Background: and Purpose Anti-agrin antibodies (agrin Abs) have recently been identified in patients with myasthenia gravis (MG), sometimes in conjunction with antibodies (Abs) to the acetylcholine receptor (AChR), muscle-specific tyrosine kinase (MuSK), or low-density lipoprotein receptor-related protein 4. This study aimed to develop an in-house cell-based assay (CBA) for detecting agrin Abs, and to test its application to serum samples collected from individuals diagnosed with MG. Methods: Agrin complementary DNA as cloned into a pCMV6-AC-GFP vector, which was subsequently transfected into human embryonic kidney 293T (HEK293T) cells. Transfected HEK293T cells were incubated with patient serum and antihuman immunoglobulin G Ab conjugated with a red fluorescent dye. Agrin Ab levels were measured using the CBA in 389 serum samples: 340 from patients with MG, 36 from patients with other neuromuscular diseases, and 13 from healthy controls. The presence of agrin Ab was determined based on the fluorescence intensity and colocalization using fluorescence microscopy. Results: The expression levels of agrin mRNA and protein in transfected HEK293T cells were confirmed using the reverse-transcription polymerase chain reaction and Western blotting, respectively. Agrin expression in cells was further confirmed by immunocytochemistry.Two (0.6%) of the 340 patients with MG tested positive for agrin Ab: 1 of 191 AChR-positive patients and 1 of 54 MuSK-positive patients. Conclusions We have developed and validated a novel CBA for detecting agrin Abs. This CBA was successfully applied to detect agrin Abs in serum samples obtained from individuals with MG.

Background: and Purpose Anti-agrin antibodies (agrin Abs) have recently been identified in patients with myasthenia gravis (MG), sometimes in conjunction with antibodies (Abs) to the acetylcholine receptor (AChR), muscle-specific tyrosine kinase (MuSK), or low-density lipoprotein receptor-related protein 4. This study aimed to develop an in-house cell-based assay (CBA) for detecting agrin Abs, and to test its application to serum samples collected from individuals diagnosed with MG. Methods: Agrin complementary DNA as cloned into a pCMV6-AC-GFP vector, which was subsequently transfected into human embryonic kidney 293T (HEK293T) cells. Transfected HEK293T cells were incubated with patient serum and antihuman immunoglobulin G Ab conjugated with a red fluorescent dye. Agrin Ab levels were measured using the CBA in 389 serum samples: 340 from patients with MG, 36 from patients with other neuromuscular diseases, and 13 from healthy controls. The presence of agrin Ab was determined based on the fluorescence intensity and colocalization using fluorescence microscopy. Results: The expression levels of agrin mRNA and protein in transfected HEK293T cells were confirmed using the reverse-transcription polymerase chain reaction and Western blotting, respectively. Agrin expression in cells was further confirmed by immunocytochemistry.Two (0.6%) of the 340 patients with MG tested positive for agrin Ab: 1 of 191 AChR-positive patients and 1 of 54 MuSK-positive patients. Conclusions We have developed and validated a novel CBA for detecting agrin Abs. This CBA was successfully applied to detect agrin Abs in serum samples obtained from individuals with MG.

Background: and Purpose Anti-agrin antibodies (agrin Abs) have recently been identified in patients with myasthenia gravis (MG), sometimes in conjunction with antibodies (Abs) to the acetylcholine receptor (AChR), muscle-specific tyrosine kinase (MuSK), or low-density lipoprotein receptor-related protein 4. This study aimed to develop an in-house cell-based assay (CBA) for detecting agrin Abs, and to test its application to serum samples collected from individuals diagnosed with MG. Methods: Agrin complementary DNA as cloned into a pCMV6-AC-GFP vector, which was subsequently transfected into human embryonic kidney 293T (HEK293T) cells. Transfected HEK293T cells were incubated with patient serum and antihuman immunoglobulin G Ab conjugated with a red fluorescent dye. Agrin Ab levels were measured using the CBA in 389 serum samples: 340 from patients with MG, 36 from patients with other neuromuscular diseases, and 13 from healthy controls. The presence of agrin Ab was determined based on the fluorescence intensity and colocalization using fluorescence microscopy. Results: The expression levels of agrin mRNA and protein in transfected HEK293T cells were confirmed using the reverse-transcription polymerase chain reaction and Western blotting, respectively. Agrin expression in cells was further confirmed by immunocytochemistry.Two (0.6%) of the 340 patients with MG tested positive for agrin Ab: 1 of 191 AChR-positive patients and 1 of 54 MuSK-positive patients. Conclusions We have developed and validated a novel CBA for detecting agrin Abs. This CBA was successfully applied to detect agrin Abs in serum samples obtained from individuals with MG.

In the rapidly evolving healthcare environment, radiologists strive to establish their rightful place.Thus, there is a need for enhanced outpatient and clinical education within the Department of Radiology and exploration of its methodologies. Accordingly, the Korean Society of Radiology established a task force to investigate the clinical and outpatient practice status of radiologists overseas, current state of related education, involvement of other specialties in radiologic practices and education in Korea, and clinical and outpatient practice status among Korean radiologists. Furthermore, a survey on clinical competency enhancement was conducted among the members of the Korean Society of Radiology. These findings suggest the need for visibility and clinical competency enhancement in radiologists and methodologies for strengthening clinical competencies.

In the rapidly evolving healthcare environment, radiologists strive to establish their rightful place.Thus, there is a need for enhanced outpatient and clinical education within the Department of Radiology and exploration of its methodologies. Accordingly, the Korean Society of Radiology established a task force to investigate the clinical and outpatient practice status of radiologists overseas, current state of related education, involvement of other specialties in radiologic practices and education in Korea, and clinical and outpatient practice status among Korean radiologists. Furthermore, a survey on clinical competency enhancement was conducted among the members of the Korean Society of Radiology. These findings suggest the need for visibility and clinical competency enhancement in radiologists and methodologies for strengthening clinical competencies.

In the rapidly evolving healthcare environment, radiologists strive to establish their rightful place.Thus, there is a need for enhanced outpatient and clinical education within the Department of Radiology and exploration of its methodologies. Accordingly, the Korean Society of Radiology established a task force to investigate the clinical and outpatient practice status of radiologists overseas, current state of related education, involvement of other specialties in radiologic practices and education in Korea, and clinical and outpatient practice status among Korean radiologists. Furthermore, a survey on clinical competency enhancement was conducted among the members of the Korean Society of Radiology. These findings suggest the need for visibility and clinical competency enhancement in radiologists and methodologies for strengthening clinical competencies.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.