A novel immunogenic cell death signature for the prediction of prognosis and therapies in glioma.

Glioma is a primary cranial malignancy with high recurrence rate, poor prognosis and high mortality. However, the roles of immunogenic cell death (ICD) in glioma remain unclear. Twenty ICD genes were analyzed to be differentially expressed between glioma tissues and non-tumor tissues in 371 glioma patients from The Cancer Genome Atlas (TCGA). Patients were classified into three subgroups via unsupervised clustering. Interestingly, the features of cell-infiltrating from three clusters were matched with three immune phenotypes. An applied scoring system was built depending on the expression of hub ICD-related genes. Notably, the ICD-related score was linked with immune checkpoints and the prognosis of glioma patients. In addition, the applied risk model could be used for the prediction of the effect of chemotherapy and immunotherapy for glioma patients. Furthermore, MYD88 was identified to play key roles in the risk model for glioma patients. MYD88 was specifically expressed in malignant cells and validated to correlate with cell proliferation and invasion. Ligand-receptor pairs are determined as novel communications indicating between immunocytes and malignant cells. Therefore, our research established an ICD-related score to investigate the potential effect to chemotherapy and immunotherapy for glioma patients and indicated that MYD88 was a key role in this risk model.

Efficacy of Er:YAG Laser as a Debridement Method in Surgical Treatment for Peri-Implantitis: A Systematic Review.

PURPOSE: The present study systematically reviewed randomised controlled trials (RCT) to investigate the efficacy of Er:YAG laser (ERL) as a debridement method in surgical treatment of advanced peri-implantitis. MATERIALS AND METHODS: An electronic database search and a manual search were performed until March 2022. Outcome measures were clinical attachment level (CAL) gain, probing depth (PD) reduction, plaque index (PI) and bleeding on probing (BOP). The addressed PICO question was: Is ERL an effective debridement tool in the surgical treatment of advanced peri-implantitis? RESULTS: Five eligible randomised clinical trials (RCTs) were included in the qualitative analysis, one of which had unclear risk of bias. One study reported a statistically significant difference in terms of implant CAL gain and PD reduction in favour of the experimental group vs the control group, while four studies did not report any difference between the two groups. CONCLUSION: Due to methodological heterogeneity, such as non-standard control groups and laser parameters, this systematic review demonstrated inconclusive findings in terms of the efficacy of Er:YAG laser as a debridement method in surgical treatment of advanced peri-implantitis. The results of this review should be considered preliminary and further, well-designed studies with standardised comparators with laser parameters are warranted.

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis.

BACKGROUND: The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT. METHODS: Two human datasets (GSE19151 and GSE48000) were analyzed by the robust rank aggregation method. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were conducted for the DEGs. To explore potential correlations between gene sets and clinical features and to identify hub genes, we utilized weighted gene coexpression network analysis (WGCNA) to build gene coexpression networks incorporating the DEGs. Then, the levels of the hub genes were analyzed in the GSE datasets. Based on the expression of the hub genes, the possible pathways were explored by gene set enrichment analysis and gene set variation analysis. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis in the GEO database. RESULTS: In this study, we identified 54 upregulated and 10 downregulated genes that overlapped between normal and VT samples. After performing WGCNA, the magenta module was the module with the strongest negative correlation with the clinical characteristics. From the key module, FECH, GYPA, RPIA and XK were chosen for further validation. We found that these genes were upregulated in VT samples, and high expression levels were related to recurrent VT. Additionally, the four hub genes might be highly correlated with ribosomal and metabolic pathways. The ROC curves suggested a diagnostic value of the four genes for VT. CONCLUSIONS: These results indicated that FECH, GYPA, RPIA and XK could be used as promising biomarkers for the prognosis and prediction of VT.