ABSTRACT
Facing the unprecedented epidemic situation of novel coronavirus pneumonia (COVID-19), medical workers in China have not only successfully controlled the spread of the epidemic in Chinese mainland in just 4 months, but also have made great achievements in scientific research on COVID-19. In the past 4 months, a total of 1 033 English papers about COVID-19 written by Chinese scholars have been published and included in PubMed database, which is 6.6 times the number of articles published in 2003. The proportion of papers published by authors in Chinese mainland has increased from 48.7% (76/156) during the SARS epidemic in 2003 to 84.8% (876/1 033) with 4 months in 2020. The papers were also published significantly earlier than before. Chinese researchers identified the novel coronavirus that caused the outbreak less than 1 month after the COVID-19 outbreak (on January 7, 2020) and reported it to the WHO. They also published articles on the genetic sequence and transmission dynamics of the virus and clinical characteristics of COVID-19 patients in that month. China pays more attention to drug safety of patients. The proportion of English and Chinese literature published by pharmaceutical authors increased from 0 and 0.2% (10/4 023) in 2003 to 2.3% (24/1 032) and 9.3% (215/2 317) from January to April in 2020, respectively. China has not only become a model for the world in epidemic control, but also made important contributions to the relevant academic research.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
The coronavirus disease 2019 (COVID-19) epidemic is facing the most critical situation. As of January 11, 2021, there have been nearly 90 million confirmed cases worldwide and nearly 2 million deaths. The local epidemic situation in China is sporadic and locally clustered, and the situation of epidemic prevention is difficult and complicated. In this situation, there are many problems in medication safety of patients, such as safety issues in off-label medication and compassionate medication of COVID-19 treatment, safety problems in the combination use of drugs for COVID-19 and drugs for other diseases, monitoring of adverse drug reactions in COVID-19 treatment, the safety issues in self-purchased drugs for prevention and treatment of COVID-19, and the medication safety in patients with other diseases during the epidemic. Therefore, it is necessary to pay more attention to the medication safety of patients to fight the epidemic scientifically and to win a greater victory in the fight against the COVID-19 epidemic at a smaller price.Copyright © 2021 Chinese Medical Association
ABSTRACT
Patients with chronic kidney disease (CKD) are at high risk for coronavirus disease 2019 (COVID-19). Government agencies or learned societies in many countries recommend prioritizing patients with CKD for COVID-19 vaccines. The immune response rate to the COVID-19 vaccines is lower in hemodialysis patients and kidney transplant recipients compared with that in healthy individuals, and increasing the number of vaccinations each member of these population may improve their immune response rate. There was no significant difference in the incidence of adverse reactions after vaccination between patients with CKD and healthy controls. Patients with stable CKD should be vaccinated against COVID-19 unless there were contraindications to vaccination. The mRNA vaccines, inactivated vaccines, and recombinant protein subunit vaccines are all safe for patients with CKD. Patients with CKD treated with rituximab or high-dose glucocorticoid need to weigh the benefits and risks before vaccination, and COVID-19 vaccines can be given when rituximab treatment ends for more than 6 months or after glucocorticoid reduction.Copyright © 2021 by the Chinese Medical Association.
ABSTRACT
Three antiviral drugs, including interferon alpha (aerosol inhalation), lopinavir/ritonavir (oral medication), and ribavirin (intravenous infusion), are recommended by Diagnosis and Treatment of Novel Coronavirus Pneumonia (revised version, the 5th ed), which was issued by the National Health Commission of People's Republic of China and National Administration of traditional Chinese Medicine. In addition, clinical trials on a new antiviral drug-remdesivir which is not yet on the market has also been launched in China. Medication safety related data on treatment for infections of severe acute respiratory syndrome coronavirus, middle respiratory syndrome coronavirus, human immunodeficiency virus, lopinavir/ritonavir, and ribavirin, safety data of remdesivir in animal experiment, phase I clinical trials and clinical trials of treating Ebola virus infection, and preliminary reports of treatment in novel coronavirus pneumonia were briefly reviewed, aiming to provide evidence for clinical safety medication.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Vaccine development and vaccination are the most effective means to prevent and control coronavirus disease 2019 (COVID-19). At present, there are 4 types of COVID-19 vaccines approved for emergency use by the World Health Organization and approved conditionally for marketing and emergency use by State Drug Administration of China, including inactivated vaccine, recombinant protein subunit vaccine, messenger RNA vaccine, and adenovirus vector-based vaccine. Pre-marketing clinical studies show that the vaccines above-mentioned can effectively stimulate the body's immune system to produce antibodies against COVID-19, the overall safety is good. Most of the adverse events after vaccination are mild or moderate. However, COVID-19 vaccination involves a large number and wide range of people, and its safety problems can not be ignored. The medical workers and researchers should be on high alert and conduct long-term monitoring to ensure vaccine safety.Copyright © 2021 by the Chinese Medical Association.
ABSTRACT
Because of the impact of the COVID-19 pandemic, more and more people are choosing to buy food online, including eggs. Although this mode of shopping is very modern, many Chinese consumers lack scientific knowledge when selecting eggs. In this study, we used the multivariate statistical analysis and sensory analysis to evaluate and compare the qualities of online sale of free-range and cage eggs. How feeding conditions influence the quality of eggs and how physical characteristics influence the price of eggs were also studied in this work. Our research showed that there is a lack of scientific support for distinguish free-range eggs from cage eggs on the appearance, the color of the yolk does not represent the amount of protein in yolk which may actually be affected by fodders. Moreover, the nutritional quality of free-range eggs is no better than that of cage eggs. Sensory analysis showed that free-range eggs taste better, which is likely because of the higher yolk ratio. Multivariate linear regression analysis showed that Rearing systems, fodder type and yolk color have significant impact on the price (Price = 0.428 × Rearing system −0.235 × Fodder type + 0.191 × Yolk color). © 2023, Sociedade Brasileira de Ciencia e Tecnologia de Alimentos, SBCTA. All rights reserved.
ABSTRACT
To analyze the mechanism of novel coronavirus prevention prescription in Hunan province by using network pharmacology method. Methods TCMSP, Batman-TCM and ETCM were used to retrieve drug composition and target information, and GeneCards, OMIM, DrugBank, TTD and PharmGkb were used to screen disease targets. The visualization network diagram of "drug-active component-target" was constructed by Cytoscape, the protein interaction network was drawn by STRING, the core targets of PPI network were analyzed by CytoNCA, GO function and KEGG pathway were analyzed, and the mechanism of action was predicted. Results A total of 418 active ingredients, 1 715 drug targets, 1 289 disease targets and 266 intersection targets were screened out. Quercetin, luteolin, kaempferol, baicalein, ursolic acid and naringin were identified as the key components, and 6 core targets were obtained: RELA, AKT1, STAT3, JUN, MAPK1 and MAPK3. The results of molecular docking showed that the binding potential and activity of the key active ingredients to the core target were good. Conclusions "Child prevention formula" has the characteristics of multi-target, multi-approach and multi-faceted prevention and treatment, which plays a role in prevention and treatment of COVID-19 among children. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.
ABSTRACT
The COVID-19 pandemic has presented serious challenges to emergency departments (EDs). EDs play an important role in responding to pandemics, as they make the first substantial strides to recuperate patients and protect them from infectious diseases, as shown in experiences of earlier infectious disease surge events (e.g., SARS-CoV, H1N1, Ebola, etc.). However, there is limited evidence on how facility design can support EDs’ response to pandemics. This chapter aims to provide a systematic literature review (SLR) of EDs’ challenges and responses to pandemics, with a primary focus on facility design strategies. After screening 2489 studies covering the literature from March 2000 to March 2021, 20 articles were reviewed to extract ED design strategies. Key findings include (a) negative-pressure rooms and (b) split flow and cohort isolation that can create various zones for patients with different risk and acuity levels are the most addressed approaches for infection control and accommodating surge capacity. Convertibility and flexibility concept (e.g., reconfiguration of spaces, temporary separation within spaces, reversible air pressure, flexible use of spaces within and adjacent to ED) is key to addressing the unique challenges of the evolving nature of pandemic outbreaks. This chapter provides a summary of existing design strategies for EDs to respond to pandemics. Multiple design strategies need to be combined to minimize the disease transmission in EDs during pandemics and provide surge capacity for the overflow of patients. Detailed design principles were synthesized based on the SLR and translated to a design prototype that aims to address the needs during various stages of pandemics. © 2023 selection and editorial matter, AnnaMarie Bliss and Dak Kopec;individual chapters, the contributors.
ABSTRACT
In the emergency of the outbreak of COVID-19 in December 2019, Shaanxi Provincial Health Committee mobilized several medical teams from major hospitals in the province, and, by relying on Xi'an Chest Hospital, jointly established an anti COVID-19 consortium to control and eradicate the epidemic in a short time. Information support is an important guarantee for winning this battle. In order to realize the efficient cooperation among multiple medical teams, we have carried out some exploratory and innovative information support services on the basis of the original information system of the chest hospital. In this process, we have gone through some detours. Some compromises were made on some problems that could not be solved in the short term. Finally, in an environment full of uncertainty, a set of information support management system with basically smooth operation was built through rapid trial and error adjustment. The system mainly includes the following aspects: support of the organizational structure and operation process of the anti-epidemic consortium, support for medical collaboration related businesses of multiple medical teams, and support for statistical reports and online meetings. Information support has played a very important role in this action, and this practice has also accumulated experience for us to deal with similar situations in the future.
ABSTRACT
For detecting COVID-19 and checking the severity of the patient's condition, CT examination of the lungs is significant. However, the current manual viewing of CT images requires professionalism. In order to improve the inspection efficiency of the huge number of CT images, it is necessary to develop an intelligent detection algorithm to perform CT inspections. This paper proposes a COVID-19 detection algorithm based on EfficientDet. EfficientDet leverages a faster and easier multi-scale fusion approach, which is more suitable for COVID-19 detection tasks with finer feature granularity. In addition, data augmentation is also significant in COVID-19 detection tasks. This paper verifies the effectiveness of EfficientDet on the SIIMFISABIO-RSNA COVID-19 Detection dataset provided by Kaggle platform. Experimental results show that EfficientDet has achieved better performance than other detection algorithms. Taking MAP@0.5 as an indicator, EfficientDet reaches 0.545, which is 7.9% and 3.3% higher than the Faster RCNN algorithm and YOLO-V5. © 2022 IEEE.
ABSTRACT
The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30(th), 2020, to answer two research questions. What are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Does significant association exist between the changing Covid-19 awareness and the pandemic outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track awareness. The lag correlations between awareness and health impacts were examined at global and country levels. Results show that users presenting the highest Covid-19 awareness were mainly those tweeting in the official languages of India and Bangladesh. Asian countries showed more disparities in awareness than European countries, and awareness in Eastern Europe was higher than in central Europe. Finally, the Ratio index had high correlations with global mortality rate, global case fatality ratio, and country-level mortality rate, with 21-31, 35-42, and 13-18 leading days, respectively. This study yields timely insights into social media use in understanding human behaviors for public health research.
ABSTRACT
The COVID-19 pandemic has significantly restricted the regular offline business activities. Nevertheless, as certain offline business activities are still indispensable, to conduct offline business under pandemic control becomes a valuable research question. This paper addressed this problem by studying business movement management based on health certificate exchange. We first observed three patterns of health certificate exchange multiplicity that serve as a basis for business movement management. Then, we reviewed published literature along two orthogonal directions, health certificates and exchange systems. We studied different health certificates published during the COVID-19 pandemic to identify the categories of health certificates and their characteristics. Meanwhile, we further studied different design paradigms and characteristics of health certificate exchange systems. Last, we mapped our findings on health certificate exchange into the four challenges of movement management systems in a pandemic, namely flexible controllability, scalable accessibility, adaptive reusability, and spatiotemporal traceability, and conceptualized how such the requirements should be achieved and a complete system should operate. © 2021 IEEE.
ABSTRACT
Based on the air pollution data in China from January 1,2014 to December 31,2020, the characteristics of extreme value and period of air quality in different regions on different time scales were studied by using wavelet analysis. Wavelet coherence analysis was used to evaluate the relationship between air quality and meteorological factors in the period of COVID-19. We found that the spatial characteristics of air quality changed significantly in summer. Generally, air pollution is more severe in spring and winter. During the lockdown period, the overall air quality in the study area improved significantly. In general, except for 03, the concentration of all other pollutants has dropped considerably. The improvement in air quality is a direct result of emission reductions due to the implementation of the COVID-19 blockade, which is unsustainable in the long term. Eventually, a prediction model attention_CNN_LSTM based on deep learning method is proposed in this paper. The experimental results show that the attention proposed in this study the model has a good prediction effect in the long-term prediction of air quality, but the attention mechanism's impact is lower. After shortening the prediction period, the attention_CNN_LSTM model has good prediction performance on most data sets, with average MAPE = 2.67% and RMSE = 2.29.
ABSTRACT
This article studies the customer satisfaction of online shopping, express delivery, airline service, online travel, express hotel, commercial bank, auto insurance and mobile communication in China in the context of COVID-19 epidemic. The research collects customer satisfaction data through questionnaire surveys and have a total of 13,000 valid samples. According to the survey, consumers are relatively satisfied with customer satisfaction in China's service industry. Among the eight industries studied, online shopping and express delivery have higher customer satisfaction scores, and mobile communications have lower score. The improvement of perceived quality and brand image will help to better improve customer satisfaction, reflecting that consumer satisfaction is more affected by subjective feelings and brand. In addition, this article also collected consumer complaints, brand value and other data, through comprehensive analysis of multi-dimensional data, it analyzes the current quality of China's service industry and provides opinions and suggestions for policy formulation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The rapid development of the COVID-19 pandemic has threatened the lives of people around the world. Many people were caught in anxiety and panic, which also prevents people from fully concentrating on their normal lives. However, the current common neurofeedback therapies used to solve the problem of lack of attention cannot fully deal with the differences in each individual. In addition, direct contact between the patient and the doctor also increases the risk of virus transmission during treatment. This article combines neurofeedback and IoT to establish an adaptive attention adjustment method. IoT connects patients and doctors remotely, reducing the direct contact between them. In order to adapt to individual differences, the feedback indicators of each individual are individually calibrated. In addition, the proportional, integral, and derivative controller was used to adjust the difficulty of the feedback task to adapt to each individual's self-regulation ability and provide the individual with a higher level of regulation. We also designed adaptive attention adjustment experiments for different individuals. The results show that through adaptive feedback training, the individual's feedback indicator has dropped by 77.90%, and the individual can adjust his attention state to the individual's optimal baseline threshold, and the oscillation error gradually reduces to the expected threshold range. This method can cope with the differences between different individuals and provide each individual with the same level of feedback regulation. In the future, this study may provide a general adjuvant treatment for other mental illnesses.
ABSTRACT
Background: The coronavirus SARS-CoV-2 is the culprit of the COVID-19 pandemic. Acute kidney injury occurs frequently in COVID-19 patients and several lines of evidence suggest local infection of kidney cells by the virus. However, this remains controversial and it is unclear how the viral proteins of SARS-CoV-2 directly impact the health of renal tubular cells infected by the virus. Methods: The viral protein ORF3A of SARS-CoV-2 was overexpressed in HK-2 renal tubular cell line and the pronephric tubule epithelia of transgenic zebrafish. The NF-kB and STAT3 signaling pathways and target gene expression were analyzed using quantitative RT-PCR and Western blots. The expression of the renal injury marker KIM-1 was also assessed by Western blots, quantitative RT-PCR and in situ hybridization. Protein interactions were studied by co-immunoprecipitation and Western blots. Results: ORF3A augments both NF-kB and STAT3 signaling by enhancing the phosphorylation of the transcription factors and results in the expression of downstream target genes and subsequently increases the expression of kidney injury molecule 1 (KIM-1) in HK-2 cells. Mechanistically, ORF3A elevates the expression of Tripartite Motif-Containing Protein 59 (TRIM59), a ubiquitin E3 ligase, which forms a protein complex with ORF3A and STAT3. This in turn excludes the phosphatase TCPIP from binding to STAT3 and inhibits the dephosphorylation of STAT3. The transgenic zebrafish expressing ORF3A in renal tubular epithelia develop severe edema starting 48 hours post fertilization and in situ hybridization shows elevated kim-1 expression in the pronephric tubules, indicating that ORF3A induces renal injury in zebrafish in vivo. Conclusions: These results demonstrate that overexpression of ORF3A is sufficient to injure renal tubular epithelial cells and uncover a previously unrecognized molecular mechanism underlying the deregulation of STAT3 activity by ORF3A that leads to renal tubular cell injury. Altogether, the results of this study support the notion that direct infection of renal epithelial cells by SARS-CoV-2 may contribute to the renal complications in COVID-19 patients.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented impacts (e.g., labor shortage, suspension and cancellation of projects, and disrupted supply and logistics) on the US construction industry. To address challenges caused by the pandemic, it is critical for the construction industry to develop a clear understanding of how the pandemic has affected the industry and how it will change in the future. However, assessing the impacts of COVID-19 on the construction industry is challenging due to the broad influence of the pandemic and the dynamic nature of the industry. The Purdue Index for Construction (Pi-C), which was developed as an indicator based on five dimensions and corresponding metrics to measure the health status of the construction industry, offers an opportunity to understand the impact of the pandemic. In this context, this paper presents a study to reveal the relationship between COVID-19 and the health status of the industry as measured through Pi-C and predict the future trend of the construction industry. This study achieves the objective via the three steps. First, the relationship between the pandemic and Pi-C metrics is identified using the Granger causality test and structural equation modeling (SEM) analysis. Second, multivariable prediction models are developed based on a long short-term memory (LSTM) network - a deep learning algorithm - to predict Pi-C metrics in the future. Third, forecasted Pi-C metrics are integrated into the existing Pi-C structure to analyze the impacts of the COVID-19 pandemic and predict its trends in 2021-2022. The results revealed that the impacts of the pandemic were conspicuous in two Pi-C dimensions (economy and stability), whereas no significant impacts were observed in the remaining Pi-C dimension (social). In addition, the Pi-C forecasted that there would be no significant adverse impacts on the US construction industry caused by the pandemic until the end of 2022. © 2021 American Society of Civil Engineers.
ABSTRACT
Coronavirus Disease 2019 (COVID-19) causes a sudden turnover to bad at some checkpoints and thus needs the intervention of intensive care unit (ICU). This resulted in urgent and large needs of ICUs posed great risks to the medical system. Estimating the mortality of critical in-patients who were not admitted into the ICU will be valuable to optimize the management and assignment of ICU. Retrospective, 733 in-patients diagnosed with COVID-19 at a local hospital (Wuhan, China), as of March 18, 2020. Demographic, clinical and laboratory results were collected and analyzed using machine learning to build a predictive model. Considering the shortage of ICU beds at the beginning of disease emergence, we defined the mortality for those patients who were predicted to be in needing ICU care yet they did not as Missing-ICU (MI)-mortality. To estimate MI-mortality, a prognostic classification model was built to identify the in-patients who may need ICU care. Its predictive accuracy was 0.8288, with an AUC of 0.9119. On our cohort of 733 patients, 25 in-patients who have been predicted by our model that they should need ICU, yet they did not enter ICU due to lack of shorting ICU wards. Our analysis had shown that the MI-mortality is 41%, yet the mortality of ICU is 32%, implying that enough bed of ICU in treating patients in critical conditions.
ABSTRACT
Vaccine development and vaccination are the most effective means to prevent and control coronavirus disease 2019 (COVID-19). At present, there are 4 types of COVID-19 vaccines approved for emergency use by the World Health Organization and approved conditionally for marketing and emergency use by State Drug Administration of China, including inactivated vaccine, recombinant protein subunit vaccine, messenger RNA vaccine, and adenovirus vector-based vaccine. Pre-marketing clinical studies show that the vaccines above-mentioned can effectively stimulate the body's immune system to produce antibodies against COVID-19, the overall safety is good. Most of the adverse events after vaccination are mild or moderate. However, COVID-19 vaccination involves a large number and wide range of people, and its safety problems can not be ignored. The medical workers and researchers should be on high alert and conduct long-term monitoring to ensure vaccine safety. Copyright © 2021 by the Chinese Medical Association.
ABSTRACT
Patients with chronic kidney disease (CKD) are at high risk for coronavirus disease 2019 (COVID-19). Government agencies or learned societies in many countries recommend prioritizing patients with CKD for COVID-19 vaccines. The immune response rate to the COVID-19 vaccines is lower in hemodialysis patients and kidney transplant recipients compared with that in healthy individuals, and increasing the number of vaccinations each member of these population may improve their immune response rate. There was no significant difference in the incidence of adverse reactions after vaccination between patients with CKD and healthy controls. Patients with stable CKD should be vaccinated against COVID-19 unless there were contraindications to vaccination. The mRNA vaccines, inactivated vaccines, and recombinant protein subunit vaccines are all safe for patients with CKD. Patients with CKD treated with rituximab or high-dose glucocorticoid need to weigh the benefits and risks before vaccination, and COVID-19 vaccines can be given when rituximab treatment ends for more than 6 months or after glucocorticoid reduction. Copyright © 2021 by the Chinese Medical Association.