Dive of Photonics in the Battle to Fight Against COVID 19: A Review

When physicist says that there is physics behind everything, he literally means everything, including how virus or diseases transmit and how it can be detected at the early stage of infection. However, from the 1918's influenza pandemic till today's corona pandemic, no efficient diagnostic tool for the sensitive identification of viral pathogens has been developed. Rapid, sensitive, and label-free detection of COVID can serve as a first line defence against the current pandemic. Emphases is put on explaining how photonics is currently applied in COVID-19 testing while simultaneously looking at how photonics is fuelling the next generation of technologies to combat COVID-19.

Ethereum and Intelligent Systems Technologies for COVID-19

Beginning in 2020, Covid has increased as a result of a burst put on by a respiratory infection with a substantial peaking fatality rate. The unforeseen occurrence and unchecked global spread of the COVID-19 illness highlight the limitations of current healthcare systems in responding to emergencies affecting public wellness. In these conditions, innovative developments like public blockchain and intelligent systems (AI) have emerged as possible treatments for the covid epidemic. In particular, block chain may help with early identification to combat pandemics. With the measures put in place to prevent infection by wearing masks, social seclusion with a 6m radius, routine testing, and two vaccine doses. This system includes mask measurement, people identification, temp sensors, information tracking, in-person interaction locating, and the current state of a user's medical chart. With the development of technology and increased smartphone usage, illnesses may be tracked and their spread controlled. Considering that the expansion of the business sector's rehabilitation and its continued broad distribution of Covid, it is more crucial to adhere to the instructions to avoid contamination. © 2022 IEEE.

Predictors of in-hospital mortality in COVID-19: a study across two peripheral district general hospitals in UK

Aim: The mortality from Coronavirus Disease 2019 (COVID-19) has remained a significant medical challenge. Internationally, patient demographics and pre-existing co-morbidities are significant determinants of mortality from COVID-19. The mortality-risk in a local population is difficult to determine. The objective of our study is to examine the risk posed by epidemiological and demographic variables, and co-morbidities in our local population. Method: A retrospective, observational study was conducted on confirmed COVID-19 patients, identified from the local microbiology database. A search of the electronic patient records was performed to collect demographic details and co-morbidities. Chi-square test and logistic regression analysis of the demographic variables and co-morbidities were utilised to calculate the predictive-risk for in-hospital mortality of adult COVID-19 patients. Results: Final analysis included 263 samples. Univariate logistic regression analysis was performed using age as an independent categorical predictor with two cohorts - those <60 and those 60 years old. Age (X2 =17.12, p<0.001) was found to be an independent predictor of mortality - this was independent of sex (X2 =1.784, p<0.182). Charlson Comorbidity Index (CCI) score was found to be a significant predictor of adverse outcome. The odds of death for patients with CCI scores 0-4 was less than half (44.8%) of those with CCI scores 5 (p=0.005). Patients with no pre-existing medical conditions had a lower mortality-risk (OR=0.181, p=0.022) than those with known medical conditions. Pre-existing renal disease predicted a poor outcome (OR=1.996, p=0.027). The odds of death for the patients coming from their own-home was only 26% of the odds for those from a longterm care-home. Long-term care facility, advanced age (OR=1.058, p <0.001), and long-term oral steroid (OR=3.412, p=0.016) use were all associated with a poor prognosis. Conclusion: People aged 60 years, residence in a long-term care-home, pre-existing renal diseases, a high CCI score and long-term oral steroids use were associated with an increased mortality-risk.

A dimeric proteomimetic prevents SARS-CoV-2 infection by dimerizing the spike protein.

Protein tertiary structure mimetics are valuable tools to target large protein-protein interaction interfaces. Here, we demonstrate a strategy for designing dimeric helix-hairpin motifs from a previously reported three-helix-bundle miniprotein that targets the receptor-binding domain (RBD) of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Through truncation of the third helix and optimization of the interhelical loop residues of the miniprotein, we developed a thermostable dimeric helix-hairpin. The dimeric four-helix bundle competes with the human angiotensin-converting enzyme 2 (ACE2) in binding to RBD with 2:2 stoichiometry. Cryogenic-electron microscopy revealed the formation of dimeric spike ectodomain trimer by the four-helix bundle, where all the three RBDs from either spike protein are attached head-to-head in an open conformation, revealing a novel mechanism for virus neutralization. The proteomimetic protects hamsters from high dose viral challenge with replicative SARS-CoV-2 viruses, demonstrating the promise of this class of peptides that inhibit protein-protein interaction through target dimerization.

Predictors of in-hospital mortality in covid-19: A study across two peripheral district general hospitals in UK

Aim-The mortality from Coronavirus Disease 2019 (COVID-19) has remained a significant medical challenge. Internationally, patient demographics and pre-existing co-morbidities are significant determinants of mortality from COVID-19. The mortality-risk in a local population is difficult to determine. The objective of our study is to examine the risk posed by epidemiological and demographic variables, and co-morbidities in our local population. Method-A retrospective, observational study was conducted on confirmed COVID-19 patients, identified from the local microbiology database. A search of the electronic patient records was performed to collect demographic details and co-morbidities. Chi-square test and logistic regression analysis of the demographic variables and co-morbidities were utilised to calculate the predictive-risk for in-hospital mortality of adult COVID-19 patients. Results-Final analysis included 263 samples. Univariate logistic regression analysis was performed using age as an independent categorical predictor with two cohorts – those <60 and those ≥60 years old. Age (2 =17.12, p<0.001) was found to be an independent predictor of mortality – this was independent of sex (2 =1.784, p<0.182). Charlson Comorbidity Index (CCI) score was found to be a significant predictor of adverse outcome. The odds of death for patients with CCI scores 0-4 was less than half (44.8%) of those with CCI scores ≥5 (p=0.005). Patients with no pre-existing medical conditions had a lower mortality-risk (OR=0.181, p=0.022) than those with known medical conditions. Pre-existing renal disease predicted a poor outcome (OR=1.996, p=0.027). The odds of death for the patients coming from their own-home was only 26% of the odds for those from a long-term care-home. Long-term care facility, advanced age (OR=1.058, p <0.001), and long-term oral steroid (OR=3.412, p=0.016) use were all associated with a poor prognosis. Conclusion-People aged ≥60 years, residence in a long-term care-home, pre-existing renal diseases, a high CCI score and long-term oral steroids use were associated with an increased mortality-risk.

Challenges in medico-legal autopsy during COVID-19 pandemic times

The COVID-19 pandemic caused by 2019-nCoV outbreaks in most of the countries has spread rapidly and became a major concern. Due to the strong infectivity nature of COVID-19 and lack of experience among forensic experts in performing autopsy during this period, it has been a challenge and a learning experience for the future. In this article, we summarize what are the issues faced and managed during and after medico-legal autopsy of confirmed or suspected cases. © 2020, Institute of Medico-Legal Publications. All rights reserved.