Learning impact of recent ICT advances based on virtual reality IoT sensors in a metaverse environment

Avatars of real individuals can be found all around the Metaverse. It has been nicknamed the "next big bang” for the Indian EdTech market, which some experts predict will reach $30 billion by 2032. Technology permeates 21st-century education, whether it is through academic programming, hands-on technical instruction, or concepts taught in classrooms and institutions. Virtual reality in the Indian educational system is still a topic of study. There isn't much research on virtual reality in education. Since women are now actively functioning as leaders and outperforming men in many spheres of life worldwide, women's empowerment is India's most powerful tool for growth. The lady governors and the countries led by these incredible women are bearing the load and pushing on alone in the struggle wherever it is needed, while the entire world holds its breath and prays every day for an unbelievable escape from the COVID-19 pandemic. Various non-governmental organizations (NGOs) seek to improve women's lives and provide them with self-sufficiency training. The government is likewise concerned about this issue and has established a number of programs to assist women. Information and communication technology (ICT) is significant in this context. ICT has improved the security, knowledge, education, employability, confidence, and popularity of women. The significance of ICT for the empowerment of women is highlighted in this study. To illuminate the various facets of ICT's impact on society, various examples have been addressed. Because of ICT, new generations of women all over the globe have defied all expectations and proven themselves in every aspect of life, even the most complicated and time-consuming realm of enterprise. In this regard, ICT may possibly become a magic wand for improving women's current situations. In this research, the eight factors that influence how ICT affects rural women's empowerment were found.

A Survey on Diagnosing Pulmonary Diseases

Due to the increase in world population, a lot of research is being done in the medical sciences. Pandemics and epidemics have multiple outbreaks in many regions of the world. In order to solve the issue, creative probing is being used. Most of the illnesses in the group are obstructive and may result in a loss of life. Heart and lung conditions make up a large portion of the obstructive illnesses in this group. More than 5 lakh people die each year from lung illnesses, generally known as pulmonary disorders, with an equal proportion of men and women affected. Each disease has unique symptoms that are connected to it in the fields of medicine and healthcare. There are several new tests that are being developed to identify each of the dangerous diseases that are on the rise. This results from the necessity for quick illness prediction. This paper examines numerous studies and experiments carried out over a variety of timelines and approaches selected by various experiments, carefully examining the benefits and drawbacks of the approaches in order to construct an appropriate model for the cause. It focuses on the study of diagnosing pulmonary disorders and making the user's task easy in understanding the scanned images obtained. © 2023 IEEE.

A Study of Prevalence of Igg Antibodies against Covid 19 in Maternal and Cord Blood

Introduction: The pandemic of COVID-19 has spread a wave of insecurity, fear and anxiety because of unknown facts about the pathogen. To have a better understanding about this infection, a systematic study is required by the principles of epidemiology with detailed investigations and researches from different angles. Hence, we are undertaking the study of seroprevalence of IgG antibody to get the idea about herd immunity in pregnant patients coming for delivery and their newborns. Objective(s): To find out the correlation between subclinical attack / mild attack of COVID 19 in the antenatal period. Method(s): This Cross-sectional study was conducted after getting cleared from Board of Studies and Ethical committee. The study population was calculated to be of 500 serum samples of both mother and newborns each. Result(s): The maternal age was 20-25 years among 230 (36.0%), 26-30 years among 164 (32.8%), 31-35 years among 88 (17.6%) and > 35 years among 18 (3.6%) patients. The maternal gestational age was <37 weeks 0 days at the time of delivery in 82 (16.4%) and that of >= 37 weeks was 418 (83.6%) patients. The exposure of COVID 19 virus and/or even the asymptomatic carriers, led to a data showing 18% (90 patients) of the study population being affected in 2nd trimester, 48.6% (243 patients) in 3rd trimester and 33.4% (167 patients) not affected at all in the pregnancy. IgG in mother at delivery was present among 21.4 % mothers. IgG in cord blood was present among 12.0% newborns. Conclusion(s): Although even at the time of diagnosis, asymptomatic pregnant women are able to reliably build a powerful IgG for receptor binding domain with neutralising response to COVID 19, as our results reveal. In addition, our findings indicate that this reaction was long-lasting, which lends credence to the notion that immunisation in this population will be successful. And after extensive research studies, pregnant females were allowed to be vaccinated against COVID 19. Copyright © 2022 Authors. All rights reserved.

A Study of Prevalence of Igg Antibodies against Covid 19 in Maternal and Cord Blood

Introduction: The pandemic of COVID-19 has spread a wave of insecurity, fear and anxiety because of unknown facts about the pathogen. To have a better understanding about this infection, a systematic study is required by the principles of epidemiology with detailed investigations and researches from different angles. Hence, we are undertaking the study of sero prevalence of IgG antibody to get the idea about herd immunity in pregnant patients coming for delivery and their newborns. Objective(s): To find out the correlation between subclinical attack/ mild attack of COVID 19 in the antenatal period. Method(s): This Cross-sectional study was conducted after getting cleared from Board of Studies and Ethical committee. The study population was calculated to be of 500 serum samples of both mother and newborns each. Result(s): The maternal age was 20-25 years among 179 (35.8%), 26-30 years among 129 (25.8%), 31-35 years among 118 (23.6%) and > 35 years among 74 (14.8%)patients. The maternal gestational age was 32-34 weeks among 59 (11.8%), 34.1-38 weeks among 98 (19.6%), 38.1-40 weeks among 275 (55.0%) and > 40 weeks among 68 (13.6%) patients. The Trimester with COVID-19 was 2nd among 152 (30.4%) and 3rd among 348 (69.6%) patients. IgG in mother at delivery was present among 59.0% mothers and IgG in cord blood was present among 54.0% newborns. Conclusion(s): Even at the time of diagnosis, aymptomatic pregnant women are able to reliably build a powerful IgG for receptor binding domain with neutralising response to COVID 19, as our results reveal. Although with opposition, majority of studies suggest that earlier the COVID 19 infection in pregnancy, better the transfer of IgG to fetus. As it is an evolving disease, extensive researches need to be established for a better result. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Hippo signaling pathway activation during SARS-CoV-2 infection contributes to host antiviral response.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), responsible for the Coronavirus Disease 2019 (COVID-19) pandemic, causes respiratory failure and damage to multiple organ systems. The emergence of viral variants poses a risk of vaccine failures and prolongation of the pandemic. However, our understanding of the molecular basis of SARS-CoV-2 infection and subsequent COVID-19 pathophysiology is limited. In this study, we have uncovered a critical role for the evolutionarily conserved Hippo signaling pathway in COVID-19 pathogenesis. Given the complexity of COVID-19-associated cell injury and immunopathogenesis processes, we investigated Hippo pathway dynamics in SARS-CoV-2 infection by utilizing COVID-19 lung samples and human cell models based on pluripotent stem cell-derived cardiomyocytes (PSC-CMs) and human primary lung air-liquid interface (ALI) cultures. SARS-CoV-2 infection caused activation of the Hippo signaling pathway in COVID-19 lung and in vitro cultures. Both parental and Delta variant of concern (VOC) strains induced Hippo pathway. The chemical inhibition and gene knockdown of upstream kinases MST1/2 and LATS1 resulted in significantly enhanced SARS-CoV-2 replication, indicating antiviral roles. Verteporfin, a pharmacological inhibitor of the Hippo pathway downstream transactivator, YAP, significantly reduced virus replication. These results delineate a direct antiviral role for Hippo signaling in SARS-CoV-2 infection and the potential for this pathway to be pharmacologically targeted to treat COVID-19.

Hyperglycemia and steroid use increase the risk of rhino-orbito-cerebral mucormycosis regardless of COVID-19 hospitalization: Case-control study, India.

BACKGROUND: In the ongoing COVID-19 pandemic, an increased incidence of ROCM was noted in India among those infected with COVID. We determined risk factors for rhino-orbito-cerebral mucormycosis (ROCM) post Coronavirus disease 2019 (COVID-19) among those never and ever hospitalized for COVID-19 separately through a multicentric, hospital-based, unmatched case-control study across India. METHODS: We defined cases and controls as those with and without post-COVID ROCM, respectively. We compared their socio-demographics, co-morbidities, steroid use, glycaemic status, and practices. We calculated crude and adjusted odds ratio (AOR) with 95% confidence intervals (CI) through logistic regression. The covariates with a p-value for crude OR of less than 0·20 were considered for the regression model. RESULTS: Among hospitalised, we recruited 267 cases and 256 controls and 116 cases and 231 controls among never hospitalised. Risk factors (AOR; 95% CI) for post-COVID ROCM among the hospitalised were age 45-59 years (2·1; 1·4 to 3·1), having diabetes mellitus (4·9; 3·4 to 7·1), elevated plasma glucose (6·4; 2·4 to 17·2), steroid use (3·2; 2 to 5·2) and frequent nasal washing (4·8; 1·4 to 17). Among those never hospitalised, age ≥ 60 years (6·6; 3·3 to 13·3), having diabetes mellitus (6·7; 3·8 to 11·6), elevated plasma glucose (13·7; 2·2 to 84), steroid use (9·8; 5·8 to 16·6), and cloth facemask use (2·6; 1·5 to 4·5) were associated with increased risk of post-COVID ROCM. CONCLUSIONS: Hyperglycemia, irrespective of having diabetes mellitus and steroid use, was associated with an increased risk of ROCM independent of COVID-19 hospitalisation. Rational steroid usage and glucose monitoring may reduce the risk of post-COVID.

Deciphering the association between Covid vaccine side effects and menstrual cycle

Introduction and Aim: In light of the ongoing pandemic Covid-19 and vaccination drive, our study intended to observe the association of reported side effects of Covid vaccine to menstrual cycle. There is no research done about covid vaccine effects on menstrual cycle. Materials and Methods: A cross-sectional online questionnaire-based study was conducted on females aged between 18-45 years who had received at least one dose of the Covid vaccine. The google form containing the questionnaire adhered to the CHERRIES guidelines for online surveys, was circulated for 10 days and had 14 questions on the menstrual cycle, Covid vaccines and their side effects. Out of the 886 responses obtained, 129 did not meet our inclusion criteria and hence, 757 responses were considered for statistical analysis. The data were subjected to descriptive, Chi-square tests. Results: The data showed a significant (p=0.027) association of age with side effects of the Covid vaccine, with the younger age group experiencing more side effects than the older age group. The side effects of the Covid vaccine did not show association (p=0.34) to menstrual cycle phases nor there was significant (p= 0.87) disturbance to the menstrual cycle post-vaccination. Conclusion: As there were no association of Covid vaccine effects to menstrual cycle, our study may allay apprehension in women who are going to take Covid vaccine and update guidance to health professionals during vaccination drive.

Allocation Optimization of Medical Samples For Distributed Testing

The world is witnessing the COVID-19 pandemic, which originated in the city of Wuhan, China, and has quickly spread to the whole world, with many cases having been reported in India as well. The healthcare system is going through unprecedented load on its resources while the available infrastructure is inadequate.COVID-19 samples are being tested at a massive scale and even small optimizations at this scale can save time, huge amounts of money, and resources. Particularly, the manual approach or even baseline greedy approach being used to allocate COVID-19 samples to medical labs across a state can lead to underutilization of resources. Hence, this work proposes a system to optimize the problem of allocation of medical samples to medical testing laboratories with high efficiency and minimal economic penalty. We use the Mixed Integer Programming (MIP) Model using high-performance MIP based solvers for custom applications by providing a tight integration with the branch-and-cut algorithms of the supported solvers to improve the results compared to baseline greedy approach. The system provides a transportation schedule optimized with respect to capacity of different labs and COVID-19 cases across the state of Karnataka. We tested the model on various datasets and observed significant improvement over the baseline greedy model.

Production of novel SARS-CoV-2 Spike truncations in Chinese hamster ovary cells leads to high expression and binding to antibodies.

SARS-CoV-2 Spike is a key protein that mediates viral entry into cells and elicits antibody responses. Its importance in infection, diagnostics, and vaccinations has created a large demand for purified Spike for clinical and research applications. Spike is difficult to express, prompting modifications to the protein and expression platforms to improve yields. Alternatively, the Spike receptor-binding domain (RBD) is commonly expressed with higher titers, though it has lower sensitivity in serological assays. Here, we improve transient Spike expression in Chinese hamster ovary (CHO) cells. We demonstrate that Spike titers increase significantly over the expression period, maximizing at 14 mg L-1 on day 7. In comparison, RBD titers peak at 54 mg L-1 on day 3. Next, we develop eight Spike truncations (T1-T8) in pursuit of truncation with high expression and antibody binding. The truncations T1 and T4 express at 130 and 73 mg L-1 , respectively, which are higher than our RBD titers. Purified proteins were evaluated for binding to antibodies raised against full-length Spike. T1 has similar sensitivity as Spike against a monoclonal antibody and even outperforms Spike for a polyclonal antibody. These results suggest that T1 is a promising Spike alternative for use in various applications.

Hippo Signaling Pathway Activation during SARS-CoV-2 Infection Contributes to Host Antiviral Response (preprint)

SARS-CoV-2, responsible for the COVID-19 pandemic, causes respiratory failure and damage to multiple organ systems. The emergence of viral variants poses a risk of vaccine failures and prolongation of the pandemic. However, our understanding of the molecular basis of SARS-CoV-2 infection and subsequent COVID-19 pathophysiology is limited. In this study, we have uncovered a critical role for the evolutionarily conserved Hippo signaling pathway in COVID-19 pathogenesis. Given the complexity of COVID-19 associated cell injury and immunopathogenesis processes, we investigated Hippo pathway dynamics in SARS-CoV-2 infection by utilizing COVID-19 lung samples, and human cell models based on pluripotent stem cell-derived cardiomyocytes (PSC-CMs) and human primary lung air-liquid interface (ALI) cultures. SARS-CoV-2 infection caused activation of the Hippo signaling pathway in COVID-19 lung and in vitro cultures. Both parental and Delta variant of concern (VOC) strains induced Hippo pathway. The chemical inhibition and gene knockdown of upstream kinases MST1/2 and LATS1 resulted in significantly enhanced SARS-CoV-2 replication, indicating antiviral roles. Verteporfin a pharmacological inhibitor of the Hippo pathway downstream transactivator, YAP, significantly reduced virus replication. These results delineate a direct antiviral role for Hippo signaling in SARS-CoV-2 infection and the potential for this pathway to be pharmacologically targeted to treat COVID-19.

Factors influencing the acquisition of COVID infection among high-risk contacts of COVID-19 patients in Madurai district-A case control study.

Introduction: COVID is a new disease; understanding the transmission dynamics and epidemiological characteristics may help in developing the effective control measures. The study is done 1. To determine the various factors influencing the acquisition of COVID-19 infection among high-risk contacts 2. To estimate the secondary attack rate among high-risk contacts 3. To determine the factors in COVID index cases influencing their secondary attack rate. Methodology: Unmatched case control study was conducted from March to August 2020 among 139 COVID index cases in Madurai district from March-May (Reference period) and their 50 COVID positive (cases), 551 COVID negative (controls) high-risk contacts. Case investigation form* and contact tracing Proforma*were used to collect data. Chi-square test and independent sample t test were used to find out the association. Univariate* and Multivariate logistic regression* were used to predict the risk of various factors in acquisition of COVID infection with the help of adjusted and unadjusted odds ratio. P value < 0.05 was considered statistically significant. Results: Male contacts (P = 0.005, OR = 2.520), overcrowding (P = 0.007, OR = 3.810), and duration of exposure to index case (for 4-7 days P = 0.014, OR = 2.902, for >7 days P = 0.001, OR = 6.748 and for > 12 hours/day P = 0.000, OR = 5.543) were significant factors predicted to be associated with acquisition of COVID infection among high-risk contacts. Reproductive number (R0)* estimated was 1.3. Secondary attack rate (SAR)* estimated among high-risk contacts was 8.32%. Index cases whose outcome was death (P = 0.026); symptomatic index cases (P = 0.000), cases with fever (P = 0.001); sorethroat (P = 0.019); breathlessness (P = 0.010); cough (P = 0.006) and running nose (P = 0.002) had significantly higher mean SAR than their counterparts. Conclusion: Contacts with above said risk factors who were found to be more prone to infection could be given special focus to prevent the transmission in them.

Blockchain Integrated Crowdfunding Platform for Enhanced Secure Transactions

Building a project starts with innovation and idea but funding is a part that decides the evolution of the project from idea to product. During the last decade funding campaign and project via crowdfunding has become a common theme. With the COVID situation, it has become a necessity for NGOs, campaigns, projects, start-ups to consider the concept of crowdfunding and build seed funds through it, therefore organizations are trying to create a safe, secure, and fraud-proof gateway for people to get funds and as well as provide funds, which is hard in the current time of pandemic and technical advancements. It has become quite easy to fall into a trap and lose your hard-earned funds with cybercrimes as identity fraud, theft of financial data, and internet fraud. This work is an attempt to create a secure, efficient, and viable tool for crowdfunding. The solution proposed has Blockchain integrated to build trust among the funders and those raising these funds, with its characteristics as decentralized, irrefutable, distributed ledgers, consensus, and faster settlement. The proposed model has been built on the smart contract protocol, created for crowdfunding transactions, campaigns for the proposed model was implemented on remix ide, this will create a campaign for those in need of funds and for donors to donate funds to these campaigns. The campaign master has the right to reject or accept requests thus creating fraud and a tamper-proof environment. The model has been subjected to positive negative unit and integration tests on mocha, the efficiency of the model obtained is at par with existing solutions with an added edge on security via smart contract protocols. © 2021 IEEE.

Mirroring hierarchical attention in adversary for crisis task identification: COVID-19, Hurricane Irma

A surge of instant local information on social media serves as the first alarming tone of need, supports, damage information, etc. during crisis. Identifying such signals primarily helps in reducing and suppressing the substantial impacts of the outbreak. Existing approaches rely on pre-trained models with huge historic information as well as on domain correlation. Additionally, existing models are often task specific and need auxiliary feature information. Mitigating these limitations, we introduce Mirrored Hierarchical Contextual Attention in Adversary (MHCoA2) model that is capable to operate under varying tasks of different crisis incidents. MHCoA2 provides attention by capturing contextual correlation among words to enhance task identification without relying on auxiliary information. The use of adversarial components and an additional feature extractor in MHCoA2 enhances its capability to achieve higher performance. MHCoA2 reports an improvement of 5 - 8% in terms of standard metrics on two real-world crisis incidents over the state-of-the-art. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

Modeling and forecasting of COVID-19 from the context of Ghana

Developing countries have had their share regarding the spread and effect of Coronavirus (COVID-19) and Ghana is no exception. We have used the data on new deaths, total deaths, total cases, new cases, collected on a daily basis from 13th March 2020 to 30th September 2020, obtained from the Ghana Health Services. We then considered appropriate time series models. This has provided robust results to help make an informed decision towards the future. The forecasted results (from the best fitted models) reveals adecrease in an amount of 174-88 in the daily new cases by flowing a linear trend, which also leads to decrease in total cases by following the same trend (from 46600 to 44942 in numbers) during the period 1-10-2020 to 10-10-2020. The government of Ghana should strictly enforce protocols established to curb COVID-19 in Ghana, encourage social distancing and other COVID-19 prevention protocols to reduce the spread of COVID-19 new cases and deaths.

A cross sectional study on psychological impact of covid19 on post graduate doctors and Compulsory Rotatory Residential interns in COVID isolation ward of a tertiary care centre, Madurai.

BACKGROUND: COVID-19 pandemic causes major impact on economic, physical, mental well-being of people all over the world. Doctors are working in stressful, unprepared, limited resource setting, and they are under the continuous threat of getting infection. Managing mental health of these warriors is great importance. Hence the present study to estimate the psychological impact of COVID-19* and factors associated with it among doctors in tertiary care hospital, Madurai. METHODS: A Cross-sectional study was conducted during October-November 2020 using a pre-designed semi structured questionnaire and DASS-21 scale which were sent through Google form to doctors who were in their quarantine period after the COVID duty. Totally 292 responses were received. Descriptive statistics done to find frequencies and percentages. Correlation for continuous variables; Univariate and multivariate regression for categorical variables were used to predict the factors influencing the psychological impact. RESULTS: In our study, 42.1% doctors were depressed, 43.8% were stressed and 50.7% had anxiety. Depression*, anxiety*, stress* scores were positively correlated with number of COVID duties(r2 0.163,0.138,0.133), number of elderly persons(r2 0.188,0.169,0.188) in their family and negatively correlated with sleep duration(r 2-0.219,-0.281,-0.239), attitude of study participants(r2-0.319,-0.274,-0.291). Multiple logistic regression showed that disturbed sleep(odd'sratio = 3.931,2.734,3.420) and poor quality of sleep which affect the next day function(odd'sratio = 3.470,2.968,3.122) were significant predictors for all three psychological impacts. CONCLUSION: High prevalence of psychological impact estimated, ensures the requirement of early screening with timely psychological intervention and establishment of guideline policies to support mental health of healthcare workers* for maintaining the functionality of healthcare system.

Effect of image transformation on EfficientNet model for COVID-19 CT image classification.

The Novel Corona Virus 2019 has drastically affected millions of people all around the world and was a huge threat to the human race since its evolution in 2019. Chest CT images are considered to be one of the indicative sources for diagnosis of COVID-19 by most of the researchers in the research community. Several researchers have proposed various models for the prediction of COVID-19 using CT images using Artificial Intelligence based algorithms (Alimadadi e al., 2020 [19], Srinivasa Rao and Vazquez, 2020 [20], Vaishya et al., 2020 [21]). EfficientNet is one of the powerful Convolutional Neural Network models proposed by Tan and Le (2019). The objective of this study is to explore the effect of image enhancement algorithms such as Laplace transform, Wavelet transforms, Adaptive gamma correction and Contrast limited adaptive histogram equalization (CLAHE) on Chest CT images for the classification of Covid-19 using the EfficientNet algorithm. SARS- COV-2 (Soares et al., 2020) dataset is used in this study. The images were preprocessed and brightness augmented. The EfficientNet algorithm is implemented and the performance is evaluated by adding the four image enhancement algorithms. The CLAHE based EfficientNet model yielded an accuracy of 94.56%, precision of 95%, recall of 91%, and F1 of 93%. This study shows that adding a CLAHE image enhancement to the EfficientNet model improves the performance of the powerful Convolutional Neural Network model in classifying the CT images for Covid-19.

SARS-CoV-2 spike binding to ACE2 is stronger and longer ranged due to glycan interaction.

Highly detailed steered molecular dynamics simulations are performed on differently glycosylated receptor binding domains of the severe acute respiratory syndrome coronavirus-2 spike protein. The binding strength and the binding range increase with glycosylation. The interaction energy rises very quickly when pulling the proteins apart and only slowly drops at larger distances. We see a catch-slip-type behavior whereby interactions during pulling break and are taken over by new interactions forming. The dominant interaction mode is hydrogen bonds, but Lennard-Jones and electrostatic interactions are relevant as well.

Production of novel Spike truncations in Chinese hamster ovary cells (preprint)

SARS-CoV-2 Spike is a key protein that mediates viral entry into cells and elicits antibody responses. Its importance in infection, diagnostics, and vaccinations has created a large demand for purified Spike for clinical and research applications. Spike is difficult to express, prompting modifications to the protein and expression platforms to improve yields. Alternatively, Spike receptor binding domain (RBD) is commonly expressed with higher titers, though it has lower sensitivity in serological assays. Here, we improve transient Spike expression in Chinese hamster ovary (CHO) cells. We demonstrate that Spike titers increase significantly over the expression period, maximizing at 14 mg/L at day 7. In comparison, RBD titers peak at 54 mg/L at day 3. Next, we develop 8 Spike truncations (T1-T8) in pursuit of a truncation with high expression and antibody binding. The truncations T1 and T4 express at 130 mg/L and 73 mg/L, respectively, which are higher than our RBD titers. Purified proteins were evaluated for binding to antibodies raised against full-length Spike. T1 has similar sensitivity as Spike against a monoclonal antibody and even outperforms Spike for a polyclonal antibody. These results suggest T1 is a promising Spike alternative for use in various applications.

In silico screening of phytoconstituents with antiviral activities against sars-cov-2 main protease, nsp12 polymerase, and nsp13 helicase proteins

Aims: The present study aimed to analyse the molecular interactions of the phytoconstituents known for their antiviral activity with the SARS-CoV-2 nonstructural proteins such as main protease (6LU7), Nsp12 polymerase (6M71), and Nsp13 helicase (6JYT). The applied in silico methodologies were molecular docking and pharmacophore modeling using Schrodinger software. Methods: The phytoconstituents were taken from PubChem, and SARS-CoV-2 proteins were downloaded from the protein data bank. The molecular interactions, binding energy, ADMET properties, and pharmacophoric features were analysed by glide XP, prime MM-GBSA, qikprop, and phase application of Schrodinger, respectively. The antiviral activity of the selected phytoconstituents was carried out by PASS predictor online tools. Results: The docking score analysis showed that quercetin 3-rhamnoside (-8.77 kcal/mol) and quercetin 3-rhamnoside (-7.89 kcal/mol) were excellent products to bind with their respective targets such as 6LU7, 6M71, and 6JYT. The generated pharmacophore hypothesis model validated the docking results, confirming the hydrogen bonding interactions of the amino acids. The PASS online tool predicted constituent's antiviral potentials. Conclusion: The docked phytoconstituents showed excellent interactions with the SARS-CoV-2 proteins, and on the outset, quercetin 3-rhamnoside and quercetin 7-rhamnoside interacted well with all the three proteins;these belong to the plant Houttuynia cordata. The pharmacophore hypothesis has revealed the characteristic features responsible for their interactions, and PASS prediction data has supported their antiviral activities. Thus, these natural compounds could be developed as lead molecules for antiviral treatment against SARS-CoV-2. Further in-vitro and in-vivo studies could be carried out to provide better drug therapy. ©2021 Bentham Science Publishers.

Modelling the factors affecting global economy during COVID-19 using ISM approach

The global pandemic created by COVID-19 has affected the world economy. The global human assets have been compelled to be lockdown and were made to maintain social distancing by the order of governments. Even in some cases, people by themselves have started taking precautionary measures to safeguard themselves, their near ones and the world at large. These steps of governments and people have stressed various economic variables. To understand the interrelation among various distressed economic variables so identified through literature, interpretive structure modelling (ISM) was applied to understand the hierarchical relationship among the variables. The results of the model and MICMAC analysis indicate that heavy expenditure on social security, rise in unemployment, catastrophe containment and relief fund and emergency fund are the top-level economic variables. The findings of this work suggest how global policymakers are creating and using various funds to mitigate health and human assets of the world. © 2021 Inderscience Enterprises Ltd.