44 research outputs found
2019 Overview
The CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews, and reports of novel findings of therapeutic relevance to the central nervous system. Its focus includes clinical pharmacology, drug development, and novel methodologies for drug evaluation in neurological and psychiatric diseases. We are pleased to announce that CNS Neuroscience & Therapeutics has become an OpenâAccess Journal as of January 2019. This would allow wider dissemination of scientific knowledge and facilitate collaborative efforts toward advancing novel and solid research on the maintenance of brain homeostasis and repairing the aging and dysfunctional brain
Inducing and Manipulating Heteroelectronic States in a Single MoS2 Thin Flake
By dual gating a few-layer MoS2 flake, we induce spatially separated electronic states showing superconductivity and Shubnikovâde Haas (SdH) oscillations. While the highly confined superconductivity forms at the K/KⲠvalleys of the topmost layer, the SdH oscillations are contributed by the electrons residing in the Q/QⲠvalleys of the rest of the bottom layers, which is confirmed by the extracted Landau level degeneracy of 3, electron effective mass of 0.6me, and carrier density of 5Ă10^12ââcm^â2. Mimicking conventional heterostructures, the interaction between the heteroelectronic states can be electrically manipulated, which enables âbipolarlikeâ superconducting transistor operation. The off-on-off switching pattern can be continuously accessed at low temperatures by a field effect depletion of carriers with a negative back gate bias and the proximity effect between the top superconducting layer and the bottom metallic layers that quenches the superconductivity at a positive back gate bias
Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer
Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed.Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. KâM analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues.Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort.Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy
A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy
Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed.Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkersâ expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy.Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05).Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients
CentralâProvincial Relations at the CCP Central Committees: Institutions, Measurement and Empirical Trends, 1978â2002
Replication Data for: The regional consequences of authoritarian power-sharing: Politburo representation and fiscal redistribution in China
Much political economy research examines how higher-level political representation of the constituent jurisdictions affects resource redistribution among the lower-level units in democracies, but little work has probed the redistributive consequences of regional political representation under dictatorship. This study investigates the effect of membership for provincial officials in the Politburo of the single-ruling Chinese Communist Party (CCP) on fiscal resource flows between the central government and provincial governments in reform-era China. I find robust evidence that the provinces overseen by CCP Politburo members tended to remit more budgetary revenues to the center but did not receive larger central budgetary subsidies. This is consistent with a territorial logic of authoritarian power-sharing in single-party states, which suggests that the regionally selective presence at a collective ruling-party decision-making forum for subnational officials aims at tighter political control to help induce greater policy compliance from below
Numerical Modeling of Stress Disturbance Characteristics during Tunnel Excavation
The stress state and principal stress axis changes of the stress-field tensor are analyzed during the advancement of a tunnel face on the basis of a given case study of the Jinping II Hydropower Station in China. First, the prevailing pole diagram in geology is used to illustrate the rotation of the stress axes as the tunnel face advances. The results show that the orientation adjustments of principal stresses in different positions near the tunnel boundary share common characteristics. The major and minor principal stress axes ahead of the tunnel face will rotate to intersect with the excavation surface at an angle, with the intermediate principal stress axis being almost parallel to the excavation surface. Furthermore, the stress triaxiality that is commonly used to indicate the deformation and damage of metal materials is introduced to describe the stress state change of the excavation-induced stress. The stress triaxiality is found to represent the stress state change due to the variation in both the magnitude and orientation of the stress-field tensor. According to the physical meaning and the change law of the stress triaxiality, stress disturbance during tunnel excavation can be divided into four stages, and the stress disturbance zone is divided into a strong disturbance zone and a weak disturbance zone. The disturbance characteristics of different stages and the distribution patterns of various zones are analyzed, which may be useful for practical application in the design and construction of rock tunnels
Facile preparation of hydroxylâfunctionalized mica nanosheets assisted by plasma treatment
The efficient exfoliation of mica, a naturally layered material, into two-dimensional (2D) nanosheets has received much attention due to its low price, good chemical stability, and better shielding function against UV light. However, fast and simple exfoliation of mica in a large-scale face a great challenge. In this work, we developed a simple and effective method for obtaining OHâfunctionalized mica nanosheets (MNs). The process involved calcination, plasma treatment, and ultrasonic exfoliation, resulting in a yield of 7.535%. Furthermore, the effects of sonication time, solvent type and particle sizes of mica were investigated. The conditions for the preparation of MNs were determined: mica calcination, plasma treatment, and sonication in ethanol for 5 h. XPS and FTâIR demonstrated that more hydroxyl groups were introduced to mica after the plasma treatment, which facilitated the exfoliation of mica
A frequent somatic mutation in the 3'UTR of GAPDH facilitates the development of ovarian cancer by creating a miRâ125b binding site
A landslide extraction method of channel attention mechanism U-Net network based on Sentinel-2A remote sensing images
Accurate landslide extraction is significant for landslide disaster prevention and control. Remote sensing images have been widely used in landslide investigation, and landslide extraction methods based on deep learning combined with remote sensing images (such as U-Net) have received a lot of attention. However, because of the variable shape and texture features of landslides in remote sensing images, the rich spectral features, and the complexity of their surrounding features, landslide extraction using U-Net can lead to problems such as false detection and missed detection. Therefore, this study introduces the channel attention mechanism called the squeeze-and-excitation network (SENet) in the feature fusion part of U-Net; the study also constructs an attention U-Net landside extraction model combining SENet and U-Net, and uses Sentinel-2A remote sensing images for model training and validation. The extraction results are evaluated through different evaluation metrics and compared with those of two models: U-Net and U-Net Backbone (U-Net Without Skip Connection). The results show that proposed the model can effectively extract landslides based on Sentinel-2A remote sensing images with an F1 value of 87.94%, which is about 2% and 3% higher than U-Net and U-Net Backbone, respectively, with less false detection and more accurate extraction results