No abstract

Subarachnoid hemorrhage (SAH) is a devastating form of stroke, which poses a series of intractable challenges to clinical practice. Imbalance of mitochondrial homeostasis has been thought to be the crucial pathomechanism in early brain injury (EBI) cascade after SAH. Irisin, a protein related to metabolism and mitochondrial homeostasis, has been reported to play pivotal roles in post-stroke neuroprotection. However, whether this myokine can exert neuroprotection effects after SAH remains unknown. In the present study, we explored the protective effects of irisin and the underlying mechanisms related to mitochondrial biogenesis in a SAH animal model. Endovascular perforation was used to induce SAH, and recombinant irisin was administered intracerebroventricularly. Neurobehavioral assessments, TdT-UTP nick end labeling (TUNEL) staining, dihydroethidium (DHE) staining, immunofluorescence, western blot, and transmission electron microscopy (TEM) were performed for post-SAH assessments. We demonstrated that irisin treatment improved neurobehavioral scores, reduced neuronal apoptosis, and alleviated oxidative stress in EBI after SAH. More importantly, the administration of exogenous irisin conserved the mitochondrial morphology and promoted mitochondrial biogenesis. The protective effects of irisin were partially reversed by the mitochondrial uncoupling protein-2 (UCP-2) inhibitor. Taken together, irisin may have neuroprotective effects against SAH via improving the mitochondrial biogenesis, at least in part, through UCP-2 related targets.

The present study aimed to identify differentially regulated genes between the peritumoral brain zone (PBZ) and tumor core (TC) of glioblastoma (GBM), to elucidate the underlying molecular mechanisms and provide a target for the treatment of tumors. The GSE13276 and GSE116520 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) for the PBZ and TC were obtained using the GEO2R tool. The bioinformatics and evolutionary genomics online tool Venn was used to identify common DEGs between the two datasets. The Database for Annotation, Visualization, and Integrated Discovery online tool was used to analyze enriched pathways of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The Search Tool for the Retrieval of Interacting Genes/Proteins online tool was used to construct a protein-protein interaction (PPI) network of DEGs. Hub genes were identified using Cytohubba, a plug-in for Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was utilized to perform survival analysis. In total, 75 DEGs, including 12 upregulated and 63 downregulated genes, were identified. In the GO term analysis, these DEGs were mainly enriched in ‘regulation of angiogenesis’ and ‘central nervous system development’. Furthermore, in the KEGG pathway analysis, the DEGs were mainly enriched in ‘bladder cancer’ and ‘endocytosis’. When filtering the results of the PPI network analysis using Cytohubba, a total of 10 hub genes, including proteolipid protein 1, myelin associated oligodendrocyte basic protein, contactin 2, myelin oligodendrocyte glycoprotein, myelin basic protein, myelin associated glycoprotein, SRY-box transcription factor 10, C-X-C motif chemokine ligand 8 (CXCL8), vascular endothelial growth factor A (VEGFA) and plasmolipin, were identified. These hub genes were further subjected to GO term and KEGG pathway analysis, and were revealed to be enriched in ‘central nervous system development’, ‘bladder cancer’ and ‘rheumatoid arthritis’. These hub genes were used to perform survival analysis using the GEPIA database, and it was determined that VEGFA and CXCL8 were significantly associated with a reduction in the overall survival of patients with GBM. In conclusion, the results suggest that the recurrence of GBM is associated with high gene expression levels VEGFA and CXCL8, and the development of the central nervous system.

Neuroinflammation can be caused by various factors in early brain injury after subarachnoid hemorrhage (SAH). One of the most important features of this process is M1 microglial activation. In turn, the TLR4/NF-κB pathway plays an essential role in activating M1 phenotypic microglia. Biglycan, a small leucine-rich proteoglycan, functions as an endogenous ligand of TLR4 and TLR2 in macrophages. However, the underlying mechanisms associated with microglial activation in stroke pathogenesis are poorly understood. Here, we aimed to identify the role of biglycan in neuroinflammation following SAH. In our study, SAH was induced by endovascular perforation in young male C57BL/6J mice. Lentiviral vector was administered intracerebroventricularly to knock down Biglycan. Post-SAH assessments included neurobehavioral tests, immunofluorescence, western blot, qRT-PCR, Co-IP, flow cytometry, and ELISA. The biglycan level was markedly elevated following SAH in vivo. Of particularly note, knockdown of biglycan significantly improved neurological outcomes.TLR4 was bound with soluble biglycan in vitro. In addition, biglycan down-regulation suppressed the expression of phosphorylated-NF-κB p65 (p-NF-κB) and inducible nitric oxide synthase (iNOS), as well as the cytokine (TNF-α, IL-1β, and IL-6) production in vivo and in vitro. Moreover, we detected a decreased expression of CD16/32 and CD86, M1 markers when biglycan was inhibited in vitro. Our work suggests that biglycan can induce neuroinflammation by promoting M1 microglial activation at least in part through TLR4/NF-κB signaling pathway after experimental SAH. Targeting biglycan may be a promising strategy for the clinical management of SAH. K E Y W O R D Sbiglycan, early brain injury, microglia, neuroinflammation, subarachnoid hemorrhage, TLR4 | 369 XIE Et al.

Glioblastoma accounts for 45.2% of central nervous system tumors. Despite the availability of multiple treatments (e.g., surgery, radiotherapy, chemotherapy, biological therapy, immunotherapy, and electric field therapy), glioblastoma has a poor prognosis, with a 5-year survival rate of approximately 5%. The pathogenesis and prognostic markers of this cancer are currently unclear. To this end, this study aimed to explore the pathogenesis of glioblastoma and identify potential prognostic markers. We used data from the GEO and TCGA databases and identified five genes (ITGA5, MMP9, PTPRN, PTX3, and STX1A) that could affect the survival rate of glioblastoma patients and that were differentially expressed between glioblastoma patients and non-tumors groups. Based on a variety of bioinformatics tools for reverse prediction of target genes associated with the prognosis of GBM, a ceRNA network of messenger RNA (STX1A, PTX3, MMP9)-microRNA (miR-9-5p)-long non-coding RNA (CRNDE) was constructed. Finally, we identified five potential therapeutic drugs (bacitracin, hecogenin, clemizole, chrysin, and gibberellic acid) that may be effective treatments for glioblastoma.