Initial trust formation on shared autonomous vehicles: Exploring the effects of personality-, transfer- and performance-based stimuli

Building initial trust is critical for the acceptance of shared autonomous vehicles (SAVs). Initial trust determines whether this emerging mobility solution will be accepted when it is available in the market. This study examines the initial trust formation process in the context of SAVs using the elaboration likelihood model and trust transfer theory. It investigates the effects of different personality-based, transfer-based, and performance-based factors on initial trust and adoption intention. A structural equation modelling is conducted in Singapore based on valid survey design principles, sampling protocols, and data analysis procedures. Results show that among three trust-building paths, the performance-based factors which include SAV capability and interaction quality are the most important. The transfer-based (i.e., trust in shared mobility) and personality-based factor (i.e., trust propensity) rank second and third, respectively. Six moderators such as covid history and shared mobility experience are also tested to investigate significant differences in the results. Based on these findings, this study offers theoretical and policy implications for scholars and practitioners.

Serological response to vaccination in post-acute sequelae of COVID.

BACKGROUND: Individuals with post-acute sequelae of COVID (PASC) may have a persistence in immune activation that differentiates them from individuals who have recovered from COVID without clinical sequelae. To investigate how humoral immune activation may vary in this regard, we compared patterns of vaccine-provoked serological response in patients with PASC compared to individuals recovered from prior COVID without PASC. METHODS: We prospectively studied 245 adults clinically diagnosed with PASC and 86 adults successfully recovered from prior COVID. All participants had measures of humoral immunity to SARS-CoV-2 assayed before or after receiving their first-ever administration of COVID vaccination (either single-dose or two-dose regimen), including anti-spike (IgG-S and IgM-S) and anti-nucleocapsid (IgG-N) antibodies as well as IgG-S angiotensin-converting enzyme 2 (ACE2) binding levels. We used unadjusted and multivariable-adjusted regression analyses to examine the association of PASC compared to COVID-recovered status with post-vaccination measures of humoral immunity. RESULTS: Individuals with PASC mounted consistently higher post-vaccination IgG-S antibody levels when compared to COVID-recovered (median log IgG-S 3.98 versus 3.74, P < 0.001), with similar results seen for ACE2 binding levels (median 99.1 versus 98.2, P = 0.044). The post-vaccination IgM-S response in PASC was attenuated but persistently unchanged over time (P = 0.33), compared to in COVID recovery wherein the IgM-S response expectedly decreased over time (P = 0.002). Findings remained consistent when accounting for demographic and clinical variables including indices of index infection severity and comorbidity burden. CONCLUSION: We found evidence of aberrant immune response distinguishing PASC from recovered COVID. This aberrancy is marked by excess IgG-S activation and ACE2 binding along with findings consistent with a delayed or dysfunctional immunoglobulin class switching, all of which is unmasked by vaccine provocation. These results suggest that measures of aberrant immune response may offer promise as tools for diagnosing and distinguishing PASC from non-PASC phenotypes, in addition to serving as potential targets for intervention.

Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?

Shared autonomous vehicles (SAVs) are revolutionizing the future of urban mobility. This study aims to investigate the effects of artificial intelligence (i.e., autonomy level and anthropomorphic characteristics), human-related, environmental, and societal factors on public trust and acceptance. Structural equation modelling is used to analyze a valid survey sample of 451 participants. Results show that autonomy level can both directly and indirectly (via trust) increase public acceptance;Whereas, anthropomorphic characteristics cannot directly affect public acceptance, but can indirectly increase their acceptance via trust. The other human-related, environmental, and societal factors also positively contribute to public acceptance. Additionally, moderators, including age, gender, income, housing size, COVID-19 history, shared mobility experience, vehicle ownership, and driving experience are also examined. In theory, this study contextualizes the trust-in-automation three-factor model, UTAUT model, and trust theory and includes two domain-specific constructs (i.e., SAV anthropomorphism and SAV autonomy) to study public trust and acceptance towards SAVs. In practice, this study suggests the incorporation of some anthropomorphic features and relatively high autonomy level in SAVs to build public trust and acceptance.

Remote Blood Oxygen Estimation From Videos Using Neural Networks.

Peripheral blood oxygen saturation (SpO 2) is an essential indicator of respiratory functionality and received increasing attention during the COVID-19 pandemic. Clinical findings show that COVID-19 patients can have significantly low SpO 2 before any obvious symptoms. Measuring an individual's SpO 2 without having to come into contact with the person can lower the risk of cross contamination and blood circulation problems. The prevalence of smartphones has motivated researchers to investigate methods for monitoring SpO 2 using smartphone cameras. Most prior schemes involving smartphones are contact-based: They require using a fingertip to cover the phone's camera and the nearby light source to capture reemitted light from the illuminated tissue. In this paper, we propose the first convolutional neural network based noncontact SpO 2 estimation scheme using smartphone cameras. The scheme analyzes the videos of an individual's hand for physiological sensing, which is convenient and comfortable for users and can protect their privacy and allow for keeping face masks on. We design explainable neural network architectures inspired by the optophysiological models for SpO 2 measurement and demonstrate the explainability by visualizing the weights for channel combination. Our proposed models outperform the state-of-the-art model that is designed for contact-based SpO 2 measurement, showing the potential of the proposed method to contribute to public health. We also analyze the impact of skin type and the side of a hand on SpO 2 estimation performance.

Willingness to participate in virtual reality technologies: Public adoption and policy perspectives for marine conservation.

Greater efforts are required to educate the public about marine conservation as the marine environment continues to deteriorate over time. A way to remotely travel during the pandemic is provided by virtual reality technologies in marine ecotourism. In order to present a theoretical framework that explains consumers' propensity to participate in virtual reality technology, this study draws on the theories of perceived risk, trust, and attitude. An online survey with 451 respondents was administered in Singapore and structural equation modeling was applied to analyze the data. The results reflect that perceived health risk, perceived financial risk, perceived social risk, and perceived performance risk, mediated by trust and attitude, have a significant influence on consumers' willingness to participate in virtual reality technologies in marine ecotourism. After analyzing their total effects, trust was found to have the highest effect on willingness to participate, followed by attitude, perceived social risk, perceived financial risk, perceived health risk, and perceived performance risk. Overall, the present research offers new perspectives on comprehending the drivers of willingness to participate, as well as implicating policies to raise public awareness of marine conservation, as well as to raise more money to support marine conservation initiatives.

A novel heterologous receptor-binding domain dodecamer universal mRNA vaccine against SARS-CoV-2 variants.

There are currently approximately 4,000 mutations in the SARS-CoV-2 S protein gene and emerging SARS-CoV-2 variants continue to spread rapidly worldwide. Universal vaccines with high efficacy and safety urgently need to be developed to prevent SARS-CoV-2 variants pandemic. Here, we described a novel self-assembling universal mRNA vaccine containing a heterologous receptor-binding domain (HRBD)-based dodecamer (HRBDdodecamer) against SARS-CoV-2 variants, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (B.1.1.28.1), Delta (B.1.617.2) and Omicron (B.1.1.529). HRBD containing four heterologous RBD (Delta, Beta, Gamma, and Wild-type) can form a stable dodecameric conformation under T4 trimerization tag (Flodon, FD). The HRBDdodecamer -encoding mRNA was then encapsulated into the newly-constructed LNPs consisting of a novel ionizable lipid (4N4T). The obtained universal mRNA vaccine (4N4T-HRBDdodecamer) presented higher efficiency in mRNA transfection and expression than the approved ALC-0315 LNPs, initiating potent immune protection against the immune escape of SARS-CoV-2 caused by evolutionary mutation. These findings demonstrated the first evidence that structure-based antigen design and mRNA delivery carrier optimization may facilitate the development of effective universal mRNA vaccines to tackle SARS-CoV-2 variants pandemic.

Lockdown effects of the COVID-19 on the spatio-temporal distribution of air pollution in Beijing, China.

To prevent the spread of COVID-19, China enacted a series of strict policies, which reduced anthropogenic activities to a near standstill. This provided a precious window to explore its effects on the spatio-temporal distribution of air pollution in Beijing, China. In this study, continuous wavelet transforms and spatial interpolation methods were used to explore the spatiotemporal variations in air pollutants and their lockdown effects. The results indicate that except O3, the annual average concentration of NO2, PM2.5 and SO2 showed a decreasing trend during 2016 and 2019; NO2, PM2.5 and SO2 show a trend of "low in summer and high in winter"; the diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume, with the first peak at the morning peak (7:00), and then accumulating gradually to second peak (22:00). The continuous wavelet analysis shows that PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. The high NO2 concentration areas were mainly in Dongcheng, Xicheng, Chaoyang and Fengtai, while the low concentration areas were located in the northern areas, such as Miyun and Huairou; the PM2.5 concentration decreased from south to north; this characteristic presented more obviously in winter. Compared to the pre-lockdown, NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation activities to the NO2, O3, PM2.5 and SO2 were estimated be 9.4 % ∼ 17.2 %, -76.4 % ∼ -42.9 %, -39.5 % ∼ -22.8 % and 5.7 % ∼ 43.7 %, respectively; the contribution rates of industrial activities were 19.9 % ∼ 26.7 %, 7.8 % ∼ 30.9 %, 1.6 % ∼ 36.2 % and -10.5 % ∼ 15.9 %, respectively. Considering meteorological factors, we inferred that pauses in anthropogenic activities indeed help improving air pollution, but it is difficult to offset the impact of extreme weather. These findings can enhance our understanding on the sources of air pollution, and can therefore provide insights on urban air pollution mitigation.

Defective Interfering Particles of Influenza Virus and Their Characteristics, Impacts, and Use in Vaccines and Antiviral Strategies: A Systematic Review.

Defective interfering particles (DIPs) are particles containing defective viral genomes (DVGs) generated during viral replication. DIPs have been found in various RNA viruses, especially in influenza viruses. Evidence indicates that DIPs interfere with the replication and encapsulation of wild-type viruses, namely standard viruses (STVs) that contain full-length viral genomes. DIPs may also activate the innate immune response by stimulating interferon synthesis. In this review, the underlying generation mechanisms and characteristics of influenza virus DIPs are summarized. We also discuss the potential impact of DIPs on the immunogenicity of live attenuated influenza vaccines (LAIVs) and development of influenza vaccines based on NS1 gene-defective DIPs. Finally, we review the antiviral strategies based on influenza virus DIPs that have been used against both influenza virus and SARS-CoV-2. This review provides systematic insights into the theory and application of influenza virus DIPs.

CRISPR-Cas-mediated diagnostics.

An ideal molecular diagnostic method should be sensitive, specific, low cost, rapid, portable, and easy to operate. Traditional nucleic acid detection methods based mainly on PCR technology have not only high sensitivity and specificity, but also some limitations, such as the need for expensive equipment and skilled technicians, being both time and labor intensive, and difficult to implement in some regions. However, with the continuous development of CRISPR-Cas technology and its application in molecular diagnosis, new approaches have been used for the construction of molecular diagnostic systems. In this review, we discuss recent advances in CRISPR-based molecular diagnostic technologies and highlight the revolution they bring to the field of molecular diagnostics.

Evidence of premature lymphocyte aging in people with low anti-spike antibody levels after BNT162b2 vaccination.

SARS-CoV-2 vaccines have unquestionably blunted the overall impact of the COVID-19 pandemic, but host factors such as age, sex, obesity, and other co-morbidities can affect vaccine efficacy. We identified individuals in a relatively healthy population of healthcare workers (CORALE study cohort) who had unexpectedly low peak anti-spike receptor binding domain (S-RBD) antibody levels after receiving the BNT162b2 vaccine. Compared to matched controls, "low responders" had fewer spike-specific antibody-producing B cells after the second and third/booster doses. Moreover, their spike-specific T cell receptor (TCR) repertoire had less depth and their CD4+ and CD8+T cell responses to spike peptide stimulation were less robust. Single cell transcriptomic evaluation of peripheral blood mononuclear cells revealed activation of aging pathways in low responder B and CD4+T cells that could underlie their attenuated anti-S-RBD antibody production. Premature lymphocyte aging may therefore contribute to a less effective humoral response and could reduce vaccination efficacy.

Awareness of SARS-CoV-2 Omicron Variant Infection Among Adults With Recent COVID-19 Seropositivity.

Importance: Some individuals who were infected by the SARS-CoV-2 Omicron variant may have been completely unaware of their infectious status while the virus was actively transmissible. Objective: To examine awareness of infectious status among individuals during the recent Omicron variant surge in a diverse and populous urban region of Los Angeles County. Design, Setting, and Participants: This cohort study analyzed the records of adult employees and patients of an academic medical center who were enrolled in a longitudinal COVID-19 serological study in Los Angeles County, California. These participants had 2 or more serial anti-nucleocapsid IgG (IgG-N) antibody measurements at least 1 month apart, with the first occurring after the end of a regional Delta variant surge (September 15, 2021) and a subsequent one occurring after the start of a regional Omicron variant surge (December 15, 2021). Adults with evidence of new SARS-CoV-2 infection occurring during the Omicron variant surge period through May 4, 2022, were included in the present study sample. Exposures: Recent Omicron variant infection as evidenced by SARS-CoV-2 seroconversion. Main Outcomes and Measures: Awareness of recent SARS-CoV-2 infection was ascertained from review of self-reported health updates, medical records, and COVID-19 testing data. Results: Of the 210 participants (median [range] age, 51 (23-84) years; 136 women [65%]) with serological evidence of recent Omicron variant infection, 44% (92) demonstrated awareness of any recent Omicron variant infection and 56% (118) reported being unaware of their infectious status. Among those who were unaware, 10% (12 of 118) reported having had any symptoms, which they attributed to a common cold or other non-SARS-CoV-2 infection. In multivariable analyses that accounted for demographic and clinical characteristics, participants who were health care employees of the medical center were more likely than nonemployees to be aware of their recent Omicron variant infection (adjusted odds ratio, 2.46; 95% CI, 1.30-4.65). Conclusions and Relevance: Results of this study suggest that more than half of adults with recent Omicron variant infection were unaware of their infectious status and that awareness was higher among health care employees than nonemployees, yet still low overall. Unawareness may be a highly prevalent factor associated with rapid person-to-person transmission within communities.

Design of Intelligent Management Platform for Industry–Education Cooperation of Vocational Education by Data Mining

Data are playing an increasingly important role in the development of industry–education cooperation strategies in vocational education and training. The objective of this study was to promote the comprehensive progress of an industry–education cooperation system and improve the effect of the application of big data technology in this system. First, we designed of a big data technology application in an intelligent management platform system for industry–education cooperation. Second, we analyzed the synthetical design of the system. Finally, we optimized and designed a support vector machine (SVM) data mining (DM) algorithm model based on big data, and evaluated the model. The results revealed that the designed algorithm model provides outstanding advantages compared with similar algorithm models. In general, the highest average computation time of the designed SVM algorithm model is about 95 ms. The overall average calculation time linearly decreases around 200 iterations and tends to be stable, and the lowest overall average computation time is about 20 ms. In the DM process, the highest accuracy rate of the model is about 97%, and the lowest is about 92%. The DM accuracy rate is always stable as the number of iterations of the model continues to increase. The designed model slowly increases the occupancy rate of the system in the process of increasing computing time. At about 60 min, the system occupancy rate of the model tends to be stable, and the highest is maintained at about 23%. This study not only provides technical support for the optimization of DM algorithms with big data technology, but also contributes to the integrated development of industry–education cooperation systems.

Droplet size distribution, atomization mechanism and dynamics of dental aerosols.

Since the outbreak of COVID-19 pandemic, maintaining safety in dental operations has challenged health care providers and policy makers. Studies on dental aerosols often focus on bacterial viability or particle size measurements inside dental offices during and after dental procedures, which limits their conclusions to specific cases. Fundamental understanding on atomization mechanism and dynamics of dental aerosols are needed while assessing the risks. Most dental instruments feature a build-in atomizer. Dental aerosols that are produced by ultrasonic or rotary atomization are considered to pose the highest risks. In this work, we aimed to characterize dental aerosols produced by both methods, namely by Mectron PIEZOSURGERY® and KaVo EXPERTtorque™. Droplet size distributions and velocities were measured with a high-speed camera and a rail system. By fitting the data to probability density distributions and using empirical equations to predict droplet sizes, we were able to postulate the main factors that determine droplet sizes. Both dental instruments had wide size distributions including small droplets. Droplet size distribution changed based on operational parameters such as liquid flow rate or air pressure. With a larger fraction of small droplets, rotary atomization poses a higher risk. With the measured velocities reaching up to 5 m s-1, droplets can easily reach the dentist in a few seconds. Small droplets can evaporate completely before reaching the ground and can be suspended in the air for a long time. We suggest that relative humidity in dental offices are adjusted to 50% to prevent fast evaporation while maintaining comfort in the office. This can reduce the risk of disease transmission among patients. We recommend that dentists wear a face shield and N95/FFP2/KN95 masks instead of surgical masks. We believe that this work gives health-care professionals, policy makers and engineers who design dental instruments insights into a safer dental practice.

Employment Management Policies for College Graduates under COVID-19 in China: Diffusion Characteristics and Core Issues.

The outbreak of COVID-19 epidemic has been having a great impact on the job market, so that graduates from all over the world are facing a more complex employment environment. Unemployment of the educated labor force often results in a waste of human capital and leads to serious economic and social problems. In the face of the impact of COVID-19, the Chinese government quickly introduced a series of employment policies for college graduates to relieve their employment pressure and create opportunities of career development. How did these employment policies for college graduates spread rapidly under the unconventional state of the COVID-19 epidemic? What are the diffusion characteristics? What are the core issues and measures? What are the differences between governments at all levels? These problems with rich connotation and research value needed to be further clarified. Based on the 72 employment support policies collected from the Chinese government network, this paper conducted a text analysis of the policies and found that in the process dimension, the employment policies of college graduates accumulated and exploded from bottom to top in the short term, and the policies diffusion followed the gradual model of "east-middle-west". In the content dimension, there were five core issues: financial subsidies, innovation and entrepreneurship to drive employment, public institutions to absorb, optimizing public services, and lowering the support threshold. Meanwhile, there were obvious differences in the choice of policy tools, policy intensity, and implementation ideas in each region. The findings are of important significance for developed and developing countries to better respond to the impact of various emergency situations.

mRNA-based therapeutics: powerful and versatile tools to combat diseases.

The therapeutic use of messenger RNA (mRNA) has fueled great hope to combat a wide range of incurable diseases. Recent rapid advances in biotechnology and molecular medicine have enabled the production of almost any functional protein/peptide in the human body by introducing mRNA as a vaccine or therapeutic agent. This represents a rising precision medicine field with great promise for preventing and treating many intractable or genetic diseases. In addition, in vitro transcribed mRNA has achieved programmed production, which is more effective, faster in design and production, as well as more flexible and cost-effective than conventional approaches that may offer. Based on these extraordinary advantages, mRNA vaccines have the characteristics of the swiftest response to large-scale outbreaks of infectious diseases, such as the currently devastating pandemic COVID-19. It has always been the scientists' desire to improve the stability, immunogenicity, translation efficiency, and delivery system to achieve efficient and safe delivery of mRNA. Excitingly, these scientific dreams have gradually been realized with the rapid, amazing achievements of molecular biology, RNA technology, vaccinology, and nanotechnology. In this review, we comprehensively describe mRNA-based therapeutics, including their principles, manufacture, application, effects, and shortcomings. We also highlight the importance of mRNA optimization and delivery systems in successful mRNA therapeutics and discuss the key challenges and opportunities in developing these tools into powerful and versatile tools to combat many genetic, infectious, cancer, and other refractory diseases.

Pseudomonas aeruginosa: pathogenesis, virulence factors, antibiotic resistance, interaction with host, technology advances and emerging therapeutics.

Pseudomonas aeruginosa (P. aeruginosa) is a Gram-negative opportunistic pathogen that infects patients with cystic fibrosis, burn wounds, immunodeficiency, chronic obstructive pulmonary disorder (COPD), cancer, and severe infection requiring ventilation, such as COVID-19. P. aeruginosa is also a widely-used model bacterium for all biological areas. In addition to continued, intense efforts in understanding bacterial pathogenesis of P. aeruginosa including virulence factors (LPS, quorum sensing, two-component systems, 6 type secretion systems, outer membrane vesicles (OMVs), CRISPR-Cas and their regulation), rapid progress has been made in further studying host-pathogen interaction, particularly host immune networks involving autophagy, inflammasome, non-coding RNAs, cGAS, etc. Furthermore, numerous technologic advances, such as bioinformatics, metabolomics, scRNA-seq, nanoparticles, drug screening, and phage therapy, have been used to improve our understanding of P. aeruginosa pathogenesis and host defense. Nevertheless, much remains to be uncovered about interactions between P. aeruginosa and host immune responses, including mechanisms of drug resistance by known or unannotated bacterial virulence factors as well as mammalian cell signaling pathways. The widespread use of antibiotics and the slow development of effective antimicrobials present daunting challenges and necessitate new theoretical and practical platforms to screen and develop mechanism-tested novel drugs to treat intractable infections, especially those caused by multi-drug resistance strains. Benefited from has advancing in research tools and technology, dissecting this pathogen's feature has entered into molecular and mechanistic details as well as dynamic and holistic views. Herein, we comprehensively review the progress and discuss the current status of P. aeruginosa biophysical traits, behaviors, virulence factors, invasive regulators, and host defense patterns against its infection, which point out new directions for future investigation and add to the design of novel and/or alternative therapeutics to combat this clinically significant pathogen.

Demographic and clinical characteristics associated with variations in antibody response to BNT162b2 COVID-19 vaccination among healthcare workers at an academic medical centre: a longitudinal cohort analysis.

OBJECTIVES: We sought to understand the demographic and clinical factors associated with variations in longitudinal antibody response following completion of two-dose regiment of BNT162b2 vaccination. DESIGN: This study is a 10-month longitudinal cohort study of healthcare workers and serially measured anti-spike protein IgG (IgG-S) antibody levels using mixed linear models to examine their associations with participant characteristics. SETTING: A large, multisite academic medical centre in Southern California, USA. PARTICIPANTS: A total of 843 healthcare workers met inclusion criteria including completion of an initial two-dose course of BNT162b2 vaccination, complete clinical history and at least two blood samples for analysis. Patients had an average age of 45±13 years, were 70% female and 7% with prior SARS-CoV-2 infection. RESULTS: Vaccine-induced IgG-S levels remained in the positive range for 99.6% of individuals up to 10 months after initial two-dose vaccination. Prior SARS-CoV-2 infection was the primary correlate of sustained higher postvaccination IgG-S levels (partial R2=0.133), with a 1.74±0.11 SD higher IgG-S response (p<0.001). Female sex (beta 0.27±0.06, p<0.001), younger age (0.01±0.00, p<0.001) and absence of hypertension (0.17±0.08, p=0.003) were also associated with persistently higher IgG-S responses. Notably, prior SARS-CoV-2 infection augmented the associations of sex (-0.42 for male sex, p=0.08) and modified the associations of hypertension (1.17, p=0.001), such that infection-naïve individuals with hypertension had persistently lower IgG-S levels whereas prior infected individuals with hypertension exhibited higher IgG-S levels that remained augmented over time. CONCLUSIONS: While the IgG-S antibody response remains in the positive range for up to 10 months following initial mRNA vaccination in most adults, determinants of sustained higher antibody levels include prior SARS-CoV-2 infection, female sex, younger age and absence of hypertension. Certain determinants of the longitudinal antibody response appear significantly modified by prior infection status. These findings offer insights regarding factors that may influence the 'hybrid' immunity conferred by natural infection combined with vaccination.

Employment Management Policies for College Graduates under COVID-19 in China: Diffusion Characteristics and Core Issues

The outbreak of COVID-19 epidemic has been having a great impact on the job market, so that graduates from all over the world are facing a more complex employment environment. Unemployment of the educated labor force often results in a waste of human capital and leads to serious economic and social problems. In the face of the impact of COVID-19, the Chinese government quickly introduced a series of employment policies for college graduates to relieve their employment pressure and create opportunities of career development. How did these employment policies for college graduates spread rapidly under the unconventional state of the COVID-19 epidemic? What are the diffusion characteristics? What are the core issues and measures? What are the differences between governments at all levels? These problems with rich connotation and research value needed to be further clarified. Based on the 72 employment support policies collected from the Chinese government network, this paper conducted a text analysis of the policies and found that in the process dimension, the employment policies of college graduates accumulated and exploded from bottom to top in the short term, and the policies diffusion followed the gradual model of 'east–middle–west';. In the content dimension, there were five core issues: financial subsidies, innovation and entrepreneurship to drive employment, public institutions to absorb, optimizing public services, and lowering the support threshold. Meanwhile, there were obvious differences in the choice of policy tools, policy intensity, and implementation ideas in each region. The findings are of important significance for developed and developing countries to better respond to the impact of various emergency situations.

Antiviral Effects of ABMA and DABMA against Influenza Virus In Vitro and In Vivo via Regulating the Endolysosomal Pathway and Autophagy

Influenza virus is an acute and highly contagious respiratory pathogen that causes great concern to public health and for which there is a need for extensive drug discovery. The small chemical compound ABMA and its analog DABMA, containing an adamantane or a dimethyl-adamantane group, respectively, have been demonstrated to inhibit multiple toxins (diphtheria toxin, Clostridium difficile toxin B, Clostridium sordellii lethal toxin) and viruses (Ebola, rabies virus, HSV-2) by acting on the host’s vesicle trafficking. Here, we showed that ABMA and DABMA have antiviral effects against both amantadine-sensitive influenza virus subtypes (H1N1 and H3N2), amantadine-resistant subtypes (H3N2), and influenza B virus with EC50 values ranging from 2.83 to 7.36 µM (ABMA) and 1.82 to 6.73 µM (DABMA), respectively. ABMA and DABMA inhibited the replication of influenza virus genomic RNA and protein synthesis by interfering with the entry stage of the virus. Molecular docking evaluation together with activity against amantadine-resistant influenza virus strains suggested that ABMA and DABMA were not acting as M2 ion channel blockers. Subsequently, we found that early internalized H1N1 virions were retained in accumulated late endosome compartments after ABMA treatment. Additionally, ABMA disrupted the early stages of the H1N1 life cycle or viral RNA synthesis by interfering with autophagy. ABMA and DABMA protected mice from an intranasal H1N1 challenge with an improved survival rate of 67%. The present study suggests that ABMA and DABMA are potential antiviral leads for the development of a host-directed treatment against influenza virus infection.