Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

BACKGROUND: Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture. METHODS: This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts. RESULTS: Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring. CONCLUSION Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.

Purpose: Obesity and metabolic syndrome are acknowledged as key factors contributing to the development of non-alcoholic fatty liver disease (NAFLD). Vitamin D (VitD) is a multifaceted secosteroid hormone known for its anti-fibrotic and anti-inflammatory properties, with its deficiency often linked to obesity. Our study aimed to investigate whether VitD supplementation could mitigate the liver pathology associated with NAFLD. Materials and Methods: The NAFLD model was developed by subjecting male C57BL/6 mice to a high-fat diet (HFD) for 14 weeks.These mice were supplemented with VitD through intraperitoneal injection at a dosage of 7 μg/kg, administered three times per week for 7 weeks. Results: HFD resulted in VitD deficiency, insulin resistance, and increased liver weight. It elevated serum levels of liver aminotransferases and triglyceride, ultimately leading to steatohepatitis with fibrosis. This model exhibited increased levels of transforming growth factor (TGF)-β1, pro-inflammatory cytokines, HNF4α transcription factors, reactive oxygen species (ROS), renin-angiotensin system activity, and epithelial-mesenchymal transitions (EMT) within the liver. Supplementation with VitD resulted in the recovery of liver weight, improvement in histologic features associated with steatohepatitis, and reduction in alanine aminotransferases and triglyceride levels induced by the HFD. Additionally, it mitigated the HFD-induced over-expressions of TGF-β1 and fibrosis-related genes, along with pro-inflammatory cytokines and ROS. Notably, no adverse effect was found due to VitD supplementation in this model. Conclusion VitD ameliorates steatohepatitis within obesity-induced NAFLD through its multifaceted pathways. VitD supplementation emerges as a potentially safe, cost-effective, and direct treatment approach for NAFLD patients dealing with obesity or metabolic dysfunction.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Aortic regurgitation (AR) in children is usually caused by congenital valve anomalies, and Behçet syndrome (BS) can be suspected in cases of isolated AR. Patients with BS undergoing aortic valve surgery due to aortic valve invasion have a high risk of complications, such as leakage around the valve and dehiscence. Cardiovascular involvement occurs in 7%–46% of adult patients with BS and is the main cause of mortality; however, its prevalence is unclear and rare in children. A 12-year-old boy was diagnosed with severe AR associated with BS. A progressive subaortic pseudoaneurysm was observed after aortic valve replacement. The periaortic intracardiac pouch was at risk of rupture; therefore, the patient underwent a Bentall operation. After the Bentall procedure, a newly developed subaortic pseudoaneurysm was detected below the prosthetic valve. However, the risk of rupture reduced as the subaortic pseudoaneurysm regressed with anti-inflammatory drugs alone without reoperation. Repeated surgery is inevitable in patients with BS undergoing aortic valve surgery due to the progressive chronic inflammatory reactions that present with a pseudoaneurysm. Here, we report an 8-year follow-up of a pediatric case of BS with subaortic pseudoaneurysm, highlighting the importance of close follow-up, medical management, and early diagnosis in treating this condition.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

BACKGROUND: Bone defects are commonly encountered due to accidents, diseases, or aging, and the demand for effective bone regeneration, particularly for dental implants, is increasing in our aging society. Mesenchymal stem cells (MSCs) are promising candidates for regenerative therapies; however, obtaining sufficient quantities of these cells for clinical applications remains challenging. DW-MSCs, derived from embryonic stem cells and developed by Daewoong Pharmaceutical, exhibit a robust proliferative capacity even after extensive culture. METHODS: This study explores the therapeutic potential of DW-MSCs in various animal models of bone defects. DWMSCs were expanded for over 13 passages for in vivo use in rat and canine models of bone defects and osteomyelitis. The research focused on the in vivo osteogenic differentiation of DW-MSCs, the establishment of a fibrin-based system for bone regeneration, the assessment of bone repair following treatment in animal models, and comparisons with commercially available bone grafts. RESULTS: Results showed that DW-MSCs exhibited superior osteogenic differentiation compared to other materials, and the fibrinization process not only preserved but enhanced their proliferation and differentiation capabilities through a 3D culture effect. In both bone defect models, DW-MSCs facilitated significant bone regeneration, reduced inflammatory responses in osteomyelitis, and achieved effective bone healing. The therapeutic outcomes of DW-MSCs were comparable to those of commercial bone grafts but demonstrated qualitatively superior bone tissue restructuring. CONCLUSION Our findings suggest that DW-MSCs offer a promising approach for bone regeneration therapies due to their high efficacy and anti-inflammatory properties.

Background: This study explores effective fixation methods for Pauwel type III femoral neck fractures by evaluating the biomechanical benefits of adding a screw to the Femoral Neck System (FNS). Methods: Computed tomography (CT) scans of an 82-year-old female patient with an intertrochanteric fracture were used to establish a finite element femur model with heterogeneous material properties. Finite element models of Pauwel type III fractures were created with and without an additional screw. The central and inferior trajectories of the FNS bolt were examined separately and combined with an additional screw for virtual fixation. Walking and stair-climbing loads were applied. Results: With the addition of a screw, both peak maximum and minimum principal strains consistently stayed comparable or decreased in models with both central and inferior bolt trajectories, while the volume of elements with principal strain exceeding 1% decreased by more than half. The peak von Mises stress observed in the implants ranged from 215.7 to 359.3 MPa, remaining below the titanium alloy's yield strength of 800 MPa. For normal walking, the addition of a screw to the central bolt trajectory model decreased the fracture gap by 50.6% and reduced sliding distance by 8.6%. For the inferior bolt trajectory, the gap was reduced by 57.9% and sliding distance by 25.0%.Under stair-climbing conditions, these improvements were also evident; the central trajectory model saw a halved fracture gap and a 7.9% decrease in sliding distance, while the inferior trajectory model experienced a 55.7% gap reduction and a 27.2% decrease in sliding distance. The additional screw increased the area ratio of the fracture site experiencing interfragmentary compression 34%–39%, while the additional screw alleviated peak interfragmentary compression by 12%–18% under both normal walking and stair-climbing conditions. Conclusions The addition of a screw reduced the fracture gap, sliding distance, and peak interfragmentary compression, while increasing the area ratio of interfragmentary compression under both walking and stair-climbing loads, regardless of the FNS bolt trajectory, suggesting a better mechanical environment for fracture healing.

Purpose: Obesity and metabolic syndrome are acknowledged as key factors contributing to the development of non-alcoholic fatty liver disease (NAFLD). Vitamin D (VitD) is a multifaceted secosteroid hormone known for its anti-fibrotic and anti-inflammatory properties, with its deficiency often linked to obesity. Our study aimed to investigate whether VitD supplementation could mitigate the liver pathology associated with NAFLD. Materials and Methods: The NAFLD model was developed by subjecting male C57BL/6 mice to a high-fat diet (HFD) for 14 weeks.These mice were supplemented with VitD through intraperitoneal injection at a dosage of 7 μg/kg, administered three times per week for 7 weeks. Results: HFD resulted in VitD deficiency, insulin resistance, and increased liver weight. It elevated serum levels of liver aminotransferases and triglyceride, ultimately leading to steatohepatitis with fibrosis. This model exhibited increased levels of transforming growth factor (TGF)-β1, pro-inflammatory cytokines, HNF4α transcription factors, reactive oxygen species (ROS), renin-angiotensin system activity, and epithelial-mesenchymal transitions (EMT) within the liver. Supplementation with VitD resulted in the recovery of liver weight, improvement in histologic features associated with steatohepatitis, and reduction in alanine aminotransferases and triglyceride levels induced by the HFD. Additionally, it mitigated the HFD-induced over-expressions of TGF-β1 and fibrosis-related genes, along with pro-inflammatory cytokines and ROS. Notably, no adverse effect was found due to VitD supplementation in this model. Conclusion VitD ameliorates steatohepatitis within obesity-induced NAFLD through its multifaceted pathways. VitD supplementation emerges as a potentially safe, cost-effective, and direct treatment approach for NAFLD patients dealing with obesity or metabolic dysfunction.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.