Image_3_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.tif

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Table_2_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.xlsx

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Table_3_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.xlsx

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Development of poly(hydroxyethyl methacrylate) nanogel for effective oral insulin delivery

Because of uncomfortable, painful and even deleterious effects of daily injection of insulin, extensive efforts are being made worldwide for developing noninvasive drug delivery systems, especially via the oral route. In this study, we synthesized hydroxyethyl methacrylate (HEMA) nanogel via emulsion polymerization method. The morphology and stability of the nanogel were characterized by scanning electronic microscope and dynamic light scattering. In vivo results showed the soft HEMA nanogel had longer half-live in the body circulation and exhibited almost negligible uptake by the macrophage cells as compared with blank cells. For the FITC-dextran tracking for intestinal penetration, the results indicated that the FITC-dextran in the soft nanogel penetrated faster from the inner side of the abdominal segment, which explained why the soft HEMA nanogel could promote intestinal absorption of encapsulated insulin. In vivo delivery of insulin encapsulated in the soft HEMA nanogel sustained blood glucose control for 12 h, and the overall bioavailability of administrated insulin was much higher than free insulin. Our results showed that the insulin-loaded HEMA nanogel was able to efficiently control blood glucose as a delivery system, suggesting the HEMA nanogel using emulsion polymerization could be an alternative carrier for oral insulin delivery.</p

Table_1_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.xlsx

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Image_1_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.tif

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Image_2_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.tif

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Table_4_Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.xlsx

AimsTo reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients.MethodsSingle-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell–cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status.ResultsDifferent types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell–cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell–cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression.ConclusionsHypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells’ MES-like transformation trend and inhibit antitumor function of immune cells.</p

Additional file 2 of Multi-dimensional omics characterization in glioblastoma identifies the purity-associated pattern and prognostic gene signatures

Additional file 2: Figure S1. Relation between purity and IDH mutation status or MGMT promotor methylation status. Figure S2. The prognostic value of purity in stratified GBMs. Figure S3. The prognostic role of purity-associated risk score in CGGA or GSE4412 cohort. Figure S4. Unsupervised analyses of global transcriptional similarities and differences between two purity subgroups. Figure S5. Adjustment of purity in differentially expressed genes analysis. Figure S6. Enrichment of KEGG pathways in differentially methylated genes. Figure S7. Relation between purity and genomic alterations. Figure S8. GO enrichment analysis of differentially amplified genes or differentially deleted genes between purity subgroups. Figure S9. Correlation between tumor purity and genomic instability. Figure S10. Correlation between CYT and mutation abundance

Fault Diagnosis of Motor Bearing Based on Current Bi-Spectrum and Convolutional Neural Network

Abstract Motor bearings are prone to different degrees of performance degradation, fatigue damage and failure undergoing complex and harsh environments. Vibration signal analysis is a mature method for diagnosing motor bearing faults, while it is not applicable for installing additional vibration sensors on many occasions. Practically, the fault of motor bearings changes the air gap flux between the rotor and stator, which leads to harmonic fluctuations in the stator current. The current signals can be used to diagnose the motor bearing faults without additional sensors. Inevitably the harmonics caused by the motor bearing faults will be coupled with the original signals. This paper combines bi-spectrum and Convolution Neural Network (CNN) to analyze the current signals of motor bearing faults. The CNN diagnosis model is trained based on the local bi-spectrum of current, and the CNN parameters are optimized. Diagnose and analyze motor bearing faults with different fault implantation methods, working conditions, fault degrees and fault locations. The diagnostic accuracy reaches more than 80%.</div