1.Clinical Practice Guideline for Blood-based Circulating Tumor DNA Assays
Jee-Soo LEE ; Eun Hye CHO ; Boram KIM ; Jinyoung HONG ; Young-gon KIM ; Yoonjung KIM ; Ja-Hyun JANG ; Seung-Tae LEE ; Sun-Young KONG ; Woochang LEE ; Saeam SHIN ; Eun Young SONG ;
Annals of Laboratory Medicine 2024;44(3):195-209
		                        		
		                        			
		                        			 Circulating tumor DNA (ctDNA) has emerged as a promising tool for various clinical applications, including early diagnosis, therapeutic target identification, treatment response monitoring, prognosis evaluation, and minimal residual disease detection. Consequently, ctDNA assays have been incorporated into clinical practice. In this review, we offer an indepth exploration of the clinical implementation of ctDNA assays. Notably, we examined existing evidence related to pre-analytical procedures, analytical components in current technologies, and result interpretation and reporting processes. The primary objective of this guidelines is to provide recommendations for the clinical utilization of ctDNA assays. 
		                        		
		                        		
		                        		
		                        	
2.Financial Benefits of Renal Dose-Adjusted Dipeptidyl Peptidase-4 Inhibitors for Patients with Type 2 Diabetes and Chronic Kidney Disease
Hun Jee CHOE ; Yeh-Hee KO ; Sun Joon MOON ; Chang Ho AHN ; Kyoung Hwa HA ; Hyeongsuk LEE ; Jae Hyun BAE ; Hyung Joon JOO ; Hyejin LEE ; Jang Wook SON ; Dae Jung KIM ; Sin Gon KIM ; Kwangsoo KIM ; Young Min CHO
Endocrinology and Metabolism 2024;39(4):622-631
		                        		
		                        			 Background:
		                        			Dipeptidyl peptidase-4 (DPP4) inhibitors are frequently prescribed for patients with type 2 diabetes; however, their cost can pose a significant barrier for those with impaired kidney function. This study aimed to estimate the economic benefits of substituting non-renal dose-adjusted (NRDA) DPP4 inhibitors with renal dose-adjusted (RDA) DPP4 inhibitors in patients with both impaired kidney function and type 2 diabetes. 
		                        		
		                        			Methods:
		                        			This retrospective cohort study was conducted from January 1, 2012 to December 31, 2018, using data obtained from common data models of five medical centers in Korea. Model 1 applied the prescription pattern of participants with preserved kidney function to those with impaired kidney function. In contrast, model 2 replaced all NRDA DPP4 inhibitors with RDA DPP4 inhibitors, adjusting the doses of RDA DPP4 inhibitors based on individual kidney function. The primary outcome was the cost difference between the two models. 
		                        		
		                        			Results:
		                        			In total, 67,964,996 prescription records were analyzed. NRDA DPP4 inhibitors were more frequently prescribed to patients with impaired kidney function than in those with preserved kidney function (25.7%, 51.3%, 64.3%, and 71.6% in patients with estimated glomerular filtration rates [eGFRs] of ≥60, <60, <45, and <30 mL/min/1.73 m2, respectively). When model 1 was applied, the cost savings per year were 7.6% for eGFR <60 mL/min/1.73 m2 and 30.4% for eGFR <30 mL/min/1.73 m2. According to model 2, 15.4% to 51.2% per year could be saved depending on kidney impairment severity. 
		                        		
		                        			Conclusion
		                        			Adjusting the doses of RDA DPP4 inhibitors based on individual kidney function could alleviate the economic burden associated with medical expenses. 
		                        		
		                        		
		                        		
		                        	
3.A Novel Retractable Robotic Device for Colorectal Endoscopic Submucosal Dissection
Sang Hyun KIM ; Chanwoo KIM ; Bora KEUM ; Junghyun IM ; Seonghyeon WON ; Byung Gon KIM ; Kyungnam KIM ; Taebin KWON ; Daehie HONG ; Han Jo JEON ; Hyuk Soon CHOI ; Eun Sun KIM ; Yoon Tae JEEN ; Hoon Jai CHUN ; Joo Ha HWANG
Gut and Liver 2024;18(4):377-385
		                        		
		                        			 Background/Aims:
		                        			Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic submucosal dissection (ESD). In this study, we developed a retractable robot-assisted traction device and evaluated its performance in colorectal ESD. 
		                        		
		                        			Methods:
		                        			An experienced endoscopist performed ESD 18 times on an ex vivo porcine colon using the robot and 18 times using the conventional method. The outcome measures were procedure time, dissection speed, procedure-related adverse events, and blind dissection rate. 
		                        		
		                        			Results:
		                        			Thirty-six colonic lesions were resected from ex vivo porcine colon samples. The total procedure time was significantly shorter in robot-assisted ESD (RESD) than in conventional ESD (CESD) (20.1±4.1 minutes vs 34.3±8.3 minutes, p<0.05). The submucosal dissection speed was significantly faster in the RESD group than in the CESD group (36.8±9.2 mm 2 /min vs 18.1±4.7 mm 2 /min, p<0.05). The blind dissection rate was also significantly lower in the RESD group (12.8%±3.4% vs 35.1%±3.9%, p<0.05). In an in vivo porcine feasibility study, the robotic device was attached to a colonoscope and successfully inserted into the proximal colon without damaging the colonic wall, and ESD was successfully performed. 
		                        		
		                        			Conclusions
		                        			The dissection speed and safety profile improved significantly with the retractable RESD. Thus, our robotic device has the potential to provide simple, effective, and safe multidirectional traction during colonic ESD. 
		                        		
		                        		
		                        		
		                        	
4.Identification of Preeclamptic Placenta in Whole Slide Images Using Artificial Intelligence Placenta Analysis
Young Mi JUNG ; Seyeon PARK ; Youngbin AHN ; Haeryoung KIM ; Eun Na KIM ; Hye Eun PARK ; Sun Min KIM ; Byoung Jae KIM ; Jeesun LEE ; Chan-Wook PARK ; Joong Shin PARK ; Jong Kwan JUN ; Young-Gon KIM ; Seung Mi LEE
Journal of Korean Medical Science 2024;39(39):e271-
		                        		
		                        			 Background:
		                        			Preeclampsia (PE) is a hypertensive pregnancy disorder linked to placental dysfunction, often involving pathological lesions like acute atherosis, decidual vasculopathy, accelerated villous maturation, and fibrinoid deposition. However, there is no gold standard for the pathological diagnosis of PE and this limits the ability of clinicians to distinguish between PE and non-PE pregnancies. Recent advances in computational pathology have provided the opportunity to automate pathological analysis for diagnosis, classification, prediction, and prediction of disease progression. In this study, we assessed whether computational pathology could be used to identify PE placentas. 
		                        		
		                        			Methods:
		                        			A total of 168 placental whole-slide images (WSIs) of patients from Seoul National University Hospital (comprising 84 PE cases and 84 normal controls) were used for model development and internal validation. For external validation of the model, 76 placental slides (including 38 PE cases and 38 normal controls) were obtained from the Boramae Medical Center (BMC). To establish standard criteria for diagnosing PE and distinguishing it from controls using placental WSIs, patch characteristics and quantification of terminal and intermediate villi were employed. In unsupervised learning, K-means clustering was conducted as a feature obtained through an Auto Encoder to extract the ratio of each cluster for each WSI. For supervised learning, quantitative assessments of the villi were obtained using a U-Net-based segmentation algorithm. The prediction model was developed using an ensemble method and was compared with a clinical feature model developed by using placental size features. 
		                        		
		                        			Results:
		                        			Using ensemble modeling, we developed a model to identify PE placentas.The model showed good performance (area under the precision-recall curve [AUPRC], 0.771; 95% confidence interval [CI], 0.752–0.790), with 77.3% of sensitivity and 71.1% of specificity, whereas the clinical feature model showed an AUPRC 0.713 (95% CI, 0.694–0.732) with 55.6% sensitivity and 86.8% specificity. External validation of the predictive model employing the BMC-derived set of placental slides also showed good discrimination (AUPRC, 0.725; 95% CI, 0.720–0.730). 
		                        		
		                        			Conclusion
		                        			The proposed computational pathology model demonstrated a strong ability to identify preeclamptic placentas. Computational pathology has the potential to improve the identification of PE placentas. 
		                        		
		                        		
		                        		
		                        	
5.Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer
Young-Gon KIM ; In Hye SONG ; Seung Yeon CHO ; Sungchul KIM ; Milim KIM ; Soomin AHN ; Hyunna LEE ; Dong Hyun YANG ; Namkug KIM ; Sungwan KIM ; Taewoo KIM ; Daeyoung KIM ; Jonghyeon CHOI ; Ki-Sun LEE ; Minuk MA ; Minki JO ; So Yeon PARK ; Gyungyub GONG
Cancer Research and Treatment 2023;55(2):513-522
		                        		
		                        			 Purpose:
		                        			Assessing the metastasis status of the sentinel lymph nodes (SLNs) for hematoxylin and eosin–stained frozen tissue sections by pathologists is an essential but tedious and time-consuming task that contributes to accurate breast cancer staging. This study aimed to review a challenge competition (HeLP 2019) for the development of automated solutions for classifying the metastasis status of breast cancer patients. 
		                        		
		                        			Materials and Methods:
		                        			A total of 524 digital slides were obtained from frozen SLN sections: 297 (56.7%) from Asan Medical Center (AMC) and 227 (43.4%) from Seoul National University Bundang Hospital (SNUBH), South Korea. The slides were divided into training, development, and validation sets, where the development set comprised slides from both institutions and training and validation set included slides from only AMC and SNUBH, respectively. The algorithms were assessed for area under the receiver operating characteristic curve (AUC) and measurement of the longest metastatic tumor diameter. The final total scores were calculated as the mean of the two metrics, and the three teams with AUC values greater than 0.500 were selected for review and analysis in this study. 
		                        		
		                        			Results:
		                        			The top three teams showed AUC values of 0.891, 0.809, and 0.736 and major axis prediction scores of 0.525, 0.459, and 0.387 for the validation set. The major factor that lowered the diagnostic accuracy was micro-metastasis. 
		                        		
		                        			Conclusion
		                        			In this challenge competition, accurate deep learning algorithms were developed that can be helpful for making a diagnosis on intraoperative SLN biopsy. The clinical utility of this approach was evaluated by including an external validation set from SNUBH. 
		                        		
		                        		
		                        		
		                        	
8.Association Between Bullying Behavior and Suicidal Ideation Among Middle School Adolescents *
Sun-Jung LEE ; Hae-Jung YANG ; Seung-Gon KIM ; Hyung-Jun YOON ; Eun-Hyun SEO
Journal of the Korean Society of Biological Therapies in Psychiatry 2022;28(2):67-73
		                        		
		                        			 Objectives:
		                        			:This study aimed to investigate the prevalence of bullying behavior and its association with suicidal ideation among middle school students. 
		                        		
		                        			Methods:
		                        			:This was a cross sectional study of a sample including 781 second grade middle school students(438 males and 343 females) in Gwang-ju metropolitan city. Information on bullying involvement, suicidal ideation and depressive/anxiety symptoms were collected using a self-administered questionnaire. Subjects were classified into subgroups of bully, victim, bully or victim, bully-victim, and witnessing. The data were analyzed using binary logistic regression analyses, adjusted for covariates. 
		                        		
		                        			Results:
		                        			:The prevalence of bullying victimization, bullying perpetration, bullying witnessing and suicidal ideation were 26.5%, 24.5%, 21.6% and 26%, respectively. Suicidal ideation was positively correlated with bullying victimization, bullying perpetration, bullying witnessing. Using binary logistic regression analyses, the odds ratio of bully-victim group compared to non bullying involvement was 2.41, the highest among all groups. 
		                        		
		                        			Conclusions
		                        			:Our findings indicate that school bullying, victim, and witnessing are associated with suicidal ideation, especially in bully and victim group. In addition, it is essential to develop prevention strategies and interventions for adolescents involved in any bullying involvement. 
		                        		
		                        		
		                        		
		                        	
9.A Case of Eosinophilic Annular Erythema
Seo Mi Gon JEONG ; Ha Eun KANG ; Yun Sun MOON ; Chi Yeon KIM
Korean Journal of Dermatology 2022;60(6):390-394
		                        		
		                        			
		                        			 Eosinophilic annular erythema (EAE) is an uncommon, recurrent eosinophilic cutaneous disease, and its etiology has not been clearly elucidated. Clinically, EAE occurs mainly in the form of annular or round erythematous, edematous plaques on the trunk or extremities. Histopathologically, it is characterized by superficial and deep perivascular inflammatory cell infiltration composed of lymphocytes and eosinophils. Based on this, some studies have stated that EAE is not an isolated rare disease but rather a spectrum that shares features similar to Wells syndrome. Herein, we report a case of EAE in a 28-year-old female patient. The clinical features were recurrent annular, erythematous patch on the both extremities. Histopathologic examination demonstrated superficial infiltrates of lymphocytes and eosinophils in the dermis. Based on the clinical and histological features, this case was diagnosed as EAE. 
		                        		
		                        		
		                        		
		                        	
10.Primary Tumor Suppression and Systemic Immune Activation of Macrophages through the Sting Pathway in Metastatic Skin Tumor
Chun-Bong SYNN ; Dong Kwon KIM ; Jae Hwan KIM ; Youngseon BYEON ; Young Seob KIM ; Mi Ran YUN ; Ji Min LEE ; Wongeun LEE ; Eun Ji LEE ; Seul LEE ; You-Won LEE ; Doo Jae LEE ; Hyun-Woo KIM ; Chang Gon KIM ; Min Hee HONG ; June Dong PARK ; Sun Min LIM ; Kyoung-Ho PYO
Yonsei Medical Journal 2022;63(1):42-55
		                        		
		                        			 Purpose:
		                        			Agonists of the stimulator of interferon genes (STING) play a key role in activating the STING pathway by promoting the production of cytokines. In this study, we investigated the antitumor effects and activation of the systemic immune response of treatment with DMXAA (5,6-dimethylxanthenone-4-acetic acid), a STING agonist, in EML4-ALK lung cancer and CT26 colon cancer. 
		                        		
		                        			Materials and Methods:
		                        			The abscopal effects of DMXAA in the treatment of metastatic skin nodules were assessed. EML4-ALK lung cancer and CT26 colon cancer models were used to evaluate these effects after DMXAA treatment. To evaluate the expression of macrophages and T cells, we sacrificed the tumor-bearing mice after DMXAA treatment and obtained the formalin-fixed paraffin-embedded (FFPE) tissue and tumor cells. Immunohistochemistry and flow cytometry were performed to analyze the expression of each FFPE and tumor cell. 
		                        		
		                        			Results:
		                        			We observed that highly infiltrating immune cells downstream of the STING pathway had increased levels of chemokines after DMXAA treatment. In addition, the levels of CD80 and CD86 in antigen-presenting cells were significantly increased after STING activation. Furthermore, innate immune activation altered the systemic T cell-mediated immune responses, induced proliferation of macrophages, inhibited tumor growth, and increased numbers of cytotoxic memory T cells. Tumor-specific lymphocytes also increased in number after treatment with DMXAA. 
		                        		
		                        			Conclusion
		                        			The abscopal effect of DMXAA treatment on the skin strongly reduced the spread of EML4-ALK lung cancer and CT26 colon cancer through the STING pathway and induced the presentation of antigens. 
		                        		
		                        		
		                        		
		                        	
            
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