Abstract
Lycorine (Lyc) is a natural alkaloid derived from medicinal plants of the Amaryllidaceae family. Lyc has been reported to inhibit the recurrence and metastasis of different kinds of tumors. ...However, Lyc’s effect on angiogenesis and its specific mechanism are still not clear. This study was designed to test the antiangiogenesis effect of Lyc and to explore the possible mechanisms. We performed cell experiments to confirm Lyc’s inhibitory effect on angiogenesis and employed sunitinib as a positive control. Moreover, the synergistic effect of Lyc and sunitinib was also explored. Next, we conducted bioinformatics analyses to predict the potential targets of Lyc and verified them by western blotting and immunofluorescence. Molecular docking, kinase activity assays, Biacore assays and cellular thermal shift assays (CETSAs) were applied to elucidate the mechanism by which Lyc inhibited target activity. Lyc inhibited angiogenesis in human umbilical vein endothelial cells (HUVECs). Employing bioinformatics, we found that Lyc’s target was PDGFRα and that Lyc attenuated PDGFRα phosphorylation. We also found that Lyc inhibited PDGFRα activation by docking to it to restrain its activity. Additionally, Lyc significantly inhibited PDGF-AA-induced angiogenesis. This study provides new insights into the molecular functions of Lyc and indicates its potential as a therapeutic agent for tumor angiogenesis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Hyperspectral image classification is a hot issue in the field of remote sensing. It is possible to achieve high accuracy and strong generalization through a good classification method that is used ...to process image data. In this paper, an efficient hyperspectral image classification method based on improved Rotation Forest (ROF) is proposed. It is named ROF-KELM. Firstly, Non-negative matrix factorization( NMF) is used to do feature segmentation in order to get more effective data. Secondly, kernel extreme learning machine (KELM) is chosen as base classifier to improve the classification efficiency. The proposed method inherits the advantages of KELM and has an analytic solution to directly implement the multiclass classification. Then, Q-statistic is used to select base classifiers. Finally, the results are obtained by using the voting method. Three simulation examples, classification of AVIRIS image, ROSIS image and the UCI public data sets respectively, are conducted to demonstrate the effectiveness of the proposed method.
•We investigate the pricing efficiency of the newly emerged crude oil futures in INE.•With a limited sample period, we employ a series of robust statistics.•Crude oil futures of INE have an ...equilibrium relationship with five representative spot markets.•The evidence of Granger causality is mixed but supports the efficiency of the INE in the Asia-Pacific region.
We investigate the pricing efficiency of the newly emerged crude oil futures market of the Shanghai International Exchange (INE) from the perspective of cointegration and Granger causality between the returns on INE crude oil futures and some representative spot markets. With a limited sample period, we employ a series of robust statistics and find that the INE crude oil futures’ returns have an equilibrium relationship with the spot returns on the Daqing, Shengli, Oman, WTI, and Brent spot markets. Both imply that the INE crude oil futures price can reflect the fundamental information of spot markets effectively. The evidence of Granger causality is mixed but supports the efficiency of the INE in the Asia-Pacific region.
316L stainless steel is widely used in various industrial fields, but its strength is relatively low. The improvement of its strength has become a research hotspot. In this study, nano titanium ...carbide (TiC) particles are ball milled with 316L with the addition of 2 wt% and 4 wt%. The composite powder was then used for the fabrication of samples by laser powder bed fusion. The results show that the TiC is uniformly distributed in the microstructure. With the addition of TiC, the average size of the grains is significantly reduced. The strength, hardness, and wear resistance of TiC/316L samples have been greatly improved. The tensile strength of formed 2 wt% TiC/316L is 948 MPa, together with a extension rate of 36.0%, which has been increased by 42.6% and 79.7%, respectively. This study provides an effective way to improve the strength at room temperature and the high temperature of 316L built by laser powder bed fusion.
A density functional theory study on nickel‐catalyzed diarylation of styrene (R1) with arylboron (R2) and aryl bromide (R3) is presented in this article, to unveil the plausible mechanism and the ...competition of the potential side reactions. The located reaction pathway involves the elementary steps of oxidative addition, migratory insertion, transmetalation, and reductive elimination. The total free‐energy barrier is computed to be 27.3 kcal/mol, which should be consistent with the experimental temperature and reaction time reported. The Heck coupling reactions between R1 and R3 in the absence and presence of R2 are investigated at the same level of theory, respectively, and it is found that the presence of R2 could not only favor the formation of a η3‐benzyl‐Ni complex leading to the desired diarylation but also disfavor the undesired β‐H elimination step as well. The Suzuki–Miyaura coupling pathway is also suppressed under the optimal conditions, because the migratory insertion of R1 takes place prior to the transmetalation of R2. However, addition of a strongly coordinating ligand could hinder the entry of R1 into the ligand field, which may retard the diarylation pathway and make the cross‐coupling pathway dominant.
The reaction mechanisms of nickel‐catalyzed heterodiarylation of alkenes are explored by DFT calculations. The competition of the diarylation against the potential side reactions, such as Heck coupling and Suzuki–Miyaura coupling, is analyzed in great detail.
In this article, we propose a metasurface with C2 symmetry in the terahertz band, which consists of an external ring resonator and an inner double split ring resonator. In order to overcome the ...problems of ohmic loss and low transmission efficiency caused by the metal structure, we selected all-dielectric materials to design. From 2.17 THz to 2.24 THz, through numerical simulation, the device we proposed can achieve high-efficiency cross-polarization conversion of linearly polarized waves and circularly polarized waves, and their transmission efficiency exceeds 0.8. We first explained it through polarization orthogonal decomposition, and then the physical mechanism is investigated specifically by the distribution of electric field and magnetic field, and the influence of structural parameters on the device is also discussed. In addition, the cell we proposed has a thickness of about
λ
/10, which is conducive to the design and integration of terahertz devices and systems.
Histone deacetylases (HDACs) play a critical role in the proliferation, differentiation, and apoptosis of cancer cells. An obstacle for the application of HDAC inhibitors as effective anti-cancer ...therapeutics is that our current knowledge on the contributions of different HDACs in various cancer types remains scarce. The present study reported that the mRNA and protein levels of HDAC5 were up-regulated in human hepatocellular carcinoma (HCC) tissues and cells as shown by quantitative real-time PCR and Western blot. MTT assay and BrdU incorporation assay showed that the down-regulation of HDAC5 inhibited cell proliferation in HepG2, Hep3B, and Huh7 cell lines. Data from in vivo xenograft tumorigenesis model also demonstrated the anti-proliferative effect of HDAC5 depletion on tumor cell growth. Furthermore, the suppression of HDAC5 promoted cell apoptosis and induced G1-phase cell cycle arrest in HCC cells. On the molecular level, we observed altered expression of apoptosis-related proteins such as p53, bax, bcl-2, cyto C, and caspase 3 in HDAC5-shRNA-transfected cells. Knockdown of HDAC5 led to a significant up-regulation of p21 and down-regulation of cyclin D1 and CDK2/4/6. We also found that the down-regulation of HDAC5 substantially increased p53 stability and promoted its nuclear localization and transcriptional activity. Our study suggested that knockdown of HDAC5 could inhibit cancer cell proliferation by the induction of cell cycle arrest and apoptosis; thus, suppression of HDAC5 may be a viable option for treating HCC patients.
Classification is one of the most popular topics in remote sensing. Consider the problems that the remote sensing data are complicated and few labeled training samples limit the performance and ...efficiency in the classification of remote sensing image. For these problems, a huge number of methods were proposed in the last two decades. However, most of them do not yield good performance. In this paper, a remote sensing image classification algorithm based on the ensemble of extreme learning machine (ELM) neural network, namely, stacked autoencoder (SAE)-ELM, is proposed. First, due to improve the ensemble classification accuracy, we adopt feature segmentation and SAE in the sample data to create high diversity among the base classifiers. Furthermore, ELM neural network is chosen as a base classifier to improve the learning speed of the algorithm. Finally, to determine the final ensemble-based classifier, Q-statistics is adopted. The experiment compares the proposed algorithm with Bagging, Adaboost, Random Forest et al., which results show that the proposed algorithm not only gets high classification accuracy on low resolution, medium resolution, high resolution and hyperspectral remote sensing images, but also has strong stability and generalization on UCI data.
Large-scale concentrated Variable Renewable Energy (VRE) sources pose a challenge to the balance and security of electricity systems. Studies have shown that the demand side may offer a greater ...responsiveness based on the shiftability of loads. However, there is currently no known literature on the demand response (DR) of large-scale shiftable loads in the residential sector. Firstly, there is no sufficiently large database of residential appliance-level load. Secondly, scheduling a large number of small residential shiftable loads simultaneously is a major challenge. Ultimately, the DR of large-scale residential buildings encounters the challenge of ensuring sufficient backup shiftable load to effectively cope with real-time VRE fluctuations during the response period. To address these issues, this paper proposes an appliance-level load data generation method based on diffusion neural networks. Meanwhile, a clustering method based on Generalized End to End (GE2E) loss neural networks is proposed to solve the complexity obstacles in simultaneous load swarm scheduling. Thirdly, a two-stage scheduling approach is proposed to address the challenges in the large-scale DR period through constructing day-ahead and real-time response models. The simulation results show that large-scale residential shiftable loads have a strong response capability to VRE fluctuations, and their response cost is lower than the conventional fuel-fired-power-plant-based-response within a certain user preference cost range. In practice, the clustering and scheduling methods proposed in this paper can be applied after the non-intrusive load monitoring (NILM) method is deployed to decompose the load data.
•This paper addresses the research gap regarding large-scale residential load response to fluctuations in concentrated variable renewable energy sources.•A novel data generation model is proposed to address the issue of insufficient data scale in existing databases.•A novel load clustering algorithm is proposed to address the curse of dimensionality in simultaneous load swarm scheduling.•A novel two-stage response model is proposed is proposed to minimize the response cost and user preference loss.•When the unit user preference cost is lower than a certain boundary, the proposed response method is more cost-effective than conventional methods.
PDF
