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Abatract: In recent years studies of nanomaterials have been explored in the field of microbiology due to the increasing evidence of antibiotic resistance. Nanomaterials could be inorganic or organic, and they may be synthesized from natural products from plant or animal origin. The therapeutic applications of nano-materials are wide, from diagnosis of disease to targeted delivery of drugs. Broad-spectrum antiviral and antimicrobial activities of nanoparticles are also well evident. The ratio of nanoparticles surface area to their volume is high and that allows them to be an advantageous vehicle of drugs in many respects. Effective uses of various materials for the synthesis of nanoparticles impart much specificity in them to meet the requirements of specific therapeutic strategies. The potential therapeutic use of nanoparticles and their mechanisms of action against infections from bacteria, fungi and viruses were the focus of this review. Further, their potential advantages, drawbacks, limitations and side effects are also included here. Researchers are characterizing the exposure pathways of nano-medicines that may cause serious toxicity to the subjects or the environment. Indeed, societal ethical issues in using nano-medicines pose a serious question to scientists beyond anything.
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Indroduction: Thrombotic complications leading to cerebrovascular events occuring in conjunction with Covid-19 vaccination though rare, is well-documented. Moyamoya Angiopathy is a progressive intracranial vasculopathy leading to recurrent strokes. Case presentation: We present two index cases of young patient presenting with stroke and TIA following Covid-19 vaccination (COVISHIELD) leading to unmasking of Moyamoya Angiopathy. Conclusion(s): Arterial stroke following Covid-19 vaccination is documented, but uncommon. However, in the background of a vasculopathy, it may not be so rare. Moyamoya Angiopathy has been closely studied in the model of inflammatory pathophysiology in genetically predisposed patients leading to progressive vaso-occlusive disease. Few reports of Covid-19 infection potentiating Moyamoya Angiopathy symptoms are also documented. Thus, as an extrapolation of the inflammatory etiopathogenesis of Moyamoya Angiopathy, Covid-19 vaccination can similarly affect the Moyamoya symptomatology. These two index cases open new lines of enquiry regarding the interplay of Covid-19 vaccination and neurological destabilization in patients with underlying vasculopathy of inflammatory pathophysiology.Copyright © 2022
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OBJECTIVE: Wide arrays of laboratory parameters have been proposed by many studies for prognosis in COVID-19 patients. In this study, we wanted to determine if the International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score in addition to certain clinical and laboratory parameters would help in predicting mortality. We wanted to determine if a greater severity score on chest x-ray at presentation translated to poor patient outcomes using the COVID-19 chest radiography score. MATERIAL AND METHODS: This retrospective study was conducted at SDS TRC and Rajiv Gandhi Institute of chest diseases, Bangalore from March 2021 to June 2021. This study included 202 real-time-polymerase chain reaction-positive COVID-19 patients aged above 18 years admitted to the intensive care unit of our hospital. Demographic characteristics and baseline hematological and inflammatory markers (serum C-reactive protein, lactate dehydrogenase, troponin-I, ferritin, and d-dimer) were collected. Radiological severity on a chest x-ray was assessed using the validated COVID-19 chest radiography score. The International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score was assigned to each patient within 24 hours of intensive care unit admission. Outcome studied was in-hospital mortality. RESULT(S): The overall mortality was 54.9% (111 cases). Age more than 50 years, >4 days of symptoms, peripheral oxygen saturation/ fraction of inspired oxygen ratio less than 200, elevated serum lactate dehydrogenase >398.5 IU/L, and hypoalbuminemia (<2.95 g/dL) were detected as independent predictors of mortality. A significant correlation of risk stratification with mortality (P = .057) was seen with International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score. There was no significant correlation between the COVID-19 chest radiography score and mortality. CONCLUSION(S): Age >50 years, peripheral oxygen saturation/fraction of inspired oxygen ratio <200, mean symptom duration of >4 days, elevated serum lactate dehydrogenase, and hypoalbuminemia are independent predictors of mortality in severe COVID-19 pneumonia. International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score was different in the survivors and deceased.Copyright © Author(s).
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The current study examines the air quality trends in response to Covid-19-induced lockdowns at various locations in Delhi. The primary pollutants like NO2, CO, and PM10 have shown reductions during the lockdown phase, but the magnitude varied significantly in different places. Also, during the lockdown, air quality in some areas of Delhi exceeded National Ambient Air Quality Standards. Secondary pollutants like O3 have shown mixed trends due to complex atmospheric processes and dependence on relative proportions of VOC and NOx levels. A total of six sites, including traffic, industrial, and residential sites, have been studied. The diurnal behavior of pollutants also differed significantly around different places. During the lockdown, Ashok Vihar, a traffic-influenced area, showed a decrease in O3 (~ 40%), while at DTU (Traffic site), O3 levels increased (~ 48%). The industrial sites Okhla and Wazirpur also showed different trends during the lockdown;O3 in Wazirpur decreased by 50%, whereas Okhla increased by 25%. NOx concentration was lesser in 2020 at all the stations compared to 2019, indicating the positive impact of the lockdown on air pollution due to vehicular emissions. The Approximate Envelope Method estimates the secondary fraction of PM2.5. This fraction of PM is dominated in the lockdown year in the residential site, while it remains unchanged in the traffic site and increased by 11% in the industrial area. Despite being not so far from each other, these sites show very different patterns of pollutants during lockdown episodes. © 2023, The Author(s) under exclusive licence to Institute of Earth Environment, Chinese Academy Sciences.
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Typhoid fever is a major concern in developing nations. People living in endemic area may frequently get exposed to the typhoid bacilli and can carry some amount of antibody in their circulations which can easily lead to misdiagnosis during other febrile illness. To assess the frequency of false sero-positivity of Salmonella specific antibody in Dengue and COVID-19 patients. An observational case control study was conducted in a multispecialty teaching hospital in north India. A total of 110 serum samples which included dengue IgM positive patients (N= 40), COVID-19 RT-PCR positive patients (N=40) and control subjects (N=30) without any febrile illness were studied. All the samples were tested for Salmonella specific antibody by Widal test and by immune chromatography strip test (ICT). Patient's detail were documented in a structured Performa. Out of 110 samples 63(57%) were male and 47(43%) were female with age mean age +/-45 years. Among the dengue IgM positive patients 8(20%) patients sample showed significant O and H titre of Salmonella typhi (O:80;H:160) in Widal test. Similarly in SARS-CoV-2 RT-PCR positive patients sample 8(20%) patients serum sample showed significant titre of O and H antigen. In control group population significant O antigen along with H antigen of Salmonella typhi were observed in 2(6.6%) sample. False positivity in the serological test should be reported with caution and repeated test should be performed until the etiological agents were not confirmed, in this way we can minimize the misdiagnosis and can prevent the morbidity and mortality as well. Copyright © 2023 The Author(s).
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The Covid-19 pandemic escalated demand for scientific explanations and guidance, creating opportunities for scientists to become publicly visible. In this study, we compared characteristics of visible scientists during the first year of the Covid-19 pandemic (January to December 2020) across 16 countries. We find that the scientists who became visible largely matched socio-cultural criteria that have characterised visible scientists in the past (e.g., age, gender, credibility, public image, involvement in controversies). However, there were limited tendencies that scientists commented outside their areas of expertise. We conclude that the unusual circumstances created by Covid-19 did not change the phenomenon of visible scientists in significant ways.
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The purpose of this study was to look at small business owners' entrepreneurial resilience and mental well-being during adversity. This paper tries to gauge the effect of the COVID-19 pandemic on an entrepreneur's mental wellness and how being resilient in their approach to handling uncertainties mediates and positively envisages their mental wellness. The quantitative approach was utilized to collect data and achieve the specified goal. The information was gathered from 159 small business owners in Varanasi, India. The partial least squares method was used to analyze the collected data. Future research should look for more accurate ways to measure resilience as well as personal traits that could be used to further analyze the person–entrepreneurial context fit. In order to improve the generalizability of the study's findings, researchers can also consider perceived adversity and resilience as mediating factors, in addition to the actual adversity and resilience assessed in this study. © 2022 Fortune Institute of International Business.
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The COVID-19 pandemic has adversely impacted the tourism industry. Tourists are refraining from going on vacation. Getting their patrons back is one of the biggest challenges of the tourism industry. This study explores the factors affecting the vacationing intention of Indian tourists in the COVID-19 period. It also studies the moderating effect of perceived risk on the willingness to pay a price premium for perceived safety measures. The findings of this study will enable the practitioners to understand the drivers of the travelling intention of Indian tourists and thereby devise a suitable strategy to encourage footfalls.
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In COVID-19, most of the patients have been diagnosed with pneumonia in their early stages. Most of the symptoms that have been in the display or have evolved in the last couple of months like fever, cough, and shortness of breath have been predominant. Moreover, based on the studies and reports of the infected patients, symptoms like heart disease, hypertension, chest pain, diarrhea, and nasal congestion have shown a significant impact in the sustenance of COVID-19. Taking all these symptoms into consideration along with the person’s age, a prediction process has been developed in this chapter to check whether the person is infected with COVID-19 or not. Based on the significance of these attributes, we have applied artificial neural network to classify the patient’s condition into three classes, which include no infection, mild infection, and serious infection. We have achieved an accuracy of 84.7% in predicting the cases. © 2022 Elsevier Inc. All rights reserved.
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NV-CoV-2, a nanoviricide composed of covalently attached polyethylene glycol and alkyl pendants that are designed to bind free virion particles of multiple strains of coronaviruses in a broad-spectrum manner at multiple points. The binding interaction is like a nano-velcro-tape and may cause a lipid–lipid fusion between nanoviricide micelle and the lipid envelope of the virus. A nanoviricide can encapsulate the virus and dismantle it without any involvement of the host immune system, ultimately disabling the infectibility of the host cells. Thus, it may be expected to count a stronger and synergistic antiviral effect by combining NV-CoV-2 with other anti-coronavirus regimens like remdesivir. Furthermore, some ligands similar to the SARS-CoV S-protein are designed by molecular modeling and attached to the nanoviricide at the same site as where the cognate cellular receptor, ACE2, binds. As a result, a competitive binding inhibition may occur. A nanoviricide can encapsulate other antiviral compounds and protect them from serum-mediated degradation in vivo. This makes the antiviral compounds available for a longer period of time to interact with RNA polymerase and inhibit it. Altogether, a multipoint antiviral efficacy can be achieved with our nanoviricide, NV-CoV-2. Copyright © 2022 Chakraborty, Diwan, Barton, Arora, Thakur, Chiniga, Tatake, Pandey, Holkar, Holkar and Pond.
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Introduction: Early and correct identification of the betacoronavirus is important for effective isolation treatment and case management. Real-time polymerase chain reaction (PCR) are consider as a gold standard for the diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2);however, for that, there are a requirement of skilled workforce and elaborate infrastructure. A rapid point of care test known as Truenat Beta CoV and Truenat SARS COV assay were recommended by the Government of India. The aim of the study was to find out the performance of Truenat assay in comparison to four RT-PCR assay kits. Materials and Methods: The cross sectional study was conducted in a COVID-19 testing laboratory in Central India. Forty known Truenat positive sample with different viral load were analyze in selected rtPCR kits from 4 different manufacturers. Results: Of the total of ten very low viral load samples, BGI kit was able to detect six samples, followed by TruePCR six samples, TaqPath five samples and NIV kit were able to detect three samples. Similarly, in the case of low viral load sample, BGI and TaqPath kit were able to detect all the 10 samples followed by NIV kit five samples and TruePCR nine samples respectably. In the case of medium and high viral load samples, all four reverse transcription-PCR (RT-PCR) kits were shown a 100% detection rate. Conclusions: Based on our findings, we believe truenat RT-PCR is a more reliable technique for the detection of SARC-CoV-2. Hence, it should be installed in the healthcare setup for better control of the pandemic.
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With the rapid spread of Covid-19 cases throughout the world, all the nations have been sentenced to partial or complete lockdowns for their safety. Throughout this one section which has been almost completely under lockdown was the Education sector where students were hardly allowed to attend physical classes around 1.5 years now. Our aim in this paper is to use the social media tweets in understanding how the people have felt throughout this course of time, what difficulties they have faced, what are the advantages, disadvantages they feel are of this new normal. We will be extracting data from the social media using natural language processing, text mining techniques, sentiment analysis to determine various insights as to what they have faced and can this New Normal be actually normal someday. We have used Tableau Software to highlight the countries where concerned tweets have been posted more. Also using Word cloud we have tried to map the main concerns. We see that there have mixed concerns related to Education from fear of letting the students attend physical mode lectures to concerns as to what side-effects would be caused due to late conduction of exams and reaction to various government laws regarding the same.
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Background: COVID-19 pandemic shifted all the classroom teaching to virtual online platforms. The overnight change in the teaching structure posed serious challenges especially for medical education. This study aims to assess the well-being of medical students undergoing online medical education during COVID-19 pandemic and their perspective on online pharmacology classes. Description: We implemented several measures like formative assessments, quiz competitions, zoom polls, student chosen revision topics, student presentations, pharmaco-mnemonic competition, etc. WHO-5 Well-Being Index was used to assess well-being of students. An internally validated questionnaire was used to assess student's perspective on online pharmacology classes. The questionnaire was administered to eligible consenting students online through Google forms. The data obtained was analysed in SPSS software. Outcome: The mean wellness score (percentage) for all participants (n=118) was 48.87%. The mean wellness score for males (58.67%) was higher than for females (42.41%). The average score for overall benefit of conducting online pharmacology classes was 3.32 out of 5. Objectively assessed online interactions like formative assessment, polls and quiz were rated higher than subjective interactions like debate. Conclusion: COVID-19 pandemic has caused massive disruption in the life of many people. In our study, we report a decreased well-being score in medical students attending virtual classes. The findings on well-being of students have implications on planning redressal mechanism in such extreme situations. Our analysis of student's perspective about online interactions has implications beyond online classes. Some of the interactions can be instituted into regular curriculum increasing the student's participation.
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Objectives: An increased risk of thrombotic or cerebrovascular complications has been documented in patients with acute COVID-19. It is not yet known if an increased risk of stroke is true for patients in long-term recovery from severe hospitalised COVID-19. This systematic literature review (SLR) aimed to assess the onset of cerebrovascular events (including stroke) in patients with post-COVID-19 syndrome ≥4 weeks following hospitalisation for severe COVID-19 infection. Methods: Embase, MEDLINE and Cochrane were searched from January 2020 to June 2021 to identify relevant clinical studies reporting the incidence of post-discharge cerebrovascular events following a severe COVID-19 infection. Supplementary sources including conferences, reference lists and key organisation websites were scanned. The SLR was conducted in accordance with the PRISMA and Cochrane guidelines. Results: A total of four studies were included from 3,789 identified articles. Two studies were conducted in the USA, one in Ukraine and one in Iran. Three studies had a short follow-up period and were conducted between February 2020 to May 2020;while one study reported data up to January 2021. Post-discharge timepoints ranged from 30 to 90 days. The incidence of stroke varied across the studies, ranging from 0.45% to 11.5%. Unsurprisingly, the study with the longest follow-up period reported the highest incidence of cerebrovascular events. Considering that limited data is available till date for patients with post-COVID-19 syndrome, newly published findings (via hand searching) from ongoing studies may be further included to minimise the paucity of evidence currently available. Conclusions: Despite the large number of peer-reviewed articles associated with the COVID-19 pandemic, there is limited published evidence demonstrating the incidence of stroke in patients who have recovered from severe COVID-19. Several studies are ongoing, and much-needed evidence is awaited from longitudinal studies that may document the risk of stroke in patients with post-COVID-19 syndrome.
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In this time of COVID-19 crisis, the threat posed by the propagation of misinformation leading to mistrust needs to be kept in check. Misinformation related to the vaccines, remedies, false symptoms, etc. are spiraling out of control. We might not be able to directly put a stop to the flow or spread of fake news to a large extent at the moment, but it may be able to identify it as such with the help of Natural Language Processing (NLP) tools and Deep Learning (DL) algorithms. Steps involved in achieving this goal can be narrowed down into collection and analysis of data from various sources, sorting out the articles as covid-relevant and categorizing them as real or fake using DL models. However, DL models use different optimizers in the learning process, which plays an important role in identifying the fake news. This chapter also compares the efficiency of different optimizers in the context of COVID-19 fake news detection using DL models. The newly developed Continuous Coin Betting (CoCoB) Optimizer for DL studied extensively for fake news detection and performed compared with four other widely used optimizers. The comparative analysis shows the CoCoB as well as popularly used Adam optimizers are quite effective in finding optimal classification results for detection of fake news related to COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: The COVID-19 pandemic has been declared a virulent epidemic by many around the world as it has caused a state of lockdown in most parts of the globe, which besets a great economic impact on the world economy. In lieu of this crisis, it is important to comprehend and estimate the total loss in order to perform crisis management and mitigate the decimation of economy. Objectives: This study aims to estimate the impact from the perspective of the Indian economy, with special emphasis on the service sector. Since the service sector forms the most colossus and cardinal part of the Indian economy, this research estimates the potential decline in the GDP and employment contributions of the service sector and its various subsectors. Methods: It implements contemporary regression models to fulfill the mentioned objective by analyzing how the potential decline, as predicted by the IMF, in gross domestic product (GDP) will affect the service sectors and its various subsectors. This is accomplished in four stages: (1) data selection and comprehension of the features dataset for each subsector, (2) understanding the co-dependency of various features, (3) using regression techniques to predict values, and (4) error calculation and results. Additionally, it also presents an elaborated and comprehensive explanation of the same, thereby suggesting some potential solutions to ameliorate the decline. Results: This research is a compendium of the aftereffects that the Indian economy will face post-COVID-19 breakdown. 1.The travel and tourism subsector faces a steep drop of 20.702%, while its employment contribution declines by 59.052%.2.Finance, real estate and business services sector’s contribution to GDP will see a gigantic drop of 20% in the first quarter, which will step down to 88.65% toward the last quarter of the coming economic year, while the sector’s contribution to employment will see an enormous decline of 98.96%.3.The contribution of trade, transportation, and communication undergoes a vast drop of 92.007% toward its GDP contribution, while its employment contribution has a hefty decline of 63.555%. Conclusion: This study explicitly evaluates and elaborates the economic perspective of the aftereffects of the pandemic across each of the major subsector category of the service sector of India for the fiscal year 2020–2021. It studies successfully and maps the impact of the pandemic on the Indian economy, thereby paving way to identify the solutions to mitigate the same. It also provides a set of preventive measures to address the issues identified. In future work, this study attempts to explore the social economic effects of the same in the post-COVID-19 world. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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INTRODUCTION: The Coronavirus (COVID-19) pandemic has impacted the economy and has resulted in changes to the working arrangements of employees who are based at home and may continue to work from home (WFH). Organizations are expected to develop an inclusive policy for their employees to promote mental health whilst working from home. The aim of this study was to document the impact of WFH on mental health and determine the expectations of employees from their organizations regarding occupational health policy. METHODOLOGY: A cross-sectional study was conducted on the impact of work from home on mental health and to document the mental health support needs of employees. Google form was floated through social media platform to receive the responses. A total of 74 responses were received. Descriptive analysis was conducted using Microsoft Excel, while qualitative answers were manually analysed. RESULTS: About 67% employees (n=45) mentioned that their workload has increased significantly during work from home. Thirty five percent (n=26) felt lonely and lost and 47% (n= 34) felt disconnected from the real world, indicating the mental health impact of work from home. Fifty three percent employees (n=40) mentioned that there were no efforts made by their organization to reduce the mental health impact of work from home. CONCLUSION: The results of this study indicate that there is an urgent need to create a comprehensive occupational health and safety policy inclusive of strategies to improve mental health by the organizations in light of "work from home" as a "new-normal". © The Author(s), 2021.
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The rapid spread of the coronavirus disease 2019 (COVID-19) epidemic poses a threat to human civilization. This infectious outbreak induced a global menace, resulting in day-to-day community and social services standstill. Countries like China and Italy are positioned at an alarming stage of this pandemic, and India is also testifying a rapid outbreak of the COVID-19.This unprecedented scenario warrants the formulation of a robust mechanism to estimate the misfortunes of this pandemic in these three countries to assist governments in countermeasuring the COVID-19 catastrophe. In the light of fast varying fatality data rendered by the World Health Organization (WHO), a spectrum of case-based fatality assessments for the COVID-19 is presented that differs considerably in measurements. This publication elucidates the scope of the curve-fitting methods in terms of the goodness-of-fit statistics and support vector machine-based regression (SVR) in estimating the misfortunes of COVID-19 in China, Italy, and India in a given time frame. Consequently, we achieved a reasonably small root mean squared error (RMSE) for the SVR method in predicting the adversities induced by this global pandemic in China and India. In contrast, conventional regression offers a better estimate to sketch the outbreak pattern in Italy. © 2022, Springer Nature Switzerland AG.