Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response.

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Transparent nanocrystal-in-glass composite fibers for multifunctional temperature and pressure sensing.

The pursuit of compact and integrated devices has stimulated a growing demand for multifunctional sensors with rapid and accurate responses to various physical parameters, either separately or simultaneously. Fluorescent fiber sensors have the advantages of robust stability, light weight, and compact geometry, enabling real-time and noninvasive signal detection by monitoring the fluorescence parameters. Despite substantial progress in fluorescence sensors, achieving multifunctional sensing in a single optical fiber remains challenging. To solve this problem, in this study, we present a bottom-up strategy to design and fabricate thermally drawn multifunctional fiber sensors by incorporating functional nanocrystals with temperature and pressure fluorescence responses into a transparent glass matrix. To generate the desired nanocrystal-in-glass composite (NGC) fiber, the fluorescent activators, incorporated nanocrystals, glassy core materials, and cladding matrix are rationally designed. Utilizing the fluorescence intensity ratio technique, a self-calibrated fiber sensor is demonstrated, with a bi-functional response to temperature and pressure. For temperature sensing, the NGC fiber exhibits temperature-dependent near-infrared emission at temperatures up to 573 K with a maximum absolute sensitivity of 0.019 K-1. A pressure-dependent upconversion emission is also realized in the visible spectral region, with a linear slope of -0.065. The successful demonstration of multifunctional NGC fiber sensors provides an efficient pathway for new paradigms of multifunctional sensors as well as a versatile strategy for future hybrid fibers with novel combinations of magnetic, optical, and mechanical properties.

Genome-Wide 5-Formylcytosine Redistribution in KCl-Stimulated Mouse Primary Cortical Neurons is Associated with Neuronal Activity.

An abundant accumulation of DNA demethylation intermediates has been identified in mammalian neurons. While the roles of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in neuronal function have been extensively studied, little is known about 5-formylcytosine (5fC) in neurons. Therefore, this study was to investigate the genome-wide distribution and potential functions of 5fC in neurons. In an in vitro culture model of mouse primary cortical neurons, we observed a dynamic increase in the total 5fC level in the neuronal genome after potassium chloride (KCl) stimulation. Subsequently, we employed chemical-labeling-enabled C-to-T conversion sequencing (CLEVER-seq) to examine the 5fC distribution at a single-base resolution. Bioinformatic analysis revealed that 5fC was enriched in promoter regions, and gene ontology (GO) analysis indicated that the differential formylation positions (DFP) were correlated with neuronal activities. Additionally, integration with previously published nascent RNA-seq data revealed a positive correlation between gene formylation and mRNA expression levels. As well, 6 neuro-activity-related genes with a positive correlation were validated. Furthermore, we observed higher chromatin accessibility and RNA pol II binding signals near the 5fC sites through multiomics analysis. Motif analysis identified potential reader proteins for 5fC. In conclusion, our work provides a valuable resource for studying the dynamic changes and functional roles of 5fC in activated mammalian neurons.

Identification, and Experimental and Bioinformatics Validation of an Immune-Related Prognosis Gene Signature for Low-Grade Glioma Based on mRNAsi.

BACKGROUND: Low-grade gliomas (LGGs), which are the second most common intracranial tumor, are diagnosed in seven out of one million people, tending to develop in younger people. Tumor stem cells and immune cells are important in the development of tumorigenesis. However, research on prognostic factors linked to the immune microenvironment and stem cells in LGG patients is limited. We critically need accurate related tools for assessing the risk of LGG patients. METHODS: In this study, we aimed to identify immune-related genes (IRGs) in LGG based on the mRNAsi score. We employed differentially expressed gene (DEG) methods and weighted correlation network analysis (WGCNA). The risk signature was then further established using a lasso Cox regression analysis and a multivariate Cox analysis. Next, we used immunohistochemical sections (HPA) and a survival analysis to identify the hub genes. A nomogram was built to assess the prognosis of patients based on their clinical information and risk scores and was validated using a DCA curve, among other methods. RESULTS: Four hub genes were obtained: C3AR1 (HR = 0.98, p < 0.001), MSR1 (HR = 1.02, p < 0.001), SLC11A1 (HR = 1.01, p < 0.01), and IL-10 (HR = 1.01, p < 0.001). For LGG patients, we created an immune-related prognostic signature (IPS) based on mRNAsi for estimating risk scores; different risk groups showed significantly different survival rates (p = 3.3 × 10-16). Then, via an evaluation of the IRG-related signature, we created a nomogram for predicting LGG survival probability. CONCLUSION: The outcome suggests that, when predicting the prognosis of LGG patients, our nomogram was more effective than the IPS. In this study, four immune-related predictive biomarkers for LGG were identified and proven to be IRGs. Therefore, the development of efficient immunotherapy techniques can be facilitated by the creation of the IPS.

The role of RNA modification in the generation of acquired drug resistance in glioma.

Glioma is the most common malignant tumor in the central nervous system. The clinical treatment strategy is mainly surgery combined with concurrent temozolomide chemotherapy, but patients can develop drug resistance during treatment, which severely limits its therapeutic efficacy. Epigenetic regulation at the RNA level is plastic and adaptable, and it can induce a variety of tumor responses to drugs. The regulators of RNA modification include methyltransferases, demethylases, and methylation binding proteins; these are also considered to play an important role in the development, prognosis, and therapeutic response of gliomas, which provides a basis for finding new targets of epigenetic drugs and resetting the sensitivity of tumor cells to temozolomide. This review discusses the relationship between the development of adaptive drug resistance and RNA modification in glioma and summarizes the progress of several major RNA modification strategies in this field, especially RNA m6A modification, m5C modification, and adenosine-to-inosine editing.

Identification of an Immune-Related Prognostic Signature for Glioblastoma by Comprehensive Bioinformatics and Experimental Analyses.

BACKGROUND: Glioblastoma (GBM), which has a poor prognosis, accounts for 31% of all cancers in the brain and central nervous system. There is a paucity of research on prognostic indicators associated with the tumor immune microenvironment in GBM patients. Accurate tools for risk assessment of GBM patients are urgently needed. METHODS: In this study, we used weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) methods to screen out GBM-related genes among immune-related genes (IRGs). Then, we used survival analysis and Cox regression analysis to identify prognostic genes among the GBM-related genes to further establish a risk signature, which was validated using methods including ROC analysis, stratification analysis, protein expression level validation (HPA), gene expression level validation based on public cohorts, and RT-qPCR. In order to provide clinicians with a useful tool to predict survival, a nomogram based on an assessment of IRGs and clinicopathological features was constructed and further validated using DCA, time-dependent ROC curve, etc. Results: Three immune-related genes were found: PPP4C (p < 0.001, HR = 0.514), C5AR1 (p < 0.001, HR = 1.215), and IL-10 (p < 0.001, HR = 1.047). An immune-related prognostic signature (IPS) was built to calculate risk scores for GBM patients; patients classified into different risk groups had significant differences in survival (p = 0.006). Then, we constructed a nomogram based on an assessment of the IRG-based signature, which was validated as a potential prediction tool for GBM survival rates, showing greater accuracy than the nomogram without the IPS when predicting 1-year (0.35 < Pt < 0.50), 3-year (0.65 < Pt < 0.80), and 5-year (0.65 < Pt < 0.80) survival. CONCLUSIONS: In conclusion, we integrated bioinformatics and experimental approaches to construct an IPS and a nomogram based on IPS for predicting GBM prognosis. The signature showed strong potential for prognostic prediction and could help in developing more precise diagnostic approaches and treatments for GBM.

Multiple recurrent aneurysms with angiitis of the central nervous system in a girl: A case report.

INTRODUCTION: Primary central nervous system (CNS) vasculitis is a rare immune inflammatory disease confined to the blood vessels of the brain and spinal cord. The total number reported in the world is about 500[1]. Most are negative in cerebral angiography or vascular stenosis and only 1 case of aortic aneurysms reported. PATIENT CONCERNS: A 12-year-old female experienced sudden headache and vomiting. Previous findings of vascular stenosis. Diagnosed as a ruptured aneurysm bleeding. The aneurysm recurred a short time after treatment. DIAGNOSIS: Multiple recurrent aneurysms with angiitis of the central nervous system. INTERVENTIONS: The patient underwent 2 aneurysm clipping operations, both of which completely clipped the aneurysm. OUTCOMES: The patient recovered well after surgery. Three months after discharge, DSA reexamination in our hospital showed that the aneurysm was completely clipped without recurrence. CONCLUSION: Subarachnoid hemorrhage after acute cerebral infarction is rare. In addition, the patient had recurrent aneurysms after the first aneurysm clipping, which emphasized the importance of postoperative drug therapy and blood pressure control.

CARD3 Promotes Cerebral Ischemia-Reperfusion Injury Via Activation of TAK1.

Background Although multiple signaling cascades and molecules contributing to the pathophysiological process have been studied, the treatments for stroke against present targets have not acquired significant clinical progress. Although CARD3 (caspase activation and recruitment domain 3) protein is an important factor involved in regulating immunity, inflammation, lipid metabolism, and apoptosis, its role in cerebral stroke is currently unknown. Methods and Results Using a mouse model of ischemia-reperfusion (I-R) injury based on transient blockage of the middle cerebral artery, we have found that CARD3 expression is upregulated in a time-dependent manner during I-R injury. Further animal study revealed that, relative to control mice, CARD3-knockout mice exhibited decreased inflammatory response and neuronal apoptosis, with reduced infarct volume and lower neuropathological scores. In contrast, neuron-specific CARD3-overexpressing transgenic (CARD3-TG) mice exhibited increased I-R induced injury compared with controls. Mechanistically, we also found that the activation of TAK1 (transforming growth factor-ß-activated kinase 1) was enhanced in CARD3-TG mice. Furthermore, the increased inflammation and apoptosis seen in injured CARD3-TG brains were reversed by intravenous administration of the TAK1 inhibitor 5Z-7-oxozeaenol. Conclusions These results indicate that CARD3 promotes I-R injury via activation of TAK1, which not only reveals a novel regulatory axis of I-R induced brain injury but also provides a new potential therapeutic approach for I-R injury.