Gravitational change-induced alteration of the vestibular function and gene expression in the vestibular ganglion of mice.

Gravity has profoundly influenced life on Earth, yet how organisms adapt to changes in gravity remains largely unknown. This study examines vestibular plasticity, specifically how the vestibular system responds to altered gravity. We subjected male C57BL/6J mice to hypergravity (2 G) followed by normal gravity (1 G) to analyze changes in vestibular function and gene expression. Mice showed significant vestibular dysfunction, assessed by righting reflex tests, which persisted for days but reversed at 1 G after exposure to 2 G. Gene expression analysis in the vestibular ganglion identified significant changes in 212 genes out of 49,585 due to gravitational changes. Specifically, 25 genes were upregulated under 2 G and recovered at 1 G after 2 G exposure, while one gene showed the opposite trend. Key neural function genes like Shisa3, Slc25a37, Ntn4, and Snca were involved. Our results reveal that hypergravity-induced vestibular dysfunction is reversible and highlight genes critical for adaptation.

Modelling the effectiveness of an isolation strategy for managing mpox outbreaks with variable infectiousness profiles.

The global outbreak of mpox in 2022 and subsequent sporadic outbreaks in 2023 highlighted the importance of nonpharmaceutical interventions such as case isolation. Individual variations in viral shedding dynamics may lead to either premature ending of isolation for infectious individuals, or unnecessarily prolonged isolation for those who are no longer infectious. Here, we developed a modeling framework to characterize heterogeneous mpox infectiousness profiles - specifically, when infected individuals cease to be infectious - based on viral load data. We examined the potential effectiveness of three different isolation rules: a symptom-based rule (the current guideline in many countries) and rules permitting individuals to stop isolating after either a fixed duration or following tests that indicate that they are no longer likely to be infectious. Our analysis suggests that the duration of viral shedding ranges from 23 to 50 days between individuals. The risk of infected individuals ending isolation too early was estimated to be 8.8% (95% CI: 6.7-10.5) after symptom clearance and 5.4% (95% CI: 4.1-6.7) after 3 weeks of isolation. While these results suggest that the current standard practice for ending isolation is effective, we found that unnecessary isolation following the infectious period could be reduced by adopting a testing-based rule.

Corrigendum: Direct evidence of abortive lytic infection-mediated establishment of Epstein-Barr virus latency during B-cell infection.

[This corrects the article DOI: 10.3389/fmicb.2020.575255.].

Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population.

As we learned during the COVID-19 pandemic, vaccines are one of the most important tools in infectious disease control. To date, an unprecedentedly large volume of high-quality data on COVID-19 vaccinations have been accumulated. For preparedness in future pandemics beyond COVID-19, these valuable datasets should be analyzed to best shape an effective vaccination strategy. We are collecting longitudinal data from a community-based cohort in Fukushima, Japan, that consists of 2,407 individuals who underwent serum sampling two or three times after a two-dose vaccination with either BNT162b2 or mRNA-1273. Using the individually reconstructed time courses of the vaccine-elicited antibody response based on mathematical modeling, we first identified basic demographic and health information that contributed to the main features of the antibody dynamics, i.e., the peak, the duration, and the area under the curve. We showed that these three features of antibody dynamics were partially explained by underlying medical conditions, adverse reactions to vaccinations, and medications, consistent with the findings of previous studies. We then applied to these factors a recently proposed computational method to optimally fit an "antibody score", which resulted in an integer-based score that can be used as a basis for identifying individuals with higher or lower antibody titers from basic demographic and health information. The score can be easily calculated by individuals themselves or by medical practitioners. Although the sensitivity of this score is currently not very high, in the future, as more data become available, it has the potential to identify vulnerable populations and encourage them to get booster vaccinations. Our mathematical model can be extended to any kind of vaccination and therefore can form a basis for policy decisions regarding the distribution of booster vaccines to strengthen immunity in future pandemics.

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers.

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

Age-related changes in the hematopoietic stem cell pool revealed via quantifying the balance of symmetric and asymmetric divisions.

Hematopoietic stem cells (HSCs) are somatic stem cells that continuously generate lifelong supply of blood cells through a balance of symmetric and asymmetric divisions. It is well established that the HSC pool increases with age. However, not much is known about the underlying cause for these observed changes. Here, using a novel method combining single-cell ex vivo HSC expansion with mathematical modeling, we quantify HSC division types (stem cell-stem cell (S-S) division, stem cell-progenitor cell (S-P) division, and progenitor cell-progenitor cell (P-P) division) as a function of the aging process. Our time-series experiments reveal how changes in these three modes of division can explain the increase in HSC numbers with age. Contrary to the popular notion that HSCs divide predominantly through S-P divisions, we show that S-S divisions are predominant throughout the lifespan of the animal, thereby expanding the HSC pool. We, therefore, provide a novel mathematical model-based experimental validation for reflecting HSC dynamics in vivo.

Two-step evolution of HIV-1 budding system leading to pandemic in the human population.

The pandemic HIV-1, HIV-1 group M, emerged from a single spillover event of its ancestral lentivirus from a chimpanzee. During human-to-human spread worldwide, HIV-1 diversified into multiple subtypes. Here, our interdisciplinary investigation mainly sheds light on the evolutionary scenario of the viral budding system of HIV-1 subtype C (HIV-1C), a most successfully spread subtype. Of the two amino acid motifs for HIV-1 budding, the P(T/S)AP and YPxL motifs, HIV-1C loses the YPxL motif. Our data imply that HIV-1C might lose this motif to evade immune pressure. Additionally, the P(T/S)AP motif is duplicated dependently of the level of HIV-1 spread in the human population, and >20% of HIV-1C harbored the duplicated P(T/S)AP motif. We further show that the duplication of the P(T/S)AP motif is caused by the expansion of the CTG triplet repeat. Altogether, our results suggest that HIV-1 has experienced a two-step evolution of the viral budding process during human-to-human spread worldwide.

Anti-HTLV-1 immunity combined with proviral load as predictive biomarkers for adult T-cell leukemia-lymphoma.

Human T-cell leukemia virus type 1 (HTLV-1) establishes chronic infection in humans and induces a T-cell malignancy called adult T-cell leukemia-lymphoma (ATL) and several inflammatory diseases such as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Persistent HTLV-1 infection is established under the pressure of host immunity, and therefore the immune response against HTLV-1 is thought to reflect the status of the disease it causes. Indeed, it is known that cellular immunity against viral antigens is suppressed in ATL patients compared to HAM/TSP patients. In this study, we show that profiling the humoral immunity to several HTLV-1 antigens, such as Gag, Env, and Tax, and measuring proviral load are useful tools for classifying disease status and predicting disease development. Using targeted sequencing, we found that several carriers whom this profiling method predicted to be at high risk for developing ATL indeed harbored driver mutations of ATL. The clonality of HTLV-1-infected cells in those carriers was still polyclonal; it is consistent with an early stage of leukemogenesis. Furthermore, this study revealed significance of anti-Gag proteins to predict high risk group in HTLV-1 carriers. Consistent with this finding, anti-Gag cytotoxic T lymphocytes (CTLs) were increased in patients who received hematopoietic stem cell transplantation and achieved remission state, indicating the significance of anti-Gag CTLs for disease control. Our findings suggest that our strategy that combines anti-HTLV-1 antibodies and proviral load may be useful for prediction of the development of HTLV-1-associated diseases.

Resistance exercise in combination with aerobic exercise reduces the incidence of serious events in patients with liver cirrhosis: a meta-analysis of randomized controlled trials.

BACKGROUND: Exercise, particularly resistance exercise, is beneficial for sarcopenia in patients with liver cirrhosis. However, the effects of exercise on events remain unclear. We aimed to examine the effects of exercise on serious events in patients with liver cirrhosis using a meta-analysis of randomized controlled trials (RCTs). METHODS: A literature search was conducted in 2022. Eleven RCTs were selected for the meta-analysis (exercise group, n = 232; control group, n = 193). Serious events were defined as death or serious complications according to the original articles. A meta-analysis was performed using a random-effects model. The primary outcome was the incidence of serious events. RESULTS: In the 11 RCTs, the incidence of serious events was 5.6% (13/232) and 12.3% (24/193) in the exercise and control groups, respectively. However, a meta-analysis demonstrated no significant difference in the incidence of serious events between the two groups (risk difference [RD] - 0.03, 95% confidence intervals (CI) - 0.07 to 0.02). In a stratification analysis based on a combination of aerobic and resistance exercise, five RCTs (n = 185) were enrolled. The incidence of serious events was 6.25% (7/112) and 24.7% (18/73) in the combination exercise and control groups, respectively. A meta-analysis demonstrated a significant reduction in the incidence of serious events in the combination exercise group compared with the control group (RD - 0.12; 95% CI - 0.21 to - 0.03). CONCLUSIONS: Resistance exercise in combination with aerobic exercise reduces serious events in patients with liver cirrhosis. A combination of aerobic and resistance exercise may be beneficial to improve the prognosis of patients with liver cirrhosis.

Infectious virus shedding duration reflects secretory IgA antibody response latency after SARS-CoV-2 infection.

Infectious virus shedding from individuals infected with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is used to estimate human-to-human transmission risk. Control of SARS-CoV-2 transmission requires identifying the immune correlates that protect infectious virus shedding. Mucosal immunity prevents infection by SARS-CoV-2, which replicates in the respiratory epithelium and spreads rapidly to other hosts. However, whether mucosal immunity prevents the shedding of the infectious virus in SARS-CoV-2-infected individuals is unknown. We examined the relationship between viral RNA shedding dynamics, duration of infectious virus shedding, and mucosal antibody responses during SARS-CoV-2 infection. Anti-spike secretory IgA antibodies (S-IgA) reduced viral RNA load and infectivity more than anti-spike IgG/IgA antibodies in infected nasopharyngeal samples. Compared with the IgG/IgA response, the anti-spike S-IgA post-infection responses affected the viral RNA shedding dynamics and predicted the duration of infectious virus shedding regardless of the immune history. These findings highlight the importance of anti-spike S-IgA responses in individuals infected with SARS-CoV-2 for preventing infectious virus shedding and SARS-CoV-2 transmission. Developing medical countermeasures to shorten S-IgA response time may help control human-to-human transmission of SARS-CoV-2 infection and prevent future respiratory virus pandemics.

Antibody Profiling of Microbial Antigens in the Blood of COVID-19 mRNA Vaccine Recipients Using Microbial Protein Microarrays.

Although studies have demonstrated that infections with various viruses, bacteria, and parasites can modulate the immune system, no study has investigated changes in antibodies against microbial antigens after the COVID-19 mRNA vaccination. IgG antibodies against microbial antigens in the blood of vaccinees were comprehensively analyzed using microbial protein microarrays that carried approximately 5000 microbe-derived proteins. Changes in antibodies against microbial antigens were scrutinized in healthy participants enrolled in the Fukushima Vaccination Community Survey conducted in Fukushima Prefecture, Japan, after their second and third COVID-19 mRNA vaccinations. Antibody profiling of six groups stratified by antibody titer and the remaining neutralizing antibodies was also performed to study the dynamics of neutralizing antibodies against SARS-CoV-2 and the changes in antibodies against microbial antigens. The results showed that changes in antibodies against microbial antigens other than SARS-CoV-2 antigens were extremely limited after COVID-19 vaccination. In addition, antibodies against a staphylococcal complement inhibitor have been identified as microbial antigens that are associated with increased levels of neutralizing antibodies against SARS-CoV-2. These antibodies may be a predictor of the maintenance of neutralizing antibodies following the administration of a COVID-19 mRNA vaccine.

Modeling COVID-19 vaccine booster-elicited antibody response and impact of infection history.

The 3-dose COVID-19 vaccine (booster vaccination) has been offered worldwide. As booster vaccinations continue, it is important to understand the antibody dynamics elicited by booster vaccination in order to evaluate and develop vaccination needs and strategies. Here, we investigated longitudinal data by monitoring IgG antibodies against the receptor binding domain (RBD) in health care workers. We extended our previously developed mathematical model to booster vaccines and successfully fitted antibody titers over time in the absence and presence of past SARS-CoV-2 infection. Quantitative analysis using our mathematical model indicated that anti-RBD IgG titers increase to a comparable extent after booster vaccination, regardless of the presence or absence of infection, but infection history extends the duration of antibody response by 1.28 times. Such a mathematical modeling approach can be used to inform future vaccination strategies on the basis of an individual's immune history. Our simple quantitative approach can be extended to any kind of vaccination and therefore can form a basis for policy decisions regarding the distribution of booster vaccines to strengthen immunity in future pandemics.

Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution.

During the COVID-19 pandemic, human behavior change as a result of nonpharmaceutical interventions such as isolation may have induced directional selection for viral evolution. By combining previously published empirical clinical data analysis and multi-level mathematical modeling, we find that the SARS-CoV-2 variants selected for as the virus evolved from the pre-Alpha to the Delta variant had earlier and higher peak in viral load dynamics but a shorter duration of infection. Selection for increased transmissibility shapes the viral load dynamics, and the isolation measure is likely to be a driver of these evolutionary transitions. In addition, we show that a decreased incubation period and an increased proportion of asymptomatic infection are also positively selected for as SARS-CoV-2 mutated to adapt to human behavior (i.e., Omicron variants). The quantitative information and predictions we present here can guide future responses in the potential arms race between pandemic interventions and viral evolution.

Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study.

In the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a single case introduced into the population), accounting for within-host viral dynamics. Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how the risk can be mitigated through pre-emptive interventions such as antigen testing. Considering SARS-CoV-2 as a case study, we quantify the within-host dynamics using data from individuals with omicron variant infections. We demonstrate that regular antigen testing reduces, but may not eliminate, the outbreak risk, depending on characteristics of local transmission. In our baseline analysis, daily antigen testing reduces the outbreak risk by 45% compared to a scenario without antigen testing. Additionally, we show that accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the impact of antigen testing. Our results therefore highlight important factors to consider when using multiscale models to design pre-emptive interventions against SARS-CoV-2 and other viruses.

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers.

Chronic infection of hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The non-invasive quantification of cccDNA using our proposed methodology holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

A Multicenter Randomized Controlled Trial To Evaluate the Efficacy and Safety of Nelfinavir in Patients with Mild COVID-19.

Nelfinavir, an orally administered inhibitor of human immunodeficiency virus protease, inhibits the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. We conducted a randomized controlled trial to evaluate the clinical efficacy and safety of nelfinavir in patients with SARS-CoV-2 infection. We included unvaccinated asymptomatic or mildly symptomatic adult patients who tested positive for SARS-CoV-2 infection within 3 days before enrollment. The patients were randomly assigned (1:1) to receive oral nelfinavir (750 mg; thrice daily for 14 days) combined with standard-of-care or standard-of-care alone. The primary endpoint was the time to viral clearance, confirmed using quantitative reverse-transcription PCR by assessors blinded to the assigned treatment. A total of 123 patients (63 in the nelfinavir group and 60 in the control group) were included. The median time to viral clearance was 8.0 (95% confidence interval [CI], 7.0 to 12.0) days in the nelfinavir group and 8.0 (95% CI, 7.0 to 10.0) days in the control group, with no significant difference between the treatment groups (hazard ratio, 0.815; 95% CI, 0.563 to 1.182; P = 0.1870). Adverse events were reported in 47 (74.6%) and 20 (33.3%) patients in the nelfinavir and control groups, respectively. The most common adverse event in the nelfinavir group was diarrhea (49.2%). Nelfinavir did not reduce the time to viral clearance in this setting. Our findings indicate that nelfinavir should not be recommended in asymptomatic or mildly symptomatic patients infected with SARS-CoV-2. The study is registered with the Japan Registry of Clinical Trials (jRCT2071200023). IMPORTANCE The anti-HIV drug nelfinavir suppresses the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. However, its efficacy in patients with COVID-19 has not been studied. We conducted a multicenter, randomized controlled trial to evaluate the efficacy and safety of orally administered nelfinavir in patients with asymptomatic or mildly symptomatic COVID-19. Compared to standard-of-care alone, nelfinavir (750 mg, thrice daily) did not reduce the time to viral clearance, viral load, or the time to resolution of symptoms. More patients had adverse events in the nelfinavir group than in the control group (74.6% [47/63 patients] versus 33.3% [20/60 patients]). Our clinical study provides evidence that nelfinavir, despite its antiviral effects on SARS-CoV-2 in vitro, should not be recommended for the treatment of patients with COVID-19 having no or mild symptoms.

Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection.

Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.

Potential Anti-Mpox Virus Activity of Atovaquone, Mefloquine, and Molnupiravir, and Their Potential Use as Treatments.

BACKGROUND: Mpox virus (MPXV) is a zoonotic orthopoxvirus and caused an outbreak in 2022. Although tecovirimat and brincidofovir are approved as anti-smallpox drugs, their effects in mpox patients have not been well documented. In this study, by a drug repurposing approach, we identified potential drug candidates for treating mpox and predicted their clinical impacts by mathematical modeling. METHODS: We screened 132 approved drugs using an MPXV infection cell system. We quantified antiviral activities of potential drug candidates by measuring intracellular viral DNA and analyzed the modes of action by time-of-addition assay and electron microscopic analysis. We further predicted the efficacy of drugs under clinical concentrations by mathematical simulation and examined combination treatment. RESULTS: Atovaquone, mefloquine, and molnupiravir exhibited anti-MPXV activity, with 50% inhibitory concentrations of 0.51-5.2 µM, which was more potent than cidofovir. Whereas mefloquine was suggested to inhibit viral entry, atovaquone and molnupiravir targeted postentry processes. Atovaquone was suggested to exert its activity through inhibiting dihydroorotate dehydrogenase. Combining atovaquone with tecovirimat enhanced the anti-MPXV effect of tecovirimat. Quantitative mathematical simulations predicted that atovaquone can promote viral clearance in patients by 7 days at clinically relevant drug concentrations. CONCLUSIONS: These data suggest that atovaquone would be a potential candidate for treating mpox.

Increased flexibility of the SARS-CoV-2 RNA-binding site causes resistance to remdesivir.

Mutations continue to accumulate within the SARS-CoV-2 genome, and the ongoing epidemic has shown no signs of ending. It is critical to predict problematic mutations that may arise in clinical environments and assess their properties in advance to quickly implement countermeasures against future variant infections. In this study, we identified mutations resistant to remdesivir, which is widely administered to SARS-CoV-2-infected patients, and discuss the cause of resistance. First, we simultaneously constructed eight recombinant viruses carrying the mutations detected in in vitro serial passages of SARS-CoV-2 in the presence of remdesivir. We confirmed that all the mutant viruses didn't gain the virus production efficiency without remdesivir treatment. Time course analyses of cellular virus infections showed significantly higher infectious titers and infection rates in mutant viruses than wild type virus under treatment with remdesivir. Next, we developed a mathematical model in consideration of the changing dynamic of cells infected with mutant viruses with distinct propagation properties and defined that mutations detected in in vitro passages canceled the antiviral activities of remdesivir without raising virus production capacity. Finally, molecular dynamics simulations of the NSP12 protein of SARS-CoV-2 revealed that the molecular vibration around the RNA-binding site was increased by the introduction of mutations on NSP12. Taken together, we identified multiple mutations that affected the flexibility of the RNA binding site and decreased the antiviral activity of remdesivir. Our new insights will contribute to developing further antiviral measures against SARS-CoV-2 infection.

Smoking enhances the expression of angiotensin-converting enzyme 2 involved in the efficiency of severe acute respiratory syndrome coronavirus 2 infection.

Smoking is one of the risk factors most closely related to the severity of coronavirus disease 2019 (COVID-19). However, the relationship between smoking history and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is unknown. In this study, we evaluated the ACE2 expression level in the lungs of current smokers, ex-smokers, and nonsmokers. The ACE2 expression level of ex-smokers who smoked cigarettes until recently (cessation period shorter than 6 months) was higher than that of nonsmokers and ex-smokers with a long history of nonsmoking (cessation period longer than 6 months). We also showed that the efficiency of SARS-CoV-2 infection was enhanced in a manner dependent on the angiotensin-converting enzyme 2 (ACE2) expression level. Using RNA-seq analysis on the lungs of smokers, we identified that the expression of inflammatory signaling genes was correlated with ACE2 expression. Notably, with increasing duration of smoking cessation among ex-smokers, not only ACE2 expression level but also the expression levels of inflammatory signaling genes decreased. These results indicated that smoking enhances the expression levels of ACE2 and inflammatory signaling genes. Our data suggest that the efficiency of SARS-CoV-2 infection is enhanced by smoking-mediated upregulation of ACE2 expression level.