CD19 CAR-expressing iPSC-derived NK cells effectively enhance migration and cytotoxicity into glioblastoma by targeting to the pericytes in tumor microenvironment.

In cancer immunotherapy, chimeric antigen receptors (CARs) targeting specific antigens have become a powerful tool for cell-based therapy. CAR-natural killer (NK) cells offer selective anticancer lysis with reduced off-tumor toxicity compared to CAR-T cells, which is beneficial in the heterogeneous milieu of solid tumors. In the tumor microenvironment (TME) of glioblastoma (GBM), pericytes not only support tumor growth but also contribute to immune evasion, underscoring their potential as therapeutic targets in GBM treatment. Given this context, our study aimed to target the GBM TME, with a special focus on pericytes expressing CD19, to evaluate the potential effectiveness of CD19 CAR-iNK cells against GBM. We performed CD19 CAR transduction in induced pluripotent stem cell-derived NK (iNK) cells. To determine whether CD19 CAR targets the TME pericytes in GBM, we developed GBM-blood vessel assembloids (GBVA) by fusing GBM spheroids with blood vessel organoids. When co-cultured with GBVA, CD19 CAR-iNK cells migrated towards the pericytes surrounding the GBM. Using a microfluidic chip, we demonstrated CD19 CAR-iNK cells' targeted action and cytotoxic effects in a perfusion-like environment. GBVA xenografts recapitulated the TME including human CD19-positive pericytes, thereby enabling the application of an in vivo model for validating the efficacy of CD19 CAR-iNK cells against GBM. Compared to GBM spheroids, the presence of pericytes significantly enhanced CD19 CAR-iNK cell migration towards GBM and reduced proliferation. These results underline the efficacy of CD19 CAR-iNK cells in targeting pericytes within the GBM TME, suggesting their potential therapeutic value for GBM treatment.

Spectral Graph Neural Network-based Multi-atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.

Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Magnetic Resonance Imaging (fMRI) has emerged as a promising tool for the objective diagnosis of MDD, enabling the investigation of functional connectivity patterns in the brain associated with this disorder. However, most existing methods focus on a single brain atlas, which limits their ability to capture the complex, multi-scale nature of functional brain networks. To address these limitations, we propose a novel multi-atlas fusion method that incorporates early and late fusion in a unified framework. Our method introduces the concept of the holistic Functional Connectivity Network (FCN), which captures both intra-atlas relationships within individual atlases and inter-regional relationships between atlases with different brain parcellation scales. This comprehensive representation enables the identification of potential disease-related patterns associated with MDD in the early stage of our framework. Moreover, by decoding the holistic FCN from various perspectives through multiple spectral Graph Convolutional Neural Networks and fusing their results with decision-level ensembles, we further improve the performance of MDD diagnosis. Our approach is easily implemented with minimal modifications to existing model structures and demonstrates a robust performance across different baseline models. Our method, evaluated on public resting-state fMRI datasets, surpasses the current multi-atlas fusion methods, enhancing the accuracy of MDD diagnosis. The proposed novel multi-atlas fusion framework provides a more reliable MDD diagnostic technique. Experimental results show our approach outperforms both single- and multi-atlas-based methods, demonstrating its effectiveness in advancing MDD diagnosis.

Identification of Micrococcin P2-Derivatives as Antibiotic Candidates against Two Gram-Positive Pathogens.

Thiopeptides exhibit potent antimicrobial activity against Gram-positive pathogens by inhibiting bacterial protein synthesis. Micrococcins are among the structurally simpler thiopeptides, but they have not been exploited in detail. This research involved a computational simulation of micrococcin P2 (MP2) docking in parallel with the structure-activity relationship (SAR) studied. The incorporation of particular nitrogen heterocycles in the side chain of MP2 enhances the antimicrobial activity. Micrococcin analogues 6c and 6d thus proved to be more effective against impetigo and C. difficile infection (CDI), respectively, as compared to current first-line treatments. Compound 6c also showed a shorter treatment period than that of a first-line treatment for impetigo. This may be attributed to its ability to downregulate pro-inflammatory cytokines. Compound 6d had no observed recurrence for C. difficile and exerted a minimal impact on the beneficial gut microbiome. Their pharmacokinetic properties and low toxicity profile make these compounds ideal candidates for the treatment of impetigo and CDI and validate their involvement in preclinical development.

Implementing Point-of-Care Ultrasound for Acute Scrotal Pain in the Pediatric Emergency Department: Screening Testicular Torsion and Patient Flow Analysis.

OBJECTIVES: Testicular torsion (TT) is a pediatric surgical emergency that requires prompt treatment. This study investigated the feasibility of point-of-care ultrasound (POCUS) for diagnosing TT in the pediatric emergency department (ED). METHODS: We retrospectively reviewed the medical records of patients, aged 18 years or younger, who visited a university-affiliated hospital pediatric ED with acute scrotal pain without trauma history and underwent diagnostic ultrasounds between January 2010 and October 2022. RESULTS: This study included 731 patients (median age: 9 years), Of these, 315 (43%) were in the POCUS-performed group: 188 in the POCUS-only group, and 127 in the POCUS-and-RADUS group. The other 416 patients (56.9%) were in the RADUS-only group. In total, 45 patients (6.2%) were diagnosed with TT (19 in the POCUS-performed group and 26 in the RADUS-only group). The sensitivity, specificity, and positive and negative predictive values of POCUS for diagnosing TT were 94.7%, 92.9%, 46.2%, and 99.6%, respectively. The median time to perform POCUS was shorter than RADUS (23 versus 61 minutes, P < .001). The POCUS-performed group had a shorter ED length of stay than the RADUS-only group (93 versus 170 minutes, P < .001). Among the patients diagnosed with TT, performing POCUS first did not significantly delay the ED process, including time to operation (250 versus 205 minutes, P = .142). CONCLUSIONS: For patients with acute scrotal pain, evaluation performed by pediatric emergency physicians using POCUS performs well in screening TT, and can decrease length of stay in the ED.

Monomer-mixed hole transport layers for improving hole injection of quantum dot light-emitting diodes.

Quantum-dot light-emitting diodes (QLEDs) are promising components for next-generation displays and related applications. However, their performance is critically limited by inherent hole-injection barrier caused by deep highest-occupied molecular orbital levels of quantum dots. Herein, we present an effective method for enhancing the performance of QLEDs by incorporating a monomer (TCTA or mCP) into hole-transport layers (HTL). The impact of different monomer concentrations on the characteristics of QLEDs were investigated. The results indicate that sufficient monomer concentrations improve the current efficiency and power efficiency. The increased hole current using monomer-mixed HTL suggests that our method holds considerable potential for high-performance QLEDs.

Difference in Sugar-Sweetened Beverage Consumption before and during the COVID-19 Pandemic among Korean Adolescents.

BACKGROUND: Previous studies have identified various factors associated with sugar-sweetened beverage (SSB) consumption among children and adolescents. Recent studies attempted to analyze changes in SSB consumption of adolescents during the COVID-19 pandemic and showed conflicting results. OBJECTIVES: This study aimed to estimate the difference in SSB consumption before (2018-2019) and during (2020-2021) the COVID-19 pandemic among Korean adolescents. METHODS: The study population consisted of students (n = 227,139) aged 12-18 y from the Korean Youth Risk Behavior Web-based Survey (KYRBWS). Data collection was done between 2018 and 2021. The primary outcome was the difference in the SSB consumption status (none/<7 times/wk, ≥7 times/wk) before and during the COVID-19 pandemic. Multinomial logistic regression was used to examine the association. Additional analysises were also conducted by gender, school grades, household income, grade point average, region, household members, fast-food intake, and fruit intake. RESULTS: The COVID-19 pandemic was associated with a decrease in adolescents' SSB intake. [(<7 times/wk) 2019: 59.4, 2020: 58.8, (≥7 times/wk) 2019: 35.3, 2020: 33.4]. CONCLUSIONS: The study found a difference in SSB consumption among Korean adolescents between before and during the COVID-19 pandemic. These findings are noteworthy considering the importance of continuous care in managing SSB intake.

Bridging the BCI illiteracy gap: a subject-to-subject semantic style transfer for EEG-based motor imagery classification.

Introduction: Brain-computer interfaces (BCIs) facilitate direct interaction between the human brain and computers, enabling individuals to control external devices through cognitive processes. Despite its potential, the problem of BCI illiteracy remains one of the major challenges due to inter-subject EEG variability, which hinders many users from effectively utilizing BCI systems. In this study, we propose a subject-to-subject semantic style transfer network (SSSTN) at the feature-level to address the BCI illiteracy problem in electroencephalogram (EEG)-based motor imagery (MI) classification tasks. Methods: Our approach uses the continuous wavelet transform method to convert high-dimensional EEG data into images as input data. The SSSTN 1) trains a classifier for each subject, 2) transfers the distribution of class discrimination styles from the source subject (the best-performing subject for the classifier, i.e., BCI expert) to each subject of the target domain (the remaining subjects except the source subject, specifically BCI illiterates) through the proposed style loss, and applies a modified content loss to preserve the class-relevant semantic information of the target domain, and 3) finally merges the classifier predictions of both source and target subject using an ensemble technique. Results and discussion: We evaluate the proposed method on the BCI Competition IV-2a and IV-2b datasets and demonstrate improved classification performance over existing methods, especially for BCI illiterate users. The ablation experiments and t-SNE visualizations further highlight the effectiveness of the proposed method in achieving meaningful feature-level semantic style transfer.

Quantitative analysis of therapeutic proteins in biological fluids: recent advancement in analytical techniques.

Pharmaceutical application of therapeutic proteins has been continuously expanded for the treatment of various diseases. Efficient and reliable bioanalytical methods are essential to expedite the identification and successful clinical development of therapeutic proteins. In particular, selective quantitative assays in a high-throughput format are critical for the pharmacokinetic and pharmacodynamic evaluation of protein drugs and to meet the regulatory requirements for new drug approval. However, the inherent complexity of proteins and many interfering substances presented in biological matrices have a great impact on the specificity, sensitivity, accuracy, and robustness of analytical assays, thereby hindering the quantification of proteins. To overcome these issues, various protein assays and sample preparation methods are currently available in a medium- or high-throughput format. While there is no standard or universal approach suitable for all circumstances, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay often becomes a method of choice for the identification and quantitative analysis of therapeutic proteins in complex biological samples, owing to its high sensitivity, specificity, and throughput. Accordingly, its application as an essential analytical tool is continuously expanded in pharmaceutical R&D processes. Proper sample preparation is also important since clean samples can minimize the interference from co-existing substances and improve the specificity and sensitivity of LC-MS/MS assays. A combination of different methods can be utilized to improve bioanalytical performance and ensure more accurate quantification. This review provides an overview of various protein assays and sample preparation methods, with particular emphasis on quantitative protein analysis by LC-MS/MS.

Bioengineered liver crosslinked with nano-graphene oxide enables efficient liver regeneration via MMP suppression and immunomodulation.

Decellularized extracellular matrix scaffold, widely utilized for organ engineering, often undergoes matrix decomposition after transplantation and produces byproducts that cause inflammation, leading to clinical failure. Here we propose a strategy using nano-graphene oxide to modify the biophysical properties of decellularized liver scaffolds. Notably, we demonstrate that scaffolds crosslinked with nano-graphene oxide show high resistance to enzymatic degradation via direct inhibition of matrix metalloproteinase activity and increased mechanical rigidity. We find that M2-like macrophage polarization is promoted within the crosslinked scaffolds, which reduces graft-elicited inflammation. Moreover, we show that low activities of matrix metalloproteinases, attributed to both nano-graphene oxide and tissue inhibitors of metalloproteinases expressed by M2c, can protect the crosslinked scaffolds against in vivo degradation. Lastly, we demonstrate that bioengineered livers fabricated with the crosslinked scaffolds remain functional, thereby effectively regenerating damaged livers after transplantation into liver failure mouse models. Overall, nano-graphene oxide crosslinking prolongs allograft survival and ultimately improves therapeutic effects of bioengineered livers, which offer an alternative for donor organs.

Cortical-blood vessel assembloids exhibit Alzheimer's disease phenotypes by activating glia after SARS-CoV-2 infection.

A correlation between COVID-19 and Alzheimer's disease (AD) has been proposed recently. Although the number of case reports on neuroinflammation in COVID-19 patients has increased, studies of SARS-CoV-2 neurotrophic pathology using brain organoids have restricted recapitulation of those phenotypes due to insufficiency of immune cells and absence of vasculature. Cerebral pericytes and endothelial cells, the major components of blood-brain barrier, express viral entry receptors for SARS-CoV-2 and response to systemic inflammation including direct cell death. To overcome the limitations, we developed cortical-blood vessel assembloids by fusing cortical organoid with blood vessel organoid to provide vasculature to brain organoids a nd obtained the characteristics of increased expression of microglia and astrocytes in brain organoids. Furthermore, we observed AD pathologies, including ß-amyloid plaques, which were affected by the inflammatory response from SARS-CoV-2 infection. These findings provide an advanced platform to investigate human neurotrophic diseases, including COVID-19, and suggest that neuroinflammation caused by viral infection facilitates AD pathology.

Did the increase in sitting time due to COVID-19 lead to obesity in adolescents?

INTRODUCTION: Since adolescent with obesity is closely linked with the incidence of cardiovascular disease, it is important to identify the factors that increase the prevalence of adolescent with obesity and prevent it early. This study aimed to examine which of the demographic and lifestyle factors including sitting hours per week for purposes other than study had the greatest influence on Korean adolescents with obesity during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We used the Korean Youth Risk Behavior Web-based Survey (KYRBWS) data. The primary outcome was the relationship between sitting hours and obesity during and after the COVID-19 pandemic. Multiple logistic regression analysis was performed to examine which of the demographic and lifestyle factors including sitting hours per week for purposes other than study had the greatest influence on Korean adolescents' obesity status. RESULTS: The prevalence of obesity was significantly higher during the COVID-19 than before the COVID-19 (OR, 1.268, CI:1.232-1.305). There was a significant increase in the OR for sitting hours per week for purposes other than study (OR, 1.021, 95% CI, 1.019-1.024). Compared to low household income, the OR decreased for middle (OR = 0.798, 95% CI:0.77, 0.826) and high-income household students (OR, 0.833, 95% CI: 0.803-0.865). DISCUSSION/CONCLUSION: The results of this study confirmed the relationship between sit-ting hours and obesity in adolescents during the pandemic. To prevent adolescent with obesity, further studies are needed to focus on the importance of promoting health policy in adolescents to avoid the continuous rising of its prevalence and needed to understand whether the increase in obesity rates during the pandemic is a temporary trend.

3D microengineered vascularized tumor spheroids for drug delivery and efficacy testing.

Tumor angiogenesis is regarded as a promising target for limiting cancer progression because tumor-associated vasculature supplies blood and provides a path for metastasis. Thus, in vitro recapitulation of vascularized tumors is critical to understand the pathology of cancer and identify the mechanisms by which tumor cells proliferate, metastasize, and respond to drugs. In this study, we microengineered a vascularized tumor spheroid (VTS) model to reproduce the pathological features of solid tumors. We first generated tumor-EC hybrid spheroids with self-assembled intratumoral vessels, which enhanced the uniformity of the spheroids and peritumoral angiogenic capacity compared to spheroids composed only with cancer cells. Notably, the hybrid spheroids also exhibited expression profiles associated with aggressive behavior. The blood vessels sprouting around the hybrid spheroids on the VTS chip displayed the distinctive characteristics of leaky tumor vessels. With the VTS chip showing a progressive tumor phenotype, we validated the suppressive effects of axitinib on tumor growth and angiogenesis, which depended on exposure dose and time, highlighting the significance of tumor vascularization to predict the efficacy of anticancer drugs. Ultimately, we effectively induced both lymphangiogenesis and angiogenesis around the tumor spheroid by promoting interstitial flow. Thus, our VTS model is a valuable platform with which to investigate the interactions between tumor microenvironments and explore therapeutic strategies in cancer. STATEMENT OF SIGNIFICANCE: We conducted an integrative study within a vascularized tumor spheroid (VTS) model. We first generated tumor-EC hybrid spheroids with self-assembled intratumoral vessels, which enhanced the uniformity of the spheroids and peritumoral angiogenic capacity compared to spheroids composed only with cancer cells. Through RNA sequencing, we elucidated that the tumor-EC hybrid spheroids exhibited expression profiles associated with aggressive behavior such as cancer progression, invasion and metastasis. The blood vessels sprouting around the hybrid spheroids on the VTS chip displayed the distinctive characteristics of leaky tumor vessels. We further validated the suppressive effects of axitinib on tumor growth and angiogenesis, depending on exposure dose and time. Ultimately, we effectively induced both lymphangiogenesis and angiogenesis around the tumor spheroid by promoting interstitial flow.

Dual-Scale Doppler Attention for Human Identification.

This paper considers a Deep Convolutional Neural Network (DCNN) with an attention mechanism referred to as Dual-Scale Doppler Attention (DSDA) for human identification given a micro-Doppler (MD) signature induced as input. The MD signature includes unique gait characteristics by different sized body parts moving, as arms and legs move rapidly, while the torso moves slowly. Each person is identified based on his/her unique gait characteristic in the MD signature. DSDA provides attention at different time-frequency resolutions to cater to different MD components composed of both fast-varying and steady. Through this, DSDA can capture the unique gait characteristic of each person used for human identification. We demonstrate the validity of DSDA on a recently published benchmark dataset, IDRad. The empirical results show that the proposed DSDA outperforms previous methods, using a qualitative analysis interpretability on MD signatures.

The rise and fall of industrial clusters: experience from the resilient transformation in South Korea.

Clusters facing a crisis could have devastating effects on the economic conditions of the regions. Therefore, it is important to study how resilience works in the lives of clusters. The purpose of the current study is to more quantitatively understand the life path of the growth and decline of industrial clusters by verifying actual patterns. Also, it is to explain why these patterns were formed by qualitatively analyzing the process of utilizing resilience. The main contribution to the field of the lifecycle of clusters would be proving the theoretical concepts with data of the entire official industrial clusters in South Korea for 2 decades. Although previous works have attempted to define life paths by classifying the groups, most of their cases only dealt with one or two cases, making it difficult to generalize to a theory that can explain all types of clusters. This research used South Korean data as representative data for classification by analyzing the 1375 industrial clusters for 20 years. The trend of their life paths was calculated using a classic time-series decomposition method, and dynamic time series warping was adopted to measure the similarity between the paths. The k-medoids method from an unsupervised machine learning technique was adopted to classify the data. They were classified into three types: Malmo-type, Silicon Valley-type, and Detroit-type. The same classification method can be applied to other countries. Through this classification, the necessary or weak determinants of resilience in their clusters can be found. By making up for these shortcomings, continuous growth can be achieved.

Severe acute respiratory syndrome coronavirus 2 variants-Possibility of universal vaccine design: A review.

Both novel and conventional vaccination strategies have been implemented worldwide since the onset of coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite various medical advances in the treatment and prevention of the spread of this contagious disease, it remains a major public health threat with a high mortality rate. As several lethal SARS-CoV-2 variants continue to emerge, the development of several vaccines and medicines, each with certain advantages and disadvantages, is underway. Additionally, many modalities are at various stages of research and development or clinical trials. Here, we summarize emerging SARS-CoV-2 variants, including delta, omicron, and "stealth omicron," as well as available oral drugs for COVID-19. We also discuss possible antigen candidates other than the receptor-binding domain protein for the development of a universal COVID-19 vaccine. The present review will serve as a helpful resource for future vaccine and drug development to combat COVID-19.

Functional ligands for improving anticancer drug therapy: current status and applications to drug delivery systems.

Conventional chemotherapy lacking target selectivity often leads to severe side effects, limiting the effectiveness of chemotherapy. Therefore, drug delivery systems ensuring both selective drug release and efficient intracellular uptake at the target sites are highly demanded in chemotherapy to improve the quality of life of patients with low toxicity. One of the effective approaches for tumor-selective drug delivery is the adoption of functional ligands that can interact with specific receptors overexpressed in malignant cancer cells. Various functional ligands including folic acid, hyaluronic acid, transferrin, peptides, and antibodies, have been extensively explored to develop tumor-selective drug delivery systems. Furthermore, cell-penetrating peptides or ligands for tight junction opening are also actively pursued to improve the intracellular trafficking of anticancer drugs. Sometimes, multiple ligands with different roles are used in combination to enhance the cellular uptake as well as target selectivity of anticancer drugs. In this review, the current status of various functional ligands applicable to improve the effectiveness of cancer chemotherapy is overviewed with a focus on their roles, characteristics, and preclinical/clinical applications.

Nitro-Group-Containing Thiopeptide Derivatives as Promising Agents to Target Clostridioides difficile.

The US Centers for Disease Control and Prevention (CDC) lists Clostridioides difficile as an urgent bacterial threat. Yet, only two drugs, vancomycin and fidaxomicin, are approved by the FDA for the treatment of C. difficile infections as of this writing, while the global pipeline of new drugs is sparse at best. Thus, there is a clear and urgent need for new antibiotics against that organism. Herein, we disclose that AJ-024, a nitroimidazole derivative of a 26-membered thiopeptide, is a promising anti-C. difficile lead compound. Despite their unique mode of action, thiopeptides remain largely unexploited as anti-infective agents. AJ-024 combines potent in vitro activity against various strains of C. difficile with a noteworthy safety profile and desirable pharmacokinetic properties. Its time-kill kinetics against a hypervirulent C. difficile ribotype 027 and in vivo (mouse) efficacy compare favorably to vancomycin, and they define AJ-024 as a valuable platform for the development of new anti-C. difficile antibiotics.

Reduced miR-371b-5p expression drives tumor progression via CSDE1/RAC1 regulation in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer; however, specific prognostic biomarkers have not yet been developed. In this study, we identified dysregulated microRNAs (miRNAs) in TNBC by profiling miRNA and mRNA expression. In patients with TNBC, miR-371b-5p expression was reduced, and miR-371b-5p overexpression significantly mitigated TNBC cell growth, migration, and invasion. In addition, we found that expression of cold shock domain-containing protein E1 (CSDE1), a direct target gene of miR-371b-5p, was upregulated in TNBC cells, and inhibition of CSDE1 expression alleviated TNBC cell growth by regulating RAC1 transcription. Mechanistically, CSDE1, phosphorylated C-terminal domain (p-CTD) of RNA polymerase II (RNAPII), and CDK7 form a complex, and downregulation of CSDE1 leads to weak interaction between RNAPII p-CTD and CDK7, resulting in a decrease in RNAPII p-CTD expression to reduce RAC1 transcript levels in CSDE1-deficient TNBC cells. Our data demonstrate that miR-371b-5p is a tumor-suppressive miRNA that regulates the CSDE1/Rac1 axis and could be a potential prognostic biomarker for TNBC.

Generation of Cortical Brain Organoid with Vascularization by Assembling with Vascular Spheroid.

BACKGROUND AND OBJECTIVES: Brain organoids have the potential to improve our understanding of brain development and neurological disease. Despite the importance of brain organoids, the effect of vascularization on brain organoids is largely unknown. The objective of this study is to develop vascularized organoids by assembling vascular spheroids with cerebral organoids. METHODS AND RESULTS: In this study, vascularized spheroids were generated from non-adherent microwell culture system of human umbilical vein endothelial cells, human dermal fibroblasts and human umbilical cord blood derived mesenchymal stem cells. These vascular spheroids were used for fusion with iPSCs induced cerebral organoids. Immunostaining studies of vascularized organoids demonstrated well organized vascular structures and reduced apoptosis. We showed that the vascularization in cerebral organoids up-regulated the Wnt/ß-catenin signaling. CONCLUSIONS: We developed vascularized cerebral organoids through assembly of brain organoids with vascular spheroids. This method could not only provide a model to study human cortical development but also represent an opportunity to explore neurological disease.

Did the COVID-19 Lockdown Reduce Smoking Rate in Adolescents?

This study examined the temporal trend of smoking use and the prevalent differences in the use of different types of cigarettes for Korean adolescents before and during the COVID-19 pandemic. In Korea, all use of e-cigarettes, including regular cigarettes, is considered smoking. Since adolescents are susceptible to peer influences in risky behaviors including smoking, social distancing could affect the smoking behaviors of youth under these unusual circumstances during the pandemic. In this study, we analyzed the Korea Youth Risk Behavior Web-based Survey (KYRBW) data collected from 2018 to 2021 to examine the association between smoking status and other covariates during the COVID-19 pandemic. As a result, it was confirmed that the influence of second-hand smoke on the smoking rate decreased before and after COVID-19, which is interpreted as a result of the social distancing policy caused by the pandemic.