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Objective To improve the diagnosis and treatment level for tuberculous meningitis (TBM) under the Coronavirus disease 2019 (COVID-19) epidemic. Methods The diagnosis and treatment course of a female patient under the COVID-19 epidemic was analyzed for high fever, vomiting for 23 days, headache, talk nonsense for 10 days, inability to stand, and double vision lasting 5 days. The patient was successively misdiagnosed to suffer from viral pneumonia and acute disseminated encephalomyelitis (ADEM) in other hospitals. The patient had a history of transit at Hankou railway station (wearing a mask without departing the station throughout the process) under the COVID-19 epidemic. The patient had a history of leukopenia and long-term medical therapy. The patient was diagnosed as TBM by applying the diagnostic scheme for the 2019 China Central Nervous System Tuberculosis Diagnosis and Treatment Guidelines after physical examination, cerebrospinal fluid test, magnetic resonance imaging (MRI) plain scan and enhanced examination. The analysis on reasons for extramural hospital misdiagnosis showed it was related to the lack of careful physical examination and lack of scientific analysis of laboratory test results. Results The intracranial pressure reduction, anti-tuberculosis treatment, adrenal cortex hormone treatment and symptomatic treatment were immediately administered according to the 2019 China Central Nervous System Tuberculosis Diagnosis and Treatment Guidelines. Intensive anti-tuberculosis treatment (4 months) was implemented firstly and followed by the anti-tuberculosis treatment (12 months) during the consolidation phase, clinically enabling the patient to be cured. Conclusion Careful inquiry of medical history, careful physical examination, timely cerebrospinal fluid examination and MRI examination and scientific analysis on clinical data are critical to confirmation of TBM. Standard anti-tuberculosis treatment, rational use of adrenal cortex hormones and lowering intracranial pressure are critical factors for curing. © 2023, Editorial Department of Medical Pest Control. All rights reserved.
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Objective To improve the diagnosis and treatment level for tuberculous meningitis (TBM) under the Coronavirus disease 2019 (COVID-19) epidemic. Methods The diagnosis and treatment course of a female patient under the COVID-19 epidemic was analyzed for high fever, vomiting for 23 days, headache, talk nonsense for 10 days, inability to stand, and double vision lasting 5 days. The patient was successively misdiagnosed to suffer from viral pneumonia and acute disseminated encephalomyelitis (ADEM) in other hospitals. The patient had a history of transit at Hankou railway station (wearing a mask without departing the station throughout the process) under the COVID-19 epidemic. The patient had a history of leukopenia and long-term medical therapy. The patient was diagnosed as TBM by applying the diagnostic scheme for the 2019 China Central Nervous System Tuberculosis Diagnosis and Treatment Guidelines after physical examination, cerebrospinal fluid test, magnetic resonance imaging (MRI) plain scan and enhanced examination. The analysis on reasons for extramural hospital misdiagnosis showed it was related to the lack of careful physical examination and lack of scientific analysis of laboratory test results. Results The intracranial pressure reduction, anti-tuberculosis treatment, adrenal cortex hormone treatment and symptomatic treatment were immediately administered according to the 2019 China Central Nervous System Tuberculosis Diagnosis and Treatment Guidelines. Intensive anti-tuberculosis treatment (4 months) was implemented firstly and followed by the anti-tuberculosis treatment (12 months) during the consolidation phase, clinically enabling the patient to be cured. Conclusion Careful inquiry of medical history, careful physical examination, timely cerebrospinal fluid examination and MRI examination and scientific analysis on clinical data are critical to confirmation of TBM. Standard anti-tuberculosis treatment, rational use of adrenal cortex hormones and lowering intracranial pressure are critical factors for curing. © 2023, Editorial Department of Medical Pest Control. All rights reserved.
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The COVID-19 pandemic has drastically affected everyday life and business. To describe the impacts, 566 COVID-19-related articles were published between January 2020 and March 2022 in 18 hospitality and tourism journals. This study identifies the research streams, using content and bibliometric analyses. Content analysis and co-citation analysis revealed six research streams and four research clusters, respectively. A critical analysis was conducted to reflect the theoretical and practical implications and provide suggestions for future research directions. The identified research weaknesses include concerns relating to generalizability, sampling and measurement-related issues, online survey methods, failure to identify different stakeholders' views on the adoption of new technologies, lack of practical coping scheme studies, lack of effort to adopt multidisciplinary theories, and little exploration of customers' reactions to virtual events. Results of this study can help facilitate and consolidate the knowledge on the impacts of the pandemic and proactively prepare for future disease crises. © The Author(s) 2023.
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Background: Traditional Chinese medicine (TCM) plays a crucial role in the prevention and control of coronavirus disease 2019 (COVID-19). Objective: The study aimed to reveal the distribution characteristics of COVID-19 TCM syndrome types and syndrome elements and the law of TCM treatment and medication. Methods: The TCM diagnosis and treatment protocol for COVID-19 and clinical research data were obtained through network retrieval, and Revman 5.3 and SPSS 23.0 were employed to analyze the composition of TCM syndromes and the situation of TCMs in meta and frequency. Results: The top three TCM syndromes of COVID-19 included damp-heat accumulation in the lung pattern, damp abundance due to spleen deficiency, and epidemic toxin invading the lung pattern, while the syndrome elements were dampness, heat, and toxin. Gypsum fibrosum, Pogostemonis herba, and Armeniacae semen were identified as the commonly used drugs. Different syndrome elements were identified at lung disease location: Forsythiae fructus, Glycyrrhizae radix, and Armeniacae semen can be used for "wind;" Glycyrrhizae radix, Armeniacae semen, and Scutellariae radix can be used for "Heat;" Armeniacae semen, Sheng Gypsum fibrosum, and Ephedrae herba can be used for "Toxin;" Ephedrae herba, Armeniacae semen, and Atractylodis rhizome can be used for "Damp;" Magnoliae officinalis Cortex, Ephedrae herba, and Zingiberis Rhizoma recens can be used for "cold;" and Armeniacae semen, Gypsum fibrosum, Ephedrae herba, and Lepidii/Descurainiae semen can be used for "epidemic. " Conclusion: The establishment of a treatment scheme based on the classification of disease syndrome elements should be considered for sudden infectious diseases, such as COVID-19. Pogostemonis herba, Armeniacae semen, Gypsum fibrosum, and Glycyrrhizae radix should be considered as effective drugs from TCM for the treatment of COVID-19.
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Disulfiram is an FDA-approved drug that has been used to treat alcoholism and has demonstrated a wide range of anti-cancer, anti-bacterial, and anti-viral effects. In the global COVID-19 pandemic, there is an urgent need for effective therapeutics and vaccine development. According to recent studies, disulfiram can act as a potent SARS-CoV-2 replication inhibitor by targeting multiple SARS-CoV-2 non-structural proteins to inhibit viral polyprotein cleavage and RNA replication. Currently, disulfiram is under evaluation in phase II clinical trials to treat COVID-19. With more and more variants of the SARS-CoV-2 worldwide, it becomes critical to know whether disulfiram can also inhibit viral entry into host cells for various variants and replication inhibition. Here, molecular and cellular biology assays demonstrated that disulfiram could interrupt viral spike protein binding with its receptor ACE2. By using the viral pseudo-particles (Vpps) of SARS-CoV-2, disulfiram also showed the potent activity to block viral entry in a cell-based assay against Vpps of different SARS-CoV-2 variants. We further established a live virus model system to support the anti-viral entry activity of disulfiram with the SARS-CoV-2 virus. Molecular docking revealed how disulfiram hindered the binding between the ACE2 and wild-type or mutated spike proteins. Thus, our results indicate that disulfiram has the capability to block viral entry activity of different SARS-CoV-2 variants. Together with its known anti-replication of SARS-CoV-2, disulfiram may serve as an effective therapy against different SARS-CoV-2 variants.
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As important personal protective equipment (PPE), face masks play a key role in self-protection during disastrous pandemics caused by the COVID-19 virus and other respiratory viruses. On the other hand, the massive utilization of disposable face masks creates big challenges not only in recycling and sterilizing the used face masks, but also in terms of plastic pollution and resource-saving. So, the development of self-sanitizing reusable face masks is highly imperative. We report herein a covalent organic framework (COF)-based face mask. In this regard, a Ag NP loaded and quinolinecarboxylic acid-linked nanoscale porphyrin COF composite of Ag@DhaTph-COOH is constructed by a three-component one-pot in situ Doebner reaction and sequential solution impregnation and NaBH4 reduction. After mixing the hydroxyl-enriched COF NPs with isocyanate-terminated polyurethane oligomers, the obtained covalently cross-linked COF-dispersion is sprayed onto the outer layer of the non-woven PET fabric surface to yield a face mask with the deposited Ag@DhaTph-COOH NPs. Our face mask is reusable and exhibits solar-powered self-sanitizing ability with excellent antibacterial and antiviral performance via a triple-modal chemo/PDT/PTT synergistic treatment under natural sunlight irradiation.
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Objective: To understand the epidemiological characteristics of three local COVID-19 epidemics in Guangzhou and provide reference for optimizing strategies and measures of COVID-19 prevention and control. Methods: The data of local COVID-19 cases in Guangzhou reported as of June 18, 2021 were collected from National Notifiable Disease Report System of China. The software Excel 2019 and SPSS 22.0 were applied for data cleaning and statistical analysis. Results: A total of 726 COVID-19 cases were reported in the three local epidemics in Guangzhou. In the epidemic associated with the outbreak of COVID-19 in Hubei province, 366 cases were reported. Most cases were female (51.6%, 189/366), aged 18-65 years (81.4%, 298/366), jobless/unemployed (32.2%, 118/366) and retired persons (20.2%,74/366). The initial symptoms of most cases were fever (71.6%, 250/349) and cough (60.7%, 212/349). In the epidemic associated with the imported COVID-19 cases from Africa, 207 cases were reported. Most cases were aged 18-40 years (72.9%, 151/207), male (69.6%, 144/207), and engaged in commercial services (62.3%,129/207). The initial symptoms of most cases were no obvious discomfort (55.6%, 15/27) and cough (37.0%, 10/27). In the epidemic associated with Delta variant of SARS-CoV-2, 153 cases were reported, in which women accounted for 58.8% (90/153), most cases were over 41 years old (64.7%,99/153), and retired persons accounted for the highest proportion (32.0%,49/153). The initial symptoms of most cases were cough (32.9%, 48/146) and no obvious discomfort (28.1%, 41/146). The household secondary attack rates of the three local epidemics were 11.2%, 5.7% and 11.5%, respectively. The median (P25, P75) of incubation periods were 6.5 (4.0,10.8) d, 4.0 (2.5, 6.0) d and 4.0 (3.0,5.0) d. The serial intervals median (P25, P75) were 4.0 (3.0, 8.0) d, 4.0 (2.5, 6.0) d and 3.0 (2.0,5.0) d. There were significant differences in gender, age, occupation, initial symptoms, household secondary attack rate and incubation period among the three local COVID-19 epidemics (all P<0.05). In the proportion of the case finding way, passive detection in patient treatment were mainly 44.3%(162/366) in the epidemic associated with the outbreak of COVID-19 in Hubei province,but active community case screening [58.5% (121/207) and 27.5% (24/153)] and close contact management in imported case were mostly [33.3% (69/207) and 67.3% (103/153)] in the epidemic associated with the imported COVID-19 cases from Africa and with Delta variant of SARS-CoV-2, respectively. Conclusions: Due to the different sources of infection, strain types and prevention and control strategies, the epidemiological characteristics of the three local COVID-19 epidemics in Guangzhou differed in demographics, clinical symptoms, transmission routes and case finding, which suggested that it is necessary to improve the key population and common symptom monitoring in the routine prevention and control of COVID-19 to prevent the reemerge of the epidemic.
Subject(s)
COVID-19 , Epidemics , Adult , China/epidemiology , Female , Humans , Male , SARS-CoV-2ABSTRACT
Image recognition has been applied to many fields, but it is relatively rarely applied to medical images. Recent significant deep learning progress for image recognition has raised strong research interest in medical image recognition. First of all, we found the prediction result using the VGG16 model on failed pneumonia X-ray images. Thus, this paper proposes IVGG13 (Improved Visual Geometry Group-13), a modified VGG16 model for classification pneumonia X-rays images. Open-source thoracic X-ray images acquired from the Kaggle platform were employed for pneumonia recognition, but only a few data were obtained, and datasets were unbalanced after classification, either of which can result in extremely poor recognition from trained neural network models. Therefore, we applied augmentation pre-processing to compensate for low data volume and poorly balanced datasets. The original datasets without data augmentation were trained using the proposed and some well-known convolutional neural networks, such as LeNet AlexNet, GoogLeNet and VGG16. In the experimental results, the recognition rates and other evaluation criteria, such as precision, recall and f-measure, were evaluated for each model. This process was repeated for augmented and balanced datasets, with greatly improved metrics such as precision, recall and F1-measure. The proposed IVGG13 model produced superior outcomes with the F1-measure compared with the current best practice convolutional neural networks for medical image recognition, confirming data augmentation effectively improved model accuracy.
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Given the rapid development of digitization, social media has become a key platform for digital campaigns to promote business and products, with an aim of maximizing profits. Yet, empirical evidence on the performance of a digital campaign for smart tourism and on-line purchasing remains under explored. Using an innovative design of an ecosystem for both smart tourism and on-line purchasing promotion becomes an important tool especially during mobility restriction due to COVID-19. The research was carried out studying the construction and operation of an ecosystem for smart tourism and on-line purchasing of one case of China. Key findings identify components of the ecosystem and its working mechanisms promoting smart tourism and on-line purchasing, and reveal the performance of the digital campaign. Although a larger data amount should be grasped by designing a more comprehensive ecosystem, results of the research show the effectiveness of social media as a marketing platform for smart tourism essence as “products”, and how an ecosystem is constructed and applied at a smart tourism destination, together with its logic combining and promoting smart tourism together with on-line purchasing. © WMSCI 2021.All right reserved.
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OBJECTIVE: Global health resources have faced huge challenges from the pandemic coronavirus disease 2019 (COVID-19) since December 2019. Numerous clinical reports have focused on the association of serum amyloid A (SAA) levels with severe COVID-19. However, a systematic analysis synthesizing these findings has not been performed. This meta-analysis aims to systematically review the role of SAA levels in distinguishing among patients with mild, severe, and critical COVID-19. MATERIALS AND METHODS: A comprehensive literature search was conducted in the PubMed, Embase, and Web of Science databases from the beginning of the COVID-19 outbreak to February 1, 2021. Two investigators independently reviewed suitable studies. Pooled standardized mean differences (SMDs), 95% confidence intervals (CIs), and correlation coefficients (r) were computed using a random-effects model. RESULTS: We included 19 of 317 titles identified by our search, involving a total of 1806 mild cases and 1529 severe cases. Compared with the mild group, the severe group had markedly higher SAA levels (SMD=1.155, 95% CI 0.89, 1.42). Subgroup analysis revealed that the SAA level differences between the severe group and the mild group were associated with age, sample size, and detection method. Sensitivity analyses showed the credibility and robustness of our results. In addition, in six studies involving 1144 patients with severe COVID-19 and 433 patients with critical COVID-19, SAA was significantly higher in patients with critical COVID-19 (SMD=0.476, 95% CI 0.13, 0.82). CONCLUSIONS: High circulating SAA levels were markedly associated with COVID-19 severity, especially for subjects aged less than 50 years, compared with patients with mild COVID-19. SAA concentrations were also significantly higher in patients with critical COVID-19 compared with those with severe COVID-19. Further studies in large cohorts are needed to confirm whether the SAA is a useful tool in discriminating among patients with stable COVID-19, those with acute exacerbations, and subjects without disease.
Subject(s)
COVID-19/blood , Serum Amyloid A Protein/analysis , Severity of Illness Index , HumansABSTRACT
At the beginning of 2020, coronavirus disease 2019 (COVID-19) spread quickly throughout China. For the health and safety of faculties and students, all schools and universities were required to postpone their spring semester;however, the Ministry of Education hoped that teaching and learning could be facilitated to decrease or even eliminate the negative impact of the postponement on the students' subsequent self-development. Taking the "Principles of Electric Circuits" course as an example, this paper presents an innovative online teaching scheme for fundamental engineering courses, including pedagogical design and interactive methods in lectures. The students' feedback was collected using delicately designed questionnaires and the results demonstrated that our online teaching scheme achieved an effect no less than that from traditional in-classroom teaching, with even better student interactions using the online networks.