Garden City University

Kar T., Narsaria U., Basak S., Deb D., Castiglione F., Mueller D.M., Srivastava A.P.

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.

George R.V., Harsh H.O., Ray P., Babu A.K.

As competition between organizations are evolving into competition between supply chains, to survive and indeed grow, it is necessary to deliver added value to customers. Traceability has emerged as one of the key measures of operational efficiencies within supply chains and ultimately, customer service. Over the years, organizations have deployed number of methods in delivering food traceability. This paper examines major methods of food traceability currently in existence and proposes a restaurant prototype for implementing more reliable food traceability using Blockchain and product identifiers. The prototype captures data from various stakeholders across the food supply chain, segregates it and finally, applies the Food Quality Index (FQI) algorithm to generate an FQI value. The FQI value helps in identifying whether the food is good for consumption on specified parameters. FQI value is generated based on extant standard storage and handling regulations specified by food safety authorities, and checks whether value so derived, is within the permissible range. The prototype helps in grading food quality for human consumption besides strengthening food (product) traceability. This prototype can be customized to address future requirements of traceability triggered through new information emanating from any stakeholder or the node in the supply chain.

Castiglione F., Deb D., Srivastava A.P., Liò P., Liso A.

BackgroundImmune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies.AimStudies of the insurgence of immunity is at the core of both SARS-CoV-2 vaccine development and therapies. This paper attempts to describe the insurgence (and the span) of immunity in COVID-19 at the population level by developing an in-silico model. We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor, and age in an artificially infected population on the course of the disease.MethodsWe use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degrees of immune competence. We use a parameter set to reproduce known inter-patient variability and general epidemiological statistics.ResultsBy assuming the viremia at day 30 of the infection to be the proxy for lethality, we reproduce in-silico several clinical observations and identify critical factors in the statistical evolution of the infection. In particular, we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection are a prognostic factor for determining the clinical outcome of the infection. Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of modeling the immune response at individual and population levels. The model developed can explain and interpret observed patterns of infection and makes verifiable temporal predictions. Within the limitations imposed by the simulated environment, this work proposes quantitatively that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population. In this work, we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunosenescence.

Chatterjee A., Paul A., Unnati G.M., Rajput R., Biswas T., Kar T., Basak S., Mishra N., Pandey A., Srivastava A.P.

Mitogen Activated Protein Kinase (MAPK) cascade is a fundamental pathway in organisms for signal transduction. Though it is well characterized in various plants, there is no systematic study of this cascade in tea. In this study, 5 genes of Mitogen Activated Protein Kinase Kinase (MKK) and 16 genes of Mitogen Activated Protein Kinase (MPK) in Camellia sinensis were found through a genome-wide search taking Arabidopsis thaliana as the reference genome. Also, phylogenetic relationships along with structural analysis which includes gene structure, location as well as protein conserved motifs and domains, were systematically examined and further, predictions were validated by the results. The plant species taken for comparative study clearly displayed segmental duplication, which was a significant candidate for MAPK cascade expansion. Also, functional interaction was carried out in C. sinensis based on the orthologous genes in Arabidopsis. The expression profiles linked to various stress treatments revealed wide involvement of MAPK and MAPKK genes from Tea in response to various abiotic factors. In addition, the expression of these genes was analysed in various tissues. This study provides the targets for further comprehensive identification, functional study, and also contributed for a better understanding of the MAPK cascade regulatory network in C. sinensis.

Satwik P.M., Sundram M.

Weather forecasting is a real time challenge that has been proven to be worst among the disaster in world over the last decade. Prediction begins even more complicated due to the ever-changing weather conditions. Many attributes have been negotiated with weather forecasting data that consider related attributes as independent variables. It is the cause of such natural disasters floods and droughts that meet people across globe every year. The higher accuracy of predicting rainfall is importance for countries like India as their economy depending on agriculture. Because of the mighty nature, few Statistical and Mathematical techniques fail to provide good rainfall accuracy prediction. The imbalance data of rainfall makes Artificial Neural Network, Recurrent Neural Networks (RNN), MANN’s (LSTM, GRU, NTM) the best process. An effective climate analysis is required to understand the various factors that contribute to climate change. It is therefore necessary to identify the relationship among these qualities to better understanding of the weather data. The purpose of this paper to give non-professionals easy access to strategies as well methods used in the field of rain forecast and compare various results of various methods and algorithms used in research.

Behera A., Awasthi S.

This study evaluated the anticancer, antimicrobial, and hemolytic potential of zinc oxide nanoparticles (ZnO-NPs) synthesized from a novel medicinal plant Lagerstroemia indica. The formation of synthesized ZnO-NPs was confirmed by ultraviolet–visible (UV–Vis) spectroscopy at a peak of 302 nm, and the X-ray diffraction (XRD) analysis confirmed particle size of 19.66 nm. The transmission electron microscopy (TEM) and scanning electron microscope (SEM) with energy dispersive spectroscopy (EDS) micrograph confirmed hexagonal shapes with purity of ZnO. Fourier transform infrared (FTIR) analysis confirmed the presence of various functional groups. The minimum inhibitory concentration (MIC) of ZnO against the four bacteria Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae was found to be 88 µg/ml, 52 µg/ml, 79 µg/ml, and 72 µg/ml, respectively, that completely inhibited the bacterial growth. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) test showed significant cytotoxic potential against MCF-7 and HeLa cells with the IC50 concentrations at 36.28 μg/ml and 30.10 μg/ml, respectively. ZnO-NPs showed subsequent reduction in mitochondrial membrane potential (MMP) and increased level of reactive oxygen species (ROS). The acridine orange/ethidium bromide (AO/EB) staining showed more number of early apoptotic and late apoptotic cells as compared to the standard drug, Camptothecin. Through real-time quantitative polymerase chain reaction (RT-qPCR), the level of Caspase 3 and p53 was upregulated, and these NPs do not have any hemolytic potential on human RBCs in both MCF-7 and HeLa cell lines. Thus, the synthesized ZnO-NPs from the medicinal plant L. indica could be used as an anticancer agent after further in vivo trials.

Paul A., Srivastava A.P., Subrahmanya S., Shen G., Mishra N.

Mitogen activated protein kinase kinase kinase (MAPKKK) form the upstream component of MAPK cascade. It is well characterized in several plants such as Arabidopsis and rice however the knowledge about MAPKKKs in tea plant is largely unknown. In the present study, MAPKKK genes of tea were obtained through a genome wide search using Arabidopsis thaliana as the reference genome. Among 59 candidate MAPKKK genes in tea, 17 genes were MEKK-like, 31 genes were Raf-like and 11 genes were ZIK- like. Additionally, phylogenetic relationships were established along with structural analysis, which includes gene structure, its location as well as conserved motifs, cis-acting regulatory elements and functional domain signatures that were systematically examined. Also, on the basis of one orthologous gene found between tea and Arabidopsis, functional interaction was carried out in C. sinensis based on an Arabidopsis association model. The expressional profiles indicated major involvement of MAPKKK genes from tea in response to various abiotic stress factors. Taken together, this study provides the targets for additional inclusive identification, functional study, and provides comprehensive knowledge for a better understanding of the MAPKKK cascade regulatory network in C. sinensis.

Kokila M.S., Chandra S., Raja Kamal C.

Due to the crisis and high unemployment, the labour market needs diversified skills. Higher education must encourage entrepreneurship. This research examines the impact of entrepreneurial incentives on prospective students’ entrepreneurial intentions and the role of entrepreneurship education on entrepreneurship development. Undergraduates’ career perspectives were investigated. Surveys collected original data. The study included 250 students, 200 of whom completed the questionnaire. Anova analyses data (single factor). Most responders are risk takers, and parent’s occupation influences entrepreneurship choice. Most respondents favour huge companies than entrepreneurship. Family morale and financial support inspired entrepreneurs. Entrepreneurship is associated to risk-taking, student understanding of financing sources, moral and financial support, and parent employment.

Deb D., Basak S., Kar T., Narsaria U., Castiglione F., Paul A., Pandey A., Srivastava A.P.

Chandipura vesiculovirus (CHPV) is a rapidly emerging pathogen responsible for causing acute encephalitis. Due to its widespread occurrence in Asian and African countries, this has become a global threat, and there is an urgent need to design an effective and nonallergenic vaccine against this pathogen. The present study aimed to develop a multi-epitope vaccine using an immunoinformatics approach. The conventional method of vaccine design involves large proteins or whole organism which leads to unnecessary antigenic load with increased chances of allergenic reactions. In addition, the process is also very time-consuming and labor-intensive. These limitations can be overcome by peptide-based vaccines comprising short immunogenic peptide fragments that can elicit highly targeted immune responses, avoiding the chances of allergenic reactions, in a relatively shorter time span. The multi-epitope vaccine constructed using CTL, HTL, and IFN-γ epitopes was able to elicit specific immune responses when exposed to the pathogen, in silico. Not only that, molecular docking and molecular dynamics simulation studies confirmed a stable interaction of the vaccine with the immune receptors. Several physicochemical analyses of the designed vaccine candidate confirmed it to be highly immunogenic and nonallergic. The computer-aided analysis performed in this study suggests that the designed multi-epitope vaccine can elicit specific immune responses and can be a potential candidate against CHPV.

Geluvaraj B., Sundaram M.

This article tells about the RS categories and HRS concepts with block diagram and finding out similarity metrices by using the equations and and understanding the datasets and dividing the Train/Test data and road map of hybrid algorithm and categories of algorithms used in RS and how to build HRS and method of combining CB and CF and Hybrid algorithm with customized algorithm by implementing it and evaluating the algorithms accuracy, sparsity and diversity and making a experimental setup on the the SurpriseLib library and loading of non identical algorithms and dataset and examining the results and comparing them against the research objectives and finding whihc algorithms yields the finest results by plotting the graphs for better understanding of the algorithms efficiency.