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1.
Viruses ; 14(8), 2022.
Article in English | MEDLINE | ID: covidwho-2010309

ABSTRACT

Porcine viral diarrhea diseases affect the swine industry, resulting in significant economic losses. Porcine epidemic diarrhea virus (PEDV) genotypes G1 and G2, and groups A and C of the porcine rotavirus, are major etiological agents of severe gastroenteritis and profuse diarrhea, particularly among piglets, with mortality rates of up to 100%. Based on the high prevalence rate and frequent co-infection of PEDV, RVA, and RVC, close monitoring is necessary to avoid greater economic losses. We have developed a multiplex TaqMan probe-based real-time PCR for the rapid simultaneous detection and differentiation of PEDV subtypes G1 and G2, RVA, and RVC. This test is highly sensitive, as the detection limits were 20 and 100 copies/μL for the G1 and G2 subtypes of PEDV, respectively, and 50 copies/μL for RVA and RVC, respectively. Eighty-eight swine clinical samples were used to evaluate this new test. The results were 100% in concordance with the standard methods. Since reassortment between porcine and human rotaviruses has been reported, this multiplex test not only provides a basis for the management of swine diarrheal viruses, but also has the potential to impact public health as well.

2.
PLoS ONE [Electronic Resource] ; 17(8):e0273344, 2022.
Article in English | MEDLINE | ID: covidwho-2002328

ABSTRACT

This study explored the roles of epidemic-spread-related behaviors, vaccination status and weather factors during the COVID-19 epidemic in 50 U.S. states since March 2020. Data from March 1, 2020 to February 5, 2022 were incorporated into panel model. The states were clustered by the k-means method. In addition to discussing the whole time period, we also took multiple events nodes into account and analyzed the data in different time periods respectively by panel linear regression method. In addition, influence of cluster grouping and different incubation periods were been discussed. Non-segmented analysis showed the rate of people staying at home and the vaccination dose per capita were significantly negatively correlated with the daily incidence rate, while the number of long-distance trips was positively correlated. Weather indicators also had a negative effect to a certain extent. Most segmental results support the above view. The vaccination dose per capita was unsurprisingly proved to be the most significant factor especially for epidemic dominated by Omicron strains. 7-day was a more robust incubation period with the best model fit while weather had different effects on the epidemic spread in different time period. The implementation of prevention behaviors and the promotion of vaccination may have a successful control effect on COVID-19, including variants' epidemic such as Omicron. The spread of COVID-19 also might be associated with weather, albeit to a lesser extent.

3.
Chinese Journal of New Drugs ; 31(14):1387-1394, 2022.
Article in Chinese | EMBASE | ID: covidwho-1976321

ABSTRACT

To block the continuously global pandemic of novel coronavirus pneumonia (COVID-19 or 2019-nCoV or SARS-CoV-2), more than 300 vaccines have been put into R&D pipelines in tens of countries within two years. At present, vaccines using different technical platforms have been fast approved to use, and widely deployed and vaccinated worldwide due to accelerated medical policies. In this article, the representative vaccines were selected from the main technical routes to analyze the strategy of vaccine R&D and management from the aspects including R&D cooperation, clinical trials, approval and access, production and circulation. We aim to provide reference for the vaccine development and supervision under the circumstance of emergency infectious diseases.

4.
Chinese Journal of Experimental Traditional Medical Formulae ; 28(8):116-122, 2022.
Article in Chinese | Scopus | ID: covidwho-1893396

ABSTRACT

The theoretical origin of the combined therapy of lung and intestine can be traced back to the Inner Canon of Huangdi, which explains the physiological and pathological interaction between the lung and the large intestine. In recent years, researchers have investigated the scientific essence of the "lung- intestine axis" theory from many aspects, which enriches the relevant theoretical basis, and applied it to the treatment of COVID-19, acute lung injury, and other lung diseases. The close relation between lung and intestine in many aspects embodies the holistic conception of traditional Chinese medicine and explains the holistic theory of interrelation between organs, which correlate to each other physiologically and pathologically. Intestinal microecological disorders can affect lung immune function and cause respiratory diseases, and respiratory diseases are usually accompanied by gastrointestinal symptoms. Lung diseases can be prevented and treated by regulating intestinal flora. According to histoembryology, the epithelial tissue of the lung and intestine comes from primitive foregut. In immunology, both lung and intestine contain mucosa-associated lymphoid tissue, and the pathological changes of the respiratory tract are also closely related to intestinal microorganisms. The tissue origin of lung and large intestine, the correlation of mucosal immunity, and the synchronization of ecological changes provide a scientific basis for the combined therapy of lung and intestine. Therefore, this paper summarizes the theoretical origin, modern research mechanism, and clinical application of combined therapy of lung and intestine, in order to provide a new direction for its application in clinical and scientific research. © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

5.
Journal of Knowledge Management ; ahead-of-print(ahead-of-print):16, 2021.
Article in English | Web of Science | ID: covidwho-1550694

ABSTRACT

Purpose Taking the COVID-19 as the background, this study aims to investigate the direct influencing factors regarding knowledge sharing behavior (KSB) on new media platforms and discuss how the characteristics of the users could enhance the KSB through moderation effect, and provide empirical evidences. Design/methodology/approach Based on the social exchange theory and after the text analysis of the data collected from the Tiktok platform in 2020, this paper uses the quantitative method to evaluate the factors influence KSB on short video social platform during the COVID-19 outbreak. Findings KSB on new media platform could be enhanced by richer knowledge content of the video posted and the attribute of the platform users directly. Platform users could affect the trustworthiness of the knowledge shared, thus influence the knowledge sharing. On the early stage of the COVID-19, the richer content of the knowledge released by users could effectively enhance the KSB. On the early stage of the emergency events, the official users could play a significant role on KS. During the mitigation stage of COVID-19, the KSB of the knowledge shared by unofficial users with richer content could be enhanced and the moderation effect is relatively stronger. Originality/value The research extends the social exchange theory to a disaster management context. The authors provide an effective reference for future governments to effectively cope with the epidemic and spread public knowledge in an emergency response context. By analyzing the influence of knowledge content and influencer characteristics, it could help the social media platform to improve content management and optimize resource allocation.

6.
2nd International Conference on Computer Vision, Image, and Deep Learning ; 11911, 2021.
Article in English | Scopus | ID: covidwho-1511402

ABSTRACT

The current COVID-19 pandemic continues with its new variants, whose mutations are unpredictable. Thus, how to predict mutations in viruses has profound meanings for vaccine and drug development as well as prevention measures. Currently the documented mutations in SARS-CoV-2 are not abundant yet, especially for making phylogenetic tree, it would be useful and easy to use the virus data with abundant mutations such as influenza A virus to build predictive model. In this study, a neural network with feedforward backpropagation algorithm is employed to predict the probabilistically possible mutation positions and mutated amino acids in hemagglutinins from Eurasia H1 influenza A virus. The study demonstrates an encouraging result and suggests the possibility to continue working along this research line. © 2021 SPIE.

7.
European Stroke Journal ; 6(1 SUPPL):17, 2021.
Article in English | EMBASE | ID: covidwho-1468038

ABSTRACT

Background and Aims: Rapid intravenous thrombolysis (IVT) for acute ischemic stroke (AIS) is crucial for improving outcomes. However, randomized trials to reduce in-hospital delay are clearly limited in China. We aimed to evaluate the effect of a multi-component intervention on thrombolytic door-to needle time (DNT) of AIS patients via video teleconference based on the Behavior Change Wheel method. Methods: This trial randomly allocated 22 hospitals equally to PEITEM (Persuasion Environment reconstruction Incentivisation Training Education Modeling) intervention or routine care plus stroke registry and subsequently enrolled 1634 AIS patients who receiving IVT within 4.5 hours upon stroke onset from participant hospitals. The PEITEM group received a one-year PEITEM intervention based on the behavioral theory monthly via video teleconference. Results: A total of 1, 634 patients from the 22 hospitals were enrolled. The proportion of DNT ≤ 60 minutes was 82.0% in the PEITEM group and 73.7% in the control group (adjusted odds ratio, 1.85;95% confidence interval [CI], 1.42 to 2.42, P<0.001). The average DNT was 43 minutes in the PEITEM group and 50 minutes in the control group (β: -9.00;95% CI, -11.37 to ≤6.63, P<0.001). Favorable neurological outcomes were achieved in 55.6% patients in the PEITEM group and 50.4% patients in the control group (adjusted odds ratio, 1.34;95% CI, 1.02 to 1.75;P=0.04). Conclusions: The teleconference-delivered PEITEM intervention resulted in a moderately but clinically relevant shorter DNT and better neurological outcomes in the AIS treated with the IVT. Video teleconference may be more appropriate and easier for quality improvement in the current global COVID-19 public health crisis disrupting healthcare services.

8.
Surgical and Experimental Pathology ; 4(1), 2021.
Article in English | EMBASE | ID: covidwho-1379803

ABSTRACT

Lymphangioleiomyomatosis (LAM) is a rare neoplastic disease of the lung with a characteristic feature of diffuse cystic changes in bilateral lungs. Lung transplantation is considered to be one of the effective treatments in end stage disease. Patients with LAM who underwent lung transplant tend to have more favorable outcome compared to other end stage lung diseases. We report a case of a female patient who was diagnosed with LAM and received bilateral lung transplantation at 45 years of age. Subsequent allograft biopsies were significant for mild acute cellular rejection (Grade A2), for which the immunosuppressive regimen was adjusted accordingly. At 7 years post-transplant, she presented with shortness of breath, cough, and fatigue, and diagnosed with a viral infection. Her chest imaging was unremarkable. However, a transbronchial biopsy was performed to rule out rejection and revealed foci of spindle cells proliferation, with positive HMB-45 and smooth muscle actin immunohistochemical studies, confirming the diagnosis of recurrent LAM. After she was discharged, she was re-admitted 1 week later with severe COVID-19. Her clinical course was complicated by acute respiratory distress syndrome, respiratory failure, and gastrointestinal hemorrhage. The patient passed away on day 36 of hospital stay. Autopsy was requested and confirmed the pathology of recurrent LAM and diffuse alveolar damage from COVID-19.

9.
Journal of Clinical Urology ; 14(1 SUPPL):26, 2021.
Article in English | EMBASE | ID: covidwho-1325315

ABSTRACT

Introduction: COVID-19 has had potential impact on presentation and outcome of patients to cancer services. The objective of this study was to analyse pandemic effects on patients with penile SCC by comparison with previous years within a stable 10 million population referral base. Patients and Methods: All patients referred to the penile supranetwork MDT (snMDT), 1st January 2020 to 31st December 2020 identified (COVID-19 Group A). Prospectively collated data from previous 3 years (2017- 19) referrals analysed to create a service year mean dataset (Non-COVID-19 Group B). Variables compared: (i) overall demographics, (ii) pathological stage (TNM 8), (iii) time from presentation to first treatment. Chi-squared test to evaluate the pathological stage (TNM 8) and Mann- Whitney U Test to assess time from presentation to first treatment. Results: Group A, 123 new referrals. Group B mean referrals 129 (118 - 147). Primary stage Group A, 45.4% pT1, 30.2% pT2, 24.4% pT3/pT4 vs Group B, 48.6% pT1, 38.2% pT2, 13.2% pT3/pT4 (p=0.01). Nodal stage pN0 Group A 62% vs 70% Group B, (NS p = 0.08). Median time (days) presentation to first treatment Group A, 22 (IQ 15 - 36) vs Group B, 26 (13 - 36.5). Conclusion: No. of referrals were statistically similar in COVID-19 and Non-COVID-19 years and managed within similar time frame. However, there was a statistically higher pT disease stage in the COVID-19 group but no significant difference in pN stage (although trend towards higher nodal stage). Data is not yet mature to determine an effect on cancer specific survival.

10.
2nd International Conference on Economic Management and Model Engineering, ICEMME 2020 ; : 1007-1011, 2020.
Article in English | Scopus | ID: covidwho-1276428

ABSTRACT

The outbreak of COVID-19 pandemic can be viewed as a surprise for its scale and impact. However, this pandemic may not be considered as a purely random event, because it is developing from a local epidemic to a global pandemic under everyone's eyes. Although COVID-19 pandemic negatively impacts the world economy, to everyone's surprise, the US stock market recovers rapidly from its initial heavy loss. For the sake of modeling, it is interesting to use a random walk model to fit SP 500 index, which is designed as the aim of current study. The results show that the random walk model can somewhat fit the SP 500 index, the shorter the time scale is, the better the fitting is. The results therefore demonstrate it impossible to use a single random seed to fit the SP 500 index from different time segments. © 2020 IEEE.

11.
Jiegou Huaxue ; 40(4):431-442, 2021.
Article in English | Scopus | ID: covidwho-1268426

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) gained tremendous attention due to its high infectivity and pathogenicity. The 3-chymotrypsin-like hydrolase protease (Mpro) of SARS-CoV-2 has been proven to be an important target for anti-SARS-CoV-2 activity. To better identify the drugs with potential in treating coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 and according to the crystal structure of Mpro, we conducted a virtual screening of FDA-approved drugs and chemical agents that have entered clinical trials. As a result, 9 drug candidates with therapeutic potential for the treatment of COVID-19 and with good docking scores were identified to target SARS-CoV-2. Consequently, molecular dynamics (MD) simulation was performed to explore the dynamic interactions between the predicted drugs and Mpro. The binding mode during MD simulation showed that hydrogen bonding and hydrophobic interactions played an important role in the binding processes. Based on the binding free energy calculated by using MM/PBSA, Lopiravir, an inhibitor of human immunodeficiency virus (HIV) protease, is under investigation for the treatment of COVID-19 in combination with ritionavir, and it might inhibit Mpro effectively. Moreover, Ombitasvir, an inhibitor for non-structural protein 5A of hepatitis C virus (HCV), has good inhibitory potency for Mpro. It is notable that the GS-6620 has a binding free energy, with respect to binding Mpro, comparable to that of ombitasvir. Our study suggests that ombitasvir and lopinavir are good drug candidates for the treatment of COVID-19, and that GS-6620 has good anti-SARS-CoV-2 activity. © 2021 Fujian Institute of Research of the Structure of Matter. All rights reserved.

12.
2nd International Conference on Computing and Data Science, CONF-CDS 2021 ; PartF168982, 2021.
Article in English | Scopus | ID: covidwho-1247422

ABSTRACT

The outbreak of pandemic of COVID-19 is a totally unexpected event, which impacts heavily on the world stock market, especially the US stock market. So far, mathematical, statistical and probabilistic models have been used in the simulation of stock markets, whereas the probabilistic models appear to be more suitable for current situation because of the unexpectedness of COVID-19 pandemic. In this study, the random walk model, which is based on random walk hypothesis of stock markets, was used to simulate the opens of Dow Jones Industrial Average Index for 7 months, 2 years and 7 months, 5 years and 7 months, 10 years and 7 months, and 20 years and 7 months, respectively. The unexpected events not only include the current COVID-19 pandemic but also the 9/11 terrorism attack on the World Trade Center. The simulations demonstrate that the random walk is still difficult to precisely describe the impact of COVID-19 pandemic on the Dow Jones Industrial Average Index although the general trends look similar. © 2021 ACM.

13.
Clinical & Applied Thrombosis/Hemostasis ; 27:10760296211010976, 2021.
Article in English | MEDLINE | ID: covidwho-1208919

ABSTRACT

The prognostic role of hypercoagulability in COVID-19 patients is ambiguous. D-dimer, may be regarded as a global marker of hemostasis activation in COVID-19. Our study was to assess the predictive value of D-dimer for the severity, mortality and incidence of venous thromboembolism (VTE) events in COVID-19 patients. PubMed, EMBASE, Cochrane Library and Web of Science databases were searched. The pooled diagnostic value (95% confidence interval [CI]) of D-dimer was evaluated with a bivariate mixed-effects binary regression modeling framework. Sensitivity analysis and meta regression were used to determine heterogeneity and test robustness. A Spearman rank correlation tested threshold effect caused by different cut offs and units in D-dimer reports. The pooled sensitivity of the prognostic performance of D-dimer for the severity, mortality and VTE in COVID-19 were 77% (95% CI: 73%-80%), 75% (95% CI: 65%-82%) and 90% (95% CI: 90%-90%) respectively, and the specificity were 71% (95% CI: 64%-77%), 83% (95% CI: 77%-87%) and 60% (95% CI: 60%-60%). D-dimer can predict severe and fatal cases of COVID-19 with moderate accuracy. It also shows high sensitivity but relatively low specificity for detecting COVID-19-related VTE events, indicating that it can be used to screen for patients with VTE.

14.
Frontiers in Built Environment ; 7, 2021.
Article in English | Scopus | ID: covidwho-1154212
15.
Lect. Notes Electr. Eng. ; 653:508-515, 2021.
Article in English | Scopus | ID: covidwho-1141391

ABSTRACT

The main incidence of pneumonia in Wuhan is that Coronavirus Disease (COVID-19) infects the lungs and causes respiratory failure [1]. Based on the technical research of lung infection detection, the medical image X-ray film can be detected by artificial intelligence technology to effectively improve the diagnosis accuracy and efficiency. We propose an end-to-end solution based on a deep learning method. This method uses a variety of convolutional neural networks to generate feature maps, and then stitch the feature maps by channel to obtain good performance on our data set. In our experiments, the accuracy rate obtained by experimenting with only one feature map is best at 0.89, and then the feature maps are stitched using four convolutional neural networks to obtain 0.91. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

16.
Chinese Journal of Microbiology and Immunology (China) ; 41(1):1-5, 2021.
Article in Chinese | Scopus | ID: covidwho-1134267

ABSTRACT

Objective: To retrospectively analyze the clinical characteristics and drug resistance among COVID-19 patients with bacterial and fungal infections. Methods: Clinical data of COVID-19 patients whose blood, urine, sputum and alveolar lavage fluid samples were positive for bacteria and fungi were collected in Tongji Hospital from February 10 to March 31, 2020. WHONET5.6 software was used to analyze drug susceptibility test results. Results: A total of 95 COVID-19 patients positive for pathogenic bacteria were enrolled and among them, 23 were non-critical patients and 72 were critical patients. The main symptoms in these patients included fever, cough with sputum, fatigue and dyspnea. Male and female critical patients accounted for 63.89% and 36.11%, respectively. Most of the patients with bacterial and fungal infections were critical type, accounting for 23.61%. The mortality rates of non-critical and critical patients were 13.04% and 61.11%, respectively. A total of 179 strains of pathogenic bacteria were isolated. The positive rate of Escherichia coli in non-critical patients was 37.50%, which was higher than that in critical patients. However, the positive rates of Acinetobacter baumannii and Klebsiella pneumoniae in critical patients were both 29.87%, higher than those in non-critical patients. There was no significant difference in the positive rate of gram-positive bacteria or fungi between non-critical and critical patients. It was noteworthy that the positive rate of Candida parapsilosis in blood samples of critical patients was relatively high, reaching 36.40%. Drug susceptibility test results showed that no carbapenem-resistant Escherichia coli stains were detected and 60.87% of Klebsiella pneumoniae strains were resistant to carbapenems. Acinetobacter baumannii strains were 100% resistant to three antimicrobial drugs. Methicillin-resistant Staphylococcus aureus strains accounted for 71.43%, but no vancomycin-resistant gram-positive cocci were found. Conclusions: Critical COVID-19 patients were mostly male and prone to multiple bacterial and fungal infections. The mortality of critical patients was higher than that of non-critical patients. Critical COVID-19 was often complicated by hospital acquired infections caused by bacteria including Acinetobacter baumannii and Klebsiella pneumoniae with high drug resistance. © 2021 Chinese Medical Association

17.
E3S Web Conf. ; 218, 2020.
Article in English | Scopus | ID: covidwho-1003344

ABSTRACT

The current COVID-19 pandemic creates the biggest aalth and economic challenges to the world. However, not much knowledge is available about this coronavirus, SARS-CoV-2, because of its novelty. Indeed, it necessarily knows the fate of proteins generated by SARS-CoV-2. Anyway, before a large-scale study on proteins from SARS-CoV-2, it would be better to conduct a small-scale study on a well-known protein from influenza A viruses, because both are positive-sense RNA viruses. Thus, we applied a simple method of amino-acid pair probability to analyze 94 neuraminidases of influenza A viruses for better understanding of t air fate. The results demonstrate three features of t ase neuraminidases: (i) the N1 neuraminidases are more susceptible to mutations, which is the current state of the neuraminidases;(ii) the N1 neuraminidases have undergone more mutations in the past, which is the history of the neuraminidases;and (iii) the N1 neuraminidases have a larger potential towards future mutations, which is the future of the neuraminidases. Moreover, our study reveals two clues on the mutation tendency, i.e. the mutations represent a degeneration process, and chickens, ducks and geese are rendered more susceptive to mutation. We hope to apply this approach to study the proteins from SARS-CoV-2 in near future. © The Authors, publis ad by EDP Sciences, 2020.

18.
J. Phys. Conf. Ser. ; 1682, 2020.
Article in English | Scopus | ID: covidwho-970095

ABSTRACT

The recent outbreak of COVID-19 pandemic is attributed to cross-species transmission of new coronavirus from bats to humans through unknown intermediate hosts, and the essence of the transmission is closely related to the mutations in coronaviruses. Furthermore, the effort to develop the vaccines against coronaviruses always faces the challenge of unexpected mutations in coronaviruses. In fact, it is very difficult to predict the mutations in any virus and bacterium, although mutations are a process of evolution. Over years, we have been applied the neural network to predict the mutations in proteins from influenza A viruses in comparison with the predictions using logistic regression. Our results are encouraging, but our approaches still need the improvements, for example, to upgrade to using machine learning and artificial intelligence instead of neural network. In this review, we summarize the rationales of neural network modelling, its strength and weakness, with the hope that we can apply the improved methods to predict the mutations in coronaviruses, thus to explore the origin of SARS-CoV-2, to find its intermediate host, and eventually to predict its mutations. © Published under licence by IOP Publishing Ltd.

19.
2020 Conference on Modern Management Based on Big Data, MMBD 2020 ; 329:132-146, 2020.
Article in English | Scopus | ID: covidwho-945607

ABSTRACT

The sudden emergence of 'COVID-19' in 2020 has tightened traffic control in various places, which has posed a huge challenge to the agricultural product supply chain. This research introduces the perspective of supply chain finance, uses in-depth case study methods, and takes Suning's agricultural supply chain finance as an example to discuss how e-commerce companies relying on big data adopt agricultural supply chain finance practices to promote accurate poverty alleviation. By analyzing Suning's four agricultural supply chain financial operation models, we find that the internal and external stakeholders of the enterprise are the driving factors for enterprises to adopt agricultural supply chain finance, and the adoption of agricultural supply chain finance measures has brought economic benefits and social benefits to enterprises benefit. Advanced big data tools, fintech and cooperation with other partners are necessary to adopt agricultural supply chain financial measures. © 2020 The authors and IOS Press.

20.
Studies in Philosophy and Education ; 2020.
Article in English | Scopus | ID: covidwho-932591

ABSTRACT

The article seeks to reclaim a type of fear lost in silent omission in education, yet central to the development of an ethical subject. It distinguishes the fear described by Martin Heidegger through the concept of befindlichkeit and fear for the other as an essential moment for ethics articulated by Emmanuel Levinas. It argues that the latter conception of fear has inverted the traditional assumption of the ideal ethical subject as fearless. It then examines how Levinas’s interpretation of fear might contribute to the discussion on fear and responsibility in the context of the COVID-19 pandemic. It concludes that fear for the other reveals our tremendous capacity to suffer for the other, which is an aspect of the emotional life that has not been identified in the general educational discourse. This inattention manifests itself as a categorical omission in which the existence of fear for the other is not recognized and impedes the ability of educators to address ethics as it is deeply lived. © 2020, Springer Nature B.V.

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