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1.
Int J Tuberc Lung Dis ; 26(10): 922-928, 2022 10 01.
Article in English | MEDLINE | ID: covidwho-2056115

ABSTRACT

BACKGROUND Despite growing concern regarding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant of concern (VOC), the respiratory and physical functions of patients with delta VOC post-discharge have not been investigated compared to those of patients with ancestral SARS-CoV-2.METHODS Sixty-three discharged patients with coronavirus disease (COVID-19) were included. Patients were divided into delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, differences in chest computed tomography, modified Medical Research Council and Borg Dyspnoea Scale scores, and Manual Muscle Test scores were compared. Prognoses of respiratory and physical function were compared between patients who recovered from moderate and severe COVID-19.RESULTS Of the 63 patients, respectively 28 and 35 were in the delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, 35 patients (56.5%) had abnormalities on imaging. Visual semi-quantitative scores of both lungs were significantly higher in the severe group. However, there was no difference in this or any other score ratings between the groups.CONCLUSION At 14 days post-discharge, ground glass opacities and pleural thickening were the most common residual findings; no difference in respiratory and physical functions during the convalescence period were noted in patients with SARS-CoV-2 delta VOC and ancestral SARS-CoV-2.


Subject(s)
COVID-19 , SARS-CoV-2 , Aftercare , Humans , Patient Discharge
2.
7th International Conference on Distance Education and Learning, ICDEL 2022 ; : 109-115, 2022.
Article in English | Scopus | ID: covidwho-2020433

ABSTRACT

:With the widespread application of information technology, the enhancement of college students' digital literacy skills has become a global concern, especially after the outbreak of COVID-19, which made regular and orderly classroom teaching impossible and eventually forced a large number of schools to focus on online courses. This paper adopts a case study approach and selects the top ten international fashion colleges as the research sample to analyze three aspects: theme-based teaching, blended teaching approach, and credit certification, and finds that the existing international fashion colleges' online education is mainly based on design-based theme-based courses. This paper adopts a blended teaching study with student-initiated learning at its core and found that: the online education of existing international fashion institutions mainly focuses on design-based theme-based courses;blended teaching, with student-initiated learning and direct participation in corporate practice projects as the core;and credit certification, which still focuses on credit assessment for enrolled students while providing industry certification examination courses. This paper concludes that the online course aspect of international fashion institutions can increase the proportion of live streaming, produce clearer and smoother streaming videos, require multiple means of management in virtual community management, and also consider helping students make the optimal choice of courses based on data recommendations. © 2022 ACM.

4.
Innovation in Aging ; 5:15-15, 2021.
Article in English | Web of Science | ID: covidwho-2012889
5.
BMJ Open ; 12(9), 2022.
Article in English | PMC | ID: covidwho-2009223

ABSTRACT

Objective: This survey study is designed to understand the impact of the COVID-19 pandemic on stress among specific subpopulations of college students. Design, settings and participants: An online questionnaire was sent to the students from University of Nevada, Las Vegas, between October 2020 and December to assess the psychological impact of COVID-19. A total of 2091 respondents signed the consent form online and their responses were collected. Main outcome measures: Measures of psychological stress, as prescribed by the Perceived Stress Scale (PSS-10). An explanatory factor analysis was carried out on the PSS-10 results. We subsequently analysed each factor using stepwise linear regression that focused on various sociodemographic groups. Results: A two-factor model was obtained using the explanatory factor analysis. After comparing with the past studies that investigated the factor structure of the PSS-10 scale, we identified these two factors as ‘anxiety’ and ‘irritability’. The subsequent stepwise linear regression analysis suggested that gender and age (p<0.01) are significantly associated with both factors. However, the ethnicities of students are not significantly associated with both factors. Conclusions: To our knowledge, this is the first study that assessed the perceived stress of university students in the USA during the COVID-19 pandemic. Through exploratory factor analysis, we showed that the PSS-10 scale could be summarised as a two-factor structure. A stepwise regression approach was used, and we found both of the factors are significantly associated with the gender of the participants. However, we found no significant association between both factors and ethnicity. Our findings will help identify students with a higher risk for stress and mental health issues in pandemics and future crises.

6.
Drug Evaluation Research ; 45(1):37-47, 2022.
Article in Chinese | Scopus | ID: covidwho-1912085

ABSTRACT

Objective Based on text mining technology and biomedical database, data mining and analysis of coronavirus disease 2019 (COVID-19) were carried out, and COVID-19 and its main symptoms related to fever, cough and respiratory disorders were explored. Methods The common targets of COVID-19 and its main symptoms cough, fever and respiratory disorder were obtained by GenCLiP 3 website, Gene ontology in metascape database (GO) and pathway enrichment analysis, then STRING database and Cytoscape software were used to construct the protein interaction network of common targets, the core genes were screened and obtained. DGIdb database and Symmap database were used to predict the therapeutic drugs of traditional Chinese and Western medicine for the core genes. Results A total of 28 gene targets of COVID-19 and its main symptoms were obtained, including 16 core genes such as IL2, IL1B and CCL2. Through the screening of DGIdb database, 28 chemicals interacting with 16 key targets were obtained, including thalidomide, leflunomide and cyclosporine et al. And 70 kinds of Chinese meteria medica including Polygonum cuspidatum, Astragalus membranaceus and aloe. Conclusion The pathological mechanism of COVID-19 and its main symptoms may be related to 28 common genes such as CD4, KNG1 and VEGFA, which may participate in the pathological process of COVID-19 by mediating TNF, IL-17 and other signal pathways. Potentially effective drugs may play a role in the treatment of COVID-19 through action related target pathway. © 2022 Tianjin Press of Chinese Herbal Medicines. All Rights Reserved.

7.
7th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2022 ; : 17-21, 2022.
Article in English | Scopus | ID: covidwho-1909212

ABSTRACT

The emergence of the COVID-19 has a huge impact on the Chinese and American economies, including the fluctuations of stock price in the financial market. It's significantly valuable to search out the rules of index variability under this post-epidemic era. In this paper, we create an improved Convolutional Neural Network to search out the future trend of Shanghai Composite Index and Nasdaq composite index by using the daily data from January 1, 2011 to April 23, 2021, and find out the characteristics through nonlinear test and random lasso algorithm. The empirical results show that the prediction correction determination coefficients of Shanghai Composite Index and Nasdaq composite index reach 0.87 and 0.97 respectively, which shows that it is feasible and effective to use convolutional neural network to predict the stock index. © 2022 IEEE.

8.
International Journal of Social Economics ; 2022.
Article in English | Scopus | ID: covidwho-1878900

ABSTRACT

Purpose: This study aims to explore and clarify the mechanism by which cognitive heuristics influence strategic decision-making during the coronavirus disease 2019 (COVID-19) pandemic in an emerging economy. Design/methodology/approach: Data collection was conducted through a survey completed by 213 top-level managers from firms located in the twin cities of Pakistan. A convenient, purposively sampling technique and snowball method were used for data collection. To examine the relationship between cognitive heuristics and strategic decision-making, hypotheses were tested by using correlation and regression analysis. Findings: The article provides further insights into the relationship between cognitive heuristics and strategic decision-making during the COVID-19 pandemic. The results suggest that cognitive heuristics (under-confidence, self-attribution and disposition effect) have a markedly negative influence on the strategic decision-making during the COVID-19 pandemic in an emerging economy. Practical implications: The article encourages strategic decision-makers to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of cognitive heuristics in strategic decision-making, which could be very useful for business actors such as managers and entire organizations. The findings of this study will help academicians, researchers and policymakers of emerging countries. Academicians can formulate new behavioural models that can depict the solutions to dealing with an uncertain situation like COVID-19. Policymakers and strategic decision-making teams can develop crisis management strategies based on concepts from behavioral strategy to better deal with similar circumstances in the future, such as COVID-19. Originality/value: The paper’s novelty is that the authors have explored the mechanism by which cognitive heuristics influence strategic decision-making during the COVID-19 pandemic in an emerging economy. It adds to the literature in strategic management, explicitly probing the impact of cognitive heuristics on strategic decision-making;this field is in its initial stage, even in developed countries, while little work has been done in emerging countries. Peer review: The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2021-0636. © 2022, Emerald Publishing Limited.

10.
Multiple Sclerosis Journal ; 28(1_SUPPL):147-147, 2022.
Article in English | Web of Science | ID: covidwho-1866169
11.
3rd International Conference on Electronic Communication and Artificial Intelligence, IWECAI 2022 ; : 512-518, 2022.
Article in English | Scopus | ID: covidwho-1831842

ABSTRACT

The sudden appearance and rapid spread of Covid-19 has a potentially catastrophic impact on furniture in many developed and developing countries. Therefore, in response to this situation, the future vaccine demand from the perspective of analytical models was predictableized to help more visualize the number of vaccines, new deaths, and each country. Then select different epidemic countries, India, South Africa, and Americaslyze their data using three models (random forests, linear regression, and port machines future. In this study, the vaccination characteristics, daily cases, and the first few weeks helped to predict vaccination demand. People found that if the epidemic was severe, the number of cases and deaths per day increased, the demand for vaccines would increase in most countries. At the same time, the need for vaccination also depends on the needs of the previous weeks. In view of the epidemic prediction and vaccination situation, this paper uses machine learning method to analyze the data of COVID-19 and the vaccination progress in detail, and further predicts the number of future vaccines through machine learning. The aim is to enable governments to prevent the virus more effectively. © 2022 IEEE.

12.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333495

ABSTRACT

BACKGROUND: The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. METHODS: We collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level. RESULTS: The median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January. CONCLUSION: Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

13.
Plant Science Today ; 9(2):427-437, 2022.
Article in English | Web of Science | ID: covidwho-1798655

ABSTRACT

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of the current ongoing global pandemic COVID-19 is yet far away from the clutches of contemporary western medicines. With the lack of conventional drugs for this deadly disease the scope for the development of herbal formulations and Ayurvedic medication is finding a sound basis in the current scenario. The past two years has witnessed detailed and focused investigations on the biologically active constituents derived from a range of medicinal plants and their potential antiviral properties against SARSCoV-2. The promising results of these investigations have intrigued the medical and plant experts in pharmacognosy enough to consider herbal medicines and plant-based products as they are more effective in combating the COVID-19 crisis. However, a large-scale application of the same would require more focused and thorough research on this matter. This review is an attempt to describe the current and future prospects of using medicinal plants and herbal compounds as natural and sustainable alternative for treating COVID-19. The current article evaluates the various strong evidences from biochemical and molecular studies that have been investigated so far for the development of herbal formulations to combat COVID-19 with detailed focus on the most potential phytochemicals of medicinal plants studied in this regard namely, Withania somnifera (L.) Dunal, Cinchona officinalis L., Curcuma longa L., Ocimum sanctum L., Azadirachta indica A. Juss. and Tinospora cordifolia (Willd.) Miers.

14.
Modern Food Science and Technology ; 38(1):29-35 and 363, 2022.
Article in Chinese | Scopus | ID: covidwho-1771823

ABSTRACT

Foodborne norovirus is an important pathogen that has triggered food safety incidents worldwide. The continued outbreak of COVID-19 has highlighted the urgency of viral safety research in the food sector. In this study, a highly efficient monoclonal antibody against foodborne norovirus obtained by our team was selected and the variable regions of its heavy chain (VH) and light chain (VL) were cloned and analyzed. Total RNA was extracted from the hybridoma cell line 1E3 secreting monoclonal antibodies against foodborne norovirus, and the DNA sequences of the VH and VL genes of the monoclonal antibody 1E3 were amplified by RT-PCR. The fragments were cloned into the PMD19-T vector and sequenced, and the primary amino acid sequences of both variable regions were then analyzed. An NCBI BLAST comparison confirmed that the amplified VH and VL sequences were of mouse antibody variable regions. Using the VBASE2 database to analyze the variable region-encoding gene structures further, the positions of the three amplified complementarity-determining regions and four amplified framework regions on VH and VL were confirmed to be complete. The VH gene was 360 bp long, encoded 120 amino acids, and belonged to the IGHV3-2*02 family. The VL gene was 339 bp long, encoded 113 amino acids, and belonged to the IGKV1-135*01 family. Through molecular docking experiments, it was found that D108 (the key amino acid residue) of the antibody VH chain bonded to N195 of the viral capsid P protein through hydrogen bonding. The successful amplification of the VH and VL fragments of this monoclonal antibody against foodborne norovirus has promoted the development of genetically engineered antibodies and the application of new microbial detection and control technologies for ensuring food safety. © 2022, Editorial Board of Modern Food Science and Technology. All right reserved.

15.
Global Mental Health ; 2022.
Article in English | EMBASE | ID: covidwho-1721250

ABSTRACT

The publisher apologises that upon publication of this article the authors affiliations were not correctly assigned to the authors. The correct listing is as below: Jing Lu1, Min Zhao1,3, Qianying Wu1, Chenyi Ma1, Xiangdong Du2, Xinchuan Lu2, Qiufang Jia2, Chuanwei Li2* 1.Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China 2.Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China 3.Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China The online version of this article has been updated.

16.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-329107

ABSTRACT

Background: Immunity after SARS-CoV-2 infection or vaccination has been threatened by recently emerged SARS-CoV-2 variants. A systematic summary of the landscape of neutralizing antibodies against emerging variants is needed. Methods: We systematically searched PubMed, Embase, Web of Science, and 3 pre-print servers for studies that evaluated neutralizing antibodies titers induced by previous infection or vaccination against SARS-CoV-2 variants and comprehensively collected individual data. We calculated lineage-specific GMTs across different study participants and types of neutralization assays. Findings: We identified 56 studies, including 2,483 individuals and 8,590 neutralization tests, meeting the eligibility criteria. Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The estimated neutralization reductions for B.1.351 compared to lineage B were 240.2-fold (95% CI: 124.0-465.6) reduction for non-replicating vector platform, 4.6-fold (95% CI: 4.0-5.2) reduction for RNA platform, and 1.6-fold (95% CI: 1.2-2.1) reduction for protein subunit platform. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9). Interpretation: Our findings indicate that the antibody response established by natural infection or vaccination might be able to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Standardized protocols for neutralization assays, as well as updating immune-based prevention and treatment, are needed. Funding: Chinese National Science Fund for Distinguished Young Scholars. Research in context: Evidence before this study: Several newly emerged SARS-CoV-2 variants have raised significant concerns globally, and there is concern that SARS-CoV-2 variants can evade immune responses that are based on the prototype strain. It is not known to what extent do emerging SARS-CoV-2 variants escape the immune response induced by previous infection or vaccination. However, existing studies of neutralizing potency against SARS-CoV-2 variants are based on limited numbers of samples and lack comparability between different laboratory methods. Furthermore, there are no studies providing whole picture of neutralizing antibodies induced by prior infections or vaccination against emerging variants. Therefore, we systematically reviewed and quantitively synthesized evidence on the degree to which antibodies from previous SARS-CoV-2 infection or vaccination effectively neutralize variants. Added value of this study: In this study, 56 studies, including 2,483 individuals and 8,590 neutralization tests, were identified. Antibodies from natural infection or vaccination are likely to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Lineage B.1.351 escaped natural-infection-mediated neutralization the most, with GMT of 79.2 (95% CI: 68.5-91.6), while neutralizing antibody titers against the B.1.1.7 variant were largely preserved (254.6, 95% CI: 214.1-302.8). Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The neutralizing antibody response after vaccinating with non-replicating vector vaccines against lineage B.1.351 was worse than responses elicited by vaccines on other platforms, with levels lower than that of individuals who were previously infected. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9). Implications of all the available evidence: Our findings indicate that antibodies from natural infection of the parent lineage of SARS-CoV-2 or vaccination may be less able to neutralize some emerging variants, and antibody-based therapies may need to be updated. Furthermore, standardized protocols for neutralizing antibody testing against SARS-CoV-2 are needed to reduce lab-to-lab variations, thus facilitating comparability and interpretability across studies.

17.
7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 ; : 304-308, 2021.
Article in English | Scopus | ID: covidwho-1704219

ABSTRACT

Frequently Asked Question (F AQ) retrieval is a valuable task which aims to find the most relevant question-answer pair from a FAQ dataset given a user query. Currently, most works implement F AQ retrieval considering the similarity between the query and the question as well as the relevance between the query and the answer. However, the query-answer relevance is difficult to model effectively due to the heterogeneity of query-answer pairs in terms of syntax and semantics. To alleviate this issue and improve retrieval performance, we propose a novel approach to consider answer information into F AQ retrieval by question generation, which provides high-quality synthetic positive training examples for dense retriever. Experiment results indicate that our method outperforms term-based BM25 and pretrained dense retriever significantly on two recently published COVID-19 F AQ datasets. © 2021 IEEE.

18.
Bull Exp Biol Med ; 172(4): 423-429, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1696762

ABSTRACT

We studied the lung-protective effect and mechanisms of the anti-inflammatory and antioxidant effects of ultra-short-wave diathermy (USWD) in a rat model of LPS-induced acute lung injury. Histological examination of the lung tissues was performed and the levels of oxidative stress-related factors and inflammatory cytokines were measured. It was shown that the lung injury score, the lung wet-to-dry weight ratio (W/D), oxidative stress-related factors malondialdehyde and acyl-CoA synthetase long-chain family member 4 (ACSL4), and inflammatory cytokines were increased after LPS administration, while USWD treatment reduced these parameters. In addition, superoxide dismutase and glutathione peroxidase 4 were decreased in rats with LPS-induced acute lung injury, while USWD therapy up-regulated the expression of these enzymes. Thus, USWD could antagonize lung injury by inhibiting oxidative stress and inflammatory response in rats with acute lung injury. USWD can be a promising adjunctive treatment to counter oxidative stress and inflammation and a potential therapeutic candidate for the treatment of patients with this pathology.


Subject(s)
Acute Lung Injury , Diathermy , Acute Lung Injury/drug therapy , Acute Lung Injury/therapy , Animals , Anti-Inflammatory Agents/pharmacology , Anti-Inflammatory Agents/therapeutic use , Antioxidants/metabolism , Humans , Lipopolysaccharides/pharmacology , Lung , Oxidative Stress , Radio Waves , Rats
19.
21st COTA International Conference of Transportation Professionals: Advanced Transportation, Enhanced Connection, CICTP 2021 ; : 703-712, 2021.
Article in English | Scopus | ID: covidwho-1628099

ABSTRACT

To ensure traffic safety, many related works have been done to avoid traveler injury during trips. However, new public health issues threaten traffic safety because travelers might get ill during trips. The more people infected by COVID-19, the more unsafe urban traffic becomes. This paper aims to verify whether COVID-19 has negative impacts on urban traffic recovery. Based on thirty Chinese cities' data, robust fixed-effects (within) regression was adopted to analyze impacts with a linear regression method. The regression results suggest that Urban Traffic Activity Index (UTAI) was positively associated with UTAI itself with short-term effect, meaning that UTAI could recover by itself, and new confirmed cases (NC) were negatively associated with UTAI with long-term effect, meaning that NC would prevent UTAI recovery. The findings also suggest that it is better for city governments to eliminate outbreaks before restarting economies. Future directions include improving models, grouping cities, and expanding data. © 2021 CICTP 2021: Advanced Transportation, Enhanced Connection - Proceedings of the 21st COTA International Conference of Transportation Professionals. All rights reserved.

20.
1st CAAI International Conference on Artificial Intelligence, CICAI 2021 ; 13069 LNAI:89-100, 2021.
Article in English | Scopus | ID: covidwho-1626470

ABSTRACT

The global spread of coronavirus disease has become a major threat to global public health. There are more than 137 million confirmed cases worldwide at the time of writing. The spread of COVID-19 has resulted in a huge medical load due to the numerous suspected examinations and community screening. Deep learning methods to automatically classify COVID-19 have become an effective assistive technology. However, the current researches on data quality and the use of CT data to diagnose COVID-19 with convolutional neural networks are poor. This study is based on CT scan data of COVID-19 patients, patients with other lung diseases, and healthy people. In this work, we find that data smoothing can improve the quality of CT images of COVID-19 and improve the accuracy of the model. Specifically, an interpolation smoothing method is proposed using the bilinear interpolation algorithm. Besides, we propose an improved ResNet structure to improve the model feature extraction and fusion by optimizing the structure of the input stem and downsampling parts. Compared with the baseline ResNet, the model improves the accuracy of the three-class classification by 3.8% to 93.83%. Our research has particular significance for research on the automatic diagnosis of COVID-19 infectious diseases. © 2021, Springer Nature Switzerland AG.

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