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Summary Background The effectiveness of different strategies in addressing the COVID-19 pandemic has been assessed, but there is still not enough evidence in Asian countries. This study aims to examine the factors influencing the trajectory of COVID-19 evolution in Asia, to provide insights for optimizing public health policies. Methods In this longitudinal analysis, we combined COVID-19 cases and vaccination percentages from Our Word in Data with the policy stringency index from the Oxford COVID-19 Government Response Tracker for 12 Asian countries between January 1, 2021, and September 30, 2022. An agglomerative hierarchical cluster analysis (HCA) was conducted to identify countries with similar COVID-19 evolution trajectories. We also investigated the potential impact of seasonal variations on the virus' trajectory. The relationship between the level of policy response, vaccination coverage, and COVID-19 cases was explored using Generalized Additive Models (GAMs). Findings There were noticeable differences in the evolution trajectory of COVID-19 among the countries. The 12 Asian countries were grouped into two clusters based on evolutionary similarities. Cluster 1 consisted of West Asian countries (Azerbaijan, Turkey, Bahrain, Israel and Lebanon); while Cluster 2 included Japan, South Korea, Singapore, Malaysia, Thailand, Cambodia and Indonesia. The analysis revealed that the stringency index and vaccination coverage were associated with a statistically significant impact (both P values < 0.0001) on the evolution trajectory of COVID-19 (adjR2=0.54). The dose-response relationships demonstrated that the continuous high levels of stringency index ([≥]87.6) or vaccination coverage ([≥] 42.0%) have led to a decrease in COVID-19 infection rates. In early 2021, the adjR2 increased to 0.93 for all countries. Furthermore, the adjR2 for Cluster 1 and Cluster 2 were 0.86 and 0.90 respectively. All GAMs models have significantly improved compared to null model (P values <0.0001). Interpretation By strengthening vaccination ahead of susceptible seasons and enhancing personal self-protection measures, the transmission of COVID-19 among the population can be reduced even during the highly infectious Omicron era.
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COVID-19ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily transmitted from person to person through respiratory droplets and aerosols. It is also possible for the virus to be transmitted indirectly through environmental contamination. The likelihood of environmental transmission depends on several factors, including the survival time of the virus in respiratory secretions. However, the stability of SARS-CoV-2 in respiratory secretions has not been investigated. In this study, we compared the half-life of the SARS-CoV-2 antigen in respiratory secretion under different conditions. We applied respiratory secretion (5 µL) to glass slides, air-dried the slides for 1 h, and kept them at 24 °C or 4 °C for 10 days. Respiratory secretions were also placed in test tubes (sealed to preserve moisture) and in normal saline for 10 days. The concentration of SARS-CoV-2 antigen in all samples was simultaneously measured using colloidal gold immunochromatography, and the half-life of the antigen was calculated. The half-life of the antigen in the wet (sealed tube) and saline samples at room temperature was 5.0 and 2.92 days, respectively. The half-life of the antigen in the air-dried sample at room temperature and at 4 °C was 2.93 and 11.4 days, respectively. The half-life was longer in respiratory secretions than that in normal saline. The half-life was also longer in respiratory secretions, at a lower temperature, and under wet conditions. Therefore, environmental transmission can also play a significant role in the spread of the virus. Robust prevention and control strategies could be developed based on the half-life of the antigen in respiratory secretions.
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COVID-19 , SARS-CoV-2 , Humans , Half-Life , Saline Solution , Respiratory Aerosols and DropletsABSTRACT
The global food crisis caused by COVID-19 and the Russia-Ukraine conflict have made many countries around the world realize the significance of agroforestry to a country's food security. However, China's agroforestry R&D innovation is currently lagging behind in development, and some agricultural seeds are heavily dependent on foreign countries, which seriously affects China's national food security. It is especially important to explore the reasons why China's agroforestry R&D and innovation is lagging behind. As listed agroforestry companies face the market demand directly, there is an urgent need to study the R&D innovations of listed agroforestry companies at present. This paper analyzes the impacts of R&D innovation, corporate management and supply chain management on the corporate performance of listed agroforestry companies using the entropy weighting method, GMM estimation and panel threshold model, mainly by selecting annual panel data from CSMAR for the period 2010 to 2021. The following conclusions were drawn: (1) There is a nonlinear relationship between R&D innovation and firm performance, and a 'U';-shaped relationship. This indicates that there is an entrance threshold for R&D innovation in the agroforestry industry, below which corporate performance does not improve. (2) There is a nonlinear relationship between corporate management and corporate performance, and a U-shaped relationship. (3) There is a nonlinear relationship between supply chain management and firm performance, with an inverted-U-shaped relationship. This paper explains the reasons for the slow development of R&D innovation in China's agriculture and forestry industry and fills the gap in the theoretical study of the nonlinear relationship between R&D innovation and corporate performance of listed companies in China's agriculture and forestry industry. Finally, this paper provides a theoretical basis for the decision making of government departments related to agriculture and forestry, and offers some suggestions for listed companies in agriculture and forestry to improve their corporate performance.
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Objective The outbreak of COVID-19 in 2020 is reminiscent of the H7N9 outbreak in 2013, which poses a huge threat to human health. We aim to compare clinical features and survival factors in fatal cases of COVID-19 and H7N9. Methods Data on confirmed COVID-19 and H7N9 fatal cases identified in mainland China were analyzed to compare demographic characteristics and clinical severity. Survival curves were estimated by the Kaplan–Meier method and compared using log-rank tests and a restricted mean survival time model. A Cox regression model was used to identify survival factors in fatal cases of COVID-19 and H7N9. Results Similar demographic characteristics were observed in fatal cases of COVID-19 and H7N9. The proportion of fatal cases of H7N9 receiving antibiotics, antiviral drugs, and oxygen treatment was higher than that of COVID-19. The potential protective factors for fatal COVID-19 cases were receiving antibiotics (HR: 0.37, 95% CI: 0.22–0.61), oxygen treatment (HR: 0.66, 95% CI: 0.44–0.99), and corticosteroids (HR: 0.46, 95% CI: 0.35–0.62). In contrast, antiviral drugs (HR: 0.21, 95% CI: 0.08–0.56) and corticosteroids (HR: 0.45, 95% CI: 0.29–0.69) were the protective factors for H7N9 fatal cases. Conclusion The proportion of males, those having one or more underlying medical condition, and older age was high in COVID-19 and H7N9 fatal cases. Offering antibiotics, oxygen treatment, and corticosteroids to COVID-19 cases extended the survival time. Continued global surveillance remains an essential component of pandemic preparedness.
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The coronavirus disease 2019 (COVID-19) pandemic has affected the mental health of individuals worldwide, and the risk of psychiatric sequelae and consequent mental disorders has increased among the general population, health care workers and patients with COVID-19. Achieving effective and widespread prevention of pandemic-related psychiatric sequelae to protect the mental health of the global population is a serious challenge. Salidroside, as a natural agent, has substantial pharmacological activity and health effects, exerts obvious neuroprotective effects, and may be effective in preventing and treating psychiatric sequelae and mental disorders resulting from stress stemming from the COVID-19 pandemic. Herein, we systematically summarise, analyse and discuss the therapeutic effects of salidroside in the prevention and treatment of psychiatric sequelae as well as its roles in preventing the progression of mental disorders, and fully clarify the potential of salidroside as a widely applicable agent for preventing mental disorders caused by stress; the mechanisms underlying the potential protective effects of salidroside are involved in the regulation of the oxidative stress, neuroinflammation, neural regeneration and cell apoptosis in the brain, the network homeostasis of neurotransmission, HPA axis and cholinergic system, and the improvement of synaptic plasticity. Notably, this review innovatively proposes that salidroside is a potential agent for treating stress-induced health issues during the COVID-19 pandemic and provides scientific evidence and a theoretical basis for the use of natural products to combat the current mental health crisis.
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Coronavirus Infections , Mental Disorders , COVID-19ABSTRACT
The ongoing COVID-19 shocked financial markets globally, including China’s crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China’s first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ FROM AUTHOR]
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False detection of SARS-CoV-2 is detrimental to epidemic prevention and control. The scalar nature of the detected signal and the imperfect target recognition property of developed methods are the root causes of generating false signals. Here, we reported a collaborative system of CRISPR-Cas13a coupling with the stabilized graphene field-effect transistor, providing high-intensity vector signals for detecting SARS-CoV-2. In this collaborative system, SARS-CoV-2 RNA generates a “big subtraction” signal with a right-shifted feature, whereas any untargets cause the left-shifted characteristic signal. Thus, the false detection of SARS-CoV-2 is eliminated. High sensitivity with 0.15 copies/μL was obtained. In addition, the wide concerned instability of the graphene field-effect transistor for biosensing in solution environment was solved by the hydrophobic treatment to its substrate, which should be a milestone in advancing it's engineering application. This collaborative system characterized by the high-intensity vector signal and amazing stability significantly advances the accurate SARS-CoV-2 detection from the aspect of signal nature.
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Drunk driving is one of the leading causes of traffic deaths in China. Although the non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic resulted in dramatic reductions in transport and mobility in 2020, to date, little is known about how drunk driving and related traffic crashes varied with the NPIs. We created a high-resolution and comprehensive drunk driving dataset. Based on 836,194 drunk driving in 335 cities in China from 2016 to 2020, we employ the causality models to examine and quantify trends in overall and subgroup drunk driving and related traffic crashes road traffic mortality throughout 2020. Subgroup analyses were done by place (urban and rural), sex, employment, education level, age group, geographical location (road, city, province and region), and by type of motor vehicle. Despite the marked reductions in drunk driving and related traffic crashes in 2020, the incidence of the induced traffic crashes increased during the stringent NPI period. Substantial differences persist across populations, locations and motor vehicles. Drunk driving occurred in the morning, at western China and rural catchment areas as well as drunk drivers aged 18–30, with high education background or white-collars have more declines. The drunk drivers aged 30–50, with high education levels, white-collar, female, and occurred at night, in the middle east China and urban areas have a higher incidence of traffic crash compared with other subgroups especially in Stage I. These comparable findings can inform decision-makers in planning precisely targeted interventions for cracking down on drunk driving during the events like public health arenas.
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COVID-19 , Pulmonary Disease, Chronic ObstructiveABSTRACT
Background Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform.
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The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.
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The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.
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Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.
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International trade relations between countries have enabled the integration of global oil trade while also creating a platform for the risk diffusion of oil supply cuts. The global energy supply shortages sparked by the Covid-19 pandemic has made the problem even more pronounced. This study develops a network-based dynamics model based on the modified bootstrap percolation theory to simulate the cascading diffusion of oil supply shortages. We assess the destructive effects of exporting countries’ cuts in oil exports on global oil trade relations and the vulnerability of importing countries when they encounter oil supply shortages. The cascading diffusion of oil supply breakdown occurs less frequently from 2015 to 2019, proving that the entire network’s antirisk capacity strengthens over time. The coronavirus pandemic has impaired the robustness of the oil trade network in 2020. OPEC’s export influence has continued to decline in recent years. The diversified evolution of the oil supply is conducive to the stability of the oil trade economy. This paper analyzes the risk propagation mechanism in the global oil trade and conducts a case study. The results have a specific early warning effect on regional oil supply risks.
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Since the outbreak of COVID-19, the opinion that the aerosol plays a key role in the transmission of SARS-CoV-2 has been controversial. The COVID-19 pandemic has continued interpersonal transmission for more than two years, especially after the emergence of Delta and Omicron variants, making the situation of COVID-19 pandemic more severe. The transmission of SARS-COV-2 variants was significantly accelerated and the time of transmission between generations was significantly shortened. Therefore, it has been questioned to attribute the close-range infection to droplet transmission. The point that the aerosol can also has a close-range transmission and may play a dominant role is neglected under the influence of traditional transmission mode of respiratory infectious diseases. A large number of studies have shown that normal breath, talk and cough could release a large number of respiratory aerosol particles, and the virus particles were mainly tiny particles(=5.0 micro m). The biological activity and infectivity of the droplet nuclei have been questioned in the studies on their physicochemical properties. Animal models of ferrets and hamsters showed that SARS-COV-2 could transmit via aerosol. Therefore, the new evidence for the aerosol transmission of SARS-COV-2 was reviewed in the article so as to provide latest evidence-based evidence for prevention and control of COVID-19.
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This observation study examines coronavirus disease 2019 (COVID-19) data from outbreak and other sites in China and worldwide in order to examine the epidemiological pattern of COVID-19 before the acquisition of immunity through widespread vaccination and infection. COVID-19-related morbidity and mortality data for January 2020 to February 2021 were obtained from the Chinese Center for Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, and the World Health Organization. The number of cases was logarithmically transformed for comparison of the rate of increase or decrease with time across areas. From January to February 2020, the number of new confirmed cases in Wuhan grew substantially but returned to zero by May 2020. In other parts of China, the rate of decrease was lower than that in Wuhan, and the mortality rate was lower outside Wuhan (1.93%) than in Wuhan (7.68%). The influenza trends were similar to those of COVID-19, but the mortality rate of influenza was much lower (0.011%) than that of COVID-19. After the early stage, similar increase in the incidence rate with time was observed globally, although the total number of cases differed between regions. The outbreak severe acute respiratory syndrome coronavirus 2 strain in Wuhan had low epidemic intensity and high virulence, but the epidemiological characteristics of severe acute respiratory syndrome coronavirus 2 may not be associated with race, geography, or economic status. Importantly, more effective prevention and control measures and vaccines should be applied for controlling the variants.
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COVID-19 , Influenza, Human , COVID-19/epidemiology , China/epidemiology , Disease Outbreaks , Humans , Influenza, Human/epidemiology , SARS-CoV-2ABSTRACT
The COVID-19 epidemic and the Russian–Ukrainian conflict have led to a global food and energy crisis, making the world aware of the importance of agroforestry development for a country. Modern agriculture mechanization leads to massive energy consumption and increased CO2 emissions. At the same time, China is facing serious demographic problems and a lack of consumption in the domestic market. The Chinese government is faced with the dilemma of balancing environmental protection with economic development in the context of the “double carbon” strategy. This article uses annual World Bank statistics from 1990 to 2020 to study the asymmetric relationships between agroforestry development, energy consumption, population size, and economic development on CO2 emissions in China using the partial least squares path model (PLS-PM), the autoregressive VAR vector time series model, and the Granger causality test. The results are as follows: (1) The relationship between economic development and carbon dioxide emissions, agroforestry development and carbon dioxide emissions, energy consumption and carbon dioxide emissions, and population size and carbon dioxide emissions are both direct and indirect, with an overall significant positive effect. There is a direct negative relationship between population size and carbon dioxide emissions. (2) The results of the Granger causality test show that economic development, energy consumption, and CO2 emissions are the causes of the development of agroforestry;economic development, agroforestry development, population size, and CO2 emissions are the causes of energy consumption;energy consumption is the cause of economic development and CO2 emissions;and agroforestry development is the cause of population size and energy consumption. (3) In the next three years, China’s agroforestry development will be influenced by the impulse response of economic development, energy consumption, and CO2 emission factors, showing a decreasing development trend. China’s energy consumption will be influenced by the impulse response of economic development, agroforestry development, population size, and CO2 emission factors, showing a decreasing development trend, followed by an increasing development trend. China’s CO2 emission will be influenced by the impulse response of energy consumption and agroforestry development. China’s CO2 emissions will be influenced by the impulse response of energy consumption and agroforestry development factors, showing a downward and then an upward development trend.
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Commonly used clinical chemotherapy drugs, such as cyclophosphamide (CTX), may cause injury to the ovaries. Hormone therapies can reduce the ovarian injury risk;however, they do not achieve the desired effect and have obvious side effects. Therefore, it is necessary to find a potential therapeutic candidate for ovarian injury after chemotherapy. N-Benzyl docosahexaenamide (NB-DHA) is a docosahexaenoic acid derivative. It was recently identified as the specific macamide with a high degree of unsaturation in maca (Lepidium meyenii). In this study, the purified NB-DHA was administered intragastrically to the mice with CTX-induced ovarian injury at three dose levels. Blood and tissue samples were collected to assess the regulation of NB-DHA on ovarian function. The results indicated that NB-DHA was effective in improving the disorder of estrous cycle, and the CTX+NB-H group can be recovered to normal levels. NB-DHA also significantly increased the number of primordial follicles, especially in the CTX+NB-M and CTX+NB-H groups. Follicle-stimulating hormone and luteinizing hormone levels in all treatment groups and estradiol levels in the CTX+NB-H group returned to normal. mRNA expression of ovarian development-related genes was positive regulated. The proportion of granulosa cell apoptosis decreased significantly, especially in the CTX+NB-H group. The expression of anti-Müllerian hormone and follicle-stimulating hormone receptor significantly increased in ovarian tissues after NB-DHA treatment. NB-DHA may be a promising agent for treating ovarian injury.
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Objective: To investigate the effect of sampling positions in nucleic acid test for COVID-19 on test results.
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Background Influenza and COVID-19 are respiratory infectious diseases that are characterized by high contagiousness and high mutation and pose a serious threat to global health. After Influenza A virus (IAV) and SARS-CoV-2 infection, severe cases may develop into acute lung injury. Immune factors act as an important role during infection and inflammation. However, the molecular immune mechanisms still remain unclear. We aimed to explore immune-related host factors and core biomarker for severe infection, to provide a new therapeutic target of host factor in patients. Methods Gene expression profiles were obtained from Gene Expression Omnibus and the Seurat R package was used for data process of single-cell transcriptome. Differentially expressed gene analysis and cell cluster were used to explore core host genes and source cells of genes. We performed Gene Ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, and gene set enrichment analysis to explore potential biological functions of genes. Gene set variation analysis was used to evaluate the important gene set variation score for different samples. We conduct Enzyme-linked immunosorbent assay (ELISA) to test plasma concentrations of Lipocalin 2 (LCN2). Results Multiple virus-related, cytokine-related, and chemokine-related pathways involved in process of IAV infection and inflammatory response mainly derive from macrophages and neutrophils. LCN2 mainly in neutrophils was significantly upregulated after either IAV or SARS-CoV-2 infection and positively correlated with disease severity. The plasma LCN2 of influenza patients were elevated significantly compared with healthy controls by ELISA and positively correlated with disease severity of influenza patients. Further bioinformatics analysis revealed that LCN2 involved in functions of neutrophils, including neutrophil degranulation, neutrophil activation involved in immune response, and neutrophil extracellular trap formation. Conclusion The neutrophil-related LCN2 could be a promising biomarker for predicting severity of patients with IAV and SARS-CoV-2 infection and may as a new treatment target in severe patients.
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Objective: To describe the clinical characteristics of liver and kidney injuries and investigate its effect on the severity and mortality in the COVID-19 patients.