Revealing Potential Binding Affinity of FDA Approved Therapeutics Targeting Main Protease (3CLpro) in Impairing Novel Coronavirus (SARS-CoV-2) Replication that Causes COVID-19

Background: Spread of COVID-19 attains a crucial transition in reveling its pandemic across the boundaries. In combating the infection caused by SARS-CoV-2, there is a spectrum of ideal strategies that have been adopted globally, of which repurposing of approved drugs considerably having high clinical relevance. 3-chymotrypsin-like protease (3CL pro) is considered to be the potential target for the researchers as it is highly essential for cleavage of polyprotein to get 16 nonstructural proteins (called nsp1-nsp16). These proteins are highly essential for viral replication and hence become a primary target for enzyme inhibitors. 3CL pro, having a structural projectile helical chain with biologically active site involved in processing viral polyproteins that are evolved from RNA genome translation. Objective(s): The major objective of the present investigation is to evaluate the enzyme inhibition potential of FDA approved therapeutic leads in targeting 3CLpro that medicates the viral replication. Method(s): Docking calculations were carried out for an array of FDA approved molecules which leads to a notable few molecules such as Emtricitabine, Oseltamivir, Ganciclovir, Chloroquine, Baricitinib, Favipiravir, Lopinavir, Ritonavir, Remdesivir, Ribavirin, Tenofovir, Umifenovir, Carbapenam, Ertap-enem and Imipenam which have both specificity and selectivity in terms of binding efficiency against 3CL proenzyme. Result(s): A combinatorial evaluation employing in-silico screening shows a major lead for remdesivir which possesses a substantial affinity to 3CL pro binding on core amino acid residues, such as Leu 27, His 41, Gly 143, Cys 145, His 164, Met 165, Glu 166, Pro 168 and His 172 which share the biological significance in mediating enzymatic action. Results of docking simulation by Autodock over a host of FDA approved molecules show high degree of selectivity and specificity in the increasing order of binding capacity;Remdesivir> Ertapenem> Imipenam> Tenofovir> Umifenovir> Chloroquine> Lopinavir> Ritonavir> Emtricitabine> Ganciclovir> Baricitinib> Ribavirin>Oseltamivir>Favipiravir> Carbapenam. Conclusion(s): Till date, there is no known cure attained for treating COVID-19 infection. In conclusion, lead molecules from already approved sources provoke promising potential which grabs the attention of the clinicians in availing potential therapeutic candidate as a drug of choice in the clinical management of COVID-19 time-dependently.Copyright © 2020 Bentham Science Publishers.

P156. Mortality of operative spinal fractures in COVID-19 positive patients using data from a national database

BACKGROUND CONTEXT: The ever-evolving COVID-19 pandemic has presented critical surgical management challenges. Increases in COVID-19 positive patients and subsequently, patients sustaining spinal fractures who test positive for COVID-19, raises the question of whether these individuals are at an increased risk of mortality and subsequent complications. PURPOSE: The purpose of this study was to characterize the cohort of COVID-19-positive patients who required surgery following a spinal fracture and investigate if these patients are at increased risk of all-cause mortality and further complications. STUDY DESIGN/SETTING: Retrospective cohort study of prospectively collected data performed from March 15, 2020 to December 12, 2021 using a national database with clinical data from 56 sites. PATIENT SAMPLE: Patients with a diagnostic test for COVID-19, who sustained spinal fractures and required operative intervention. OUTCOME MEASURES: The primary outcome was all-cause mortality. Additional outcomes included acute kidney injury (AKI), acute respiratory distress syndrome (ARDS), venous thromboembolism (VTE) and sepsis. METHOD(S): A total population of 8.4 million patients was examined using the National COVID Cohort Collaborative (N3C) data enclave. The N3C is a centralized national data resource that compiles data using electronic health care records from over 8 million patients. Inclusion criteria consisted of adults 18 years old or older with a diagnostic test for COVID-19, who sustained spinal fractures and required operative intervention. Patients' information from this database was collected and grouped according to lab-confirmed COVID-19-positive and negative testing which was acquired via the "SARS-CoV-2 RT-PCR and Antigen" test. Those who tested positive for COVID-19 were compared to a control group that was COVID-19-negative using the same standardized PCR and antigen testing methods. RESULT(S): A total of 2,745 patients with operative spinal fractures were identified. A group of 207 (8%) patients tested COVID-19 positive at the time of surgery. At baseline, the groups were comparable in age (57 vs 58 years), gender (41% women in each group), body mass index (28 in each group), cervical spinal cord injury (9.8% vs 8.1%) and length of stay (8 days in each group) (all p>0.05). The COVID-19positive cohort had a higher all-cause mortality than the COVID-19 negative group (14% vs 7%, p<0.001). There were increased odds for AKI [1.62(1.15, 2.26)], ARDS [2.78(2.07, 3.73)], VTE [1.65(1.18, 2.30)], and sepsis [2.58(1.88,3.53)] [Odds Ratio (Lower Limit, Upper Limit)] in patients testing positive for COVID-19. CONCLUSION(S): This national analysis of operative spinal fractures and COVID-19 showed increased mortality and perioperative events (AKI, ARDS, VTE, Sepsis). Further research is needed to investigate potential interventions for testing and management related to COVID-19 in the context of operative spinal fractures. FDA DEVICE/DRUG STATUS: This does not discuss or include any applicable devices or drugs. Copyright © 2022

Digital Payment and Its Growth in the Time of COVID – 19

The Indian payments landscape has undergone a makeover in the recent past with the decision to demonetise leading to a shortage of physical currency. The current COVID-19 pandemic created a contamination fear while exchanging and using currency. Hence, the customers started adopting digital payments. Research was conducted in this context to investigate the behaviour intentions of the customers regarding digital payment usage through application of the Unified Theory of Acceptance and Use of the Technology-2 (UTAUT2) model. This paper explores the behaviour intentions of using digital payments during the pandemic. A survey questionnaire was designed to collect the required information from 271 respondents through the judgemental sampling technique. The data were analysed using SPSS and AMOS. The results revealed that, among the seven constructs examined, effort expectancy and habit had a positive effect on behaviour intentions. No association was elicited between social influence, facilitating condition and price value on behaviour intentions. The findings also uncovered a moderately significant negative relationship between performance expectancy and hedonic motivation on behaviour intentions. Compared to prior studies, the findings regarding a few constructs from our study were in line with earlier work, whilst others were found to be not so. Also, the timing of the study might have played a role in influencing the results as most of the customers felt it was convenient to use digital payments compared to physical currency during the pandemic © All rights reserved 2021 Transnational Press London

Squamous Cell Carcinoma Surgery During a Global Pandemic – a Single UK Tertiary Centre Experience

Aim To determine excision rates for squamous cell carcinoma (SCC) both before and during the COVID 19 pandemic. Method Between April 2020 to March 2021, a retrospective cohort study of patients undergoing SCC surgery in Cambridge University Hospitals (CUH) was undertaken. Data was collected from the hospital patient record system (EPIC) and included preoperative diagnosis, excision margins, histological subtype, and operative technique. Results 287 primary SCCs were excised during this period. 70% of SCC patients were male, with the commonest site being the head and neck (72%). The rate of incompletely excised SSCs doubled from 5.5% in 2018–19 to 11.3% in 2020–21. Of these, most incomplete excisions were due to inadequate deep margins (9.8%). The majority of incomplete excisions were performed by registrars (14.8%) followed by consultants (9.1%). Conclusions Whilst diagnostic accuracy remains high, we report a decline in complete excision rates. Deferral of non-urgent visits due to the COVID-19 pandemic may have resulted in delayed diagnosis of SCCs, resulting in larger and deeper cancers. The more invasive SCCs may have then resulted in a higher rate of inadequate excision. A potential solution is the use of templates in operative notes, in order to ensure an accurate record of deep and peripheral margins is made.

"Design-Based" Instruction - Teaching Engineering Design in the Context of Practice

This Research-to-Practice Full Paper discusses what "designbased" instruction is and how it can be used to place the teaching of engineering into the context of practice as required by the recent 2019-2020 accreditation criteria. This paper will describe a hands-on design and build project that has been used with great success in a junior level fluid mechanics course for more than 30 years;an iconic project that students look forward to from their freshman year. Far more than just a project, it is an approach to teaching design that permeates the entire course - building expectation, stimulating creativity, and pulling several fluid mechanics principles taught in the course into a single theme through the application of concepts and skills to a particular end product. Students design, build, and test a 1/12 scale model sailboat and use the model tests to predict full-scale prototype performance. They must work within constraints of the material provided for the hull, and as a last step, they must be able to race their models forward over a test course with the wind coming from the side. Over the years, this project has forged an approach to teaching the entire course. A five-step iterative scheme for the design process serves as a framework for design-based instruction, and while this will be illustrated for the fluids project, it can be extended to any engineering course project. Successful design also involves the use of three types of literacy that serve to place the design experience in the context of practice: conceptual literacy (knowledge of theory and concepts), mechanical literacy (knowledge of tools, machines, and components), and cultural literacy (knowledge of how to communicate and how to properly place a design into a social framework). A planning matrix that enables the instructor to plan the mix and balance of the steps of design and types of literacy will be presented in this paper. The matrix can also be used to address the 7 student outcomes in Criterion 3 of the ABET Criteria. This approach was severely tested during the COVID-19 pandemic and subsequent lockdown that required all courses to be delivered remotely;however, the framework and approach to teaching enabled the authors to distill the critical features and to adapt the project and the course approach to the online environment.

Covid-19 Tracker: A data visualization tool for time series data of pandemic in India

Covid-19 first originated in Wuhan, China, became a global pandemic and spread to many countries due to its high transmissibility. Digital technology could prove to be of great use in pandemic management with many strategies like screening for infection, tracking, contact tracing, and many more. Covid-19 tracker is one such application of digital technology. This helps in visualizing the pattern of public health through graphs, search results, and tables that can be easily understood by the user. It is built using HTML and JavaScript. Covid-19 Tracker uses data from certain authentic sources and helps to visualize the spread of Covid-19 throughout India. The main features incorporated in our dashboard are: total cases reported, graphs for daily trends, search functionality, state-wise comparative evaluations, and hotspot distribution map of the entire country. This dashboard provides a variety of user involvement possibilities and extracts useful data in a simple and easy-to-understand way.

On Individualized Online Assessments in STEM Subjects

As traditional paper-based examinations became difficult to conduct during the Covid-19 pandemic, more and more universities sought to look at online alternatives. While online assessments have their advantages, they lend themselves to collusion as well as contract-cheating. This paper proposes individualized questions as a potential solution, and presents an approach for designing and implementing individualized questions for online assessments. This approach is deemed to work particularly well in STEM subjects, and scales to large classes. © 2021 IEEE.

An Expert System for COVID-19 Infection Tracking in Lungs Using Image Processing and Deep Learning Techniques.

The proposed method introduces algorithms for the preprocessing of normal, COVID-19, and pneumonia X-ray lung images which promote the accuracy of classification when compared with raw (unprocessed) X-ray lung images. Preprocessing of an image improves the quality of an image increasing the intersection over union scores in segmentation of lungs from the X-ray images. The authors have implemented an efficient preprocessing and classification technique for respiratory disease detection. In this proposed method, the histogram of oriented gradients (HOG) algorithm, Haar transform (Haar), and local binary pattern (LBP) algorithm were applied on lung X-ray images to extract the best features and segment the left lung and right lung. The segmentation of lungs from the X-ray can improve the accuracy of results in COVID-19 detection algorithms or any machine/deep learning techniques. The segmented lungs are validated over intersection over union scores to compare the algorithms. The preprocessed X-ray image results in better accuracy in classification for all three classes (normal/COVID-19/pneumonia) than unprocessed raw images. VGGNet, AlexNet, Resnet, and the proposed deep neural network were implemented for the classification of respiratory diseases. Among these architectures, the proposed deep neural network outperformed the other models with better classification accuracy.

App Based Teleoperated UV Disinfectant Robot for COVID Cause

Disinfecting a closed space is a widely discussed topic since the spread of coronavirus. Different methods like chemicals in liquids and gases are used to eliminate pathogens. But these methods would cause environmental damage, which would become another problem for humanity. We developed a robot which uses ultraviolet-C (UV-C) technology for surface disinfection, particularly room in houses, offices, hospitals etc. UV-C radiation is effective against coronavirus and is extremely effective in breaking down the DNA of microorganisms which means they cannot replicate and cause disease. The teleoperated robot is capable of 360-degree disinfection with three UV-C lamps used. It is controlled using an Android app through Bluetooth wireless interface. Due to wireless control, the operator can safely operate the robot from outside the room. The robot is also equipped with a self-timer for turning off the UV-C lamps automatically. The robot has been deployed in our lab and Amrita Institute of Medical Sciences, Kochi to sanitize the patient's rooms and bathrooms. © 2021 IEEE.

Contamination fear and ABS during COVID-19

Purpose: Access-based services (ABS) have been adversely impacted by the COVID-19 pandemic. This study aims to validate customer barriers to ABS focusing on the contamination barrier. As service employees’ presence violates the COVID-19 physical distancing norms and heightens contamination fear, this paper tests its effects on continued use intentions of ABS. This study also empirically examines the role of conspicuous virtue signaling and organizational response. Design/methodology/approach: The study was conducted in the context of scooter sharing and uses a mixed-method to explore the relatively under-researched problem of contamination fear in ABS. Study one uses the survey method and study two uses a 2 × 2 matrix between-subject design. Findings: The results reveal that perceptions of resource sufficiency positively affect continued use intentions of ABS. The presence of a service employee hurts continued use intentions. Further, there are a three-way interaction between ABS type (service employee presence/absence), organizational response (solution-oriented/general information) and resource sufficiency perceptions. Organizational response mitigates the negative effect of service employee presence on the link between resource adequacy perceptions and ABS continued use intentions. Originality/value: In contrast with prior research, this study shows that contamination fear invokes protection motivation, resulting in better preparedness and continued use intentions of ABS. The predicted difference is primarily between customers who attribute responsibility and ABS type differently (presence/absence of service employee). This study also explores the role of organizational response to COVID-19. © 2021, Emerald Publishing Limited.

On Upholding Academic Integrity in Online Examinations

Covid-19 has brought online examinations to the spotlight after many universities resorted to online teaching and assessment. One major difficulty with online examinations is the enforcement of academic integrity, making sure that students do not cheat. This paper is an experience report discussing the pros and cons of various approaches to deal with academic integrity in examinations conducted online. It discusses the effect online tutoring platforms have on some of our online examinations, and proposes individualized online examinations as a scalable approach that could uphold academic integrity. © 2020 IEEE.