5G and Beyond 5G networks (B5G) face the greatest obstacle to ensure accessibility with all categories of users. A significant part of the emerging wireless networks will greatly facilitate connectivity, and cooperation in high-speed communications from Unmanned Aviation Vehicles (UAVs) is expected. UAV has excellent features such as versatile delivery, simple line of sight (LOS) connecting, gradual independence and connectivity architecture speeds, and fixed framework communication systems. Given that many UAVs can achieve specific coverage for surface user terminals (UTs), one problem is how they can be implemented optimally. According to critical constraints, the implementation task was shaped as minimization, including the numbers of UAVs and the optimization of their network load: UAV should form a secure network structure and sustain links with the specified base stations (BSs). The challenge has been split into subtasks to address this problem of optimization with a core framework. The Unified Greedy Quest Algorithm for the Internet of Medical Things (UGQA-IoMT) algorithm is used for telemedicine applications and achieves a minimum number of UAVs and optimal places. The algorithm proposed refers to various scenarios in which UAVs are installed by themselves or with the set BSs, irrespective of the UT deployment. The performance gains in mean SNR of -3 dB, network load stability ratio of 99.89%, and coverage ratio of 97.5% are validated in coherent simulations of the proposed methodology for the real-time implementation.
Trichosanthes cucumerina (Cucurbitaceae) commonly known as Snake gourd or Labu
Ular is considered the largest genre in the Cucurbitaceae family and is mainly found in the
southeast areas of Asia. It has been used in Ayurvedic medicine as a treatment for certain
diseases such as Diabetes mellitus, but these acclaims lack scientific-based evidence. In
this study, water and ethanol extracts of three parts of Trichosanthes cucumerina namely;
whole vegetable, peels, and seeds, were assessed for toxicity through a cell viability assay
using 3T3-L1 pre-adipocytes model which revealed a maximum toleration concentration
of 0.063 mg/mL. The extracts were further tested on adipocytes’ differentiation and
positively showed a stimulation of lipid droplets formation during adipogenesis and
This study was conducted to evaluate the phytochemical contents and antimalarial properties of the oils extracted from the leaves of Malaysian Plectranthus amboinicus in mice infected with Plasmodium berghei. The essential oils were extracted and prepared by using steam distillation technique and subjected to phytochemical screening by using GC-MS. Antimalarial activity of different extract doses of the essential oil was tested in vivo in ICR mice infected with Plasmodium berghei (PZZ1/100) during early, established and residual infections. In all, 5 compounds made up 88.34% of total oil and the major chemical compounds were carvacrol (85.14%), thymoquinone (1.65%), terpinen-4-ol (0.70%), octenol (0.62%) and thymol (0.23%). Antimalarial assay showed this essential oil as a potential prophylactic agent with the percentage chemosuppression of 45.23%, 18.28%, 45.38% and 58.26% while treated with 50, 200, 400 and 1000 µL/kg respectively of essential oil and curative agent with percentage of chemo suppression of 54.10%, 47.35%, 56.75% and 65.38% while treated with the above dose of essential oil. Statistically no reduction of parasitemia was calculated for suppressive test. The extract has prophylactic and curative effects on P.berghei in mice
The current world faces a considerable traffic rate on roads due to the increase in various types of vehicles. It caused emergency vehicles to delay and increasing the patients' health risk factor. Internet of vehicle-based artificial neural network (IoV-ANN) has been proposed for effective health autonomous system in medical things. The proposed IoV-ANN provides a secure network to monitor and track the vehicle's motion using the global positioning system. It consists of an autonomous system which is enabled with an artificial neural network (ANN). ANN model has three layers. First layers collect the data using IoV sensors. Second or hidden layers process the sensor data, predict the road's traffic condition and reroute the emergency vehicle to an exact route. IoV-ANN helps to reduce road congestion in this article to enhance the timely functioning of an emergency vehicle. ANN categorizes the congestion networks of traffic. Traffic restrictions such as changing the queue gap in the road signals and the alternative roads are altered automatically due to congestion. It allows the government to develop ideas for alternate routes to enhance traffic control. The output layer gives commands to the driver autonomously. The simulation analysis of the proposed method proved that the system could work independently. The IoV-ANN achieves the highest performance rate of (97.89%), with a reduced error rate (9.12%) traffic congestion rate (10.31%), travel period (32 s), vehicle detection rate (93.61%), classification accuracy (95.02%), MAPE (8.4%), throughput rate (93.50%) when compared to other popular methods.
Raloxifene hydrochloride, a highly effective drug for the treatment of invasive breast cancer and osteoporosis in post-menopausal women, shows poor oral bioavailability of 2%. The aim of this study was to develop, statistically optimize, and characterize raloxifene hydrochloride-loaded transfersomes for transdermal delivery, in order to overcome the poor bioavailability issue with the drug. A response surface methodology experimental design was applied for the optimization of transfersomes, using Box-Behnken experimental design. Phospholipon(®) 90G, sodium deoxycholate, and sonication time, each at three levels, were selected as independent variables, while entrapment efficiency, vesicle size, and transdermal flux were identified as dependent variables. The formulation was characterized by surface morphology and shape, particle size, and zeta potential. Ex vivo transdermal flux was determined using a Hanson diffusion cell assembly, with rat skin as a barrier medium. Transfersomes from the optimized formulation were found to have spherical, unilamellar structures, with a homogeneous distribution and low polydispersity index (0.08). They had a particle size of 134±9 nM, with an entrapment efficiency of 91.00%±4.90%, and transdermal flux of 6.5±1.1 μg/cm(2)/hour. Raloxifene hydrochloride-loaded transfersomes proved significantly superior in terms of amount of drug permeated and deposited in the skin, with enhancement ratios of 6.25±1.50 and 9.25±2.40, respectively, when compared with drug-loaded conventional liposomes, and an ethanolic phosphate buffer saline. Differential scanning calorimetry study revealed a greater change in skin structure, compared with a control sample, during the ex vivo drug diffusion study. Further, confocal laser scanning microscopy proved an enhanced permeation of coumarin-6-loaded transfersomes, to a depth of approximately160 μM, as compared with rigid liposomes. These ex vivo findings proved that a raloxifene hydrochloride-loaded transfersome formulation could be a superior alternative to oral delivery of the drug.
Documented to exhibit cytotoxicity and poor oral bioavailability, alpha-mangostin was encapsulated into PLGA microspheres with optimization of formulation using response surface methodology. Mixed levels of four factors Face central composite design was employed to evaluate critical formulation variables. With 30 runs, optimized formula was 1% w/v polyvinyl alcohol, 1:10 ratio of oil to aqueous and sonicated at 2 and 5 min time for primary and secondary emulsion, respectively. Optimized responses for encapsulation efficiency, particle size and polydispersity index were found to be 39.12 ± 0.01%, 2.06 ± 0.017 µm and 0.95 ± 0.009, respectively, which matched values predicted by mathematical models. About 44.4% of the encapsulated alpha-mangostin was released over 4 weeks. Thermal analysis of the microspheres showed physical conversion of alpha-mangostin from crystallinity to amorphous with encapsulated one had lower in vitro cytotoxicity than free alpha-mangostin. Aerodynamic diameter (784.3 ± 7.5 nm) of this alpha-mangostin microsphere suggests suitability for peripheral pulmonary delivery.
In attempt to discover a small active compound that could promote adipogenesis, we investigated the ability of cinnamon (Cinnamomum zeylanicum) extracts to stimulate 3T3-L1 preadipocytes, In this study, we designed an experiment by replacing insulin with cinnamon extracts. The differentiated of 3T3-L1 adipocytes were monitored using oil red O staining method. Induction of adipocyte formation by cinnamtannin B1 or water extract gave the similar effects to insulin activity in adipogenesis.
The antioxidant activity and the total phenolic content, as well as the influence of petroleum ether, chloroform and methanol extracts from the leaves of Gynotroches axillaris, on microorganisms were studied. The total phenolic contents were evaluated by using Folin-Ciocalteu reagent and the obtained values ranged from 70.0 to 620 mg GAE/g. The efficiency of antioxidation, which was identified through the scavenging of free radical DPPH, exhibited that the highest IC50 was in the methanolic extract (44.7 µg/mL) as compared to the standard ascorbic acid (25.83 µg/mL) and to standard BHT (17.2 µg/mL). In vitro antimicrobial activity of extracts was tested against Gram-negative bacteria, Gram-positive bacteria and fungi. Methanol extract showed activity in the range (225-900 μg/mL) with both types, while petroleum ether and chloroform extracts were only active with Bacillus subtilis. The three extracts strongly inhibited all fungi with activity 225-450 μg/mL. The toxicity test against brine shrimps indicated that all extracts were non-toxic with LC50 value more than 1000 µg/mL. The finding of this study supports the safety of these extracts to be used in medical treatments.
The leaves of Gynotroches axillaris were chemically and biologically studied. Sequential extraction of the leaves using petroleum ether, chloroform, and methanol afforded three extracts. Purification of pet. ether extract yielded, squalene and β-amyrin palmitate as the major compounds, together with palmitic acid and myristic acid as the minor components. The methanol extract yielded two flavonoids, quercitrin and epicatechin. The isolated compounds were characterized by MS, IR and NMR (1D and 2D). Anti-acetyl cholinesterase screening using TLC bio-autography assay showed that palmitic acid and myristic acid were the strongest inhibition with detection limit 1.14 and 1.28 μ/g/ 5 μL respectively. Antibacterial against Gram-positive and negative and antifungal activities exhibited that β-amyrin palmitate was the strongest (450-225 μ/mL) against all the tested microbes. The tyrosinase inhibition assay of extracts and the pure compounds were screened against tyrosinase enzyme. The inhibition percentage (I%) of methanol extract against tyrosinase enzyme was stronger than the other extracts with value 68.4%. Quercitrin (59%) was found to be the highest in the tyrosinase inhibition activity amongst the pure compounds. To the best of our knowledge, this is first report on the phytochemicals, tyrosinase inhibition, anti-acetycholinesterase and antimicrobial activities of the leaves of G. axillaris.
Supercritical carbon dioxide (SC-CO2) extraction of fucoxanthin is more advantageous over conventional solvent extraction as it is less toxic, less hazardous to the environment and preserves the bioactivity of fucoxanthin. A face-centered central composite design (FCCCD) based on response surface methodology (RSM) was employed for SC-CO2 extraction of oils and fucoxanthin from the brown seaweed Sargassum binderi, with ethanol as a co- solvent. Three independent parameters namely, extraction temperature (A: 40, 50, 60oC), pressure (B: 2900, 3625, 4350 psig and particle size (C: 90, 500 and 1000 µm) were investigated to optimize extraction oil yields (EOY) and fucoxanthin yields (FY). A regression model was developed, tested for quality of fit (R2) and expressed in the form of 3D response surface curve and 2D contour. The optimum extraction conditions were obtained at extraction temperature (A) 50oC, pressure (B) 3625 psig and particle size (C) 500 µm. Under these conditions, optimal EOY and FY were 10.04 mg/g and 3188.99 µg/g, respectively. The difference between the lowest and the highest response in EOY and FY were 5.44 – 10.04 mg/g and 2109.10 - 3188.90 µg/g, respectively. The lowest yields were identified at 60oC, 2900 psig and 1000 µm. The regression models generated showing interactions between the variables and EOY and FY response were significant as tested by ANOVA (p < 0.0005 and p < 0.0007, respectively) with high R2 values (0.9848 and 0.9829, respectively). Interactions between the parameters had a strong synergistic effect on EOY and FY values, as indicated by the 3D response surface curve and 2D contour. The experimental results matched the predicted results closely. This indicated the suitability of the models developed and the success of FCCCD under RSM in optimizing the S. binderi extraction conditions.
The purpose of this study was to determine the phytochemical constituents and pharmacological properties of Garcinia xanthochymus which is commonly known as gamboge, yellow mangosteen and false mangosteen. The phytochemicals constituents, pharmacological benefits and their mechanisms were previously presented in a number of studies including in vitro and in vivo studies from published books, journals and articles. The literature used in this review were published between 1970 and 2017 and were available from databases such as Google Scholar, ScienceDirect, Scopus, PubMed, ProQuest and others. The chemical structures in this paper are drawn using ChemBio Ultra 14.0. G. xanthocymus contains many phytochemicals that can be extracted from its constituent parts; the bark, fruits, leaves, roots, twigs and seeds. The predominant extracted phytochemicals are xanthones, benzophenones, flavonoids, depsidones and isocoumarins. These phytochemicals contribute to the pharmacological activities of this plant as an antioxidant, antidiabetic, and for having Nerve Growth Factor-potentiating, antimicrobial and cytotoxic activities. This species contains a broad range of phytochemicals with curative properties that can be greatly beneficial to man. Notably, this review focused on those studies of the pharmacological effects of this plant that were concentrated on by previous researchers. Thus, further study needs to be done on G. xanthocymus in order to unlock additional potential activities and to pinpoint the exact mechanisms of how these activities can be induced, leading to new drug discoveries which have fewer side effects.
By 9 February 2021, the Coronavirus has killed 2,336,650 people worldwide and it has been predicted that this number continues to increase in year 2021. The study aimed to identify therapeutic approaches and drugs that can potentially be used as interventions in Coronavirus 2019 (COVID-19) management. A systematic scoping review was conducted. Articles reporting clinical evidence of therapeutic management of COVID-19 were selected from three different research databases (Google Scholar, PubMed, and Science Direct). From the database search, 31 articles were selected based on the study inclusion and exclusion criteria. This review paper showed that remdesivir and ivermectin significantly reduced viral ribonucleic acid (RNA) activity. On the other hand, convalescent plasma (CP) significantly improved COVID-19 clinical symptoms. Additionally, the use of corticosteroid increased survival rates in COVID-19 patients with acute respiratory distress syndrome (ARDS). Findings also indicated that both hydroxychloroquine and favipiravir were effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, lopinavir-ritonavir combination was not effective against COVID-19. Finally, ribavirin, galidesivir, and sofosbuvir showed potential therapeutic benefit in treating COVID-19, but there is a lack of clinical evidence on their effectiveness against SARS-CoV-2. Remdesivir, ivermectin, favipiravir, hydroxychloroquine, dexamethasone, methylprednisolone, and CP are the therapeutic agents that can potentially be used in COVID-19 management.
The internet of reality or augmented reality has been considered a breakthrough and an outstanding critical mutation with an emphasis on data mining leading to dismantling of some of its assumptions among several of its stakeholders. In this work, we study the pillars of these technologies connected to web usage as the Internet of things (IoT) system's healthcare infrastructure. We used several data mining techniques to evaluate the online advertisement data set, which can be categorized as high dimensional with 1,553 attributes, and the imbalanced data set, which automatically simulates an IoT discrimination problem. The proposed methodology applies Fischer linear discrimination analysis (FLDA) and quadratic discrimination analysis (QDA) within random projection (RP) filters to compare our runtime and accuracy with support vector machine (SVM), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) in IoT-based systems. Finally, the impact on number of projections was practically experimented, and the sensitivity of both FLDA and QDA with regard to precision and runtime was found to be challenging. The modeling results show not only improved accuracy, but also runtime improvements. When compared with SVM, KNN, and MLP in QDA and FLDA, runtime shortens by 20 times in our chosen data set simulated for a healthcare framework. The RP filtering in the preprocessing stage of the attribute selection, fulfilling the model's runtime, is a standpoint in the IoT industry. Index Terms: Data Mining, Random Projection, Fischer Linear Discriminant Analysis, Online Advertisement Dataset, Quadratic Discriminant Analysis, Feature Selection, Internet of Things.
Smart applications and intelligent systems are being developed that are self-reliant, adaptive, and knowledge-based in nature. Emergency and disaster management, aerospace, healthcare, IoT, and mobile applications, among them, revolutionize the world of computing. Applications with a large number of growing devices have transformed the current design of centralized cloud impractical. Despite the use of 5G technology, delay-sensitive applications and cloud cannot go parallel due to exceeding threshold values of certain parameters like latency, bandwidth, response time, etc. Middleware proves to be a better solution to cope up with these issues while satisfying the high requirements task offloading standards. Fog computing is recommended middleware in this research article in view of the fact that it provides the services to the edge of the network; delay-sensitive applications can be entertained effectively. On the contrary, fog nodes contain a limited set of resources that may not process all tasks, especially of computation-intensive applications. Additionally, fog is not the replacement of the cloud, rather supplement to the cloud, both behave like counterparts and offer their services correspondingly to compliance the task needs but fog computing has relatively closer proximity to the devices comparatively cloud. The problem arises when a decision needs to take what is to be offloaded: data, computation, or application, and more specifically where to offload: either fog or cloud and how much to offload. Fog-cloud collaboration is stochastic in terms of task-related attributes like task size, duration, arrival rate, and required resources. Dynamic task offloading becomes crucial in order to utilize the resources at fog and cloud to improve QoS. Since this formation of task offloading policy is a bit complex in nature, this problem is addressed in the research article and proposes an intelligent task offloading model. Simulation results demonstrate the authenticity of the proposed logistic regression model acquiring 86% accuracy compared to other algorithms and confidence in the predictive task offloading policy by making sure process consistency and reliability.
Malaria is a mosquito-borne disease caused by parasitic protozoa from the genus of Plasmodium. The protozoans have developed resistance against many of current drugs. It is urgent to find an alternative source of new antimalarial agent. In the effort to discover new antimalarial agents, this research has been conducted on Plectranthus amboinicus.
Friedelin and lanosterol have been isolated from twigs of Garcinia prainiana. Their structures were elucidated by spectroscopic methods. The compounds were examined for their effects on 3T3-L1 adipocytes. In the MTT assay, it was found that the compounds had no cytotoxic effects up to 25 µM. Adipocyte differentiation analysis was carried out by Oil Red O staining method. In the presence of adipogenic cocktail (MDI), it was found that friedelin and lanosterol enhanced intracellular fat accumulation by 2.02 and 2.18-fold, respectively, compared with the vehicle-treated cells. Deoxyglucose uptake assay was used to examine the insulin sensitivity of adipocytes in the presence of the compounds. It was found that friedelin was able to stimulate glucose uptake up to 1.8-fold compared with insulin-treated cells. It was suggested that friedelin and lanosterol may be beneficial to mimic insulin action that would be useful in the treatment of diabetes type 2 patients.
A polyisoprenylated ketone named enervosanone has been isolated from the stem bark of Calophyllum enervosum together with three known compounds, cambogin, osajaxanthone and epicatechin. Their structures were determined by spectroscopic analysis. The antimicrobial evaluations of the isolated compounds were also reported.
Various parts of Garcinia mangostana Linn., including its pericarp, have been traditionally used to treat a variety of ailments. In an attempt to establish its medicinal value, the present study was carried out to determine the hypoglycaemic potential of G. mangostana pericarp ethanolic extract (GME) using the streptozotocin-induced (STZ) diabetic rats.
This study aims to investigate the use of palm olein as the oil phase for betamethasone 17-valerate (BV) emulsions. The physicochemical properties of the formulations were characterized. In vitro drug release study was performed with the Hanson Vertical Diffusion Cell System; the samples were quantified with HPLC and the results were compared with commercial products. Optimized emulsion formulations were subjected to stability studies for 3 months at temperatures of 4, 25, and 40°C; the betamethasone 17-valerate content was analyzed using HPLC. The formulations produced mean particle size of 2-4 μm, viscosities of 50-250 mPa.s, and zeta potential between -45 and -68 mV. The rheological analyses showed that the emulsions exhibited pseudoplastic and viscoelastic behavior. The in vitro release of BV from palm olein emulsion through cellulose acetate was 4.5 times higher than that of commercial products and more BV molecules deposited in rat skin. Less than 4% of the drug was degraded in the formulations during the 3-month period when they were subjected to the three different temperatures. These findings indicate that palm olein-in-water emulsion can be an alternative vehicle for topical drug delivery system with superior permeability.