Coronaviral ORF6 protein mediates inter-organelle contacts and modulates host cell lipid flux for virus production.

Lipid droplets (LDs) form inter-organelle contacts with the endoplasmic reticulum (ER) that promote their biogenesis, while LD contacts with mitochondria enhance ß-oxidation of contained fatty acids. Viruses have been shown to take advantage of lipid droplets to promote viral production, but it remains unclear whether they also modulate the interactions between LDs and other organelles. Here, we showed that coronavirus ORF6 protein targets LDs and is localized to the mitochondria-LD and ER-LD contact sites, where it regulates LD biogenesis and lipolysis. At the molecular level, we find that ORF6 inserts into the LD lipid monolayer via its two amphipathic helices. ORF6 further interacts with ER membrane proteins BAP31 and USE1 to mediate ER-LDs contact formation. Additionally, ORF6 interacts with the SAM complex in the mitochondrial outer membrane to link mitochondria to LDs. In doing so, ORF6 promotes cellular lipolysis and LD biogenesis to reprogram host cell lipid flux and facilitate viral production.

An alternative mechanism for skeletal muscle dysfunction in long-term post-viral lung disease.

Chronic lung disease is often accompanied by disabling extrapulmonary symptoms, notably skeletal muscle dysfunction and atrophy. Moreover, the severity of respiratory symptoms correlates with decreased muscle mass and in turn lowered physical activity and survival rates. Previous models of muscle atrophy in chronic lung disease often modeled chronic obstructive pulmonary disease (COPD) and relied on cigarette smoke exposure and LPS stimulation, but these conditions independently affect skeletal muscle even without accompanying lung disease. Moreover, there is an emerging and pressing need to understand the extrapulmonary manifestations of long-term post-viral lung disease (PVLD) as found in COVID-19. Here, we examine the development of skeletal muscle dysfunction in the setting of chronic pulmonary disease caused by infection due to the natural pathogen Sendai virus using a mouse model of PVLD. We identify a significant decrease in myofiber size when PVLD is maximal at 49 days after infection. We find no change in the relative types of myofibers, but the greatest decrease in fiber size is localized to fast-twitch-type IIB myofibers based on myosin heavy chain immunostaining. Remarkably, all biomarkers of myocyte protein synthesis and degradation (total RNA, ribosomal abundance, and ubiquitin-proteasome expression) were stable throughout the acute infectious illness and chronic post-viral disease process. Together, the results demonstrate a distinct pattern of skeletal muscle dysfunction in a mouse model of long-term PVLD. The findings thereby provide new insights into prolonged limitations in exercise capacity in patients with chronic lung disease after viral infections and perhaps other types of lung injury.NEW & NOTEWORTHY Our study used a mouse model of post-viral lung disease to study the impact of chronic lung disease on skeletal muscle. The model reveals a decrease in myofiber size that is selective for specific types of myofibers and an alternative mechanism for muscle atrophy that might be independent of the usual markers of protein synthesis and degradation. The findings provide a basis for new therapeutic strategies to correct skeletal muscle dysfunction in chronic respiratory disease.

Coronavirus Subverts ER-phagy by Hijacking FAM134B and ATL3 into p62 Condensates to Facilitate Viral Replication

ER-phagy is a form of autophagy, which is mediated by ER-phagy receptors and selectively degrades endoplasmic reticulum (ER). RNA viruses have been shown to utilize the ER as a membrane source to establish their replication organelles double-membrane vesicles (DMVs). However, whether viruses modulate ER-phagy to drive viral DMV formation and its underlying molecular mechanisms remain largely unknown. Here, we demonstrate that coronavirus subverts ER-phagy by hijacking the ER-phagy receptors FAM134B and ATL3 into p62 condensates, resulting in increased viral replication. Mechanistically, we show that viral protein ORF8 binds to and undergoes condensation with p62. FAM134B and ATL3 interact with homodimer of ORF8 and are aggregated into ORF8/p62 liquid droplets, leading to ER-phagy inhibition. ORF8/p62 condensates disrupt ER-phagy to facilitate viral DMV formation and activates ER stress. Together, our data highlight how coronavirus modulates ER-phagy to drive viral replication by hijacking ER-phagy receptors. Graphical abstract Tan et al. describe an important mechanism by which SARS-CoV-2 protein ORF8 inhibits ER-phagy by hijacking the receptors FAM134B and ATL3 into p62 condensates, facilitating the production of viral replication organelle double membrane vesicles.

Coronavirus subverts ER-phagy by hijacking FAM134B and ATL3 into p62 condensates to facilitate viral replication.

ER-phagy is a form of autophagy that is mediated by ER-phagy receptors and selectively degrades endoplasmic reticulum (ER). Coronaviruses have been shown to use the ER as a membrane source to establish their double-membrane vesicles (DMVs). However, whether viruses modulate ER-phagy to drive viral DMV formation and its underlying molecular mechanisms remains largely unknown. Here, we demonstrate that coronavirus subverts ER-phagy by hijacking the ER-phagy receptors FAM134B and ATL3 into p62 condensates, resulting in increased viral replication. Mechanistically, we show that viral protein ORF8 binds to and undergoes condensation with p62. FAM134B and ATL3 interact with homodimer of ORF8 and are aggregated into ORF8/p62 liquid droplets, leading to ER-phagy inhibition. ORF8/p62 condensates disrupt ER-phagy to facilitate viral DMV formation and activate ER stress. Together, our data highlight how coronavirus modulates ER-phagy to drive viral replication by hijacking ER-phagy receptors.

Valence-arousal classification of emotion evoked by Chinese ancient-style music using 1D-CNN-BiLSTM model on EEG signals for college students.

During the COVID-19 pandemic, young people are using multimedia content more frequently to communicate with each other on Internet platforms. Among them, music, as psychological support for a lonely life in this special period, is a powerful tool for emotional self-regulation and getting rid of loneliness. More and more attention has been paid to the music recommender system based on emotion. In recent years, Chinese music has tended to be considered an independent genre. Chinese ancient-style music is one of the new folk music styles in Chinese music and is becoming more and more popular among young people. The complexity of Chinese-style music brings significant challenges to the quantitative calculation of music. To effectively solve the problem of emotion classification in music information search, emotion is often characterized by valence and arousal. This paper focuses on the valence and arousal classification of Chinese ancient-style music-evoked emotion. It proposes a hybrid one-dimensional convolutional neural network and bidirectional and unidirectional long short-term memory model (1D-CNN-BiLSTM). And a self-acquisition EEG dataset for Chinese college students was designed to classify music-induced emotion by valence-arousal based on EEG. In addition to that, the proposed 1D-CNN-BILSTM model verified the performance of public datasets DEAP and DREAMER, as well as the self-acquisition dataset DESC. The experimental results show that, compared with traditional LSTM and 1D-CNN-LSTM models, the proposed method has the highest accuracy in the valence classification task of music-induced emotion, reaching 94.85%, 98.41%, and 99.27%, respectively. The accuracy of the arousal classification task also gained 93.40%, 98.23%, and 99.20%, respectively. In addition, compared with the positive valence classification results of emotion, this method has obvious advantages in negative valence classification. This study provides a computational classification model for a music recommender system with emotion. It also provides some theoretical support for the brain-computer interactive (BCI) application products of Chinese ancient-style music which is popular among young people.

Valence-arousal classification of emotion evoked by Chinese ancient-style music using 1D-CNN-BiLSTM model on EEG signals for college students

During the COVID-19 pandemic, young people are using multimedia content more frequently to communicate with each other on Internet platforms. Among them, music, as psychological support for a lonely life in this special period, is a powerful tool for emotional self-regulation and getting rid of loneliness. More and more attention has been paid to the music recommender system based on emotion. In recent years, Chinese music has tended to be considered an independent genre. Chinese ancient-style music is one of the new folk music styles in Chinese music and is becoming more and more popular among young people. The complexity of Chinese-style music brings significant challenges to the quantitative calculation of music. To effectively solve the problem of emotion classification in music information search, emotion is often characterized by valence and arousal. This paper focuses on the valence and arousal classification of Chinese ancient-style music-evoked emotion. It proposes a hybrid one-dimensional convolutional neural network and bidirectional and unidirectional long short-term memory model (1D-CNN-BiLSTM). And a self-acquisition EEG dataset for Chinese college students was designed to classify music-induced emotion by valence-arousal based on EEG. In addition to that, the proposed 1D-CNN-BILSTM model verified the performance of public datasets DEAP and DREAMER, as well as the self-acquisition dataset DESC. The experimental results show that, compared with traditional LSTM and 1D-CNN-LSTM models, the proposed method has the highest accuracy in the valence classification task of music-induced emotion, reaching 94.85%, 98.41%, and 99.27%, respectively. The accuracy of the arousal classification task also gained 93.40%, 98.23%, and 99.20%, respectively. In addition, compared with the positive valence classification results of emotion, this method has obvious advantages in negative valence classification. This study provides a computational classification model for a music recommender system with emotion. It also provides some theoretical support for the brain-computer interactive (BCI) application products of Chinese ancient-style music which is popular among young people.

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review.

Traditional Chinese medicine, as a complementary and alternative medicine, has been practiced for thousands of years in China and possesses remarkable clinical efficacy. Thus, systematic analysis and examination of the mechanistic links between Chinese herbal medicine (CHM) and the complex human body can benefit contemporary understandings by carrying out qualitative and quantitative analysis. With increasing attention, the approach of network pharmacology has begun to unveil the mystery of CHM by constructing the heterogeneous network relationship of "herb-compound-target-pathway," which corresponds to the holistic mechanisms of CHM. By integrating computational techniques into network pharmacology, the efficiency and accuracy of active compound screening and target fishing have been improved at an unprecedented pace. This review dissects the core innovations to the network pharmacology approach that were developed in the years since 2015 and highlights how this tool has been applied to understanding the coronavirus disease 2019 and refining the clinical use of CHM to combat it.

The effect of i-deals on employees’ unethical behavior during the COVID-19 pandemic: The roles of hubristic pride and grandiose narcissism

The COVID-19 pandemic has created enormous challenges for organizations and employees. Due to the effectiveness of idiosyncratic deals (i-deals for short) in management practices, more and more organizations use this human resource management tool to address the challenges posed by the COVID-19 pandemic. However, whether there are potential risks or negative effects of i-deals in the COVID-19 pandemic environment is not very clear. Drawing upon social cognitive theory, we proposed that i-deals may foment focal employees’ unethical behavior by triggering their hubristic pride, and such process may be moderated by their trait of grandiose narcissism. We conducted a survey during the COVID-19 outbreak and tested our hypotheses with 492 samples from Shandong Province, China. Consistent with predictions, we found a positive relationship between i-deals and hubristic pride, which, in turn, increased their unethical behavior. And the relationship between i-deals and unethical behavior was mediated by hubristic pride. Furthermore, grandiose narcissism strengthened the positive relationship between i-deals and hubristic pride, as well as the indirect effect of i-deals on unethical behavior via hubristic pride. Our findings contributed to the literature on i-deals and provided guidance for organizations to address the challenges posed by the COVID-19 pandemic.

Impact of the SARS-CoV-2 Delta Variant on the Psychological States and Health-Related Quality of Life in Patients With Crohn's Disease.

Background: Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic first reported in Wuhan, China, several research on the psychological impact of the pandemic on patients with Crohn's disease (CD) have been conducted. However, with the progression of the global pandemic and the emergence of the SARS-CoV-2 B.1.617.2 (Delta) variant, follow-up studies need to be performed to monitor the alterations of psychological status and health-related quality of life (HRQoL) among CD patients. Aims: We aimed to evaluate the impact of the SARS-CoV-2 Delta variant on the mental health and life quality among the CD population and tried to explore potent risk factors. Methods: This observational study included 153 CD patients who responded to our pre-designed self-reported questionnaire. Demographic, clinical, and psychological information were collected and analyzed. Results: Quite a number of CD patients were confronted with different levels of anxiety and depression, with incidence of 28.10 and 31.37% for anxiety and depression, respectively. Compared with non-pandemic circumstances, the life quality of CD patients due to the present situation was more often compromised. Isolation [odds ratio (OR): 4.71, P = 0.007] was verified as a risk factor for anxiety while use of telemedicine could help relieve anxiety (OR: 0.22, P < 0.001). Worsening of symptoms (OR: 4.92, P = 0.006), isolation (OR: 5.75, P = 0.005), and drug withdrawn (OR: 2.66, P = 0.026) were identified to be independent factors for developing depression. Likewise, use of telemedicine (OR: 0.13, P < 0.001) was negatively related to depression. Considering life quality, vaccination (OR: 3.07, P = 0.021) together with no medication (OR: 7.73, P = 0.010) was relevant to better life quality while worsening of symptoms (OR: 0.09, P = 0.034) were an independent risk factor for impaired life quality. Conclusion: Many CD patients suffered from symptoms of anxiety and depression and impaired life quality during the COVID-19 pandemic. Those in isolation or with worsening of symptoms and drug withdrawn were more prone to experience psychological stress. Individualized management such as drug delivery and telemedicine should be promoted to maintain control of mental health and life quality during the pandemic.

The Impacts of COVID-19 on Distance Education with the Application of Traditional and Digital Appliances: Evidence from 60 Developing Countries.

Educational disruptions from the COVID-19 pandemic during school closures have become a remarkable social issue, particularly among the developing countries. Ample literature has verified the adverse effects of the long-lasing epidemic on school education. However, rare studies seek to understand the association between the severity of COVID-19 and distance learning, an alternative education pattern, and foster policy designs to promote educational transition, particularly targeting the post-crisis phase of the COVID-19. By combining four data surveys, this article empirically examines the impacts of COVID-19 on children's distance education with the application of various appliances across 60 developing countries. The results suggest that, after controlling socio-economic, geographic, and demographic variables, a higher level of mortality rate of COVID-19 contributes to more households participating in distance education. In particular, this positive term is larger for distance education by using TVs and radios compared with the usage of digital appliances. To explore the potential channel of the above linkage, this article argues that the positive association between mortality rate and the use of traditional appliances is weakened through higher levels of stringency in lockdown measures. Timely policies are, therefore, recommended to guide towards distance learning with economic and technological supports to guarantee a wave of inclusive educational recovery in the ongoing post-COVID-19 era.

The Impacts of COVID-19 on Distance Education with the Application of Traditional and Digital Appliances: Evidence from 60 Developing Countries

Educational disruptions from the COVID-19 pandemic during school closures have become a remarkable social issue, particularly among the developing countries. Ample literature has verified the adverse effects of the long-lasing epidemic on school education. However, rare studies seek to understand the association between the severity of COVID-19 and distance learning, an alternative education pattern, and foster policy designs to promote educational transition, particularly targeting the post-crisis phase of the COVID-19. By combining four data surveys, this article empirically examines the impacts of COVID-19 on children's distance education with the application of various appliances across 60 developing countries. The results suggest that, after controlling socio-economic, geographic, and demographic variables, a higher level of mortality rate of COVID-19 contributes to more households participating in distance education. In particular, this positive term is larger for distance education by using TVs and radios compared with the usage of digital appliances. To explore the potential channel of the above linkage, this article argues that the positive association between mortality rate and the use of traditional appliances is weakened through higher levels of stringency in lockdown measures. Timely policies are, therefore, recommended to guide towards distance learning with economic and technological supports to guarantee a wave of inclusive educational recovery in the ongoing post-COVID-19 era.

Efficacy of a 6-Week Home-Based Online Supervised Exercise Program Conducted During COVID-19 in Patients With Post Percutaneous Coronary Intervention: A Single-Blind Randomized Controlled Trial.

Objective: The aim of this study was to assess the efficacy of a 6-week cardiac rehabilitation (CR) program designed for patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI) that involved an online supervised exercise program that they could access during COVID-19. Methods: One hundred patients were randomly allocated into control group (CG) and supervision group (SG). CG accepted conventional health education with a home exercise program booklet delivered before discharge, SG had an additional home-based online supervised exercise program (HOSEP). Questionnaires, motor function and lipid profile were administered at baseline. Questionnaires included the Godin-Shephard Leisure-Time Physical Activity questionnaire (GSLTPAQ) and Bandura's Exercise Self-efficacy (ESE). Motor function included: 6-min walk test (6 MWT), timed up and go test (TUG), 30-s sit to stand (30-s STS), and Hand Grip Strength (HG). Lipid profile included: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC) and triglycerides (TG). The questionnaires were re-administered after 2-weeks, all tests were re-evaluated after 6-weeks. Results: the questionnaire results showed that scores on GSLTPAQ and ESE were significantly improved in the SG. The changes in GSLTPAQ scores from baseline to 2- and 6-weeks in the SG were significantly higher than in the CG (2-week: 6.9 ± 13.0 for SG and 0.2 ± 10.2 for CG, p = 0.005; 6-week: 9.4 ± 18.1 for SG and 0.2 ± 11.8 for CG, p = 0.003). in terms of motor function, both the CG and SG improved TUG and 6 MWT performance, with the 6 MWT improvement being significantly greater in the SG than CG (43.7 ± 39.2 m for SG and 16.6 ± 39.1 m for CG, p = 0.001). Improvement in the 30-s STS was significantly greater in the SG than CG (2.4 ± 3.6 repetitions for SG and 0.4 ± 3.5 repetitions for CG, p = 0.007). the lipid profile level significantly improved over baseline in both SG and CG after 6-week intervention, and these changes were not statistically different between groups. Conclusion: This pilot randomized control study demonstrated that a 6-week HOSEP, when added to education delivered pre-hospital discharge for CAD patients following PCI, was beneficial with respect to exercise self-efficacy, exercise behavior, motor function and lipid profile. Supervised exercise programs delivered online in addition to education providing effective and accessible CR during COVID-19.

A study on the influencing factors of online student engagement and learning outcome in preventive medicine undergraduates during COVID-2019 epidemic

Objective: Taking the undergraduate education and preventive medicine for example, this paper examines and evaluates the student engagement and learning outcome in online learning during the period of "suspending classes without stopping learning", and to explore the influencing factors.

Efficacy and Safety of "Three Chinese Patent Medicines and Three TCM Prescriptions" for COVID-19: A Systematic Review and Network Meta-Analysis.

OBJECTIVE: To systematically evaluate the efficacy, safety, and precision of TMTP for COVID-19. METHODS: Randomized controlled trials and retrospective studies were searched in 11 electronic databases. This network meta-analysis included trials using TMTP to treat patients with COVID-19. The traditional pairwise meta-analysis was done by using Stata 15, and Bayesian network meta-analysis was done with WinBUGS. RESULTS: 18 trials were included with 2036 participants and 7 drugs. The results showed that LHQW had the most significant effects on improving expectoration, shortness of breath, sore throat, nausea, emesis, inappetence, muscle soreness, and headache, and it could produce the least adverse reactions. XBJ was the best drug for fever, fatigue, and diarrhea, which showed great advantages in lowering WBC levels. XFBD was the most effective drug for cough and chest distress, which had the least exacerbation rate. JHQG was the most effective for rhinobyon and rhinorrhea, while QFPD was the best drug in decreasing CRP levels. CONCLUSION: This study was the first most large-scale and comprehensive research of TMTP for COVID-19. The results showed that LHQW had good efficacy without obvious adverse reactions. Therefore, we believe that it should be firstly recommended for COVID-19 treatment. In addition, XBJ is recommended for patients with a severe fever, fatigue, and diarrhea, and JHQG is recommended for patients with obvious rhinobyon and rhinorrhea; then, XFBD is recommended for patients with cough and chest tightness as the main manifestation. Our findings will help experts develop new COVID-19 treatment guidelines to better guide clinical medication for protecting the health of COVID-19 patients.

Longitudinal Metabolomics Reveals Ornithine Cycle Dysregulation Correlates With Inflammation and Coagulation in COVID-19 Severe Patients.

COVID-19 is a severe disease in humans, as highlighted by the current global pandemic. Several studies about the metabolome of COVID-19 patients have revealed metabolic disorders and some potential diagnostic markers during disease progression. However, the longitudinal changes of metabolomics in COVID-19 patients, especially their association with disease progression, are still unclear. Here, we systematically analyzed the dynamic changes of the serum metabolome of COVID-19 patients, demonstrating that most of the metabolites did not recover by 1-3 days before discharge. A prominent signature in COVID-19 patients comprised metabolites of amino acids, peptides, and analogs, involving nine essential amino acids, 10 dipeptides, and four N-acetylated amino acids. The levels of 12 metabolites in amino acid metabolism, especially three metabolites of the ornithine cycle, were significantly higher in severe patients than in mild ones, mainly on days 1-3 or 4-6 since onset. Integrating blood metabolomic, biochemical, and cytokine data, we uncovered a highly correlated network, including 6 cytokines, 13 biochemical parameters, and 49 metabolites. Significantly, five ornithine cycle-related metabolites (ornithine, N-acetylornithine, 3-amino-2-piperidone, aspartic acid, and asparagine) highly correlated with "cytokine storms" and coagulation index. We discovered that the ornithine cycle dysregulation significantly correlated with inflammation and coagulation in severe patients, which may be a potential mechanism of COVID-19 pathogenicity. Our study provided a valuable resource for detailed exploration of metabolic factors in COVID-19 patients, guiding metabolic recovery, understanding the pathogenic mechanisms, and creating drugs against SARS-CoV-2 infection.

Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine.

Over the last two decades, a large number of non-communicable/chronic disorders reached an epidemic level on a global scale such as diabetes mellitus type 2, cardio-vascular disease, several types of malignancies, neurological and eye pathologies-all exerted system's enormous socio-economic burden to primary, secondary, and tertiary healthcare. The paradigm change from reactive to predictive, preventive, and personalized medicine (3PM/PPPM) has been declared as an essential transformation of the overall healthcare approach to benefit the patient and society at large. To this end, specific biomarker panels are instrumental for a cost-effective predictive approach of individualized prevention and treatments tailored to the person. The source of biomarkers is crucial for specificity and reliability of diagnostic tests and treatment targets. Furthermore, any diagnostic approach preferentially should be noninvasive to increase availability of the biomaterial, and to decrease risks of potential complications as well as concomitant costs. These requirements are clearly fulfilled by tear fluid, which represents a precious source of biomarker panels. The well-justified principle of a "sick eye in a sick body" makes comprehensive tear fluid biomarker profiling highly relevant not only for diagnostics of eye pathologies but also for prediction, prognosis, and treatment monitoring of systemic diseases. One prominent example is the Sicca syndrome linked to a cascade of severe complications that include dry eye, neurologic, and oncologic diseases. In this review, protein profiles in tear fluid are highlighted and corresponding biomarkers are exemplified for several relevant pathologies, including dry eye disease, diabetic retinopathy, cancers, and neurological disorders. Corresponding analytical approaches such as sample pre-processing, differential proteomics, electrophoretic techniques, high-performance liquid chromatography (HPLC), enzyme-linked immuno-sorbent assay (ELISA), microarrays, and mass spectrometry (MS) methodology are detailed. Consequently, we proposed the overall strategies based on the tear fluid biomarkers application for 3P medicine practice. In the context of 3P medicine, tear fluid analytical pathways are considered to predict disease development, to target preventive measures, and to create treatment algorithms tailored to individual patient profiles.

Longitudinal and proteome-wide analyses of antibodies in COVID-19 patients reveal features of the humoral immune response to SARS-CoV-2.

Introduction: The SARS-CoV-2 pandemic has endangered global health, the world economy, and societal values. Despite intensive measures taken around the world, morbidity and mortality remain high as many countries face new waves of infection and the spread of new variants. Worryingly, more and more variants are now being identified, such as 501Y.V1 (B.1.1.7) in the UK, 501Y.V2 (B.1.351) in South Africa, 501Y.V3 in Manaus, Brazil, and B.1.617/B.1.618 in India, which could lead to a severe epidemic rebound. Moreover, some variants have a stronger immune escape ability. To control the new SARS-CoV-2 variant, we may need to develop and redesign new vaccines repeatedly. So it is important to investigate how our immune system combats and responds to SARS-CoV-2 infection to develop safe and effective medical interventions. Objectives: In this study, we performed a longitudinal and proteome-wide analysis of antibodies in the COVID-19 patients to revealed some immune processes of COVID-19 patients against SARS-CoV-2 and found some dominant epitopes of a potential vaccine. Methods: Microarray assay, Antibody depletion assays, Neutralization assay. Results: We profiled a B-cell linear epitope landscape of SARS-CoV-2 and identified the epitopes specifically recognized by either IgM, IgG, or IgA. We found that epitopes more frequently recognized by IgM are enriched in non-structural proteins. We further identified epitopes with different immune responses in severe and mild patients. Moreover, we identified 12 dominant epitopes eliciting antibodies in most COVID-19 patients and identified five key amino acids of epitopes. Furthermore, we found epitope S-82 and S-15 are perfect immunogenic peptides and should be considered in vaccine design. Conclusion: This data provide useful information and rich resources for improving our understanding of viral infection and developing a novel vaccine/neutralizing antibodies for the treatment of SARS-CoV-2.

Appraisal of China's Response to the Outbreak of COVID-19 in Comparison With SARS.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, was first reported in Wuhan, China, in December 2019 and has since become a pandemic. The COVID-19 containment measures were comparable to those used with severe acute respiratory syndrome (SARS), although these were stricter and more organized, and were initiated earlier and on a larger scale. Based on the lessons learned from SARS, the Chinese government acted aggressively in response to COVID-19, through a unified and effective commanding system, using law-based and science-driven strategies, and coordinated deployment of medical resources. Additionally, the application of high-tech measures, traditional Chinese medicine, and hierarchical medical systems also played an important role in control measures. Despite the remarkable performance, the initial delay in response suggests that the coordination between public health and medical services, reserve and coordination of emergency materials, and capacity for disease control and prevention need to be strengthened.

Abnormal upregulation of cardiovascular disease biomarker PLA2G7 induced by proinflammatory macrophages in COVID-19 patients.

High rate of cardiovascular disease (CVD) has been reported among patients with coronavirus disease 2019 (COVID-19). Importantly, CVD, as one of the comorbidities, could also increase the risks of the severity of COVID-19. Here we identified phospholipase A2 group VII (PLA2G7), a well-studied CVD biomarker, as a hub gene in COVID-19 though an integrated hypothesis-free genomic analysis on nasal swabs (n = 486) from patients with COVID-19. PLA2G7 was further found to be predominantly expressed by proinflammatory macrophages in lungs emerging with progression of COVID-19. In the validation stage, RNA level of PLA2G7 was identified in nasal swabs from both COVID-19 and pneumonia patients, other than health individuals. The positive rate of PLA2G7 were correlated with not only viral loads but also severity of pneumonia in non-COVID-19 patients. Serum protein levels of PLA2G7 were found to be elevated and beyond the normal limit in COVID-19 patients, especially among those re-positive patients. We identified and validated PLA2G7, a biomarker for CVD, was abnormally enhanced in COVID-19 at both nucleotide and protein aspects. These findings provided indications into the prevalence of cardiovascular involvements seen in patients with COVID-19. PLA2G7 could be a potential prognostic and therapeutic target in COVID-19.