The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background: Posttransplant diabetes mellitus (PTDM) complicates kidney transplant recipients (KTRs) in morbidity and mortality. This study aimed to predict PTDM risk in KTRs using machine learning and deep learning models. Methods: Data were obtained from the Korea Organ Transplantation Registry, a nationwide cohort study of KTRs. Four machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), CatBoost, light gradient boosting machine and logistic regression, and deep learning were implemented on 41 pretransplant and 31 posttransplant variables to predict PTDM. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, precision, recall, and F1 score. Results: Among 3,213 KTRs, 497 patients (15.5%) developed PTDM within 1 year. The PTDM group had higher age, body mass index (BMI), triglyceride level, and prevalence of hypertension and cardiovascular disease, and lower total cholesterol level at baseline than the No-PTDM group. The XGBoost model showed the highest AUC (0.738) and F1 score (0.42), and modest accuracy (0.86), while the CatBoost model exhibited the highest accuracy (0.87) and precision (0.79). Feature importance in XGBoost was highest for recipient age, followed by baseline BMI, triglyceride level at posttransplant 6 months, baseline glycated hemoglobin and high-density lipoprotein cholesterol level, white blood cell (WBC) count and serum uric acid level at 6 months, baseline WBC count, and tacrolimus trough level at discharge. Conclusion The XGBoost model demonstrated the best performance for predicting PTDM within 1 year, offering an accurate tool for early identification and personalized care of high-risk KTRs for PTDM.

Objective: Since its development in 2002 by the Korean College of Neuropsychopharmacology and the Korean Society for Affective Disorders, the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) has undergone five revisions. Methods: To improve survey efficiency, reflect general clinical practice, and facilitate comparisons with previous KMAP-DD revisions, the overall structure of the questionnaire was retained. The six sections of the questionnaire were as follows:1) pharmacological treatment strategies for major depressive disorder with and without psychotic features; 2) pharmacological treatment strategies for persistent depressive disorder and other depressive disorder subtypes; 3) consensus on treatment-resistant depression; 4) selection of an antidepressant in consideration of safety, adverse effects, and comorbid physical conditions; 5) treatment strategies for special populations (children/adolescents, elderly, and women); and 6) non-pharmacological biological therapies. First-, second-, and third-line treatment recommendations were statistically derived. Results: Compared to KMAP-DD 2021, only minor changes were noted, due to the limited introduction of new medications or treatment modalities. Nonetheless, notable shifts included an increased preference for atypical antipsychotics (AAPs), and higher preference of combination strategies involving AAPs and mood stabilizers, indicating a more proactive and intensive treatment trend in Korea. Conclusion KMAP-DD is expected to serve as a valuable clinical resource by providing expert consensus-based recommendations on specific treatment strategies and pharmacological options for major depressive disorders, thereby supporting the integration of real-world clinical practice with evidence-based medicine.

Transient global amnesia (TGA) and transient epileptic amnesia (TEA) are inherently challenging to diagnose and share many similarities, which can easily lead to confusion. In this report, we present a case of a 57-year-old female patient experienced recurrent transient amnesia with incidentally found chronic ischemic temporo-parietal lesion including hippocampus and also revealed frequent interictal epileptiform discharges in acute period which can be features of TEA. We aim to explore the differences between TEA and TGA through this confusing case and when further evaluation may be necessary.

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.

Background: Islet transplantation holds promise for treating selected type 1 diabetes mellitus patients, yet the scarcity of human donor organs impedes widespread adoption. Porcine islets, deemed a viable alternative, recently demonstrated successful longterm survival without zoonotic risks in a clinically relevant pig-to-non-human primate islet transplantation model. This success prompted the development of a clinical trial protocol for porcine islet xenotransplantation in humans. Methods: A single-center, open-label clinical trial initiated by the sponsor will assess the safety and efficacy of porcine islet transplantation for diabetes patients at Gachon Hospital. The protocol received approval from the Gachon Hospital Institutional Review Board (IRB) and the Korean Ministry of Food and Drug Safety (MFDS) under the Investigational New Drug (IND) process. Two diabetic patients, experiencing inadequate glycemic control despite intensive insulin treatment and frequent hypoglycemic unawareness, will be enrolled. Participants and their family members will engage in deliberation before xenotransplantation during the screening period. Each patient will receive islets isolated from designated pathogen-free pigs. Immunosuppressants and systemic infection prophylaxis will follow the program schedule. The primary endpoint is to confirm the safety of porcine islets in patients, and the secondary endpoint is to assess whether porcine islets can reduce insulin dose and the frequency of hypoglycemic unawareness. Conclusion A clinical trial protocol adhering to global consensus guidelines for porcine islet xenotransplantation is presented, facilitating streamlined implementation of comparable human trials worldwide.