Severe Acute Hepatitis in Children

Viral infections affecting the liver had a serious impact on humanity, as they have led to significant morbidity and mortality in patients with acute and chronic infections. The discovery of the viral agents of severe acute hepatitis in children triggered interest of the scientific community to establish the pathogenesis and diagnostic techniques to identify the affected population. But, WHO, together with scientists in various affected countries, are working to understand the cause of this infection that does not appear to belong to any of the known five types of hepatitis viruses: A, B, C, D and E. Many cases of severe acute hepatitis of unknown origin in children <10 years of age were reported by the International Health Regulations (IHR) was mainly by adenovirus infection, HAdV-41. Although most acute infections cause mild disease and even go undetected, some can lead to complications and turn fatal. With the rapid scientific and technological advances in the last centuries, controlling and even curing the infections became a possibility, with a large focus on preventive medicine through vaccination. The review article describes the epidemiology, pathogenesis, clinical presentation, diagnostic tools and current medication regimens for severe acute hepatitis of unknown origin in children.Copyright © 2022, Global Research Online. All rights reserved.

COVID-19 related stringencies and financial market volatility: sectoral evidence from India

Purpose: This study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020–05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques. Design/methodology/approach: For this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility. Findings: Results show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors. Originality/value: The key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework. © 2022, Emerald Publishing Limited.

Viral Pneumonia and Covid Screening on Lung Ultrasound

The rise of Covid-19 pandemic has exaggerated the necessity for safe, quick and sensitive diagnostic tools to confirm the protection of tending employees and patients. Although ML has shown success in medical imaging, existing studies concentrate on Covid-19 medicine victimization using Deep Learning (DL) with X-ray and computed axial Tomography (CT) scans. During this study we tend to aim to implement CNN model on Lung Ultrasound (LUS), to assist doctors with the designation of Covid-19 patients. We selected LUS since it's quicker, cheaper and additional out there in rural areas compared to CT and X- ray. We have used the biggest public dataset containing LUS pictures and videos of Covid, Pneumonia and healthy patients that has been collected from totally different resources. We tried out frame level approach that extracted 5 frames per patient video. We'll use this dataset to experiment with a CNN model that has hyper parameter calibration. We conjointly enclosed explainable AI using Grad-CAM that uses gradients of a selected target that flows through the convolutional network to localize and highlight regions of the target within the image. Moreover, we'll experiment with completely different data preprocessing techniques that may aid with pattern recognition and increasing the DL model's accuracy like histogram equalization, standardization, Principle Component Analysis (PCA) and Synthetic Minority Oversampling Technique (SMOTE). Lastly, we tend to create a straightforward application that diagnoses LUS videos with our CNN model, and shows the frame results with visual illustration of why the model has taken certain prediction with the help of Gradient-Weighted category Activation Mapping (Grad-CAM). © 2022 IEEE.

COVID-19 related stringencies and financial market volatility: sectoral evidence from India

PurposeThis study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020-05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques. Design/methodology/approachFor this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility. FindingsResults show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors. Originality/valueThe key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework.

Clinical Profile, Treatment and Outcome of Pediatric ''Coffee Bean'' Histiocytosis: A Single Center Experience

Introduction: Langerhans Cell Histiocytosis is a group of diseases with a myriad of clinical manifestations and biological behavior, characterized by proliferation and accumulation of Langerhans cells in different organs. Aims & Objectives: This study is to demonstrate the varied clinical presentations and the treatment outcome of the children in one of the few pediatriccenters in North India that cater to various benign and malignant blood disorders of children. Material(s) and Method(s): The study describes the 4-year experience of our center in managing children with LCH. The clinical presentations, relevant laboratory, and radiological findings, treatment, and outcome of all the 14 children presenting between December 2018 and August 2022 were retrieved from our Hospital Information system. The LCH IV protocol was taken as the backbone for classification, risk organ involvement, stratum allocation, for deciding on treatment strategy, treatment response, and outcome. Result(s): A total of 14 children were diagnosed with LCH during the study period. The mean age at diagnosis was 36 months(range: 10-110 months, median: 34 months). The male: female ratio was 9:5. 12 children had multisystem LCH while 2 children had single system LCH. Lymphadenopathy was the most common clinical presentation while the skeletal system was the most common system involved, affecting 64% of the children. There were a total of 8(57%) children who were in complete remission, of which 1 child expired and one relapsed, though went into the second remission. One child had a progressive disease. Three(21%) children left against medical advice while 1 child abandoned treatment 2 weeks into therapy. One of the children became covid positive after diagnosis and expired before the treatment could be initiated. Conclusion(s): The wide array of clinical manifestations warrants the need for a high index of suspicion for an earlier diagnosis of LCH. The morphological identification of Langerhan's cells and positive IHC for CD1a, S100, and/or CD207 are necessary for definitive diagnosis. All patients with LCH should undergo BRAF-V600E mutational testing to aid in diagnosis and treatment.

An Optimized Deep Learning Approach for the Prediction of Social Distance Among Individuals in Public Places During Pandemic.

Social distancing is considered as the most effective prevention techniques for combatting pandemic like Covid-19. It is observed in several places where these norms and conditions have been violated by most of the public though the same has been notified by the local government. Hence, till date, there has been no proper structure for monitoring the loyalty of the social-distancing norms by individuals. This research has proposed an optimized deep learning-based model for predicting social distancing at public places. The proposed research has implemented a customized model using detectron2 and intersection over union (IOU) on the input video objects and predicted the proper social-distancing norms continued by individuals. The extensive trials were conducted with popular state-of-the-art object detection model: regions with convolutional neural networks (RCNN) with detectron2 and fast RCNN, RCNN with TWILIO communication platform, YOLOv3 with TL, fast RCNN with YOLO v4, and fast RCNN with YOLO v2. Among all, the proposed (RCNN with detectron2 and fast RCNN) delivers the efficient performance with precision, mean average precision (mAP), total loss (TL) and training time (TT). The outcomes of the proposed model focused on faster R-CNN for social-distancing norms and detectron2 for identifying the human 'person class' towards estimating and evaluating the violation-threat criteria where the threshold (i.e., 0.75) is calculated. The model attained precision at 98% approximately (97.9%) with 87% recall score where intersection over union (IOU) was at 0.5.

Post Covid 19 Care: Suggestive Tests and Scans

The COVID 19 virus can leave long-lasting, lingering side effects even after the viral load has depleted. Most of the people they get better within few weeks. But in some people, especially those who got critically ill, needed to stay in the ICU, be put on a ventilator, or have other types of breathing support, in them the virus can impact many vital organs of the body, either directly or sometimes very badly hamper immune response. So, special precautions, some tests and scans might be worth taking it. Our study adds some novelty about the identification of effective biomarkers of progressive disease, and which might be helpful for diagnosis, prevention of complications, and effective therapy. Copyright © The Authors.

Comprehensive Bibliometric Overview of Research Trends of Indian Journal of Pharmaceutical Education and Research

In this study, we have examined the research trends of the Indian Journal of Pharmaceutical Education and Research for the year 2008-2020. We have used bibliometric indicators in two ways on the 1261 documents published in the journal. First, we have presented the performance analysis of the journal, like year-wise distribution of documents, authorship pattern, prolific authors, institutions, and countries. Secondly, the science mapping like keyword analysis, country collaboration, etc., was done using R and Vosviewer. The bibliographic and citation data of 1261 documents were extracted from the Scopus database.

Influence of Hydroxychloroquine Dosage on the Occurrence of Arrhythmia in COVID-19 Infected Ventricle

The interaction mechanisms of Hydroxychloroquine (HCQ) in a COVID-19 infected ventricle and its vulnerability to arrhythmogenesis for different dosage levels is not clearly understood. To address this, a 2D transmural anisotropic ventricular tissue model consisting of endocardial, midmyocardial and epicardial myocytes are configured for mild and severe COVID-19 conditions as well as for three dosage levels of HCQ (1 mu M, 10 mu M and 100 mu M). Results show that under control and mild COVID conditions, increasing the dosage of HCQ prolongs the QT interval as well as QRS duration, although under severe COVID-19 conditions, inverted T-waves are observed. In addition, on pacing with premature beats (PBs), it is observed that under all condition, premature ventricular complexes (PVCs) are created at 1 mu M and 10 mu M HCQ. However, the PVCs are sustained for a longer duration in presence of 10 mu M HCQ. ST elevation is observed under mild COVID-19 conditions and 1 mu M HCQ and reentrant arrhythmic activity is generated in severe COVID-19 conditions and 10 mu MHCQ dosage. Under all conditions, 100 mu M HCQ doesn't generate arrhythmia or PVCs in presence of PBs. This in-silico ventricular model indicates that the dosage of HCQ as well as pacing sequence influences the appearance of arrhythmic activity and could help in guiding HCQ therapy.

Perceived Stress among Medical Students during COVID-19 Pandemic and its Impact on Sleep and Studies - A Cross-sectional Study in South India

Background: COVID-19 pandemic has adversely affected the mental health of medical students due to the lockdown of colleges and educational institutions that had imposed a feeling of uncertainty and insecurity in students. Objectives: The present study aims todetermine the prevalence of stress among medical undergraduate students and its association with sleep and studies during the COVID-19 pandemic. Method: Perceived stress and sleep quality during COVID-19 pandemic was assessed among 446 undergraduate medical students using Perceived Stress Scale (PSS) and Pittsburgh Sleep Quality Index (PSQI) tools. An online questionnaire containing questions retrieved from PSS and PSQI tools was prepared in Google Forms and was shared by e-mail to the students. The students were classified into three categories based on PSS total scores and compared for differences in sleep quality and learning difficulties. Results: The mean score of PSS was 13.38 ± 6.87. 252 (56.5%) had low perceived stress, 146 (32.7%) had moderate and 48 (10.8%) had high perceived stress. First year and final year medical students perceived more stress when compared with others. Among the 446 study participants, 34 (7.6%) reported poor sleep quality and it was significantly associated with the presence of stress (pvalue<0.001). 215 (48.2%) students had difficulty in concentrating on their studies. Conclusion: The COVID-19 pandemic has resulted in perceived stress among medical undergraduate students of which most of them had moderate perceived stress which warrants immediate action. Copyright (c) 2022: Author(s).

Impact of Corona Virus Disease in Pregnancy and Newborn

Background: The novel corona virus has made the world standstill. In India COVID first and second wave has created dramatic fear among the pregnant mothers and the treating obstetricians. Objectives: To study the impact of COVID-19 in pregnancy, newborn and to compare the maternal and neonatal outcome among COVID-19 negative and COVID-19 positive pregnant women during the first and second COVID wave. Materials and Method: This was a prospective study done over one year from July 2020 to July 2021 in a tertiary care hospital in South India. 400 pregnant women attending antenatal outpatient department during COVID willing to participate in the study were included. Nasopharyngeal RT-PCR was done. Socio-demographic profile, maternal and neonatal outcome were compared between non COVID and COVID positive pregnant women. Results: A total of 400 pregnant women were screened for corona virus. 75 pregnant mothers turned positive for COVID-19 and 325 were negative. Among them, 10 were positive during first wave and 65 during second wave. Of them, 20 (26.7%) were asymptomatic and 55 (73.3%) were symptomatic. During the second COVID wave, there was a rise in missed miscarriage (21.5%), intrauterine growth restriction (46.15%), oligohydramnios (53.8%) and intrauterine demise (4.6%). The rate of caesarean and neonatal intensive care unit admission also increased to 70.3% and 59.5% respectively. Conclusion: This study has found increased maternal and neonatal adverse effects associated with COVID second wave. Hence vaccine should be recommended for all pregnant women. Copyright (c) 2022: Author(s).

A Comparative Study of Perception of Online Teaching Versus Traditional Teaching among MBBS Students during COVID Crisis

Background: COVID-19 pandemic has created thelargest disruption in education systems in history. Numerous medical institutions have shifted to online teaching with the hope to reduce viral transmission. Objectives: To compare the effectiveness of online teaching and traditional teaching in the domains of collaborative learning, critical thinking skills and social interaction and to describe the advantages and difficulties faced in online learning by MBBS students. Materials and Methods: Anonline-based cross-sectional study was conducted fromMay 2021 to August 2021 in a private medical college in Salem district of Tamil Nadu, India. Among the 600 MBBS students attending online classes from the first year to final year MBBS, 574 students consented tothe study through mail and were studied using a semi-structured questionnaire prepared in Google form and sent through mail. Descriptive analysis was done and the association between the categorical variables were tested using chi-square test. Results: Traditional way of teaching was perceived to improve the critical thinking skills (p <0.0006), social interaction skills (p<0.044) and collaborative learning (p <0.01) more than online teaching. Advantages of online teaching identified were comfortable learning environment (38%) easier for slow learners (19%), learning at their own pace (18%) etc. Difficulties faced in online teaching were technical difficulties (62%), lack of self-motivation (61%), time management (56%) etc. Conclusion: Challenges faced by the students need to be identified earlier and Governments/educational institutions can focus more on removing the barriers to connectivity. © 2022 Indian Society for Malaria and Communicable Diseases. All rights reserved.

Simplified Cas13-based assays for the fast identification of SARS-CoV-2 and its variants.

The widespread transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for rapid nucleic acid diagnostics that are easy to use outside of centralized clinical laboratories. Here we report the development and performance benchmarking of Cas13-based nucleic acid assays leveraging lyophilised reagents and fast sample inactivation at ambient temperature. The assays, which we named SHINEv.2 (for 'streamlined highlighting of infections to navigate epidemics, version 2'), simplify the previously reported RNA-extraction-free SHINEv.1 technology by eliminating heating steps and the need for cold storage of the reagents. SHINEv.2 detected SARS-CoV-2 in nasopharyngeal samples with 90.5% sensitivity and 100% specificity (benchmarked against the reverse transcription quantitative polymerase chain reaction) in less than 90 min, using lateral-flow technology and incubation in a heat block at 37 °C. SHINEv.2 also allows for the visual discrimination of the Alpha, Beta, Gamma, Delta and Omicron SARS-CoV-2 variants, and can be run without performance losses by using body heat. Accurate, easy-to-use and equipment-free nucleic acid assays could facilitate wider testing for SARS-CoV-2 and other pathogens in point-of-care and at-home settings.

Unlocking the Psychological Toolbox: To Transform or to Sustain

During the current COVID-19 pandemic, soldiers have a unique set of challenges as they are on the frontline, serving a variety of roles. The soldiers have constantly exemplified resilience by proactively adapting to unpredictable situations while preserving their physical, mental, and social well-being. The study, therefore, aims to explore the extant literature on a myriad of evidence-based psychological techniques which can help soldiers augment their reservoir of psychological resources during the current pandemic. An interactive workbook was developed which consisted of exercises to help them develop healthy coping strategies. Thereafter, posters were developed from the workbook so that the information can be disseminated to a wider group of soldiers. Thus, during the current pandemic, this preventive measure aims to help soldiers help themselves, personally as well as cohesively, so that they grow through these challenging experiences. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Comparative analysis of the COVID-19 sequences in India and investigate the trialogue relationship between the miR- NA with Coronavirus and Gut Microbiota

Background: The Coronavirus disease 2019 (COVID -19), an infectious disease caused by newly discovered Novel Coro- navirus. COVID-19 has spread worldwide causing a pandemic, with maximum death -cases. Hence there is an urgent need for vaccines and treatments to be developed to combat the COVID -19. To overcome this Micro RNA (miRNA) based therapy will be an effective option in controlling infection. The miRNA is a noncoding single -stranded RNA that is smaller in size (17-24nucleotides). They are also able to regulate the Gut Microbiota, an essential factor of host immune response. The usage of miRNA instead of other techniques has many advantages that include early detection, improved pathogen identification, detection of latent infection, personalized medicine. Methods: Selective COVID 19 genome sequences with special reference from India by NCBI genome database and Nextstrain.org. Coronavirus subtyping and Mutation analysis carried out by Genome Detective Coronavirus Typing Tool (version 1.1.3) and CLUSTAL OMEGA software. The prediction of antiviral miRNA are performed online by Tar- getscan.org Results: This study integrated selective bioinformatics tools and databases to investigate the COVID -19 sequences in India and the trialogue relationship between the miRNA with Coronavirus and Gut Microbiota. The miRNA is found to be a potential biomarker and also therapeutics for diseases in viral diseases. Conclusions: The miRNA has been extensively documented for their key roles in combating the disease and it is still an unexplored area. As the miRNA regulates the gene of the target, altering the expression can bring in a desired therapeu- tic outcome.

THE COVID-19 EFFECTS ON DENTISTRY

The rapid spread of the COVID-19virus and related pneumonia has posed a major challenge for healthcare systems worldwide. The infection was discovered in the city of Wuhan, Central of China and swept across the world.Theincubation period of the viruscan range from 1-14 days, and the virus spread can happen in the absence of clinical symptoms as well.The most frequently reported symptoms are fever, cough, dyspnea, and myalgia or fatigue. Modes for transmission of virus include direct transmission through coughing,sneezing, and inhalation of droplets and contact transmission through contact with nasal, oral, and ocular mucosa. Droplet and aerosol transmission of the virus are the most common causes of COVID-19 infection in dental clinics and hospitals.COVID-19 virus has lately been detected in saliva of infected patients, thus posing an alert to health professionals to be customarily vigilant in protecting against the infectious disease spread. Because of the presence of virus in saliva, it may be helpful as a non-invasive tool in the rapid detection of the virus.During this pandemic dissemination of COVID-19, dental treatment must be confined to the procedures that cannot be deferred. All the precautions must be taken in terms of triaging, personal protective equipment, hand hygiene, pre-procedural mouthrinse, use of rubber dam, disinfection of the surfaces. Dental professionals are at the highest risk of COVID-19 infection;hence, dental practicehas to be reorganized in order to ensure higher safety standards for both dentists and patients.

Synthesis and bioactivity of readily hydrolysable novel cationic lipids for potential lung delivery application of mRNAs.

Lipid nanoparticles (LNPs) mediated mRNA delivery has gained prominence due to the success of mRNA vaccines against Covid-19, without which it would not have been possible. However, there is little clinical validation of this technology for other mRNA-based therapeutic approaches. Systemic administration of LNPs predominantly targets the liver, but delivery to other organs remains a challenge. Local approaches remain a viable option for some disease indications, such as Cystic Fibrosis, where aerosolized delivery to airway epithelium is the preferred route of administration. With this in mind, novel cationic lipids (L1-L4) have been designed, synthesized and co-formulated with a proprietary ionizable lipid. These LNPs were further nebulized, along with baseline control DOTAP-based LNP (DOTAP+), and tested in vitro for mRNA integrity and encapsulation efficiency, as well as transfection efficiency and cytotoxicity in cell cultures. Improved biodegradability and potentially superior elimination profiles of L1-L4, in part due to physicochemical characteristics of putative metabolites, are thought to be advantageous for prospective therapeutic lung delivery applications using these lipids.

Covid-19 pandemic: Share price volatility behaviour of selected food processing companies in NSE

The Indian financial market and global markets experienced volatility due to pandemic. Estimations of volatility helps to measure the performance of the share price of the company. This paper studies about the impact of pandemic on the food processing companies listed in NSE. The objective of the paper is to examine the level of volatility prevailing in the selected food processing companies share returns. The daily returns of the companies are collected from January 1, 2019 to November 27, 2020.the returns of the selected period is considered for this purpose. GARCH model is used to capture the volatility of the returns. Findings reveal that the high volatility is experienced during the Covid period observations. While comparing the returns of the stock, the returns are positive during the Covid period than the Pre-Covid period. Thus reflecting the bounce back from the unprecedented Covid shocks in the market. © 2021 American Institute of Physics Inc.. All rights reserved.

Effectiveness of implementation of 5S tool in food industry during COVID 19

5S housekeeping is the basics of Lean Manufacturing systems. As a tool for cleansing, sorting, organizing and providing the required basic initial changes for workplace improvement. This paper studies the effectiveness of implementation of 5S methodology in the Angel starch and food Pvt ltd. By following the 5S methodology, it shows important improvements to safety, productivity, efficiency and housekeeping. It also intends to create a stronger work ethic inside the management and staff who would be expected to continue the great practices. To identify the potential level of quality improvement and at the same time will analyse their ability and weakness of every division within the company. Effectiveness of 5S is analysed using before and after implementation in Angel starch and food Pvt ltd using tools. Tools like inventory turnover ratio, labour productivity, process rejection etc… has been used for measurement of daily production, sales, customer return, process rejection, machine breakdown. Result of this research is obtained from comparative measurement of before and after organisational performance. The result shows that 5S is a effective tool for improvement of organisation performance. © 2021 American Institute of Physics Inc.. All rights reserved.

A Safety Measuring Tool to Maintain Social Distancing On COVID-19 Using Deep Learning Approach

Due to this recent wave of the Deadly corona virus disease, which has spread widely all over the world, so physical or Social distancing has become a mandatory precaution to avoid close contact. As of January 2021, the count of affected cases is 10.8 million and recovered cases are 10.5 million and the death rate is 155 thousand. In conformity, we have proposed a system that elucidates the usage of Python, computer vision, and deep learning to monitor whether people are maintaining Social distance at public areas in roads, pathways, work places and, even in hospitals. For the purpose of monitoring social distances among people, we have developed a social distancing detection tool that can keep track of safe distance and determine the distance between people in order to reduce the impact of the corona virus pandemic by analyzing real-time video Streaming, such as CCTV or Camera which can be added with the security camera system at hospitals, workplaces, markets, Jewelers shop etc. As an output, the detection tool will throw A Voice alert or a Notification, so that people would be remained to maintain a social distance.