The impact of digital change on student learning and mental anguish in the COVID era

There is a lot of change in the learning of the students after the pandemic COVID-19. To study the resulting impact on their learning is the main aim of this article. To review this, a dataset of the various students is created and subsequently processed and visualized. The data is undergone to the various classification techniques using machine learning. It is observed after the analysis that the support vector machine (SVM) method is best in terms of the classification accuracy while random forest (RF) method is best in terms of the classification sensitivity. © 2022 Nova Science Publishers, Inc..

Antiviral Potential of Medicinal Plants for the COVID-19

Background: SARS-CoV-2 infection has spread throughout the globe and has become a terrible epidemic. Researchers all around the globe are working to understand the characteristics of coronavirus and are trying to find antiviral compounds as an alternative to vaccines. Objective(s): The present study has been conceptualized to screen the various metabolites of traditional therapeutic plants that can have crucial antiviral activity against COVID-19. Method(s): Medicinal plants are rich sources of therapeutic agents of human origin. In this study, active metabolites from plants such as O. sanctum, C. longa, A. indica, Z. officinale, A. paniculata, G. glabra, A. sativum, P. guajava, V. negundo and S. aromaticum have been studied. This study aims to control COVID-19, either by interfering with the Cysteine-like protease (3CLpro) component of COVID-19 or by blocking viral entry via the human angiotensin-converting enzyme 2 (ACE 2) receptor. The molecular docking of forty plant metabolites was studied with the 3Clpro component and ACE 2 receptors. In addition to this, the binding capacity of these two targets was also compared with hydroxychloroquine used for its treatment. Result(s): The results reveal that Glycyrrhizin binds to 3CLpro in a highly stable manner with the lowest binding energy. Glabridin, beta-sitosterol, beta-Caryophyllene, alpha-Curcumene, and Apigenin, among others, have shown effective interactions with both ACE 2 and 3CLpro. The study reveals the ability of more than 20 plant-based compounds against the COVID-19 infection cycle, which are more effective than hydroxychloroquine. Conclusion(s): Medicinal plant-based therapeutic compounds might provide quickly, sensitive, precise, and cost-effective alternative therapies. To reduce adverse effects, many pharmacological characteristics of medicinal plant agents should be adjusted. Copyright © 2022 Bentham Science Publishers.

An insight into the molecular mechanisms of mesenchymal stem cells and their translational approaches to combat COVID-19

The COVID-19 pandemic has posed a challenge to healthcare management systems around the globe. The communicability and pathogenicity of the virus are unmatched and extensive. The most common symptoms in mild cases include cough, cold, fever, headaches, shortness of breath, while in serious cases it can lead to sepsis, multiple organ failure, and ultimately death. The management of this disease has caused extreme shortness of medical aids, hospital beds, oxygen availability, and drug availability. Even though many approaches have been tried, none of them have fully catered to the therapeutic needs against this disease. This had led to the failure of all pretested therapeutic aids and drugs and made the world almost succumb to despair. The formulation and manufacturing of vaccines are still underway, and their credibility against different mutated variants of SARS-CoV-2 is another dubious factor. Under such unpredictable circumstances, the evidenced immunomodulatory abilities of mesenchymal stem cells (MSCs) have risen to popularity. There have been several trials registered for the testing of MSC therapy against COVID-19 and they have demonstrated safety and efficacy. MSCs exhibit various molecular mechanisms which are responsible for their regenerative abilities and help in combating COVID-19. However the risk of transplanting whole cells still remains a concern due to a probability of causing emboli formation due to the high dose of cell infusion, moreover the need for repetitive doses due to viability issues with MSCs is another problematic factor. Due to this there has been a shift in the focus of therapy from whole cells toward the use of their derivative extracellular vesicles (EVs). The small size, membrane bound structure, and functionality of EVs has the potential to lead to a medical revolution and assist in combating the COVID-19 pandemic holistically. © 2022 Elsevier Inc. All rights reserved.

Observational study of Covid-19 patients presenting with acute coronary syndrome at a tertiary care center in India

Aim: Patients with Covid-19 are theoretically at a higher risk of ACS, as respiratory infections can often lead to coronary endothelial damage and plaque rupture. Initial reports during start of pandemic suggested decrease in STEMI patients, however this has been explained by iatrophobia rather than actual decrease. Data on pathophysiology and outcome of patients presenting with ACS is scarce. We did a prospective observational study to study epidemiology and outcomes of Covid-19 patients with ACS. Methods: A total of 654 patients were admitted with Covid-19 at PGIMER, Chandigarh from August 2020 to February 2021, 35 (5.3%) consecutive patients of ACS were enrolled into the study. Acute myocardial infarction was defined as per fourth universal definition of myocardial infarction. Diagnosis of Covid-19 was established using RT-PCR from nasopharyngeal swab. Angiographic assessment was done by two interventional cardiologists. Results: Mean age of patients was 59.5±11.8 years, males comprised majority (80%) of study group. Most common risk factor was hypertension seen in around 70% followed by DM in 57% patients. Most common symptom at presentation was rest angina seen >90% while history of fever was present in only 31.4%. STEMI was most common ACS seen in 45.7% followed by USA in 23% patients. CS was present in 15% patients at presentation while another 5% developed shock in hospital. Oxygen requirement was required in over half the patients while 25% patients succumbed to illness in hospital.Thrombolysis was done in half the patients of STEMI. In view of Covid-19 disease 71.4% required dexamethasone and remdesivir. Coronary angiography was done in around 20% patients, which revealed obstructive CAD in 83% patients with 60% patients having 100% occlusion of IRA. Percutaneous intervention was done in 66% patients. Hypoalbuminemia was commonly seen patients with mean albumin of 3.3 gm/dL. Low T3 syndrome was most common thyroid function abnormality seen in 37.1%.On univariate analysis age, BNP levels and albumin were able to predict 30-day mortality. Conclusion: ACS can be first presentation of patients with Covid-19 as shown by our study only 30% patients had prior history of fever. Our data reaffirms that patients with Covid-19 and ACS have worse prognosis. Interestingly mortality in our study was comparable to western study, despite low rate of angiography and intervention thus underscoring individualization of therapy. We believe Type-2 myocardial infarction is common in pathophysiology of patients who benefit most from medical therapy.

AN AHP-BASED OPTIMAL DISTRIBUTION MODEL AND ITS APPLICATION IN COVID-19 VACCINATION

COVID-19 is causing a large number of causalities and producing tedious healthcare management problems at a global level. During a pandemic, resource availability and optimal distribution of the resources may save lives. Due to this issue, the authors have proposed an Analytical Hierarchy Process (AHP) based optimal distribution model. The proposed distribution model advances the AHP and enhances real-time model applicability by eliminating judgmental scale errors. The model development is systematically discussed. Also, the proposed model is utilized as a state-level optimal COVID-19 vaccine distribution model with limited vaccine availability. The COVID-19 vaccine distribution model used 28 Indian states and 7 union territories as the decision elements for the vaccination problem. The state-wise preference weights were calculated using the geometric mean AHP analysis method. The optimal state-level distribution of the COVID-19 vaccine was obtained using preference weights, vaccine availability and the fact that a patient requires exactly rvaccine doses to complete a vaccination schedule. The optimal COVID-19 vaccine distribution along with state and union territory rank, and preference weights were compiled. The obtained results found Kerala, Maharashtra, Uttarakhand, Karnataka, and West Bengal to be the most COVID-19 affected states. In the future, the authors suggest using the proposed model to design an optimal vaccine distribution strategy at the district or country level, and to design a vaccine storage/inventory model to ensure optimal use of a vaccine storage center covering nearby territories. © 2020. All Rights Reserved.

A Three-Fold Machine Learning Approach for Detection of COVID-19 from Audio Data

Most work on leveraging machine learning techniques has been focused on using chest CT scans or X-ray images. However, this approach requires special machinery, and is not very scalable. Using audio data to perform this task is still relatively nascent and there is much room for exploration. In this paper, we explore using breath and cough audio samples as a means of detecting the presence of COVID-19, in an attempt to reduce the need for close contact required by current techniques. We apply a three-fold approach of using traditional machine learning models using handcrafted features, convolutional neural networks on spectrograms and recurrent neural networks on instantaneous audio features, to perform a binary classification of whether a person is COVID-positive or not. We provide a description of the preprocessing techniques, feature extraction pipeline, model building and a summary of the performance of each of the three approaches. The traditional machine learning model approaches state-of-the-art metrics using fewer features as compared to similar work in this domain. © 2021, Springer Nature Switzerland AG.

Impact of covid-19 pandemic and national lockdown on mental health among general urban indian population: An online based cross-sectional survey

Purpose: The aim of the study is to assess the prevalence of anxiety and depression among the urban Indian population during the period of national lockdown imposed by the government of India to combat the COVID-19 pandemic Method: Total 278 participants were participated in an online, cross-sectional survey. Anxiety and depression was assessed. Gender, age, occupation and average time spent on gathering information on COVID-19 was assessed. Results: less than 30 years of age and students showed higher prevalence of depression. Participants spending more than three hours on COVID-19 information showed that 18.2%, 42.4% and 37.9% were mildly, moderately and severely affected by anxiety symptoms, respectively and 19.7%, 47% and 24.2% were mildly, moderately and severely affected with depression. Further, more than three hours of time spent on COVID-19 showed strong association with mild, moderate and severe anxiety (p<0.001) as well as mild, moderate and severe depression (p≤0.01). Conclusions: Participants, less than 30 years of age and students were found more likely to have anxiety and depression symptoms. Participants who have been spending more than three hours on COVID-19 information were strongly affected with mild, moderate and severe anxiety as well as depression.

Mesenchymal stem cell-derived exosome as a nano weapon to target the COVID-19 pandemic

In these times of despair when a nano-sized organism, the SARS-CoV-2, has rendered the human race helpless, made the global health status decline, and drowned the world economy, a ray of hope comes from another nano-sized particle, the exosome. The potential of mesenchymal stem cells has already been established in COVID-19;however, cell-based therapy has its risks. We thereby propose cell-free therapy using stem cells-derived exosomes to fight against COVID-19, as they can be a game-changer owing to their immunomodulatory nature, which combats the cytokine storm characterizing this disease, and their practical efficiency, which will realistically aid large access to therapy worldwide.

Physical activity and emotional status of college students and working sector on 1 month lockdown

Introduction: Due to COVID-19 pandemic outbreak, a lot of countries are under lockdown for more than 30 days. The study is about the physical activity and emotional status of college students and the working sector for 1 month lockdown. Aim: To check the physical and emotional status of college students and in the working sector, while the response is either positive or negative towards the health concern. Method: A web survey was used which is based on IPAQ and PERS scales by 150 candidates. Result: IPAQ show the physical activity perform by the 150 candidates where the maximum candidate was of low activity and PERS shows the positive and negative reactivity of the candidates where the negative reactivity was high than positive reactivity. Conclusion: The low physical activity stimulates the negative reactivity.

Epidemiological and clinical profile of covid-19 in nepali children: An initial experience

Introduction: COVID-19 has spread all around the world with huge toll of human lives and suffering since it evolved in China. Nepal had slow rise in morbidity due to COVID 19 in early days but has been gripped by the pandemic's exponential growth lately. This study was conducted with the aim to describe the clinical and epidemiological features of Nepali children in early phase of the pandemic. Methods: This was an observational study conducted at 11 COVID care centres designated by the Government of Nepal with availability of supervision by paediatricians between January and August 2020 in children under 18 years of age diagnosed with COVID 19. Data was collected based on definitions outlined in data collection resources available at WHO-ISARIC Global COVID-19 clinical resources platform and analysed. Results: One hundred and twenty one children diagnosed with COVID 19 who presented to the designated centres were enrolled. Majority of children (83.4%) were identified as a part of contact tracing, 28.1% had an identified contact to a person with COVID 19 prior to their diagnosis and 20.7% had another household member diagnosed with COVID 19. The mean age of admitted children was 8.8 years (SD 5.6 years) with the largest proportion being adolescents (40.5%). Male (58.7%) children were more commonly affected. There were 15 (12.4%) infants and 8 (6%) of them were under two months of age. Most children (87, 71.9%) were asymptomatic, 21 (22.3%) had mild symptoms and six (4.9%) had moderately severe symptoms. Fever (18.2%) was the most commonly reported symptom. All children were discharged after a median of 14 days of hospitalisation. Conclusions: Nepali children of all ages are affected by COVID 19 and present with asymptomatic or mildly symptomatic infection. Fever and respiratory symptoms are the most commonly reported symptoms. Most children do not develop complications. Continued surveillance in larger population of children as the pandemic unfolds will generate more stringent observations.

SARS-CoV-2 detection in urine sediment suggests infection of kidneys and correlates with risk of AKI and poor COVID-19 prognosis

Background: Since the emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), most of the focus has been on the respiratory failure caused by the resulting disease, COVID-19. However, the effects of COVID-19 in the kidney are increasingly recognized. Acute kidney injury (AKI) has been identified with varying prevalence around the world with higher rates (37-46%) reported in the USA. It is debatable whether AKI is an indirect consequence of systemic inflammation or a consequence of viral renal cell infection and tropism. We hypothesize that SARSCoV- 2 directly infects kidney tissue and increases the risk of developing AKI, worsening prognosis of COVID-19 patients. Methods: We studied 88 COVID-19 patients admitted to the Henry Ford Hospital, Detroit after April 15, 2020. Demographics were: mean age 60, 71% African American, 55% male. We quantified viral copies by RT-PCR (S and N genes) in urine sediments from 52 PCR-confirmed COVID-19 patients. We performed immunofluorescence for Membrane and Spike viral proteins in two COVID-19 biopsies. Results: The prevalence of AKI was 72%, with 32% of patients admitted to the ICU. The overall mortality rate was 14%, with no deaths in non-AKI patients. Viral proteins M and S were detected in the glomerulus, parietal cells and tubules of COVID-19 patients. In some tubules, positive SARS-CoV-2 overlapped with ACE2, the receptor for viral entry. Virus was detected in 61% of urine sediments, with 6-fold greater viral load in AKIpatient urines (copies/ng RNA: AKI, 7422±1338 vs No-AKI: 1523 ± 404;p<0.05, n=52). The highest viral loads were detected three weeks post-AKI at 11,374±2248 copies/ng RNA (p<0.01). Among COVID-19 AKI-patients who died, the urine viral load exceeded 8000 copies/ng RNA. Above this threshold, the mortality rate was 55%. Conclusions: Our data support that direct viral renal cell infection occurs in COVID-19 AKI patients with urinary viral genome detection. Greater urinary viral loads portend increased mortality. Urinary viral detection can facilitate management and treatment of COVID-19 and improve outcomes. Future research should focus on studying whether urine contains infective virus or sheds non-infective genomic fragments.

nSARS-Cov-2, pulmonary edema and thrombosis: possible molecular insights using miRNA-gene circuits in regulatory networks.

BACKGROUND: Given the worldwide spread of the novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection pandemic situation, research to repurpose drugs, identify novel drug targets, vaccine candidates have created a new race to curb the disease. While the molecular signature of nSARS-CoV-2 is still under investigation, growing literature shows similarity among nSARS-CoV-2, pulmonary edema, and thromboembolic disorders due to common symptomatic features. A network medicine approach is used to to explore the molecular complexity of the disease and to uncover common molecular trajectories of edema and thrombosis with nSARS-CoV-2. RESULTS AND CONCLUSION: A comprehensive nSARS-CoV-2 responsive miRNA: Transcription Factor (TF): gene co-regulatory network was built using host-responsive miRNAs and it's associated tripartite, Feed-Forward Loops (FFLs) regulatory circuits were identified. These regulatory circuits regulate signaling pathways like virus endocytosis, viral replication, inflammatory response, pulmonary vascularization, cell cycle control, virus spike protein stabilization, antigen presentation, etc. A unique miRNA-gene regulatory circuit containing a consortium of four hub FFL motifs is proposed to regulate the virus-endocytosis and antigen-presentation signaling pathways. These regulatory circuits also suggest potential correlations/similarity in the molecular mechanisms during nSARS-CoV-2 infection, pulmonary diseases and thromboembolic disorders and thus could pave way for repurposing of drugs. Some important miRNAs and genes have also been proposed as potential candidate markers. A detailed molecular snapshot of TGF signaling as the common pathway, that could play an important role in controlling common pathophysiologies among diseases, is also put forth. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s41544-020-00057-y.

Prevalence of SARS-CoV-2 infection in India: Findings from the national serosurvey, May-June 2020.

BACKGROUND & OBJECTIVES: Population-based seroepidemiological studies measure the extent of SARS-CoV-2 infection in a country. We report the findings of the first round of a national serosurvey, conducted to estimate the seroprevalence of SARS-CoV-2 infection among adult population of India. METHODS: From May 11 to June 4, 2020, a randomly sampled, community-based survey was conducted in 700 villages/wards, selected from the 70 districts of the 21 States of India, categorized into four strata based on the incidence of reported COVID-19 cases. Four hundred adults per district were enrolled from 10 clusters with one adult per household. Serum samples were tested for IgG antibodies using COVID Kavach ELISA kit. All positive serum samples were re-tested using Euroimmun SARS-CoV-2 ELISA. Adjusting for survey design and serial test performance, weighted seroprevalence, number of infections, infection to case ratio (ICR) and infection fatality ratio (IFR) were calculated. Logistic regression was used to determine the factors associated with IgG positivity. RESULTS: Total of 30,283 households were visited and 28,000 individuals were enrolled. Population-weighted seroprevalence after adjusting for test performance was 0.73 per cent [95% confidence interval (CI): 0.34-1.13]. Males, living in urban slums and occupation with high risk of exposure to potentially infected persons were associated with seropositivity. A cumulative 6,468,388 adult infections (95% CI: 3,829,029-11,199,423) were estimated in India by the early May. The overall ICR was between 81.6 (95% CI: 48.3-141.4) and 130.1 (95% CI: 77.0-225.2) with May 11 and May 3, 2020 as plausible reference points for reported cases. The IFR in the surveyed districts from high stratum, where death reporting was more robust, was 11.72 (95% CI: 7.21-19.19) to 15.04 (9.26-24.62) per 10,000 adults, using May 24 and June 1, 2020 as plausible reference points for reported deaths. INTERPRETATION & CONCLUSIONS: Seroprevalence of SARS-CoV-2 was low among the adult population in India around the beginning of May 2020. Further national and local serosurveys are recommended to better inform the public health strategy for containment and mitigation of the epidemic in various parts of the country.

A nonlinear epidemiological model considering asymptotic and quarantine classes for SARS CoV-2 virus.

In this article, we develop a mathematical model considering susceptible, exposed, infected, asymptotic, quarantine/isolation and recovered classes as in case of COVID-19 disease. The facility of quarantine/isolation have been provided to both exposed and infected classes. Asymptotic individuals either recovered without undergo treatment or moved to infected class after some duration. We have formulated the reproduction number for the proposed model. Elasticity and sensitivity analysis indicates that model is more sensitive towards the transmission rate from exposed to infected classes rather than transmission rate from susceptible to exposed class. Analysis of global stability for the proposed model is studied through Lyapunov's function.