COMPUTATIONAL SCREENING AND MOLECULAR DOCKING OF LICHEN SECONDARY METABOLITES AGAINST SEVERE ACUTE RESPIRATORY SYNDROME-COV-2 MAIN PROTEASE AND SPIKE PROTEIN

Objective: At present, the coronavirus disease (COVID)-19 pandemic is increasing global health concerns. This coronavirus outbreak is caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Since, no specific antiviral for treatment against COVID-19, so identification of new therapeutics is an urgent need. The objective of this study is to the analysis of lichen compounds against main protease and spike protein targets of SARS-CoV-2 using in silico approach. Methods: A total of 108 lichen compounds were subjected to ADMET analysis and 14 compounds were selected based on the ADMET properties and Lipinski’s rule of five. Molecular docking was performed for screening of selected individual lichen metabolites against the main protease and spike proteins of SARS-CoV-2 by Schrodinger Glide module software. Results: Among the lead compounds, fallacinol showed the highest binding energy value of −11.83 kcal/mol against spike protein, 4-O-Demethylbarbatic acid exhibited the highest dock score of −11.67 kcal/mol against main protease. Conclusion: This study finding suggests that lichen substances may be potential inhibitors of SARS-CoV-2

HYDROGEL FORMULATION FROM CALOTROPIS GIGANTEA PLANT EXTRACT AGAINST FOOT ULCER CAUSING BACTERIA IN DIABETES

Objective: The objective of present study was to develop hydrogel formulations loaded with Calotropis gigantea leaves extract. Methods: The prepared hydrogel formulations were compliance with their color, odor, homogeneity, pH, and spreadability. Results: As all the formulations were complies with the all parameters and it can be suggest as a Good antibacterial gel. It is evident that, ethanolic extract of Calotropis gigantea showed a maximum inhibitory zone against bacteria associated with foot ulcer. Conclusions: The In vitro studies showed a quantity dependent increase in antibacterial activity against foot ulcer causing bacteria, a contraction which is higher than that produced by the control groups. These contractions were statistically significant (p<0.05), during the study with leave extract against foot ulcer causing bacteria in diabetes

Development and Evaluation of Curcumin Loaded Nanoparticles for Treatment of Diabetes

A nanometer is one billionth of a metre, hence nanotechnology is an intersection of science, engineering, and technology that works with structures and materials at the nanoscale scale, often in the range of 1 to 100 nanometers. Materials frequently display distinctive and innovative features at this scale that are distinct from those at the macroscopic or even microscopic levels. Nanotechnology is the manipulation, design, and control of materials and devices at the nanoscale to produce new products, technologies, and applications. Nanotechnology is essential to the development of tailored medication delivery systems, imaging agents, and diagnostic instruments in medicine. It offers the promise for more targeted treatments that are also less likely to cause negative effects. Since ancient times, turmeric (Curcuma longa L.) has been widely used as a spice and a remedy. Curcumin, a polyphenol that aids in the prevention and management of neurological, pulmonary, cardiovascular, metabolic, inflammatory, and autoimmune illnesses as well as some malignancies, is the primary active component of turmeric. Curcumin does have certain disadvantages, though, including limited water solubility, poor absorption, rapid metabolism, rapid systemic elimination, inadequate bioavailability subpar pharmacokinetics, low stability, and subpar penetration targeting effectiveness. A typical approach is to encapsulate curcumin in nanocarriers for targeted distribution to get over these disadvantages. Concerns have been raised about the degradation of nanocarrier products. In this study, curcumin nanoparticles and nanocurcumin were created without the aid of nanocarriers. To do this, raw turmeric rhizome was soxhlet extracted to obtain curcumin. The stock solutions of various curcumin concentrations made in dichloromethane were sonicated for varying lengths of time and included in boiling water at various flow rates. With 5.00 mg/mL of stock solution concentration, 0.10 mL/min flow rate, and 30 minutes of sonication, an average particle size of 82 04 nm was produced. Particle size seems to decline with sonication time but tends to increase with flow rate and curcumin content in the stock solution. Although nanocurcumins are amorphous, X-ray diffraction reveals crisp and powerful diffraction peaks for curcumin, suggesting its integrity and high crystallinity. The presence of all the functional groups of curcumin in nanocurcumin is confirmed by Fourier-transform infrared spectroscopy spectra. Images obtained using transmission and scanning electron microscopy display the morphology of completely spherical objects

Evaluation of dentifrice containing nano-hydroxyapatite for dentinal hypersensitivity: a randomized controlled trial

This randomized, double-blind, parallel arm study was carried out to evaluate and compare the effectiveness between nano-hydroxyapatite (HAP) and a benchmark dentifrice in reducing dentin hypersensitivity.About 36 patients were selected, randomly divided into two groups and was evaluated clinically using three different stimuli, i.e., tactile, air blast, and cold water test. The patient's responses to various stimuli were recorded using a visual analog scale at baseline and after 4 weeks.Statistical analysis was done using unpaired and paired t-tests. It was seen that patients treated in both groups showed significant reductions scores across all sensitivity measures at the end of 4 weeks.The HAP containing toothpaste was effective in reducing dentin hypersensitivity with pre-existing benchmark toothpaste tested and hence can be advocated in the management of hypersensitivity

Performance Evaluation of Stateful Firewall-Enabled SDN with Flow-Based Scheduling for Distributed Controllers

Software-defined networking (SDN) is a network approach achieved by decoupling of the control and data planes. The control plane is logically centralized and the data plane is distributed across the network elements. The real-time network is in need of the incorporation of distributed controllers to maintain distributed state information of the traffic flows. Software-based solutions aid distributed SDN controllers to handle fluctuating network traffic and the controller’s configurations are dynamically programmed in real time. In this study, SDN controllers were programmed with a stateful firewall application to provide firewall functionalities without the support of committed hardware. A stateful firewall filtered traffic based on the complete context of incoming packets; it continuously evaluated the entire context of traffic flows, looking for network entry rather than specific traffic flows. In addition, a flow-based scheduling module was implemented in the distributed controllers to improve network scalability. A network cluster was configured with three distributed controllers and we experimented with three independent network topologies. The performance of the proposed network model was evaluated by measuring and analyzing metrics such as network throughput (kbps), delay (ms) and network overhead (pkt/ms) for various combinations of controllers and topologies. The results of the analysis were determined using the mininet emulator. The findings of the performance evaluation indicate that the distributed SDN controllers performs better than a centralized controller. When comparing distributed SDN with two controllers and distributed SDN with three controllers the overall network throughput is increased by 64%, the delay is decreased by 43% and network overhead is reduced by 39%

Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network

Decoupled data and control planes in Software Defined Networks (SDN) allow them to handle an increasing number of threats by limiting harmful network links at the switching stage. As storage, high-end servers, and network devices, Network Function Virtualization (NFV) is designed to replace purpose-built network elements with VNFs (Virtualized Network Functions). A Software Defined Network Function Virtualization (SDNFV) network is designed in this paper to boost network performance. Stateful firewall services are deployed as VNFs in the SDN network in this article to offer security and boost network scalability. The SDN controller’s role is to develop a set of guidelines and rules to avoid hazardous network connectivity. Intruder assaults that employ numerous socket addresses cannot be adequately protected by these strategies. Machine learning algorithms are trained using traditional network threat intelligence data to identify potentially malicious linkages and probable attack targets. Based on conventional network data (DT), Bayesian Network (BayesNet), Naive-Bayes, C4.5, and Decision Table (DT) algorithms are used to predict the target host that will be attacked. The experimental results shows that the Bayesian Network algorithm achieved an average prediction accuracy of 92.87%, Native–Bayes Algorithm achieved an average prediction accuracy of 87.81%, C4.5 Algorithm achieved an average prediction accuracy of 84.92%, and the Decision Tree algorithm achieved an average prediction accuracy of 83.18%. There were 451 k login attempts from 178 different countries, with over 70 k source IP addresses and 40 k source port addresses recorded in a large dataset from nine honeypot servers

Caffeic acid protects rat heart mitochondria against isoproterenol-induced oxidative damage

Cardiac mitochondrial dysfunction plays an important role in the pathology of myocardial infarction. The protective effects of caffeic acid on mitochondrial dysfunction in isoproterenol-induced myocardial infarction were studied in Wistar rats. Rats were pretreated with caffeic acid (15 mg/kg) for 10 days. After the pretreatment period, isoproterenol (100 mg/kg) was subcutaneously injected to rats at an interval of 24 h for 2 days to induce myocardial infarction. Isoproterenol-induced rats showed considerable increased levels of serum troponins and heart mitochondrial lipid peroxidation products and considerable decreased glutathione peroxidase and reduced glutathione. Also, considerably decreased activities of isocitrate, succinate, malate, α-ketoglutarate, and NADH dehydrogenases and cytochrome-C-oxidase were observed in the mitochondria of myocardial-infarcted rats. The mitochondrial calcium, cholesterol, free fatty acids, and triglycerides were considerably increased and adenosine triphosphate and phospholipids were considerably decreased in isoproterenol-induced rats. Caffeic acid pretreatment showed considerable protective effects on all the biochemical parameters studied. Myocardial infarct size was much reduced in caffeic acid pretreated isoproterenol-induced rats. Transmission electron microscopic findings also confirmed the protective effects of caffeic acid. The possible mechanisms of caffeic acid on cardiac mitochondria protection might be due to decreasing free radicals, increasing multienzyme activities, reduced glutathione, and adenosine triphosphate levels and maintaining lipids and calcium. In vitro studies also confirmed the free-radical-scavenging activity of caffeic acid. Thus, caffeic acid protected rat’s heart mitochondria against isoproterenol-induced damage. This study may have a significant impact on myocardial-infarcted patients