All the plants and their secondary metabolites used in the present study were obtained from Ayurveda, with historical roots in the Indian subcontinent. The selected secondary metabolites have been ...experimentally validated and reported as potent antiviral agents against genetically-close human viruses. The plants have also been used as a folk medicine to treat cold, cough, asthma, bronchitis, and severe acute respiratory syndrome in India and across the globe since time immemorial. The present study aimed to assess the repurposing possibility of potent antiviral compounds with SARS-CoV-2 target proteins and also with host-specific receptor and activator protease that facilitates the viral entry into the host body. Molecular docking (MDc) was performed to study molecular affinities of antiviral compounds with aforesaid target proteins. The top-scoring conformations identified through docking analysis were further validated by 100 ns molecular dynamic (MD) simulation run. The stability of the conformation was studied in detail by investigating the binding free energy using MM-PBSA method. Finally, the binding affinities of all the compounds were also compared with a reference ligand, remdesivir, against the target protein RdRp. Additionally, pharmacophore features, 3D structure alignment of potent compounds and Bayesian machine learning model were also used to support the MDc and MD simulation. Overall, the study emphasized that curcumin possesses a strong binding ability with host-specific receptors, furin and ACE2. In contrast, gingerol has shown strong interactions with spike protein, and RdRp and quercetin with main protease (Mpro) of SARS-CoV-2. In fact, all these target proteins play an essential role in mediating viral replication, and therefore, compounds targeting aforesaid target proteins are expected to block the viral replication and transcription. Overall, gingerol, curcumin and quercetin own multitarget binding ability that can be used alone or in combination to enhance therapeutic efficacy against COVID-19. The obtained results encourage further in vitro and in vivo investigations and also support the traditional use of antiviral plants preventively.
•MD simulation revealed Ayurvedic medicinal plants possess anti SARS-CoV-2 activity.•Gingerol showed high binding affinity for SARS-CoV-2 spike RBD protein and RdRp.•Curcumin interact strongly with host ACE2 and furin and thus may be effective against COVID-19.•Gingerol, quercetin and curcumin possess repurposing potential against SARS-CoV-2.•MD result of bioactive compounds was further validated by reference drug, Remdesivir with RdRp.
Bioactive peptides can be defined as isolated small fragments of proteins which provide some physiological health benefits. They act as potential modifiers reducing the risk of many chronic diseases. ...To the best of our knowledge, limited literature is available for the methods of isolation of these peptides from different protein sources with their in vitro and vivo physiological effects. Also, there is a need to adopt healthy lifestyle choices for prevention of diseases, to counter increase in consumption of functional foods and nutraceuticals day-by-day. Thus, these peptides play a major role in the development of various functional foods. In the present study, attempts are made to review different physiological effects from peptides. Also, effects of processing on the peptides are discussed with special emphasis on its bioavailability, safety and future application for further development.
Fog computing paradigm extends the storage, networking, and computing facilities of the cloud computing toward the edge of the networks while offloading the cloud data centers and reducing service ...latency to the end users. However, the characteristics of fog computing arise new security and privacy challenges. The existing security and privacy measurements for cloud computing cannot be directly applied to the fog computing due to its features, such as mobility, heterogeneity, and large-scale geo-distribution. This paper provides an overview of existing security and privacy concerns, particularly for the fog computing. Afterward, this survey highlights ongoing research effort, open challenges, and research trends in privacy and security issues for fog computing.
The Assam Roofed Turtle, Pangshura sylhetensis is an endangered and least studied species endemic to India and Bangladesh. The present study decodes the first complete mitochondrial genome of P. ...sylhetensis (16,568 bp) by using next-generation sequencing. The assembly encodes 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), two ribosomal RNAs (rRNAs), and one control region (CR). Most of the genes were encoded on the majority strand, except NADH dehydrogenase subunit 6 (nad6) and eight tRNAs. All PCGs start with an ATG initiation codon, except for Cytochrome oxidase subunit 1 (cox1) and NADH dehydrogenase subunit 5 (nad5), which both start with GTG codon. The study also found the typical cloverleaf secondary structures in most of the predicted tRNA structures, except for serine (trnS1) which lacks of conventional DHU arm and loop. Both Bayesian and maximum-likelihood phylogenetic inference using 13 concatenated PCGs demonstrated strong support for the monophyly of all 52 Testudines species within their respective families and revealed Batagur trivittata as the nearest neighbor of P. sylhetensis. The mitogenomic phylogeny with other amniotes is congruent with previous research, supporting the sister relationship of Testudines and Archosaurians (birds and crocodilians). Additionally, the mitochondrial Gene Order (GO) analysis indicated plesiomorphy with the typical vertebrate GO in most of the Testudines species.
Bears are iconic mammals with a complex evolutionary history. Natural bear hybrids and studies of few nuclear genes indicate that gene flow among bears may be more common than expected and not ...limited to polar and brown bears. Here we present a genome analysis of the bear family with representatives of all living species. Phylogenomic analyses of 869 mega base pairs divided into 18,621 genome fragments yielded a well-resolved coalescent species tree despite signals for extensive gene flow across species. However, genome analyses using different statistical methods show that gene flow is not limited to closely related species pairs. Strong ancestral gene flow between the Asiatic black bear and the ancestor to polar, brown and American black bear explains uncertainties in reconstructing the bear phylogeny. Gene flow across the bear clade may be mediated by intermediate species such as the geographically wide-spread brown bears leading to large amounts of phylogenetic conflict. Genome-scale analyses lead to a more complete understanding of complex evolutionary processes. Evidence for extensive inter-specific gene flow, found also in other animal species, necessitates shifting the attention from speciation processes achieving genome-wide reproductive isolation to the selective processes that maintain species divergence in the face of gene flow.
Natural fiber-based hybrid composites have been explored in this study as possible structural materials. Detailed investigation of sound insulation property of a series of hybrid and nonhybrid ...composites has been carried out using impedance tube having four microphones. Hybrid biocomposites were prepared with chopped and randomly oriented coir and banana fibers. Polypropylene was used as a matrix and compression molding technique was used for composite fabrication. The ratio of both fibers in hybrid biocomposites was maintained at 1:1. The effect of fiber loading and arrangement of fibers on sound insulation property of composites was investigated. It was found that fiber loading and hybridization bear a significant role in improving sound insulation property of hybrid composites. Experimental results showed that increase in fiber loading considerably improved the sound insulation up to a certain limit. The sound insulation property of hybrid and nonhybrid composites has been subsequently discussed. The results showed that sound insulation performance can be customized by structural parameters such as volume fraction, dispersion, ratio, and placement of fibers with respect to sound source, without necessitating a change in raw material.
This review aims to take stock of the extant international human resource management (IHRM) research by identifying gaps and mapping out a future research agenda for IHRM scholars. Based on an ...extensive bibliographic analysis of 1924 articles published in the field of IHRM, we confirm three key clusters of existing knowledge: (a) expatriation management; (b) global human capital; and (c) international human resource policies and practices. Moreover, using scientific mapping tools, sub-themes in each cluster are classified, issues and deficiencies are examined and discussed. Furthermore, a future IHRM research agenda is proposed, including managing global work to cope with the adverse social and economic conditions, and to localize emerging market multinationals; building global human capital towards developing sustainability and nurturing digital multinationals; developing new perspectives and theories on transferring IHRM policies and practices; and embracing rigorous or innovative empirical methods in the field.
Add a touch of data analytics to your healthcare systems and get insightful outcomesKey FeaturesPerform healthcare analytics with Python and SQLBuild predictive models on real healthcare data with ...pandas and scikit-learnUse analytics to improve healthcare performanceBook DescriptionIn recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes.
This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed.
By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples.What you will learnGain valuable insight into healthcare incentives, finances, and legislationDiscover the connection between machine learning and healthcare processesUse SQL and Python to analyze dataMeasure healthcare quality and provider performanceIdentify features and attributes to build successful healthcare modelsBuild predictive models using real-world healthcare dataBecome an expert in predictive modeling with structured clinical dataSee what lies ahead for healthcare analyticsWho this book is forHealthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
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