AI and the Clinical Immunology/Immunoinformatics for COVID-19

Artificial Intelligence (AI) is contributing to the campaign against the Coronavirus Disease 2019 (COVID-19). Since 2019, more and more AI frameworks and applications in COVID-19 have been proposed, and the recent research has shown that AI is a promising technology because AI can achieve a higher degree of scalability, a more comprehensive and identification of patterns in the vast amount of unstructured and noisy data, accelerated processing power, and strategies to outperform traditional methods in many specific tasks. In this chapter, we focus on the specific AI applications in the clinical immunology/immunoinformatics for COVID-19. More precisely, on one hand, we discuss the application of deep learning in designing SARS-CoV-2 vaccines, and, on the other hand, we discuss the development of a machine learning framework for investigating the SARS-CoV-2 mutations that can help us better respond to the future mutant viruses, including designing more robust vaccines based on such AI approaches. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Adoptive Transfer of Regulatory T Cells Induced by Pregnancy May Mitigate the Severity of COVID-19 Infection in Pregnant Women

Severe coronavirus disease of 2019 (COVID-19) usually begins approximately one week after the onset of symptoms. Dyspnea is the most common symptom of severe disease and is often accompanied by hypoxemia. Progressive respiratory failure develops in many patients with severe COVID-19 after the onset of dyspnea and hypoxemia. These patients commonly meet the criteria for acute respiratory distress syndrome (ARDS), which is defined as the acute onset of bilateral infiltrates, severe hypoxemia, and lung edema. The majority of patients with severe COVID-19 showed some thromboembolic complications as well central or peripheral nervous system complications. Severe COVID-19 may also lead to acute cardiac, kidney, and liver injury, cardiac arrhythmias, coagulopathy, and shock. These organ failures may be associated with uncontrolled inflammation characterized by elevations in C-reactive protein and pro-inflammatory cytokines, including Interleukin-6, Interleukin-1, and tumor necro-sis factor-alpha. This may associate with high fevers, thrombocytopenia, and exacerbating lung and cardiovascular complications. According to the American College of Obstetricians and Gynecologists (ACOG), the relative risk of COVID-19 infection is con-siderably lower relative to the risk of pandemic H1N1 (hemagglutinin type 1 and neuraminidase type 1) influenza infection in pregnant women. Less severe COVID-19 in pregnancy also was reported. Regulatory T cells (Tregs) are important in controlling adverse inflammatory reactions in severe COVID-19 making them effective cells for immunotherapy in severe COVID-19. Im-pairment in the number and/or function of Tregs was reported in severe COVID-19. Tregs are also part of the complex network of immune cells at the feto-maternal interface, and in peripheral blood that may have a critical role in facilitating implantation, pla-cental development, and maintaining maternal tolerance. Pregnancy-induced Tregs are developed to control immune responses against paternal antigens. This review provides a new insight into whether the severity of COVID-19 could be influenced by the adoptive transfer of pregnancy-induced regulatory T cells in pregnant women.

Social carrying capacity and emotion dynamics in urban national parks during the COVID-19 pandemic

The COVID-19 pandemic has changed the mobility, accessibility, and behaviors of visitors dramatically. Under the impact of COVID-19, the social carrying capacity and emotion dynamics in parks and recreation areas are expected to change due to the uncertainty of health risks associated with visitors' behaviors. This study con-ducted an on-site visitor survey at Leiqiong Global Geological Park, a national park located in urban-proximate areas in Haikou, China. This study aims to examine factors impacting visitors' perceived crowding and emotions under varying levels of visitor use in urban national parks in the context of COVID-19. Study results suggest that visitors have the highest level of motivation for scenery and culture viewing and are generally satisfied with the environmental quality and design and COVID-19 prevention strategies and implementation efforts within the park. Moreover, this study suggests that the level of crowding and COVID-19 prevention strategies and imple-mentation can affect visitors' emotions in urban natioanl parks significantly. These findings highlight the importance of enforcing the social carrying capacity limits and COVID-19 prevention strategies for urban parks and protected areas to mitigate physical and mental health risks during the COVID-19 pandemic. Management implication: This study is one of the pilot studies that examines the social carrying capacity and emotion dynamics in urban national parks under the impact of the COVID-19 pandemic. Study results identify the thresholds of social carrying capacity and visitors' positive emotions based on the indicator of People Per View (PPV). Moreover, COVID-19 prevention strategies (e.g., mask-wearing and social distancing) can reduce visitors' perceived crowding and enhance positive emotions. These findings suggest that urban national parks should monitor visitor use levels based on the social carrying capacity framework to reduce visitors' perceived crowding and maintain positive emotions in the post-COVID-19 era.

NON-LINEAR OPERATOR APPROXIMATIONS FOR INITIAL VALUE PROBLEMS

Time-evolution of partial differential equations is fundamental for modeling several complex dynamical processes and events forecasting, but the operators associated with such problems are non-linear. We propose a Padé approximation based exponential neural operator scheme for efficiently learning the map between a given initial condition and the activities at a later time. The multiwavelets bases are used for space discretization. By explicitly embedding the exponential operators in the model, we reduce the training parameters and make it more data-efficient which is essential in dealing with scarce and noisy real-world datasets. The Padé exponential operator uses a recurrent structure with shared parameters to model the non-linearity compared to recent neural operators that rely on using multiple linear operator layers in succession. We show theoretically that the gradients associated with the recurrent Padé network are bounded across the recurrent horizon. We perform experiments on non-linear systems such as Korteweg-de Vries (KdV) and Kuramoto-Sivashinsky (KS) equations to show that the proposed approach achieves the best performance and at the same time is data-efficient. We also show that urgent real-world problems like epidemic forecasting (for example, COVID-19) can be formulated as a 2D time-varying operator problem. The proposed Padé exponential operators yield better prediction results (53% (52%) better MAE than best neural operator (non-neural operator deep learning model)) compared to state-of-the-art forecasting models. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

Analysis of vitamin D nutritional status among children aged 0 to 12 years in Chongqing

Objective To investigate the nutritional status and associated factors of vitamin D among children aged 0 to 12 years old in Chongqing. Methods From January 2019 to December 2021 1 877 children aged 0-6 years who received regular child health care were randomly selected from Chongqing maternal and child health hospital and 707 school-age children were also selected from three primary school in Chongqing for investigation. The serum sample were collected for detecting serum 25- OH -D level by chemiluminescence method and the possible influencing factors of vitamin D deficiency VDD were analyzed. Results The average serum 25- OH -D concentration of children was 39.9±9.1 ng/mL with the positive rate of VDD was 14.59%. There were significant differences of VDD positive rate in different age visiting time visiting season body shape outdoor activity time and vitamin D supplementation 0-3 years old vs 4-6 years old vs 7-12 years old 14.73% vs 22.19% vs 10.47% visiting season spring vs summer vs autumn vs winter 12.97% vs 10.65% vs 14.86% vs 21.33% pre COVID-19 epidemic vs post COVID-19 epidemic 11.18% vs 17.08% underweight or normal vs overweight or obesity 12.34% vs 26.13% adequate outdoor activity time vs inadequate 11.84% vs 16.27% regular vitamin D supplementation vs irregular vitamin D supplementation 11.71% vs 15.62% χ2 = 26.17 17.59 30.98 53.74 9.60 6.17 P<0.05. Underweight or normal body weight sufficient outdoor activities and regular vitamin D supplementation were associated with less vitamin D deficiency with OR OR95%CI at 0.68 0.55-0.84 0.57 0.25-0.77 and 0.62 0.44-0.85 P<0.05. Conclusion The prevalence of VDD among preschool and school-age children is high in Chongqing. Integrated prevention and control strategies incluing overweight or obesity control increasing outdoor activities and oral vitamin D supplements should be taken. © 2022 Authors. All rights reserved.

Tourists' Visual Attention and Stress Intensity in Nature-Based Tourism Destinations: An Eye-Tracking Study During the COVID-19 Pandemic

Tourists' visual attention has a central function in constructing their visual experiences and affects their perceptual and cognitive processes. Visual attention might be affected by environmental factors;however, the effects of environmental factors on visual attention are still vague in the literature. Moreover, visual attention might influence tourists' stress intensity. This study explores how tourists' visual attention patterns vary under environmental factors and quantifies the effects of visual attention on stress intensity by a mixed- methodology involving observations, eye-tracking experiments, and post-experiment surveys. Findings suggest that crowding is an important environmental factor affecting tourists' visual attention patterns. Moreover, natural sounds enhance tourists' visual attention to natural landscapes and mitigate tourists' stress simultaneously. Mask-wearing can reduce tourists' visual attention to human crowds but cannot reduce stress intensity directly. Our findings extend the attention restoration theory by a multi-sensory perspective and the transactional theory of stress through eye-tracking analytics.

Wired to seek, comment and share? Examining the relationship between personality, news consumption and misinformation engagement

Purpose - News consumption is critical in creating informed citizenry;however, in the current context of media convergence, news consumption becomes more complex as social media becomes a primary news source rather than news media. The current study seeks to answer three questions: why the shifted pattern of news seeking only happens to some but not all of the news consumers;whether the differentiated patterns of news seeking (news media vs social media) would result in different misinformation engagement behaviors;and whether misperceptions would moderate the relationship between news consumption and misinformation engagement. Design/methodology/approach - A survey consisted of questions related to personality traits, news seeking, misperceptions and misinformation engagement was distributed to 551 individuals. Multiple standard regression and PROCESS Macro model 1 were used to examine the intricate relationships between personality, news use and misinformation engagement. Findings - Results indicate that extroversion was positively associated with social media news consumption while openness was inversely related to it. Social media news consumption in turn positively predicted greater misinformation sharing and commenting. No association was found between Big Five personality traits and news media news seeking. News media news seeking predicted higher intention to reply to misinformation. Both relationships were further moderated by misperceptions that individuals with greater misperceptions were more likely to engage with misinformation. Originality/value - The current study integrates personality traits, news consumption and misperceptions in understanding misinformation engagement behaviors. Findings suggest that news consumption via news media in the digital era merits in-depth examinations as it may associate with more complex background factors and also incur misinformation engagement. Social media news consumption deserves continuous scholarly attention. Specifically, extra attention should be devoted to extrovert and pragmatic individuals in future research and interventions. People with these characteristics are more prone to consume news on social media and at greater risk of falling prey to misinformation and becoming a driving force for misinformation distribution. Peer review -The peer review history for this article is available at:https://publons.com/publon/10.1108/OIR-10-2021-0520

Inflammatory Response Inhibition and Improvement of COVID-19 Symptoms in COVID-19 Patients by Combination of Antiviral Regimen and Tanreqing Injection

The present study explored the inflammatory response and clinical efficacy of Tanreqing injection in combination with antiviral therapy in patients with coronavirus disease (COVID-19). The results demonstrated that the levels of C-reactive protein (CRP) and interleukin-6 (IL-6) in the treatment group were significantly lower than those in the control group (p < 0.05). Clinical efficacy assessment revealed a significant improvement in the time necessary for image absorption improvement in the treatment group (p < 0.05), while the time taken for fever and muscle soreness symptoms to resolve significantly reduced (p < 0.05). Furthermore, the time taken to obtain a negative COVID-19 test result was significantly shortened (p < 0.05). Tanreqing injection combined with antiviral treatment improved clinical symptoms of COVID-19 faster than when the anti-viral treatments were used alone and this may be related to the reduction in inflammatory response. Copyright © 2022, Colegio de Farmaceuticos de la Provincia de Buenos Aires. All rights reserved.

An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors

Tremendous efforts have been made to improve diagnosis and treatment of COVID-19, but knowledge on long-term complications is limited. In particular, a large portion of survivors has respiratory complications, but currently, experienced radiologists and state-of-the-art artificial intelligence systems are not able to detect many abnormalities from follow-up computerized tomography (CT) scans of COVID-19 survivors. Here we propose Deep-LungParenchyma-Enhancing (DLPE), a computer-aided detection (CAD) method for detecting and quantifying pulmonary parenchyma lesions on chest CT. Through proposing a number of deep-learning-based segmentation models and assembling them in an interpretable manner, DLPE removes irrelevant tissues from the perspective of pulmonary parenchyma, and calculates the scan-level optimal window, which considerably enhances parenchyma lesions relative to the lung window. Aided by DLPE, radiologists discovered novel and interpretable lesions from COVID-19 inpatients and survivors, which were previously invisible under the lung window. Based on DLPE, we removed the scan-level bias of CT scans, and then extracted precise radiomics from such novel lesions. We further demonstrated that these radiomics have strong predictive power for key COVID-19 clinical metrics on an inpatient cohort of 1,193 CT scans and for sequelae on a survivor cohort of 219 CT scans. Our work sheds light on the development of interpretable medical artificial intelligence and showcases how artificial intelligence can discover medical findings that are beyond sight. Respiratory complications after a COVID infection are a growing concern, but follow-up chest CT scans of COVID-19 survivors hardly present any recognizable lesions. A deep learning-based method was developed that calculates a scan-specific optimal window and removes irrelevant tissues such as airways and blood vessels from images with segmentation models, so that subvisual abnormalities in lung scans become visible.

Understanding the "infodemic": social media news use, homogeneous online discussion, self-perceived media literacy and misperceptions about COVID-19

Purpose - This study has three main purposes: (1) to investigate the association between social media news use and misperceptions about COVID-19;(2) to explore the mediating role of homogeneous online discussion;(3) and to understand whether the extent to which one perceives themselves as media-literate could moderate the relationship. Design/methodology/approach - The authors conducted an online survey and collected data through Amazon Mechanical Turk. A total of 797 participants aged 18 and above completed the survey. The average age of the respondents is 38.40 years (SD = 12.31), and 41.2% were female. In terms of party identification, 30.8% were reported leaning toward Republicans;53.7% leaned toward Democrats, and 15.4% were reported neutral. Findings - Results from a moderated mediation model show that social media news use is positively associated with misperceptions about the COVID-19. Moreover, homogeneous online discussion was a significant mediator of the relationship between social media news use and misperceptions about COVID-19. Further, self-perceived media literacy (SPML) significantly moderated the main and indirect effects between social media news use and COVID-19 misperceptions, such that the associations became weaker among those with higher SPML. Originality/value - Findings provide insights into the significance of online information sources, discussion network heterogeneity and media literacy education. Although there have been many studies on misinformation, prior research has not examined these relationships, which may help provide solutions to cope with misinformation.

Assessment of pulmonary ventilation function and influencing factors in COVID‑19 patients six months after discharge from hospital

Objective: To assess the level of pulmonary ventilation function in patients with COVID‑19 after six months post⁃discharge and analyze the relevant influencing factors. Methods: In November 2020, patients with COVID‑19 were investigated in a district of Wuhan City, Hubei Province. Their pulmonary ventilation function indicators were measured, including forced vital capacity of percent predicted (FVC%pred), forced expiratory volume in one second of percent predicted (FEV1%pred), FEV1/FVC ratio (FEV1/FVC%), forced expiratory flow at 50% of percent predicted (FEF50%pred), forced expiratory flow at 75% of percent predicted (FEF75%pred), mean forced expiratory flow between 25% and 75% of percent predicted (MMEF%pred). The related factors affecting pulmonary ventilation function were analyzed. Results: A total of 151 discharged cases were recruited, which included 64 cases of mild illness, 87 cases of moderate illness. The average age of both men and women in the mild group was significantly higher than that in the moderate group (P<0.05). The mean values of the lung ventilation function indexes were all within the normal range. The FVC%pred in both male and female and FEV1%pred in female were better in the mild group than that in the moderate group (P<0.05). Some patients had mild abnormal pulmonary ventilation function and 11 cases in the mild group, 46 cases in the moderate group. Multi‑factor logistic regression analysis showed that women [OR=3.012, 95%CI(1.249,7.264)], the presence of a previous history of chronic disease [OR=2.739, 95%CI(1.186,6.326)], and cases of moderate illness [OR=6.365, 95%CI(2.730,14.840)] were the risk factors for abnormal pulmonary ventilation function after discharge. Conclusion: Half a year after discharge, the pulmonary ventilation function of both mild and moderate group patients recovered well. Women and those with chronic disease in the past should have more targeted health guidance during the post‑discharge recovery period. © 2022, Editorial Board of Medical Journal of Wuhan University. All right reserved.

Integrated innovation of Chinese and western medicine: Target-combined Holistic Treatment

With the development of biomedicine, and significant success achieved by targeted therapy in the treatment of complex and refractory diseases such as cancers, clinical treatment and drug discovery based on molecular targets become the main direction of modern medical research. Guided by holistic concept, traditional Chinese medicine (TCM) has a unique advantage with regards to the prevention and treatment of complex diseases through its comprehensive effect. However, at present, TCM research is insufficient and problems such as inaccurate clinical findings, lack of dominant diseases, unclear evaluation of efficacy, and unclear mechanisms, cannot be solved easily. Therefore, the authors believe that the development of TCM should adopt an innovative approach that integrates the advantages of TCM and western medicine, and positively influences the development of TCM and even future medicine. This article proposes Target-combined Holistic Treatment (THT), a new concept based on the integration of TCM and western medicine. While being guided by the holistic and systematic perspective of TCM, THT also factors in the latest advances in both TCM and modern biomedical research, and uses macro-micro combination, target-syndrome combination, and internal and external codivision, as the primary strategies to establish a clinical diagnosis model that combines disease differentiation, syndrome differentiation, and target differentiation. It also uses drug ingredients/components to enable comprehensive interventions against multiple targets linked to a disease, and establishes target medication and research strategy of TCM, so as to improve its pertinence, efficacy, and safety, and ensure precise and effective medication. The theories and methods of THT fully integrate the advantages of TCM and western medicine, factoring in both macro-control and micro intervention, and also systematic confrontation, precision treatment, and embracing TCM theory and modern technology. This can guide the further development of TCM, western medicine, as well as the combination of TCM and western medicine. It will therefore help promote the integration and innovation of both TCM and western medicine, and the in-depth development of TCM. The theories and methods of THT can be used to guide not only the whole process of clinical diagnosis but also the development of innovative drugs. THT has been used to guide the formulation of TCM diagnosis and treatment for COVID-19 and has shown remarkable results. We have developed a Chinese herbal prescription "Keguan-1", to prevent and treat COVID-19 based on the theory and method of THT, and use the doctrine of "resist foreign aggression and pacify the interior" of TCM against COVID-19. Using the findings of research in modern medicine, THT can innovate and develop TCM based treatments, and thus aid in the treatment of various diseases, and also help promote the integration and development of TCM and western medicine. © 2021, Science Press. All right reserved.

A computational approach for designing novel SARS-CoV-2 Mproinhibitors: combined QSAR, molecular docking, and molecular dynamics simulation techniques

The normal expression of the main protease (Mpro) plays a vital role in the life cycle of coronavirus. Highly active inhibitors could inhibit the normal circulation of the main protease to achieve therapeutic effects as anti-coronavirus agents. In the present research, 48 peptide compounds with SARS-CoV Mproinhibition selected from the literature were used to establish robust Topomer CoMFA (q2= 0.743,r2= 0.938, andrpred2= 0.700) and HQSAR (q2= 0.774,r2= 0.955, andrpred2= 0.723) models. Structural modification information was used for designing new Mproinhibitors. The high contribution-value descriptor generated by Topomer CoMFA was used to screen for the fragments that possess significant inhibitory activities from the ZINC drug database, and 24 new compounds with predicted high inhibitory activity at nanomolar concentration were designed by combining the high contribution value fragments. The molecular docking results further justified that these potential inhibitors could form hydrogen bonds with the residues of CYS145, GLN189, GLU166, HIS163, and GLY143 of target Mpro, which well explains their strong inhibitory effects. The molecular dynamics simulation results indicated that four highly active compounds could stably bond with SARS-CoV-2 Mproand might be promising anti-SARS-CoV-2 Mprocandidates. Finally, all the newly designed compounds showed premium ADMET properties as per the predictions by the server in the public domain. This research work not only provides robust QSAR models as valuable screening tools for future anti-coronavirus drug development but also renders the newly designed SARS-CoV-2 Mproinhibitors with activity at nanomolar concentration, which can be used for further characterization to obtain novel anti-coronavirus drugs for both SARS-CoV and SARS-CoV-2.

Predicting the Molecular Mechanism of “Angong Niuhuang Pills” in the Treatment of COVID-19 Based on Network Pharmacology

Introduction: Angong Niuhuang Pills (AGNH), a Chinese patent medicine recommended in the “Diagnosis and Treatment Plan for COVID-19 (8th Edition),” may be clinically effective in treating COVID-19. The active components and signal pathways of AGNH through network pharmacology have been examined, and its potential mechanisms determined. Methods: We screened the components in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) via Drug-like properties (DL) and Oral bioavailability (OB);PharmMapper and GeneCards databases were used to collect components and COVID-19 related targets;KEGG pathway annotation and GO bioinformatics analysis were based on KOBAS3.0 database;“herb-components-targets-pathways” (H-C-T-P) network and protein-protein interaction network (PPI) were constructed by Cytoscape 3.6.1 software and STRING 10.5 database;we utilized virtual molecular docking to predict the binding ability of the active components and key proteins. Results: A total of 87 components and 40 targets were screened in AGNH. The molecular docking results showed that the docking scores of the top 3 active components and the targets were all greater than 90. Conclusion: Through network pharmacology research, we found that moslosooflavone, oroxylin A, and salvigenin in AGNH can combine with ACE2 and 3CL, and then are involved in the MAPK and JAK-STAT signaling pathways. Finally, it is suggested that AGNH may have a role in the treatment of COVID-19.

A Novel Framework with Weighted Heterogeneous Educational Network Embedding for Personalized Freshmen Recommendation Under the Impact of COVID-19 Storm

The global explosion of COVID-19 has brought unprecedented challenges to traditional higher education, especially for freshmen who have no major;they cannot determine what their real talents are. Thus, it is difficult for them to make correct choices based on their skills. Generally, existing methods mainly mine isomorphic information, ignoring relationships among heterogeneous information. Therefore, this paper proposes a new framework to give freshmen appropriate recommendations by mining heterogeneous educational information. This framework is composed of five stages: after data preprocessing, a weighted heterogeneous educational network (WHEN) is constructed according to heterogeneous information in student historical data. Then, the WHEN is projected into different subnets, on which metapaths are defined. Next, a WHEN-based embedding method is proposed, which helps mine the weighted heterogeneous information on multiple extended metapaths. Finally, with the information mined, a matrix factorization algorithm is used to recommend learning resources and majors for freshmen. A large number of experimental results show that the proposed framework can achieve better results than other baseline methods. This indicates that the proposed method is effective and can provide great help to freshmen during the COVID-19 storm. CCBY

A possible conceptualization of the information systems (IS) artifact: A general systems theory perspective1

This opinion paper addresses and contributes to the discourse on whether there is a central artifact that captures the essence of the information systems (IS) discipline. It argues that the IS discipline can, and should be, faithfully captured by an IS artifact. We offer a theoretical conception of the IS artifact by drawing upon General Systems Theory (GST). Key concepts of GST are distilled as meta-principles which inform our formulation of the IS artifact. We use the meta-principles of the IS artifact to develop salient assertions that theorize what an ‘IS’ is. To demonstrate the appropriateness of our conception, we illustrate how the assertions we developed are consistent with patterns related to emerging topics in IS research, notably, healthcare and IT, and Fintech. We formulate a research agenda on these emerging topics—based upon the conceptions developed in the paper—to guide future research. We conclude with the contributions and implications of our study, including the relevance for IT-enabled work in the era of the COVID-19 pandemic. © 2020 John Wiley & Sons Ltd

Influencing factors for positive duration of viral nucleic acid in patients with severe coronavirus disease 2019

Objective To analyze the positive duration of viral nucleic acid in severe coronavirus disease 2019 (COVID-19) patients and to explore its influencing factors, so as to understand the virus clearance state and provide evidence for treatment and management. Methods The clinical data of 41 patients with severe COVID-19 were retrospectively collected;the patients were hospitalized in Sino-French New City Branch of Tongji Hospital in Wuhan, Hubei Province from Feb. 10 to Mar. 28, 2020. The detection results of viral nucleic acid, clinical information and laboratory findings in oropharyngeal secretion were collected. The time from onset to negative of viral nucleic acid was defined as the positive duration of viral nucleic acid. Multivariate Cox regression analysis was used to explore the influencing factors affecting the positive duration of viral nucleic acid in severe COVID-19 patients. Results Among 41 patients with severe COVID-19, 20 (48.8%) were males and 21 (51.2%) were females, with a median age of 68.0 (58.5, 74.0) years. The average positive duration of viral nucleic acid was (28.98±11.71) d in the patients. Multivariate Cox regression analysis indicated that diabetes mellitus, lymphocyte count and use of high dose of glucocorticoid (total hormone≥300 mg) were associated with the positive duration of viral nucleic acid (all P<0.05), while use of low dose of glucocorticoid (total hormone<300 mg) was not related to the positive duration of viral nucleic acid (P>0.05). Conclusion Positive duration of viral nucleic acid is longer in severe COVID-19 patients. Comorbidity of diabetes mellitus, decreased lymphocyte count and use of high dose of glucocorticoid (total hormone≥300 mg) are independent risk factors for positive duration of viral nucleic acid.

False-positive results of gold immunochromatography assay for IgM and IgG antibodies to 2019-nCoV

Objective: To investigate the specificity of three gold immunochromatography assay (GICA) kits for IgM and IgG antibodies against 2019 novel coronavirus (2019-nCoV), and explore the interference factors causing false-positive results and methods for eliminating interference. Methods: The serum samples were retrospectively collected from the patients presented to the Peking University Third Hospital from March 6, 2020 to April 20, 2020. Three commercial GICA kits were used to detect SARS-CoV-2 antibodies in serum samples from the following 4 groups. ①Healthy control group: 120 serum samples. ②Special pathogen group: 139 samples, including 42 Hepatitis B virus (HBV) antibody positive sera, 27 Hepatitis C virus (HCV) antibody positive sera, 11 Treponema Pallidum (TP) antibody positive sera, 12 Cytomegalovirus (CMV) IgM positive sera, 12 Rubella virus (RV) IgM positive sera, 8 Epstein-Barr virus (EBV) IgM positive sera, 12 sera with Escherichia coli confirmed by blood cultures, 15 sera from influenza A virus infected patients and 15 influenza B virus infected patients. ③Endogenous interference group:242 samples, including 20 sera with elevated total IgM, 20 sera with elevated total IgG, 15 sera with elevated total complement, 9 sera with elevated alpha fetoprotein (AFP), 84 sera with normal rheumatoid factor (RF) level and 94 sera with elevated RF level. ④Pregnant women and patients with malignant tumor: 126 samples. Reverse transcription polymerase chain reaction (RT-PCR) was used to detect 2019-nCoV viral nucleic acid in the throat swabs. Statistical analysis was performed by SPSS, version 19.0. Results: The false-positive rates of 2019-nCoV IgM and IgG in healthy controls tested by A kit were 0 and 0.83% (1/120), 4.17% (5/120) by B kit, and 0 by C kit. One in 12 serum samples collected from patients with E. coli bactereia was positive for 2019-nCoV antibodies tested by three kits. The false-positive rate of 2019-nCoV antibodies in HCV antibody positive sera was 7.41% (2/27) by B kit. The false-positive rates of 2019-nCoV antibodies in sera with normal and elevated RF level tested by B kit were 9.52% (8/84) and 54.26%(51/94) (χ²=40.05, P<0.001), 3 serum samples in elevated RF group were positive for 2019-nCoV IgM/IgG antibodies by A and C kits. The overall false-positive rates of A, B and C antibody test kits in all the subjects were 0.55%(3/548), 4.2%(23/548) and 0.73% (4/548), respectively. Conclusions: The specificity of GICA kits varies greatly among different manufacturers. Rheumatoid factor is the main factor leading to false-positive results of 2019-nCoV antibodies tested by B kit. The use of high-purity antibody and suitable immunoassay blocking reagent will be helpful to improve the specificity of GICA kits.

AKI is related to mortality in COVID-19 patients without underlying kidney disease

Background: Due to its high infectivity and mortality, coronavirus disease 2019 (COVID-19) has become a global public health issue. The kidneys act as critical metabolic organs, therefore, whether COVID-19 can induce renal damage is of utmost importance but remains controversial, and the prognosis of COVID-19 encountering acute kidney injury (AKI) is unknown. Moreover, the efficacy of different treatments that COVID-19 patients undergo needs to be explored. In this study, we aimed to explore these questions. Methods: A single-centered, retrospective study was conducted in which 96 patients with COVID-19 were enrolled. Epidemiological, clinical, and laboratory characteristics, as well as treatments and patient outcomes were described. Characteristics were compared between severe cases and critical cases. Relevant factors of AKI were filtrated, and the treatment efficacy was also evaluated. Results: A total of 6 patients (6.3%) died during hospitalization. Four patients (4.2%) developed AKI, among which 3 patients (75%) died. Statistical analysis indicated that AKI was not common in COVID-19 patients without underlying kidney disease, but was related to mortality. Age, severity of disease, procalcitonin, C-reactive protein and interleukin-6 were correlated with AKI onset in COVID-19 patients, while lymphocyte count and estimated glomerular filtration rate at admission were inversely related to the development of AKI. Conclusions: In conclusion, AKI is not common in COVID-19 patients without underlying kidney disease but related to mortality.