Astrocyte plays important roles in the pathogenesis of ischemic stroke and reperfusion injury. They intensively participate in the energy metabolism of the brain, while their heterogeneity and function after ischemic stroke remain controversial. By employing single-cell sequencing of mice cortex at 12 h after transient middle cerebral artery occlusion (tMCAO) and comparing with the similar published datasets of 24h after tMCAO, we uncover the cellular phenotypes and dynamic change of astrocytes at the acute phase of ischemic stroke. In this study, we separately identified 3 major subtypes of astrocytes at the 12 h-tMCAO-system and 24 h-tMCAO-system, indicated the significant differences in the expression of genes and metabolic pathways in the astrocytes between the two time nodes after ischemic stroke, and detected the major change in the energy metabolism. These results provided a comprehensive understanding of the characteristic changes of astrocytes after ischemic stroke and explored the potential astrocytic targets for neuroprotection.

Background. In tumor progression and epigenetic regulation, long non-coding RNA (lncRNA) and necroptosis are crucial regulators. However, in glioma microenvironment, the role of necroptosis-related lncRNAs (NRLs) remains unknown. Method. In this study, the RNA-seq and clinical annotation of glioma patients were analyzed using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To investigate prognosis and tumor microenvironment of NRLs in gliomas, we conducted a prediction model based on the training cohort. The accuracy of the model was verified in the verification cohort. Results. A signature composed of 13 NRLs was identified, and all glioma patients were divided into two groups. We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status. The necroptosis-related lncRNA signature (NRLS) model was found to be an independent risk factor in multivariate Cox analysis. Immunosuppressive microenvironment was positively correlated with the high-risk group. Due to significantly different IC50 between risk groups, NRLS could be used as a guide for chemotherapeutic treatment. Further, the entire cohort was divided into two clusters depending on NRLs. Consensus clustering method and the risk scoring system were basically similar. Survival probability was higher in Cluster 2, while Cluster 1 has stronger immunologic infiltration. Conclusion. The predictive signature could be a prognostic factor independently and serve to detect the role of NRLs in glioma immunotherapy response.

The latest 2021 WHO classification redefines glioblastoma (GBM) as the hierarchical reporting standard by eliminating glioblastoma, IDH-mutant and only retaining the tumor entity of “glioblastoma, IDH-wild type.” Knowing that subclassification of tumors based on molecular features is supposed to facilitate the therapeutic choice and increase the response rate in cancer patients, it is necessary to carry out molecular classification of the newly defined GBM. Although differentiation trajectory inference based on single-cell sequencing (scRNA-seq) data holds great promise for identifying cell heterogeneity, it has not been used in the study of GBM molecular classification. Single-cell transcriptome sequencing data from 10 GBM samples were used to identify molecular classification based on differentiation trajectories. The expressions of identified features were validated by public bulk RNA-sequencing data. Clinical feasibility of the classification system was examined in tissue samples by immunohistochemical (IHC) staining and immunofluorescence, and their clinical significance was investigated in public cohorts and clinical samples with complete clinical follow-up information. By analyzing scRNA-seq data of 10 GBM samples, four differentiation trajectories from the glioblastoma stem cell-like (GSCL) cluster were identified, based on which malignant cells were classified into five characteristic subclusters. Each cluster exhibited different potential drug sensitivities, pathways, functions, and transcriptional modules. The classification model was further examined in TCGA and CGGA datasets. According to the different abundance of five characteristic cell clusters, the patients were classified into five groups which we named Ac-G, Class-G, Neo-G, Opc-G, and Undiff-G groups. It was found that the Undiff-G group exhibited the worst overall survival (OS) in both TCGA and CGGA cohorts. In addition, the classification model was verified by IHC staining in 137 GBM samples to further clarify the difference in OS between the five groups. Furthermore, the novel biomarkers of glioblastoma stem cells (GSCs) were also described. In summary, we identified five classifications of GBM and found that they exhibited distinct drug sensitivities and different prognoses, suggesting that the new grouping system may be able to provide important prognostic information and have certain guiding significance for the treatment of GBM, and identified the GSCL cluster in GBM tissues and described its characteristic program, which may help develop new potential therapeutic targets for GSCs in GBM.

The classification of microglial M1/M2 polarization in the acute phase of ischemic stroke remains controversial, which has limited further advances in neuroprotective strategy. To thoroughly assess the microglial phenotypes, we made the middle cerebral artery occlusion model in mice to simulate the acute pathological processes of ischemic stroke from normal conditions to acute cerebral ischemia and then to the early reperfusion period. The temporal changes in gene profiles, cell subtypes, and microglial function were comprehensively analyzed using single-cell RNA sequencing. We identified 37,614 microglial cells and divided them into eight distinct subpopulations. Mic_home, Mic_pre1, and Mic_pre2 subpopulations were three clusters mainly composed of cells from the control samples, in which Mic_home was a homeostatic subpopulation characterized by high expression of Hpgd and Tagap, and Mic_pre1 and Mic_pre2 were two clusters with preliminary inflammatory activation characteristics marked by P2ry13 and Wsb1 respectively. Mic_M1L1 and Mic_M1L2 subpopulations exhibited M1-like polarization manifested by the upregulation of inflammatory genes after ischemic stroke, while the intrinsic heterogeneity on the level of inflammatory responses and neurotrophic support properties was observed. Moreover, we identified three unique clusters of cells with low inflammation levels. Mic_np1, Mic_np2, and Mic_np3 were characterized by high expression of Arhgap45, Rgs10, and Pkm respectively. However, these cells did not show significant M2-like characteristics and their classic microglia function was also attenuated. These subpopulations exhibited higher activation of neuropeptide functional pathways. At last, we performed cell-cell communication analysis and identified major couplings contributing to the interaction between microglia and other cell populations. In summary, our study elucidated the temporal heterogeneity of microglia in the acute phase of ischemic stroke, which may facilitate the identification of effective neuroprotective targets to curb ischemic damage at an early stage.

Background Chronic subdural hematoma (CSDH) is a common disease that forms between the dura and arachnoid membranes of the brain. With the development of medications and surgery, significant progress has been made in the diagnosis and treatment of CSDH. However, there is no comprehensive analysis available on CSDH-related studies published in the literature. This study aimed to collect and analyze CSDH-related studies published since the twenty-first century using bibliometric analysis and to summarize the current status of research in this field for the sake of providing systematic data for further study of CSDH. Methods CSDH-related studies were searched in the Web of Science Core Collection (WoSCC) database using the Medical Subject Heading (MeSH) term ‘chronic subdural hematoma’. Data analysis and visualization were performed by R and CiteSpace software. Results This study retrieved 1424 CSDH-related articles published since the beginning of the twenty-first century. There was a general increase in both the number of published articles and the mean number of citations. The authors, institutions and journals that contributed the most to the field of CSDH were Jianning Zhang, Tianjin Medical University, and world neurosurgery, respectively. The reference co-citation network identified 13 clusters with significant modularity Q scores and silhouette scores (Q = 0.7124, S = 0.8536). The major research categories were (1) evolution of the therapeutic method and (2) the etiology and pathology of CSDH. Keyword analysis revealed that ‘middle meningeal artery embolization’ was the latest burst keyword. Conclusions This study identified the most influential countries, authors, institutions and journals contributing to CSDH research and discussed the hotspots and the latest subjects of CSDH research.