Sodium Octahydridotriborate as a Solid Electrolyte with Excellent Stability Against Sodium-Metal Anode.

Solid-state sodium metal batteries have been extensively investigated because of their potential to improve safety, cost-effectiveness, and energy density. The development of such batteries urgently required a solid-state electrolyte with fast Na-ion conduction and favorable interfacial compatibility. Herein, the progress on developing the NaB3H8 solid-state electrolytes is reported, which show a liquid-like ionic conductivity of 0.05 S cm-1 at 56 °C with an activation energy of 0.35 eV after an order-disorder phase transformation, matching or surpassing the best single-anion hydridoborate conductors investigated up to now. The steady polarization voltage and significantly decreased resistance are achieved in the symmetric Na/NaB3H8/Na cell, indicating the great electrochemical stability and favorable interfacial contact with the Na metal of NaB3H8. Furthermore, a Na/NaB3H8/TiS2 battery, the first high-rate (up to 1 C) solid-state sodium metal battery using the single-anion hydridoborate electrolyte, is demonstrated, which exhibits superior rate capability (168.2 mAh g-1 at 0.1 C and 141.2 mAh g-1 at 1 C) and long-term cycling stability (70.9% capacity retention at 1 C after 300 cycles) at 30 °C. This work may present a new possibility to solve the interfacial limitations and find a new group of solid-state electrolytes for high-performance sodium metal batteries.

Development and validation of an immune infiltration/tumor proliferation-related Notch3 nomogram for predicting survival in patients with primary glioblastoma.

Background: Notch receptors (Notch 1/2/3/4), the critical effectors of the Notch pathway, participate in the tumorigenesis and progression of many malignancies. However, the clinical roles of Notch receptors in primary glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alteration-related prognostic values of Notch receptors were determined in the GBM dataset from The Cancer Genome Atlas (TCGA). Two GBM datasets from TCGA and Chinese Glioma Genome Atlas (CGGA) were used to explore the differential expression between Notch receptors and IDH mutation status, and GBM subtypes. The biological functions of Notch Receptors were explored by Gene Ontology and KEGG analysis. The expression and prognostic significance of Notch receptors were determined in the TCGA and CGGA datasets and further validated in a clinical GBM cohort by immunostaining. A Notch3-based nomogram/predictive risk model was constructed in the TCGA dataset and validated in the CGGA dataset. The model performance was evaluated by receiver operating curves, calibration curves, and decision curve analyses. The Notch3-related phenotypes were analyzed via CancerSEA and TIMER. The proliferative role of Notch3 in GBM was validated in U251/U87 glioma cells by Western blot and immunostaining. Results: Notch receptors with genetic alterations were associated with poor survival of GBM patients. Notch receptors were all upregulated in GBM of TCGA and CGGA databases and closely related to the regulation of transcription, protein-lysine N-methyltransferase activity, lysine N-methyltransferase activity, and focal adhesion. Notch receptors were associated with Classical, Mesenchymal, and Proneural subtypes. Notch1 and Notch3 were closely correlated with IDH mutation status and G-CIMP subtype. Notch receptors displayed the differential expression at the protein level and Notch3 showed a prognostic significance in a clinical GBM cohort. Notch3 presented an independent prognostic role for primary GBM (IDH1 mutant/wildtype). A Notch3-based predictive risk model presented favorable accuracy, reliability, and net benefits for predicting the survival of GBM patients (IDH1 mutant/wildtype and IDH1 wildtype). Notch3 was closely related to immune infiltration (macrophages, CD4+ T cells, and dendritic cells) and tumor proliferation. Conclusion: Notch3-based nomogram served as a practical tool for anticipating the survival of GBM patients, which was related to immune-cell infiltration and tumor proliferation.

Development and validation of a predictive model in diagnosis and prognosis of primary glioblastoma patients based on Homeobox A family.

BACKGROUND: Homeobox A (HOXA) family is involved in the development of malignancies as either tumor suppressors or oncogenes. However, their roles in glioblastoma (GBM) and clinical significance have not been fully elucidated. METHODS: HOXA mutation and expressions in pan-cancers were investigated using GSCA and Oncomine, which in GBM were validated by cBioPortal, Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas (TCGA) datasets. Kaplan-Meier analyses were conducted to determine prognostic values of HOXAs at genetic and mRNA levels. Diagnostic roles of HOXAs in tumor classification were explored by GlioVis and R software. Independent prognostic HOXAs were identified using Cox survival analyses, the least absolute shrinkage and selection operator (LASSO) regression, quantitative real-time PCR, and immunohistochemical staining. A HOXAs-based nomogram survival prediction model was developed and evaluated using Kaplan-Meier analysis, time-dependent Area Under Curve, calibration plots, and Decision Curve Analysis in training and validation cohorts. RESULTS: HOXAs were highly mutated and overexpressed in pan-cancers, especially in CGGA and TCGA GBM datasets. Genetic alteration and mRNA expression of HOXAs were both found to be prognostic. Specific HOXAs could distinguish IDH mutation (HOXA1-7, HOXA9, HOXA13) and molecular GBM subtypes (HOXA1-2, HOXA9-11, HOXA13). HOXA1/2/3/10 were confirmed to be independent prognostic members, with high expressions validated in clinical GBM tissues. The HOXAs-based nomogram model exhibited good prediction performance and net benefits for patients in training and validation cohorts. CONCLUSION: HOXA family has diagnostic values, and the HOXAs-based nomogram model is effective in survival prediction, providing a novel approach to support the treatment of GBM patients.

Identification of CCL20 as a Key Biomarker of Inflammatory Responses in the Pathogenesis of Intracerebral Hemorrhage.

Inflammatory responses after intracerebral hemorrhage (ICH) contribute to severe secondary brain injury, leading to poor clinical outcomes. However, the responsible genes for effective anti-inflammation treatment in ICH remain poorly elucidated. The differentially expressed genes (DEGs) of human ICH were explored by online GEO2R. Go and KEGG were used to explore the biological function of DEGs. Protein-protein interactions (PPI) were built in the String database. Critical modules of PPI were identified by a molecular complex detection algorithm (MCODE). Cytohubba was used to determine the hub genes. The mRNA-miRNA interaction network was built in the miRWalk database. The rat ICH model was applied to validate the key genes. A total of 776 DEGs were identified in ICH. Go and KEGG analyses indicated that DEGs were mainly involved in neutrophil activation and the TNF signaling pathway. GSEA analysis presented that DEGs were significantly enriched in TNF signaling and inflammatory response. PPI network was constructed in the 48 differentially expressed inflammatory response-related genes. The critical module of the PPI network was constructed by 7 MCODE genes and functioned as the inflammatory response. The top 10 hub genes with the highest degrees were identified in the inflammatory response after ICH. CCL20 was confirmed as a key gene and mainly expressed in neurons in the rat ICH model. The regulatory network between CCL20 and miR-766 was built, and the miR-766 decrease was confirmed in a human ICH dataset. CCL20 is a key biomarker of inflammatory response after intracerebral hemorrhage, providing a potential target for inflammatory intervention in ICH.

Lactate-to-albumin ratio is associated with in-hospital mortality in patients with spontaneous subarachnoid hemorrhage and a nomogram model construction.

Introduction: Subarachnoid hemorrhage (SAH) is a severe hemorrhagic stroke with high mortality. However, there is a lack of clinical tools for predicting in-hospital mortality in clinical practice. LAR is a novel clinical marker that has demonstrated prognostic significance in a variety of diseases. Methods: Critically ill patients diagnosed and SAH with their data in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) were included in our study. Multivariate logistic regression was utilized to establish the nomogram. Results: A total of 244 patients with spontaneous SAH in the MIMIC-IV database were eligible for the study as a training set, and 83 patients in eICU-CRD were included for external validation. Data on clinical characteristics, laboratory parameters and outcomes were collected. Univariate and multivariate logistic regression analysis identified age (OR: 1.042, P-value: 0.003), LAR (OR: 2.592, P-value: 0.011), anion gap (OR: 1.134, P-value: 0.036) and APSIII (OR: 1.028, P-value: < 0.001) as independent predictors of in-hospital mortality and we developed a nomogram model based on these factors. The nomogram model incorporated with LAR, APSIII, age and anion gap demonstrated great discrimination and clinical utility both in the training set (accuracy: 77.5%, AUC: 0.811) and validation set (accuracy: 75.9%, AUC: 0.822). Conclusion: LAR is closely associated with increased in-hospital mortality of patients with spontaneous SAH, which could serve as a novel clinical marker. The nomogram model combined with LAR, APSIII, age, and anion gap presents good predictive performance and clinical practicability.

Chromobox 7/8 serve as independent indicators for glioblastoma via promoting proliferation and invasion of glioma cells.

Background: The chromobox family, a critical component of epigenetic regulators, participates in the tumorigenesis and progression of many malignancies. However, the roles of the CBX family members (CBXs) in glioblastoma (GBM) remain unclear. Methods: The mRNA expression of CBXs was analyzed in tissues and cell lines by Oncomine and Cancer Cell Line Encyclopedia (CCLE). The differential expression of CBXs at the mRNA level was explored in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases with the "beeswarm" R package. The protein expression of CBXs in GBM was further examined on Human Protein Atlas (HPA). The correlations between CBXs and IDH mutation and between CBXs and GBM subtypes were investigated in the TCGA portal and CGGA database with the "survminer" R package. The alteration of CBXs and their prognostic value were further determined via the cBioPortal and CGGA database with the "survival" R package. The univariate and multivariate analyses were performed to screen out the independent prognostic roles of CBXs in the CGGA database. Cytoscape was used to visualize the functions and related pathways of CBXs in GBM. U251 and U87 glioma cells with gene intervention were used to validate the role of CBX7/8 in tumor proliferation and invasion. Proliferation/invasion-related markers were conducted by Western blot and immunostaining. Results: CBXs presented significantly differential expressions in pan-cancers. CBX2/3/5/8 were upregulated, whereas CBX6/7 were downregulated at mRNA level in GBM of TCGA and CGGA databases. Similarly, high expression of CBX2/3/5 and low expression of CBX6/8 were further confirmed at the protein level in the HPA. CBX2/6/7 were positively correlated with IDH mutation and CBX1/2/4/5/8 were closely related to GBM subtypes. CBX7 and CBX8 presented the independent prognostic factors for GBM patient survival. GO and KEGG analyses indicated that CBXs were closely related to the histone H3-K36, PcG protein complex, ATPase, and Wnt pathway. The overexpression of CBX7 and underexpression of CBX8 significantly inhibited the proliferation and invasion of glioma cells in vivo and in vitro. Conclusion: Our results suggested that CBX7 and CBX8 served as independent prognostic indicators that promoted the proliferation and invasion of glioma cells, providing a promising strategy for diagnosing and treating GBM.