Background and Objectives: Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue–based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Methods: Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography–mass spectrometry.Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. Results: The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Conclusions Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Background and Objectives: Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue–based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Methods: Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography–mass spectrometry.Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. Results: The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Conclusions Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Background and Objectives: Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue–based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Methods: Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography–mass spectrometry.Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. Results: The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Conclusions Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Background and Objectives: Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue–based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Methods: Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography–mass spectrometry.Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. Results: The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Conclusions Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

An educational outcome cohort has been established at Keimyung University School of Medicine to help make educational policy decisions and improve educational programs based on data. The purpose of the educational outcome cohort is to support educational policy decisions for achieving graduation outcomes smoothly and to accomplish the intended human resources development of the university through objective analyses and regular monitoring, providing continuous feedback. The data collected for the educational outcome cohort include the student identifications of freshmen, entrance exam scores, premedical and medical school grades, titles and forms of student academic research, the results of psychological testing, scholarship recipient lists, volunteer clubs, and so forth. The data are collected using an information utilization agreement approved by the Institutional Review Board, and the collected data are encrypted and stored on a dedicated computer for enhanced personal information security. Proposals to access and utilize the educational outcome cohort data must be discussed and approved by the Educational Outcome Cohort Committee, which decides on the scope and method of utilization. The collected and managed educational outcome cohort data have been used to develop comparative programs to improve students’ competency and to support admission policy decisions through an analysis of the characteristics and performance of medical school students. The establishment and utilization of the educational outcome cohort will play an important role in determining the School of Medicine’s educational policies and suggesting new directions for educational policies in the future.

Background: Polo-like kinase 4 (PLK4) is a serine/threonine protein kinase located in the centriole of the chromosome during the cell cycle. PLK4 overexpression has been described in a variety of many common human epithelial tumors. Conversely, PLK4 acts as a haploinsufficient tumor suppressor in some situations, highlighting the importance of strict regulation of PLK4 expression, activity, and function. Meanwhile, the importance of chemoradiation resistance in rectal cancer is being emphasized more than ever. We aimed to analyze PLK4 expression and the tumor regression grade (TRG) in patients with rectal cancer, treated with chemoradiotherapy (CRT). Methods: A retrospective study was conducted on 102 patients with rectal cancer who received preoperative CRT. Immunohistochemistry for PLK4 in paraffin-embedded tissue was performed from the biopsy and surgical specimens. Results: We found significant association between high expression of PLK4 and poor response to neoadjuvant CRT (according to both Mandard and The Korean Society of Pathologists TRG systems) in the pre-CRT specimens. Other clinicopathologic parameters did not reveal any correlation with PLK4 expression. Conclusions This study revealed an association between high expression of PLK4 in the pre-CRT specimens and TRG. Our results indicated that PLK4 could potentially be a new predictor for CRT effect in patients with rectal cancer.

Background: Pituitary tumor transforming gene 1 (PTTG1), paired-like homeodomain 2 (PITX2), and galectin-3 have been widely studied as predictive biomarkers for various tumors and are involved in tumorigenesis and tumor progression. We evaluated the usefulness of PTTG1, PITX2, and galectin-3 as predictive biomarkers for invasive non-functioning pituitary adenomas (NFPAs) by determining the relationship between the expressions of these three proteins and the invasiveness of the NFPAs. We also investigated whether PTTG1, E-cadherin, and Ki-67, which are known to be related to each other, show a correlation with NFPA features. Methods: A retrospective study was conducted on 87 patients with NPFAs who underwent surgical removal. The NFPAs were classified into three groups based on magnetic resonance imaging findings of suprasellar extension and cavernous sinus invasion. Immunohistochemical staining for PTTG1, PITX2, galectin-3, E-cadherin, and Ki-67 was performed on tissue microarrays. Results: PTTG1 expression showed a statistically significant correlation with the invasiveness of NFPAs, whereas PITX2 and galectin-3 did not have a relationship with the invasiveness of NFPAs. Moreover, there was no association among PTTG1, E-cadherin, and Ki-67 expression. Conclusions PTTG1 has the potential to serve as a predictive biomarker for invasive NFPA. Furthermore, this study may serve as a reference for the development of PTTG1-targeted therapeutic agents.

The aim of this study was to analyze the research trends in articles published in the Korean Journal of Medical Education (KJME) and Korean Medical Education Review (KMER) using keyword network analysis. The analyses included 507 papers from 2010 to 2019 published in KJME and KMER. First, keyword frequency analysis showed that the research topics that appeared in both journals were “medical student,” “curriculum,” “clinical clerkship,” and “undergraduate medical education.” Second, centrality analysis of a network map of the keywords identified “curriculum” and “medical student” as highly important research topics in both journals. Third, a cluster analysis of 20 core keywords in KMER identified research clusters related to academic motivation, achievement, educational measurement, medical competence, and clinical practice (centered on “learning,” while in KJME, clusters were related to educational method and program evaluation, medical competence, and clinical practice (centered on “teaching”). In conclusion, future medical education research needs to expand to encompass other research areas, such as educational methods, student evaluations, the educational environment, student counseling, and curriculum.