnormally enhanced in SZ patients compared with HCs, whereas all the selected functional connectivity features decreased in SZ patients. The above results showed that our proposed method has great potential to become a tool for the auxiliary diagnosis of SZ.

Background: A growing number of studies have revealed significant abnormalities in EEG microstate in patients with depression, but these findings may be affected by medication. Therefore, how the EEG microstates abnormally change in patients with depression in the early stage and without the influence of medication has not been investigated so far. Methods: Resting-state EEG data and Hamilton Depression Rating Scale (HDRS) were collected from 34 first-episode drug-naïve adolescent with depression and 34 matched healthy controls. EEG microstate analysis was applied and nonlinear characteristics of EEG microstate sequences were studied by sample entropy and Lempel-Ziv complexity (LZC). The microstate temporal parameters and complexity were tried to train a SVM for classification of patients with depression. Results: Four typical EEG microstate topographies were obtained in both groups, but microstate C topography was significantly abnormal in depression patients. The duration of microstate B, C, D and the occurrence and coverage of microstate B significantly increased, the occurrence and coverage of microstate A, C reduced significantly in depression group. Sample entropy and LZC in the depression group were abnormally increased and were negatively correlated with HDRS. When the combination of EEG microstate temporal parameters and complexity of microstate sequence was used to classify patients with depression from healthy controls, a classification accuracy of 90.9% was obtained. Conclusion: Abnormal EEG microstate has appeared in early depression, reflecting an underlying abnormality in configuring neural resources and transitions between distinct brain network states. EEG microstate can be used as a neurophysiological biomarker for early auxiliary diagnosis of depression.

The development of tissue-engineered blood vessels provides a new source of donors for coronary artery bypass grafting and peripheral blood vessel transplantation. Fibrin fiber has good biocompatibility and is an ideal tissue engineering vascular scaffold, but its mechanical property needs improvement. Methods: We mixed polyurethane (PU) and fibrin to prepare the PU/fibrin vascular scaffolds by using electrospinning technology in order to enhance the mechanical properties of fibrin scaffold. We investigated the morphological, mechanical strength, hydrophilicity, degradation, blood and cell compatibility of PU/fibrin (0:100), PU/fibrin (5:95), PU/fibrin (15:85) and PU/fibrin (25:75) vascular scaffolds. Based on the results in vitro, PU/fibrin (15:85) was selected for transplantation in vivo to repair vascular defects, and the extracellular matrix formation, vascular remodeling, and immune response were evaluated. Results: The results indicated that the fiber diameter of the PU/fibrin (15:85) scaffold was about 712nm. With the increase of PU content, the mechanical strength of the composite scaffolds increased, however, the degradation rate decreased gradually. The PU/fibrin scaffold showed good hydrophilicity and hemocompatibility. PU/fibrin (15:85) vascular scaffold could promote the adhesion and proliferation of mesenchymal stromal cells (MSCs). Quantitative RT-PCR experimental results showed that the expression of collagen, survivin and vimentin genes in PU/fibrin (15:85) was higher than that in PU/fibrin (25:75). The results in vivo indicated the mechanical properties and compliance of PU/fibrin grafts could meet clinical requirements and the proportion of thrombosis or occlusion was significantly lower. The graft showed strong vasomotor response, and the smooth muscle cells, endothelial cells, and ECM deposition of the neoartery were comparable to that of native artery after 3 months. At 3 months, the amount of macrophages in PU/fibrin grafts was significantly lower, and the secretion of pro-inflammatory and anti-inflammatory cytokines decreased. Conclusion: PU/fibrin (15:85) vascular scaffolds had great potential to be used as smalldiameter tissue engineering blood vessels.

Novel LSD1 inhibitors with potential activity are designed using a series of computer-aided drug design methods.