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1.
Traditional Medicine Research ; 8(3), 2023.
Article in English | Web of Science | ID: covidwho-2207099

ABSTRACT

Background: Shengmai decoction, which has been included in the diagnosis and treatment of coronavirus disease 2019 (COVID-19), is effective in the early treatment of patients with severe COVID-19. Yiqi Fumai lyophilized injection (YQFM) is a modern Chinese medicine preparation of the Shengmai decoction. The mechanism of its intervention at the molecular level in the severe stage of COVID-19 remains unclear. Therefore, it is necessary to investigate the mechanism of YQFM in the treatment of patients with severe COVID-19. Methods: The corresponding target genes of the main active ingredients in YQFM and COVID-19 were obtained by using multiple databases and literature retrieval. A protein-protein interaction network was constructed, and enrichment analysis of the target was performed using Cytoscape 3.8.1. Lastly, the docking of all the identified compounds with angiotensin-converting enzyme II was confirmed by applying molecular docking technology. Results: YQFM has anti-inflammatory effects on RAW267.4 macrophages. The main active compounds of YQFM are all effective anti-inflammatory agents, and these active compounds also show beneficial physiological functions, such as anti-oxidation, anti-bacterial, and anticancer activities. Gene Ontology analysis showed enrichment in the following pathways: lipopolysaccharides, interleukins, NF-kappa B, interleukin-2 and others, revealing that YQFM may play a role in the treatment of patients with severe COVID-19 through these pathways. Conclusion: YQFM has multicomponent and multitarget characteristics, and it could reduce lung injury by inhibiting inflammatory reactions, promoting antiviral activities, and regulating immunity, among other functions, to treat patients with severe COVID-19.

2.
ACS Appl Bio Mater ; 6(1):238-245, 2023.
Article in English | MEDLINE | ID: covidwho-2185490

ABSTRACT

Since the onset of the SARS-CoV-2 pandemic, the world has witnessed over 617 million confirmed cases and more than 6.54 million confirmed deaths, but the actual totals are likely much higher. The virus has mutated at a significantly faster rate than initially projected, and positive cases continue to surge with the emergence of ever more transmissible variants. According to the CDC, and at the time of this manuscript submission, more than 77% of all current US cases are a result of the B.5 (omicron). The continued emergence of highly transmissible variants makes clear the need for more effective methods of mitigating disease spread. Herein, we have developed an antimicrobial fabric capable of destroying a myriad of microbes including betacoronaviruses. We have demonstrated the capability of this highly porous and nontoxic metal organic framework (MOF), gamma-CD-MOF-1, to serve as a host for varied-length benzalkonium chlorides (BACs;active ingredient in Lysol). Molecular docking simulations predicted a binding affinity of up to -4.12 kcal.mol(-1), which is comparable to that of other reported guest molecules for this MOF. Similar Raman spectra and powder X-ray diffraction patterns between the unloaded and loaded MOFs, accompanied by a decrease in the Brunauer-Emmett-Teller surface area from 616.20 and 155.55 m(2) g(-1) respectively, corroborate the suggested potential for pore occupation with BAC. The MOF was grown on polypropylene fabric, exposed to a BAC-loading bath, washed to remove excess BAC from the external surface, and evaluated for its microbicidal activity against various bacterial and viral classes. Significant antimicrobial character was observed against Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, bacteriophage, and betacoronavirus. This study shows that a common mask material (polypropylene) can be coated with BAC-loaded gamma-CD-MOF-1 while maintaining the guest molecule's antimicrobial effects.

3.
Front Pharmacol ; 13, 2022.
Article in English | PubMed Central | ID: covidwho-2163081

ABSTRACT

Chloroquine was once thought to be a promising treatment for COVID-19 but it quickly failed due to its inefficiency and association with increased mortality. Further, comorbidities such as hypertension may have contributed this failure. The safety and toxicity of chloroquine at doses required for treating SARS-CoV-2 infection in hypertensive patients remain unknown. Herein, to investigate these effects, we performed a safety evaluation of chloroquine at the approved dose (63 mg/kg) and at a high dose (126 mg/kg) in hypertensive rats. We found that chloroquine increased the mortality of hypertensive rats to 18.2% and 100%, respectively, after 7 days. During the chloroquine exposure period, the bodyweight, feed, and water consumption of hypertensive rats were decreased significantly. In addition, we show that chloroquine induces prolongation of QTc interval, elevation of LDH and CK, and histopathological damage of the myocardium in hypertensive rats. Ocular toxicity was observed in hypertensive rats in the form of hemorrhage in the eyes and retinal damage. Furthermore, we also observed intestinal toxicity in hypertensive rats, which presented as thinning intestinal walls with hemorrhagic contents, and histopathological changes of the jejunum. Hepatotoxicity was also evidenced by elevated ALT, and vacuolization of hepatocytes was also observed. Nephrotoxicity was observed only in high dose chloroquine-treated hypertensive rats, presenting as alterations of urinalysis and renal function. Immune alterations were also found in high-dose chloroquine-treated hypertensive rats with elevation of serum IL-10, IL-1β and GRO, and moderate damage to the spleen. In summary, this study partially explains the reason for the failure of chloroquine as a COVID-19 therapy, and underlines the importance of safety evaluation and medical supervision of chloroquine to avoid patient harm, especially to those with hypertension.

4.
6th International Conference on Education and Multimedia Technology, ICEMT 2022 ; : 451-458, 2022.
Article in English | Scopus | ID: covidwho-2153132

ABSTRACT

The outbreak of COVID-19 has accelerated the development of artificial intelligence and promoted the method of online teaching. In the post-pandemic era, modern information technology and teaching represented by artificial intelligence are increasingly converging, and they are also facing increasing difficulties and challenges. For example, the educational concept lags behind the technology development, the information literacy of teachers and students needs to be improved, and the humanistic emotional exchange in the information-based classroom is not enough. Primary and secondary school teachers need to constantly update the concept of information education, strengthen the awareness of learning and application of artificial intelligence, adhere to the belief that computer information technology serves people, improve their ability to apply information technology to innovative teaching, and focus on classroom innovation and reform. © 2022 ACM.

5.
J Med Virol ; 2022.
Article in English | PubMed | ID: covidwho-2148393

ABSTRACT

OBJECTIVES: To investigate COVID-19 vaccine coverage in immunosuppressed children, assess guardians' intention to vaccinate children, and determine reasons and associated factors. In addition, we attempted to capture the characteristics of them with Omicron. METHODS: We obtained the vaccination coverage and guardian vaccine acceptance among pediatric transplant recipients through a web-based questionnaire conducted from April 12 to April 28, 2022, and performed the statistical analysis. Seven organ transplant recipient children with Omicron were also clinically analyzed. RESULTS: The three-dose vaccine coverage for LT (n = 563) and HSCT (n = 122) recipient children was 0.9% and 4.9%, and guardian vaccine acceptance was 63.8%. Independent risk factors for vaccine acceptance were the child's age, geographic location, type of transplant, guardian's vaccination status, guardian's level of distress about epidemic events, guardian's risk perception ability, anxiety, and knowledge of epidemic control. The main reasons for vaccine hesitancy were fear of vaccine-induced adverse events and doubts about efficacy. Ultimately, most children infected with Omicron have mild or no symptoms and are infected by intra-family. CONCLUSIONS: Since vaccine coverage and guardian acceptance are lowest among liver transplant children, and the infected are mainly intra-family, we should devise more targeted education and vaccination instructions for their guardians. This article is protected by copyright. All rights reserved.

6.
IEEE Sensors Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2136429

ABSTRACT

Due to the COVID-19 global pandemic, there are more needs for remote patient care especially in rehabilitation requiring direct contact. However, traditional Chinese rehabilitation technologies, such as gua sha, often need to be implemented by well-trained professionals. To automate and professionalize gua sha, it is necessary to record the nursing and rehabilitation process and reproduce the process in developing smart gua sha equipment. This paper proposes a new signal processing and sensor fusion method for developing a piece of smart gua sha equipment. A novel stabilized numerical integration method based on information fusion and detrended fluctuation analysis (SNIF-DFA) is performed to obtain the velocity and displacement information during gua sha operation. The experimental results show that the proposed method outperforms the traditional numerical integration method with respect to information accuracy and realizes accurate position calculations. This is of great significance in developing robots or automated machines that reproduce the nursing and rehabilitation operations of medical professionals. IEEE

7.
2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations (Naacl-Hlt 2021) ; : 66-77, 2021.
Article in English | Web of Science | ID: covidwho-2068449

ABSTRACT

To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities and their visual chemical structures, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence. All of the data, KGs, reports(1), resources, and shared services are publicly available(2).

8.
19th IEEE International Conference on Mechatronics and Automation, ICMA 2022 ; : 997-1002, 2022.
Article in English | Scopus | ID: covidwho-2052008

ABSTRACT

Socia1 distance has been a growing concern since the COVID-19 pandemic broke out globally. Statistics indicate that keeping social distance is of great practical significance in slowing the spread of the pandemic. Traditional ranging methods rely on ultrasonic, infrared, laser or others. Unfortunately, most of these methods require Bluetooth modules or particular measuring sensors and need to fix hardwire devices on objects, which makes it costly and difficult to apply for measuring distances in various scenes. In order to reduce cost and extend application scope, this paper studies a novel ranging method based on monocular vision, which is proposed to estimate the distance between people in surveillance images. Our approach is to measure the social distance via the world coordinate relationship transformation or the principle of pinhole imaging after performing pedestrian detection. It is worth mentioning that this method only needs computer monocular vision technology, which is low in cost and suitable for an abundance of application scenarios. Through the experiment and analysis, our method shows good performance of social distance measuring in application. © 2022 IEEE.

9.
11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022 ; : 929-934, 2022.
Article in English | Scopus | ID: covidwho-2051966

ABSTRACT

As a huge disaster for humanity, the COVID-19 has caused many negative effects on the lives of people around the world with a rapid growth. Moreover, the global pandemic of Neocoronavirushas produced many mutated strains. Although the most commonly used test for COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR), CXR becomes an irreplaceable tool for the diagnosis and analysis for a more complete and accurate visualization of the lung lesion process. Therefore, it is of high value for classification and identification studies. In this paper, the high-frequency emphasis filtering based convolutional neural networks (HFEF-CNN) are proposed for solving the automatic detection of COVID-19. Firstly, the HFEF is used to denoise the image data to make some features in the image more obvious. Then some major CNNs are used to train image classification models to achieve better detection performance. Finally, Some experiments are conducted on the 'COVID-19 Chest X-Ray Database' dataset. To verify the effectiveness of the HFEF-CNN, a histogram equalization based CNN (HE-CNN) and a restricted contrast adaptive histogram equalization based CNN (CLAHE-CNN) are compared. The experimental results show that the HFEF-CNN outperformed the above two methods. © 2022 IEEE.

10.
28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022 ; : 4790-4791, 2022.
Article in English | Scopus | ID: covidwho-2020401

ABSTRACT

Misinformation is a pressing issue in modern society. It arouses a mixture of anger, distrust, confusion, and anxiety that cause damage on our daily life judgments and public policy decisions. While recent studies have explored various fake news detection and media bias detection techniques in attempts to tackle the problem, there remain many ongoing challenges yet to be addressed, as can be witnessed from the plethora of untrue and harmful content present during the COVID-19 pandemic, which gave rise to the first social-media infodemic, and the international crises of late. In this tutorial, we provide researchers and practitioners with a systematic overview of the frontier in fighting misinformation. Specifically, we dive into the important research questions of how to (i) develop a robust fake news detection system that not only fact-checks information pieces provable by background knowledge, but also reason about the consistency and the reliability of subtle details about emerging events;(ii) uncover the bias and the agenda of news sources to better characterize misinformation;as well as (iii) correct false information and mitigate news biases, while allowing diverse opinions to be expressed. Participants will learn about recent trends, representative deep neural network language and multimedia models, ready-to-use resources, remaining challenges, future research directions, and exciting opportunities to help make the world a better place, with safer and more harmonic information sharing. © 2022 Owner/Author.

11.
28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2022 ; : 4832-4833, 2022.
Article in English | Scopus | ID: covidwho-2020400

ABSTRACT

Exploring the vast amount of rapidly growing scientific text data is highly beneficial for real-world scientific discovery. However, scientific text mining is particularly challenging due to the lack of specialized domain knowledge in natural language context, complex sentence structures in scientific writing, and multi-modal representations of scientific knowledge. This tutorial presents a comprehensive overview of recent research and development on scientific text mining, focusing on the biomedical and chemistry domains. First, we introduce the motivation and unique challenges of scientific text mining. Then we discuss a set of methods that perform effective scientific information extraction, such as named entity recognition, relation extraction, and event extraction. We also introduce real-world applications such as textual evidence retrieval, scientific topic contrasting for drug discovery, and molecule representation learning for reaction prediction. Finally, we conclude our tutorial by demonstrating, on real-world datasets (COVID-19 and organic chemistry literature), how the information can be extracted and retrieved, and how they can assist further scientific discovery. We also discuss the emerging research problems and future directions for scientific text mining. © 2022 Owner/Author.

12.
60th Annual Meeting of the Association-for-Computational-Linguistics (ACL) ; : 135-144, 2022.
Article in English | Web of Science | ID: covidwho-1976151

ABSTRACT

The COVID-19 pandemic has received extensive media coverage, with a vast variety of claims made about different aspects of the virus. In order to track these claims, we present COVID-19 Claim Radar(1), a system that automatically extracts claims relating to COVID-19 in news articles. We provide a comprehensive structured view of such claims, with rich attributes (such as claimers and their affiliations) and associated knowledge elements (such as events, relations and entities). Further, we use this knowledge to identify inter-claim connections such as equivalent, supporting, or refuting relations, with shared structural evidence like claimers, similar centroid events and arguments. In order to consolidate claim structures at the corpus-level, we leverage Wikidata(2) as the hub to merge coreferential knowledge elements, and apply machine translation to aggregate claims from news articles in multiple languages. The system provides users with a comprehensive exposure to COVID-19 related claims, their associated knowledge elements, and related connections to other claims. The system is publicly available on GitHub(3) and DockerHub(4), with complete documentation(5).

13.
International Journal of Advanced and Applied Sciences ; 9(6):110-118, 2022.
Article in English | Web of Science | ID: covidwho-1918249

ABSTRACT

This paper analyzes trends in forest healing studies based on the published graduates' theses and domestic journals in Korea from January 1, 2006, to June 30, 2021. The results of the study will provide data for forest healing researchers. According to the research results, research related to forest healing in Korea has been steadily increasing since the early 2000s, and from 2020, most works are being actively performed. The gender ratio of researchers was 5.4% higher in females than males in the case of degree dissertations and 25.0% higher in males than females in the case of journals. In terms of publication type, the highest number of journals was 184 articles (61.3%), followed by master's thesis with 82 articles (27.3%) and doctoral dissertation with 34 articles (11.3%). In terms of research methods, most of the papers (77.3%) are quantitative studies. When the study subjects were classified into the general group, occupational group, disease group, and social target, the general group for the purpose of prevention were the most with 78 articles (61.9%). The topics of the papers related to forest healing were in the order of analysis of the effects of forest healing programs, development of forest healing programs, and forest healing facilities. At a time when more attention is being paid to forests, which are places of healing due to the COVID-19 pandemic, it becomes basic data for forest healing researchers through objective data analysis of domestic forest healing. When analyzing domestic and foreign trends in the future, if you analyze paradigm changes and trends in various media, such as news as well as YouTube videos, using big data-related technologies that have been used in recent research papers, broader insights can be provided. (C) 2022 The Authors. Published by IASE.

14.
Progress in Chemistry ; 34(1):207-226, 2022.
Article in English | Web of Science | ID: covidwho-1870090

ABSTRACT

The novel coronavirus pneumonia epidemic (COVID over line 19) brings a serious threat to the development of human society and the health of human beings. Due to the stability of the severe acute respiratory syndrome coronavirus 2 ( SARS over line CoV over line 2) in urban sewage, which has become one of the virus pollution sources, it has been a focus how to eliminate the existing virus in water. SARS over line CoV over line 2 structurally consists of RNA chains and protein capsids, and thus can be inactivated via reactive oxygen species ( ROS) attack. Moreover, block of biochemical metabolism and destruction of virus structure are also effective inactivation methods for SARS over line CoV over line 2 inactivation. Nanomaterials exhibit surface and interface effects, specific microstructure and excellent physicochemical properties, implying their high application potential in SARS over line CoV over line 2 inactivation. In this study, we overall review application of nanotechnologies for SARS over line CoV over line 2 inactivation, including photocatalysis, heterogeneous catalytic oxidation, ion toxicity induced inactivation, and structural effects inactivation method. Furthermore, based on the structural composition, as well as survival and transmission characteristics of SARS over line CoV over line 2 in water environment, the application potential of various nanotechnologies for SARS over line CoV over line 2 inactivation are deeply discussed. This study can provide a theoretical basis and practical reference for the application of nanotechnology for the SARS over line CoV over line 2 inactivation and the secondary transmission interruption in water.

15.
Chinese Journal of Laboratory Medicine ; 44(5):388-393, 2021.
Article in Chinese | EMBASE | ID: covidwho-1526869

ABSTRACT

Objective: To evaluate the impact of sample pooling strategy on 2019-nCoV RNA detection results. Methods: Ten negative swabs were stored in 6 ml virus transport medium, mixed thoroughly and diluted 1:2 and 1:10. Inactivated 2019-nCoV culture medium was added to simulate pooling samples: 10 pooling samples, 5 pooling samples and 1 swab sample. Extraction and amplification were made using three nucleic acid extraction reagents a, b, and c with different extraction methods and systems, as well as five 2019-nCoV detection reagents A-E with various template loading volumes and sensitivities respectively. Results: For the same sample, the Ct values of extracted templates a were 2.10±0.47 and 3.46±0.62 earlier than extracted templates b and c. For samples with identical amplifying, the Ct valves of N and ORF1ab gene of A reagent were 1.16±0.48 and 2.36±0.54 earlier than that of reagent B. Adding nucleic acid of 10 negative swabs to the amplification system lagged the Ct values of reagent A by about 1.36±0.32 Ct, while Ct values of reagent B were not affected. Extracted by regent a, a lag of 1.66±0.39 Ct on average was observed in C, D, and E reagents in detecting pooling samples of ten swabs as compared with one swab sample. When extracting 400 copies/ml pooling samples of ten swabs by reagent a, N gene could be detected by reagents C and E, but not by reagent D. Conclusion: Large amount of extraneous DNA is introduced by sample pooling, which could interfere the effiency of extraction and amplification. Strategies of using extraction reagents with large loading volume and high effiency, together with amplification reagents with large template volume and low limit of detection are helpful for ensuring detection sensitivity of pooling samples, and greatly reducing the risk of false negative results.

16.
Basic & Clinical Pharmacology & Toxicology ; 128:208-208, 2021.
Article in English | Web of Science | ID: covidwho-1113112
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