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1.
Front Immunol ; 13: 918731, 2022.
Article in English | MEDLINE | ID: covidwho-2022708

ABSTRACT

The receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to the human angiotensin-converting enzyme 2 (ACE2) receptor, which is a prerequisite for the virus to enter the cell. C-reactive protein (CRP) is an important marker of inflammation and is a putative soluble pattern recognition receptor. Clinical elevation of CRP levels in patients with COVID-19 is one of the characteristics of the disease; however, whether CRP is involved in COVID-19 pathogenesis is unknown. Here, we report that monomeric CRP (mCRP) can bind to the SARS-CoV-2 spike RBD and competitively inhibit its binding to ACE2. Furthermore, truncated mutant peptide competition assays and surface plasmon resonance binding experiments showed that the cholesterol-binding sequence (CBS, amino acids 35-47) in mCRP was critical for mediating the binding of mCRP to spike RBD. In a cell model of spike RBD and ACE2 interaction, the CBS motif effectively reduced the binding of spike RBD to ACE2 overexpressed on the cell surface. Thus, this study highlights the pattern recognition function of mCRP in innate immunity and provides a preliminary theoretical basis for the development of the CBS motif in mCRP into a functional peptide with both diagnostic significance and potential therapeutic capabilities.


Subject(s)
Angiotensin-Converting Enzyme 2 , C-Reactive Protein , COVID-19 , Spike Glycoprotein, Coronavirus , Angiotensin-Converting Enzyme 2/metabolism , C-Reactive Protein/metabolism , Cholesterol , Humans , Receptors, Virus/metabolism , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism
2.
Frontiers in immunology ; 13, 2022.
Article in English | EuropePMC | ID: covidwho-1958142

ABSTRACT

The receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to the human angiotensin-converting enzyme 2 (ACE2) receptor, which is a prerequisite for the virus to enter the cell. C-reactive protein (CRP) is an important marker of inflammation and is a putative soluble pattern recognition receptor. Clinical elevation of CRP levels in patients with COVID-19 is one of the characteristics of the disease;however, whether CRP is involved in COVID-19 pathogenesis is unknown. Here, we report that monomeric CRP (mCRP) can bind to the SARS-CoV-2 spike RBD and competitively inhibit its binding to ACE2. Furthermore, truncated mutant peptide competition assays and surface plasmon resonance binding experiments showed that the cholesterol-binding sequence (CBS, amino acids 35-47) in mCRP was critical for mediating the binding of mCRP to spike RBD. In a cell model of spike RBD and ACE2 interaction, the CBS motif effectively reduced the binding of spike RBD to ACE2 overexpressed on the cell surface. Thus, this study highlights the pattern recognition function of mCRP in innate immunity and provides a preliminary theoretical basis for the development of the CBS motif in mCRP into a functional peptide with both diagnostic significance and potential therapeutic capabilities.

3.
Front Psychol ; 13: 890327, 2022.
Article in English | MEDLINE | ID: covidwho-1933842

ABSTRACT

Aims: A negative association between the lower level of psychological resilience (PR) and increased risk of compassion fatigue (CF) and higher Coronavirus disease 2019 (COVID-19) stress has been revealed. However, bibliometric studies have not been performed to comprehensively investigate this topic. This study aimed to identify the status and trends in the CF and PR field from 2008 to 2021 and during the COVID-19 pandemic. Methods: We identified relevant literature from the Web of Science Core Collection® database using "resilience" and "compassion fatigue" on September 30, 2021. All search results were exported in plain text format for collaboration network analysis, reference-based co-citation analysis, analysis of journals, and keywords-based co-occurrence analysis, which were performed using Citespace® 5.8.R1. Results: A total of 388 publications were identified finally, and there has been an increasing trend in the annual number of publications with light fluctuations. The analysis of journals and keywords indicated that nurses and social workers are the main research targets, and their mental problems are the main research topics. The turnover intention of health care providers has been a research focus, particularly during the COVID-19. Conclusion: The results of the present study help us understand the status of the CF and PR field and its recent developments.

4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-323574

ABSTRACT

This study, using a virus-free mouse model, explores the pathogenic roles of certain antibodies specific to the spike proteins of highly pathogenic coronaviruses such as the COVID-19 and the SARS-CoV viruses. Our data showed that these pathogenic antibodies, through a mechanism of Antibody Dependent Auto-Attack (ADAA), target and bind to host vulnerable cells or tissues such as damaged lung epithelium cells, initiate a self-attack immune response, and lead to serious conditions including ARDS, cytokine release, and death. Moreover, the pathogenic antibodies also induced inflammation and hemorrhage of the kidneys, brain, and heart. Furthermore, the pathogenic antibodies can bind to unmatured fetal tissues and cause abortions, postpartum labors, still births, and neonatal deaths of pregnant mice. Novel clinical interventions, through disrupting the host-binding of these pathogenic antibodies, can be developed to fight the COVID-19 pandemic. In addition, the new concept of ADAA explored by this study may be applicable to other infectious diseases, such as the highly pathogenic influenza infections. It should be noted that the majority of anti-spike antibodies are non-pathogenic, as only 2 of 7 monoclonal antibodies tested showed significant pathogenic effects.

5.
Front Microbiol ; 12: 729455, 2021.
Article in English | MEDLINE | ID: covidwho-1470761

ABSTRACT

Objectives: COVID-19 is highly infectious and has been widely spread worldwide, with more than 159 million confirmed cases and more than 3 million deaths as of May 11, 2021. It has become a serious public health event threatening people's lives and safety. Due to the rapid transmission and long incubation period, shortage of medical resources would easily occur in the short term of discovering disease cases. Therefore, we aimed to construct an artificial intelligent framework to rapidly distinguish patients with COVID-19 from common pneumonia and non-pneumonia populations based on computed tomography (CT) images. Furthermore, we explored artificial intelligence (AI) algorithms to integrate CT features and laboratory findings on admission to predict the clinical classification of COVID-19. This will ease the burden of doctors in this emergency period and aid them to perform timely and appropriate treatment on patients. Methods: We collected all CT images and clinical data of novel coronavirus pneumonia cases in Inner Mongolia, including domestic cases and those imported from abroad; then, three models based on transfer learning to distinguish COVID-19 from other pneumonia and non-pneumonia population were developed. In addition, CT features and laboratory findings on admission were combined to predict clinical types of COVID-19 using AI algorithms. Lastly, Spearman's correlation test was applied to study correlations of CT characteristics and laboratory findings. Results: Among three models to distinguish COVID-19 based on CT, vgg19 showed excellent diagnostic performance, with area under the curve (AUC) of the receiver operating characteristic (ROC) curve at 95%. Together with laboratory findings, we were able to predict clinical types of COVID-19 with AUC of the ROC curve at 90%. Furthermore, biochemical markers, such as C-reactive protein (CRP), LYM, and lactic dehydrogenase (LDH) were identified and correlated with CT features. Conclusion: We developed an AI model to identify patients who were positive for COVID-19 according to the results of the first CT examination after admission and predict the progression combined with laboratory findings. In addition, we obtained important clinical characteristics that correlated with the CT image features. Together, our AI system could rapidly diagnose COVID-19 and predict clinical types to assist clinicians perform appropriate clinical management.

6.
ACS Omega ; 6(11): 7951-7958, 2021 Mar 23.
Article in English | MEDLINE | ID: covidwho-1155694

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a worldwide pandemic. To understand the changes in plasma proteomics upon SARS-CoV-2 infection, we analyzed the protein profiles of plasma samples from 10 COVID-19 patients and 10 healthy volunteers by using the DIA quantitative proteomics technology. We compared and identified differential proteins whose abundance changed upon SARS-CoV-2 infection. Bioinformatic analyses were then conducted for these identified differential proteins. The GO/KEEG database was used for functional annotation and enrichment analysis. The interaction relationship of differential proteins was evaluated with the STRING database, and Cytoscape software was used to conduct network analysis of the obtained data. A total of 323 proteins were detected in all samples. Difference between patients and healthy donors was found in 44 plasma proteins, among which 36 proteins were up-regulated and 8 proteins were down-regulated. GO functional annotation showed that these proteins mostly composed of cellular anatomical entities and proteins involved in biological regulation, cellular processes, transport, and other processes. KEEG functional annotation further showed that these proteins were mainly involved in complement system activation and infectious disease processes. Importantly, a KEEG pathway (natural killer cell-mediated cytotoxicity) was enriched, with three important activators of this pathway, ICAM1/2 and IgG, being up-regulated. Protein-protein interaction (PPI) statistics indicated that, among these 44 proteins, 6 were the most significantly up-regulated (DBH, SHGB, TF, ICAM2, THBS1, and C1RL) while 2 were the most significantly down-regulated (APCS and ORM1). Results from this study showed that a few proteins associated with immune activation were up-regulated in patient plasma. In addition, this study established a method for extraction and quantitative determination of plasma components in convalescent plasma from COVID-19 patients.

7.
Med Sci Monit ; 27: e926751, 2021 Feb 11.
Article in English | MEDLINE | ID: covidwho-1079820

ABSTRACT

BACKGROUND Coronavirus disease 2019 (COVID-19) is spreading rapidly worldwide, and scientists are trying to find a way to overcome the disease. We explored the risk factors that influence patient outcomes, including treatment regimens, which can provide a reference for further treatment. MATERIAL AND METHODS A retrospective cohort study analysis was performed using data from 97 patients with COVID-19 who visited Wuhan Union Hospital from February 2020 to March 2020. We collected data on demographics, comorbidities, clinical manifestations, laboratory tests, treatment methods, outcomes, and complications. Patients were divided into a recovered group and a deceased group. We compared the differences between the 2 groups and analyzed risk factors influencing the treatment effect. RESULTS Seventy-six patients recovered and 21 died. The average age and body mass index (BMI) of the deceased group were significantly higher than those of the recovered group (69.81±6.80 years vs 60.79±11.28 years, P<0.001 and 24.95±3.14 kg/m² vs 23.09±2.97 kg/m², P=0.014, respectively). The combination of antiviral drugs and supportive therapy appears to be associated with the lowest mortality (P<0.05). Multivariate Cox regression analysis revealed that age, BMI, H-CRP, shock, and acute respiratory distress syndrome (ARDS) were independent risk factors for patients with COVID-19 (P<0.05). CONCLUSIONS Elderly patients and those with a high BMI, as well as patients who experience shock and ARDS, may have a higher risk of death from COVID-19. The combination of antiviral drugs and supportive therapy appears to be associated with lower mortality, although further research is needed.


Subject(s)
COVID-19/drug therapy , COVID-19/mortality , Respiratory Distress Syndrome/mortality , Shock/mortality , Age Factors , Aged , Antiviral Agents/therapeutic use , COVID-19/complications , COVID-19/virology , China/epidemiology , Drug Therapy, Combination/methods , Drugs, Chinese Herbal/therapeutic use , Female , Hospital Mortality , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Prognosis , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/therapy , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , SARS-CoV-2/pathogenicity , Shock/etiology , Shock/therapy , Treatment Outcome , gamma-Globulins/therapeutic use
8.
Medicine (Baltimore) ; 99(27): e21026, 2020 Jul 02.
Article in English | MEDLINE | ID: covidwho-619205

ABSTRACT

BACKGROUND: This study will explore the effect of advanced nursing care (ANC) on psychological disorder (PD) in patients with Coronavirus Disease 2019 (COVID-19). METHODS: This study will search the following electronic databases up to June 30, 2020: Cochrane Library, PUBMED, EMBASE, PsycINFO, Web of Science, OpenGrey, Cumulative Index to Nursing and Allied Health Literature, CNKI, and WANGFANG. We will not impose any language limitations. Two authors will independently identify titles/abstracts and full-text of all potential studies, and will collect data from eligible studies. Additionally, study quality will be assessed by Cochrane risk of bias. If necessary, we will conduct meta-analysis if sufficient trials are included. RESULTS: This study will explore the effect of ANC on PD in patients with COVID-19 through outcome indicators. CONCLUSION: The findings of this study may supply summarized evidence of ANC for the management of PD in COVID-19. PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020187610.


Subject(s)
Coronavirus Infections/psychology , Mental Disorders/nursing , Pneumonia, Viral/psychology , Betacoronavirus , COVID-19 , Humans , Mental Disorders/virology , Pandemics , SARS-CoV-2 , Systematic Reviews as Topic
9.
J Med Virol ; 92(9): 1449-1459, 2020 09.
Article in English | MEDLINE | ID: covidwho-31398

ABSTRACT

BACKGROUND: Currently, the epidemic of coronavirus disease 2019 (COVID-19) has begun to spread worldwide. We aim to explore reliable evidence for the diagnosis and treatment of the COVID-19 by analyzing all the published studies by Chinese scholars on the clinical and imaging features in novel coronavirus pneumonia caused by SARS-CoV-2. METHODS: We searched five medical databases including two Chinese and three English databases for all published articles on COVID-19 since the outbreak. A random-effects model was designed, and the imaging and clinical data from all studies were collected for meta-analysis. RESULTS: Overall, 31 articles and 46 959 patients were included, including 10 English articles and 21 Chinese articles. The results of meta-analysis showed that the most common clinical manifestations were fever (87.3%; 0.838-0.909), cough (58.1%; 0.502-0.660), dyspnea (38.3%; 0.246-0.520), muscle soreness or fatigue (35.5%; 0.253-0.456), and chest distress (31.2%; -0.024 to 0.648). The main imaging findings were bilateral pneumonia (75.7%; 0.639-0.871) and ground-glass opacification (69.9%; 0.602-0.796). Among the patients, the incidence that required intensive care unit (ICU) was (29.3%; 0.190-0.395), the incidence with acute respiratory distress syndrome was (28.8%; 0.147-0.429), the incidence with multiple organ dysfunction syndrome was (8.5%; -0.008 to 0.179), and the case fatality rate of patients with COVID-19 was (6.8%; 0.044-0.093). CONCLUSION: COVID-19 is a new clinical infectious disease that mainly causes bilateral pneumonia and lung function deteriorates rapidly. Nearly a third of patients need to be admitted to the ICU, and patients are likely to present respiratory failure or even death.


Subject(s)
COVID-19/diagnostic imaging , Adult , Female , Humans , Lung/diagnostic imaging , Lung/virology , Male , Middle Aged , Respiratory Insufficiency/virology , Tomography, X-Ray Computed
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