Density Functional Theory, Molecular Dynamics and AlteQ Studies Approaches of Baimantuoluoamide A and Baimantuoluoamide B to Identify Potential Inhibitors of Mpro Proteins: a Novel Target for the Treatment of SARS COVID-19

COVID-19 has resulted in epidemi conditions over the world. Despite efforts by scientists from all over the world to develop an effective va ine against this virus, there is presently no recognized cure for COVID-19. The most succeed treatments for various ailments come from natural components found in medicinal plants, which are also rucial for the development of new medications. This study intends to understand the role of the baimantuoluoamide A and baimantuoluoamide B molecules in the treatment of Covid19. Initially, density functional theory (DFT) used to explore their electronic potentials along with the Becke3-Lee-Yang-Parr (B3LYP) 6-311 + G(d, p) basis set. A number of characteristics, including the energy gap, hardness, local softness, electronegativity, and electrophilicity, have also been calculated to discuss the reactivity of mole ules. Using natural bond orbital, the title compound's bioactive nature and stability were investigated. Further, both compounds potential inhibitors with main protease (Mpro) proteins, molecular dynamics simulations and AlteQ investigations also studied. Supplementary Information The online version contains supplementary material available at 10.1134/S0021364023600039.

An overview of COVID-19 with special reference to Janapadodhwamsa

Virus, bacteria and fungi are the most common causes for spreading illness in human and in animals. These are the microorganisms and they can cause epidemic and pandemic diseases. World is passing through many viral epidemics affecting respiratory system since last twenty years. It includes SARS-CoV 2002-2003, H1N1 Influenza 2009, MERS-CoV 2012 to the recent COVID-2019. COVID-19 is a viral pandemic infection this is air borne illness that is spreading through droplet infection. This virus especially affects the respiratory system by doing immunosuppression in person. In Ayurveda there are references of Janapadodhwamsa in Charaka samhita vimansthan. Janapadodhwamsa - is the term coined by Charak which means destruction of population living in same place at the same time because of 4 main reasons i.e. Dushit vayu (Air), Dushit jala (water), Dushit desh (land), Dushit kaal (time) Janapadodhwamsha causes death of individuals in the affected area inflicting huge destruction.

Potential Investment Opportunities in Gcc Healthcare during Covid Pandemic: A Research & Review

The COVID-19 pandemic has brought an additional set of challenges to theeconomiesoftheGulf Cooperation Council (GCC). Theregionhasbeen struggling to attract more and better FDI, constrained by investment climateweaknesses and regional geopolitical tensions. While the projected short-termdeclinesareexpectedtohittheGCC economieshard,thecrisiscouldalso bring new opportunities to benefit from global trends, such as reshoringand restructuring of global and regional value chains. The extent to whichthisispossiblewilldependonsustainingexistingreformsunderway,enactingtargetednew strategiesandmeasuresforthepost-COVID-19context,andreinforcingregionalcooperation.ThisbriefprovidesanoverviewoftheimpactoftheC OVID-19crisisoninvestmentintheregionandhighlights GCC government policy responses to catalyze investment andfoster an inclusive post-crisis recovery.Copyright © 2020 Ubiquity Press. All rights reserved.

Ethical conflicts in the context of the COVID-19 pandemic

Background: Healthcare setups in India are encountering a lot of medical, ethical, legal, and social challenges endorsed by the ongoing COVID-19 crisis, modifying the healthcare protocols, which are considered a standard of care. The ethical conflicts are pressurizing the decision-makers of society, to revamp the basic principles and traditional assumptions of our present healthcare modalities. Objectives: This report addresses the common but crucial ethical issues, encountered by healthcare workers e.g., doctors and paramedics in day-to-day healthcare practice during the COVID-19 pandemic. Materials and methods: This report tries to cover several ethical aspects of COVID-19 such as: setting priority of screening;professional responsibility of healthcare workers;dilemma encountered by a doctor;compromise of patient confidentiality;allocation of scanty resources;end-of-life situation, and certain critical clinical scenarios. Results and conclusion: COVID warriors from the health sector possess dual responsibilities of taking utmost care of COVID patients ethically, along with self-protection from this havoc. COVID-19 has taught us the lesson that, extra-ordinary time calls for extra-ordinary measures. Also, intervention performed upon the patient affects not only the patient, but also the whole of society. © 2023, Faculty of Associated Medical Sciences, Chiang Mai University. All rights reserved.

Therapeutic Options for the Treatment of 2019-Novel Coronavirus in India: A Review

Purpose: As of, from 30th Jan to 31st May, 2020, more than 182,143 confirmed cases were reported in India along with 86,984 recovered cases and 5164 deceased cases of COVID-19. More than 53 countries are also affected with this pandemic virus. However, the lack of specific drugs to prevent/treat this pandemic disease is a major problem in this current scenario. In this re-gard, this systemic review was conducted to identify the therapeutic approaches and researches, which are ongoing in India against COVID-19. Method(s): We had screened Google Scholar database with the keywords nCoV, corona virus in In-dia, effect of SARS-CoV-2 in India, 2019-nCoV, treatment pattern in India for nCoV and therapy used to treat nCoV in India. In the final review, we had included a total of 49 articles. Result(s): As a result we had found that the Indian Council of Medical Research and NIH have giv-en a standard guideline of Hydroxychloroquine and other antiviral drugs for nCoV, and also there are various researches going on related to nCoV treatment like, chemicals from natural products, herbs and spices commonly used in India, combination therapy of lopinavir and ritonavir, ultra-vio-let radiation therapy, molecular dynamic (MD) simulations of molecules for vaccine preparation, Convalescent plasma transfusion (CPT) therapy and many more. Conclusion(s): New drugs and therapy are in the premature stage for this hazardous pandemic. We need more time to gain the detailed knowledge of the life cycle of the nCoV, which can speed up the drug/vaccine development process against nCoV.Copyright © 2022 Bentham Science Publishers.

Education 4.0: Explainable Machine Learning for Classification of Student Adaptability

Because of the Covid 19 outbreak, which forced the closure of schools and institutions in India after March 2020, online education gained even greater traction in the country. The flexibility of online education allows students to rewatch recorded lectures as many times as they need to fully comprehend the topic. However, there are challenges and ethical concerns associated with using this technology in the classroom. Future possibilities, benefits, and drawbacks of using AI in the classroom are yet to be explored. Despite the great popularity and efficiency of online education, some studies have demonstrated that it may be detrimental to students. This research investigates students' attitudes on the use of technology in the classroom. We use the idea of Explainable Machine Learning (XML), in which the outcomes of ML calculations are explicable to people. On the other hand, the 'black box' approach holds that not even the creators of an AI can explain how it arrived at a certain choice. Several machine learning methods were used to forecast the extent to which students will embrace Industry 4.0 features. The most successful method was shown to be Neural Network (NN) which achieved an impressive 93% accuracy in classification. By detailing the inner workings of models to give some level of explainability, we can fully grasp the promise of this algorithm. © 2022 IEEE.

Prediction of Customer Review's Helpfulness Based on Feature Engineering Driven Deep Learning Model

Online consumer reviews play a pivotal role in boosting online shopping. After Covid-19, the e-commerce industry has been grown exponentially. The e-commerce industry is greatly impacted by the online customer reviews, and a lot of work has been done in this regard to identify the usefulness of reviews for purchasing online products. In this proposed work, predicting helpfulness is taken as binary classification problem to identify the helpfulness of a review in context to structural, sentimental, and voting feature sets. In this study, the authors implemented various leading ML algorithms such as KNN, LR, GNB, LDA and CNN. In comparison to these algorithms and other existing state of art methods, CNN yielded better classification results, achieving highest accuracy of 95.27%. Besides, the performance of these models was also assessed in terms of precision, recall, F1 score, etc. The results shown in this paper demonstrate that proposed model will help the producers or service providers to improve and grow their business.

Deep Learning Methods for Early Detection of Monkeypox Skin Lesion

As the world has not fully recovered from the aftermath of COVID-19, a new pandemic appears on the horizon. Monkey Pox is emerging as a new threat to the health of the world population. With the recorded spread over 40 countries worldwide it might be soon declared a pandemic. Monkey Pox shares common features with chickenpox and measles making it difficult to diagnose. Developing a new test kit at this early stage is a challenging task for the medical fraternity. This paper proposes the use of deep learning models that can be used to make the process of diagnosis automated. This paper tries to come up with a performance comparison of ResNet50, EfficientNetB3 and EfficientNetB7 algorithms. This study suggests a method for early detection of Monkey Pox Skin Lesion. Though an extensive study with other models on a larger dataset containing more images from various countries of the world needs to be carried out but this study gives some promising results on this limited dataset. © 2022 IEEE.

Prediction of Customer Review's Helpfulness Based on Feature Engineering Driven Deep Learning Model

Online consumer reviews play a pivotal role in boosting online shopping. After Covid-19, the e-commerce industry has been grown exponentially. The e-commerce industry is greatly impacted by the online customer reviews, and a lot of work has been done in this regard to identify the usefulness of reviews for purchasing online products. In this proposed work, predicting helpfulness is taken as binary classification problem to identify the helpfulness of a review in context to structural, sentimental, and voting feature sets. In this study, the authors implemented various leading ML algorithms such as KNN, LR, GNB, LDA and CNN. In comparison to these algorithms and other existing state of art methods, CNN yielded better classification results, achieving highest accuracy of 95.27%. Besides, the performance of these models was also assessed in terms of precision, recall, F1 score, etc. The results shown in this paper demonstrate that proposed model will help the producers or service providers to improve and grow their business. © 2022 Taru Publications. All rights reserved.

Education 4.0: Classification of Student Adaptability Level in E-Education

In India, online education is an important part of the educational system, but it grew even more popular during the Covid 19 epidemic since schools and universities were closed after March 2020. Students benefit from online instructions since they may record lectures and watch them as many times as necessary to grasp the material. However, the application of this technology in the sphere of education presents obstacles and ethical issues. Artificial Intelligence's prospects, advantages, and problems in education is be examined in this research. Several researches have shown that pupils might be hindered by online education, despite its widespread appeal and effectiveness. This study examines whether or not students are accepting of technology in the classroom. This article uses machine learning algorithms to classify the adaptability level of pupils. To predict the amount of student adoption of Industry 4.0 capabilities, we used a variety of machine learning techniques. With 93% classification accuracy, neural network and random forest techniques were shown to be the most effective. © 2022 IEEE.

A Review Article on the Therapeutic Potential of Medicinal Plants for Prevention and Treatment of Secondary Infection in Patients with COVID-19

COVID-19 is an infectious disease caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) that has rapidly spread all over the world, causing an international health crisis. Earlier, various synthetic antiviral drugs and clinical therapies have been used to control viral infections, but at present, there is no specific treatment available for COVID-19 infection. Several drugs, like ritonavir, lopinavir, hydroxychloroquine, and chloroquine, have been proposed. India is a hub of medicinal plants, so there is a chance to find effective means to combat the COVID-19 pandemic. The medicinal herbal formulations may enhance immunity and help develop a powerful antiviral drug, which is urgently needed to control the outbreak of coronavirus. In this review arti-cle, we have discussed the epidemiology, clinical outcomes, treatment, and prevention of this novel epidemic coronavirus from the medicinal herbal formulation perspective. We have also empha-sized the reported antiviral activity and immunity-boosting properties of the Indian medicinal plants. This article also suggests that the drug or formulation obtained from plant sources would have low fatal outcomes, exhibit quick response, and be safe in the management and prevention of this pandemic outbreak. Copyright © 2022 Bentham Science Publishers.

A Novel Approach for Analysis of Air Quality Index Before and After Covid-19 Using Machine Learning

The third Industrial Revolution brought about major changes in the lives of people. But people were too late to realize that the impact of the Revolution had an adverse effect on the environment and the biodiversity. With more and more industries and automobiles thriving around, improper waste management techniques, and increasing deforestation, the air quality started declining rapidly. Higher AQI level indicates poorer air quality and vice-versa. The Corona Virus Disease or Covid-19 is a pandemic that has claimed millions of lives till date. To contain its spread, countries are imposing nationwide lockdowns. With the imposition of lockdown, life came to a still. Almost everything flourished online pertaining to which, the air quality started getting better and better. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

“Socio-demographic profile and treatment Outcome of Covid-19 Patients attending Covid Hospitals of Datia, M.P. INDIA’’

Background- In December 2019, a series of pneumonia cases were identified with presumptive viral origin in Wuhan, China, the virus was initially designated as the novel coronavirus (2019-nCoV), later WHO renamed as Corona Virus Disease 2019 (COVID-19). Objective- To describe the sociodemographic profile & Treatment Outcome of Covid -19 Patients attending Covid Hospitals of Datia district of M.P. Methods -it was descriptive, cross sectional observational study conducted among COVID-19 positive cases admitted & managed at Covid hospitals (DCH & DCHC) affiliated to Government Medical College Datia,M.P. from 1st April 2020 to 15th December 2020. Data was collected regarding age,sex, Occupation, Residence and Treatment Outcome of Covid 19 patients and analysed accordingly with the help of EpiInfo software. Results- The mean age of the patients was found 37.69±16.74 years. 65.7% of patients were belonged to a middle age group & male sex. Only 23.14% belongs to peripheral area& remaining were of urban area. Out of total 1620 positive patients, 78.76% patients were admitted & remaining were advised for home isolation. 92.47% had been discharged &cured,only 1.72 % patients were up referred and only 0.39 % death had been occurred among of all admitted patients. Conclusion- As only 1.72 % patients were up referred and 0.39 % death had been occurred among of all admitted patients which shows a good quality care of covid patients and may be also be due to mainly middle aged patients were found infected with covid -19 without any more significant co morbid conditions.

Development of robust, indigenous ELISA for detection of IgG antibodies against CoV-2 N and S proteins: mass screening.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has adversely affected humankind and caused millions of deaths globally since January 2020. Robust and quick serological tests such as antibody detection assays for SARS-CoV-2 provide relevant information and aid in the process of vaccine development and diagnostics, as well as in sero-epidemiological monitoring of antibody response to the virus. The receptor-binding domain (RBD) of spike and nucleocapsid protein are specific targets for detecting SARS-CoV-2 antibodies. Here, we present the development of a stable spike (S) and nucleocapsid (N) protein-based ELISA antibody detection test "CoroSuchak," with 99% sensitivity, 98% specificity, cost-effective, and detection in a minimum time for serodiagnosis and mass screening of the population for antibodies against SARS-CoV-2. Blood samples were analyzed from 374 SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) positive, 772 negative and asymptomatic, and 874 random groups of subjects. We found that the antibody titer was significantly higher (p < 0.0001) in infected and vaccinated group compared to the only vaccinated and only infected group. Using enzyme-linked immunosorbent assay (ELISA), we detected SARS-CoV-2 immunoglobulin G (IgG) antibodies in 118/123 (96%) infected individuals, 570/653 (87%) non-infected but vaccinated individuals, 231/237 (97%) individuals who were both infected and vaccinated, and 499/874 (57%) from randomly selected individuals from the first and second waves of the pandemic. Similarly in the third wave, 14/14 (100%) infected and 16/20 (80%) RT-PCR-negative but symptomatic subjects were detected. Thus, the highly sensitive and specific in-house developed ELISA antibody detection kit "CoroSuchak" is extremely useful to determine the seroprevalence of SARS-CoV-2 antibodies in the coronavirus-exposed population. KEY POINTS: •Indigenous kit using a combination of spike and nucleocapsid proteins and peptide sequences. •High sensitivity and specificity to detect variants. •Highly sensitive for mass screening.

Perceptions, experiences, expectations, and challenges of Indian public health programs

The COVID-19 pandemic has served as a wake-up call for India’s public health system. Public health if aided by strong political will, academic reforms, and awareness among youth (as a career choice)–will get a boost. Skilled public health professionals would be expected to play a key role in strengthening public health systems. Thus, to bring deep structural health reforms, it is imperative to analyse the perceptions of key public health stakeholders. In this study, we explored stakeholders’ perspectives about public health, and their views regarding the current state of public health education. Thirty-nine semi-structured in-depth interviews were conducted during 2017–2018 across India among stakeholders that included students of public health programs, public health professionals (PHPs), faculty of public health institutions, employers of public health graduates, and policymakers. Thematic analysis of the data was undertaken focusing on 10 themes emanating around the focus areas of the study. Public health stakeholders suggested that for building a competent public health workforce there is a need to match supply and demand of PHPs, create job opportunities, institutionalising a large body of guidance such as a separate Ministry or Council of public health (for educational institutions, quality assurance of curriculum etc.). Within India, the public health profession & education remains under-researched. This study is the first from a lower middle income country (LMIC) & from Asia to offer insight about public health programs–from policy, education, and professional perspective.

Clinical Profile of Non Strabismic Binocular Vision Anomalies in MBBS and Nursing Students in a Teaching Hospital: A Cross-sectional Study

Introduction: MBBS and nursing students spend a lot of time in near vision activities daily while studying. In the covid and post COVID-19 pandemic era, the emphasis on electronic teaching and studying has increased immensely. Students have started depending more on online studying, teaching and search for study material leading to more time being spent using electronic devices like mobile phones, tabs, PC etc. This can lead to lot of eye strain (digital eye strain) and this predisposes them to develop Non Strabismic Binocular Vision Anomalies (NSBVA) related to accommodation and convergence of eyes. Aim: To study prevalence of NSBVA and report associated ocular symptoms and association of electronic devices (mobile, laptop) use with prevalence NSBVA, in MBBS and nursing students of a teaching hospital in Western Maharashtra. Materials and Methods: This study was a prospective observational study conducted between November 2020 to April 2021at Rajiv Gandhi Medical College and CSM Hospital, Thane, Maharashtra, India. In this study, a total of 110 students including both MBBS and nursing students from all academic years of the hospital were examined for a comprehensive ophthalmic examination and complete binocular vision assessment. The prevalence of NSBVA, associated ocular symptoms, prevalence of refractive errors and duration of electronic device use in the students was documented. Student's t-test was used to compare the total daily duration of electronic devices (mobile, laptop, Computer tablets) use between students with and without NSBVA. Chi-square test was used to find association of variables duration of electronic device use and occurrence of NSBVA. Results: Out of 110 students examined, there were 37.27% (n=41) were males and 62.72% (n=69) females. Age range was 18-30 years with mean age 21.85±2.67 years. Overall, 47 (42.72%) students had NSBVA including 34 MBBS and 13 nursing students. 12 (11%) students had ocular symptoms with NSBVA while 35 (31.8%) students had NSBVA without any ocular symptom. Eye strain was the most common ocular symptom. Average electronic device use was 4.53 hours/day. Most used electronic device was mobile phone. There was no association between NSBVA and electronic device use. Conclusion: The NSBVA is highly prevalent among MBBS and nursing students. Ocular symptoms are absent in many students with NSBVA which may lead to delayed diagnosis and worsening of ocular symptoms due to NSBVA. Older age group of students have higher prevalence of NSBVA. Electronic device exposure is not significantly associated with NSBVA in these students. Screening of such at risk population is important for timely diagnosis and treatment of NSBVA.

Analysis of Contrast and Correlation between Deep Learning Algorithms for Diagnosis of COVID 19 from Lung Ultrasonography

Although identification of COVID-19 in patients from chest Computed Tomography (CT) scan has been the most prevalent approach, it exposes the patient to X-ray radiations and is not a suitable approach for frequent monitoring. Computer analysis of ultrasound pulmonary images is a relatively modern approach that shows promising ways to diagnose pulmonary states, which is a profitable and safer alternative to CT scan. Deep learning techniques for computerized study of Lung Ultrasound (LUS) images offer promising opportunities for identifying and diagnosing COVID-19. This paper aims to bring up a Convolution Neural Networking (CNN) model, which accurately predicts the condition of COVID-19 via the output produced lung ultrasound. Three models were developed using various parameters and were tested on the same dataset in order to compare each on standard statistical procedures. The best model achieved an accuracy of 94.67%, sensitivity 55% and specificity of 60% on the test data. © The Electrochemical Society

Information source utilization by livestock and poultry farmers of Uttar Pradesh

The study was conducted during 2020-2021 to assess the information sources utilization pattern of livestock and poultry farmers of Uttar Pradesh. A total of 120 farmers, 40 from each group i.e., dairy, piggery and poultry were selected randomly. Semi-structured personal interview and online survey through google forms were considered together for collection of data keeping in view the COVID-19 second wave. Information source utilization by majority of the respondents was medium. ICT utilization among the respondents was maximum with mean score of 0.63 followed by mass media with mean score of 0.51 and extension agency contact with mean score of 0.498. Education, land holding and experience in farming business were found to be significant contributors in information source utilization. Except age, all the variables such as education, annual income, land holding, experience in farming business and number of trainings undergone were positively correlated with information source utilization of the respondents.

Emerging coronavirus disease COVID-19, a pandemic public health emergency with animal linkages: current status update

After the appearance of first cases of pneumonia of unknown origin in the Wuhan city, China, during late 2019, the disease progressed fast. Its cause was identified as a novel coronavirus, named provisionally 2019-nCoV. Subsequently, an official name was given as SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus-2 by the International Committee on Taxonomy of Viruses ICTV study group. The World Health Organization WHO named the Coronavirus disease-2019 as COVID-19. The epidemics of COVID-2019 have been recorded over 113 countries/territories/areas apart from China and filched more than 4,292 humans, affecting severely around 1,18,326 cases in a short span. The status of COVID-2019 emergency revised by the WHO within 42 days from Public Health International Emergency January 30, 2020 to a pandemic March 11, 2020. Nonetheless, the case fatality rate CFR of the current epidemic is on the rise between 2-4%, relatively is lower than the previous SARS-CoV 2002/2003 and MERS-CoV 2012 outbreaks. Even though investigations are on its way, the researchers across the globe have assumptions of animal-origin of current SARS-CoV-2. A recent case report provides evidence of mild COVID-2019 infection in a pet dog that acquired COVID-2019 infection from his owner in Hong Kong. The news on travellers associated spread across the globe have also put many countries on alert with the cancellation of tourist visa to all affected countries and postponement of events where international visits were required. A few diagnostic approaches, including quantitative and differential real-time polymerase chain reaction assays, have been recommended for the screening of the individuals at risk. In the absence of any selective vaccine against SARS-CoV-2, re-purposed drugs are advocated in many studies. This article discourse the current worldwide situation of COVID-2019 with information on virus, epidemiology, host, the role of animals, effective diagnosis, therapeutics, preventive and control approaches making people aware on the disease outcomes.

Comparative pathology, molecular pathogenicity, immunological features, and genetic characterization of three highly pathogenic human coronaviruses (MERS-CoV, SARS-CoV, and SARS-CoV-2).

The last two decades have witnessed the emergence of three deadly coronaviruses (CoVs) in humans: severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There are still no reliable and efficient therapeutics to manage the devastating consequences of these CoVs. Of these, SARS-CoV-2, the cause of the currently ongoing coronavirus disease 2019 (COVID-19) pandemic, has posed great global health concerns. The COVID-19 pandemic has resulted in an unprecedented crisis with devastating socio-economic and health impacts worldwide. This highlights the fact that CoVs continue to evolve and have the genetic flexibility to become highly pathogenic in humans and other mammals. SARS-CoV-2 carries a high genetic homology to the previously identified CoV (SARS-CoV), and the immunological and pathogenic characteristics of SARS-CoV-2, SARS-CoV, and MERS contain key similarities and differences that can guide therapy and management. This review presents salient and updated information on comparative pathology, molecular pathogenicity, immunological features, and genetic characterization of SARS-CoV, MERS-CoV, and SARS-CoV-2; this can help in the design of more effective vaccines and therapeutics for countering these pathogenic CoVs.