Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data.The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4 + and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: The purpose of this study was to examine the influential factors on retention intention among nurses in small-medium sized hospitals. Methods: This study was conducted with 185 nurses of 6 small-medium sized general hospitals located in B metropolitan city. Data were collected from July 10 to July 19, 2022 using on-line self-report questionnaires. A descriptive analysis and hierarchical multiple regression were used for data analysis utilizing IBM SPSS Statistics for Windows version 25.0. Results: The variables influencing the retention intention of the subjects were perceived value of work (β=.36, p<.001), nurse manager ability, leadership, and support of nurses (β=.22, p=.024), positive psychological capital (β=.15, p=.042), and subjective health status (β=.14, p=.035), and the total explanatory power (R2 ) of these variables was 38.0% (F=12.24, p<.001). Conclusion Based on the results, in order to increase the retention intention for nurses in small and medium-sized hospitals, it is necessary to create an environment and culture as well as educational strategies for fostering a sense of work value and positive psychological capital. In addition, proactive organizational efforts are required to strengthen nurses’ subjective health and nurse managers’ supporting capabilities and leadership in small-medium sized hospitals.

Purpose: The purpose of this study was to examine the influential factors on retention intention among nurses in small-medium sized hospitals. Methods: This study was conducted with 185 nurses of 6 small-medium sized general hospitals located in B metropolitan city. Data were collected from July 10 to July 19, 2022 using on-line self-report questionnaires. A descriptive analysis and hierarchical multiple regression were used for data analysis utilizing IBM SPSS Statistics for Windows version 25.0. Results: The variables influencing the retention intention of the subjects were perceived value of work (β=.36, p<.001), nurse manager ability, leadership, and support of nurses (β=.22, p=.024), positive psychological capital (β=.15, p=.042), and subjective health status (β=.14, p=.035), and the total explanatory power (R2 ) of these variables was 38.0% (F=12.24, p<.001). Conclusion Based on the results, in order to increase the retention intention for nurses in small and medium-sized hospitals, it is necessary to create an environment and culture as well as educational strategies for fostering a sense of work value and positive psychological capital. In addition, proactive organizational efforts are required to strengthen nurses’ subjective health and nurse managers’ supporting capabilities and leadership in small-medium sized hospitals.

Background/Aims: We investigated sex- and stage-specific associations of body mass index (BMI), fasting glucose, and high-density lipoprotein cholesterol (HDL-C) with gastric cancer. Methods: In total, 3,382 patients with gastric cancer and 19,609 healthy controls were enrolled. BMI was categorized into five groups. HDL-C was classified as low (< 40 and < 50 mg/ dl in males and females, respectively) and normal (≥ 40 and ≥ 50 mg/dl in males and females, respectively). Logistic regression analysis was performed to calculate odd ratios (ORs) and 95% confidence intervals (CIs). Results: After adjustment, low BMI (OR, 1.44; 95% CI, 1.13–1.84), low HDL levels (OR, 2.28;95% CI, 2.07–2.50), and high fasting glucose levels (OR, 2.94; 95% CI, 2.22–2.99) were associated with gastric cancer, whereas high BMI (OR, 0.61–0.81) was inversely associated with gastric cancer. In sex-specific analysis, BMI was inversely associated with gastric cancer only in males (trend: p < 0.001). Low serum HDL and high fasting glucose levels were strongly associated with gastric cancer in both males and females. The effect of high glucose content was more pronounced in females (OR, 4.02) than in males (OR, 2.58). BMI was inversely associated with both AGC (trend: p < 0.001) and EGC (trend: p = 0.001). Low serum HDL and high fasting glucose levels were strongly associated with gastric cancer in EGC and AGC. Conclusions The effect of BMI on gastric cancer varies by sex and stage, whereas low HDL levels are associated with gastric cancer regardless of these factors.

Background/Aims: We investigated sex- and stage-specific associations of body mass index (BMI), fasting glucose, and high-density lipoprotein cholesterol (HDL-C) with gastric cancer. Methods: In total, 3,382 patients with gastric cancer and 19,609 healthy controls were enrolled. BMI was categorized into five groups. HDL-C was classified as low (< 40 and < 50 mg/ dl in males and females, respectively) and normal (≥ 40 and ≥ 50 mg/dl in males and females, respectively). Logistic regression analysis was performed to calculate odd ratios (ORs) and 95% confidence intervals (CIs). Results: After adjustment, low BMI (OR, 1.44; 95% CI, 1.13–1.84), low HDL levels (OR, 2.28;95% CI, 2.07–2.50), and high fasting glucose levels (OR, 2.94; 95% CI, 2.22–2.99) were associated with gastric cancer, whereas high BMI (OR, 0.61–0.81) was inversely associated with gastric cancer. In sex-specific analysis, BMI was inversely associated with gastric cancer only in males (trend: p < 0.001). Low serum HDL and high fasting glucose levels were strongly associated with gastric cancer in both males and females. The effect of high glucose content was more pronounced in females (OR, 4.02) than in males (OR, 2.58). BMI was inversely associated with both AGC (trend: p < 0.001) and EGC (trend: p = 0.001). Low serum HDL and high fasting glucose levels were strongly associated with gastric cancer in EGC and AGC. Conclusions The effect of BMI on gastric cancer varies by sex and stage, whereas low HDL levels are associated with gastric cancer regardless of these factors.

Purpose: The purpose of this study was to examine the influential factors on retention intention among nurses in small-medium sized hospitals. Methods: This study was conducted with 185 nurses of 6 small-medium sized general hospitals located in B metropolitan city. Data were collected from July 10 to July 19, 2022 using on-line self-report questionnaires. A descriptive analysis and hierarchical multiple regression were used for data analysis utilizing IBM SPSS Statistics for Windows version 25.0. Results: The variables influencing the retention intention of the subjects were perceived value of work (β=.36, p<.001), nurse manager ability, leadership, and support of nurses (β=.22, p=.024), positive psychological capital (β=.15, p=.042), and subjective health status (β=.14, p=.035), and the total explanatory power (R2 ) of these variables was 38.0% (F=12.24, p<.001). Conclusion Based on the results, in order to increase the retention intention for nurses in small and medium-sized hospitals, it is necessary to create an environment and culture as well as educational strategies for fostering a sense of work value and positive psychological capital. In addition, proactive organizational efforts are required to strengthen nurses’ subjective health and nurse managers’ supporting capabilities and leadership in small-medium sized hospitals.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.