Background: Primary cutaneous CD30+ lymphoproliferative disorders (pcCD30-LPDs) are a diseases with various clinical and prognostic characteristics. Objective: Increasing our knowledge of the clinical characteristics of pcCD30-LPDs and identifying potential prognostic variables in an Asian population. Methods: Clinicopathological features and survival data of pcCD30-LPD cases obtained from 22 hospitals in South Korea were examined. Results: A total of 413 cases of pcCD30-LPDs (lymphomatoid papulosis [LYP], n=237; primary cutaneous anaplastic large cell lymphoma [C-ALCL], n=176) were included. Ninety percent of LYP patients and roughly 50% of C-ALCL patients presented with multiple skin lesions. Both LYP and C-ALCL affected the lower limbs most frequently. Multiplicity and advanced T stage of LYP lesions were associated with a chronic course longer than 6 months. Clinical morphology with patch lesions and elevated serum lactate dehydrogenase were significantly associated with LPDs during follow-up in LYP patients. Extracutaneous involvement of C-ALCL occurred in 13.2% of patients. Lesions larger than 5 cm and increased serum lactate dehydrogenase were associated with a poor prognosis in C-ALCL. The survival of patients with C-ALCL was unaffected by the anatomical locations of skin lesions or other pathological factors. Conclusion The multiplicity or size of skin lesions was associated with a chronic course of LYP and survival among patients with C-ALCL.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Since the role of the liver in metabolic dysfunction, including type 2 diabetes mellitus, was demonstrated, studies on non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have shown associations between fatty liver disease and other metabolic diseases. Unlike the exclusionary diagnostic criteria of NAFLD, MAFLD diagnosis is based on the presence of metabolic dysregulation in fatty liver disease. Renaming NAFLD as MAFLD also introduced simpler diagnostic criteria. In 2023, a new nomenclature, steatotic liver disease (SLD), was proposed. Similar to MAFLD, SLD diagnosis is based on the presence of hepatic steatosis with at least one cardiometabolic dysfunction. SLD is categorized into metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related/-associated liver disease, alcoholrelated liver disease, specific etiology SLD, and cryptogenic SLD. The term MASLD has been adopted by a number of leading national and international societies due to its concise diagnostic criteria, exclusion of other concomitant liver diseases, and lack of stigmatizing terms. This article reviews the diagnostic criteria, clinical relevance, and differences among NAFLD, MAFLD, and MASLD from a diabetologist’s perspective and provides a rationale for adopting SLD/MASLD in the Fatty Liver Research Group of the Korean Diabetes Association.