Downregulation of TLX induces TET3 expression and inhibits glioblastoma stem cell self-renewal and tumorigenesis

International audienceGlioblastomas have been proposed to be maintained by highly tumorigenic glioblastoma stem cells (GSCs) that are resistant to current therapy. Therefore, targeting GSCs is critical for developing effective therapies for glioblastoma. In this study, we identify the regulatory cascade of the nuclear receptor TLX and the DNA hydroxylase Ten eleven translocation 3 (TET3) as a target for human GSCs. We show that knockdown of TLX expression inhibits human GSC tumorigenicity in mice. Treatment of human GSC-grafted mice with viral vector-delivered TLX shRNA or nanovector-delivered TLX siRNA inhibits tumour development and prolongs survival. Moreover, we identify TET3 as a potent tumour suppressor downstream of TLX to regulate the growth and self-renewal in GSCs. This study identifies the TLX-TET3 axis as a potential therapeutic target for glioblastoma

Genome-Wide Profiling Identified a Set of miRNAs that Are Differentially Expressed in Glioblastoma Stem Cells and Normal Neural Stem Cells

A major challenge in cancer research field is to define molecular features that distinguish cancer stem cells from normal stem cells. In this study, we compared microRNA (miRNA) expression profiles in human glioblastoma stem cells and normal neural stem cells using combined microarray and deep sequencing analyses. These studies allowed us to identify a set of 10 miRNAs that are considerably up-regulated or down-regulated in glioblastoma stem cells. Among them, 5 miRNAs were further confirmed to have altered expression in three independent lines of glioblastoma stem cells by real-time RT-PCR analysis. Moreover, two of the miRNAs with increased expression in glioblastoma stem cells also exhibited elevated expression in glioblastoma patient tissues examined, while two miRNAs with decreased expression in glioblastoma stem cells displayed reduced expression in tumor tissues. Furthermore, we identified two oncogenes, NRAS and PIM3, as downstream targets of miR-124, one of the down-regulated miRNAs; and a tumor suppressor, CSMD1, as a downstream target of miR-10a and miR-10b, two of the up-regulated miRNAs. In summary, this study led to the identification of a set of miRNAs that are differentially expressed in glioblastoma stem cells and normal neural stem cells. Characterizing the role of these miRNAs in glioblastoma stem cells may lead to the development of miRNA-based therapies that specifically target tumor stem cells, but spare normal stem cells

Balancing Strength and Ductility in Al Matrix Composites Reinforced by Few-Layered MoS2 through In-Situ Formation of Interfacial Al12Mo

In this work, few-layered MoS2 (FLM) nanosheet-reinforced Al matrix composites are developed through powder metallurgy and hot extrusion. The microstructure, mechanical properties, and strengthening mechanisms have been systematically investigated. It is found that Al12Mo and Al2S3 can be formed in-situ during the sintering process, resulting in the improvement of interfacial bonding between FLM and Al matrix. With 1.5 wt.% of FLM addition, an improved tensile strength of 234 MPa with a high elongation of 17% can be obtained. Moreover, the strengthening mechanisms are also demonstrated to be grain refinement, dislocation strengthening, and load transfer, and the calculation indicates that load transfer is the main contribution factor. This work will inspire more new designs of metal matrix composites with balanced strength and ductility

Activated Carbon Nanochains with Tailored Micro-Meso Pore Structures and Their Application for Supercapacitors

Carbon nanochains (CNCs) were synthesized by a facile chemical vapor deposition process consisting of a 1D chain of interconnected carbon nano-onions for potential application in supercapacitors. In this study, the CNCs were further activated by a chemical method using potassium hydroxide (KOH) as the activation agent to obtain micro-meso pore structures. To improve the specific surface area (SSA) and optimize the pore size distribution (PSD) to enhance the capacitance performance, we investigated the activation parameters, including the KOH content, temperature and duration. The results indicated that CNCs with a hierarchical pore structure and high SSA could be achieved using an activation process with a KOH-to-CNC ratio of 2 at 900 °C for 20 h. The mechanism is also discussed. The activation temperature and duration affect the promotion of the carbon graphitization and exaggeration of the carbon etching. The CNCs activated using the optimal parameters exhibited a high capacitance performance of 112.7 F g^–1 at 50 mV s^–1 with excellent stability in 6 M KOH electrolyte, which was due to the improved surface and micromesoporosity without sacrificing their electronic transmission properties

Machine Learning Enabled Capacitance Prediction for Carbon-Based Supercapacitors

Carbon is the most widely used electrode for the supercapacitors. To predict the capacitance of carbon-based supercapacitors, this work applies three machine learning (ML) methods, including linear regression, Lasso and artificial neural network. For training the ML process, we extracted data from hundreds of published papers. Moreover, five variables were selected to figure out their impact on capacitance, including specific surface area, calculated pore size, ID/IG ratio, N-doping level and voltage window. By evaluated with the real data, all of three methods achieve acceptable prediction results, and ANN exhibits the best performance. More importantly, this work shows the potential of ML in material science and advanced applications