SARS-CoV-2 Spike Protein S1 Exposure Increases Susceptibility to Angiotensin II-Induced Hypertension in Rats by Promoting Central Neuroinflammation and Oxidative Stress.

The SARS-CoV-2 spike S1 subunit (S1) can cross the blood-brain barrier and elicit neuroinflammatory response independent of viral infection. Here we examined whether S1 influences blood pressure (BP) and sensitizes the hypertensive response to angiotensin (ANG) II by enhancing neuroinflammation and oxidative stress in hypothalamic paraventricular nucleus (PVN), a key brain cardiovascular regulatory center. Rats received central S1 or vehicle (VEH) injection for 5 days. One week after injection, ANG II or saline (control) was subcutaneously delivered for 2 weeks. S1 injection induced greater increases in BP, PVN neuronal excitation and sympathetic drive in ANG II rats but had no effects in control rats. One week after S1 injection, mRNA for proinflammatory cytokines and oxidative stress marker were higher but mRNA of Nrf2, the master regulator of inducible antioxidant and anti-inflammatory responses, was lower in the PVN in S1-injected rats than in VEH-injected rats. Three weeks after S1 injection, mRNA for proinflammatory cytokines and oxidative stress marker, microglia activation and reactive oxygen species in the PVN were comparable between S1 and VEH treated control rats but were elevated in two groups of ANG II rats. Notably, ANG II-induced elevations in these parameters were exaggerated by S1. Interestingly, ANG II increased PVN Nrf2 mRNA in VEH-treated rats but not in S1-treated rats. These data suggest that S1 exposure has no effect on BP, but post-S1 exposure increases susceptibility to ANG II-induced hypertension by downregulating PVN Nrf2 to promote neuroinflammation and oxidative stress and augment sympathetic excitation.

Nursing Faculty Job Satisfaction During COVID-19: A Mixed-Methods Study.

AIM: The aim of this study was to understand stress, resilience, and compassion satisfaction of nursing faculty during the COVID-19 pandemic and identify factors related to their job satisfaction. BACKGROUND: The impacts of COVID-19 on faculty stress, resilience, compassion satisfaction, and job satisfaction were unknown. METHOD: A mixed-methods survey was distributed electronically to nursing faculty in the United States. RESULTS: Compassion satisfaction and resilience were positively correlated with job satisfaction; stress and job satisfaction were negatively correlated. Feeling safe to teach, feeling supported by administration, and spending more hours teaching online were positively associated with job satisfaction. Three themes were identified: challenges in the workplace, struggles with personal stressors, and building capacity in the face of the unknown. CONCLUSION: Faculty reported a strong professional commitment to nursing education during the COVID-19 pandemic. Leadership that supported faculty through concern for their safety contributed to participants' ability to respond to the challenges experienced.

Analyzing U.S. State Governments' COVID-19 Homepages during the Initial Lockdown in March and April 2020: Information Content and Interactivity.

During times of a pandemic, government emergency response webpages are an important communication channel and if properly managed, will mitigate pandemic impacts. Guided by the Crisis and Emergency Risk Communication (CERC) framework and web interactivity literature, this study examined the information content and interactivity of U.S. state governments' COVID-19 homepages when many states declared stay-at-home orders in March or April of 2020. Using a web archive service, we retrieved 48 state governments' COVID-19 homepages. Three coders coded these pages for the presence or absence of information content on five dimensions (timely updates, sensemaking information, efficacy information, targeted guidance, and anti-stigma communication) and interactivity on four dimensions (accessibility, navigability, media richness, and engagement). Results revealed that a large proportion of state governments' COVID-19 homepages provided timely information facilitating people's understanding of the pandemic. Yet, there were some information gaps regarding how to cope with the pandemic or its related problems, such as mental stress and social discrimination. While many COVID-19 homepages allowed easy navigation, page engagement and accessibility seemed inadequate. U.S. state governments' COVID-19 homepages could be a good source for sensemaking. Practitioners and researchers should explore how to better harness interactive Internet technologies and present information that fosters people's efficacy to manage through the pandemic.

HRL4EC: Hierarchical reinforcement learning for multi-mode epidemic control.

Infectious diseases, such as Black Death, Spanish Flu, and COVID-19, have accompanied human history and threatened public health, resulting in enormous infections and even deaths among citizens. Because of their rapid development and huge impact, laying out interventions becomes one of the most critical paths for policymakers to respond to the epidemic. However, the existing studies mainly focus on epidemic control with a single intervention, which makes the epidemic control effectiveness severely compromised. In view of this, we propose a Hierarchical Reinforcement Learning decision framework for multi-mode Epidemic Control with multiple interventions called HRL4EC. We devise an epidemiological model, referred to as MID-SEIR, to describe multiple interventions' impact on transmission explicitly, and use it as the environment for HRL4EC. Besides, to address the complexity introduced by multiple interventions, this work transforms the multi-mode intervention decision problem into a multi-level control problem, and employs hierarchical reinforcement learning to find the optimal strategies. Finally, extensive experiments are conducted with real and simulated epidemic data to validate the effectiveness of our proposed method. We further analyze the experiment data in-depth, conclude a series of findings on epidemic intervention strategies, and make a visualization accordingly, which can provide heuristic support for policymakers' pandemic response.

Are inflammatory bowel diseases associated with an increased risk of COVID-19 susceptibility and severity? A two-sample Mendelian randomization study.

Background: Due to inconsistent findings in observational studies regarding the relationship between inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn's disease (CD), and COVID-19, our objective is to explore a potential causative correlation between IBD and COVID-19 susceptibility and its severity using a two-sample Mendelian randomization (MR) analysis. Methods: Using summary data from genome-wide association studies, IBD, including UC and CD, were used as exposure instruments, while COVID-19 susceptibility, hospitalization, and very severe illness were employed as the outcome. The five analysis methods were adopted to evaluate the causal relationship between two diseases, with the inverse variance weighted (IVW) method being the most important. Also, sensitivity analyses were done to make sure that the main results of the MR analyses were reliable. Results: In the analysis using five methods, all p-values were higher than 0.05. There was no association between IBD and COVID-19 susceptibility, hospitalization, and severity in our MR study. The random-effect model was applied due to the existence of heterogeneity. MR-Egger regression revealed no indication of directional pleiotropy, and sensitivity analysis revealed similar relationships. Conclusion: This MR study found no evidence to support that IBD (which includes UC and CD) increases the risk of COVID-19 susceptibility or severity. Our result needs further confirmation through larger epidemiological studies.

A tissue specific-infection mouse model of SARS-CoV-2.

Animal models play crucial roles in the rapid development of vaccines/drugs for the prevention and therapy of COVID-19, but current models have some deficits when studying the pathogenesis of SARS-CoV-2 on some special tissues or organs. Here, we generated a human ACE2 and SARS-CoV-2 NF/F knockin mouse line that constitutively expresses human ACE2 and specifically expresses SARS-CoV-2 N gene induced by Cre-recombinase. By crossing with Cre transgenic lines allowing for lung-specific and constitutive expression, we generated lung-specific (Sftpc-hACE2-NF/F) and constitutive SARS-CoV-2 N (EIIa-hACE2-NF/F) expressing mice. Upon intranasal infection with a SARS-CoV-2 GFP/ΔN strain which can only replicate in SARS-CoV-2 N expressed cells, we demonstrated that both the Sftpc-hACE2-NF/F and EIIa-hACE2-NF/F mice support viral replication. Consistent with our design, viral replication was limited to the lung tissues in Sftpc-hACE2-NF/F mice, while the EIIa-hACE2-NF/F mice developed infections in multiple tissues. Furthermore, our model supports different SARS-CoV-2 variants infection, and it can be successfully used to evaluate the effects of therapeutic monoclonal antibodies (Ab1F11) and antiviral drugs (Molnupiravir). Finally, to test the effect of SARS-CoV-2 infection on male reproduction, we generated Sertoli cell-specific SARS-CoV-2 N expressed mice by crossing with AMH-Cre transgenic line. We found that SARS-CoV-2 GFP/ΔN strain could infect Sertoli cells, led to spermatogenic defects due to the destruction of blood-testis barrier. Overall, combining with different tissue-specific Cre transgenic lines, the human ACE2 and SARS-CoV-2 NF/F line enables us to evaluate antivirals in vivo and study the pathogenesis of SARS-CoV-2 on some special tissues or organs.

Investigating Students' Satisfaction with Online Collaborative Learning During the COVID-19 Period: An Expectation-Confirmation Model.

The recent outbreak of COVID-19 posed discontinuous disruption to traditional learning modes worldwide. In order to keep social distance, online collaborative learning has become a necessity during the pandemic. However, our understanding of students' well-being and satisfaction with online collaborative learning is limited, especially during the COVID-19 period. Leveraging expectation confirmation theory, this study focuses on the triggers and inhibitors of students' cognitive load during online collaborative learning process and their subsequent satisfaction with the learning mode during the pandemic. We used a mixed-method approach in this study. We conducted a qualitative study with interview data and a quantitative study with surveys. The results indicate several psychological and cognitive antecedents of students' cognitive load during online collaborative learning. Findings also indicate that a high level of cognitive load will decrease students' perceived usefulness of the online learning platform and expectation confirmation, thus leading to a low level of satisfaction with online collaborative learning. This study can provide theoretical and practical implications for a better understanding of online student groups' satisfaction with online collaborative learning during the COVID-19 period.

Developing and testing a protocol to systematically assess social interaction with urban outdoor environment.

Social interaction is significant for individuals' mental and psychological well-being in communities. With the growing demand for outdoor activities in urban settings under the COVID­19 pandemic, urban parks have become important public resources for human social activities. Researchers have developed numerous instruments to measure park use behaviors, but most are designed for assessing physical activity while ignoring social interactive behaviors. Despite the importance, no single protocol objectively assesses the range of social interactions in urban outdoor environments. To bridge the research gap, we have developed a social interaction scale (SIS) based on Parten's scheme. The innovative protocol, named Systematically Observing Social Interaction in Parks (SOSIP) was developed based on the SIS, allowing systematic evaluation of human's interactive behaviors in outdoor environment both from their levels of social interaction and group size. The psychometric properties of SOSIP were established through the verification of content validity and reliability tests. Additionally, we applied SOSIP to explore relationships between park features and social interaction via hierarchical linear models (HLMs). Statistical comparisons between SOSIP and other forms of social interaction were discussed and indicated strong reliability of applying SOSIP. The results indicated SOSIP is a valid and reliable protocol for objectively assessing social interactive behaviors within urban outdoor environments and informing better understanding of individuals' mental and psychological health benefits.

To trust or not to trust: a qualitative study of older adults' online communication during the COVID-19 pandemic

Online communication is an effective solution to the social isolation of older adults that can result from attempts to avoid COVID-19 transmission, but they may not be familiar with virtual identities in online communication and struggle to develop trusting relationships. We address this dilemma in this study by using qualitative methods including semi-structured interviews. We employ the social exchange theory and trust transfer theory to develop a conceptual model from three perspectives: the characteristics of the trustor, those of the trustee, and their shared factors. We find that trust is moderated by social isolation and health concerns experienced by older adults during the pandemic and that outcomes associated with trust building include satisfaction, reliance, and loyalty. The findings enrich our understanding of the mental health of older adults and online interactions during the COVID-19 pandemic, and can be extended to similar contexts in which long-term isolation is necessary. Supplementary Information The online version contains supplementary material available at 10.1007/s10660-023-09679-4.

Low‐Altitude UAV Imaging Accurately Quantifies Eelgrass Wasting Disease From Alaska to California

Declines in eelgrass, an important and widespread coastal habitat, are associated with wasting disease in recent outbreaks on the Pacific coast of North America. This study presents a novel method for mapping and predicting wasting disease using Unoccupied Aerial Vehicle (UAV) with low‐altitude autonomous imaging of visible bands. We conducted UAV mapping and sampling in intertidal eelgrass beds across multiple sites in Alaska, British Columbia, and California. We designed and implemented a UAV low‐altitude mapping protocol to detect disease prevalence and validated against in situ results. Our analysis revealed that green leaf area index derived from UAV imagery was a strong and significant (inverse) predictor of spatial distribution and severity of wasting disease measured on the ground, especially for regions with extensive disease infection. This study highlights a novel, efficient, and portable method to investigate seagrass disease at landscape scales across geographic regions and conditions.Alternate abstract:Plain Language SummaryDiseases of marine organisms are increasing in many regions worldwide, therefore, efficient time‐series monitoring is critical for understanding the dynamics of disease and examining its progression in time to implement management interventions. In the first study of its kind, we use high‐resolution Unoccupied Aerial Vehicle (UAV) imagery collected to detect disease at 12 sites across the North‐East Pacific coast of North America spanning 18 degrees of latitude. The low altitude UAV visible‐bands imagery achieved 1.5 cm spatial resolution, and analysis was performed at the seagrass leaf scale based on object‐oriented image analysis. Our findings suggest that drone mapping of coastal plants may substantially increase the scale of disease risk assessments in nearshore habitats and further our understanding of seagrass meadow spatial‐temporal dynamics. These can be scaled up by searching for environmental signals of the pathogen, for example, with surveillance of wastewater for signs of Covid in human populations. This application could easily apply to other areas to construct a high‐resolution monitoring network for seagrass conservation.

Development of an Antigen Detection Kit Capable of Discriminating the Omicron Mutants of SARS-CoV-2.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread around the world, caused millions of deaths and a severe illness which poses a serious threat to human health. OBJECTIVE: To develop an antigen detection kit that can identify Omicron novel coronavirus mutants. METHODS: BALB/c mice were immunized with the nucleocapsid protein of SARS-CoV-2 Omicron mutant treated with ß-propiolactone. After fusion of myeloma cells with immune cells, Elisa was used to screen the cell lines capable of producing monoclonal antibodies. The detection kit was prepared by colloidal gold immunochromatography. Finally, the sensitivity, specificity and anti-interference of the kit were evaluated by simulating positive samples. RESULTS: The sensitivity of the SARS-CoV-2 antigen detection kit can reach 62.5 TCID50/mL, and it has good inclusiveness for different SARS-CoV-2 strains. The kit had no cross-reaction with common respiratory pathogens, and its sensitivity was still not affected under the action of different concentrations of interferences, indicating that it had good specificity and stability. CONCLUSION: In this study, monoclonal antibodies with high specificity to the N protein of the Omicron mutant strain were obtained by monoclonal antibody screening technology. Colloidal gold immunochromatography technology was used to prepare an antigen detection kit with high sensitivity to detect and identify the mutant Omicron strain.

Induction of pulmonary HLA-G expression by SARS-CoV-2 infection.

The non-classical human leukocyte antigen (HLA)-G exerts immune-suppressive properties modulating both NK and T cell responses. While it is physiologically expressed at the maternal-fetal interface and in immune-privileged organs, HLA-G expression is found in tumors and in virus-infected cells. So far, there exists little information about the role of HLA-G and its interplay with immune cells in biopsies, surgical specimen or autopsy tissues of lung, kidney and/or heart muscle from SARS-CoV-2-infected patients compared to control tissues. Heterogeneous, but higher HLA-G protein expression levels were detected in lung alveolar epithelial cells of SARS-CoV-2-infected patients compared to lung epithelial cells from influenza-infected patients, but not in other organs or lung epithelia from non-viral-infected patients, which was not accompanied by high levels of SARS-CoV-2 nucleocapsid antigen and spike protein, but inversely correlated to the HLA-G-specific miRNA expression. High HLA-G expression levels not only in SARS-CoV-2-, but also in influenza-infected lung tissues were associated with a high frequency of tissue-infiltrating immune cells, but low numbers of CD8+ cells and an altered expression of hyperactivation and exhaustion markers in the lung epithelia combined with changes in the spatial distribution of macrophages and T cells. Thus, our data provide evidence for an involvement of HLA-G and HLA-G-specific miRNAs in immune escape and as suitable therapeutic targets for the treatment of SARS-CoV-2 infections.

Face-mask-aware Facial Expression Recognition based on Face Parsing and Vision Transformer.

As wearing face masks is becoming an embedded practice due to the COVID-19 pandemic, facial expression recognition (FER) that takes face masks into account is now a problem that needs to be solved. In this paper, we propose a face parsing and vision Transformer-based method to improve the accuracy of face-mask-aware FER. First, in order to improve the precision of distinguishing the unobstructed facial region as well as those parts of the face covered by a mask, we re-train a face-mask-aware face parsing model, based on the existing face parsing dataset automatically relabeled with a face mask and pixel label. Second, we propose a vision Transformer with a cross attention mechanism-based FER classifier, capable of taking both occluded and non-occluded facial regions into account and reweigh these two parts automatically to get the best facial expression recognition performance. The proposed method outperforms existing state-of-the-art face-mask-aware FER methods, as well as other occlusion-aware FER methods, on two datasets that contain three kinds of emotions (M-LFW-FER and M-KDDI-FER datasets) and two datasets that contain seven kinds of emotions (M-FER-2013 and M-CK+ datasets).

Open Innovation in Times of Crisis: An Overview of the Healthcare Sector in Response to the COVID-19 Pandemic

The COVID-19 pandemic has caused huge and disruptive technological changes in the healthcare sector, transforming the way businesses and societies function. To respond to the global health crisis, there have been numerous innovation projects in the healthcare sector, including the fast design and manufacturing of personal protective equipment (PPE) and medical devices, and testing, treatment, and vaccine technologies. Many of these innovative activities happen beyond organizational boundaries with collaboration and open innovation. In this paper, we review the current literature on open innovation strategy during the pandemic and adopt the co-evolution view of business ecosystems to address the context of change. Based on a detailed exploration of the COVID-19-related technologies in the UK and global healthcare sectors, we identify the key emerging themes of open innovation in crisis. Further discussions are conducted in relation to each theme. Our results and analysis can help provide policy recommendations for the healthcare sector, businesses, and society to recover from the crisis.

RBM24 inhibits the translation of SARS-CoV-2 polyproteins by targeting the 5'-untranslated region.

SARS-CoV-2 is a betacoronavirus with single-stranded positive-sense RNA, which is a serious global threat to human health. Understanding the molecular mechanism of viral replication is crucial for the development of antiviral drugs. The synthesis of viral polyproteins is a crucial step in viral progression. The synthesis of viral polyproteins in coronaviruses is regulated by the 5'-untranslated region (UTR); however, the detailed regulatory mechanism needs further investigation. The present study demonstrated that the RNA binding protein, RBM24, interacts with the RNA genome of SARS-CoV-2 via its RNA recognition submotifs (RNPs). The findings revealed that RBM24 recognizes and binds to the GUGUG element at stem-loop 4 (SL4) in the 5'-UTR of SARS-CoV-2. The interaction between RBM24 and 5'-UTR prevents 80S ribosome assembly, which in turn inhibits polyproteins translation and the replication of SARS-CoV-2. Notably, other RNA viruses, including SARS-CoV, MERS-CoV, Ebolavirus, rhinovirus, West Nile virus, Zika virus, Japanese encephalitis virus, yellow fever virus, hepatitis C virus, and human immunodeficiency virus-1 also contain one or several G(U/C/A)GUG sequences in the 5'-UTR, which is also targeted by RBM24. In conclusion, the present study demonstrated that RBM24 functions by interacting with the 5'-UTR of SARS-CoV-2 RNA, and elucidated that RBM24 could be a host restriction factor for SARS-CoV-2 and other RNA viruses.

Effects of housing environments on COVID-19 transmission and mental health revealed by COVID-19 Participant Experience data from the All of Us Research Program in the USA: a case-control study.

OBJECTIVES: To examine the association between housing types and COVID-19 infection (or mental health) during the early stages of the pandemic by using the large-scale individual-level All of Us Research Program COVID-19 Participant Experience (COPE) survey data. We hypothesise that housing types with a shared component are associated with elevated COVID-19 infection and subsequent mental health conditions. DESIGN: A retrospective case-control study. SETTING: Secondary analysis of online surveys conducted in the USA. PARTICIPANTS: 62 664 participant responses to COPE from May to July 2020. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome measure is the self-reported COVID-19 status, and the secondary outcome measures are anxiety or stress. Both measures were applied for matched cases and controls of the same race, sex, age group and survey version. RESULTS: A multiple logistic regression analysis revealed that housing types with a shared component are significantly associated with COVID-19 infection (OR=1.19, 95% CI 1.1 to 1.3; p=2×10-4), anxiety (OR=1.26, 95% CI 1.1 to 1.4; p=1.1×10-6) and stress (OR=1.29, 95% CI 1.2 to 1.4; p=4.3×10-10) as compared with free-standing houses, after adjusting for confounding factors. Further, frequent optional shopping or outing trips, another indicator of the built environment, are also associated with COVID-19 infection (OR=1.36, 95% CI 1.1 to 1.8; p=0.02), but not associated with elevated mental health conditions. Confounding factors are controlled in the analysis such as ethnicity, age, social distancing behaviour and house occupancy. CONCLUSION: Our study demonstrates that houses with a shared component tend to have an increased risk of COVID-19 transmission, which consequently leads to high levels of anxiety and stress for their dwellers. The study also suggests the necessity to improve the quality of the built environment such as residential housing and its surroundings through planning, design and management, ensuring a more resilient society that can cope with future pandemics.

ZBP1: A Powerful Innate Immune Sensor and Double-Edged Sword in Host Immunity.

Z-conformation nucleic acid binding protein 1 (ZBP1), a powerful innate immune sensor, has been identified as the important signaling initiation factor in innate immune response and the multiple inflammatory cell death known as PANoptosis. The initiation of ZBP1 signaling requires recognition of left-handed double-helix Z-nucleic acid (includes Z-DNA and Z-RNA) and subsequent signaling transduction depends on the interaction between ZBP1 and its adapter proteins, such as TANK-binding kinase 1 (TBK1), interferon regulatory factor 3 (IRF3), receptor-interacting serine/threonine-protein kinase 1 (RIPK1), and RIPK3. ZBP1 activated innate immunity, including type-I interferon (IFN-I) response and NF-κB signaling, constitutes an important line of defense against pathogenic infection. In addition, ZBP1-mediated PANoptosis is a double-edged sword in anti-infection, auto-inflammatory diseases, and tumor immunity. ZBP1-mediated PANoptosis is beneficial for eliminating infected cells and tumor cells, but abnormal or excessive PANoptosis can lead to a strong inflammatory response that is harmful to the host. Thus, pathogens and host have each developed multiplex tactics targeting ZBP1 signaling to maintain strong virulence or immune homeostasis. In this paper, we reviewed the mechanisms of ZBP1 signaling, the effects of ZBP1 signaling on host immunity and pathogen infection, and various antagonistic strategies of host and pathogen against ZBP1. We also discuss existent gaps regarding ZBP1 signaling and forecast potential directions for future research.

Exploring Factors Associated with Chinese-Americans' Willingness to Receive an Additional Hypothetical Annual Dose of the COVID-19 Vaccine.

Chinese-Americans are one of the largest groups of Asian-Americans in the US with distinctive behavioral and cultural characteristics that influence health service use. Although Chinese-Americans have significantly higher COVID-19-related mortality rates, relative to other racial and ethnic groups, limited literature is available examining their willingness to accept the COVID-19 vaccine. With recent development of the combination influenza-COVID-19 vaccine by biotechnology companies to mitigate COVID-19 infection, we examined factors associated with Chinese-Americans' acceptance of hypothetical annual doses of COVID-19 vaccination before the vaccine rollout. A total of 241 Chinese-Americans who received at least one dose of the COVID-19 vaccine completed an online questionnaire developed and based on health behavior theories. Our results indicated that Chinese-American participants who were satisfied with their prior COVID-19 vaccination experience, who had more accurate knowledge and perceived higher susceptibility of getting COVID-19, were more willing to receive the annual COVID-19 vaccine in the future. The findings of our current study may be used to guide the development of strategic messages to promote uptake of the annual COVID-19 vaccine by Chinese-Americans in the U.S.

A highly sensitive bead-based flow cytometric competitive binding assay to detect SARS-CoV-2 neutralizing antibody activity.

Accurate detection of SARS-CoV-2 neutralizing antibody (nAb) is critical for assessing the immunity levels after virus infection or vaccination. As fast, cost-effective alternatives to viral infection-based assays, competitive binding (CB) assays were developed to quantitate nAb by monitoring the ability of sera to inhibit the binding of viral spike (S) protein to the angiotensin converting enzyme 2 (ACE2) receptor. Herein, we established a bead-based flow cytometric CB assay and tested the detection performance of six combination models, i.e. immobilized ACE2 and soluble Fc-tagged S1 subunit of S protein (iACE2/S1-Fc), immobilized ACE2 and soluble Fc-tagged receptor binding domain (RBD) of S protein (iACE2/RBD-Fc), immobilized S1 and soluble Fc-tagged ACE2 (iS1/ACE2-Fc), immobilized S1 and soluble His-tagged ACE2 (iS1/ACE2-His), immobilized RBD and soluble Fc-tagged ACE2 (iRBD/ACE2-Fc), and immobilized RBD and soluble His-tagged ACE2 (iRBD/ACE2-His). Using SARS-CoV-2 monoclonal antibodies and sera of convalescent COVID-19 patients and vaccinated subjects, the combination models iACE2/RBD-Fc, iACE2/S1-Fc and iS1/ACE2-His were identified to be able to specifically detect SARS-CoV-2 nAb, among which iACE2/RBD-Fc model showed the highest sensitivity, superior to a commercial SARS-CoV-2 surrogate virus neutralization test (sVNT) ELISA kit. Further studies demonstrated that the sensitivity and specificity of CB assays were affected by the tag of ACE2, type of spike and method of measuring binding rate between ACE2 and spike. Moreover, the iACE2/RBD-Fc model showed good performance in detecting kinetic development of nAb against both the prototype SARS-CoV-2 strain and an omicron variant of SARS-CoV-2 in people immunized by an inactivated SARS-CoV-2 vaccine, and the results of iACE2/RBD-Fc model are correlated well with those of live virus-based and pseudovirus-based neutralization tests, demonstrating the potential to be developed into a highly sensitive, specific, versatile and high-throughput method for detecting SARS-CoV-2 nAb in clinical practice.

JAK-STAT signaling as an ARDS therapeutic target: Status and future trends.

Acute respiratory distress syndrome (ARDS) is characterized by noncardiogenic pulmonary edema. It has a high mortality rate and lacks effective pharmacotherapy. With the outbreak of COVID-19 worldwide, the mortality of ARDS has increased correspondingly, which makes it urgent to find effective targets and strategies for the treatment of ARDS. Recent clinical trials of Janus kinase (JAK) inhibitors in treating COVID-19-induced ARDS have shown a positive outcome, which makes the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway a potential therapeutic target for treating ARDS. Here, we review the complex cause of ARDS, the molecular JAK/STAT pathway involved in ARDS pathology, and the progress that has been made in strategies targeting JAK/STAT to treat ARDS. Specifically, JAK/STAT signaling directly participates in the progression of ARDS or colludes with other pathways to aggravate ARDS. We summarize JAK and STAT inhibitors with ARDS treatment benefits, including inhibitors in clinical trials and preclinical studies and natural products, and discuss the side effects of the current JAK inhibitors to reveal future trends in the design of JAK inhibitors, which will help to develop effective treatment strategies for ARDS in the future.