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Background: Since the SARS-CoV-2 outbreak in December 2019 in Wuhan, China, the virus has infected more than 153 million individuals across the world due to its human-to-human transmission. The USA is the most affected country having more than 32-million cases till date. Sudden high fever, pneumonia and organ failure have been observed in infected individuals., Objectives: In the current situation of emerging viral disease, there is no specific vaccine, or any therapeutics available for SARS-CoV-2, thus there is a dire need to design a potential vaccine to combat the virus by developing immunity in the population. The purpose of present study was to develop a potential vaccine by targeting B and T-cell epitopes using bioinformatics approaches., Methods: B- and T-cell epitopes are predicted from novel M protein-SARS-CoV-2 for the development of a unique multiple epitope vaccine by applying bioinformatics approaches. These epitopes were analyzed and selected for their immunogenicity, antigenicity scores, and toxicity in correspondence to their ability to trigger immune response. In combination to epitopes, best multi-epitope of potential immunogenic property was constructed. The epitopes were joined using EAAAK, AAY and GPGPG linkers., Results: The constructed vaccine showed good results of worldwide population coverage and promising immune response. This constructed vaccine was subjected to in-silico immune simulations by C-ImmSim. Chimeric protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using snapgene., Conclusion: This vaccine design proved effective in various computer-based immune response analysis as well as showed good population coverage. This study is solely dependent on developing M protein-based vaccine, and these in silico findings would be a breakthrough in the development of an effective vaccine to eradicate SARS-CoV-2 globally., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

COVID-19 may manifest as mild, moderate or severe disease with each grade of severity having its own features and post-viral implications. With the rising burden of the pandemic, it is vital to identify not only active disease but any post-recovery complications as well. This study was conducted with the aim of identifying the presence of post-viral symptomatology in patients recovered from mild COVID-19 disease. Presence or absence of 11 post-viral symptoms was recorded and we found that 8 of the 11 studied symptoms were notably more prevalent amongst the female sample population. Our results validate the presence of prolonged symptoms months after recovery from mild COVID-19 disease, particularly in association with the female gender. Hence, proving the post-COVID syndrome is a recognizable diagnosis in the bigger context of the post-viral fatigue syndrome.

Severe acute respiratory syndrome corona virus 2 (SARS CoV-2) is the cause of Corona virus disease 2019 (COVID-19), which turned into a pandemic in late 2019 and early 2020. SARS CoV-2 causes endothelial cell destruction and swelling, microthrombosis, constriction of capillaries, and malfunction of pericytes, all of which are detrimental to capillary integrity, angiogenesis, and healing processes. Cytokine storming has been connected to COVID-19 disease. Hypoxemia and tissue hypoxia may arise from impaired oxygen diffusion exchange in the lungs due to capillary damage and congestion. This personal view will look at how inflammation and capillary damage affect blood and tissue oxygenation, cognitive function, and the duration and intensity of COVID-19 disease. The general effects of microvascular injury, hypoxia, and capillary damage caused by COVID-19 in key organs are also covered in this point of view. Once initiated, this vicious cycle leads to diminished capillary function, which exacerbates inflammation and tissue damage, and increased inflammation due to hypoxia. Brain damage may result from low oxygen levels and high cytokines in brain tissue. In this paper we give a summary in this direction with focus on the role of the neuropeptide Substance P. On the basis of this, we discuss selected approaches to the question: “How Substance P is involved in the etiology of the COVID-19 and how results of our research could improve the prevention or therapy of corona? Thereby pointing out the role of Substance P in the post-corona syndrome and providing novel concepts for therapy and prevention.

Over the past 20 years, outbreaks related to coronavirus-associated diseases, such as MERS and SARS, have been threatening the whole world. The novel coronavirus emerged in Wuhan, China and belongs to the SARS family. It has been named “Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2)”. Keeping in view the history of pandemics faced by the world, it would be fair to say that each of them has been one of its kind, bringing an equal amount of distress and damage to the humanity. With the help of other countries, Pakistan has coped well with the pandemic. Measures taken by different countries included curfews imposed in Italy, Spain, Russia, and India, while the UK, Ireland, and China opted for a more passive approach. South Korea imposed strict self-isolation requirements across the country, whereas UAE suspended all ferry services from Iran. Vaccines authorized by FDA to treat COVID-19 include Pfizer manufactured by Biotech which has 95% efficiency, Moderna with 94% efficiency, and Johnson and Johnson which has an overall efficiency of 72% and 86% efficiency in case of severe infection. These stats are from the USA. Whereas, vaccines such as Sinopharm, Sinovac, CanSino-Bio, and Sputnik have been administered in Pakistan following their approval by the Drug Regulatory Authority of Pakistan (DRAP). This study aims to review the various aspects of the COVID-19 pandemic such as disease symptoms, the mode of action, a brief comparison of control measures taken by different countries, therapeutic trials to cure COVID-19, and the status of vaccines.

The overarching structures like intuitionistic fuzzy sets, Pythagorean fuzzy sets, m-polar fuzzy sets, and neutrosophic fuzzy sets etc. have their own inadequacies and impediments. These models are unable to do work because of their impediments in many real life situations. To overcome these deficiencies, in this paper, we introduce a set entitled Pythagorean m-polar fuzzy neutrosophic set (PmFNS), as a hybrid model of Pythagorean fuzzy set, m-polar fuzzy set and single-valued neutrosophic set. We define some notions related to PmFNS with the help of illustrations. We also present some concept of Pythagorean m-polar fuzzy neutrosophic topology alongside its leading characteristics. We render two applications of PmFNS of scarcity of water and uplifting economy ruined due to COVID-19 using TOPSIS.

BACKGROUND & OBJECTIVE: During the COVID-19 pandemic, burden on healthcare facilities has increased worldwide; which has led to acceptance of the ‘telehealth services’ by the pediatricians. Objective of this study was to determine the impact on frequency of use of tele-health services by pediatricians during the COVID-19 pandemic; and to determine the factors promoting and preventing the use of tele-health services by pediatricians. METHODOLOGY: This descriptive cross-sectional study was carried out from August 2020 to January 2021 among the pediatricians of Children Hospital Faisalabad and other affiliated hospitals of Faisalabad Medical University, Pakistan. An e-questionnaire was circulated among 357 pediatricians, which was filled and submitted by 114 pediatricians online. Demographic details and other data were collected and analyzed by SPSS v.20. P-value

Severe acute respiratory syndrome corona virus 2 (SARS CoV-2) is the cause of Corona virus disease 2019 (COVID-19), which turned into a pandemic in late 2019 and early 2020. SARS CoV-2 causes endothelial cell destruction and swelling, microthrombosis, constriction of capillaries, and malfunction of pericytes, all of which are detrimental to capillary integrity, angiogenesis, and healing processes. Cytokine storming has been connected to COVID-19 disease. Hypoxemia and tissue hypoxia may arise from impaired oxygen diffusion exchange in the lungs due to capillary damage and congestion. This personal view will look at how inflammation and capillary damage affect blood and tissue oxygenation, cognitive function, and the duration and intensity of COVID-19 disease. The general effects of microvascular injury, hypoxia, and capillary damage caused by COVID-19 in key organs are also covered in this point of view. Once initiated, this vicious cycle leads to diminished capillary function, which exacerbates inflammation and tissue damage, and increased inflammation due to hypoxia. Brain damage may result from low oxygen levels and high cytokines in brain tissue. In this paper we give a summary in this direction with focus on the role of the neuropeptide Substance P. On the basis of this, we discuss selected approaches to the question: "How Substance P is involved in the etiology of the COVID-19 and how results of our research could improve the prevention or therapy of corona? Thereby pointing out the role of Substance P in the postcorona syndrome and providing novel concepts for therapy and prevention. [ABSTRACT FROM AUTHOR]

COVID-19 is an epidemic, causing an enormous death toll. The mutational changing of an RNA virus is causing diagnostic complexities. RT-PCR and Rapid Tests are used for the diagnosis, but unfortunately, these methods are ineffective in diagnosing all strains of COVID-19. There is an utmost need to develop a diagnostic procedure for timely identification. In the proposed work, we come up with a lightweight algorithm based on deep learning to develop a rapid detection system for COVID-19 with thorax chest x-ray (CXR) images. This research aims to develop a fine-tuned convolutional neural network (CNN) model using improved EfficientNetB5. Design is based on compound scaling and trained on the best possible feature extraction algorithm. The low convergence rate of the proposed work can be easily deployed into limited computational resources. It will be helpful for the rapid triaging of victims. 2-fold cross-validation further improves the performance. The algorithm proposed is trained, validated, and testing is performed in the form of internal and external validation on a self-collected and compiled a real-time dataset of CXR. The training dataset is relatively extensive compared to the existing ones. The performance of the proposed technique is measured, validated, and compared with other state-of-the-art pre-trained models. The proposed methodology gives remarkable accuracy (99.5%) and recall (99.5%) for biclassification. The external validation using two different test dataset also give exceptional predictions. The visual depiction of predictions is represented by Grad-CAM maps, presenting the extracted features of the predicted results. [ABSTRACT FROM AUTHOR]

Purpose: Although the research stream in the area of career plateau acknowledges its ramifications, yet investigation on how this phenomenon can be reduced is sparse. This study aims to address this gap by illuminating the role of proactive personality (PP) as a factor of minimizing plateau via playful work design (PWD), career adaptability (CA) and perceived work-life balance (PWLB). Design/methodology/approach: A cross-sectional study design was applied and structural equation modelling was used to assess the hypothesized relationships among PP, CA, PWD, perceived work design and career plateau. A total of 338 employees from public and private universities were sampled from February 2020 to July 2020. Findings: The results highlighted that CA mediated the relationship between PP and PWLB, as well as, PWD mediated the association between PP and PWLB. Further, the authors got support for both serial mediation paths i.e. PP, CA, PWLB and career plateau and PP, PWD, PWLB and career plateau. Originality/value: The findings of this study provide much needed ways to overcome career plateau in the academic sector. Moreover, the use of multiple serial paths has enhanced the underlying factors of PP and career plateau nexus. [ABSTRACT FROM AUTHOR]

The overarching structures like intuitionistic fuzzy sets, Pythagorean fuzzy sets, m-polar fuzzy sets, and neutrosophic fuzzy sets etc. have their own inadequacies and impediments. These models are unable to do work because of their impediments in many real life situations. To overcome these deficiencies, in this paper, we introduce a set entitled Pythagorean m-polar fuzzy neutrosophic set (PmFNS), as a hybrid model of Pythagorean fuzzy set, m-polar fuzzy set and single-valued neutrosophic set. We define some notions related to PmFNS with the help of illustrations. We also present some concept of Pythagorean m-polar fuzzy neutrosophic topology alongside its leading characteristics. We render two applications of PmFNS of scarcity of water and uplifting economy ruined due to COVID-19 using TOPSIS. [ABSTRACT FROM AUTHOR]

BACKGROUND & OBJECTIVE: During the COVID-19 pandemic, burden on healthcare facilities has increased worldwide; which has led to acceptance of the 'telehealth services' by the pediatricians. Objective of this study was to determine the impact on frequency of use of tele-health services by pediatricians during the COVID-19 pandemic; and to determine the factors promoting and preventing the use of tele-health services by pediatricians. METHODOLOGY: This descriptive cross-sectional study was carried out from August 2020 to January 2021 among the pediatricians of Children Hospital Faisalabad and other affiliated hospitals of Faisalabad Medical University, Pakistan. An e-questionnaire was circulated among 357 pediatricians, which was filled and submitted by 114 pediatricians online. Demographic details and other data were collected and analyzed by SPSS v.20. P-value <0.05 was taken as significant. RESULTS: Out of 114 participants, 29(25.4%) paediatricians were already using Telehealth before the COVID-19 pandemic. Whereas, 101(88.6%) participants used Telehealth during the pandemic. There was an increase in frequency of telehealth use during the pandemic by 72(63.2%) paediatricians (p-value= 0.037). Most common factor promoting the use of telehealth during pandemic was 'decreased chance of cross infection and maintenance of social distancing'. Most frequent factor preventing its use was 'lack of confidence on virtual examination findings'. CONCLUSION: Telehealth provided an effective means of practicing social distancing by the paediatricians without any breach in healthcare provision. However, there are a few factors contributing to hesitancy towards it. Therefore, more platforms must be provided and incentives must be given to paediatricians to promote the use of telehealth. [ABSTRACT FROM AUTHOR]

The purpose of this systematic literature review is to review the major studies about misinformation and fake news during COVID-19 on social media. A total of 144 articles studies were retrieved from ScienceDirect, Scopus, and Web of Science databases and 20 relevant articles were selected using the PRISMA technique. It was found that altruism, instant news sharing, self-promotion, and socialization are predictors of fake news sharing. Furthermore, the human mind plays a significant role in spreading misinformation while the role of critical thinking of individuals is very much important in controlling the flow of misinformation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Kirkuk University for Administrative & Economic Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The prompt spread of Coronavirus (COVID-19) subsequently adorns a big threat to the people around the globe. The evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare sector. Drastically increase of COVID-19 has rendered the necessity to detect the people who are more likely to get infected. Lately, the testing kits for COVID-19 are not available to deal it with required proficiency, along with-it countries have been widely hit by the COVID-19 disruption. To keep in view the need of hour asks for an automatic diagnosis system for early detection of COVID-19. It would be a feather in the cap if the early diagnosis of COVID-19 could reveal that how it has been affecting the masses immensely. According to the apparent clinical research, it has unleashed that most of the COVID-19 cases are more likely to fall for a lung infection. The abrupt changes do require a solution so the technology is out there to pace up, Chest X-ray and Computer tomography (CT) scan images could significantly identify the preliminaries of COVID-19 like lungs infection. CT scan and X-ray images could flourish the cause of detecting at an early stage and it has proved to be helpful to radiologists and the medical practitioners. The unbearable circumstances compel us to flatten the curve of the sufferers so a need to develop is obvious, a quick and highly responsive automatic system based on Artificial Intelligence (AI) is always there to aid against the masses to be prone to COVID-19. The proposed Intelligent decision support system for COVID-19 empowered with deep learning (ID2S-COVID19-DL) study suggests Deep learning (DL) based Convolutional neural network (CNN) approaches for effective and accurate detection to the maximum extent it could be, detection of coronavirus is assisted by using X-ray and CT-scan images. The primary experimental results here have depicted the maximum accuracy for training and is around 98.11 percent and for validation it comes out to be approximately 95.5 percent while statistical parameters like sensitivity and specificity for training is 98.03 percent and 98.20 percent respectively, and for validation 94.38 percent and 97.06 percent respectively. The suggested Deep Learning-based CNN model unleashed here opts for a comparable performance with medical experts and it is helpful to enhance the working productivity of radiologists. It could take the curve down with the downright contribution of radiologists, rapid detection of COVID-19, and to overcome this current pandemic with the proven efficacy. [ABSTRACT FROM AUTHOR]

COVID-19 is an ongoing pandemic which has affected the globe socioeconomically. It is a pandemic different from the previous pandemics in context of its spread, medical and social aspects. The social aspects of this pandemic are as important as the medical aspect due to global interconnectivity (globalization). This article is an effort to gain a sociological insight to the social connectedness and detachment during COVID-19. The article is a review based whereby journal articles are preferred while reliable web sources are also considered. The discussion shows that social connectedness is affected by COVID-19 in many dimensions such as at micro level as well as macro level. The global interconnectivity has played role in its spread at macro level, and at macro level the connectedness is affected. This include closure of global businesses and trade, tourism, migration and traveling. At micro level individuals and families are affected, for example, isolation, quarantines, avoiding others etc. This have multifaceted impact on micro and macro level including economic, social and mental. Besides, sociological perspectives have been applied in context of COVID-19, social connectedness and social detachment. The discussion concludes that structural functionalism, conflict perspective and symbolic interactionism successfully explains the social connectedness and social detachment in context of COVID-19. [ABSTRACT FROM AUTHOR]

• A new series of diazenyl azo-phenol derivatives have been synthesized via diazo-coupling approach. • Spectroscopic characterization (FTIR, NMR and HR-MS) was carried out to confirm the synthesis of the synthesized diazenyl azo-phenol derivatives. • The compounds were tested for urease inhibition potential and kinetic analysis. • In silico structure-activity against urease, ribosomal protein S1 (RpsA) of Mycobacterium tuberculosis , main protease (Mpro) of SARS-CoV-2 and ADME studies were also carried out to explore the drug-like properties of the synthesized diazenyl azo-phenol derivatives. In the present study, a new series of diazenyl azo-phenol derivatives (TC-1 to TC-8) have been synthesized via diazo-coupling approach between substituted aromatic amines and phenol derivatives produced azo–phenol compounds in moderate to good yields (40–80%). The appearance of characteristic prominent peak of azo derivatives i.e. N=N peak at 1500–1400cm−1 and disappearance of NH 2 stretch at 3500–3200 cm−1, presence of a broad OH stretch in the range of 3300–3000 cm−1 in FTIR spectra, while presence of OH peak in spectral range of 15–10 ppm and aromatic protons in the region of 8.0–6.0 ppm and disappearance of NH 2 peak in 5.0–4.0 spectral region in 1H NMR spectra confirms the synthesis of new diazenyl azo-phenol derivatives. Similarly, appearance of carbon attached with -N=N- group in the range of 149–144 ppm, C−OH in the range of 164–162 ppm, C−N of pyridine ring at 175 ppm, aromatic carbons at 140–108 ppm while aliphatic carbons at 21–20 ppm in 13C NMR spectra give strong indication of synthesis of proposed compounds and HRMS also confirmed the masses of proposed structure of diazenyl azo-phenol derivatives. In case of urease inhibition potential, the in vitro results suggested that the compound TC-6 (IC 50 value 0.62 ± 0.04 µM) to be most active compared to the standard drug thiourea (IC 50 value 21.44 ± 0.78 µM), kinetic analysis revealed that TC-6 behaved as a mixed-type inhibitor with irreversible mode of action. The SAR showed the stable docked complex due to the presence of dihydroxy hydrogen atoms in TC-6 (-6.01 kcal/mol) and strong binding interactions with the active site residues of the target protein urease (3LA4). The detailed in silico analysis of the diazenyl azo-phenol derivatives (TC-1 to TC-17) against the ribosomal protein S1 (RpsA) of Mycobacterium tuberculosis (4NNI) and main protease (Mpro) of SARS-CoV-2 (6LU7) was also performed and SAR showed that among all the docked compounds, TC-6 and TC-9 showed best docked conformational poses by exhibiting strong interactions with the active site residues of the target proteins (4NNI & 6LU7) with minimum binding energy values i.e. -5.36 kcal/mol and -4.84 kcal/mol respectively. The ADME calculations showed that the synthesized ligands quietly obey rule of five without any considerable violations. [ABSTRACT FROM AUTHOR]