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The additional impact of emission-reduction measures in North China (NC) during autumn and winter on the air quality of downwind regions is an interesting but less addressed topic. The mass concentrations of routine air pollutants, the chemical compositions, and sources of fine particles (PM2.5) for January 2018, 2019, and 2020 at a megacity of Central China were identified, and meteorology-isolated by a machine-learning technique. Their variations were classified according to air mass direction. An unexpectedly sharp increase in emission-related PM2.5 by 22.7% (18.0 mug m-3) and 25.7% (19.4 mug m-3) for air masses from local and NC in 2019 was observed compared to those of 2018. Organic materials exhibited the highest increase in PM2.5 compositions by 6.90 mug m-3 and 6.23 mug m-3 for the air masses from local and NC. PM2.5 source contributions related to emission showed an upsurge from 1.39 mug m-3 (biomass burning) to 24.9 mug m-3 (secondary inorganic aerosol) in 2019 except for industrial processes, while all reduced in 2020. From 2018 to 2020, the emission-related contribution of coal combustion to PM2.5 increased from 10.0% to 19.0% for air masses from the local area. To support the priority natural gas quotas in northern China, additional coal in cities of southern China was consumed, raising related emissions from transportation activities and road dust in urban regions, as well as additional biofuel consumption in suburban or rural regions. All these activities could explain the increased primary PM2.5 and related precursor NO2. This study gave substantial evidence of air pollution control measures impacting the downwind regions and promote the necessity of air pollution joint control across the administration.Copyright © 2023 Elsevier Ltd
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Objective To investigate the mental health status of military healthcare workers in shelter hospitals in Shanghai during the epidemic caused by severe acute respiratory syndrome coronavirus 2 omicron variant and its influencing factors. Methods A total of 540 military healthcare workers in shelter hospitals in Shanghai were investigated with patient health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7) and Athens insomnia scale (AIS) to explore their mental health status, and logistic regression was used to analyze the influencing factors. Results A total of 536 valid questionnaires were collected, with an effective rate of 99.3% (536/540). The incidence of depression, anxiety and insomnia among military healthcare workers in shelter hospitals in Shanghai was 45.5% (244/536), 26.1% (140/536) and 59.5% (319/536), respectively. Logistic regression analysis showed that whether people resided in Shanghai, the proportion of negative information in daily browsing information and diet status in shelter hospitals were the influencing factors of depression, anxiety and insomnia (all P<0.05);age and confidence in the future of Shanghai were the influencing factors of depression and insomnia (all P<0.05);and the time spent daily on epidemic-related information was an influencing factor of insomnia (P=0.021). Conclusion The incidence of depressive, anxiety and insomnia among military healthcare workers in shelter hospitals in Shanghai is high during the epidemic caused by severe acute respiratory syndrome coronavirus 2 omicron variant. Psychological consequences of the epidemic should be monitored regularly and continuously to promote the mental health of military healthcare workers.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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CD4+CD25+FOXP3+regulatory T cells (Tregs) contribute to the maintenance of immune homeostasis and tolerance in the body. The expression levels and functional stability of FOXP3 control the function and plasticity of Tregs. Tregs critically impact infectious diseases, especially by regulating the threshold of immune responses to pathogenic microorganisms. The functional regulatory mechanism and cell-specific surface markers of Tregs in different tissues and inflammatory microenvironments have been investigated in depth, which can provide novel ideas and strategies for immunotherapies targeting infectious diseases.Copyright © 2021. All rights reserved.
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Objective To investigate the mental health status of military healthcare workers in shelter hospitals in Shanghai during the epidemic caused by severe acute respiratory syndrome coronavirus 2 omicron variant and its influencing factors. Methods A total of 540 military healthcare workers in shelter hospitals in Shanghai were investigated with patient health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7) and Athens insomnia scale (AIS) to explore their mental health status, and logistic regression was used to analyze the influencing factors. Results A total of 536 valid questionnaires were collected, with an effective rate of 99.3% (536/540). The incidence of depression, anxiety and insomnia among military healthcare workers in shelter hospitals in Shanghai was 45.5% (244/536), 26.1% (140/536) and 59.5% (319/536), respectively. Logistic regression analysis showed that whether people resided in Shanghai, the proportion of negative information in daily browsing information and diet status in shelter hospitals were the influencing factors of depression, anxiety and insomnia (all P<0.05);age and confidence in the future of Shanghai were the influencing factors of depression and insomnia (all P<0.05);and the time spent daily on epidemic-related information was an influencing factor of insomnia (P=0.021). Conclusion The incidence of depressive, anxiety and insomnia among military healthcare workers in shelter hospitals in Shanghai is high during the epidemic caused by severe acute respiratory syndrome coronavirus 2 omicron variant. Psychological consequences of the epidemic should be monitored regularly and continuously to promote the mental health of military healthcare workers.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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[Background] Since the outbreak of COVID-19, primary health care workers have been facing un-precedented work pressure, and their occupational stress should be taken seriously. [Objective] To analyze the occupational stress situation and its influencing factors of primary health care workers in Guangdong Province, and to propose targeted interventions. [Methods] Using a multi-stage stratified random sampling method, each prefecture-level city in Guangdong Province was classified into "good", "medium", or "poor" category based on its gross domestic product (GDP) in 2019 released by the Guangdong Provincial Bureau of Statistics. In September 2021, four primary health care institutions were randomly selected from each stra-tum, and a total of 1 327 staff members were selected for the study. The Core Occupational Stress Scale (COSS) and a basic information questionnaire designed by the authors were used. Mann-Whitney U test was used to compare the means between two groups, and Kruskal-Walis H test was used to compare the means among multiple groups. The comparison of categorical data was performed by trend chi2 test or Pearson chi2 test;the analysis of factors influencing occupational stress was performed by dichotomous multiple logistic regression analysis. [Results] There were 365 health care workers reporting occupational stress in this survey, and the positive rate of occupational stress was 27.5%. The total occupational stress score in M (P25, P75) and the scores of social support, organization and reward, demand and effort, and control were 45.0 (40.0, 50.0), 20.0 (17.0, 21.0), 14.0 (12.0, 17.0), 12.0 (10.0, 15.0), and 5.0 (4.0, 6.0), re-spectively. The results of dichotomous multiple logistic regression analysis showed that high education, low income, doctor positions, long working hours in a day, and shift work were associated with the occurrence of reporting occupational stress (P < 0.05). [Conclusion] Education, average monthly income, job category, daily working hours, and shifts are factors influencing the occurrence of reporting occupational stress in primary health care workers;targeted interventions should be implemented to reduce their occupational stress levels.Copyright © 2023, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.
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At present, severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still rampant worldwide.As of September 10, 2021, there were about 222 million confirmed cases of corona virus disease 2019(COVID-19)and more than 4.6 million deaths worldwide.With the development of COVID-19 vaccines and the gradual vaccination worldwide, the increasing number of cases in children and unvaccinated young people has drawn attention.According to World Health Organization surveillance data, the proportion of COVID-19 infection cases in children gradually increased, and the proportion of cases in the age groups of under 5 years and 5-14 years increased from 1.0% and 2.5% in January 2020 to 2.0% and 8.7% in July 2021, respectively.At present, billions of adults have been vaccinated with various COVID-19 vaccines worldwide, and their protective effects including reducing infection and transmission, reducing severe disease and hospitalization, and reducing death, as well as high safety have been confirmed.Canada, the United States, Europe and other countries have approved the emergency COVID-19 vaccination in children and adolescents aged 12 to 17 years, and China has also approved the phased vaccination of COVID-19 vaccination in children and adolescents aged 3 to 17 years. For smooth advancement and implementation of COVID-19 vaccination in children, academic institutions, including National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, and The Society of Pediatrics, Chinese Medical Association organized relevant experts to reach this consensus on COVID-19 vaccination in children.Copyright © 2021 by the Chinese Medical Association.
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Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still worldwide.As a vulnerable group, severe and dead pediatric cases are also reported.Under this severe epidemic situation, children should be well protected.With the widespread vaccination of SARS-CoV-2 vaccine in adults, the infection rate have decreased.Therefore, SARS-CoV-2 vaccine inoculation for children groups step by step is of great significance to the protection of children and the prevention and control of corona virus disease 2019(COVID-19) as a whole.But the safety of children vaccinated with SARS-CoV-2 vaccine is a main concern of parents.Therefore, in order to ensure the safety of vaccination and the implementation of vaccination work, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health and the Society of Pediatrics, Chinese Medical Association organized experts to interpret the main issue of parents about SARS-CoV-2 vaccine for children, in order to answer the doubts of parents.Copyright © 2021 by the Chinese Medical Association.
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2019 novel coronavirus(2019-nCoV) outbreak is one of the public health emergency of international concern.Since the 2019-nCoV outbreak, China has been adopting strict prevention and control measures, and has achieved remarkable results in the initial stage of prevention and control.However, some imported cases and sporadic regional cases have been found, and even short-term regional epidemics have occurred, indicating that the preventing and control against the epidemic remains grim.With the change of the incidence proportion and the number of cases in children under 18 years old, some new special symptoms and complications have appeared in children patients.In addition, with the occurrence of virus mutation, it has not only attracted attention from all parties, but also proposed a new topic for the prevention and treatment of 2019-nCoV infection in children of China.Based on the second edition, the present consensus further summarizes the clinical characteristics and experience of children's cases, and puts forward recommendations on the diagnostic criteria, laboratory examination, treatment, prevention and control of children's cases for providing reference for further guidance of treatment of 2019-nCoV infection in children.Copyright © 2021 Chinese Medical Association
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Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world. © 2022 The Authors
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Background: The COVID-19 pandemic is a huge challenge to world health systems. The harm of public panic is more serious than that of the virus infection. Public panic will create a lot of rumours;Rumours will not only hinder the government's handling of public health emergencies, but also disrupt the public's awareness and behaviour of preventing viruses and cause social unrest. Purpose(s): In order to investigate the demand of the ordinary personnel and health professionals for emergency popularisation of science, discover the current problems in popular science work during public health emergencies, and provided suggestions for future health popular science work. Method(s): This study designed two versions of the health emergency science questionnaire, which are divided into ordinary personnel version and health professional version. From 21st February to 10th March 2020, the authors received questionnaires from 25,935 ordinary personnel and 30,143 professionals from all provinces of China. Result(s): The public has a high demand for health emergency popularisation of science about COVID-19, and the professional demand is higher than the ordinary personnel. Ordinary personnel's evaluation of the role of health emergency popular science in COVID-19 pandemic is 8.58+/-1.80 points (out of ten points), and the professional's evaluation is 8.93+/-1.44 points. Conclusion(s): Ordinary personnel and professionals have highly evaluated the role of health emergency popular science during the COVID-19 pandemic. Mobile Internet is currently the main channel for the public to obtain emergency popular science information, but due to rumours, the public's trust in mobile Internet is low.
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Nucleic acid vaccine based on messenger RNA (mRNA) is a kind of mRNA technology emerging in recent years. mRNA vaccines have many advantages over traditional vaccines, which can be manufactured in a cell-free manner, enabling rapid, economical and efficient production. In addition, single mRNA vaccines can encode multiple antigens, enhance the immune response against certain pathogens, improve the efficiency of treatment process of diseases, and can target multiple microbial or viral variants in a single formulation. mRNA is seen as a revolutionary vaccine technology in COVID-19 prevention and control, which has been developed and successfully applied in record time. The mRNA vaccine is with poor stability, so the development and applications of novel delivery systems are essential. With the intensive study of pharmacology of mRNA vaccines, the clinical applications of mRNA vaccines enter into a new stage. Recently, mRNA technologies were used in the prevention and therapies of diseases, and some results were published. Here, the output of mRNA vaccines used in prevention and therapies of diseases was summarized, and the development of mRNA vaccines was also discussed. © 2022, China Biotechnology Press. All rights reserved.
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With the global outbreak of virulent infectious diseases such as COVID-19, the lack of medical resources has become a serious social problem. More and more online users who encounter physical discomfort will first choose to look up the relevant symptoms on the Internet. Some online platforms have been able to understand the symptoms entered by users and provide auxiliary diagnosis suggestions. However, the professionalism and accuracy of online health and medical Question Answering (QA) systems are very insufficient. How to obtain and utilize massive medical symptom data from multiple data sources such as the Internet, medical symptom libraries and medical professional electronic books has become a difficult problem. The development of big data, artificial intelligence, and especially knowledge graph technology has provided ideas and methods to solve this problem. In this paper, a medical knowledge graph NWNU-KG is constructed on the basis of multi-source data, and the BiLSTM-CRF-CNN-Dict (BCCD) joint model is used for entity recognition and relationship extraction of user-asked questions to implement a healthcare knowledge QA system. Numerous experiments have found that the joint model BCCD proposed in this paper has a higher accuracy rate compared with the best available models, and can filter the answers to questions and return them to users in multi-source, heterogeneous and massive healthcare data, which has some practical value. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Parkinson's disease(PD) is a progressive neu-rodegenerative disease defined by clinical syndrome including bradykinesia, tremor and postural instability. The PD-related disability and impairment are usually monitored by clinicals using the MDS-UPDRS scale. However, due to COVID-19, it became much harder for the patients to reach hospitals and obtain necessary assessment and treatment. Nowadays, 2D videos are easily accessible and can be a promising so-lution for on-site and remote diagnosis of movement disorder. Inspired by the frequency-based video processing mechanism of human visual system, we propose a video-based SlowFast GCN network to quantify the gait disorder. The model consists of two parts: the fast pathway and the slow pathway. The former detects characteristics such as tremor and bilateral asymmetry, while the latter extracts characteristics such as bradykinesia and freezing of gait. Furthermore, in order to investigate the influence of age on the model performance, an aged control group and a young control group were set up for verification. The proposed model was evaluated on a video dataset collected from 68 participants. We achieved a balanced accuracy of 87.5% and precision of 87.9%, which outperformed existing competing methods. When replacing the young healthy controls with the same number of older controls, the balanced accuracy and precision were decreased by 10.4% and 9.7%, which indicates that age has a significant effect on the model perfomance. © 2022 IEEE.
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In recent years, the resource shortage and environmental degradation have made enterprises and governments increasingly aware of the importance of sustainable development. Meanwhile, the COVID-19 pandemic has also increased the shortage of medical materials. Based on this, we investigate the tradeoff of the critical medical devices refurbishing strategies when blockchain is used in three different structures: manufacturer refurbishing, retailer refurbishing, and third-party refurbishing in the two-period refurbishing strategies. We find that the manufacturer always benefits from the adoption of blockchain technology strategy in the manufacturer refurbishing scenario. However, for the retailer in the second period, the retailer references the adoption of blockchain only if the willingness to pay is extremely high. Additionally, when the medical supply chain channel member chooses retailer refurbishing or third-party strategy, the manufacturer always likes to use blockchain technology. That's because it will help the information value spillover from the retailer to the manufacturer, which leads the manufacturer to get more profits and a lower profit for the retailer. However, in the retailer refurbishing or third-part strategy, the whole channel profits are higher than not adopting blockchain technology. Therefore, business managers can be based on our research to achieve profits Pareto-improving.
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The COVID-19 infections segmentation is a challenging task due to the high variation in shape, size and position of infections or lesions in medical images. To solve it, we propose a deep learning-based segmentation method for COVID-19 chest CT images that can automatically segment COVID-19 lung lesions. Based on the U-Net model, we introduce a feature fusion and an attention block for increasing the multi-scale feature learning capacity. Moreover, the network is also equipped with a residual block and a deep supervision mechanism to improve model segmentation accuracy and completeness rate. Experimental results show that the method has a good test effect after training, and the Dice index can reach 63.26%, which is beneficial for the diagnosis of the coronary pneumonia. © 2022 ACM.
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Since December 2019, COVID-19 epidemic is continuing to spread globally. It not only jeopardizing the lives and health of people around the world seriously and putting a severe test on the public medical and health system, but also causes a huge impact on economic and trade activities and has a deep influence on the international community. In order to help researchers and policy makers understand the mechanism of virus transmission and adopt reasonable anti-epidemic policies to inhibit the further spread of the virus, some studies have adopted mathematical prediction models to simulate the spread of the virus and the development of the epidemic. However, the existing research has certain limitations, such as single method selection, excessive reliance on model parameters selection, and virus transmission and policy adjustments caused time variability of data. To solve the above problems, this paper proposes a comprehensive ensemble forecasting framework, which bases on six single prediction models, including time-varying Jackknife model averaging (TVJMA), time-varying parameters (TVP), time-varying parameter SIR (vSIR), logistic regression (LR), polynomial regression (PNR), autoregressive moving average (ARMA). The proposed method is used to predict the cumulative number of confirmed cases in the 6 most severely affected countries in different regions. Empirical results show that for a single prediction method, the TVJMA method outperforms the other five methods;the comprehensive ensemble forecasting method is significantly better than any single method in most cases, especially, the multi-model combined forecasting method based on error correction weights improves the prediction accuracy significantly. For different prediction steps, the comprehensive ensemble forecasting method is robust. © 2022, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
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Resilience has become an important concept for the ski resorts of China, which have suffered heavy losses due to COVID-19. In order to help China’s ski resort service industry successfully adapt to the crisis and achieve sustainable development, the goal of this paper is to develop the definition of resilience of the ski resort service industry through interviews based on the concept and general analysis framework of resilience. The ski resort resilience theory analysis framework is then constructed from the three basic elements (market, skiing, and stakeholders) and four system features (flexibility, adaptability, and collaborative learning ability). The results indicate several measures that can be taken to spread risk: enrich the product supply;eliminate risks and build a multi-agent networked industrial governance system;and establish a risk prevention and management mechanism based on a multi-organization alternative learning mechanism to overcome the difficulties encountered in the development of ski resorts. © 2022, Editorial office of Journal of Resources and Ecology. All rights reserved.