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1.
Frontiers in Public Health ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2199463

ABSTRACT

IntroductionSARS-CoV-2 has ravaged the world and undergone multiple mutations during the course of the COVID-19 pandemic. On 7 April 2022, an epidemic caused by SARS-CoV-2 Omicron (BA.2) variant broke out in Guangzhou, China, one of the largest transportation and logistical hubs of the country. MethodsTo fast curtained the Omicron epidemic, based on the routine surveillance on the risk population of SARS-CoV-2 infection, we identify key places of the epidemic and implement enhanced control measures against Omicron. ResultsTransmission characteristics of the Omicron variant were analyzed for 273 confirmed cases, and key places involved in this epidemic were fully presented. The median incubation time and the generation time were 3 days, and the reproduction number Rt was sharply increased with a peak of 4.20 within 2 days. We tried an all-out effort to tackle the epidemic in key places, and the proportion of confirmed cases increased from 61.17% at Stage 2 to 88.89% at Stage 4. Through delimited risk area management, 99 cases were found, and the cases were isolated in advance for 2.61 +/- 2.76 days in a lockdown zone, 0.44 +/- 1.08 days in a controlled zone, and 0.27 +/- 0.62 days in a precautionary zone. People assigned with yellow code accounted for 30.32% (84/277) of confirmed COVID-19 cases, and 83.33% of them were detected positive over 3 days since code assignment. For the districts outside the epicenter, the implementation duration of NPIs was much shorter compared with the Delta epidemic last year. ConclusionBy blocking out transmission risks and adjusting measures to local epidemic conditions through the all-out effort to tackle the epidemic in key places, by delimiting risk area management, and by conducting health code management of the at-risk population, the Omicron epidemic could be contained quickly.

2.
Frontiers in Microbiology ; 13 (no pagination), 2022.
Article in English | EMBASE | ID: covidwho-2199027

ABSTRACT

Currently, it is believed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an airborne virus, and virus-containing aerosol particles have been found concurrent with the onset of COVID-19, which may contribute to the noncontact transmission of SARS-CoV-2. Exploring agents to block SARS-CoV-2 transmission is of great importance to prevent the COVID-19 pandemic. In this study, we found that inactivated Parapoxvirus ovis (iORFV), a kind of immunomodulator, could compress the proportion of small particle aerosols exhaled by Syrian golden hamsters. Notably, the concentration of SARS-CoV-2 RNA-containing aerosol particles was significantly reduced by iORFV in the early stages after viral inoculation. Importantly, smaller aerosol particles (<4.7 mum) that carry infectious viruses were completely cleared by iORFV. Consistently, iORFV treatment completely blocked viral noncontact (aerosol) transmission. In summary, iORFV may become a repurposed agent for the prevention and control of COVID-19 by affecting viral aerosol exhalation and subsequent viral transmission. Copyright © 2022 Cui, Zhao, Zhang, Lin, Sun, Li, Du, Zhang, Liu, Gao, He, Gao, Guo and Guan.

3.
3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022 ; : 522-530, 2022.
Article in English | Scopus | ID: covidwho-2194148

ABSTRACT

Since 2019, the COVID-19 virus has spread worldwide, posing a significant health and safety concern. The application of mobile robots in the medical field has gradually demonstrated their unique advantages. Therefore, we focus on the application of mobile robots inwards. By collating and summarizing some of the most popular existing path planning algorithms, this paper illustrates that different algorithms can produce varying outcomes depending on different environments and hardware used. MATLAB is used in this study to simulate four algorithms: To determine the most efficient path, A∗, RRT, RRT∗, and PRM in a specific hospital map are compared, as well as parameters including path length, average execution time, and resource consumption. Modelling a single-layer hospital map makes it possible for mobile robots in the medical field to execute tasks more efficiently between entry and ward in the COVID-19 hospital environment. Based on a comparison and comprehensive consideration of the data derived from the simulations, it is found that the A∗algorithm is superior in terms of optimality, completeness, time complexity, and spatial complexity. Therefore, the A∗algorithm is more valuable in finding the best path for a mobile robot in a hospital environment. © 2022 ACM.

4.
mBio ; : e0305422, 2022.
Article in English | MEDLINE | ID: covidwho-2193467

ABSTRACT

Porcine hemagglutinating encephalomyelitis virus (PHEV) is a member of the family Coronaviridae, genus Betacoronavirus, and subgenus Embecovirus that causes neurological disorders, vomiting and wasting disease (VWD), or influenza-like illness (ILI) in pigs. Exosomes regulate nearby or distant cells as a means of intercellular communication;however, whether they are involved in the transmission of viral reference materials during PHEV infection is unknown. Here, we collected exosomes derived from PHEV-infected neural cells (PHEV-exos) and validated their morphological, structural, and content characteristics. High-resolution mass spectrometry indicated that PHEV-exos carry a variety of cargoes, including host innate immunity sensors and viral ingredients. Furthermore, transwell analysis revealed that viral ingredients, such as proteins and RNA fragments, could be encapsulated in the exosomes of multivesicular bodies (MVBs) to nonpermissive microglia. Inhibition of exosome secretion could suppress PHEV infection. Therefore, we concluded that the mode of infectious transmission of PHEV is likely through a mixture of virus-modified exosomes and virions and that exosomal export acts as a host strategy to induce an innate response in replicating nonpermissive bystander cells free of immune system recognition. IMPORTANCE The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a large number of deaths worldwide. Clinical neurological complications have occurred in some cases;however, knowledge of the natural history of coronavirus in the central nervous system (CNS) is thus far limited. PHEV is a typical neurotropic betacoronavirus (beta-CoV) that propagates via neural circuits in the host CNS after peripheral incubation rather than through the bloodstream. It is therefore a good prototype pathogen to investigate the neuropathological pathogenesis of acute human coronavirus infection. In this study, we demonstrate a new association between host vesicle-based secretion and PHEV infection, showing that multivesicular-derived exosomes are one of the modes of infectious transmission and that they mediate the transfer of immunostimulatory cargo to uninfected neuroimmune cells. These findings provide novel insights into the treatment and monitoring of neurological consequences associated with beta-CoV, similar to those associated with SARS-CoV-2.

5.
Applied Microbiology & Biotechnology ; 05:05, 2023.
Article in English | MEDLINE | ID: covidwho-2174051

ABSTRACT

Porcine deltacoronavirus (PDCoV) is an emerging swine enteropathogenic coronavirus that caused diarrhea and/or vomiting in neonatal piglets worldwide. Coronaviruses nucleocapsid (N) protein is the most conserved structural protein for viral replication and possesses good antigenicity. In this study, three monoclonal antibodies (mAbs), 3B4, 4D3, and 4E3 identified as subclass IgG2akappa were prepared using the lymphocytic hybridoma technology against PDCoV N protein. Furthermore, the B-cell epitope recognized by mAb 4D3 was mapped by dozens of overlapping truncated recombinant proteins based on the western blotting. The polypeptide 28QFRGNGVPLNSAIKPVE44 (EP-4D3) in the N-terminal of PDCoV N protein was identified as the minimal linear epitope for binding mAb 4D3. And the EP-4D3 epitope's amino acid sequence homology study revealed that PDCoV strains are substantially conserved, with the exception of the Alanine43 substitution Valine43 in the China lineage, the Early China lineage, and the Thailand, Vietnam, and Laos lineage. The epitope sequences shared high similarity (94.1%) with porcine coronavirus HKU15-155 (PorCoV HKU15), Asian leopard cats coronavirus (ALCCoV), sparrow coronavirus HKU17 (SpCoV HKU17), and sparrow deltacoronavirus. In contrast, the epitope sequences shared a very low homology (11.8 to 29.4%) with other porcine CoVs (PEDV, TGEV, PRCV, SADS-CoV, PHEV). Overall, the study will enrich the biological function of PDCoV N protein and provide foundational data for further development of diagnostic applications. KEY POINTS: * Three monoclonal antibodies against PDCoV N protein were prepared. * Discovery of a novel B-cell liner epitope (28QFRGNGVPLNSAIKPVE44) of PDCoV N protein. * The epitope EP-4D3 was conserved among PDCoV strains.

6.
Sci Rep ; 12(1):21096, 2022.
Article in English | PubMed | ID: covidwho-2151081

ABSTRACT

China detected the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with Delta variant in May 2021. We assessed control strategies against this variant of concern. We constructed a robust transmission model to assess the effectiveness of interventions against the Delta variant in Guangzhou with initial quarantine/isolation, followed by social distancing. We also assessed the effectiveness of alternative strategies and that against potentially more infectious variants. The effective reproduction number (R(t)) fell below 1 when the average daily number of close contacts was reduced to ≤ 7 and quarantine/isolation was implemented on average at the same day of symptom onset in Guangzhou. Simulations showed that the outbreak could still be contained when quarantine is implemented on average 1 day after symptom onset while the average daily number of close contacts was reduced to ≤ 9 per person one week after the outbreak's beginning. Early quarantine and reduction of close contacts were found to be important for containment of the outbreaks. Early implementation of quarantine/isolation along with social distancing measures could effectively suppress spread of the Delta and more infectious variants.

7.
6th International Conference on Big Data and Internet of Things, BDIOT 2022 ; : 20-26, 2022.
Article in English | Scopus | ID: covidwho-2088937

ABSTRACT

Accurate prediction of 2019 novel coronavirus diseases (COVID-19) has been playing an important role in making more effective prevention and control policies during pandemic crises. The aim of this paper was to develop an innovative stacking based prediction of COVID-19 pandemic cumulative confirmed cases (StackCPPred) by integrating infectious disease dynamics model and traditional machine learning. Based on population migration characteristics, five feature indicators were first extracted from the population flow data in the early stage of this epidemic, which were collected from the National Health Commission of the People's Republic of China. Then, stacking based ensemble learning (SEL) model was established for COVID-19 prediction using traditional machine learning, including the multiple linear regression (MLR) and the tree regression model (XGBoost and LightGBM). By introducing the variable "death state", an improved Susceptible-Infected-Recovered (ISIR) model was established. Finally, a hybrid model, StackCPPred was proposed by incorporating the ISIR model outputs and the five feature indicators into the SEL model. Real data on population movements and daily cumulative number of newly confirmed cases across the country from January 23 to February 6 were used to validate our model. The results positively proved that the proposed StackCPPred model outperformed the existing models for COVID-19 prediction, as quantified by the root mean square error (RMSE), the root mean square logarithmic error (RMSLE) and the coefficient of determination (R2) (g1/41841 persons, g1/40.1 and >0.9, respectively). Furthermore, this study confirms the validity and usefulness of the StackCPPred model for COVID-19 prediction. © 2022 ACM.

8.
IEEE Transactions on Parallel and Distributed Systems ; : 1-3, 2022.
Article in English | Scopus | ID: covidwho-2078260

ABSTRACT

Ankit Srivastava et al. [1] proposed a parallel framework for Constraint-Based Bayesian Network (BN) Learning via Markov Blanket Discovery (referred to as ramBLe) and implemented it over three existing BN learning algorithms, namely, GS, IAMB and Inter-IAMB. As part of the Student Cluster Competition at SC21, we reproduce the computational efficiency of ramBLe on our assigned Oracle cluster. The cluster has 4x36 cores in total with 100 Gbps RoCE v2 support and is equipped with Centos-compatible Oracle Linux. Our experiments, covering the same three algorithms of ramBLe, evaluate its strong and weak scalability of the algorithms using real COVID-19 data sets. We verify part of the conclusions in the paper and propose our explanation of the differences. IEEE

9.
Chest ; 162(4):A2658-A2659, 2022.
Article in English | EMBASE | ID: covidwho-2060979

ABSTRACT

SESSION TITLE: Late Breaking Chest Infections Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/18/2022 01:30 pm - 02:30 pm PURPOSE: The science continues to develop in terms of the epidemiology of persistent, or long COVID, especially in the pediatric population. The impact of persistent COVID-19 on cardiorespiratory fitness in the form of physical activity and athletic performance among children/adolescents is not well described, especially among vulnerable populations. METHODS: A retrospective electronic health record review identified children/adolescents with previously diagnosed COVID (N=312, 52.9% male, mean age at diagnosis 6.6 [SD 5.9] years, 20.5% non-Hispanic White [NHW], 19.2% non-Hispanic Black [NHB], and 54.5% Hispanic, 85.26% hospitalized due to COVID-19 illness) from one pediatric healthcare system that serves predominantly Medicaid-dependent families. Patients or caregivers completed a follow-up telephone survey from March 2021- February 2022 to estimate the prevalence of persistent COVID symptoms, defined as the presence of symptoms lasting ≥ 30 days. Multiple logistic regression models explored the association between physical activity and the presence of long COVID. RESULTS: 71 (22.8%) patients reported long COVID and the most prevalent symptoms included tiredness (21 [6.7%]), shortness of breath (18 [5.8%]), cough (16 [5.1%]), headache (14 [4.5%]), difficulty with thinking/concentration (14 [4.5%]), disrupted sleep (14 [4.5%]), other symptoms (12 [3.8%]), anxiety (11 [3.5%]), body aches (11 [3.5%]), joint pain (10 [3.2%]) chest pain (9 [2.9%]), intermittent fever (6 [1.9%]), and loss taste/smell (5 [1.6%]). Almost a third (32%, N = 24) of patients who participated in any athletics or physical activity in or outside of school reported a negative impact on physical or athletic performance, and 66.7% reported it was directly related to COVID-19 illness. Specific complaints when returning to physical activity post-COVID illness included tiredness (7 [36.8%]) and shortness of breath (2 [10.5%]). The odds of a decline in physical activity performance was over twice that (OR 2.17, 95% CI 0.54-8.71, p = 0.28) among children with long COVID versus those reporting no long COVID after adjusting for demographics. There was no difference by age (mean 9.8 vs. 9.7 years, p = 0.93), sex (50% girls vs. 50% boys, p =0.71), or race/ethnicity (25% NHW vs. 25% NHB vs. 37.5% Hispanic, p = 0.25) in terms of decline in physical activity performance. Two children were recommended to delay re-entry into physical activity. CONCLUSIONS: A substantial proportion of ethnically diverse children from low resource backgrounds who had severe COVID illness are reporting long-term impacts on physical activity and cardiorespiratory fitness. Findings can inform pediatricians about this vulnerable population in post-COVID-19 recovery efforts. CLINICAL IMPLICATIONS: Pediatric pulmonologists and other sub-specialists should screen and monitor patients who have had previous severe COVID-19 illness for persistent cardiorespiratory impacts. DISCLOSURES: No relevant relationships by Kubra Melike Bozkanat No relevant relationships by Jackson Francis No relevant relationships by Weiheng He No relevant relationships by Alejandra Lozano No relevant relationships by Matthew Mathew No relevant relationships by Sarah Messiah No relevant relationships by Angela Rabl No relevant relationships by Sumbul shaikH No relevant relationships by Nimisha Srikanth No relevant relationships by Apurva Veeraswamy No relevant relationships by Sitara Weerakoon No relevant relationships by Luyu Xie

10.
Journal of Silk ; 59(5):20-27, 2022.
Article in Chinese | Scopus | ID: covidwho-1934318

ABSTRACT

Polypropylene (PP) nonwoven fabric has good physical and mechanical properties, and the production process is simple and cost is low, so it is widely used in the fields of adsorption and filtration, medical and health care. After the outbreak of COVID-19 pandemic, the market demand for PP nonwovens for medical and health care, such as masks and protective clothing has surged. Nanosilver, with high efficiency and broad-spectrum antibacterial activity, has potential application prospects in the new generation of medical nonwoven materials. However, due to the undiversified macromolecular structure of polypropylene and the lack of polar functional groups on the surface, it is not easy for inorganic antimicrobial agents to hind to PP nonwoven substrates, thus limiting its application and development to a certain extent. Therefore, it is of great practical significance to research and develop PP nonwoven fabric with antibacterial and antiviral properties to achieve long-lasting antibacterial effects. Surface modification methods such as radiation grafting, plasma treatment and chemical etching are commonly used for nonwoven fabric to improve the binding properties of fabrics with antimicrobial agents, but these methods involve harsh treatment conditions and complicated preparation processes. Therefore, this study intends to develop a simple nonwoven modification pathway to enhance the surface binding of inorganic antimicrobial agents to fabrics and achieve sustainability of the antimicrobial effect of PP nonwoven fabric. Dopamine is a low-molecular-weight catecholamine that mimics an adhesion protein and can polymerize spontaneously on various organic-inorganic surfaces to form uniform polydopamine (PDA) films under mild conditions. In addition, the phenolic hydroxyl groups in PDA have redox activity and thus can be used as metal reducing agents. In this paper, inspired by mussel adhesion proteins, PDA coatings were deposited on the surface of PP nonwovens by impregnation using nonwovens with different structures as substrates, and the optimal process conditions for dopamine impregnation were optimally selected using orthogonal tests. Further, nanosilver was generated in situ on the modified PP nonwoven surface by chemical plating method, and the antibacterial PP nonwoven fabric was characterized using FTIR , XRD, SEM, and pore testing. The results showed that the best film formation and coating effect of PDA was achieved when the dopamine concentration was 4 g/L, the pH of the buffer solution was 8.5, and the impregnation time was 24 h. When the amount of PVP was small, irregular silver nanoparticles were easily generated on the fabric surface, and the appropriate amount of PVP could effectively prevent the agglomeration of Ag nanoparticles;when mPVp∗mAKN03 = 1:1, spherical Ag with narrow particle size distribution range and good dispersion was obtained, the antibacterial performance was tested using agar plate diffusion method, and the results showed that 25 g/nr sample fabric after 30 times of water washing. The antibacterial activity of the sample was 74. 22% against influenza A ( HI N1) virus. In this study, an effective antibacterial and potentially antiviral PP nonwoven fabric was prepared based on the surface modification of mussel mimicry, which expands its application in the medical and health care field. © 2022 China Silk Association. All rights reserved.

11.
International Review of Research in Open and Distributed Learning ; 23(2):25-43, 2022.
Article in English | Web of Science | ID: covidwho-1865957

ABSTRACT

Within the COVID-19 pandemic and the new normal period, online learning has become one of the main options for learning. Previous studies on self-regulated learning have shown that it was a better predictor of online learning effectiveness. However, this discussion has not been extended to the situation of the COVID-19 pandemic. To address this gap, this study aims to explore the relationship between the three stages of self-regulated learning (SRL) and learning ineffectiveness (LI). Data of 370 high school students were collected during the period of COVID-19. Structural equation modeling was used to perform confirmatory factor analysis on the data. Findings show that the preparatory stage was positively related to the stages of performance and appraisal, and the performance stage was positively related to the appraisal stage;on the other hand, the stages of performance and appraisal were negatively related to learning ineffectiveness. In addition, the preparatory stage had no direct relation to learning ineffectiveness, but the preparatory stage was correlated with learning ineffectiveness, mediated by the stages of performance and appraisal. These results suggest that better performance in the three stages of self-regulated learning decrease learners' perceived online learning ineffectiveness. This understanding can have implications for global education.

12.
Creativity and Innovation Management ; 2022.
Article in English | Scopus | ID: covidwho-1788836

ABSTRACT

During the corona virus disease of 2019 (COVID-19) pandemic, employees have begun to lack a sense of cognitive detachment from their work. Furthermore, employees with high creativity are better able to help their organizations to survive the economic decline caused by this pandemic. However, scholars currently know relatively little about how and why cognitive detachment influences employee creativity. Leveraging boundary theory and a dual pathway to creativity model (DPCM), the present study hypothesized that cognitive detachment from work will influence employee creativity in an inverse U-shaped pattern, with cognitive flexibility as a mediator and the boundary condition of intrinsic motivation for creativity being included. Our results, which were gained from a sample of 304 research and development (R&D) employees, indicate that employees' cognitive detachment from work and their degree of creativity possess a curvilinear relationship and that cognitive flexibility is a likely mediator between them. Notably, this inverse U-shaped relationship is significant only if the employees have high intrinsic motivation for creativity. This study uncovers the complicated influence of cognitive detachment from work on individual creativity, while also investigating the underlying cognitive processes (i.e., cognitive flexibility) involved and the importance of intrinsic motivation. © 2022 John Wiley & Sons Ltd.

13.
Journal of Virology ; 96(1):11, 2022.
Article in English | Web of Science | ID: covidwho-1756184

ABSTRACT

Over the past 20 years, the severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and SARS-CoV-2 emerged, causing severe human respiratory diseases throughout the globe. Developing broad-spectrum drugs would be invaluable in responding to new, emerging coronaviruses and to address unmet urgent clinical needs. Main protease (Mpro;also known as 3CL(pro)) has a major role in the coronavirus life cycle and is one of the most important targets for anti-coronavirus agents. We show that a natural product, noncovalent inhibitor, shikonin, is a pan-main protease inhibitor of SARS-CoV-2, SARS-CoV, MERS-CoV, human coronavirus (HCoV)-HKU1, HCoV-NL63, and HCoV-229E with micromolar half maximal inhibitory concentration (IC50) values. Structures of the main protease of different coronavirus genus, SARS-CoV from the betacoronavirus genus and HCoV-NL63 from the alphacoronavirus genus, were determined by X-ray crystallography and revealed that the inhibitor interacts with key active site residues in a unique mode. The structure of the main protease inhibitor complex presents an opportunity to discover a novel series of broad-spectrum inhibitors. These data provide substantial evidence that shikonin and its derivatives may be effective against most coronaviruses as well as emerging coronaviruses of the future. Given the importance of the main protease for coronavirus therapeutic indication, insights from these studies should accelerate the development and design of safer and more effective antiviral agents. IMPORTANCE The current pandemic has created an urgent need for broad-spectrum inhibitors of SARS-CoV-2. The main protease is relatively conservative compared to the spike protein and, thus, is one of the most promising targets in developing anticoronavirus agents. We solved the crystal structures of the main protease of SARSCoV and HCoV-NL63 that bound to shikonin. The structures provide important insights, have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational design of broad-spectrum anti-coronavirus ligands as new therapeutic agents.

14.
Open Forum Infectious Diseases ; 8(SUPPL 1):S425, 2021.
Article in English | EMBASE | ID: covidwho-1746396

ABSTRACT

Background. The American Academy of Pediatrics recommends tuberculin skin tests (TSTs) or interferon gamma release assays (IGRAs) to test for tuberculosis (TB) infection in children ≥2 years old, and prioritizes IGRA testing in Bacille Calmette-Guerin vaccine recipients due to cross-reactivity. TSTs require a return visit, which frequently results in loss to follow up. Growing evidence supports accuracy of IGRA testing in pediatric patients, including young children, leading to calls for preferential use of IGRA over TST. We sought to evaluate trends in IGRA use in children over time. Methods. We identified all TB infection tests conducted in children 5-17 years old at 2 academic medical systems in Boston from October 2015-January 2021. TSTs were identified using medication administration records, and IGRAs were identified using laboratory records. We computed the proportion of tests per month that were IGRA and TST. We used Pearson correlation to determine the association between month of testing and proportion of tests that were IGRAs. Results. 21,471 TB infection tests were obtained from 16,778 patients during our timeframe. Median age of testing was 13.4 years (IQR 9.2 - 16.2 years). During the study period, there was a significant increase in the monthly proportion of TB infection tests that were IGRAs (Pearson correlation coefficient 0.92, P < 0.001). The total number of tests performed per month also increased, with seasonal increases in testing in late summer and early fall and a substantial decline in testing early in the COVID-19 pandemic. Tuberculosis infection tests and proportion IGRA. Total number of tuberculosis infection tests per month and proportion of tests that were interferon gamma release assays, from October 2015 - January 2021. Conclusion. Use of IGRAs among patients age 5-17 years of age increased significantly overall and compared to TST in two large Boston healthcare systems over a 5-year period. These results suggest a shift towards blood-based TB infection testing in a low-burden setting, which may improve completion of the pediatric TB infection care cascade. Future research is needed to determine reasons for changing testing modalities, and similar patterns in other settings.

15.
Information Discovery and Delivery ; 49(3):189-192, 2021.
Article in English | Web of Science | ID: covidwho-1691708
16.
Chinese Journal of New Drugs ; 30(22):2029-2033, 2021.
Article in Chinese | Scopus | ID: covidwho-1589974

ABSTRACT

mRNA-based drug has already become a focus as a potential new type of drug in recent years. With the rapidly evolving technologies, mRNA has been widely applied in various areas of clinical research, such as immune disease, oncological disease, infectious disease, and congenital metabolic disorder. Since the outbreak of COVID-19, there has been a great leap in mRNA vaccine development, forecasting that much more mRNA medicines will enter the market in the near future. In order to meet industrial requirements, this article provides an overview of the product profiles of mRNA-based drugs and their industrial landscape, and further discusses the key considerations in the manufacturing of such medicines. © 2021, Chinese Journal of New Drugs Co. Ltd. All right reserved.

17.
Electronic Library ; 2021.
Article in English | Scopus | ID: covidwho-1541633

ABSTRACT

Purpose: COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective. Design/methodology/approach: The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods. Findings: Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media. Research limitations/implications: This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study. Originality/value: This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention. © 2021, Emerald Publishing Limited.

18.
Journal of Building Engineering ; 44:6, 2021.
Article in English | Web of Science | ID: covidwho-1482735

ABSTRACT

Respiratory supporting, as an important medical treatment for new coronavirus pneumonia patients, must be effectively guaranteed by medical oxygen supply. However, the medical oxygen system designed and configured by the existing hospitals according to the current specifications cannot meet the oxygen needs for patients with new coronavirus pneumonia. This paper aimed to study the design of medical oxygen system in new coronavirus pneumonia emergency hospital. By investigating the oxygen treatment plan for the novel coronavirus pneumonia patients in the health emergency hospital, the oxygen treatment characteristics of different patients were studied. The oxygen characteristics of different respiratory support terminals were explored to study the oxygen demands of new coronavirus pneumonia emergency hospitals. Through calculating flow rates of medical gas system air source referring to 'technical code for medical gases engineering', the proportion coefficient of severe patients converted into respiratory distress patients was introduced, and the model of calculating flow rates of medical oxygen system air source in emergency hospital was proposed. The cases were verified in a typical health emergency hospital that the developed calculation flow model of medical oxygen source met the demands of hospital oxygen. The outcomes provide a reference for the design and construction of medical oxygen in such health emergency hospitals.

19.
Annals of Epidemiology ; 61:17-17, 2021.
Article in English | Academic Search Complete | ID: covidwho-1401174
20.
JMIR Formative Research ; 5(4):e22983, 2021.
Article in English | MEDLINE | ID: covidwho-1208606

ABSTRACT

BACKGROUND: Strict social distancing measures owing to the COVID-19 pandemic have led people to rely more heavily on social media, such as Facebook groups, as a means of communication and information sharing. Multiple Facebook groups have been formed by medical professionals, laypeople, and engineering or technical groups to discuss current issues and possible solutions to the current medical crisis. OBJECTIVE: This study aimed to characterize Facebook groups formed by laypersons, medical professionals, and technical professionals, with specific focus on information dissemination and requests for crowdsourcing. METHODS: Facebook was queried for user-created groups with the keywords "COVID," "Coronavirus," and "SARS-CoV-2" at a single time point on March 31, 2020. The characteristics of each group were recorded, including language, privacy settings, security requirements to attain membership, and membership type. For each membership type, the group with the greatest number of members was selected, and in each of these groups, the top 100 posts were identified using Facebook's algorithm. Each post was categorized and characterized (evidence-based, crowd-sourced, and whether the poster self-identified). STATA (version 13 SE, Stata Corp) was used for statistical analysis. RESULTS: Our search yielded 257 COVID-19-related Facebook groups. Majority of the groups (n=229, 89%) were for laypersons, 26 (10%) were for medical professionals, and only 2 (1%) were for technical professionals. The number of members was significantly greater in medical groups (21,215, SD 35,040) than in layperson groups (7623, SD 19,480) (P<.01). Medical groups were significantly more likely to require security checks to attain membership (81% vs 43%;P<.001) and less likely to be public (3 vs 123;P<.001) than layperson groups. Medical groups had the highest user engagement, averaging 502 (SD 633) reactions (P<.01) and 224 (SD 311) comments (P<.01) per post. Medical professionals were more likely to use the Facebook groups for education and information sharing, including academic posts (P<.001), idea sharing (P=.003), resource sharing (P=.02) and professional opinions (P<.001), and requesting for crowdsourcing (P=.003). Layperson groups were more likely to share news (P<.001), humor and motivation (P<.001), and layperson opinions (P<.001). There was no significant difference in the number of evidence-based posts among the groups (P=.10). CONCLUSIONS: Medical professionals utilize Facebook groups as a forum to facilitate collective intelligence (CI) and are more likely to use Facebook groups for education and information sharing, including academic posts, idea sharing, resource sharing, and professional opinions, which highlights the power of social media to facilitate CI across geographic distances. Layperson groups were more likely to share news, humor, and motivation, which suggests the utilization of Facebook groups to provide comedic relief as a coping mechanism. Further investigations are necessary to study Facebook groups' roles in facilitating CI, crowdsourcing, education, and community-building.

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