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2.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-337444

ABSTRACT

Background SARS-CoV-2 Omicron variant BA.1 first emerged on the Chinese mainland in January 2022 in Tianjin and caused a large wave of infections. During mass PCR testing, a total of 430 cases infected with Omicron were recorded between January 8 and February 7, 2022, with no new infections detected for the following 16 days. Most patients had been vaccinated with SARSCoV-2 inactivated vaccines. The disease profile associated with BA.1 infection, especially after vaccination with inactivated vaccines, is unclear. Whether BA.1 breakthrough infection after receiving inactivated vaccine could create a strong enough humoral immunity barrier against Omicron is not yet investigated. Methods We collected the clinical information and vaccination history of the 430 COVID-19 patients infected with Omicron BA.1. Re-positive cases and inflammation markers were monitored during the patient’s convalescence phase. Ordered multiclass logistic regression model was used to identify risk factors for COVID-19 disease severity. Authentic virus neutralization assays against SARS-CoV-2 wildtype, Beta and Omicron BA.1 were conducted to examine the plasma neutralizing titers induced after post-vaccination Omicron BA.1 infection, and were compared to a group of uninfected healthy individuals who were selected to have a matched vaccination profile. Findings Among the 430 patients, 316 (73.5%) were adults with a median age of 47 years, and 114 (26.5%) were under-age with a median age of 10 years. Female and male patients account for 55.6% and 44.4%, respectively. Most of the patients presented with mild (47.7%) to moderate diseases (50.2%), with only 2 severe cases (0.5%) and 7 (1.6%) asymptomatic infections. No death was recorded. 341 (79.3%) of the 430 patients received inactivated vaccines (54.3% BBIBP-CorV vs. 45.5% CoronaVac), 49 (11.4%) received adenovirus-vectored vaccines (Ad5-nCoV), 2 (0.5%) received recombinant protein subunit vaccines (ZF2001), and 38 (8.8%) received no vaccination. No vaccination is associated with a substantially higher ICU admission rate among Omicron BA.1 infected patients (2.0% for vaccinated patients vs. 23.7% for unvaccinated patients, P<0.001). Compared with adults, child patients presented with less severe illness (82.5% mild cases for children vs. 35.1% for adults, P<0.001), no ICU admission, fewer comorbidities (3.5% vs. 53.2%, P<0.001), and less chance of turning re-positive on nucleic acid tests (12.3% vs. 22.5%, P=0.019). For adult patients, compared with no prior vaccination, receiving 3 doses of inactivated vaccine was associated with significantly lower risk of severe disease (OR 0.227 [0.065-0.787], P=0.020), less ICU admission (OR 0.023 [0.002-0.214], P=0.001), lower re-positive rate on PCR (OR 0.240 [0.098-0.587], P=0.002), and shorter duration of hospitalization and recovery (OR 0.233 [0.091-0.596], P=0.002). At the beginning of the convalescence phase, patients who had received 3 doses of inactivated vaccine had substantially lower systemic immune-inflammation index (SII) and C-reactive protein than unvaccinated patients, while CD4+/CD8+ ratio, activated Treg cells and Th1/Th2 ratio were higher compared to their 2-dose counterparts, suggesting that receipt of 3 doses of inactivated vaccine could step up inflammation resolution after infection. Plasma neutralization titers against Omicron, Beta, and wildtype significantly increased after breakthrough infection with Omicron. Moderate symptoms were associated with higher plasma neutralization titers than mild symptoms. However, vaccination profiles prior to infection, whether 2 doses versus 3 doses or types of vaccines, had no significant effect on post-infection neutralization titer. Among recipients of 3 doses of CoronaVac, infection with Omicron BA.1 largely increased neutralization titers against Omicron BA.1 (8.7x), Beta (4.5x), and wildtype (2.2x), compared with uninfected healthy individuals who have a matched vaccination profile. Interpretation Receipt of 3-dose inactivated vaccines can substantially reduce the disease severity of Omicr n BA.1 infection, with most vaccinated patients presenting with mild to moderate illness. Child patients present with less severe disease than adult patients after infection. Omicron BA.1 convalescents who had received inactivated vaccines showed significantly increased plasma neutralizing antibody titers against Omicron BA.1, Beta, and wildtype SARS-CoV-2 compared with vaccinated healthy individuals.

3.
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.

4.
27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) ; : 3717-3725, 2021.
Article in English | Web of Science | ID: covidwho-1736111

ABSTRACT

Information overload is a prevalent challenge in many high-value domains. A prominent case in point is the explosion of the biomedical literature on COVID-19, which swelled to hundreds of thousands of papers in a matter of months. In general, biomedical literature expands by two papers every minute, totalling over a million new papers every year. Search in the biomedical realm, and many other vertical domains is challenging due to the scarcity of direct supervision from click logs. Self-supervised learning has emerged as a promising direction to overcome the annotation bottleneck. We propose a general approach for vertical search based on domain-specific pretraining and present a case study for the biomedical domain. Despite being substantially simpler and not using any relevance labels for training or development, our method performs comparably or better than the best systems in the official TREC-COVID evaluation, a COVID-related biomedical search competition. Using distributed computing in modern cloud infrastructure, our system can scale to tens of millions of articles on PubMed and has been deployed as Microsoft Biomedical Search, a new search experience for biomedical literature: https://aka.ms/biomedsearch.

5.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-329456

ABSTRACT

Antiviral agents blocking SARS-CoV-2 viral replication are desperately needed to complement vaccination to end the COVID-19 pandemic. Viral replication and assembly are entirely dependent on two viral cysteine proteases: 3C-like protease (3CLpro) and the papain-like protease (PLpro). PLpro also has deubiquitinase (DUB) activity, removing ubiquitin (Ub) and Ub-like modifications from host proteins, disrupting the host immune response. 3CLpro is inhibited by many known cysteine protease inhibitors, whereas PLpro is a relatively unusual cysteine protease, being resistant to blockade by such inhibitors. A high-throughput screen of biased and unbiased libraries gave a low hit rate, identifying only CPI-169 and the positive control, GRL0617, as inhibitors with good potency (IC50 < 10 lower case Greek muM). Analogues of both inhibitors were designed to develop structure-activity relationships;however, without a co-crystal structure of the CPI-169 series, we focused on GRL0617 as a starting point for structure-based drug design, obtaining several co-crystal structures to guide optimization. A series of novel 2-phenylthiophene-based non-covalent SARS-CoV-2 PLpro inhibitors were obtained, culminating in low nanomolar potency. The high potency and slow inhibitor off-rate were rationalized by newly identified ligand interactions with a 'BL2 groove' that is distal from the active site cysteine. Trapping of the conformationally flexible BL2 loop by these inhibitors blocks binding of viral and host protein substrates;however, until now it has not been demonstrated that this mechanism can induce potent and efficacious antiviral activity. In this study, we report that novel PLpro inhibitors have excellent antiviral efficacy and potency against infectious SARS-CoV-2 replication in cell cultures. Together, our data provide structural insights into the design of potent PLpro inhibitors and the first validation that non-covalent inhibitors of SARS-CoV-2 PLpro can block infection of human cells with low micromolar potency.

7.
Economic Research-Ekonomska Istrazivanja ; : 15, 2021.
Article in English | Web of Science | ID: covidwho-1354166

ABSTRACT

Growth in China's economy is driven by the troika: consumption, investment and export. This paper examines the effect of uncertain events such as the global financial crisis in 2008, and the COVID-19 pandemic on the troika. Based on the construction of a new uncertainty index of China's economy, the relationship between uncertainty and growth in the troika is examined by using a TVP-VAR model. Results show that fluctuations in the uncertainty index during the COVID-19 epidemic had the greatest negative impact on consumption and investment at a magnitude of -0.27, notably greater than that during the period of the global financial crisis. The negative impact on export reached -0.73, smaller than that during the global financial crisis. Against a backdrop of the novel coronavirus epidemic, it is also found that expansionary monetary policies can have a relatively large impact on investment and export, reaching 1.75 and 1.57 respectively, while short-term impact on consumption is relatively weak, averaging at 0.51.

8.
Ifac Papersonline ; 53(5):857-862, 2020.
Article in English | Web of Science | ID: covidwho-1272455

ABSTRACT

In this paper, a BP neural network and an LSTM network are applied respectively to the prediction of Coronavirus Disease 2019 (COVID-19) in Wuhan, China and South Korea. The methods do not require specific theories of modelling and the predicted values can be obtained as long as the conventional parameters are set. The mean absolute percentage error (MAPS) of all the experiments are below 5% and the values of the determinable coefficient R-2 are all larger than 0.9. The experiments show that the models can fit the actual values well and make relatively accurate predictions. As of March 29, 2020, the cumulative number of confirmed cases in Wuhan is expected to reach 50,068 using BP neural networks and 49,972 using LSTM network, respectively. As of April 13, 2020, the cumulative number of confirmed cases in South Korea is expected to reach 8,862 using BP neural networks and 8,716 using LSTM network, respectively. The models of neural networks are effective in predicting the trend of the COVID-19 epidemic, which is meaningful to prevent and control the epidemic. Copyright (C) 2020 The Authors.

9.
Environmental Geotechnics ; 8(3):172-192, 2020.
Article in English | Scopus | ID: covidwho-1259277

ABSTRACT

The outbreak of the coronavirus disease 2019 (Covid-19) pandemic not only has created a health crisis across the world but is also expected to impact negatively the global economy and societies at a scale that is maybe larger than that of the 2008 financial crisis. Simultaneously, it has inevitably exerted many negative consequences on the geoenvironment on which human beings depend. The current paper articulates the role of environmental geotechnics in elucidating and mitigating the effects of the current pandemic. It is the belief of all authors that the Covid-19 pandemic presents not only significant challenges but also opportunities for the development of the environmental geotechnics field. This discipline should make full use of geoenvironmental researchers' and engineers' professional skills and expertise to look for development opportunities from this crisis, to highlight the irreplaceable position of the discipline in the global fight against pandemics and to contribute to the health and prosperity of communities, to serve humankind better. In order to reach this goal while taking into account the specificity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the uncertainty of its environmental effects, it is believed that more emphasis should be placed on the following research directions: pathogen-soil interactions;isolation and remediation technologies for pathogen-contaminated sites;new materials for pathogen-contaminated soil;recycling and safe disposal of medical wastes;quantification of uncertainty in geoenvironmental and epidemiological problems;emerging technologies and adaptation strategies in civil, geotechnical and geoenvironmental infrastructures;pandemic-induced environmental risk management;and modelling of pathogen transport and fate in geoenvironment, among others. Moreover, Covid-19 has made it clear to the environmental geotechnics community the importance of urgent international co-operation and of multidisciplinary research actions that must extend to a broad range of scientific fields, including medical and public health disciplines, in order to meet the complexities posed by the Covid-19 pandemic. © 2021 ICE Publishing: All rights reserved.

10.
Chinese General Practice ; 23(9):1071-1077, 2020.
Article in Chinese | Scopus | ID: covidwho-832018

ABSTRACT

The COVID-19 outbreak occurred in Wuhan, China, in December 2019 has aroused wide public concern. Both 2019-nCoV and SARS-CoV belong to the coronaviridae family, and invade target cells through ACE2.So an in-depth understanding of ACE2 and a series of pathophysiological changes caused by the virus invading the human body may help to discover and explain the corresponding clinical manifestations and then deal with them timely. In addition, ACE2 is a potential therapeutic target, according to this, we can find the corresponding treatment strategy. This article explains the role of ACE2 in multiple organ damage caused by 2019-nCoV and SARS-CoV, and blockers targeting ACE2, and inflammation inhibitors, with a view to providing a basis for subsequent related research, diagnosis and treatment, and drug development. Copyright © 2020 by the Chinese General Practice.

11.
Chinese Journal of Endocrinology and Metabolism ; 36(6):512-514, 2020.
Article in Chinese | Scopus | ID: covidwho-831373

ABSTRACT

The cause and treatment of refractory hyperglycemia in a critically ill coronavirus disease 2019 (COVID-19) patient during treatment were analyzed retrospectively, indicating that novel coronavirus infection may cause damage to glucose metabolism, so the monitoring and control of blood glucose should be strengthened in clinical treatment. Copyright © 2020 by the Chinese Medical Association.

12.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-2130

ABSTRACT

The Covid-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on Covid-19 and related historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19 has been downloaded over 75K times and has served as the basis of many Covid-19 text mining and discovery systems. In this article, we describe the mechanics of dataset construction, highlighting challenges and key design decisions, provide an overview of how CORD-19 has been used, and preview tools and upcoming shared tasks built around the dataset. We hope this resource will continue to bring together the computing community, biomedical experts, and policy makers in the search for effective treatments and management policies for Covid-19.

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