Spontaneous coronary artery dissection (SCAD) is a condition in which an intramural hematoma within the coronary artery leads to acute coronary syndrome without atherosclerosis, trauma, or iatrogenic causes. It predominantly affects middle-aged women and is associated with several predisposing conditions, including fibromuscular dysplasia, systemic inflammatory disorders, connective tissue diseases, and coronary artery spasms. We report the case of a 64-year-old male with a history of hypertension who died of SCAD. His death occurred suddenly and without preceding trauma while the decedent was working overtime at a construction site. On gross examination, a thrombus-like material was identified in a branch of the left anterior descending artery and was initially presumed to be a postmortem clot. However, microscopic examination revealed an intramural hemorrhage, medial dissection, and formation of a false lumen within the coronary artery. This case report highlights the importance of a thorough histopathological examination of the coronary arteries during autopsy, even in the absence of atherosclerosis.

Spontaneous coronary artery dissection (SCAD) is a condition in which an intramural hematoma within the coronary artery leads to acute coronary syndrome without atherosclerosis, trauma, or iatrogenic causes. It predominantly affects middle-aged women and is associated with several predisposing conditions, including fibromuscular dysplasia, systemic inflammatory disorders, connective tissue diseases, and coronary artery spasms. We report the case of a 64-year-old male with a history of hypertension who died of SCAD. His death occurred suddenly and without preceding trauma while the decedent was working overtime at a construction site. On gross examination, a thrombus-like material was identified in a branch of the left anterior descending artery and was initially presumed to be a postmortem clot. However, microscopic examination revealed an intramural hemorrhage, medial dissection, and formation of a false lumen within the coronary artery. This case report highlights the importance of a thorough histopathological examination of the coronary arteries during autopsy, even in the absence of atherosclerosis.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.

Spontaneous coronary artery dissection (SCAD) is a condition in which an intramural hematoma within the coronary artery leads to acute coronary syndrome without atherosclerosis, trauma, or iatrogenic causes. It predominantly affects middle-aged women and is associated with several predisposing conditions, including fibromuscular dysplasia, systemic inflammatory disorders, connective tissue diseases, and coronary artery spasms. We report the case of a 64-year-old male with a history of hypertension who died of SCAD. His death occurred suddenly and without preceding trauma while the decedent was working overtime at a construction site. On gross examination, a thrombus-like material was identified in a branch of the left anterior descending artery and was initially presumed to be a postmortem clot. However, microscopic examination revealed an intramural hemorrhage, medial dissection, and formation of a false lumen within the coronary artery. This case report highlights the importance of a thorough histopathological examination of the coronary arteries during autopsy, even in the absence of atherosclerosis.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.