Identification of angiogenesis-related genes signature for predicting survival and its regulatory network in glioblastoma.

Glioblastoma (GBM) is notorious for malignant neovascularization that contributes to undesirable outcome. However, its mechanisms remain unclear. This study aimed to identify prognostic angiogenesis-related genes and the potential regulatory mechanisms in GBM. RNA-sequencing data of 173 GBM patients were obtained from the Cancer Genome Atlas (TCGA) database for screening differentially expressed genes (DEGs), differentially transcription factors (DETFs), and reverse phase protein array (RPPA) chips. Differentially expressed genes from angiogenesis-related gene set were extracted for univariate Cox regression analysis to identify prognostic differentially expressed angiogenesis-related genes (PDEARGs). A risk predicting model was constructed based on 9 PDEARGs, namely MARK1, ITGA5, NMD3, HEY1, COL6A1, DKK3, SERPINA5, NRP1, PLK2, ANXA1, SLIT2, and PDPN. Glioblastoma patients were stratified into high-risk and low-risk groups according to their risk scores. GSEA and GSVA were applied to explore the possible underlying GBM angiogenesis-related pathways. CIBERSORT was employed to identify immune infiltrates in GBM. The Pearson's correlation analysis was performed to evaluate the correlations among DETFs, PDEARGs, immune cells/functions, RPPA chips, and pathways. A regulatory network centered by three PDEARGs (ANXA1, COL6A1, and PDPN) was constructed to show the potential regulatory mechanisms. External cohort of 95 GBM patients by immunohistochemistry (IHC) assay demonstrated that ANXA1, COL6A1, and PDPN were significantly upregulated in tumor tissues of high-risk GBM patients. Single-cell RNA sequencing also validated malignant cells expressed high levels of the ANXA1, COL6A1, PDPN, and key DETF (WWTR1). Our PDEARG-based risk prediction model and regulatory network identified prognostic biomarkers and provided valuable insight into future studies on angiogenesis in GBM.

Metal Cations in Efficient Perovskite Solar Cells: Progress and Perspective.

Metal halide perovskite solar cells (PVSCs) have revolutionized photovoltaics since the first prototype in 2009, and up to now the highest efficiency has soared to 24.2%, which is on par with commercial thin film cells and not far from monocrystalline silicon solar cells. Optimizing device performance and improving stability have always been the research highlight of PVSCs. Metal cations are introduced into perovskites to further optimize the quality, and this strategy is showing a vigorous development trend. Here, the progress of research into metal cations for PVSCs is discussed by focusing on the position of the cations in perovskites, the modulation of the film quality, and the influence on the photovoltaic performance. Metal cations are considered in the order of alkali cations, alkaline earth cations, then metal cations in the ds and d regions, and ultimately trivalent cations (p- and f-block metal cations) according to the periodic table of elements. Finally, this work is summarized and some relevant issues are discussed.

MicroRNA-132 attenuates cerebral injury by protecting blood-brain-barrier in MCAO mice.

MicroRNAs (miRNAs) have been widely reported to induce posttranscriptional gene silencing and led to an explosion of new strategies for the treatment of human disease. It has been reported that the expression of MicroRNA-132 (miR-132) are altered both in the blood and brain after stroke. However, the effect of miR-132 on blood-brain barrier (BBB) disruption in ischemia stroke has not been studied. Here we will investigate the effects of miR-132 on the permeability of BBB after ischemic stroke and explore the potential mechanism underlying observed protection. Eight week-old mice were injected intracerebroventricularly with miR-132, antagomir-132 or agomir negative control (agomir-NC) 2 h before middle cerebral artery occlusion (MCAO), followed by animal behavior tests and infraction volume measurement at 24 h after MCAO. BBB permeability and integrity were measured by Evan's blue extravasation and brain water content. The expression of tight junction proteins was detected by immnostaining and Western blots. The level of MiR-132 and its targeted gene Mmp9 were assayed. Treatment with exogenous MiR-132 (agomir-132) decreased the infraction volume, reduced brain edema, and improved neurological functions compared to control mice. Agomir-132 increased the level of MiR-132 in brain tissue, suppressed the expression of MMP-9 mRNA and decreased the degradation of tight junction proteins VE-cadherin and ß-Catenin in ischemic stroke mice. Inhibition of MMP-9 has a similar protective effect to agomir-132 on infraction volume, brain edema, and tight-junction protein expression after MCAO. Our results indicated that miR-132/MMP-9 axis might be a novel therapeutic target for BBB protection in ischemic stroke.

Selection of an ASIC1a-blocking combinatorial antibody that protects cells from ischemic death.

Acid-sensing ion channels (ASICs) have emerged as important, albeit challenging therapeutic targets for pain, stroke, etc. One approach to developing therapeutic agents could involve the generation of functional antibodies against these channels. To select such antibodies, we used channels assembled in nanodiscs, such that the target ASIC1a has a configuration as close as possible to its natural state in the plasma membrane. This methodology allowed selection of functional antibodies that inhibit acid-induced opening of the channel in a dose-dependent way. In addition to regulation of pH, these antibodies block the transport of cations, including calcium, thereby preventing acid-induced cell death in vitro and in vivo. As proof of concept for the use of these antibodies to modulate ion channels in vivo, we showed that they potently protect brain cells from death after an ischemic stroke. Thus, the methodology described here should be general, thereby allowing selection of antibodies to other important ASICs, such as those involved in pain, neurodegeneration, and other conditions.

Long non-coding RNAs: potential molecular biomarkers for gliomas diagnosis and prognosis.

The current grade classification system of gliomas is based on the histopathological features of these tumors and has great significance in defining groups of patients for clinical assessment. However, this classification system is also associated with a number of limitations, and as such, additional clinical assessment criteria are required. Long non-coding RNAs (lncRNAs) play a critical role in cellular functions and are currently regarded as potential biomarkers for glioma diagnosis and prognosis. Therefore, the molecular classification of glioma based on lncRNA expression may provide additional information to assist in the systematic identification of glioma. In the present paper, we review the emerging evidence indicating that specific lncRNAs may have the potential for use as key novel biomarkers and thus provide a powerful tool for the systematic diagnosis of glioma.