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1.
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi ; 57(6): 774-777, 2022 Jun 07.
Article in Chinese | MEDLINE | ID: covidwho-1903516
3.
Modern Pathology ; 35(SUPPL 2):385-386, 2022.
Article in English | EMBASE | ID: covidwho-1857880

ABSTRACT

Background: With COVID-19 restrictions remaining in place for the past year in Ontario, Canada, we have integrated weekly virtual gross rounds (VGR) as a part of regular post-graduate training since May 2020. We used Zoom (Zoom Video Communication, San Jose, CA USA) to livestream our rounds and maintained a steady attendance and interest. In addition to resident trainees, our VGR sessions are now attended by residents, staff, and pathologists' assistants (PA), PA students and medical laboratory technologists at community and academic institutions throughout Canada. We aimed to evaluate whether a virtual platform could maintain an engaging learning community in pathology. Specifically, we sought to identify the key elements and tools within a virtual format, as well as the attitudes of our learners, that were most conducive to virtual learning and building a pathology learning community for residents and PAs. Design: Surveys were sent to 237 registered participants of VGR at 12 months from the start of VGR. Residents and PA respondents were asked to rate their overall experience and rank the perceived effectiveness of VGR on pathology community building. In addition, survey participants ranked the least and most effective virtual engagement tools used during the sessions. Results: 78 participants completed the survey, a response rate of 33%. Both residents (n=21) and PAs (n=49) had an overall positive reception of VGR (average score 4.4/5) during this time. The tools which enhanced a sense of learning community were ranked from most to least useful (Table 1). Our participants identified the polls and chats as the most effective ways of engaging with each other. Most participants agreed or strongly agreed that VGR was effective at creating an online learning community as well as building interprofessional connections among residents and PAs (Figure 1 and 2). The availability of archived, edited, and interactive video recordings of the VGR sessions was identified as an important resource for learning. Conclusions: We report continued positive perception of virtual gross pathology learning among our residents and PA attendees. Specifically, we highlight the role of virtual learning in building a gross pathology learning community in Canada. We identified the ideal tools and techniques that are most helpful in engaging learners and sustaining an online community.

4.
International Journal of Electrochemical Science ; 17, 2022.
Article in English | Scopus | ID: covidwho-1847942

ABSTRACT

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV CoV-2) pathogen and protein biomarkers can improve the diagnosis accuracy for Coronavirus disease 2019 (COVID-19). Electrochemical biosensors have attracted extensive attention in the scientific community because of their simple design, fast response, good portability, high sensitivity and high selectivity. In this review, we summarized the progress in the electrochemical detection of COVID-19 pathogen and SARS-CoV-2 biomarkers, including SARS-CoV-2 spike protein and nucleocapsid protein and their antibodies. © 2022. The Authors. Published by ESG. All Rights Reserved.

5.
2021 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2021 ; : 641-646, 2021.
Article in English | Scopus | ID: covidwho-1832578

ABSTRACT

Since the spread of COVID-19 around the world, a series of policies and measures are adopted by the Japanese government to control the epidemic. As a result of these policies, people's daily life and the functional division of society have changed. In order to understand the changes in urban function and people's daily behavior over the past year, we collected and analyzed over 1.13 million social media data (Twitter in our example) containing geographic information. We propose regional competitiveness, which represents the access frequency of social data in each raster unit to several attributes. In order to analyze the regional competitiveness in different categories and map tiles, we applied an improved spatio-temporal graph attention network model (ST-GAT) based on unstructured POI (point of interest) data and Twitter data in different levels of the map to the city-regional competitiveness. We have developed and evaluated the competitiveness map tiles based on 5 attributes utilized Twitter data at 2020 of Kyoto in Japan. As the spread of COVID-19 disease and government anti-epidemic measures change the frequency of visits to the core of the city and the trend of regional competitiveness, and our results showed that the regional competitiveness in the map tiles obtained by social media data and POI data visualizes the dynamic change analysis of crowd behavior activities and urban social functions. This research enlightens the promising future of spatio-temporal GAT in users' dynamic responses with geographic information. © 2021 ACM.

6.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334871

ABSTRACT

The emerging SARS-CoV-2 variants of concern (VOCs) exhibit enhanced transmission and immune escape, reducing the efficacy and effectiveness of the two FDA-approved mRNA vaccines. Here, we explored various strategies to develop novel mRNAs vaccines to achieve safer and wider coverage of VOCs. Firstly, we constructed a cohort of mRNAs that feature a furin cleavage mutation in the spike (S) protein of predominant VOCs, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2). Not present in the mRNA vaccines currently in use, the mutation abolished the cleavage between the S1 and S2 subunits, potentially enhancing the safety profile of the immunogen. Secondly, we systematically evaluated the induction of neutralizing antibodies (nAb) in vaccinated mice, and discovered that individual VOC mRNAs elicited strong neutralizing activity in a VOC-specific manner. Thirdly, the IgG produced in mice immunized with Beta-Furin and Washington (WA)-Furin mRNAs showed potent cross-reactivity with other VOCs, which was further corroborated by challenging vaccinated mice with the live virus of VOCs. However, neither WA-Furin nor Beta-Furin mRNA elicited strong neutralizing activity against the Omicron variant. Hence, we further developed an Omicron-specific mRNA vaccine that restored protection against the original and the sublineages of Omicron variant. Finally, to broaden the protection spectrum of the new Omicron mRNA vaccine, we tested the concept of bivalent immunogen. Instead of just fusing two RBDs head-to-tail, we for the first time constructed an mRNA-based chimeric immunogen by introducing the RBD of Delta variant into the entire S antigen of Omicron. The resultant chimeric mRNA was capable of inducing potent and broadly acting nAb against Omicron (both BA.1 and BA.2) and Delta, which paves the way to develop new vaccine candidate to target emerging variants in the future.

7.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-334725

ABSTRACT

With the emergence of SARS-CoV-2 variants, there is urgent need to develop broadly neutralizing antibodies. Here, we isolate two V H H nanobodies (7A3 and 8A2) from dromedary camels by phage display, which have high affinity for the receptor-binding domain (RBD) and broad neutralization activities against SARS-CoV-2 and its emerging variants. Cryo-EM complex structures reveal that 8A2 binds the RBD in its up mode and 7A3 inhibits receptor binding by uniquely targeting a highly conserved and deeply buried site in the spike regardless of the RBD conformational state. 7A3 at a dose of a5 mg/kg efficiently protects K18-hACE2 transgenic mice from the lethal challenge of B.1.351 or B.1.617.2, suggesting that the nanobody has promising therapeutic potentials to curb the COVID-19 surge with emerging SARS-CoV-2 variants. ONE-SENTENCE SUMMARY: Dromedary camel ( Camelus dromedarius ) V H H phage libraries were built for isolation of the nanobodies that broadly neutralize SARS-CoV-2 variants.

8.
Zhonghua Kou Qiang Yi Xue Za Zhi ; 57(5): 455-461, 2022 May 09.
Article in Chinese | MEDLINE | ID: covidwho-1818247

ABSTRACT

Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.


Subject(s)
COVID-19 , Oral Medicine , Consensus , Humans , Oral Health
9.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333772

ABSTRACT

BACKGROUND: The first confirmed case of SARS-CoV-2 in North America was identified in Washington state on January 21, 2020. We aimed to quantify the number and temporal trends of out-of-state introductions of SARS-CoV-2 into Washington. METHODS: We conducted a phylogenetic analysis of 11,422 publicly available whole genome SARS-CoV-2 sequences from GISAID sampled between December 2019 and September 2020. We used maximum parsimony ancestral state reconstruction methods on time-calibrated phylogenies to enumerate introductions/exports, their likely geographic source (e.g. US, non-US, and between eastern and western Washington), and estimated date of introduction. To incorporate phylogenetic uncertainty into our estimates, we conducted 5,000 replicate analyses by generating 25 random time-stratified samples of non-Washington reference sequences, 20 random polytomy resolutions, and 10 random resolutions of the reconstructed ancestral state. RESULTS: We estimated a minimum 287 separate introductions (median, range 244-320) into Washington and 204 exported lineages (range 188-227) of SARS-CoV-2 out of Washington. Introductions began in mid-January and peaked on March 29, 2020. Lineages with the Spike D614G variant accounted for the majority (88%) of introductions. Overall, 61% (range 55-65%) of introductions into Washington likely originated from a source elsewhere within the US, while the remaining 39% (range 35-45%) likely originated from outside of the US. Intra-state transmission accounted for 65% and 28% of introductions into eastern and western Washington, respectively. CONCLUSIONS: There is phylogenetic evidence that the SARS-CoV-2 epidemic in Washington is continually seeded by a large number of introductions, and that there was significant inter- and intra-state transmission. Due to incomplete sampling our data underestimate the true number of introductions.

10.
16th International Conference on Ubiquitous Information Management and Communication, IMCOM 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1788734

ABSTRACT

With the COVID-19 pandemic, maintaining social distancing is particularly important in daily life. In recently, indoor situations such as face-to-face teaching for university restart are tried to make feasible suggestions depend on the spread of the COVID-19. In this research, we analyze and forecast the COVID-19 spreading curve of the resumption of in-person classes at university by the graph structure with the spread weight of edges based on each student's relation. Our approach is based on the effectiveness of three distancing strategies designed to keep the curve flat and aid make the spread of the COVID-19 controllable. By detecting the possibility of student relation by three strategies, we can analyze the COVID-19 spreading curve by Graph Neural Network(GNN) and SIR model. The SIR model is a simple model that considers a population that belongs to one of the following states: Susceptible (S), Infected (I), and Recovered (R), and we calculate the contagion rate of the pathogen. In this article, we discuss two types of Open Group and Closed Group on university campuses and analyze face-to-face lectures, indoor social activities, and campus cafeterias. To verify the effectiveness of our two types of group, we simulated with the random infection curve by graph neural network model. The simulation analysis results show that our social distancing strategies can reduce the risk of COVID-19 transmission after school restarts. © 2022 IEEE.

11.
2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022 ; : 121-128, 2022.
Article in English | Scopus | ID: covidwho-1788621

ABSTRACT

As the reopening of the university after the spread of COVID-19 on campus and we simulate and visualize the initial states spreading of COVID-19. In this research, we analyze and forecast the COVID-19 spreading curve of the resumption of in-person classes at university by the graph structure with the spread weight of edges based on each student's relation. Our approach is based on the effectiveness of three distancing strategies designed to keep the curve flat and aid make the spread of the COVID-19 controllable. By detecting the possibility of student relation based on three strategies, we can analyze the COVID-19 spreading curve by Graph Neural Network (GNN) and SIR model. In this article, we discuss two types of Open Group and Closed Group on university campuses and analyze face-to-face lectures, indoor social activities, and campus cafeterias. To verify the effectiveness of our two types of group, we simulated with the random infection curve by graph neural network model. At last, we visualized the COVID-19 spreading process and the results of diffusion prediction. © 2022 IEEE.

12.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(3): 355-359, 2022 Mar 06.
Article in Chinese | MEDLINE | ID: covidwho-1776391

ABSTRACT

This study aimed to explore the application value of new biological specimen oral fluid in SARS-CoV-2 nucleic acid and antibody detection. Oral fluid and paired respiratory and blood specimens from 7 confirmed cases of two COVID-19 cluster epidemic were collected in Beijing from October to November 2021. SARS-CoV-2 virus and IgG antibody were detected by real time PCR kits and serum antibody detection reagents, and SARS-CoV-2 IgG antibody in oral fluids was detected by a new established method of magnetic particle chemiluminescence. The results showed that the nucleic acid amplification test of SARS-CoV-2 on nasopharyngeal swabs, throat swabs and oral fluid specimens from 3 confirmed cases of COVID-19 was positive, among which the Ct value for ORF1a/b and N gene of oral fluid samples in 2 cases was close to that of throat swab, and the Ct value of oral fluid sample for 1 case was higher than that of throat swab. The complete genome sequence of one oral fluid specimen was obtained, which belonged to the VOC/Delta variant strain. The SARS-CoV-2 IgG antibodies of the paired oral fluid and serum were all positive, and the S/CO values of oral fluid were all lower than those of serum. The series of oral fluid results showed that SARS-CoV-2 IgG antibody level increased from 11 to 32 days after the onset of the disease.


Subject(s)
COVID-19 , Nucleic Acids , COVID-19/diagnosis , Humans , SARS-CoV-2 , Sensitivity and Specificity
13.
Open Forum Infectious Diseases ; 8(SUPPL 1):S553, 2021.
Article in English | EMBASE | ID: covidwho-1744149

ABSTRACT

Background. Respiratory virus infections are associated with significant and specific local and systemic inflammatory response patterns, which may lead to reactivation of latent viruses. We examined whether viral upper (URTI) or lower respiratory tract infection (LRTI) with common respiratory viruses increased the risk of CMV viremia after allogeneic hematopoietic cell transplantation (HCT). Methods. We retrospectively analyzed patients undergoing allogeneic HCT between 4/2008 and 9/2018. CMV surveillance was performed weekly and the presence of upper and lower respiratory symptoms were evaluated by multiplex respiratory viral PCR. We used Cox proportional hazards models to evaluate risk factors for development of any CMV viremia or high level CMV viremia in the first 100 days post-HCT. Each respiratory virus infection episode was considered positive for 30 days beginning the day of diagnosis. Results. Among 2,545 patients (404 children, 2141 adults), 1,221 and 247 developed CMV viremia and high level CMV viremia, respectively, in the first 100 days post-HCT. Infections due to human rhinoviruses (HRV, N=476) were most frequent, followed by parainfluenza viruses 1-4 (PIV, N=139), seasonal human coronaviruses (COV, N=134), respiratory syncytial virus (RSV, N=77), influenza A/B (FLU, N=35), human metapneumovirus (MPV, N=37), and adenovirus (ADV, N=61). In adjusted models, RSV LRTI was associated with increased risk of developing CMV viremia at all levels (Figures 1 and 2), and PIV or RSV URTI increased the risk of high level CMV viremia;all other viruses showed no association in univariable models. Figure 1. Model estimates for associations between LRTI and development of any CMV viremia Figure 2. Model estimates for associations between LRTI and development of high level CMV viremia Conclusion. We demonstrated that RSV and PIV infections are associated with an increased risk for development of CMV viremia after allogeneic HCT. This novel association provides the rationale to explore virus-specific inflammatory pathways that may trigger CMV reactivation. CMV viremia may also serve as an endpoint in clinical trials that assess new preventative or therapeutic interventions of RSV or PIV infection.

15.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-329057

ABSTRACT

Background: The COVID-19 pandemic is dominated by variant viruses;the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. Methods: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. Findings: 58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages;Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. Conclusion: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. Summary: Hospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

16.
2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020 ; 2020.
Article in English | Scopus | ID: covidwho-1706502

ABSTRACT

Computed tomography (CT) of COVID-19 manifests a relatively global effect through the whole lungs, like peripheral ground glass, consolidation, reticular pattern, nodules etc. This characteristic effect renders the difficulties in differentiating COVID-19 from the normal body or other lung diseases by CT. This work presents a novel method to relieve the difficulties by reducing the global effect through the 3D whole lung volume into 2D-like domain. The hypothesis is that the lung tissue shares the similar anatomic structure within a small lung sub-volume for normal subjects. Therefore, the anatomic land-markers along the z-axis, denoted as Lung Marks are used to eliminate axial variable. Our experiments indicated that 30 Lung Marks are sufficient to eliminate the axial variable. The method computes texture measures from each 2D-like volumetric data and maps the measures on to the corresponding Lung Mark, resulting in a profile along the z-axis. The difference of the profiles between two different abnormalities is the proposed sensitive merit to differentiate COVID-19 cases from others in CT images. 48 COVID-19 cases and 48 normal screening cases were used to test the effectiveness of the proposed sensitive merit. Intensity and gradient based texture descriptors were computed from each axial cross image at the corresponding Lung Mark along the z-axis. Euclidean, Jaccard and Dice distances are calculated to generate the profiles of the proposed sensitive merit. Consistent results are observed across texture descriptor types and distance types in the texture measure between the normal and COVID-19 subjects. Uneven Profiles demonstrate the variation along the z-axis. With Lung Mark, the variation of texture descriptor has been reduced prominently. The Gradient based descriptor is more sensitive. Individual Haralick features analysis shows the 2nd and 10th dimensions are most distinguishable. © 2020 IEEE

17.
MEDLINE;
Preprint in English | MEDLINE | ID: ppcovidwho-326567

ABSTRACT

Since its emergence and detection in Wuhan, China in late 2019, the novel coronavirus SARS-CoV-2 has spread to nearly every country around the world, resulting in hundreds of thousands of infections to date. The virus was first detected in the Pacific Northwest region of the United States in January, 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the U.S., we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated impacts of federal travel restrictions. This study provides evidence for widespread, sustained transmission of SARS-CoV-2 within the U.S. and highlights the critical need for local surveillance.

18.
PUBMED; 2021.
Preprint in English | PUBMED | ID: ppcovidwho-293066

ABSTRACT

Background: The COVID-19 pandemic is now dominated by variant lineages;the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the risk of hospitalization following infection with nine variants of concern or interest (VOC/VOI). Methods: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System and with available viral genome data, from December 1, 2020 to July 30, 2021. The main analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for the risk of hospitalization following infection with a VOC/VOI, adjusting for age, sex, and vaccination status. Findings: Of the 23,563 cases, 22,068 (93.7%) were sequenced through sentinel surveillance, of which 582 (2.6%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.23, 95% CI 2.19-4.76), Beta (HR 3.03, 95% CI 1.68-5.47), Delta (HR 2.35, 95% CI 1.72-3.22), and Alpha (HR 1.61, 95% CI 1.28-2.03) compared to infections with an ancestral lineage. Following VOC infection, unvaccinated patients show a similar higher hospitalization risk, while vaccinated patients show no significant difference in risk, both when compared to unvaccinated, ancestral lineage cases. Interpretation: Infection with a VOC results in a higher hospitalization risk, with an active vaccination attenuating that risk. Our findings support promoting hospital preparedness, vaccination, and robust genomic surveillance.

19.
PUBMED; 2021.
Preprint in English | PUBMED | ID: ppcovidwho-292966

ABSTRACT

With the emergence of SARS-CoV-2 variants, there is urgent need to develop broadly neutralizing antibodies. Here, we isolate two V H H nanobodies (7A3 and 8A2) from dromedary camels by phage display, which have high affinity for the receptor-binding domain (RBD) and broad neutralization activities against SARS-CoV-2 and its emerging variants. Cryo-EM complex structures reveal that 8A2 binds the RBD in its up mode and 7A3 inhibits receptor binding by uniquely targeting a highly conserved and deeply buried site in the spike regardless of the RBD conformational state. 7A3 at a dose of a5 mg/kg efficiently protects K18-hACE2 transgenic mice from the lethal challenge of B.1.351 or B.1.617.2, suggesting that the nanobody has promising therapeutic potentials to curb the COVID-19 surge with emerging SARS-CoV-2 variants. One-Sentence Summary: Dromedary camel ( Camelus dromedarius ) V H H phage libraries were built for isolation of the nanobodies that broadly neutralize SARS-CoV-2 variants.

20.
29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021 ; : 423-426, 2021.
Article in English | Scopus | ID: covidwho-1528578

ABSTRACT

COVID-19 has brought about substantial social, economic and health related burdens, motivating different control measures from policy makers worldwide. Contact tracing plays a pivotal role in the COVID-19 era. However, contact tracing is by nature entirely retrospective: it can only identify contacts of known or suspected cases. Our proposed system is prospective, aiming to 'create' networks that will ultimately make contact tracing and pandemic management easier. As contact tracing seeks to reconstruct the underlying interaction network, we can improve the process by reducing the complexity of contact network structure;we introduce a method for reducing contact network complexity through strategic scheduling. The method functions through pairwise comparison of individual trajectories in a coordinate space of activities, locations, and time intervals. We demonstrate the method through a simulated scenario where individuals (students) register for activities using a mobile application in a campus. The application then applies our algorithm to provide individuals with schedules that reduce the complexity of the overall network, without compromising individual privacy. © 2021 Owner/Author.

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