Impact of Toll-Like Receptor 2 and 9 Gene Polymorphisms on COVID-19: Susceptibility, Severity, and Thrombosis.

Background: Toll-like receptors (TLRs) play an important role in activation of innate and adaptive immune responses. Aim: We aimed to detect the association between TLR2 rs5743708 G>A and TLR9 rs5743836 C>T variants and COVID-19 disease susceptibility, severity, and thrombosis by using neutrophil extracellular traps (NETs). Subjects and Methods: We included 100 adult COVID-19 patients as well as 100 age- and gender-matched normal controls. Participants were genotyped for TLR2 rs5743708 and TLR9 rs5743836. Citrullinated Histone (H3) was detected as an indicator of NETs. Results: The mutant (G/A and C/C) genotypes and (A and C) alleles of TLR2 rs5743708 and TLR9 rs5743836, respectively, have been significantly related to a higher risk of COVID-19 infection, representing a significant risk factor for the severity of COVID-19. There was no significant association between the two variants and citrullinated histone (H3). Conclusion: TLR2 rs5743708 and TLR9 rs5743836 variants have been significantly related to a higher risk and severity of COVID-19 infection but had no effect on thrombus formation.

Evolution of BIM to DTs: A Paradigm Shift for the Post-Pandemic AECO Industry

The architecture, engineering, construction, and operation (AECO) industry is evolving rapidly. In particular, technological advancements and lessons learned from the COVID-19 pandemic are shaping the industry's future. Various artificial intelligence (AI), building information modeling (BIM), and Internet of Things (IoT) techniques have contributed to the industry's modernization by enabling more self-reliable, self-automated, self-learning, time-saving, and cost-effective processes throughout the various life cycle phases of a smart building or city. As a result, the concept of digital twins (DTs) has recently emerged as a potential solution to optimize the AECO sector to achieve the required cyber-physical integration, particularly following the pandemic. Based on a systematic review, the study develops and proposes theoretical models that examine the evolution of DTs in the context of BIM, cutting-edge technologies, platforms, and applications throughout the project's life cycle phases. This study demonstrates DTs' high potential as a comprehensive approach to planning, managing, predicting, and optimizing AECO projects that will achieve more Sustainable Development Goals (SDGs). However, while DTs offer many new opportunities, they also pose technical, societal, and operational challenges that must be addressed.

Prognostic significance of complement factors in severely ill patients with COVID-19.

Coagulopathy, cytokine release, platelet hyperactivity and endothelial activation are regarded as potential major contributors to COVID-19 morbidity. Complement activation might provide a bridge linking these factors in severe COVID-19 illness. In this study, we investigated the prognostic significance of selected complement factors in hospitalized patients with severe COVID-19 infection. The study included 300 hospitalized adults with severe COVID-19 infection. Complement factors (C3, C3a, C4, sC5b-9) were assessed by commercial ELISA kits. Outcome parameters included mortality, intensive care unit admission and duration of hospital stay. It was found that survivors had significantly higher serum C3 (median (IQR): 128.5 (116.3-141.0) mg/dL vs 98.0 (70.0-112.8) mg/dL, p<0.001) and C4 (median (IQR): 36.0 (30.0-42.0) mg/dL vs 31.0 (26.0-35.0) mg/dL, p<0.001) levels when compared with non-survivors. On the other hand, it was shown that survivors had significantly lower C3a (median (IQR): 203.0 (170.3-244.0) ng/mL vs 385.0 (293.0-424.8) ng/mL, p<0.001) and sC5b-9 (median (IQR): 294.0 (242.0-318.8) ng/mL vs 393.0 (342.0-436.5) ng/mL, p<0.001) levels when compared with non-survivors. Multivariate logistic regression analysis identified C3a (OR: 0.97 (95% CI 0.96 to 0.99), p<0.001) and C4 (OR: 0.92 (95% CI 0.86 to 0.98), p=0.011) levels as significant predictors of mortality. In conclusion, serum levels of complement factors are related to mortality in severely ill patients with COVID-19.

Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features.

COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not prevent the disease but rather reduce the severity of the symptoms. Until a vaccine is developed that can prevent COVID-19 infection, the testing of individuals will be a continuous process. Medical personnel monitor and treat all health conditions; hence, the time-consuming process to monitor and test all individuals for COVID-19 becomes an impossible task, especially as COVID-19 shares similar symptoms with the common cold and pneumonia. Some off-the-counter tests have been developed and sold, but they are unreliable and add an additional burden because false-positive cases have to visit hospitals and perform specialized diagnostic tests to confirm the diagnosis. Therefore, the need for systems that can automatically detect and diagnose COVID-19 automatically without human intervention is still an urgent priority and will remain so because the same technology can be used for future pandemics and other health conditions. In this paper, we propose a modified machine learning (ML) process that integrates deep learning (DL) algorithms for feature extraction and well-known classifiers that can accurately detect and diagnose COVID-19 from chest CT scans. Publicly available datasets were made available by the China Consortium for Chest CT Image Investigation (CC-CCII). The highest average accuracy obtained was 99.9% using the modified ML process when 2000 features were extracted using GoogleNet and ResNet18 and using the support vector machine (SVM) classifier. The results obtained using the modified ML process were higher when compared to similar methods reported in the extant literature using the same datasets or different datasets of similar size; thus, this study is considered of added value to the current body of knowledge. Further research in this field is required to develop methods that can be applied in hospitals and can better equip mankind to be prepared for any future pandemics.

Exploration of Community Care Awareness about COVID-19 Sterilization.

BACKGROUND: COVID-19 affects millions of people worldwide so WHO declared the COVID-19 pandemic on 11 March 2020. Since the vaccine is in the early trial phase and until it proves its efficacy, the need of finding alternative methods, which can help to curb this pandemic is urgent, so its prevention depends on standard infection control measures. This study's aim is to assess the knowledge, awareness, and practice level of Taif population towards Corona Virus disease - 2019 (COVID-19) sterilization. METHODS: A cross sectional study was conducted on 504 participants by administering a well-structured questionnaire comprising three sections including demographics, knowledge, attitude, and practice among the general population in Taif governorate KSA, over a duration of three months from July until September 2020. The descriptive analysis was carried out for demographics and dependent variables using the statistical program for social sciences. The t-test was used to detect any relationship between knowledge and practice score percentage of the general population response with respect to their gender and level of education. A p-value of < 0.05 was considered statistically significant. RESULTS: A total of 504 respondents willingly participated in the survey, there is a highly significant difference in the knowledge score percentage in respondents aged between 41 - 60 years old in comparison to the age group < 20 - 40 years old also between urban residence in comparison to rural residence, and a highly significant difference in the knowledge and practice score percentage in post graduate respondents in comparison to undergraduate. In addition, there was a significant difference in the practice score percentage in respondents aged between 41 - 60 years old in comparison to age group < 20 - 40, and a highly significant difference was seen in the practice score percentage in respondents living in urban areas in comparison to rural areas. CONCLUSIONS: The suggestion of this study was that knowledge and practice gaps among population, especially in the young age group, had to be covered by holding training programs through workshops or to include courses in the curriculum of ministry of health.

Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review.

BACKGROUND: Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies. OBJECTIVE: This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic. METHODS: We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data. RESULTS: Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%). CONCLUSIONS: Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.

COVID-19 and urban spaces: A new integrated CFD approach for public health opportunities.

Safe urban public spaces are vital owing to their impacts on public health, especially during pandemics such as the ongoing COVID-19 pandemic. Urban public spaces and urbanscape elements must be designed with the risk of viral transmission in mind. This work therefore examines how the design of urbanscape elements can be revisited to control COVID-19 transmission dynamics. Nine proposed models of urban public seating were thus presented and assessed using a transient three-dimensional computational fluid dynamics (CFD) model, with the Eulerian-Lagrangian method and discrete phase model (DPM). The proposed seating models were evaluated by their impact on the normalized air velocity, the diameter of coughing droplets, and deposition fraction. Each of the proposed models demonstrated an increase in the normalized velocity, and a decrease in the deposition fraction by >29%. Diagonal cross linear and curved triangle configurations demonstrated an improved airflow momentum and turbulent flow, which decreased the droplets deposition fraction by 68%, thus providing an improved, healthier urban public seating option.

Profiling Inflammatory Cytokines in a Cohort Study of Egyptian Patients with COVID-19 Infection.

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic is an international public health emergency with major disruptions and devastating health consequences resulting from the associated cytokine storm syndrome. The aim of our research was to assess the inflammatory biomarkers and risk factors associated with severity of (COVID-19) patients. METHODS: A cross-sectional study was conducted and included 150 Egyptian patients with COVID-19. Patients were classified into mild, moderate, and severe according to the clinical and CT chest findings. Blood samples were collected from patients for laboratory assessment of inflammatory biomarkers. RESULTS: Our results showed significant negative correlation between oxygen saturation percent and serum levels of inflammatory markers. The correlations were statistically significant with IL-6, CRP, ferritin, LDH, and D-dimer which can be used as sensitive biomarkers for assessment of the risk of severity of infection in COVID 19 patients. CONCLUSIONS: The study revealed that the risk factors associated with severity of COVID 19 infection included older age, male gender, presence of underlying chronic disease, and increased levels of inflammatory biomarkers: CRP, LDH, ferritin, IL-6, and D-dimer.

A Review of Mobile Chatbot Apps for Anxiety and Depression and their Self-Care Features

Background Anxiety and depression rates are at an all-time high. Smartphone-based mental health chatbots can aid psychiatrists replacing some of the costly human based interaction providing a unique opportunity to expand the availability and quality of mental health intervention whilst providing an alternative approach to fill the much-needed self-care gap. Objective Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. Methods A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbot apps for anxiety and depression. Eligibility was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and post-installation by two reviewers. Information on quality was assessed by following the mHONcode principles. Results Only a handful (n=11) of chatbots were included from an initial search of 1000 that provide a substitute for human-human based interaction and clearly had a therapeutic human substitute goal in mind. The majority of reviewed apps had a high number of downloads indicating their popularity. The apps were also of a general high quality based on our assessment according to the mHONcode principles. Conclusion The general popularity of apps reviewed, and results of our quality assessment indicate chatbots have a promising future within the realm of anxiety and depression. Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed low-cost assistance to professionals.