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: 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: 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.

Background: Baseball players are subjected to repeated loads on the supraspinatus and long head biceps tendon from youth, and repetitive pitching motions can cause shoulder injuries. The purpose of this study was to evaluate the immediate changes caused by pitching in the supraspinatus muscle-tendon, long head of the bicep tendon (LHBT), and shoulder range of motion (ROM) and to verify their recovery over time in youth baseball players. Methods: Fifteen youth baseball players (mean age, 11.5 ± 1.3 years) were enrolled. The thicknesses of the supraspinatus tendon and LHBT and the strain ratios (SRs) of supraspinatus muscle and tendon were measured by sonoelastography. ROMs of shoulder joints (abduction, external rotation at 90° of abduction [ABER], and internal rotations at 90° of abduction [ABIR]) and horizontal adduction (HA) were measured using a goniometer. All measurements were performed on the throwing shoulders before and immediately after pitching (mean pitch count, 78.3 ± 13.3) and at 30 minutes, 24 hours, and 72 hours after pitching. Results: The thickness of supraspinatus tendon (6.64–6.27 mm, p = 0.026) and that of LHBT (2.56–2.26 mm, p = 0.021) significantly decreased immediately after pitching. The SRs of supraspinatus muscle tended to decrease, whereas SRs of supraspinatus tendon tended to increase immediately after pitching. ABER increased (119.7°–127.3°, p = 0.001) and HA decreased (34.7°–29.3°, p = 0.023) immediately after pitching. All immediate changes recovered 72 hours after pitching. Conclusions The immediate effects of pitching on the supraspinatus muscle-tendon, LHBT, and shoulder ROM in youth baseball players were confirmed in the current study. These changes were recovered to pre-pitch levels 72 hours after pitching. Therefore, we recommend that youth baseball players should rest for three days after pitching to minimize the risk of shoulder injury.

Background: Baseball players are subjected to repeated loads on the supraspinatus and long head biceps tendon from youth, and repetitive pitching motions can cause shoulder injuries. The purpose of this study was to evaluate the immediate changes caused by pitching in the supraspinatus muscle-tendon, long head of the bicep tendon (LHBT), and shoulder range of motion (ROM) and to verify their recovery over time in youth baseball players. Methods: Fifteen youth baseball players (mean age, 11.5 ± 1.3 years) were enrolled. The thicknesses of the supraspinatus tendon and LHBT and the strain ratios (SRs) of supraspinatus muscle and tendon were measured by sonoelastography. ROMs of shoulder joints (abduction, external rotation at 90° of abduction [ABER], and internal rotations at 90° of abduction [ABIR]) and horizontal adduction (HA) were measured using a goniometer. All measurements were performed on the throwing shoulders before and immediately after pitching (mean pitch count, 78.3 ± 13.3) and at 30 minutes, 24 hours, and 72 hours after pitching. Results: The thickness of supraspinatus tendon (6.64–6.27 mm, p = 0.026) and that of LHBT (2.56–2.26 mm, p = 0.021) significantly decreased immediately after pitching. The SRs of supraspinatus muscle tended to decrease, whereas SRs of supraspinatus tendon tended to increase immediately after pitching. ABER increased (119.7°–127.3°, p = 0.001) and HA decreased (34.7°–29.3°, p = 0.023) immediately after pitching. All immediate changes recovered 72 hours after pitching. Conclusions The immediate effects of pitching on the supraspinatus muscle-tendon, LHBT, and shoulder ROM in youth baseball players were confirmed in the current study. These changes were recovered to pre-pitch levels 72 hours after pitching. Therefore, we recommend that youth baseball players should rest for three days after pitching to minimize the risk of shoulder injury.

Purpose: The objective of this study was to modify and validate an emergency department (ED) triage system with improved prediction performance on hospital outcomes by modifying the Korean Triage and Acuity Scale (KTAS). Materials and Methods: We performed a retrospective observational study at three academic universities in South Korea. The KTAS code, determined by the chief complaint and the selected modifier of a patient, was used to derive the Modified KTAS (MKTAS). We calculated the area under the receiver operating characteristics curve (AUC) and the test characteristics to evaluate the performance of MKTAS to predict hospital mortality, critical outcome, and admission. Results: A total of 272402 and 128831 ED visits were used for the derivation and validation of MKTAS, respectively. Compared to KTAS, MKTAS had significantly higher AUC values for the prediction of hospital mortality [MKTAS 0.826 (0.818–0.835) vs. KTAS 0.794 (0.784–0.803)], critical outcome [MKTAS 0.836 (0.830–0.841) vs. 0.798 (0.792–0.804)], and admission [MKTAS 0.725 (0.723– 0.728) vs. KTAS 0.685 (0.682–0.688)]. The sensitivity for predicting hospital mortality and critical outcome, as well as the specificity for predicting admission, were significantly improved. Conclusion MKTAS was derived by modifying the KTAS, and then validated. Compared with KTAS, MKTAS showed better discriminating ability to predict hospital outcomes. Continuous efforts to evaluate and modify widely used triage systems are required to improve their performance.

OBJECTIVES: The purpose of this study was to investigate the distinctive features of bodily panic symptoms and the predisposing conditions in Korean patients with panic disorder. METHODS: This was a retrospective chart review study and the data were collected from twelve university-affiliated hospitals in Korea. The patients selected met the diagnostic criteria for panic disorder, were older than 20 years of age, and had initially visited a psychiatry department. The assessments included the chief complaints related to bodily panic symptoms, recent stressors, recent history of alcohol and sleep problems, and time to visit an outpatient clinic. RESULTS: A total of 814 participants were included in the study. The most commonly experienced symptoms were cardiovascular and respiratory symptoms, which were observed in 63.9% and 55.4% of participants, respectively. Just before the onset of a panic attack, 25.6% of participants experienced sleep-related problems. Episodic binge drinking was also frequently observed (13.2%) and was more prevalent in men than in women (22.6% vs. 4.9%, p<0.001). About 75% of participants experienced stressful life events just before panic onset. Work-related issues were more prevalent in men than in women (22.0% vs. 13.4%, p=0.001). Family-related issues (4.8% vs. 14.1%, p<0.001) and conflict with a spouse or partner (4.0% vs.11.7%, p<0.001) were more prominent in women than in men. CONCLUSION Our results suggest that cardiovascular symptoms are the most common bodily panic symptoms in Korean patients. Our results suggest that a substantial portion of the Korean patients experienced stressful life events, sleep problems, and/or episodic binge drinking just before the onset of panic disorder.