Therapeutic Repurposing Approach: New Opportunity for Developing Drugs Against COVID-19

The coronavirus disease 2019 (COVID-19) pandemic initiated by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has encouraged the repurposing of various drugs to treat the morbidity, mortality, and extent of the disease. Nowadays, the COVID-19 pandemic is a major health concern as it has already affected the whole world in all aspects. Drug repurposing is considered a new potential strategy as it is a cost-effective and less time-consuming process to establish a new indication for existing drugs. The present chapter has focused on the pathophysiology of COVID-19 and the reuse of the drugs based on pharmacological mechanisms. In the literature, various drugs like favipiravir, lopinavir, ritonavir, arbidol, chloroquine, hydroxychloroquine, interferons, etc. have been reported for repurposing purposes against COVID-19. Most of them are effective in in vitro and clinical studies. Drugs act mainly on viral entry, viral replication, angiotensin-converting enzyme-2 (ACE2), inflammatory mechanisms, etc. Based on viral pathogenesis and the mechanism of drugs using in silico, in vitro, and clinical studies, repurposing medicines might be considered an excellent opportunity to cure COVID-19. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Antiviral activity of the human endogenous retrovirus-R envelope protein against SARS-CoV-2

Coronavirus-induced disease-19 (COVID-19), caused by SARS-CoV-2, is still a major global health challenge. Human endogenous retroviruses (HERVs) represent retroviral elements that were integrated into the ancestral human genome. HERVs are important in embryonic development as well as in the manifestation of diseases, including cancer, inflammation, and viral infections. Here, we analyze the expression of several HERVs in SARS-CoV-2-infected cells and observe increased activity of HERV-E, HERV-V, HERV-FRD, HERV-MER34, HERV-W, and HERV-K-HML2. In contrast, the HERV-R envelope is downregulated in cell-based models and PBMCs of COVID-19 patients. Overexpression of HERV-R inhibits SARS-CoV-2 replication, suggesting its antiviral activity. Further analyses demonstrate the role of the extracellular signal-regulated kinase (ERK) in regulating HERV-R antiviral activity. Lastly, our data indicate that the crosstalk between ERK and p38 MAPK controls the synthesis of the HERV-R envelope protein, which in turn modulates SARS-CoV-2 replication. These findings suggest the role of the HERV-R envelope as a prosurvival host factor against SARS-CoV-2 and illustrate a possible advantage of integration and evolutionary maintenance of retroviral elements in the human genome.Copyright © 2023 The Authors.

A Practical and Empirical Comparison of Three Topic Modeling Methods using a COVID-19 Corpus: LSA, LDA, and Top2Vec

This study was prepared as a practical guide for researchers interested in using topic modeling methodologies. This study is specially designed for those with difficulty determining which methodology to use. Many topic modeling methods have been developed since the 1980s namely, latent semantic indexing or analysis (LSI/LSA), probabilistic LSI/LSA (pLSI/pLSA), naïve Bayes, the Author-Recipient-Topic (ART), Latent Dirichlet Allocation (LDA), Topic Over Time (TOT), Dynamic Topic Models (DTM), Word2Vec, Top2Vec and \variation and combination of these techniques. For researchers from disciplines other than computer science may find it challenging to select a topic modeling methodology. We compared a recently developed topic modeling algorithm-Top2Vec- with two of the most conventional and frequently-used methodologies-LSA and LDA. As a study sample, we used a corpus of 65,292 COVID-19-focused s. Among the 11 topics we identified in each methodology, we found high levels of correlation between LDA and Top2Vec results, followed by LSA and LDA and Top2Vec and LSA. We also provided information on computational resources we used to perform the analyses and provided practical guidelines and recommendations for researchers. © 2023 IEEE Computer Society. All rights reserved.

Intention to Use Social Media in Online and Blended Learning: Potential Predictors and Mediation of Collectivism

The COVID-19 pandemic has drastically impacted traditional classroom education and all the associated multi-stakeholders (Universities, teachers, and students). With education embracing online media, there is a need to develop sustainable models of education. Social media is a tool that can be effectively used to create sustainable development in higher education. In this context, this study emphasizes on the development of an empirical model for intention to use social media in online/blended learning in a multi-stakeholder (Universities, teachers, and students) context. A total of 330 samples were collected through an online survey from students/faculties of various public and private higher educational institutions in India. The data from the survey was analyzed employing Explorative Factor Analysis (EFA) using R-Studio and, Confirmatory Factor Analysis (CFA) and Path Analysis (AP) using Structure Equation Modelling (SEM) on the AMOS 20.0 software platform. Results demonstrate a significant impact of perceived privacy, perceived security, ICT facility, and trust, on the intention to use social media in educational institutions following online/blended learning methods. The mediation of collectivism is also confirmed in this study. Hence, our findings will add value to the existing literature on online/blended learning and the sustainable development of education. By implementing more stringent security and privacy policies, good Internet connectivity, better technology infrastructure, and excellent and smart features in mobile, tablets, and laptops social media and collective effort of students, instructors, and external student communities may generate trust in the stakeholders, motivating them to use social media as a tool in higher education. IEEE

Satisfaction of Patients Other Than COVID-19 During the Pandemic at a Multidisciplinary Centre with COVID-19 Services

Background: The services rendered by hospitals during the pandemic may not be efficient. This might impact the satisfaction of patients seeking healthcare. The aim of this study is to assess the satisfaction level of patients other than those with COVID-19 during the pandemic with different services provided by the hospital. Method: A quantitative, analytical and cross-sectional study was carried out in a multidisciplinary hospital. Valid questionnaire, derived from PSQ III and PSQ 18, was used for data collection from 250 outpatients. Ethical approval was obtained. Systematic random sampling was done to enrol patients into the study after taking their consent. Descriptive analysis was performed using frequency, proportion, median and inter-quartile range. Mann–Whitney U test and Kruskal–Wallis test were carried out to find the association between overall satisfaction and different socio-demographic and other variables. Statistical significance was set at p-value < 0.05. Result: Almost two-thirds of the respondents visiting the hospital during the pandemic were female (male: 35.6% and female: 64.4%). More than half (50.4%) of the patients reported that access to the hospital was feasible. Of the patients reporting dissatisfaction, most of them (86.4%) considered the establishment of separate COVID-19 hospitals as the best option. The median satisfaction score for the overall satisfaction of patients towards different service domains was 54.0 (45–60). Almost all respondents (95.6%) found that services were easily available. Patient satisfaction score was significantly associated with expenditure (p < 0.001). Satisfaction score was also significantly associated with the time spent in the hospital by the patients (p < 0.001). Conclusion: Majority of the patients reporting to the multidisciplinary hospital were satisfied with the provisioning of treatment and different services during the COVID-19 pandemic. Relatively lesser satisfaction was reported for the provision of maintenance of social distance, availability of hand washing/sanitisation, overall hospital cleanliness and cost of treatment. Moreover, satisfaction among patients was associated with their perceived fear of the pandemic. © 2023 Indian Institute of Health Management Research.

At the Crossroads of One Health: Lessons Learned from Foot and Mouth Disease in COVID-19 Pandemic

Foot-and-mouth disease (FMD) and Coronavirus Disease 2019 (COVID-19) are transboundary diseases caused by single-stranded positive-sense RNA viruses with similarities in genome replication and viral protein synthesis. In FMD, asymptomatic infection leads to carrier status and persistently infected animals that threaten the animals vaccinated with a trivalent inactivated whole virus vaccine. Similar information on COVID-19 is not yet available. As COVID-19 vaccination is introduced in January 2021 (since 16 January 2021 in India), its outcome can be assessed by the year-end;and while doing so, the experiences gained in the control of FMD in livestock worldwide can be applied, including monitoring of vaccination response, duration of immunity, level of herd immunity developed, and antigenic matching of the vaccine virus. Antigenic divergence of the virus is a major issue in FMD, and different geographical regions in the world use different virus strains in vaccine preparations to antigenically match circulating virus strains in respective regions for control of the disease. Non-synonymous mutations in the critical antigenic determinants of SARS-CoV-2 have been observed, and there is likely the existence/development of antigenic variants. Therefore, during the post-COVID-19 vaccination regime, it will be essential to monitor the suitability of the in-use vaccine strain region-wise from time to time, as there could be an eruption of isolated outbreaks in a country arising due to antigenic variation and variants. In the context of the present scenario of COVID-19 around the Globe and multiple ongoing efforts to develop suitable vaccine(s) to control the disease, it is a must to develop NSP-antibody (that differentiate infected from vaccinated) assays to differentiate infected from vaccinated individuals(DIVI;DIVA in veterinary epidemiology). The techniques used and experiences gained in ongoing FMD control programs in the endemic countries can be applied to COVID-19 control in a country;and finally, the Globe. After achieving the control of COVID-19, the aim would be to eradicate the virus, which will be tough even with vaccination, as the disease/infection may become endemic during the time to come. To achieve this, applying the principles of Progressive Control Pathway for Foot-and-Mouth Disease (PCP-FMD;FAO/OIE) to COVID-19 control will be beneficial in its control. The present review discusses the issue of control of COVID-19. © 2021 by the authors.

Inclusive organizational behaviour – the dynamic rules of building new workplaces

Purpose: This study aims to reflect on the future of work dimensions through the new concept of inclusive organizational behaviour (IOB) and its practices. Design/methodology/approach: This work is a reflective concept development paper that focuses on new dimensions of organizational behaviour (OB) exploring IOB practices in the new workplace which can broaden the concept of OB that fits into the future of work. Findings: The IOB practices will adapt and help in adapting to the new work dynamics that can create more humane and stimulating workplaces, thereby benefiting society at large. Individual positive psychological traits, team dynamics and a fusion of digital corporate culture with a human-centric approach and sustainability are highlighted in the redefined IOB, expanding the concept of OB from the three levels of analysis (individual, group and the entire organization's behaviour) in the new normal post-COVID situation. Research limitations/implications: Limited research studies are being conducted to investigate the future of work dynamics in the new standard post-COVID environment, which is dominated by digitization. The lack of literature and the changing situations that impact OB are the limitations. Practical implications: Corporate houses, policymakers and leaders who understand the workplace dynamics in the post-COVID scenario can effectively leverage the insights from this work and may chalk out a road map for future work through IOB practices. Originality/value: This research extends knowledge pertaining to IOB practices and the changing dynamics that need to be followed in the future OB practices. © 2023, Emerald Publishing Limited.

Molecular identification and characterization of SARS-Co V-2 from the clinical stool and sewage samples to study waste water-based epidemiology and monitoring circulating virus

The Coronaviridae family's severe acute respiratory syndrome corona virus 2 (SARS-Co V-2) outbreak has infected a large number of the population during the COVID- 19 pandemic. The most prominent mode of virus transmission is considered through respiratory droplets of the infected person. Virus-mediated respiratory infection depends upon the binding between spike protein and the Angiotensinconverting enzyme 2 (ACE2) receptor expressed in lung alveolar type 2 cells. But some studies reported that gastrointestinal infection is also one of the prominent symptoms of COVID-19 because of the high expression of the ACE2 receptor in absorptive enterocytes of the small intestine. In a country like India, with high population density and due to unhygienic sanitation, it is crucial to understand the potential fecal-oral transmission route of SARS-CoV-2 during infection because of presence of ACE2 in small intestine. Therefore in our study, we aim to trace the potential fecal-oral transmission route of SARS-Co V-2 by examining human stool (collected from hospital settings) and nearby sewage water systems, followed by molecular characterization and viral load kinetics evaluation of SARSCOV- 2. qRT-PCR and NGS sequencing methods were used. The presence of SARS-COV-2 was reported in around 70% of samples (both clinical and environmental), this will help us to establish the epidemiological link between clinical and environmental samples after genomic analysis to alter the circulation of silent SARS Co V2 in the community.

Dynamic connectedness of green bond with financial markets of European countries under OECD economies

This paper examines the dynamic connectedness between green bonds and OECD financial markets of European countries. The study is conducted on daily price of green bonds and selected European stock markets from January 27, 2015, to August 4, 2021. Top ten European countries namely Luxembourg, Switzerland, Norway, Denmark, Germany, Netherlands, Iceland, Austria, Sweden, and Belgium are included within the OECD economies. The study uses Diebold and Yilmaz and Barunik & Krehlic tests to examine the connectedness between the economies and green bonds in short, medium, and long term. Result exhibits volatility across all frequency cycles. Brussel Stock Exchange and Euronext Amsterdam are identified as high-risk markets in the OECD European market. Evidence emerging from this study advocate the inclusion of green bonds in these financial markets for shorter time periods only. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, suggesting incorporation of green bonds in investor portfolio for efficient diversification of risk. © 2022, The Author(s).

Time and Frequency Connectedness Among Emerging Markets and QGREEN, FinTech and Artificial Intelligence-Based Index: Lessons from the Outbreak of COVID-19

The study is about contributing to the ongoing discussion on the diversification opportunities for emerging markets with non-conventional asset class. The limited literature in the era of fourth industrial revolution motivates us to gauge diversification opportunities. This study is focusing on identifying diversification opportunities with a set of unique asset classes that are the proxies for Green Funds, FinTech and Artificial Intelligence-based index funds. The method and model applied in the study are time and frequency connectedness in a Wavelet Coherence, and for the robustness check—Network analysis has been applied. The originality of the study lies in identifying the impact of the outbreak of COVID-19. The results captured that FinTech-based asset was the most resilient asset class during the pre- and post-outbreak of COVID-19, followed by AI-based fund and finally by Green fund. Henceforth, FinTech provides superior diversification opportunities among all with MSCI Emerging Market. AI and Green funds are captured to be invested in the long term for diversification, whereas FinTech is suitable for both long- and short-term assets. The results are relevant for investors in emerging markets and for policymakers as well. © 2023 MDI.

District Level Covid Case Prediction using LSTM Models

Covid-19 has had an adverse effect on the world, with more than 440 million cases recorded so far. The outbreak has hampered the country's healthcare and economy. This calls for an accurate prediction model for the prediction of Covid Cases, so that it gives some time to the hospitals and administration, to make the necessary arrangement. For population-dense countries like India, the covid case dynamics of every district is different, hence this requires a district-wise case prediction of Covid Cases. In this paper, we perform prediction of covid cases across all districts of India using different architectures of Long short-term memory (LSTM) and performed a comparative analysis between them. To the best of our knowledge, this is the first such attempt at the district level. Bidirectional LSTM encoder-decoder outperformed other LSTM-based models and, gave a test set MAPE of 15.44, followed by LSTM Encoder Decoder, giving a MAPE of 19.72. © 2022 IEEE.

Evaluation Of Indoor Air Quality In Hospitals: With Respect To Green Building Rating Systems

The World Health Organization tightened the various indoor air quality parameters to improve the quality of the air globally during COVID-19. In light of this, research (Pollution and Health: a progress update, 2022)made public in India in 2022 shows that air pollution is a major problem worldwide, with a projected 66.7 lac people dying as a result. Similar issues are present in developing countries like India, where 16.7 million fatalities were expected in 2019. According to the study (Air Quality Life Index: India Fact Sheet, 2022), air pollution shortens Indians' life expectancy by an average of 5 years. It is crucial to check that these new standards after Covid are compatible with the Green Building Rating Systems. The study is also based on in-depth discussions with doctors, administrators, green building designers, and building tenants, as well as surveys using questionnaires and interviews. The existing Green Rating Systems were found to require revision, with the weighting of the elements linked to air quality requiring strengthening with the installation of appropriate air quality monitoring of different contaminants. The study's main objective is to examine the air quality parameters, their weightings, and the monitoring tools. The study was focused on the evaluation of Green Rated healthcare buildings in India based on different Air Quality parameters. The overall evaluation of the air quality is found to be very critical and, in the areas, where extreme care and precautions are required with respect to cleanliness and hygiene like the Intensive care unit and Operation Theatre the values of the air pollutants like Formaldehyde, Volatile Organic Compound, Carbon Monoxide and Carbon Di Oxide are indicating serious problems. Copyright © 2022 Ubiquity Press. All rights reserved.

Predicting Students' Drop-Out Rate Using Machine Learning Models: A Comparative Study

One of the major challenges facing Private Higher Educational Institutes in India is to reduce drop-out rate of first year students. The problem has got exacerbated post-covid specially for Engineering and management discipline. This research is an empirical study on efficiency and accuracy of various Machine Learning (ML) Prediction algorithms to predict the drop-out rate of students based on dataset available on predictors such as Family size, Study time, Time spent on extra- curricular activities, Time spent on Internet, Health, Absenteeism etc. A comparison of the performance of the ML models based on 'Accuracy' and 'F1 score' (to cater for variations in costs of false positives and false negatives) has been made to identify the best algorithm for given problem. This would help HEIs to identify potential drop-out students beforehand and take course correction measures thus improving retention. The study is conducted for B.Tech First year students with a sample size of 395 students using Logistic regression and K-NN algorithms. This preliminary work could be extended using other ML models such as;Support Vector Machine (SVM), Naïve Bayes, Decision Tree etc. or a combination of in an ensemble fashion in future. © 2022 IEEE.

A systematic review and meta-analysis of otorhinolaryngological manifestations of coronavirus disease 2019 in paediatric patients.

BACKGROUND: This meta-analysis provides a quantitative measure of the otorhinolaryngological manifestations of coronavirus disease 2019 in children. METHODS: A structured literature review was carried out using PubMed, Embase and Cochrane Central, employing pertinent search terms. The statistical analysis was performed using Stata version 14.2 software, and the analysed data were expressed as the pooled prevalence of the symptoms with 95 per cent confidence intervals. RESULTS: The commonest symptoms noted were cough (38 per cent (95 per cent confidence interval = 33-42; I2 = 97.5 per cent)), sore throat (12 per cent (95 per cent confidence interval =10-14; I2 = 93.7 per cent)), and nasal discharge (15 per cent (95 per cent confidence interval = 12-19; I2 = 96.9 per cent)). Anosmia and taste disturbances showed a pooled prevalence of 8 per cent each. Hearing loss, vertigo and hoarseness were rarely reported. CONCLUSION: Cough, sore throat and nasal discharge were the commonest otorhinolaryngological symptoms in paediatric patients with coronavirus disease 2019. Compared with adults, anosmia and taste disturbances were infrequently reported in children.

Disease, Demon, and the Deity: Case of Corona Mata and Coronasur in India

As India faced multiple waves of the pandemic, religious responses arose to accommodate and make sense of the situation. In the face of uncertainty, disease and death, people turn not just towards the medical sciences but also religion. The emergence of a new Hindu goddess, Corona Mata/Coronavirus Mardhini encapsulates people's fear, faith, and devotion. Although the goddess is new, the tradition of disease goddesses is ancient. The Indian Subcontinent has a long history of mother goddesses who have been protecting their devotees from diseases such as smallpox, fever, plague, etc. This paper attempts to examine the emergence of Corona Mata in the historical context of these 'protective mothers'. On one hand, historically, these goddesses have emerged as a result of interaction between Brahmanical religion and regional practices. On the other hand, these disease-centred goddesses can also be seen as the result of fear and faith. This paper will analyse the location of Corona Mata in the ever-evolving pantheon of Hindu deities in the context of a 21st-century pandemic.

CAVITATORY LUNG RHIZOPUS INFECTION IN RENAL TRANSPLANT RECIPIENT: RARE CASE REPORT

Introduction: Mucormycosis is a life threatening fungal infection commonly seen in diabetics and immunocompromised individuals. It is caused by one of the members of mucoraceae family which includes mucor, rhizopus, rhizomucor, absidia and others. Its prevalence has become more common in covid pandemic. Methods: We report a rare case of large cavitatory Rhizopus infection in a renal transplant recipient. Patient was initiated on antitubercular therapy for tubercular lymphadenitis two months prior to transplant. He was given rabbit ATG as induction agent and was on triple maintenance immunosuppression with tacrolimus/ mycophenolate mofetil/ steroids. Patient developed post transplant Diabetes mellitus. Four months post transplant he presented with cough, fever and left sided chest and shoulder pain for 10 days. Covid RT PCR was done twice and it came out to be negative. High Resolution Computed tomography Chest revealed thick walled cavity abutting the chest wall (10.3 x 7.1cm) in left upper lobe. Blood culture was sterile after five days of incubation. Serum Beta galactomannan was negative. He was empirically started on broad spectrum antibiotics and antifungals (oral voriconazole). He underwent bronchoscopy on day 4 of admission. As tuberculosis was a differential, gene expert, tubercular culture and AFB stain was obtained on Bronchoalveolar(BAL) fluid which all came out to be negative. Microbiological sample from BAL Fluid revealed growth of Rhizopus species. He was started on Liposomal amphotericin B. Since the cavitatory lesion occupied almost the entire left lung, surgical resection was offered to the patient to which patient refused. Results: He improved symptomatically after 10 days of Liposomal amphotericin B. Total of 10 weeks of Liposomal amphotericin B was given. Follow up CT after 40 days showed significant reduction in size of cavity to 7.5cm. A surprising complete resolution of the lung cavity was seen after 4 months. Conclusions: This case is one of the very few reported cases of invasive pulmonary rhizopus infections. It emphasizes how medical treatment alone can lead to complete resolution of such large cavitatory lesions without surgical intervention. No conflict of interest

Dynamic connectedness of green bond with financial markets of European countries under OECD economies

This paper examines the dynamic connectedness between green bonds and OECD financial markets of European countries. The study is conducted on daily price of green bonds and selected European stock markets from January 27, 2015, to August 4, 2021. Top ten European countries namely Luxembourg, Switzerland, Norway, Denmark, Germany, Netherlands, Iceland, Austria, Sweden, and Belgium are included within the OECD economies. The study uses Diebold and Yilmaz and Barunik & Krehlic tests to examine the connectedness between the economies and green bonds in short, medium, and long term. Result exhibits volatility across all frequency cycles. Brussel Stock Exchange and Euronext Amsterdam are identified as high-risk markets in the OECD European market. Evidence emerging from this study advocate the inclusion of green bonds in these financial markets for shorter time periods only. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, suggesting incorporation of green bonds in investor portfolio for efficient diversification of risk.

Multitargeted Molecular Dynamic Understanding of Butoxypheser Against SARS-CoV-2: An in Silico Study

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was initially reported in the Wuhan province of China, spread throughout the world, and caused massive destruction in the form of a global pandemic that started back in 2020. SARS-CoV-2 is an RNA virus with various proteins like main protease, spike protein, NSP15 endoribonuclease, RNA-dependent RNA polymerase, and papain-like protease targeted to screen and find the novel drug candidate that can potentially work against the virus. Previous studies have reported multiple drugs after screening and validation against a single target and reported multiple medications. Nevertheless, many drugs are being used to date but do not have enough potential to work against SARS-CoV-2 and curb the spread and death rate. In this study, with the hypothesis of 1 drug and multiple targets, we have taken 5 main target proteins and screened the Asinex's complete BioDesign library (1,70,269 compounds) and identified N-{2-[(2S)-2-Amino-3-methylbutoxy]-6-propylbenzoyl}-L-phenylalanyl-L-serine (Butoxypheser) as multitarget inhibitor against SARS-CoV-2. Also, Butoxypheser has shown excellent docking scores, hydrogen bonding, and other bonding configurations like van der Waals force and water bridges. The stability and interaction pattern of the compound was validated with structural interaction fingerprints (SIFts) and molecular dynamics (MD) simulation. The Butoxypheser has performed flawlessly throughout the study, and the same results were used to compare the compound's activity against multiple targets. After a thorough theoretical comparative analysis, Butoxypheser can be treated as a multitargeted inhibitor candidate against SARS-CoV-2. Further, this study needs to be validated experimentally before human use.

Evolution of modern age drug discovery of lipopeptides and computer-aided drug discovery in India

The endeavor has been attempted to present a review on the evolution of modern age drug discovery in India. The contribution of next generation therapeutics options microbial metabolites and the computational drug discovery aspects to the global market from India have been represented. Microbial metabolites such as lipopeptides and peptide therapeutics are gaining worldwide importance due to their multiple applications as broad-spectrum antimicrobial, antiviral, anticancer properties etc. Due to the surge of microbial resistance, tumor resistance, and ongoing pandemic due to constantly mutating corona virus, there is a need to develop next-generation therapeutics options from natural origin, less toxic to the environment, and have higher specificity towards target. Small molecule therapeutics are certainly less specific towards cancer targets hence the cytotoxicity is a major issue in cancer treatment while drug resistance due to the mutations are coming as challenges every day for drug discovery researchers. Microbial lipopeptide reserves a sweet spot in between the small molecule inhibitors and peptide therapeutics because of their amphiphilic compounds consist of a fatty acid side chain and a cyclic peptide moiety of hydrophilic nature. The computational drug discovery approach accelerates the drug discovery process due to the advancement in supercomputer facilities provided by various funding agencies such as the Department of Biotechnology (DBT) and the Department of Science and Technology (DST) in India. The current review article is focusing light on the research contribution of Indian Scientists and Govt. of India in the field of lipopeptide-based research and applications of Computer-aided drug discovery. © 2022, National Institute of Science Communication and Information Resources. All rights reserved.

Study on yoga practices and biochemical, physical and physiological alterations: A perspective on yoga as preventive strategy against COVID 19

Background: During the COVID pandemic period, our home-restricted life led to many undesirable physical, physiological, and mental alterations. Yoga a traditional system of medicines by virtue of its holistic approach toward health and disease and also due to reasonable cost, the technique has an edge in dealing with health problems and with primary prevention of disease. Aim: The current study has been designed to assess the effect of short-term (for 3 months for 5 days in a week or 40 days) yoga practice on lipid profile, and blood glucose level, C-reactive protein (CRP), and other physical and physiological parameters among healthy controls. Materials and Methods: Students went for yoga practice for 3 months (90 days) for 5 days in a week under the supervision of trained yoga instructor. Yoga activity was conducted via Google Meet app through broadband connectivity. The procedure began with Surya Namaskar (Sun Saluation) with a session of 12 asanas (fixed postures) for 20 min, followed by 15 min Pranayam (breathing exercise including anulome-vilome, surya bandana, sheetali, and bhramari). The session ended with 10 min meditation. Yoga program was started on September 27, 2020, and ended on December 27, 2020, after the completion of 3 months. Biochemical investigation (lipid profile, fasting blood glucose, CRP) and physiological parameters (blood pressure [BP], pulse), and other anthropometric parameters including weight, height body mass index reports were collected before September 27 and after December 27 in 5 days after the completion of 3 months tenure. Results: Results of the study clearly indicate fasting sugar, systolic BP, and low-density lipoprotein were significantly decreased (with value <0.02, 0.007, and 0.001, respectively) in the postyoga phase as compared to preyoga baseline investigation. Conclusion: The The present study substantiates some good results of the yoga training. Although all the tested parameters could not show desired changes and they were statistically insignificant. © 2022 Journal of Datta Meghe Institute of Medical Sciences University ;Published by Wolters Kluwer - Medknow.