Insights from establishing a high throughput viral diagnostic laboratory for SARS-CoV-2 RT-PCR testing facility: challenges and experiences.

Background: The World Health Organization declared the coronavirus disease 2019 (COVID-19) a global pandemic on 11 March 2020. Identifying the infected people and isolating them was the only measure that was available to control the viral spread, as there were no standardized treatment interventions available. Various public health measures, including vaccination, have been implemented to control the spread of the virus worldwide. India, being a densely populated country, required laboratories in different zones of the country with the capacity to test a large number of samples and report test results at the earliest. The Indian Council of Medical Research (ICMR) took the lead role in developing policies, generating advisories, formulating guidelines, and establishing and approving testing centers for COVID-19 testing. With advisories of ICMR, the National Institute of Cancer Prevention and Research (NICPR) established a high-throughput viral diagnostic laboratory (HTVDL) for RT-PCR-based diagnosis of SARS-CoV-2 in April 2020. HTVDL was established during the first lockdown to serve the nation in developing and adopting rapid testing procedures and to expand the testing capacity using "Real-Time PCR." The HTVDL provided its testing support to the national capital territory of Delhi and western Uttar Pradesh, with a testing capacity of 6000 tests per day. The experience of establishing a high-throughput laboratory with all standard operating procedures against varied challenges in a developing country such as India is explained in the current manuscript which will be useful globally to enhance the knowledge on establishing an HTVDL in pandemic or non-pandemic times.

Failure to Detect Viral Ribonucleic Acid in Follicular Fluid of a Severe Acute Respiratory Syndrome Coronavirus 2-Infected Female - A Report from the Indian Subcontinent.

Till today, we are still not clear about the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on reproductive tissues and its vertical transmission through the gametes and embryos. There are few case reports that aim to detect the presence or absence of SARS-CoV-2 viral ribonucleic acid (RNA) in the follicular fluid of the infected females. We hereby present the case report of a 33-year-old woman who was undergoing intracytoplasmic sperm injection with testicular sperm aspiration and was found to be positive for SARS-CoV-2 infection. The follicular fluid analysis failed to detect the presence of viral RNA in the sample. Ours is the first case report from India trying to detect the viral RNA from the follicular fluid of a female with SARS-CoV-2 positive status.

Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN.

The emerging novel variants and re-merging old variants of SARS-CoV-2 make it critical to study the transmission probability in mixed-mode ventilated office environments. Artificial neural network (ANN) and curve fitting (CF) models were created to forecast the R-Event. The R-Event is defined as the anticipated number of new infections that develop in particular events occurring over the course of time in any defined space. In the spring and summer of 2022, real-time data for an office environment were collected in India in a mixed-mode ventilated office space in a composite climate. The performances of the proposed CF and ANN models were compared with respect to traditional statistical indicators, such as the correlation coefficient, RMSE, MAE, MAPE, NS index, and a20-index, in order to determine the merit of the two approaches. Thirteen input features, namely the indoor temperature (TIn), indoor relative humidity (RHIn), area of opening (AO), number of occupants (O), area per person (AP), volume per person (VP), CO2 concentration (CO2), air quality index (AQI), outer wind speed (WS), outdoor temperature (TOut), outdoor humidity (RHOut), fan air speed (FS), and air conditioning (AC), were selected to forecast the R-Event as the target. The main objective was to determine the relationship between the CO2 level and R-Event, ultimately producing a model for forecasting infections in office building environments. The correlation coefficients for the CF and ANN models in this case study were 0.7439 and 0.9999, respectively. This demonstrates that the ANN model is more accurate in R-Event prediction than the curve fitting model. The results show that the proposed ANN model is reliable and significantly accurate in forecasting the R-Event values for mixed-mode ventilated offices.

Trim69 is a microtubule regulator that acts as a pantropic viral inhibitor.

Through a screen that combines functional and evolutionary analyses, we identified tripartite motif protein (Trim69), a poorly studied member of the Trim family, as a negative regulator of HIV-1 infection in interferon (IFN)-stimulated myeloid cells. Trim69 inhibits the early phases of infection of HIV-1, but also of HIV-2 and SIVMAC in addition to the negative and positive-strand RNA viruses vesicular stomatitis virus and severe acute respiratory syndrome coronavirus 2, with magnitudes that depend on the combination between cell type and virus. Mechanistically, Trim69 associates directly to microtubules and its antiviral activity is linked to its ability to promote the accumulation of stable microtubules, a program that we uncover to be an integral part of antiviral IFN-I responses in myeloid cells. Overall, our study identifies Trim69 as the antiviral innate defense factor that regulates the properties of microtubules to limit viral spread and highlights the cytoskeleton as an unappreciated battleground in the host-pathogen interactions that underlie viral infections.

Multinational Study to Assess Stress Levels Among the Health Care Workers of Radiation Oncology Community at the Outset of the COVID-19 Pandemic.

PURPOSE: To evaluate stress levels among the health care workers (HCWs) of the radiation oncology community in Asian countries. METHODS: HCWs of the radiation oncology departments from 29 tertiary cancer care centers of Bangladesh, India, Indonesia and Nepal were studied from May 2020 to July 2020. A total of 758 eligible HCWs were identified. The 7-Item Generalized Anxiety Disorder, 9-Item Patient Health Questionnaire, and 22-Item Impact of Events Scale-Revised were used for assessing anxiety, depression, and post-traumatic stress disorder. Univariate and multivariate analysis was done to identify the causative factors affecting mental health. RESULTS: A total of 758 participants from 794 HCWs were analyzed. The median age was 31 years (IQR, 27-28). The incidence of moderate to severe levels of anxiety, depression, and stress was 34.8%, 31.2%, and 18.2%, respectively. Severe personal concerns were noticed by 60.9% of the staff. On multivariate analysis, the presence of commonly reported symptoms of COVID-19 during the previous 2 weeks, contact history (harzard ratio [HR], 2.04; CI, 1.15 to 3.63), and compliance with precautionary measures (HR, 1.69; CI, 1.19 to 2.45) for COVID-19 significantly predicted for increasing anxiety (HR, 2.67; CI, 1.93 to 3.70), depression (HR, 3.38; CI 2.36 to 4.84), and stress (HR, 2.89; CI, 1.88 to 4.43) (P < .001). A significant regional variation was also noticed for anxiety, stress, and personal concerns. CONCLUSION: This survey conducted during the COVID-19 pandemic revealed that a significant proportion of HCWs in the radiation oncology community experiences moderate to severe levels of anxiety, depression, and stress. This trend is alarming and it is important to identify and intervene at the right time to improve the mental health of HCWs to avoid any long-term impacts.

A Regional Pooling Intervention in a High-Throughput COVID-19 Diagnostic Laboratory to Enhance Throughput, Save Resources and Time Over a Period of 6 Months.

An effective and rapid diagnosis has great importance in tackling the ongoing COVID-19 pandemic through isolation of the infected individuals to curb the transmission and initiation of specialized treatment for the disease. It has been proven that enhanced testing capacities contribute to efficiently curbing SARS-CoV-2 transmission during the initial phases of the outbreaks. RT-qPCR is considered a gold standard for the diagnosis of COVID-19. However, in resource-limited countries expenses for molecular diagnosis limits the diagnostic capacities. Here, we present interventions of two pooling strategies as 5 sample pooling (P-5) and 10 sample pooling (P-10) in a high-throughput COVID-19 diagnostic laboratory to enhance throughput and save resources and time over a period of 6 months. The diagnostic capacity was scaled-up 2.15-folds in P-5 and 1.8-fold in P-10, reagents (toward RNA extraction and RT-qPCR) were preserved at 75.24% in P-5 and 86.21% in P-10, and time saved was 6,290.93 h in P-5 and 3147.3 h in P-10.

Potential of Natural Alkaloids From Jadwar (Delphinium denudatum) as Inhibitors Against Main Protease of COVID-19: A Molecular Modeling Approach.

The ongoing pandemic coronavirus disease (COVID-19) caused by a novel corona virus, namely, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a major impact on global public health. COVID-19 cases continue to increase across the globe with high mortality rates in immunocompromised patients. There is still a pressing demand for drug discovery and vaccine development against this highly contagious disease. To design and develop antiviral drugs against COVID-19, the main protease (Mpro) has emerged as one of the important drug targets. In this context, the present work explored Jadwar (Delphinium denudatum)-derived natural alkaloids as potential inhibitors against Mpro of SARS-CoV-2 by employing a combination of molecular docking and molecular dynamic simulation-based methods. Molecular docking and interaction profile analysis revealed strong binding on the Mpro functional domain with four natural alkaloids viz. panicutine (-7.4 kcal/mol), vilmorrianone (-7.0 kcal/mol), denudatine (-6.0 kcal/mol), and condelphine (-5.9 kcal/mol). The molecular docking results evaluated by using the MD simulations on 200 nanoseconds confirmed highly stable interactions of these compounds with the Mpro. Additionally, mechanics/generalized Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations also affirmed the docking results. Natural alkaloids explored in the present study possess the essential drug-likeness properties, namely, absorption, distribution, metabolism, and excretion (ADME), and are in accordance with Lipinski's rule of five. The results of this study suggest that these four bioactive molecules, namely, condelphine, denudatine, panicutine, and vilmorrianone, might be effective candidates against COVID-19 and can be further investigated using a number of experimental methods.

Impact of the First Wave of COVID-19 Pandemic on Radiotherapy Practice at Tata Memorial Centre, Mumbai: A Longitudinal Cohort Study.

PURPOSE: Delivery of cancer care during the pandemic required adopting various changes in the standard management. We analyzed the impact of the first wave of the COVID-19 pandemic on radiation oncology treatment practices at Tata Memorial Hospital in India. MATERIALS AND METHODS: From March 1 to October 31, 2020, all consecutive patients who attended the radiation oncology department for radiotherapy treatment were included in this study. Electronic medical records, patient files, and telephonic consult were used to collect patient's data including changes in the standard treatment practice, COVID-19 testing and its results, and subsequent impact on radiotherapy treatment. Comparison was done with the same period data of 2019 for the number of the caseload, radiotherapy regimen, referral rates, and noncompliance rates. RESULTS: Our study included 4,256 patients with a median age of 52 years (interquartile range 41-61 years). There was a significant drop in the new-patient registrations (approximately 63%), radiotherapy consultations (44.9%), and referrals to other centers (27.8%). The reduction in the caseload was highest for genitourinary cases (-58.5%) and the lowest for breast cases (-11.5%) when compared with the 2019 cohort. Among those treated with radical intent, the noncompliance rate was 15%. Hypofractionation was the commonly adopted regimen across all sites. Compared with 2019, the maximum reduction in the average fractions per patient was seen in the breast cancer cases (-8.2 fraction), followed by genitourinary cases (-4.9 fraction). Of the 27.8% of patients tested for COVID-19, 13.4% turned positive and 3.4% died due to the disease. CONCLUSION: The COVID-19 pandemic adversely affected the number of radiotherapy consultations and treatments at our institute. However, our department offered uninterrupted services despite grave challenges. Hypofractionated regimen was used across disease sites to minimize patient visits and allow planned treatment completion. Radiotherapy was delivered safely, and patients experienced low rates of COVID positivity during radiotherapy and even lower mortality.

COVID-19 induced lockdown effect on wheat supply chain and prices in India - Insights from state interventions led resilience.

COVID-19 incidence in India, impacted the food market, wheat in particular, as the crop harvest coincided with the lockdown disrupting the supply chain and prices posing a few researchable issues - the lockdown effect on wheat supply chain; how the state intervention bolstered the sector to restore; the insights the government interventions offer, etc. The study, using the interrupted time series analysis, investigated the disruption in wheat supply chain, and captured the impact of lockdown on wheat prices. Despite relaxation allowed to agricultural-related activities, lack of transport and labour shortage were reported. Nevertheless, the country registered a record wheat procurement of 38.99 million tonnes. Though the prices spiked post-lockdown, there was no evidence of structural-break and persisting volatility. The findings affirm that supply chain disruption is the main driver for the observed price changes and government interventions like staggered procurement and logistics support resulted in restoration of the wheat economy. The relief measures, infrastructure and its efficient usage, and easing restrictions rendered resilience to wheat supply chain against the COVID-19 shocks. The experience of coordinated efforts of the state machinery and the cooperative farm communities offers confidence about the national capacities to manage disasters of even greater scale in agriculture.

Multifaceted roles of plant derived small molecule inhibitors on replication cycle of SARS-CoV-2.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is an illness caused by the new coronavirus severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). It has affected public health and the economy globally. Currently approved vaccines and other drug candidates could be associated with several drawbacks which urges developing alternative therapeutic approaches. AIM: To provide a comprehensive review of anti-SARS-CoV-2 activities of plants and their bioactive compounds. METHODS: Information was gathered from diverse bibliographic platforms such as PubMed, Google Scholar, and ClinicalTrials.gov registry. RESULTS: The present review highlights the potential roles of crude extracts of plants as well as plant-derived small molecules in inhibiting SARS-CoV-2 infection by targeting viral or host factors essential for viral entry, polyprotein processing, replication, assembly and release. Their anti-inflammatory and antioxidant properties as well as plant-based therapies that are under development in the clinical trial phases-1 to 3 are also covered. CONCLUSION: This knowledge could further help understanding SARS-CoV-2 infection and anti-viral mechanisms of plant-based therapeutics.

Shaping the Innate Immune Response Through Post-Transcriptional Regulation of Gene Expression Mediated by RNA-Binding Proteins

Innate immunity is the frontline of defense against infections and tissue damage. It is a fast and semi-specific response involving a myriad of processes essential for protecting the organism. These reactions promote the clearance of danger by activating, among others, an inflammatory response, the complement cascade and by recruiting the adaptive immunity. Any disequilibrium in this functional balance can lead to either inflammation-mediated tissue damage or defense inefficiency. A dynamic and coordinated gene expression program lies at the heart of the innate immune response. This expression program varies depending on the cell-type and the specific danger signal encountered by the cell and involves multiple layers of regulation. While these are achieved mainly via transcriptional control of gene expression, numerous post-transcriptional regulatory pathways involving RNA-binding proteins (RBPs) and other effectors play a critical role in its fine-tuning. Alternative splicing, translational control and mRNA stability have been shown to be tightly regulated during the innate immune response and participate in modulating gene expression in a global or gene specific manner. More recently, microRNAs assisting RBPs and post-transcriptional modification of RNA bases are also emerging as essential players of the innate immune process. In this review, we highlight the numerous roles played by specific RNA-binding effectors in mediating post-transcriptional control of gene expression to shape innate immunity.

Immune profile and responses of a novel dengue DNA vaccine encoding an EDIII-NS1 consensus design based on Indo-African sequences.

The ongoing COVID-19 pandemic highlights the need to tackle viral variants, expand the number of antigens, and assess diverse delivery systems for vaccines against emerging viruses. In the present study, a DNA vaccine candidate was generated by combining in tandem envelope protein domain III (EDIII) of dengue virus serotypes 1-4 and a dengue virus (DENV)-2 non-structural protein 1 (NS1) protein-coding region. Each domain was designed as a serotype-specific consensus coding sequence derived from different genotypes based on the whole genome sequencing of clinical isolates in India and complemented with data from Africa. This sequence was further optimized for protein expression. In silico structural analysis of the EDIII consensus sequence revealed that epitopes are structurally conserved and immunogenic. The vaccination of mice with this construct induced pan-serotype neutralizing antibodies and antigen-specific T cell responses. Assaying intracellular interferon (IFN)-γ staining, immunoglobulin IgG2(a/c)/IgG1 ratios, and immune gene profiling suggests a strong Th1-dominant immune response. Finally, the passive transfer of immune sera protected AG129 mice challenged with a virulent, non-mouse-adapted DENV-2 strain. Our findings collectively suggest an alternative strategy for dengue vaccine design by offering a novel vaccine candidate with a possible broad-spectrum protection and a successful clinical translation either as a stand alone or in a mix and match strategy.

Smokeless tobacco quitting during COVID-19: A mixed-methods pilot study among participants screened for a cessation trial in India.

INTRODUCTION: COVID-19 and subsequent country-wide lockdown has impacted smokeless tobacco (SLT) product availability in India. We aimed to examine SLT quitting during COVID-19 lockdown among SLT users who consented to be enrolled in a cessation programme. METHODS: Between January-March 2020, we screened 227 exclusive SLT users to be enrolled in a randomized-controlled feasibility study on SLT cessation. However, all activities were suspended due to national lockdown in response to the COVID-19 pandemic. To examine the quitting intention and behaviour during COVID-19 lockdown, we re-contacted these individuals telephonically; during September-October 2020. RESULTS: Of 227 participants, 87 (38.3%) could not be contacted on phone. We conducted telephonic qualitative interviews and assessed the SLT use status, willingness to quit and participate in the SLT cessation trial among the remaining 140 participants. Among these, 12.1% (17/140) showed no willingness to participate in the study due to migration. Since COVID-19 lockdown, 32.1% (45/140) participants reported quitting SLT due to non-availability, increased cost of products, shifts in community norms and family pressures. CONCLUSIONS: COVID-19 pandemic presented an opportunity for tobacco cessation as stringent bans and isolation from social circles enabled tobacco cessation. It also triggered improvement in dissemination of public health information at an unprecedented scale, particularly related to the vulnerability of tobacco users to co-morbidities and harm from SARS CoV-2 infection. Implementation of strict bans on sale and consumption of SLT and strengthening of cessation support may lead to sustainable tobacco control. This study provides insight into effective policy strategies to reduce SLT use; which need to be substantiated with adequate cessation support.

A Review on Indoor Environment Quality of Indian School Classrooms

The progress of Indoor Environmental Quality (IEQ) research in school buildings has increased profusely in the last two decades and the interest in this area is still growing worldwide. IEQ in classrooms impacts the comfort, health, and productivity of students as well as teachers. This article systematically discusses IEQ parameters related to studies conducted in Indian school classrooms during the last fifteen years. Real-time research studies conducted on Indoor Air Quality (IAQ), Thermal Comfort (TC), Acoustic Comfort (AcC), and Visual Comfort (VC) in Indian school classrooms from July 2006 to March 2021 are considered to gain insight into the existing research methodologies. This review article indicates that IEQ parameter studies in Indian school buildings are tortuous, strewn, inadequate, and unorganized. There is no literature review available on studies conducted on IEQ parameters in Indian school classrooms. The results infer that in India, there is no well-established method to assess the indoor environmental condition of classrooms in school buildings to date. Indian school classrooms are bleak and in dire need of energy-efficient modifications that maintain good IEQ for better teaching and learning outcomes. The prevailing COVID-19 Pandemic, Artificial Intelligence (AI), National Education Policy (NEP), Sick Building Syndrome (SBS), Internet of Things (IoT), and Green Schools (GS) are also discussed to effectively link existing conditions with the future of IEQ research in Indian school classrooms.

Inhibition Potencies of Phytochemicals Derived from Sesame Against SARS-CoV-2 Main Protease: A Molecular Docking and Simulation Study.

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, has now spread across the nations with high mortality rates and multifaceted impact on human life. The proper treatment methods to overcome this contagious disease are still limited. The main protease enzyme (Mpro, also called 3CLpro) is essential for viral replication and has been considered as one of the potent drug targets for treating COVID-19. In this study, virtual screening was performed to find out the molecular interactions between 36 natural compounds derived from sesame and the Mpro of COVID-19. Four natural metabolites, namely, sesamin, sesaminol, sesamolin, and sesamolinol have been ranked as the top interacting molecules to Mpro based on the affinity of molecular docking. Moreover, stability of these four sesame-specific natural compounds has also been evaluated using molecular dynamics (MD) simulations for 200 nanoseconds. The molecular dynamics simulations and free energy calculations revealed that these compounds have stable and favorable energies, causing strong binding with Mpro. These screened natural metabolites also meet the essential conditions for drug likeness such as absorption, distribution, metabolism, and excretion (ADME) properties as well as Lipinski's rule of five. Our finding suggests that these screened natural compounds may be evolved as promising therapeutics against COVID-19.

The Role of Machine Learning and Artificial Intelligence for making a Digital Classroom and its sustainable Impact on Education during Covid-19.

During the Disease outbreak and in the future, there will be a lot of learning. Since the pandemic has interrupted global schooling, remote learning has emerged as a viable option, depending on machine learning to accomplish its goals. Using the example of ten international science journals that speak out about artificial intelligence in education today and the future of earning, we hope to gain a better understanding of the large extend of the power of artificial intelligence in education, both during the COVID-19 period and during the future learning time frame. Additionally, in addition to evaluating 10 articles, we used an internet search engine to look for relevant material. We conducted searches using terms such as artificial intelligence, learning during a pandemic, and Machine learning, among other things. After that, we used a phenomenological technique to confirm that our results answered the research questions, which was done in accordance with a qualitative approach. Our findings can be summarized by taking into account the evidence from research and literature. Among our findings are that the detailed assessment of artificial intelligence in education, the use of AI in education, typical learning in the pandemic era, and the role of artificial intelligence (AI) disease outbreak learning are all important for both current and future residents. While statistical methods and automated based on learning jobs that are smarter than normal continue to be important, learning is becoming more automated. It helps individuals to be more concentrated on their learning opportunities and to recognize when they do not grasp a subject completely. First and foremost, the instructors provide valuable assistance throughout the assessment process of student learning outcomes.

Deep Learning Approach for Analyzing the COVID-19 Chest X-Rays.

PURPOSE: The purpose of this study is to analyze the utility of Convolutional Neural Network (CNN) in medical image analysis. In this study, deep learning (DL) models were used to classify the X-ray into COVID, viral pneumonia, and normal categories. MATERIALS AND METHODS: In this study, we have compared the results 9 layers CNN model (9 LC) developed by us with 2 transfer learning models (Visual Geometry Group) 16 and VGG19. Two different datasets used in this study were obtained from the Kaggle database and the Radiodiagnosis department of our institution. RESULTS: In our study, VGG16 yields the highest accuracy among all three models for different datasets as the Kaggle dataset-94.96% and the department of Radiodiagnosis dataset 85.71%. Although, the precision was found better while using 9 LC and VGG19 for both datasets. CONCLUSIONS: DL can help the radiologists in the speedy prediction of diseases and detecting minor features of the disease which may be missed by the human eye. In the present study, we have used three models, i.e.,, CNN with 9 LCs, VGG16, and VGG19 transfer learning models for the classification of X-ray images with good accuracy and precision. DL may play a key role in analyzing the medical image dataset.

ROLE OF EMOTIONAL INTELLIGENCE AND STRATEGIC HUMAN RESOURCE MANAGEMENT DURING COVID-19 PANDEMIC

The strategic human resource management approach can help HR managers in applying emotional intelligence. In this research paper, the authors are looking for an effective solution for human resource managers in the form of strategic human resource management to manage the crisis at the organizational level. The emotional intelligence of the human resource managers will also play an important role in managing the employees. The strategic human resource management system can provide a sustainable competitive advantage to the employees, and it can further help them in improving their competencies and capabilities.

A TWO-DECADE LITERATURE REVIEW ON CHALLENGES FACED BY SMES IN TECHNOLOGY ADOPTION

The purpose of this study is to discuss the importance of technology for SMEs. The world is moving towards technology 5.0, SMEs have not able to adopt technology 2.0 effectively. COVID-19 pandemic has taught the world about the importance of technology in effective working from remote places. In the first section of this study, the authors will discuss the importance of technology adoption;later, the second section will focus on the various challenges in the adoption of technology. The research methodology is based on a systematic literature review. The authors have reviewed the literature of the last twenty years to judge the challenges pertaining to technology adoption. The literature has been reviewed in a longitudinal manner. The findings of this study suggest that the significant challenges in technology adoption are the cost of technology and infrastructure, technical skills and efficiency, adoption challenges, lack of organizational support, and governmental support.