Green Synthesis of Silymarin–Chitosan Nanoparticles as a New Nano Formulation with Enhanced Anti-Fibrotic Effects against Liver Fibrosis

Background: Silymarin (SIL) has long been utilized to treat a variety of liver illnesses, but due to its poor water solubility and low membrane permeability, it has a low oral bioavailability, limiting its therapeutic potential. Aim: Design and evaluate hepatic-targeted delivery of safe biocompatible formulated SIL-loaded chitosan nanoparticles (SCNPs) to enhance SIL’s anti-fibrotic effectiveness in rats with CCl₄-induced liver fibrosis. Methods: The SCNPs and chitosan nanoparticles (CNPs) were prepared by ionotropic gelation technique and are characterized by physicochemical parameters such as particle size, morphology, zeta potential, and in vitro release studies. The therapeutic efficacy of successfully formulated SCNPs and CNPs were subjected to in vivo evaluation studies. Rats were daily administered SIL, SCNPs, and CNPs orally for 30 days. Results: The in vivo study revealed that the synthesized SCNPs demonstrated a significant antifibrotic therapeutic action against CCl₄-induced hepatic injury in rats when compared to treated groups of SIL and CNPs. SCNP-treated rats had a healthy body weight, with normal values for liver weight and liver index, as well as significant improvements in liver functions, inflammatory indicators, antioxidant pathway activation, and lipid peroxidation reduction. The antifibrotic activities of SCNPs were mediated by suppressing the expression of the main fibrosis mediators TGFβR1, COL3A1, and TGFβR2 by boosting the hepatic expression of protective miRNAs; miR-22, miR-29c, and miR-219a, respectively. The anti-fibrotic effects of SCNPs were supported by histopathology and immunohistochemistry (IHC) study. Conclusions: According to the above results, SCNPs might be the best suitable carrier to target liver cells in the treatment of liver fibrosis.     

An Indexing Method for Answering Queries on Moving Objects

We consider the problem of indexing a set of objects moving in d-dimensional spaces along linear trajectories. A simple external-memory indexing scheme is proposed to efficiently answer general range queries. The following are examples of the queries that can be answered by the proposed method: report all moving objects that will (i) pass between two given points within a specified time interval; (ii) become within a given distance from some or all of a given set of other moving objects. Our scheme is based on mapping the objects to a dual space, where queries about moving objects are transformed into polyhedral queries concerning their speeds and initial locations. We then present a simple method for answering such polyhedral queries, based on partitioning the space into disjoint regions and using a B+-tree to index the points in each region. By appropriately selecting the boundaries of each region, we guarantee an average search time that matches a known lower bound for the problem. Specifically, for a fixed d, if the coordinates of a given set of N points are statistically independent, the proposed technique answers polyhedral queries, on the average, in O((N/B)^1−1/d⋅(log _B N)^1/d+K/B) I/O's using O(N/B) space, where B is the block size, and K is the number of reported points. Our approach is novel in that, while it provides a theoretical upper bound on the average query time, it avoids the use of complicated data structures, making it an effective candidate for practical applications. The proposed index is also dynamic in the sense that it allows object insertion and deletion in an amortized update cost of log _B(N) I/O's. Experimental results are presented to show the superiority of the proposed index over other methods based on R-trees. recommend Ahmed Elmagarmid     

A Multistage In Silico Study of Natural Potential Inhibitors Targeting SARS-CoV-2 Main Protease

Among a group of 310 natural antiviral natural metabolites, our team identified three compounds as the most potent natural inhibitors against the SARS-CoV-2 main protease (PDB ID: 5R84), M^pro. The identified compounds are sattazolin and caprolactin A and B. A validated multistage in silico study was conducted using several techniques. First, the molecular structures of the selected metabolites were compared with that of GWS, the co-crystallized ligand of M^pro, in a structural similarity study. The aim of this study was to determine the thirty most similar metabolites (10%) that may bind to the M^pro similar to GWS. Then, molecular docking against M^pro and pharmacophore studies led to the choice of five metabolites that exhibited good binding modes against the M^pro and good fit values against the generated pharmacophore model. Among them, three metabolites were chosen according to ADMET studies. The most promising M^pro inhibitor was determined by toxicity and DFT studies to be caprolactin A (292). Finally, molecular dynamics (MD) simulation studies were performed for caprolactin A to confirm the obtained results and understand the thermodynamic characteristics of the binding. It is hoped that the accomplished results could represent a positive step in the battle against COVID-19 through further in vitro and in vivo studies on the selected compounds.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.     

The Small and Silent Force Multiplier: A Swarm UAV—Electronic Attack

At the last two decades, according to UAVs concepts and technological advances, there have been lots of unimagined improvements. Nowadays there are serious works and researches about the usage of UAVs in military operations at electronic warfare (EW) missions. But most of the work on UAV platforms is based upon the advantages of a single, big, expensive, and non-expendable platform. In this study, to get rid off the disadvantages of a stand alone platform a new concept is developed consisting of multiple UAVs with smaller dimensions, at a cheaper price and a wider coverage. According to clarify the study, firstly the EW and RADAR systems and then the swarm UAV concepts are explained. In this manner the current and previous works are pointed out and then the use of the swarm UAVs for EA in military operations is stated. Objectively, the swarm UAV concept’s advantages and some outstanding challenges to the intra-theater space have been put forward regarding the information mentioned above. As a result it is considered that the swarm UAV systems will be tasked important EW missions in the future operation theatres, as soon as the technical handicaps are solved.     

维吾尔语意见挖掘关系抽取研究

在分析维吾尔语词性规则和语法特征的基础上,以维吾尔语评论性语句为研究语料,提出了一种基于Bootstrapping算法的意见挖掘关系抽取方法.在每一次迭代过程中,根据改进的评分公式选取最优模式抽取主题词-意见词对;迭代结束后,对于主题-意见词对为空的评论语句,使用最近匹配算法抽取主题-意见词对;用并联模式和否定模式对抽取的主题-意见词对进行扩展和修正.关系抽取的最终目标是为每一个评论性语句建立一个或多个二元组＜主题词,意见词＞,并使主题词和意见词一一对应.实验结果表明了该方法在关系抽取上的有效性.     

The Improvement of the Quality of Raffinate Obtained from Solvent Extraction of Lubricating Oils

Abstract

Vacuum distillates of an Egyptian crude oil were subjected to solvent extraction process applying N-methyl-2-pyrrolidone (NMP) and furfural as dearomatization solvents. The study shows that the extraction solvent together with the temperature and solvent-to-oil ratio have a significant effect on the yield and quality of produced lubricating oils. The optimum temperature for extracting light waxy distillates with NMP is 55°C at the solvent-to-feed ratio 2:1. These conditions are appropriate to remove the major portion of aromatics from the raffinate. The apparent activation energy (Ea), enthalpy (ΔH*), entropy (ΔS*), and free energy of activation (ΔG*) were calculated for the solvent dearomatization process.     

Active node determination for correlated data gathering in wireless sensor networks

In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. Given that the sensor nodes that are selected as active form a connected wireless network, the inactive sensor nodes can be turned off. Allowing some sensor nodes to be active and some sensor nodes inactive interchangably during the lifecycle of the application helps the wireless sensor network to have a longer lifetime. The problem of determining a set of active sensor nodes in a correlated data environment for a fully operational wireless sensor network can be formulated as an instance of the connected correlation-dominating set problem. In this work, our contribution is twofold; we propose an effective and runtime-efficient iterative improvement heuristic to solve the active sensor node determination problem, and a benefit function that aims to minimize the number of active sensor nodes while maximizing the residual energy levels of the selected active sensor nodes. Extensive simulations we performed show that the proposed approach achieves a good performance in terms of both network lifetime and runtime efficiency.     

Investigation of micro-milling process parameters for surface roughness and milling depth

The main objective of this study is to investigate the micro-milling performance of the AISI H13 with different process parameters namely laser power, scan speed, frequency, and fill spacing using 30W fiber laser marking machine and to find the optimal operation conditions for minimum surface roughness and maximum milling depth. The 108 different combinations occurred with the interaction of each level of the parameters used in this study. Therefore, the main contribution of this paper to the related literature is that it produces new evidence regarding the effects of the multi-scan times on both surface roughness and milling depth. The experimental results are showed that 0.03?mm of fill spacing, the highest scan speed (800?mm/s), lowest frequency (20?kHz), and laser power (60%) produced better surface roughness, which is 1.75???m. The deeper cavity on the geometry is obtained under the experimental combination as 200?mm/s of scan speed, 0.02?mm of fill spacing, 60% of laser power, and 40?kHz of frequency, which is 195???m. The regression analysis was used to develop a mathematical model and determine the effect of process parameters on the surface roughness and milling depth. The results of subsequent tests verifies regression models.