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The recently emerged novel coronavirus, \"severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)\", caused a highly contagious disease called coronavirus disease 2019 (COVID-19). The virus was first reported from Wuhan city in China in December, 2019, which in less than three months spread throughout the globe and was declared a global pandemic by the World Health Organization (WHO) on 11th of March, 2020. So far, the ongoing pandemic severely damaged the world's most developed countries and is becoming a major threat for low- and middle-income countries. The poorest continent, Africa with the most vulnerable populations to infectious diseases, is predicted to be significantly affected by the ongoing COVID-19 outbreak. Therefore, in this review we collected and summarized the currently available literature on the epidemiology, etiology, vulnerability, preparedness and economic impact of COVID-19 in Africa, which could be useful and provide necessary information on ongoing COVID-19 pandemics in the continent. We also briefly summarized the concomitance of the COVID-19 pandemic and global warming.

Through the conventional DFT computation, we have designed new oxide double perovskites Ba 2 FeNiO 6 and Ba 2 CoNiO 6 . The structural and thermodynamic stabilities are predicted by optimizing the crystal structure and evaluation of enthalpy of formation, respectively. Then by using the optimized lattice constant, we have explored the different physical properties. The GGA + mBJ electronic band-structure illustrates Ba 2 FeNiO 6 is a half-metal with 100% spin polarization at the Fermi level. While Ba 2 CoNiO 6 shows a ferromagnetic semiconducting nature. The change in the electronic structure when Fe is replaced by Co is explained with the help of the orbital diagram and exchange interaction. The e g -e g hybridization that happens via O-p states is strong because Fe–O–Ni and Co–O–Ni bond angles are strictly 180°. The narrow bandgaps in the semiconducting channels prompted us to analyze the applicability of these materials towards thermoelectric technology. Besides this, we have investigated the dependency of transport properties on electronic band structure. The semiconducting nature in Ba 2 CoNiO 6 results in a significant ZT around 0.8 at room temperature makes it suitable for wasted-energy regeneration

Over the past several years, many healthcare applications have been developed to enhance the healthcare industry. Recent advancements in information technology and blockchain technology have revolutionized electronic healthcare research and industry. The innovation of miniaturized healthcare sensors for monitoring patient vital signs has improved and secured the human healthcare system. The increase in portable health devices has enhanced the quality of health-monitoring status both at an activity/fitness level for self-health tracking and at a medical level, providing more data to clinicians with potential for earlier diagnosis and guidance of treatment. When sharing personal medical information, data security and comfort are essential requirements for interaction with and collection of electronic medical records. However, it is hard for current systems to meet these requirements because they have inconsistent security policies and access control structures. The new solutions should be directed towards improving data access, and should be managed by the government in terms of privacy and security requirements to ensure the reliability of data for medical purposes. Blockchain paves the way for a revolution in the traditional pharmaceutical industry and benefits from unique features such as privacy and transparency of data. In this paper, we propose a novel platform for monitoring patient vital signs using smart contracts based on blockchain. The proposed system is designed and developed using hyperledger fabric, which is an enterprise-distributed ledger framework for developing blockchain-based applications. This approach provides several benefits to the patients, such as an extensive, immutable history log, and global access to medical information from anywhere at any time. The Libelium e-Health toolkit is used to acquire physiological data. The performance of the designed and developed system is evaluated in terms of transaction per second, transaction latency, and resource utilization using a standard benchmark tool known as Hyperledger Caliper. It is found that the proposed system outperforms the traditional health care system for monitoring patient data.

Heme oxygenase-1 (HO-1) is considered to be the main protein in diseases arising as a result of oxidative and inflammatory insults. Tremendous research has been carried out on HO-1 since years, pertaining its cytoprotective effect against oxidative injury and other cellular stresses. HO-1, by regulating intracellular levels of pro-oxidant heme, or by other benefits of its by-products such as carbon monoxide (CO) and biliverdin (BV) had become an important candidate protein to be up-regulated to combat diverse stressful events. Although the beneficial effects of HO-1 induction have been reported in a number of cells and tissues, a growing body of evidence indicates that this increased HO-1 expression may lead to the progression of several diseases such as neurodegeneration, carcinogenesis. But it is not clear, what accounts for the increased expression of HO-1 in cells and tissues. The observed friendly role of HO-1 in a wide range of stress conditions since times is now doubtful. Therefore, more studies are needed to elucidate the exact role of HO-1 in various stressful events. Being more concise, elucidating the effect of HO-1 up-regulation on critical genes involved in particular diseases such as cancer will help to a larger extent to comprehend the exact role of HO-1. This review will assist in understanding the dual role (protective and detrimental) of HO-1 and the signaling pathway involved and will help in unraveling the doubtful role of HO-1 induction.

The need for enhancing microbial food safety and quality, without compromising the nutritional, functional, and sensory characteristics of foods, has created an increasing interest in innovative technologies in food industry. Plasma is an emerging, green processing technology offering many potential applications and fulfills the need of the industry. The present review presents the latest developments and applications of plasma technology in food industry. Recent research investigations showed that plasma processing have caught the interest of various areas of industry including cereal, meat, poultry, dairy, fruits, vegetables, packaging, etc. Plasma processing helps to modify the food material for the desirable trait, and maintains the nutritional and textural properties in addition to microbial decontamination.

Deep learning is a sub-branch of artificial intelligence that acquires knowledge by training a neural network. It has many applications in the field of banking, automobile industry, agriculture, and healthcare industry. Deep learning has played a significant role in solving complex tasks related to computer vision, such as image classification, natural language processing, and object detection. On the other hand, optimizers also play an intrinsic role in training the deep learning model. Recent studies have proposed many deep learning models, such as VGG, ResNet, DenseNet, and ImageNet. In addition, there are many optimizers such as stochastic gradient descent (SGD), Adam, AdaDelta, Adabelief, and AdaMax. In this study, we have selected those models that require lower hardware requirements and shorter training times, which facilitates the overall training process. We have modified the Adam based optimizers and minimized the cyclic path. We have removed an additional hyper-parameter from RMSProp and observed that the optimizer works with various models. The learning rate is set to minimum and constant. The initial weights are updated after each epoch, which helps to improve the accuracy of the model. We also changed the position of the epsilon in the default Adam optimizer. By changing the position of the epsilon, it accumulates the updating process. We used various models with SGD, Adam, RMSProp, and the proposed optimization technique. The results indicate that the proposed method is effective in achieving the accuracy and works well with the state-of-the-art architectures.

Significant implications of glycogen synthase kinase-3β (GSK-3β) have been reported in various neuronal disorders and malignant cancers. GSK-3β modulates diverse protein targets through phosphorylation, and its aberrant activity leads to neurological complications as well as tumour onset. Therefore, inhibiting GSK-3β activity through active-site fitting molecules may offer a favourable strategy for intercepting these disorders. This comprehensive study used multiple assays in tandem in order to explore the most potent GSK-3β inhibitor. Following structural similarity screening, 135 molecular docking and 135 standard MM-GBSA experiments were performed using AZD1080, a known inhibitor as standard. Among the 32 molecules demonstrating a stronger binding affinity than reference, only the two most potent molecules were chosen and their binding free energy was compared to AZD1080 using the Desmond trajectory clustering and eventual MM-GBSA. Additionally, the interaction status of these molecules and AZD1080 with GSK-3β was explored post-molecular dynamics. The stability of the strongest molecule (most potent) was evaluated in the active site of the above-mentioned kinase keeping its apo-form as reference. Notably, the e-Pharmacophores mapping was performed to address the level of complementarity of the most potent molecule and AZD1080 with the functional site of GSK-3β. Using various techniques, we identified the molecule with PubChem CID: 11167509 as the strongest molecule for obstructing GSK-3β, which may serve as a promising therapeutic after the meticulous evaluation on diverse models.

As an approach to the exploration of cold-active enzymes, in this study, we isolated a cold-active protease produced by psychrotrophic bacteria from glacial soils of Thajwas Glacier, Himalayas. The isolated strain BO1, identified as Bacillus pumilus , grew well within a temperature range of 4–30 °C. After its qualitative and quantitative screening, the cold-active protease (Apr-BO1) was purified. The Apr-BO1 had a molecular mass of 38 kDa and showed maximum (37.02 U/mg) specific activity at 20 °C, with casein as substrate. It was stable and active between the temperature range of 5–35 °C and pH 6.0–12.0, with an optimum temperature of 20 °C at pH 9.0. The Apr-BO1 had low K m value of 1.0 mg/ml and V max 10.0 µmol/ml/min. Moreover, it displayed better tolerance to organic solvents, surfactants, metal ions and reducing agents than most alkaline proteases. The results exhibited that it effectively removed the stains even in a cold wash and could be considered a decent detergent additive. Furthermore, through protein modelling, the structure of this protease was generated from template, subtilisin E of Bacillus subtilis (PDB ID: 3WHI), and different methods checked its quality. For the first time, this study reported the protein sequence for psychrotrophic Apr-BO1 and brought forth its novelty among other cold-active proteases.

The biosynthesis of algal-based zinc oxide (ZnO) nanoparticles has shown several advantages over traditional physico-chemical methods, such as lower cost, less toxicity, and greater sustainability. In the current study, bioactive molecules present in Spirogyra hyalina extract were exploited for the biofabrication and capping of ZnO NPs, using zinc acetate dihydrate and zinc nitrate hexahydrate as precursors. The newly biosynthesized ZnO NPs were characterized for structural and optical changes through UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDX). A color change in the reaction mixture from light yellow to white indicated the successful biofabrication of ZnO NPs. The UV-Vis absorption spectrum peaks at 358 nm (from zinc acetate) and 363 nm (from zinc nitrate) of ZnO NPs confirmed that optical changes were caused by a blue shift near the band edges. The extremely crystalline and hexagonal Wurtzite structure of ZnO NPs was confirmed by XRD. The involvement of bioactive metabolites from algae in the bioreduction and capping of NPs was demonstrated by FTIR investigation. The SEM results revealed spherical-shaped ZnO NPs. In addition to this, the antibacterial and antioxidant activity of the ZnO NPs was investigated. ZnO NPs showed remarkable antibacterial efficacy against both Gram-positive and Gram-negative bacteria. The DPPH test revealed the strong antioxidant activity of ZnO NPs.

Nanotechnology explores a variety of promising approaches in the area of material sciences on a molecular level, and silver nanoparticles (AgNPs) are of leading interest in the present scenario. This review is a comprehensive contribution in the field of green synthesis, characterization, and biological activities of AgNPs using different biological sources. Biosynthesis of AgNPs can be accomplished by physical, chemical, and green synthesis; however, synthesis via biological precursors has shown remarkable outcomes. In available reported data, these entities are used as reducing agents where the synthesized NPs are characterized by ultraviolet-visible and Fourier-transform infrared spectra and X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. Modulation of metals to a nanoscale drastically changes their chemical, physical, and optical properties, and is exploited further via antibacterial, antifungal, anticancer, antioxidant, and cardioprotective activities. Results showed excellent growth inhibition of the microorganism. Novel outcomes of green synthesis in the field of nanotechnology are appreciable where the synthesis and design of NPs have proven potential outcomes in diverse fields. The study of green synthesis can be extended to conduct the in silco and in vitro research to confirm these findings.