Organic Electrochemical Transistors functionalized with Protein Minibinders for Sensitive and Specific Detection of SARS-CoV-2

There is a need for rapid, sensitive, specific, and low-cost virus sensors. Recent work has demonstrated that organic electrochemical transistors (OECTs) can detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Here, a simple and low-cost approach to the fabrication of OECT devices with excellent stability and unprecedented sensitivity and specificity for the detection of SARS-CoV-2 virus is demonstrated. The devices rely on the engineered protein minibinder LCB1, which binds strongly to SARS-CoV-2. The resulting devices exhibit excellent sensitivity for the detection of SARS-CoV-2 virus and SARS-CoV-2 spike protein receptor binding domain (RBD). These results demonstrate a simple, effective, and low-cost biomolecular sensor applicable to the real-time detection of SARS-CoV-2 virus and a general strategy for OECT device design that can be applied for the detection of other pathogenic viruses.

Analysing Shifts in Perceptions of Indians during COVID-19 Pandemic by Mining Tweets

Current pandemic situation has a significant impact affecting human life not only socially and economically, but emotionally and psychologically as well. This impact can be easily observed on social media platforms. Along with the knowledge exchange related to Covid-19 pandemic on social media, there is an emotional trauma wave that can be felt by carefully analyzing the activities of this social media. Keeping this view in thought, we analyze around 12000 tweets of Indian people to find out whether there is a trend shift of thinking pattern and mindset of Indian people as the pandemic progresses. The study is bifurcated into stages to clearly see the paradigm shift. We use tweets since twitter is a rich medium that can be leveraged to its optimum to have a good amount of understanding of the sentiments of the people. Analyzing the twitter dataset, we derive results and find out whether the amount of negative tweets v/s positive (or motivational) tweets have increased or not as the pandemic progresses. The study is supported by graphical visualizations of the polarity of the tweets month wise. Further, Wordmap approach is used to perform qualitative mining analysis in addition to the sentiment score based calculation. This work helps us to understand how the public opinions are changing with the changes in the spread dynamics of the virus. This kind of mood mining helps in identifying the Covid-19 situation from the psychological perspective that whether there is a sense of fear among people or they are quite optimistic of the situation. It can help in a great extend to the strategic and decision making bodies to plan out for future decisions. Further, such kind of studies can be used as reference to provide insights about mental health of people for any future incident or event of such nature. © 2023 IEEE.

Blockchain in Healthcare: A Review

Since Bitcoin introduced the blockchain, research has been conducted to expand its use cases beyond finance. One sector where blockchain is anticipated to have a big influence is healthcare. Researchers and practitioners in health informatics constantly struggle to keep up with the advancement of this field's young but quickly expanding body of research. This chapter provides a thorough review of studies carried out to demonstrate the benefits of blockchain technology that have been utilized in the domain of healthcare, in addition to the pandemic, COVID-19, which led to a massive and pervasive repercussion on healthcare and has significantly accelerated the implementation of digital technology. This chapter also depicts how researchers have presented the use cases for adopting Blockchain technology in the healthcare sector. The state-of-the-art blockchain application development for healthcare has also been described in this chapter, along with any inadequacies and potential future study topics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Virtual Hands: Real Time Keyboard, Desktop & Application Navigation using Gestures

In computer system keyboard is the most prominent input medium of all time. But lately, human community is living in an era of global pandemic being afraid of suffering from Coronavirus (Covid-19) and hence each and every person avoids touching anything. This is because of the fear of contracting this contagious virus and their mutants. So, to mitigate this issue, we present a method "webcam based virtual keyboard interface"to interact with a computer system. The code of this method is written using pre-built modules like OpenCV, MediaPipe, PyVDA, Win32API, etc. and Python 3.9. This approach uses matching the index finger and middle finger on the specific key. After that the virtual desktop switching mechanism is done by PyVDA. The PyttSX3 library plays the sound whenever any key is pressed or when a desktop switch is initiated, corresponding to the key pressed or the desktop switched. In this approach no additional hardware device other than the webcam, that is already available in the system, is required. This approach is also useful for those persons who wants the access the system, even when their hands are dirty. © 2022 IEEE.

Advance Eye wear with warm white LEDs: A Preventive Approach Against Asthenopia in Post-covid Era

"Eyes are windows to the soul" - we can smell a rose but cannot see the immense beauty of it without eyes. Dramatic increase in asthenopic symptoms in the students and workers caused by electricity outage is common ocular problem in the rural areas of India. Moreover, Computer vision syndrome (CVS) has extended their deteriorative arms worldwide in post-COVID era due to increased screentime by extensive use of digital gadgets. Blue light released from digital gadgets causes macular degeneration through various factors including oxidative stress. Thus, there is a dire need of mitigative measures against CVS and electricity outage mediated asthenopic symptoms. The aim of the present study was to develop a preventive measure against asthenopia induced mental and ocular disorder. A spectacle frame having blue light blocking glasses along with strip of warm white LED was taken. The hollow temples of spectacles had a wire which was connected to LED strip on one end and another end was connected with neck band having rechargeable battery and intensity regulator feature. A prototype of advance eyewear was developed and patent was published (IPR Application no. 202211006479). Product of this prototype will be developed and commercialized through optical agencies (under discussion with Lenskart & Royal son). First 1 00 samples of the product will be distributed to the students of rural areas under community services. Therefore, it's most plausible applications may be Used as a preventive approach against asthenopia caused by electricity outage and CVS.Useful for the professionals working in dark areas (mechanic, Plumber, Electrician etc).

Semantic analysis of blockchain intelligence with proposed agenda for future issues

Integrating blockchain technology with artificial intelligence (AI) i.e., blockchain Intelligence makes an extremely powerful tool that solves many multidimensional problems in several domains. Blockchain technology has the potential to provide links to shared data, transactions, and records in a decentralized, safe, and reliable manner, including the information and decision-making capability of AI which makes machines similar as capable as humans. This study is intended to present an updated systematic review of the integration of Blockchain and AI in various application areas. We have studied and summarized more than 100 research papers to present an updated version of the review. We also discuss the future of Blockchain technologies with AI. By integrating these two technologies results increases the security, efficiency, and productivity of the applications. Past works feature a few possible advantages of integration of Blockchain and AI, yet just give a restricted hypothetical system to depict forthcoming certifiable combination instances of the two advances. We survey and orchestrate surviving exploration on the integration of AI and Blockchain are other ways around to thoroughly build up a future research plan on the fusion of the two innovations. We also proposed an agenda to develop a secure system of cyber threat intelligence information exchange by using features of blockchain and artificial intelligence. This paper mainly focusses on explaining how collaboration of blockchain and AI gives immense boost in latest domains like Cybersecurity, Healthcare, Supply Chain Management, Finance and Banking and Social Media Analytics. © 2023, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

Global perspective of cardiac rehabilitation in Post COVID patients

The long-standing style of care known as cardiac rehabilitation (CR) may have been created to lessen the significant burden of cardiovascular diseases (CVD) on people all over the world. In Post COVID era, maintenance of cardiac health in COVID affected patients has been received much attention. Cardiac rehabilitation (CR) may be a sophisticated intervention with multiple components which can provide support in developing health cardiovascular system. The calibre of CR services can vary greatly and have an impact on the extent of patient benefit. The research has demonstrated that cardiac rehabilitation improves quality of life and reduces clinical psychological distress (DSM sadness and anxiety) (QoL). Subclinical discomfort and psychological well-being also demonstrated pertinent clinical implications in cardiac situations. Cardiac rehabilitation could also be an economical. According to studies, the benefits of CR are effective for patients with a variety of cardiac conditions, such as those who have undergone myocardial infarction (MI), coronary artery bypass surgery, stable angina, stable chronic heart failure, heart valve replacement, percutaneous coronary treatments, heart transplantation, cardiac arrhythmias, or severe arterial hypertension. As CR, and in several contexts "pre-habilitation," are in increased demand, a chronic disability management programme is being given more commonly in home and community settings. As a result of the COVID-19 pandemic's new requirements, the employment of distant, personalised solutions within this delivery paradigm is currently changing.

Podocytopathy After COVID-19 Vaccine Administration in a Patient With Autosomal Dominant Polycystic Kidney Disease

Introduction: Development of vaccines against SARS-COV-2 has resulted in considerable reduction in severe complications and mortality. Several cases of glomerular disease have been recently reported such as Minimal Change disease and Focal Segmental Glomerulosclerosis. We describe a patient with autosomal dominant polycystic kidney disease (ADPKD) who developed nephrotic syndrome, soon after receiving COVID-19 vaccine. Case Description: 40-year-old male with history of chronic kidney disease stage-3 due to ADPKD diagnosed 20 years ago. Baseline serum creatinine 2 - 2.5 mg/dl and minimal proteinuria. Other comorbidities include well-controlled type 2 diabetes mellitus and hypertension. Received two doses of Covid-19 vaccine on February 25 and March 24, 2021. He had malaise, myalgia, and fatigue after vaccination. On April 2021, was noted to have 3+ protein on dipstick, no quantification done. In May of 2021 patient presented to hospital with heart failure and ejection fraction of 39% in association with acute coronary syndrome due to ST elevation myocardial infarction, underwent placement of a drug-eluting stent and placement on dual antiplatelet therapy (DAPT). He had 3+ protein on dipstick. In June 2021 developed abdominal pain with hematuria which was attributed to cyst-hemorrhage, underwent decortication of left renal cyst. However, the patient continued having gross hematuria requiring multiple blood transfusions and cessation of DAPT. Patient was admitted to UTSW in September 2021 and was noted to have nephrotic syndrome with proteinuria of 3925 mg, low serum albumin of 2.0 g/ dL and pedal edema concerning for podocytopathy associated with COVID-19 vaccine. Kidney biopsy was deferred due to active bleeding. Patient was empirically started on Prednisone 60mg with rapid taper. At discharge 12 days later, proteinuria was down to 0.6 g/g of creatinine, serum albumin 3.2 g/dL and hematuria resolved. On his last follow up, proteinuria was 0.3 g/g, serum albumin 3.6 g/dL and serum creatinine 2.67 mg/dl. Discussion(s): Millions of mRNA vaccines have been administered since the developement of the COVID-19 vaccine. Proposed mechanisms when mounting a response to the vaccine are toll-like receptors promoting podocyte damage in the glomeuruli. These glomerulpathies once noted have been treated with immunosupression and there has been remission reported.

Oxi-Inflammatory Stress and Biomolecular Deterioration: A Mysterious Convergence in Post COVID Patients

Background: Despite several scientific efforts against COVID 19, conundrum of biomolecular deterioration in Post COVID syndrome patients are still in dark at an unprecedented scale globally and affected the patient's health multidimensionally. It is conceivable that patients recovered from COVID-19 after second wave are at enhanced risk of secondary complications.Aim: The present study was carried out to estimate the serum vitamin D and total antioxidant activity (TAC) along with markers of oxi-inflammatory stress in post COVID patients diagnosed RT-PCR negative after second wave of COVID-19 and to determine their role in predicting secondary complications.Methodology: 50 subjects (30-55 years) of Delhi-NCR region were recruited and categorized into two groups (n=25 in each group;on the basis of their history of COVID infection). By using standard methods, study group parameters were estimated in Post COVID patients and statistically compared it with that of 25 non affected healthy controls by using student's t-test.Result: Serum CRP, TNF-alpha, MDA and uric acid levels were significantly high (p<0.05) in Post COVID patients as compared to healthy controls. Conversely, serum vitamin D and TAC levels along with SOD activities were found to be significantly low (P<0.001) in Post COVID patients as compared healthy controls. However, ceruloplasmin level was altered insignificantly (p<0.1) with respect to Group I subjects. Vitamin D levels were positively correlated with TAC and SOD activity (P<0.001) and negatively correlated with MDA, CRP, TNF-alpha and uric acid levels in post COVID patients.Conclusion: Therefore, the present study emphasizes the dire need of special attention to Post COVID population by providing vitamin D supplementation, antioxidant and mineral rich diet along with adoption of regular aerobic exercise not only to rejuvenate the biomolecular homeostasis but also to reduce oxi-inflammatory stress mediated future complications.

Ensemble method for multiclassification of COVID-19 virus using spatial and frequency domain features over X-ray images

In early 2020, WHO declared COVID-19, a pandemic disease, which severely infected human inhabitant and health. Researchers, doctors, etc., are finding ways to combat the disease. RT-PCR testing is the initial type of testing that was used to detect whether a patient is COVID (+) or COVID (−).This test kit is costly and the result takes around 6hours. So testing a heavy chunk of the population with RT-PCR is a difficult task. To counter this, X-rays/CT scan-based testing can be used to detect COVID (+) cases to control its spread. X-rays are preferable to CT as they are cheaper and even produce low radiations. The second issue that was noticed during this pandemic period was the availability of doctors. To resolve this issue, a robust automated system for early prediction is essential. Automated systems using machine learning (ML), deep learning (DL) approaches are giving promising results in the detection of COVID (+) cases. In this chapter, we propose a framework for automatic recognition of COVID (+), normal, and pneumonia cases (i.e., multiclassification) over X-ray images. In the proposed method, a dataset of COVID (+), normal, and pneumonia images is used. Initially, the dataset is preprocessed, followed by feature extraction using gray level cooccurrence matrix (GLCM), gray level difference method (GLDM), wavelet transform (WT), and fast Fourier transform (FFT) methods. Features extracted are concatenated to construct a feature pool and these features are used for multiclassification using ML algorithms: support vector machines (SVM) and XG Boost. XG Boost performs better than SVM. © 2022 Elsevier Inc. All rights reserved.

Exploring Covid-19 Second Wave Dynamics Using SIR Epidemic Model

This chapter illustrates the SIR model-based exploration of the second wave dynamics of Covid-19 for the same selected regions of India. The chapter explains the model-based variability in the growth trend, lockdown impact, vaccination, herd immunity, etc. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Result Analysis of SIR-Based Covid-19 Model

After collecting insights from Chap. 4, several facets of Covid-19 modelling have been explored in this chapter. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

SIR Model-Based Experimental Investigations over Covid-19

In this chapter, simulations of real data have been conducted using the SIR model. The chapter also investigates the effect of lockdown for the four prominently Covid-19 hit areas of India. Afterwards, the estimated fraction of the population that will get infected is determined. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Understanding and Analysing the Spread Pattern of Covid-19

The chapter here defines the exponential trajectory of the growth dynamics of the disease. From infection growth trend to recovery and casualty growth rate, all follow an exponential rise with respect to time. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Introduction

According to WHO [2], the novel Coronavirus (Covid-19) epidemic began in Wuhan, China, on the 2nd of January, 2020, and was declared a Public Health Emergency of International Concern (PHEIC) on the 30th of January, 2020. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Effect of COVID-19 Infection on Menstruation: A Retrospective Study

Background: The global coronavirus disease-2019 (COVID-19) pandemic has infected a large subset of women in the reproductive age-group, but the effect of COVID-19 infection on menstruation is still unclear. This study outlines the influence of COVID-19 infection on the menstrual cycle. Methods: Women in the reproductive age-group, admitted with COVID-19 infection were followed up with a structured telephonic interview. Women with previously regular menstrual cycles were included in the study. The questions included severity of COVID-19 infection, details of menstrual cycle before and after the infection, and COVID-related stress recorded by Perceived Stress Scale-10. Results: Data from 350 women with COVID-19 infection were presented. Moreover, 59.1% (n = 207) of women reported a change in their menstrual cycles. About 43.7% (n = 153) noted changes in the volume of flow with 78.4% (n = 120/153) experiencing less flow. Irregular menstrual cycles were reported by 37.1% (n = 130) women, 50.8% (n = 66/130), experienced infrequent menstruation, with delay varying from 45 to 90 days, and 13.8% (n = 18/130) of these women also experienced intermenstrual spotting. Most of these women recovered, and only 17.1% continue to have irregular menstrual cycles even after 1 year of COVID infection. Moreover, 34.28% (n = 120) reported worsening of premenstrual symptoms, and 22.44% (n = 55) reported worsening of dysmenorrhea after the COVID-19 infection. The stress score was not significantly associated with the severity of COVID-19 infection (p >0.05). Social factors like concern about health of other family members, quarantine, and isolation were the biggest contributors to stress. Conclusion: COVID-19 infection and associated stress can influence normal menstruation. Clinical significance: The findings of this study outline the short-and long-term effects of COVID-19 infection on menstruation. This information can be used to reassure the patients and will be helpful in counseling to allay their fears related to altered menstrual cycles after the COVID-19 infection.

Seroconversion in COVID-19: A tool for risk assessment in frontline COVID warriors

Objectives : To analyse the seroconversion rate of COVID-19 antibody and its association with risk of future infection in frontline COVID warriors. Methodology: Longitudinal cohort study conducted in 218 frontline COVID warriors. Baseline anti-spike IgG antibodies estimated and followed up for RT-PCR positive infection. Seropositive subjects were followed up with serial titres at 4 visits upto 6 months. Statistical analysis: SPSS ver. 22.0 used employing chi-square test for association of seropositivity with RT-PCR outcome. Antibody kinetics was calculated using a mathematical linear regression model. Incidence rate was calculated per 10000 person years at risk and relative risk was calculated. Results: IgG positivity was seen in 93.8% subjects who had COVID infection in past 30 days. Significantly higher incidence of infection was observed in seronegative subjects who were at 10 times higher risk of infection than seropositive cases (p<0.001). A sharp rise in infectivity was seen in August 2020 which declined after 2 months. Antibody titres peaked during 1.5-3months followed by steep decline till 4th-5th month and gradual decline till 6 months. Only 2 asymptomatic cases turned seronegative by the end of study. Conclusion: Analysis of natural antibody response postulated a persistence of antibodies till 6 months post RT PCR confirmed infection. The seronegative subjects were 10 times more prone to COVID infection due to lack of innate immunity.

Dynamics of anti SARS CoV2 IGG antibody response in health care workers: A prospective cohort study from India

Objectives: To analyse COVID-19 antibody response, duration of protection, half-life kinetics and its association with disease severity in health care workers (HCW's). Methodology: Prospective cohort study conducted in 230 HCW's of a 1250-bedded tertiary care hospital in India. Baseline IgG antibodies estimated and followed up for RT-PCR positive infection. Seropositive HCWs were followed up with serial titres every 45 days uptil 6 months. Statistical analysis: SPSS ver. 22.0 used employing chi-square test for association of seropositivity with PCR outcome. Assuming log-normal distribution of antibody-titres, half-life estimated using linear regression model. Adjusted risk ratio was computed for incidence rate in baseline seronegative versus seropositive cases. Results: Seroconversion rate was 93.8% in seropositive HCWs at 30 days post infection. Incidence rate of infection was 12.96 (in seronegatives) and 1.29 (in seropositives) per 10,000 person days. Adjusted risk ratio was 8.12 (95% CI 1.068 61.755, p<0.001). Incidence of future infection was inversely associated with baseline seropositivity (p=0.018) with spike in infectivity seen during Aug-Sep 2020 and again in Nov.2020. A peak in mean titres seen at 46-90 day follow-up followed by steep decline till 135 days and gradual waning till 180 days. Median half-life was 125 days (62-155 days). 95.7% seropositive cases sustained seropositivity till the end of study and only 2 asymptomatic ones demonstrated complete seroreversion. Conclusion: Dynamics of humoral immune response revealed an 8-times higher risk of infection in seronegative HCW's. Anti SARS CoV2 IgG antibodies persist for at least 6 months post-infection, offering significant protective immunity against reinfection.

Role of Epigenetics in Developing Therapeutic Strategies against COVID-19

Epigenetics showcases an interconnection between genes and the environment. The expression or repression of genes can result from epigenetic regulatory mechanisms like Deoxyribonucleic Acid (DNA) methylation, histone modifications and chromatin remodelling. The Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) regulates host epigenetic machineries to mutate itself, improve its replication and increase its persistence by alienating the host's antigen-presenting molecules and modulating interferons expressing genes. The previous outbreak of Middle East Respiratory Syndrome Corona Virus (MERS-CoV) reveals that DNA methylation by the virus plays a crucial role in the loss of antigen-presenting molecules in the host. Since these coronaviruses share an ancestorial link, it is believed that the new coronavirus acts similarly. Recent reports of increasing morbidity, mortality and persistence of COVID-19 points to the rapid mutation and evading of immunity of the host. Vaccines, although they have helped to prevent the pandemic but their action remains questionable with new developing variants. We explore the possibility of developing epigenetic-based drugs and vaccines and other immune modulators that are being investigated to end the present COVID-19 pandemic and open new avenues for any such pandemics in the future. Comprehensive review regarding COVID-19 was obtained from PubMed and other search engines. Insights about the COVID-19 vaccines were reported from scientific sources. Epigenetics is a crucial subject to explore for the development of therapeutic strategies against the COVID-19 virus. Epigenetic modulators that can be re-programmed to counter the replication and infection efficiency of this virus and medications, including transcription suppressors, nucleoside inhibitors, can be one of the new strategies which may have a better outcome.