Filopodial Mechanotransduction is regulated by Angiotensin-Converting Enzyme 2 (ACE2) and by SARS-CoV-2 spike protein (preprint)

Filopodia are dynamic, actin-rich cellular protrusions, increasingly linked to cellular mechanotransduction. However, how dynamic filopodia translate external mechanical cues remains poorly understood. Recent studies show that the SARS-CoV-2 spike (S) protein binds the ACE2 receptor on airway multicilia and that cilia are required for viral infection(1) and sufficient to induce filopodial extension and viral binding. To test if spike protein is sufficient to induce filopodial expansion, we employed live-cell single-particle tracking with quantum dots targeting ACE2, to reveal a robust filopodia extension and virus binding mechanism requiring the enzymatic activity of ACE2. Using time-lapse imaging, we reveal that spike protein binding to filopodia is associated with intracellular actin remodeling, alterations in bulk cell stiffness, and an elevation in intracellular calcium levels linked to actin-rearrangement, filopodia initiation, and persistence. We propose the activation of ACE2 creates an active signaling and mechanosensory environment within adherent cells and airway epithelial cells that allows the remodeling of actin in filopodia to trap virus and potentially organize viral exit from cells.

Clinical characteristics and analysis of risk factors for disease progression in patients on maintenance hemodialysis infected with SARS-CoV-2 omicron variant (preprint)

Objective:To summarize the clinical characteristics of patients on maintenance hemodialysis (MHD) with the novel coronavirus omicron variant and explore the risk factors for severe cases. Methods:We retrospectively analyzed the data of 158 patients on MHD from Zhongnan Hospital of Wuhan University between December 7, 2022 and January 31, 2023. We collected clinical data, described clinical characteristics, and analyzed the relationships between these factors and critical illness using univariate and multivariate logistic regression analyses. Results: The median age of the 158 patients was 63 (interquartile range: 52–71) years, and 128 (63.7%) were men. Fever (62.7%) and cough (60.1%) were the two most common symptoms. Hypertension (80.4%) was the most common comorbidity, followed by diabetes (31.0%), cardiovascular disease (22.8%), and cerebrovascular disease (15.2%). Unvaccinated patients constituted the majority of the enrolled patients (88.6%, 140/158), whereas only a small proportion (11.4%, 18/158) had been vaccinated (including fully vaccinated and partially vaccinated patients). Multivariate logistic regression analysis indicated that an elevated C-reactive protein (CRP) level (odds ratio [OR]: 1.03, 95% confidence interval [CI], 1.014–1.046], p<0.001) and a decreased platelet count (OR: 0.986, 95% CI, 0.986 (0.976–0.997), p=0.013) during hospitalization were risk factors for the severe group. Conclusions:This study demonstrated a high mortality rate among patients on MHD infected with omicron variant. Furthermore, advanced age, increased CRP levels, and decreased platelet count were predictors of critical illness.

Effect of Multimedia E-Book Use on the Information Literacy of Nursing Students and Health Communication in Student-Led Large- and Small-Group Community Health Education Sessions

The integration of digital technology into healthcare is critical for health communication. This study analyzed a group of nursing students who applied multimedia health education e-books to different groups of varying sizes to explore the efficiency of implementing health communication and nursing information literacy in the nursing industry. If medical personnel can make appropriate use of technology, combine medical operations with information systems, and disseminate the purpose of health to groups of different sizes properly, the quality of patient care will improve. Thirty-two junior nursing students at the college level were divided into three groups, each subject to a 3-week internship. After the internship, a questionnaire survey was conducted. Additionally, nine nursing students were interviewed in a 45-min semistructured format. Regarding the effectiveness of nursing students using multimedia e-books to implement health communication and the development of nursing information literacy, the statistical analysis results demonstrated no significant differences between large groups and small groups. However, their 5-point Likert scale average values were all greater than 4, indicating that regardless of group size, their feedback on using e-books was positive. This means multimedia e-books can effectively help nursing students practice health communication application effectiveness and develop nursing information literacy.

Intranasal delivery of NS1-deleted influenza virus vectored COVID-19 vaccine restrains the SARS-CoV-2 inflammatory response (preprint)

The emergence of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) variants and "anatomical escape" characteristics threaten the effectiveness of current coronavirus disease (COVID-19) vaccines. There is an urgent need to understand the immunological mechanism of broad-spectrum respiratory tract protection to guide broader vaccines development. In this study, we investigated immune responses induced by an NS1-deleted influenza virus vectored intranasal COVID-19 vaccine (dNS1-RBD) which provides broad-spectrum protection against SARS-CoV-2 variants. Intranasal delivery of dNS1-RBD induced innate immunity, trained immunity and tissue-resident memory T cells covering the upper and lower respiratory tract. It restrained the inflammatory response by suppressing early phase viral load post SARS-CoV-2 challenge and attenuating pro-inflammatory cytokine (IL-6, IL-1B, and IFN-{gamma}) levels, thereby reducing excess immune-induced tissue injury compared with the control group. By inducing local cellular immunity and trained immunity, intranasal delivery of NS1-deleted influenza virus vectored vaccine represents a broad-spectrum COVID-19 vaccine strategy to reduce disease burden.

The impact of COVID-19 lockdown on maternal and neonatal outcomes of uninfected woman in late pregnancy: A multicenter study in China (preprint)

Background COVID-19 pandemic has had direct and indirect impacts on health-care system and maternal and neonatal health, but no multicenter evidence from China of this effects has been undertaken. The purpose of this study was to investigate the impacts of COVID-19 lockdown on maternal and fetal outcomes in China.Methods This retrospective cohort study included 3540 women in their late pregnancy without COVID-19 who received perinatal healthcare in three hospitals in Wuhan, Shanghai and Haikou during COVID-19 lockdown period in 2020 or the non-lockdown period in 2019. Propensity-score matching was used to compare preterm birth (< 37 weeks) and its classification, very preterm birth (< 34 weeks), caesarean section and its indications, the length of hospital stay, birth weight and other pregnancy outcomes between two groups.Results Preterm births before 37 weeks’ gestation (5.4% vs. 5.3%, P = 0.83) and very preterm birth (0.7% vs. 0.8%, P = 0.58) were not significantly changed overall. But medical-induced preterm birth before 37 weeks’ gestation in Wuhan was decreased (0.8% vs. 1.7%, P = 0.04). The cesarean section for maternal factors was decreased (21.4% vs. 24.3%, P = 0.003). The length of maternal (4.2d vs 4.5d, P < 0.001) and neonatal (3.4d vs 3.7d, P < 0.001) hospital stay was shortened. No overall significant effects were identified for other outcomes included in the quantitative analysis: maternal gestational diabetes; pregnancy-induced hypertension; preterm birth with premature rupture of membranes; low birthweight (< 2500 g); neonatal intensive care unit admission; or abnormal Apgar score.Conclusions This study demonstrated that there was protective impact of the COVID-19 lockdown on maternal and neonatal outcomes among women in their late pregnancy in China.

Linguistic Pattern-Infused Dual-Channel Bidirectional Long Short-term Memory With Attention for Dengue Case Summary Generation From the Program for Monitoring Emerging Diseases-Mail Database: Algorithm Development Study.

BACKGROUND: Globalization and environmental changes have intensified the emergence or re-emergence of infectious diseases worldwide, such as outbreaks of dengue fever in Southeast Asia. Collaboration on region-wide infectious disease surveillance systems is therefore critical but difficult to achieve because of the different transparency levels of health information systems in different countries. Although the Program for Monitoring Emerging Diseases (ProMED)-mail is the most comprehensive international expert-curated platform providing rich disease outbreak information on humans, animals, and plants, the unstructured text content of the reports makes analysis for further application difficult. OBJECTIVE: To make monitoring the epidemic situation in Southeast Asia more efficient, this study aims to develop an automatic summary of the alert articles from ProMED-mail, a huge textual data source. In this paper, we proposed a text summarization method that uses natural language processing technology to automatically extract important sentences from alert articles in ProMED-mail emails to generate summaries. Using our method, we can quickly capture crucial information to help make important decisions regarding epidemic surveillance. METHODS: Our data, which span a period from 1994 to 2019, come from the ProMED-mail website. We analyzed the collected data to establish a unique Taiwan dengue corpus that was validated with professionals' annotations to achieve almost perfect agreement (Cohen κ=90%). To generate a ProMED-mail summary, we developed a dual-channel bidirectional long short-term memory with attention mechanism with infused latent syntactic features to identify key sentences from the alerting article. RESULTS: Our method is superior to many well-known machine learning and neural network approaches in identifying important sentences, achieving a macroaverage F1 score of 93%. Moreover, it can successfully extract the relevant correct information on dengue fever from a ProMED-mail alerting article, which can help researchers or general users to quickly understand the essence of the alerting article at first glance. In addition to verifying the model, we also recruited 3 professional experts and 2 students from related fields to participate in a satisfaction survey on the generated summaries, and the results show that 84% (63/75) of the summaries received high satisfaction ratings. CONCLUSIONS: The proposed approach successfully fuses latent syntactic features into a deep neural network to analyze the syntactic, semantic, and contextual information in the text. It then exploits the derived information to identify crucial sentences in the ProMED-mail alerting article. The experiment results show that the proposed method is not only effective but also outperforms the compared methods. Our approach also demonstrates the potential for case summary generation from ProMED-mail alerting articles. In terms of practical application, when a new alerting article arrives, our method can quickly identify the relevant case information, which is the most critical part, to use as a reference or for further analysis.

Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay† † Electronic supplementary information (ESI) available: ESI 1 and ESI file 2. See DOI: 10.1039/d1ra00426c

The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to the cell receptor and affect the potency of vaccines and antibodies. Here we used an in silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay results show that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated the in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit the development of broadly neutralizing vaccine and antibody. The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates viral cell attachment and serves as a promising target for therapeutics development.

Lineage-mosaic and mutation-patched spike proteins for broad-spectrum COVID-19 vaccine (preprint)

The widespread SARS-CoV-2 in humans results in the continuous emergence of new variants. Recently emerged Omicron variant with multiple spike mutations sharply increases the risk of breakthrough infection or reinfection, highlighting the urgent need for new vaccines with broad-spectrum antigenic coverage. Using inter-lineage chimera and mutation patch strategies, we engineered a recombinant monomeric spike variant (STFK1628x), which showed high immunogenicity and mutually complementary antigenicity to its prototypic form (STFK). In hamsters, a bivalent vaccine comprised of STFK and STFK1628x elicited high titers of broad-spectrum antibodies to neutralize all 14 circulating SARS-CoV-2 variants, including Omicron; and fully protected vaccinees from intranasal SARS-CoV-2 challenges of either the ancestral strain or immune-evasive Beta variant. Strikingly, the vaccination of hamsters with the bivalent vaccine completely blocked the within-cage virus transmission to unvaccinated sentinels, for either the ancestral SARS-CoV-2 or Beta variant. Thus, our study provides new insights and antigen candidates for developing next-generation COVID-19 vaccines.

Fusobacterium nucleatum bacteremia with liver abscess following administration of anti-COVID-19 vector-based vaccine (preprint)

Immunization of the population through vaccination against COVID-19 is recognized as a public health priority. The most difficult scientific challenge for vaccines is the clinical safety and efficacy. We report a patient presenting with Fusobacterium nucleatum bacteremia and liver abscess formation following administration of anti-COVID-19 viral-vectored vaccine.

Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19

Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, ;LogFC;≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.

The Influence of COVID-19 on Irrational Consumption Behavior in a Chinese Sample: Based on a Serial Mediating Model.

Based on the scarcity theory, this study focuses on exploring the relationship between the severity of public health emergencies (i.e., COVID-19) and individual irrational consumer behaviors through the serial mediating variables of perceived scarcity (PS) and negative mentality (NM). An online questionnaire was used to collect data from participants in China and we obtained 466 effective (115 male and 351 female) questionnaires in total. The findings showed that the relationship between each pair of factors - perceived pandemic severity, PS, NM, and irrational consumption behaviors - was significantly positive. Although the perception of the severity of this public health emergency did not directly predict irrational consumer behavior, the effect was mediated by PS and NM independently and serially. These findings reveal that people who strongly perceive scarcity and are prone to negative attitudes are more likely to demonstrate irrational consumer behaviors (such as rushing to buy and hoard living supplies) once the public perceives a public health emergency as severe. This effect occurs because the PS that results from the epidemic affects people's cognition, emotion, and behavior.

A live attenuated influenza virus-vectored intranasal COVID-19 vaccine provides rapid, prolonged, and broad protection against SARS-CoV-2 infection (preprint)

Remarkable progress has been made in developing intramuscular vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, they are limited with respect to eliciting local immunity in the respiratory tract, which is the primary infection site for SARS-CoV-2. To overcome the limitations of intramuscular vaccines, we constructed a nasal vaccine candidate based on an influenza vector by inserting a gene encoding the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2, named CA4-dNS1-nCoV-RBD (dNS1-RBD). A preclinical study showed that in hamsters challenged 1 day and 7 days after single-dose vaccination or 6 months after booster vaccination, dNS1-RBD largely mitigated lung pathology, with no loss of body weight, caused by either the prototype-like strain or beta variant of SARS-CoV-2. Lasted data showed that the animals could be well protected against beta variant challenge 9 months after vaccination. Notably, the weight loss and lung pathological changes of hamsters could still be significantly reduced when the hamster was vaccinated 24 h after challenge. Moreover, such cellular immunity is relatively unimpaired for the most concerning SARS-CoV-2 variants. The protective immune mechanism of dNS1-RBD could be attributed to the innate immune response in the nasal epithelium, local RBD-specific T cell response in the lung, and RBD-specific IgA and IgG response. Thus, this study demonstrates that the intranasally delivered dNS1-RBD vaccine candidate may offer an important addition to fight against the ongoing COVID-19 pandemic, compensating limitations of current intramuscular vaccines, particularly at the start of an outbreak.

Potent Anti-Delta Effect By a Booster Third-Dose of UB-612, a Precision-Designed SARS-CoV-2 Multitope Protein-Peptide Vaccine (preprint)

SARS-CoV-2 breakthrough infection occurs due to waning immunity time-to-vaccine, to which the globally-dominant, highly-contagious Delta variant is behind the scene. In the primary 2-dose and booster series of clinical Phase-1 trial, UB-612 vaccine, which contains S1-RBD and synthetic Th/CTL peptide pool for activation of humoral and T-cell immunity, induces substantial, prolonged viral-neutralizing antibodies that goes parallel with a long-lasting T-cell immunity; and a booster (3rd ) dose can prompt recall of memory immunity to induce profound, striking antibodies with the highest level of 50% viral-neutralizing GMT titers against live Delta variant reported for any vaccine. The unique design of S1-RBD only plus multitope T-cell peptides may have underpinned UB-612’s potent anti-Delta effect, while the other full S protein-based vaccines are affected additionally by mutations in the N-terminal domain sequence which contains additional neutralizing epitopes. UB-612, safe and well-tolerated, could be effective for boosting other vaccine platforms that have shown modest homologous boosting. [Funded by United Biomedical Inc., Asia; ClinicalTrials.gov ID: NCT04967742 and NCT04545749]

High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA.

OBJECTIVE: Incorporating spatial analyses and online health information queries may be beneficial in understanding the role of Google relative search volume (RSV) data as a secondary public health surveillance tool during pandemics. This study identified coronavirus disease 2019 (COVID-19) clustering and defined the predictability performance of Google RSV models in clustered and non-clustered areas of the USA. METHODS: Getis-Ord General and local G statistics were used to identify monthly clustering patterns. Monthly country- and state-level correlations between new daily COVID-19 cases and Google RSVs were assessed using Spearman's rank correlation coefficients and Poisson regression models for January-December 2020. RESULTS: Huge clusters involving multiple states were found, which resulted from various control measures in each state. This demonstrates the importance of state-to-state coordination in implementing control measures to tackle the spread of outbreaks. Variability in Google RSV model performance was found among states and time periods, possibly suggesting the need to use different frameworks for Google RSV data in each state. Moreover, the sign of correlation can be utilized to understand public responses to control and preventive measures, as well as in communicating risk. CONCLUSION: COVID-19 Google RSV model accuracy in the USA may be influenced by COVID-19 transmission dynamics, policy-driven community awareness and past outbreak experiences.

Emerging Technologies of Natural Language-Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics

Natural language processing (NLP) is a critical part of the digital transformation. NLP enables user-friendly interactions between machine and human by making computers understand human languages. Intelligent chatbot is an essential application of NLP to allow understanding of users’ utterance and responding in understandable sentences for specific applications simulating human-to-human conversations and interactions for problem solving or Q&As. This research studies emerging technologies for NLP-enabled intelligent chatbot development using a systematic patent analytic approach. Some intelligent text-mining techniques are applied, including document term frequency analysis for key terminology extractions, clustering method for identifying the subdomains, and Latent Dirichlet Allocation for finding the key topics of patent set. This research utilizes the Derwent Innovation database as the main source for global intelligent chatbot patent retrievals.

Citizen-state collaboration in combating COVID-19 in China: Experiences and lessons from the perspective of co-production

From the perspective of co-production, this article examines how Chinese citizens and governments worked together in fighting against COVID-19 in a health emergency context. Based on observations, as well as analyses of policy documents and self-organization cases, this article shows that Chinese citizens and governments collaborated through three different channels in fighting against the virus, but different channels produced different results. First, through residential committees, Chinese governments successfully mobilized most citizens to comply with stay-at-home orders, contact traced and isolated suspected cases through existing networks within the communities. Second, as a formal channel for state-society interaction during the crisis, government-organized nongovernmental organizations (NGOs) failed in bridging demands of the health system and contributions from citizens. Third, self-organizations emerged as a key informal channel for citizens to fight against the virus. The experiences and lessons learned in this citizen-government collaboration in combating the virus may offer some implications for other settings. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Epidemiological feature, viral shedding, and antibody seroconversion among asymptomatic SARS-CoV-2 carriers and symptomatic/presymptomatic COVID-19 patients (preprint)

Summary Novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pandemic. However, data concerning the epidemiological features, viral shedding, and antibody dynamics between asymptomatic SARS-CoV-2 carriers and COVID-19 patients remain controversial. We enrolled 193 subjects infected with SARS-CoV-2 in Ningbo and Zhoushan, Zhejiang, China from January 21 to March 6, 2020. All subjects were followed up to monitor the dynamics of immunoglobulin M (IgM) and IgG against SARS-CoV-2. Of those, 31 were asymptomatic carriers, 149 were symptomatic patients, and 14 were presymptomatic patients. Compared to symptomatic patients, asymptomatic carriers were younger and had higher levels of white blood cell and lymphocyte, lower levels of C-reactive protein and viral load, and shorter viral shedding duration. Conversion of IgM from positive to negative was shorter in asymptomatic carriers than in COVID-19 patients ( P =0.030). The proportion of those persistently seropositive for IgG was higher in COVID-19 patients than in asymptomatic carriers ( P =0.037). Viral load was higher in symptomatic than presymptomatic patients. Viral shedding was longer in presymptomatic patients than in asymptomatic carriers. Conclusively, asymptomatic carriers have a higher antiviral immunity to clear SARS-CoV-2 than do symptomatic patients and this antiviral immunity is not contributable to humoral immunity.