Background and Objectives: Electronic cigarette (e-cigarette) is a device that generate vapor by heating e-cigarettes liquid. E-cigarette damages the respiratory immune system and renders the respiratory tract vulnerable to inflammations. However, there are no studies on how the inflammatory reactions in respiratory epithelial cells caused by e-cigarette occur, and the effects of Korean red ginseng (KRG) and saponin on inflammation induced by e-cigarette are unknown. This study aimed to compare the inflammatory reactions caused by e-cigarette and lipopolysaccharide (LPS), and to investigate the effects of KRG and saponin on cytokine and mucin expression induced by e-cigarette in respiratory epithelial cells.Subjects and Method In bronchoalveolar lavage fluid and lung tissue of mice, the effects of KRG and saponin on cytokines (interleukin [IL]-1β, IL-6, IL-8) and mucin 5AC/5B (MUC5AC/5B) expression induced by e-cigarette were investigated using real-time polymerase chain reaction, enzyme linked immunosorbent assay, and immunohistochemistry staining. Results: Inflammatory cells, cytokines (IL-1β, IL-6, IL-8) and MUC5AC/5B messenger RNA expression and protein production were increased by e-cigarette, similar to LPS. KRG and saponin decreased the expression of cytokines (IL-1β, IL-6, IL-8) and MUC5AC/5B induced by e-cigarette. KRG and saponin showed effects similar to that of dexamethasone. Conclusion E-cigarette causes inflammation similar to that caused by LPS. KRG and saponin regulate the expression of cytokine and MUC5AC/5B increased by e-cigarette in respiratory epithelial cells. KRG and saponin may be an effective therapeutic option for inflammatory responses induced by e-cigarette in respiratory epithelial cells.

Cancer immunotherapy is widely used to treat various cancers to augment the weakened host immune response against tumors. Dendritic cells (DCs) are specialized antigen-presenting cells that play dual roles in inducing innate and adaptive immunity. Toxoplasma gondii is a protozoan parasite that exhibits anti-tumor activity against certain types of cancers. However, little is known about the anti-tumor effects of T. gondii or tumor/parasite antigen-pulsed DCs (DC vaccines, DCV) in breast cancer. In this study, C57BL/6 mice were administered E0771 mouse breast cancer cells (Cancer-injected) subcutaneously, T. gondii Me49 cysts orally (TG-injected), or DCs pulsed with breast cancer cell lysate antigen and T. gondii lysate antigens (DCV-injected) intraperitoneally. Tumor size and immunological characteristics were subsequently evaluated. We also evaluated matrix metalloproteinase (MMP)-2 and MMP-9 levels in E0771 mouse breast cancer cells co-cultured with T. gondii or DCs by RT-PCR. The tumor volumes of mice injected with breast cancer cells and antigen-pulsed DCs (Cancer/DCV-injected mice) were similar to those of Cancer-injected mice; however, they were significantly reduced in T. gondii-infected tumor-bearing (TG/Cancer-injected) mice. Moreover, tumor volumes were significantly reduced by adding antigen-pulsed DCs (TG/Cancer/DCV-injected mice) compared to TG/Cancer-injected mice. The levels of IFN-γ, serum IgG2a levels, and CD8+ T cell populations were significantly higher in DCV- and TG-injected mice than in control mice, while no significant differences between Cancer- and Cancer/DCV-injected mice were observed. The levels of IFN-γ, the IgG2a levels, and the percentage of CD8+ T cells were significantly increased in TG/Cancer- and TG/Cancer/DCV-injected mice than in Cancer-injected mice. IFN-γ levels and serum IgG2a levels were further increased in TG/Cancer/DCV-injected mice than in TG/Cancer-injected mice. The MMP-2 and MMP-9 mRNA expressions were significantly decreased in mouse breast cancer cells co-cultured with live T. gondii, T. gondii lysate antigen, or antigen-pulsed DCs (DCV) but not in inactivated DCs. These results indicate that T. gondii induces anti-tumor effects in breast cancer-bearing mice through the induction of strong Th1 immune responses, but not in antigen-pulsed DCs alone. The addition of antigen-pulsed DCs further augments the anti-tumor effects of T. gondii.

Background and Objectives: Electronic cigarette (e-cigarette) is a device that generate vapor by heating e-cigarettes liquid. E-cigarette damages the respiratory immune system and renders the respiratory tract vulnerable to inflammations. However, there are no studies on how the inflammatory reactions in respiratory epithelial cells caused by e-cigarette occur, and the effects of Korean red ginseng (KRG) and saponin on inflammation induced by e-cigarette are unknown. This study aimed to compare the inflammatory reactions caused by e-cigarette and lipopolysaccharide (LPS), and to investigate the effects of KRG and saponin on cytokine and mucin expression induced by e-cigarette in respiratory epithelial cells.Subjects and Method In bronchoalveolar lavage fluid and lung tissue of mice, the effects of KRG and saponin on cytokines (interleukin [IL]-1β, IL-6, IL-8) and mucin 5AC/5B (MUC5AC/5B) expression induced by e-cigarette were investigated using real-time polymerase chain reaction, enzyme linked immunosorbent assay, and immunohistochemistry staining. Results: Inflammatory cells, cytokines (IL-1β, IL-6, IL-8) and MUC5AC/5B messenger RNA expression and protein production were increased by e-cigarette, similar to LPS. KRG and saponin decreased the expression of cytokines (IL-1β, IL-6, IL-8) and MUC5AC/5B induced by e-cigarette. KRG and saponin showed effects similar to that of dexamethasone. Conclusion E-cigarette causes inflammation similar to that caused by LPS. KRG and saponin regulate the expression of cytokine and MUC5AC/5B increased by e-cigarette in respiratory epithelial cells. KRG and saponin may be an effective therapeutic option for inflammatory responses induced by e-cigarette in respiratory epithelial cells.

Cancer immunotherapy is widely used to treat various cancers to augment the weakened host immune response against tumors. Dendritic cells (DCs) are specialized antigen-presenting cells that play dual roles in inducing innate and adaptive immunity. Toxoplasma gondii is a protozoan parasite that exhibits anti-tumor activity against certain types of cancers. However, little is known about the anti-tumor effects of T. gondii or tumor/parasite antigen-pulsed DCs (DC vaccines, DCV) in breast cancer. In this study, C57BL/6 mice were administered E0771 mouse breast cancer cells (Cancer-injected) subcutaneously, T. gondii Me49 cysts orally (TG-injected), or DCs pulsed with breast cancer cell lysate antigen and T. gondii lysate antigens (DCV-injected) intraperitoneally. Tumor size and immunological characteristics were subsequently evaluated. We also evaluated matrix metalloproteinase (MMP)-2 and MMP-9 levels in E0771 mouse breast cancer cells co-cultured with T. gondii or DCs by RT-PCR. The tumor volumes of mice injected with breast cancer cells and antigen-pulsed DCs (Cancer/DCV-injected mice) were similar to those of Cancer-injected mice; however, they were significantly reduced in T. gondii-infected tumor-bearing (TG/Cancer-injected) mice. Moreover, tumor volumes were significantly reduced by adding antigen-pulsed DCs (TG/Cancer/DCV-injected mice) compared to TG/Cancer-injected mice. The levels of IFN-γ, serum IgG2a levels, and CD8+ T cell populations were significantly higher in DCV- and TG-injected mice than in control mice, while no significant differences between Cancer- and Cancer/DCV-injected mice were observed. The levels of IFN-γ, the IgG2a levels, and the percentage of CD8+ T cells were significantly increased in TG/Cancer- and TG/Cancer/DCV-injected mice than in Cancer-injected mice. IFN-γ levels and serum IgG2a levels were further increased in TG/Cancer/DCV-injected mice than in TG/Cancer-injected mice. The MMP-2 and MMP-9 mRNA expressions were significantly decreased in mouse breast cancer cells co-cultured with live T. gondii, T. gondii lysate antigen, or antigen-pulsed DCs (DCV) but not in inactivated DCs. These results indicate that T. gondii induces anti-tumor effects in breast cancer-bearing mice through the induction of strong Th1 immune responses, but not in antigen-pulsed DCs alone. The addition of antigen-pulsed DCs further augments the anti-tumor effects of T. gondii.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Background: Prevention of contrast-induced nephropathy (CIN) is crucial in acute myocardial infarction (AMI) patients undergoing coronary interventions. Previous studies suggest that high-dose statins may aid in CIN prevention, yet comparative studies among different statin types using cystatin C (cysC) as a biomarker for CIN are absent. This study evaluated the effectiveness of high-dose rosuvastatin versus atorvastatin in preventing cysC-based CIN (cysC-CIN) in AMI patients. Methods: This multicenter registry included 431 patients (rosuvastatin 20 mg: n = 231, atorvastatin 40 mg: n = 200). The primary endpoint was cysC-CIN incidence within 48 hours post contrast; the secondary endpoints were creatinine-based CIN (cr-CIN) incidence within 72 hours post contrast and post 30 days adverse events. Results: The incidences of cysC-CIN (12.1% vs. 7.5%, P = 0.103) and cr-CIN (6.2% vs. 3.5%, P = 0.103) were higher in the atorvastatin group without significant statistical differences.Multivariable regression analysis, which was adjusted for CIN risk factors and the variables with univariate association, showed no increased odds ratio (OR) (OR, 2.185; 95% confidence interval [CI], 0.899, 5.315; P = 0.085) for cysC-CIN in the atorvastatin group compared to the rosuvastatin group. However, statin-naïve atorvastatin subgroup had significantly increased odds of cysC-CIN compared to the rosuvastatin group (OR, 2.977; 95% CI, 1.057, 8.378; P = 0.039). At post 30 days renal, cardiovascular, and mortality event rates were both low and similar between the two groups. Conclusion No significant difference in cysC-CIN incidence was found between the highdose rosuvastatin and atorvastatin groups in AMI patients and cysC was more sensitive to the early detection of CIN than creatinine.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Background: Prevention of contrast-induced nephropathy (CIN) is crucial in acute myocardial infarction (AMI) patients undergoing coronary interventions. Previous studies suggest that high-dose statins may aid in CIN prevention, yet comparative studies among different statin types using cystatin C (cysC) as a biomarker for CIN are absent. This study evaluated the effectiveness of high-dose rosuvastatin versus atorvastatin in preventing cysC-based CIN (cysC-CIN) in AMI patients. Methods: This multicenter registry included 431 patients (rosuvastatin 20 mg: n = 231, atorvastatin 40 mg: n = 200). The primary endpoint was cysC-CIN incidence within 48 hours post contrast; the secondary endpoints were creatinine-based CIN (cr-CIN) incidence within 72 hours post contrast and post 30 days adverse events. Results: The incidences of cysC-CIN (12.1% vs. 7.5%, P = 0.103) and cr-CIN (6.2% vs. 3.5%, P = 0.103) were higher in the atorvastatin group without significant statistical differences.Multivariable regression analysis, which was adjusted for CIN risk factors and the variables with univariate association, showed no increased odds ratio (OR) (OR, 2.185; 95% confidence interval [CI], 0.899, 5.315; P = 0.085) for cysC-CIN in the atorvastatin group compared to the rosuvastatin group. However, statin-naïve atorvastatin subgroup had significantly increased odds of cysC-CIN compared to the rosuvastatin group (OR, 2.977; 95% CI, 1.057, 8.378; P = 0.039). At post 30 days renal, cardiovascular, and mortality event rates were both low and similar between the two groups. Conclusion No significant difference in cysC-CIN incidence was found between the highdose rosuvastatin and atorvastatin groups in AMI patients and cysC was more sensitive to the early detection of CIN than creatinine.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.