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Background: Glioblastoma (GBM) is the most common and malignant type of brain tumor. A large number of studies have shown that the immunotherapy of tumors is effective, but the immunotherapy effect of GBM is not poor. Thus, further research on the immune-related hub genes of GBM is extremely important. Methods: The GBM highly correlated gene clusters were screened out by differential expression, mutation analysis, and weighted gene co-expression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and proportional hazards model (COX) regressions were implemented to construct prognostic risk models. Survival, receiver operating characteristic (ROC) curve, and compound difference analyses of tumor mutation burden were used to further verify the prognostic risk model. Then, we predicted GBM patient responses to immunotherapy using the ESTIMATE algorithm, GSEA, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Results: A total of 834 immune-related differentially expressed genes (DEGs) were identified. The five hub genes (STAT3, SEMA4F, GREM2, MDK, and SREBF1) were identified as the prognostic risk model (PRM) screened out by WGCNA and LASSO analysis of DEGs. In addition, the PRM has a significant positive correlation with immune cell infiltration of the tumor microenvironment (TME) and expression of critical immune checkpoints, indicating that the poor prognosis of patients is due to TIDE. Conclusion: We constructed the PRM composed of five hub genes, which provided a new strategy for developing tumor immunotherapy.
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OBJECTIVE: The aim of this study was to investigate auditory cortical development using mismatch negativity (MMN) in prelingual severe-to-profound hearing-impaired children from the stage of cochlear implant (CI) power-up to 6 months after power-up. METHOD: Eighteen children were recruited and examined at the stage of CI initial power-up (M0), as well as several follow-up periods, that is, 1 month (M1), 3 months (M3), and 6 months (M6) after CI power-up. The MMN responses were measured using a 128-Channel Dense Array EEG System. The group average and individual MMN analysis were used to investigate the longitudinal changes of the MMN characteristics. The relationship between MMN characteristics and scores of categories of auditory performance (CAP) was also investigated. RESULTS: Although the MMN incidence was much lower at the periods of M0 and M1, significantly higher MMN incidence was found in M3 and M6. The MMN latencies decreased significantly from M3 to M6, but no significant difference in the amplitudes was found between these periods. There was a negative correlation between the increment of CAP scores and decrement of MMN latency from M3 to M6. CONCLUSION: MMN incidence increment and latency decrement are likely to be the objective and noninvasive indicators for evaluating auditory central development at an early stage in children after cochlear implantation. Moreover, the latency decrement from M3 to M6 correlated significantly with the increment of the CAP scores, indicating a fast maturation period, which might be a key period for auditory rehabilitation.