HYSSOP and POLIUM could help to prevent COVID-19 in high-risk population: The results of a parallel randomized placebo-controlled field trial

243-253This study was conducted to evaluate the effect of HYSSOP (composed of Hyssopus officinalis L., Echium amoenum Fisch & C. A. Mey and Glycyrrhiza glabra L.) and POLIUM (contained Teucrium polium L., Cuscuta epithymum Murr and Cichorium intybus L.) combined distilled herbal medicines compared to placebo in the prevention of COVID-19. This is a double-blind parallel placebo-controlled field trial conducted on 751 asymptomatic individuals whose one of the family members recently had a positive RT-PCR test for COVID-19. They were divided into three groups including POLIUM, HYSSOP and placebo using random blocks with a 1:1:1 allocation ratio. Participants received daily 5 cc (under 12 years) or 10 cc (over 12 years) of allocated oral medications for 20 days. The primary outcome was the frequency of positive RT-PCR test among participants who became symptomatic. The mean age of participants was 36.6. Nineteen participants get infected by COVID-19 during the intervention; fifteen of them belonged to the placebo and four to the POLIUM group. Fisher's exact test indicated significant differences between HYSSOP and placebo (p<0.001) as well as POLIUM and placebo (p=0.009) groups in terms of COVID-19 confirmed by PCR tests. Cox regression model adjusted for confounders illustrated that the hazard of getting infection by COVID-19 in POLIUM and HYSSOP groups decreased by 66% (OR (95% CI): 0.34 (0.12 to 0.94); p=0.038) and 93% (OR (95% CI): 0.07 (0.01to 0.56); p=0.012) respectively, compared to placebo .Oral administration of HYSSOP and POLIUM with the other supportive health care could decrease the risk of getting COVID-19

The Use of MALDI-TOF Mass Spectrometry Technology in Molecular Analysis of Microbial Pathogenesis

Mass spectrometry is a method of evaluation used to identify which particles compose an example based on the ions' mass spectrum. Mass spectrometers can perform conventional detection and quantitation of target analytes. However, they can also be used for the rapid discovery of bacteria within a medical setting. Matrix-assisted laser desorption/ionization-time of flight mass spectrometer is one of the most prominent MS tools applied in biology, with its robust and accurate recognition of categories and types of a wide variety of Gram-positive and negative microorganisms. Mass spectrometry detection is based on determining a particular range of each kind and matching it with a comprehensive data source within the tool. Today's study describes the history and sample preparation of the MALDI-TOF MS technique. Moreover, the applications of MALDI-TOF MS microbial recognition in the center and the presence of antimicrobial resistance will be presented. Besides, the present restrictions and future use of MALDI-TOF MS in forthcoming daily scientific practice are reviewed. In this review, microorganisms will also be addressed in future clinical applications, primarily using MALDI-TOF MS in microbiology to identify and analyze antibiotic resistance

Optimizing Truss Structures Using Composite Materials under Natural Frequency Constraints with a New Hybrid Algorithm Based on Cuckoo Search and Stochastic Paint Optimizer (CSSPO)

This article highlights the absence of published paradigms hybridized by The Cuckoo Search (CS) and Stochastic Paint Optimizer (SPO) for optimizing truss structures using composite materials under natural frequency constraints. The article proposes a novel optimization algorithm called CSSPO for optimizing truss structures made of composite materials, known as fiber-reinforced polymer (FRP) composites, to address this gap. Optimization problems of truss structures under frequency constraints are recognized as challenging due to their non-linear and non-convex search spaces that contain numerous local optima. The proposed methodology produces high-quality optimal solutions with less computational effort than the original methods. The aim of this work is to compare the performance of carbon FRP (CFRP), glass FRP (GFRP), and steel using a novel hybrid algorithm to provide valuable insights and inform decision-making processes in material selection and design. Four benchmark structure trusses with natural frequency constraints were utilized to demonstrate the efficiency and robustness of the CSSPO. The numerical analysis findings indicate that the CSSPO outperforms the classical SPO and exhibits comparable or superior performance when compared to the SPO. The study highlights that implementing CFRP and GFRP composites in truss construction leads to a notable reduction in weight compared to using steel

Transcriptome Analysis Methods: From the Serial Analysis of Gene Expression and Microarray to Sequencing new Generation Methods

Up-to-date research in biology, biotechnology, and medicine requires fast genome and transcriptome analysis technologies to investigate cellular state, physiology, and activity. Gene expression is the process of generating messenger RNA copies of a gene. The transcriptome, which contains the mRNA of the cell, reflects the cell's overall gene expression pattern. Understanding the nature and frequency of each RNA molecule in a given cell under certain circumstances is necessary to examine the transcriptome. Microarray and serial analysis of gene expression are two primary techniques researchers use in transcriptome studies. Here, microarray technology and next-generation sequencing of transcripts are states of the art. Since microarray technology is limited to RNA, quantifying transcript levels and sequence information, RNA-Seq provides nearly unlimited possibilities in modern bioanalysis. Sequencing of RNA, or RNA-Seq, is now a standard method to analyze gene expression and uncover novel RNA species. In addition, aspects of RNA biogenesis and metabolism can be interrogated with specialized techniques for cDNA library preparation. The present study will introduce and compare new high-performance methods used in examining the transcriptome. This also presents a detailed description of next-generation sequencing, describes the impact of this technology on transcriptome analysis, and explains its possibilities to explore the modern RNA world

Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization

A Wireless Sensor Network (WSN) is a collection of sensor nodes that dynamically self-organizes themselves into a wireless network with- out the utilization of any pre-existing infrastructure. One of the major problems in WSNs is the energy consumption, whereby the energy will be caused to increase or reduce the network’s lifetime. In this paper, we propose an optimal routing protocol for WSN inspired by the foraging behavior of ants. The ants try to find existing paths between the source and base station. Furthermore, we have combined this behavior of ants with fuzzy logic in order for the ants to make the best decision. In other words, the fuzzy logic is applied to make the use of these paths optimal. Our algorithm uses the principles of the Fuzzy Ant Colony Optimization Routing (FACOR) to develop a suitable problem solution. The performance of our routing algorithm is evaluated by Network Simulation2 (NS2). The simulation results show that our algorithm optimizes the energy consumption amount, decrease the number of routing request packets and increase the network’s lifetime in comparison with the orig- inal AODV

Evaluation of resistance form of different preparation features on mandibular molars

Aims: Resistance form of full metal-ceramic crown is an important feature that determines longevity of these restorations. This study evaluated the resistance form of full metal-ceramic prepared with four different design features. Materials and Methods: An acrylic tooth was prepared with 20° total occlusal convergence (TOC) angle, 2.5 mm of occlusocervical dimension and a shoulder finishing line. This design lacked resistance form. The crown preparation was subsequently modified by preparing Mesial Occlusal Distal isthmus, placing occlusal inclined plane, and reducing TOC. Four metal dies from these designs were constructed by lathe machine and then 10 metal copings were fabricated for each preparation. Metal coping were cemented on metal dies with temp-bond cement. Force was applied at 45° from lingual to buccal direction with universal testing machine. Statistical analysis used: The data were evaluated by Kruskal-Wallis and non-parametric Mann-Whitney test. Results: All features increased resistance form when compare to control group. However, reduce TOC group showed greatest value of resistance. Conclusion: Within the limitation of this study, reducing the tapering of occlusocervival dimension is the most effective way in increasing resistance form, although, other features were also effective

Efficient Intelligent Energy Routing Protocol in Wireless Sensor Networks

In wireless sensor networks energy is a very important issue because these networks consist of lowpower sensor nodes. This paper proposes a new protocol to reach energy efficiency. The protocol has a different priority in energy efficiency as reducing energy consumption in nodes, prolonging lifetime of the whole network, increasing system reliability, increasing the load balance of the network, and reducing packet delays in the network. In the new protocol is proposed an intelligent routing protocol algorithm. It is based on reinforcement learning techniques. In the first step of the protocol, a new clustering method is applied to the network and the network is established using a connected graph. Then data is transmitted using the Q -value parameter of reinforcement learning technique. The simulation results show that our protocol has improvement in different parameters such as network lifetime, packet delivery, packet delay, and network balance

A non-cooperative decentralized model for Volt-VAr optimization of active distribution networks with multiple AC and DC microgrids

Volt-VAr optimization (VVO) is an important issue for distribution network operators in active distribution networks with a number of AC and DC microgrids. This paper introduces a coordinated decentralized framework with application to Volt-VAr optimization in distribution networks with multiple AC and DC microgrids in the presence of distributed energy resources (DERs). To this end, a non-cooperative coordination model is proposed so that micro-grids operators (MGOs) and distribution system operator (DSO) could minimize their own active power losses, separately. In fact, the DSO and MGOs interact together to achieve an equilibrium that satisfies their expected active power loss. In order to solve the proposed coordinated non-cooperative problem, a novel decentralized optimization approach is suggested so that the master problem is decomposed into two sub-problems from DSO and MGOs point of views. These two sub-problems are linked to each other through sharing boundary information. On this basis, the communicational and computational loads are decreased while information secrecy is guaranteed. The modified IEEE 69-bus distribution network considering a number of AC and DC MGs has been chosen with the aim of conducting several numerical analyses.©2023 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed