Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Background: Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy. To define the altered pathway in GDM placenta, we investigated the transcriptomic profiles from human placenta between GDM and controls. Methods: Clinical parameters and postpartum complications were reviewed in all participants.Differentially expressed canonical pathways were analyzed between the GDM and control groups based on transcriptomic analysis. CD4 + T, CD8 + T, and senescent T cell subsets were determined by flow cytometry based on staining for specific intracellular cytokines. Results: Gene ontology analysis revealed that the placenta of GDM revealed upregulation of diverse mitochondria or DNA replication related pathways and downregulation of T-cell immunity related pathways. The maternal placenta of the GDM group had a higher proportion of CD4 + T and CD8 + T cells than the control group. Interestingly, senescent CD4 + T cells tended to increase and CD8 + T cells were significantly increased in GDM compared to controls, along with increased programmed cell death-1 (CD274 + ) expression. Programmed death-ligand 1 expression in syncytotrophoblasts was also significantly increased in patients with GDM. Conclusion This study demonstrated increased proinflammatory T cells, senescent T cells and immune-check point molecules in GDM placentas, suggesting that changes in senescent T cells and immune-escape signaling might be related to the pathophysiology of GDM.

UI026 is an expectorant and antitussive agent which is a new combination of Pelargonium sidoides extract andCoptis extract. The bioactive compounds of Pelargonium sidoides and Coptis extracts were identified as epicatechin and berberine, respectively. This study evaluated the effect of food on the pharmacokinetics (PKs) and safety of UI026. A randomized, openlabel, single-dose, 2-treatment, parallel study in 12 healthy male subjects was performed. Subjects received a single oral dose of UI026 (27 mL of syrup) under a fed or fasted condition according to their randomly assigned treatment. Blood samples for the PK analysis were obtained up to 24 hours post-dose for berberine and 12 hours post-dose for epicatechin. The PK parameters were calculated by non-compartmental analysis. In the fed condition, the mean maximum plasma concentration (C max ) and mean area under the plasma concentrationtime curve from time zero to the last observed time point (AUC last ) for berberine were approximately 33% and 67% lower, respectively, compared with the fasted condition, both showing statistically significant difference. For epicatechin, the mean C max and mean AUC last were about 29% and 45% lower, respectively, compared to the fasting condition, neither of which showed a statistically significant difference. There were no drug-related adverse events. This finding suggests that food affects the systemic exposure and bioavailability of berberine and epicatechin.

Purpose: Various changes in nutrition, metabolism, immunity, and psychological status occur through multiple mechanisms after gastrectomy. The purpose of this study was to predict disease status after gastrectomy by analyzing diseases pattern that occur or change after gastrectomy. Materials and Methods: A retrospective cohort study was conducted using nationwide claims data. Patients with gastric cancer who underwent gastrectomy or endoscopic resection were included in the study. Eighteen target diseases were selected and categorized based on their underlying mechanism. The incidence of each target disease was compared by dividing the study sample into those who underwent gastrectomy (cases) and those who underwent endoscopic resection for early gastric cancer (controls). The cases were matched with controls using propensity score matching. Thereafter, Cox proportional hazard models were used to evaluate intergroup differences in disease incidence after gastrectomy. Results: A total of 97,634 patients who underwent gastrectomy (84,830) or endoscopic resection (12,804) were included. The incidence of cholecystitis (P<0.0001), pancreatitis (P=0.034), acute kidney injury (P=0.0083), anemia (P<0.0001), and inguinal hernia (P=0.0007) were higher after gastrectomy, while incidence of dyslipidemia (P<0.0001), vascular diseases (ischemic heart disease, stroke, and atherosclerosis; P<0.0001, P<0.0001, and P=0.0005), and Parkinson's disease (P=0.0093) were lower after gastrectomy. Conclusions This study identifies diseases that may occur after gastrectomy in patients with gastric cancer.

To analyze medical professors’ evaluation of their online education experiences in an attempt to support faculty members and indicate the future direction of medical education. Faculty members who taught online in the first semester of 2020 at Yonsei University College of Medicine in South Korea were surveyed. The results of the survey were analyzed in June 2020. There were 88 respondents (35.1% of 251): 59 professors (67.0%), 16 associate professors (18.2%), and 13 assistant professors (14.8%). Their specialties lay in basic medicine (25.0%), clinical medicine (65.9%), and research and special purposes (9.1%). Sixteen participants (18.2%) had previous experience in online lectures; 23 (26.1%) reported that preparation time for online lectures was the same as before; 65 (73.9%) reported that the preparation time had increased; 38 (43.2%) faced difficulties in preparation and lecturing online, and among them 16 (42.1%) indicated inadequate interaction with students; 11 (28.9%) needed extra preparation time; and 11 (28.9%) attributed their difficulties to technical issues with the online platform. Participants’ satisfaction with online lectures was low (p<0.001). In the free response question on overall experience with online education, 38.3% mentioned the need for an instructional design that allows students to actively participate and interact with professors, 29.5% mentioned the need for the establishment of an information & communications technology system, and 17.0% mentioned the necessity of faculty development. To prepare for the current pandemic and more in the long term, an appropriate educational support system must be constructed, and a learner-centered instructional design that enables wider interactions and active learning is needed.

We used the nationwide claims database to calculate the incidence of thrombotic events and predict their overall 2-week incidence. From 2006 to 2020, the incidence of deep vein thrombosis (DVT), pulmonary embolism (PE), and disseminated intravascular coagulation (DIC) tended to increase. Unlike intracranial venous thrombosis (ICVT) and intracranial thrombophlebitis (ICTP), which showed no age difference, other venous embolism, and thrombosis (OVET), DIC, DVT, and PE were significantly more common in over 65 years.The overall 2-week incidence of ICVT was 0.21/1,000,000 (95% confidence interval [CI], 0.11–0.32). ICTP, OVET, DIC, DVT and PE were expected to occur in 0.08 (95% CI, 0.02– 0.14), 7.66 (95% CI, 6.08–9.23), 5.95 (95% CI, 4.88–7.03), 13.28 (95% CI, 11.92–14.64), 14.09 (95% CI, 12.80–15.37) per 1,000,000, respectively. To date, of 8,548,231 patients vaccinated with ChAdOx1 nCoV-19 in Korea, two had confirmed thrombosis with thrombocytopenia syndrome within 2 weeks. The observed incidence of ICVT after vaccination was 0.23/1,000,000.