A radiomics-based model for the outcome prediction in COVID-19 positive patients through deep learning with both longitudinal chest x-ray and chest computed tomography images

The coronavirus disease 2019 (COVID-19) pandemic had a major impact on global health and was associated with millions of deaths worldwide. During the pandemic, imaging characteristics of chest X-ray (CXR) and chest computed tomography (CT) played an important role in the screening, diagnosis and monitoring the disease progression. Various studies suggested that quantitative image analysis methods including artificial intelligence and radiomics can greatly boost the value of imaging in the management of COVID-19. However, few studies have explored the use of longitudinal multi-modal medical images with varying visit intervals for outcome prediction in COVID-19 patients. This study aims to explore the potential of longitudinal multimodal radiomics in predicting the outcome of COVID-19 patients by integrating both CXR and CT images with variable visit intervals through deep learning. 2274 patients who underwent CXR and/or CT scans during disease progression were selected for this study. Of these, 946 patients were treated at the University of Pennsylvania Health System (UPHS) and the remaining 1328 patients were acquired at Stony Brook University (SBU) and curated by the Medical Imaging and Data Resource Center (MIDRC). 532 radiomic features were extracted with the Cancer Imaging Phenomics Toolkit (CaPTk) from the lung regions in CXR and CT images at all visits. We employed two commonly used deep learning algorithms to analyze the longitudinal multimodal features, and evaluated the prediction results based on the area under the receiver operating characteristic curve (AUC). Our models achieved testing AUC scores of 0.816 and 0.836, respectively, for the prediction of mortality. © 2023 SPIE.

Evolution and trends in entrepreneurial finance: reflections and insights from COVID-19

Entrepreneurship contributes substantially to the modernization and commercial development of an economy. Access to financial resources is key to the successful operation of new ventures which is arrested by COVID-19. Therefore, the present study aims to address the architecture of entrepreneurial finance since the inception of COVID-19. The research adopts a Systematic literature review approach to study the 127 articles chosen for analysis. The findings reveal the usage of novel sources of finance such as crowdfunding, and Initial Coin Offerings during COVID-19. Apart from this, the research also encapsulates the contributions of the articles on venture capital, P2P lending, and angel finance. Also, the study highlights promising avenues for future research focusing on different financing options and drivers of financing choices. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Impacts of COVID-19 on Public Health in Urban Slums in India and Lessons for the Future

This paper examines the impact of the pandemic on India's public health system of the country, especially from the perspective of urban slumdwellers. Drawing on a qualitative study carried out by the Urban Health Resource Centre in selected slums in Indore and Agra, the paper reflects the impact of the pandemic on the provision of essential health services such as maternal and child healthcare, family planning, immunization for children and the detection and treatment of non-COVID ailments such as tuberculosis. The authors argue that the veritable collapse of healthcare to the most vulnerable sections of the population exposed the structural weaknesses of India's healthcare system. To build a more robust public health system in India to tackle future crises of this kind, the authors call for strengthening the health infrastructure in small to medium-sized cities and reinforcing other crucial determinants of well-being such as food security, livelihood opportunities and support and enhanced education opportunities. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Recurrent Liver Abscess in a Non-Toxic Patient

Introduction: Liver abscesses are caused by direct spread from peritonitis, biliary tract infection or via hematogenous seeding from a distant source. Most are polymicrobial, however Escherichia coli and Klebsiella pneumoniae are the most common offending pathogens. Patients usually present with pain, fever, and clinical signs of infection. We describe a case of spontaneous liver abscess in a non-toxic patient that recurred 10 years after a previous abscess. Case Description/Methods: A 73-year-old-man with a history of type 2 diabetes mellitus, hypertension, CAD status post CABG and PCI 3 years ago, and abdominal aortic aneurysm status post endovascular aneurysm repair presented with 2 weeks of dark urine. After receiving his COVID-19 booster and influenza vaccinations, he developed flu-like symptoms with a self-resolving fever of 101.8degreeF. He had dark amber urine without dysuria or hematuria. Later, he experienced generalized weakness and decreased oral intake. Outpatient labs showed elevated liver function tests, and he was told to present to the ED. On arrival, he was afebrile with stable vitals. Physical exam was unremarkable. Laboratory evaluation showed a hemoglobin of 11.7 g/dL, sodium of 133 mEq/L, creatinine of 1.4 mg/dL, aspartate aminotransferase of 117 U/L, alanine aminotransferase of 212 U/L, alkaline phosphatase of 825 U/L, total bilirubin of 4.1 mg/dL, and direct bilirubin of 2.1 mg/dL. Triple-phase CT showed a 2.8 cm mass in the right liver lobe with linear enhancement. Ultrasound showed mixed echogenicity measuring 3.6 x 2.9 x 3.3 cm in segment 8 of the liver. On further evaluation, patient had an E. coli abscess diagnosed 10 years prior, managed with antibiotics and drainage. At that time, the abscess was within the right inferior liver lobe, similar to his current abscess. LFTs downtrended. Abscess was aspirated, with culture growing oxidase negative, gramnegative rods, likely E. coli. Patient started on ceftriaxone and metronidazole, to undergo colonoscopy as an outpatient and rule out colonic bacterial translocation. Discussion(s): Pyogenic liver abscess can result in significant morbidity and mortality because of worsening infection and sepsis. Abscesses occur because of spread from adjacent infection or after recent surgeries. Recurrence is very rare. Here, we describe a very unusual case of a pyogenic liver abscess growing E. coli in a non-toxic patient, with the same location and causative organism as an abscess managed 10 years prior. (Figure Presented).

Quality of Work Life and Medical Teachers? Commitment: A Moderated Mediation Analysis of Fear of Covid-19 and Job Satisfaction

This study is principally the first to test a moderated mediation model of COVID-19 fear and job satisfaction in the Quality of Work Life (QWL)-commitment relationship of medical teachers during the pandemic. The conceptual model draws its theoretical tenet from spillover and conservation of resources theories. Cluster sampling was incorporated from four metropolitan cities in India. A mixed-method research design was administered to 378 medical teachers amidst the pandemic. The partial least squares structural equation modeling (PLS-SEM) results indicate a significant positive association between the constructs. Path analyses have highlighted positive associations between QWL, job satisfaction, and affective commitment to medical institutions. Further, a partial mediation effect of job satisfaction in the QWL-commitment relationship is highlighted, adding a new dimension to past studies. Intriguingly, each of the positive associations between QWL, job satisfaction, and commitment was negated and significantly moderated by the fear of COVID-19 experienced by the medical teaching fraternity. The findings offer practical implications to the stakeholders (Ministry of Health and Family Welfare, Department of Higher Education, Government of India, and State Governments) in enriching the QWL, job satisfaction, and medical teachers' commitment induced by psychological stress, anxiety, role conflict, post-traumatic stress disorder, and fear of COVID-19 in the global pandemic.

Therapeutic Index of Herbal Medicine in Pandemic COVID-19: A Review

The study of this review focus on effective herbal medicine against COVID-19. There have been many such plants on which a lot of research has been done earlier, and these have been very good for health as we know that the current situation of the whole world is very serious with the novel COVID-19 virus epidemic. Hence, people consume a lot of herbal medicine to increase their immunity, such as kadha (brewing), and it is also very effective against this viral infection. If we take brewing in the proper dose, research should be done from clinical trials. We have been taking many medicines since old times and have been doing research on them which is Antiviral and useful in different types of infection caused by bacteria, viruses, microbes, etc. The plant's diversity included their chemical constituents, showing the promise of their therapeutic level against the antiviral activity, without any toxicity with plasma concentration. Many plants show effectively against viral infections that are Flavonoids, Glycosides, polyphenols, alkaloids, etc.. Still, any clinical trials on humans do not prove their proper research on them, but the Chinese system of medicine claimed that Traditional Chinese medicine improves the COVID-19 patient. According to this review, we aim to collate data of plants the various large in the quantity of natural active constituents from individual medicinal plant species that may have potential therapeutic efficacy. The continuing development of novel antiviral drugs needs to isolate and synthesize more new active constituents. © 2021 by the authors.

BERIS: An mBERT-based Emotion Recognition Algorithm from Indian Speech

Emotions, the building blocks of the human intellect, play a vital role in Artificial Intelligence (AI). For a robust AI-based machine, it is important that the machine understands human emotions. COVID-19 has introduced the world to no-touch intelligent systems. With an influx of users, it is critical to create devices that can communicate in a local dialect. A multilingual system is required in countries like India, which has a large population and a diverse range of languages. Given the importance of multilingual emotion recognition, this research introduces BERIS, an Indian language emotion detection system. From the Indian sound recording, BERIS estimates both acoustic and textual characteristics. To extract the textual features, we used Multilingual Bidirectional Encoder Representations from Transformers. For acoustics, BERIS computes the Mel Frequency Cepstral Coefficients and Linear Prediction coefficients, and Pitch. The features extracted are merged in a linear array. Since the dialogues are of varied lengths, the data are normalized to have arrays of equal length. Finally, we split the data into training and validated set to construct a predictive model. The model can predict emotions from the new input. On all the datasets presented, quantitative and qualitative evaluations show that the proposed algorithm outperforms state-of-the-art approaches. © 2022 Association for Computing Machinery.

Smart and Portable IoT Drug Dispensing System for Elderly and Disabled Person

The necessity of modern intensive care units (ICU) based on IoT is becoming obvious as a result of the population boom and, most notably, coronavirus disease (COVID-19). The continual monitoring of patients' vital indicators (Blood Pressure, ECG, Heart Rate, Blood Saturation, Body Temperature) is one of the most important aspects of an ICU. Existing improvements in informatics, signal processing, or engineering, which potentially reduce the pressure on ICUs, have yet to be implemented. It's possible due to a lack of user participation in research and development. This manuscript focuses on the improvement of a completely integrated system where the doctors can directly connect to patients through the Smart Portable ICU, and physicians can access the patients. Thus, the crucial boundaries of a patient to the concerned specialist at a far-off position have been resolved simply and helpfully. Thus, the specialist can attend to the patient remotely and infuse lifesaving drugs from the distant area if necessary. © 2022 IEEE.

The SARS-CoV-2 Omicron Variant and its Multiple Sub-lineages: Transmissibility, Vaccine Development, Antiviral Drugs, Monoclonal Antibodies, and Strategies for Infection Control – a Review

The Omicron (B.1.1.529), fifth variant of concern (VOC) of SARS-CoV-2, initially identified following a steep increase in COVID-19 cases in Southern Africa in November 2021. It is a highly-mutated variant and is more contagious as compared with the Delta variant, however less deadly. Due to its high transmission rate, it spreads dramatically, and causing huge surges worldwide. It causes "mild infection”, with hospitalisations less likely to occur. However, this variant is known to show resistance to neutralizing antibodies (nAbs) generated through vaccination and/or prior infection as well as to monoclonal antibodies (mAbs) used to treat COVID-19 patients. In many countries, booster doses of vaccines have been recommended to increase the protective levels of antibodies in vaccinated individuals. Along with the implementation of appropriate prevention and control strategy measures, current efforts are also focussed on the development of better vaccines and mAbs to counter this variant. This review highlights the global health concerns and challenges posed by the Omicron variant and present an update on its sub-lineages. © 2023 Wiley-VCH GmbH.

Impact on Pharmaceutical Industry due to Sudden Pandemic Attack (COVID-19)

The coronavirus disease (COVID-19) was first detected in Wuhan, China, in the month of December 2019. Further, in March 2020, the COVID-19 epidemic was described by the World Health Organisation (WHO) as a global pandemic. COVID-19 quickly spread around the world in the following months, affecting about 2.5 million individuals by April 2020. World markets, including the pharmaceutical industry, were devastated by this pandemic. Although no specific solution for this emerging infectious disease is currently available, the pharmaceutical industry is helping policymakers meet unmet COVID-19 desires, ranging from research and advancement initiatives on possible prevention methods to the management of the supply chain of drugs in times of crisis. Changes in demand, commodity shortages, contact adjustments, etc., are hindering developments in the mechanism of technology, research and development and are putting an impact on the health market of COVID-19. Other implications of COVID-19 on the physical condition and pharmaceutical market may include acceptance delays, heading to self-sufficiency in the delivery chain, etc. In addition, the pharmaceutical markets are battling to sustain natural consumer flows, as the latest pandemic has had an effect on access to essential drugs at reasonable rates, which is the key priori-ty of all pharmaceutical systems.Copyright © 2022 Bentham Science Publishers.

Assessing the feasibility of hyperlocal delivery model as an effective distribution channel

Purpose: The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context. Design/methodology/approach: A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes. Findings: The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology. Originality/value: This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM). © 2023, Emerald Publishing Limited.

The Role of Aquatic Plants in Natural Products and Drug Discovery

Background: Phytochemicals and their derivatives/analogues represent over 50% of the current medicines worldwide in clinical use. Despite a significant contribution to the total bioactive natural plant products, aquatic plants are underestimated, and several species are extinct and in the endangered list. Objective(s): The aim of this review article is to draw the attention of common people and scientists toward a few important contributions of the aquatic plants to natural product chemistry and drug discovery by highlighting the chemical and pharmaceutical aspects of the same. Method(s): The presented data were collected and selected from the literature obtained by an online search for the ethnomedicinal properties, biological activities and bioactive chemical constituents of aquatic plants using Google Scholar, PubMed and Scifinder chemical abstract service. Result(s): The selected literature data revealed that the extract and compounds isolated from several aquatic plants possess significant biological/pharmaceutical properties. For example, the alpha-asarone (24) and asiatic acid (33) isolated from Acorus calamus and Centella asiatica, respectively, exhibited significant neuroprotective effects in vitro and in vivo. The cripowellin A (59), cripowellin C (60), cripowellin B (61) and cripowellin D (62), isolated from Crinum erubescens, exhibited potent antiplasmodial and antiproliferative activities with half maximal inhibitory concentration (IC50) in nanomolar range (11-260 nM). Several other alkaloids from different Crinum species have also shown anticancer properties against different cancer cell lines with IC50 value <5 microM. Alkaloids and resin glycosides, isolated from different Ipomoea species, have displayed significant psychotropic, psychotomimetic, anticancer, and antibacterial activities with IC50 value <5 microM. Conclusion(s): The aquatic plants play a significant role in the discovery of bioactive natural products. Although several biological activities and bioactive compounds have been reported from these plants, further assessment and scientific validation of most of their traditional usages still need to be done. There are several other similar species that are underestimated and not much explored. Many aquatic plants, such as Ipomoea carnea Jacq., Juncus lomatophyllus Spreng., Commelina benghalensis Linn, Gunnera perpensa L., Scirpus maritimus L. and Mentha longifolia (L.) L., may be considered for further evaluation. In addition to these, one should not undermine the potential of Crinum macowanii for COVID-19 pathogenesis, as its chemical constituent lycorine has shown significant SARS-CoV-2 inhibitory potential (EC50, 0.3 muM;SI >129). Furthermore, most rural communities are still using the wetland resources for their cultural, medicinal, economic, domestic, and agricultural needs. Hence, the conservation of aquatic plants and wetlands is an issue of great concern.Copyright © 2023 Bentham Science Publishers.

Interventions to enhance psychosocial competence among children in low-and middle-income countries

The study of the psychosocial development of children in low-and middle-income countries (LMIC) is mapped by the realities of childhood that are embedded and enfolded in conventional family values, the sociocultural ethos, and choices of a combination of environmental factors that result in a variety of childhoods. This chapter begins with the definition and scope of psychosocial development in children, followed by the conceptual framework and approaches included in various interventions. It provides an overview of systematic reviews and meta-analysis of various interventions with a focus on early childhood development, children with developmental disabilities, mental health, and life skills in LMICs. Quality early childhood development programs present an opportunity to drastically reduce early health and educational disadvantages for children in LMICs. The impact of Covid-19 on the development of children is presented. © 2022 John Wiley & Sons Ltd.

Online reviews towards reducing risk

Purpose: This paper aims to examine the impact of online reviews on behavioral intentions via perceived risk. Perceived risk is both analytical and emotional. Stimulus–organism–response (S–O–R) framework guided this study to explore the interaction between online reviews, perceived risk and behavioral intentions. Design/methodology/approach: The conceptual model proposed in this research has been validated using confirmatory factor analysis (CFA) and structural equation modeling to assess the measurement model and the validity of the scale, based on primary responses collected from 473 travelers. Findings: Findings of this study suggest the role of online consumer reviews in reducing the perceived risk associated with experience dominant services like tourism. Process model test proves the mediating role of perceived risk between online reviews and behavioral intentions. Results indicate the significance of online review in lowering the perceived risk leading to positive behavioral intentions. Practical implications: Destination marketing organizations (DMOs) should understand the role of online reviews in effectively reducing risk and uncertainty, thereby influencing behavioral intentions. Originality/value: This paper is unique in attempting to empirically examine the mediating role of perceived risk between online reviews and behavioral intentions. The study is a forerunner in using S–O–R framework to test the interaction between online review, perceived risk and behavioral intention. © 2023, Neha Yadav, Sanjeev Verma and Rekha Chikhalkar.

Severe Covid-19 Associated Hemophagocytic Lymphohistiocytosis : A Comparative Study with Hemophagocytic Lymphohistiocytosis Secondary to Causes Other Than Covid-19

Introduction: Severe COVID-19 infection in a subset of patients is associated with hyperinflammation similar to hemophagocytic lymphohistiocytosis (HLH) however it may not fulfill the required diagnostic criteria (HLH 2004 criteria or H score). We compared clinical, laboratory parameters, bone marrow findings and disease outcome of severe COVID-19 infection related HLH with HLH secondary to causes other than severe COVID-19 to describe features specific to severe COVID-19 associated HLH and limitations of currently available diagnostic criteria of HLH in context to severe COVID -19 infection induced hyperinflammation. Method(s): We analyzed 69 patients diagnosed as HLH of which 47 had severe COVID-19 and 22 had HLH secondary to causes other than COVID-19. Clinical, hematological and biochemical parameters were compared using Mann-Whitney U test. Bone marrow examination (BME) was done in all for presence of hemophagocytosis. Immunohistochemical staining for CD68 and CD163 were done for identification of histiocytes. Occurrence of COVID-19 related HLH was taken as the dependent variable to determine predictors of COVID-19 HLH. Result(s): Organomegaly was seen in only 4.3% (2/47) cases with COVID-19 related HLH as compared to 54.5% (12/22) with non-COVID HLH (p< 0.001). Amongst the quantitative variables, a significant difference in COVID-19 related and non-COVID-19 related HLH was found in the following parameters: Age (p< 0.001), Triglyceride (p=0.009), Fibrinogen (p< 0.001), Ferritin (p< 0.001), Hemoglobin (p< 0.001), Total leukocyte count (p=0.003), Absolute neutrophil count (p< 0.001), Neutrophil lymphocyte ratio (p< 0.001) and H score (p< 0.001). BME of all patients showed presence of hemophagocytes. Only 6.4% (3/47) cases with COVID related HLH had 5/8 HLH 2004 criteria as compared to 63.6% (14/22) cases with non-COVID related HLH (p< 0.001). H-Score >=169 was also significantly less common in COVID HLH as compared to non-COVID HLH (40.42% vs 86.36%, p=0.001). Conclusion(s): Organomegaly, cytopenias, hypofibrinogenemia and hypertriglyceridemia which are part of HLH diagnostic criteria are rare in severe COVID-19 making it difficult to diagnose. Demonstration of hemophagocytes in bone marrow should be recommended in suspicious cases for initiation of early immunosuppressive therapy. (Figure Presented).

Summarization and Simplification of Medical Articles using Natural Language Processing

Health literacy is the ability of a person to read and understand medical text and to use that information to make informed healthcare decisions. Unfortunately, medical articles are difficult to comprehend by common people as they use complex language and domain-specific terms. Improving health literacy is important for empowering communities against emerging threats and the COVID-19 pandemic bears testimony to this statement. One way to improve health literacy is easing access to complex healthcare information by summarising medical texts and simplifying them lexically by translating specific medical terminology to laymen's terms. In this paper we propose a system that performs extractive summarization on the medical article given as input followed by named entity recognition for identifying medical terms. The meanings of identified medical entities are then found through web scraping and displayed to the user along with the summary. We have experimented with state-of-the-art summarization models and Albert (A lite BERT) has provided the best ROUGE-1 score of 0.3789 and ROUGE-L of 0.2084. © 2022 IEEE.

Computational Method on Hydroxychloroquine and Azithromycin for SARS-CoV-2: Binding Affinity Studies

World is facing a new pandemic called covid-19SARS-CoV-2) since a year ago. Unfortunately there is no treatment for Covid 19 nowadays as well as no potential therapies has been developed to overcome from coronavirus pandemic. Some potential drug molecules with combination have ability to respond for covid19 virus. From the research it was found that the reduction of viral load can be treated with hydroxychloroquine and azithromycin combination. We evaluate the mode of interactions of hydroxychloroquine and azithromycin with the dynamic site of SARS-CoV-2 coronavirus main protease. Molecular Structure-based computational approach viz. molecular docking simulations were performed to scale up their affinity and binding fitness of the docked complex of novel SARS-CoV-2 coronavirus protease and hydroxychloroquine and azithromycin. The natural inhibitor N3 of novel SARS-CoV-2 coronavirus protease were exhibited highest affinity in terms of MolDock score (-167.203Kcal/mol), and hydroxychloroquine was found with lowest target affinity (-55.917 Kcal/mol).The amino acid residue cysteine 145 and histidine 41 is bound covalently and formed hydrogen bond interaction with SARS-CoV-2 inhibitor known as inhibitor N3 as such, hydroxychloroquine and azithromycin also formed hydrogen bond interaction. The binding patterns of the inhibitor N3 of SARS-CoV-2 coronavirus main protease could be used as a guideline for medicinal chemist to explore their SARS-CoV-2 inhibitory potential. Copyright © RJPT All right reserved.

COVID-19 and Pneumonia classification Using Ensembling with Transfer Learning

The world has been rapidly devastated by the Covid-19 virus, which first appeared in the Republic of China. For medical imaging, deep learning-based algorithms show promising results for quick and accurate diagnosis. Various research has been done for the earlier diagnosis of the disease using various deep learning models. Researchers use different medical imaging for the classification of COVID-19. This study explores COVID-19 diagnosis using a chest X-Ray. The Chest X-Ray images were classified with the help of transfer learning using VGG16, DenseNet, and MobileNet. To ensure better results Ensemble Learning is incorporated to provide a strong learner by using the aggregation of weak learners. These models are trained on three different classes of patients: COVID-19, Pneumonia, and Normal. The final testing results using ensembling aggregation show an overall accuracy of 95.2%, which is significantly higher than the model performances individually. The result obtained through the proposed model can be used in conjunction with the X-Ray images to classify COVID-19, thus the process can be implemented as an alternative to RT-PCR. © 2022 IEEE.

Blueprint for impedance-based electrochemical biosensors as bioengineered tools in the field of nano-diagnostics

Electrochemical biosensors are analytical devices that hold a current across the surface of an electrode on which biological receptors are immobilized. These devices enable the conversion of physio-biochemical reactions by biological molecules into electron movements, so the output can be observed as the flow of charge across the electrode. These biosensing platforms detect changes in the reactive and resistive properties of the electrode surface when an alternating current (AC) or voltage is applied to output signals. Impedance-based electrochemical biosensors have advantages compared with other biosensors, such as high sensitivity, low cost, and ease of operation. In addition to uses as miniature detection tools, biosensors and microfluidics play vital roles in nano-diagnostics. Many sensors have been developed at the nanoscale by exploiting the greater conductivity across the electrodes and improved specificity for biorecognition element-receptor binding in biosensing devices. Several of these sensors have been assessed in trials and emerged as clinical products for detecting and diagnosing diseases, bacteria, viruses, deficiencies, and biofluid malfunctions in the human body. This review summarizes advances in impedance-based biosensors and their working principles and classifications, as well as providing relevant illustrations by focusing on the essential biorecognition elements, receptors, and target molecules during diagnosis. Copyright © 2022 The Authors

A Detailed Scientometric Review of Coronavirus Research

A deadly novel coronavirus disease or severe acute respiratory syndrome (COVID-19 or SARS-CoV-2) has taken the entire globe in its grip and claimed over more than 0.1 million lives across the globe in barely four months of time. This has attracted researchers, medical practitioners, scientists, biologist's fraternity, etc. all over the world to join hands in fighting the pandemic. Therefore, a detailed study in the field of coronavirus, especially related to the research status and gaps under a common umbrella, will further help in understanding and improving the current scenario. In the present paper, the scientometric analysis technique was utilized for understanding the recent research activities, scientific trends, and global involvement in the research on coronavirus. Herein, Web of Science database was used for searching the documents. The "articles” in the "English” language were considered in the study. The VoSviewer software was used for carrying out the scientometric analysis. The scanning of the research publication status on a year-on-year basis suggested an increase in the field of research on coronavirus in the recent past. From 2000 till 2020, a total of 9257 number of research articles were published. Among all other countries, USA has the most number of documents published. Analysis of the journals, authors, organizations, funding agencies of the countries and their co-operation network were also analyzed based on citations. Further, co-occurrence analysis of the different keywords suggested that coronavirus related diseases are known to precipitate severe acute respiratory syndrome in the patients. This is also true in the case of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.