Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

BACKGROUND: Exogenous Cushing’s syndrome, which results from prolonged glucocorticoid treatment, is associated with metabolic abnormalities. Previously, we reported the inhibitory effect of tonsil-derived mesenchymal stem cell conditioned medium (T-MSC CM) on glucocorticoid signal transduction. In this study, we investigated the therapeutic efficacy of T-MSCs in a mouse model of exogenous Cushing’s syndrome. METHODS: Exogenous Cushing’s syndrome model mice was generated by corticosterone administration in the drinking water for 5 weeks, and T-MSCs were injected intraperitoneally twice during the third week. Serum lipid profiles were measured using a chemistry analyzer. HepG2 cells were treated with dexamethasone and co-cultured with T-MSCs.Expression levels of genes involved in cholesterol metabolism were examined using real-time PCR. Low-density lipoprotein receptor (LDLR) protein levels were determined using western blotting and immunohistochemistry. Liver RNA extracted from the CORT and CORT ? MSC mouse groups was used for transcriptome sequencing analysis and protein– protein interaction analysis. RESULTS: Weight reduction and improvements in dyslipidemia by T-MSC administration were observed only in female mice. T-MSCs reduce circulating LDL cholesterol levels by downregulating liver X receptor a (LXRa) and inducible degrader of LDLR (IDOL) expression, thereby stabilizing LDLRs in the liver. Transcriptome analysis of liver tissue revealed pathways that are regulated by T-MSCs administration. CONCLUSION Administration of MSCs to female mice receiving chronic corticosterone treatment reduced the circulating LDL cholesterol level by downregulating the LXRa–IDOL axis in hepatocytes. These results suggest that T-MSCs may offer a novel therapeutic strategy for managing exogenous Cushing’s syndrome by regulating cholesterol metabolism.

Background: Lung ultrasound (LUS) has proven valuable in the initial assessment of coronavirus disease 2019 (COVID-19), but its role in detecting pulmonary fibrosis following intensive care remains unclear. This study aims to assess the presence of pulmonary sequelae and fibrosis-like changes using LUS in survivors of severe COVID-19 pneumonia one month after discharge. Methods: We prospectively enrolled patients with severe COVID-19 who required mechanical ventilation in the intensive care unit (ICU) and conducted LUS assessments from admission to the outpatient visit after discharge. We tracked changes in key LUS findings and applied our proprietary LUS scoring system. To evaluate LUS accuracy, we correlated measured LUS values with computed tomography scores. Results: We evaluated B-line presence, pleural thickness, and consolidation in 14 eligible patients. The LUS scores exhibited minimal changes, with values of 19.1, 19.2, and 17.5 at admission, discharge, and the outpatient visit, respectively. Notably, the number of B-lines decreased significantly, from 1.92 at admission to 0.56 at the outpatient visit (p<0.05), while pleural thickness increased significantly, from 2.05 at admission to 2.48 at the outpatient visit (p≤0.05). Conclusion This study demonstrates that LUS can track changes in lung abnormalities in severe COVID-19 patients from ICU admission through to outpatient follow-up. While pleural thickening and B-line patterns showed significant changes, no correlation was found between LUS and high-resolution computed tomography fibrosis scores. These findings suggest that LUS may serve as a supplementary tool for assessing pulmonary recovery in severe COVID-19 cases.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

BACKGROUND: Exogenous Cushing’s syndrome, which results from prolonged glucocorticoid treatment, is associated with metabolic abnormalities. Previously, we reported the inhibitory effect of tonsil-derived mesenchymal stem cell conditioned medium (T-MSC CM) on glucocorticoid signal transduction. In this study, we investigated the therapeutic efficacy of T-MSCs in a mouse model of exogenous Cushing’s syndrome. METHODS: Exogenous Cushing’s syndrome model mice was generated by corticosterone administration in the drinking water for 5 weeks, and T-MSCs were injected intraperitoneally twice during the third week. Serum lipid profiles were measured using a chemistry analyzer. HepG2 cells were treated with dexamethasone and co-cultured with T-MSCs.Expression levels of genes involved in cholesterol metabolism were examined using real-time PCR. Low-density lipoprotein receptor (LDLR) protein levels were determined using western blotting and immunohistochemistry. Liver RNA extracted from the CORT and CORT ? MSC mouse groups was used for transcriptome sequencing analysis and protein– protein interaction analysis. RESULTS: Weight reduction and improvements in dyslipidemia by T-MSC administration were observed only in female mice. T-MSCs reduce circulating LDL cholesterol levels by downregulating liver X receptor a (LXRa) and inducible degrader of LDLR (IDOL) expression, thereby stabilizing LDLRs in the liver. Transcriptome analysis of liver tissue revealed pathways that are regulated by T-MSCs administration. CONCLUSION Administration of MSCs to female mice receiving chronic corticosterone treatment reduced the circulating LDL cholesterol level by downregulating the LXRa–IDOL axis in hepatocytes. These results suggest that T-MSCs may offer a novel therapeutic strategy for managing exogenous Cushing’s syndrome by regulating cholesterol metabolism.

Background: Lung ultrasound (LUS) has proven valuable in the initial assessment of coronavirus disease 2019 (COVID-19), but its role in detecting pulmonary fibrosis following intensive care remains unclear. This study aims to assess the presence of pulmonary sequelae and fibrosis-like changes using LUS in survivors of severe COVID-19 pneumonia one month after discharge. Methods: We prospectively enrolled patients with severe COVID-19 who required mechanical ventilation in the intensive care unit (ICU) and conducted LUS assessments from admission to the outpatient visit after discharge. We tracked changes in key LUS findings and applied our proprietary LUS scoring system. To evaluate LUS accuracy, we correlated measured LUS values with computed tomography scores. Results: We evaluated B-line presence, pleural thickness, and consolidation in 14 eligible patients. The LUS scores exhibited minimal changes, with values of 19.1, 19.2, and 17.5 at admission, discharge, and the outpatient visit, respectively. Notably, the number of B-lines decreased significantly, from 1.92 at admission to 0.56 at the outpatient visit (p<0.05), while pleural thickness increased significantly, from 2.05 at admission to 2.48 at the outpatient visit (p≤0.05). Conclusion This study demonstrates that LUS can track changes in lung abnormalities in severe COVID-19 patients from ICU admission through to outpatient follow-up. While pleural thickening and B-line patterns showed significant changes, no correlation was found between LUS and high-resolution computed tomography fibrosis scores. These findings suggest that LUS may serve as a supplementary tool for assessing pulmonary recovery in severe COVID-19 cases.