Neurosurgical robots in China: State of the art and future prospect.

Neurosurgical robots have developed for decades and can effectively assist surgeons to carry out a variety of surgical operations, such as biopsy, stereo-electroencephalography (SEEG), deep brain stimulation (DBS), and so forth. In recent years, neurosurgical robots in China have developed rapidly. This article will focus on several key skills in neurosurgical robots, such as medical imaging systems, automatic manipulator, lesion localization techniques, multimodal image fusion technology, registration method, and vascular imaging technology; introduce the clinical application of neurosurgical robots in China, and look forward to the potential improvement points in the future based on our experience and research in the field.

The NONRATT023402.2/rno-miR-3065-5p/NGFR axis affects levodopa-induced dyskinesia in a rat model of Parkinson's disease.

Levodopa-induced dyskinesia (LID) is a common motor complication in Parkinson's disease. However, few studies have focused on the pathogenesis of LID at the transcriptional level. NONRATT023402.2, a long non-coding RNA (lncRNA) that may be related to LID was discovered in our previous study and characterized in rat models of LID. In the present study, NONRATT023402.2 was overexpressed by injection of adeno-associated virus (AAV) in striatum of LID rats, and 48 potential target genes, including nerve growth factor receptor (NGFR) were screened using next-generation sequencing and target gene predictions. The NONRATT023402.2/rno-miR-3065-5p/NGFR axis was verified using a dual luciferase reporter gene. Overexpression of NONRATT023402.2 significantly increased the abnormal involuntary movements (AIM) score of LID rats, activated the PI3K/Akt signaling pathway, and up-regulated c-Fos in the striatum. NGFR knockdown by injection of ShNGFR-AAV into the striatum of LID rats resulted in a significant decrease in the PI3K/Akt signaling pathway and c-Fos expression. The AIM score of LID rats was positively correlated with the expressions of NONRATT023402.2 and NGFR. A dual luciferase reporter assay showed that c-Fos, as a transcription factor, bound to the NONRATT023402.2 promoter and activated its expression. Together, the results showed that NONRATT023402.2 regulated NGFR expression via a competing endogenous RNA mechanism, which then activated the PI3K/Akt pathway and promoted c-Fos expression. This suggested that c-Fos acted as a transcription factor to activate NONRATT023402.2 expression, and form a positive feedback regulation loop in LID rats, thus, aggravating LID symptoms. NONRATT023402.2 is therefore a possible novel therapeutic target for LID.

Astrocyte-derived SerpinA3N promotes neuroinflammation and epileptic seizures by activating the NF-κB signaling pathway in mice with temporal lobe epilepsy.

Impaired activation and regulation of the extinction of inflammatory cells and molecules in injured neuronal tissues are key factors in the development of epilepsy. SerpinA3N is mainly associated with the acute phase response and inflammatory response. In our current study, transcriptomics analysis, proteomics analysis, and Western blotting showed that the expression level of Serpin clade A member 3N (SerpinA3N) is significantly increased in the hippocampus of mice with kainic acid (KA)-induced temporal lobe epilepsy, and this molecule is mainly expressed in astrocytes. Notably, in vivo studies using gain- and loss-of-function approaches revealed that SerpinA3N in astrocytes promoted the release of proinflammatory factors and aggravated seizures. Mechanistically, RNA sequencing and Western blotting showed that SerpinA3N promoted KA-induced neuroinflammation by activating the NF-κB signaling pathway. In addition, co-immunoprecipitation revealed that SerpinA3N interacts with ryanodine receptor type 2 (RYR2) and promotes RYR2 phosphorylation. Overall, our study reveals a novel SerpinA3N-mediated mechanism in seizure-induced neuroinflammation and provides a new target for developing neuroinflammation-based strategies to reduce seizure-induced brain injury.

Identification of Cuproptosis Clusters and Integrative Analyses in Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD.

Design and Implementation of Personalized Push Service Based on Feature Extraction and Pattern Recognition.

Personalized push service is one of the more popular research and application fields, which has received more and more attention. Its application prospects are also more and more extensive. This research mainly designs and implements personalized push services through feature extraction and pattern recognition. In this study, the Chinese texts of user-visited pages are classified according to keywords, so as to obtain the user's interest characteristic data. Then, according to the frequency of each feature category, the weight of the user's interest feature is calculated, and the user's interest field is predicted and identified. After that, resources that match the user's interest field are pushed to it. In order to verify the effectiveness of the improved model, this study carried out experiments and comparisons on the precision rate, recall rate, and comprehensive classification rate of the original model and the improved model on the implemented personalized push service system. In the research, the error between the interest results under each interest topic in the test set and the results obtained by the statistical analysis of the training set is within a reasonable range, the maximum of which is about 5%. The accuracy of interest degree prediction in different scenarios can reach more than 90%, which directly confirms the good applicability and effectiveness of the analysis and calculation method and the constructed model for user interest in this study. The personalized push service framework proposed in this study has good application value in the field of time-sensitive information services.

Design, Synthesis, Biological Evaluation, and Molecular Modeling of 2-Difluoromethylbenzimidazole Derivatives as Potential PI3Kα Inhibitors.

PI3Kα is one of the potential targets for novel anticancer drugs. In this study, a series of 2-difluoromethylbenzimidazole derivatives were studied based on the combination of molecular modeling techniques 3D-QSAR, molecular docking, and molecular dynamics. The results showed that the best comparative molecular field analysis (CoMFA) model had q2 = 0.797 and r2 = 0.996 and the best comparative molecular similarity indices analysis (CoMSIA) model had q2 = 0.567 and r2 = 0.960. It was indicated that these 3D-QSAR models have good verification and excellent prediction capabilities. The binding mode of the compound 29 and 4YKN was explored using molecular docking and a molecular dynamics simulation. Ultimately, five new PI3Kα inhibitors were designed and screened by these models. Then, two of them (86, 87) were selected to be synthesized and biologically evaluated, with a satisfying result (22.8 nM for 86 and 33.6 nM for 87).

A novel pyroptosis-related gene signature predicts the prognosis of glioma through immune infiltration.

BACKGROUND: Glioma is the most common primary intracranial tumour and has a very poor prognosis. Pyroptosis, also known as inflammatory necrosis, is a type of programmed cell death that was discovered in recent years. The expression and role of pyroptosis-related genes in gliomas are still unclear. METHODS: In this study, we analysed the RNA-seq and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) database and Chinese Glioma Genome Atlas (CGGA) database. To investigate the prognosis and immune microenvironment of pyroptosis-related genes in gliomas, we constructed a risk model based on the TCGA cohort. The patients in the CGGA cohort were used as the validation cohort. RESULTS: In this study, we identified 34 pyroptosis-related differentially expressed genes (DEGs) in glioma. By clustering these DEGs, all glioma cases can be divided into two clusters. Survival analysis showed that the overall survival time of Cluster 1 was significantly higher than that of Cluster 2. Using the TCGA cohort as the training set, a 10-gene risk model was constructed through univariate Cox regression analysis and LASSO Cox regression analysis. According to the risk score, gliomas were divided into high-risk and low-risk groups. Survival analysis showed that the low-risk group had a longer survival time than the high-risk group. The above results were verified in the CGGA validation cohort. To verify that the risk model was independent of other clinical features, the distribution and the Kaplan-Meier survival curves associated with risk scores were performed. Combined with the characteristics of the clinical cases, the risk score was found to be an independent factor predicting the overall survival of patients with glioma. The analysis of single sample Gene Set Enrichment Analysis (ssGSEA) showed that compared with the low-risk group, the high-risk group had immune cell and immune pathway activities that were significantly upregulated. CONCLUSION: We established 10 pyroptosis-related gene markers that can be used as independent clinical predictors and provide a potential mechanism for the treatment of glioma.

Transcriptome analysis revealed CENPF associated with glioma prognosis.

Gliomas are common malignant tumors of the central nervous system. Despite the surgical resection and postoperative radiotherapy and chemotherapy, the prognosis of glioma remains poor. Therefore, it is important to reveal the molecular mechanisms that promotes glioma progression. Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to identify 428 differentially expressed genes (DEGs) and a core module from three microarray datasets. Heat maps were drawn based on DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database. The core module was significantly involved in several KEGG pathways, such as "cell cycle", "viral carcinogenesis", "progesterone-mediated oocyte maturation", "p53 signaling pathway". The protein-protein interaction (PPI) networks and modules were built using the STRING database and the MCODE plugin, respectively, which were visualized using Cytoscape software. Identification of hub genes in the core module using the CytoHubba plugin. The top modular genes AURKA, CDC20, CDK1, CENPF, and TOP2A were associated with glioma development and prognosis. In the Human Protein Atlas (HPA) database, CDC20, CENPF and TOP2A have significant protein expression. Univariate and multivariate cox regression analysis showed that only CENPF had independent influencing factors in the CGGA database. GSEA analysis found that CENPF was significantly enriched in the cell cycle, P53 signaling pathway, MAPK signaling pathway, DNA replication, spliceosome, ubiquitin-mediated proteolysis, focal adhesion, pathway in cancer, glioma, which was highly consistent with previous studies. Our study revealed a core module that was highly correlated with glioma development. The key gene CENPF and signaling pathways were identified through a series of bioinformatics analysis. CENPF was identified as a candidate biomarker molecule.

The dual roles of autophagy in gliomagenesis and clinical therapy strategies based on autophagic regulation mechanisms.

Autophagy, a self-digestion intracellular catabolic process, plays a crucial role in cellular homeostasis under conditions of starvation, oxidative stress and genotoxic stress. The capability of maintaining homeostasis contributes to preventing malignant behavior in normal cells. Many studies have provided compelling evidence that autophagy is involved in brain tumor recurrence and chemotherapy and radiotherapy resistance. Gliomas, as the primary central nervous system (CNS) tumors, are characterized by rapid, aggressive growth and recurrence and have a poor prognosis and bleak outlook even with modern multimodality strategies involving maximal surgical resection, radiotherapy and alkylating agent-based chemotherapy. Autophagy-associated signaling pathways, such as the extracellular signal-regulated kinase1/2 (ERK1/2) pathway, class I phosphatidylinositol 3-phosphate kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway and nuclear factor kappa-B (NF-κB) pathway, act as tumor suppressors or protect tumor cells against chemotherapy/radiotherapy-induced cytotoxicity in gliomagenesis. Through these pathways, both lethal autophagy and protective autophagy play crucial roles in tumor initiation, chemoresistance and glioma stem cell differentiation. Moreover, lethal autophagy and protective autophagy have been identified as novel therapeutic targets in glioma according to the mechanisms described above. Here, we discuss the multiple impacts of the autophagic response on distinct phases of gliomagenesis and the advanced progress of therapies based on this concept.

Upregulated Expression of CUX1 Correlates with Poor Prognosis in Glioma Patients: a Bioinformatic Analysis.

Cut-like homeobox-1 (CUX1) is expressed in the upper layer of the cortex and participates in DNA replication, cell cycle control, and DNA repair. It has been shown to be involved in the proliferation of various types of solid tumors. The aims of this study were to explore the relationship between CUX1 expression and the prognosis of glioma by performing a series of functional experiments and bioinformatic analyses. Firstly, we found that CUX1 expression levels differed among patients with different grades of gliomas, and they were significantly correlated with the prognosis of glioma patients according to an analysis of data from a public database. qRT-PCR, western blotting, and immunohistochemical analysis of CUX1 were performed to demonstrate that the expression of CUX1 was positively correlated with the glioma WHO grade (P < 0.05) and several malignant clinical pathological parameters, including Ki67 and P53mut. In addition, the multivariate Cox regression and Kaplan-Meier curves showed that CUX1 expression exerted predictive value for overall survival. Finally, to further investigate the functions of CUX1, we identified CUX1-associated genes and, though GO/KEGG analysis, their associated biological functions and signaling pathways; the results suggested that the activity of CUX1 might be exerted via the JAK-STAT pathway or other key regulators of the cell cycle to promote proliferation, inflammation, and chemotherapy resistance in glioma. Taken together, these results indicate that CUX1 is a potential biomarker of malignancy and prognosis and may serve as a potential therapeutic target for glioma patients.