Sofosbuvir Selects for Drug-Resistant Amino Acid Variants in the Zika Virus RNA-Dependent RNA-Polymerase Complex In Vitro

The nucleotide analog sofosbuvir, licensed for the treatment of hepatitis C, recently revealed activity against the Zika virus (ZIKV) in vitro and in animal models. However, the ZIKV genetic barrier to sofosbuvir has not yet been characterized. In this study, in vitro selection experiments were performed in infected human hepatoma cell lines. Increasing drug pressure significantly delayed viral breakthrough (p = 0.029). A double mutant in the NS5 gene (V360L/V607I) emerged in 3 independent experiments at 40–80 µM sofosbuvir resulting in a 3.9 ± 0.9-fold half- maximal inhibitory concentration (IC₅₀) shift with respect to the wild type (WT) virus. A triple mutant (C269Y/V360L/V607I), detected in one experiment at 80 µM, conferred a 6.8-fold IC₅₀ shift with respect to the WT. Molecular dynamics simulations confirmed that the double mutant V360L/V607I impacts the binding mode of sofosbuvir, supporting its role in sofosbuvir resistance. Due to the distance from the catalytic site and to the lack of reliable structural data, the contribution of C269Y was not investigated in silico. By a combination of sequence analysis, phenotypic susceptibility testing, and molecular modeling, we characterized a double ZIKV NS5 mutant with decreased sofosbuvir susceptibility. These data add important information to the profile of sofosbuvir as a possible lead for anti-ZIKV drug development.     

Optimal filtering and control for wireless networked closed-loop control systems

This article studies the optimal filtering and control for wireless networked control systems (WNCSs). In WNCSs, packets may be lost in both control and feedback channels and user datagram protocol is usually used to improve the performance of the real-time control. Relevant literature indicates that the conventional optimal filtering for such a system cannot be applied in practice due to the complex calculation with Gaussian mixtures. This paper proposes a novel scheme to realize the optimal filtering and the linear quadratic Gaussian control for WNCSs, in which the controlled node performs a local estimation and the remote-control node performs the final estimation and control, and a synchronization of two estimators is guaranteed by a communication mechanism. An optimal filtering algorithm is developed, the stability condition of the filtering error covariance is obtained, optimal finite-horizon and infinite-horizon control are derived, and the stability of the closed-loop control system is proved. Numerical simulations show the validity and feasibility of the theoretical results.     

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

This paper proposes the application of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in fixed structure H_∞ loop shaping controller design. Integral Time Absolute Error (ITAE) performance requirement is incorporated as a constraint with an objective of maximization of stability margin in the fixed structure H_∞ loop shaping controller design problem. Pneumatic servo system, separating tower process and F18 fighter aircraft system are considered as test systems. The CMA-ES designed fixed structure H_∞ loop-shaping controller is compared with the traditional H_∞ loop shaping controller, non-smooth optimization and Heuristic Kalman Algorithm (HKA) based fixed structure H_∞ loop shaping controllers in terms of stability margin. 20% perturbation in the nominal plant is used to validate the robustness of the CMA-ES designed H_∞ loop shaping controller. The effect of Finite Word Length (FWL) is considered to show the implementation difficulties of controller in digital processors. Simulation results demonstrated that CMA-ES based fixed structure H_∞ loop shaping controller is suitable for real time implementation with good robust stability and performance.     

A multi-start central force optimization for global optimization

Central force optimization (CFO) is an efficient and powerful population-based intelligence algorithm for optimization problems. CFO is deterministic in nature, unlike the most widely used metaheuristics. CFO, however, is not completely free from the problems of premature convergence. One way to overcome local optimality is to utilize the multi-start strategy. By combining the respective advantages of CFO and the multi-start strategy, a multi-start central force optimization (MCFO) algorithm is proposed in this paper. The performance of the MCFO approach is evaluated on a comprehensive set of benchmark functions. The experimental results demonstrate that MCFO not only saves the computational cost, but also performs better than some state-of-the-art CFO algorithms. MCFO is also compared with representative evolutionary algorithms. The results show that MCFO is highly competitive, achieving promising performance.     

Microenvironment and related genes predict outcomes of patients with cervical cancer: evidence from TCGA and bioinformatic analysis

Cervical cancer (CESC) is one of the most common cancers and affects the female genital tract. Consistent HPV infection status has been determined to be a vital cause of tumorigenesis. HPV infection may induce changes to the immune system and limit the host’s immune response. Immunotherapy is therefore essential to improving the overall survival of both locally advanced and recurrent CESC patients. Using 304 relevant samples from TCGA, we assessed immune cell function in CESC patients to better understand the status of both tumor micro-environment cells and immune cells in CESC. Functional enrichment analysis, pathway enrichment analysis, and PPI network construction were performed to explore the differentially expressed genes (DEGs). The analysis identified 425 DEGs, which included 295 up-regulated genes and 130 down-regulated genes. We established that upregulation of CCL5 was correlated with significantly better survival, meaning that CCL5 expression could serve as a novel prognostic biomarker for CESC patients. We further focused on CCL5 as a hub gene in CESC, as it had significant correlations with increased numbers of several types of immune cells. Cell-type fractions of M1 macrophages were significantly higher in the high-immune-scores group, which was associated with better overall survival. Finally, we concluded that CCL5 is a promising prognostic biomarker for CESC, as well as a novel chemotherapeutic target.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

一种军棋机器博弈的多棋子协同博弈方法

针对在军棋博弈不完全信息对弈中，面对棋子不同价值、不同位置、不同搭配所产生的不同棋力，传统的单子意图搜索算法，不能满足棋子之间的协同性与沟通性，同时也缺乏对敌方的引诱与欺骗等高级对抗能力。本文提出一种结合UCT搜索策略的高价值棋子博弈方法，实现高价值棋子协同博弈的策略。实战经验表明:高价值多棋子军棋协同博弈策略优于单棋子军棋博弈策略。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

Combination of vegetable soup and glucan demonstrates synergistic effects on macrophage-mediated immune responses

Vegetable soup (VS), a plant-based functional food, has been used as a traditional folk medicine and is attracting attention for its ability to enhance the immune response. β-Glucan, a well-established and effective immunomodulator, has synergistic effects when used in combination with some bioactive compounds. In the present study, we aimed to evaluate the synergistic immunomodulatory effects of the combination of VS and β-glucan on macrophage-mediated immune responses. β-Glucan was demonstrated to synergistically enhance the VS-stimulated immune response, including the production of interleukin-6, tumor necrosis factor-α, and nitric oxide, mainly through the mitogen-activated protein kinase pathway in macrophages. In addition, this combination has the potential for further development in functional foods with immune-enhancing activity.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10068-021-00888-x.     

一种改进的新三步搜索算法

在对三步法工作原理进行研究的基础上提出了新三步搜索算法（NITSS）。该方法充分利用视频序列运动矢量概率分布上的中心偏置特性．在三步搜索算法的基础上引入了十字型分布的4个点构成搜索点群。实验结果表明。新三步搜索算法解决了三步法的小运动估计效果较差问题．提高了搜索精度，保持了三步法的高效率。