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1.
Nature Machine Intelligence ; : 17, 2022.
Article in English | Web of Science | ID: covidwho-1886237

ABSTRACT

B-cell receptors (BCRs) and their impact on B cells play a vital role in our immune system;however, the manner in which B cells are activated by BCRs are still poorly understood. Ze Zhang and colleagues present a graph-based method that connects BCR and single B-cell RNA sequencing data and identifies notable coupling between BCR and B-cell expression in COVID-19. B-cell receptors (BCRs) are a crucial player in the development and activation of B cells, and their mature forms are secreted as antibodies, which execute functions such as the neutralization of invading pathogens. All current analytical approaches for BCRs solely investigate the BCR sequences and ignore their correlations with the transcriptomics of the B cells, yielding conclusions of unknown functional relevance regarding the roles of BCRs and B cells, and could generate biased interpretation. Many single-cell RNA-sequencing (scRNA-seq) techniques can now capture both the gene expression and BCR of each B cell, which could potentially address this issue. Here, we investigated 43,938 B cells from 13 scRNA-seq datasets with matched scBCR sequencing, and we observed an association between the BCRs and the B cells' transcriptomics. Motivated by this, we developed the Benisse model (BCR embedding graphical network informed by scRNA-seq) to provide refined analyses of BCRs guided by single-cell gene expression. Benisse revealed a gradient of B-cell activation along BCR trajectories. We discovered a stronger coupling between BCRs and B-cell gene expression during COVID-19 infections. We found that BCRs form a directed pattern of continuous and linear evolution to achieve the highest antigen targeting efficiency, compared with the convergent evolution pattern of T-cell receptors. Overall, a simultaneous digestion of the BCR and gene expression of B cells, viewed through the lens of Benisse, will lead to a more insightful interpretation of the functional relevance of the BCR repertoire in different biological contexts.

2.
12th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP) ; : 52-55, 2021.
Article in English | English Web of Science | ID: covidwho-1883137

ABSTRACT

The outbreak of COVID-19 calls for the improvement of infectious disease dynamics model to meet the requirements of future infectious disease's prediction and risk assessment. On the basis of SEIR model, a new transmission dynamics model named as SSEIR is proposed. In order to describe the dynamics evolution of the SSEIR model, a new set of ordinary differential equations (ODE) is constructed. The SSEIR dynamics model is used to simulate and predict the progress of pandemic situation inWuhan, China. Because that the suspected people have different dynamics characteristics from the susceptible people and the exposed people, this paper put them in a new independent category. To describe the dynamics evolution of SSEIR model, a new set of ordinary differential equations (ODE) is constructed. The SSEIR model can be used to simulate and predict the progress of infectious diseases.

3.
American Journal of Respiratory and Critical Care Medicine ; 205:1, 2022.
Article in English | English Web of Science | ID: covidwho-1880965
6.
Zhonghua Er Ke Za Zhi ; 60(6): 539-544, 2022 Jun 02.
Article in Chinese | MEDLINE | ID: covidwho-1879501

ABSTRACT

Objective: To understand the clinical characteristics of children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region. Methods: This retrospective study was conducted to collect the data including clinical manifestations, outcomes and vaccination of 107 children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region to be admitted to the designated referral hospital in Shanghai from February to March 2022. According to the occurrence of clinical symptoms, the cases were divided into asymptomatic group and symptomatic group. According to the age of diagnosis, the cases were divided into <3 years group, 3-<6 years group and 6-<18 years group, and the clinical manifestations in different age group were analyzed with t-test and Mann-Whitney rank-sum test. Besides, to analyze the effectiveness of vaccination against SARS-CoV-2 Omicron infection in different age group, the cases aged 3-<18 years were also subdivided into unvaccinated group, 1-dose group and 2-dose group, and the relative risk (RR) was used to demonstrate the effectiveness. Results: Among the 107 cases, 66 were male and 41 were female, with infection age of 10 (5, 14) years. There were 29 cases in the asymptomatic group, and 78 cases in the symptomatic group, and no significant difference in the age of infection was observed between the 2 groups (11 (6, 14) vs. 10 (5, 14) years, Z=0.49, P>0.05). And there were no severe cases in symptomatic group. The length of hospitalization was (18±6) days, and was longer in symptomatic group than that in asymptomatic group ((19±6) vs. (16±7) d, t=0.17, P=0.030). Eight-two cases (76.6%) had a history of epidemiological exposure and, among whom, 81 cases (75.7%) were associated with household transmission. Among symptomatic group, 57 cases (73.1%) had fever and 20 cases (25.6%) had cough. Of the 74 cases undergoing chest CT examination, 17 cases (23.0%) showed mild abnormalities. Of the 83 cases who received the lab tests, 23 cases (27.7%) had white blood cell counts<4×109/L, 3 cases (3.6%) had C-reaction protein >8.0 mg/L, and 6 cases (7.2%) had slightly elevated aspartate transaminase and alanine aminotransferase. Among the 92 children aged 3-<18 years, 31 cases were unvaccinated, 34 cases received 1 dose, and 27 cases received 2 doses. The interval between the last vaccination and infection was 2.2 (0.6, 6.0) months; the interval between the last vaccination and infection in the 2-dose group was longer than that in 1-dose group (6.0 (4.5, 7.3) vs. 0.7 (0.3,2.0) months, Z=3.59, P<0.001).The risk of symptomatic infection was reduced by 45% (RR=0.55, 95% CI 0.35-0.87) with two-dose vaccination compared to non-vaccination in cases aged 3-<18 years. All these cases recovered completely. Conclusions: Children infected with SARS-CoV-2 Omicron are usually mild or asymptomatic. Household transmission is the main pattern of infection with SARS-CoV-2 Omicron in children. Two-dose SARS-CoV-2 vaccination in children aged 3-<18 years can provide partial protection against disease caused by SARS-CoV-2 Omicron.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19 Vaccines , Child , China/epidemiology , Female , Hong Kong/epidemiology , Humans , Male , Retrospective Studies
7.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-338229

ABSTRACT

The Omicron BA.2 variant has become a dominant infective strain worldwide. Receptor binding studies reveal that the Omicron BA.2 spike trimer have 11-fold and 2-fold higher potency to human ACE2 than the spike trimer from the wildtype (WT) and Omicron BA.1 strains. The structure of the BA.2 spike trimer complexed with human ACE2 reveals that all three receptor-binding domains (RBDs) in the spike trimer are in open conformation, ready for ACE2 binding, thus providing a basis for the increased infectivity of the BA.2 strain. JMB2002, a therapeutic antibody that was shown to have efficient inhibition of Omicron BA.1, also shows potent neutralization activities against Omicron BA.2. In addition, both BA.1 and BA.2 spike trimers are able to bind to mouse ACE2 with high potency. In contrast, the WT spike trimer binds well to cat ACE2 but not to mouse ACE2. The structures of both BA.1 and BA.2 spike trimer bound to mouse ACE2 reveal the basis for their high affinity interactions. Together, these results suggest a possible evolution pathway for Omicron BA.1 and BA.2 variants from human-cat-mouse-human circle, which could have important implications in establishing an effective strategy in combating viral infection.

8.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-338077

ABSTRACT

Purpose: In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. Methods: A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. Results: Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). Conclusion: Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

9.
2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2022 ; : 62-65, 2022.
Article in English | Scopus | ID: covidwho-1874335

ABSTRACT

Although both face recognition and object inpainting have become promising approaches through the use of deep learning, the COVID-19 pandemic has created a tremendous challenge to their further development. Masks, which people have become accustomed to as an effective sanitary measure to prevent infection of COVID-19, have also become an undeniable physical barrier between devices applying face recognition authentication and the faces to be recognized. Therefore, methods that can overcome this dilemma are urgently needed. This study proposes a method that applies a generative model to recognize masked faces based on face inpainting. We introduced a newly proposed identity loss term to conform to the identity information. The reconstructed face will be fed into a face recognition network to extract the feature embeddings for a distance comparison. Taking a naive generative model without an identity loss term introduced as the baseline, the model with an identity loss term improves the recognition accuracy by more than 4%. © 2022 IEEE.

10.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-337382

ABSTRACT

Children typically experience more mild symptoms of COVID-19 when compared to adults. There is a strong body of evidence that children are also less susceptible to SARS-CoV-2 infection with the ancestral viral isolate. However, the emergence of SARS-CoV-2 variants of concern (VOCs) has been associated with an increased number of pediatric infections. Whether this is the result of widespread adult vaccination or fundamental changes in the biology of SARS-CoV-2 remains to be determined. Here, we use primary nasal epithelial cells from children and adults, differentiated at an air-liquid interface to show that the ancestral SARS-CoV-2 replicates to significantly lower titers in the nasal epithelial cells of children compared to those of adults. This was associated with a heightened antiviral response to SARS-CoV-2 in the nasal epithelial cells of children. Importantly, the Delta variant also replicated to significantly lower titres in the nasal epithelial cells of children. This trend was markedly less pronounced in the case of Omicron. It is also striking to note that, at least in terms of viral RNA, Omicron replicated better in pediatric NECs compared to both Delta and the ancestral virus. Taken together, these data show that the nasal epithelium of children supports lower infection and replication of ancestral SARS-CoV-2, although this may be changing as the virus evolves.

11.
View ; : 7, 2022.
Article in English | Web of Science | ID: covidwho-1850257

ABSTRACT

The outbreak of coronavirus disease 2019 (COVID-19, caused by SARS-Cov-2) is a big challenge for global health systems and the economy. Rapid and accurate tests are crucial at early stages of this pandemic. Reverse transcription-quantitative real-time polymerase chain reaction is the current gold standard method for detection of SARS-Cov-2. It is impractical and costly to test individuals in large-scale population screens, especially in low- and middle-income countries due to their shortage of nucleic acid testing reagents and skilled staff. Accordingly, sample pooling, such as for blood screening for syphilis, is now widely applied to COVID-19. In this paper, we survey and review several different pooled-sample testing strategies, based on their group size, prevalence, testing number, and sensitivity, and we discuss their efficiency in terms of reducing cost and saving time while ensuring sensitivity.

13.
Chinese Pharmaceutical Journal ; 57(6):428-452, 2022.
Article in Chinese | Scopus | ID: covidwho-1847717

ABSTRACT

OBJECTIVE: Isatidis Radix is the dried root of Isatis indigotica Fortune of Cruciferae. As a representative traditional Chinese medicine for heat-clearing and detoxification, Isatidis Radix and its preparations are widely used in the prevention and treatment of all kinds of colds and have played an active role in the prevention and treatment of SARS, H1N1 and COVID-19. Although the chemical ingredient of Isatidis Radix has been studied deeply, there is no information bank, website or literature that can comprehensively query the information of all compounds at home and abroad, which is not conducive to the development of related research. So establishment of the chemical composition information bank is in need. METHODS: According to the category of chemical ingredients, the Chinese and English names, molecular formulas, exact molecular weights, structural formulas and references of nearly 400 chemical components in Isatidis Radix were comprehensively sorted out, and the chemical composition information bank of Isatidis Radix was constructed. RESULTS: By September 2020, a total of 392 compounds in 17 categories had been extracted, isolated and identified from Isatidis Radix. CONCLUSIONT: The established chemical composition information bank can provide the basis for the separation and identification of chemical components, quality control, material basis mining, network pharmacology research and so on. Copyright 2022 by the Chinese Pharmaceutical Association.

15.
Drugs and Clinic ; 37(3):653-658, 2022.
Article in Chinese | Scopus | ID: covidwho-1838080

ABSTRACT

Artemisinin, extracted from the traditional Chinese medicine Artemisia annua Linn., has a powerful antimalarial effect. With further research, artemisinin and its derivatives have been found to have antiviral effects against a variety of viruses from different viral families, including Herpesviridae, Flaviridae, and Coronaviraceae, and can inhibit virus-induced inflammatory responses. The possible antiviral mechanisms include alkylation of DNA binding domain of NF-κB P65 subunit, inhibition of plasmidic nuclear transport of NF-κB p65, production of reactive oxygen species or activation of carbon center free radicals to regulate host Keap1/Nrf2/ARE pathway to inhibit viral replication. The inflammatory response was alleviated by inhibiting the activation of NF-κB and ERK pathways induced by the virus. This paper reviews the possible antiviral mechanism of artemisinin and its derivatives to provide reference for artemisinin to fight new viruses and promote new use of old drugs. © 2022 by the authors.

16.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

17.
Acm Journal of Data and Information Quality ; 14(2):24, 2022.
Article in English | Web of Science | ID: covidwho-1819938

ABSTRACT

Aspect-level sentiment analysis identifies fine-grained emotion for target words. There are three major issues in current models of aspect-level sentiment analysis. First, few models consider the natural language semantic characteristics of the texts. Second, many models consider the location characteristics of the target words, but ignore the relationships among the target words and among the overall sentences. Third, many models lack transparency in data collection, data processing, and results generating in sentiment analysis. In order to resolve these issues, we propose an aspect-level sentiment analysis model that combines a bidirectional Long Short-Term Memory (LSTM) network and a Graph Convolutional Network (GCN) based on Dependency syntax analysis (Bi-LSTM-DGCN). Our model integrates the dependency syntax analysis of the texts, and explicitly considers the natural language semantic characteristics of the texts. It further fuses the target words and overall sentences. Extensive experiments are conducted on four benchmark datasets, i.e., Restaurantl4, Laptop, Restaurantl6, and Twitter. The experimental results demonstrate that our model outperforms other models like Target-Dependent LSTM (TD-LSTM), Attention-based LSTM with Aspect Embedding (ATAE-LSTM), LSTM+SynATT+TarRep and Convolution over a Dependency Tree (CDT). Our model is further applied to aspect-level sentiment analysis on "government" and "lockdown" of 1,658,250 tweets about "#COVID-19" that we collected from March 1, 2020 to July 1, 2020. The experimental results show that Twitter users' positive and negative sentiments fluctuated over time. Through the transparency analysis in data collection, data processing, and results generating, we discuss the reasons for the evolution of users' emotions over time based on the tweets and on our models.

18.
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
19.
Ieee Transactions on Intelligent Transportation Systems ; : 13, 2022.
Article in English | Web of Science | ID: covidwho-1816471

ABSTRACT

As the safety problems and economic losses caused by traffic accidents are becoming more and more serious, intelligent transportation system (ITS) came into being. After the outbreak of COVID-19, how to achieve effective traffic scheduling and macro command under less contact has attracted more attention. Therefore, the location estimation of traffic objectives is a key issue. In the developed framework, for the target parameter estimation in traffic, frequency diversity array multiple-input multiple-output (FDA-MIMO) radar is introduced into ITS, and tensor decomposition is used to process transportation big data (TBD) to improve the real-time performance of target location estimation. Unfortunately, spatial colored noise and array gain-phase error will affect the performance of FDA-MIMO radar in ITS. An algorithm that can solve the angle-range estimation problem of FDA-MIMO radar in the co-existence of array gain-phase error and spatial colored noise is proposed. Firstly, the four-dimensional tensor is constructed by using the temporal un-correlation of colored noise. Therefore, the influence of colored noise in ITS is removed. Secondly, the direction matrix containing target information is obtained by parallel factor (PARAFAC) decomposition. For the array gain-phase error, the optimization problem is constructed, and the Lagrange multiplier is employed to calculate the optimal solution. The effect of gain-phase error is eliminated by utilizing the optimal solution and the direction matrices. Finally, the location information of motor vehicle is achieved by calculating the solution of least square (LS) fitting. The developed scheme can achieve the location information of motor vehicles in the co-existence of array gain-phase error and spatial colored noise. Comprehensive numerical experiments illustrate that the developed scheme in ITS can efficiently obtain the location information of motor vehicles.

20.
Journal of Retailing and Consumer Services ; 66:12, 2022.
Article in English | Web of Science | ID: covidwho-1814807

ABSTRACT

Panic buying behaviour is inherently undesirable due to its detrimental impact on community's resources and disruptions to supply chain systems. The prevailing COVID-19 pandemic has seen a resurgence of this phenomenon across the world, leaving supermarkets in stockout situations. While panic buying is largely reasoned as a psychological reaction to an extreme event, it is also a socially relevant behaviour as our perception of a crisis can be shaped by our observations and interactions within the society. The social determinants of panic buying behaviour, particularly on how these factors heighten one's perception of scarcity, and trigger panic buying behaviour, are studied. A theoretical model is developed to explain panic buying behaviour in a social context by synthesizing various social and behavioural theories, and the inter-relationship among the latent constructs is analysed using the structural equation modelling approach. Accordingly, an online survey was administered and analysis of the data confirmed that non-coercive social influence, social norm and observational learning directly influence one's perception of scarcity. Additionally, perceived scarcity can motivate panic buying behaviour directly or indirectly through feelings of anticipated regret. This study has contributed to the limited literature on panic buying. Understanding the underlying mechanisms of panic buying will aid policymakers and businesses in developing intervention or support strategies to cope with such behaviour.

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