PurposeThis study focused on identification of long non-coding RNAs (lncRNAs) for prognosis prediction of glioblastoma (GBM) through weighted gene co-expression network analysis (WGCNA) and L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model.Materials and methodsWGCNA was performed based on RNA expression profiles of GBM from Chinese Glioma Genome Atlas (CGGA), National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), and the European Bioinformatics Institute ArrayExpress for the identification of GBM-related modules. Subsequently, prognostic lncRNAs were determined using LASSO Cox PH model, followed by constructing a risk scoring model based on these lncRNAs. The risk score was used to divide patients into high- and low-risk groups. Difference in survival between groups was analyzed using Kaplan–Meier survival analysis. IncRNA-mRNA networks were built for the prognostic lncRNAs, followed by pathway enrichment analysis for these networks.ResultsThis study identified eight preserved GBM-related modules, including 188 lncRNAs. Consequently, C20orf166-AS1, LINC00645, LBX2-AS1, LINC00565, LINC00641, and PRRT3-AS1 were identified by LASSO Cox PH model. A risk scoring model based on the lncRNAs was constructed that could divide patients into different risk groups with significantly different survival rates. Prognostic value of this six-lncRNA signature was validated in two independent sets. C20orf166-AS1 was associated with antigen processing and presentation and cell adhesion molecule pathways, involving nine common genes. LBX2-AS1, LINC00641, PRRT3-AS1, and LINC00565 were related to focal adhesion, extracellular matrix receptor interaction, and mitogen-activated protein kinase signaling pathways, which shared 12 common genes.ConclusionThis prognostic six-lncRNA signature may improve prognosis prediction of GBM. This study reveals many pathways and genes involved in the mechanisms behind these lncRNAs.

Patients with diabetes mellitus are easy to experience diabetic encephalopathy (DE) and other cognition dysfunction, whereas the neural alterations in developing this disease are unknown yet. Chrysophanol (CHR) is one of traditional Chinese medicine which was reported to show protective effects in cognition dysfunction and inflammatory in previously studies. In this current study, whether CHR protects learning and memory dysfunctions induced by diabetes disease or not and underlying mechanisms were studied. DE model was induced by streptozotocin (STZ, i.p.) in ICR mice. CHR was administrated 3 days after STZ treated mice which was confirmed with diabetes for consecutive 6 days. Learning and memory function was tested by Morris water maze after the CHR injection. The morphology of neuronal cells in hippocampus CA3 region was stained by HE-staining. ELISA and Western blot assay were used to determine the levels of pro-inflammation cytokines (IL-1β, IL-4, IL-6, TNF-α) in hippocampus. Here, we demonstrated that mice harboring diabetes mellitus induced by STZ exhibit high blood glucose, learning and memory deficits detected by Morris water maze behavior tests. Application with CHR right after developing diabetes disease rescues partial blood sugar increasing, learning and memory deficits. The data also indicated that the death rate of neurons and the number of astrocytes in hippocampus CA3 region was significantly improved in diabetic mice. Moreover, the underlying mechanisms of CHR's protective effect are likely associated with anti-inflammation by downregulating the expression of pro-inflammation cytokines (IL-1β, IL-4, IL-6, TNF-α) in hippocampus and inhibiting the over-activation of astrocytes in hippocampus CA3 region. Therefore, application with CHR contributes to the learning and memory deficits induced by diabetes disease via inhibitory expressions of inflammatory in hippocampus region.

The present study aimed to develop a pathway-based prognosis prediction model for glioblastoma (GBM). Univariate and multivariate Cox regression analysis were used to identify prognosis-related genes and clinical factors using mRNA-seq data of GBM samples from The Cancer Genome Atlas (TCGA) database. The expression matrix of prognosis-related genes was transformed into pathway deregulation score (PDS) based on the Gene Set Enrichment Analysis (GSEA) repository using Pathifier software. With PDS scores as input, L1-penalized estimation-based Cox-proportional hazards (PH) model was used to identify prognostic pathways. Consequently, a prognosis prediction model based on these prognostic pathways was constructed for classifying patients in the TCGA set or each of the three validation sets into two risk groups. The survival difference between these risk groups was then analyzed using Kaplan-Meier survival analysis and log-rank test. In addition, a gene-based prognostic model was constructed using the Cox-PH model. The model of prognostic pathway combined with clinical factors was also evaluated. In total, 148 genes were discovered to be associated with prognosis. The Cox-PH model identified 13 prognostic pathways. Subsequently, a prognostic model based on the 13 pathways was constructed, and was demonstrated to successfully differentiate overall survival in the TCGA set and in three independent sets. However, the gene-based prognosis model was validated in only two of the three independent sets. Furthermore, the pathway+clinic factor-based model exhibited better predictive results compared with the pathway-based model. In conclusion, the present study suggests a promising prognosis prediction model of 13 pathways for GBM, which may be superior to the gene-level information-based prognostic model.

Background: Borneol is the processed item from resin of Dryobalanops aromatica Gaertn. f. It can enhance the activity of antioxidant enzymes in brain tissue and reduce inflammatory response by improving the energy metabolism of ischemic brain regions, and thereby reduces brain tissue damage. The objective of this paper was to study the anti-cerebral ischemia effect of borneol and its mechanism. Materials and Methods:The anti-cerebral ischemia effect of borneol was studied by ligation of bilateral common carotid arteries (CCA), and vagus nerves in mice and the acute cerebral ischemia-reperfusion experiment in rats.Results: Compared with the blank and solvent control groups, the borneol low-; medium-; and high-dose groups can significantly prolong the gasping time of mice after decapitation, and extend the survival time of mice after ligation of bilateral CCA, and vagus nerves.Conclusion: Compared with the Xueshuantong injection group, the prolongation of survival time of mice after ligation of bilateral CCA, and vagus nerves was more apparent in the high-dose borneol experimental group; each experimental group can significantly reduce the number of leukocyte infiltration, the number of ICAM-1-positive vessels, as well as the number of TNF-α-positive cells. Conclusion:Borneol has an anti-cerebral ischemia effect.

RESULTSThe mean serum visfatin level of the patients in Group B was higher than that in Group A (75.5 ± 77.80 ng/mL vs.8.6 ± 4.69 ng/mL; p < 0.05) and the level was higher in patients from Group B2 than those from Group B1 (89.0 ± 80.68 ng/mL vs. 50.4 ± 72.44 ng/mL; p < 0.05). Multivariate regression analysis showed that CCA-IMT values were not significantly associated with visfatin levels. However, logistic regression analysis showed that serum visfatin was an independent risk factor for atherosclerosis (odds ratio 37.80; p = 0.004).CONCLUSION Serum visfatin may be an independent risk factor for cerebral infarction, as high serum visfatin levels are positively associated with the underlying pathogenic mechanisms of ischaemic cerebrovascular disease.