Understanding the Molecular Mechanism(s) of SARS-CoV2 Infection and Propagation in Human to Discover Potential Preventive and Therapeutic Approach

Exported across the world might create a serious controversy. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection into the host undergoes a huge number of complex repli-cative machineries which remains unclear. Understanding the mechanism (s) of replication and mode of infection of SARS-CoV2 to human cells will help us in the development of novel vaccines or drugs for the eradication and prevention of the disease. This review compiles the knowledge of SARS-CoV2 rep-licative machinery, mode of infection to the human cells and the development of drugs and vaccines which are currently under clinical trials.Copyright © 2020 Bentham Science Publishers.

SPONTANEOUS CECAL PERFORATION IN COVID-19 - AN UNCOMMON MANIFESTATION

BACKGROUND: Gastrointestinal (GI) manifestations are the most frequently reported extrapulmonary symptoms of COVID-19 infection with a prevalence of 10%-50%. Most common ones are nausea, vomiting, diarrhea and abdominal pain. GI perforation especially spontaneous colonic perforations are rare in the disease course. METHODS: We report the case of a patient with COVID-19 infection, who developed cecal perforation while recovering from COVID pneumonia, necessitating emergent surgical treatment, and the current literature was reviewed. CASE PRESENTATION: 65-year-old male presented to the hospital with shortness of breath, myalgias and fever. He was admitted to ICU secondary to acute hypoxemic respiratory failure due to COVID 19 pneumonia. He was treated with steroids, tocilizumab and remdesivir. On day-11, he developed severe abdominal pain with worsening leukocytosis. His CXR showed air under diaphragm and abdominal CT showed large pneumoperitoneum, suggestive of a perforated viscus. He underwent emergent laparotomy and was found to have non-obstructive cecal perforation. A colonic de-tension and right colectomy with ileotransverse anastomosis was performed and he was successfully discharged later. The tissue pathology showed distended colon, active colitis, transmural granulocytic inflammation, micro-abscesses, and ulceration suggestive of bowel perforation. DISCUSSIONS: ACE2 protein, a cell receptor for SARS-CoV-2, has been found in glandular cells of gastrointestinal epithelia. Direct viral infection, small vessel thrombosis, or nonocclusive mesenteric ischemia are some possible explanations for the spectrum of bowel findings. SARS-CoV-2 can have direct inflammatory effect on vascular endothelium too. Use of steroids, tocilizumab and systemic coagulopathy seen in severe COVID-19 infection also contributes to these manifestations. In our patient, an acute over-distension of colon, without mechanical distal obstruction, in the setting of COVID-19 infection & tocilizumab led to cecal perforation. Our literature review confirmed only 33 case-reports or series of bowel perforation (either as presenting symptom or during hospital course) in the setting of COVID-19 infection have been reported, with combined 28.5% mortality rate and 5 studies not reporting the outcome. Considering the worldwide incidence of this pandemic, it is a rare complication. CONCLUSIONS: GI perforation is a rare but dangerous complication of COVID19. Treatment with interleukin- 6 inhibitors or steroids is often associated in most cases. As we are gaining more knowledge about clinical spectrum of this novel disease, we are learning more about its possible rare expression, associations, and complications. Our case underlines the need to be vigilant for severe GI symptoms in setting of COVID-19 infection to enrich our understanding of this pandemic and as a result improve patients' outcome. (Figure Presented)

Rise and fall in sars-cov-2 global pandemic strain rate–an overview

After its discovery in Hubei in China in December 2019, the deadly rise of modern coronavirus (COVID-19 or 2019-nCoV) has spread globally. SARS-CoV-2 disease COVID-19 has quickly spread worldwide, posing a serious threat to health and the economy. As of 25th January 2021, more than 100 million confirmed cases of 2,165,581 deaths have been reported by WHO and Worldometer. Many of the cases reported are caused by infection from human to human and are the carriers of this lethal coronavirus. Due to its calamitous nature, the whole world was under lockdown restricting all sorts of movements and means of transportation in hampering the countries economic balance. Presently, the world's endeavor to create and develop a safe and effective COVID-19 vaccine is bearing the fruit. A handful of vaccines now have been authorized around the globe and many more remain in the development phase. In addition, social isolation and knowledge of hygiene (facial masks and sanitizers) are potential methods of controlling the further dissemination of global pandemics COVID-19. This research article presents a brief overview of the catastrophic effect caused by COVID-19 disease globally and particularly in different states of India. Additionally, the article also discusses the recent variant of SARS-CoV-2 and its vulnerable impact. Furthermore, the article investigates the currently available vaccines and those in their development phase for the treatment of COVID-19 disease. This investigatory literature may provide comprehensive details on COVID-19 disease from its inception to grow and later fall in its strain rate.

Real-time robust estimation of breathing rate from PPG using commercial-grade smart devices: Demo abstract

In this work, we present a solution for an accurate and real-time monitoring of breathing rate (BR) from photoplethysmogram (PPG) signal on both smartphone and smartwatch. Respiration induces multiple modulations in a PPG signal which are difficult to extract from low-quality PPG signal collected using consumer devices. We present an effective method of validating the breathing signal data which is evaluated and compared on an open dataset. The solution is also implemented as a smartphone and smartwatch app to provide an on-device real-time BR, and evaluated on multiple subjects. For the demonstration, we shall show breathing rate and breathing pattern both on smartphone and smartwatch, which can be visualized in real-time on a dashboard. © 2020 ACM.

Graph analytics on proximity data to fight contagion

As social distancing has become the new normal, it is eminent for enterprises and administrations to make decisions based on analytics on human proximity data. Graph Analytics can serve as an essential technology to understand human network behaviors and contact tracing inferences in pandemic and post-pandemic scenarios. A large amount of work has happened on epidemiology of pandemics. However, a formal application of graph analytics backed by visualization and mapping of graph algorithms has remained neglected in pandemic scenarios. This paper has addressed this important need backed by graph modeling, methods and analytics. © 2020 CEUR-WS. All rights reserved.

ProxiTrak: A robust solution to enforce real-time social distancing & contact tracing in enterprise scenario

In the wake of recent COVID-19 pandemic, contact tracing has turned out to be an indispensable technique to help administrative authorities contain localized infections efficiently. In the absence of a definitive and an official vaccine for the infection, practicing social distancing has proved to be an effective norm to prevent the risk of infection. In this paper, we present 'ProxiTrak', a smartphone based solution for an enterprise scenario capable of not only tracing the chain of possible infection transmission among a set of population, but also guiding the users towards following social distancing norms by alerting them in real-time about any possible violation of proximity norms on their smartphones. We devise an effective classification model to make proximity decisions on the smartphone itself using Received Signal Strength Indicator (RSSI) data of on-board Bluetooth Low Energy (BLE) module using multiple mobile devices in different environments, with novel addition of using temporal features from BLE data to boost the model's accuracy. We briefly discuss ProxiTrak's corresponding server-side framework for tracing a possible chain of infection and analysing social connectivities graphically. We also propose on-device decision aggregation and server-side pruning of proximity events to lower the false positive events. Our model is capable of making strong proximity decisions to an accuracy of up to 94% on the devices trained with the model. © 2020 ACM.