Objective: This study aimed to establish the basic veterinary clinical skills required to ensure graduates of Korean veterinary universities have the day-one competency to independently perform their professional duties. Methods: The Education Committee of the Korean Association of Veterinary Medical Colleges, composed of veterinary school professors and an experienced veterinarian in the clinic, reviewed domestic and international veterinary education-related materials to define basic clinical skills. Results: The Korean Veterinarian Entrustable Professional Activities (KVEPA) was introduced, followed by the subsequent development of 54 essential clinical skills based on the KVEPA. Conclusions and Relevance: The veterinary basic clinical skills established through this study can be used as a specific guide for clinical education in Korean veterinary school, and is expected to play an important role in meeting the needs of the educational sector of the veterinary education accreditation standards.

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

Competencies are defined as an observable and assessable set of knowledge, skills, and attitudes. Graduation competencies, which are more comprehensive, refer to the required abilities of students to perform on-site work immediately after graduation. As graduation competencies set the goal of education, various countries and institutions have introduced them for new veterinary graduates. The Korean Association of Veterinary Medical Colleges has recently established such competencies to standardize veterinary education and enhance quality levels thereof. The purpose of this study is to describe the process of establishing graduation competencies as well as their implication for veterinary education in Korea.Graduation competencies for veterinary education in Korea comprise 5 domains (animal health care and disease management, one health expertise, communication and collaboration, research and learning, and veterinary professionalism). These are further divided into 11 core competencies, and 33 achievement standards, which were carefully chosen from previous case analyses and nation-wide surveys. Currently, graduation competencies are used as a standard for setting clear educational purposes for both instructors and students. Establishing these competencies further initiated the development of detailed learning outcomes, and of a list of basic veterinary clinical performances and skills, which is useful for assessing knowledge and skills. The establishment of graduation competencies is expected to contribute to the continuous development of Korean veterinary education in many ways. These include curriculum standardization and licensing examination reform, which will eventually improve the competencies of new veterinary graduates.

For primary prevention, it is important for public health and clinical medicine to identify and characterize modifiable risk factors of stroke. In existing literature, the impact of occupational variables on ischemic and hemorrhagic stroke has been extensively studied. This review summarizes the available data on the significance of occupational variables in stroke. The results of this review suggest that there is sufficient evidence for the relationship between increased risk of stroke and job stress, working in extreme temperatures, long working hours, and/or shift work. The association between long working hours and occupational exposure to noise and chemicals remains inconclusive although several studies have reported this finding. This review will act as a step toward future research and provide information that may serve as a baseline for developing targeted interventions to prevent stroke in the working population.

Background: and Purpose The natural course of adult-onset moyamoya disease (MMD) is unknown, and there is no medical treatment that halts its progression. We hypothesized that progressive shrinkage of large intracranial arteries occurs in adult-onset MMD, and that cilostazol inhibits this process. Methods: Serial high-resolution magnetic resonance imaging (HR-MRI) was performed on 66 patients with MMD: 30 patients received cilostazol, 21 received other antiplatelets, and 15 received no antiplatelets or had poor compliance to them. Serial HR-MRI was performed (interval between MRI scans: 29.67±18.02 months, mean±SD), and changes in outer diameter, luminal stenosis, and vascular enhancement were measured. Factors affecting HR-MRI changes were evaluated, including vascular risk factors and the ring finger protein 213 gene variant. Results: The progression of stenosis to occlusion, recurrent ischemic stroke, and the development of new stenotic segments were observed in seven, seven, and three patients, respectively. Serial HR-MRI indicated that the degree of stenosis increased with negative remodeling (outer diameter shrinkage). Patients who received cilostazol presented significantly larger outer diameters and lower degrees of stenosis compared with other groups (p=0.005 and p=0.031, respectively). After adjusting for clinical and genetic factors, only cilostazol use was independently associated with negative remodeling (odds ratio=0.29, 95% confidence interval=0.10–0.84, p=0.023). While vascular enhancement was observed in most patients (61 patients), the progression of enhancement or the occurrence of new vascular enhancement was rarely observed on follow-up HR-MRI (6 and 1 patients, respectively). Conclusions Adult-onset MMD induces progressive shrinkage of large intracranial arteries, which cilostazol treatment may prevent. Further randomized clinical trials are warranted.

Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951–0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6–42.6 msec); for ECV, r = 0.987 (95% CI, 0.980–0.991) and bias of 0.7% (95% LOA, -2.8%–4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98–0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97–1.00 and 0.99–1.00 for native T1 and ECV, respectively). Conclusion The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Objective: The purpose of this study was to evaluate the magnetic resonance (MR) characteristics and applicability of new, uniform, extremely small iron-based nanoparticles (ESIONs) with 3–4-nm iron cores using contrast-enhanced magnetic resonance angiography (MRA). Materials and Methods: Seven types of ESIONs were used in phantom and animal experiments with 1.5T, 3T, and 4.7T scanners. The MR characteristics of the ESIONs were evaluated via phantom experiments. With the ESIONs selected by the phantom experiments, animal experiments were performed on eight rabbits. In the animal experiments, the in vivo kinetics and enhancement effect of the ESIONs were evaluated using half-diluted and non-diluted ESIONs. The between-group differences were assessed using a linear mixed model. A commercially available gadolinium-based contrast agent (GBCA) was used as a control. Results: All ESIONs showed a good T1 shortening effect and were applicable for MRA at 1.5T and 3T. The relaxivity ratio of the ESIONs increased with increasing magnetic field strength. In the animal experiments, the ESIONs showed peak signal intensity on the first-pass images and persistent vascular enhancement until 90 minutes. On the 1-week follow-up images, the ESIONs were nearly washed out from the vascular structures and organs. The peak signal intensity on the first-pass images showed no significant difference between the non-diluted ESIONs with 3-mm iron cores and GBCA (p = 1.000). On the 10-minutes post-contrast images, the non-diluted ESIONs showed a significantly higher signal intensity than did the GBCA (p < 0.001). Conclusion In the phantom experiments, the ESIONs with 3–4-nm iron oxide cores showed a good T1 shortening effect at 1.5T and 3T. In the animal experiments, the ESIONs with 3-nm iron cores showed comparable enhancement on the first-pass images and superior enhancement effect on the delayed images compared to the commercially available GBCA at 3T.

Objective: The purpose of this study was to evaluate the magnetic resonance (MR) characteristics and applicability of new, uniform, extremely small iron-based nanoparticles (ESIONs) with 3–4-nm iron cores using contrast-enhanced magnetic resonance angiography (MRA). Materials and Methods: Seven types of ESIONs were used in phantom and animal experiments with 1.5T, 3T, and 4.7T scanners. The MR characteristics of the ESIONs were evaluated via phantom experiments. With the ESIONs selected by the phantom experiments, animal experiments were performed on eight rabbits. In the animal experiments, the in vivo kinetics and enhancement effect of the ESIONs were evaluated using half-diluted and non-diluted ESIONs. The between-group differences were assessed using a linear mixed model. A commercially available gadolinium-based contrast agent (GBCA) was used as a control. Results: All ESIONs showed a good T1 shortening effect and were applicable for MRA at 1.5T and 3T. The relaxivity ratio of the ESIONs increased with increasing magnetic field strength. In the animal experiments, the ESIONs showed peak signal intensity on the first-pass images and persistent vascular enhancement until 90 minutes. On the 1-week follow-up images, the ESIONs were nearly washed out from the vascular structures and organs. The peak signal intensity on the first-pass images showed no significant difference between the non-diluted ESIONs with 3-mm iron cores and GBCA (p = 1.000). On the 10-minutes post-contrast images, the non-diluted ESIONs showed a significantly higher signal intensity than did the GBCA (p < 0.001). Conclusion In the phantom experiments, the ESIONs with 3–4-nm iron oxide cores showed a good T1 shortening effect at 1.5T and 3T. In the animal experiments, the ESIONs with 3-nm iron cores showed comparable enhancement on the first-pass images and superior enhancement effect on the delayed images compared to the commercially available GBCA at 3T.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.