Myocardium damage and electrocardiogram characteristics of patients infected with SARS-CoV-2 Omicron variant in Zhuhai

Aim To explore the myocardial damage, abnormal electrocardiogram characteristics of patients infected with SARS-CoV-2 Omicron variant in Zhuhai. Methods 84 patients with SARS-CoV-2 Omicron variant (Omicron variant group) admitted to the Fifth Affiliated Hospital of Sun Yat-sen University from January 13 to March 20, 2022 were included, and 88 patients with non SARS-CoV-2 Omicron variant (non-Omicron variant group) from January 17 to February 17, 2020 were included. A retrospective study was conducted to compare myocardial damage, abnormal electrocardiogram and clinical characteristics between the two groups. Results The mean age of patients in Omicron variant group was smaller than that in non-Omicron variant group [(36. 6±15. 6) years vs. (49. 8±14. 3) years, P<0. 01], and the proportion of patients with body temperature, systolic blood pressure and fever at admission was lower than that of non-Omicron variant group (P<0. 05). The neutrophil / lymphocyte ratio [(2. 93 (3. 03, 5. 81) vs. 7. 06 (2. 32, 11. 27), P<0. 001], interleukin-2 (IL-2) and interleukin-6 (IL-6) levels in Omicron variant group were significantly lower than those in non-Omicron variant group (P<0. 01). Cardiac troponin I (cTnI) was negative in Omicron variant group, and the concentrations of cTnI, creatine kinase-MB isozyme (CK-MB) and N-terminal pro-brain natriuretic peptide (NT-proB-NP) and the proportion of patients with elevated levels were significantly lower than those of non-Omicron variant group (P<0. 01). The incidence of abnormal electrocardiogram in Omicron variant group was also significantly lower than that in non-Omicron variant group (25. 0% vs. 42. 0%, P = 0. 001), sinus tachycardia, atrial premature beats and T wave changes were the main symptoms. Atrial premature beats, T wave changes, ST segment depression and bundle branch block were the main symptoms in non-Omicron variant group. Conclusions The patients infected with SARS-CoV-2 Omicron variant in Zhuhai may not have obvious myocardial damage because most of the patients have been vaccinated with COVID-19 vaccine. The incidence of abnormal electrocardiogram is also significantly lower than that of non-Omicron variant group, mainly sinus tachycardia, atrial premature beats and T wave changes. © 2022, Editorial Office of Chinese Journal of Arteriosclerosis. All rights reserved.

Framing blockchain-integrated digital twins for emergent healthcare management at local and city levels: A proof of concept

It has been witnessed that digital technology has the potential to improve the efficiency of emergent healthcare management in COVID-19, which however has not been widely adopted due to unclear definition and configuration. This research aims to propose a proof of concept of digital twins for emergent healthcare management through configuring the cyber and functional interdependencies of healthcare systems at local and city levels. Critical interdependencies of healthcare systems have been firstly identified at both levels, then the information and associated cyber and functional interdependencies embedded in seven critical hospital information systems (HISs) have been identified and mapped. The proposed conceptual digital twin-based approach has been then developed for information coordination amongst these critical HISs at both local and city levels based on permissioned blockchain to (1) integrate and manage the information from seven critical HISs, and further (2) predict the demands of medical resources according to patient trajectory. A case study has been finally conducted at three hospitals in London during the COVID-19 period, and the results showed that the developed framework of blockchain-integrated digital twins is a promising way to provide more accurate and timely procurement information to decision-makers and can effectively support evidence-based decisions on medical resource allocation in the pandemic. © 2023 ICE Publishing: All rights reserved.

Match Performance Statistics Related to Winning of Chinese Super League Under Different Match Stages

This paper aims to determine relationships between 160 matches statistics and the match results in two match stages of 2020 CSL under the COVID-19 pandemic prevention and control. A team's winning probability was evaluated by a two-standard-deviation increase in the value of each variable. The smallest worthwhile change was used to evaluate nonclinical magnitude-based inferences. The results showed that for group round robin stage, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Set Piece, Cross Accuracy, Counterattack, Won Challenge, Tackle Gaining, HIR Distance in BP, Sprinting Distance in BP), two had obviously negative effects (Distance Covered in Penalty Area, Sprinting Distance Out of BP), other twenty-three statistics had either trivial or unclear effects. While for the knockout stage, the effects of nine match statistics (Pass Accuracy, Forward Pass Accuracy, Delivery into Attacking Third, Delivery into Penalty Area, Dribble into Attacking Third, Corner, Foul Committed, Yellow Card, Distance Covered in Attacking Third) turned to clearly positive, the effects of Won Challenge, Cross Accuracy turned to trivial and clearly negative, respectively. Coaches and players should take these different aspects into account when planning practices and competitions for their teams. © 2023 SPIE.

Comparison of adaptive thermal comfort with face masks in library building in Guangzhou, China

During the COVID-19 pandemic, wearing masks in public spaces has become a protective strategy. Field tests and questionnaire surveys were carried out at a university library in Guangzhou, China, during June 2021 and January 2022. The indoor environmental parameters were observed, thermal sensation votes of students on various environmental parameters were collected, symptoms of students wearing masks were quantified, and the appropriate amount of time to wear masks was established. To identify acceptable and comfortable temperature ranges, the relationship between thermal sensation and thermal index was investigated. During summer and winter, people wearing masks are symptomatic for a certain duration. The most frequently voted symptom was facial heat (62.7 % and 54.6 % during summer and winter, respectively), followed by dyspnea. During summer, more than 80 % of the participants subjects were uncomfortable and showed some symptoms after wearing masks for more than 2 h (3 h during winter). In the summer air conditioning environment in Guangzhou, the neutral Top was 26.4 °C, and the comfortable Top range was 25.1–27.7 °C. Under the natural ventilation environment in winter, the neutral Top was 20.5 °C, and the comfortable Top range was 18.5–22.5 °C. This study may provide guidance for indoor office work and learning to wear masks in Guangzhou. © 2022 Elsevier Ltd

A Silicon-Based Radio Platform for Integrated Edge Sensing and Communication Toward Sustainable Healthcare

Faced with COVID-19 and the trend of aging, it is demanding to develop an online health metrics sensing solution for sustainable healthcare. An edge radio platform owning the function of integrated sensing and communications is promising to address the challenge. Radar demonstrates the capability for noncontact healthcare with high sensitivity and excellent privacy protection. Beyond conventional radar, this article presents a unique silicon-based radio platform for health status monitoring supported by coherent frequency-modulated continuous-wave (FMCW) radar at Ku-band and communication chip. The radar chip is fabricated by a 65-nm complementary metal–oxide–semiconductor (CMOS) process and demonstrates a 1.5-GHz chirp bandwidth with a 15-GHz center frequency in 220-mW power consumption. A specific small-volume antenna with modified Vivaldi architecture is utilized for emitting and receiving radar beams. Biomedical experiments were implemented based on the radio platform cooperating with the antenna and system-on-chip (SoC) field-programmable gate array (FPGA) edge unit. An industrial, scientific, and medical (ISM)-band frequency-shift keying (FSK) communication chip in 915-MHz center frequency with microwatt-level power consumption is used to attain communications on radar-detected health information. Through unified integration of radar chip, management software, and communication unit, the integrated radio platform featuring <inline-formula> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula>72-dBm sensitivity with a 500-kb/s FSK data rate is exploited to drastically empower sustainable healthcare applications. IEEE

Creating an Open Data City for Healthcare: A Critical Review of Data Management Strategy and Development in China

The unexpected increased cases of COVID-19 pressured the healthcare system to be exposed to unprecedented challenges, where healthcare management is a complex but essential process to manage and coordinate all information and resources. Critical problems are emerging in this new routine and demanding a higher efficiency of medical data sharing. It is becoming necessary to improve the performances of city systems and create an open data city for reliable information and data sharing (e.g., medical and testing) for better public awareness and healthcare services. This research aims to critically review past efforts in open data city for healthcare from the perspective of data management strategy and development. China was selected as a representative due to its fast development in healthcare infrastructure and medical big data, and 79 out of 4,611 articles were selected, reviewed, and analyzed. A mixed-method approach was implemented to review and assess the existing efforts of open data city for healthcare through latitudinal and longitudinal analyses from five aspects based on sociotechnical systems: technology, people, infrastructure, processes, and culture. The gaps, missions, and challenges of developing an open data city for healthcare are also summarized, and an open data city healthcare reinforcement framework is proposed accordingly. This research contributes a new multidimensional way to rethink the development of open data city in healthcare and helps establish the state of the art of open data city. © 2022 American Society of Civil Engineers.

Modeling SARS-CoV-2 RNA degradation in small and large sewersheds

Wastewater-based epidemiology has played a significant role in monitoring the COVID-19 pandemic, yet little is known about degradation of SARS-CoV-2 in sewer networks. Here, we used advanced sewershed modeling software to simulate SARS-CoV-2 RNA degradation in sewersheds across Houston, TX under various temperatures and decay rates. Moreover, a novel metric, population times travel time (PT), was proposed to identify localities with a greater likelihood of undetected COVID-19 outbreaks and to aid in the placement of upstream samplers. Findings suggest that travel time has a greater influence on RNA degradation across the sewershed as compared to temperature. SARS-CoV-2 RNA degradation at median travel times was approximately two times greater in 20 degrees C wastewater between the small sewershed, Chocolate Bayou, and the larger sewershed, 69th Street. Lastly, placement of upstream samplers according to the PT metric can provide a more representative snapshot of disease incidence in large sewersheds. This study helps to elucidate discrepancies between SARS-CoV-2 viral load in wastewater and clinical incidence of COVID-19. Incorporating travel time and SARS-CoV-2 RNA decay can improve wastewater surveillance efforts.

Synthesis of Chiral Impurities in Production Process of Remdesivir

To improve quality control of remdesivir, the key chiral impurities easily generated in the production process of remdesivir were designed and synthesized. The structures of these compounds included (S)-2-ethylbutyl 2-[[(S)-[[(2R,3S,4R,5S)-5-(4-aminopyrrolo[2,1-f][1,2,4]triazin-7-yl)-5-cyano-3,4-dihydroxytetrahydrofuran-2-yl]-methoxy](phenoxy)phosphoryl]amino]propanoate, (S)-2-[(R)-(2R,3S,4R,5R)]-type and (S)-2-[(R)-(2R,3S,4R,5S)]type optical isomers were confirmed by MS and NMR. This method was suitable for laboratory synthesis due to its mild reaction conditions, high yield and no need for chiral separation. Copyright © 2022 Shanghai Institute of Pharmaceutical Industry. All rights reserved.

Changes in Hospitalizations and In-Hospital Deaths for Adults Aged 65 Years and Older in the Initial Period of the COVID-19 Pandemic (April-December 2020), 29 States: Statistical Brief #293

This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents data from 29 States on hospitalizations across time periods with a focus on the initial impact of the COVID-19 pandemic. The number of hospitalizations and in-hospital deaths for patients aged 65 years and older is presented overall and by patient characteristics across 29 States from April to December 2020 using quarterly HCUP inpatient data compared with State-level averages from April to December in 2016-2019 using the HCUP State Inpatient Databases (SID). The percentages of all hospitalizations and in-hospital deaths related to COVID-19 during the April-December 2020 timeframe are also provided. Because of the large sample size of the HCUP data, small differences can be statistically significant but not meaningful. Thus, only differences greater than or equal to 10 percent are discussed in the text.

Blockchain Meets COVID-19: A Framework for Contact Information Sharing and Risk Notification System

COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce infection and death rates. There are three disadvantages to the existing contact tracing system: 1. User data is stored in a centralized database that could be stolen and tampered with, 2. User's confidential personal identity may be revealed to a third party or organization, 3. Existing contact tracing systems [1] [2] only focus on information sharing from one dimension, such as location-based tracing, which significantly limits the effectiveness of such systems. We propose a global COVID-19 information sharing and risk notification system that utilizes the Blockchain, Smart Contract, and Bluetooth. To protect user privacy, we design a novel Blockchain-based platform that can share consistent and non-tampered contact tracing information from multiple dimensions, such as location-based for indirect contact and Bluetooth-based for direct contact. Hierarchical smart contract architecture is also designed to achieve global agreements from users about how to process and utilize user data, thereby enhancing the data usage transparency. Furthermore, we propose a mechanism to protect user identity privacy from multiple aspects. More importantly, our system can notify the users about the exposure risk via smart contracts. We implement a prototype system to conduct extensive measurements to demonstrate the feasibility and effectiveness of our system.

Creating an Inter-Hospital Resilient Network for Pandemic Response Based on Blockchain and Dynamic Digital Twins

Developing and using the rich data implied by dynamic digital twins and blockchain is relevant to manage both patients and medical resources (e.g., doctors/nurses, ventilators etc.) at the COVID-19 and post COVID period. This paper aims at exploring the blockchain solutions for preparing healthcare systems ready for both efficient operation daily and in pandemic through (1) information integration of patient and medical resource flow from healthcare and medical records;(2) optimizing the deployment of such resources based on hospitals, regions and local pandemic levels switching from normal to the outbreak. The main idea is to develop the concepts of the novel framework for creating an inter-hospital resilient network for pandemic response based on blockchain and dynamic digital twin, which will set up innovative ways to best care for patients, protect NHS staff, and support government scientific decisions to beat COVID-19 now and manage the crisis in the future. © 2021 IEEE.

Facing the volatility of tweets in altmetric research

The data re-collection for tweets from data snapshots is a common methodological step in Twitter-based research. Understanding better the volatility of tweets over time is important for validating the reliability of metrics based on Twitter data. We tracked a set of 37,918 original scholarly tweets mentioning COVID-19-related research daily for 56 days and captured the reasons for the changes in their availability over time. Results show that the proportion of unavailable tweets increased from 1.6 to 2.6% in the time window observed. Of the 1,323 tweets that became unavailable at some point in the period observed, 30.5% became available again afterwards. "Revived" tweets resulted mainly from the unprotecting, reactivating, or unsuspending of users' accounts. Our findings highlight the importance of noting this dynamic nature of Twitter data in altmetric research and testify to the challenges that this poses for the retrieval, processing, and interpretation of Twitter data about scientific papers.

The Theory Prospect of Crowd Dynamics-oriented Observation

During the development of COVID-19 virus's global epidemic, the fundamental research and various applications of crowd dynamics-oriented observation theories have attracted much attention from many researchers and people all over the world within some related disciplines, such as public health, clinical medicine, geography, public management, etc. Researchers conducted many interdisciplinary explorations in theories and methods of monitoring epidemic dynamics scientifically, preventing and controlling spatial transmission precisely, predicting accurately, and responding effectively. However, no crowd dynamics-oriented observation theories have been proposed in literature so far. This paper revisits the concept and introduces a theory framework of crowd dynamics-oriented observation, which tries to include the core theories of observation from geospatial big data and to support diverse potential developments. Firstly, this article introduces the research background of crowd dynamics-oriented observation, and then summarizes its three core questions (how to observe its change, how to analyze its change, and how to control its change). From the interdiscipline view of geographic information science, surveying and mapping science, this paper explains the research significance and disciplinary value of crowd dynamics-oriented observation theories. Secondly, this paper introduces a framework of crowd dynamics-oriented observation and its spatiotemporal application, and then elaborates on the bottleneck problems of the key observation theories of crowd dynamics, such as fundamental space-time framework theory, space-time quantification and comprehensive observation theory, spatiotemporal process optimization theory, etc. Thirdly, this paper preliminarily introduces some changes of crowd dynamics-oriented observation theories, for example, refined observation driven by the application needs of digital society governance and public safety/health emergency, personal privacy protection and personalized observations by balancing the public interest and personal privacies, the development of integrated observation theories for human-oriented observation and earth-oriented observation, and the theory of crowd dynamicsoriented observation for high-level management and service. Finally, this article points out the potential directions of crowd dynamics-oriented observation theory and methods, such as, the development of big datadriven crowd perception, multi-space refined crowd dynamics observation, and human-land systematical interaction modeling, so as to realize some differentiated, integrated, and hierarchical crowd dynamics-oriented observations. All potential theories are helpful to the scientific decision-making of public management and public service. The crowd dynamics-oriented observation theory should focus on the fundamental research questions related to studying, analyzing, and servicing human beings, which has become a research frontier in geospatial information science, and could play very important roles in supporting national development strategies, such as "New urbanization", "beautiful China", "artificial intelligence", and "new infrastructure", so as to contribute to a green, efficient, smart, and sustainable regional and urban development. © 2021, Science Press. All right reserved.

Similarities and Differences of CT Features between COVID-19 Pneumonia and Heart Failure

Aims: During the COVID-19 epidemic, chest computed tomography (CT) has been highly recommended for screening of patients with suspected COVID-19 because of an unclear contact history, overlapping clinical features, and an overwhelmed health system. However, there has not been a full comparison of CT for diagnosis of heart failure or COVID-19 pneumonia. Methods: Patients with heart failure (n = 23) or COVID-19 pneumonia (n = 23) and one patient with both diseases were retrospectively enrolled. Clinical information and chest CT images were obtained and analyzed. Results: There was no difference in ground-glass opacity, consolidation, crazy paving pattern, the lobes affected, and septal thickening between heart failure and COVID-19 pneumonia. However, a less rounded morphology (4% vs. 70%, P = 0.00092), more peribronchovascular thickening (70% vs. 35%, P = 0.018) and fissural thickening (43% vs. 4%, P = 0.002), and less peripheral distribution (30% vs. 87%, P = 0.00085) were found in the heart failure group than in the COVID-19 group. Importantly, there were also more patients with upper pulmonary vein enlargement (61% vs. 4%, P = 0.00087), subpleural effusion (50% vs. 0%, P = 0.00058), and cardiac enlargement (61% vs. 4%, P = 0.00075) in the heart failure group than in the COVID-19 group. Besides, more fibrous lesions were found in the COVID-19 group, although there was no statistical difference (22% vs. 4%, P = 0.080). Conclusions: Although there is some overlap of CT features between heart failure and COVID-19, CT is still a useful tool for differentiating COVID-19 pneumonia.

The Promotion of Online Communication Ability of Mainstream Media

With the rapid development of mobile Internet, public access to information channels have undergone disruptive changes. This article novel coronavirus pneumonia epidemic situation and other public emergencies, analyzed the current public access to information channel characteristics, discussed the new situation of traditional media information dissemination challenges, and put forward some measures to enhance the transmission power, aimed at improving the effectiveness of journalism. © 2021, Springer Nature Switzerland AG.

N95 respirator decontamination: a study in reusability.

The coronavirus disease 2019 (COVID-19) pandemic had caused a severe depletion of the worldwide supply of N95 respirators. The development of methods to effectively decontaminate N95 respirators while maintaining their integrity is crucial for respirator regeneration and reuse. In this study, we systematically evaluated five respirator decontamination methods using vaporized hydrogen peroxide (VHP) or ultraviolet (254 nm wavelength, UVC) radiation. Through testing the bioburden, filtration, fluid resistance, and fit (shape) of the decontaminated respirators, we found that the decontamination methods using BioQuell VHP, custom VHP container, Steris VHP, and Sterrad VHP effectively inactivated Cardiovirus (3-log10 reduction) and bacteria (6-log10 reduction) without compromising the respirator integrity after 2-15 cycles. Hope UVC system was capable of inactivating Cardiovirus (3-log10 reduction) but exhibited relatively poorer bactericidal activity. These methods are capable of decontaminating 10-1000 respirators per batch with varied decontamination times (10-200 min). Our findings show that N95 respirators treated by the previously mentioned decontamination methods are safe and effective for reuse by industry, laboratories, and hospitals.

Complement c3 a-chain as an indicator of disease severity in COVID-19

INTRODUCTION: As we combat the novel coronavirus SARS-CoV-2, elucidating its immunological pathogenesis is vital for both understanding and treating the disease. A few case studies have suggested that the complement system may play an important role in the course of infection, but its specific role is unclear. Our group has shown that higher circulating levels of the complement C3, particularly C3 α-chain, can be a significant predictor of survival in septic shock patients. We therefore sought to investigate if a similar relationship could be seen in SARS-CoV-2. METHODS: Thirty-six COVID-19 patients were consented for this study. Serial blood samples were collected at different time points from 22 patients not in the ICU and 14 in the ICU at the time of collection. The plasma samples were analyzed using Western Blot for circulating C3 α-chain levels. Clinical data on hematologic, respiratory, renal and coagulation status were collected. The data were analyzed for differences in ICU and Non-ICU patients and for correlations of C3 α-chain levels and clinical parameters. RESULTS: In ICU patients, in mean levels of C3 α-chain had a statistically significant increase from Days 0-5 since admission to Days 16-20 (p = 0.042). C3 α-chain levels were positively correlated with time since admission (R = 0.5401, p = 0.0115). In ICU patients, C3 α-chain levels were negatively correlated with Creatinine levels (R = -0.4515, p<0.05), Neutrophil Percentage (R = -0.5525, p<0.001) and Absolute Count (R = -0.6297, p<0.001) and positively correlated with Lymphocyte Percentage (R= 0.6748, p<0.001). In Non-ICU patients, C3 α-chain levels were negatively correlated with Neutrophil Percentage (R = -0.4929, p<0.05), BUN levels (R = -0.5055, p<0.001), and positively correlated with Lymphocyte Percentage (R = 0.45, p<0.05) and Absolute Count (R = 0.6134, p<0.001) and platelet levels (R = 0.4636, p<0.05). CONCLUSIONS: In summary, levels of circulating C3 α- chain increased with time in ICU patients. C3 α-chain levels negatively correlated with renal injury markers and systemic neutrophil levels. Moreover, C3 α-chain levels positively correlated with circulating lymphocyte levels. These results indicate that native C3 is important in fighting against COVID-19 infection and may be a critical prognostic marker of disease progression.

Prediction of potential therapeutic drugs against SARS-CoV-2 by using Connectivity Map based on transcriptome data.

OBJECTIVE: Transcriptome data related to severe acute respiratory syndrome-related coronavirus 2 (a novel coronavirus discovered in 2019, SARS-CoV-2) in GEO database were downloaded. Based on the data, influence of SARS-CoV-2 on human cells was analyzed and potential therapeutic compounds against the SARS-CoV-2 were screened. MATERIALS AND METHODS: R package "DESeq2" was used for differential gene analysis on the data of cells infected or non-infected with SARS-CoV-2. The "ClusterProfiler" package was used for GO functional annotation and KEGG pathway enrichment analysis of the differentially expressed genes (DEGs). A protein-protein interaction (PPI) network of the DEGs was constructed through STRING website, and the key subset in the PPI network was identified after visualization by Cytoscape software. Connectivity Map (CMap) database was used to screen known compounds that caused genomic change reverse to that caused by SARS-CoV-2. RESULTS: By intersecting DEGs in two datasets, a total of 145 DEGs were screened out, among which 136 genes were upregulated and 9 genes were downregulated in SARS-CoV-2-infected cells. Functional enrichment analyses revealed that these genes were mainly associated with the pathways involved in viral infection, inflammatory response, and immunity. The CMap research found that there were three compounds with a median_tau_score less than -90, namely triptolide, tivozanib and daunorubicin. CONCLUSIONS: SARS-CoV-2 can cause abnormal changes in a large number of molecules and related signaling pathways in human cells, among which IL-17 and TNF signaling pathways may play a key role in pathogenic process of SARS-CoV-2. Here, three compounds that may be effective for the treatment of SARS-CoV-2 were screened, which would provide new options for improving treatment of patients infected with SARS-CoV-2.

LNBFSM: A Food Safety Management System Using Blockchain and Lightning Network

Food safety management (FSM) has drawn attention recently, specifically after COVID-19 outbreak, due to lack of supervision in food products delivery chain. To address this issue, we propose a lightning network-blockchain FSM system. Our approach guarantees data authenticity by utilizing the technical characteristics of blockchain (e.g., tamper-resistant and traceability). We use lightning network to solve the throughput bottleneck issue in order to enable the proposed scheme adoptable in practice. The prototype of our approach has been evaluated and examined in our study. © 2020, Springer Nature Switzerland AG.