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Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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This paper investigates a government's subsidy strategy for motivating a manufacturer to set up a flexible production line for emergency supplies. Four subsidy strategies are proposed to ensure a desired service level in case of an emergency: zero subsidy, a fixed subsidy, a marginal subsidy, and a hybrid subsidy. We develop a game theoretical model to examine how the government can induce a manufacturer to set up a flexible production line that can respond promptly to an emergency, based on the manufacturer's cost structure (fixed and marginal costs). We find that when the marginal profit of an emergency product is higher than that of the manufacturer's regular product, a fixed (marginal) subsidy is the dominant strategy if the manufacturer's fixed (marginal) cost is high, while a hybrid subsidy strategy is dominant if both costs are high. When the marginal profit of an emergency product is lower than that of the manufacturer's regular product, neither a fixed subsidy nor a zero subsidy will be the dominant strategy. We also find that a marginal subsidy can ensure the effectiveness of the strategy, while a fixed subsidy helps improve strategy efficiency. We use government subsidy strategies implemented for Chinese COVID-19 emergency supplies as examples to demonstrate the effectiveness and efficiency of the subsidy strategies under the proposed framework. We also extend the discussion by considering the manufacturer's social consciousness.
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Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P<0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P>0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P>0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio [OR]=5.618, 95% confidence interval [CI]) 2.136-14.776, P<0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P<0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P>0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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Background: COVID-19 vaccine booster uptake remains low and preventable COVID-19 deaths continue to occur, making access to oral antivirals for those most at risk of severe COVID-19 outcomes essential. Method(s): We estimated age and gender adjusted prevalence ratios of oral nirmatrelvir-ritonavir (NMV/r) uptake by sociodemographics, clinical characteristics, and prescription eligibility (based on age, underlying medical conditions, body mass index, physical inactivity, pregnancy, or smokers), among participants in a large U.S. national prospective cohort who were infected with SARS-CoV-2 between December 2021 and October 2022. Among participants who reported NMV/r uptake, we also described the proportion who reported (1) taking NMV/r as directed and (2) NMV/r was helpful for reducing COVID-19 symptoms. Result(s): Among 1,594 participants with a SARS-CoV-2 infection as of October 2022, 1,356 were eligible for NMV/r prescription;of whom 209 (15.4% [95%CI:13.5-17.3]) reported receiving NMV/r. NMV/r uptake increased from 2.2% (95%CI:1.0-3.4) between December 2021 and March 2022 to 16.5% (95% CI:13.0-20.0) between April and July 2022 and 28.6% (95%CI:24.4-32.8) between August and October 2022, respectively. Participants >=65 years of age reported the highest uptake of NMV/r (30.2% [95%CI:22.2-38.2]). Black non-Hispanic participants (7.2% [95%CI:2.4-12.0]) and those in the lowest income group (10.6% [95%CI:7.3-13.8]) had lower uptake than white non-Hispanic (15.8% [95%CI:13.6-18.0]) and high-income individuals (18.4% [95%CI:15.2-21.7]), respectively. Participants with type 2 diabetes had greater uptake (28.8% [95%CI:20.4-37.3]), compared to those without it (12.4% [95%CI:4.8-20.0]). Among a subset of 278 participants who had a prior SARSCoV-2 infection, those who had a history of long COVID reported greater uptake (22.0% [95%CI:13.9-30.1]) for a subsequent SARS-CoV-2 infection than those without a history of long COVID (7.9% [95%CI:3.9-11.8]). Among all participants who were prescribed NMV/r (N=216), 89% (95%CI:85-93) reported that they took NMV/r as directed and 63% (95%CI:57-70) stated NMV/r was helpful for reducing COVID-19 symptoms. Conclusion(s): Uptake of NMV/r increased over time coinciding with national efforts to increase awareness and access. However, most individuals who were eligible for NMV/r did not receive it. Lower NMV/r uptake among racial/ethnic minorities and individuals with lower household income suggests a need to improve awareness and address barriers to uptake in these populations.
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We collect a total of 1830 data from January 2020 to June 2022 and use R for data processing and wavelet analysis. Moreover, we analyze the interactions between the COVID-19 pandemic, the Russian-Ukrainian war, crude oil price, the S&P 500 and economic policy uncertainty within a time-frequency frame work. As a result that the COVID-19 pandemic and the Russian-Ukrainian war has the extraordinary effects on the three indexes and the effect of the Russian- Ukrainian war on the crude oil price and US stock price higher than on the US economic uncertainty. © COPYRIGHT SPIE.
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Clinical question What is the role of drug interventions in the treatment and prevention of covid-19? Recommendations The first version on this living guidance focuses on corticosteroids. It contains a strong recommendation for systemic corticosteroids in patients with severe and critical covid-19, and a weak or conditional recommendation against systemic corticosteroids in patients with non-severe covid-19. Corticosteroids are inexpensive and are on the World Health Organisation list of essential medicines. How this guideline was created This guideline reflects an innovative collaboration between the WHO and the MAGIC Evidence Ecosystem Foundation, driven by an urgent need for global collaboration to provide trustworthy and living covid-19 guidance. A standing international panel of content experts, patients, clinicians, and methodologists, free from relevant conflicts of interest, produce recommendations for clinical practice. The panel follows standards, methods, processes, and platforms for trustworthy guideline development using the GRADE approach. We apply an individual patient perspective while considering contextual factors (that is, resources, feasibility, acceptability, equity) for countries and healthcare systems. The evidence A living systematic review and network meta-analysis, supported by a prospective meta-analysis, with data from eight randomised trials (7184 participants) found that systemic corticosteroids probably reduce 28 day mortality in patients with critical covid-19 (moderate certainty evidence;87 fewer deaths per 1000 patients (95% confidence interval 124 fewer to 41 fewer)), and also in those with severe disease (moderate certainty evidence;67 fewer deaths per 1000 patients (100 fewer to 27 fewer)). In contrast, systemic corticosteroids may increase the risk of death in patients without severe covid-19 (low certainty evidence;absolute effect estimate 39 more per 1000 patients, (12 fewer to 107 more)). Systemic corticosteroids probably reduce the need for invasive mechanical ventilation, and harms are likely to be minor (indirect evidence). Understanding the recommendations The panel made a strong recommendation for use of corticosteroids in severe and critical covid-19 because there is a lower risk of death among people treated with systemic corticosteroids (moderate certainty evidence), and they believe that all or almost all fully informed patients with severe and critical covid-19 would choose this treatment. In contrast, the panel concluded that patients with non-severe covid-19 would decline this treatment because they would be unlikely to benefit and may be harmed. Moreover, taking both a public health and a patient perspective, the panel warned that indiscriminate use of any therapy for covid-19 would potentially rapidly deplete global resources and deprive patients who may benefit from it most as potentially lifesaving therapy. Updates This is a living guideline. Work is under way to evaluate other interventions. New recommendations will be published as updates to this guideline. Readers note This is version 1 of the living guideline, published on 4 September (BMJ 2020;370:m3379) version 1. Updates will be labelled as version 2, 3 etc. When citing this article, please cite the version number. Submitted August 28 Accepted August 31Copyright © Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to.
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Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality. © 2022
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Background and Purpose: When the coronavirus disease 2019 (COVID-19) outbreak became paramount, medical care for other devastating diseases was negatively impacted. In this study, we investigated the impact of the COVID-19 outbreak on stroke care across China. Method(s): Data from the Big Data Observatory Platform for Stroke of China consisting of 280 hospitals across China demonstrated a significant drop in the number of cases of thrombolysis and thrombectomy. We designed a survey to investigate the major changes during the COVID-19 outbreak and potential causes of these changes. The survey was distributed to the leaders of stroke centers in these 280 hospitals. Result(s): From the data of Big Data Observatory Platform for Stroke of China, the total number of thrombolysis and thrombectomy cases dropped 26.7% (P<0.0001) and 25.3% (P<0.0001), respectively, in February 2020 as compared with February 2019. We retrieved 227 valid complete datasets from the 280 stroke centers. Nearly 50% of these hospitals were designated hospitals for COVID-19. The capacity for stroke care was reduced in the majority of the hospitals. Most of the stroke centers stopped or reduced their efforts in stroke education for the public. Hospital admissions related to stroke dropped =40%;thrombolysis and thrombectomy cases dropped =25%, which is similar to the results from the Big Data Observatory Platform for Stroke of China as compared with the same period in 2019. Many factors contributed to the reduced admissions and prehospital delays;lack of stroke knowledge and proper transportation were significant limiting factors. Patients not coming to the hospital for fear of virus infection was also a likely key factor. Conclusion(s): The COVID-19 outbreak impacted stroke care significantly in China, including prehospital and in-hospital care, resulting in a significant drop in admissions, thrombolysis, and thrombectomy. Although many factors contributed, patients not coming to the hospital was probably the major limiting factor. Recommendations based on the data are provided.Copyright © 2020 Authors. All rights reserved.
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The new energy industry is crucial for solving the problem of pollution, and its development requires support from the stock market. This paper proposes a Chinese investor sentiment index based on the Long Short-Term Memory (LSTM) deep learning method, and investigates the effect of investor sentiment on new energy stock returns as well as value at risks (VaR) behavior before and during COVID-19. It also compares these effects on traditional energy companies to identify differences between the new energy and traditional companies. The empirical results show that investor sentiment has significant effects on stock returns and VaR of both new and traditional energy companies but the effects are stronger in the new energy industry. The effects of investor sentiment have increased during COVID-19, and investors pay more attention on risks than returns during COVID-19. These results provide guidance for small and medium-sized investors in China to optimize their investment strategies and alleviate losses associated with extreme risks. © 2022 Elsevier Inc.
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The COVID-19 pandemic has forced expatriates in many organizations to do virtual work, while virtual communication is becoming a critical skill, especially for second-language speakers. We explore how expatriates with high and low levels of host-country language (HCL) proficiency use different mechanisms to improve their virtual work adaptivity during the COVID-19 pandemic. Drawing upon the Job Demands-Resources (JD-R) theory, we argue that expatriates with high HCL proficiency tend to adopt approach crafting, whereas expatriates with low HCL proficiency tend to use avoidance crafting. We further examine the role of language-related human resource (HR) practices in reducing the tendency of expatriates with low HCL proficiency to choose avoidance crafting. We tested our predictions using data collected from 994 expatriates working in eight countries during the COVID-19 virtual work period, and the results generally supported our hypotheses. Our study sheds light on the importance of HCL skills in influencing expatriates' job-crafting behavior and adaptivity in virtual work, and the significant role of language-related HR practices. Last, we offer practical insights into improving virtual work during a crisis in relation to employees' HCL and organizational support. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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Aquaculture is regarded as one of the fastest methods for preparing food and may be relied upon more and more in the future. Production can be seeded from fish caught in the wild and can be maintained with imported fish food however, aquaculture output and quality is limited by cost and resources, and there is an incentive to make it more environmentally sustainable. If these goals can be achieved, we will produce better quality fish and in higher volumes. Microbial protein feed (MPF) offers a sustainable feedstuff solution for the aquaculture industry in China, with the net benefits of taking less time to prepare, using less water and land, being recyclable and also reducing carbon emissions. MPF provides stable and high quality proteins and is produced through the fermentation of microorganisms by utilizing agricultural and industrial waste as substrates and been extensively used in fish and shrimp production in China. This review describes the microorganisms, raw materials, fermentation processes and nutritional components used in MPF production in aquaculture. We shall discuss also MPF large-scale production processes in detail and then finally, what opportunities and challenges are faced by MPF in Chinese aquaculture in the context of "double carbon"targets and Covid-19. High-efficiency biosynthesis technology using mono-carbon gases to produce protein will become an important field in the future, as it shall facilitate sustainable and healthy feedstocks for the aquaculture industry, and allow China to achieve the goal of lower carbon emissions. © 2023 Elsevier Ltd.
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Under the COVID-19 and other terrible environments workers are constrained to sweep campus and public area. Intelligent and driverless sanitation robot can solve the problem. Obstacle avoidance and garbage cleanup are its important functions. Based on the driverless sanitation robot project introduced by Sanda University, this paper carries out recognition of campus vehicles and improves its obstacle avoidance function. Through image processing, the object features of different environment and climate conditions are extracted, analyzed and recognized, so as to achieve more accurate recognition of campus vehicles. And opencv and python language are used to complete the implementation of vehicle detection. © 2022 IEEE.
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In January 2020, the outbreak of COVID in China attracted widespread attention and discussion on social media. Evolution of public opinion can help us understand users' hot topics and the evolution rule among these topics. Therefore, a public opinion evolution model based on microblog data is proposed in this paper. Firstly, a web crawler is used to obtain microblog data. Then the idea of sentiment analysis and topic extraction in order is used to analyze, and divide the stages through the emotional conflict evolution diagram. Finally, fine-grained emotion visualization is carried out for the hot topics in each stage, the evolution rule of public opinion on COVID-19 is summarized, and the effectiveness and scientificity of the method are also verified. © 2022 ACM.
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To fight against infectious diseases (e.g., SARS, COVID-19, Ebola, etc.), government agencies, technology companies and health institutes have launched various contact tracing approaches to identify and notify the people exposed to infection sources. However, existing tracing approaches can lead to severe privacy and security concerns, thereby preventing their secure and widespread use among communities. To tackle these problems, this paper proposes CoAvoid, an edge-based, privacy-preserved contact tracing system that features good dependability and usability. CoAvoid leverages the Google/Apple Exposure Notification (GAEN) API to achieve decent device compatibility and operating efficiency. It utilizes Bluetooth Low Energy (BLE) to detect close contact with other people and leverages GPS with fine-grained matching algorithms to verify user information. In addition, to enhance privacy protection, CoAvoid applies fuzzification and obfuscation measures to shelter sensitive data, making both servers and users agnostic to information of both low and high-risk populations. The evaluation demonstrates good efficacy and security of CoAvoid. Compared with four state-of-the-art contact tracing applications, CoAvoid can reduce the size of upload data by at least 90% and reduce the verification time by 92%. More importantly, CoAvoid can preserve user privacy and resist replay and wormhole attacks in all analysis scenarios. IEEE
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Sjogren's syndrome (SS) is a chronic and systemic autoimmune disease characterized by lymphocytic infiltration and the development of dry eyes and dry mouth due to the secretory dysfunction of the lacrimal and salivary glands. In recent years, infectious pathogens have been proved to be associated with SS, including Cytomegalovirus, Coxsackie, EBV, and lymphotropic virus-1 (HTLV-1). Studies suggest that infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may trigger an autoimmune response, as evidenced by increased autoantibodies in patients diagnosed with Coronavirus disease 2019 (COVID-19). To investigate the relationship between SARS-CoV-2 and SS, the study was performed by infecting humanized ACE2 mice with SARS-CoV-2. Mice infected with the virus showed a decreased saliva flow rate, elevated antinuclear antibodies (ANAs) and anti-SSB/La, and lymphocyte infiltration in the lacrimal and salivary glands. We detected the viral nucleocapsid protein in mice exocrine glands with significant apoptotic bodies by the acinar cells. Confirmed with clinical data, we also observed the elevation of SS-specific autoantibodies (ANA, anti-SSB/Ro52, and anti-SSA/La) and specific ANA patterns in sera from COVID-19 patients. One unique aspect of SS is the high degree of sexual dimorphism, with women being affected 10-20 times more than men. To determine whether COVID-19 patients exhibited an element of sexual dimorphism in the autoantibody response, we grouped the sera by sex. We found the male patients showed elevated anti-SSA/Ro52 compared to female patients (p=0.0029), and female patients had more diverse ANA patterns. Lastly, monoclonal antibodies isolated from recovered patients using singlecell antibody nanowells technology were shown to recognize the nuclear antigens. Overall, by observing SS-like phenotypes in mouse models and patients, our study confirms a direct pathogenic role of SARS-CoV-2 in SS.
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Currently with the changes in living habits and eating habits of China consumers have higher requirements for the wearing comfort and fit of head and face products such as helmets and masks. In addition the outbreak of COVID-19 in 2019 has made suitable masks an important protective equipment for medical staff and the general population. How to improve the safety protection level of masks has also become a hot social issue of concern. The fit of the mask is directly related to the protection effectiveness so it is urgent to measure track and update human head and face data. The research on the characteristics and classification of human head and face is an important basis for the structural design size formulation fit research and plate shape optimization of masks and helmets. Multilayer perceptron is an ANN algorithm. With the development of neural network technology it is gradually applied to prediction and classification. The model with strong nonlinear approximation function simple structure controllable number of input variables and strong operability can be applied to the classification and prediction of human body shape. In order to improve the adaptability of head and face products this paper took 189 female college students aged 18 - 26 as the research subjects and used the Martin measuring instrument to measure the head and face of the subjects. Feature factors affecting head and face shape were extracted by principal component analysis PCA the K-Means method was used to classify the head and face morphology and the index classification method was used to quantify head and face morphology. As a result a head-face shape prediction model based on MLP-ANN was proposed to improve the problem of low production work efficiency caused by too many head and face sizes in classifying or selecting models with too many references. The study found that through the analysis of head and face characteristics of 189 subjects seven important characteristic factors affecting the head and face shape were extracted head contour factor morphological facial factor morphological facial factor eye factor nose factor and mouth & lip factor. The head and face shapes were divided into five sizes according to the clustering center value of each category XS type/morphological index > 93 S type/morphological index 88 93 M type/morphological index 84 88 L type/morphological index 79 84 XL type/morphological index 79 and the M type was the most widely distributed and had a big coverage rate so it can be used as an intermediate type. Then through the MLP neural network seven head-face feature factors were used to predict head-face shape classification. The generated model had a 93. 42% correct prediction result and the research results can provide a reference for the design and production of head and face products. This paper provides an objective method for the study of head and facial features but there are still some limitations. In the future we can continue to improve the classification of head and face shape by expanding the area and age of the experimental subjects for comparative research. We can apply the classification to the head and face product specification system so as to accumulate morphological data for the study of the head and face characteristics of contemporary Chinese people and the design of head and face products such as masks for the Chinese market. © 2022 China Silk Association. All rights reserved.
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Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.