Preso enhances mGluR1-mediated excitotoxicity by modulating the phosphorylation of mGluR1-Homer1 complex and facilitating an ER stress after traumatic brain injury.

Glutamate receptor (GluR)-mediated excitotoxicity is an important mechanism causing delayed neuronal injury after traumatic brain injury (TBI). Preso, as a core scaffolding protein of postsynaptic density (PSD), is considered an important regulator during excitotoxicity and TBI and combines with glutamate receptors to form functional units for excitatory glutamatergic neurotransmission, and elucidating the mechanisms of these functional units will provide new targets for the treatment of TBI. As a multidomain scaffolding protein, Preso directly interacts with metabotropic GluR (mGluR) and another scaffold protein, Homer. Because the mGluR-Homer complex plays a crucial role in TBI, modulation of this complex by Preso may be an important mechanism affecting the excitotoxic damage to neurons after TBI. Here, we demonstrate that Preso facilitates the interaction between metabotropic mGluR1 and Homer1 to activate mGluR1 signaling and cause excitotoxic neuronal injury and endoplasmic reticulum (ER) stress after TBI. The regulatory effect of Preso on the mGluR1-Homer1 complex is dependent on the direct association between Preso and this complex and also involves the phosphorylation of the interactive binding sites of mGluR1 and Homer1 by Preso. Further studies confirmed that Preso, as an adaptor of cyclin-dependent kinase 5 (CDK5), promotes the phosphorylation of the Homer1-binding site on mGluR1 by CDK5 and thereby enhances the interaction between mGluR1 and Homer1. Preso can also promote the formation of the mGluR1-Homer1 complex by inhibiting the phosphorylation of the Homer1 hinge region by Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα). Based on these molecular mechanisms, we designed several blocking peptides targeting the interaction between Preso and the mGluR1-Homer1 complex and found that directly disrupting the association between mGluR1 and scaffolding proteins significantly promotes the recovery of motor function after TBI.

Highly-Efficient and Robust Zn Anodes Enabled by Sub-1-µm Zincophilic CrN Coatings.

For exploring advanced Zn-ion batteries (ZIBs) with long lifespan and high Coulombic efficiency (CE), the critically important point is to limit the undesired Zn dendrite and parasitic reactions. Among the coating for electrode is a promising strategy, relying on the trade-off between its thickness and stability to achieve the ultra-stable Zn anodes in ZIBs. Herein, a submicron-thick (≈0.4 µm) zincophilic CrN coatings are fabricated by a facile and industry-compatible magnetron sputtering approach. It is exhilarating that the ultrathin and dense CrN coatings with strong adsorption ability for Zn2+ exhibit an impressive lifespan up to 3700 h with ≈100% CE at 1 mA cm-2. Along with the experiments and theoretical calculations, it is verified that the introduced CrN coatings cannot only effectively suppress the dendrite growth and notorious parasitic reactions, but also allow the uniform Zn deposition due to the reduced nucleation energy. Moreover, the as-assembled Zn@CrN‖MnO2 full cell delivers a high specific capacity of 171.1 mAh g-1 after 1000 cycles at 1 A g-1, much better than that of Zn‖MnO2 analog (97.8 mAh g-1). This work provides a facile strategy for scalable fabrication of ultrathin zincophilic coating to push forward the practical applications of ZIBs.

Identification of INSRR as an immune-related gene in the tumor microenvironment of glioblastoma by integrated bioinformatics analysis.

Gliomas are the most common malignant tumors in the central nervous system. The tumor microenvironment (TME) plays a crucial role in tumor proliferation, invasion, angiogenesis, and immune escape. However, little is known about TME in gliomas. The purpose of this study was to explore the biomarkers associated with TME in glioblastoma (GBM) to predict immunotherapy effectiveness and prognosis in patients. Based on RNA-seq transcriptome data and clinical features of 1222 samples (113 normal samples and 1109 tumor samples) in The Cancer Genome Atlas (TCGA) database, the ImmuneScore, StromalScore, and ESTIMATEScore were calculated by ESTIMATE algorithm. The differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were determined in the TCGA GBM cohort. Furthermore, gene set enrichment analysis (GSEA) was used to investigate the enrichment pathways of INSRR genes with abnormal expression. The proportion of tumor-infiltrating immune cells (TIICs) was evaluated by CIBERSORT. Frequent mutations of TP53, EGFR, and PTEN occurred in high and low immune scores. The cross-analysis of DEGs and DMGs revealed that INSRR was an immune-related biomarker in the TCGA GBM cohort. According to GSEA, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway with INSRR abnormal expression were IgA-produced intestinal immune network and Alzheimer's disease, oxidative phosphorylation, and Parkinson's disease, respectively. Additionally, INSRR expression was correlated with dendritic cells activated, dendritic cells resting, T cells CD8, and T cell gamma delta. INSRR is associated with the immune microenvironment in GBM and is used as a biomarker to predict immune invasion.

Pulsed Electromagnetic Fields Protect Against Brain Ischemia by Modulating the Astrocytic Cholinergic Anti-inflammatory Pathway.

Neuroinflammation is one of the most important pathological processes following brain ischemia. Pulsed electromagnetic fields (PEMFs) protect against brain ischemia, but their role in regulating neuroinflammation remains unclear. In the present study, we investigated the biological effects of PEMF exposure on brain ischemia-induced neuroinflammation through the astrocytic cholinergic anti-inflammatory pathway. PEMF exposure reduced the activation of astrocytes and neuroinflammation following brain ischemia by directly modulating astrocytic injury and inflammatory cytokine release. Inhibition of nicotinic acetylcholine receptor alpha 7 subunit (α7nAChR) by a specific antagonist reversed the regulatory effects of PEMF on astrocytes. Furthermore, negative regulation of signal transducer and activator of transcription 3 (STAT3) by α7nAChR was found to be an important downstream mechanism through which PEMF regulates astrocyte-related neuroinflammation. PEMF suppressed STAT3 phosphorylation and nuclear translocation by activating α7nAChR. These results demonstrate that PEMF exerts anti-inflammatory effects in the context of brain ischemia by modulating astrocytic α7nAChR/STAT3 signaling.

Identification of a Fibroblast-Related Prognostic Model in Glioma Based on Bioinformatics Methods.

BACKGROUND: Glioma is the most common primary tumor of the central nervous system with a high lethality rate. This study aims to mine fibroblast-related genes with prognostic value and construct a corresponding prognostic model. METHODS: A glioma-related TCGA (The Cancer Genome Atlas) cohort and a CGGA (Chinese Glioma Genome Atlas) cohort were incorporated into this study. Variance expression profiling was executed via the "limma" R package. The "clusterProfiler" R package was applied to perform a GO (Gene Ontology) analysis. The Kaplan-Meier (K-M) curve, LASSO regression analysis, and Cox analyses were implemented to determine the prognostic genes. A fibroblast-related risk model was created and affirmed by independent cohorts. We derived enriched pathways between the fibroblast-related high- and low-risk subgroups using gene set variation analysis (GSEA). The immune infiltration cell and the stromal cell were calculated using the microenvironment cell populations-counter (MCP-counter) method, and the immunotherapy response was assessed with the SubMap algorithm. The chemotherapy sensitivity was estimated using the "pRRophetic" R package. RESULTS: A total of 93 differentially expressed fibroblast-related genes (DEFRGs) were uncovered in glioma. Seven prognostic genes were filtered out to create a fibroblast-related gene signature in the TCGA-glioma cohort training set. We then affirmed the fibroblast-related risk model via TCGA-glioma cohort and CGGA-glioma cohort testing sets. The Cox regression analysis proved that the fibroblast-related risk score was an independent prognostic predictor in prediction of the overall survival of glioma patients. The fibroblast-related gene signature revealed by the GSEA was applicable to the immune-relevant pathways. The MCP-counter algorithm results pointed to significant distinctions in the tumor microenvironment between fibroblast-related high- and low-risk subgroups. The SubMap analysis proved that the fibroblast-related risk score could predict the clinical sensitivity of immunotherapy. The chemotherapy sensitivity analysis indicated that low-risk patients were more sensitive to multiple chemotherapeutic drugs. CONCLUSION: Our study identified prognostic fibroblast-related genes and generated a novel risk signature that could evaluate the prognosis of glioma and offer a theoretical basis for clinical glioma therapy.