SOX7 is involved in polyphyllin D-induced G0/G1 cell cycle arrest through down-regulation of cyclin D1

The incidence of mortality of prostate cancer (PCa) has been an uptrend in recent years. Our previous study showed that the sex-determining region Y-box 7 (SOX7) was low-expressed and served as a tumor suppressor in PCa cells. Here, we describe the effects of polyphyllin D (PD) on proliferation and cell cycle modifications of PCa cells, and whether SOX7 participates in this process. PC-3 cells were cultured in complete medium containing PD for 12, 24, and 48 h. MTT assay was used to investigate the cytotoxic effects of PD. Cell cycle progression was analyzed using propidium iodide (PI) staining, and protein levels were assayed by Western blot analysis. Our results showed low expression of SOX7 in PCa tissues/cells compared to their non-tumorous counterparts/RWPE-1 cells. Moreover, PD inhibited the proliferation of PC-3 cells in a dose- and time-dependent manner. PD induced G0/G1 cell cycle arrest, while co-treatment with short interfering RNA targeting SOX7 (siSOX7) had reversed this effect. PD downregulated SOX7, cyclin D1, cyclin-dependent kinase 4 (CDK4), and cyclin-dependent kinase6 (CDK6) expressions in a dose-dependent manner, whereas co-treatment of siSOX7 and PD rescued the PD-inhibited cyclin D1 expression. However, no obvious changes were observed in CDK4 or CDK6 expression. These results indicate that SOX7 is involved in PD-induced PC-3 cell cycle arrest through down-regulation of cyclin D1

Map-based Channel Modeling and Generation for U2V mmWave Communication

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well

A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture

Considering the unmanned aerial vehicle (UAV) three-dimensional (3D) posture, a novel 3D non-stationary geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) UAV-to-vehicle (U2V) channels. It consists of a line-of-sight (LoS) and non-line-of-sight (NLoS) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e. the temporal autocorrelation function (ACF) and spatial cross correlation function (CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.Comment: 12 pages, 8 figures, CNCO

Decentralized Threshold Signatures with Dynamically Private Accountability

Threshold signatures are a fundamental cryptographic primitive used in many practical applications. As proposed by Boneh and Komlo (CRYPTO'22), TAPS is a threshold signature that is a hybrid of privacy and accountability. It enables a combiner to combine t signature shares while revealing nothing about the threshold t or signing quorum to the public and asks a tracer to track a signature to the quorum that generates it. However, TAPS has three disadvantages: it 1) structures upon a centralized model, 2) assumes that both combiner and tracer are honest, and 3) leaves the tracing unnotarized and static. In this work, we introduce Decentralized, Threshold, dynamically Accountable and Private Signature (DeTAPS) that provides decentralized combining and tracing, enhanced privacy against untrusted combiners (tracers), and notarized and dynamic tracing. Specifically, we adopt Dynamic Threshold Public-Key Encryption (DTPKE) to dynamically notarize the tracing process, design non-interactive zero knowledge proofs to achieve public verifiability of notaries, and utilize the Key-Aggregate Searchable Encryption to bridge TAPS and DTPKE so as to awaken the notaries securely and efficiently. In addition, we formalize the definitions and security requirements for DeTAPS. Then we present a generic construction and formally prove its security and privacy. To evaluate the performance, we build a prototype based on SGX2 and Ethereum